# Patent

## Title
Lipid biomarkers for stable and unstable heart disease

## Abstract

The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particular, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.

## Background
RELATED APPLICATIONS
This application is a U.S. National Phase of International Application No. PCT/AU2010/001596, filed Nov. 26, 2010, designating the U.S., and published as WO 2011/063470 on Jun. 3, 2011 which claims the benefit of U.S. Provisional Application No. 61/264,767 filed Nov. 27, 2009.


FIELD
The present invention relates generally to the field of diagnostic and prognostic assays for heart disease. More particularly, the present invention provides an assay for diagnosing the presence or extent of development of heart disease or its classification or state thereof. The assay of the present invention is also useful in the stratification of a subject with respect to a risk of developing heart disease. The assay of the present invention is also capable of integration into pathology architecture to provide a diagnostic and reporting system.
BACKGROUND
Bibliographic details of references provided in the subject specification are listed at the end of the specification.
Reference to any prior art is not, and should not be taken as an acknowledgment or any form of suggestion that this prior art forms part of the common general knowledge in any country.
Atherosclerosis (AS) is the single most common cause of heart disease and is the major contributor to the development of angina, heart attacks and stroke. Despite the introduction of statin-based therapy to reduce levels of plasma low density lipoprotein (LDL) cholesterol, the epidemic of heart disease is claiming tens of thousands of lives each year, particularly in Western countries and costs the health system over billions of dollars per year (National Health Survey: Summary of Results, Australia, 2004-05, cat. no. 4364.0, ABS, Can berra, Vol: Australian Bureau of Statistics, 2006, (AIHW) AIoHaW. Health system expenditure on disease and injury in Australia, 2000-01. Health and Welfare Expenditure Series No. 19, 2004; HWE 26).
Atherosclerosis begins to develop early in life and progresses with time. However, the rate of progression is, to a large extent, unpredictable and differs markedly amongst seemingly comparable individuals. One of the early events leading to Atherosclerosis is the formation of “fatty streaks”, deposits of monocytes, macrophages, foam cells and lipids within the intima of the arterial wall. Fatty streaks exist in most adults and can remain as fatty streaks for years or decades, having little or no adverse clinical effects. Some, but not all, fatty steaks progress into fibriolipid plaques which are distinguished by the presence of smooth muscle cells and increased extracellular fibres within the intima. Cell death within the plaque leads to the formation of a necrotic core, the accumulation of extracellular material and the formation of the complex plaque. At this stage, the plaque may severely restrict blood flow leading to a range of clinical complications; however, many individuals will be unaware of the problem and show no symptoms.
Complex plaques can become unstable (a “vulnerable” plaque) as a result of the thinning of the smooth muscle cell layer over the plaque. Unstable plaques may rupture leading to thrombosis, myocardial infarction and stroke with the associated morbidity and mortality (the “vulnerable” patient). Although plaque accumulation and development is progressive throughout life, the switch from stable to unstable plaque can occur earlier or later in the disease process. Thus a 45 year old with relatively low levels of plaque can become unstable leading to a coronary event.
Despite our detailed knowledge of plaque pathology and progression many individuals have no clinical symptoms and so are unaware of their risk. In 30 to 50% of these individuals, the first indicator of Atherosclerosis is an acute heart attack which is often fatal (Heart Disease and Stroke Statistics-2006 Update, Dallas Tex.: American Heart Association, 2006. Available at http://www.americanheart.org/downloadable/heart/1198257493273HS_Stats%202008.pdf)
A non-invasive assay is required to identify and monitor heart disease.
SUMMARY
Each embodiments described herein is to be applied mutatis mutandis to each any every embodiment unless specifically stated otherwise.
The present invention applies a lipidomic approach to identifying the presence, development, stage or severity of heart disease or its various manifestations.
An association is therefore identified between the level of lipidomic analytes in a subject and heart disease. The term “analyte” includes biomarker and indicator. By “heart disease” is meant an individual condition as well as a collection of conditions within the clinical spectrum of symptomatic or asymptomatic heart disease. The lipidomic biomarkers provide a range of risk indicators of the severity of disease and rate of progression and a classification of the disease such as stable or unstable in relation to plaques. This risk ranges from minor to extreme. Knowledge of the level of risk enables intervention to mitigate further development of heart disease. The ability to monitor and identify markers of heart disease including diagnosing it in asymptomatic subjects further enables decisions on the type of medical intervention required from behavioural modification and medicaments to surgical intervention. The lipidomic biomarkers are also instructive as to the level of risk for an individual developing more severe symptomology associated with heart disease. The lipidomic profile also defines a desired state of health in subjects. Hence, monitoring changing levels of lipid analytes is a useful tool in pharmacotranslational studies and clinical management of patients.
Reference to “heart disease” includes conditions such as coronary heart disease (including coronary artery disease, angina pectoris and myocardial infarction), atherosclerosis, cardiomyopathy (including that associated with arrhythmia), cardiovascular disease, ischaemic heart disease, heart failure (including cor pulmonale), hypertensive heart disease (including left ventricular hypertrophy and congestive heart failure), inflammatory heart disease (including endocarditis, inflammatory cardiomegaly and myocarditis) and valvular heart disease (including aortic valve stenosis and mitral valve prolapse). Heart disease spectrum also includes associated conditions such as aortic aneurysm, hypertension, thrombosis and pericarditis. Heart disease is a spectrum of clinical manifestations.
The present invention is predicated in part on the determination that subjects with heart disease or at risk of developing heart disease exhibit altered lipid metabolism. The levels of particular lipidomic analytes correlate with the state, stage and/or classification of heart disease and its progression in symptomatic and asymptomatic subjects. By “classification” includes identifying subjects with stable and unstable plaques and hence, individuals can be classified as vulnerable or non-vulnerable subjects. Hence, the present invention enables stratification of subjects into risk categories, treatment categories and likely progression outcomes.
Twenty-three different lipid classes and three hundred and twenty-nine lipid analytes were analysed. Ten different lipid classes comprising thirty lipid analytes were particularly useful for distinguishing between vulnerable and non-vulnerable subjects. Further, eighteen lipid classes comprising ninety-five lipid analytes were useful for distinguishing between control normal subjects and subjects with coronary artery disease. Furthermore, as summarised in Table 16, phosphatidylinositol lipids including seventeen lipid analytes in this class were on average significantly reduced in vulnerable subjects; thirteen lipid classes were reduced on average in coronary artery disease subjects and one lipid class, the diacylglycerols, was increased in coronary artery disease subjects.
The lipidomic approach uses one or more of three groups of lipid analytes:

    
    
        (i) modified ceramides (modCER), modified phosphatidylcholines (modPC) and, modified cholesterol esters (modCE) selected from those listed in Table 1;
        (ii) two or more non-modified lipid analytes selected from the list in Table 1; and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte (modCER, modPC and/or modCE) and at least one is a non-modified lipid analyte selected from the list in Table 1.
    
    


The levels or ratios of levels the lipidomic analytes are determined relative to a control. The assay may also be automated or semi-automated. In particular, the levels or ratios of, levels may be used as input data for multivariate or univariate analysis leading to an algorithm which can be used to generate an index of probability of having or progressing with heart disease.
The levels of the lipid biomarkers may also be used in combination with other standard indicators of heart disease, whether biochemical markers, symptoms or electrocardial techniques.
Accordingly, one aspect of the present invention is directed to an assay to stratify a subject as a vulnerable or non-vulnerable subject with respect to plaques, the assay comprising determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control identifies the subject as being vulnerable or non-vulnerable.

    
    


Yet another aspect of the present invention contemplates an assay to stratify a subject with respect to heart disease, the assay comprising determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation as to the presence, state, classification or progression of heart disease.

    
    


In some embodiments, the assays comprise determining the levels of at least two lipid analytes.
Still another aspect of the present invention contemplates the use of a panel of lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

in the manufacture of an assay to identify the presence, state, classification or progression of heart disease in a subject. In particular embodiments, the assay is used to identify vulnerable or non-vulnerable subjects.

    
    


Even yet another aspect of the present invention relates to a method of treatment or prophylaxis of a subject comprising assaying the subject with respect to heart disease by determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease and then providing therapeutic and/or behavioural modification to the subject.

    
    


The “stratification” is in effect a level of risk that a subject has heart disease or is developing heart disease or is likely to develop symptoms of heart disease.
The determination of the levels or ratios of the lipid biomarkers may be used in combination with other indicators of heart disease and may be used to monitor efficacy of treatment. In addition, the assay may be useful in determining the most effective therapeutic or behavioural intervention to treat heart disease in symptomatic or asymptomatic subjects.
The assay may also be used in a personalized medicine approach in the management of heart disease and/or as part of a pathology architecture platform.
The above summary is not and should not be seen in any way as an exhaustive recitation of all embodiments of the present invention.







TABLE 1







Lipid Analytes (Biomarkers)








No. (#)
Analyte











1
Cer 16:0


 S1
Cer 17:0 (IS)


2
Cer 18:1


3
Cer 18:0


4
Cer 20:0


5
Cer 22:0


6
Cer 24:1


7
Cer 24:0


8
MHC 16:0


 S2
MHC 16:0d3 (IS)


9
MHC 18:1


10
MHC 18:0


11
MHC 20:0


12
MHC 22:0


13
MHC 24:1


14
MHC 24:0


15
DHC 16:0


 S3
DHC 16:0d3 (IS)


16
DHC 18:1


17
DHC 18:0


18
DHC 20:0


19
DHC 22:0


20
DHC 24:1


21
DHC 24:0


22
THC 16:0


 S4
THC 17:0 (IS)


23
THC 18:1


24
THC 18:0


25
THC 20:0


26
THC 22:0


27
THC 24:1


28
THC 24:0


29
GM3 16:0


30
GM3 18:0


31
GM3 20:0


32
GM3 22:0


33
GM3 24:1


34
GM3 24:0


35
modCer 576.5/7.68


36
modCer 614.6/5.72


37
modCer 632.6/9.22


38
modCer 651.6/7.56


39
modCer 703.6/5.87


40
modCer 731.6/6.22


41
modCer 766.6/7.17


42
modCer 769.6/8.01


43
modCer 798.7/7.29


 S5
Acyl Cer 17:0 18:1 (IS)


44
modCer 875.7/9.23


45
modCer 883.8/7.75


46
modCer 886.8/9.06


47
modCer 910.8/8.98


48
modCer 921.8/9.05


 S6
SM 12:0 (IS)


 S6
SM 12:0 (IS)


 S6
SM 12:0 (IS)


49
SM 14:0


50
SM 15:0


51
SM 16:1


52
SM 16:0


53
SM 18:1


54
SM 18:0


55
SM 20:1


56
SM 22:1


57
SM 22:0


58
SM 24:2


59
SM 24:1


60
SM 24:0


61
PG 16:1 18:1


62
PG 16:0 18:1


 S7
PG 17:0 17:0 (IS)


63
PG 18:1 18:1


64
PG 18:0 18:1


 S8
BMP 14:0 14:0 (IS)


65
BMP 18:1 18:1


 S9
PS 17:0/17:0


66
PS 36:2


67
PS 36:1


68
PS 38:5


69
PS 38:4


70
PS 38:3


71
PS 40:6


72
PS 40:5


73
PE 32:1


74
PE 32:0


75
PE 34:2


76
PE 34:1


S10
PE 17:0/17:0 (IS)


77
PE 36:5


78
PE 36:4


79
PE 36:3


80
PE 36:2


81
PE 36:1


82
PE 36:0


83
PE 38:6


84
PE 38:5


85
PE38:4


86
PE 38:3


87
PE 38:2


88
PE 38:1


89
PE 40:7


90
PE 40:6


91
PI 32:1


92
PI 32:0


93
PI 34:1


94
PI 34:0


95
PI 36:4


96
PI 36:3


97
PI 36:2


98
PI 36:1


99
PI 36:0


100
PI 38:6


101
PI 38:5


102
PI 38:4


103
PI 38:3


104
PI 38:2


105
PI 40:6


106
PI 40:5


107
PI 40:4


S11
LPC 13:0 (IS)


108
LPC 14:0


109
LPC 15:0


110
LPC 16:1


111
LPC 16:0


112
LPC 18:2


113
LPC 18:1


114
LPC 18:0


115
LPC 20:5


116
LPC 20:4


117
LPC 20:3


118
LPC 20:2


119
LPC 20:1


120
LPC 20:0


121
LPC 22:6


122
LPAF 16:0


123
LPAF 18:1


124
LPAF 18:0


S12
PC 13:0/13:0


S12
PC 13:0/13:0


125
PC 30:2


126
PC 32:2


127
PC 32:1


128
PC 32:0


129
PC 34:3


130
PC 34:2


131
PC 34:1


132
PC 34:0


133
PC 36:5


134
PC 36:4


135
PC 36:3


136
PC 36:2


137
PC 38:6


138
PC 38:5


139
PC 38:4


140
PC 40:7


141
PC 40:6


142
PC 40:5


S13
PC 21:0 21:0 (IS)


S13
PC 21:0 21:0 (IS)


S13
PC 21:0 21:0 (IS)


143
PC 44:12


144
oddPC 31:1


145
oddPC 31:0


146
oddPC 33:0


147
oddPC 33:1


148
oddPC 33:2


149
oddPC 35:4


150
oddPC 35:3


151
oddPC 35:2


152
oddPC 35:1


153
oddPC 35:0


154
oddPC 37:6


155
oddPC 37:5


156
oddPC 37:4


157
oddPC 37:3


158
oddPC 37:2


159
APC 32:1


160
APC 32:0


161
APC 34:2


162
APC 34:1


163
APC 34:0


164
APC 36:5


165
APC 36:4


166
APC 36:3


167
APC 36:2


168
APC 36:1


169
APC 36:0


170
APC 38:6


171
APC 38:5


172
APC 38:4


173
APC 38:3


174
APC 38:2


175
modPC 506.3/3.50


176
modPC 508.3/3.30 (LPAF 18:1)


177
modPC 510.3/4.00 (LPAF 18:0)


178
modPC 512.3/1.70


179
modPC 536.3/3.50


180
modPC 538.3/4.10


181
modPC 552.4/3.90 (LPC 20:0)


182
modPC 564.4/4.70 (LPAF 22:1)


183
modPC 566.4/5.10 (LPAF 22:0)


184
modPC 580.4/4.84 (LPC 22:0)


187
modPC 594.4/3.26


189
modPC 608.4/3.84


190
modPC 610.4/2.03


191
modPC 622.4/4.54.(PC 24:0)


192
modPC 633.4/4.51


193
modPC 636.4/3.37


194
modPC 645.4/4.49


195
modPC 650.4/3.24


196
modPC 650.4/4.44


197
modPC 650.4/3.94


198
modPC 664.4/4.22


199
modPC 666.4/2.99


200
modPC 678.4/4.37


201
modPC 678.4/4.94


202
modPC 678.4/5.51 (PC 28:0)


203
modPC 690.4/4.11


204
modPC 690.4/4.90


205
modPC 690.4/6.00


206
modPC 692.4/5.05


207
modPC 692.4/5.52 (APC 30:0)


208
modPC 692.4/6.10


209
modPC 694.4/6.20


210
modPC 703.5/4.09


211
modPC 704.5/3.81


212
modPC 706.5/3.79


213
modPC 720.5/4.52


214
modPC 736.5/5.38


215
modPC 743.5/5.91


217
modPC 752.5/5.58 (PC34:5)


220
modPC 772.5/5.37


221
modPC 773.6/6.47


222
modPC 788.6/5.19


223
modPC 801.6/6.70


224
modPC 816.6/5.58


225
modPC 818.6/6.10


226
modPC 818.6/6.48 (APC 40:7)


227
modPC 828.6/6.03


228
modPC 843.6/7.10


229
modPC 866.6/7.24


230
modPC 878.6/5.98 (modPC877.6/7.1)


231
modPC 881.6/6.05 (modPC879.6/6.1)


232
COH


S14
COH d7 (IS)


233
CE 14:0


234
CE 15:0


235
CE 16:2


236
CE 16:1


237
CE 16:0


238
CE 17:1


239
CE 17:0


240
CE 18:3


241
CE 18:2


242
CE 18:1


243
CE 18:0


S15
CE 18:0 d6 (IS)


S15
CE 18:0 d6 (IS)


S15
CE 18:0 d6 (IS)


244
CE 20:5


245
CE 20:4


246
CE 20:3


247
CE 20:2


248
CE 20:1


249
CE 22:6


250
CE 22:5


251
CE 22:4


252
CE 22:3


253
CE 22:2


254
CE 22:1


255
CE 22:0


256
CE 24:6


257
CE 24:5


258
CE 24:4


259
CE 24:3


260
CE 24:2


261
CE 24:1


262
CE 24:0


263
modCE 558.5/7.74


264
modCE 588.5/7.94


265
modCE 682.7/8.76


266
modCE 790.8/6.57


267
DG 14:0 14:0


268
DG 14:1 16:0


269
DG 14:0 16:0


S16
DG 15:0 15:0 (IS)


270
DG 14:0 18:2


271
DG 14:0 18:1


272
DG 16:0 16:0


273
DG 16:0 18:2


274
DG 16:1 18:1


275
DG 16:0 18:1


276
DG 18:0 16:1


277
DG 16:0 18:0


278
DG 16:0 20:4


279
DG 18:1 18:3


280
DG 18:2 18:2


281
DG 16:0 20:3


282
DG 18:1 18:2


283
DG 18:0 18:2


284
DG 18:1 18:1


285
DG 18:0 18:1


286
DG 16:0 20:0


287
DG 18:0 18:0


288
DG 16:0 22:6


289
DG 16:0 22:5


290
DG 18:1 20:4


291
DG 18:0 20:4


292
DG 18:1 20:3


293
DG 18:1 20:0


294
TG 14:0 16:1 18:2


295
TG 16:1 16:1 16:1


296
TG 14:0 16:0 18:2


297
TG 14:0 16:1 18:1


298
TG 14:1 16:0 18:1


299
TG 14:1 16:1 18:0


300
TG 18:1 14:0 16:0


301
TG 16:0 16:0 16:0


302
TG 15:0 18:1 16:0


303
TG 17:0 16:0 16:1


304
TG 17:0 18:1 14:0


305
TG 14:0 18:2 18:2


306
TG 14:1 18:0 18:2


307
TG 14:1 18:1 18:1


308
TG 16:1 16:1 18:1


309
TG 16:0 16:0 18:2


310
TG 16:1 16:1 18:0


311
TG 16:0 16:1 18:1


312
TG 14:0 18:0 18:1


313
TG 16:0 16:0 18:1


314
TG 16:0 16:0 18:0


315
TG 15:0 18:1 18:1


316
TG 17:0 18:1 16:1


317
TG 17:0 18:2 16:0


318
TG 17:0 18:1 16:0


319
TG 17:0 16:0 18:0


S17
TG 17:0 17:0 17:0 (IS)


S17
TG 17:0 17:0 17:0 (IS)


320
TG 16:0 18:2 18:2


321
TG 16:1 18:1 18:2


322
TG 16:1 18:1 18:1


323
TG 16:0 18:1 18:2


324
TG 16:0 18:1 18:1


325
TG 16:0 18:0 18:1


326
TG 17:0 18:1 18:1


327
TG 18:2 18:2 18:2


328
TG 18:1 18:2 18:2


329
TG 18:0 18:2 18:2


330
TG 18:1 18:1 18:2


331
TG 18:1 18:1 18:1


332
TG 18:0 18:1 18:1


333
TG 18:0 18:0 18:1


334
TG 18:0 18:0 18:0


335
TG 18:2 18:2 20:4


336
TG 18:1 18:1 20:4


337
TG 18:1 18:1 22:6









List of Abbreviations
















acCer
acylceramide



APC
alkylphosphatidylcholine



BMP
bis(monoacylglycero)phosphate



CE
cholesterol ester



Cer
ceramide



COH
cholesterol



DG
diacylglycerol



DHC
dihexosylceramide



GM3
GM3 ganglioside



LPAF
lysoplatelet activating factor



LPC
lysophosphatidylcholine



MHC
monohexosylceramide



modCE
modified cholesterol ester



modCer
modified ceramide



modPC
modified phosphatidylcholine



oddPC
odd chain phosphatidylcholine



PC
phosphatidylcholine



PE
phosphatidylethanolamine



PG
phosphatidylglycerol



PI
phosphatidylinositol



PS
phosphatidylserine



SM
sphingomyelin



TG
triaclyglycerol



THC
trihexosylcermide













BRIEF DESCRIPTION OF THE FIGURES
Some figures contain color representations or entities. Color photographs are available from the Patentee upon request or from an appropriate Patent Office. A fee may be imposed if obtained from a Patent Office.
FIGS. 1(A) and (B) are graphical representations of the area under the curve and error rate resulting from stable CAD vs unstable CAD models. Recursive feature elimination (RFE) with three-fold cross validation (repeated 100 times) was used to develop multivariate models using support vector machine learning. This was done for models of varying feature size (e.g., 1, 2, 4, 8, 16, 32 and 64) and for models that included either traditional risk factors alone (blue circles) lipids alone (green squares) or lipids with traditional risk factors (red triangles). ROC analysis was performed to give area under the curve (panel A) and error rates (panel B). Error bars represent 95% confidence limits.
FIGS. 2(A) and (B) are graphical representations of the area under the curve and error rate resulting from control vs CAD models. Recursive feature elimination (RFE) with three-fold cross validation (repeated 100 times) was used to develop multivariate models using support vector machine learning. This was done for models of varying feature size (e.g., 1, 2, 4, 8, 16, 32 and 64) and for models that included either traditional risk factors alone (blue circles) lipids alone (green squares) or lipids with traditional risk factors (red triangles). ROC analysis was performed to give area under the curve (panel A) and error rates (panel B). Error bars represent 95% confidence limits.
FIG. 3 is a graphical representation of ROC analysis of classification models of stable CAD vs unstable CAD. Multivariate models created with either the 13 traditional risk factors (Table 5), the 8 highest tanked lipids (Table 13) or a combination of both were validated by three-fold cross validation repeated 10 times and the results combined in a ROC analyses.
FIG. 4 is a graphical representation of ROC analysis of classification models of control vs CAD. Multivariate models created with either the 13 traditional risk factors (Table 5), the 16 highest ranked lipids (Table 14) or a combination of both were validated by three-fold cross validation repeated 10 times and the results combined in a ROC analyses.
FIGS. 5A-5D provide graphical representations of data showing recursive feature elimination analysis of CAD. Multivariate models containing different numbers of lipids alone (circles) or traditional risk factors (squares) or combined lipids and risk factors (triangles) were created to discriminate between control and CAD (left panels) and between stable and unstable CAD (right panels). C-statistics (top panels) and % accuracy (lower panels) with 95% confidence intervals for each model are plotted against the number of variables in the model.
FIG. 6 provides a graphical representation of data showing receiver operator characteristic (ROC) analysis of multivariate models. Multivariate classification models were created by recursive feature elimination with three-fold cross-validation (repeated 100 times) using support vector machine learning. ROC analysis was performed on the optimised models containing either 16 lipids alone, 8 risk factors alone or a combination of 8 lipids and risk factors.
FIG. 7 provides graphical representations of data showing plasma levels of selected lipid species. Lipid species were measured in each group as described in Materials and Methods. The concentration of each lipid species expressed as pmol/mL is plotted for each group. The bar represents the median value, the box represents the 25th to 75th percentile and the whiskers the upper and lower limits. Circles show outliers (>1.5× height of the box from the median) and asterisks show extreme outliers (>3.0× height of the box from the median).



BRIEF DESCRIPTION OF THE TABLES
Table 1 provides a numbered list of 331 lipid analytes (biomarkers) identified in predetermined control vulnerable or non-vulnerable subjects, normal (healthy) subjects or heart disease subjects. Numbers prefaced by “s” identify internal standards used as internal controls for lipid analysis as described in the Examples.
Table 2 provides a description of the internal standard mix composition and concentration.
Table 3 provides mass spectrometer settings used for precursor ion scans.
Table 4 tabulates the scan methods used to create MRM acquisition methods for plasma lipid profiling for each lipid class.
Table 5 provides clinical and biochemical characteristics of patients.
Table 6 provides the medication of stable and unstable CAD cohorts.
Table 7 provides details of lipid analytes measured in MRM experiment 1 as described in the Examples.
Table 8 provides details of lipid analytes measured in MRM experiment 2 as described in the Examples.
Table 9 provides details of lipid analyte levels in stable and unstable cohorts.
Table 9a provides details of lipid analyte levels in control and CAD cohorts (continued).
Table 10 provides a summary of the univariate analysis of plasma lipids in control, stable CAD and unstable CAD cohorts.
Table 11 provides an analysis of variance of stable vs unstable cohorts.
Table 12 provides an analysis of variance of control vs CAD cohorts.
Table 13 provides ranked list of analytes based on recursive feature elimination of stable and unstable CAD cohorts.
Table 14 provides a ranked list of analytes based on recursive feature elimination of control vs CAD.
Table 15 provides final conditions for precursor ion scan and MRM acquisition methods for lipid identification and quantification.
Table 16 provides a final summary of univariate analysis of plasma lipids in control, CAD, stable CAD and unstable CAD groups.
Table 17 provides logistic regression models of stable CAD vs unstable CAD and logistic regression models of control vs CAD.
Table 18 provides ranked lipids in the stable CAD vs unstable CAD logistic model.
Table 19 provides ranked risk factors in the stable CAD vs unstable CAD logistic models.
Table 20 provides ranked features in the stable CAD vs unstable CAD logistic model.
Table 21 provides ranked lipids in the control vs CAD logistic model.
Table 22 provides ranked risk factors in the control vs CAD logistic model.
Table 23 provides ranked features in the control vs CAD logistic model.
Table 24 provides ranked features in the stable CAD vs unstable CAD recursive feature elimination models.
Table 25 provides ranked features in the control vs CAD recursive feature elimination models.
Table 26 provides a description of the lipid species affected by statin use.
Table 27 provides the medication of stable and unstable CAD cohorts.
DETAILED DESCRIPTION
Throughout this specification and the claims which follow, unless the context requires otherwise, the word “comprise”, and variations such as “comprises” and “comprising”, will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.
As used in the subject specification, the singular forms “a”, “an” and “the” include plural aspects unless the context clearly dictates otherwise. Thus, for example, reference to “a biomarker” includes a single biomarker, as well as two or more biomarkers; reference to “an analyte” includes a single analyte or two or more analytes; reference to “the invention” includes single and multiple aspects of the invention; and so forth.
The use of numerical values in the various ranges specified in this application, unless expressly indicated otherwise, are stated as approximations as though the minimum and maximum values within the stated ranges were both preceded by the word “about”. In this manner, slight variations above and below the stated ranges can be used to achieve substantially the same results as values within the ranges. Also, the disclosure of these ranges is intended as a continuous range including every value between the minimum and maximum values. In addition, the present invention extends to ratios of two or more markers providing a numerical value associated with a level of risk of heart disease development or presence.
A rapid, efficient and sensitive assay is provided for the stratification of heart disease in symptomatic and asymptomatic subject.
“Stratification” includes identification, diagnosing, clarification, monitoring and/or determination of the presence, level, severity, state and/or classification of heart disease. Generally, this is based on comparing a knowledge base of levels or ratios of lipid analytes in body fluid or tissue extract to another knowledge base of predetermined levels, statistically correlated to heart disease or a condition or symptom within the spectrum of heart disease.
Hence, the present invention identifies a correlation between the level or ratios of particular lipid analytes in a subject and heart disease. The term “heart disease” as used herein is to be considered as an individual condition as well as a spectrum of conditions including a range of risk indicators of the level of disease progression. This risk ranges from minor to extreme. The ability to monitor and identify markers of heart disease enables decisions on the type of medical intervention required from behavioural modification and medicaments to surgical intervention. This is particularly the case with asymptomatic individuals or those having a family history of heart disease.
The present invention extends to any or all conditions within the clinical spectrum of “heart disease”.
Such conditions include, without being limited to, cardiomyopathies, such as, alcoholic cardiomyopathy, coronary artery disease, congenital heart disease, nutritional diseases affecting the heart, ischemic (or ischaemic) cardiomyopathy, hypertensive cardiomyopathy, valvular cardiomyopathy, inflammatory cardiomyopathy, cardiovascular disease, such as atherosclerosis, ischaemic heart disease, heart failure, hypertensive heart disease, such as, left ventricular hypertrophy, coronary heart disease, (congestive) heart failure, hypertensive cardiomyopathy, cardiac arrhythmias, inflammatory heart disease, such as, endocarditis, inflammatory cardiomegaly, myocarditis, valvular heart disease, such as, aortic valve stenosis, mitral valve prolapse and valvular cardiomyopathy
Reference herein to a “subject” includes a human which may also be considered an individual, patient, host, recipient or target. The subject may also be an animal or an animal model. The term “analyte” includes a biomarker, marker, indicator, risk factor and the like.
The lipidomic approach uses one or more of three groups of lipid analytes:

    
    
        (i) modified ceramides (modCER), modified phosphatidylcholines (modPC) and modified cholesterol esters (modCE) selected from those listed in Table 1;
        (ii) two or more non-modified lipid analytes selected from the list in Table 1; and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte (modCER, modPC and/or modCE) and at least one is a non-modified lipid analyte selected from the list in Table 1.
    
    


Accordingly, one aspect of the present invention is directed to an assay to stratify a subject as a vulnerable or non-vulnerable subject with respect to plaques, the assay comprising determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control identifies the subject as being vulnerable or non-vulnerable.

    
    


The present invention enables, therefore, a risk profile to be determined for a subject based on a lipidomic profile. The stratification or profiling enables early diagnosis, conformation of a clinical diagnosis, treatment monitoring and treatment selection.
In a particular embodiment, the lipidomic profile is associated with heart disease, the predisposition of development and/or the risk level for severity and progression.
In, a particular embodiment, the invention provides an assay to stratify a subject as a vulnerable or non-vulnerable subject with respect to plaques, the assay comprising determining the levels of at least two lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1; and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level of an individual lipid analyte listed in Table 1 is different between vulnerable subjects and non-vulnerable subjects and wherein the level of the lipid analytes in the subject relative to a control identifies the subject as being vulnerable or non-vulnerable.

    
    


In another embodiment, the assays comprise comparing the level of the at least two lipid analytes in the subject to the respective levels of the same lipid analytes in at least one control subject selected from a vulnerable subject and a non-vulnerable subject, wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the non-vulnerable subject identifies the subject as being non-vulnerable, and wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the vulnerable subject identifies the subject as being vulnerable.
Reference to a “control” broadly includes data that the skilled person would use to facilitate the accurate interpretation of technical data. In an illustrative example, the level or levels of lipid analyte(s) from a subject are compared to the respective level or levels of the same lipid analyte(s) in one or more cohorts (populations/groups) of control subjects selected from a vulnerable subject cohort wherein the subjects have been diagnosed with unstable heart disease, a non-vulnerable subject cohort wherein the subjects have been diagnosed with stable heart disease, a normal subject cohort wherein the subjects have been predetermined not to have heart disease, and a heart disease subject cohort that comprises the members of the vulnerable and non-vulnerable cohorts. In some embodiments, the control may be the level or ratio of one or more lipid analytes in a sample from the test subject taken at an earlier time point. Thus, a temporal change in analyte levels can be used to identify vulnerability or provide a correlation as to the state of heart diseases. In some embodiments, the relative levels of two or more lipid analytes provides a useful control.
In some embodiments, a control subject is a group of control subjects. The level of analytes in a control subject group may be a mean value or a preselected level, threshold or range of levels that define, characterise or distinguish a particular group. Thresholds may be selected that provide an acceptable ability to predict diagnostic or prognostic risk, treatment success, etc. In illustrative examples, receiver operating characteristic (ROC) curves are calculated by plotting the value of one or more variables versus its relative frequency in two populations (called arbitrarily “disease” and “normal” or “low risk” and “high risk” groups for example). For any particular lipid analyte(s) or class(es), a distribution of level(s) for subjects in the two populations will likely overlap. Under such conditions, a test level does not absolutely distinguish “disease” and “normal” or “vulnerable” and “non-vulnerable” with 100% accuracy, and the area of overlap indicates where the test cannot distinguish between groups. Accordingly, in some embodiments, a threshold or range is selected, above which (or below which, depending on how a lipid analyte level changes with heart disease or prognosis) the test is considered to be “positive” and below which the test is considered to be “negative”. As described in Example 4, non-parametric tests were used to establish the statistical significance of differences between different analyte levels in the different control groups (See Table 16). Linear regression analysis was also used to identify lipid analytes that are independent predictors of group assignment. Several lipid analytes were found to be independent predictor of stable or unstable CAD, specifically PI 34:0, DHC 18:1, modCer 703.6.5.87, SM 22:1 and GM3 18:0. Similarly, twenty one lipid analytes were able to distinguish individually between control and CAD patients (Table 12, Model 6). Multivariate analysis is particularly suitable for developing a predictive model based on plasma lipid profiles. A range of models including different numbers of lipid analytes (1, 2, 4, 8, 16, 22, 64 . . . 329) either alone or with traditional risk factors were examined for their ability to distinguish a particular group (Tables 18 to 20). The values from these models were used to perform ROC analyses to determine the severity and specificity of the models (see Example 6, FIG. 6). Accordingly it is possible, as demonstrated, herein to use the full range of lipid analytes or to select particular subsets of lipid analytes capable of distinguishing between particular groups.
Alternatively, or in addition, thresholds may be established by obtaining an analyte level from the same patient, to which later results may be compared. In these embodiments, the individual in effect acts as their own “control group.” In markers that increase with disease severity or prognostic risk, an increase over time in the same patient can indicate a worsening or development of disease or risk of disease or a failure of a treatment regimen, while a decrease over time can indicate remission of disease or success of a treatment regimen. Various further controls will be routinely applied by the skilled artisan. In an illustrative example, the levels of a range or panel of lipid analytes within one or more lipid class are determined and compared to predetermined levels in one or more control subject groups. Lipid analytes determined herein not to be correlated with heart disease or unstable plaques can be included as internal controls and are therefore also useful in some embodiments.
In some embodiments, lipid analyte levels in control groups are used to generate a profile of lipid analyte levels reflecting difference between levels in two control groups. Thus, a particular lipid analyte may be more abundant or less abundant in one control group compared to another control group. The data may be represented as an overall signature score or the profile may be represented as a barcode or other graphical representation. The lipid analyte levels from a test subject may be represented in the same way and similarity with the signature scope or level of “fit” to a signature barcode or other graphical representation may be determined. In other embodiments, the levels of a particular lipid analyte or lipid class are analysed and a downward or an upward trend in analyte level determined. Thus, for example, as shown in the Examples, the total PI species were 13.8% lower in unstable vs stable CAD, over and above a 13.5% decrease in the CAD group compared to control groups. In another Example, lower levels of LPC species (except LPC 20:4 and LPC 20:2) were found to be predictive of disease severity/unstable CAD, e.g. LPC 16:1 and LPC 14:0. In another example, SMI 018:0 was over represented in the unstable CAD group.
In another embodiment, the assays further comprise comparing the level of the at least two lipid analytes in the subject to the respective levels of the same lipid analytes in at least one normal subject, wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the normal subject identifies the subject as being normal with respect to plaques.
In yet another embodiment, the assays comprise determining or determining and comparing the level of at least 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30 or more lipid analytes including 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, or 331 biomarkers (lipid analytes).
In some embodiments, the lipid analytes are selected that fall within a single lipid class. Thus, in some embodiments, the level of two or more lipid analytes in one or more lipid classes are determined and compared.
In some particular embodiments, the assays further comprise determining the levels of at least two lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1; and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analytes listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level of an individual lipid analyte listed in Table 1 is different between normal subjects and heart disease subjects and wherein the level of the lipid analytes in the subject relative to a control identifies the subject as being a normal subject or a heart disease subject.

