[Skip to Navigation]
Sign In
Table 1. Study Sample Characteristics by hsCRP Tertilea
Study Sample Characteristics by hsCRP Tertilea
Table 2. Logistic Regression Models of hsCRP and Impairment by Cognitive Scores
Logistic Regression Models of hsCRP and Impairment by Cognitive Scores
Table 3. Logistic Regression Models of hsCRP, APOE ε4, and Impairment
Logistic Regression Models of hsCRP, APOE ε4, and Impairment
1.
Craft  S Insulin resistance syndrome and Alzheimer's disease: age- and obesity-related effects on memory, amyloid, and inflammation.  Neurobiol Aging 2005;26 ((suppl 1)) 65- 69PubMedGoogle ScholarCrossref
2.
de Luca  COlefsky  JM Inflammation and insulin resistance.  FEBS Lett 2008;582 (1) 97- 105PubMedGoogle ScholarCrossref
3.
Singer  GGranger  DN Inflammatory responses underlying the microvascular dysfunction associated with obesity and insulin resistance.  Microcirculation 2007;14 (4-5) 375- 387PubMedGoogle ScholarCrossref
4.
Yanbaeva  DGDentener  MACreutzberg  ECWesseling  GWouters  EF Systemic effects of smoking.  Chest 2007;131 (5) 1557- 1566PubMedGoogle ScholarCrossref
5.
Ridker  PMRifai  NRose  LBuring  JECook  NR Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events.  N Engl J Med 2002;347 (20) 1557- 1565PubMedGoogle ScholarCrossref
6.
Rost  NSWolf  PAKase  CS  et al.  Plasma concentration of C-reactive protein and risk of ischemic stroke and transient ischemic attack: the Framingham study.  Stroke 2001;32 (11) 2575- 2579PubMedGoogle ScholarCrossref
7.
Elkind  MSTai  WCoates  KPaik  MCSacco  RL High-sensitivity C-reactive protein, lipoprotein-associated phospholipase A2, and outcome after ischemic stroke.  Arch Intern Med 2006;166 (19) 2073- 2080PubMedGoogle ScholarCrossref
8.
Ridker  PM High-sensitivity C-reactive protein, inflammation, and cardiovascular risk: from concept to clinical practice to clinical benefit.  Am Heart J 2004;148 (1) ((suppl 1)) S19- S26Google ScholarCrossref
9.
Luchsinger  JAMayeux  R Cardiovascular risk factors and Alzheimer's disease.  Curr Atheroscler Rep 2004;6 (4) 261- 266PubMedGoogle ScholarCrossref
10.
Gupta  APansari  K Inflammation and Alzheimer's disease.  Int J Clin Pract 2003;57 (1) 36- 39PubMedGoogle Scholar
11.
Frank  RAGalasko  DHampel  H  et al. National Institute on Aging Biological Markers Working Group, Biological markers for therapeutic trials in Alzheimer's disease. Proceedings of the biological markers working group; NIA initiative on neuroimaging in Alzheimer's disease.  Neurobiol Aging 2003;24 (4) 521- 536PubMedGoogle ScholarCrossref
12.
Tang  MXCross  PAndrews  H  et al.  Incidence of Alzheimer's disease in African-Americans, Caribbean Hispanics and Caucasians in northern Manhattan.  Neurology 2001;5649- 56Google ScholarCrossref
13.
US Census Bureau, Census of Population and Housing Summary Tape File 1, Technical Documentation.  Washington, DC US Census Bureau1991;
14.
Hixson  JEVernier  DT Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI.  J Lipid Res 1990;31 (3) 545- 548PubMedGoogle Scholar
15.
Mayeux  ROttman  RMaestre  G  et al.  Synergistic effects of traumatic head injury and apolipoprotein-epsilon 4 in patients with Alzheimer's disease.  Neurology 1995;45 (3, pt 1) 555- 557PubMedGoogle ScholarCrossref
16.
Luchsinger  JAReitz  CHonig  LSTang  MXShea  SMayeux  R Aggregation of vascular risk factors and risk of incident Alzheimer disease.  Neurology 2005;65 (4) 545- 551Google ScholarCrossref
17.
Chobanian  AVBakris  GLBlack  HR  et al. National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee, The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report [see comment] [erratum in JAMA. 2003;290(2):197].  JAMA 2003;289 (19) 2560- 2572PubMedGoogle ScholarCrossref
18.
Hatano  S Experience from a multicentre stroke register: a preliminary report.  Bull World Health Organ 1976;54 (5) 541- 553PubMedGoogle Scholar
19.
Buschke  HFuld  PA Evaluating storage, retention, and retrieval in disordered memory and learning.  Neurology 1974;24 (11) 1019- 1025PubMedGoogle ScholarCrossref
20.
Benton  AL The Visual Retention Test.  New York, NY The Psychological Corporation1955;
21.
Benton  AL Revised Visual Retention Test. 4th New York, NY Psychological Corporation1974;
22.
Rosen  W The Rosen Drawing Test.  Odessa, FL Psychological Assessment Resources1981;
23.
Benton  A The Visual Retention Test.  New York, NY The Psychological Corporation1955;
24.
Kaplan  EGoodglass  HWeintraub  S Boston Naming Test.  Philadelphia, PA Lea & Febiger1983;
25.
Benton  ALHamsher  K Multilingual Aphasia Examination.  Iowa City, IA AJA Associates, Inc1983;
26.
Goodglass  HKaplan  D The Assessment of Aphasia and Related Disorders. 2nd Philadelphia, PA Lea and Febiger1983;
27.
D'Elia  LFSatz  PUchiyama  CLWhite  T Color Trails Test Professional Manual.  Odessa, FL Psychological Assessment Resources1994;
28.
Wechsler  D Wechsler Adult Intelligence Scale-Revised.  New York, NY The Psychological Corporation1981;
29.
Sliwinski  MLipton  RBBuschke  HStewart  W The effects of preclinical dementia on estimates of normal cognitive functioning in aging.  J Gerontol B Psychol Sci Soc Sci 1996;51 (4) 217- 225PubMedGoogle ScholarCrossref
30.
Manly  JJBell-McGinty  STang  MXSchupf  NStern  YMayeux  R Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community.  Arch Neurol 2005;62 (11) 1739- 1746PubMedGoogle ScholarCrossref
