Relationship between plasma lipids and mild cognitive impairment in the elderly Chinese: a case-control study
He et al. Lipids in Health and Disease
Relationship between plasma lipids and mild cognitive impairment in the elderly Chinese: a case-control study
Qian He 1 3
Qing Li 1 2
Jiangang Zhao 1 2
Tianfeng Wu 1 2
Lu Ji 1 2
Guowei Huang 1 2
Fei Ma 0 1
0 Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University , No 22 Qixiangtai Road, Heping District, Tianjin 300070 , China
1 intervals; CSF , Cerebrospinal fluid; HDL-C, High-density lipoprotein cholesterol; LDL-C, Low-density lipoprotein cholesterol; MCI, Mild cognitive impairment; MMSE, Mini-Mental Status Examination; OR, Odds ratio; SD, standard deviation; T2DM, Type 2 diabetes millitus; TC, Total cholesterol; TG, Triglyceride
2 Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University , Tianjin 300070 , China
3 Department of Laboratory, General Hospital of Tianjin Medical University , Tianjin 300052 , China
Background: High lipid levels may constitute a more important risk factor for cognitive health in previous studies. However, the association of plasma lipids with mild cognitive impairment (MCI) among elderly people had not been studied exactly. This study aims to explore the relationship between plasma lipids/lipoproteins and the risk of MCI in elderly Chinese individuals. Methods: CSI-MCI study was a preliminary case-control study of the association of plasma lipids/lipoproteins with MCI in 112 MCI cases and 115 cognitively normal controls. Plasma total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) levels were measured in fasting blood samples. Multivariable logistic regression was used to evaluate the potential association between MCI and these factors. Statistical models were adjusted for multiple demographic and biological covariates. Results: The subjects with MCI were significantly older, higher percentage of females and less educated than controls (P <0.05). As expected, subjects with MCI had lower MMSE score compared with controls (P <0.05). Multivariate logistic regression analysis showed that higher plasma TC level was associated with the risk of MCI in models adjusting for age, sex and education. However, This association was attenuated after adjusting for BMI, Type 2 diabetes mellitus, heart disease and hypertension. Plasma TG level was negatively associated with the risk of MCI. The adjusted odds ratio (OR) of MCI was significantly reduced for the highest quartile of plasma TG level (OR: 0.76, 95 % CI: 0.48-0.97), but not for the second or third quartile, compared with the lowest quartile (adjusted models). Plasma HDL level was significantly negatively associated with the risk of MCI. There was no association between plasma LDL level and the risk of MCI, adjustment for demographics, vascular disorders did not change this relation. Conclusions: Plasma TC was significantly higher in MCI subjects compared to cognitively normal controls, Elevated plasma HDL and triglyceride were associated with the occurrence of MCI. These findings need to be confirmed in further longitudinal studies.
Mild cognitive impairment; Lipid; Lipoprotein; Elderly; Case-control study
Mild cognitive impairment (MCI) is regarded as a
transition stage between the cognitive changes of normal aging
and the more serious problems caused by Alzheimer’s
disease (AD) [
]. Persons with MCI convert to AD at an
annual rate of 10–12 % in contrast to 1–2 % in the elderly
population without MCI [
]. Early diagnosis and
intervention of MCI could postpone or prevent the onset of
subsequent dementia. It is critical to identify potentially
protective factors for the development of MCI and
progression to dementia. There is an important clinical
need for diagnostic biomarkers to identify geriatric
individuals prone to dementia. In recent decades, efforts
have been made to discover biological markers for
dementia and MCI.
Blood-based (non-genetic) biomarkers are important
because they are easily acquired, relatively inexpensive
compared to brain imaging biomarkers, less invasive
than cerebrospinal fluid (CSF) acquisition, and more
amenable to large-scale screening. Lipids and
lipoproteins may directly affect neurodegeneration [
There are numerous studies investigating the relation
between plasma lipid/lipoprotein levels and dementia.