    
    


In some embodiments, the or each modified lipid analyte in (i) is selected from a modified ceramide (modCER) and a modified phosphatidylcholine (modPC).
In other embodiments, the non-modified lipid analytes in (ii) are selected from a dihexosylceramide (DHC), a sphingomyelin (SM), a phosphatidylinositol (PI), a lysophosphatidylcholine (LPC), a phosphatidylcholine (PC), an alkylphosphatidylcholine (APC), a cholesterol ester (CE), a diacylglycerol (DG) and a triacylglycerol (TG).
In still further embodiments of the assay, the or each modified lipid analyte in (iii) is selected from a modified ceramide (modCER) and a modified phosphatidylcholine (modPC) and the or each non-modified lipid in (iii) is selected from a dihexosylceramide (DHC), a sphingomyelin (SM), a phosphatidylinositol (PI), a lysophosphatidylcholine (LPC), a alkylphosphatidylcholine (APC), a cholesterol ester (CE), a diacylglycerol (DG) and a triacylglycerol (TG).
In another embodiment, the assays comprise determining the levels of at least two lipid analytes selected from modCer 731.6, GM3 18:0, PC34:5, DHC 18:1, APC 34:2, SM 18:0, Cer 18:1, PI 36:1, APC 36:0, DG 18:1 20:0, LPC 14:0, LPC 16:1, PC 24:0, Cer 18:0, PI 36:3, PI 38:2, modPC.622.4/40, LPC 18:2, LPC 24:0, PC 34:3, modPC 752.6/5.58, PI 34:0, modCer 703.6/5.87 and SM 22:1.
In another embodiment, the assays comprise determining the levels of at least four, six, eight or sixteen lipid analytes selected from the group consisting of modCer 731.6, GM3 18:0, PC34:5, DHC 18:1, APC 34:2, SM 18:0, Cer 18:1, PI 36:1, APC 36:0, DG 18:1 20:0, LPC 14:0, LPC 16:1, PC 24:0, Cer 18:0, PI 36:3, PI 38:2, modPC.622.4/40, LPC 18:2, LPC 24:0, PC 34:3, modPC 752.6/5.58, PI 34:0, modCer 703.6/5.87 and SM 22:1.
In particular embodiments, the assayed levels of lipid analytes are used in combination with one or more traditional risk factors selected from age, sex, smoker, diabetes, hypertension, CAD family history, BMI, total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP to thereby identify the subject as being vulnerable or non-vulnerable.
Suitably, the assays comprise, in some embodiments, comparing the level of the at least two lipid analytes in the subject to the respective levels of the same lipid analytes in at least one control subject selected from a normal subject and a heart disease subject, wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the heart disease subject identifies the subject as having heart disease, and wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the normal subject identifies the subject as being normal with respect to heart disease.
In yet another embodiment, the assays comprise determining or determining and comparing the levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 or 95 lipid analytes, preferably 8, 9, 10, 11, 12, 13, 14, 15 or 16 lipid analytes in Table 1 wherein the level of an individual lipid analyte listed in Table 1 is different between normal subjects and heart disease subjects. In some embodiments, any number between 2 and 331 lipid analytes include but 2 and 18 lipid analytes or any number between 2 and 18 lipid classes including 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 or 18 lipid classes are analysed.
In some embodiments, the modified lipid analyte in (i) is one or more of a modified ceramide (modCER) and a modified phosphatidylcholine (modPC).
In other embodiments, the non-modified lipid analyte in (ii) is two or more of a ceramide (CER), monohexosylceramide (MHC), dihexosylceramide (DHC), trihexosylceramide (THC), GM3 Ganglioside (GM3), modified ceramides (modCer), sphingomyelin (SM), phosphatidylserine (PS), phosphatidylinositol (PI), lysophosphatidylcholine (LPC), lysoplatelet activating factor (LPAF), phosphatidylcholine (PC), odd-chain phosphatidylcholine (oddPC), alkylphosphatidylcholine (APC), modified phosphatidylcholine (modPC), cholesterol esters (CE), diacylglycerol (DG), and triacylglycerol (TG).
In still further embodiments, the or each modified lipid analyte in (iii) is one or more of a modified ceramide (modCER) and a modified phosphatidylcholine (modPC) and the or each non-modified lipid in (iii) is selected from a ceramide (CER), a monohexosylceramide (MHC), a dihexosylceramide (DHC), trihexosylceramide (THC), GM3 Ganglioside (GM3), modified ceramides (modCer), sphingomyelin (SM), phosphatidylserine (PS), phosphatidylinositol (PI), lysophosphatidylcholine (LPC), lysoplatelet activating factor (LPAF), phosphatidylcholine (PC), odd-chain phosphatidylcholine (oddPC), alkylphosphatidylcholine (APC), modified phosphatidylcholine (modPC), cholesterol esters (CE), diacylglycerol (DG) and a triacylglycerol (TG).
In an illustrative example, the lipid analytes are two or more of LPC 22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0 and CE 22:4.
In a further illustrative example, the lipid analytes are two or more of LPC 22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0, CE 22:4, ModPC 580.4/4.84, PS 40:6, modPC 752.6/5.58, APC 32:1, oddPC 37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC 20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1, modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1, modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19, C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM 18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG 18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.
In another illustrative example, the lipid analytes are four or more, six or more, eight or more or sixteen or more of LPC 22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0, CE 22:4, ModPC 580.4/4.84, PS 40:6, modPC 752.6/5.58, APC 32:1, oddPC 37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC 20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1, modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1, modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19, C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM 18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG 18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.
In some further embodiments, the assayed levels of lipid analytes are used in combination with one or more traditional risk factors selected from age, sex, smoker, diabetes, hypertension, CAD family history, BMI, total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP to thereby identify the subject as being normal or having heart disease.
In a different embodiment, the present invention contemplates an assay to stratify a subject with respect to heart disease, the assay comprising determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a indication or correlation as to the presence, absence state, classification or progression of heart disease.

    
    


In particular embodiments, the invention provides an assay to stratify a subject with respect to heart disease, the assay comprising determining the levels of at least two lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level of an individual lipid analyte listed in Table 1 is different between normal and heart disease subjects and wherein the level of the lipid analytes in the subject relative to a control provides an indication of the presence or absence of heart disease.

    
    


In some embodiments, the assays comprise comparing the level of the at least two lipid analytes in the subject to the respective levels of the same lipid analytes in at least one control subject selected from a normal subject and a heart disease subject, wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the heart disease subject identifies the subject having heart disease, and wherein a similarity in the respective levels of the at least two lipid analytes between the subject and the normal subject identifies the subject as a normal subject with respect to heart disease.
In illustrative embodiments, the assays comprise determining or determining and comparing the levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39; 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 or 95, preferably at least 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 lipid analytes wherein the level of an individual lipid analyte listed in Table 1 is different between normal and heart disease subjects.
In some embodiments, the modified lipid analyte in (i) is one or more of a modified ceramide (modCER) and a modified phosphatidylcholine (modPC).
In other embodiments, the non-modified lipid analyte in (ii) is two or more of a ceramide (CER), monohexosylceramide (MHC), dihexosylceramide (DHC), trihexosylceramide (THC), GM3 Ganglioside (GM3), modified ceramides (modCer), sphingomyelin (SM), phosphatidylserine (PS), phosphatidylinositol (PI), lysophosphatidylcholine (LPC), lysoplatelet activating factor (LPAF), phosphatidylcholine (PC), odd-chain phosphatidylcholine (oddPC), alkylphosphatidylcholine (APC), modified phosphatidylcholine (modPC), cholesterol esters (CE), diacylglycerol (DG), and triacylglycerol (TG).
In still further embodiments, the or each modified lipid analyte in (iii) is one or more of a modified ceramide (modCER) and a modified phosphatidylcholine (modPC) and the or each non-modified lipid in (iii) is selected from a ceramide (CER), a monohexosylceramide (MHC), a dihexosylceramide (DHC), trihexosylceramide (THC), GM3 Ganglioside (GM3), modified ceramides (modCer), sphingomyelin (SM), phosphatidylserine (PS), phosphatidylinositol (PI), lysophosphatidylcholine (LPC), lysoplatelet activating factor (LPAF), phosphatidylcholine (PC), odd-chain phosphatidylcholine (oddPC), alkylphosphatidylcholine (APC), modified phosphatidylcholine (modPC), cholesterol esters (CE), diacylglycerol (DG) and a triacylglycerol (TG).
In an illustrative example, the lipid analytes are two or more of LPC 22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0, CE 22:4, ModPC 580.4/4.84, PS 40:6, modPC 752.6/5.58, APC 32:1, oddPC 37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC 20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1, modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1, modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19, C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM 18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG 18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.
In another illustrative example, the lipid analytes are four or more, six or more, eight or more or sixteen or more of LPC 22:0, PS 40:6, PI 34:0, Cer 20:0, Cer 18:0, APC 34:2, PC 34:5, LPC 20:3, PC 28:0, modPC 692.4/5.8, APC 30:0, modPC 736.5/5.7, LPC 20:4, APC 38:6, modPC 720.5.4.5, PI 36:0, LPC 24:0, PS 40:5, LPC 20:0, modPC 877.6/6.0, CE 22:4, ModPC 580.4/4.84, PS 40:6, modPC 752.6/5.58; APC 32:1, oddPC 37:3, GM3 24:1, oddPC 33:0, APC 36:0, CE 24:3, SM 20:1, SM 18:0, LPC 20:0, modCE 682.7/8.76, COH, Cer 20:0, LPC 16:1, TG 16:1 16:1 16:1, modPC 564.4/4.70, modPC 720.6/4.52, modPC 608.4/5.33, PE 38:3, PE 38:1, modPC 580.4/4.84, PS 40:6, GM3 22:0, PC 37:3, PC 33:0, modPC 788.6/5.19, C24:3, C24:4, modPC 666.4/2.99, modPC 678.4/4.37, modCer 731.6/6.22, SM 18:1, APC 36:5, modPC 769.6/6.25, APC 36:3, oddPC 35:4, PG 18:1 18:1, TG 18:1 18:1 18:2, modPC 881.7/6.05, CE 17:0 and PI 38:5.
In some further embodiments, the assayed levels of lipid analytes are used in combination with one or more traditional risk factors selected from age, sex, smoker, diabetes, hypertension, CAD family history, BMI, total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP to thereby identify the subject as being normal or having heart disease.
Still another aspect of the present invention contemplates the use of a panel of lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

in the manufacture of an assay to identify the presence, state, classification or progression of heart disease in a subject.

    
    


In some embodiments, lipid analytes are two or more selected from a ceramide (Cer) including Cer 16:0, Cer 18:1, Cer 18:0, Cer 20:0, Cer 22:0, Cer 24:1, Cer 24:0; a monohexosylceramide (MHC) including MHC 16:0, MHC 18:1, MHC 18:0, MHC 20:0, MHC 22:0, MHC 24:1, MHC 24:0; a dihexosylceramide (DHC) including DHC 16:0, DHC 18:1, DHC 18:0, DHC 20:0, DHC 22:0, DHC 24:1, DHC 24:0; a trihexosylcermide (THC) including THC 16:0, THC 18:1, THC 18:0, THC 20:0, THC 22:0, THC 24:1, THC 24:0; a GM3 ganglioside (GM3) including GM3 16:0, GM3 18:0, GM3 20:0, GM3 22:0, GM3 24:1, GM3 24:0; a sphingomyelin (SM) including SM 14:0, SM 15:0, SM 16:1, SM 16:0, SM 18:1, SM 18:0, SM 20:1, SM 22:1, SM 22:0, SM 24:2, SM 24:1, SM 24:0; a phosphatidylglycerol (PG) including PG 16:1 18:1, PG 16:0 18:1, PG 18:1 18:1, PG 18:0 18:1; a bis(monoacylglycerol)phosphate (BMP) including BMP 18:1 18:1; phosphatidylserine (PS) including PS 36:2, PS 36:1, PS 38:5, PS 38:4, PS 38:3, PS 40:6, PS 40:5; phosphatidylethanolamine (PE) including PE 32:1, PE 32:0, PE 34:2, PE 34:1, PE 36:5, PE 36:4, PE 36:3, PE 36:2, PE 36:1, PE 36:0, PE 38:6, PE 38:5, PE 38:4, PE 38:3, PE 38:2, PE 38:1, PE 40:7, PE 40:6; a phosphatidylinositol (PI) including PI 32:1, PI 32:0, PI 34:1, PI 34:0, PI 36:4, PI 36:3, PI 36:2, PI 36:1, PI 36:0, PI 38:6, PI 38:5, PI 38:4, PI 38:3, PI 38:2, PI 40:6, PI 40:5, PI 40:4; a lysophosphatidylcholine (LPC) including LPC 14:0, LPC 15:0, LPC 16:1, LPC 16:0, LPC 18:2, LPC 18:1, LPC 18:0, LPC 20:5 LPC 20:4, LPC 20:3, LPC 20:2, LPC 20:1, LPC 20:0, LPC 22:6; a lysoplatelet activating factor (LPAF) including LPAF 16:0, LPAF 18:1, LPAF 18:0; a phosphatidylcholine (PC) including PC 30:2, PC 32:2, PC 32:1, PC 32:0, PC 34:3, PC 34:2, PC 34:1, PC 34:0, PC 36:5, PC 36:4, PC 36:3, PC 36:2, PC 38:6, PC 38:5, PC 38:4, PC 40:7, PC 40:6, PC 40:5, PC 44:12; an alkylphosphatidylcholine (APC) including APC 32:1, APC 32:0, APC 34:2, APC 34:1, APC 34:0, APC 36:5, APC 36:4, APC 36:3, APC 36:2, APC 36:1, APC 36:0, APC 38:6, APC 38:5, APC 38:4, APC 38:3, APC 38:2; a cholesterol ester (CE) including CE 14:0, CE 15:0, CE 16:2, CE 16:1, CE 16:0, CE 17:1, CE 17:0, CE 18:3, CE 18:2, CE 18:1, CE 18:0, CE 20:5, CE 20:4, CE 20:3, CE 20:2, CE 20:1, CE 22:6, CE 22:5, CE 22:4, CE 22:3, CE 22:2, CE 22:1, CE 22:0, CE 24:6, CE 24:5, CE 24:4, CE 24:3, CE 24:2, CE 24:1, CE 24:0; a diacylglycerol (DG) including DG 14:0 14:0, DG 14:1 16:0, DG 14:0 16:0, DG 14:0 18:2, DG 14:0 18:1, DG 16:0 16:0, DG 16:0 18:2, DG 16:1 18:1, DG 16:0 18:1, DG 18:0 16:1, DG 16:0 18:0, DG 16:0 20:4, DG 18:1 18:3, DG 18:2 18:2, DG 16:0 20:3, DG 18:1 18:2, DG 18:0 18:2, DG 18:1 18:1, DG 18:0 18:1, DG 16:0 20:0, DG 18:0 18:0, DG 16:0 22:6, DG 16:0 22:5, DG 18:1 20:4, DG 18:0 20:4, DG 18:1 20:3, DG 18:1 20:0; and a triaclyglycerol (TG) including TG 14:0 16:1 18:2, TG 16:1 16:1 16:1, TG 14:0 16:0 18:2, TG 14:0 16:1 18:1, TG 14:1 16:0 18:1, TG 14:1 16:1 18:0, TG 18:1 14:0 16:0, TG 16:0 16:0 16:0, TG 15:0 18:1 16:0, TG 17:0 16:0 16:1, TG 17:0 18:1 14:0, TG 14:0 18:2 18:2, TG 14:1 18:0 18:2, TG 14:1 18:1 18:1, TG 16:1 16:1 18:1, TG 16:0 16:0 18:2, TG 16:1 16:1 18:0, TG 16:0 16:1 18:1, TG 14:0 18:0 18:1, TG 16:0 16:0 18:1, TG 16:0 16:0 18:0, TG 15:0 18:1 18:1, TG 17:0 18:1 16:1, TG 17:0 18:2 16:0, TG 17:0 18:1 16:0, TG 17:0 16:0 18:0, TG 16:0 18:2 18:2, TG 16:1 18:1 18:2, TG 16:1 18:1 18:1, TG 16:0 18:1 18:2, TG 16:0 18:1 18:1, TG 16:0 18:0 18:1, TG 17:0 18:1 18:1, TG 18:2 18:2 18:2, TG 18:1 18:2 18:2, TG 18:0 18:2 18:2, TG 18:1 18:1 18:2, TG 18:1 18:1 18:1, TG 18:0 18:1 18:1, TG 18:0 18:0 18:1, TG 18:0 18:0 18:0, TG 18:2 18:2 20:4, TG 18:1 18:1 20:4, TG 18:1 18:1 22:6; a modified ceramide (modCer) including modCer 576.5/7.68, modCer 614.6/5.72, modCer 632.6/9.22, modCer 651.6/7.56, modCer 703.6/5.87, modCer 731.6/6.22, modCer 766.6/7.17, modCer 769.6/8.01, modCer 798.7/7.29, modCer 875.7/9.23, modCer 883.8/7.75, modCer 886.8/9.06, modCer 910.8/8.98, modCer 921.8/9.05; phosphatidylcholine (modPC) including modPC 506.3/3.50, modPC 508.3/3.30, modPC 510.3/4.00, modPC 512.3/1.70, modPC 536.3/3.50, modPC 538.3/4.10, modPC 552.4/3.90, modPC 564.4/4.70, modPC 566.4/5.10, modPC 580.4/4.84, modPC 594.4/3.26, modPC 608.4/3.84, modPC 610.4/2.03, modPC 622.4/4.54, modPC 633.4/4.51, modPC 636.4/3.37, modPC 645.4/4.49, modPC 650.4/3.24, modPC 650.4/4.44, modPC 650.4/3.94, modPC 664.4/4.22, modPC 666.4/2.99, modPC 678.4/4.37, modPC 678.4/4.94, modPC 678.4/5.51, modPC 690.4/4.11, modPC 690.4/4.90, modPC 690.4/6.00, modPC 692.4/5.05, modPC 692.4/5.52, modPC 692.4/6.10, modPC 694.4/6.20, modPC 703.5/4.09, modPC 704.5/3.81, modPC 706.5/3.79, modPC 720.5/4.52, modPC 736.5/5.38, modPC 743.5/5.91, modPC 752.5/5.58, modPC 772.5/5.37, modPC 773.6/6.47, modPC 788.6/5.19, modPC 801.6/6.70, modPC 816.6/5.58, modPC 818.6/6.10, modPC 818.6/6.48, modPC 828.6/6.03, modPC 843.6/7.10, modPC 866.6/7.24, modPC 878.6/5.98, modPC 881.6/6.05; and a cholesterol ester (modCE) including modCE 558.5/7.74, modCE 588.5/7.94, modCE 682.7/8.76, modCE 790.8/6.57.
The lipidomic profile further enables determination of endpoints in pharmacotranslational studies. For example, clinical trials can take many months or even years to establish the pharmacological parameters for a medicament to be used in coronary care. However, these parameters may be associated with a lipidomic profile associated with a health state. Hence, the clinical trial can be expedited by first selecting a medicament and pharmaceutical parameters which result in a lipidomic profile associated with the desired health state.
Accordingly, another aspect of the present invention contemplates a method for determining the pharmacoefficacy of a medicament for use in heart disease treatment, the method comprising selecting a medicament and its concentration and/or formulation parameters which provide a lipidomic profile associated or characteristic of a healthy individual, the lipidomic profile identified by determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation as to the presence, state, classification or progression of heart disease.

    
    


Another aspect of the present invention provides a method for conducting a clinical trial for a medicament for the treatment or prophylaxis of heart disease, the method comprising conducting the clinical trial using a formulation of the medicament which generates a lipidomic profile associated or characteristic of a healthy individual, the lipidomic profile identified by determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation as to the presence, state, classification or progression of heart disease.

    
    


The lipidomic profile, therefore, can be used as a marker to define a desired state of health in an individual. It can be considered, therefore, a defined surrogate endpoint or desired endpoint in clinical management of subjects having heart disease treatment.
There are many methods which may be used to detect lipid analyte levels including mass spectrometry. In a particular, liquid chromatography, electrospray ionization-tandem mass spectrometry is used.
Immunological assays can also be done in any convenient formats known in the art. These include Western blots, immunohistochemical assays and ELISA assays. Any means for detecting a level of a lipid analyte can be used in accordance with the present invention.
The biological sample is any fluid or cell or tissue extract in a subject which comprises lipids. In one embodiment, the biological sample is a tissue of the heart or surrounding the heart. In another embodiment, the biological sample includes blood, plasma, serum, lymph, urine and saliva or cell extracts.
The present invention identifies the presence of a lipidomic profile associated with heart disease or a risk of developing same. In order to detect a lipid analyte, a biological sample is prepared and analyzed for a difference in levels or ratios of levels between the subject being tested and a control. In this context, a “control” includes the levels in a statistically significant normal population.
The identification of the association between the pathophysiology of heart disease and levels of or ratios of lipids permits the early presymptomatic screening of individuals to identify those at risk for developing heart disease or to identify the cause of such a disorder or the risk that any individual will develop same. The subject assay enables practitioners to identify or stratify individuals at risk for certain behavioural states associated with heart disease or its manifestations including an inability to overcome symptoms of heart disease after initial treatment. Certain behavioural or therapeutic or dietary protocols may then be introduced to reduce the risk of developing heart disease. Presymptomatic diagnosis will enable better treatment of heart disease, including the use of existing medical therapies. Lipidotyping of individuals is useful for (a) identifying a form of heart disease which will respond to particular drugs, (b) identifying types of heart disease which responds well to specific medications or medication types with fewer adverse effects and (c) guide new drug discovery and testing.
Even yet another aspect of the present invention relates to a method of treatment or prophylaxis of a subject comprising assaying the subject with respect to heart disease by determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease and then providing therapeutic and/or behavioural modification to the subject.

    
    


The present invention further provides a web-based system where data on expression levels of lipids are provided by a client server to a central processor which analyses and compares to a control and optionally considers other information such as patient age, sex, weight and other medical conditions and then provides a report, such as, for example, a risk factor for disease severity or progression or status or an index of probability of heart disease in symptomatic or asymptomatic individuals.
Hence, knowledge-based computer software and hardware also form part of the present invention.
In particular, the assays of the present invention may be used in existing or newly developed knowledge-based architecture or platforms associated with pathology services. For example, results from the assays are transmitted via a communications network (e.g. the internet) to a processing system in which an algorithm is stored and used to generate a predicted posterior probability value which translates to the index of disease probability which is then forwarded to an end user in the form of a diagnostic or predictive report.
The assay may, therefore, be in the form of a kit or computer-based system which comprises the reagents necessary to detect the concentration of the lipid biomarkers and the computer hardware and/or software to facilitate determination and transmission of reports to a clinician.
The assay of the present invention permits integration into existing or newly developed pathology architecture or platform systems. For example, the present invention contemplates a method of allowing a user to determine the status of a subject with respect to a heart disease or subtype thereof or stage of heart disease, the method including:

    
    
        (a) receiving data in the form of levels or concentrations of a lipid analyte selected from the list consisting of:
        
            (i) one or more modified lipid analytes listed in Table 1;
            (ii) two or more non-modified lipid analytes listed in Table 1, and
            (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;
            wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease;
            from the user via a communications network;
        
        
        (b) processing the subject data via multivariate analysis to provide a disease index value;
        (c) determining the status of the subject in accordance with the results of the disease index value in comparison with predetermined values; and
        (d) transferring an indication of the status of the subject to the user via the communications network reference to the multivariate analysis includes an algorithm which performs the multivariate or univariate analysis function.
    
    


Conveniently, the method generally further includes:

    
    
        (a) having the user determine the data using a remote end station; and
        (b) transferring the data from the end station to the base station via the communications network.
    
    


The base station can include first and second processing systems, in which case the method can include:

    
    
        (a) transferring the data to the first processing system;
        (b) transferring the data to the second processing system; and
        (c) causing the first processing system to perform the multivariate analysis function to generate the disease index value.
    
    


The method may also include:

    
    
        (a) transferring the results of the multivariate analysis function to the first processing system; and
        (b) causing the first processing system to determine the status of the subject.
    
    


In this case, the method also includes at least one of:

    
    
        (a) transferring the data between the communications network and the first processing system through a first firewall; and
        (b) transferring the data between the first and the second processing systems through a second firewall.
    
    


The second processing system may be coupled to a database adapted to store predetermined data and/or the multivariate analysis function, the method include:

    
    
        (a) querying the database to obtain at least selected predetermined data or access to the multivariate analysis function from the database; and
        (b) comparing the selected predetermined data to the subject data or generating a predicted probability index.
    
    


The second processing system can be coupled to a database, the method including storing the data in the database.
The method can also include having the user determine the data using a secure array, the secure array of elements capable of determining the level of biomarker and having a number of features each located at respective position(s) on the respective code.
In this case, the method typically includes causing the base station to:

    
    
        (a) determine the code from the data;
        (b) determine a layout indicating the position of each feature on the array; and
        (c) determine the parameter values in accordance with the determined layout, and the data.
    
    


The method can also include causing the base station to:

    
    
        (a) determine payment information, the payment information representing the provision of payment by the user; and
        (b) perform the comparison in response to the determination of the payment information.
    
    


The present invention also provides a base station for determining the status of a subject with respect to a heart disease or a subtype thereof or a stage of heart disease, the base station including:

    
    
        (a) a store method;
        (b) a processing system, the processing system being adapted to:
        (c) receive subject data from the user via a communications network, the data including levels or concentrations of a lipid analyte selected from the list consisting of:
        
            (i) one or more modified lipid analytes listed in Table 1;
            (ii) two or more non-modified lipid analytes listed in Table 1, and
            (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;
            wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease;
        
        
        (d) performing an algorithmic function including comparing the data to predetermined data;
        (e) determining the status of the subject in accordance with the results of the algorithmic function including the comparison; and
        (f) output an indication of the status of the subject to the user via the communications network.
    
    


The processing system can be adapted to receive data from a remote end station adapted to determine the data.
The processing system may include:

    
    
        (a) a first processing system adapted to:
        
            (i) receive the data; and
            (ii) determine the status of the subject in accordance with the results of the multivariate analysis function including comparing the data; and
        
        
        (b) a second processing system adapted to:
        
            (i) receive the data from the processing system;
            (ii) perform the multivariate or univariate analysis function including the comparison; and
            (iii) transfer the results to the first processing system.
        
        
    
    


The base station typically includes:

    
    
        (a) a first firewall for coupling the first processing system to the communications network; and
        (b) a second firewall for coupling the first and the second processing systems.
    
    


The processing system can be coupled to a database, the processing system being adapted to store the data in the database.
Still another aspect of the present invention contemplates the use of a panel of lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

in the manufacture of an assay to identify the presence, state, classification or progression of heart disease in a subject.

    
    


In another embodiment, the present invention contemplates an assay for determining the presence of heart disease in a subject, the assay comprising determining the concentration of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease in a biological sample from the subject wherein an altered concentration in the lipid or lipids is indicative of the subject having heart disease.

    
    


In accordance with this embodiment, levels of the lipid(s) may be screened alone or in combination with other biomarkers or heart disease indicators. An “altered” level means an increase or elevation or a decrease or reduction in the concentrations of the lipids.
The determination of the concentrations or levels of the biomarkers enables establishment of a diagnostic rule based on the concentrations relative to controls. Alternatively, the diagnostic rule is based on the application of a statistical and machine learning algorithm. Such an algorithm uses relationships between biomarkers and disease status observed in training data (with known disease status) to infer relationships which are then used to predict the status of patients with unknown status. An algorithm is, employed which provides an index of probability that a patient has heart disease or a state or form or class thereof. The algorithm performs a multivariate analysis function.
Hence, the present invention provides a diagnostic rule based on the application of statistical and machine learning algorithms. Such an algorithm uses the relationships between lipidomic biomarkers and disease status observed in training data (with known disease status) to infer relationships which are then used to predict the status of patients with unknown status. Practitioners skilled in the art of data analysis recognize that many different forms of inferring relationships in the training data may be used without materially changing the present invention.
Hence, the present invention contemplates the use of a knowledge base of training data comprising levels of lipid biomarkers from a subject with a heart condition to generate an algorithm which, upon input of a second knowledge base of data comprising levels of the same biomarkers from a patient with an unknown heart disease condition, provides an index of probability that predicts the nature of the heart disease condition.
The term “training data” includes knowledge of levels of lipid biomarkers relative to a control. A “control” includes a comparison to levels of biomarkers in a subject devoid of the heart disease condition or cured of the condition or may be a statistically determined level based on trials. The term “levels” also encompasses ratios of levels of lipid biomarkers.
Hence, the “training data” includes levels or ratios of one or more of three groups of lipid analytes selected from

    
    
        (i) modified ceramides (modCER), modified phosphatidylcholines (modPC) and modified cholesterol esters (modCE) selected from those listed in Table 1;
        (ii) two or more non-modified lipid analytes selected from the list in Table 1; and/or
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 (modCER, modPC and/or modCE) and at least one is a non-modified lipid analyte, selected from the list in Table 1.
    
    


The present invention further provides a panel of lipidomic biomarkers useful in the detection of a heart disease, the panel comprising lipid analytes selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes, relative to a control provides a correlation to the presence, state, classification or progression of heart disease.

    
    


The lipid biomarkers contemplated herein include from one to 331 biomarkers such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330 or 331 biomarkers. The levels or concentrations of the biomarkers provide the input test data referred to herein as a “second knowledge base of data”. The second knowledge base of data either is considered relative to a control or is fed into an algorithm generated by a “first knowledge base of data” which comprise information of the levels of biomarkers in a subject with a known heart disease condition. The second knowledge base of data is from a subject of unknown status with respect to a heart disease condition. The output of the algorithm or the comparison to a control is a probability or risk factor, referred to herein as “an index of probability”, of a subject having a particular heart disease condition or not having the condition. This includes determining whether the subject has unstable (vulnerable patient) or stable (non-vulnerable patient) plaques:
Data generated from the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

are input data. The input of data comprising the lipid analytes is compared with a control or is put into the algorithm which provides a risk value of the likelihood that the subject has, for example, heart disease. A treatment regime can also be monitored as well as a likelihood of a relapse.

    
    


In context of the present disclosure, “fluid” includes any blood fraction, for example serum or plasma, that can be analyzed according to the methods described herein. By measuring blood levels of a particular lipid biomarker(s), it is meant that any appropriate blood fraction can be tested to determine blood levels and that data can be reported as a value present in that fraction. Other fluids contemplated herein include ascites, tissue exudate, urine, lymph fluid, mucus and respiratory fluid.
As described above, methods for diagnosing heart disease by determining levels of specific identified lipid biomarkers as listed in Table 1 and using these levels as second knowledge base data in an algorithm generated with first knowledge base data or levels of the same biomarkers in patents with a known disease. Also provided are methods of detecting symptomatic heart disease comprising determining the presence and/or velocity of specific identified lipid biomarkers in a subject's sample. By “velocity” it is meant the change in the concentration of the biomarker in a patient's sample over time.
The term “sample” as used herein means any sample containing lipid analytes that one wishes to detect including, but not limited to, biological fluids (including blood, plasma, serum, ascites), tissue extracts, freshly harvested cells, and lysates of cells which have been incubated in cell cultures. In a particular embodiment, the sample is heart tissue, one or more plaque, blood, serum, plasma or ascites.
As indicated above, the “subject” can be any mammal, generally human, suspected of having or having heart disease. The subject may be symptomatic or asymptomatic.
The term “control sample” includes any sample that can be used to establish a first knowledge base of data from subjects with a known disease status.
The method of the subject invention may be used in the diagnosis and staging of heart disease. The present invention may also be used to monitor the progression of a condition and to monitor whether a particular treatment is effective or not. In particular, the method can be used to confirm the absence or amelioration of the symptoms of the condition such as following surgery, stents, medication or behavioural change.
In an embodiment, the subject invention contemplates a method for monitoring the progression of heart disease in a patient, comprising:

    
    
        (a) providing a sample from a patient;
        (b) determining the level of a lipid analyte selected from the list consisting of:
        
            (i) one or more modified lipid analytes listed in Table 1;
            (ii) two or more non-modified lipid analytes listed in Table 1, and
            (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease subjecting the levels to an algorithm to provide an index of probability of the patient having heart disease; and

        
        
        (c) repeating steps (a) and (b) at a later point in time and comparing the result of step (b) with the result of step (c) wherein a difference in the index of probability is indicative of the progression of the condition in the patient.
    
    


In particular, an increased index of probability of a disease condition at the later time point may indicate that the condition is progressing and that the treatment (if applicable) is not being effective. In contrast, a decreased index of probability at the later time point may indicate that the condition is regressing and that the treatment (if applicable) is effective.
The present invention further provides an algorithm-based screening assay to screen samples from patients. Generally, input data are collected based on levels of one or more lipid biomarkers and subjected to an algorithm to assess the statistical significance of any elevation or reduction in levels which information is then output data. Computer software and hardware for assessing input data are encompassed by the present invention.
Another aspect of the present invention contemplates a method of treating a patient with heart disease the method comprising subjecting the patient to a diagnostic assay to determine an index of probability of the patient having the heart condition, the assay comprising determining the levels of a lipid analyte selected from the list consisting of:

    
    
        (i) one or more modified lipid analytes listed in Table 1;
        (ii) two or more non-modified lipid analytes listed in Table 1, and
        (iii) two or more lipid analytes wherein at least one is a modified lipid analyte listed in Table 1 and at least one is a non-modified lipid analyte listed in Table 1;

wherein the level or ratio of the lipid analyte or analytes relative to a control provides a correlation to the presence, state, classification or progression of heart disease and where there is a risk of the patient having the condition, subjecting the patient to surgical intervention, medication and/or behavioural change and then monitoring index of probability over time.

