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Original Contribution |

Contribution of Vascular Risk Factors to the Progression in Alzheimer Disease FREE

Elizabeth P. Helzner, PhD; José A. Luchsinger, MD; Nikolaos Scarmeas, MD; Stephanie Cosentino, PhD; Adam M. Brickman, PhD; M. Maria Glymour, PhD; Yaakov Stern, PhD
[+] Author Affiliations

Author Affiliations: Gertrude H. Sergievsky Center (Drs Helzner, Luchsinger, Scarmeas, Cosentino, and Stern), Taub Institute for Research in Alzheimer's Disease and the Aging Brain (Drs Luchsinger, Scarmeas, Brickman, and Stern), and Department of Neurology (Drs Luchsinger, Scarmeas, and Stern), Columbia University Medical Center; and Department of Epidemiology, Mailman School of Public Health, Columbia University (Dr Glymour), New York, New York.


Arch Neurol. 2009;66(3):343-348. doi:10.1001/archneur.66.3.343.
Text Size: A A A
Published online

Background  Vascular factors including medical history (heart disease, stroke, diabetes, and hypertension), smoking, and prediagnosis blood lipid measurements (cholesterol: total, high-density lipoprotein, low-density lipoprotein [LDL-C], and triglyceride concentrations) may be predictors for progression of Alzheimer disease (AD).

Objective  To determine whether prediagnosis vascular risk factors are associated with progression of AD.

Design  Inception cohort followed up longitudinally for a mean of 3.5 (up to 10.2) years.

Setting  Washington Heights/Inwood Columbia Aging Project, New York, New York.

Patients  One hundred fifty-six patients with incident AD (mean age at diagnosis, 83 years).

Main Outcome Measure  Change in a composite score of cognitive ability from diagnosis onward.

Results  In generalized estimating equation models (adjusted for age, race/ethnicity, and years of education), higher cholesterol (total cholesterol and LDL-C) concentrations and history of diabetes were associated with faster cognitive decline. Each 10-U increase in cholesterol and LDL-C was associated with a 0.10-SD decrease in cognitive score per year of follow-up (P < .001 for total cholesterol; P = .001 for LDL-C). High-density lipoprotein cholesterol and triglyceride concentrations were not associated with rate of decline. A history of diabetes was associated with an additional 0.05-SD decrease in cognitive score per year (P = .05). History of heart disease and stroke were associated with cognitive decline only in carriers of the apolipoprotein E ε4 (APOE-ε4) gene. In a final generalized estimating equation model that included high-density lipoprotein cholesterol and LDL-C concentrations and history of diabetes, only higher LDL-C was independently associated with faster cognitive decline.

Conclusion  Higher prediagnosis total cholesterol and LDL-C concentrations and history of diabetes were associated with faster cognitive decline in patients with incident AD, which provides further evidence for the role of vascular risk factors in the course of AD.

Figures in this Article

Few treatment options are available to improve the prognosis in patients with Alzheimer disease (AD). Controlling vascular conditions may be one way of delaying the disease course. Vascular risk factors and vascular disease are associated with higher risk of vascular dementia1,2 and AD.3,4 Members of our group previously reported associations between stroke,5 hyperinsulinemia,6 diabetes mellitus,7 current smoking,8 and hypertension9 and higher risk of AD. We found that high total cholesterol and low-density lipoprotein cholesterol (LDL-C) concentrations are related to increased risk of vascular dementia10,11 but not AD.

While vascular risk factors have been studied as predictors of AD,4,12 few studies have assessed their influence on disease progression.13,14 We examined the interplay between vascular factors and course of AD in participants from the Washington Heights/Inwood Columbia Aging Project, a multiethnic, community-based, prospective study of aging in northern Manhattan (New York, New York).

