Age and Ageing 2008; 37: 559–564
doi:10.1093/ageing/afn144
Published electronically 30 July 2008
 The Author 2008. Published by Oxford University Press on behalf of the British Geriatrics Society.
All rights reserved. For Permissions, please email: [email protected]
Vascular biomarkers of cognitive performance in
a community-based elderly population: the
Dublin Healthy Ageing study
AI-VYRN CHIN1 , DAVID J. ROBINSON1 , HENRY O’CONNELL1 , FIONA HAMILTON1 , IRENE BRUCE1 ,
ROBERT COEN1 , BERNARD WALSH1 , DAVIS COAKLEY1 , ANNE MOLLOY2 , JOHN SCOTT2 , BRIAN A. LAWLOR1 ,
CONAL J. CUNNINGHAM1
1
Mercer’s Institute for Research on Ageing, St. James’s Hospital, Dublin 8, Ireland
of Biochemistry and Immunology, Trinity College, Dublin 2, Ireland
2 School
Address correspondence to: D. J. Robinson. Tel: (+353)-1-4162640. Email: [email protected]
Abstract
Background: population studies suggest that cardiovascular risk factors may be associated with cognitive impairment.
Epidemiological studies evaluating individual markers of vascular disease as risk factors for cognitive dysfunction have yielded
inconsistent results. Homocysteine has emerged as a marker consistently associated with poorer outcomes. Existing studies
have largely examined individual vascular risks in isolation and have tended to ignore patient psychological status.
Objective: to investigate the association between markers of vascular disease and cognition in a community-dwelling
non-demented elderly population while adjusting for vascular and non-vascular confounds.
Design: cross-sectional community based assessment.
Participants: 466 subjects with mean age 75.45 (s.d., 6.06) years. 208 (44.6%) were male.
Results: higher levels of homocysteine were consistently associated with poorer performance in tests assessing visual memory
and verbal recall. No other vascular biomarker was found to be associated with cognitive performance. Factors such as alcohol
use, tea intake, life satisfaction, hypertension and smoking were positively correlated with global cognitive performance.
Negative correlations existed between cognitive performance and depression, past history of stroke, intake of fruit and use
of psychotropic medication.
Conclusions: homocysteine was the only vascular biomarker associated with poorer function in a number of domains on
neuropsychological testing, independent of vascular and non-vascular confounds. Other psychosocial factors may need to be
taken into account as potential confounds in future studies investigating cognition.
Keywords: epidemiology, vascular, cognition, elderly, homocysteine
Introduction
The ageing of populations worldwide raises concern
regarding the prevalence of cognitive dysfunction in the
future. Therefore, it becomes increasingly important to
identify risk factors associated with cognitive impairment.
Epidemiological studies have linked cardiovascular disease,
vascular comorbidities and specific vascular biomarkers such
as cholesterol, HbA1c, homocysteine and C-reactive protein
(CRP) [1–3] with cognitive decline and dementia. These
factors are highly prevalent in the elderly and are potentially
modifiable. Population studies evaluating individual markers
of vascular disease as risk factors for cognitive dysfunction
have been inconclusive. One reason for this uncertainty
may be that most existing studies examined individual
vascular risks in isolation and tended to ignore patient
psychological status when adjusting for potential confounds.
Individual vascular risk factors or biomarkers may influence
each other [4], leading to over- or underestimation of
their individual effects on cognition. In addition, other
biophysical and psychosocial patient factors may influence
observed associations between vascular risks, biomarkers
and cognition [5].
The potential for prevention of cognitive decline and
dementia through modifying vascular risk factors is therefore
dependent on an understanding of their effects individually
and collectively. Similar examples include the observed
benefit of anti-oxidants and oestrogen hormone replacement
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A.-V. Chin et al.
therapy on vascular disease—this may have been due to
disease-avoiding behaviour on the part of those taking such
therapies [6, 7]. In order to better evaluate the correlations
between vascular biomarkers and cognition, we carried out
a population-based study adjusting for known vascular comorbid and psychosocial factors while testing for cognitive
dysfunction in a community-dwelling population.
Methodology
Study population and design
The Dublin Healthy Ageing study is a community-based
study examining physical, psychiatric, cognitive and social
health characteristics of older people. It is a crosssectional examination of 466 non-demented elderly subjects,
stratified for age, and randomly selected from the patient
lists of four general practitioners in the catchment area
of St. James’s Hospital, Dublin. All medically stable,
non-demented community-dwelling individuals aged over
65 years who were able to provide consent and cooperation
with neuropsychological testing were eligible for recruitment.