    
    


Reference to an “algorithm” or “algorithmic functions” as outlined above includes the performance of a multivariate or univariate analysis function. A range of different architectures and platforms may be implemented in addition to those described above. It will be appreciated that any form of architecture suitable for implementing the present invention may be used. However, one beneficial technique is the use of distributed architectures. In particular, a number of end stations may be provided at respective geographical locations. This can increase the efficiency of the system by reducing data bandwidth costs and requirements, as well as ensuring that if one base station becomes congested or a fault occurs, other end stations could take over. This also allows load sharing or the like, to ensure access to the system is available at all times.
In this case, it would be necessary to ensure that the base station contains the same information and signature such that different end stations can be used.
It will also be appreciated that in one example, the end stations can be hand-held devices, such as PDAs, mobile phones, or the like, which are capable of transferring the subject data to the base station via a communications network such as the Internet, and receiving the reports.
In the above aspects, the term “data” means the levels or concentrations of the biomarkers. The “communications network” includes the internet. When a server is used, it is generally a client server or more particularly a simple object application protocol (SOAP).
A report outlining the likelihood of heart disease by the subject is issued.
The present invention is further described by the following non-limiting Examples. Materials and Methods used in these Examples are provided below.
Materials and Methods
Sample Collection
Plasma samples from the CAD patients used in this study were collected as part of a previous study conducted by White et al. Cardiovascular Research 75:813-20, 2007. A total of 202 patients with de novo presentation of CAD who were undergoing coronary angiography were recruited (White et al. supra 2007). Patients who had undergone previous coronary revascularization were excluded. Of the original 202 patients, plasma samples from 143 were available for use in this project. Patients were classified as either stable (n=61) or unstable (n=81) by two independent cardiologists on the basis of their symptoms, 12-lead ECG and cardiac troponin I measurements in accordance with the Braunwald criteria (White et al. supra 2007; Braunwald E. Circulation 80:410-4, 1989). Venous blood samples were collected into EDTA tubes. The plasma was prepared by centrifugation (1000×g, 15 minutes at 4° C.) and stored at −80° C. until required. Biochemical, lipid, and hematological parameters as well as clinical characteristics were measured. These included total cholesterol, LDL, high density lipoprotein (HDL), blood pressure, C reactive protein (CRP), smoking status, medications and body mass index (BMI).
Plasma samples from a cohort of 61 healthy individuals were obtained and used as control samples. Patients were not receiving medication for coronary vascular disease (CVD), diabetes or hypertension and had no history of myocardial infarction (MI). Additionally, patients displayed blood pressure <131/86 mm Hg, fasting total cholesterol <5.6 mmol/L, fasting triglycerides <2.0 mmol/L and fasting plasma glucose <6.1 mmol/L. Plasma was prepared by centrifugation (1500×g, 10 minutes at 4° C.) within 24 hours of collection. The plasma samples had not been thawed prior to this study.
Sample Preparation and Lipid Extraction
Plasma samples (200 μL) were thawed and treated with the antioxidant butylhydroxytoluene (BHT) (1 μL of 100 mM in ethanol) and immediately vortexed. Lipid extraction was performed using a modification of the method of Folch et al. J Biol Chem 226:497-509, 1957. A 10 μL aliquot of plasma was transferred to an eppendorf tube with 104 of internal standard mix 1 and 5 μL of internal standard mix 2 (Table 2). CHCl3/MeOH (2:1) (200 μL) was added followed by brief vortexing. Samples were placed on a rotary mixer for ten minutes and then sonicated in a water bath at room temperature for thirty minutes. After sonication, the samples were incubated for twenty minutes at room temperature followed by centrifugation (16,000×g, 10 minutes at room temperature). The supernatant was transferred into a 0.5 mL polypropylene 96 well plate and dried under a stream of nitrogen at 40° C. The samples were resuspended in 50 μL water saturated butanol followed by ten minutes sonication. Then 50 μL of 10 mM ammonium formate in methanol was added. The samples were centrifuged (3,350×g, 5 minutes at room temperature) and the supernatant transferred into 0.2 mL micro-inserts placed into 32×11.6 mm glass vials with Teflon insert caps. Once extracted the samples were immediately subjected to mass spectrometry.
Mass Spectrometry
Lipid analysis was performed by liquid chromatography, electrospray ionisation-tandem mass spectrometry (LC ESI-MS/MS) using a HP 1200 liquid chromatography system combined with a PE Sciex API 4000 Q/TRAP mass spectrometer with a turbo-ionspray source (350° C.) and Analyst 1.5 data system. A Zorbax C18, 1.8 μm, 50×2.1 mm column was used for LC separation. The mobile phase consisted of tetrahydrofuran:methanol:water in the ratios 30:20:50 (Solvent A) and 75:20:5 (Solvent B), both containing 10 mM NH4COOH. The following gradient conditions were employed for all lipids except the DG and TG; 100% A/0% B reducing to 0% A/100% B over eight minutes followed by 2 minutes at 0% A/100% B, a return to 100% A/0% B over 0.5 minute then held for 3.5 minutes at 100% A/0% B prior to the next injection. DG and TG were separated using the same system with an isocratic flow at 15% A/85% for 6 minutes between injections.
The optimisation of voltages for collision energy (CE), declustering potential (DP), entrance potential (EP) and cell exit potential (CXP) was carried out using the tuning and optimisation feature of the instrument software (Analyst 1.5).
Nomenclature
The nomenclature (both systematic and common names) used in this document has come primarily from the two recent publications on this topic from the Lipid Maps Consortium (See Fahy et al., J Lipid Res. 51(6): 1618, 2010 and Fahy et al., J Lipid Res. 50: S9-14, 2009).
In addition, a number of terms have been used to define lipid species where the full structure is not known but where characteristic collision induced fragmentation data has provided us with a partial structure of the lipid species. These are as follows
modPC xxx.x/yy.y=modified or undefined phosphocholine containing lipid species with mass/charge ratio of the M+H ion denoted by xxx.x and retention time under the presently disclosed defined chromatographic conditions defined as yy.y minutes.
modCer xxx.x/yy.y=modified or undefined sphingosine containing lipid species with mass/charge ratio of the M+H ion denoted by xxx.x and retention time under the presently disclosed defined chromatographic conditions defined as yy.y minutes.
modCE xxx.x/yy.y=modified or undefined cholesterol containing lipid species with mass/charge ratio of the M+H ion denoted by xxx.x and retention time under the presently disclosed defined chromatographic conditions defined as yy.y minutes.
Modified PC species initially referred to as modPC 552.4/3.90, modP C 580.4/4.84, modPC 508.3/3.30, modPC 510.3/4.00, modPC 564.4/4.70, modPC 566.4/5.10, modPC752.5/5.7, modPC692.4/5.8, modPC678.4/5.4, modPC622.4/4.0, modPC878.6/7.1, modPC881.6/6.1 and modPC818.6/6.6, have been reclassified as LPC 20:0, LPC 22:0, LPAF 18:1, LPAF 18:0, LPAF 22:1, LPAF 22:0, PC34:5, APC 30:0, PC 28:0, PC 24:0, modPC877.6/7.1, modPC879.6/6.1 and APC 40:7, respectively. A small number of modPC species have been removed from Table 1, namely modPC 590.4/4.80, modPC 592.4/5.10, modPC 608.4/5.33, modPC 745.5/6.35, modPC 764.5/6.52 and modPC 769.5/6.25.
Identification of Potential Biomarkers:
1-O-acylceramides, oxidized phosphatidylcholine (OxPC) and oxidized cholesterol esters (OxCE) were thought to be potential biomarkers of the presence and progression of CAD. To identify lipid species in each of these classes, precursor ion scans were performed on a subset of 30 individuals (10 healthy controls, 10 stable CAD and 10 unstable CAD) chosen at random from our cohort.
Identification of Modified Ceramides:
Precursor scans were performed to identify 1-O-acylceramide species in plasma. Fragmentation of ceramides by CID in Q2 cleaves the bond between the carbon and the nitrogen at the sphingoid base and, with the loss of water, produces a daughter ion with a m/z 264.3 (Murphy et al. Chem Rev 101:479-526, 2001). Thus a precursor ion scan for m/z 264 will identify all modified ceramides including 1-O-acylceramides. These are referred to collectively as modified ceramides (modCer). Two precursor ion scans for m/z 264.3 were performed to cover the m/z ranges 530-760 for low molecular weight modCer and m/z 750-980 for high molecular weight modCer (Table 3).
Identification of Modified Phosphatidylcholines:
OxPC species may include non-truncated OxPCs which involve the addition of oxygen at the double bonds of the polyunsaturated acyl moities (Davis et al. J Biol Chem 283:6428-37, 2008) or truncated oxPCs where the oxidized acyl chains are cleaved to produce lower molecular weight species. A precursor ion scan for m/z 184 will identify all species of lipids containing a phosphocholine head group including oxidized phosphatidylcholines. However other phosphocholine species may also be identified, we have referred to these species as modified PC (modPC). To cover the possible m/z ranges that would cover all OxPCs, three precursor ion scan experiments were performed. The m/z ranges for Q1 for these three experiments were 490-670, 640-820 and 800-980. Fragmentation of phospholipids by CID of PC species produces a daughter ion of 184.1 which was used as the m/z setting in Q3 (Davis et al. supra 2008, Cui and Thomas Journal of Chromatography B; 877:2709-15, 2009) (Table 3).
Identification of Oxidized Cholesterol Esters:
As with phosphatidylcholine species, cholesterol esters which contain polyunsaturated fatty acids are susceptible to oxidation. A precursor ion scan of m/z 369 will identify all species of cholesterol ester, those with oxidized fatty acids. These are referred to as modified cholesterol esters (modCE). The mass ranges for the two precursor ion scan experiments aimed at identifying modCEs were m/z 450-650 and m/z 650-850 in Q1 with a m/z setting of 369.3 for Q3 (Table 3).
Plasma Lipid Profiling:
MRM experiments were established for each of the new lipid biomarkers identified from the precursor ion scans. These were then combined with a larger set of MRM experiments that had been developed by identifying the major species of each lipid class in plasma extracts using precursor ion and neutral loss scans (Table 4 and as updated in Table 15).
Plasma lipid profiling using these MRM experiments was performed on each of the 202 plasma samples in the cohort in addition to 14 quality control (QC) plasma samples. Each ion pair was monitored for between 10 and 50 ms (using scheduled MRM mode) with a resolution of 0.7 amu at half-peak height and the area under the resulting chromatogram was calculated. The peak area data was analysed using Applied Biosystems Analyst 1.5. Raw data for each class was normalised against the internal standard and converted into pmol per mL of plasma.
Statistical Analysis
Data Processing and Statistical Analysis of Precursor Ion Scan Data:
Data resulting from the precursor ion scans were analysed using Markerview (version 1.2). Data were normalized against the respective internal standard of the lipid class under investigation.
A Student's t-test was performed to identify which lipid analytes were significantly different between stable and unstable CAD groups and between control and CAD groups (stable and unstable CAD combined). Analytes with a p value <0.1 that did not correspond to known lipid species were then incorporated into the plasma profiling methods, these lipid species were termed modCer, modPC and modCE.
Data Processing and Statistical Analysis of MRM Data:
Non-parametric, Mann-Whitney-U tests were used to determine the analytes that were significantly different between stable vs unstable CAD groups and the control vs CAD groups. Analysis of variance (ANOVA) was performed on linear regression models to determine the relative contribution of the traditional risk factors and lipid analytes to classification models (SPSS version 17.0, SPSS Inc).
Multivariate analysis was applied for the creation of prediction models. This analysis followed a statistical machine learning approach and methodology comprising multiple cross-validation iterations to assess the power of proposed solutions (National ICT Australia). Briefly, recursive feature elimination (RFE) analysis with three-fold cross-validation repeated multiple times (100) was applied to develop multivariate models using support vector machine learning. This was done for models of varying feature size (e.g., 2, 4, 8, 16, 32 and 64). The output of this exercise was a ranked list of the lipids according to the frequency of their recurrent incorporation in generated models. This approach also allowed the removal of those highly correlated variables that did not add significantly to the model. For each set of models with different numbers of analytes Receiver Operator Characteristic (ROC) analysis was performed, calculating Area Under the Curve (AROC).
ROC analysis is used extensively in diagnostic testing to determine the performance of a given model (Fawcett T Pattern Recogn Lett 27:861-74, 2006).
EXAMPLE 1
Patient Characteristics
The patients in the stable and unstable cohorts were closely matched, with the exception of smoking status and hsCRP (Table 5). In contrast, most of the clinical and biochemical parameters differed significantly between the control cohort and the CAD cohort (combined stable and unstable CAD patients) (Table 5).
The medication profile of the stable and unstable CAD patients was examined for lipid lowering, antihypertensive, antiplatelet, anticoagulant, anti-anginal anti-arrhythmic and anti-diabetic treatments. X2 revealed that four medications were significantly different between these two cohorts (Table 6). The medications that showed differences were statins for the lipid lowering medications, angiotensin II blockers and intravenous glycerol nitrate from the anti-hypertensive medications and heparin infusion from the anticoagulant medications.
EXAMPLE 2
Identification of Biomarkers
Precursor ion scans were used to identify modCer, modPC and modCE biomarkers using Markerview software (version 1.2).
This software aligns and then tabulates the m/z and retention time for all the peaks (also called features) within the precursor ions scans. It then normalizes the data against the relevant internal standard. A student t-test was then applied to the features to identify which were different between stable and unstable CAD cohorts and between the control and CAD cohorts, at a significance of p<0.10. The spectra of these peaks were then examined to remove known lipid species and isotopes.
From this process a total of 75 markers (14 modCer, 57 modPC and 4 modCE) were selected across the three lipid classes, these markers are shown in Table 7.
EXAMPLE 3
Plasma Lipid Profiling of Control, Stable Cad and Unstable CAD Cohorts
Each of the 202 plasma samples in the cohort was analyzed for a total of 331 lipid species by the two scheduled MRM experiments (Tables 7 and 8). From the lipid concentrations in the 14 QC samples the coefficients of variation (% CV) were determined across the entire analytical run. % CV values were less than 20% for 271 of the 331 lipid species. Those lipids which had a % CV greater that 20% were primarily lipid species that were in low abundance (<200 pmol/mL) these did not include the top ranking lipid analytes.
EXAMPLE 4
Univariate Analysis
A Mann Whitney-U test was used to distinguish which lipids showed significant differences between cohorts (stable CAD vs unstable CAD and control vs CAD). This identified 73 lipids that were significantly different between the stable and unstable CAD cohorts (p<0.05) and 198 lipids that showed statistical significance (p<0.05) between the control and CAD cohorts and (Table 9). A summary of the total number of lipids per lipid class that show differences between these cohorts is shown in Table 10.
Anova
In order to identify lipids that were independent predictors of class assignment linear regression analysis was performed. A number of different models were created to analyse different subsets of the cohort for covariates.
Models 1 to 3 were created with the stable CAD and unstable CAD cohorts. Model one used only the 13 traditional risk factors (age, sex, smoking status, diabetes, hypertension, family history of CAD, BMI, total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP, Table 5). Model 2 was created using only the lipids (see Table 9 and 10) and Model 3 included both the lipids as well as the traditional risk factors. The ANOVA results and covariates that were independent predictors and showed significance (p<0.05) are shown in Table 11. The partial correlation values show the relative contribution of the independent variables to the model when the linear effects of the other independent variables in the models have been removed. From the R2 values (measure of the fit of the model) it can be seen that model 3 (R2=0.473) shows the best fit indicating that the combination of the lipid biomarkers and the traditional risk factors provides a better classification of the stable and unstable CAD cohorts than the traditional risk factors or the lipids alone. Whilst CRP is the most significant sources of variation between these two cohorts, the lipids PI 34:0. DHC 18:1, modCer 703.6/5.87, SM 22:1 and GM3 18:0 were also shown to be independent predictors.
Models 4, 5 & 6 represent models created with the control and CAD cohorts using traditional risk factors alone, lipids alone or a combination of both respectively. The fit of these models (R2 values shown in Table 12) parallel that of the stable versus unstable CAD models with the data showing an improvement in the fit to the predictive model when traditional risk factors and lipids were combined. Twenty-one lipids were identified as being able to distinguish between control and CAD patients independently of all other factors (Table 12, model 6).
EXAMPLE 5
Multivariate Analysis
Linear regression modeling was able to create models that examined the influence of traditional risk factors, lipids and a combination of these in classifying between stable and unstable CAD patients, and control and CAD patients. However, given the complexity of the data set and the large number of variables, multivariate modeling is more appropriate to create a predictive model based upon the plasma lipid profile (Bylesjö et al. Journal of Chemometrics 20:341-51, 2006).
Recursive feature elimination (RFE) analysis was applied using three-fold cross validation (repeated 100 times) to develop multivariate models using support vector machine learning. This was done for models of varying feature size (e.g., 1, 2, 4, 8, 16, 32 and 64) and for models that included either lipids alone or lipids with traditional risk factors. The output of this exercise was a ranked list of the lipids according to the frequency of their recurrent incorporation in the generated models to distinguish stable CAD from unstable CAD (Table 13) or control from CAD (Table 14). This approach also allowed the removal of those significant but highly correlated variables that did not add significantly to the model.
The Y predictor values from these models were used to perform Receiver Operator Characteristic (ROC) analysis, which measures the sensitivity and specificity of the model and can be used as a measure of the model's ability to correctly classify cases (Stenlund et al. Analytical Chemistry 80:6898-906, 2008). The area under the curve (AUC) from these ROC analyses was potted against the number of variables to identify the minimum number required for optimal discrimination (FIGS. 1(A) and (B) and 2(A) and (B)). In the models created to discriminate between stable CAD and unstable CAD increasing the number of lipids in the model increased the AUC which reached a maximum at 8-16 lipid analytes (FIG. 1 panel A). Using a combination of traditional risk factors and lipids gave the best discrimination with a maximum AUC achieved with 8 features. FIG. 2, panel B shows that lipid only models had a lower error rate that the traditional risk factor only models but that the combined traditional risk factor and lipid models had the lowest error rates.
Models created to distinguish control and CAD had higher AUC and continued to show a slight increase up to 256 lipids although 16 lipids was sufficient to produce an AUC of 0.94 (FIG. 2 panel A). Similar to the stable CAD vs unstable CAD models, the combination of traditional risk factors and lipids resulted in the highest AUC with 16 features showing an AUC of 0.96. The combination of traditional risk factors and lipids also resulted in the lowest error rates in the control vs CAD models (FIG. 2, panel B).
The two models created with the 8 and 16 lipids (stable CAD vs unstable CAD and control vs CAD) were compared to the models created with the traditional risk factors and then to models created with a combination of the traditional risk factors and the lipids. These traditional risk factors included age, sex, smoking status, diabetes, hypertension, family history of CAD, BMI, total cholesterol, LDL, HDL, triglycerides, glucose and hsCRP. Whilst CRP is not classified as a traditional risk factor it was included in these models because CRP is a marker of inflammation and has also been used in other risk prediction scores such as the Reynolds Risk Score (Ridker et al. Circulation 109:IV-6-19, 2004; Ridker et al. JAMA: Journal of the American Medical Association 297:611-9, 2007; Shearer et al. PLoS ONE 4:e5444, 2009).
Models were validated by three-fold cross validation repeated 10 times and the results combined in a ROC analyses. In the stable CAD vs unstable CAD models, traditional risk factors alone gave an AUC of 0.723 compared with 0.748 for 8 lipids, while the 13 traditional risk factors combined with the 8 lipids resulted in an AUC of 0.765 (FIG. 3). In the control vs CAD models, traditional risk factors alone gave an AUC of 0.927 compared with 0.963 for 16 lipids, while the 13 traditional risk factors combined with the 16 lipids resulted in an AUC of 0.973 (FIG. 4).
Discussion
There are no current screening methods that can prospectively identify unstable plaque. As proposed herein, plasma lipids are suitable biomarkers to identify plaque instability and patient vulnerability. ModCer, modPC and modCE lipid species were identified as useful biomarkers that can distinguish between stable and unstable CAD. These markers as well as previously characterised lipids enabled the creation of a plasma lipid profile that reflected the changes in lipid metabolism associated with the progression of CAD. In combination with the traditional risk factors, the plasma lipid profiles improved the ability to stratify CAD patients into stable and unstable cohorts, and may serve as a cost effective, non-invasive clinical screening method to identify non-symptomatic patients at risk (Damas and Aukrust Scand Cardiovasc J 40:262-6, 2006; Naghavi et al. Circulation 108:1772-8, 2003).
Identification of New Biomarkers for CAD:
Whilst the exact changes that occur in lipid metabolism during the progression of CAD are not fully understood, there is growing evidence to suggest that the lipid peroxidation products play a role in atherogenesis (Davis et al. supra 2008; Oei et al. Circulation 111:570-5, 2005). Precursor ion scanning allowed the identification of modPCs and modCer based upon their characteristic fragmentation. The plasma concentrations of these lipids were significantly different between the stable and unstable CAD cohorts as well as the control and CAD cohorts. This supports the concept that ModPCs and modCers are involved in the changes that occur in lipid metabolism with the progression of the disease. Whilst precursor ion scanning enabled the determination of the parent ion m/z for these lipids, it is not able to provide information regarding their exact structure. By identifying the species of interest (i.e. those that show a significant difference between cohorts), this provides an efficient means of targeting specific lipids to be further characterised by either further mass spectrometric analysis or other structural methods such as nuclear magnetic resonance spectroscopy. This information may further unravel the mechanism behind the changes in lipid metabolism driving plaque progression and instability.
EXAMPLE 6
Updated Results
Updated Patient Characteristics
The patients in the stable and unstable cohorts did not differ in conventional risk factors, with the exception of smoking status, and hsCRP (Table 1). In contrast, most clinical and biochemical parameters differed significantly between the control cohort and the CAD cohort (combined stable and unstable CAD patients) (Table 1). This selection of the control group was made to optimise the ability to identify differentiating lipid species. Medication use was similar between the stable and unstable groups with the exception of statin and antigoagulant use (Table 2).
Identification of New Biomarkers and Plasma Lipid Profiling
Analysis of the plasma lipid extracts from 10 control, 10 stable and 10 unstable CAD patients by precursor ion scanning identified 38 species of modPC, 13 species of modCer and 4 species of modCE that displayed a significant difference between control and CAD groups. These were combined with the other lipid species identified in plasma to define the plasma lipid profile (Table 1, Table 7 and Table 8).
Plasma samples were analysed for 329 lipid species by two scheduled MRM experiments. Quality control plasma samples (QC; 14 replicates) were evenly spaced within the cohort. The coefficients of variation (CV) within the QC samples were less than 20% for 271 of the 329 lipid species. Those lipids which had a CV greater that 20% were primarily lipid species that were in low abundance (<200 pmol/mL); none of these were included in the top ranked lipid analytes used in the multivariate models.
Binary logistic regression analysis, adjusting for age and sex identified 30 lipids that were significantly different (p<0.01) between the stable CAD and unstable CAD groups and 95 lipids that were different (p<0.01) between the control and CAD (stable and unstable combined) groups (Table 16).
Multivariate Analysis
Binary logistic regression models (3-fold cross validation repeated 100 times) were created to assess the relative contribution of lipids and risk factors to the differentiation of stable CAD from unstable CAD and control from CAD. Models (stable CAD vs unstable CAD) using lipids only, traditional risk factors only or a combination of both produced C-statistics of 0.739 (CI 0.734-0.745), 0.679 (CI 0.673-0.685) and 0.804 (CI 0.798-0.811) and % accuracy of 69.5, 64.5 and 73.3 respectively (Table 17A). The multiple cross validation enabled us to rank the lipids and traditional risk-factors based on their recurrent incorporation in the logistic models. The ranked lists for the lipid only and risk factor only models are shown in Tables 18 and 19. Table 20 shows the ranked list for the combined lipids and traditional risk factor models. Models of control vs CAD using lipids only, traditional risk factors only or a combination of both produced C-statistics of 0.946 (CI 0.944-0.948), 0.956 (CI 964-0.958 and 0.982 CI 0.981-0.983 and % accuracy of 87.4, 90.3 and 92.3 respectively (Table 17B). The ranked features for the separate lipid and risk factor models are shown in Supplementary Tables 21 and 22. The ranked features for the combined lipids and risk factors model are shown in Table 23.
Recursive feature elimination (RFE) analysis was also applied using three-fold cross validation (repeated 100 times) to develop multivariate models using support vector machine learning. Models of varying feature size (e.g., 1, 2, 4, 8, 16 . . . , 329) that included either lipids alone, risk factors alone or lipids with risk factors were developed. The ranked list of the lipids/risk factors according to the frequency of their recurrent incorporation in the generated models is shown in Tables 24 and 25. The C-statistic and % accuracy from each model was plotted against the number of variables to assess the performance of the different models and identify the minimum number required for optimal discrimination (FIG. 5). Models using lipids alone (FIG. 5A circles) to discriminate stable CAD from unstable CAD showed a maximum C-statistic (0.739, CI 0.734-0.745) with only 16 lipids in the model. This was significantly better than the model created with risk factors alone (FIG. 5A squares) (C-statistic of 0.679, CI 0.673-0.685), while the model containing a combination of lipids and risk factors performed best (C-statistic of 0.804 (CI 0.798-0.811)) with only eight features (FIG. 6). This model also had the highest accuracy of 73.3% compared to risk factors alone (FIG. 5A triablges and FIG. 6) (64.5%) or lipids alone (69.5%) (FIG. 5B).
Classification of CAD from control using lipids only gave a C-statistic of 0.939 (CI 0.937-0.945) with 128 lipids in the model, however, only 16 lipids were sufficient to give a C-statistic of 0.919 (See FIG. 5C) (CI 0.917-0.921). While the traditional risk factors performed slightly better than lipids with a C-statistic of 0.965 (CI 0.964-0.966), the combined lipids and risk factor model performed best with a C-statistic of 0.973 (CI 0.972-0.974) with 16 features. This model also had the highest accuracy of 85.3% compared to risk factors (83.2%) or lipids (80.2%) (FIG. 5D). The high level of discrimination of control from CAD with all models reflects the CAD status of the control group specifically chosen to highlight differences in the lipid profile between these groups.
Updated Discussion
This study has identified differences in the plasma lipidome between stable CAD and unstable CAD. Multivariate models combining traditional risk factors and plasma lipids gave a significant improvement over traditional risk factors alone such that over 73% of patients could be correctly classified as either stable or unstable CAD. These findings indicate that plasma lipid profiling has significant diagnostic and prognostic potential for the identification of individuals at risk for unstable coronary syndromes.
The healthy control group was selected to provide the greatest phenotypic difference with the CAD groups and thereby optimise the ability to identify new lipid markers associated with CAD. Subsequent analyses of these new lipid markers and 276 known lipid species in the stable and unstable CAD groups identified 30 of these lipid species as potential biomarkers of unstable CAD. The single most prominent difference between stable and unstable CAD was the concentration of PI species. Total PI was 13.8% lower in the unstable CAD group relative to the stable CAD group with 9 of the 17 species showing a significantly lower level (p<0.01) and a further five species showing a negative trend. This is in addition to a 13.5% decrease in the stable CAD group relative to the control group, demonstrating an association between PI species and disease severity. The relevance of these observations may lie in the fact that PI, via the action of PLA2, is the primary source of arachidonic acid which is required for the biosynthesis of the prostaglandins and other ecosanoids that are involved in the activation of monocytes and macrophages and associated with matrix metalloproteinase production, a hallmark of plaque instability. PLA2 has been detected in atherosclerotic lesions, both co-localised with macrophages and in the extracellular matrix where it is thought to act on LDL to release arachidonic acid.
In contrast to PI, PS which also showed a decrease in stable CAD relative the control group (−36.1%, p=3.03E-04) displayed a higher level in the unstable CAD relative to the stable CAD group (23.9%, non-significant). PS is released from activated platelets in membrane vesicles and enhances the activation of prothrombin to thrombin during blood coagulation and thrombogenesis. However, PS is also a substrate for a number of phospholipases which may account for the lower levels in the stable CAD group relative to the control group.
In addition to differences between stable CAD and unstable CAD, many lipids showed a significant difference between the control and CAD groups. Alkylphosphatidylcholine (APC) species were almost uniformly lower in the CAD cohort with 9 of 17 species significantly different at the p<0.01 level and all but one species showing a negative trend. This may relate to the higher oxidative stress in the CAD group and the action of ROS on the polyunsaturated fatty acids of the APC species or directly on the vinyl ether linkages of the plasmalogens, which are also included in this lipid class. Alternatively, lower APC may be the result of increased PLA2 activity in these patients. The primary source of PLA2 activity in circulation is the lipoprotein PLA2 (Lp-PLA2), also known as the platelet activating factor acetylhydrolase which has been associated with increased risk of cardiovascular disease in numerous epidemiological studies.
However, while the action of ROS and PLA2 on these lipids would be expected to lead to the generation of LPC, which has previously been positively associated with inflammation and atherosclerosis, as described herein, lower levels of all LPC species with the exception of LPC 20:4 and LPC 20:3 which were significantly higher in the CAD group. The lower levels may result from an increase in the catabolism of these species were observed here, but more likely relates to their more efficient removal from circulation into tissues, either in the form of modified low-density lipoprotein or directly from albumin, which represents the major form of plasma LPC.
Some of these lipids (APC 34:2, LPC 16:1, LPC14:0) displayed a further decrease in the unstable CAD relative to the stable CAD again demonstrating an association with disease severity. LPC 14:0 had median levels of 2038, 1619 and 1192 pmol/mL in control, stable and unstable CAD groups respectively (FIG. 7). However, other lipids were altered specifically in the unstable CAD group relative to the combined control and stable CAD groups; SM 18:0 showed no difference between control and CAD but was significantly higher in the unstable CAD group relative to the stable CAD group (p=3.37E-3) (FIG. 7).
Differences of this type may reflect specific alterations in lipid metabolism associated with unstable disease.
Whilst the exact changes that occur in lipid metabolism during the progression of CAD are not fully understood, there is growing evidence to suggest that lipid peroxidation products play a role in atherogenesis. Precursor ion scanning allowed the identification of modified forms of PC (modPC) that have previously been reported as oxidised and truncated species (Davis et al., J. Biol. Chem. 283: 6428-6437, 2008; Oei et al., Circulation. 111: 570-575, 2005). These were also decreased in the CAD groups relative to the control group and some species showed a further decrease in unstable CAD relative to stable CAD. This may also be a reflection of increased PLA2 activity and tissue uptake as oxidised PC species are reported to be preferred substrates for LpPLA2 (Davis et al., 2008 (supra)) and high affinity ligands for scavenger receptors. Modified Cer species (modCer) were also identified as potential biomarkers and may relate to the formation of acylceramide species associated with lysosomal PLA2 activity involved in turnover of oxLDL.
Despite the incomplete knowledge of the lipid metabolism associated with CAD lipid biomarkers are described herein as useful for the development of multivariate models to effectively stratify individuals based on disease status. The inventors' strategy was to incorporate lipid classes that reflect the multiple biological functions and processes that underlie the progression of CAD, then apply recursive feature elimination with multiple cross validation to create optimal classification models with the minimum number of lipids. This process demonstrated that only 8-16 lipids were required to achieve almost maximum discrimination of disease status (FIGS. 5A and C). These lipids (Tables 24 and 25) showed a strong homology with the top ranked lipids identified by the logistic regression (Tables 20 and 23) as those most often incorporated into the multivariate models, thereby supporting the RFE selection process.
The influence of statins on the plasma lipid profile was examined in the stable CAD cohort; 9 of 229 lipids showed a correlation with statin use (15-76% difference in concentration, p<0.01) with a further 19 having 0.01>p<0.05. However, only three of these 28 were identified as discriminating stable CAD from unstable CAD and only six lipid species were identified in the 95 that were statistically different between the control and CAD groups (Table 26). Two of these (PC 37:4 and PS 38:4) showed an opposite trend with statin use, to that observed in the CAD group, suggesting that statin use may partially correct these lipid levels.
Notwithstanding the limitations of a cross sectional study to develop predictive models, many of the lipids identified as discriminatory for unstable CAD displayed an association with disease severity suggesting that they are altered prior to the onset of ACS. The application of recursive feature elimination (RFE) using support vector machine learning enabled the development and cross validation of multivariate models for the classification of CAD patients as stable or unstable. The combination of only eight traditional risk factors and plasma lipids provided the best discrimination with a C-statistic of 0.804 (CI, 0.798-0.811) a significant improvement on the traditional risk factors alone which produced a C-statistic of only 0.679 (CI, 0.673-0.685) (FIG. 6).
The Examples demonstrate the potential of plasma lipid profiling for the identification of stable and unstable CAD.
Many modifications will be apparent to those skilled in the art without departing from the scope of the present invention.