PARTICIPANTS

Participants in the Washington Heights/Inwood Columbia Aging Project are from 2 population-based cohorts of Medicare enrollees. Recruitment for the first cohort began in January 1992. The study area comprised 41 census tracts in Manhattan between 155th Street and 181st Street. Lists of Medicare recipients in the study area were obtained from the Health Care Financing Administration. Potential participants were selected by systematic random sampling into 1 of 6 strata on the basis of race/ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and age (65-74 or >75 years). At baseline, 2125 subjects were interviewed. A cohort of 2183 additional participants was formed in November 1999 using similar methods with several exceptions: new lists of beneficiaries were obtained but those drawn into the 1992 cohort were excluded, subjects who reported receiving a diagnosis of dementia in the course of arranging for the initial evaluation were excluded, and the study area was extended to encompass Manhattan north of 145th Street.

The sample for this analysis was restricted to individuals with lipid assessments before diagnosis of dementia. During follow-up, 417 individuals developed AD. Of these, prediagnosis vascular risk factor data were available for 319, 156 of whom also had postdiagnosis follow-up data (Figure). Of the individuals with incident AD with vascular risk factors, 44 (14%) died, 55 (17%) received the diagnosis in the most recent interview wave and, therefore, had no postdiagnosis data available, and 64 (20%) were not followed up because of refusal or study dropout. Excluded patients with AD were similar to the analysis sample insofar as age, sex, race/ethnicity; cognitive status at diagnosis; APOE-ε4 status; total cholesterol, high-density lipoprotein cholesterol (HDL-C), and LDL concentrations; and presence of hypertension, stroke, and heart disease. However, excluded participants had achieved higher educational levels (8.1 vs 6.6 years; P = .002), had a higher prevalence of diabetes (29% vs 18% of the analysis; P = .02), and had lower triglyceride concentrations (mean, 154.9 vs 173.2 mg/dL; P = .04) (to convert to millimoles per liter, multiply by 1.8).

Place holder to copy figure label and caption
Figure.

Flowchart of analysis sample selection. AD indicates Alzheimer disease; CDR, Clinical Dementia Rating Scale.

Graphic Jump Location

The study was approved by the Columbia University Institutional Review Board. Written informed consent was obtained from all subjects.

ASSESSMENT OF INCIDENT AD

Alzheimer disease was diagnosed using physician-administered physical and neurologic examinations along with a standardized neuropsychologic battery of tests.15 All assessments were administered at baseline and at follow-up visits, which occurred at approximately 18-month intervals. Evaluations were conducted in English or Spanish according to participant preference. All available information including medical records and imaging studies was considered in the evaluations.

Consensus diagnosis of dementia was made at conferences attended by neurologists and neuropsychologists using the neuropsychologic battery of tests and evidence of social or occupational functional deficits per Diagnostic and Statistical Manual of Mental Disorders (Third Edition Revised) criteria. Diagnosis of probable or possible AD was based on the National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer Disease and Related Disorders Association criteria.16

OUTCOME MEASURES

Five cognitive domains were assessed including (1) Memory: total and delayed recall of the Selective Reminding Test17 and the Recognition Subtest of the multiple-choice Benton Visual Retention Test18; (2) Abstract Reasoning: Wechsler Adult Intelligence Scale–Revised Similarities Subtest19; Identities and Oddities Subtest of the Dementia Rating Scale20; (3) Visual-Spatial: 5 items from the Rosen Drawing Test21; the matching component of the multiple-choice Benton Visual Retention Test18; (4) Language: 15-item Boston Naming Test22 and the 8 high-probability items from the Repetition Subtest and the first 6 items of the Comprehension Subtest of the Boston Diagnostic Aphasia Examination22; and (5) Executive-Speed: mean scores for phonemic fluency assessed by the Controlled Oral Word Association Test and category fluency (Animals, Food, and Clothing) mean scores.23

The 12 test scores were transformed into z scores. Means and standard deviations were calculated from baseline scores for subjects without dementia matched for age, race/ethnicity, and years of education. The z scores were averaged within cognitive domains, which were subsequently averaged to produce the composite cognitive score.24 The outcome measure was the rate of change in the composite score from diagnosis onward.

