alzheimer disease ( ad ) is a rapidly expanding health crisis affecting over 26 million people , with the prevalence expected to rise dramatically ( brookmeyer et al . , 2007 ) . research examining ad biomarkers suggests a rise in underlying pathology a decade or more before the onset of dementia , and continuing throughout the early stages of the disease ( bateman et al . , 2012 ; benzinger et al . , 2013 ; jack et al . , there is need to translate such biomarkers from a laboratory setting into a clinical environment to assist with disease diagnosis and prognosis . the hallmarks of ad pathology are the formation of amyloid beta ( a ) plaques and the aggregation of tau into neurofibrillary tangles ( nfts ) ( braak and braak , 1995 ; hardy and higgins , 1992 ) . early elevations in such pathology are subsequently followed by hypometabolism , structural atrophy , and cognitive impairment ( bateman et al . , 2012 ; benzinger et al . , 2013 ; jack et al . , 2010 ) . atrophy of cortical and subcortical gray matter has long been noted in ad ( e.g. fox et al . , 1996 ; gordon et al . , 2013 ; scheltens et al . , 1992 ) . less attention has been paid to white matter damage and declines tied to ad disease progression . early work with computed tomography ( ct ) images noted increased incidence of white matter leukoaraiosis in individuals with ad ( blennow et al . , 1991 ; rezek et al . , similar results were found with the introduction of magnetic resonance imaging ( mri ) ( barber et al . , 1999 ; fazekas et al . , 1987 ) . in this initial work the most common way to characterize white matter damage was to use semi - quantitative scales ( fazekas et al . , 1987 ; kapeller et al . , 2003 ; scheltens et al . , 1995 ) to grade the severity of white matter hyperintensities ( wmhs ) on t2-weighted or fluid - attenuated inversion recovery ( flair ) scans . at a pathological level , higher ratings on these scales are associated with both cognitive decline ( debette et al . . , 2008 ) and cortical atrophy ( capizzano , 2004 ; schmidt et al . , 2005 ) . in general there is a rising interest on the clinical importance of wmh across diseases ( debette and markus , 2010 ) . the relationship between wmh and amyloid is complex and has not been fully evaluated , although there are suggestions that both contribute to cognitive impairment ( provenzano et al . , 2013 ) . white matter damage may be both a downstream result of elevated a levels , as well as a marker of comorbid pathology ( e.g. cardiovascular disease ) . a leads to oxidative damage and the formation of free radicals ( hensley et al . 1996 ) , and the administration of a damages oligodendrocytes in vitro ( roth et al . , 2005 ) and in vivo ( jantaratnotai et al . , 2003 ) . conversely damage to myelin releases iron molecules that promote a oligomerization ( bartzokis et al . an initial rise in a would damage white matter , which in turn would elevate a levels , subsequently leading to more white matter damage in a continuing cyclical process . alternatively , white matter lesions from a secondary process ( e.g. head injury ) may release iron , and initiate or accelerate the pathological influences of a on white matter . such results can been seen in the literature as circulating levels of a are associated with wmh ( gurol et al . , 2006 ) , and baseline levels of white matter lesions predict an accelerated accumulation of amyloid over time ( grimmer et al . , 2012 ) . using semi - quantitative scales , white matter lesions have often been seen in individuals with compromised cardiovascular systems ( breteler et al . , 1994 ; consistent with these results , there has been a suggestion that ad may have a larger vascular component than often recognized ( bartzokis , 2011 ; de la torre , 2010 ; launer , 2002 ) . indeed , in epidemiological studies , cardiovascular risk factors such as diabetes or stroke lead to increased risk of ad ( luchsinger et al . , damage to the cardiovascular system , such as a thickening and sclerosis of arteries , may lead to an impaired drainage of molecules such as a ( huang et al . , it is of interest to know whether the incidence of wmhs provides any diagnostic value above and beyond levels of a pathology in the brain . white matter damage in the brain can be assessed using visual ratings