The longitudinal association between dyslipidemia and cognitive trajectory

Abstract

Background

The literature on dyslipidemia and cognitive trajectories among cognitively unimpaired (CU) persons remains inconclusive.

Objective

To investigate the association between baseline dyslipidemia and change in global and domain specific (i.e., memory, language, attention/executive function, and visuospatial skills) cognition in a population-based setting and whether the association differs by sex, age, or APOE ɛ4 carrier status.

Methods

We conducted a longitudinal study derived from the Mayo Clinic Study of Aging, involving 4236 CU persons aged ≥ 50 years. We ran linear mixed-effect models to examine baseline dyslipidemia in predicting longitudinal cognitive global and domain-specific z-scores adjusted for age, sex, education, medical comorbidity, repeated cognitive testing, and APOE ɛ4. We examined interactions among dyslipidemia, years since baseline, and separately by sex, age, and APOE ɛ4 carrier status.

Results

Over a median follow-up period of 6.4 years, CU individuals with dyslipidemia showed faster decline in z-scores of all domains, i.e., memory, language, attention/executive function, visuospatial and global cognition relative to CU individuals without dyslipidemia. Three-way interactions showed that dyslipidemia's effect on decline in z-scores of global cognition, attention and visuospatial skills was less pronounced in males than females. Higher age increased dyslipidemia's effect on decline in z-scores of attention but not global cognition or any other domain. APOE ɛ4 carrier status did not modify the effect of dyslipidemia on cognitive z-scores.

Conclusions

Dyslipidemia was associated with faster global and domain-specific cognitive decline over time in older community-dwelling individuals who were cognitively unimpaired at baseline. The effect of dyslipidemia on cognitive trajectories may be sex-influenced.

Keywords

Alzheimer's disease cognitive decline cognitive domains cognitive trajectory dyslipidemia

Introduction

Cardiovascular disease (CVD) and dementia are leading causes of morbidity and mortality in late life,^1,2 with CVD and dementia sharing risk factors. For example, hypertension, smoking, diabetes, and hypercholesterolemia are risk factors for CVD and vascular dementia.^3–5 Additionally, observational studies reported that hypertension, smoking, and hypercholesterolemia are also risk factors for clinically diagnosed Alzheimer's disease (AD), the most common form of dementia.^4,6

Thus, it may be possible to prevent or delay the onset of both CVD and dementia by addressing shared risk factors. One example could be dyslipidemia, i.e., elevated total cholesterol, low density lipoprotein (LDL) cholesterol, higher triglycerides and low levels of high density lipoprotein (HDL) cholesterol. Even though the literature is inconsistent, previous studies have reported that dyslipidemia, especially in midlife, were associated with increased risk of clinically diagnosed AD syndrome and vascular dementia.^7,8

Apolipoprotein E (APOE) ɛ4 carrier status is a genetic risk factor for AD⁹ and has also been associated with vascular risk factors.¹⁰ Previous studies examining interactions between APOE ɛ4 carrier status and dyslipidemia on increased dementia risk have been inconclusive¹¹ and some reported stronger associations between elevated lipid levels and accelerated cognitive decline in APOE ɛ4 carriers.¹²

There is a scarcity of prospective population-based studies primarily designed to rigorously examine cognition longitudinally, and which allow for investigating associations between dyslipidemia and cognitive outcomes, stratified by sex, age, and APOE ɛ4 carrier status.

Therefore, we sought to examine the potential role of dyslipidemia in predicting cognitive trajectories (i.e., global and domain-specific z-scores) in community-dwelling, cognitively unimpaired individuals at baseline and whether the association differed by sex, age, or APOE ɛ4 carrier status.

Methods

Study design and sample

The population-based Mayo Clinic Study of Aging (MCSA) is a prospective cohort study of adults in Olmsted County, MN. Details of the study procedures have been reported elsewhere.¹³ The MCSA was approved by the Mayo Clinic and Olmsted Medical Center institutional review boards, and informed consent for participation was obtained from every participant.

