Patent Description:
Alzheimer's disease (AD) is a progressive degenerative disease of the central nervous system characterized by progressive and increasing memory loss, followed by loss of control of limbs and bodily functions and eventual death. It is by far the most common cause of dementia affecting <NUM> to <NUM>% of people over the age of <NUM> years and between <NUM> to <NUM>% of those over <NUM>. AD is distinguished from other types of dementia by several pathological features, including the progressive appearance in the brain of the patients of senile plaques in the extracellular space between neurons. The plaques have central cores of amyloid deposits formed mainly by fibrils of a <NUM>-<NUM> amino acids peptide referred to amyloid β peptide (Aβ) surrounded by degenerated neuritis and glial cells. This peptide results from the proteolytic processing of a precursor protein called β amyloid precursor protein (βAPP). AD can be classified according to the age of appearance as early onset (age under <NUM> years) and late onset (age above <NUM> years), according to the existence of an autosomic dominant inheritance, as familiar AD or sporadic AD respectively. Early onset familiar forms of AD can be associated to known mutation in the genes coding for βAPP, presenilin <NUM> and presenilin <NUM> (located, respectively, on chromosomes <NUM>, <NUM> and <NUM>).

These classifications are not mutually exclusive. The most frequent forms are sporadic late-onset forms. In clinical praxis, diagnosis of AD is carried out using clinical criteria based on the presence of typical clinical hallmarks and the exclusion of other types of dementia using neuroimaging techniques and blood analysis. Using these criteria, diagnostic reliability is acceptable although, according to studies done using brain autopsy, between <NUM>-<NUM>% of the patients diagnosed with AD suffered from a different disease.

Frontotemporal dementia (FTD) is another neurodegenerative disease. It is the second most prevalent dementia of patients below age <NUM>. The disease is often misdiagnosed in the early stage, either as a psychiatric disorder, or as a different type of dementia such as Alzheimer's disease (AD).

The underlying pathological spectrum of FTD, frontotemporal lobar degeneration (FTLD), can be divided in <NUM> main subtypes characterized by either tau or TDP-<NUM> accumulations.

According with the Alzheimer's Association, the disorders grouped under FTD fall into three subtypes:.

Methods are known in the prior art to diagnose AD by detecting the levels of biomarkers present in the brain or cerebrospinal fluid (CSF) of patients. Different biomarkers have been characterized whose determination is carried out in CSF. CSF reflects directly the composition of the extracellular space of the central nervous system and thus, provides higher concentrations of biomarkers. The cerebrospinal fluid (CSF) biomarkers for AD, i.e. (p) Tau and amyloid beta-<NUM>, appear to be of limited value for the diagnosis of clinical FTD. While structural MR scans can be used to detect frontal lobe or temporal lobe atrophy, the early stages of FTD are normally not detectable.

However, CSF can only be retrieved by means of lumbar puncture, which is not a routine diagnostic method easily accepted by patients suffering from dementia, let alone in patients with memory disorders. Thus, there is a need for AD biomarkers which can be detected in samples which can be non-invasively retrieved from the body. Suitable AD biomarkers described in the prior art and which can be detected in plasma include (i) markers derived from the amyloid plaque, (ii) autoantibodies against Aβ o βAPP, (iii) inflammatory markers such IL-<NUM>, its receptor or gp130, C-reactive protein or oxidative stress (isoprostanes), (iv) markers of lipidic metabolism (apoE, oxysterols) and (v) vascular disease markers (homocysteine, lipoprotein b C1q) (<NPL>). <CIT>, <CIT> and <CIT> are also describing different biomarkers found in non-invasive samples.

Regarding FTD, <CIT> describes a method of classifying the FTD status of an individual, comprising determining the concentration of a panel of biomarkers selected from a biological sample from said individual. However, among all the biomarkers that they found relevant only one seems to be correlated in CSF and serum samples.