Several studies show that elderly people with AD or
with dementia or cognitive deficits have higher plasma
total cholesterol (TC) or higher low-density lipoprotein
cholesterol (LDL-C) than sex- and age-matched
nondemented peers [
]. Others fail to find such differences
], and still others find negative correlations of serum
lipid values with AD (or with all dementias) [
discrepancy in the results of a significant number of recent
studies indicates that further investigation of lipid
parameters is required, particularly in view of their increased
biological importance and the ease of evaluation in everyday
In this context, using a retrospective study design, we
aimed to explore whether plasma lipid levels are
associated with the risk of MCI in an elderly,
communitydwelling population. Furthermore, we explored whether
observed associations between individual components of
the adverse lipid profiles and risk of MCI were
dependent on or independent of demographics and
Study design and participants
The Community Screening Interview for MCI (CSI-MCI)
study was a population-based case-control study of
comparing MCI subjects with cognitively normal controls. 1151
subjects 65 years or older were randomly selected using the
medical records-linkage system of Binhai New Area in
Tianjin, China. Each participant underwent an interview of
general health and function, medical history, and a
neuropsychological battery. Subjects with a preexisting diagnosis
of dementia were identified by screening their medical
record, and the clinical information was reviewed in detail by a
neurologist (Dr Jiangang Zhao). Subjects confirmed to have
dementia were not invited to participate in the study. A
total of 1028 subjects without dementia were included in
the active evaluation. The evaluations was conducted by
trained graduate students and mental health clinicians, and
conducted from April, 2014 to July, 2014. Among 1028
eligible participants, 112 had MCI. Detailed screening process
can be seen in Fig. 1.
Definition of cases and controls
MCI was identified according with the modified Petersen’s
(1)Subjective memory complaint, with at least 2-week
duration, was reported by the participant and
corroborated by an informant (family or physician);
(2)Objective memory impairment for age and
education has been defined by performing at least
1.5 SD below age and education-matched controls on
memory subtask of Mini-Mental Status Examination
(3)Normal general cognitive function impairment was
defined as a test performance more than 1.5 SD
below age- and education-specific norms;
(4)Essentially preserved activities of daily living, as
measured by Activities of Daily Living scale (ADL),
i.e. a score <26 [
(5)Absence of dementia (Diagnostic and Statistical
Manual of Mental Disorders-IV), AD (the National
Institute of Neurological and Communicative Disorders
and Stroke and the Alzheimer’s Disease and Related
Disorders Association), or psychiatric disorders,
cerebral damages, or physical diseases that may
account for cognitive impairment, and any active
neuropsychiatric condition producing disability.
Cognitive normal controls were screened by using
MMSE tool. MMSE scores ranged from 0 to 30, with
higher scores indicating better cognition. Cognitive
function was classified into four groups based on the standard
classification system [
]:no cognitive impairment (scores
24–30); mild cognitive impairment (scores 18–23);
moderate cognitive impairment(scores 10–17) and severe
cognitive impairment (scores 0–9). Cognitive normal controls
were randomly selected from subjects who scores 24–30
in MMSE. Control subjects had no cognitive complaints,
no evidence of impairment in the ADL due to cognitive
disturbances, In both groups, persons having had a general
anesthesia in the last 6 months, history of neurological
diseases or events (i.e. Parkinson’s disease, epilepsy, brain
anoxia), psychiatric disorder (schizophrenia, major
depression, alcoholism) or traumatic brain injury were excluded
from this study. Presence of other chronic diseases was
not a reason for exclusion.
these comorbidities were confirmed with information
from the medical records-linkage system.
Questionnaire survey and health examination
Structured interviews were carried out with all
participants face-to-face. A variety of potential risk factors for
cognitive function were included in the questionnaire.