Data were collected between 2003 and 2005. Ethical approval
was obtained from both the Hospital and GP ethics
committees. Subjects were contacted by post and offered
participation. A total of 1349 letters to individuals were sent.
Of these, 419 (31%) individuals refused participation. A total
of 159 (11.8%) did not meet inclusion criteria; 175 (13%)
had passed away and 71 (5.3%) were no longer at their given
addresses; 59 patients were no longer on the GP list. A
research psychologist and a doctor visited individuals who
agreed to participate in their own home on a single occasion.
The duration of each assessment was approximately 2 h.
Assessments
A structured interview recorded self-reported information
on demographic details, education, medical history, current
medications, diet, smoking status, alcohol use, exercise,
psychosocial history and family history. Lifetime alcohol
intake was estimated from self-report and calculated in
the number of units/week. Pack years were calculated by
dividing the number of cigarettes smoked per day by 20 and
multiplying this by the number of years smoked.
Biophysical measurements such as the subjects’ height
(cm), waist circumference (cm) and hip circumference (cm)
were measured using a standard tape measure accurate to
1 mm. Weight (kg) was measured on a calibrated scale accurate to 0.5 kg with normal indoor clothing. Subjects’ waist :
hip ratio (waist/hip) and body mass index (weight/height2 )
were calculated according to standard equations.
Blood pressure measurements were performed with the
subject sitting, with a standard aneroid sphygmomanometer accurate to 3 mmHg. A comprehensive assessment of
neurological status and mood was performed by a medical doctor. Further clinical assessments were performed if
deemed necessary.
Cognitive status was assessed in a variety of domains
using standardised instruments. These domains included
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pre-morbid intellect (National Adult Reading Test (NARTR) [8]), psychomotor processing speed (Wechsler Adult
Intelligence Scale (WAIS)—III-digit symbol coding [9]),
verbal fluency and category fluency (FAS test and animal
fluency [10]), and verbal learning, interference, delayed recall
and recognition (Wechsler Memory Scale (WMS)—IIIserial word lists [11]). Visual memory was assessed using
the Wechsler Memory Scale—revised visual reproduction.
Working memory was tested using the Wechsler Memory
Scale—III-letter number sequencing [12]. Test scores were
standardised using a z-transformation (subject score minus
sample mean divided by sample standard deviation) to enable
comparison of tests with different ranges. A composite score
consisting of the average of the sum of the standardised
test scores [13] was used as a global measure of cognitive
performance (global composite: GC). The Mini-Mental State
Examination (MMSE) [14] was performed as a second
general index of cognitive functioning. Personality was
measured using the Eysenck Personality Inventory (EPI) [15]
which measures two important personality dimensions,
extroversion–introversion and neuroticism-stability.
Blood samples were collected by venepuncture and nonfasting samples taken for homocysteine, glucose, glycosylated
haemoglobin, lipid profile and CRP. All samples were measured by a commercial laboratory. Homocysteine samples
were transported on ice, spun within 30 min and stored at
−20◦ C or below until analysed. Quantitative measurement of
L-homocysteine in serum was by fluorescence polarization
immunoassay (Imx system; Abbott laboratories). Sensitivity
of these assays were calculated to <0.50 µmol/l corresponding to the upper limit of the 95% confidence interval.
Precision of these assays was determined by assaying samples
on 5 days, i.e. 2 runs/day across 10 instruments. Samples with
mean value 5.9, 10.8, 21.6 mol/l yielded within-run coefficient of variation (CV)% of 2.2, 1.9 and 1.4 respectively and
total CV% of 5.2, 4.1 and 3.7 respectively. Glucose levels were
determined enzymatically (bioMerieux) with CV range of
0.75–0.81%. Glycosylated haemoglobin was measured using
high-performance liquid chromatography (Hi-AUTO A1c
Analyser system) with a CV of 5–10%. Serum cholesterol,
high-density lipoprotein (HDL) and low-density lipoprotein
(LDL) were measured by enzymatic clearance assay (Randox
Laboratories) using a Hitachi 737 or 747 with a CV range of
0.88–1.2% for HDL, and CV 0.49–1.79% for LDL. Triglyceride levels were measured by the triglycerides liquicolor test
(Human Gesellschaft fur Biochemica und Diagnostica mbH)
with a CV range between 2.0 and 3.5%. C-reactive protein
was measured by particle enhanced immunonephelometry
(BN Systems) with a CV range between 2.1 and 5.7%.