<CIT> provides methods to determine if a mammal has a neurodegenerative disease based on TDP-<NUM> levels and/or TDP-<NUM> cleavage products in a biological fluid. However, the method although useful in non-invasive methods (plasma and serum) is not able to classify which neurodegenerative disease the patient is suffering from.

<CIT> is describing a differential method for diagnosis AD or FTD based in serum biomarkers with statistical values but the number of samples used in this study for each group is very limited.

However, none of these non-invasive biomarkers panels described so far have reached the right level of precision to enable a reliable diagnosis, and even less reliable if it is in a preclinical stage. Consequently, so far no evidence has been incorporated into clinical practice.

We present here a multiparametric biomarker panel that fulfills a long-felt need in the art with strong statistic potency based in a high number of samples, useful for diagnosing and predicting the onset of both Alzheimer's disease and FTD based on the analysis of bodily fluids, which can be easily obtainable by non-invasive means.

The authors of the present invention have identified a series of metabolic markers present in the plasma samples collected from subjects previously diagnosed with Alzheimer Disease (AD) or Frontotemporal dementia (FTD, (variants bvFTD and PPA). These metabolic markers selected are significantly differentiated between Healthy Controls (HC) and AD or FTD and between AD and FTD. These metabolic markers can then be used in a non-invasive diagnostic method identifying and classifying patients with AD or FTD patients versus HC.

In a first aspect, the invention relates to a diagnostic method to distinguish AD patients versus non-affected patients by determining in a biological sample of a subject the levels of at least one, preferably all, of the <NUM> biomarkers described in table <NUM>.

The diagnostic methods of AD versus HC is by determining in a biological sample of a subject suspected of suffering from AD the levels of at least one metabolic marker or markers described in table 1wherein.

In a second aspect, the invention relates to a method for monitoring the progression of AD disease comprising determining in a biological sample of a subject, without having been treated or having been treated with a therapy indicated for AD, the levels of at least one metabolic marker or markers described in table <NUM> wherein.

It is noted that all of the above methods can be complemented by detecting the presence or absence of APOE4 in the biological sample.

Before the present methods are described, it is to be understood that this invention is not limited to particular methods, and experimental conditions described, methods and conditions may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only in the appended claims.

In a first aspect the invention relates to a diagnostic method to distinguish AD patient subjects comprising determining in a biological sample of said subject the levels of at least one metabolic marker described in table <NUM> and comparing the levels of said marker or markers with respect the levels of the same marker or markers in a HC patient or with respect to a reference value as described through-out the present specification, wherein the subject is classified as suffering AD as explained throughout the specification and in the examples.

The term "diagnosis", as used herein, refers both to the process of attempting to determine and/or identify a possible disease in a subject, i.e. the diagnostic procedure, and to the opinion reached by this process, i.e. the diagnostic opinion. As such, it can also be regarded as an attempt at classification of an individual's condition into separate and distinct categories (such as predicting the "increasing risk" of suffering a disease, meaning "increasing risk" as an increased chance of developing or acquiring a disease compared with a normal individual) that allow medical decisions about treatment and prognosis to be made. It is to be understood that the method, in a preferred embodiment, is a method carried out in vitro, i.e. not practiced on the human or animal body. In particular, the diagnosis to determine AD patients, relates to the capacity to identify and classify AD patients. This diagnosis, as it is understood by a person skilled in the art does not claim to be correct in <NUM>% of the analyzed samples. However, it requires that a statistically significant amount of the analyzed samples are classified correctly. The amount that is statistically significant can be established by a person skilled in the art by means of using different statistical tools; illustrative, non-limiting examples of said statistical tools include determining confidence intervals, determining the p-value, the Chi-Square test discriminating functions, etc. Preferred confidence intervals are at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%. The p-values are, preferably less than <NUM>, less than <NUM>, less than <NUM>, less than <NUM> or less than <NUM>. The teachings of the present invention preferably allow correctly diagnosing in at least <NUM>%, in at least <NUM>%, in at least <NUM>%, or in at least <NUM>% of the subjects of a determining group or population analyzed.

