Skip to main content
PMC home page
Neurology logoLink to Neurology
. 2023 Sep 12;101(11):e1127–e1136. doi: 10.1212/WNL.0000000000207595

Association Between Fluctuations in Blood Lipid Levels Over Time With Incident Alzheimer Disease and Alzheimer Disease–Related Dementias

Ethan D Moser 1, Sheila M Manemann 1, Nicholas B Larson 1, Jennifer L St Sauver 1, Paul Y Takahashi 1, Michelle M Mielke 1, Walter A Rocca 1, Janet E Olson 1, Véronique L Roger 1, Alan T Remaley 1, Paul A Decker 1, Jill M Killian 1, Suzette J Bielinski 1,✉
PMCID: PMC10513892  PMID: 37407257

Abstract

Background and Objectives

Prevention strategies for Alzheimer disease and Alzheimer disease–related dementias (AD/ADRDs) are urgently needed. Lipid variability, or fluctuations in blood lipid levels at different points in time, has not been examined extensively and may contribute to the risk of AD/ADRD. Lipid panels are a part of routine screening in clinical practice and routinely available in electronic health records (EHR). Thus, in a large geographically defined population-based cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD.

Methods

All residents living in Olmsted County, Minnesota on the index date January 1, 2006, aged 60 years or older without an AD/ADRD diagnosis were identified. Persons with ≥3 lipid measurements including total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in the 5 years before index date were included. Lipid variation was defined as any change in individual's lipid levels over time regardless of direction and was measured using variability independent of the mean (VIM). Associations between lipid variation quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Participants were followed through 2018 for incident AD/ADRD.

Results

The final analysis included 11,571 participants (mean age 71 years; 54% female). Median follow-up was 12.9 years with 2,473 incident AD/ADRD cases. After adjustment for confounding variables including sex, race, baseline lipid measurements, education, BMI, and lipid-lowering treatment, participants in the highest quintile of total cholesterol variability had a 19% increased risk of incident AD/ADRD, and those in highest quintile of triglycerides, variability had a 23% increased risk.

Discussion

In a large EHR derived cohort, those in the highest quintile of variability for total cholesterol and triglyceride levels had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this association are needed.

Introduction

Vascular risk factors, including hyperlipidemia, measured at a single point in midlife have been associated with the risk of Alzheimer disease and Alzheimer disease–related dementias (AD/ADRD), albeit with inconsistent results.1-6 However, these studies primarily examined these risk factors at a single point in time. Only a few studies have considered whether changes in blood lipids levels over time are associated with AD/ADRD independent of mean lipid levels.

The authors of a study found there was a significant association between total cholesterol variation and incident all-cause dementia, Alzheimer disease (AD), and vascular dementia.7 Variation in body mass index (BMI), systolic blood pressure, and glucose had similar associations, and there was a composite effect between the number of high-varying (highest quartile) parameters, and the risk of incident all-cause dementia, AD, and vascular dementia.7 Similarly, the authors of another study8 found that persons in the highest quartile of total cholesterol variation had a significantly increased risk of incident AD and all-cause dementia compared with persons in the lowest quartile of variation; however, this was not seen for vascular dementia. These results were significant after adjustment for mean lipid levels which may indicate that management of overall lipid levels alongside intraindividual lipid variation may be important in reducing the risk of AD/ADRD.

Thus, while total cholesterol variation over time has been consistently associated with AD/ADRD, cholesterol types such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides and their association to AD/ADRD are not fully understood. An understanding of these cholesterol types may provide insight for the pathologic process between lipid variation and AD/ADRD. In addition, understanding which of these lipid components poses a risk for AD/ADRD may give insight into how current treatments for different cholesterol types play a role in this process. Therefore, in a large geographically defined population cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD.

Methods

Study Population

The Rochester Epidemiology Program (REP) is a medical records-linkage system facilitating the retrieval of health care data from community providers delivering care to residents of southern Minnesota and western Wisconsin for clinical research studies.9-11 REP resources were used to identify a cohort of 21,132 Olmsted County, Minnesota residents aged 60 or older on January 1, 2006. The REP indexes were searched to identify all lipid level results and potential confounding variables between January 1, 2001, and December 31, 2005. Individuals were excluded if they had a previous diagnosis of AD/ADRD (n = 1,223) or if they did not have 3 or more lipid measurements within the baseline data collection period (n = 8,338). The final cohort included 11,571 participants.