Statistical Analysis
Multiple linear regression models were used to investigate
the relationship between vascular biomarkers and neuropsychological tests, controlling for identified covariates.
The relationship between neuropsychological test scores
and vascular biomarkers (homocysteine, C-reactive protein,
Vascular biomarkers of cognitive performance in the elderly
glycosylated haemoglobin and LDL-cholesterol) were first
modelled individually in base models controlling for gender,
age, social class and educational status.
Associations between global cognitive performance and
potential lifestyle, dietary, psychosocial and clinical confounders were explored in backward regression models. In
the final analysis, the relationship between neuropsychological test scores and vascular biomarkers were determined
using multivariate analysis while adjusting for all significant confounders determined in exploratory analyses. All
statistical analyses were performed using SPSS 13.0 [16].
Results
Demographic, clinical, biochemical, psychosocial, dietary
and lifestyle characteristics are summarised in Table 1. There
were 466 subjects with a mean age (SD) of 75.5 (6.1), of which
55.4% were female. Neuropsychological test characteristics
are summarised in Table 2. Due to fatigue or illiteracy some
subjects were unable to complete all the neuropsychological
tests.
Homocysteine
Raised homocysteine was consistently associated in base
models with poorer function in several domains on
neuropsychological testing, specifically, tests assessing visual
memory, verbal recall, psychomotor processing speed and a
measure of global cognition, the MMSE (Table 3). This was
independent of known confounds.
In multivariable models, controlling for other covariates,
homocysteine remained consistently associated with visual
memory and verbal recall (Table 3). There were no consistent
associations found between other vascular biomarkers
investigated and cognitive tests.
Lifestyle and psychosocial factors
Factors negatively associated with global cognition scores
included increased age, lower social class and a history
of stroke or depression (please see Appendix 1 in the
supplementary data at Age and Ageing Online Table 1). Factors
that correlated positively included education, higher life
satisfaction, increased fruit intake, alcohol and tea intake and
a history of hypertension. Cigarette smoking also correlated
positively with cognition.
Discussion
In this elderly non-demented community population, raised
homocysteine concentrations were significantly associated
with poorer performance in neuropsychological tests
assessing visual memory and verbal recall. This was
independent of biophysical and psychosocial factors and
other vascular biomarkers. There were no consistent
associations found between other biochemical markers of
vascular disease and cognition. Aside from the known
confounds of cognitive performance such as age, educational
status and social class, this study identified other potential
Table 1. Population characteristics
Subjects (n = 466)
................................................................
Demographic Characteristics
Gender (females)
55.4%
Age (mean [SD])
75.45 (6.06)
Education (mean [SD] age left school)
14.88 (2.15)
Social class 1 + 2
15.7%
Clinical characteristics
Current smokers
16.5%
Pack years (mean [SD])
24.38 (35.57)
Teetotalers
22.1%
Hypertension
39.3%
Systolic blood pressure (mean [SD])
156.70 (23.56)
Diastolic blood pressure (mean [SD])
82.15 (13.27)
Type 2 diabetes mellitus
9.9%
Cardiovascular disease
23.3%
Stroke
11.2%
Atrial fibrillation
6.0%
Body Mass Index (mean [SD])
26.77 (4.88)
Psychotropic medications
16.8%
Statins
27.3%
Anti-hypertensives
52.5%
Non-steroidal anti-inflammatories
40%
Psychosocial characteristics
Life satisfaction index (mean [SD])
14.04 (3.95)
Total depression scale (mean [SD])
7.73 (10.32)
Anxiety (case level)
2.6%
Depression (case level)
9%
Dietary and lifestyle Characteristics: Mean (SD)
Tea (cups/day)
4.46 (2.57)
Fish (portions/week)
1.35 (0.70)
Vegetables (portions/week)
3.01 (0.832)
Fruit (portions/week)
2.57 (1.23)
Exercise (minutes/fortnight)
396 (492.29)
Biochemical characteristics mean, (sd)
Glucose (mmol/l)
6.02 (3.14)
HbA1c
5.98 (0.81) %
Total cholesterol (mmol/l)
5.17 (1.12)
Low-density lipoprotein (LDL) (mmol/l)
2.90 (0.92)
High density lipoprotein (HDL) (mmol/l)
1.39 (0.39)
Triglycerides (mmol/l)
1.75 (0.97)
Homocysteine (µmol/l)
13.86 (6.11)
C-reactive protein (CRP) (mg/l)
7.29 (14.1)
psychosocial confounds which should be taken into
consideration in studies assessing cognition.