The term "Alzheimer's disease" or "AD", as used herein, refers a mental deterioration associated with specific degenerative brain disease that is characterized by senile plaques, neuritic tangles and progressive neuronal loss which manifests clinically in progressive memory deficits, confusion, behavioral problems, inability to care for oneself, gradual physical deterioration and, ultimately, death. As used herein, this term is intended to include all the stages (such as preclinical stage) of the disease.

The term "Frontotemporal dementia" or "FTD", as used herein refers to a disorder caused by the degeneration of the brain's frontal lobes. Diagnostic criteria according to the Lund-Manchester criteria include insidious onset and gradual progression, early decline in social interpersonal conduct, early impairment in regulation of personal conduct, early emotional blunting, and early loss of insight. Symptoms of FTD generally appear between the ages of <NUM> and <NUM> years of age.

As used herein, this term is intended to include all the stages (such as preclinical stage) and subtypes of the disease.

The terms "subject", "patient" or "individual‴ are used herein interchangeably to refer to all the animals classified as mammals and includes but is not limited to domestic and farm animals, primates and humans, for example, human beings, non-human primates, cows, horses, pigs, sheep, goats, dogs, cats, or rodents. Preferably, the subject is a male or female human being of any age or race.

The term "metabolic marker" or "metabolite" or "biomarker", are used herein interchangeably to refers to small molecule compounds, such as substrates for enzymes of metabolic pathways, intermediates of such pathways or the products obtained by a metabolic pathway, the occurrence or amount of which is characteristic for a specific situation, for example AD. The metabolic markers useful for the diagnostic method of the invention are those defined in table <NUM>. Table1contains the abbreviated common names of the metabolites and the lipid family. The lipid family is further described by the reference number of said lipid family in the LIPID MAPS structure database using the LIPID MAPS Classification System (Fahy E. , Journal of Lipid Research <NUM>, <NUM>: S9-S14). The lipid metabolic markers of table <NUM> is intended to refer to any isomer thereof, including structural and geometric isomers. The term "structural isomer", as used herein, refers to any of two or more chemical compounds, having the same molecular formula but different structural formulas. The term "geometric isomer" or "stereoisomer" as used herein refers to two or more compounds which contain the same number and types of atoms, and bonds (i.e., the connectivity between atoms is the same), but which have different spatial arrangements of the atoms, for example cis and trans isomers of a double bond, enantiomers, and diastereomers. The abbreviated common name of the amino acid or protein corresponds to the Amino Acid name or Protein to which it belongs followed by an accession number described in the Human Metabolome Database HMDB.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of L-Arginine. It is noted that a decrease of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of L-Glutamic Acid. It is noted that a decrease of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of Ornithine. It is noted that an increase of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of Putrescine. It is noted that an increase of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of Lyso PC a C18:<NUM>. It is noted that a decrease of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of PC aa C34:<NUM>. It is noted that an increase of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of PC ae C30:<NUM>. It is noted that an increase of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of PC ae C36:<NUM>. It is noted that a decrease of said marker with respect to HC or with respect to a reference value is indicative that the subject suffers from AD.

In a particular embodiment, the diagnostic method of the invention comprises determining the presence of allele APOE4. It is noted that the presence of said allele is indicative that the subject suffers from AD.

In a preferred embodiment the method further comprises confirming the diagnosis of AD by means of the clinical examination of the patient, preferably by using anamnesis and neuropsychological tests (such as the MiniMental State Examination (MMSE) or clinical dementia Rating (CDR). Blood tests are used to rule out dementia due to other causes such as syphilis, Vitamin B12 deficiency, abnormal thyroid levels or HIV.

It is further noted that Diagnostic accuracy can be increased through the analysis of biomarkers ((p) Tau and amyloid beta-<NUM>) in CSF by ELISA; through the analysis of Amyloid beta, Tau or p-Tau in cerebral tissue (by Positron Emision Tomography (PET) using specific radioligands; through the analysis of brain hypometabolism in specific areas of the brain by means of fluoro-D-glucose PET (FdG PET); through the analysis of cerebral blood flow in specific brain areas using single photon emission computed tomography (SPECT), and through the analysis of the atrophy of temporal areas of the brain using magnetic resonance imaging (MRI). None of the above-mentioned diagnostic methods provide a definitive AD diagnosis, which can only be achieved by a brain autopsy.