Lipid values (total cholesterol, HDL-C, LDL-C, and triglycerides) were collected, and the most recent measurement before January 1, 2006, was considered the baseline lipid measurement. Distribution of the number of measurements per person by lipid type can be found in eFigures 1–4 (links.lww.com/WNL/C931).

The data collection methods for this cohort have been previously described.12 In brief, BMI was calculated as k/m2. Patient-provided information was used to ascertain smoking status, educational attainment, and relationship status. The Centers for Medicare & Medicaid Services (CMS) International Classification of Disease (ICD) code set for comorbidities was used to determine whether participants had a history of hyperlipidemia, diabetes, cancer, myocardial infarction, and/or stroke.13 Baseline antilipidemic or lipid-lowering therapy use was ascertained using National Drug File Reference Terminology classifications C8912 (antilipidemic agents) and C9438 (nicotinic acid). Individuals with an active prescription at index were considered to be on lipid-lowering treatment. In addition, lipid-lowering treatment adherence was divided into 3 categories: (1) continuous (<30 days between prescriptions), (2) intermediate (>30 days between prescriptions), and (3) no lipid-lowering treatment prescription during baseline data collection.

The primary outcome was an incident diagnosis of AD/ADRD, as defined by the CMS ICD code list (eTable 1, links.lww.com/WNL/C931).13 Any billing using these ICD codes was considered a dementia diagnosis. We did not differentiate by dementia type but included all dementia under the AD/ADRD definition. This validated code set includes ICD codes related to frontotemporal dementia including Pick disease. However, only a small number of patients were affected by these codes; thus, we left the code set as presented. The study population was followed from baseline to incident AD/ADRD, death, or until December 31, 2018, whichever came first. Participants who died were censored on their death date and those without AD/ADRD were censored at the last date known to be not deceased.

Statistical Analysis

Participants included in the study were compared with those excluded using the two-sample t test (or the Wilcoxon rank-sum test) for continuous variables and the χ2 test (or the Fisher exact test) for categorical variables. Lipid variability was calculated when 3 or more lipid measurements were available on 3 different days. Variability was assessed using variability independent of the mean (VIM)14,15 because this measure is robust to heteroscedasticity and uncorrelated with the mean measurement. VIM is a measure of lipid variation over time without regard to the directionality and was calculated as:

graphic file with name WNL-2023-000408m1.jpg

where Inline graphic is calculated from fitting a power model Inline graphic

and Inline graphic. Variability will be used to refer to VIM throughout the rest of the article.

As a sensitivity analysis, we also assessed variation by using the standard deviation, coefficient of variation, average real variability, successive variation, and root-mean-squared error (eTable 2, links.lww.com/WNL/C931). Moreover, we conducted a sensitivity analysis excluding individuals who had events or censored 1, 2, and 3 years from the start of follow-up. Age-stratified analysis of 60–69-year-olds and those aged 70 years and older was also conducted. The association of patient characteristics with variability quintiles was assessed using the Kruskal–Wallis or χ2 tests as appropriate. The association of lipid variation with AD/ADRD was assessed using Cox proportional hazards regression using age as a time scale. Based primarily on the Framingham dementia risk score,16 2 models were fit: Model 1 included sex, race/ethnicity, and the baseline lipid measurement as covariates. Model 2 included sex, race/ethnicity, baseline lipid measurement, relationship status, education level, BMI at index, prior stroke, prior diabetes, prior myocardial infarction, prior cancer (excluding nonepithelial skin cancer), and lipid-lowering treatment as covariates. Multiple imputation was used for missing covariates. Five data sets were imputed for each analysis, and the results were pooled using Rubin rules. Each lipid cohort was imputed separately because not all participants had at least 3 measurements for each lipid. Complete-case and multiple imputation analyses are reported. Two-sided p-values < 0.05 were considered statistically significant. SAS version 9.4 was used for all analyses.17

Standard Protocol Approvals, Registrations, and Patient Consents

This study was approved by the Mayo Clinic and Olmsted Medical Center Institutional Review Boards. The study was considered minimal risk by both Institutional Review Boards; thus, the requirement for informed consent was waived. However, patients who did not provide authorization to use their medicals records for research were excluded.

Data Availability

Because of the sensitive nature of the data collected for this study, requests to access the data set from qualified researchers trained in human subject confidentiality protocols may be sent to info@rochesterproject.org.