TABLE 2







Internal standard mix composition and concentrationa













Concentration


#
Lipid species
Internal standard
(pmol/15 μL)













1
bis(monoacylglycero)phosphate
BMP 14:0/14:0
100



(BMP)


2
ceramide (Cer)
Cer17:0
100


3
monohexosylceramide (MHC)
MHC 16:0 d3
50


4
dihexosylceramide (DHC)
DHC 16:0 d3
50


5
trihexosylceramide (THC)
THC 17:0
50


6
1-O-acylceramide (acCer)
acCer 17:0 18:1
100


7
sphingomyelin (SM)
SM 12:0
200


8
phosphatidylglycerol (PG)
PG 17:0 17:0
100


9
phosphatidylcholine (PC)
PC 13:0 13:0
100


10
phosphatidylcholine (PC)
PC 21:0 21:0
100


11
phosphatidylethanolamine
PE 17:0 17:0
100



(PE)


12
phosphatidylserine (PS)
PS 17:0 17:0
100


13
lysophosphatidylcholine
LPC 13:0
100



(LPC)


14
diacylglycerol (DG)
DG 15:0 15:0
200


15
triacylglycerol (TG)
TG
100




17:0 17:0 17:0


16
cholesterol (COH)
COH d7
1000


17
cholesterol ester (CE)
CE 18:0 d6
1000





aprepared in CHCL3/MeOH (1:1), 15 μL used in each plasma sample













TABLE 3







Mass spectrometer settings used for precursor ion scans














Q1 m/z
Q3






Species
range
m/z setting
DPa
EPb
CEc
CXPd
















modified ceramide
530-760
264.3
70
10
35-50
12



750-980
264.3
70
10
50-65
12


modified
490-670
184.1
100
10
45
12


phosphatidylcholine
640-820
184.1
100
10
45
12



800-900
184.1
100
10
45
12


modified
450-650
369.3
55
10
20
12


cholesterol ester
650-850
369.3
55
10
20
12





aDP, declustering potential


bEP, entrance potential


cCE, collision energy


dCXP, cell exit potential













TABLE 4







Scan methods used to create MRM acquisition methods for plasma lipid profiling
















No. of









Lipid class
species
Internal standard
Parent ion
MRM type
DP
EP
CE
CXP


















ceramide (Cer)
7
Cer 17:0
[M + H]+
PISa, 264.3 m/z
50
10
35
12


monohexosylceramide (MHC)
7
MHC 16:0 d3
[M + H]+
PIS, 264.3 m/z
77
10
50
12


dihexosylceramide (DHC)
7
DHC 16:0 d3
[M + H]+
PIS, 264.3 m/z
100
10
65
12


trihexosylcermide (THC)
7
THC 17:0
[M + H]+
PIS, 264.3 m/z
130
10
73
12


GM3 ganglioside (GM3)
6
THC 17:0
[M + H]+
PIS, 264.3 m/z
155
10
105
16


modified ceramide (modCer)
14
acCer 17:0
[M + H]+
PIS, 264.3 m/z
70
10
50
16


sphingomyelin (SM)
12
SM 12:0
[M + H]+
PIS, 184.1 m/z
65
10
35
12


phosphatidylglycerol (PG)
4
PG 17:0 17:0
[M+ NH4]+
NLb, 189 Da
60
10
25
12


bis(monoacylglycerol)phosphate (BMP)
1
BMP 14:0 14:0
[M+ NH4]+
PIS, 339.3 m/z
65
10
35
12


phosphatidylserine (PS)
7
PS 17:0 17:0
[M + H]+
NL, 185 Da
86
10
29
12


phosphatidylethanolamine (PE)
18
PE 17:0 17:0
[M + H]+
NL, 141 Da
80
10
31
12


phosphatidylinositol (PI)
17
PE 17:0 17:0
[M+ NH4]+
PIS, 184.1 m/z
51
10
43
14


lysophosphatidylcholine (LPC)
14
LPC 13:0
[M + H]+
PIS, 184.1 m/z
90
10
38
12


lysoplatelet activating factor (LPAF)
3
LPC 13:0
[M + H]+
PIS, 285.2 m/z
90
10
42
5


phosphatidylcholine (PC)
19
PC 21:0 21:0c
[M + H]+
PIS, 184.1 m/z
100
10
45
11


odd-chain phosphatidylcholine (oddPC)
15
PC 21:0 21:0c
[M + H]+
PIS, 184.1 m/z
100
10
45
11


alkylphosphatidylcholine (APC)
16
PC 21:0 21:0c
[M + H]+
PIS, 184.1 m/z
100
10
45
11


modified phosphatidylcholine (modPC)
57
PC 21:0 21:0c
[M + H]+
PIS, 184.1 m/z
100
10
45
11


free cholesterol (COH)
1
COH d7
[M+ NH4]+
PIS, 369.3 m/z
55
10
17
12


cholesterol ester (CE)
30
CE 18:0 d6
[M+ NH4]+
PIS, 369.3 m/z
30
10
20
12


modified cholesterol ester (modCE)
4
CE 18:0 d6
[M+ NH4]+
PIS, 369.3 m/z
55
10
20
12


diacylglycerol (DG)
27
DG 15:0 15:0
[M+ NH4]+
NL, fatty acid
55
10
30
22


triaclyglycerol (TG)
44
TG 17:0 17:0 17:0
[M+ NH4]+
NL, fatty acid
95
10
30
12





aNL, neutral loss scan


bPIS, precursor ion scan


cPC 13:0/13:0 was used as internal standard for species with m/z <700













TABLE 5







Clinical and biochemical characteristics of patientsa













Control
Stable CAD
Unstable CAD
P (stable CAD to



Characteristic
(n = 61)
(n = 62)
(n = 81)
unstable CAD)b
P (Control to CAD)b















age (years)
60 ± 6 
66 ± 10
65 ± 11
0.35
<0.0001c


sex (% female)
34
18
25
0.229
0.077


smoker (%)
3
15
30
0.030
0.001


diabetes (%)
0
32
32
0.976
<0.0001


hypertension (%)
0
66
51
0.075
<0.0001


CAD, family history (%)
48
40
32
0.335
0.120


BMI, (kg/m2)
25.72 ± 2.25 
28.00 ± 4.12 
27.65 ± 3.85 
0.62
0.003


total cholesterol, (mmol/L)
4.77 ± 0.45
4.38 ± 1.08
4.11 ± 0.96
0.13
0.001


LDL cholesterol, (mmol/L)
2.93 ± 0.49
2.59 ± 0.93
2.35 ± 0.77
0.12
0.0001


HDL cholesterol, (mmol/L)
1.34 ± 0.43
1.09 ± 0.31
1.10 ± 0.29
0.81
<0.0001


triglycerides, (mmol/L)
1.06 ± 0.58
1.63 ± 0.87
1.51 ± 0.97
0.47
0.0002


glucose, (mmol/L)
5.02 ± 0.48
6.88 ± 3.47
6.48 ± 2.27
0.45
<0.0001


hsCRP, mg/L
2.04 ± 2.29
3.41 ± 3.95
10.32 ± 8.32 
<0.0001
<0.0001





aData are mean ± standard deviation


bp values for age, sex, smoker, diabetes, CAD family history and statin use were calculated using Chi Square. p Values for the other characteristics were calculated using Mann Whitney-U tests


cvariable with p < 0.05 are bolded













TABLE 6







Medication of stable and unstable CAD cohorts














Chi






Square


Medication
Stable %
Unstable %
value
Significance














Clopidogrela
18
27
1.625
0.202


Aspirina
95
94
0.103
0.748


statinb
54
88
19.991
0.000h


beta blockerc
59
65
0.612
0.434


ACE inhibitorc
43
56
2.328
0.127


angiotensin-II blockerc
23
6
1.076
0.300


oral/top nitratec
31
27
0.269
0.604


intravenous glyceryl
0
6
3.903
0.048


trinitrate (IV GTN)c


Ca channel blackerc
26
19
1.212
0.271


heparin infusiond
0
21
14.544
0.000


low molecular weight
0
11
7.236
0.007


heparin (LMWH)d


insuling
7
5
0.172
0.679


warfarind
2
0
1.337
0.248


amiodaronef
2
1
0.041
0.839


spironolactonec
3
0
2.694
0.101


abciximaba
0
1
0.758
0.384


tirofibana
0
6
3.903
0.048


frusemidec
11
9
0.314
0.575


sulfonylureag
15
14
0.040
0.842


metforming
23
11
3.593
0.058





aantiplatelet


blipid lowering


cantihypertensive


danticoagulant


eanti-anginal


fanti-arrhythmic


ganti-diabetic


hvariable with p < 0.05 are bolded













TABLE 7







Lipid analytes measured in MRM experiment 1

















#
Analyte
exact mass
Q1a
Q3b
tRc
IDd
DPe
EPf
CEg
CXPh




















 1
Cer 16:0
537.512
538.5
264.3
7.10
Cer 16:0
50
10
35
12


S1
Cer 17:0 (IS)
551.528
552.5
264.3
7.26
Cer 17:0 (IS)
50
10
35
12


 2
Cer 18:1
563.528
564.5
264.3
7.20
Cer 18:1
50
10
35
12


 3
Cer 18:0
565.543
566.6
264.3
7.41
Cer 18:0
50
10
35
12


 4
Cer 20:0
593.575
594.6
264.3
7.80
Cer 20:0
50
10
35
12


 5
Cer 22:0
621.606
622.6
264.3
7.94
Cer 22:0
50
10
35
12


 6
Cer 24:1
647.622
648.6
264.3
7.95
Cer 24:1
50
10
35
12


 7
Cer 24:0
649.637
650.6
264.3
8.18
Cer 24:0
50
10
35
12


 8
MHC 16:0
699.565
700.6
264.3
6.26
MHC 16:0
77
10
50
12


S2
MHC 16:0d3 (IS)
702.582
703.60
264.3
6.26
MHC 16:0d3 (IS)
77
10
50
12


 9
MHC 18:1
725.581
726.6
264.3
6.40
MHC 18:1
77
10
50
12


 10
MHC 18:0
727.596
728.6
264.3
6.61
MHC 18:0
77
10
50
12


 11
MHC 20:0
755.628
756.6
264.3
6.93
MHC 20:0
77
10
50
12


 12
MHC 22:0
783.659
784.7
264.3
7.21
MHC 22:0
77
10
50
12


 13
MHC 24:1
809.674
810.7
264.3
7.22
MHC 24:1
77
10
50
12


 14
MHC 24:0
811.690
812.7
264.3
7.47
MHC 24:0
77
10
50
12


 15
DHC 16:0
861.618
862.6
264.3
5.91
DHC 16:0
100
10
65
12


S3
DHC 16:0d3 (IS)
864.635
865.6
264.3
5.91
DHC 16:0d3 (IS)
100
10
65
12


 16
DHC 18:1
887.633
888.6
264.3
6.03
DHC 18:1
100
10
65
12


 17
DHC 18:0
889.649
890.7
264.3
6.27
DHC 18:0
100
10
65
12


 18
DHC 20:0
917.680
918.7
264.3
6.60
DHC 20:0
100
10
65
12


 19
DHC 22:0
945.712
946.7
264.3
6.90
DHC 22:0
100
10
65
12


 20
DHC 24:1
971.727
972.7
264.3
6.91
DHC 24:1
100
10
65
12


 21
DHC 24:0
973.743
974.8
264.3
7.17
DHC 24:0
100
10
65
12


 22
THC 16:0
1023.671
1024.7
264.3
5.69
THC 16:0
130
10
73
12


S4
THC 17:0 (IS)
1037.686
1038.7
264.3
5.87
THC 17:0 (IS)
130
10
73
12


 23
THC 18:1
1049.686
1050.7
264.3
5.84
THC 18:1
130
10
73
12


 24
THC 18:0
1051.702
1052.7
264.3
6.06
THC 18:0
130
10
73
12


 25
THC 20:0
1079.733
1080.7
264.3
6.39
THC 20:0
130
10
73
12


 26
THC 22:0
1107.764
1108.8
264.3
6.70
THC 22:0
130
10
73
12


 27
THC 24:1
1133.780
1134.8
264.3
6.70
THC 24:1
130
10
73
12


 28
THC 24:0
1135.796
1136.8
264.3
6.98
THC 24:0
130
10
73
12


 29
GM3 16:0
1152.713
1153.7
264.3
4.82
GM3 16:0
155
10
105
16


 30
GM3 18:0
1180.744
1181.8
264.3
5.15
GM3 18:0
155
10
105
16


 31
GM3 20:0
1208.776
1209.8
264.3
5.49
GM3 20:0
155
10
105
16


 32
GM3 22:0
1236.807
1237.8
264.3
5.77
GM3 22:0
155
10
105
16


 33
GM3 24:1
1262.823
1263.8
264.3
5.78
GM3 24:1
155
10
105
16


 34
GM3 24:0
1264.838
1265.8
264.3
6.04
GM3 24:0
155
10
105
16


 35
modCer 576.5/7.68
575.500
576.5
264.3
7.68
modCer 576.5/7.68
70
10
50
16


 36
modCer 614.6/5.72
613.600
614.6
264.3
5.72
modCer 614.6/5.72
70
10
50
16


 37
modCer 632.6/9.22
631.600
632.6
264.3
9.22
modCer 632.6/9.22
70
10
50
16


 38
modCer 651.6/7.56
650.600
651.6
264.3
7.56
modCer 651.6/7.56
70
10
50
16


 39
modCer 703.6/5.87
702.620
703.61
264.3
5.87
modCer 703.6/5.87
70
10
50
16


 40
modCer 731.6/6.22
730.600
731.6
264.3
6.22
modCer 731.6/6.22
70
10
50
16


 41
modCer 766.6/7.17
765.600
766.6
264.3
7.17
modCer 766.6/7.17
70
10
50
16


 42
modCer 769.6/8.01
768.600
769.6
264.3
8.01
modCer 769.6/8.01
70
10
50
16


 43
modCer 798.7/7.29
797.700
798.7
264.3
7.29
modCer 798.7/7.29
70
10
50
16


S5
Acyl Cer 17:0 18:1 (IS)
815.800
816.8
264.3
8.90
Acyl Cer 17:0 18:1 (IS)
70
10
50
16