Currently, there are not disease-modifying treatment for Alzheimer's Disease. Patients diagnosed with AD are treated with drugs aimed to reduce symptomatology. The two most common drugs prescribed for AD patients are acethylcholinesterase inhibitors such as donezepil for mild to moderate AD and NMDA glutamate receptor blocking agents such as mematine, for moderate to severe AD.

The most tested strategies in phase III clinical trials are therapies directed to reduce either the amount or the formation of Aβ. They include the use of antibodies directed to soluble Aβ and/or Aβ plaques in the brain, and inhibitors of beta-secretase (BACE, the enzyme that cleavages the amyloid precursor protein and favors the accumulation of Aβ). All phase III clinical trials with these compounds were directed to mild to moderate stages of the disease and all failed to improve performance in neuropsychological tests. These compounds are now being tested on earlier stages of the disease including asymptomatic phases, with the hope that they will be more effective in stages where the neurodegeneration has not already happened.

Other therapeutic strategies being tested in phase III clinical trials include but are not limited to dietary interventions (for example ketogenic diets or DHA supplements), drugs targeting Tau, or agonist/antagonists of neurotransmitters such as serotonine and dopamine.

It will be understood that the method of the invention can be carried out by determining the level of a variable number of metabolites defined in table 1in the biological sample of the subject under study. For example, the level(s) of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least nine, or ten of the markers selected from table <NUM>.

The determination of levels of combinations of the metabolic markers may allow greater sensitivity and specificity in the diagnosis of AD.

In a preferred embodiment the metabolic markers of table <NUM> correspond to the molecules disclosed in table <NUM> and <NUM>.

The term "sample" or "biological sample", as used herein, refers to biological material isolated from a subject. The biological sample may contain any biological material suitable for detecting the desired biomarker and may comprise cellular and/or non-cellular material from the subject. The sample can be isolated from any suitable biological tissue or fluid such as, for example, blood, blood plasma, serum, cerebral spinal fluid (CSF), urine, amniotic fluid, lymph fluids, external secretions of the respiratory, intestinal, genitourinary tracts, tears, saliva, white blood cells. Preferably, the samples used for the determination of the level(s) of the metabolic markers are samples which can be obtained using minimally invasive procedures. In a preferred embodiment, the samples are plasma samples.

The term "level" or "presence", as used herein, refers to the quantity of a biomarker detectable in a sample. Techniques to assay levels of individual biomarkers from test samples are well known to the skilled technician, and the invention is not limited by the means by which the components are assessed. In one embodiment, levels of the individual components of the lipidomic profile are assessed using mass spectroscopy, high performance liquid chromatography (HPLC) and the like. Other methods of assessing levels of the individual components includes isoelectric focusing (IEF) and sandwich ELISA, Immunoturbidimetry, qPCR, northern blot, RNA dot blot, Taq Man, tag based methods such as serial analysis of gene expression (SAGE) including variants such as LongSAGE and SuperSAGE microarrays. In a preferred embodiment the presence of the Apolipoprotein E isoform <NUM> (APOE4) is determined by quantitative PCR, preferably Real-Time PCR (RT-PCR) reverse transcription polymerase chain reaction (RT-PCR). In more preferred embodiment, the the presence of allele of the Apolipoprotein E isoform <NUM> is determined by methods of Immunoturbidimetry as explained in detail in <CIT>.

The detection can be carried out in individual samples or in tissue microarrays.

The assessment of the levels of the individual components can be expressed as absolute or relative values and may or may not be expressed in relation to another component, a standard an internal standard or another molecule of compound known to be in the sample. If the levels are assessed as relative to a standard or internal standard, the standard may be added to the test sample prior to, during or after sample processing.