Results

A total of 11,571 individuals were included in the final analysis. The comparison of the cohort participants free of AD/ADRD at baseline who met the inclusion requirements and those excluded from the analysis are summarized in Table 1. Compared with persons excluded, persons included were younger (mean age 71 vs 73 years, p < 0.001) and less likely to be female (54% vs 59%). Regarding medical conditions, persons included in the analyses were more likely to have a history of stroke (13% vs 9%), myocardial infarction (7% vs 2%), diabetes (35% vs 13%), or cancer (22% vs 17%). In addition, persons included in the analysis were more likely to be on lipid-lowering treatment at baseline (50% vs 6%) and within the 5 years before baseline (67% vs 11%) than persons excluded.

Table 1.

Baseline Characteristics of Participants Free of Alzheimer Disease and Alzheimer Disease–Related Dementias at Baseline With and Without Lipid Data

graphic file with name WNL-2023-000408t1.jpg

Open in a new tab

Table 2 summarizes the baseline characteristics of the study population stratified by quintiles of variability for total cholesterol. Baseline characteristics by quintiles of variability for triglycerides, HDL-C, and LDL-C are included in eTables 3–5 (links.lww.com/WNL/C931). The proportion of female patients decreased as quintile of variability increased for total cholesterol and triglycerides, whereas the inverse was observed for HDL-C. There was a higher proportion of never smokers in the lowest quintile for all lipids. In addition, as quintile of variability for total cholesterol increased, mean HDL and LDL levels decreased, and mean triglyceride levels increased.

Table 2.

Baseline Characteristics by Quintile of Total Cholesterol Variability Independent of the Mean (VIM)

graphic file with name WNL-2023-000408t2.jpg

Open in a new tab

Over a mean (SD) follow-up of 10 (4.0) years, 2,473 individuals (21%) developed incident AD/ADRD. The multiple imputation analysis showed that persons in the highest quintile of variation had an increased risk of incident AD/ADRD of 19% (Q5 vs Q1 HR: 1.19, 95% confidence interval [CI] 1.04 to 1.36, p = 0.011) for total cholesterol and 23% (Q5 vs Q1 HR 1.23, 95% CI 1.08 to 1.41, p = 0.002) for triglycerides in the fully adjusted model (Figure 1). By contrast, variations in LDL-C and HDL-C were not associated with an increased risk of AD/ADRD in fully adjusted models. The results for the complete case analyses were consistent with the multiple imputation analyses (eTable 6, links.lww.com/WNL/C931). Similarly, the results using the other lipid variation measures listed in eTable 2 (e.g., coefficient of variation, standard deviation, etc.) were consistent (data not shown). Finally, we performed weighted models using inverse weight of the number of lipid measurements, and the results were similar (data not shown).

Figure 1. Association of Incident AD/ADRD With Variability Independent of the Mean (VIM) Quintile of Total Cholesterol, Triglycerides, Low-Density Lipoprotein Cholesterol (LDL-C), and High-Density Lipoprotein Cholesterol (HDL-C).

Figure 1

Open in a new tab

Model 1 adjusted for sex, race/ethnicity, and baseline lipid measurement. Model 2 adjusted for model 1 variables plus relationship status, education level, BMI, stroke, diabetes, myocardial infarction, cancer except nonepithelial skin cancer, and lipid-lowering treatment.

Analyses excluding individuals with events or censored within 1, 2, and 3 years yielded similar results after adjusting for confounders (eTable 7, links.lww.com/WNL/C931). Age-stratified sensitivity analysis found total cholesterol and triglycerides were not significantly associated with AD/ADRD among participants aged 60–69 years in the fully adjusted multiple imputation model (eTable 8). In the fully adjusted model for participants aged 70 years and older, the association between total cholesterol and AD/ADRD at the highest quintile was attenuated with borderline statistical significance (p = 0.063) while quintiles 2 (p = 0.038) and 3 (p = 0.017) were statistically significant (eTable 9). Among participants aged 70 years and older, triglycerides association to AD/ADRD was similar (Q5 vs Q1 HR 1.23, 95% CI 1.05–1.43, p = 0.009; eTable 9).