In the current analysis, we included men and women aged 50 to 91 years at baseline who had valid data from neuropsychological testing, were cognitively unimpaired at baseline, and had information on the presence or absence of dyslipidemia at baseline. Neuropsychological testing was performed nearly every 15 months and individuals included in the longitudinal aspects of the models (N = 4236) had at least one follow-up cognitive evaluation. The MCSA is an ongoing study and 721 individuals had one baseline but no follow-up neuropsychological assessment and were therefore only included in the cross-sectional baseline aspects of the models. Individuals with a diagnosis of mild cognitive impairment (MCI) or dementia at baseline were excluded from this analysis.

Cognitive evaluation

Participants of the MCSA underwent the following face-to-face evaluations: 1) risk factor ascertainment and baseline evaluation (including Clinical Dementia Rating Scale)¹⁴ performed by a nurse or study coordinator; 2) a neurologic evaluation including a neurologic interview, Short Test of Mental Status,¹⁵ and neurologic examination performed by behavioral neurologists; 3) neuropsychological evaluation of four cognitive domains - memory (delayed recall trials from the Auditory Verbal Learning Test¹⁶ and the Wechsler Memory Scale–Revised,¹⁷ Logical Memory and Visual Reproduction subtests); language (Boston Naming Test¹⁸ and category fluency); visuospatial (Wechsler Adult Intelligence Scale–Revised,¹⁹ Picture Completion and Block Design subtests); and executive function (Trail Making Test Part B²⁰ and the Wechsler Adult Intelligence Scale–Revised,¹⁹ Digit Symbol subtest). All tests were administered by psychometrists and supervised by neuropsychologists. The determination of cognitive unimpairment and the diagnosis of MCI or dementia were made by an expert consensus panel and based on published criteria.^13,21

Furthermore, we created domain-specific cognitive z-scores by z-scoring the average of the test-specific z-scores included in each domain; and a global z-score was created by z-scoring the average of the domain-specific z-scores. The outcomes of interest for the statistical analyses were longitudinal changes in global and domain-specific (i.e., memory, attention/executive function, language, visuospatial skills) cognitive z-scores.

Determination of dyslipidemia

MCSA nurse abstractors reviewed the health care records of all study participants at baseline using the Rochester epidemiology project resources²² to identify physician diagnosis of dyslipidemia or dyslipidemia treatment.

APOE ε4 genotyping

Blood was drawn blood from study participants after obtaining informed consent. Laboratory technicians who were kept unaware of other study variables performed APOE ε4 genotyping by standard methods.²³

Assessment of confounders

We assessed traditional confounders (i.e., age, sex, education) based on self-report. Medical comorbidity was assessed using the Charlson Comorbidity Index.²⁴

Statistical analysis

The data was summarized as median (Q1, Q3) for continuous variables and N (%) for categorical variables and groups were compared using the Wilcoxon rank-sum test for continuous variables and using the Chi-squared test for categorical variables (Table 1, Supplemental Tables 1 and 2). We conducted linear mixed-effect models with random participant-specific intercepts and slopes over time to examine associations of dyslipidemia at baseline in predicting longitudinal changes in global and domain-specific (i.e., memory, attention/executive function, language, and visuospatial) cognitive z-scores over time. We included a term for time in years since baseline and an interaction term between time and the dyslipidemia variable. Models were adjusted for age at baseline, sex, education, medical comorbidity at baseline, repeated cognitive testing, and APOE ɛ4 carrier status. We also ran three-way interaction models with age (considered a continuous variable), sex (females; males), and APOE ɛ4 carrier status (APOE ɛ4 carriers; non-carriers) each separately with time and dyslipidemia (these models also included the corresponding two-way interactions).

Table 1.

Participant characteristics at baseline by dyslipidemia.