To assess levels of the individual components of the subject, a sample is taken from the subject. The sample may or may not processed prior assaying levels of the components of the lipidomic profile. For example, whole blood may be taken from an individual and the blood sample may be processed, e.g., centrifuged, to isolate plasma or serum from the blood. The sample may or may not be stored, e.g., frozen, prior to processing or analysis.

Individual components of the lipidomic profile include but are not limited to phosphatidyl cholines (PC), Lyso PCs, Fatty Acids and Fatty Amides. Specific examples of PCs, Lyso PCs, Fatty Acids and Fatty Amides that can be included as constituents of the lipidomic profile include but are not limited to L-Arginine, L-Glutamic Acid, Ornithine, Aminoadipic acid, Putrescine, Lyso PC a C18:<NUM>, PC aa C34:<NUM>, PC ae C30:<NUM>, PC ae C36:<NUM>, L-Alanine, L-Lysine, L-Tryptophan, C18:<NUM>, PC aa C34:<NUM>, PC aa C42:<NUM>, PC ae C38:<NUM>, PC ae C34:<NUM>. Those of skill in the art will recognize the specific identity of each constituent listed based upon the nomenclature above. For example, metabolite Lyso PC a C18:<NUM> is known as Lysophosphatidylcholine a C18:<NUM>, metabolite PC aa C34:<NUM> is known as Phosphatidylcholine with dyacyl residue sum C <NUM>:<NUM>), metabolite PC ae C34:<NUM> is known as Phosphatidylcholine with acyl-alkyl residue sum C34:<NUM>.

Once the sample has been processed, the first method of the invention involves the determination of the levels of the biomarker in the sample. The expression "determining the levels of the biomarker", as used herein, refers to ascertaining the absolute or relative amount or concentration of the biomarker in the sample. There are many ways to collect quantitative or relational data on biomarkers or metabolites, and the analytical methodology does not affect the utility of metabolite concentrations in assessing a diagnosis. Suitable methods for determining the levels of a given metabolite include, without limitation, refractive index spectroscopy (RI), Ultra-Violet spectroscopy (UV), fluorescent analysis, radiochemical analysis, Infrared spectroscopy (IR), Nuclear Magnetic Resonance spectroscopy (NMR), Light Scattering analysis (LS), Mass Spectrometry, Pyrolysis Mass Spectrometry, Nephelometry, Dispersive Raman Spectroscopy, gas chromatography combined with mass spectroscopy, liquid chromatography combined with mass spectroscopy, supercritical fluid chromatography combined with mass spectroscopy, MALDI combined with mass spectroscopy, ion spray spectroscopy combined with mass spectroscopy, capillary electrophoresis combined with mass spectrometry, NMR combined with mass spectrometry and IR combined with mass spectrometry.

In a particular embodiment, the levels of the metabolic markers are determined by mass spectrometry.

The diagnostic method of the invention comprises comparing the level(s) of the metabolic marker(s) with a reference value.

The term "reference value", as used herein, relates to a predetermined criteria used as a reference for evaluating the values or data obtained from the samples collected from a subject. The reference value or reference level can be an absolute value, a relative value, a value that has an upper or a lower limit, a range of values, an average value, a median value, a mean value, or a value as compared to a particular control or baseline value. A reference value can be based on an individual sample value or can be based on a large number of samples, such as from population of subjects of the chronological age matched group, or based on a pool of samples including or excluding the sample to be tested.

The reference value according to the diagnostic method of the invention can be obtained from one or more subjects who do not suffer from AD or FTD impairment (i.e., healthy control subjects), from subjects suffering from AD or FTD at early stage, non-symptomatic (preclinical stage) or from the same subjects that is been diagnosed or monitoring suffering from AD or FTD but at an earlier time point.