The association found between elevated levels of
homocysteine and cognitive dysfunction in this study
is consistent with that observed in other population
studies although this has not been universal [17–19].
Hyperhomocysteinaemia has previously been implicated
in the pathogenesis of arteriosclerosis and a number of
epidemiological studies have shown a relationship between
vascular disease and homocysteine concentrations [20]. High
homocysteine levels may contribute to cognitive decline
through silent brain infarcts [21]. However, whether elevated
levels of homocysteine is a causative factor in vascular
disease or the consequence of tissue damage is still uncertain.
In vitro studies have shown that homocysteine potentiates β
amyloid neurotoxicity [22]. Thus, homocysteine may play a
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A.-V. Chin et al.
Table 2. Neuropsychological test scores
Neuropsychological tests: mean, (SD)
.................................................................................
Mini-mental state examination
26.04 (2.87)
98.09 (12.55)
Pre-morbid IQ (NARTa )
Letter fluency (FAS)
25.32 (10.38)
Category fluency (Animals)
13.68 (4.38)
Psychomotor processing speed (WAIS-III digit symbol codingb )
33.45 (12.01)
Working memory (WMS-III letter number sequencingc )
6.52 (2.99)
33.50 (14.99)
Visual memory (immediate and delayed) (WMS-R visual reproductiond )
Verbal memory (WMS-III serial wordsc )
Learn slope
3.63 (1.96)
Short delay recall
3.70 (2.49)
Long delay recall
3.95 (2.46)
Recognition
21.32 (2.59)
Total recall list 1–4
23.23 (6.17)
List B recall
4.12 (1.56)
Proactive interference
−0.45 (1.74)
Retroactive interference
3.62 (2.25)
a
National Adult Reading Test.
Wechsler Adult Intelligence Scale.
c Wechsler Memory Scale—III.
d Wechsler Memory Scale—Revised Visual Reproduction.
b
more direct role in the pathogenesis of neurodegenerative
disorders [23]. While several randomised controlled trials
have failed to demonstrate that reduction of homocysteine
levels protects against cognitive decline [24, 25], one
limitation of these studies is that the time span in which
they are conducted may be insufficient to detect an effect.
Results of studies investigating the association between
cognition and other vascular biomarkers such as CRP,
glycosylated haemoglobin and LDL-cholesterol have been
mixed [17, 26–28]. This study found no consistent association between these vascular biomarkers and cognitive
performance. Potential explanations include differences in
populations studied such as educational status, the degree of
cardiovascular co-morbidity and the use of disease-modifying
drugs such as statins. Age may also be a factor—the mean
age of this sample was 75 years, and all subjects were over
65 years of age. Subjects with adverse outcomes related to
these vascular biomarkers may not have survived to inclusion in this study or may have become ineligible. It is also
possible that vascular biomarkers are related to cognitive
performance in younger individuals only. Levels at the age
of entry may not reflect levels earlier in life. Finally, it is possible that there is no association between CRP, glycosylated
haemoglobin and LDL-cholesterol with cognitive performance, and that previous positive reports could be due to
residual and uncontrolled confounding.
Limitations of this study include a single timed measurement of vascular biomarkers, which lends itself to
measurement error. This, if non-differential, could have contributed to an underestimation of the effect of homocysteine
on cognitive performance and the lack of association found
with the other vascular biomarkers. Homocysteine samples in
this study were obtained from non-fasting subjects. However,
studies have found no significant difference between levels of
562
pre- and post-prandial homocysteine when measured in the
same subject [29]. Our sample was an urban Caucasian community population and our findings may not be applicable
to rural or other ethnic populations. Although the response
rate is comparable to other studies, this does not out-rule the
possibility of response bias reducing any association between
the vascular biomarkers and cognitive performance. Due to
the cross-sectional nature of this study, we were unable to
account for survival bias or establish cause and effect.
Finally, our findings support evidence from other studies
suggesting that lifestyle and psychosocial factors may be
important in determining cognitive performance [5, 30].