of wmh , quantification of wmh volumes , and using diffusion tensor imaging ( dti ) . while there is a clear utility to quantifying damage using dti and wmh volumetric measurement , visual rating scales are an easily obtained radiological measure available across both research and clinical settings . here we examine the relationships between a deposition , white matter damage , and dementia in a population of cognitively normal , very mildly demented , and mildly demented individuals . based upon prior work in the literature , we hypothesize that more severe semi - quantitative ratings of white matter damage will be related to an impaired cognitive status . middle aged and older adults were drawn from studies on aging and dementia conducted through the knight alzheimer 's disease research center ( adrc ) at washington university in st . louis . based upon the clinical dementia rating ( cdr ) scale ( morris , 1993 ) participants were classified as cognitively normal ( cdr  =  0 , n  =  397 , female  =  256 ) , very mildly demented ( cdr  =  0.5 , n  =  51 , female  =  20 ) , or mildly demented ( cdr  =  1 , n  =  11 , female  =  1 ) . individuals with dementia using these diagnoses individuals whose dementia was thought to be from a non - alzheimer cause ( e.g. lewy bodies , vascular dementia , depression ) were excluded from all analyses . the population ranged in age from 42 to 90 , with a mean age of 68.5  years ( table  1 ) . all participants underwent a structural imaging session as well as positron emission tomography ( pet ) to estimate amyloid deposition using [ c ] pittsburgh compound b ( pib ) ( klunk et al . , 2004 ) . all procedures where approved by washington university 's institutional review board and were conducted in accordance with the declaration of helsinki . high - resolution t2-weighted images were acquired on a siemens trio 3  t scanner ( siemens medical systems , iselin , nj ) . scan parameters were : repetition time ( tr ) of 3200  ms , echo time ( te ) of 455 , flip angle ( fa )  =  120 , with a 256    256 field of view , and a 1  mm isotropic resolution . a trained neurologist ( s.n . ) , blind to clinical diagnosis , examined the t2-weighted images . the presence and severities of wmh were rated using criteria outlined by fazekas et al . briefly , periventricular hyperintensities ( pvwmhs ) were rated as follows : 0 absence of wmh ; 1  caps  or pencil - thin linings ; 2  halos  ; and 3 irregular pvh extending into deep white matter . ratings of wmh in the deep white matter ( dwmh ) were rated as follows : 0 absence of wmh , 1 solitary foci ; 2 the beginning aggregation of foci ; and 3 large confluent areas of wmh . examples are given in fig .  1 and distributions of scores across the three clinical groups binding potentials were calculated for multiple regions of interest ( rois ) derived from freesurfer using a cerebellar reference for regions - of - interest . the raw time activity curve for each region was adjusted by a csf dilution factor in a given voxel to yield partial volume corrected data . an average across both left and right lateral orbitofrontal , interior parietal , precuneus , rostral middle frontal , superior frontal , superior temporal , and middle temporal rois yielded the mean cortical binding potential ( mcbp ) . all analyses used mcbp as a continuous variable . as supplementary analyses , individuals were also codified as pib positive or negative using a previously published value from our center of unadjusted mcbp of 0.18 ( vlassenko et al . , 2011 ) . a second supplementary analysis defined the cutoff on partial - volume corrected mcbp data derived from a roc analysis comparing 212 cognitively normal individuals to 59 cdr  =  0.5 with an ad diagnosis . using this approach the partial - volume adjusted mcbp cutoff was determined to be .23 , which was the point that maximized the youden index ( sensitivity  +  specificity    1 ) . , individuals were also codified as pib positive or negative using a previously published value from our center of unadjusted mcbp of 0.18 ( vlassenko et al . , 2011 ) . a second supplementary analysis defined the cutoff on partial - volume corrected mcbp data derived from a roc analysis comparing 212 cognitively normal individuals to 59 cdr  =  0.5 with an ad diagnosis . using this approach the partial - volume adjusted mcbp cutoff was determined to be .23 , which was the point that maximized the youden index ( sensitivity  +  specificity    1 ) . 