Thus, in a particular embodiment, when the reference value is obtained from a subject not suffering from AD, increased level(s) of ornithine, putrescine, PC aa C34:<NUM> and/or PC ae C30:<NUM> from table <NUM> are indicative that the subject suffers from AD; and/or
decreased level(s) of L-Arginine, L-Glutamic Acid, Alpha-AAA, Lyso PC a C18:<NUM> and/or PC ae C36:<NUM> from table <NUM> are indicative that the subject suffers from AD.

According to the diagnostic methods of the invention, the level of a metabolic marker is considered "decreased" when the level of said marker in a sample is lower than its reference value. The level of a marker is considered to be lower than its reference value when it is at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, or more lower than its reference value. Likewise, in the context of the diagnostic methods of the invention, the level of a marker is considered "increased" when the level of said marker in a sample is higher than its reference value. The level of a marker is considered to be higher than its reference value when it is at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, at least <NUM>%, or more higher than its reference value.

In a second aspect, the invention relates to a method for monitoring the progression of a subject suffering from AD comprising determining in a biological sample of a subject, over the course of a therapy or not, the levels of at least one metabolic marker or markers described in table <NUM> wherein.

The terms "AD", "subject", "metabolic marker", "biological sample", "level", "decreased" and "increased" have been defined in connection with the first diagnostic method of the invention. The metabolic markers defined in Table <NUM>, as well as the techniques for determining the level of these markers, have also been defined in connection to the diagnostic methods of the invention. The particular and preferred embodiments of the diagnostic methods of the invention regarding these terms are also applicable to the fourth method of the invention.

The term "subject suffering from AD" refers to a subject who has been diagnosed with AD.

The term "monitoring the progression", as used herein, refers to the determination of the evolution of the disease in a subject diagnosed with AD i.e., whether the AD is worsening or whether it is ameliorating.

The term "progression in the AD", as used herein, is understood as a worsening of the disease, i.e., that the disease is progressing to a later stage with respect to a stage at an earlier time point measured. In a particular embodiment, a progression in the AD means a progression from AD in a preclinical stage (non- symptomatic subjects) to AD with clinical symptoms (symptomatic subjects).

In a particular embodiment, the biological samples are plasma samples.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of L-Arginine.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of L-Glutamic Acid.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of Ornithine.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of Putrescine.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of Lyso PC a C18:<NUM>.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of PC aa C34:<NUM>. ln a particular embodiment, the diagnostic method of the invention comprises determining the levels of PC ae C30:<NUM>.

In a particular embodiment, the diagnostic method of the invention comprises determining the levels of PC ae C36:<NUM>.

In a particular embodiment, the method of the invention comprises determining the levels of at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or ten of the markers selected from table <NUM>.

In a preferred embodiment the metabolic markers of Table <NUM> correspond to the molecules disclosed in Tables <NUM> and <NUM>.

The fourth method of the invention involves comparing the levels of one or more metabolic markers in a sample from a subject with a reference value, i.e., the levels of the same marker or markers, determined in a sample from said subject at an earlier time point. In a particular embodiment, the level of the marker in a sample is compared with the level of said marker in the same type of sample.

In a particular embodiment, the determination of the level of the one or more metabolic markers is carried out by mass spectrometry. In particular, by using a kit suitable for mass spectrometry assay preparation. Such kit should preferably deliver the widest range of metabolomic information available from a single targeted assay, covering a large number of key metabolites from main metabolic pathways. This kit should thus quantitatively analyze a large number of metabolites that have already been identified herein as part of key biochemical pathways, providing fundamental data to link changes in the metabolome to biological events. Preferably, such kit should preferably comprise at least one, preferably all, of the following components; a kit's plate, a silicone mat cover for the plate, solvents preferably in sealed glass ampoules, quality controls, standards, a deep well capture plate, a memory stick having a software to link changes in the metabolome to biological events and a user manual.

Yet another aspect of the present invention includes a kit for a diagnosis of AD comprising: biomarker detecting reagents for determining a differential expression level of at least one of the markers identified in table <NUM> or any combination thereof, preferably comprising biomarker detecting reagents for determining a differential expression level of all of the biomarkers identified in table <NUM>.