Variable	No Dyslipidemian = 1127 (22.7%)	Dyslipidemian = 3830 (77.3%)	TotalN = 4957	p
Age, median (Q1, Q3), years	71.7 (61.0, 79.6)	74.0 (67.3, 80.5)	73.5 (65.7, 80.3)	<0.001
Sex, females	641 (56.9)	1869 (48.8)	2510 (50.6)	<0.001
Education, median (Q1, Q3), years	15.0 (12.0, 16.0)	14.0 (12.0, 16.0)	14.0 (12.0, 16.0)	<0.001
APOEɛ4 carriers	244 (21.7)	1053 (27.5)	1297 (26.2)	<0.001
Charlson Comorbidity Index, median (Q1, Q3), years	1.00 (0.00, 3.00)	3.00 (1.00, 5.00)	2.00 (1.00, 4.00)	<0.001
Diabetes	35 (3.1)	822 (21.5)	857 (17.3)	<0.001
Dyslipidemia with Treatment	0 (0)	2730 (71.3)	2730 (55.1)	<0.001
BMI^a, median (Q1, Q3)	26.3 (23.5, 29.9)	28.2 (25.4, 32.0)	27.9 (24.9, 31.6)	<0.001
BMI ^a ≥30	264 (23.8)	1411 (37.5)	1675 (34.4)	<0.001
Hypertension	510 (45.3)	2784 (72.7)	3294 (66.5)	<0.001
Smoking ^b	471 (41.8)	1819 (47.5)	2290 (46.2)	<0.001
Coronary artery disease	89 (7.9)	1247 (32.6)	1336 (27.0)	<0.001
Peripheral vascular disease	18 (1.6)	284 (7.4)	302 (6.1)	<0.001
Domain z-scores, median (Q1, Q3)
Memory domain score^c	0.20 (−0.62, 0.92)	−0.04 (−0.76, 0.67)	0.01 (−0.73, 0.74)	<0.001
Language domain score^d	0.19 (−0.47, 0.85)	0.01 (−0.64, 0.66)	0.07 (−0.60, 0.69)	<0.001
Attention domain score^e	0.29 (−0.45, 0.95)	0.04 (−0.62, 0.62)	0.08 (−0.58, 0.69)	<0.001
Visuospatial domain score^f	0.16 (−0.53, 0.84)	0.02 (−0.68, 0.67)	0.04 (−0.65, 0.72)	<0.001
Global cognition score^g	0.25 (−0.49, 0.94)	−0.00 (−0.69, 0.65)	0.05 (−0.66, 0.72)	<0.001

Q1 = Quartile 1; Q3 = quartile 3. Data are presented as n (%) unless indicated otherwise. p values for continuous variables are from the Wilcoxon rank-sum test, and for categorical variables, from the Chi-squared test.

data missing on 82 participants, ^b data missing on 2 participants, ^c data missing on 19 participants, ^d data missing on 126 participants, ^e data missing on 122 participants, ^f data missing on 145 participants, ^g data missing on 258 participants.

For a visual display of data, we plotted the linear mixed effects models for the presence of dyslipidemia corresponding to the “average” person in our data set in terms of covariates predicting cognitive z-scores to illustrate the trajectories. Statistical testing was done at the conventional two-tailed alpha level of 0.05. Analyses were performed using SAS System, version 9.4 software (SAS Institute, Cary, NC) and R, version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).

Results

Demographics

Participants included 4957 individuals (50.6% women) at baseline, enrolled between 2004 and 2023 with a median (Q1, Q3) age of 73.5 (65.7, 80.3) years, education level of 14.0 (12.0, 16.0) years, and Charlson Comorbidity Index of 2.0 (1.0, 4.0); 26.2% were APOE ɛ4 carriers and 77.3% had dyslipidemia. The complete demographic characteristics at baseline by dyslipidemia status are summarized in Table 1. Four thousand two hundred thirty-six participants were followed for a median of 6.4 years (range 1–19).