1 . we assessed the presence ( 1 ) or absence ( 0 ) of a history of hypertension , heart attack , atrial fibrillation , angioplasty , bypass surgery , congestive heart failure , stroke , transient ischemic attack , and diabetes . height information and weight information were used to calculate bmi , and coded for the presence or absence of obesity ( bmi  >  30 ) . an aggregate vascular risk factor was created by summing the scores of all variables ( possible range of 010 ) ( actual range 06 , mean 1.14 , median 0 ) . across the entire sample there was a modest bivariate correlation between a history of hypertension and pvwmh ( r  =  .21 , p  < .0001 ) and dwmh ( r  =  .19 , p  <  .0001 ) scores . similarly the summary vascular risk score significantly correlated with both pvwmh ( r  =  .17 , p  <  .001 ) and dwmh ( r  =  .16 , p  <  .001 ) . unsurprisingly , a history of hypertension and the vascular risk were highly correlated ( r  =  .65 , p  < initial stepwise logistic regressions examined the effects of age , gender , mcbp and a measure of white matter damage ( either dwmh or pvwmh ) . models additionally allowed for an interaction between white matter damage and mcbp to enter the model . models tested whether each predictor discriminated between cognitively normal individuals and demented individuals ( combined cdr  =  0.5 and 1 ) . for the gender variable women were coded as 0 and males as 1 . for each predictor the exponentiation of the beta coefficient ( exp(b ) ) indicates the odds ratio , or the change in relative log odds of being in the tested group ( e.g. cdr  >  0 ) relative to the reference group ( e.g. cdr  =  0 ) with a one unit change in the predictor . if the odds ratio for a given predictor ( e.g. age ) is > 1 , then an increase in the predictor indicates a greater likelihood to be in the test group ( e.g. cdr  >  0 ) . if the odds ratio is < 1 , then the outcome is more likely to be in the reference group ( e.g. cdr  =  0 ) . for all analyses an increase in the exp(b ) indicated greater cognitive impairment . an additional way to examine the data was presented by calculating the area under the curve ( auc ) values from receiver operating characteristics ( roc ) curves separating cognitively normal individuals from demented individuals . the first model looked at the auc only using the initial covariates of age and gender . a second set of models examined the auc using the covariates and then one predictor of interest ( i.e. mcbp , pvwmh , or dwmh ) . a final set of models examined the auc when using covariates , mcbp , and either of the wmh measures . significant changes in the auc were assessed using delong 's test for correlated roc curves ( delong et al . , 1988 ) using a package implemented in r ( robin et al . , 2011 ) . these analyses test whether each predictor of interest ( e.g. wmh , mcbp , age ) significantly differs between each level of the dependent variable ( cdr 0 , 0.5 , and 1 ) . the structure of these models was set to be identical to that revealed by the stepwise logistic regression comparing cognitively normal to all demented individuals . middle aged and older adults were drawn from studies on aging and dementia conducted through the knight alzheimer 's disease research center ( adrc ) at washington university in st . louis . based upon the clinical dementia rating ( cdr ) scale ( morris , 1993 ) participants were classified as cognitively normal ( cdr  =  0 , n  =  397 , female  =  256 ) , very mildly demented ( cdr  =  0.5 , n  =  51 , female  =  20 ) , or mildly demented ( cdr  =  1 , n  =  11 , female  =  1 ) . individuals with dementia using these diagnoses individuals whose dementia was thought to be from a non - alzheimer cause ( e.g. lewy bodies , vascular dementia , depression ) were excluded from all analyses . the population ranged in age from 42 to 90 , with a mean age of 68.5  years ( table  1 ) . all participants underwent a structural imaging session as well as positron emission tomography ( pet ) to estimate amyloid deposition using [ c ] pittsburgh compound b ( pib ) ( klunk et al . , 2004 ) . all procedures where