Covariates included sociodemographic information [age,
gender, years of education and body mass index (BMI)],
lifestyle (smoking and drinking). BMI was calculated as
weight in kilograms divided by the square of height in
meters. Type 2 diabetes mellitus(T2DM) were defined as
a history of either disorder provided by patients at any
time during life and confirmed by clinical evaluation. If
affirmed, they were asked whether they were under
treatment and the specific type of medication.
Hypertension was defined as SBP > 140 mmHg, DBP > 90 mmHg,
or the use of antihypertensive medication. All
pharmacological treatments received during the month preceding
the interview were recorded. Medical prescriptions and,
when feasible, the medications were checked by the
interviewer. The presence of stroke was ascertained from
an interview with participants and their informants.
When available, previous medical records were reviewed.
Heart disease was defined as a history of myocardial
infarction, congestive heart failure, digitalis use, or angina
pectoris at any time during life. Whenever possible,
Determination of plasma lipids
Blood samples were obtained from each participant after
12-h overnight fasting by standard venipuncture. kept at
4 °C for 1 h, and centrifuged at 3000 rpm for 10 min at
4 °C to obtain plasma and stored at −80 °C until
Plasma TC (normal range: 80–220 mg/dl) and
Triglyceride(TG) (30–200 mg/dl) concentrations were
measured by an Automatic Biochemistry Analyzer (Hitachi
7180, Japan) using commercially available diagnostic kits
(Roche Diagnostic, Mannheim, Germany). High-density
lipoprotein cholesterol (HDL-C) (normal range: 35–
80 mg/dl) concentrations was measured with a Hitachi
911 autoanalyzer. LDL-C (30–160 mg/dl) was estimated
with the Friedenwald equation [
]: LDL-C = TC −
(HDL-C) − (TG/5). Concentrations of plasma lipids and
lipoproteins were grouped into four equal strata
representing decreasing concentrations of lipids and
lipoproteins. All laboratory analyses were conducted by the
central lab in school of public health, Tianjin Medical
University in Tianjin, China.
Lipid levels and other potentially relevant factors were
compared among individuals with MCI and cognitively
normal controls. Mann–Whitney or t-test for
continuous variables and χ2 test for categorical variables (or
trend tests if applicable) were used to test for significant
differences between the groups. Because the distribution
of HDL-C and TG levels was skewed, we performed
logarithmic transformation of these data and repeated
the statistical tests. Multivariate logistic regression was
used to estimate the odds ratio (OR) of MCI associated
with plasma lipid levels. ORs and 95 % confidence
intervals (95 % CIs) were calculated. After adjusting for sex,
age, and education, we performed a second model
adjusting for BMI, T2DM, hypertension, and heart
disease. P < 0.05 was considered statistically significant, and
all P-values were two-sided. All analyses were performed
using SPSS PASW Statistics for Windows, version 18.0
(SPSS Inc., Released 2009, Chicago, IL, USA).
The principal characteristics of the two groups
This study included a total of 227 participants, including
112 persons with MCI and 115 cognitively normal
controls. Lipid levels, demographics, and vascular risk
factors were compared among individuals with MCI and
controls in univariate analyses (Table 1). The subjects
with MCI were significantly older, higher percentage of
females and less educated than controls. As expected,
subjects with MCI had lower MMSE score compared
with controls. No significant differences were found
between MCI subjects and controls for current smoking.
TC concentration was higher in MCI compared with
controls (P <0.05), while HDL-C and TG was lower in
MCI compared with controls (P < 0.05). No statistical
significance was found for LDL-C data between MCI
and control groups. A history of T2DM, heart disease,
and hypertension was more frequent in the MCI groups
compared with the control group (P <0.05).