The interaction between lipid-lowering medication history (i.e., never, intermittent, continuous) and variability quintiles for each lipid measure was assessed. No statistically significant interactions were observed (p > 0.08 in each case for multiple imputation analysis; p > 0.07 in each case for complete case analysis). In addition, there was no statistically significant interaction between sex and lipid variability.

Discussion

In this study, high variability in total cholesterol and triglyceride levels was associated with incident AD/ADRD in a large population-based cohort. This association was found independent of multiple confounders including baseline cholesterol levels and adherence to lipid-lowering treatment. By contrast, variability in LDL-C and HDL-C levels was not associated with incident AD/ADRD.

The present association between high variation in total cholesterol or triglycerides and risk of AD/ADRD is consistent with previous studies.7,8 Specifically, total cholesterol variation was found to be a predictor of cardiovascular and coronary incidence and mortality, myocardial infarction, stroke, and all-cause mortality.18,19 In addition, previous studies have found that LDL-C, HDL-C, and triglyceride variation were predictors of coronary and cardiovascular events, stroke, and myocardial infarction independent of mean levels and lipid-lowering treatment.20,21 Moreover, variation in fasting blood glucose and total cholesterol, systolic blood pressure, and BMI had significant association with all-cause mortality, myocardial infarction, and stroke.19 Finally, an additive effect was seen in the number of high-variation parameters and risk of both cardiovascular and dementia outcomes.7,22 This pattern may indicate that lipid variation comes with a risk of adverse vascular and neurologic events.

It should be noted that our study excluded individuals younger than 60 years resulting in an older population than previous studies; however, the prevalence of AD/ADRD is small among those younger than 60 years.7,8 Although potential mechanisms contributing to the association between increased variation in lipids and risk of AD/ADRD are not well understood, 1 explanation could be endothelial dysfunction which has been shown to be an early marker for atherosclerosis.23 Increased levels of serum markers related to endothelial dysfunction have also been shown to increase the risk of cognitive impairment and lower cerebral blood flow which may increase the risk of incident AD/ADRD in later life.24,25 Moreover, atherosclerosis has been found to increase the risk of Alzheimer disease.26 Total cholesterol variation may also lead to plaque instability increasing the risk of cerebrovascular damage potentially contributing to incident AD/ADRD.27

The association between lipids and AD/ADRD has shown inconsistent results much of which is dependent on when lipids are measured. High total cholesterol during midlife has been associated with increased risk of Alzheimer disease in later life.1,28 However, high total cholesterol levels during late life have been associated with decreased risk of Alzheimer disease.2,3 To account for potential differences between lipid variability associations by age, we stratified our sample by those aged 60–69 years and aged 70 years and older. Those aged 70 years and older in the highest quintile of total cholesterol had borderline significant association with incident AD/ADRD, and those in quintiles 2 and 3 had significant associations to AD/ADRD. It is unclear why those in quintile 2 and 3 but not quintile 5 had significant associations. We also found that only the highest quintile of triglyceride variability remained significantly associated with AD/ADRD among those aged 70 years and older. It may be that fluctuation in triglycerides is related to early stages of dementia and changes in behavior. Those in the highest quintile of triglyceride variability had the lowest BMI and also the lowest triglyceride levels. Lower BMI is associated with decreased triglyceride levels, and decreasing BMI is also associated with early phases of Alzheimer disease.29 This may indicate that triglyceride variability is a biomarker of AD/ADRD rather than a risk factor. However, in our analyses, we adjusted for both baseline lipid levels and BMI in addition to conducting sensitivity analysis excluding individuals with an event or censored within 1, 2, and 3 years of follow-up which did not attenuate results.

Our results also indicated that LDL-C and HDL-C variation were not associated with incident AD/ADRD. Few studies have investigated the association between LDL-C and HDL-C variability with AD/ADRD. Previous studies have observed an association of LDL-C variation and decreased cognitive function and lower cerebral blood flow.30 It is possible that LDL-C variation contributes to AD/ADRD through lower cerebral blood flow and decreased cognitive function. Both low and high levels of plasma HDL-C have been associated with increased AD/ADRD risk.31 The null relationship between HDL-C and LDL-C variation and AD/ADRD risk may be due to decreased sensitivity of these lipid profiles to early stages of dementia, diet, and other factors related to aging and frailty. Plasma HDL-C and apolipoprotein E (APOE) may be associated because HDL-like particles and APOE are critical for neuronal function within the CNS.31 HDL-C and HDL-C variations relationship to AD/ADRD may be dependent on APOE haplotypes; however, our study did not have access to this information.32