Association of dyslipidemia with cognitive decline

At baseline, dyslipidemia was not associated with cognitive z-scores. Over time, those without dyslipidemia showed longitudinal decline in cognitive z-scores in all domains, i.e., memory, language, attention/executive function, and visuospatial skills, as well as in global cognition. Having dyslipidemia was associated with faster decline in z-scores of global cognition and all domains (Table 2). For example, with each passing year, for those without dyslipidemia, global cognition z-score decreased by 0.055 (95% CI: −0.062 to −0.047), on average. Those with dyslipidemia decreased by an additional 0.019 (95% CI: −0.027 to −0.010) annually for a total average yearly decline of 0.074 (i.e., 0.055 + 0.019) (Table 2). For a visual display of data, please refer to Figure 1.

Figure 1.

Plot of linear mixed effects models for presence/absence of dyslipidemia corresponding to the person in our data set with “average” covariate values predicting global and domain-specific cognition z-scores. zGlobal: Global cognition z-score; zMemory: Memory domain z-score; zLanguage: Language domain z-score; zAttention: Attention domain z-score; zVisual Spatial: visuospatial domain z-score.

Table 2.

Results of linear mixed-effects models on associations between dyslipidemia at baseline and cognitive change (z-scores).

	Global cognition z-scores^a		Memory z-scores^b		Language z-scores^c		Attention z-scores^d		Visuospatial z-scores^e
	β Estimate(95% CI)	p	β Estimate(95% CI)	p	β Estimate(95% CI)	p	β Estimate(95% CI)	p	β Estimate(95% CI)	p
Dyslipidemia	0.019(−0.032, 0.070)	0.4696	0.047(−0.009, 0.103)	0.1015	0.031(−0.026, 0.088)	0.2804	0.034(−0.018, 0.087)	0.2009	0.014(−0.041, 0.068)	0.6169
Time	−0.055(−0.062, −0.047)	<0.0001	−0.029(−0.037, −0.020)	<0.0001	−0.049(−0.057, −0.041)	<0.0001	−0.070(−0.078, −0.062)	<0.0001	−0.011(−0.016, −0.005)	0.0003
Time * Dyslipidemia	−0.019(−0.027, −0.010)	<0.0001	−0.017(−0.026, −0.007)	0.0005	−0.013(−0.022, −0.005)	0.0030	−0.023(−0.032, −0.015)	<0.0001	−0.011(−0.018, −0.005)	0.0005

CI: confidence interval; All models were adjusted for age at baseline, sex, education, medical comorbidity at baseline, repeated cognitive testing, and APOE ɛ4.

Three-way interactions between dyslipidemia, sex, age and APOE ɛ4 carrier status with cognitive decline

Three-way interaction models between sex (males) * dyslipidemia * time showed that dyslipidemia's effect on decline over time in z-scores of global cognition, attention and visuospatial skills was significantly less pronounced in males as compared to females (Table 3). Three-way interaction models between age (as continuous variable) * dyslipidemia * time showed that individuals with dyslipidemia and higher age declined significantly faster over time in z-scores of attention compared to those in either of those states individually. However, three-way interactions between age * dyslipidemia * time were not significant for z-scores of global cognition or any other cognitive domain (i.e., memory, language, or visuospatial skills) (Table 3).

Table 3.

Results of linear mixed-effects models examining three-way interactions between dyslipidemia, sex and age with cognitive change (z-scores).