In one preferred embodiment of this aspect of the invention, the kit further comprises instructions for use in diagnosing risk for AD, wherein the instruction comprise step-by-step directions to compare the expression level of at least one, preferably all, of the markers identified in table <NUM>, when measuring the expression of a sample obtained from a subject suspected of having AD with the expression level of a sample obtained from a normal subject, wherein the normal subject is a healthy subject not suffering from AD, or with a reference value. In another aspect, the kit further comprises tools, vessels and reagents necessary to obtain samples from a subject selected from the group consisting of one or more biological fluids, a plasma sample, a serum sample, a blood sample, a tissue sample, or a faecal sample, preferably a plasma sample.

Yet another aspect of the present invention includes a computer program suitable for implementing any of the methods of the present invention. In addition, a device comprising the above mentioned computer program also forms part of the present invention as well as its use for the diagnosis of AD in a human subject.

In particular this aspect of the invention refers to the in vitro use of a diagnostic kit or device comprising reagents capable of measuring the levels of at least one metabolic marker selected from the list of biomarkers of table <NUM> or any combination thereof in a plasma sample, for distinguish Alzheimer's patient subjects from subjects not suffering from Alzheimer's disease. Preferably said Kit comprises reagents capable of measuring the levels of all of the metabolic markers identified in table <NUM>.

Another preferred embodiment of the present invention refers to the in vitro use of a kit or device comprising reagents capable of measuring the levels of at least one metabolic marker selected from the list of biomarkers of table <NUM> or any combination thereof in a plasma sample,. Preferably said Kit comprises reagents capable of measuring the levels of all of the metabolic markers identified in table <NUM>.

Another preferred embodiment of the present invention refers to the in vitro use of a kit or device comprising reagents capable of measuring the levels of at least one metabolic marker selected from the list of biomarkers of table <NUM> or any combination thereof in a plasma sample, for monitoring the progression of AD in a subject in a subject according to the third aspect of the invention. Preferably said Kit comprises reagents capable of measuring the levels of all of the metabolic markers identified in table <NUM>.

Another preferred embodiment of the present invention refers to the in vitro use of a kit or device comprising reagents capable of measuring the levels of at least one metabolic marker selected from the list of biomarkers of table <NUM> or any combination thereof in a plasma sample, for monitoring the progression of AD in a subject in a subject according to the fourth aspect of the invention. Preferably said Kit comprises reagents capable of measuring the levels of all of the metabolic markers identified in table <NUM>.

The assignment of a patient into a specific group of patients, such as patients with AD, by any of the methods of the invention can be done by a computer program, preferably, after introducing the data into said program. Thus, in another preferred embodiment, the step of assigning a patient into a specific group of patients, such as patients with AD, according to any of the methods described in the present specification, is a computer implemented step wherein the data obtained in the previous steps of the method are inserted in a computer program and the program assigns the patient into one of the groups of patients.

This differentiation between patients may help to determine the best treatment aimed to reduce the symptomatology of AD.

The present invention is further illustrated by the following examples which merely illustrate the invention and do not limit the same.

A total of <NUM> volunteers participated in this multicenter international study (<NUM> Spanish, <NUM> French and <NUM> Belgian hospitals/centers were involved) the participants were classified as follow:.

Patients recruited were fasted (minimum of <NUM> hours), and then the analytical sample was extracted. Two tubes of whole blood (<NUM> Vacutainer tube with EDTA, one tube for Vacutainer serum without anticoagulant, in total a maximum volume of <NUM>) were obtained, which were processed within <NUM> hours (room temperature). Once the different fractions were obtained they were stored at -<NUM> ° C until processed.

Analysis of APOE4: APOE genotype was carried out using Real Time PCR. An individual was assigned with a value of <NUM>, if the genotype revealed the presence of one ε4 allele or two ε4 alleles of the APOE gene, or <NUM> if the genotype revealed the absence of the ε4 allele.