approved by washington university 's institutional review board and were conducted in accordance with the declaration of helsinki . high - resolution t2-weighted images were acquired on a siemens trio 3  t scanner ( siemens medical systems , iselin , nj ) . scan parameters were : repetition time ( tr ) of 3200  ms , echo time ( te ) of 455 , flip angle ( fa )  =  120 , with a 256    256 field of view , and a 1  mm isotropic resolution . a trained neurologist ( s.n . ) , blind to clinical diagnosis , examined the t2-weighted images . the presence and severities of wmh were rated using criteria outlined by fazekas et al . briefly , periventricular hyperintensities ( pvwmhs ) were rated as follows : 0 absence of wmh ; 1  caps  or pencil - thin linings ; 2  halos  ; and 3 irregular pvh extending into deep white matter . ratings of wmh in the deep white matter ( dwmh ) were rated as follows : 0 absence of wmh , 1 solitary foci ; 2 the beginning aggregation of foci ; and 3 large confluent areas of wmh . examples are given in fig .  1 and distributions of scores across the three clinical groups the intraclass correlation was .91 for periventricular ratings and .98 for deep white matter ratings . binding potentials were calculated for multiple regions of interest ( rois ) derived from freesurfer using a cerebellar reference for regions - of - interest . the raw time activity curve for each region was adjusted by a csf dilution factor in a given voxel to yield partial volume corrected data . an average across both left and right lateral orbitofrontal , interior parietal , precuneus , rostral middle frontal , superior frontal , superior temporal , and middle temporal rois yielded the mean cortical binding potential ( mcbp ) . all analyses used mcbp as a continuous variable . as supplementary analyses , individuals were also codified as pib positive or negative using a previously published value from our center of unadjusted mcbp of 0.18 ( vlassenko et al . , 2011 ) . a second supplementary analysis defined the cutoff on partial - volume corrected mcbp data derived from a roc analysis comparing 212 cognitively normal individuals to 59 cdr  =  0.5 with an ad diagnosis . using this approach the partial - volume adjusted mcbp cutoff was determined to be .23 , which was the point that maximized the youden index ( sensitivity  +  specificity    1 ) . , individuals were also codified as pib positive or negative using a previously published value from our center of unadjusted mcbp of 0.18 ( vlassenko et al . , 2011 ) . a second supplementary analysis defined the cutoff on partial - volume corrected mcbp data derived from a roc analysis comparing 212 cognitively normal individuals to 59 cdr  =  0.5 with an ad diagnosis . using this approach the partial - volume adjusted mcbp cutoff was determined to be .23 , which was the point that maximized the youden index ( sensitivity  +  specificity    1 ) . we assessed the presence ( 1 ) or absence ( 0 ) of a history of hypertension , heart attack , atrial fibrillation , angioplasty , bypass surgery , congestive heart failure , stroke , transient ischemic attack , and diabetes . height information and weight information were used to calculate bmi , and coded for the presence or absence of obesity ( bmi  >  30 ) . an aggregate vascular risk factor was created by summing the scores of all variables ( possible range of 010 ) ( actual range 06 , mean 1.14 , median 0 ) . across the entire sample there was a modest bivariate correlation between a history of hypertension and pvwmh ( r  =  .21 , p  <  .0001 ) and dwmh ( r  =  .19 , p  <  .0001 ) scores . similarly the summary vascular risk score significantly correlated with both pvwmh ( r  =  .17 , p  <  .001 ) and dwmh ( r  =  .16 , p  <  .001 ) . unsurprisingly , a history of hypertension and the vascular risk were highly correlated ( r  =  .65 , p  <  .00001 ) . initial stepwise logistic regressions examined the effects of age , gender , mcbp and a measure of white matter damage ( either dwmh or pvwmh ) . models additionally allowed for an interaction between white matter damage and mcbp to enter the model . models tested whether each predictor discriminated between cognitively normal individuals and demented individuals ( combined cdr  =  0.5 and 1 ) . for the gender variable women