PREDICTOR VARIABLES

Baseline age, sex, race/ethnicity, and years of education were collected by interview. Stroke was defined by World Health Organization criteria.25 Diabetes and hypertension were defined based on self-report or documented treatment of either disorder at any time up to diagnosis of AD. Heart disease was defined as a history of myocardial infarction, congestive heart failure, or angina pectoris at any time up to diagnosis of AD.

Fasting plasma total cholesterol and triglyceride concentrations were measured at a mean (SD) of 3.3 (2.2) years before diagnosis using standard enzymatic techniques. High-density lipoprotein cholesterol concentrations were determined after precipitation of apolipoprotein B–containing lipoproteins with phosphotungstic acid. Low-density lipoprotein cholesterol concentrations were recalculated using the Friedewald formula.26 Because HDL-C and triglyceride values were not normally distributed, log-transformed versions of these variables were used. Apolipoprotein E (APOE) genotype, determined using established methods,27 was available for 132 of the 156 participants (85%) and was classified on the basis of presence of at least 1 APOE-ε4 allele.

STATISTICAL ANALYSIS

Generalized estimating equations28 were used to examine the relation of vascular factors to rates of cognitive change. By treating each subject's repeated measures as a cluster, generalized estimating equations account for the correlation of repeated measures in the same individual. Two models were developed.

Model 1

Separate models were developed to assess the association of each vascular variable (heart disease, stroke, diabetes, hypertension, smoking, and prediagnosis lipid concentrations) with postdiagnosis cognitive decline. Taking diabetes as an example, the dependent variable was the composite cognitive score, and predictor variables were diabetes, time (years), and a diabetes-time interaction. Age at AD incidence, sex, race/ethnicity, years of education (years), and study cohort were simultaneously introduced into models. A significant diabetes effect would suggest a diabetes-associated difference in cognition at diagnosis. A significant time effect would suggest change in cognitive scores over time regardless of diabetes status. A significant interaction term would suggest differential rates of postdiagnosis cognitive change associated with diabetes. The interval between lipid measurement and AD incidence was included as a covariate in the lipid models.

Model 2

To determine whether any vascular factor was independently associated with cognitive decline, we constructed a post hoc model that simultaneously included all variables associated with cognitive decline after age- or multivariable-adjustment (cholesterol concentrations and diabetes) (model 1), their interactions with time, and demographic factors. Diabetes and LDL-C and HDL-C concentrations but not total cholesterol concentration were included in this model.

Supplementary Analyses

We repeated our analyses within APOE-ε4 strata in the subsample with genotyping data (n = 132). We also examined whether use of lipid-lowering agents (LLAs) was associated with cognitive decline and whether cholesterol concentrations predicted rate of decline similarly in LLA users vs nonusers.

Characteristics of the overall sample are given in Table 1. At diagnosis, most participants (93%) had a clinical dementia rating of 1.0 (mild).29 The mean (SD) follow-up time between diagnosis and last follow-up was 3.5 (2.2) years (range, 1.0-10.3 years), with 1.6 (0.9) postdiagnostic assessments (range, 2-5).

Table Graphic Jump LocationTable 1. Characteristics of Patients With Incident Alzheimer Disease
PREDICTOR VARIABLES AND BASELINE CHARACTERISTICS

There were no sex-related differences in predictor variables except for higher total cholesterol concentrations in women (201.16 vs 184.53 mg/dL; P = .01). At diagnosis, non-Hispanic whites were, on average, 2.6 years older than blacks (P = .26) and 3.4 years older than Hispanics (P = .03). Prevalent disease variables (heart disease, stroke, diabetes, and hypertension) did not vary by race/ethnicity. Blacks had higher mean HDL-C concentrations (55.3 mg/dL) compared with whites (43.8 mg/dL; P = .004) and Hispanics (43.2 mg/dL; P < .001) and lower mean triglyceride concentrations (139.5 mg/dL) compared with whites (207.1 mg/dL; P = .001) and Hispanics (186.1 mg/dL; P < .001). There were no differences by race/ethnicity for sex, total cholesterol or LDL-C concentrations, or APOE-ε4 status (data not shown).