 44
modCer 875.7/9.23
874.700
875.7
264.3
9.23
modCer 875.7/9.23
70
10
50
16


 45
modCer 883.8/7.75
882.800
883.8
264.3
7.75
modCer 883.8/7.75
70
10
50
16


 46
modCer 886.8/9.06
885.800
886.8
264.3
9.06
modCer 886.8/9.06
70
10
50
16


 47
modCer 910.8/8.98
909.800
910.8
264.3
8.98
modCer 910.8/8.98
70
10
50
16


 48
modCer 921.8/9.05
920.800
921.8
264.3
9.05
modCer 921.8/9.05
70
10
50
16


S6
SM 12:0 (IS)
646.505
647.5
184.1
4.70
SM 12:0 (IS)
65
10
35
12


S6
SM 12:0 (IS)
646.505
648.5
185.1
4.70
SM 12:0 + 1 (IS)
65
10
35
12


S6
SM 12:0 (IS)
646.505
649.5
186.1
4.70
SM 12:0 + 2 (IS)
65
10
35
12


 49
SM 14:0
674.536
676.5
185.1
5.15
SM 14:0 + 1
65
10
35
12


 50
SM 15:0
688.552
690.6
185.1
5.40
SM 15:0 + 1
65
10
35
12


 51
SM 16:1
700.552
702.6
185.1
5.30
SM 16:1 + 1
65
10
35
12


 52
SM 16:0
702.568
705.6
186.1
5.58
SM 16:0 + 2
65
10
35
12


 53
SM 18:1
728.583
730.6
185.1
5.70
SM 18:1 + 1
65
10
35
12


 54
SM 18:0
730.599
732.6
185.1
6.04
SM 18:0 + 1
65
10
35
12


 55
SM 20:1
756.615
758.6
185.1
6.09
SM 20:1 + 1
65
10
35
12


 56
SM 22:1
784.646
786.7
185.1
6.44
SM 22:1 + 1
65
10
35
12


 57
SM 22:0
786.661
788.7
185.1
6.68
SM 22:0 + 1
65
10
35
12


 58
SM 24:2
810.661
812.7
185.1
6.46
SM 24:2 + 1
65
10
35
12


 59
SM 24:1
812.677
813.7
184.1
6.60
SM 24:1
65
10
35
12


 60
SM 24:0
814.693
816.7
185.1
6.98
SM 24:0 + 1
65
10
35
12


 61
PG 16:1 18:1
746.510
764.5
575.5
5.44
PG 16:1 18:1
60
10
25
12


 62
PG 16:0 18:1
748.525
766.6
577.5
5.68
PG 16:0 18:1
60
10
25
12


S7
PG 17:0 17:0 (IS)
750.541
768.6
579.5
5.93
PG 17:0 17:0 (IS)
60
10
25
12


 63
PG 18:1 18:1
774.541
792.6
603.5
5.76
PG 18:1 18:1
60
10
25
12


 64
PG 18:0 18:1
776.557
794.6
605.6
6.00
PG 18:0 18:1
60
10
25
12


S8
BMP 14:0 14:0 (IS)
666.447
684.5
285.2
5.01
BMP 14:0 14:0 (IS)
65
10
35
5


 65
BMP 18:1 18:1
774.541
792.6
339.3
5.76
BMP 18:1 18:1
65
10
35
5


S9
PS 17:0/17:0
763.536
764.5
579.5
5.78
PS 17:0/17:0
86
10
29
16


 66
PS 36:2
787.536
788.5
603.5
5.67
PS 36:2
86
10
29
16


 67
PS 36:1
789.552
790.6
605.6
5.87
PS 36:1
86
10
29
16


 68
PS 38:5
809.521
810.5
625.5
5.49
PS 38:5
86
10
29
16


 69
PS 38:4
811.536
812.5
627.5
5.69
PS 38:4
86
10
29
16


 70
PS 38:3
813.552
814.6
629.6
5.82
PS 38:3
86
10
29
16


 71
PS 40:6
835.536
836.5
651.5
5.69
PS 40:6
86
10
29
16


 72
PS 40:5
837.552
838.6
653.6
5.73
PS 40:5
86
10
29
16


 73
PE 32:1
689.500
690.5
549.5
6.25
PE 32:1
80
10
31
7


 74
PE 32:0
691.515
692.5
551.5
6.40
PE 32:0
80
10
31
7


 75
PE 34:2
715.515
716.5
575.5
6.30
PE 34:2
80
10
31
7


 76
PE 34:1
717.531
718.5
577.5
6.50
PE 34:1
80
10
31
7


S10
PE 17:0/17:0 (IS)
719.547
720.6
579.5
6.53
PE 17:0/17:0 (IS)
80
10
31
7


 77
PE 36:5
737.500
738.5
597.5
6.15
PE 36:5
80
10
31
7


 78
PE 36:4
739.515
740.5
599.5
6.33
PE 36:4
80
10
31
7


 79
PE 36:3
741.531
742.5
601.5
6.39
PE 36:3
80
10
31
7


 80
PE 36:2
743.547
744.6
603.5
6.57
PE 36:2
80
10
31
7


 81
PE 36:1
745.562
746.6
605.6
6.83
PE 36:1
80
10
31
7


 82
PE 36:0
747.578
748.6
607.6
7.00
PE 36:0
80
10
31
7


 83
PE 38:6
763.515
764.5
623.5
6.31
PE 38:6
80
10
31
7


 84
PE 38:5
765.531
766.5
625.5
6.40
PE 38:5
80
10
31
7


 85
PE38:4
767.547
768.6
627.5
6.66
PE38:4
80
10
31
7


 86
PE 38:3
769.562
770.6
629.6
6.84
PE 38:3
80
10
31
7


 87
PE 38:2
771.578
772.6
631.6
6.86
PE 38:2
80
10
31
7


 88
PE 38:1
773.593
774.6
633.6
7.07
PE 38:1
80
10
31
7


 89
PE 40:7
789.531
790.5
649.5
6.38
PE 40:7
80
10
31
7


 90
PE 40:6
791.547
792.6
651.5
6.63
PE 40:6
80
10
31
7


 91
PI 32:1
808.510
826.5
549.5
5.09
PI 32:1
51
10
43
14


 92
PI 32:0
810.526
828.6
551.6
5.34
PI 32:0
51
10
43
14


 93
PI 34:1
836.541
854.6
577.6
5.44
PI 34:1
51
10
43
14


 94
PI 34:0
838.557
856.6
579.6
5.69
PI 34:0
51
10
43
14


 95
PI 36:4
858.526
876.6
599.6
5.26
PI 36:4
51
10
43
14


 96
PI 36:3
860.541
878.6
601.6
5.32
PI 36:3
51
10
43
14


 97
PI 36:2
862.557
880.6
603.6
5.58
PI 36:2
51
10
43
14


 98
PI 36:1
864.573
882.6
605.6
5.77
PI 36:1
51
10
43
14


 99
PI 36:0
866.588
884.6
607.6
5.99
PI 36:0
51
10
43
14


100
PI 38:6
882.526
900.6
623.6
5.26
PI 38:6
51
10
43
14


101
PI 38:5
884.541
902.6
625.6
5.34
PI 38:5
51
10
43
14


102
PI 38:4
886.557
904.6
627.6
5.61
PI 38:4
51
10
43
14


103
PI 38:3
888.573
906.6
629.6
5.71
PI 38:3
51
10
43
14


104
PI 38:2
890.588
908.6
631.6
5.86
PI 38:2
51
10
43
14


105
PI 40:6
910.557
928.6
651.6
5.60
PI 40:6
51
10
43
14


106
PI 40:5
912.573
930.6
653.6
5.67
PI 40:5
51
10
43
14


107
PI 40:4
914.588
932.6
655.6
5.84
PI 40:4
51
10
43
14


S11
LPC 13:0 (IS)
453.286
454.3
184.1
1.22
LPC 13:0 (IS)
90
10
38
12


108
LPC 14:0
467.301
468.3
184.1
1.20
LPC 14:0
90
10
38
12


109
LPC 15:0
481.317
482.3
184.1
1.70
LPC 15:0
90
10
38
12


110
LPC 16:1
493.317
494.3
184.1
1.50
LPC 16:1
90
10
38
12


111
LPC 16:0
495.332
496.3
184.1
2.30
LPC 16:0
90
10
38
12


112
LPC 18:2
519.332
520.3
184.1
1.90
LPC 18:2
90
10
38
12


113
LPC 18:1
521.348
522.4
184.1
2.80
LPC 18:1
90
10
38
12


114
LPC 18:0
523.364
524.4
184.1
3.60
LPC 18:0
90
10
38
12


115
LPC 20:5
541.317
542.3
184.1
1.51
LPC 20:5
90
10
38
12


116
LPC 20:4
543.332
544.3
184.1
2.00
LPC 20:4
90
10
38
12


117
LPC 20:3
545.348
546.4
184.1
2.51
LPC 20:3
90
10
38
12


118
LPC 20:2
547.364
548.4
184.1
3.60
LPC 20:2
90
10
38
12


119
LPC 20:1
549.379
550.4
184.1
3.80
LPC 20:1
90
10
38
12


120
LPC 20:0
551.395
552.41
184.1
4.30
LPC 20:0
90
10
38
12


121
LPC 22:6
567.332
568.3
184.1
2.10
LPC 22:6
90
10
38
12


122
LPAF 16:0
481.353
482.4
104.1
3.00
LPAF 16:0
90
10
42
5


123
LPAF 18:1
507.369
508.4
104.1
3.30
LPAF 18:1
90
10
42
5


124
LPAF 18:0
509.385
510.4
104.1
3.90
LPAF 18:0
90
10
42
5


S12
PC 13:0/13:0
649.468
650.5
184.1
5.05
PC 13: 13:0 (IS)
100
10
45
11


S12
PC 13:0/13:0
650.492
651.5
185.1
5.05
PC 13: 13:0 + 1 (IS)
100
10
45
11


125
PC 30:2
701.500
703.5
185.1
5.31
PC 30:2 + 1
100
10
45
11


126
PC 32:2
729.531
731.5
185.1
5.80
PC 32:2 + 1
100
10
45
11


127
PC 32:1
732.547
733.6
184.1
5.96
PC 32:1 + 1
100
10
45
11


128
PC 32:0
733.562
735.6
185.1
6.24
PC 32:0 + 1
100
10
45
11


129
PC 34:3
755.547
757.6
185.1
5.88
PC 34:3 + 1
100
10
45
11


130
PC 34:2
757.562
760.6
186.1
6.16
PC 34:2 + 2
100
10
45
11


131
PC 34:1
759.578
761.6
185.1
6.28
PC 34:1 + 1
100
10
45
11


132
PC 34:0
761.593
763.6
185.1
6.37
PC 34:0 + 1
100
10
45
11


133
PC 36:5
779.547
781.6
185.1
5.92
PC 36:5 + 1
100
10
45
11


134
PC 36:4
781.562
784.6
186.1
6.17
PC 36:4 + 2
100
10
45
11


135
PC 36:3
783.578
785.6
185.1
6.25
PC 36:3 + 1
100
10
45
11


136
PC 36:2
785.593
788.6
186.1
6.40
PC 36:2 + 2
100
10
45
11


137
PC 38:6
805.562
807.6
185.1
6.16
PC 38:6 + 1
100
10
45
11


138
PC 38:5
807.578
809.6
185.1
6.23
PC 38:5 + 1
100
10
45
11


139
PC 38:4
809.593
812.6
186.1
6.50
PC 38:4 + 2
100
10
45
11


140
PC 40:7
831.578
833.6
185.1
6.20
PC 40:7 + 1
100
10
45
11


141
PC 40:6
833.593
835.6
185.1
6.50
PC 40:6 + 1
100
10
45
11


142
PC 40:5
835.609
837.6
185.1
6.55
PC 40:5 + 1
100
10
45
11


S13
PC 21:0 21:0 (IS)
873.719
874.7
184.1
7.80
PC 21:0 21:0 (IS)
100
10
45
11


S13
PC 21:0 21:0 (IS)
874.719
875.7
185.1
7.80
PC 21:0 21:0 + 1 (IS)
100
10
45
11


S13
PC 21:0 21:0 (IS)
875.719
876.7
186.1
7.80
PC 21:0 21:0 + 2 (IS)
100
10
45
11


143
PC 44:12
877.562
879.6
185.1
7.22
PC 44:12 + 1
100
10
45
11


144
oddPC 31:1
717.531
718.5
184.1
5.94
PC 31:1
100
10
45
11


145
oddPC 31:0
719.547
720.60
184.1
6.20
PC 31:0
100
10
45
11


146
oddPC 33:0
743.547
744.60
184.1
6.07
PC 33:2
100
10
45
11


147
oddPC 33:1
745.562
746.60
184.1
6.29
PC 33:1
100
10
45
11


148
oddPC 33:2
747.578
748.6
184.1
6.50
PC 33:0
100
10
45
11


149
oddPC 35:4
767.547
768.60
184.1
6.09
PC 35:4
100
10
45
11


150
oddPC 35:3
769.562
770.60
184.1
6.19
PC 35:3
100
10
45
11


151
oddPC 35:2
771.578
772.6
184.1
6.41
PC 35:2
100
10
45
11


152
oddPC 35:1
773.593
774.60
184.1
6.63
PC 35:1
100
10
45
11


153
oddPC 35:0
775.609
776.6
184.1
6.83
PC 35:0
100
10
45
11


154
oddPC 37:6
791.547
792.60
184.1
6.07
PC 37:6
100
10
45
11


155
oddPC 37:5
793.562
794.60
184.1
6.22
PC 37:5
100
10
45
11


156
oddPC 37:4
795.578
796.60
184.1
6.41
PC 37:4
100
10
45
11


157
oddPC 37:3
797.593
798.60
184.1
6.60
PC 37:3
100
10
45
11


158
oddPC 37:2
799.609
800.6
184.1
6.71
PC 37:2
100
10
45
11


159
APC 32:1
717.567
718.6
184.1
6.28
APC 32:1
100
10
45
11


160
APC 32:0
719.583
720.61
184.1
6.53
APC 32:0
100
10
45
11


161
APC 34:2
743.583
744.61
184.1
6.40
APC 34:2
100
10
45
11


162
APC 34:1
745.599
746.61
184.1
6.59
APC 34:1
100
10
45
11


163
APC 34:0
747.614
748.6
184.1
6.88
APC 34:0
100
10
45
11


164
APC 36:5
765.567
766.6
184.1
6.30
APC 36:5
100
10
45
11


165
APC 36:4
767.583
768.61
184.1
6.41
APC 36:4
100
10
45
11


166
APC 36:3
769.599
770.61
184.1
6.59
APC 36:3
100
10
45
11


167
APC 36:2
771.614
772.6
184.1
6.69
APC 36:2
100
10
45
11


168
APC 36:1
773.630
774.61
184.1
6.95
APC 36:1
100
10
45
11


169
APC 36:0
775.645
776.7
184.1
7.20
APC 36:0
100
10
45
11


170
APC 38:6
791.583
792.61
184.1
6.39
APC 38:6
100
10
45
11


171
APC 38:5
793.599
794.60
184.1
6.52
APC 38:5
100
10
45
11


172
APC 38:4
795.614
796.61
184.1
6.75
APC 38:4
100
10
45
11


173
APC 38:3
797.630
798.61
184.1
6.86
APC 38:3
100
10
45
11


174
APC 38:2
799.645
800.7
184.1
7.03
APC 38:2
100
10
45
11


175
modPC 506.3/3.50
505.300
506.3
184.1
3.50
modPC 506.3/3.50
100
10
45
11


176
modPC 508.3/3.30
507.310
508.3
184.1
3.30
modPC 508.3/3.30
100
10
45
11


177
modPC 510.3/4.00
509.300
510.3
184.1
4.00
modPC 510.3/4.00
100
10
45
11


178
modPC 512.3/1.70
511.300
512.3
184.1
1.70
modPC 512.3/1.70
100
10
45
11


179
modPC 536.3/3.50
535.300
536.3
184.1
3.50
modPC 536.3/3.50
100
10
45
11


180
modPC 538.3/4.10
537.300
538.3
184.1
4.10
modPC 538.3/4.10
100
10
45
11


181
modPC 552.4/3.90
551.400
552.40
184.1
3.90
modPC 552.4/3.90
100
10
45
11


182
modPC 564.4/4.70
563.400
564.4
184.1
4.70
modPC 564.4/4.70
100
10
45
11


183
modPC 566.4/5.10
565.400
566.4
184.1
5.10
modPC 566.4/5.10
100
10
45
11


184
modPC 580.4/4.84
579.400
580.4
184.1
4.84
modPC 580.4/4.84
100
10
45
11


185
modPC 590.4/4.80
589.400
590.4
184.1
4.80
modPC 590.4/4.80
100
10
45
11


186
modPC 592.4/5.10
591.400
592.4
184.1
5.10
modPC 592.4/5.10
100
10
45
11


187
modPC 594.4/3.26
593.400
594.4
184.1
3.26
modPC 594.4/3.26
100
10
45
11


188
modPC 608.4/5.33
607.410
608.41
184.1
5.33
modPC 608.4/5.33
100
10
45
11


189
modPC 608.4/3.84
607.400
608.40
184.1
3.84
modPC 608.4/3.84
100
10
45
11


190
modPC 610.4/2.03
609.400
610.4
184.1
2.03
modPC 610.4/2.03
100
10
45
11


191
modPC 622.4/4.54
621.400
622.4
184.1
4.54
modPC 622.4/4.54
100
10
45
11


192
modPC 633.4/4.51
632.400
633.4
184.1
4.51
modPC 633.4/4.51
100
10
45
11


193
modPC 636.4/3.37
635.400
636.4
184.1
3.37
modPC 636.4/3.37
100
10
45
11


194
modPC 645.4/4.49
644.400
645.4
184.1
4.49
modPC 645.4/4.49
100
10
45
11


195
modPC 650.4/3.24
649.403
650.40
184.1
3.24
modPC 650.4/3.24
100
10
45
11


196
modPC 650.4/4.44
649.430
650.42
184.1
4.44
modPC 650.4/4.44
100
10
45
11


197
modPC 650.4/3.94
649.420
650.41
184.1
3.94
modPC 650.4/3.94
100
10
45
11


198
modPC 664.4/4.22
663.420
664.4
184.1
4.32
modPC 664.4/4.22
100
10
45
11


199
modPC 666.4/2.99
665.400
666.4
184.1
2.99
modPC 666.4/2.99
100
10
45
11


200
modPC 678.4/4.37
677.400
678.40
184.1
4.37
modPC 678.4/4.37
100
10
45
11


201
modPC 678.4/4.94
677.410
678.41
184.1
5.16
modPC 678.4/4.94
100
10
45
11


202
modPC 678.4/5.51
677.420
678.42
184.1
5.34
modPC 678.4/5.51
100
10
45
11


203
modPC 690.4/4.11
689.400
690.40
184.1
4.11
modPC 690.4/4.11
100
10
45
11


204
modPC 690.4/4.90
689.400
690.41
184.1
4.90
modPC 690.4/4.90
100
10
45
11


205
modPC 690.4/6.00
689.410
690.42
184.1
6.00
modPC 690.4/6.00
100
10
45
11


206
modPC 692.4/5.05
691.400
692.40
184.1
5.05
modPC 692.4/5.05
100
10
45
11


207
modPC 692.4/5.52
691.420
692.41
184.1
5.52
modPC 692.4/5.52
100
10
45
11


208
modPC 692.4/6.10
691.440
692.42
184.1
6.10
modPC 692.4/6.10
100
10
45
11


209
modPC 694.4/6.20
693.400
694.4
184.1
6.20
modPC 694.4/6.20
100
10
45
11


210
modPC 703.5/4.09
702.500
703.5
184.1
4.09
modPC 703.5/4.09
100
10
45
11


211
modPC 704.5/3.81
703.500
704.5
184.1
3.81
modPC 704.5/3.81
100
10
45
11


212
modPC 706.5/3.79
705.500
706.5
184.1
3.79
modPC 706.5/3.79
100
10
45
11


213
modPC 720.5/4.52
719.510
720.5
184.1
4.52
modPC 720.5/4.52
100
10
45
11


214
modPC 736.5/5.38
735.500
736.5
184.1
5.38
modPC 736.5/5.38
100
10
45
11


215
modPC 743.5/5.91
742.500
743.5
184.1
5.91
modPC 743.5/5.91
100
10
45
11


216
modPC 745.5/6.35
744.500
745.5
184.1
6.35
modPC 745.5/6.35
100
10
45
11


217
modPC 752.5/5.58
751.500
752.5
184.1
5.58
modPC 752.5/5.58
100
10
45
11


218
modPC 764.5/6.52
763.500
764.5
184.1
6.52
modPC 764.5/6.52
100
10
45
11


219
modPC 769.5/6.25
768.500
769.5
184.1
6.25
modPC 769.5/6.25
100
10
45
11


220
modPC 772.5/5.37
771.500
772.5
184.1
5.37
modPC 772.5/5.37
100
10
45
11


221
modPC 773.6/6.47
772.500
773.5
184.1
6.47
modPC 773.6/6.47
100
10
45
11


222
modPC 788.6/5.19
787.500
788.5
184.1
5.19
modPC 788.6/5.19
100
10
45
11


223
modPC 801.6/6.70
800.600
801.6
184.1
6.70
modPC 801.6/6.70
100
10
45
11


224
modPC 816.6/5.58
815.600
816.60
184.1
5.58
modPC 816.6/5.58
100
10
45
11


225
modPC 818.6/6.10
817.610
818.61
184.1
6.39
modPC 818.6/6.10
100
10
45
11


226
modPC 818.6/6.48
817.620
818.62
184.1
6.64
modPC 818.6/6.48
100
10
45
11


227
modPC 828.6/6.03
827.600
828.6
184.1
6.03
modPC 828.6/6.03
100
10
45
11


228
modPC 843.6/7.10
842.600
843.6
184.1
7.10
modPC 843.6/7.10
100
10
45
11


229
modPC 866.6/7.24
865.600
866.6
184.1
7.24
modPC 866.6/7.24
100
10
45
11


230
modPC 878.6/5.98
877.600
878.6
184.1
5.98
modPC 878.6/5.98
100
10
45
11


231
modPC 881.6/6.05
880.600
881.6
184.1
6.05
modPC 881.6/6.05
100
10
45
11


232
COH
386.355
404.4
369.3
6.81
COH
55
10
17
12


S14
COH d7 (IS)
393.399
411.4
376.3
6.80
COH-d7
55
10
17
12


233
CE 14:0
596.553
614.6
369.3
9.35
C14:0
30
10
20
12


234
CE 15:0
610.569
628.6
369.3
9.27
C15:0
30
10
20
12


235
CE 16:2
620.553
638.6
369.3
9.21
C16:2
30
10
20
12


236
CE 16:1
622.569
640.6
369.3
9.33
C16:1
30
10
20
12


237
CE 16:0
624.585
642.6
369.3
9.36
C16:0
30
10
20
12


238
CE 17:1
636.585
654.6
369.3
9.48
C17:1
30
10
20
12


239
CE 17:0
638.600
656.6
369.3
9.39
C17:0
30
10
20
12


240
CE 18:3
647.577
665.6
370.3
9.22
C18:3 + 1
30
10
20
12


241
CE 18:2
650.601
668.6
371.3
9.33
C18:2 + 2
30
10
20
12


242
CE 18:1
651.608
669.6
370.3
9.46
C18:1 + 1
30
10
20
12


243
CE 18:0
652.616
670.6
369.3
9.60
C18:0
30
10
20
12


S15
CE 18:0 d6 (IS)
658.653
676.7
375.3
9.85
C18:0 d6 (IS)
30
10
20
12


S15
CE 18:0 d6 (IS)
659.661
677.7
376.3
9.85
C18:0 d6 + 1 (IS)
30
10
20
12


S15
CE 18:0 d6 (IS)
660.669
678.7
377.3
9.85
C18:0 d6 + 2 (IS)
30
10
20
12


244
CE 20:5
672.585
690.6
371.3
9.13
C20:5 + 2
30
10
20
12


245
CE 20:4
674.601
692.6
371.3
9.24
C20:4 + 2
30
10
20
12


246
CE 20:3
674.600
692.6
369.3
9.34
C20:3
30
10
20
12


247
CE 20:2
676.616
694.6
369.3
9.31
C20:2
30
10
20
12


248
CE 20:1
678.631
696.7
369.3
9.42
C20:1
30
10
20
12


249
CE 22:6
682.663
700.7
371.3
9.18
C22:6 + 2
30
10
20
12


250
CE 22:5
696.585
714.6
369.3
9.25
C22:5
30
10
20
12


251
CE 22:4
698.600
716.6
369.3
9.39
C22:4
30
10
20
12


252
CE 22:3
700.616
718.6
369.3
9.32
C22:3
30
10
20
12


253
CE 22:2
702.631
720.7
369.3
9.42
C22:2
30
10
20
12


254
CE 22:1
704.647
722.7
369.3
9.54
C22:1
30
10
20
12


255
CE 22:0
706.663
724.7
369.3
9.68
C22:0
30
10
20
12


256
CE 24:6
708.678
726.7
369.3
9.12
C24:6
30
10
20
12


257
CE 24:5
724.616
742.6
369.3
9.22
C24:5
30
10
20
12


258
CE 24:4
726.631
744.7
369.3
9.33
C24:4
30
10
20
12


259
CE 24:3
728.647
746.7
369.3
9.43
C24:3
30
10
20
12


260
CE 24:2
730.663
748.7
369.3
9.53
C24:2
30
10
20
12


261
CE 24:1
732.678
750.7
369.3
9.64
C24:1
30
10
20
12


262
CE 24:0
734.694
752.7
369.3
9.78
C24:0
30
10
20
12


263
modCE 558.5/7.74
557.510
558.5
369.3
7.74
modCE 558.5/7.74
55
10
20
12


264
modCE 588.5/7.94
587.500
588.5
369.3
7.94
modCE 588.5/7.94
55
10
20
12


265
modCE 682.7/8.76
681.700
682.7
369.3
8.76
modCE 682.7/8.76
55
10
20
12


266
modCE 790.8/6.57
789.800
790.8
369.3
6.57
modCE 790.8/6.57
55
10
20
12





aQ1, m/z setting for quardupole 1


bQ2, m/z setting for quardupole 2


ctR, retention time


dID, analyte identity (+1) and (+2) designate the isotope species


eDP, declustering potential


fEP, entrance potential


gCE, collision energy


fCXP, cell exit potential













TABLE 8







Lipid analytes measured in MRM experiment 2

















#
Analyte
exact mass
Q1a
Q3b
tRc
IDd
DPe
EPf
CEg
CXPh




















267
DG 14:0 14:0
512.444
530.5
285.2
1.90
DG 14:0 14:0
55
10
30
22


268
DG 14:1 16:0
538.465
556.5
313.3
1.90
DG 14:1 16:0
55
10
30
22


269
DG 14:0 16:0
540.475
558.5
313.3
2.00
DG 14:0 16:0
55
10
30
22


S16
DG 15:0 15:0 (IS)
540.475
558.5
299.3
2.10
DG 15:0 15:0 (IS)
55
10
30
22


270
DG 14:0 18:2
564.475
582.5
285.2
1.90
DG 14:0 18:2
55
10
30
22


271
DG 14:0 18:1
566.491
584.5
285.2
2.00
DG 14:0 18:1
55
10
30
22


272
DG 16:0 16:0
568.507
586.5
313.3
2.10
DG 16:0 16:0
55
10
30
22


273
DG 16:0 18:2
592.507
610.5
313.3
2.10
DG 16:0 18:2
55
10
30
22


274
DG 16:1 18:1
592.507
610.5
339.3
2.00
DG 16:1 18:1
55
10
30
22


275
DG 16:0 18:1
594.522
612.6
339.3
2.10
DG 16:0 18:1
55
10
30
22


276
DG 18:0 16:1
594.522
612.6
311.3
2.10
DG 18:0 16:1
55
10
30
22


277
DG 16:0 18:0
596.538
614.6
341.3
2.20
DG 16:0 18:0
55
10
30
22


278
DG 16:0 20:4
616.507
634.5
313.3
2.00
DG 16:0 20:4
55
10
30
22


279
DG 18:1 18:3
616.507
634.5
339.3
2.00
DG 18:1 18:3
55
10
30
22


280
DG 18:2 18:2
616.507
634.5
337.3
2.00
DG 18:2 18:2
55
10
30
22


281
DG 16:0 20:3
618.522
636.6
313.3
2.10
DG 16:0 20:3
55
10
30
22


282
DG 18:1 18:2
618.522
636.6
339.3
2.00
DG 18:1 18:2
55
10
30
22


283
DG 18:0 18:2
620.538
638.6
341.3
2.10
DG 18:0 18:2
55
10
30
22


284
DG 18:1 18:1
620.538
638.6
339.3
2.10
DG 18:1 18:1
55
10
30
22


285
DG 18:0 18:1
622.554
640.6
339.3
2.20
DG 18:0 18:1
55
10
30
22


286
DG 16:0 20:0
624.569
642.6
313.3
2.30
DG 16:0 20:0
55
10
30
22


287
DG 18:0 18:0
624.569
642.6
341.3
2.40
DG 18:0 18:0
55
10
30
22


288
DG 16:0 22:6
640.507
658.5
313.3
2.00
DG 16:0 22:6
55
10
30
22


289
DG 16:0 22:5
642.522
660.6
313.3
2.00
DG 16:0 22:5
55
10
30
22


290
DG 18:1 20:4
642.522
660.6
339.3
2.00
DG 18:1 20:4
55
10
30
22


291
DG 18:0 20:4
644.538
662.6
341.3
2.10
DG 18:0 20:4
55
10
30
22


292
DG 18:1 20:3
644.538
662.6
339.3
2.10
DG 18:1 20:3
55
10
30
22


293
DG 18:1 20:0
650.585
668.6
369.3
2.20
DG 18:1 20:0
55
10
30
22


294
TG 14:0 16:1 18:2
800.736
818.8
521.5
3.26
TG 14:0 16:1 18:2
95
10
30
12


295
TG 16:1 16:1 16:1
800.736
818.8
547.5
3.18
TG 16:1 16:1 16:1
95
10
30
12


296
TG 14:0 16:0 18:2
802.736
820.8
547.5
3.47
TG 14:0 16:0 18:2
95
10
30
12


297
TG 14:0 16:1 18:1
802.736
820.8
521.5
3.46
TG 14:0 16:1 18:1
95
10
30
12


298
TG 14:1 16:0 18:1
802.736
820.8
577.6
3.46
TG 14:1 16:0 18:1
95
10
30
12


299
TG 14:1 16:1 18:0
802.736
820.8
549.5
3.46
TG 14:1 16:1 18:0
95
10
30
12


300
TG 18:1 14:0 16:0
804.736
822.8
523.5
3.77
TG 18:1 14:0 16:0
95
10
30
12


301
TG 16:0 16:0 16:0
806.736
824.8
551.5
4.17
TG 16:0 16:0 16:0
95
10
30
12


302
TG 15:0 18:1 16:0
818.752
836.8
577.5
3.79
TG 15:0 18:1 16:0
95
10
30
12


303
TG 17:0 16:0 16:1
818.752
836.8
563.5
3.92
TG 17:0 16:0 16:1
95
10
30
12


304
TG 17:0 18:1 14:0
818.752
836.8
537.5
3.96
TG 17:0 18:1 14:0
95
10
30
12


305
TG 14:0 18:2 18:2
826.747
844.8
599.5
3.23
TG 14:0 18:2 18:2
95
10
30
12


306
TG 14:1 18:0 18:2
828.767
846.8
603.6
3.46
TG 14:1 18:0 18:2
95
10
30
12


307
TG 14:1 18:1 18:1
828.767
846.8
547.5
3.43
TG 14:1 18:1 18:1
95
10
30
12


308
TG 16:1 16:1 18:1
828.767
847.8
576.6
3.43
TG 16:1 16:1 18:1 +1
95
10
30
12


309
TG 16:0 16:0 18:2
830.767
848.8
551.5
3.82
TG 16:0 16:0 18:2
95
10
30
12


310
TG 16:1 16:1 18:0
830.767
848.8
547.5
3.78
TG 16:1 16:1 18:0
95
10
30
12


311
TG 16:0 16:1 18:1
830.767
849.8
550.5
3.75
TG 16:0 16:1 18:1 +1
95
10
30
12


312
TG 14:0 18:0 18:1
832.767
850.8
605.6
4.06
TG 14:0 18:0 18:1
95
10
30
12


313
TG 16:0 16:0 18:1
832.767
851.8
552.5
4.12
TG 16:0 16:0 18:1
95
10
30
12


314
TG 16:0 16:0 18:0
834.767
852.8
551.5
4.12
TG 16:0 16:0 18:0
95
10
30
12


315
TG 15:0 18:1 18:1
844.783
862.8
603.6
3.90
TG 15:0 18:1 18:1
95
10
30
12


316
TG 17:0 18:1 16:1
844.783
862.8
563.5
3.89
TG 17:0 18:1 16:1
95
10
30
12


317
TG 17:0 18:2 16:0
844.783
862.8
589.6
3.92
TG 17:0 18:2 16:0
95
10
30
12


318
TG 17:0 18:1 16:0
846.783
864.8
565.5
4.33
TG 17:0 18:1 16:0
95
10
30
12


319
TG 17:0 16:0 18:0
848.783
866.8
593.6
4.28
TG 17:0 16:0 18:0
95
10
30
12


S17
TG 17:0 17:0 17:0 (IS)
848.783
866.8
579.5
4.77
TG 17:0 17:0 17:0 (IS)
95
10
30
12


S17
TG 17:0 17:0 17:0 (IS)
848.783
867.8
580.5
4.77
TG 17:0 17:0 17:0 (IS)
95
10
30
12


320
TG 16:0 18:2 18:2
854.798
872.8
599.6
3.58
TG 16:0 18:2 18:2
95
10
30
12


321
TG 16:1 18:1 18:2
854.798
872.8
573.6
3.45
TG 16:1 18:1 18:2
95
10
30
12


322
TG 16:1 18:1 18:1
856.798
874.8
603.6
3.70
TG 16:1 18:1 18:1
95
10
30
12


323
TG 16:0 18:1 18:2
856.798
875.8
578.6
3.80
TG 16:0 18:1 18:2 +1
95
10
30
12


324
TG 16:0 18:1 18:1
858.798
877.8
604.6
4.06
TG 16:0 18:1 18:1 +1
95
10
30
12


325
TG 16:0 18:0 18:1
860.798
878.8
577.5
4.05
TG 16:0 18:0 18:1
95
10
30
12


326
TG 17:0 18:1 18:1
872.814
890.8
603.6
4.03
TG 17:0 18:1 18:1
95
10
30
12


327
TG 18:2 18:2 18:2
878.830
896.9
599.6
3.29
TG 18:2 18:2 18:2
95
10
30
12


328
TG 18:1 18:2 18:2
880.830
898.9
599.6
3.49
TG 18:1 18:2 18:2
95
10
30
12


329
TG 18:0 18:2 18:2
882.803
900.8
599.5
3.56
TG 18:0 18:2 18:2
95
10
30
12


330
TG 18:1 18:1 18:2
882.830
900.9
603.9
3.73
TG 18:1 18:1 18:2
95
10
30
12


331
TG 18:1 18:1 18:1
884.830
903.9
604.6
4.02
TG 18:1 18:1 18:1 +1
95
10
30
12


332
TG 18:0 18:1 18:1
886.830
904.9
603.6
4.02
TG 18:0 18:1 18:1
95
10
30
12


333
TG 18:0 18.0 18:1
888.830
906.9
607.6
4.37
TG 18:0 18:0 18:1
95
10
30
12


334
TG 18:0 18:0 18:0
890.830
908.9
607.6
4.90
TG 18:0 18:0 18:0
95
10
30
12


335
TG 18:2 18:2 20:4
902.861
920.9
599.6
3.29
TG 18:2 18:2 20:4
95
10
30
12


336
TG 18:1 18:1 20:4
906.861
924.9
603.6
3.60
TG 18:1 18:1 20:4
95
10
30
12


337
TG 18:1 18:1 22:6
930.892
948.9
603.7
3.42
TG 18:1 18:1 22:6
95
10
30
12





aQ1, m/z setting for quardupole 1


bQ2, m/z setting for quardupole 2


ctR, retention time


dID, analyte identity (+1) and (+2) designate the isotope species


eDP, declustering potential


fEP, entrance potential


gCE, collision energy


fCXP, cell exit potential













TABLE 9







Lipid analyte levelsa in stable and unstable cohorts













#
Analyte
stable (median)
unstable (median)
stable/unstable
Mann-Whitney U
Asymp. Sig. (2-tailed)
















1
Cer 16:0
388
400
1.03
2370
5.66E−01


2
Cer 18:1
203
212
1.04
1921
1.62E−02


3
Cer 18:0
170
196
1.15
1857
7.72E−03


4
Cer 20:0
139
148
1.07
2305
4.01E−01


5
Cer 22:0
794
761
0.96
2454
8.16E−01


6
Cer 24:1
1233
1207
0.98
2409
6.78E−01


7
Cer 24:0
2647
2332
0.88
2364.5
5.51E−01


8
MHC 16:0
1756
1734
0.99
2372
5.71E−01


9
MHC 18:1
53
61
1.15
2275.5
3.37E−01


10
MHC 18:0
351
366
1.04
2403.5
6.61E−01


11
MHC 20:0
505
440
0.87
2143
1.34E−01


12
MHC 22:0
3490
3239
0.93
2400.5
6.53E−01


13
MHC 24:1
4547
4066
0.89
2386
6.11E−01


14
MHC 24:0
5646
4785
0.85
2248.5
2.85E−01


15
DHC 16:0
8510
8786
1.03
2096.5
9.13E−02


16
DHC 18:1
61
76
1.24
1844
6.59E−03


17
DHC 18:0
141
145
1.03
2358
5.33E−01


18
DHC 20:0
104
113
1.09
2380
5.94E−01


19
DHC 22:0
593
640
1.08
2274
3.34E−01


20
DHC 24:1
2169
2268
1.05
2247
2.82E−01


21
DHC 24:0
585
637
1.09
2466
8.55E−01


22
THC 16:0
1516
1472
0.97
2300
3.90E−01


23
THC 18:1
166
162
0.98
2487
9.22E−01


24
THC 18:0
172
159
0.93
2202.5
2.09E−01


25
THC 20:0
67
64
0.96
2400.5
6.53E−01


26
THC 22:0
247
270
1.09
2337
4.78E−01


27
THC 24:1
617
614
0.99
2452.5
8.12E−01


28
THC 24:0
310
322
1.04
2284.5
3.56E−01


29
GM3 16:0
1443
1509
1.05
2439.5
7.71E−01


30
GM3 18:0
500
453
0.90
2022
4.64E−02


31
GM3 20:0
333
325
0.98
2324
4.46E−01


32
GM3 22:0
713
725
1.02
2472
8.74E−01


33
GM3 24:1
1103
1037
0.94
2291.5
3.71E−01


34
GM3 24:0
641
638
1.00
2467
8.58E−01


35
modCer 576.5/7.68
21
22
1.06
2275
3.36E−01


36
modCer 614.6/5.72
20
22
1.09
2052
6.15E−02


37
modCer 632.6/9.22
4
4
1.04
2503
9.74E−01


38
modCer 651.6/7.56
288
262
0.91
2330
4.61E−01


39
modCer 703.6/5.87
651
626
0.96
2451.5
8.08E−01


40
modCer 731.6/6.22
45
56
1.24
1533
6.78E−05


41
modCer 766.6/7.17
24
22
0.90
2275
3.36E−01


42
modCer 769.6/8.01
158
142
0.90
2334
4.71E−01


43
modCer 798.7/7.29
142
134
0.94
2312
4.18E−01


44
modCer 875.7/9.23
354
395
1.12
1993
3.49E−02


45
modCer 883.8/7.75
77
83
1.07
2420
7.11E−01


46
modCer 886.8/9.06
48
49
1.03
2156
1.48E−01


47
modCer 910.8/8.98
36
40
1.10
2027
4.87E−02


48
modCer 921.8/9.05
84
82
0.98
2450.5
8.05E−01


49
SM 14:0
12650
12696
1.00
2464
8.48E−01


50
SM 15:0
7961
8841
1.11
2205.5
2.13E−01


51
SM 16:1
18788
20000
1.06
2231
2.54E−01


52
SM 16:0
108207
114439
1.06
2214.5
2.27E−01


53
SM 18:1
14013
16230
1.16
1761
2.25E−03


54
SM 18:0
26090
30897
1.18
1543
8.04E−05


55
SM 20:1
8941
9374
1.05
2490
9.32E−01


56
SM 22:1
15073
15742
1.04
2171
1.66E−01


57
SM 22:0
26334
27440
1.04
2129
1.20E−01


58
SM 24:2
52283
52810
1.01
2333
4.68E−01


59
SM 24:1
67438
66486
0.99
2432.5
7.49E−01


60
SM 24:0
17117
17197
1.00
2386
6.11E−01


61
PG 16:1 18:1
6
5
0.90
2401.5
6.56E−01


62
PG 16:0 18:1
68
63
0.93
2250
2.88E−01


63
PG 18:1 18:1
111
100
0.90
2110.5
1.03E−01


64
PG 18:0 18:1
66
63
0.96
2236
2.63E−01


65
BMP 18:1 18:1
31
34
1.11
2266
3.18E−01


66
PS 36:2
138
147
1.06
2330
4.61E−01


67
PS 36:1
876
926
1.06
2419
7.08E−01


68
PS 38:5
50
51
1.03
2345
4.99E−01


69
PS 38:4
844
981
1.16
2295
3.79E−01


70
PS 38:3
182
191
1.05
2426
7.29E−01


71
PS 40:6
101
96
0.96
2286
3.59E−01


72
PS 40:5
89
95
1.07
2385
6.08E−01


73
PE 32:1
119
111
0.93
2272
3.30E−01


74
PE 32:0
52
55
1.05
2208.5
2.18E−01


75
PE 34:2
1505
1746
1.16
2362
5.44E−01


76
PE 34:1
1092
1305
1.20
2162
1.55E−01


77
PE 36.5
221
186
0.84
2014.5
4.31E−02


78
PE 36:4
2409
2253
0.94
2418
7.05E−01


79
PE 36:3
974
1034
1.06
2290
3.68E−01


80
PE 36:2
3848
3741
0.97
2290
3.68E−01


81
PE 36:1
842
826
0.98
2374
5.77E−01


82
PE 36:0
22
21
0.95
2485
9.16E−01


83
PE 38:6
2582
2994
1.16
2240
2.70E−01


84
PE 38:5
1890
1834
0.97
2481
9.03E−01


85
PE 38:4
4774
5155
1.08
2304
3.99E−01


86
PE 38:3
540
521
0.96
2392
6.28E−01


87
PE 38:2
90
98
1.10
2333
4.68E−01


88
PE 38:1
49
54
1.09
2357.5
5.32E−01


89
PE 40:7
227
225
0.99
2451
8.07E−01


90
PE 40:6
1359
1515
1.11
2296
3.81E−01


91
PI 32:1
238
196
0.82
1987.5
3.30E−02


92
PI 32:0
88
71
0.81
2052
6.15E−02


93
PI 34:1
1815
1361
0.75
1840
6.27E−03


94
PI 34:0
36
29
0.80
1832
5.68E−03


95
PI 36:4
1355
1234
0.91
1831.5
5.64E−03


96
PI 36:3
1196
915
0.77
1612
2.50E−04


97
PI 36:2
5407
5396
1.00
2499
9.61E−01


98
PI 36:1
1572
1165
0.74
1588
1.70E−04


99
PI 36:0
6
6
0.95
2164
1.58E−01


100
PI 38:6
231
203
0.88
2008
4.05E−02


101
PI 38:5
878
760
0.87
1802
3.88E−03


102
PI 38:4
11667
10321
0.88
2124
1.15E−01


103
PI 38:3
2445
2078
0.85
1990
3.38E−02


104
PI 38:2
169
126
0.75
1718
1.24E−03


105
PI 40:6
544
503
0.92
2151
1.43E−01


106
PI 40:5
572
508
0.89
2205
2.13E−01


107
PI 40:4
153
136
0.89
1916
1.54E−02


108
LPC 14:0
1606
1082
0.67
1428
1.03E−05


109
LPC 15:0
1028
911
0.89
2227.5
2.48E−01


110
LPC 16:1
3754
3022
0.81
1581
1.52E−04


111
LPC 16:0
63869
62301
0.98
2319
4.34E−01


112
LPC 18:2
26381
20565
0.78
1758
2.16E−03


113
LPC 18:1
23188
18279
0.79
1611.5
2.48E−04


114
LPC 18:0
20232
19420
0.96
2314
4.22E−01


115
LPC 20:5
1599
1333
0.83
1895
1.21E−02


116
LPC 20:4
7636
7843
1.03
2414.5
6.94E−01


117
LPC 20:3
3237
2916
0.90
1959.5
2.47E−02


118
LPC 20:2
325
280
0.86
1866
8.60E−03


119
LPC 20:1
227
230
1.01
2407
6.72E−01


120
LPC 20:0
97
83
0.86
2016
4.38E−02


121
LPC 22:6
2689
2520
0.94
2507
9.87E−01


122
LPAF 16:0
453
421
0.93
2196
1.99E−01


123
LPAF 18:1
325
336
1.03
2491
9.35E−01


124
LPAF 18:0
113
111
0.98
2436.5
7.62E−01


125
PC 30:2
5779
6472
1.12
2160
1.53E−01


126
PC 32:2
10897
10519
0.97
2252
2.91E−01


127
PC 32:1
173997
160377
0.92
2244.5
2.78E−01


128
PC 32:0
12453
12478
1.00
2399.5
6.50E−01


129
PC 34:3
24565
19297
0.79
1673
6.41E−04


130
PC 34:2
257882
250685
0.97
2329
4.58E−01


131
PC 34:1
156440
154331
0.99
2322
4.41E−01


132
PC 34:0
4083
3782
0.93
2094
8.94E−02


133
PC 36:5
42661
34479
0.81
2013.5
4.27E−02


134
PC 36:4
115623
118023
1.02
2429.5
7.40E−01


135
PC 36:3
119722
113636
0.95
2080.5
7.95E−02


136
PC 36:2
202275
182018
0.90
1986
3.25E−02


137
PC 38:6
53779
55364
1.03
2351
5.15E−01


138
PC 38:5
57321
56032
0.98
2483.5
9.11E−01


139
PC 38:4
99515
93722
0.94
2502
9.71E−01


140
PC 40:7
4389
4527
1.03
2485
9.16E−01


141
PC 40:6
26276
28390
1.08
2225
2.44E−01


142
PC 40:5
16485
17300
1.05
2420
7.11E−01


143
PC 44:12
1865
1862
1.00
2453
8.13E−01


144
oddPC 31:1
2474
2671
1.08
2193
1.95E−01


145
oddPC 31:0
1354
1132
0.84
1970
2.75E−02


146
oddPC 33:0
1958
1895
0.97
2359.5
5.37E−01


147
oddPC 33:1
5456
5000
0.92
2044
5.71E−02


148
oddPC 33:2
4922
4848
0.99
2495
9.48E−01


149
oddPC 35:4
2077
2232
1.07
2460.5
8.37E−01


150
oddPC 35:3
2365
2098
0.89
1886.5
1.10E−02


151
oddPC 35:2
10642
10938
1.03
2478
8.93E−01


152
oddPC 35:1
9601
9814
1.02
2382
5.99E−01


153
oddPC 35:0
428
383
0.89
2022
4.64E−02


154
oddPC 37:6
1040
1050
1.01
2399.5
6.50E−01


155
oddPC 37:5
1925
1549
0.80
2143
1.34E−01


156
oddPC 37:4
7032
7012
1.00
2250.5
2.89E−01


157
oddPC 37:3
5051
4875
0.97
2382
5.99E−01


158
oddPC 37:2
7640
8107
1.06
2402.5
6.59E−01


159
APC 32:1
487
478
0.98
2353
5.20E−01


160
APC 32:0
2060
2130
1.03
2374
5.77E−01


161
APC 34:2
3121
2567
0.82
1789
3.27E−03


162
APC 34:1
4539
4636
1.02
2478.5
8.95E−01


163
APC 34:0
617
682
1.11
2357.5
5.32E−01


164
APC 36:5
7280
7273
1.00
2244
2.77E−01


165
APC 36:4
10625
10287
0.97
2154
1.46E−01


166
APC 36:3
4020
3839
0.96
2129
1.20E−01


167
APC 36:2
2421
2460
1.02
2271
3.28E−01


168
APC 36:1
1134
1168
1.03
2496.5
9.53E−01


169
APC 36:0
108
112
1.04
2426.5
7.31E−01


170
APC 38:6
4055
3832
0.94
2106
9.90E−02


171
APC 38:5
9768
9868
1.01
2439.5
7.71E−01


172
APC 38:4
9135
8994
0.98
2472
8.74E−01


173
APC 38:3
1473
1425
0.97
2226
2.46E−01


174
APC 38:2
563
570
1.01
2510.5
9.98E−01


175
modPC 506.3/3.50
10
10
0.96
2274.5
3.35E−01


176
modPC 508.3/3.30
76
75
0.98
2454.5
8.18E−01


177
modPC 510.3/4.00
29
29
1.02
2480
9.00E−01


178
modPC 512.3/1.70
103
102
0.99
2467.5
8.59E−01


179
modPC 536.3/3.50
53
46
0.88
2015
4.33E−02


180
modPC 538.3/4.10
48
40
0.84
1984
3.18E−02


181
modPC 552.4/3.90
61
51
0.83
2036
5.30E−02


182
modPC 564.4/4.70
6
6
0.94
2199.5
2.04E−01


183
modPC 566.4/5.10
7
6
0.95
2196
1.99E−01


184
modPC 580.4/4.84
13
11
0.80
1833
5.75E−03


185
modPC 590.4/4.80
3
3
1.05
2428
7.35E−01


186
modPC 592.4/5.10
17
14
0.86
2010
4.13E−02


187
modPC 594.4/3.26
132
168
1.27
2377
5.85E−01


188
modPC 608.4/5.33
36
30
0.84
1758.5
2.17E−03


189
modPC 608.4/3.84
19
26
1.40
2377
5.85E−01


190
modPC 610.4/2.03
43
48
1.12
2343.5
4.95E−01


191
modPC 622.4/4.54
3
3
0.94
2506
9.84E−01


192
modPC 633.4/4.51
12
12
1.00
2485.5
9.17E−01


193
modPC 636.4/3.37
174
168
0.96
2438.5
7.68E−01


194
modPC 645.4/4.49
21
21
1.00
2382
5.99E−01


195
modPC 650.4/3.24
701
761
1.09
2502
9.71E−01


196
modPC 650.4/4.44
28
30
1.10
2435
7.57E−01


197
modPC 650.4/3.94
22
29
1.30
2321.5
4.40E−01


198
modPC 664.4/4.22
76
75
0.99
2471
8.71E−01


199
modPC 666.4/2.99
156
165
1.06
2498
9.58E−01


200
modPC 678.4/4.37
215
251
1.17
2428
7.35E−01


201
modPC 678.4/4.94
68
68
0.99
2477
8.90E−01


202
modPC 678.4/5.51
238
124
0.52
1437
1.21E−05


203
modPC 690.4/4.11
66
56
0.85
2296
3.81E−01


204
modPC 690.4/4.90
1734
1915
1.10
2192
1.94E−01


205
modPC 690.4/6.00
104
93
0.90
2134
1.25E−01


206
modPC 692.4/5.05
13
14
1.07
2037.5
5.38E−02


207
modPC 692.4/5.52
98
65
0.66
1508.5
4.43E−05


208
modPC 692.4/6.10
115
105
0.92
2063
6.80E−02


209
modPC 694.4/6.20
11
10
0.89
2045
5.77E−02


210
modPC 703.5/4.09
51
65
1.28
2321
4.39E−01


211
modPC 704.5/3.81
12
11
0.97
2440.5
7.74E−01


212
modPC 706.5/3.79
4
5
1.19
2430
7.41E−01


213
modPC 720.5/4.52
18
11
0.61
2480
9.00E−01


214
modPC 736.5/5.38
28
22
0.80
1874
9.46E−03


215
modPC 743.5/5.91
672
805
1.20
1969
2.73E−02


216
modPC 745.5/6.35
1242
1038
0.84
1853
7.35E−03


217
modPC 752.5/5.58
260
122
0.47
1373.5
3.59E−06


218
modPC 764.5/6.52
447
424
0.95
2255
2.97E−01


219
modPC 769.5/6.25
4772
4611
0.97
2160
1.53E−01


220
modPC 772.5/5.37
75
75
0.99
2473
8.77E−01


221
modPC 773.6/6.47
5940
6158
1.04
2275
3.36E−01


222
modPC 788.6/5.19
101
106
1.05
2286
3.59E−01


223
modPC 801.6/6.70
13486
13988
1.04
2235
2.61E−01


224
modPC 816.6/5.58
32
29
0.93
2488
9.25E−01


225
modPC 818.6/6.10
142
136
0.96
2143
1.34E−01


226
modPC 818.6/6.48
1301
1244
0.96
2466
8.55E−01


227
modPC 828.6/6.03
46
85
1.84
2484
9.12E−01


228
modPC 843.6/7.10
410
405
0.99
2487.5
9.24E−01


229
modPC 866.6/7.24
77
71
0.92
2266.5
3.19E−01


230
modPC 878.6/5.98
28
26
0.92
2218
2.33E−01


231
modPC 881.6/6.05
15
12
0.82
2049
5.98E−02


232
COH
490638
486413
0.99
2268.5
3.23E−01


233
CE 14:0
11554
8074
0.70
1729.5
1.46E−03


234
CE 15:0
9042
7827
0.87
2248
2.84E−01


235
CE 16:2
9336
7547
0.81
1929
1.77E−02


236
CE 16:1
136571
114150
0.84
2036
5.30E−02


237
CE 16:0
183893
185978
1.01
2490
9.32E−01


238
CE 17:1
26988
23067
0.85
2029
4.96E−02


239
CE 17:0
10576
10203
0.96
2390
6.22E−01


240
CE 18:3
799367
682914
0.85
1934.5
1.89E−02


241
CE 18:2
4990566
5209877
1.04
2488
9.25E−01


242
CE 18:1
1046679
1083523
1.04
2364
5.49E−01


243
CE 18:0
24069
23270
0.97
2419
7.08E−01


244
CE 20:5
1804461
1693410
0.94
2299
3.88E−01


245
CE 20:4
4606083
4687500
1.02
2371
5.68E−01


246
CE 20:3
313482
332744
1.06
2400
6.51E−01


247
CE 20:2
6701
6193
0.92
2329
4.58E−01


248
CE 20:1
865
873
1.01
2469
8.64E−01


249
CE 22:6
1125037
1241975
1.10
2254
2.95E−01


250
CE 22:5
79354
87933
1.11
2278
3.43E−01


251
CE 22:4
7099
7820
1.10
2396
6.39E−01


252
CE 22:3
365
352
0.96
2358
5.33E−01


253
CE 22:2
137
146
1.07
2279
3.45E−01


254
CE 22:1
540
578
1.07
2437
7.63E−01


255
CE 22:0
323
308
0.95
2321
4.39E−01


256
CE 24:6
1566
1664
1.06
2489
9.29E−01


257
CE 24:5
919
882
0.96
2426.5
7.31E−01


258
CE 24:4
288
293
1.02
2437
7.63E−01


259
CE 24:3
29
31
1.09
2500
9.64E−01


260
CE 24:2
246
229
0.93
2352
5.17E−01


261
CE 24:1
1132
981
0.87
2291
3.70E−01


262
CE 24:0
431
363
0.84
2236
2.63E−01


263
modCE 558.5/7.74
17347
21339
1.23
2354
5.22E−01


264
modCE 588.5/7.94
3552
3368
0.95
2461
8.39E−01


265
modCE 682.7/8.76
7518
6876
0.91
2119
1.10E−01


266
modCE 790.8/6.57
8677
8481
0.98
2403
6.60E−01


267
DG 14:0 14:0
16
10
0.62
1776
2.75E−03


268
DG 14:1 16:0
64
42
0.66
1861
8.10E−03


269
DG 14:0 16:0
334
249
0.75
1954
2.33E−02


270
DG 14:0 18:2
249
196
0.79
2017
4.42E−02


271
DG 14:0 18:1
778
497
0.64
1888
1.12E−02


272
DG 16:0 16:0
1171
1063
0.91
2416
6.99E−01


273
DG 16:0 18:2
2520
2949
1.17
2300
3.90E−01


274
DG 16:1 18:1
2974
2296
0.77
2118
1.09E−01


275
DG 16:0 18:1
6236
6222
1.00
2503
9.74E−01


276
DG 18:0 16:1
215
133
0.62
2036
5.30E−02


277
DG 16:0 18:0
898
729
0.81
2123
1.14E−01


278
DG 16:0 20:4
524
536
1.02
2400.5
6.53E−01


279
DG 18:1 18:3
1180
1179
1.00
2258
3.03E−01


280
DG 18:2 18:2
878
1055
1.20
2108
1.01E−01


281
DG 16:0 20:3
311
216
0.70
2003
3.85E−02


282
DG 18:1 18:2
7235
8569
1.18
2276
3.38E−01


283
DG 18:0 18:2
636
614
0.97
2461
8.39E−01


284
DG 18:1 18:1
8232
9135
1.11
2492
9.38E−01


285
DG 18:0 18:1
1099
984
0.90
2274
3.34E−01


286
DG 16:0 20:0
70
50
0.71
1766
2.41E−03


287
DG 18:0 18:0
281
269
0.96
2399
6.48E−01


288
DG 16:0 22:6
274
242
0.88
2357
5.30E−01


289
DG 16:0 22:5
166
166
1.00
2477
8.90E−01


290
DG 18:1 20:4
1801
1800
1.00
2462
8.42E−01


291
DG 18:0 20:4
196
187
0.96
2468
8.61E−01


292
DG 18:1 20:3
881
749
0.85
2086
8.34E−02


293
DG 18:1 20:0
136
84
0.62
1592
1.81E−04


294
TG 14:0 16:1 18:2
1960
1117
0.57
1711
1.12E−03


295
TG 16:1 16:1 16:1
1015
545
0.54
1709
1.09E−03


296
TG 14:0 16:0 18:2
4686
2933
0.63
1828.5
5.43E−03


297
TG 14:0 16:1 18:1
6521
3704
0.57
1709
1.09E−03


298
TG 14:1 16:0 18:1
7417
6243
0.84
2265
3.16E−01


299
TG 14:1 16:1 18:0
6201
3692
0.60
1798
3.68E−03


300
TG 18:1 14:0 16:0
9040
5803
0.64
1752
1.99E−03


301
TG 16:0 16:0 16:0
2820
2009
0.71
2060
6.62E−02


302
TG 15:0 18:1 16:0
6769
6293
0.93
2380
5.94E−01


303
TG 17:0 16:0 16:1
2598
1751
0.67
2079
7.84E−02


304
TG 17:0 18:1 14:0
2370
1840
0.78
2087
8.41E−02


305
TG 14:0 18:2 18:2
668
486
0.73
2011
4.17E−02


306
TG 14:1 18:0 18:2
649
471
0.73
1845
6.67E−03


307
TG 14:1 18:1 18:1
3661
2683
0.73
1931
1.81E−02


308
TG 16:1 16:1 18:1
4479
3547
0.79
2019
4.51E−02


309
TG 16:0 16:0 18:2
9040
9235
1.02
2504
9.77E−01


310
TG 16:1 16:1 18:0
381
251
0.66
1797
3.63E−03


311
TG 16:0 16:1 18:1
37315
26921
0.72
2004
3.89E−02


312
TG 14:0 18:0 18:1
524
344
0.66
1768
2.47E−03


313
TG 16:0 16:0 18:1
33096
30064
0.91
2301
3.92E−01


314
TG 16:0 16:0 18:0
3805
2691
0.71
2122
1.13E−01


315
TG 15:0 18:1 18:1
1399
1428
1.02
2395
6.37E−01


316
TG 17:0 18:1 16:1
6309
5383
0.85
2241
2.71E−01


317
TG 17:0 18:2 16:0
3076
2308
0.75
2212
2.23E−01


318
TG 17:0 18:1 16:0
3476
2551
0.73
2220
2.36E−01


319
TG 17:0 16:0 18:0
317
218
0.69
2140
1.31E−01


320
TG 16:0 18:2 18:2
11136
11393
1.02
2344
4.96E−01


321
TG 16:1 18:1 18:2
9590
8250
0.86
2314
4.22E−01


322
TG 16:1 18:1 18:1
10230
9729
0.95
2136
1.27E−01


323
TG 16:0 18:1 18:2
43541
47844
1.10
2192
1.94E−01


324
TG 16:0 18:1 18:1
97258
104695
1.08
2494.5
9.46E−01


325
TG 16:0 18:0 18:1
3702
4087
1.10
2504
9.77E−01


326
TG 17:0 18:1 18:1
2351
2207
0.94
2303
3.97E−01


327
TG 18:2 18:2 18:2
2752
3083
1.12
2504
9.77E−01


328
TG 18:1 18:2 18:2
4822
5347
1.11
2496
9.51E−01


329
TG 18:0 18:2 18:2
966
1085
1.12
2481.5
9.04E−01


330
TG 18:1 18:1 18:2
6735
7857
1.17
2191
1.92E−01


331
TG 18:1 18:1 18:1
44053
45755
1.04
2509
9.93E−01


332
TG 18:0 18:1 18:1
8120
7955
0.98
2337.5
4.80E−01


333
TG 18:0 18:0 18:1
1715
1686
0.98
2275
3.36E−01


334
TG 18:0 18:0 18:0
257
166
0.64
1972
2.81E−02


335
TG 18:2 18:2 20:4
1288
1269
0.99
2441
7.76E−01


336
TG 18:1 18:1 20:4
6211
6972
1.12
2255.5
2.98E−01


337
TG 18:1 18:1 22:6
637
661
1.04
2333.5
4.70E−01





alevels are expressed as pmol/mL plasma













TABLE 9a







Lipid analyte levelsa in control (normal) and CAD (heart disease)













control
CAD
CAD/

Asymp. Sig.