Multivariate logistic regression analysis
In Table 2 are reported the results of multivariate
logistic regression analysis assessing the effect of plasma
lipids and other variables on the likelihood of having
MCI. Higher plasma TC level was associated with the
risk of MCI in models adjusting for age, sex and
education. However, this association was attenuated after
adjusting for BMI, T2DM, heart disease and
hypertension. Plasma TG level was negatively associated with the
risk of MCI. The adjusted OR of MCI was significantly
reduced for the highest quartile of plasma TG
concentration (OR: 0.76, 95 % CI: 0.48–0.97), but not for the
second or third quartile, compared with the lowest
quartile (adjusted models). Plasma HDL level was
significantly negatively associated with the risk of MCI. There
was no association between plasma LDL level and the
risk of MCI, adjustment for demographics, vascular
disorders did not change this relation.
Heart disease 42 (37.50)* 27 (23.48) 0.031
Figures in parentheses indicate percentages; Values for continuous variables are mean ± standard deviation
Abbreviations: BMI Body Mass Index, HDL-C High-density lipoprotein cholesterol, LDL-C Low-density lipoprotein cholesterol, T2DM diabetes mellitus type II, TC Total
Cholesterol, TG Triglyceride
*significant at P < 0.05 vs control group
aDichotomous variables (n, %) were tested using χ2 test
bContinuous variables (mean, SD) were tested for differences between the two groups using Mann–Whitney or t-test
Data in the table are adjusted OR and 95 % CI
aAdjusted for potential confounders including age, gender, education level
bAdjusted for age, gender, education level, BMI, hypertension, T2DM, and heart disease
In the present study, we explore the association between
blood lipid/lipoprotein profiles and the risk of MCI.
According to our results, after adjustment for some
potential confounding factors, logistic regression models
showed plasma TC was significantly higher in the MCI
subjects compared to cognitively normal controls, while
levels of HDL-C and TG were significantly lower.
LDLC levels did not differ significantly between two groups.
Blood lipid levels are modifiable through diet, exercise,
medications, and/or change in adverse lifestyle habits
such as smoking. Therefore, all these results have an
important policy implication. Strategies to intervene blood
lipid/lipoprotein levels may be a viable population-wide
intervention strategy to help maintain cognitive function
Studies examining the role of plasma lipid levels in
cognitive function reported inconsistent results [
]. Controversial results have also been obtained in
animal studies [
]. Most observational studies were
cross-sectional, the few longitudinal studies mostly
examined manifest dementia but not MCI as the endpoint.
While studies have found a relation between high
cholesterol during mid-life and cognitive impairment or MCI in
old age [
], the Honolulu Asia Aging Study recently
reported in a study with 26 years of follow-up that
cholesterol levels in men with dementia at the end of follow-up
declined at least 15 years before the diagnosis and
remained lower than cholesterol levels in men without
]. Associations relating late-life lipids with
cognitive impairment or dementia were also inconsistent.
Plasma TC level differed significantly between MCI
and control groups. TC were significantly higher in MCI
group compared with the control. We initially observed
that higher TC are associated with MCI adjusting for
age, sex, and education, However, these associations
were attenuated after adjusting for BMI, T2DM, heart
disease and hypertension indicating that the initially
observed inverse associations were caused by confounding.
Notably, our findings are consistent with several
previous studies. One cross-sectional population based study
found that higher levels of TC were associated with a
decreased risk of incident AD after adjustment for many
confounding factors among the Finnish elderly aged 69
to 78 [
]. Prospective longitudinal studies also revealed
that hypercholesterolaemia was associated with a
protective effect for development of dementia and cognitive
decline in the Australian elderly aged 75 years and over
]. Elevated TC level was associated with a
significantly higher risk of MCI, independent of potential
confounding variables, suggesting that cholesterol fractions
could be involved in both AD and MCI. The mechanism
by which raised TC might lead to dementia is unclear.