were coded as 0 and males as 1 . for each predictor the exponentiation of the beta coefficient ( exp(b ) ) indicates the odds ratio , or the change in relative log odds of being in the tested group ( e.g. cdr  >  0 ) relative to the reference group ( e.g. cdr  =  0 ) with a one unit change in the predictor . if the odds ratio for a given predictor ( e.g. age ) is > 1 , then an increase in the predictor indicates a greater likelihood to be in the test group ( e.g. cdr  >  0 ) . if the odds ratio is < 1 , then the outcome is more likely to be in the reference group ( e.g. cdr  =  0 ) . for all analyses an increase in the exp(b ) indicated greater cognitive impairment . an additional way to examine the data was presented by calculating the area under the curve ( auc ) values from receiver operating characteristics ( roc ) curves separating cognitively normal individuals from demented individuals . the first model looked at the auc only using the initial covariates of age and gender . a second set of models examined the auc using the covariates and then one predictor of interest ( i.e. mcbp , pvwmh , or dwmh ) . a final set of models examined the auc when using covariates , mcbp , and either of the wmh measures . significant changes in the auc were assessed using delong 's test for correlated roc curves ( delong et al . , 1988 ) using a package implemented in r ( robin et al . , 2011 ) . these analyses test whether each predictor of interest ( e.g. wmh , mcbp , age ) significantly differs between each level of the dependent variable ( cdr 0 , 0.5 , and 1 ) . the structure of these models was set to be identical to that revealed by the stepwise logistic regression comparing cognitively normal to all demented individuals . there were more males in the cdr 0.5 (   =  12.2 , p  <  .0005 ) and cdr 1 (   =  14.1 , p  <  .0005 ) groups relative to cdr 0 . compared to cdr 0 individuals , cdr 0.5 individuals were older ( t  =  7.0 , p  <  .000001 ) , had lower mmse ( 13.2 , p  <  .000001 ) , greater mcbp ( t  =  8.3 , p  < .00001 ) , and a greater proportion of pib+ individuals (   =  45.2 , p  <  .000001 ) . similarly relative to cdr 0 individuals those with a cdr  =  1 were older ( t  =  3.81 , p  <  .001 ) , had lower mmse ( 18.9 , p  < .00001 ) , and a greater proportion of pib+ individuals (   =  22.7 , p  <  .000005 ) . cdr 1 individuals had lower mmse than cdr 0.5 individuals but did not significantly differ in any other way . as age and gender differed across groups , they were considered as covariates when examining the effects of wmh and amyloid on cognition . the full results from the initial logistic regressions are presented in table  2 . for all significant effects , an increase in the odds ratio for the measure of interest ( e.g. age ) indicated a greater likelihood of being cognitively impaired . when examining mcbp alongside pvwmh there was a significant effect of age ( exp(b ) 1.08 , p  <  0.001 ) , gender ( exp(b ) 3.50 , p  <  0.001 ) , mcbp ( exp(b ) 3.68 , p  <  0.0001 ) , and pvwhm ( exp(b ) 2.03 , p  <  0.01 ) . when examining mcbp alongside dwmh there was a significant effect of age ( exp(b ) 1.10 , p  <  0.001 ) , gender ( exp(b ) 3.60 , p  <  0.001 ) , mcbp ( exp(b ) 3.63 , p  <  0.0001 ) , and dwmh ( exp(b ) 1.52 , p  <  0.05 ) . the interaction terms between mcbp and wmh were non - significant and not entered into either model . 2 , which depicts the distribution of the fazekas scores for periventricular white matter hyperintensities ( pvwmhs ) and deep white matter hyperintensities ( dwmhs ) across the three groups . treating amyloid deposition as a dichotomous pib+/ variable did not substantively change the models ( supplementary tables  1 and 2 ) . it is possible to gain a bit more understanding of the size of these effects by calculating the roc auc . when predicting dementia status solely from the covariates ( age and gender ) the auc is .831 . when adding mcbp to the model the auc significantly increased to .875 ( z  =  2.41 , there were non - significant increases in the auc when adding only the pvwmh ( auc.849 , z  =  1.34 , p  =  .18 ) or dwmh ( auc  =  .836 , z  =  .5242 , p  =  .60 ) to the covariate only model . including both mcbp and pvwmh led to an auc of .886 ( z  =  2.63 , p  <  .01 ) and auc of .876 when using mcbp