31.
Heaton  RKGrant  IMatthews  CG Comprehensive Norms for an Expanded Halstead-Reitan Battery.  Odessa, FL Psychological Assessment Resources Inc1991;
32.
Petersen  RCDoody  RKurz  A  et al.  Current concepts in mild cognitive impairment.  Arch Neurol 2001;58 (12) 1985- 1992PubMedGoogle ScholarCrossref
33.
Libby  PRidker  PM Inflammation and atherosclerosis: role of C-Reactive protein in risk assessment.  Am J Med 2004;116 ((suppl 6A)) 9S- 16SPubMedGoogle ScholarCrossref
34.
Bonetti  POLerman  LOLerman  A Endothelial dysfunction: a marker of atherosclerotic risk.  Arterioscler Thromb Vasc Biol 2003;23 (2) 168- 175PubMedGoogle ScholarCrossref
35.
Lerman  AZeiher  AM Endothelial function: cardiac events.  Circulation 2005;111 (3) 363- 368PubMedGoogle ScholarCrossref
36.
Hoth  KFTate  DFPoppas  A  et al.  Endothelial function and white matter hyperintensities in older adults with cardiovascular disease.  Stroke 2007;38 (2) 308- 312PubMedGoogle ScholarCrossref
37.
Markus  HSHunt  BPalmer  KEnzinger  CSchmidt  HSchmidt  R Markers of endothelial and hemostatic activation and progression of cerebral white matter hyperintensities: longitudinal results of the Austrian Stroke Prevention Study.  Stroke 2005;36 (7) 1410- 1414PubMedGoogle ScholarCrossref
38.
Vicenzini  ERicciardi  MCAltieri  M  et al.  Cerebrovascular reactivity in degenerative and vascular dementia: a transcranial Doppler study.  Eur Neurol 2007;58 (2) 84- 89PubMedGoogle Scholar
39.
Silvestrini  MPasqualetti  PBaruffaldi  R  et al.  Cerebrovascular reactivity and cognitive decline in patients with Alzheimer disease.  Stroke 2006;37 (4) 1010- 1015PubMedGoogle ScholarCrossref
40.
Lavi  SGaitini  DMilloul  VJacob  G Impaired cerebral CO2 vasoreactivity: association with endothelial dysfunction.  Am J Physiol Heart Circ Physiol 2006;291 (4) H1856- H1861PubMedGoogle ScholarCrossref
41.
Novak  VLast  DAlsop  DC  et al.  Cerebral blood flow velocity and periventricular white matter hyperintensities in type 2 diabetes.  Diabetes Care 2006;29 (7) 1529- 1534PubMedGoogle ScholarCrossref
42.
Semmler  AOkulla  TSastre  MDumitrescu-Ozimek  LHeneka  MT Systemic inflammation induces apoptosis with variable vulnerability of different brain regions.  J Chem Neuroanat 2005;30 (2-3) 144- 157PubMedGoogle ScholarCrossref
43.
Perry  VHCunningham  CHolmes  C Systemic infections and inflammation affect chronic neurodegeneration.  Nat Rev Immunol 2007;7 (2) 161- 167PubMedGoogle ScholarCrossref
44.
Schunkert  HSamani  NJ Elevated C-reactive protein in atherosclerosis: chicken or egg?  N Engl J Med 2008;359 (18) 1953- 1955PubMedGoogle ScholarCrossref
45.
Zacho  JTybjaerg-Hansen  AJensen  JSGrande  PSillesen  HNordestgaard  BG Genetically elevated C-reactive protein and ischemic vascular disease.  N Engl J Med 2008;359 (18) 1897- 1908PubMedGoogle ScholarCrossref
46.
Pugh  KGLipsitz  LA The microvascular frontal-subcortical syndrome of aging.  Neurobiol Aging 2002;23 (3) 421- 431PubMedGoogle ScholarCrossref
47.
O'Brien  JTErkinjuntti  TReisberg  B  et al.  Vascular cognitive impairment.  Lancet Neurol 2003;2 (2) 89- 98PubMedGoogle ScholarCrossref
48.
Yaffe  KKanaya  ALindquist  K  et al.  The metabolic syndrome, inflammation, and risk of cognitive decline.  JAMA 2004;292 (18) 2237- 2242PubMedGoogle ScholarCrossref
49.
Yaffe  KLindquist  KPenninx  BW  et al.  Inflammatory markers and cognition in well-functioning African-American and white elders.  Neurology 2003;61 (1) 76- 80PubMedGoogle ScholarCrossref
50.
Tan  ZSBeiser  ASVasan  RS  et al.  Inflammatory markers and the risk of Alzheimer disease: the Framingham Study.  Neurology 2007;68 (22) 1902- 1908PubMedGoogle ScholarCrossref
51.
Schram  MTEuser  SMde Craen  AJ  et al.  Systemic markers of inflammation and cognitive decline in old age.  J Am Geriatr Soc 2007;55 (5) 708- 716PubMedGoogle ScholarCrossref
52.
Ravaglia  GForti  PMaioli  F  et al.  Blood inflammatory markers and risk of dementia: The Conselice Study of Brain Aging.  Neurobiol Aging 2007;28 (12) 1810- 1820PubMedGoogle ScholarCrossref
53.
Engelhart  MJGeerlings  MIMeijer  J  et al.  Inflammatory proteins in plasma and the risk of dementia: the Rotterdam Study.  Arch Neurol 2004;61 (5) 668- 672PubMedGoogle ScholarCrossref
54.
Dik  MGJonker  CHack  CESmit  JHComijs  HCEikelenboom  P Serum inflammatory proteins and cognitive decline in older persons.  Neurology 2005;64 (8) 1371- 1377PubMedGoogle ScholarCrossref
55.
Weuve  JRidker  PMCook  NRBuring  JEGrodstein  F High-sensitivity C-reactive protein and cognitive function in older women.  Epidemiology 2006;17 (2) 183- 189PubMedGoogle ScholarCrossref
56.
Jordanova  VStewart  RDavies  ESherwood  RPrince  M Markers of inflammation and cognitive decline in an African-Caribbean population.  Int J Geriatr Psychiatry 2007;22 (10) 966- 973PubMedGoogle ScholarCrossref
57.
Laurin  DDavid Curb  JMasaki  KHWhite  LRLauner  LJ Midlife C-reactive protein and risk of cognitive decline: a 31-year follow-up.  Neurobiol Aging 2009;30 (11) 1724- 1727PubMedGoogle ScholarCrossref
58.
Haan  MNAiello  AEWest  NAJagust  WJ C-reactive protein and rate of dementia in carriers and non carriers of Apolipoprotein APOE4 genotype.  Neurobiol Aging 2008;29 (12) 1774- 1782PubMedGoogle ScholarCrossref
Original Contribution
January 2010