#
(median)
(median)
control
Mann-Whitney U
(2-tailed)















1
385
395
1.03
3847
1.83E−01


2
202
208
1.03
3635.5
6.00E−02


3
129
180
1.39
2167
1.31E−08


4
121
144
1.20
3120
1.30E−03


5
845
776
0.92
3649
6.49E−02


6
1152
1211
1.05
3551
3.58E−02


7
3139
2539
0.81
2848
8.83E−05


8
2115
1734
0.82
2702
1.72E−05


9
66
59
0.90
3840
1.77E−01


10
408
362
0.89
3492.5
2.44E−02


11
632
453
0.72
2539
2.35E−06


12
5053
3352
0.66
1935.5
3.29E−10


13
5179
4346
0.84
2923
1.94E−04


14
7718
5057
0.66
2055
2.30E−09


15
9745
8562
0.88
3155.5
1.78E−03


16
79
72
0.91
3520.5
2.94E−02


17
154
142
0.92
3803.5
1.48E−01


18
114
107
0.93
3949
2.85E−01


19
755
625
0.83
2842
8.28E−05


20
2716
2214
0.82
2811
5.91E−05


21
754
608
0.81
2627
7.02E−06


22
1730
1479
0.85
2994
3.96E−04


23
168
163
0.97
3808
1.52E−01


24
185
164
0.89
3403.5
1.31E−02


25
72
66
0.90
3635.5
6.00E−02


26
309
262
0.85
3147
1.65E−03


27
741
614
0.83
3287.5
5.40E−03


28
418
321
0.77
2237
3.72E−08


29
1648
1485
0.90
3353
8.99E−03


30
603
477
0.79
2322
1.27E−07


31
346
330
0.95
3705
8.90E−02


32
857
719
0.84
3240.5
3.69E−03


33
1145
1059
0.92
3900.5
2.32E−01


34
806
638
0.79
2664
1.10E−05


35
18
22
1.18
3321
7.03E−03


36
25
21
0.83
2686.5
1.43E−05


37
4
4
0.88
3146.5
1.65E−03


38
347
273
0.79
2795.5
4.98E−05


39
623
641
1.03
4148.5
5.81E−01


40
45
51
1.11
3493
2.45E−02


41
32
23
0.70
1880
1.29E−10


42
185
150
0.81
2818
6.38E−05


43
194
136
0.70
2181.5
1.63E−08


44
344
367
1.07
4114
5.21E−01


45
79
79
1.01
3777.5
1.30E−01


46
43
48
1.11
3177
2.15E−03


47
37
38
1.03
3909
2.41E−01


48
68
83
1.22
4163
6.07E−01


49
15313
12696
0.83
2580.5
3.96E−06


50
10000
8246
0.82
2690.5
1.50E−05


51
22484
19403
0.86
2962
2.89E−04


52
127011
112450
0.89
2408
4.18E−07


53
15061
15330
1.02
4025
3.83E−01


54
27213
28333
1.04
3846
1.82E−01


55
9541
9096
0.95
3648
6.46E−02


56
17806
15509
0.87
2692.5
1.54E−05


57
33168
27073
0.82
2348.5
1.84E−07


58
51907
52810
1.02
4240
7.53E−01


59
72611
67172
0.93
2801
5.29E−05


60
22588
17197
0.76
2084
3.64E−09


61
7
6
0.79
3503
2.62E−02


62
66
65
1.00
4138.5
5.63E−01


63
117
106
0.90
3821
1.61E−01


64
67
64
0.96
4166.5
6.13E−01


65
30
33
1.12
4195
6.66E−01


66
216
145
0.67
3004
4.37E−04


67
1176
886
0.75
3453
1.86E−02


68
95
51
0.53
2596
4.80E−06


69
1290
909
0.70
2862
1.03E−04


70
263
185
0.71
3027.5
5.49E−04


71
150
98
0.66
2168
1.33E−08


72
148
90
0.61
2352
1.93E−07


73
104
113
1.09
3660
6.92E−02


74
60
53
0.89
3643
6.27E−02


75
1727
1608
0.93
3949
2.85E−01


76
1055
1181
1.12
3865
1.98E−01


77
226
201
0.89
3537
3.27E−02


78
2115
2297
1.09
4105
5.06E−01


79
1214
1023
0.84
3379
1.09E−02


80
4647
3822
0.82
3527
3.06E−02


81
978
826
0.85
3662
7.00E−02


82
23
21
0.94
3433
1.62E−02


83
2630
2691
1.02
4199
6.74E−01


84
1869
1864
1.00
4287
8.47E−01


85
4566
4988
1.09
4022
3.79E−01


86
468
529
1.13
3938.5
2.73E−01


87
104
94
0.90
4032
3.93E−01


88
58
50
0.87
3843.5
1.80E−01


89
238
226
0.95
4153
5.89E−01


90
1289
1405
1.09
4100
4.98E−01


91
206
210
1.02
4023
3.81E−01


92
120
73
0.61
2332
1.46E−07


93
2026
1591
0.78
2824
6.81E−05


94
53
33
0.62
1975
6.32E−10


95
1776
1290
0.73
2931
2.11E−04


96
1446
941
0.65
2024
1.40E−09


97
6918
5398
0.78
2199
2.12E−08


98
1925
1370
0.71
2174
1.46E−08


99
8
6
0.69
2625
6.85E−06


100
310
219
0.71
2511.5
1.65E−06


101
1055
808
0.77
2359
2.13E−07


102
12132
10752
0.89
3273
4.81E−03


103
2831
2187
0.77
3219
3.08E−03


104
180
143
0.80
3041
6.25E−04


105
665
523
0.79
2942
2.36E−04


106
628
545
0.87
3241
3.70E−03


107
168
142
0.85
3669
7.28E−02


108
1969
1313
0.67
2097
4.46E−09


109
1276
971
0.76
2615
6.06E−06


110
3938
3413
0.87
3190
2.41E−03


111
74468
63237
0.85
2594
4.68E−06


112
32914
24015
0.73
2268
5.85E−08


113
24820
20963
0.84
2897
1.48E−04


114
26571
20000
0.75
2457
8.07E−07


115
1894
1427
0.75
3398
1.26E−02


116
7632
7778
1.02
3952
2.89E−01


117
3236
3061
0.95
4026
3.85E−01


118
385
301
0.78
3258
4.26E−03


119
293
228
0.78
2730.5
2.39E−05


120
150
86
0.57
1208
3.11E−16


121
2456
2533
1.03
3792
1.40E−01


122
551
436
0.79
2683
1.37E−05


123
404
327
0.81
3199
2.60E−03


124
145
112
0.77
2768
3.66E−05


125
6822
6130
0.90
3343
8.33E−03


126
12050
10636
0.88
2938
2.26E−04


127
156579
163194
1.04
3946
2.82E−01


128
14091
12478
0.89
3309
6.40E−03


129
27705
21007
0.76
2613
5.91E−06


130
280676
252174
0.90
2814
6.10E−05


131
148026
155147
1.05
4046.5
4.14E−01


132
4705
3851
0.82
2271
6.12E−08


133
46569
36846
0.79
3304
6.15E−03


134
107556
115909
1.08
3711.5
9.22E−02


135
117647
116393
0.99
3785
1.35E−01


136
230220
190000
0.83
2352
1.93E−07


137
61373
55038
0.90
3369
1.01E−02


138
61353
56179
0.92
3603.5
4.96E−02


139
88083
95378
1.08
3848.5
1.84E−01


140
5171
4496
0.87
3500.5
2.57E−02


141
25528
27091
1.06
4231
7.35E−01


142
16434
17222
1.05
4194.5
6.65E−01


143
2224
1862
0.84
3342.5
8.30E−03


144
2872
2630
0.92
3720
9.66E−02


145
1524
1188
0.78
3169.5
2.02E−03


146
2116
1919
0.91
3608
5.09E−02


147
5147
5180
1.01
4355
9.87E−01


148
5753
4850
0.84
2946
2.46E−04


149
2298
2141
0.93
3736.5
1.05E−01


150
2637
2179
0.83
3095
1.03E−03


151
12749
10895
0.85
3205
2.74E−03


152
9750
9643
0.99
4279.5
8.32E−01


153
481
398
0.83
2988
3.74E−04


154
1343
1049
0.78
2965
2.97E−04


155
1924
1732
0.90
3272
4.77E−03


156
6800
7013
1.03
4330
9.35E−01


157
4760
4902
1.03
4000.5
3.50E−01


158
8960
7970
0.89
2910.5
1.71E−04


159
575
482
0.84
2843
8.37E−05


160
2302
2097
0.91
3457
1.91E−02


161
4266
2754
0.65
1526
2.05E−13


162
5162
4618
0.89
3350.5
8.82E−03


163
742
646
0.87
3111
1.20E−03


164
8600
7273
0.85
2663.5
1.09E−05


165
12154
10517
0.87
2777
4.05E−05


166
4892
3935
0.80
2276
6.57E−08


167
3434
2456
0.72
2220
2.90E−08


168
1429
1148
0.80
3115.5
1.25E−03


169
135
109
0.81
3005.5
4.44E−04


170
5355
3902
0.73
2199
2.12E−08


171
11176
9833
0.88
2831
7.35E−05


172
10267
9030
0.88
3392
1.20E−02


173
1681
1460
0.87
3242
3.73E−03


174
812
570
0.70
2573.5
3.63E−06


175
15
10
0.69
2480
1.09E−06


176
96
76
0.79
2842
8.28E−05


177
40
29
0.73
2563
3.18E−06


178
127
103
0.81
2918
1.84E−04


179
64
48
0.75
2855
9.52E−05


180
73
44
0.60
1758
1.54E−11


181
98
54
0.56
1143
7.59E−17


182
8
6
0.67
2141
8.81E−09


183
9
7
0.72
1954
4.47E−10


184
24
11
0.49
844
8.09E−20


185
4
3
0.66
2376
2.70E−07


186
20
16
0.77
2607
5.49E−06


187
166
168
1.01
4185.5
6.48E−01


188
53
33
0.62
1157
1.03E−16


189
22
24
1.07
4355
9.87E−01


190
45
47
1.05
4077.5
4.62E−01


191
5
3
0.68
3658
6.84E−02


192
15
12
0.78
2313.5
1.12E−07


193
253
171
0.68
3966
3.06E−01


194
29
21
0.71
2666
1.12E−05


195
973
747
0.77
3551
3.58E−02


196
37
30
0.82
3754
1.16E−01


197
34
27
0.80
3802
1.47E−01


198
96
75
0.78
4054
4.26E−01


199
189
162
0.86
4041
4.06E−01


200
320
246
0.77
3387.5
1.16E−02


201
82
68
0.83
2928
2.04E−04


202
340
150
0.44
2000
9.51E−10


203
66
61
0.93
3645
6.34E−02


204
2277
1866
0.82
2575
3.69E−06


205
143
98
0.69
2268
5.85E−08


206
18
14
0.80
2580
3.93E−06


207
131
78
0.59
2100
4.67E−09


208
157
109
0.69
2020
1.31E−09


209
13
10
0.76
2322
1.27E−07


210
79
59
0.75
3766
1.23E−01


211
17
11
0.65
3823
1.63E−01


212
4
4
1.11
4157
5.96E−01


213
29
15
0.50
3610
5.16E−02


214
34
24
0.71
2142
8.95E−09


215
840
764
0.91
3724
9.86E−02


216
1658
1128
0.68
1599.5
8.37E−13


217
312
165
0.53
2197.5
2.07E−08


218
427
436
1.02
4261
7.95E−01


219
5503
4684
0.85
2760
3.34E−05


220
76
75
0.98
4157.5
5.97E−01


221
6973
6082
0.87
3001.5
4.27E−04


222
101
103
1.01
4305.5
8.85E−01


223
16763
13719
0.82
2697.5
1.63E−05


224
34
31
0.89
3802
1.47E−01


225
196
139
0.71
2644.5
8.67E−06


226
1680
1301
0.77
3080.5
9.05E−04


227
58
70
1.20
3788
1.37E−01


228
514
405
0.79
2743
2.76E−05


229
110
74
0.67
1706.5
6.08E−12


230
45
28
0.61
2362
2.22E−07


231
21
12
0.58
2002
9.82E−10


232
606232
486683
0.80
2616
6.13E−06


233
9908
9498
0.96
4063.5
4.40E−01


234
9154
8247
0.90
3866
1.99E−01


235
9287
8247
0.89
3721
9.71E−02


236
107973
121688
1.13
3653.5
6.66E−02


237
193265
185566
0.96
3809
1.52E−01


238
21999
25811
1.17
3900
2.32E−01


239
11940
10329
0.87
3543
3.40E−02


240
826948
739499
0.89
3571
4.06E−02


241
5662848
5062762
0.89
4049
4.18E−01


242
1114956
1054500
0.95
4135
5.57E−01


243
28381
23908
0.84
2800
5.23E−05


244
1972637
1731501
0.88
3773
1.27E−01


245
4259259
4687500
1.10
3791
1.39E−01


246
262959
328193
1.25
2990
3.81E−04


247
6736
6448
0.96
4044
4.11E−01


248
1247
873
0.70
2464
8.86E−07


249
1316413
1201639
0.91
4083
4.71E−01


250
78516
81625
1.04
3954.5
2.92E−01


251
6344
7497
1.18
3454
1.87E−02


252
372
362
0.97
4128
5.45E−01


253
197
142
0.72
2502
1.46E−06


254
666
570
0.86
3240
3.67E−03


255
455
317
0.70
2594
4.68E−06


256
1616
1595
0.99
4169
6.18E−01


257
1124
902
0.80
3496
2.50E−02


258
324
292
0.90
3772
1.27E−01


259
64
30
0.48
3553
3.62E−02


260
286
231
0.81
3186
2.33E−03


261
1318
1077
0.82
3308
6.35E−03


262
517
386
0.75
2942
2.36E−04


263
18709
19891
1.06
4223
7.20E−01


264
5392
3376
0.63
3790
1.39E−01


265
7857
7002
0.89
3735
1.05E−01


266
8557
8601
1.01
4228
7.29E−01


267
16
13
0.79
3544
3.42E−02


268
61
53
0.88
4055.5
4.28E−01


269
259
289
1.12
4361.5
1.00E+00


270
258
211
0.82
3731
1.02E−01


271
534
590
1.10
4135
5.57E−01


272
735
1129
1.54
3133
1.46E−03


273
2380
2913
1.22
3601
4.88E−02


274
1785
2610
1.46
3191
2.43E−03


275
4167
6222
1.49
3067
7.98E−04


276
140
156
1.12
3641
6.20E−02


277
665
825
1.24
3936
2.70E−01


278
397
530
1.34
3221
3.13E−03


279
1044
1179
1.13
4037
4.01E−01


280
959
980
1.02
4195
6.66E−01


281
178
240
1.35
3045
6.49E−04


282
6258
7786
1.24
3563
3.86E−02


283
509
625
1.23
3738
1.06E−01


284
6148
8768
1.43
2991
3.85E−04


285
786
1035
1.32
3511
2.76E−02


286
79
53
0.67
3169
2.01E−03


287
282
275
0.98
3835
1.73E−01


288
247
262
1.06
4316.5
9.07E−01


289
136
166
1.23
3539
3.31E−02


290
1359
1800
1.32
3053
7.00E−04


291
189
189
1.00
4141
5.68E−01


292
529
812
1.54
2709.5
1.87E−05


293
134
98
0.73
2937
2.24E−04


294
1993
1407
0.71
3168.5
2.00E−03


295
1027
707
0.69
3154
1.76E−03


296
4329
3333
0.77
3249
3.95E−03


297
6584
4673
0.71
3153
1.74E−03


298
5439
6702
1.23
4135.5
5.58E−01


299
5238
4194
0.80
3811.5
1.54E−01


300
8485
6784
0.80
3314.5
6.68E−03


301
2780
2333
0.84
3833
1.71E−01


302
5385
6398
1.19
4214
7.02E−01


303
1823
2017
1.11
4032.5
3.94E−01


304
1973
1986
1.01
3907.5
2.40E−01


305
952
581
0.61
2724
2.22E−05


306
714
526
0.74
3294
5.69E−03


307
3257
3062
0.94
3507
2.69E−02


308
3629
3879
1.07
4324
9.23E−01


309
7924
9235
1.17
4209.5
6.94E−01


310
398
288
0.72
3247
3.89E−03


311
28012
29731
1.06
4279.5
8.32E−01


312
494
406
0.82
3385
1.14E−02


313
23735
31195
1.31
4127.5
5.44E−01


314
3559
3197
0.90
3986
3.31E−01


315
1312
1415
1.08
4133
5.54E−01


316
4941
5824
1.18
3942
2.77E−01


317
2207
2558
1.16
3924.5
2.58E−01


318
2392
2780
1.16
4177
6.33E−01


319
218
234
1.07
4297.5
8.68E−01


320
10838
11250
1.04
4003.5
3.54E−01


321
8416
8594
1.02
4143.5
5.72E−01


322
8477
9857
1.16
3717
9.50E−02


323
38613
45076
1.17
4068
4.47E−01


324
82550
104525
1.27
3475
2.16E−02


325
3150
4077
1.29
3541
3.35E−02


326
1949
2246
1.15
3743
1.09E−01


327
3239
2856
0.88
3746
1.11E−01


328
5850
5042
0.86
3715
9.40E−02


329
1139
1039
0.91
3620
5.48E−02


330
7221
7221
1.00
4183
6.44E−01


331
37654
45293
1.20
3674
7.49E−02


332
7800
8015
1.03
4086
4.75E−01


333
1676
1686
1.01
4274
8.21E−01


334
232
197
0.85
3804
1.49E−01


335
1600
1269
0.79
3347
8.59E−03


336
6531
6756
1.03
4283
8.39E−01


337
689
648
0.94
3984
3.28E−01





alevels are expressed as pmol/mL plasma













TABLE 10







Initial summarya of univariate analysis of plasma lipids in control, stable CAD and unstable CAD cohorts.














Stable vs
Stable vs






unstable
unstable
control vs CAD
control vs


Lipid group
# of Species
p < 0.05
p < 0.01
p < 0.05
CAD p < 0.01















ceramide (CER)
7
2
1
4
3


monohexosylceramide (MHC)
7
0
0
6
5


dihexosylceramide (DHC)
7
1
1
5
4


trihexosylcermide (THC)
7
0
0
5
4


GM3 Ganglioside (GM3)
6
1
0
4
4


modified ceramides (modCer)
14
3
1
9
8


sphingomyelin (SM)
12
2
2
8
8


phosphatidylglycerol (PG)
4
0
0
1
0


bis(monoacylglycero)phosphate (BMP)
1
0
0
0
0


phosphatidylserine (PS)
7
0
0
7
6


phosphatidylethanolamine (PE)
18
1
0
4
0


phosphatidylinositol (PI)
17
11
7
15
15


lysophosphatidylcholine (LPC)
14
8
5
11
10


lysoplatelet activating factor (LPAF)
3
0
0
3
3


phosphatidylcholine (PC)
19
3
1
12
9


odd-chain phosphatidylcholine (oddPC)
15
3
0
8
8


alkylphosphatidylcholine (APC)
16
1
1
16
14


modified phosphatidylcholine (modPC)
57
11
7
37
35


free cholesterol (COH)
1
0
0
1
1


cholesterol esters (CE)
30
4
1
14
9


modified cholesterol esters (modCE)
4
0
0
0
0


diacylglycerol (DG)
27
8
4
15
10


triaclyglycerol (TG)
44
14
9
13
9


Total lipid species
337
73
40
198
165





atable shows the number of lipids in each class with p values below the indicated level













TABLE 11







Analysis of variancea of stable vs unstable cohort








ANOVA
Covariates
















Sum of

Mean



Partial




Squares
df
Square
F
Sig.
Variable
Correlation
Sig











Model 1 (traditional risk factors) R2 = 0.304















Regression
8.095
2
4.048
22.705
.000b
CRP
.532
.000


Residual
18.540
104
.178


smoker
.236
.015


Total
26.636
106







Model 2 (lipids) R2 = 0.353















Regression
12.388
4
3.097
18.803
.000†
modPC 752.6/5.58
−.196
.021


Residual
22.730
138
.165


GM3 18:0
−.391
.000


Total
35.119
142



DG 18:1 20:0
−.206
.015








SM 18:0
.449
.000







Model 3 (lipids + traditional risk factors) R2 = 0.473















Regression
12.604
6
2.101
14.972
.000†
CRP
.516
.000


Residual
14.031
100
.140


PI 34:0
−.280
.004


Total
26.636
106



DHC 18:1
.250
.011








modCer 703.6/5.87
.247
.012








SM 22:1
.327
.001








GM3 18:0
−.225
.023





alinear regression analysis was performed for ANOVA













TABLE 12







Analysis of variancea of control vs CAD cohort








ANOVA
Covariates
















Sum of

Mean



Partial




Squares
df
Square
F
Sig.
Variable
Correlation
Sig











Model 4 (traditional risk factors) R2 = 0.577















Regression
22.181
7
3.169
30.980
.000
hypertension
.492
.000


Residual
16.263
159
.102


CRP
.382
.000


Total
38.443
166



smoker
.313
.000








sex (0 = M)
−.302
.000








trigs
.260
.001








gluc
.163
.039








age
.162
.040







Model 5 (lipids) R2 = 0.809















Regression
35.114
25
1.405
32.700
.000
modPC 580.4/4.84
−.280
.000


Residual
7.646
178
.043


PS 40:6
−.439
.000


Total
42.760
203



modPC 752.6/5.58
−.505
.000








APC 32:1
−.333
.000








oddPC 37:3
.326
.000








GM3 24:1
.313
.000








oddPC 33:0
−.234
.001








APC 36:0
.218
.003








CE 24:3
−.310
.000








SM 20:1
.382
.000








SM 18:0
−.320
.000








LPC 20:0
−.311
.000








modCE 682.7/8.76
.351
.000








COH
−.240
.001








Cer 20:0
.218
.003








LPC 16:1
.336
.000








TG 16:1 16:1 16:1
−.285
.000








modPC 564.4/4.70
−.245
.001








modPC 720.6/4.52
−.212
.004








modPC 608.4/5.33
.162
.028








PE 38:3
−.217
.003








PE 38:1
.158
.032







Model 6 (lipids + traditional risk factors) R2 = 0.904















Regression
34.443
26
1.325
46.359
.000
modPC 580.4/4.84
−.713
.000


Residual
4.001
140
.029


hypertension
.638
.000


Total
38.443
166



PS 40:6
−.387
.000








GM3 22:0
.462
.000








PC 37:3
.616
.000








PC 33:0
−.219
.009








modPC 788.6/5.19
.409
.000








C24.3
−.372
.000








C24:4
.481
.000








modPC 666.4/2.99
.323
.000








PG 16:1 18:1
−.303
.000








diabetes
−.238
.005








gluc
.253
.002








modPC 678.4/4.37
−.282
.001








smoker
.234
.005








modCer 731.6/6.22
−.452
.000








SM 18:1
.429
.000








sex
−.401
.000








APC 36:5
−.376
.000








modPC 769.6/6.25
.428
.000








APC 36:3
−.449
.000








oddPC 35:4
−.365
.000








PG 18:1 18:1
−.367
.000








TG 18:1 18:1 18:2
.211
.012








modPC 881.7/6.05
−.326
.000








CE 17:0
−.239
.004








PI 38:5
.213
.011





alinear regression analysis was performed for ANOVA













TABLE 13







Ranked list of analytes based on recursive feature elimination of stable


CAD vs unstable CAD


Stable vs Unstable











Lipids and Traditional



Lipids Only
risk Factors













Asymp.

Asymp.




Sig.

Sig.