Recent evidence indicates that alterations in brain
cholesterol homeostasis have been linked to the main
pathological features of AD, in particular Aβ [
evidence suggests that amyloidogenic APP processing
may preferentially occur in the cholesterol-rich regions
of membranes known as lipid rafts, and that changes in
cholesterol levels could exert their effects by altering the
distribution of APP-cleaving enzymes within the
membrane . Functional cell biology studies further
support a critical involvement of lipid raft cholesterol in the
modulation of Aβ precursor protein processing by
βsecretase and γ-secretase resulting in altered Aβ
production. Reduction of cholesterol levels have been shown to
inhibit β-secretase activity [
], but increase the activity
of α-secretase [
], the main proteolytic enzymes
involved in APP metabolism.
Moreover, the HDL-C level was significantly lower in
MCI subjects compared to controls. Which is consistent
with previous research findings [
]. Lower HDL-C
level is associated with more severe lesions of white matter
changes, leading to MCI, even AD . The mechanisms
associating low levels of HDL-C with cognitive impairment
are unknown, and different explanations might be
proposed. HDL-C has been described as a negative risk factor
for the development of cognitive impairment . HDL-C
can prevent aggregation and polymerization of β-amyloid,
thus slowing or even preventing the development of AD
[39, 40]. HDL-C is also reported to have antiinflammatory
properties . Markers of inflammation are found in and
around amyloid plaques and are considered to be
important in the neurodegenerative process. These findings are of
great clinical importance because they suggest that
increasing HDL-C rather than lowering TC might prevent the
development of cognitive impairment and dementia. Existing
cardiovascular research suggests that HDL-C can be raised
relatively easily through a diet containing monounsaturated
and polyunsaturated fats, exercise, eliminating smoking,
and using medications such as niacin, statins and fibrates
among others when necessary . New preventive and
therapeutic strategies should identify the effects of HDL-C
on cognitive function in the elderly.
Currently, there are very few studies on the direct
association between cognitive function and TG. Among
them, some studies show that the level of TG was lower
in patients with cognitive impairment compared with
control group [43, 44], while several found no
relationship between TG and cognition , and others found
that high levels of TG were inversely related with
performance on various cognitive measures [46, 47]. In our
study, high levels of TG were significantly related to
lower odds of MCI. This suggests that higher level of
TG are beneficial for cognitive function. A pathological
concentration of TG may outweigh any protective
effects. These results suggest that TG supplementation to
high normal levels is worthy of study in clinical trials to
determine whether it may improve cognitive function in
In our study, some limitations need to be addressed.
First, this was a case-control study, and cannot prove
causality. These findings need to be confirmed in further
longitudinal studies. Second, our subjects were Chinese
elderly, so these results may not be generalised to other
populations of different nationalities or ages. Third,
although group differences were observed for different
lipid measures, the numerical difference between groups
is small and there is substantial overlap. Perhaps,
population type, diagnostic procedure, confounding control,
presence of bias, statistical power can influence the
accuracy and precision. To better capture the combined
effects of these blood lipids on cognitive function,
longitudinal analysis with multiple consistent lipoproteins
and cognitive measures are needed from mid adulthood
into older ages. The last limitation of the study is the
lack of data for brain imaging or biomarker data (such
as apolipoprotein E 4 allele) of the population sample.
Therefore, a follow-up study, brain imaging, and
biomarker tests will be conducted in the future.
Despite limitations, the chief strength of the present
study include: First, extensively tested and well designed
measurements of neuropsychiatric symptoms provided
reliable diagnoses of MCI and dementia; Second, This is
one of few studies which investigated the blood lipid/
lipoprotein profiles related to cognitive impairment in a
developing country, and adjusted for various important
confounders including vascular risk factors. Third, the
availability of pre-study plasma lipids/lipoproteins levels
and other covariates.
Based on the findings of the present study, it can be
concluded that plasma TC was significantly higher in the
patients with MCI compared to cognitively normal
controls, while HDL-C and TG levels were significantly
lower. LDL-C level did not differ significantly between
two groups. Because associations are not proof of a
causal relation, large randomized controlled clinical
trials regarding blood lipid/lipoprotein profiles and the
onset and course of MCI, AD are under way.