Association of C-Reactive Protein With Cognitive Impairment

Author Affiliations

Author Affiliations: Gertrude H. Sergievsky Center, Columbia University (Drs Noble, Manly, Schupf, Tang, Mayeux, and Luchsinger); Taub Institute for Research of Alzheimer's Disease and the Aging Brain, Columbia University (Drs Noble, Manly, Schupf, Mayeux, and Luchsinger); Departments of Neurology (Drs Noble and Mayeux) and Psychiatry (Dr Mayeux), and Division of General Medicine, Department of Medicine (Dr Luchsinger), Columbia University College of Physicians and Surgeons; and Departments of Epidemiology (Drs Schupf, Mayeux, and Luchsinger) and Biostatistics (Dr Tang), Joseph P. Mailman School of Public Health, Columbia University, New York, New York.

Arch Neurol. 2010;67(1):87-92. doi:10.1001/archneurol.2009.308
Abstract

Background  High-sensitivity C-reactive protein (hsCRP) is a biomarker of cardiovascular risk that is suggested to be a biomarker for cognitive impairment.

Objective  To explore the association between hsCRP and cognitive impairment.

Design  Cross-sectional analysis of a population-based community aging study.

Setting  Northern Manhattan, New York, New York.

Other Participants  One thousand three hundred thirty-one participants from a longitudinal study of aging without dementia and with available hsCRP and neuropsychological testing data at baseline.

Main Outcome Measures  Four cognitive scores (memory, visuospatial, executive, and language impairment) derived from a neuropsychological battery. Cognitive impairment was defined by scores below 1.5 SDs of demographically corrected means.

Results  Participants in the highest hsCRP tertile had higher adjusted odds of impaired memory (odds ratio [OR], 1.5; 95% confidence interval [CI], 1.0-2.1; P = .03) than participants in the lowest tertile. Subjects in the highest hsCRP tertile also had greater odds of visuospatial impairment (OR, 1.6; 95% CI, 1.0-2.3; P = .03). Higher hsCRP was not associated with executive or language impairment. Persons with at least 1 APOE ε4 allele and hsCRP in the highest tertile had the greatest odds of impaired memory (OR, 2.7; 95% CI, 1.6-4.4).

Conclusions  High hsCRP may be a marker of memory and visuospatial impairment in the elderly. The role of APOE ε4 requires further exploration.

Creactive protein (CRP) is known to be elevated in those with risk factors common to stroke and dementia, including diabetes,1,2 obesity,3 and smoking,4 and is associated with adverse risk of cardiovascular disease,5 increased risk of primary stroke,6 and increased stroke severity.7 High-sensitivity CRP (hsCRP) is increasingly used in clinical practice as a marker of cardiovascular risk and to guide therapy.8 Cardiovascular disease9 and inflammation may also be important in Alzheimer disease,10 and hsCRP has been suggested to be an Alzheimer disease biomarker.11 We sought to investigate the cross-sectional association between hsCRP and impairment in specific cognitive domains among a multiethnic nondemented elderly population in northern Manhattan.