dwmh ( z  =  2.26 , p  =  < while significant relative to the covariate only models , the increase in auc in the models combining mcbp and wmh was not significantly different from models considering mcbp alone . combined with the results from the logistic regressions , this suggests only modest effects of wmh above amyloid deposition . the full results from the multinomial logistic regressions are presented in tables  3 and 4 . these results are quite similar to the logistic regressions above when comparing cognitively normal individuals to either group of demented individuals . when contrasting those with very mild dementia ( cdr 0.5 ) to those with mild dementia ( cdr 1 ) there were no significant effects , although gender , mcbp , and dwmh demonstrated modest trends . as wmh are thought to be vascular in nature ( breteler et al . , 1994 ) , we additionally examined the initial models predicting dementia status with mcbp and measures of wmh while including a history of hypertension , or an aggregate vascular risk factor in the model . a history of hypertension was not significant in either model ( pvwmh or dwmh , see table  5 ) and only slightly lowered the contributions of wmh to the model , but such effects were still significant . the aggregate vascular risk factor was significant in both models , but again the effects on the wmh scores were minor ( table  6 ) . there were more males in the cdr 0.5 (   =  12.2 , p  <  .0005 ) and cdr 1 (   =  14.1 , p  <  .0005 ) groups relative to cdr 0 . compared to cdr 0 individuals , cdr 0.5 individuals were older ( t  =  7.0 , p  <  .000001 ) , had lower mmse ( 13.2 , p  <  .000001 ) , greater mcbp ( t  =  8.3 , p  < .00001 ) , and a greater proportion of pib+ individuals (   =  45.2 , p  <  .000001 ) . similarly relative to cdr 0 individuals those with a cdr  =  1 were older ( t  =  3.81 , p  <  .001 ) , had lower mmse ( 18.9 , p  < .00001 ) , and a greater proportion of pib+ individuals (   =  22.7 , p  <  .000005 ) . cdr 1 individuals had lower mmse than cdr 0.5 individuals but did not significantly differ in any other way . as age and gender differed across groups , they were considered as covariates when examining the effects of wmh and amyloid on cognition . the full results from the initial logistic regressions are presented in table  2 . for all significant effects , an increase in the odds ratio for the measure of interest ( e.g. age ) indicated a greater likelihood of being cognitively impaired . when examining mcbp alongside pvwmh there was a significant effect of age ( exp(b ) 1.08 , p  <  0.001 ) , gender ( exp(b ) 3.50 , p  <  0.001 ) , mcbp ( exp(b ) 3.68 , p  <  0.0001 ) , and pvwhm ( exp(b ) 2.03 , p  <  0.01 ) . when examining mcbp alongside dwmh there was a significant effect of age ( exp(b ) 1.10 , p  <  0.001 ) , gender ( exp(b ) 3.60 , p  <  0.001 ) , mcbp ( exp(b ) 3.63 , p  <  0.0001 ) , and dwmh ( exp(b ) 1.52 , p  <  0.05 ) . the interaction terms between mcbp and wmh were non - significant and not entered into either model . 2 , which depicts the distribution of the fazekas scores for periventricular white matter hyperintensities ( pvwmhs ) and deep white matter hyperintensities ( dwmhs ) across the three groups . treating amyloid deposition as a dichotomous pib+/ variable did not substantively change the models ( supplementary tables  1 and 2 ) . it is possible to gain a bit more understanding of the size of these effects by calculating the roc auc . when predicting dementia status solely from the covariates ( age and gender ) the auc is .831 . when adding mcbp to the model the auc significantly increased to .875 ( z  =  2.41 , p  < there were non - significant increases in the auc when adding only the pvwmh ( auc.849 , z  =  1.34 , p  =  .18 ) or dwmh ( auc  =  .836 , z  =  .5242 , p  =  .60 ) to the covariate only model . including both mcbp and pvwmh led to an auc of .886 ( z  =  2.63 , p  <  .01 ) and auc of .876 when using mcbp dwmh ( z  =  2.26 , p  =  <  .05 ) . while significant relative to the covariate only models , the increase in auc in the models combining mcbp and wmh was not significantly different from models considering mcbp alone combined with the results from the logistic regressions , this suggests only modest effects of wmh above amyloid deposition . the full