COGNITIVE DECLINE OVER TIME

A generalized estimating equation model indicated an overall decline in composite cognitive score of 0.08 SD per year (β = −.08, P < .001). A quadratic term for time, added to the model to test whether cognitive change was nonlinear, was nonsignificant.

VASCULAR FACTORS AND COGNITIVE DECLINE

Results of model 1 for each predictor are given in Table 2. Higher total cholesterol and LDL-C concentrations were associated with faster cognitive decline. Each 10-mg/dL–U increase in total cholesterol or LDL-C concentration was associated with an additional 0.10-SD decline in cognitive score per year (P < .001 for total cholesterol and P = .003 for LDL-C) (to convert all types of cholesterol to millimoles per liter, multiply by 0.0259). Neither HDL-C nor triglyceride concentration was associated with cognitive decline. Of the medical history variables, only diabetes was associated with faster decline (β = −.05, P = .045).

Table Graphic Jump LocationTable 2. Separate GEE Models Measuring Decline in Cognitive Function Associated With Vascular Risk Factorsa
MODEL 2

In a post hoc model that simultaneously included HDL-C and LDL-C concentrations and diabetes and their interactions with time, only LDL-C was independently associated with faster cognitive decline (Table 3).

Table Graphic Jump LocationTable 3. Post Hoc GEE Model Including Vascular Risk Factors Significantly Associated With Cognition in Individual Modelsa
SUPPLEMENTARY ANALYSES

In participants with genotype data, the presence of at least 1 APOE-ε4 allele was associated with faster cognitive decline (model 1) (multivariable-adjusted β for interaction with time: β = −.08, P = .05). The APOE-ε4–stratified models revealed that in APOE-ε4 noncarriers (n = 89), higher prediagnosis total cholesterol, LDL-C, and HDL-C concentrations were associated with faster cognitive decline (multivariable-adjusted β for interactions with time: total cholesterol, β = −.001, P < .001; LDL-C, β = −.001, P = .02; and HDL-C, β = −.13, P = .01). Triglyceride concentrations and medical history were not associated with cognitive decline (data not shown). Among APOE-ε4 carriers (n = 41), higher total cholesterol (β = −.002, P = .03) and LDL-C (β = −.002, P = .03) concentrations and stroke (β = −.18, P = .02) and heart disease (β = −.19, P = .001) were associated with faster decline. No associations were seen with the remaining vascular variables (data not shown).

The use of LLAs was not associated with rate of cognitive decline. Models of the association of cholesterol concentration with cognitive decline were repeatedly stratified by use of LLAs, and results were similar (data not shown).

There has been intense interest in identifying modifiable AD risk factors such as cardiovascular risk factors, with the goal of preventing or at least delaying disease onset.4 However, little attention has been given to the influence of these factors on disease progression. Cerebrovascular lesions, common in patients with AD, may accelerate the clinical manifestation of AD.30 Vascular risk factors may increase oxidative stress or activate a neuroinflammatory response, triggering amyloid production. Thus, it has been suggested that AD and cerebrovascular disease may work synergistically to cause cognitive decline.31

Consistent with previous research,32 we found that higher total cholesterol and LDL-C concentrations were associated with faster cognitive decline in patients with AD. An earlier study of the Washington Heights/Inwood Columbia Aging Project cohort found that higher total cholesterol concentration was associated with lower risk of incident AD.10 The prodromal stage of AD is associated with decreased plasma cholesterol concentrations, possibly owing to dietary insufficiency and weight loss. By limiting the present study to incident cases, we may have eliminated bias or confounding in cholesterol concentrations associated with frailty and preclinical AD. This may explain the difference with our findings for incident AD.

Lipid-lowering agents have previously been associated with slower cognitive decline in patients with AD.33 Nevertheless, consistent with others,13 we found no association between LLAs and cognitive decline.

Of the medical history variables, only diabetes was associated with faster cognitive decline. Diabetes may influence AD progression via an inflammatory mechanism or by contributing to amyloid plaque and neurofibrillary tangle formation.34 Heart disease, stroke, hypertension, and smoking history were not associated with disease progression in the overall sample.