APOE, specifically APOE ε4 allele, has long been known to significantly increase the risk of late-onset AD because of its role in lipid homeostasis.33 APOE has been shown to modulate the impact of cerebrovascular risk factors on the AD risk. Increases in the Framingham coronary heart disease risk score was associated with decreased cognitive decline in patients with late-onset AD only among patients carrying APOE4+ haplotypes (ε4/ε4, ε4/ε3, ε4/ε2).34 Moreover, APOE4+ carriers with AD functional and cognitive scores were not affected by variations in lipid profiles, while APOE4 carriers with AD benefited from increased LDL-C and were negatively affected by increased HDL-C levels.35 It has been found that there is a positive linear association between APOE haplotypes (e2/e2, e2/e3, e2/e4, e3/e3, e3/e4, e4/e4) with both total cholesterol and LDL-C levels among healthy individuals.36 A weak inverse relationship was found for HDL-C levels.36 The impact of APOE on lipid profiles and how they affect AD risk could further affect lipid variability association with AD/ADRD. In our study, no significant interaction between lipid-lowering treatment history and lipid variation on AD/ADRD risk was found. Previous studies have found that high cholesterol is associated with increased cognitive decline among patients with AD who use cholinesterase inhibitors.37 Moreover, lipophilic statins have been found to have varying effects on patients with late-onset AD depending on APOE haplotypes and other gene-gene interactions.38,39 The importance of APOE haplotypes has shown to be pertinent to lipid profiles of healthy individuals and those with AD and modulates the impact of lipid-lowering treatments on AD. This shows the importance of stratification and adjustment by APOE haplotypes for future studies looking at the association between lipid variability and AD/ADRD as well as the role different types of lipid-lowering treatments play in this.

This study has some limitations that should be mentioned. First, the persons included in the analyses were different from the persons excluded. In general, the persons included had higher levels of comorbidity and less missing data. Although this might be expected because of the requirement of multiple lipid panel screening tests in the EHR within 5 years, the degree to which this might bias the results is unknown. Second, we used ICD codes to ascertain AD/ADRD diagnosis and underdiagnosis has been previously reported.40 Thus, our outcomes likely reflect more severe disease. Third, we did not differentiate dementia subtypes, rather included the entire spectrum with AD/ADRD definition. Moreover, we did not have data available on APOE haplotypes, and therefore, we could not adjust for its impact on lipid variation. We also could not account for the specific type of lipid-lowering medication participants were taking. In addition, our analyses involved extraction of lipid levels from the EHR, which may not be uniformly collected like in other prospective cohort studies. Moreover, we used VIM to assess lipid variation which does not assess directionality. In addition, lipid variation could be a result of AD/ADRD or other health outcomes associated with frailty. Frail individuals may have difficulties in self-care and keeping up proper nutrition leading to variation in lipid levels. An important question is whether lipid variation is a risk factor for incident AD/ADRD or whether AD/ADRD is a proxy for frailty. Lipid variation association may not be specific to AD/ADRD but may involve other conditions associated with frailty. This study is further limited because of having no baseline cognitive data to fully account for undiagnosed AD/ADRD cases. Reverse causation with undiagnosed AD/ADRD may cause changes in eating and activity leading to lipid variation. To account for potential reverse causation, we conducted sensitivity analyses excluding participants with events or censored within 1, 2, and 3 years. Undiagnosed AD/ADRD causing lipid variation may bias our results, but this is likely toward the null, making our estimates conservative. In addition, while this study explored the association of lipid variabilities with AD/ADRD using 3 measurements from different days before baseline, we lacked ample data to explore this relationship longitudinally. To further elucidate this association, future studies should explore the longitudinal relationship between lipid variability and AD/ADRD. Furthermore, our cohort was predominantly White, representing the upper Midwest population, so we were unable to assess heterogeneity across races/ethnicities. Finally, although it is routine clinical practice to measure lipid levels in a fasting state, we are unable to confirm this with our data.

This study also has several strengths. First, our population included everyone in a defined geographical region with robust capture of real-world EHR data within the community through the REP. Second, our study had a long follow-up period (mean = 12 years), and we accounted for the use of lipid-lowering treatment and adherence to such treatments in our analysis. Finally, in addition to studying total cholesterol, we also assessed the association of the lipid subtypes with AD/ADRD.