#
Analyte
(2-tailed)
Analyte
(2-tailed)














1
modPC 752.5/5.58
3.59E−06
CRP



2
modCer 731.6/6.22
6.78E−05
modPC 752.5/5.58
3.59E−06


3
DHC 18:1
6.59E−03
modCer 731.6/6.22
6.78E−05


4
APC 34:2
3.27E−03
DHC 18:1
6.59E−03


5
SM 18:0
8.04E−05
SM 18:0
8.04E−05


6
GM3 18:0
4.64E−02
APC 34:2
3.27E−03


7
LPC 16:1
1.52E−04
GM3 18:0
4.64E−02


8
DG 18:1 20:0
1.81E−04
DG 18:1 20:0
1.81E−04


9
Cer 18:1
1.62E−02
PI 36:1
1.70E−04


10
PI 36:1
1.70E−04
Cer 18:1
1.62E−02


11
PC 34:3
6.41E−04
LPC 16:1
1.52E−04


12
LPC 14:0
1.03E−05
PC 34:3
6.41E−04


13
PI 36:3
2.50E−04
PI 36:3
2.50E−04


14
modPC 745.5/6.35
7.35E−03
APC 36:0
7.31E−01


15
APC 36:0
7.31E−01
LPC 14:0
1.03E−05


16
PI 38:2
1.24E−03
modPC 745.5/6.35
7.35E−03


17
SM 18:1
2.25E−03
PI 38:2
1.24E−03


18
Cer 18:0
7.72E−03
SM 18:1
2.25E−03


19
PG 18:1 18:1
1.03E−01
modPC 622.4/4.54
9.84E−01


20
modCer 910.8/8.98
4.87E−02
modCer 703.6/5.87
8.08E−01


21
modPC 622.4/4.54
9.84E−01
LDL



22
modPC 736.5/5.38
9.46E−03
PG 18:1 18:1
1.03E−01


23
modPC 608.4/5.33
2.17E−03
modPC 736.5/5.38
9.46E−03


24
modCer 703.6/5.87
8.08E−01
modPC 608.4/5.33
2.17E−03


25
DHC 22:0
3.34E−01
modPC 743.5/5.91
2.73E−02


26
LPC 18:1
2.48E−04
THC 18:0
2.09E−01


27
THC 18:0
2.09E−01
PI 34:0
5.68E−03


28
modPC 743.5/5.91
2.73E−02
DHC 22:0
3.34E−01


29
modPC 694.4/6.20
5.77E−02
DG 16:0 20:0
2.41E−03


30
modPC 692.4/5.05
5.38E−02
total_cholesterol



31
TG 16:1 16:1 16:1
1.09E−03
TG 16:1 16:1 16:1
1.09E−03


32
PI 34:0
5.68E−03
smoker_cont



33
DG 16:0 20:0
2.41E−03
SM 22:0
1.20E−01


34
SM 22:0
1.20E−01
hist_of_CAD



35
modPC 690.4/6.00
1.25E−01
modPC 692.4/5.52
4.43E−05


36
LPC 18:2
2.16E−03
Cer 18:0
7.72E−03


37
modPC 678.4/5.51
1.21E−05
LPC 18:1
2.48E−04


38
modPC 692.4/5.52
4.43E−05
modPC 694.4/6.20
5.77E−02


39
modPC 878.6/5.98
2.33E−01
TG 14:0 16:1 18:1
1.09E−03


40
TG 14:0 16:1 18:1
1.09E−03
age



41
PE 32:0
2.18E−01
modPC 690.4/6.00
1.25E−01


42
PI 38:3
3.38E−02
PE 36:0
9.16E−01


43
TG 14:1 18:0 18:2
6.67E−03
modPC 692.4/5.05
5.38E−02


44
modPC 580.4/4.84
5.75E−03
PE 32:0
2.18E−01


45
PC 40:6
2.44E−01
SM 22:1
1.66E−01


46
modCer 886.8/9.06
1.48E−01
modPC 678.4/5.51
1.21E−05


47
modPC 818.6/6.10
1.34E−01
hypertension



48
THC 18:1
9.22E−01
LPC 18:2
2.16E−03


49
DHC 16:0
9.13E−02
sex



50
PC 32:0
6.50E−01
modCer 910.8/8.98
4.87E−02


51
PE 36:0
9.16E−01
DHC 16:0
9.13E−02


52
TG 14:0 16:1 18:2
1.12E−03
TG 14:0 16:1 18:2
1.12E−03


53
CE 14:0
1.46E−03
CE 14:0
1.46E−03


54
modPC 769.5/6.25
1.53E−01
PI 40:4
1.54E−02


55
MHC 20:0
1.34E−01
TG 14:1 18:0 18:2
6.67E−03


56
APC 36:4
1.46E−01
APC 36:5
2.77E−01


57
PG 16:0 18:1
2.88E−01
modPC 878.6/5.98
2.33E−01


58
modCer 875.7/9.23
3.49E−02
modPC 769.5/6.25
1.53E−01


59
APC 36:5
2.77E−01
modCer 798.7/7.29
4.18E−01


60
PI 36:4
5.64E−03
PC 40:6
2.44E−01


61
DG 18:1 20:3
8.34E−02
APC 36:4
1.46E−01


62
modCer 614.6/5.72
6.15E−02
PI 38:3
3.38E−02


63
TG 16:1 18:1 18:1
1.27E−01
modCer 875.7/9.23
3.49E−02


64
modPC 816.6/5.58
9.25E−01
PG 16:0 18:1
2.88E−01


65
PI 40:4
1.54E−02
modPC 580.4/4.84
5.75E−03


66
modPC 704.5/3.81
7.74E−01
TG 16:1 18:1 18:1
1.27E−01


67
modPC 692.4/6.10
6.80E−02
PI 40:6
1.43E−01


68
PI 40:6
1.43E−01
THC 18:1
9.22E−01


69
modPC 881.6/6.05
5.98E−02
modPC 818.6/6.10
1.34E−01


70
PS 36:2
4.61E−01
modPC 594.4/3.26
5.85E−01


71
modPC 566.4/5.10
1.99E−01
modCer 886.8/9.06
1.48E−01


72
SM 22:1
1.66E−01
PC 32:0
6.50E−01


73
modCer 798.7/7.29
4.18E−01
PI 36:4
5.64E−03


74
PS 38:5
4.99E−01
PI 32:0
6.15E−02


75
DHC 24:1
2.82E−01
modPC 881.6/6.05
5.98E−02


76
CE 15:0
2.84E−01
TG 17:0 18:1 18:1
3.97E−01


77
PC 30:2
1.53E−01
DG 18:1 20:3
8.34E−02


78
modPC 818.6/6.48
8.55E−01
PE 34:1
1.55E−01


79
LPC 20:5
1.21E−02
MHC 20:0
1.34E−01


80
PE 34:1
1.55E−01
modPC 704.5/3.81
7.74E−01


81
PE 38:2
4.68E−01
modPC 816.6/5.58
9.25E−01


82
oddPC 35:0
4.64E−02
CE 17:1
4.96E−02


83
oddPC 37:5
1.34E−01
PE 38:2
4.68E−01


84
oddPC 37:4
2.89E−01
LPC 20:3
2.47E−02


85
TG 14:1 18:1 18:1
1.81E−02
TG 14:1 18:1 18:1
1.81E−02


86
THC 24:0
3.56E−01
oddPC 37:4
2.89E−01


87
GM3 20:0
4.46E−01
HDL



88
PS 40:6
3.59E−01
oddPC 35:0
4.64E−02


89
CE 22:2
3.45E−01
modPC 818.6/6.48
8.55E−01


90
TG 14:0 18:2 18:2
4.17E−02
CE 15:0
2.84E−01


91
PI 32:0
6.15E−02
modPC 692.4/6.10
6.80E−02


92
DG 16:0 22:6
5.30E−01
TG 16:0 16:1 18:1
3.89E−02


93
TG 16:1 16:1 18:0
3.63E−03
oddPC 37:5
1.34E−01


94
PE 34:2
5.44E−01
PG 18:0 18:1
2.63E−01


95
DG 16:0 18:2
3.90E−01
modCer 614.6/5.72
6.15E−02


96
PI 38:5
3.88E−03
TG 14:0 18:2 18:2
4.17E−02


97
TG 17:0 18:1 18:1
3.97E−01
TG 16:1 16:1 18:0
3.63E−03


98
CE 16:2
1.77E−02
PS 38:4
3.79E−01


99
LPC 20:3
2.47E−02
oddPC 33:1
5.71E−02


100
CE 22:5
3.43E−01
THC 24:0
3.56E−01


101
PE 36:5
4.31E−02
PC 36:5
4.27E−02


102
modPC 594.4/3.26
5.85E−01
DG 16:0 18:2
3.90E−01


103
modPC 706.5/3.79
7.41E−01
PI 38:6
4.05E−02


104
CE 17:1
4.96E−02
PS 36:2
4.61E−01


105
PI 38:6
4.05E−02
PE 34:2
5.44E−01


106
PC 36:2
3.25E−02
modPC 608.4/3.84
5.85E−01


107
modPC 828.6/6.03
9.12E−01
CE 16:2
1.77E−02


108
PG 18:0 18:1
2.63E−01
DHC 24:1
2.82E−01


109
DHC 20:0
5.94E−01
PC 36:2
3.25E−02


110
CE 24:5
7.31E−01
PC 40:5
7.11E−01


111
modCer 632.6/9.22
9.74E−01
TG 14:0 18:0 18:1
2.47E−03


112
oddPC 35:3
1.10E−02
modPC 592.4/5.10
4.13E−02


113
LPC 20:0
4.38E−02
PG 16:1 18:1
6.56E−01


114
CE 22:3
5.33E−01
PE 36:5
4.31E−02


115
modPC 510.3/4.00
9.00E−01
PS 38:5
4.99E−01


116
DG 18:1 20:4
8.42E−01
LPC 20:1
6.72E−01


117
APC 36:2
3.28E−01
modPC 828.6/6.03
9.12E−01


118
PC 36:4
7.40E−01
PI 38:5
3.88E−03


119
TG 17:0 18:1 14:0
8.41E−02
gluc



120
CE 22:6
2.95E−01
PI 36:0
1.58E−01


121
modPC 538.3/4.10
3.18E−02
DG 16:0 22:6
5.30E−01


122
APC 34:0
5.32E−01
modPC 650.4/3.94
4.40E−01


123
modCer 766.6/7.17
3.36E−01
CE 22:5
3.43E−01


124
modPC 801.6/6.70
2.61E−01
TG 18:0 18:0 18:0
2.81E−02


125
PC 40:5
7.11E−01
COH
3.23E−01


126
modPC 843.6/7.10
9.24E−01
PC 38:6
5.15E−01


127
modCE 682.7/8.76
1.10E−01
BMI



128
PC 38:6
5.15E−01
APC 36:3
1.20E−01


129
PC 32:1
2.78E−01
oddPC 35:3
1.10E−02


130
TG 16:1 18:1 18:2
4.22E−01
oddPC 31:0
2.75E−02


131
PG 16:1 18:1
6.56E−01
APC 32:1
5.20E−01


132
modCer 921.8/9.05
8.05E−01
diabetes



133
BMP 18:1 18:1
3.18E−01
modPC 590.4/4.80
7.35E−01


134
modPC 608.4/3.84
5.85E−01
TG 17:0 18:1 14:0
8.41E−02


135
PC 38:4
9.71E−01
CE 20:1
8.64E−01


136
THC 20:0
6.53E−01
THC 22:0
4.78E−01


137
PC 34:2
4.58E−01
TG 17:0 18:1 16:1
2.71E−01


138
modPC 650.4/3.94
4.40E−01
CE 20:2
4.58E−01


139
TG 18:0 18:0 18:0
2.81E−02
PE 40:7
8.07E−01


140
modPC 703.5/4.09
4.39E−01
MHC 18:1
3.37E−01


141
PI 34:1
6.27E−03
PC 30:2
1.53E−01


142
PS 38:4
3.79E−01
CE 24:2
5.17E−01


143
modPC 720.5/4.52
9.00E−01
modPC 843.6/7.10
9.24E−01


144
modPC 773.6/6.47
3.36E−01
modPC 566.4/5.10
1.99E−01


145
PE 38:1
5.32E−01
modPC 678.4/4.37
7.35E−01


146
DG 16:0 16:0
6.99E−01
APC 36:2
3.28E−01


147
DHC 24:0
8.55E−01
GM3 16:0
7.71E−01


148
TG 17:0 16:0 18:0
1.31E−01
GM3 20:0
4.46E−01


149
modPC 552.4/3.90
5.30E−02
CE 24:3
9.64E−01


150
THC 22:0
4.78E−01
DG 18:2 18:2
1.01E−01


151
oddPC 31:0
2.75E−02
THC 20:0
6.53E−01


152
GM3 24:1
3.71E−01
CE 24:4
7.63E−01


153
DG 18:0 18:0
6.48E−01
modPC 720.5/4.52
9.00E−01


154
CE 20:1
8.64E−01
modPC 706.5/3.79
7.41E−01


155
modPC 678.4/4.37
7.35E−01
modPC 773.6/6.47
3.36E−01


156
PE 36:3
3.68E−01
GM3 24:1
3.71E−01


157
DHC 18:0
5.33E−01
PC 36:4
7.40E−01


158
TG 16:0 16:1 18:1
3.89E−02
MHC 16:0
5.71E−01


159
oddPC 33:1
5.71E−02
APC 34:1
8.95E−01


160
modPC 590.4/4.80
7.35E−01
modPC 510.3/4.00
9.00E−01


161
modPC 592.4/5.10
4.13E−02
modPC 650.4/3.24
9.71E−01


162
modPC 610.4/2.03
4.95E−01
trigs



163
APC 36:3
1.20E−01
CE 24:5
7.31E−01


164
TG 14:0 18:0 18:1
2.47E−03
APC 38:3
2.46E−01


165
MHC 16:0
5.71E−01
modPC 552.4/3.90
5.30E−02


166
APC 34:1
8.95E−01
TG 18:1 18:1 20:4
2.98E−01


167
DG 14:0 16:0
2.33E−02
TG 14:1 16:1 18:0
3.68E−03


168
DG 18:1 18:2
3.38E−01
PE 38:6
2.70E−01


169
DG 14:0 18:2
4.42E−02
TG 18:1 18:1 18:2
1.92E−01


170
APC 36:1
9.53E−01
modPC 610.4/2.03
4.95E−01


171
DG 18:0 18:1
3.34E−01
modPC 538.3/4.10
3.18E−02


172
DG 16:0 22:5
8.90E−01
TG 18:1 14:0 16:0
1.99E−03


173
TG 16:1 16:1 18:1
4.51E−02
PC 38:4
9.71E−01


174
DG 16:1 18:1
1.09E−01
PS 38:3
7.29E−01


175
DG 18:0 18:2
8.39E−01
CE 24:6
9.29E−01


176
DG 14:0 18:1
1.12E−02
TG 16:0 18:1 18:1
9.46E−01


177
DG 16:0 18:1
9.74E−01
modCE 588.5/7.94
8.39E−01


178
modPC 666.4/2.99
9.58E−01
DG 16:0 20:4
6.53E−01


179
DG 16:0 20:3
3.85E−02
PS 36:1
7.08E−01


180
DG 16:0 20:4
6.53E−01
CE 22:4
6.39E−01


181
DG 18:1 18:3
3.03E−01
modCE 790.8/6.57
6.60E−01


182
CE 20:4
5.68E−01
CE 22:0
4.39E−01


183
CE 18:3
1.89E−02
DG 16:0 18:0
1.14E−01


184
TG 17:0 18:1 16:1
2.71E−01
CE 22:1
7.63E−01


185
Cer 22:0
8.16E−01
APC 32:0
5.77E−01


186
CE 20:5
3.88E−01
PS 40:5
6.08E−01


187
CE 18:0
7.08E−01
CE 22:2
3.45E−01


188
CE 18:2
9.25E−01
DG 14:1 16:0
8.10E−03


189
COH
3.23E−01
APC 36:1
9.53E−01


190
TG 18:1 18:1 22:6
4.70E−01
CE 24:0
2.63E−01


191
TG 17:0 18:2 16:0
2.23E−01
PS 40:6
3.59E−01


192
CE 16:0
9.32E−01
DG 18:1 18:3
3.03E−01


193
CE 16:1
5.30E−02
CE 18:2
9.25E−01


194
CE 24:4
7.63E−01
TG 17:0 16:0 16:1
7.84E−02


195
modCE 790.8/6.57
6.60E−01
modPC 690.4/4:90
1.94E−01


196
CE 24:1
3.70E−01
CE 22:3
5.33E−01


197
CE 24:2
5.17E−01
modCE 558.5/7.74
5.22E−01


198
CE 24:3
9.64E−01
DG 14:0 16:0
2.33E−02


199
modCE 588.5/7.94
8.39E−01
DG 14:0 18:2
4.42E−02


200
Cer 16:0
5.66E−01
DG 16:0 16:0
6.99E−01


201
LPAF 16:0
1.99E−01
TG 17:0 18:1 16:0
2.36E−01


202
CE 22:4
6.39E−01
TG 16:0 16:0 18:1
3.92E−01


203
CE 20:2
4.58E−01
TG 18:1 18:1 18:1
9.93E−01


204
modCer 651.6/7.56
4.61E−01
TG 18:1 18:1 22:6
4.70E−01


205
CE 24:6
9.29E−01
modPC 690.4/4.11
3.81E−01


206
CE 22:0
4.39E−01
Cer 20:0
4.01E−01


207
TG 18:0 18:0 18:1
3.36E−01
TG 14:1 16:0 18:1
3.16E−01


208
TG 16:0 16:0 18:1
3.92E−01
CE 16:1
5.30E−02


209
Cer 24:1
6.78E−01
PE 36:3
3.68E−01


210
TG 16:0 16:0 18:2
9.77E−01
TG 14:0 16:0 18:2
5.43E−03


211
TG 18:0 18:1 18:1
4.80E−01
oddPC 37:6
6.50E−01


212
TG 15:0 18:1 18:1
6.37E−01
TG 16:0 16:0 18:2
9.77E−01


213
TG 16:0 16:0 18:0
1.13E−01
TG 16:0 16:0 18:0
1.13E−01


214
TG 14:1 16:1 18:0
3.68E−03
TG 18:0 18:2 18:2
9.04E−01


215
TG 14:1 16:0 18:1
3.16E−01
TG 18:1 18:2 18:2
9.51E−01


216
DG 18:0 20:4
8.61E−01
DG 18:0 20:4
8.61E−01


217
TG 17:0 16:0 16:1
7.84E−02
TG 18:0 18:0 18:1
3.36E−01


218
TG 15:0 18:1 16:0
5.94E−01
TG 16:0 16:0 16:0
6.62E−02


219
TG 16:0 16:0 16:0
6.62E−02
TG 18:0 18:1 18:1
4.80E−01


220
modCE 558.5/7.74
5.22E−01
DG 16:1 18:1
1.09E−01


221
CE 17:0
6.22E−01
oddPC 31:1
1.95E−01


222
TG 18:1 18:1 18:1
9.93E−01
DG 18:1 18:1
9.38E−01


223
TG 18:1 18:1 18:2
1.92E−01
LPC 20:2
8.60E−03


224
TG 18:2 18:2 20:4
7.76E−01
CE 20:3
6.51E−01


225
oddPC 37:3
5.99E−01
DG 14:0 18:1
1.12E−02


226
CE 22:1
7.63E−01
DG 16:0 20:3
3.85E−02


227
TG 16:0 18:1 18:2
1.94E−01
TG 16:0 18:0 18:1
9.77E−01


228
PE 38:5
9.03E−01
TG 15:0 18:1 18:1
6.37E−01


229
PI 32:1
3.30E−02
DG 18:1 18:2
3.38E−01


230
TG 18:0 18:2 18:2
9.04E−01
APC 38:5
7.71E−01


231
TG 18:2 18:2 18:2
9.77E−01
CE 18:1
5.49E−01


232
TG 16:0 18:0 18:1
9.77E−01
CE 17:0
6.22E−01


233
oddPC 31:1
1.95E−01
CE 18:3
1.89E−02


234
PC 44:12
8.13E−01
DG 18:1 20:4
8.42E−01


235
SM 20:1
9.32E−01
CE 18:0
7.08E−01


236
CE 24:0
2.63E−01
CE 20:5
3.88E−01


237
oddPC 33:2
9.48E−01
DG 16:0 22:5
8.90E−01


238
modPC 536.3/3.50
4.33E−02
GM3 22:0
8.74E−01


239
PC 38:5
9.11E−01
DG 14:0 14:0
2.75E−03


240
PC 34:1
4.41E−01
PC 34:1
4.41E−01


241
TG 16:0 18:1 18:1
9.46E−01
CE 22:6
2.95E−01


242
PC 32:2
2.91E−01
PC 32:1
2.78E−01


243
PC 36:3
7.95E−02
CE 16:0
9.32E−01


244
Cer 24:0
5.51E−01
PC 36:3
7.95E−02


245
PC 34:0
8.94E−02
DG 18:0 18:0
6.48E−01


246
modPC 690.4/4.90
1.94E−01
PC 32:2
2.91E−01


247
APC 32:0
5.77E−01
oddPC 35:4
8.37E−01


248
APC 32:1
5.20E−01
modCer 651.6/7.56
4.61E−01


249
modPC 772.5/5.37
8.77E−01
modCer 632.6/9.22
9.74E−01


250
DG 14:1 16:0
8.10E−03
modCer 883.8/7.75
7.11E−01


251
LPAF 18:0
7.62E−01
modCer 769.6/8.01
4.71E−01


252
oddPC 37:2
6.59E−01
modCer 766.6/7.17
3.36E−01


253
oddPC 35:2
8.93E−01
modPC 666.4/2.99
9.58E−01


254
CE 20:3
6.51E−01
oddPC 37:2
6.59E−01


255
oddPC 33:0
5.37E−01
oddPC 37:3
5.99E−01


256
PS 38:3
7.29E−01
LPAF 18:0
7.62E−01


257
oddPC 37:6
6.50E−01
modPC 564.4/4.70
2.04E−01


258
oddPC 35:1
5.99E−01
APC 34:0
5.32E−01


259
LPC 18:0
4.22E−01
modCE 682.7/8.76
1.10E−01


260
SM 15:0
2.13E−01
CE 24:1
3.70E−01


261
SM 16:1
2.54E−01
oddPC 33:2
9.48E−01


262
modCer 769.6/8.01
4.71E−01
DG 18:0 18:1
3.34E−01


263
THC 16:0
3.90E−01
SM 15:0
2.13E−01


264
TG 18:1 14:0 16:0
1.99E−03
APC 38:4
8.74E−01


265
MHC 24:0
2.85E−01
oddPC 35:2
8.93E−01


266
PC 36:5
4.27E−02
LPC 20:5
1.21E−02


267
Cer 20:0
4.01E−01
DHC 20:0
5.94E−01


268
TG 18:1 18:1 20:4
2.98E−01
MHC 24:1
6.11E−01


269
GM3 16:0
7.71E−01
MHC 18:0
6.61E−01


270
MHC 22:0
6.53E−01
Cer 24:0
5.51E−01


271
MHC 18:0
6.61E−01
DHC 18:0
5.33E−01


272
modCer 576.5/7.68
3.36E−01
Cer 24:1
6.78E−01


273
SM 24:0
6.11E−01
MHC 24:0
2.85E−01


274
SM 24:2
4.68E−01
Cer 22:0
8.16E−01


275
SM 16:0
2.27E−01
TG 18:2 18:2 18:2
9.77E−01


276
oddPC 35:4
8.37E−01
TG 16:1 16:1 18:1
4.51E−02


277
modPC 633.4/4.51
9.17E−01
PC 34:2
4.58E−01


278
modCer 883.8/7.75
7.11E−01
TG 17:0 16:0 18:0
1.31E−01


279
GM3 22:0
8.74E−01
MHC 22:0
6.53E−01


280
THC 24:1
8.12E−01
modPC 506.3/3.50
3.35E−01


281
MHC 18:1
3.37E−01
modCer 576.5/7.68
3.36E−01


282
SM 14:0
8.48E−01
SM 16:0
2.27E−01


283
GM3 24:0
8.58E−01
SM 16:1
2.54E−01


284
TG 14:0 16:0 18:2
5.43E−03
SM 14:0
8.48E−01


285
DG 14:0 14:0
2.75E−03
SM 24:0
6.11E−01


286
modPC 508.3/3.30
8.18E−01
SM 24:1
7.49E−01


287
PE 36:2
3.68E−01
SM 20:1
9.32E−01


288
APC 38:3
2.46E−01
GM3 24:0
8.58E−01


289
PE38:4
3.99E−01
DG 18:0 18:2
8.39E−01


290
PE 38:6
2.70E−01
THC 16:0
3.90E−01


291
PE 36:1
5.77E−01
DHC 24:0
8.55E−01


292
DG 18:0 16:1
5.30E−02
PC 34:0
8.94E−02


293
PC 40:7
9.16E−01
THC 24:1
8.12E−01


294
modPC 788.6/5.19
3.59E−01
modPC 536.3/3.50
4.33E−02


295
modPC 764.5/6.52
2.97E−01
PC 38:5
9.11E−01


296
SM 24:1
7.49E−01
BMP 18:1 18:1
3.18E−01


297
modPC 866.6/7.24
3.19E−01
APC 38:2
9.98E−01


298
LPC 20:2
8.60E−03
modPC 866.6/7.24
3.19E−01


299
PI 38:4
1.15E−01
PE 36:4
7.05E−01


300
PI 36:0
1.58E−01
LPC 20:4
6.94E−01


301
PI 36:2
9.61E−01
PE 32:1
3.30E−01


302
PS 40:5
6.08E−01
PC 44:12
8.13E−01


303
PS 36:1
7.08E−01
TG 16:0 18:2 18:2
4.96E−01


304
PI 40:5
2.13E−01
PC 40:7
9.16E−01


305
MHC 24:1
6.11E−01
SM 24:2
4.68E−01


306
PE 40:7
8.07E−01
TG 17:0 18:2 16:0
2.23E−01


307
DG 18:1 18:1
9.38E−01
modPC 788.6/5.19
3.59E−01


308
PE 38:3
6.28E−01
modPC 772.5/5.37
8.77E−01


309
DG 16:0 18:0
1.14E−01
PI 40:5
2.13E−01


310
TG 16:0 18:2 18:2
4.96E−01
PI 34:1
6.27E−03


311
PE 40:6
3.81E−01
PE 40:6
3.81E−01


312
LPAF 18:1
9.35E−01
PE 38:1
5.32E−01


313
LPC 22:6
9.87E−01
Cer 16:0
5.66E−01


314
LPC 20:1
6.72E−01
PI 38:4
1.15E−01


315
modPC 512.3/1.70
8.59E−01
PI 36:2
9.61E−01


316
PE 36:4
7.05E−01
TG 16:1 18:1 18:2
4.22E−01


317
modPC 506.3/3.50
3.35E−01
LPC 18:0
4.22E−01


318
LPC 20:4
6.94E−01
PE 36:1
5.77E−01


319
APC 38:4
8.74E−01
PE 36:2
3.68E−01


320
APC 38:5
7.71E−01
PE 38:3
6.28E−01


321
APC 38:6
9.90E−02
PE38:4
3.99E−01


322
LPC 15:0
2.48E−01
PE 38:5
9.03E−01


323
APC 38:2
9.98E−01
modPC 508.3/3.30
8.18E−01


324
PE 32:1
3.30E−01
LPC 20:0
4.38E−02


325
modPC 678.4/4.94
8.90E−01
CE 20:4
5.68E−01


326
LPC 16:0
4.34E−01
DG 18:0 16:1
5.30E−02


327
DG 18:2 18:2
1.01E−01
modPC 801.6/6.70
2.61E−01


328
TG 17:0 18:1 16:0
2.36E−01
LPAF 18:1
9.35E−01


329
modPC 564.4/4.70
2.04E−01
LPAF 16:0
1.99E−01


330
modPC 690.4/4.11
3.81E−01
oddPC 33:0
5.37E−01


331
modPC 664.4/4.22
8.71E−01
PI 32:1
3.30E−02


332
modPC 636.4/3.37
7.68E−01
TG 16:0 18:1 18:2
1.94E−01


333
CE 18:1
5.49E−01
APC 38:6
9.90E−02


334
TG 18:1 18:2 18:2
9.51E−01
LPC 15:0
2.48E−01


335
modPC 650.4/4.44
7.57E−01
modPC 764.5/6.52
2.97E−01


336
modPC 650.4/3.24
9.71E−01
LPC 16:0
4.34E−01


337
modPC 645.4/4.49
5.99E−01
modPC 703.5/4.09
4.39E−01


338


modPC 678.4/4.94
8.90E−01


339


modPC 664.4/4.22
8.71E−01


340


modPC 650.4/4.44
7.57E−01


341


modCer 921.8/9.05
8.05E−01


342


TG 18:2 18:2 20:4
7.76E−01


343


DG 16:0 18:1
9.74E−01


344


oddPC 35:1
5.99E−01


345


TG 15:0 18:1 16:0
5.94E−01


346


LPC 22:6
9.87E−01


347


modPC 512.3/1.70
8.59E−01


348


modPC 645.4/4.49
5.99E−01


349


modPC 636.4/3.37
7.68E−01


350


modPC 633.4/4.51
9.17E−01
















TABLE 14







Ranked list of analytes based on recursive feature


elimination of control vs CAD groups


Control vs CAD











Lipids and Traditional



Lipids Only
risk Factors













Asymp.

Asymp.




Sig.

Sig.