Methods
Subjects

The source sample was 2776 participants from a prospective study of aging and dementia in Medicare-eligible northern Manhattan residents aged 65 years and older (Washington/Hamilton Heights-Inwood Columbia Aging Project [WHICAP] II). The WHICAP II cohort represents a combination of continuing members of a cohort originally recruited in 1992 (WHICAP I; n = 602) and members of a new cohort recruited between 1999 and 2001 (n = 2174). The sampling strategies and recruitment outcomes of these 2 cohorts have been described in detail elsewhere.12 The population from which participants were drawn is composed of individuals from 3 broadly defined ethnic categories (ie, Hispanic, African American, and white). Participants have been followed up at approximately 18-month intervals with similar assessments at each interval. Ethnic group was determined by self-report using the format of the 2000 US Census.13 All individuals were first asked to report their race (ie, American Indian/Alaska Native, Asian, Native Hawaiian or other Pacific Islander, black or African American, or white), then, in a second question, were asked whether or not they were Hispanic. Recruitment, informed consent, and study procedures were approved by the institutional review boards of Columbia Presbyterian Medical Center and Columbia University Health Sciences and the New York State Psychiatric Institute.

High-sensitivity CRP was measured in 2008 in frozen plasma obtained in 1999-2001 in the WHICAP II baseline examination. Participants without prevalent dementia at baseline and at least 1 follow-up examination were chosen. Of the total 2776 participants, 356 were excluded owing to prevalent dementia, 544 were excluded owing to lack of follow-up, and 542 were excluded for lack of a frozen plasma sample; hsCRP was measured in 1352 persons. The group with hsCRP measurements was younger than those excluded, had a lower proportion of women than those with prevalent dementia and without blood measurements, had a higher proportion of white individuals than those with prevalent dementia, had a lower proportion of black individuals than those without blood measurements, and had a lower proportion of Hispanic individuals than those with prevalent dementia (eTable 1). Of the 1352 persons with hsCRP measured, 1330 had sufficient information for memory scores, 1328 had sufficient information for visuospatial scores, 1331 had sufficient information for language and executive scores, 906 had sufficient information for Color Trails Test 1, and 854 had sufficient information for Color Trails Test 2.

MEASUREMENT OF hsCRP AND OTHER COVARIATES

C-reactive protein was measured with an ultra-sensitive enzyme-linked immunosorbent assay. Sociodemographic covariates included age, sex, race/ethnicity using the format of the 1990 census (subjects were categorized as Hispanic, white, or black), and education (recorded as a continuous variable and categorized for the purposes of these analyses as 0-6, 7-12, 13-16, and >16 years of education).13APOE genotypes were determined as described by Hixson and Vernier14 with slight modification.15 We classified persons by the presence (homozygous or heterozygous) or absence of the APOE ε4 allele.

Vascular risk factors have been found to be predictors of cognitive impairment in our cohort.16 Thus, we included them as covariates. Vascular covariates included type 2 diabetes, hypertension, heart disease, stroke, smoking, and use of lipid-lowering medications. Determination of the presence of diabetes was based on self-report or by medications indicated for the treatment of diabetes. Hypertension was also based on self-report or medication use, but also on blood pressure measurements. Based on standardized criteria,17 hypertension was defined by a systolic blood pressure greater than 140 mm Hg or diastolic blood pressure greater than 90 mm Hg. Blood pressure measurements did not significantly affect the predictive value over self-report, and results included in this study only reflect self-report and/or medication use. Heart disease was defined by a history of atrial fibrillation or other arrhythmias, coronary artery disease including myocardial infarction or angina pectoris, or congestive heart failure. Stroke was defined according to the World Health Organization criteria18 and was based on questioning of the participant or relatives, supplemented by a neurological examination or review of medical records. Smoking was also determined by self-report, and individuals were classified as current smokers, former smokers, or nonsmokers. Lipid-lowering medications significantly reduce hsCRP.5 Thus, we included them as a covariate. The use of lipid-lowering medications was based on self-report or review of medications.

Cognitive measures

Learning and memory were assessed with the Selective Reminding Test,19 including delayed recall and delayed recognition, and with recognition from the Benton Visual Retention Test.20,21 Visuospatial ability was assessed with the Rosen Drawing Test22 and the Benton Visual Retention Test–Matching.23 Language was assessed with the Boston Naming Test,24 the Controlled Oral Word Association Test,25 and Category Fluency Test.26 Psychomotor speed was assessed with the Color Trails Test 1.27 Executive Functioning was assessed with the Similarities subtest from the Wechsler Adult Intelligence Scale–Revised28 and the Color Trails Test 2.