This study was also supported by a grant from the National Natural Science
Foundation of China (grant number: 81130053). Funding from the National
Natural Science Foundation of China supported this research in the design
of the study and collection, analysis, and interpretation of data and in
writing the manuscript. The authors thank all of the subjects for their
Conceived and designed the experiments: FM, QH and GWH; Performed the
experiments: QL, JGZ and TFW; Analyzed the data: QH, QL and LJ; Wrote the
manuscript: FM, QH. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Ethics approval and consent to participate
The study was conducted in compliance with the ethical principles of the
Declaration of Helsinki. All participants were informed of the objectives of
the study and their consent to participate in the study was obtained. The
datasets during and/or analysed during the current study available from the
corresponding author on reasonable request. The research protocol was
approved by the medical ethics committee of Tianjin Medical University,
1. Pankratz VS , Roberts RO , Mielke MM , Knopman DS , Jack Jr CR , Geda YE , et al. Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging . Neurology. 2015 ; 84 : 1433 - 42 .
2. Petersen RC , Smith GE , Waring SC , Ivnik RJ , Tangalos EG , Kokmen E. Mild cognitive impairment:clinical characterization and outcome . Arch Neurol . 1999 ; 56 : 303 - 8 .
3. Hall K , Murrell J , Ogunniyi A , Deeg M , Baiyewu O , Gao S , et al. Cholesterol, APOE genotype, and Alzheimer disease: an epidemiologic study of Nigerian Yoruba . Neurology. 2006 ; 66 : 223 - 7 .
4. Li G , Shofer JB , Kukull WA , Peskind ER , Tsuang DW , Breitner JC , et al. Serum cholesterol and risk of Alzheimer disease: a community-based cohort study . Neurology . 2005 ; 65 : 1045 - 50 .
5. Fischer P , Zehetmayer S , Bauer K , Huber K , Jungwirth S , Tragl KH . Relation between vascular risk factors and cognition at age 75 . Acta Neurol Scand . 2006 ; 114 : 84 - 90 .
6. Reitz C , Tang MX , Manly J , Schupf N , Mayeux R , Luchsinger JA . Plasma lipid levels in the elderly are not associated with the risk of mild cognitive impairment . Dement Geriatr Cogn Disord . 2008 ; 25 : 232 - 7 .
7. Evans RM , Emsley CL , Gao S , Sahota A , Hall KS , Farlow MR , et al. Serum cholesterol, APOE genotype, and the risk of Alzheimer's disease: a population-based study of African Americans . Neurology. 2000 ; 54 : 240 - 2 .
8. Yaffe K , Barrett-Connor E , Lin F , Grady D. Serum lipoprotein levels, statin use, and cognitive function in older women . Arch Neurol . 2002 ; 59 : 378 - 84 .
9. Lesser G , Kandiah K , Libow LS , Likourezos A , Breuer B , Marin D , et al. Elevated serum total and LDL cholesterol in very old patients with Alzheimer's disease . Dement Geriatr Cogn Disord . 2001 ; 12 : 138 - 45 .
10. Kalmijn S , Foley D , White L , Burchfiel CM , Curb JD , Petrovitch H , et al. Metabolic cardiovascular syndrome and risk of dementia in JapaneseAmerican elderly men: the Honolulu-Asia Aging Study . Arterioscler Thromb Vasc Biol . 2000 ; 20 : 2255 - 60 .
11. Tan ZS , Seshadri S , Beiser A , Wilson PW , Kiel DP , Tocco M , et al. Plasma total cholesterol level as a risk factor for Alzheimer disease: the Framingham study . Arch Intern Med . 2003 ; 163 : 1053 - 7 .
12. Slooter AJ , Cruts M , Ott A , Bots ML , Witteman JC , Hofman A , et al. The effect of APOE on dementia is not through atherosclerosis: the Rotterdam study . Neurology . 1999 ; 53 : 1593 - 5 .