results from the multinomial logistic regressions are presented in tables  3 and 4 . these results are quite similar to the logistic regressions above when comparing cognitively normal individuals to either group of demented individuals . when contrasting those with very mild dementia ( cdr 0.5 ) to those with mild dementia ( cdr 1 ) there were no significant effects , although gender , mcbp , and dwmh demonstrated modest trends . as wmh are thought to be vascular in nature ( breteler et al . , 1994 ) , we additionally examined the initial models predicting dementia status with mcbp and measures of wmh while including a history of hypertension , or an aggregate vascular risk factor in the model . a history of hypertension was not significant in either model ( pvwmh or dwmh , see table  5 ) and only slightly lowered the contributions of wmh to the model , but such effects were still significant . the aggregate vascular risk factor was significant in both models , but again the effects on the wmh scores were minor ( table  6 ) . in the current analyses we examined whether measures of amyloid deposition and white matter damage predict cognitive impairment . we found that both amyloid burden , estimated by pib mcbp , as well as measures of wmh independently discriminate between cognitively normal individuals and those with very mild or mild dementia . this is unsurprising as the correlation between ratings of dwmh and pvwmh lesions was .58 ( p the fazekas visual rating of white matter disease was associated with a greater risk of ad . this can clearly been seen in how the distribution of the fazekas scores shifts across groups in fig .  2 . individuals who are cognitively normal have highly right skewed distributions , with the vast majority of individuals having no observable white matter damage . as dementia severity increases , the scores become more and more left skewed as higher proportions of the population accrue white matter damage . although the graphs in fig . 2 suggest differences between cdr  =  0.5 and 1 individuals the effects were not statistically significant . this is most likely due to the modest sample size of mildly demented subjects ( cdr  =  1 , n  =  11 ) . alternatively these markers may possess nonlinear trajectories that do not significantly differ across graded levels of dementia severity . in our cohort all of the individuals with a cdr  =  1 had a primary clinical diagnosis of dementia of the alzheimer 's type at baseline . of the 51 individuals with a cdr rating of 0.5 , 21 had a dat diagnosis at baseline and 14 received a diagnosis at a later clinical point . along with the high levels of amyloid deposition , this would suggest that the majority of the impaired cohort are representative of an ad trajectory . there were no significant differences in age , gender composition , or severity of white matter damage between those with and without an ad diagnosis . this suggests that the white matter effects are not being driven by a small subsample of individuals who are demented but are not on an ad trajectory . many healthy older adults show elevated levels of amyloid without significant cognitive impairment ( arriagada et al . , 1992 ) . additionally there are numerous risk factors for a clinical diagnosis of ad including a family history of ad ( breitner et al . , 1988 ) , the apoe 4 genotype ( corder et al . , 1993 ) , head trauma ( mortimer et al . , 1985 ) , and diabetes ( luchsinger et al . , 2001 ) . the additive effects in our study of whm and pib deposition are consistent with a broader view of ad that suggests that multiple factors can influence substantial cognitive decline and dementia . for example after head trauma there is a deposition of a in the cortex , and this deposition is increased in individuals with the apoe 4 genotype ( mayeux et al . , 1995 ) . the results of our analyses are consistent with a large body of prior work linking white matter damage with impaired cognition ( bozzali et al . , 2002 ; , 2010 ; frisoni et al . , 2007 ; head et al . , 2004 ; prins et al . , 2004 ) . an increased prevalence of white matter damage is thought to be mainly vascular in nature , as hypertension , stroke , and diabetes all lead to increases in white matter lesions ( debette and markus , 2010 ; pico et al . there were