The APOE-ε4 genotype may contribute to both vascular disease and AD neuropathologic features, with effects of vascular risk factors more pronounced among APOE-ε4 carriers.35 A previous study of this cohort found faster cognitive decline in participants with mild AD who were APOE-ε4 carriers.36 In our APOE-ε4–stratified models, higher total cholesterol and LDL-C concentrations predicted faster decline in both groups, whereas history of heart disease or stroke predicted faster decline in APOE-ε4 carriers only.

Few studies have examined the simultaneous effects of multiple vascular risk factors on AD progression. A study of prevalent AD found that stroke but not other vascular factors was associated with faster decline on the Mini-Mental State Examination.13 A study of incident cases found faster decline on the Clinical Dementia Rating Scale and the Mini-Mental State Examination in those with a history of atrial fibrillation, systolic hypertension, and angina at baseline, and diabetes was associated with slower decline.14 Our findings may differ from those of these studies for several reasons: (1) we measured cognitive change using a comprehensive battery of cognitive tests, which is potentially more sensitive than the Mini-Mental State Examination; (2) one of the previous studies13 included some participants with relatively advanced AD; and (3) both of the previous studies were limited to whites, who, on average, were more highly educated than our multiethnic sample. In our post hoc model, only higher LDL-C concentration emerged as an independent predictor. The negative finding for diabetes as an independent predictor may be to the result of reduced power in the post hoc analysis because the β value associated with diabetes-related cognitive change was similar to the diabetes-specific model.

This study has limitations. Because disease history (heart disease, stroke, and diabetes) was self-reported, the prevalence of these conditions in our sample was likely underestimated. Further, 44 of the participants with incident AD were not included in this analysis because they died before the next follow-up assessment. Cause of death was unavailable; however, it is likely that many of these deaths were due to vascular disease. If so, the effect size we found may be an underestimate. We had only 1 lipid assessment, potentially resulting in measurement error. Although lipid concentrations were measured before diagnosis, some participants may have had prodromal AD. We attempted to account for this by adjusting for the interval between lipid measurement and diagnosis; results were unchanged. Similarly, AD-associated reductions in blood pressure may have masked an association between hypertension and disease progression that might have been noted had blood pressure been measured at midlife. In future longitudinal studies, it would be better to measure these factors earlier in life. Our AD diagnoses were not neuropathologically confirmed, and imaging was not consistently used as part of the diagnostic process. Previous studies using magnetic resonance imaging and neuropathologic data suggest that, especially in the oldest old, mixed dementia (AD plus vascular dementia) is the most common cause of dementia.37 Therefore, it is likely that some of our patients with AD actually had mixed dementia. In addition, there is always the possibility that our findings could be due to chance.

Despite these limitations, clinical diagnosis was based on uniform application of widely accepted criteria and, unlike cognitive screening instruments used in some studies, our cognitive assessment comprised a comprehensive battery of tests evaluating a range of cognitive domains. Our use of a population-based sample limited to individuals with incident AD reduced biases associated with convenience samples (disease registries and hospital- or clinic-based samples), which may not accurately reflect the course of the disease in the general population.

In conclusion, we found that higher prediagnosis total cholesterol and LDL-C concentrations and prevalent diabetes were associated with accelerated postdiagnostic cognitive decline. History of heart disease or stroke was predictive of faster decline in APOE-ε4 carriers only. Prevention or treatment of these conditions can potentially slow the course of AD.

Correspondence: Yaakov Stern, PhD, Columbia University Medical Center, 630 W 168th St, P&S Box 16, New York, NY 10032 (ys11@columbia.edu).

Accepted for Publication: September 9, 2008.

Author Contributions: Dr Helzner 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: Helzner, Scarmeas, and Stern. Acquisition of data: Stern. Analysis and interpretation of data: Helzner, Luchsinger, Scarmeas, Cosentino, Brickman, Glymour, and Stern. Drafting of the manuscript: Helzner and Luchsinger. Critical revision of the manuscript for important intellectual content: Scarmeas, Cosentino, Brickman, Glymour, and Stern. Statistical analysis: Helzner, Scarmeas, Cosentino, Glymour, and Stern. Obtained funding: Luchsinger and Stern. Administrative, technical, and material support: Scarmeas. Study supervision: Scarmeas and Stern.