		Global cognition z-scores^a		Memory z-scores^b		Language z-scores^c		Attention z-scores^d		Visuospatial z-scores^e
		Estimate(95% CI)	p	Estimate (95% CI)	p	Estimate(95% CI)	p	Estimate(95% CI)	p	Estimate(95% CI)	p
Sex	Time	−0.048(−0.059, −0.038)	<0.0001	−0.027(−0.038, −0.015)	<0.0001	−0.049(−0.059, −0.038)	<0.0001	−0.065(−0.076, −0.054)	<0.0001	−0.003(−0.010, 0.005)	0.5329
	Time * Male	−0.014(−0.029, 0.002)	0.0832	−0.005(−0.021, 0.012)	0.5866	−0.001(−0.017, 0.014)	0.8813	−0.011(−0.026, 0.005)	0.1729	−0.018(−0.029, −0.006)	0.0022
	Time * Dyslipidemia	−0.031(−0.043, −0.019)	<0.0001	−0.023(−0.036, −0.010)	0.0004	−0.020(−0.032, −0.008)	0.0011	−0.034(−0.047, −0.022)	<0.0001	−0.020(−0.029, −0.012)	<0.0001
	Time * Dyslipidemia * Male	0.025(0.007, 0.042)	0.0052	0.013(−0.006, 0.032)	0.1710	0.013(−0.005, 0.031)	0.1437	0.022(0.005, 0.040)	0.0132	0.020(0.007, 0.032)	0.0026
Age	Time	−0.075(−0.082, −0.068)	<0.0001	−0.046(−0.054, −0.037)	<0.0001	−0.066(−0.074, −0.058)	<0.0001	−0.090(−0.098, −0.083)	<0.0001	−0.024(−0.030, −0.018)	<0.0001
	Time * Age	−0.055(−0.061, −0.049)	<0.0001	−0.045(−0.053, −0.038)	<0.0001	−0.043(−0.050, −0.036)	<0.0001	−0.050(−0.057, −0.044)	<0.0001	−0.032(−0.037, −0.026)	<0.0001
	Time * Dyslipidemia	−0.001(−0.009, 0.007)	0.7435	−0.002(−0.012, 0.007)	0.6249	0.000(−0.008, 0.009)	0.9708	−0.008(−0.016, 0.001)	0.0708	−0.001(−0.007, 0.005)	0.7763
	Time * Dyslipidemia * Age	−0.001(−0.009, 0.006)	0.7460	0.001(−0.008, 0.010)	0.8541	−0.001(−0.009, 0.007)	0.7975	−0.009(−0.016, −0.001)	0.0294	0.002(−0.004, 0.008)	0.4971

CI, confidence interval; All models were adjusted for age at baseline (for sex interactions only), sex (for age interactions only), education, medical comorbidity at baseline, repeated cognitive testing, and APOE ɛ4.

Furthermore, APOE ɛ4 carrier status did not modify dyslipidemia's effect on longitudinal cognitive decline (Table 4).

Table 4.

Results of linear mixed-effects models examining three-way interactions between dyslipidemia and APOE ɛ4 with cognitive change (z-scores).

		Global cognition z-scores^a		Memory z-scores^b		Language z-scores^c		Attention z-scores^d		Visuospatial z-scores^e
		Estimate(95% CI)	p	Estimate (95% CI)	p	Estimate(95% CI)	p	Estimate(95% CI)	p	Estimate(95% CI)	p
APOE ɛ4	Time	−0.051(−0.059, −0.042)	<0.0001	−0.023(−0.033, −0.014)	<0.0001	−0.044(−0.053, −0.035)	<0.0001	−0.066(−0.075, −0.057)	<0.0001	−0.010(−0.017, −0.004)	0.0021
	Time * APOE ɛ4+	−0.016(−0.034, 0.002)	0.0787	−0.023(−0.042, −0.003)	0.0221	−0.022(−0.041, −0.004)	0.0173	−0.019(−0.037, −0.0003)	0.0467	−0.002(−0.015, 0.012)	0.8281
	Time * Dyslipidemia	−0.016(−0.026, −0.006)	0.0016	−0.015(−0.026, −0.004)	0.0060	−0.014(−0.025, −0.004)	0.0049	−0.023(−0.033, −0.013)	<0.0001	−0.009(−0.017, −0.002)	0.0113
	Time * Dyslipidemia * APOE ɛ4+	−0.006(−0.027, 0.014)	0.5429	−0.002(−0.024, 0.020)	0.8532	0.008(−0.013, 0.028)	0.4613	0.000(−0.020, 0.021)	0.9729	−0.006(−0.021, 0.009)	0.4149

CI: confidence interval; APOE ɛ4+, APOE ɛ4 carriers; All models were adjusted for age at baseline, sex, education, medical comorbidity at baseline, and repeated cognitive testing.