A total of <NUM> metabolites were analyzed in plasma samples from patients and controls using the validated quantitative kit Absolute® IDQ p180 kit (Biocrates, Innsbruck Austria). This kit performed a targeted metabolite profiling by electrospray ionization (ESI) tandem mass spectrometry (MS/MS) and it was performed on a fee-for-service basis on its quantitative metabolomics platform at Biocrates Life Sciences AG, Austria. The experimental metabolomics measurement technique is described in detail by <CIT>. This kit comprises <NUM> acylcarnitines, <NUM> amino acids and biogenic amines, <NUM> sphingolipids, <NUM> glycerophospholipids and sum hexoses.

An iterative model building approach was applied to identify discriminative signatures:.

The univariate analysis was performed for each comparison group to investigate the variables that had a significant association at the <NUM>% level with an individual's classification. To do so, a simple logistic regression was performed, modelling the diagnosis as a binary response with <NUM> for a case, and <NUM> as a control, against each variable of interest. Variables were assessed using the Wald test to determine the significance of each variable. The models were also tested for convergence, to identify issues such as quasi-complete or complete separation of data points which could cause further modelling issues downstream.

Following the univariate analysis, a list of variables from the relevant parameter groups which had a significant association at the <NUM>% level with an individual's classification, and did not present any convergence issues in the univariate analyses were retained. Whilst the association of the demographic variables, age and sex, may be significant, these variables were excluded from subsequent analyses. As a result, only the markers of interest were included in the final classification models built using a process of stepwise selection within a series of cross validations.

Cross-validation was utilized as a robust method to determine the combination of variables that are significantly associated with an individual's classification, independent of the sample of data being analyzed. The cross-validations consisted of <NUM> random samples using a <NUM>% sample for the training dataset, whilst the remaining <NUM>% sample of data was used for validation.

Within each cross-validation, a logistic regression assuming stepwise selection, and using an entry criteria equalling p<<NUM> and stay criteria equalling p<<NUM>, was used to determine a final model for each iteration. The frequency of times a variable was included within the final models was recorded. Those variables found within at least <NUM>% of derived models were then included within a fixed logistic regression model without selection to determine the combination of markers to be included in the final model for classification. Again, the performance of the final marker combination was further evaluated using the conservative method of cross-validation.

Evaluation of the final models: the second round of cross-validation enabled the determination of accuracy rates based upon the classification rules containing the final marker combination. Two types of accuracy rates were observed, namely the area under the ROC curve (AUC) and <NUM>-misclassifcation rate.

The cross-validation performed logistic regression without selection on the most frequent variables chosen as above. Again, the cross-validations consisted of <NUM> random samples using a <NUM>% sample for the training dataset, whilst the remaining <NUM>% sample of data was used for validation. Doing so enabled the average, standard deviation and <NUM>% confidence intervals of these accuracy rates to be determined for each diagnosis comparison. The ROC curves and parameter estimates were provided based on the logistic regression model with an AUC closest to the average AUC calculated through cross-validation.

Tables <NUM> shows the values of the cross-validation method that undergone these selected metabolites.

Claim 1:
A diagnostic method to distinguish Alzheimer's patient subjects, comprising determining in a plasma sample of said subject the levels of each of the metabolites of the list consisting of: aminoadipic acid (alpha-AAA), butane-<NUM>,<NUM>-diamine (putrescine), arginine, ornithine, glutamic acid, Lyso PC a C18:<NUM>, PC aa C34:<NUM>, PC ae C30:<NUM>, and PC ae C36:<NUM> and the presence of allele APOE4, and comparing the levels of said markers with respect to the levels of the same markers in a healthy control patient or with respect to a reference value, wherein the subject is classified as suffering Alzheimer's disease or as having an increased risk of suffering from Alzheimer's disease if there is an increased level(s) of ornithine, putrescine, PC aa C34:<NUM>, and PC ae C30:<NUM> and presence of allele APOE4 and a decreased level(s) of L-Arginine, L-Glutamic Acid, Alpha-AAA, Lyso PC a C18:<NUM> and PC ae C36:<NUM>.