In conclusion, high variation in total cholesterol and triglycerides after the age of 60 is associated with an increased risk of incident AD/ADRD. Further studies looking at this relationship across diverse populations and at the potential biological mechanisms for such a relationship are needed. Moreover, studies looking at how APOE genotype modifies this association are needed. Whether lipid variability is a biomarker for AD/ADRD or a risk factor remains unclear. Prospective studies looking at longitudinal changes in this relationship may better elucidate this relationship.

Glossary

AD

Alzheimer disease

AD/ADRD

Alzheimer disease and Alzheimer disease–related dementias

BMI

body mass index

CI

confidence interval

CMS

Centers for Medicare & Medicaid Services

EHR

electronic health records

HDL-C

high-density lipoprotein cholesterol

ICD

International Classification of Disease

LDL-C

low-density lipoprotein cholesterol

REP

Rochester Epidemiology Program

VIM

variability independent of the mean

Appendix. Authors

Appendix.

Open in a new tab

Footnotes

CME Course: NPub.org/cmelist

Study Funding

Funding for this study was provided by a grant from the National Heart, Lung, and Blood Institute (R01 HL136659). This study used the resources of the Rochester Epidemiology Project (REP) medical records-linkage system, which is supported by the National Institute on Aging (NIA; AG 058738), by the Mayo Clinic Research Committee, and by fees paid annually by REP users. The content of this article is solely the responsibility of the authors and does not represent the official views of the NIH or Mayo Clinic.

Disclosure

M.M. Mielke has served on scientific advisory boards and/or has consulted for Biogen, LabCorp., Lilly, Merck, and Siemens Healthineers and receives grant support from the National Institute of Health and Department of Defense; all other authors report no disclosures relevant to the manuscript. Go to Neurology.org/N for full disclosures.