13. Mielke MM , Zandi PP , Sjogren M , Gustafson D , Ostling S , Steen B , et al. High total cholesterol levels in late life associated with a reduced risk of dementia . Neurology . 2005 ; 64 : 1689 - 95 .
14. Solfrizzi V , Panza F , D'Introno A , Colacicco AM , Capurso C , Basile AM , et al. Lipoprotein(a), apolipoprotein E genotype, and risk of Alzheimer's disease . J Neurol Neurosurg Psychiatry . 2002 ; 72 : 732 - 6 .
15. Petersen RC . Mild cognitive impairment as a diagnostic entity . J Intern Med . 2004 ; 256 : 183 - 94 .
16. Ritchie K , Artero S , Touchon J . Classification criteria for mild cognitive impairment. A population-based validation study . Neurology . 2001 ; 56 : 37 - 42 .
17. Perneczky R , Pohl C , Sorg C , Hartmann J , Komossa K , Alexopoulos P , Wagenpfeil S , et al. Complex activities of daily living in mild cognitive impairment: conceptual and diagnostic issues . Age Ageing . 2006 ; 35 : 240 - 5 .
18. Tombaugh TN , McIntyre NJ . The mini-mental state examination: a comprehensive review . J Am Geriatr Soc . 1992 ; 40 : 922 - 35 .
19. Friedewald WT , Levy RI , Fredrickson DS . Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of preparative ultracentrifuge . Clin Chem . 1972 ; 18 : 499 - 502 .
20. Michikawa M. Cholesterol paradox: is high total or low HDL cholesterol level a risk for Alzheimer's disease? J Neurosci Res . 2003 ; 72 : 141 - 6 .
21 Kivipelto M , Helkala EL , Hanninen T , Laakso MP , Hallikainen M , Alhainen K , et al. Midlife vascular risk factors and late-life mild cognitive impairment: a population-based study . Neurology . 2001 ; 56 : 1683 - 9 .
22 Li G , Higdon R , Kukull WA , Peskind E , Van Valen MK , Tsuang D , et al. Statin therapy and risk of dementia in the elderly: a communitybased prospective cohort study . Neurology . 2004 ; 63 : 1624 - 8 .
23 Schreurs BG , Smith-Bell CA , Lochhead J , Sparks DL . Cholesterol modifies classical conditioning of the rabbit (Oryctolagus cuniculus) nictitating membrane response . Behav Neurosci . 2003 ; 117 : 1220 - 32 .
24 Sparks DL , Schreurs BG . Trace amounts of copper in water induce beta-amyloid plaques and learning deficits in a rabbit model of Alzheimer's disease . Proc Natl Acad Sci U S A . 2003 ; 100 : 11065 - 9 .
25 Stewart R , White LR , Xue QL , Launer LJ . Twenty-six-year change in total cholesterol levels and incident dementia: the Honolulu-Asia Aging Study . Arch Neurol . 2007 ; 64 : 103 - 7 .
26 Kuusisto J , Koivisto K , Mykkänen L , Helkala E , Vanhanen M , Hänninen T , et al. Association between features of the insulin resistance syndrome and Alzheimer's disease independently of apolipoprotein E4 phenotype: cross sectional population based study . BMJ . 1997 ; 315 : 1045 - 9 .
27 Piguet O , Grayson DA , Creasey H , Bennett HP , Brooks WS , Waite LM , et al. Vascular risk factors, cognition and dementia incidence over 6 years in the Sydney Older Persons Study . Neuroepidemiology . 2003 ; 22 : 165 - 71 .
28 Burns M , Duff K. Cholesterol in Alzheimer's disease and tauopathy . Ann N Y Acad Sci . 2002 ; 977 : 367 - 75 .
29 Sponne I , Fifre A , Koziel V , Oster T , Olivier JL , Pillot T. Membrane cholesterol interferes with neuronal apoptosis induced by soluble oligomers but not fibrils of amyloid-beta peptide . FASEB J . 2004 ; 18 : 836 - 8 .