The normative sample used to define cognitive impairment was selected from participants recruited in 1992 and 1999 by means of the robust norms approach.29 Details of the normative sample are published elsewhere.30 Demographically corrected T scores were developed on the basis of the Heaton et al31 regression method. Influences of age, years of education, race/ethnicity, and sex on each cognitive test score were assessed by performing multiple linear regression analyses. Racial/ethnic group and language (ie, Spanish vs English) were highly related, since most of the Hispanic individuals were tested in Spanish and all of the white and African American individuals were tested in English; therefore, we did not add language into the model. Each of the 4 cognitive domain scores were included as dependent variables: memory (average composite of total raw scores for immediate recall and delayed recall from the Selective Reminding Test and Benton Visual Retention Test–Recognition); language (average composite of total correct responses on the 15-item Boston Naming Test, number of phrases correctly produced on the Boston Diagnostic Aphasia Examination repetition, and number of correct responses on Boston Diagnostic Aphasia Examination comprehension); executive function (average composite of total correct responses on the Mattis Identities and Oddities test, raw score on the Wechsler Adult Intelligence Scale–Revised Similarities subtest, and mean number of words generated during three 60-second trials for category and letter fluency); and visuospatial skill (average composite of number correct on the Rosen Drawing Test and Benton Visual Retention Test–Matching). Continuous predictors were age and years of education. Sex was a categorical predictor, as was racial/ethnic classification. For each of the 4 regression analyses, we first included all 4 predictors in the model, retaining only the variables that significantly contributed to prediction of cognitive test score. The β weights of each of these predictors in the final model as well as the standard error of each regression model were used to calculate predicted scores on each test. These predicted scores were subtracted from each participant's actual composite score to calculate residual scores. Residual scores were converted to T scores according to the following formula: T score = [(residual score/standard error of the estimate for the regression equation) × 10] + 50. T scores have a mean of 50 and a standard deviation (SD) of 10, allowing a T score of 35 to be the −1.5-SD mark for each of the 4 composite scores. We defined cognitive impairment as scores in specific cognitive domains of less than 1.5 SD below these demographically corrected means,30 as previously done in our cohort for the diagnosis of mild cognitive impairment.32 This definition of cognitive impairment differs from the definition of mild cognitive impairment in that it did not require the memory complaint or the functional impairment criteria. The Color Trails Tests 1 and 2 were not originally part of the cognitive scores in our cohort30 and were not available in all participants. Thus, we defined impairment in the Color Trails Tests 1 and 2 separately, also using the 1.5-SD cutoff and conducted secondary analyses with these tests.

Statistical analysis

First, we examined the distribution of all variables. High-sensitivity CRP was not normally distributed, but was normally distributed after log transformation. We used the χ2 test in bivariate analyses of dichotomous variables and the t test for continuous variables. For multivariable analyses, we used logistic regression relating hsCRP to the presence of cognitive impairment. Models were constructed for each of the cognitive scores. We report several models for the multivariable analyses in the tables: one adjusted for age and sex, one further adjusted for education, ethnic group, and APOE ε4, and another one adjusted for vascular risk factors. We report the second model in the text unless otherwise indicated. We decided a priori that changes in the odds ratio (OR) in the model adjusted for vascular risk factors would be evidence of mediation and not confounding since vascular risk factors and hsCRP are in the same hypothetical causal pathway.33 All analyses were conducted using SAS 9.1.

Results

Table 1 shows the general characteristics of the sample and compares characteristics among hsCRP tertiles. Compared with the first tertile, persons in the third tertile where younger; more likely to be women, black, or Hispanic; less likely to be white and to have the APOE ε4 allele; and more likely to be current or past smokers, have hypertension, and have memory or visuospatial impairment.

We conducted multivariable analyses, first relating log-transformed hsCRP as a continuous variable with the cognitive scores. High-sensitivity CRP was associated with memory impairment (adjusted OR, 1.1; 95% confidence interval [CI], 1.0-1.3); this association was not attenuated by adjustment for vascular risk factors and stroke. Log-transformed hsCRP was also associated with visuospatial impairment (OR, 1.2; 95% CI, 1.0-1.34) after adjusting for sociodemographics and APOE, but was modestly attenuated and became nonsignificant after adjusting for vascular factors (OR, 1.1; 95% CI, 0.96-1.27). We found no association between hsCRP and language, executive, or cognitive impairment in the Color Trails Tests 1 and 2.

We explored the thresholds of the association between hsCRP tertiles and cognitive impairment (Table 2). Compared with participants in the lowest hsCRP tertile, participants in the highest hsCRP tertile had a 50% greater odds of impaired memory, which was not attenuated after adjustment for vascular risk factors. The OR for the second tertile was 1 and not statistically significant, suggesting a threshold for the association between hsCRP and memory impairment.

Subjects in the highest hsCRP tertile had a 60% greater odds of visuospatial impairment (Table 2). Additionally adjusting for vascular factors, heart disease, diabetes, hypertension, smoking, stroke, and use of lipid-lowering medications led to marked attenuation of the association between hsCRP and the visuospatial factor, suggesting that vascular factors may be mediators in this association. Similar to memory, in all models the OR for the middle tertile of hsCRP and visuospatial impairment was not significant; furthermore, crude models of hsCRP and visuospatial factors as well as models adjusted for sociodemographic factors suggested a dose-response relationship between hsCRP and visuospatial impairment.

High-sensitivity CRP was not associated with executive function language. We conducted secondary analyses in a subset of participants with data on Color Trails Tests 1 and 2, but there was no association with either. The OR for the third tertile of hsCRP of the Color Trails Test 1 was 1.1 (95% CI, 0.8-1.5; P = .62) and 0.9 for Color Trails Test 2 (95% CI, 0.7-1.3; P = .75).

We examined effect modification by APOE ε4 by constructing strata of APOE ε4 and hsCRP levels as suggested for the examination of gene-environment interactions (Table 3).15 Because only the third tertile of hsCRP was associated with memory and visuospatial impairment, we created a dichotomous variable defining high hsCRP as the third tertile. The interaction term of APOE ε4 and high hsCRP was of borderline statistical significance (P = .06). Persons with both the highest tertile of hsCRP and APOE 4ε had a higher risk of memory impairment compared with those with neither. Persons with either risk factor alone did not have a higher risk of memory impairment. These findings suggest an additive interaction. Both risk factors were associated with a higher risk of visuospatial impairment in isolation, with only a modest increase in risk with their joint presence.

Comment

In cross-sectional analyses of a large, elderly, multiethnic, community-based cohort, we found that high hsCRP was related to memory and visuospatial impairment. The association between high hsCRP and memory seemed to occur in the presence of APOE ε4.