References

  • 1.Kivipelto M, Helkala EL, Laakso MP, et al. . Midlife vascular risk factors and Alzheimer's disease in later life: longitudinal, population based study. BMJ. 2001;322(7300):1447-1451. doi: 10.1136/bmj.322.7300.1447 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Reitz C, Tang MX, Luchsinger J, Mayeux R. Relation of plasma lipids to Alzheimer disease and vascular dementia. Arch Neurol. 2004;61(5):705-714. doi: 10.1001/archneur.61.5.705 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Mielke MM, Zandi PP, Sjogren M, et al. , High total cholesterol levels in late life associated with a reduced risk of dementia. Neurology. 2005;64(10):1689-1695. doi: 10.1212/01.WNL.0000161870.78572.A5 [DOI] [PubMed] [Google Scholar]
  • 4.Zhou F, Deng W, Ding D, et al. . High low-density lipoprotein cholesterol inversely relates to dementia in community-dwelling older adults: the Shanghai Aging Study. Front Neurol. 2018;9:952. doi: 10.3389/fneur.2018.00952 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.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(1):103-107. doi: 10.1001/archneur.64.1.103 [DOI] [PubMed] [Google Scholar]
  • 6.Mielke MM, Zandi PP, Shao H, et al. . The 32-year relationship between cholesterol and dementia from midlife to late life. Neurology. 2010;75(21):1888-1895. doi: 10.1212/WNL.0b013e3181feb2bf [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Lee SH, Han K, Cho H, et al. . Variability in metabolic parameters and risk of dementia: a nationwide population-based study. Alzheimers Res Ther. 2018;10(1):110. doi: 10.1186/s13195-018-0442-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Chung HS, Lee JS, Kim JA, et al. . Variability in total cholesterol concentration is associated with the risk of dementia: a nationwide population-based cohort study. Front Neurol. 2019;10:441. doi: 10.3389/fneur.2019.00441 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.StSauver JL, Grossardt BR, Leibson CL, Yawn BP, Melton LJ 3rd, Rocca WA. Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project. Mayo Clin Proc. 2012;87(2):151-160. doi: 10.1016/j.mayocp.2011.11.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Rocca WA, Yawn BP, StSauver JL, Grossardt BR, Melton LJ 3rd. History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population. Mayo Clin Proc. 2012;87(12):1202-1213. doi: 10.1016/j.mayocp.2012.08.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Rocca WA, Grossardt BR, Brue SM, et al. . Data resource profile: expansion of the Rochester Epidemiology Project medical records-linkage system (E-REP). Int J Epidemiol. 2018;47(2):368-368j. doi: 10.1093/ije/dyx268 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Manemann SM, StSauver JL, Liu H, et al. . Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population. BMJ Open. 2021;11(6):e044353. doi: 10.1136/bmjopen-2020-044353 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.CCW CfMMSCCDW. CCW Condition Algorithms. Accessed February 2, 2023. ccwdata.org/web/guest/condition-categories. [Google Scholar]
  • 14.Rothwell PM, Howard SC, Dolan E, et al. . Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet. 2010;375(9718):895-905. doi: 10.1016/S0140-6736(10)60308-X [DOI] [PubMed] [Google Scholar]
  • 15.Webb AJ, Fischer U, Rothwell PM. Effects of beta-blocker selectivity on blood pressure variability and stroke: a systematic review. Neurology. 2011;77(8):731-737. doi: 10.1212/WNL.0b013e31822b007a [DOI] [PubMed] [Google Scholar]
  • 16.Li J, Ogrodnik M, Devine S, Auerbach S, Wolf PA, Au R. Practical risk score for 5-, 10-, and 20-year prediction of dementia in elderly persons: Framingham Heart Study. Alzheimers Dement. 2018;14(1):35-42. doi: 10.1016/j.jalz.2017.04.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.SAS. SAS v9.4. SAS Institute Inc. Accessed February 22, 2023. sas.com/en_us/contact.html. [Google Scholar]
  • 18.Kreger BE, Odell PM, D'Agostino RB, Wilson PF. Long-term intraindividual cholesterol variability: natural course and adverse impact on morbidity and mortality—the Framingham Study. Am Heart J. 1994;127(6):1607-1614. doi: 10.1016/0002-8703(94)90393-x [DOI] [PubMed] [Google Scholar]
  • 19.Kim MK, Han K, Kim HS, et al. . Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population-based study. Eur Heart J. 2017;38(48):3560-3566. doi: 10.1093/eurheartj/ehx585 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Waters DD, Bangalore S, Fayyad R, et al. . Visit-to-visit variability of lipid measurements as predictors of cardiovascular events. J Clin Lipidol. 2018;12(2):356-366. doi: 10.1016/j.jacl.2017.12.003 [DOI] [PubMed] [Google Scholar]
  • 21.Bangalore S, Breazna A, DeMicco DA, et al. . Visit-to-visit low-density lipoprotein cholesterol variability and risk of cardiovascular outcomes: insights from the TNT trial. J Am Coll Cardiol. 2015;65(15):1539-1548. doi: 10.1016/j.jacc.2015.02.017 [DOI] [PubMed] [Google Scholar]
  • 22.Kim MK, Han K, Park YM, et al. . Associations of variability in blood pressure, glucose and cholesterol concentrations, and body mass index with mortality and cardiovascular outcomes in the general population. Circulation. 2018;138(23):2627-2637. doi: 10.1161/CIRCULATIONAHA.118.034978 [DOI] [PubMed] [Google Scholar]