Financial Disclosure: None reported.

Funding/Support: This study was supported by Neuroepidemiology Training Grant 5T32NS007153-22 (Dr Helzner) and federal grants AG007232 (Washington Heights/Inwood Columbia Aging Project) and P01-AG07232 and by the Taub Institute for Research in Alzheimer's Disease and the Aging Brain.

Additional Contributions: Nicole Schupf, PhD, reviewed the manuscript.

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PubMed Link to Article
DeCarli  C The role of cerebrovascular disease in dementia. Neurologist 2003;9 (3) 123- 136
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Korczyn  AD The underdiagnosis of the vascular contribution to dementia. J Neurol Sci 2005;229-2303- 6
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Luchsinger  JAMayeux  R Cardiovascular risk factors and Alzheimer's disease. Curr Atheroscler Rep 2004;6 (4) 261- 266
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Luchsinger  JATang  MXShea  SMayeux  R Hyperinsulinemia and risk of Alzheimer disease. Neurology 2004;63 (7) 1187- 1192
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Luchsinger  JATang  MXStern  YShea  SMayeux  R Diabetes mellitus and risk of Alzheimer's disease and dementia with stroke in a multiethnic cohort. Am J Epidemiol 2001;154 (7) 635- 641
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Figures

Place holder to copy figure label and caption
Figure.

Flowchart of analysis sample selection. AD indicates Alzheimer disease; CDR, Clinical Dementia Rating Scale.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Characteristics of Patients With Incident Alzheimer Disease
Table Graphic Jump LocationTable 2. Separate GEE Models Measuring Decline in Cognitive Function Associated With Vascular Risk Factorsa
Table Graphic Jump LocationTable 3. Post Hoc GEE Model Including Vascular Risk Factors Significantly Associated With Cognition in Individual Modelsa

References

Barba  RMartínez-Espinosa  SRodríguez-García  EPondal  MVivancos  JDel Ser  T Poststroke dementia: clinical features and risk factors. Stroke 2000;31 (7) 1494- 1501
PubMed Link to Article
DeCarli  C The role of cerebrovascular disease in dementia. Neurologist 2003;9 (3) 123- 136
PubMed Link to Article
Korczyn  AD The underdiagnosis of the vascular contribution to dementia. J Neurol Sci 2005;229-2303- 6
PubMed Link to Article
Luchsinger  JAMayeux  R Cardiovascular risk factors and Alzheimer's disease. Curr Atheroscler Rep 2004;6 (4) 261- 266
PubMed Link to Article
Honig  LSTang  MXAlbert  S  et al.  Stroke and the risk of Alzheimer disease [published correction appears in Arch Neurol. 2004;61(3):368]. Arch Neurol 2003;60 (12) 1707- 1712
PubMed Link to Article
Luchsinger  JATang  MXShea  SMayeux  R Hyperinsulinemia and risk of Alzheimer disease. Neurology 2004;63 (7) 1187- 1192
PubMed Link to Article
Luchsinger  JATang  MXStern  YShea  SMayeux  R Diabetes mellitus and risk of Alzheimer's disease and dementia with stroke in a multiethnic cohort. Am J Epidemiol 2001;154 (7) 635- 641
PubMed Link to Article
Merchant  CTang  MXAlbert  SManly  JStern  YMayeux  R The influence of smoking on the risk of Alzheimer's disease. Neurology 1999;52 (7) 1408- 1412
PubMed Link to Article
Posner  HBTang  MXLuchsinger  JLantigua  RStern  YMayeux  R The relationship of hypertension in the elderly to AD, vascular dementia, and cognitive function. Neurology 2002;58 (8) 1175- 1181
PubMed Link to Article
Reitz  CTang  MXLuchsinger  JMayeux  R Relation of plasma lipids to Alzheimer disease and vascular dementia. Arch Neurol 2004;61 (5) 705- 714
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