There are several mechanisms through which inflammation could affect cognition. Endothelial function depends on the sum of all factors contributing to and attenuating atherogenesis and is an important risk factor for cardiovascular outcomes.34,35 Diseases associated with systemic inflammation may lead to impaired endothelial function, which has been associated with cerebral white matter hyperintensities,36,37 vascular dementia, and Alzheimer disease.38-40 Noninfectious systemic inflammatory markers have been independently associated with impaired cerebral blood flow,41 and animal inflammatory models suggest focal dysregulation in cerebrovascular flow in areas important to memory, such as the hippocampus.42 It can be postulated that high systemic inflammation could be a marker of vascular disease,8 but it could also directly affect the amyloid cascade.43 Recent findings suggest that CRP is a marker of vascular disease, but its elevation does not have direct effects on vascular outcomes.44,45 We found that the inclusion of vascular risk factors in multivariable models attenuated the association between hsCRP and visuospatial abilities, but not memory. Acknowledging the limitations of our cross-sectional analyses, one could speculate that the association of hsCRP with visuospatial abilities, affected most by cerebrovascular disease and disruption of frontal subcortical pathways,46 is mediated by vascular disease, while the association with memory is explained by nonvascular mechanisms. Surprisingly, we did not find an association of hsCRP with a subcortical pattern of cognitive impairment, with hallmarks of impaired executive function, processing speed, and attention as described in patients with vascular cognitive impairment.47

Several studies have examined the association of several markers of inflammation and incident cognitive decline.48-50 Although some longitudinal studies have found associations specifically between hsCRP and incident cognitive decline,49 others have revealed conflicting results, including minimal or no overall association with incident decline in memory,51-53 dementia,50 or neuropsychological test performance.54,55 Compared with other studies of cognition and hsCRP, our threshold level of the highest hsCRP tertile was much higher in this population than in some other studies of dementia and memory. Studies examining hsCRP and cognition have classified high hsCRP as higher than 1.0 to 4.1 mg/L48-50,52,56,57 or at least 5.3 mg/L.54 However, levels of hsCRP in our study are comparable with other reports in northern Manhattan7 as well as elderly Hispanic individuals in California.7,58

Among the oldest, persons with high hsCRP and APOE ε4 carriers may be at greatest risk for impaired memory,51 but this has not previously been found in other studies with wider age ranges.57,58 Our findings suggest an additive interaction between APOE ε4 and hsCRP for memory impairment, but this observation is limited by the cross-sectional nature of the study.

High-sensitivity CRP is currently being used as a marker of cardiovascular risk8 and lipid-lowering treatments.5 Our results suggest that it could also be used as a marker of cognitive impairment in persons without dementia and could serve as the basis for interventions. This possibility requires further exploration.

Correspondence: José A. Luchsinger, MD, MPH, 630 W 168th St, PH9E-105, New York, NY 10032 (jal94@columbia.edu).

Accepted for Publication: May 20, 2009.

Author Contributions: Dr Noble had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Noble, Mayeux, and Luchsinger. Acquisition of data: Manly, Schupf, and Luchsinger. Analysis and interpretation of data: Noble, Manly, Schupf, Tang, Mayeux, and Luchsinger. Drafting of the manuscript: Noble and Luchsinger. Critical revision of the manuscript for important intellectual content: Noble, Schupf, Tang, Mayeux, and Luchsinger. Statistical analysis: Noble, Schupf, Tang, and Luchsinger. Obtained funding: Manly, Mayeux, and Luchsinger. Administrative, technical, and material support: Manly and Mayeux. Study supervision: Manly, Mayeux, and Luchsinger.

Financial Disclosure: Dr Schupf has consulted for Elan Pharmaceuticals.

Funding/Support: Support for this work was provided by grant P01AG07232 from the National Institutes of Health.