Factors such as alcohol use, tea intake, depression,
life satisfaction, hypertension, smoking, past history of
stroke, intake of fruit and use of psychotropic medication
were all found to be associated with global cognitive
performance. These factors may need to be taken into
account as potential confounds in future studies investigating
cognition.
Key points
•
•
•
In a cross-sectional study of 466 community-dwelling,
non-demented older people, higher serum homocysteine
was associated with poorer cognitive function.
Other biomarkers such as c-reactive protein, glycosylated
haemaglobin and low-density lipoprotein were not
associated with cognitive function.
A number of psychosocial factors including alcohol use,
tea intake, depression, life satisfaction, smoking and intake
of fruit were all found to be associated with cognitive
performance.
Model 2
Model 1
Model 2
C-reactive protein
Model 1
Model 2
Glycosylated haemaglobin
Model 1
Model 2
Low-density lipoprotein
Standar
Standar
Standar
Standar
Standar
Standar
Standar
Standar
-dised
-dised
-dised
-dised
-dised
-dised
-dised
-dised
P
beta
P
P
beta
beta
beta
P
P
P
beta
beta
P
Cognitive test
P
beta
beta
........................................................................................................................................................................
FAS test
0.010 0.836
0.013 0.796 −0.053 0.361
0.028 0.620
0.013 0.797
0.023 0.637 −0.037 0.510
0.015 0.782
Animals
−0.31
0.504
0.026 0.620 −0.042 0.361 −0.044 0.375
0.066 0.153
0.041 0.418
0.010 0.825 −0.053 0.306
Visual reproduction1
0.021 0.656
−0.127 0.008 −0.117 0.038
0.047 0.390
0.010 0.856
0.037 0.443 <0.001 1.0
0.005 0.921
−0.127 0.008 −0.139 0.012
Visual reproduction2
0.033 0.700
0.030 0.527
0.041 0.440 −0.025 0.594 −0.017 0.752
0.053 0.346
Letter number sequencing
−0.078 0.144 −0.089 0.148 −0.040 0.446 −0.087 0.150 −0.027 0.608
0.008 0.892 −0.099 0.064 −0.028 0.653
Digit symbol score
−0.134 0.006 −0.084 0.121 −0.073 0.130 −0.031 0.564 −0.503 0.268 −0.045 0.400 −0.038 0.439 −0.012 0.829
Verbal immediate free recall −0.086 0.080 −0.114 0.033
0.029 0.546
0.021 0.696
0.008 0.872
0.116 0.018
0.012 0.812
0.031 0.560
Verbal Short delay recall
−0.057 0.243 −0.091 0.093 −0.017 0.720 −0.041 0.442 −0.019 0.692 −0.007 0.900
0.052 0.284 −0.020 0.719
Verbal recognition
−0.076 0.129 −0.088 0.119 −0.034 0.497 −0.024 0.659
0.023 0.643 −0.005 0.929
0.023 0.652 −0.089 0.120
Verbal list B recall
0.026 0.587
−0.125 0.011 −0.127 0.022 −0.048 0.320 −0.006 0.918
0.007 0.900 −0.015 0.764 −0.129 0.022
−0.105 0.053 −0.082 0.178 −0.017 0.758 −0.099 0.101
Composite global score
0.018 0.741
0.063 0.300
0.009 0.865 −0.065 0.311
MMSE
−0.107 0.025 −0.086 0.117
0.014 0.772
0.046 0.338 −0.034 0.545
0.034 0.523 −0.078 0.098 −0.007 0.898
Model 1
Homocysteine
Table 3. Associations between cognitive score and blood tests-adjusted for age, gender, education and social class (model 1) adjusted for age, gender,
education, social class alcohol, tea intake, depression, life satisfaction, hypertension, use of psychotropic medications, smoking, stroke, fruit intake
(model 2)
Vascular biomarkers of cognitive performance in the elderly
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A.-V. Chin et al.
Conflict of interest
None
Ethics approval
Ethics approval was obtained from both the Irish College of
General Practitioners Research Ethics Committee and the St.
James’s Hospital and Federated Dublin Voluntary Hospitals
Joint Research Ethics Committee.
Acknowledgements
This study was funded by Mercer’s Institute for Research on
Ageing.
Supplementary data
Supplementary data for this article are available at Age and
Ageing Online.
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Received 4 September 2007; accepted in revised form 13 March
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