modest correlations ( rs  <  .2 ) between measures of vascular health and wmh . further an aggregate measure of vascular risk was itself predictive of dementia status above the effects of amyloid deposition and wmh . however measures of wmh were still predictive of dementia status after including vascular risk as a covariate . this may be due to the fact that our measures of vascular health are imperfect as they are derived from self - report and do not account for medication usage . although the examinations presented here indicated unique statistical effects of age , mcbp , and wmh this does not necessarily mean that the biological processes these values represent are truly orthogonal processes . one of the greatest challenges facing ongoing studies of ad is how to tease apart the contributions of comorbid pathologies . large cohort studies are just now reaching the point to investigate modifiers ( e.g. cardiovascular health , stroke , diabetes , head trauma ) of longitudinal ad biomarker trajectories . individuals suffering from autosomal dominant ad become demented at a much earlier age than those with sporadic ad . due to the young age of onset of clinical symptoms , this population may provide greater insight into the relationship between white matter damage and ad removed from age - related comorbidities such as cardiovascular health . the current work demonstrates a significant relationship between both levels of amyloid deposition and white matter damage on cognition . the sample contained only a modest number of mildly demented individuals ( cdr  =  1 ) , limiting our ability to detect differences with progressive increases in dementia severity . as commonly done in the literature , our visual ratings were made on t2-weighted sequences , although more precise measures may have been obtained using a more optimal sequence ( e.g. flair ) . additionally , although visual ratings of wmh such as the fazekas rating scale have a clear utility , they do not provide the fine - grained detail as would be obtained from a quantification of wmh volume . finally , although the fazekas scale separates lesions into periventricular and deep white matter scores , three - dimensional renderings of typical lesions suggest that such lesions are part of the same process rather than representing disparate effects . the work presented here demonstrated the detrimental influences of advancing age , amyloid deposition in the brain , and white matter damage . these factors independently discriminated healthy controls from very mildly and mildly demented individuals . from a clinical standpoint , this suggests that easily available radiological measures of white matter health could be an asset in disease diagnosis in addition to psychometric testing and ad biomarkers such as amyloid imaging . 1distributions of unadjusted mean cortical binding potentials in cognitively normal ( left ) and demented ( right ) participants . distributions of unadjusted mean cortical binding potentials in cognitively normal ( left ) and demented ( right ) participants .
background and purposeelevated levels of amyloid deposition as well as white matter damage are thought to be risk factors for alzheimer disease ( ad ) . 
 here we examined whether qualitative ratings of white matter damage predicted cognitive impairment beyond measures of amyloid.materials and methodsthe study examined 397 cognitively normal , 51 very mildly demented , and 11 mildly demented individuals aged 4290 ( mean 68.5 ) . 
 participants obtained a t2-weighted scan as well as a positron emission tomography scan using 11[c ] pittsburgh compound b. periventricular white matter hyperintensities ( pvwmhs ) and deep white matter hyperintensities ( dwmhs ) were measured on each t2 scan using the fazekas rating scale . 
 the effects of amyloid deposition and white matter damage were assessed using logistic regressions.resultslevels of amyloid deposition ( ps  <  0.01 ) , as well as ratings of pvwmh ( p  <  0.01 ) and dwmh ( p  <  0.05 ) discriminated between cognitively normal and demented individuals.conclusionsthe amount of amyloid deposition and white matter damage independently predicts cognitive impairment . 
 this suggests a diagnostic utility of qualitative white matter scales in addition to measuring amyloid levels .