References
1.
Craft  S Insulin resistance syndrome and Alzheimer's disease: age- and obesity-related effects on memory, amyloid, and inflammation.  Neurobiol Aging 2005;26 ((suppl 1)) 65- 69PubMedGoogle ScholarCrossref
2.
de Luca  COlefsky  JM Inflammation and insulin resistance.  FEBS Lett 2008;582 (1) 97- 105PubMedGoogle ScholarCrossref
3.
Singer  GGranger  DN Inflammatory responses underlying the microvascular dysfunction associated with obesity and insulin resistance.  Microcirculation 2007;14 (4-5) 375- 387PubMedGoogle ScholarCrossref
4.
Yanbaeva  DGDentener  MACreutzberg  ECWesseling  GWouters  EF Systemic effects of smoking.  Chest 2007;131 (5) 1557- 1566PubMedGoogle ScholarCrossref
5.
Ridker  PMRifai  NRose  LBuring  JECook  NR Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events.  N Engl J Med 2002;347 (20) 1557- 1565PubMedGoogle ScholarCrossref
6.
Rost  NSWolf  PAKase  CS  et al.  Plasma concentration of C-reactive protein and risk of ischemic stroke and transient ischemic attack: the Framingham study.  Stroke 2001;32 (11) 2575- 2579PubMedGoogle ScholarCrossref
7.
Elkind  MSTai  WCoates  KPaik  MCSacco  RL High-sensitivity C-reactive protein, lipoprotein-associated phospholipase A2, and outcome after ischemic stroke.  Arch Intern Med 2006;166 (19) 2073- 2080PubMedGoogle ScholarCrossref
8.
Ridker  PM High-sensitivity C-reactive protein, inflammation, and cardiovascular risk: from concept to clinical practice to clinical benefit.  Am Heart J 2004;148 (1) ((suppl 1)) S19- S26Google ScholarCrossref
9.
Luchsinger  JAMayeux  R Cardiovascular risk factors and Alzheimer's disease.  Curr Atheroscler Rep 2004;6 (4) 261- 266PubMedGoogle ScholarCrossref
10.
Gupta  APansari  K Inflammation and Alzheimer's disease.  Int J Clin Pract 2003;57 (1) 36- 39PubMedGoogle Scholar
11.
Frank  RAGalasko  DHampel  H  et al. National Institute on Aging Biological Markers Working Group, Biological markers for therapeutic trials in Alzheimer's disease. Proceedings of the biological markers working group; NIA initiative on neuroimaging in Alzheimer's disease.  Neurobiol Aging 2003;24 (4) 521- 536PubMedGoogle ScholarCrossref
12.
Tang  MXCross  PAndrews  H  et al.  Incidence of Alzheimer's disease in African-Americans, Caribbean Hispanics and Caucasians in northern Manhattan.  Neurology 2001;5649- 56Google ScholarCrossref
13.
US Census Bureau, Census of Population and Housing Summary Tape File 1, Technical Documentation.  Washington, DC US Census Bureau1991;
14.
Hixson  JEVernier  DT Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI.  J Lipid Res 1990;31 (3) 545- 548PubMedGoogle Scholar
15.
Mayeux  ROttman  RMaestre  G  et al.  Synergistic effects of traumatic head injury and apolipoprotein-epsilon 4 in patients with Alzheimer's disease.  Neurology 1995;45 (3, pt 1) 555- 557PubMedGoogle ScholarCrossref
16.
Luchsinger  JAReitz  CHonig  LSTang  MXShea  SMayeux  R Aggregation of vascular risk factors and risk of incident Alzheimer disease.  Neurology 2005;65 (4) 545- 551Google ScholarCrossref
17.
Chobanian  AVBakris  GLBlack  HR  et al. National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee, The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report [see comment] [erratum in JAMA. 2003;290(2):197].  JAMA 2003;289 (19) 2560- 2572PubMedGoogle ScholarCrossref
18.
Hatano  S Experience from a multicentre stroke register: a preliminary report.  Bull World Health Organ 1976;54 (5) 541- 553PubMedGoogle Scholar
19.
Buschke  HFuld  PA Evaluating storage, retention, and retrieval in disordered memory and learning.  Neurology 1974;24 (11) 1019- 1025PubMedGoogle ScholarCrossref
20.
Benton  AL The Visual Retention Test.  New York, NY The Psychological Corporation1955;
21.
Benton  AL Revised Visual Retention Test. 4th New York, NY Psychological Corporation1974;
22.
Rosen  W The Rosen Drawing Test.  Odessa, FL Psychological Assessment Resources1981;
23.
Benton  A The Visual Retention Test.  New York, NY The Psychological Corporation1955;
24.
Kaplan  EGoodglass  HWeintraub  S Boston Naming Test.  Philadelphia, PA Lea & Febiger1983;
25.
Benton  ALHamsher  K Multilingual Aphasia Examination.  Iowa City, IA AJA Associates, Inc1983;
26.
Goodglass  HKaplan  D The Assessment of Aphasia and Related Disorders. 2nd Philadelphia, PA Lea and Febiger1983;
27.
D'Elia  LFSatz  PUchiyama  CLWhite  T Color Trails Test Professional Manual.  Odessa, FL Psychological Assessment Resources1994;
28.
Wechsler  D Wechsler Adult Intelligence Scale-Revised.  New York, NY The Psychological Corporation1981;
29.
Sliwinski  MLipton  RBBuschke  HStewart  W The effects of preclinical dementia on estimates of normal cognitive functioning in aging.  J Gerontol B Psychol Sci Soc Sci 1996;51 (4) 217- 225PubMedGoogle ScholarCrossref
30.
Manly  JJBell-McGinty  STang  MXSchupf  NStern  YMayeux  R Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community.  Arch Neurol 2005;62 (11) 1739- 1746PubMedGoogle ScholarCrossref
31.
Heaton  RKGrant  IMatthews  CG Comprehensive Norms for an Expanded Halstead-Reitan Battery.  Odessa, FL Psychological Assessment Resources Inc1991;