30 Cordy JM , Hooper NM , Turner AJ . The involvement of lipid rafts in Alzheimer's disease . Mol Membr Biol . 2006 ; 23 : 111 - 22 .
31 Simons M , Keller P , De Strooper B , Beyreuther KT , Dotti CG , Simons K. Cholesterol depletion inhibits the generation of b-amyloid in hippocampal neurons . Proc Natl Acad Sci U S A . 1998 ; 95 : 6460 .
32 Kojro E , Gimpl G , Lammich S , März W , Fahrenholz F. Low cholesterol stimulates the nonamyloidogenic pathway by its effect on the a-secretase ADAM 10 . Proc Natl Acad Sci . 2001 ; 98 : 5815 .
33 Atzmon G , Gabriely I , Greiner W , Davidson D , Schechter C , Barzilai N . Plasma HDL levels highly correlate with cognitive function in exceptional longevity .
2002 ;57: M712 - 5 .
Károssy K , Kerekes Z , Horváth D , G˝oocze P, Kállai J . Association of high and low density serum cholesterol, cognitive performance and emotional well-being in menopausal women . Rev Psychol . 2007 ; 14 : 13 - 23 .
Reynolds CA , Gatz M , Prince JA , Berg S , Pedersen NL . Serum lipid levels and cognitive change in late life . J Am Geriatr Soc . 2010 ; 58 : 501 - 9 .
van den Kommer T , Dik M , Comijs H , Jonker C , Deeg D. The role of lipoproteins and inflammation in cognitive decline: do they interact? Neurobiol Aging . 2012 ; 33 : 196 . e191 - 196 . e112 .
Zhuang L , Sachdev PS , Trollor JN , Reppermund S , Kochan NA , Brodaty H , et al. Microstructural white matter changes, not hippocampal atrophy, detect early amnestic mild cognitive impairment . PLoS One . 2013 ; 8 : e58887 .
Castano EM , Prelli F , Wisniewski T , et al. Fibrillogenesis in Alzheimer's disease of amyloid β peptides and apolipoprotein E. Biochem J. 1995 ; 306 : 599 - 604 .
Cockerill GW , Rye KA , Gamble JR , Vadas MA , Barter PJ . High density lipoproteins inhibit cytokine-induced expression of endothelial cell adhesion molecules . Arterioscler Thromb Vasc Biol . 1995 ; 15 : 1987 - 94 .
McGeer EG , McGeer PL . The importance of inflammatory mechanisms in Alzheimer's disease . Exp Gerontol . 1998 ; 33 : 371 - 8 .
Cockerill GW , Huehns TW , Weerasinghe A , Stocker C , Lerch PG , Miller NE , et al. Elevation of plasma high-density lipoprotein concentration reduces interleukin-1-induced expression of E-selection in an in vivo model of acute inflammation . Circulation . 2001 ; 103 : 108 - 12 .
Andersen CJ , Fernandez ML . Dietary approaches to improving atheroprotective HDL functions . Food & Function . 2013 ; 4 : 1304 - 13 .
Characterization of the lipid profile in dementia and depression in the elderly . J Geriatr Psychiatry Neurol . 2007 ; 20 : 138 - 44 .
Lepara O , Valjevac A , Alajbegović A , Zaciragic A , Nakas-Icindic E . Decreased serum lipids in patients with probable Alzheimer's disease . Bosn J Basic Med Sci . 2009 ; 9 : 215 - 20 .
Huang CQ , Dong BR , Wu HM , Zhang YL , Wu JH , Lu ZC , et al. Association of cognitive impairment with serum lipid/lipoprotein among Chinese nonagenarians and centenarians . Dement Geriatr Cogn Disord . 2009 ; 27 : 111 - 6 .
Relationships among blood pressure, triglycerides and verbal learning in African Americans . J Natl Med Assoc . 2008 ; 100 : 1193 - 8 .