  • 23.Davignon J, Ganz P. Role of endothelial dysfunction in atherosclerosis. Circulation. 2004;109(23 suppl 1):III27-III32. doi: 10.1161/01.CIR.0000131515.03336.f8 [DOI] [PubMed] [Google Scholar]
  • 24.Quinn TJ, Gallacher J, Deary IJ, Lowe GD, Fenton C, Stott DJ. Association between circulating hemostatic measures and dementia or cognitive impairment: systematic review and meta-analyzes. J Thromb Haemost. 2011;9(8):1475-1482. doi: 10.1111/j.1538-7836.2011.04403.x [DOI] [PubMed] [Google Scholar]
  • 25.Sabayan B, Westendorp RG, Grond J, et al. . Markers of endothelial dysfunction and cerebral blood flow in older adults. Neurobiol Aging. 2014;35(2):373-377. doi: 10.1016/j.neurobiolaging.2013.08.020 [DOI] [PubMed] [Google Scholar]
  • 26.de la Torre JC. Is Alzheimer's disease a neurodegenerative or a vascular disorder? Data, dogma, and dialectics. Lancet Neurol. 2004;3(3):184-190. doi: 10.1016/S1474-4422(04)00683-0 [DOI] [PubMed] [Google Scholar]
  • 27.Chen Z, Ichetovkin M, Kurtz M, et al. . Cholesterol in human atherosclerotic plaque is a marker for underlying disease state and plaque vulnerability. Lipids Health Dis. 2010;9:61. doi: 10.1186/1476-511X-9-61 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Anstey KJ, Ashby-Mitchell K, Peters R. Updating the evidence on the association between serum cholesterol and risk of late-life dementia: review and meta-analysis. J Alzheimers Dis. 2017;56(1):215-228. doi: 10.3233/JAD-160826 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Nordestgaard LT, Christoffersen M, Frikke-Schmidt R. Shared risk factors between dementia and atherosclerotic cardiovascular disease. Int J Mol Sci. 2022;23(17):9777. doi: 10.3390/ijms23179777 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Smit RA, Trompet S, Sabayan B, et al. . Higher visit-to-visit low-density lipoprotein cholesterol variability is associated with lower cognitive performance, lower cerebral blood flow, and greater white matter hyperintensity load in older subjects. Circulation. 2016;134(3):212-221. doi: 10.1161/CIRCULATIONAHA.115.020627 [DOI] [PubMed] [Google Scholar]
  • 31.Kjeldsen EW, Nordestgaard LT, Frikke-Schmidt R. HDL cholesterol and non-cardiovascular disease: a narrative review. Int J Mol Sci. 2021;22(9):4547. doi: 10.3390/ijms22094547 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Hong BV, Zheng J, Agus JK, et al. . High-density lipoprotein changes in Alzheimer's disease are APOE genotype-specific. Biomedicines. 2022;10(7):1495. doi: 10.3390/biomedicines10071495 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Corder EH, Saunders AM, Strittmatter WJ, et al. . Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science. 1993;261(5123):921-923. doi: 10.1126/science.8346443 [DOI] [PubMed] [Google Scholar]
  • 34.Oliveira FF, Chen ES, Smith MC, Bertolucci PH. Predictors of cognitive and functional decline in patients with Alzheimer disease dementia from Brazil. Alzheimer Dis Assoc Disord. 2016;30(3):243-250. doi: 10.1097/WAD.0000000000000117 [DOI] [PubMed] [Google Scholar]
  • 35.de Oliveira FF, Chen ES, Smith MC, Bertolucci PHF. Longitudinal lipid profile variations and clinical change in Alzheimer's disease dementia. Neurosci Lett. 2017;646:36-42. doi: 10.1016/j.neulet.2017.03.003 [DOI] [PubMed] [Google Scholar]
  • 36.Bennet AM, Di Angelantonio E, Ye Z, et al. . Association of apolipoprotein E genotypes with lipid levels and coronary risk. JAMA. 2007;298(11):1300-1311. doi: 10.1001/jama.298.11.1300 [DOI] [PubMed] [Google Scholar]
  • 37.Borroni B, Pettenati C, Bordonali T, Akkawi N, Di Luca M, Padovani A. Serum cholesterol levels modulate long-term efficacy of cholinesterase inhibitors in Alzheimer disease. Neurosci Lett. 2003;343(3):213-215. doi: 10.1016/s0304-3940(03)00336-7 [DOI] [PubMed] [Google Scholar]
  • 38.de Oliveira FF, Chen ES, Smith MC, Bertolucci PHF. Selected LDLR and APOE polymorphisms affect cognitive and functional response to lipophilic statins in Alzheimer's disease. J Mol Neurosci. 2020;70(10):1574-1588. doi: 10.1007/s12031-020-01588-7 [DOI] [PubMed] [Google Scholar]
  • 39.de Oliveira FF, Bertolucci PHF, Chen ES, Smith MC. Pharmacogenetic analyses of therapeutic effects of lipophilic statins on cognitive and functional changes in Alzheimer's disease. J Alzheimers Dis. 2022;87(1):359-372. doi: 10.3233/JAD-215735 [DOI] [PubMed] [Google Scholar]
  • 40.Knopman DS, Petersen RC, Rocca WA, Larson EB, Ganguli M. Passive case-finding for Alzheimer's disease and dementia in two U.S. communities. Alzheimers Dement. 2011;7(1):53-60. doi. 10.1016/j.jalz.2010.11.001 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Because of the sensitive nature of the data collected for this study, requests to access the data set from qualified researchers trained in human subject confidentiality protocols may be sent to info@rochesterproject.org.

Articles from Neurology are provided here courtesy of American Academy of Neurology

RESOURCES