32.
Petersen  RCDoody  RKurz  A  et al.  Current concepts in mild cognitive impairment.  Arch Neurol 2001;58 (12) 1985- 1992PubMedGoogle ScholarCrossref
33.
Libby  PRidker  PM Inflammation and atherosclerosis: role of C-Reactive protein in risk assessment.  Am J Med 2004;116 ((suppl 6A)) 9S- 16SPubMedGoogle ScholarCrossref
34.
Bonetti  POLerman  LOLerman  A Endothelial dysfunction: a marker of atherosclerotic risk.  Arterioscler Thromb Vasc Biol 2003;23 (2) 168- 175PubMedGoogle ScholarCrossref
35.
Lerman  AZeiher  AM Endothelial function: cardiac events.  Circulation 2005;111 (3) 363- 368PubMedGoogle ScholarCrossref
36.
Hoth  KFTate  DFPoppas  A  et al.  Endothelial function and white matter hyperintensities in older adults with cardiovascular disease.  Stroke 2007;38 (2) 308- 312PubMedGoogle ScholarCrossref
37.
Markus  HSHunt  BPalmer  KEnzinger  CSchmidt  HSchmidt  R Markers of endothelial and hemostatic activation and progression of cerebral white matter hyperintensities: longitudinal results of the Austrian Stroke Prevention Study.  Stroke 2005;36 (7) 1410- 1414PubMedGoogle ScholarCrossref
38.
Vicenzini  ERicciardi  MCAltieri  M  et al.  Cerebrovascular reactivity in degenerative and vascular dementia: a transcranial Doppler study.  Eur Neurol 2007;58 (2) 84- 89PubMedGoogle Scholar
39.
Silvestrini  MPasqualetti  PBaruffaldi  R  et al.  Cerebrovascular reactivity and cognitive decline in patients with Alzheimer disease.  Stroke 2006;37 (4) 1010- 1015PubMedGoogle ScholarCrossref
40.
Lavi  SGaitini  DMilloul  VJacob  G Impaired cerebral CO2 vasoreactivity: association with endothelial dysfunction.  Am J Physiol Heart Circ Physiol 2006;291 (4) H1856- H1861PubMedGoogle ScholarCrossref
41.
Novak  VLast  DAlsop  DC  et al.  Cerebral blood flow velocity and periventricular white matter hyperintensities in type 2 diabetes.  Diabetes Care 2006;29 (7) 1529- 1534PubMedGoogle ScholarCrossref
42.
Semmler  AOkulla  TSastre  MDumitrescu-Ozimek  LHeneka  MT Systemic inflammation induces apoptosis with variable vulnerability of different brain regions.  J Chem Neuroanat 2005;30 (2-3) 144- 157PubMedGoogle ScholarCrossref
43.
Perry  VHCunningham  CHolmes  C Systemic infections and inflammation affect chronic neurodegeneration.  Nat Rev Immunol 2007;7 (2) 161- 167PubMedGoogle ScholarCrossref
44.
Schunkert  HSamani  NJ Elevated C-reactive protein in atherosclerosis: chicken or egg?  N Engl J Med 2008;359 (18) 1953- 1955PubMedGoogle ScholarCrossref
45.
Zacho  JTybjaerg-Hansen  AJensen  JSGrande  PSillesen  HNordestgaard  BG Genetically elevated C-reactive protein and ischemic vascular disease.  N Engl J Med 2008;359 (18) 1897- 1908PubMedGoogle ScholarCrossref
46.
Pugh  KGLipsitz  LA The microvascular frontal-subcortical syndrome of aging.  Neurobiol Aging 2002;23 (3) 421- 431PubMedGoogle ScholarCrossref
47.
O'Brien  JTErkinjuntti  TReisberg  B  et al.  Vascular cognitive impairment.  Lancet Neurol 2003;2 (2) 89- 98PubMedGoogle ScholarCrossref
48.
Yaffe  KKanaya  ALindquist  K  et al.  The metabolic syndrome, inflammation, and risk of cognitive decline.  JAMA 2004;292 (18) 2237- 2242PubMedGoogle ScholarCrossref
49.
Yaffe  KLindquist  KPenninx  BW  et al.  Inflammatory markers and cognition in well-functioning African-American and white elders.  Neurology 2003;61 (1) 76- 80PubMedGoogle ScholarCrossref
50.
Tan  ZSBeiser  ASVasan  RS  et al.  Inflammatory markers and the risk of Alzheimer disease: the Framingham Study.  Neurology 2007;68 (22) 1902- 1908PubMedGoogle ScholarCrossref
51.
Schram  MTEuser  SMde Craen  AJ  et al.  Systemic markers of inflammation and cognitive decline in old age.  J Am Geriatr Soc 2007;55 (5) 708- 716PubMedGoogle ScholarCrossref
52.
Ravaglia  GForti  PMaioli  F  et al.  Blood inflammatory markers and risk of dementia: The Conselice Study of Brain Aging.  Neurobiol Aging 2007;28 (12) 1810- 1820PubMedGoogle ScholarCrossref
53.
Engelhart  MJGeerlings  MIMeijer  J  et al.  Inflammatory proteins in plasma and the risk of dementia: the Rotterdam Study.  Arch Neurol 2004;61 (5) 668- 672PubMedGoogle ScholarCrossref
54.
Dik  MGJonker  CHack  CESmit  JHComijs  HCEikelenboom  P Serum inflammatory proteins and cognitive decline in older persons.  Neurology 2005;64 (8) 1371- 1377PubMedGoogle ScholarCrossref
55.
Weuve  JRidker  PMCook  NRBuring  JEGrodstein  F High-sensitivity C-reactive protein and cognitive function in older women.  Epidemiology 2006;17 (2) 183- 189PubMedGoogle ScholarCrossref
56.
Jordanova  VStewart  RDavies  ESherwood  RPrince  M Markers of inflammation and cognitive decline in an African-Caribbean population.  Int J Geriatr Psychiatry 2007;22 (10) 966- 973PubMedGoogle ScholarCrossref
57.
Laurin  DDavid Curb  JMasaki  KHWhite  LRLauner  LJ Midlife C-reactive protein and risk of cognitive decline: a 31-year follow-up.  Neurobiol Aging 2009;30 (11) 1724- 1727PubMedGoogle ScholarCrossref
58.
Haan  MNAiello  AEWest  NAJagust  WJ C-reactive protein and rate of dementia in carriers and non carriers of Apolipoprotein APOE4 genotype.  Neurobiol Aging 2008;29 (12) 1774- 1782PubMedGoogle ScholarCrossref
×