#
Analyte
(2-tailed)
Analyte
(2-tailed)














1
modPC 580.4/4.84
8.09E−20
modPC 580.4/4.84
8.09E−20


2
modPC 608.4/5.33
1.03E−16
hypertension



3
modPC 552.4/3.90
7.59E−17
modPC 608.4/5.33
1.03E−16


4
PS 40:6
1.33E−08
PS 40:6
1.33E−08


5
LPC 20:0
3.11E−16
modPC 552.4/3.90
7.59E−17


6
PS 40:5
1.93E−07
LPC 20:0
3.11E−16


7
PI 34:0
6.32E−10
PS 40:5
1.93E−07


8
Cer 20:0
1.30E−03
PI 34:0
6.32E−10


9
modPC 745.5/6.35
8.37E−13
Cer 20:0
1.30E−03


10
APC 34:2
2.05E−13
modPC 745.5/6.35
8.37E−13


11
modPC 678.4/5.51
9.51E−10
modPC 678.4/5.51
9.51E−10


12
Cer 18:0
1.31E−08
Cer 18:0
1.31E−08


13
PI 36:0
6.85E−06
APC 34:2
2.05E−13


14
modPC 752.5/5.58
2.07E−08
smoker_cont



15
modPC 878.6/5.98
2.22E−07
modPC 752.5/5.58
2.07E−08


16
LPC 20:3
3.85E−01
modPC 881.6/6.05
9.82E−10


17
modPC 692.4/5.52
4.67E−09
PI 36:0
6.85E−06


18
modPC 690.4/6.00
5.85E−08
LPC 20:3
3.85E−01


19
APC 38:6
2.12E−08
modPC 878.6/5.98
2.22E−07


20
oddPC 37:3
3.50E−01
modPC 692.4/5.52
4.67E−09


21
LPC 20:4
2.89E−01
HDL



22
CE 20:3
3.81E−04
modPC 690.4/6.00
5.85E−08


23
modPC 692.4/6.10
1.31E−09
APC 38:6
2.12E−08


24
modPC 881.6/6.05
9.82E−10
modPC 866.6/7.24
6.08E−12


25
modPC 736.5/5.38
8.95E−09
trigs



26
modCer 766.6/7.17
1.29E−10
LPC 20:4
2.89E−01


27
modCer 576.5/7.68
7.03E−03
age



28
modPC 866.6/7.24
6.08E−12
gluc



29
modPC 633.4/4.51
1.12E−07
modPC 736.5/5.38
8.95E−09


30
modPC 694.4/6.20
1.27E−07
modPC 692.4/6.10
1.31E−09


31
modPC 566.4/5.10
4.47E−10
modCer 576.5/7.68
7.03E−03


32
CE 20:1
8.86E−07
modCer 766.6/7.17
1.29E−10


33
LPC 22:6
1.40E−01
CE 22:4
1.87E−02


34
PE 32:0
6.27E−02
DG 18:1 20:0
2.24E−04


35
DG 18:1 20:0
2.24E−04
oddPC 37:3
3.50E−01


36
PS 38:5
4.80E−06
PI 32:0
1.46E−07


37
PI 32:0
1.46E−07
modPC 694.4/6.20
1.27E−07


38
CE 22:4
1.87E−02
CE 20:3
3.81E−04


39
modPC 720.5/4.52
5.16E−02
PS 38:5
4.80E−06


40
CE 22:2
1.46E−06
modPC 720.5/4.52
5.16E−02


41
APC 36:3
6.57E−08
CE 24:3
3.62E−02


42
CE 24:3
3.62E−02
PE 32:0
6.27E−02


43
modPC 706.5/3.79
5.96E−01
hist_of_CAD



44
Cer 18:1
6.00E−02
APC 36:3
6.57E−08


45
PI 36:1
1.46E−08
DG 16:0 20:0
2.01E−03


46
DG 18:1 20:4
7.00E−04
modPC 566.4/5.10
4.47E−10


47
Cer 16:0
1.83E−01
CE 20:1
8.86E−07


48
modPC 692.4/5.05
3.93E−06
LPC 14:0
4.46E−09


49
PC 38:4
1.84E−01
modPC 633.4/4.51
1.12E−07


50
CE 22:0
4.68E−06
modPC 706.5/3.79
5.96E−01


51
CE 17:1
2.32E−01
LPC 22:6
1.40E−01


52
PE 36:0
1.62E−02
modPC 692.4/5.05
3.93E−06


53
THC 24:0
3.72E−08
modCer 798.7/7.29
1.63E−08


54
GM3 24:1
2.32E−01
TG 14:0 18:2 18:2
2.22E−05


55
DG 16:0 20:0
2.01E−03
CE 22:2
1.46E−06


56
SM 22:0
1.84E−07
PI 36:1
1.46E−08


57
modCer 614.6/5.72
1.43E−05
CRP



58
GM3 18:0
1.27E−07
PC 38:4
1.84E−01


59
PC 34:2
6.10E−05
Cer 18:1
6.00E−02


60
modPC 678.4/4.94
2.04E−04
PG 16:1 18:1
2.62E−02


61
modPC 538.3/4.10
1.54E−11
THC 24:0
3.72E−08


62
APC 36:2
2.90E−08
CE 22:0
4.68E−06


63
SM 24:0
3.64E−09
PC 34:2
6.10E−05


64
modCer 798.7/7.29
1.63E−08
sex



65
modPC 704.5/3.81
1.63E−01
APC 32:1
8.37E−05


66
PG 16:1 18:1
2.62E−02
PI 40:6
2.36E−04


67
APC 32:1
8.37E−05
modPC 678.4/4.94
2.04E−04


68
TG 14:0 18:2 18:2
2.22E−05
SM 14:0
3.96E−06


69
DG 18:1 18:3
4.01E−01
SM 24:2
7.53E−01


70
SM 14:0
3.96E−06
PE 36:0
1.62E−02


71
LPC 14:0
4.46E−09
modPC 538.3/4.10
1.54E−11


72
PI 40:6
2.36E−04
modPC 818.6/6.48
8.67E−06


73
PI 36:2
2.12E−08
CE 17:1
2.32E−01


74
SM 24:2
7.53E−01
total_cholesterol



75
PI 38:6
1.65E−06
BMI



76
APC 38:2
3.63E−06
modPC 512.3/1.70
1.84E−04


77
Cer 24:0
8.83E−05
SM 24:0
3.64E−09


78
MHC 22:0
3.29E−10
DG 18:1 20:4
7.00E−04


79
TG 16:0 16:0 16:0
1.71E−01
GM3 18:0
1.27E−07


80
modPC 828.6/6.03
1.37E−01
TG 14:0 16:0 18:2
3.95E−03


81
modPC 818.6/6.48
8.67E−06
LDL



82
COH
6.13E−06
oddPC 37:6
2.97E−04


83
PS 38:4
1.03E−04
modPC 816.6/5.58
1.47E−01


84
modPC 816.6/5.58
1.47E−01
oddPC 37:4
9.35E−01


85
modPC 590.4/4.80
2.70E−07
PI 36:2
2.12E−08


86
DG 18:1 18:2
3.86E−02
COH
6.13E−06


87
modPC 512.3/1.70
1.84E−04
modPC 818.6/6.48
9.05E−04


88
modCer 632.6/9.22
1.65E−03
modPC 590.4/4.80
2.70E−07


89
APC 36:5
1.09E−05
SM 22:0
1.84E−07


90
DG 16:0 20:4
3.13E−03
GM3 20:0
8.90E−02


91
Cer 24:1
3.58E−02
PI 38:6
1.65E−06


92
TG 17:0 18:1 14:0
2.40E−01
PC 34:0
6.12E−08


93
LPC 18:2
5.85E−08
APC 38:2
3.63E−06


94
oddPC 37:4
9.35E−01
modCer 614.6/5.72
1.43E−05


95
LPC 20:2
4.26E−03
PE 36:2
3.06E−02


96
PC 34:0
6.12E−08
APC 36:2
2.90E−08


97
modPC 769.5/6.25
3.34E−05
LPC 18:2
5.85E−08


98
PE 36:3
1.09E−02
modPC 828.6/6.03
1.37E−01


99
TG 14:0 16:0 18:2
3.95E−03
TG 18:1 14:0 16:0
6.68E−03


100
PG 18:1 18:1
1.61E−01
modCer 632.6/9.22
1.65E−03


101
SM 16:0
4.18E−07
PS 38:4
1.03E−04


102
modPC 690.4/4.90
3.69E−06
APC 36:5
1.09E−05


103
TG 14:0 18:0 18:1
1.14E−02
PC 36:2
1.93E−07


104
DG 14:0 14:0
3.42E−02
GM3 22:0
3.69E−03


105
DHC 24:1
5.91E−05
CE 18:1
5.57E−01


106
TG 16:0 16:0 18:0
3.31E−01
MHC 16:0
1.72E−05


107
TG 16:1 16:1 18:0
3.89E−03
CE 18:3
4.06E−02


108
GM3 20:0
8.90E−02
PI 40:5
3.70E−03


109
DHC 18:0
1.48E−01
TG 18:1 18:1 18:2
6.44E−01


110
DG 16:0 18:0
2.70E−01
CE 20:2
4.11E−01


111
DG 16:0 22:6
9.07E−01
PI 38:4
4.81E−03


112
TG 18:1 18:1 20:4
8.39E−01
SM 16:1
2.89E−04


113
PI 40:4
7.28E−02
CE 18:0
5.23E−05


114
PI 40:5
3.70E−03
CE 20:5
1.27E−01


115
APC 36:0
4.44E−04
PE 40:6
4.98E−01


116
TG 14:0 16:1 18:2
2.00E−03
PI 38:2
6.25E−04


117
SM 16:1
2.89E−04
PI 36:4
2.11E−04


118
PC 36:5
6.15E−03
PS 38:3
5.49E−04


119
GM3 16:0
8.99E−03
CE 15:0
1.99E−01


120
PI 38:4
4.81E−03
CE 14:0
4.40E−01


121
MHC 18:1
1.77E−01
PE 36:1
7.00E−02


122
DG 14:0 18:1
5.57E−01
TG 16:0 16:1 18:1
8.32E−01


123
PE 40:7
5.89E−01
PI 38:3
3.08E−03


124
PI 34:1
6.81E−05
PS 36:2
4.37E−04


125
DG 14:0 16:0
1.00E+00
TG 16:1 16:1 18:1
9.23E−01


126
PI 36:4
2.11E−04
CE 17:0
3.40E−02


127
DHC 16:0
1.78E−03
CE 16:2
9.71E−02


128
PI 32:1
3.81E−01
PS 36:1
1.86E−02


129
PE 40:6
4.98E−01
CE 16:1
6.66E−02


130
PS 36:1
1.86E−02
TG 14:1 16:1 18:0
1.54E−01


131
modPC 650.4/4.44
1.16E−01
PE 38:1
1.80E−01


132
DG 16:0 18:1
7.98E−04
modCE 558.5/7.74
7.20E−01


133
DG 16:0 18:2
4.88E−02
CE 16:0
1.52E−01


134
TG 16:0 18:1 18:1
2.16E−02
PI 40:4
7.28E−02


135
DG 18:0 18:2
1.06E−01
CE 24:0
2.36E−04


136
DG 14:0 18:2
1.02E−01
PE 38:3
2.73E−01


137
DG 18:1 18:1
3.85E−04
modCE 682.7/8.76
1.05E−01


138
CE 16:0
1.52E−01
TG 18:2 18:2 20:4
8.59E−03


139
TG 16:1 18:1 18:2
5.72E−01
modCE 790.8/6.57
7.29E−01


140
CE 14:0
4.40E−01
PE38:4
3.79E−01


141
CE 16:2
9.71E−02
PE 38:5
8.47E−01


142
CE 18:2
4.18E−01
modCE 588.5/7.94
1.39E−01


143
TG 16:0 18:0 18:1
3.35E−02
THC 16:0
3.96E−04


144
CE 17:0
3.40E−02
CE 22:1
3.67E−03


145
CE 18:3
4.06E−02
CE 24:6
6.18E−01


146
TG 18:1 18:1 18:1
7.49E−02
PI 38:5
2.13E−07


147
DG 16:0 22:5
3.31E−02
CE 22:5
2.92E−01


148
TG 18:0 18:2 18:2
5.48E−02
CE 22:3
5.45E−01


149
TG 18:1 18:1 18:2
6.44E−01
DG 16:0 18:1
7.98E−04


150
PI 38:3
3.08E−03
PI 34:1
6.81E−05


151
THC 20:0
6.00E−02
TG 16:0 18:1 18:2
4.47E−01


152
TG 18:0 18:0 18:0
1.49E−01
CE 24:4
1.27E−01


153
TG 16:0 18:2 18:2
3.54E−01
PI 36:3
1.40E−09


154
CE 18:0
5.23E−05
TG 17:0 16:0 16:1
3.94E−01


155
CE 24:1
6.35E−03
THC 18:0
1.31E−02


156
modPC 703.5/4.09
1.23E−01
TG 17:0 18:1 16:1
2.77E−01


157
PI 36:3
1.40E−09
TG 17:0 18:2 16:0
2.58E−01


158
CE 24:2
2.33E−03
DG 18:1 20:3
1.87E−05


159
TG 17:0 18:1 16:1
2.77E−01
TG 15:0 18:1 18:1
5.54E−01


160
modCE 790.8/6.57
7.29E−01
TG 16:0 16:0 18:0
3.31E−01


161
modCE 558.5/7.74
7.20E−01
TG 14:0 16:1 18:2
2.00E−03


162
modCE 588.5/7.94
1.39E−01
TG 16:1 16:1 16:1
1.76E−03


163
CE 22:6
4.71E−01
DG 16:0 22:6
9.07E−01


164
CE 22:3
5.45E−01
PC 32:0
6.40E−03


165
CE 20:4
1.39E−01
modPC 690.4/4.11
6.34E−02


166
CE 20:2
4.11E−01
TG 17:0 18:1 16:0
6.33E−01


167
CE 24:6
6.18E−01
Cer 24:0
8.83E−05


168
CE 24:5
2.50E−02
DG 16:0 22:5
3.31E−02


169
CE 22:5
2.92E−01
TG 14:1 18:0 18:2
5.69E−03


170
TG 18:1 14:0 16:0
6.68E−03
TG 15:0 18:1 16:0
7.02E−01


171
DG 16:0 20:3
6.49E−04
TG 16:0 16:0 16:0
1.71E−01


172
TG 14:1 16:0 18:1
5.58E−01
TG 16:0 16:0 18:2
6.94E−01


173
TG 14:1 16:1 18:0
1.54E−01
CE 24:1
6.35E−03


174
TG 16:1 16:1 16:1
1.76E−03
TG 17:0 18:1 14:0
2.40E−01


175
PI 38:2
6.25E−04
TG 18:1 18:1 22:6
3.28E−01


176
LPAF 16:0
1.37E−05
TG 16:1 16:1 18:0
3.89E−03


177
TG 14:1 18:0 18:2
5.69E−03
TG 14:1 16:0 18:1
5.58E−01


178
TG 15:0 18:1 16:0
7.02E−01
TG 14:0 16:1 18:1
1.74E−03


179
TG 17:0 16:0 16:1
3.94E−01
TG 16:0 16:0 18:1
5.44E−01


180
DG 18:0 18:0
1.73E−01
TG 18:1 18:1 20:4
8.39E−01


181
modPC 843.6/7.10
2.76E−05
PE 40:7
5.89E−01


182
modCer 883.8/7.75
1.30E−01
TG 14:0 18:0 18:1
1.14E−02


183
DG 18:0 18:1
2.76E−02
modPC 743.5/5.91
9.86E−02


184
modPC 818.6/6.48
9.05E−04
DG 16:0 18:2
4.88E−02


185
DG 18:2 18:2
6.66E−01
DG 16:0 16:0
1.46E−03


186
TG 18:0 18:1 18:1
4.75E−01
CE 18:2
4.18E−01


187
DG 18:0 20:4
5.68E−01
DG 16:1 18:1
2.43E−03


188
TG 14:1 18:1 18:1
2.69E−02
modCer 875.7/9.23
5.21E−01


189
TG 16:1 18:1 18:1
9.50E−02
PC 30:2
8.33E−03


190
PC 30:2
8.33E−03
DG 14:0.16:0
1.00E+00


191
TG 17:0 16:0 18:0
8.68E−01
TG 18:0 18:0 18:0
1.49E−01


192
TG 18:2 18:2 20:4
8.59E−03
DG 14:1 16:0
4.28E−01


193
TG 17:0 18:1 18:1
1.09E−01
PG 18:1 18:1
1.61E−01


194
TG 18:2 18:2 18:2
1.11E−01
TG 18:0 18:1 18:1
4.75E−01


195
DG 16:1 18:1
2.43E−03
TG 18:0 18:0 18:1
8.21E−01


196
CE 18:1
5.57E−01
TG 16:0 18:2 18:2
3.54E−01


197
TG 18:0 18:0 18:1
8.21E−01
TG 16:1 18:1 18:1
9.50E−02


198
TG 16:0 16:0 18:1
5.44E−01
TG 16:0 18:1 18:1
2.16E−02


199
TG 16:0 16:0 18:2
6.94E−01
DG 18:1 18:2
3.86E−02


200
TG 16:0 16:1 18:1
8.32E−01
TG 16:1 18:1 18:2
5.72E−01


201
TG 17:0 18:2 16:0
2.58E−01
APC 38:4
1.20E−02


202
TG 17:0 18:1 16:0
6.33E−01
DG 18:1 18:1
3.85E−04


203
TG 15:0 18:1 18:1
5.54E−01
DG 16:0 20:3
6.49E−04


204
modCE 682.7/8.76
1.05E−01
TG 17:0 18:1 18:1
1.09E−01


205
PC 34:1
4.14E−01
DG 16:0 18:0
2.70E−01


206
DG 18:0 16:1
6.20E−02
DG 18:0 16:1
6.20E−02


207
PC 32:0
6.40E−03
DG 18:2 18:2
6.66E−01


208
oddPC 37:5
4.77E−03
TG 16:0 18:0 18:1
3.35E−02


209
TG 16:0 18:1 18:2
4.47E−01
TG 14:1 18:1 18:1
2.69E−02


210
PC 38:5
4.96E−02
modPC 594.4/3.26
6.48E−01


211
PG 18:0 18:1
6.13E−01
modCer 886.8/9.06
2.15E−03


212
PC 36:2
1.93E−07
PC 32:2
2.26E−04


213
modCer 886.8/9.06
2.15E−03
PC 32:1
2.82E−01


214
modCer 910.8/8.98
2.41E−01
APC 32:0
1.91E−02


215
modCer 875.7/9.23
5.21E−01
DG 14:0 18:1
5.57E−01


216
PE 36:4
5.06E−01
modCer 921.8/9.05
6.07E−01


217
PC 32:2
2.26E−04
oddPC 31:0
2.02E−03


218
PC 32:1
2.82E−01
oddPC 37:2
1.71E−04


219
modCer 921.8/9.05
6.07E−01
PC 34:3
5.91E−06


220
PC 38:6
1.01E−02
SM 22:1
1.54E−05


221
PC 40:7
2.57E−02
DHC 18:1
2.94E−02


222
oddPC 35:1
8.32E−01
modCer 651.6/7.56
4.98E−05


223
PE 38:5
8.47E−01
modPC 608.4/3.84
9.87E−01


224
oddPC 35:3
1.03E−03
SM 24:1
5.29E−05


225
oddPC 35:2
2.74E−03
TG 18:0 18:2 18:2
5.48E−02


226
CE 24:0
2.36E−04
modCer 883.8/7.75
1.30E−01


227
PE 36:2
3.06E−02
modCer 703.6/5.87
5.81E−01


228
PC 34:3
5.91E−06
modCer 769.6/8.01
6.38E−05


229
DG 14:1 16:0
4.28E−01
oddPC 35:4
1.05E−01


230
PC 44:12
8.30E−03
oddPC 35:3
1.03E−03


231
oddPC 31:1
9.66E−02
oddPC 33:2
2.46E−04


232
DHC 22:0
8.28E−05
oddPC 33:1
9.87E−01


233
PC 40:5
6.65E−01
oddPC 35:0
3.74E−04


234
oddPC 33:1
9.87E−01
oddPC 35:1
8.32E−01


235
oddPC 33:0
5.09E−02
oddPC 35:2
2.74E−03


236
PE 38:2
3.93E−01
PE 38:6
6.74E−01


237
modPC 772.5/5.37
5.97E−01
PC 36:5
6.15E−03


238
modCer 703.6/5.87
5.81E−01
modPC 801.6/6.70
1.63E−05


239
THC 16:0
3.96E−04
PC 38:5
4.96E−02


240
DHC 20:0
2.85E−01
PC 36:4
9.22E−02


241
PC 40:6
7.35E−01
TG 17:0 16:0 18:0
8.68E−01


242
TG 18:1 18:1 22:6
3.28E−01
PC 44:12
8.30E−03


243
THC 22:0
1.65E−03
APC 38:3
3.73E−03


244
THC 18:1
1.52E−01
PC 40:6
7.35E−01


245
THC 18:0
1.31E−02
PC 40:5
6.65E−01


246
SM 24:1
5.29E−05
MHC 18:1
1.77E−01


247
MHC 18:0
2.44E−02
MHC 24:0
2.30E−09


248
PE 38:1
1.80E−01
DHC 16:0
1.78E−03


249
MHC 16:0
1.72E−05
MHC 20:0
2.35E−06


250
DHC 18:1
2.94E−02
MHC 24:1
1.94E−04


251
PS 38:3
5.49E−04
DHC 20:0
2.85E−01


252
MHC 20:0
2.35E−06
GM3 16:0
8.99E−03


253
MHC 24:0
2.30E−09
CE 20:4
1.39E−01


254
THC 24:1
5.40E−03
DHC 18:0
1.48E−01


255
DG 16:0 16:0
1.46E−03
DG 16:0 20:4
3.13E−03


256
LPC 16:1
2.41E−03
PC 40:7
2.57E−02


257
CE 22:1
3.67E−03
CE 24:2
2.33E−03


258
PI 38:5
2.13E−07
diabetes



259
SM 18:0
1.82E−01
DG 14:0 18:2
1.02E−01


260
modCer 769.6/8.01
6.38E−05
LPC 18:1
1.48E−04


261
DHC 24:0
7.02E−06
APC 36:1
1.25E−03


262
modCer 731.6/6.22
2.45E−02
Cer 16:0
1.83E−01


263
GM3 24:0
1.10E−05
Cer 22:0
6.49E−02


264
SM 15:0
1.50E−05
GM3 24:0
1.10E−05


265
GM3 22:0
3.69E−03
TG 18:1 18:1 18:1
7.49E−02


266
BMP 18:1 18:1
6.66E−01
TG 18:1 18:2 18:2
9.40E−02


267
APC 34:1
8.82E−03
GM3 24:1
2.32E−01


268
SM 22:1
1.54E−05
modPC 650.4/3.94
1.47E−01


269
modPC 510.3/4.00
3.18E−06
SM 20:1
6.46E−02


270
SM 18:1
3.83E−01
SM 16:0
4.18E−07


271
APC 32:0
1.91E−02
SM 18:1
3.83E−01


272
modPC 773.6/6.47
4.27E−04
DHC 22:0
8.28E−05


273
modPC 788.6/5.19
8.85E−01
modPC 506.3/3.50
1.09E−06


274
modPC 764.5/6.52
7.95E−01
THC 18:1
1.52E−01


275
oddPC 33:2
2.46E−04
LPC 15:0
6.06E−06


276
DG 18:1 20:3
1.87E−05
DHC 24:0
7.02E−06


277
TG 14:0 16:1 18:1
1.74E−03
THC 24:1
5.40E−03


278
APC 38:3
3.73E−03
PC 34:1
4.14E−01


279
modPC 650.4/3.94
1.47E−01
THC 20:0
6.00E−02


280
modPC 666.4/2.99
4.06E−01
THC 22:0
1.65E−03


281
modPC 536.3/3.50
9.52E−05
modPC 690.4/4.90
3.69E−06


282
modPC 650.4/3.24
3.58E−02
DG 18:1 18:3
4.01E−01


283
modPC 664.4/4.22
4.26E−01
modPC 536.3/3.50
9.52E−05


284
CE 20:5
1.27E−01
CE 22:6
4.71E−01


285
PC 36:4
9.22E−02
modPC 703.5/4.09
1.23E−01


286
oddPC 35:4
1.05E−01
modPC 764.5/6.52
7.95E−01


287
modPC 690.4/4.11
6.34E−02
PG 16:0 18:1
5.63E−01


288
LPC 18:0
8.07E−07
PI 32:1
3.81E−01


289
PE 36:1
7.00E−02
DHC 24:1
5.91E−05


290
PE 38:6
6.74E−01
modPC 610.4/2.03
4.62E−01


291
TG 18:1 18:2 18:2
9.40E−02
modPC 645.4/4.49
1.12E−05


292
oddPC 37:2
1.71E−04
SM 18:0
1.82E−01


293
PE 38:3
2.73E−01
PE 36:5
3.27E−02


294
oddPC 31:0
2.02E−03
modPC 636.4/3.37
3.06E−01


295
oddPC 37:6
2.97E−04
PE 34:2
2.85E−01


296
PE38:4
3.79E−01
modPC 664.4/4.22
4.26E−01


297
PG 16:0 18:1
5.63E−01
modPC 650.4/4.44
1.16E−01


298
PC 36:3
1.35E−01
TG 18:2 18:2 18:2
1.11E−01


299
oddPC 35:0
3.74E−04
PE 32:1
6.92E−02


300
modPC 608.4/3.84
9.87E−01
modPC 769.5/6.25
3.34E−05


301
PE 34:2
2.85E−01
modPC 666.4/2.99
4.06E−01


302
PE 36:5
3.27E−02
PG 18:0 18:1
6.13E−01


303
PE 32:1
6.92E−02
modPC 622.4/4.54
6.84E−02


304
TG 16:1 16:1 18:1
9.23E−01
PE 36:4
5.06E−01


305
LPC 16:0
4.68E−06
modPC 678.4/4.37
1.16E−02


306
LPC 18:1
1.48E−04
PE 34:1
1.98E−01


307
LPC 15:0
6.06E−06
modPC 772.5/5.37
5.97E−01


308
modCer 651.6/7.56
4.98E−05
PC 38:6
1.01E−02


309
modPC 743.5/5.91
9.86E−02
PE 38:2
3.93E−01


310
LPC 20:1
2.39E−05
modPC 773.6/6.47
4.27E−04


311
LPC 20:5
1.26E−02
modPC 788.6/5.19
8.85E−01


312
CE 15:0
1.99E−01
modPC 704.5/3.81
1.63E−01


313
modPC 678.4/4.37
1.16E−02
BMP 18:1 18:1
6.66E−01


314
CE 24:4
1.27E−01
SM 15:0
1.50E−05


315
SM 20:1
6.46E−02
modCer 731.6/6.22
2.45E−02


316
APC 34:0
1.20E−03
APC 36:0
4.44E−04


317
APC 38:4
1.20E−02
oddPC 31:1
9.66E−02


318
modPC 801.6/6.70
1.63E−05
oddPC 33:0
5.09E−02


319
APC 36:1
1.25E−03
APC 38:5
7.35E−05


320
APC 38:5
7.35E−05
DG 18:0 18:1
2.76E−02


321
MHC 24:1
1.94E−04
LPC 16:0
4.68E−06


322
modPC 594.4/3.26
6.48E−01
LPAF 18:0
3.66E−05


323
modPC 508.3/3.30
8.28E−05
DG 14:0 14:0
3.42E−02


324
Cer 22:0
6.49E−02
LPC 16:1
2.41E−03


325
modPC 592.4/5.10
5.49E−06
oddPC 37:5
4.77E−03


326
modPC 636.4/3.37
3.06E−01
modCer 910.8/8.98
2.41E−01


327
modPC 645.4/4.49
1.12E−05
APC 34:1
8.82E−03


328
modPC 610.4/2.03
4.62E−01
modPC 843.6/7.10
2.76E−05


329
CE 16:1
6.66E−02
DG 18:0 18:0
1.73E−01


330
LPAF 18:0
3.66E−05
APC 36:4
4.05E−05


331
modPC 506.3/3.50
1.09E−06
Cer 24:1
3.58E−02


332
PS 36:2
4.37E−04
APC 34:0
1.20E−03


333
LPAF 18:1
2.60E−03
MHC 18:0
2.44E−02


334
modPC 564.4/4.70
8.81E−09
DG 18:0 18:2
1.06E−01


335
modPC 622.4/4.54
6.84E−02
MHC 22:0
3.29E−10


336
PE 34:1
1.98E−01
modPC 508.3/3.30
8.28E−05


337
APC 36:4
4.05E−05
modPC 510.3/4.00
3.18E−06


338


PE 36:3
1.09E−02


339


CE 24:5
2.50E−02


340


modPC 564.4/4.70
8.81E−09


341


modPC 592.4/5.10
5.49E−06


342


DG 18:0 20:4
5.68E−01


343


modPC 650.4/3.24
3.58E−02


344


LPC 20:2
4.26E−03


345


LPC 18:0
8.07E−07


346


LPC 20:5
1.26E−02


347


LPAF 16:0
1.37E−05


348


LPAF 18:1
2.60E−03


349


LPC 20:1
2.39E−05


350


PC 36:3
1.35E−01
















TABLE 15







Final conditions for precursor ion scan and MRM acquisition methods for lipid identification and quantification

















No. of

(pmol/








Lipid class
species
Internal standard
15 □L)
Parent ion
MRM type
DP
EP
CE
CXP



















ceramide (Cer)
7
Cer17:0
100
[M + H]+
PISa, 264.3 m/z
50
10
35
12


monohexosylceramide (MHC)
7
MHC 16:0 d3
50
[M + H]+
PIS, 264.3 m/z
77
10
50
12


dihexosylceramide (DHC)
7
DHC 16:0 d3
50
[M + H]+
PIS, 264.3 m/z
100
10
65
12


trihexosylcermide (THC)
7
THC 17:0
50
[M + H]+
PIS, 264.3 m/z
130
10
73
12


GM3 ganglioside (GM3)
6
THC 17:0
50
[M + H]+
PIS, 264.3 m/z
155
10
105
16


modified ceramide (modCer)
13
acCer 17:0 18:1
100
[M + H]+
PIS, 264.3 m/z
70
10
50
16


sphingomyelin (SM)
12
SM 12:0
200
[M + H]+
PIS, 184.1 m/z
65
10
35
12


phosphatidylglycerol (PG)
4
PG 17:0 17:0
100
[M+ NH4]+
NLb, 189 Da
60
10
25
12


bis(monoacylglycerol)phosphate (BMP)
1
BMP 14:0/14:0
100
[M+ NH4]+
PIS, 339.3 m/z
65
10
35
12


phosphatidylserine (PS)
7
PS 17:0 17:0
100
[M + H]+
NL, 185 Da
86
10
29
12


phosphatidylethanolamine (PE)
18
PE 17:0 17:0
100
[M + H]+
NL, 141 Da
80
10
31
12


phosphatidylinositol (PI)
17
PE 17:0 17:0
100
[M+ NH4]+
PIS, 184.1 m/z
51
10
43
14


lysophosphatidylcholine (LPC)
16
LPC 13:0
100
[M + H]+
PIS, 184.1 m/z
90
10
38
12


lysoplatelet activating factor (LPAF)
7
LPC 13:0
100
[M + H]+
PIS, 285.2 m/z
90
10
42
5


phosphatidylcholine (PC)
22
PC 13:0 13:0
100
[M + H]+
PIS, 184.1 m/z
100
10
45
11


odd chain phosphatidylcholine (oddPC)
16
PC 13:0 13:0
100
[M + H]+
PIS, 184.1 m/z
100
10
45
11


alkylphosphatidylcholine (APC)
18
PC 13:0 13:0
100
[M + H]+
PIS, 184.1 m/z
100
10
45
11


modified phosphatidylcholine (modPC)
38
PC 13:0 13:0
100
[M + H]+
PIS, 184.1 m/z
100
10
45
11


free cholesterol (COH)
1
COH d7
1000
[M+ NH4]+
PIS, 369.3 m/z
55
10
17
12


cholesterol ester (CE)
30
CE 18:0 d6
1000
[M+ NH4]+
PIS, 369.3 m/z
30
10
20
12


modified cholesterol ester (modCE)
4
CE 18:0 d6
1000
[M+ NH4]+
PIS, 369.3 m/z
55
10
20
12


diacylglycerol (DG)
27
DAG 15:0 15:0
200
[M+ NH4]+
NL, fatty acid
55
10
30
22


triaclyglycerol (TG)
44
TAG 17:0 17:0 17:0
100
[M+ NH4]+
NL, fatty acid
95
10
30
12





aNL, neutral loss scan;


bPIS, precursor ion scan;


cPC 13:0 13:0 was used as internal standard for species with m/z <700;


aDP, declustering potential;


bEP, entrance potential;


cCE, collision energy;


dCXP, exit potential.













TABLE 16







Final summarya of univariate analysis of plasma


lipids in control, stable CAD and unstable CAD groups










#of species
% differenceb














control vs
stable vs

stable vs


Lipid class
total
CAD p < 0.01a
unstable p < 0.01a
control vs CAD
unstable















ceramide (CER)
7
2

−6.3
0.6


monohexosylceramide (MHC)
7
4

−24.9
−4.6


dihexosylceramide (DHC)
7
2
1
−12.8
8.1


trihexosylcermide (THC)
7
2

−13.6
2.0


GM3 Ganglioside (GM3)
6
1

−9.3
−3.2


modified ceramides (modCer)
13
5
1
−9.4
2.1


sphingomyelin (SM)
12
4
1
−9.3
2.9


phosphatidylglycerol (PG)
4


−7.0
−11.7


bis(monoacylglycero)phosphate (BMP)
1


2.6
6.4


phosphatidylserine (PS)
7
6

−27.4
23.9


phosphatidylethanolamine (PE)
18


−2.3
5.5


phosphatidylinositol (PI)
17
7
9
−20.4
−13.8


lysophosphatidylcholine (LPC)
16
10
8
−14.5
−10.7


lysoplatelet activating factor (LPAF)
7
2

−12.1
1.5


phosphatidylcholine (PC)
22
9
3
−7.2
−3.5


odd-chain phosphatidylcholine (oddPC)
16
7

−8.5
−2.5


alkylphosphatidylcholine (APC)
17
9
2
−16.0
−4.9


modified phosphatidylcholine (modPC)
39
15

−12.4
2.7


free cholesterol (COH)
1


−16.7
−3.9


cholesterol esters (CE)
30
4
1
−0.6
−2.0


modified cholesterol esters (modCE)
4


6.6
0.4


diacylglycerol (DG)
27
5
2
29.1
−2.8


triaclyglycerol (TG)
44
1
2
2.1
−7.3


Total lipid species
329
95
30





atable shows the number of lipids in each class with p < 0.01


b% difference between mean values for each lipid class, bold signifies p < 0.01 (Mann Whitney U test)
















TABLE 17





Model
features1
C-statistic2
% accuracy2















A. Logistic Regression Models of Stable CAD vs Unstable CAD










Lipids
4.4
72.9 (72.1-73.6)
67.0 (66.3-67.6)


Risk Factors
1.4
65.4 (65.0-65.8)
68.5 (68.1-68.8)


Lipids and Risk
4.8
78.8 (78.1-79.4)
71.0 (70.3-71.6)


Factors










B. Logistic Regression Models of Control vs CAD










Lipids
5.7
94.6 (94.4-94.8)
87.3 (87.1-87.6)


Risk Factors
4.2
95.6 (95.4-95.8)
90.4 (90.1-90.7)


Lipids and Risk
5.5
98.2 (98.1-98.3)
92.4 (92.1-92.6)


Factors





1mean number of features in the model.


2mean value and 95% confidence intervals.













TABLE 18







Ranked Lipids in the Stable CAD vs Unstable CAD Logistic Model1












features
% occurrence2
odds ratio3
95% CI















modCer 731.6
61.0
1.77
1.75-1.79



GM3 18:0
59.7
0.64
0.63-0.65



PC34:5
59.3
0.61
0.60-0.61



DHC 18:1
36.7
1.52
1.51-1.54



APC 34:2
28.7
0.66
0.65-0.66



SM 18:0
18.0
1.70
1.65-1.74



Cer 18:1
15.7
1.47
1.45-1.49



PI 36:1
14.0
0.63
0.61-0.64



APC 36:0
13.7
1.42
1.40-1.43



DG 18:1 20:0
13.3
0.65
0.63-0.66



LPC 14:0
11.0
0.65
0.63-0.66



LPC 16:1
10.0
0.62
0.60-0.63



PC 24:0
7.3
1.46
1.41-1.50



Cer 18:0
5.7
1.47
1.42-1.53



PI 36:3
5.3
0.64
0.61-0.66



PI 38:2
4.7
0.64
0.61-0.67





1lipids only.


2indicates the frequency of occurrence within the model.


3indicates the risk associated with a change of 1 standard deviation.













TABLE 19







Ranked Risk Factors in the Stable CAD vs


Unstable CAD Logistic Models1












features
% occurrence2
odds ratio3
95% CI















hsCRP
100.0
1.71
1.69-1.72



diabetes
16.3
0.70
0.69-0.71



smoker
13.0
1.43
1.41-1.45



HDL
6.3
0.68
0.66-0.70



SBP
4.7
0.72
0.72-0.73



BMI
1.0
0.66
0.54-0.84



cholesterol
0.7
0.72
0.70-0.74



age
0.3
0.71




Hist of CAD
0.3
0.72




sex
0.3
1.36




TRIGs
0.3
1.48





1risk factors only.


2indicates the frequency of occurrence within the model.


3indicates the risk associated with a change of 1 standard deviation.













TABLE 20







Ranked Features in the Stable CAD vs Unstable CAD Logistic Model1












features
% occurrence2
odds ratio3
95% CI















hsCRP
99.0
1.79
1.77-1.81



PC 34:5
72.0
0.59
0.59-0.60



DHC 18:1
49.7
1.53
1.52-1.55



Cer 18:1
42.7
1.51
1.49-1.52



modCer 731.6
37.7
1.70
1.67-1.72



GM3 18:0
31.7
0.63
0.62-0.64



LPC 16:1
20.7
0.60
0.59-0.62



DG 18:1/20:0
17.0
0.64
0.63-0.65



LPC 14:0
11.0
0.62
0.60-0.64



LPC 18:1
10.3
0.65
0.63-0.66



smoker
10.3
1.46
1.44-1.48



modPC.622.4/4.0
6.3
1.47
1.44-1.51



LPC 18:2
5.7
0.65
0.64-0.66



APC 34:2
5.7
0.67
0.66-0.68



LPC 24:0
4.7
0.66
0.64-0.67



PI 36:1
4.0
0.63
0.61-0.66





1lipids and risk factors combined.


2indicates the frequency of occurrence within the model.


3indicates the risk associated with a change of 1 standard deviation.













TABLE 21







Ranked Lipids in the Control vs CAD Logistic Model1












features
% occurrence2
odds ratio3
95% CI















LPC 22:0
100.0
0.40
0.40-0.40



PS 40:6
96.7
0.56
0.56-0.56



PI 34:0
42.0
0.61
0.60-0.61



Cer 20:0
39.3
1.61
1.59-1.63



Cer 18:0
39.0
1.72
1.70-1.74



APC 34:2
28.0
0.58
0.57-0.59



PC 34:5
22.7
0.59
0.58-0.60



LPC 20:3
16.7
1.50
1.48-1.51



PC 28:0
15.3
0.63
0.61-0.64



modPC 692.4/5.8
15.3
0.62
0.60-0.63



APC 30:0
14.7
0.63
0.61-0.64



modPC 736.5/5.7
14.3
0.61
0.59-0.62



LPC 20:4
14.0
1.51
1.49-1.53



APC 38:6
13.3
0.62
0.60-0.63



modPC 720.5.4.5
11.3
0.69
0.68-0.70



PI 36:0
11.0
0.64
0.63-0.66





1lipids only.


2indicates the frequency of occurrence within the model.


3indicates the risk associated with a change of 1 standard deviation.













TABLE 22







Ranked Risk Factors in the Control vs CAD Logistic Model1












features
% occurrence2
odds ratio3
95% CI















hsCRP
100.0
3.02
3.01-3.04



age
99.0
1.82
1.81-1.84



TRIGs
91.0
1.71
1.70-1.72



SBP
82.0
0.65
0.65-0.66



HDL
22.0
1.58
1.56-1.60



sex
17.0
0.70
0.69-0.70



Hist of CAD
8.7
1.44
1.42-1.45



BMI
1.0
0.67
0.65-0.68



cholesterol
0.0





1risk factors only.


2indicates the frequency of occurrence within the model.


3indicates the risk associated with a change of 1 standard deviation.













TABLE 23







Ranked Features in the Control vs CAD Logistic Model1












features
% occurrence2
odds ratio3
95% CI















hsCRP
100.0
2.35
2.33-2.36



LPC 22.0
99.7
0.47
0.47-0.47



age
97.0
1.76
1.74-1.77



PS 40:6
94.7
0.60
0.59-0.60



PC 34:5
37.7
0.63
0.62-0.63



SBP
18.7
0.65
0.65-0.66



modPC 879.6/6.1
13.0
0.63
0.62-0.64



APC 30:0
10.7
0.63
0.62-0.64



APC 38:6
10.7
0.62
0.61-0.64



Cer 18:0
10.3
1.61
1.59-1.63



modPC 877.6/6.0
8.7
0.66
0.65-0.68



modPC 736.5/5.7
8.3
0.61
0.60-0.62



HDL
7.3
1.57
1.54-1.60



LPC 20:3
7.3
1.52
1.49-1.54



PC 28:0
7.0
0.63
0.62-0.64



Cer 20:0
4.0
1.52
1.47-1.58





1lipids and risk factors combined.


2indicates the frequency of occurrence within the model.


3indicates the risk associated with a change of 1 standard deviation.













TABLE 24







Ranked Features in the Stable CAD vs Unstable CAD Recursive


Feature Elimination Models1









% occurrence3



# features in model













Feature
% change2
1
2
4
8
16
















hsCRP
243
38
82
97
100
100


PC 34:5
−11
40
61
76
87
95


modCer 731.6
20
3
13
53
83
96


DHC 18:1
24
1
4
26
67
86


GM3 18:0
−11
0
2
19
62
88


LPC 16:1
−23
6
11
31
49
60


Cer 18:1
4
0
3
18
47
67


APC 34:2
−19
0
0
4
41
72


DG 18:1 20:0
−40
3
7
23
37
53


SM 18:0
16
1
2
9
26
56


smoker
101
0
0
3
16
49


APC 36:0
13
0
0
0
6
35


PC 24:0
16
0
0
0
3
29


PI 36:1
−24
1
1
3
11
24


PC 34:3
−20
1
1
1
6
23


LPC 14:0
−26
4
5
6
10
19





1lipids and risk factors combined.


2% difference of mean unstable CAD value relative to mean stable CAD value.


3indicates the frequency of occurrence within the models of each size as indicated.













TABLE 25







Ranked Features in the Control vs CAD


Recursive Feature Elimination Models1









% occurrence3



# features in model













Feature
% difference2
1
2
4
8
16
















LPC 22:0
−48
55
100
100
100
100


hsCRP
260
45
99
100
100
100


PS 40:6
−54
0
1
80
99
100


age
19
0
0
28
91
100


LPC 24:0
−37
0
0
34
73
91


PS 40:5
−49
0
0
2
62
96


LPC 20:0
−42
0
0
5
18
66


PI 34:0
−43
0
0
3
14
53


Cer 20:0
17
0
0
0
17
42


HDL
−18
0
0
0
15
40


Systolic BP
11
0
0
0
9
38


modPC 877.6/6.0
8
0
0
4
18
33


PC 34:5
19
0
0
9
21
30


LPC 20:3
19
0
0
0
8
34


APC 38:6
−23
0
0
3
14
28


CE 22:4
−15
0
0
0
4
30





1lipids and risk factors combined.


2% difference of mean CAD value relative to mean control value.


3indicates the frequency of occurrence within the models of each size as indicated.













TABLE 26







Lipid Species Affected by Statin Use












% difference

% difference
% difference



with

Control
stable CAD vs


Lipid species
statin use
p value1
vs CAD2
unstable CAD2














Cer 18:1
−4.6
4.13E−02
2.9
4.2


DHC 18:1
−14.7
3.59E−02
−11.3
24.1


GM3 16:0
−14.2
3.15E−03
−7.2
1.1


PC 36:5
18.1
4.42E−02
−19.2
−10.1


PC 36:4
20.7
1.33E−02
6.6
0.5


PC 38:6
9.6
1.90E−02
−11.2
2.6


PC 38:5
15.1
9.18E−03
−8.9
−2.0


PC 38:4
21.4
1.04E−02
4.3
−0.9


PC 40:6
15.4
2.89E−02
−6.1
5.4


PC 40:5
16.8
9.99E−03
−5.3
−1.8


PC 37:5
23.0
4.27E−02
−16.6
−11.9


APC 32:0
−11.7
3.22E−02
−7.2
1.0


APC 34:1
−14.5
3.71E−02
−10.0
−2.5


APC 36:2
−18.6
3.59E−02
−27.1
−8.1


LPC 20:5
35.0
3.22E−02
−14.7
−18.1


PI 36:2
−27.1
1.86E−03
−27.9
−10.5


PI 38:4
17.3
4.42E−02
−13.0
−9.8


PS 38:4
51.5
4.27E−02
−30.6
23.7


DG 16:0 20:0
46.0
4.74E−02
−45.2
−36.0


DG 18:1 20:3
76.2
8.08E−03
64.8
−25.7


DG 18:1 20:0
54.1
3.99E−02
−41.6
−39.9


C22:3
−18.8
2.94E−02
−1.6
0.3


C22:2
−39.1
4.99E−03
−27.5
4.2


C22:1
−22.4
1.63E−02
−20.0
−0.6


C24:5
−34.7
4.61E−04
−7.3
20.0


C24:4
−27.5
5.96E−03
−3.4
2.3


C24:2
−29.6
6.51E−03
−14.7
−3.0


C24:1
−19.9
3.34E−02
−14.5
1.5





1p value calculated from Mann Whitney U test.


2bold numbers indicate significant differences (p < 0.01, from logistic regression adjusted for age and sex).













TABLE 27







Medication of stable and unstable CAD cohorts











Medication
Stable %
Unstable %
Chi Square
p














clopidogrel1
18
27
1.625
0.202


aspirin1
95
94
0.103
0.748


statin2
54
88
19.991
0.000


beta blocker3
59
65
0.612
0.434


ACE inhibitor3
43
56
2.328
0.127


angiotensin-II blocker3
23
6
1.076
0.300


oral/sublingual nitrate3
31
27
0.269
0.604


Ca channel blocker3
26
19
1.212
0.271


heparin infusion4
0
21
14.544
0.000


low molecular
0
11
7.236
0.007


weight heparin4






tirofiban1
0
6
3.903
0.048


frusemide3
11
9
0.314
0.575


sulfonylurea5
15
14
0.040
0.842


metformin5
23
11
3.593
0.058





1antiplatelet,


2lipid lowering,


3antihypertensive,


4anticoagulant,


5anti-diabetic.






BIBLIOGRAPHY


    (AIHW) AIoHaW. Health system expenditure, on disease and injury in Australia, 2000-01. Health and Welfare Expenditure Series No. 19, 2004; HWE 26
    Braunwald, Circulation 80:410-4, 1989
    Bylesjö et al. Journal of Chemometrics 20:341-51, 2006
    Cui and Thomas, Journal of Chromatography B; 877:2709-15, 2009
    Damas and Aukrust Scand Cardiovasc J 40:262-6, 2006
    Davis et al., J. Biol. Chem. 283: 6428-6437, 2008
    Fahy et al., J Lipid Res. 50: S9-14, 2009
    Fahy et al., J Lipid Res. 51(6): 1618, 2010
    Fawcett T Pattern Recogn Lett 27:861-74, 2006
    Folch et al. J Biol Chem 226:497-509, 1957
    Heart Disease and Stroke Statistics-2006 Update, Dallas Tex.: American Heart Association, 2006 Available at http://www.americanheartorg/downloadable/heart/1198257493273HS_Stats%202008.pdf
    Murphy et al. Chem Rev 101:479-526, 2001
    Naghavi et al. Circulation 108:1772-8, 2003
    National Health Survey: Summary of Results, Australia, 2004-05, cat. no. 4364.0, ABS, Canberra, Vol: Australian Bureau of Statistics, 2006
    Oei et al., Circulation. 111: 570-575, 2005
    Ridker et al. Circulation 109:IV-6-19, 2004
    Ridker et al. JAMA: Journal of the American Medical Association 297:611-9, 2007
    Shearer et al. PLoS ONE 4:e5444, 2009
    Stenlund et al. Analytical Chemistry 80:6898-906, 2008
    White et al. Cardiovascular Research 75:813-20, 2007

## Claims

1. A method of treatment or prophylaxis of a subject suspected of being vulnerable or non-vulnerable to plaque rupture, the method comprising:
a) obtaining a lipid sample from the subject;
b) determining the levels of a lipid analyte in the lipid sample selected from the list consisting of modCer 731.6 and DHC 18:1; wherein the level of the individual lipid analytes is different between vulnerable subjects and non-vulnerable subjects and wherein the level of the lipid analytes in the subject relative to a control identifies the subject as being vulnerable or non-vulnerable to plaque rupture; and
c) providing therapeutic and/or behavioral modification to the subject based on whether the subject is determined to be vulnerable or non-vulnerable to plaque rupture.

2. The method of claim 1, further comprising comparing the level of the at least two lipid analytes in the sample to the respective levels of the same lipid analytes in at least one control sample selected from a first control sample from a subject that is vulnerable to plaque rupture and a second control sample from a subject that is non-vulnerable to plaque rupture, wherein a similarity in the respective levels of the at least two lipid analytes between the sample and the second control sample identifies the subject as being non-vulnerable to plaque rupture, and wherein a similarity in the respective levels of the at least two lipid analytes between the sample and the first control sample identifies the subject as being vulnerable to plaque rupture.

3. The method of claim 2, further comprising comparing the level of the at least two lipid analytes in the sample to the respective levels of the same lipid analytes in at least one sample from a healthy subject, wherein a similarity in the respective levels of the at least two lipid analytes between the sample and the sample(s) from the healthy subject identifies the subject as being healthy with respect to vulnerability to plaque rupture.

4. The method of claim 1, further comprising determining or determining and comparing the levels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 lipid analytes listed in Table 1 wherein the level of an individual lipid analyte listed in Table 1 is different between subjects that are vulnerable to plaque rupture and subjects that are non-vulnerable to plaque rupture.

5. The method of claim 1, further comprising determining the levels of at least two further lipid analytes selected from the group consisting of GM3 18:0, PC34:5, APC 34:2, SM 18:0, Cer 18:1, PI 36:1, APC 36:0, DG 18:1 20:0, LPC 14:0, LPC 16:1, PC 24:0, Cer 18:0, PI 36:3, PI 38:2, modPC.622.4/40, LPC 18:2, LPC 24:0, PC 34:3, modPC 752.6/5.58, PI 34:0, modCer 703.6/5.87 and SM 22:1.

6. The method of claim 5, comprising determining the levels of at least four, six, eight or sixteen lipid analytes selected from the group consisting of, GM3 18:0, PC34.5, APC 34:2, SM 18:0, Cer 18:1, PI 36:1, APC 36:0, DG 18:1 20:0, LPC 14:0, LPC 16:1, PC 24:0, Cer 18:0, PI 36:3, PI 38:2, modPC.622.4/40, LPC 18:2 and LPC 24:0, PC 34:3, modPC 752.6/5.58, PI 34:0, modCer 703.6/5.87 and SM 22:1.

7. The method of claim 1, wherein the levels of lipid analytes are used in combination with one or more traditional risk factors selected from age, sex, smoker, diabetes, hypertension, coronary heart disease (CAD) family history, body mass index (BMI), total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, glucose and high-sensitivity C-reactive protein (hsCRP) to thereby identify the subject as being vulnerable or non-vulnerable to plaque rupture.