Discussion

Here, we report that cognitively unimpaired individuals with dyslipidemia showed faster decline over time in z-scores of global cognition and all cognitive domains, i.e., memory, language, attention/executive function, and visuospatial skills relative to those without dyslipidemia. The effect of dyslipidemia on cognitive trajectories may be sex-influenced, i.e., greater in females as compared to males. Additionally, individuals with dyslipidemia and higher age declined significantly faster over time in z-scores of attention, but not global cognition or any other domain (i.e., memory, language, visuospatial skills, or global cognition). Furthermore, the effect of dyslipidemia on cognitive trajectories may not be different in APOE ɛ4 carriers (versus non-carriers).

The previous literature on dyslipidemia and risk of dementia is inconsistent. While some reported that higher cholesterol levels were associated with lower risk of dementia,²⁵ others found no significant associations.^26,27 In contrast, several studies observed that higher serum total cholesterol and triglyceride levels were associated with increased risk of AD and vascular dementia.^7,8 Similarly, investigators from the Washington Heights–Inwood Columbia Aging Project reported a weak association between higher non-HDL and LDL cholesterol, as well as lower HDL cholesterol levels with the risk of vascular dementia.²⁸ Even though, previously a non-linear relationship between serum cholesterol levels and cognition has been suggested,²⁹ the authors of a dose-response meta-analysis reported that higher blood total cholesterol or triglyceride level was linearly associated with increased relative risk of AD.⁸ Similarly, investigators of a recent longitudinal study found a dose-response relationship between age at hyperlipidemia diagnosis and risk of dementia, with younger age at diagnosis of hyperlipidemia being associated with higher subsequent risk.³⁰

While the association between dyslipidemia and dementia has been widely studied, less is known about the associations between dyslipidemia and global and domain-specific cognitive trajectories as assessed from repeated neuropsychological testing. Previously, investigators from the Washington Heights–Inwood Columbia Aging Project followed 1147 elderly individuals without dementia or cognitive impairment at baseline for 7 years and did not observe a significant association between plasma lipid levels and changes in performance in tests of memory, visuospatial, or language abilities.³¹ Additionally, investigators from the Three-City Study reported that hypertriglyceridemia and low HDL cholesterol were significantly associated with higher decline in Mini-Mental State Examination but not on a test of verbal fluency or visual working memory.³²

Furthermore, investigators from the Atherosclerosis Risk in Communities (ARIC) study conducted a prospective cohort study and followed 13,997 middle-aged individuals for 20 years, assessed cognition through three cognitive tests and reported that higher total cholesterol, triglycerides, and LDL were associated with greater 20-year decline on a test of attention/executive function. Additionally, higher total cholesterol and triglyceride levels were associated with greater decline in memory scores and a summary z-score on all three cognitive tests.¹²

Differences in findings across prior studies may be due to discrepancies in study methodology including the study sample and design, timing of dyslipidemia measurement and cognitive evaluation. For example, it appears that dyslipidemia in earlier or midlife is more strongly associated with risk of dementia than dyslipidemia in older age.^30,33,34

We contribute to the literature by showing that in our sample of more than 4000 cognitively unimpaired individuals who underwent extensive cognitive assessment, dyslipidemia was associated with greater decline in z-scores of all assessed domains, i.e., memory, language, attention/executive function, visuospatial, as well as global cognition. While this effect is statistically significant, it is modest in magnitude. However, even small annual declines can be important at the population level, particularly over extended follow-up periods, as they may contribute to a greater risk of cognitive impairment or dementia in aging populations.³⁵ These findings highlight the potential for cumulative impact and identifying individuals at high risk for early intervention.

There is a scarcity of studies evaluating sex differences in the association between dyslipidemia and cognitive decline. A recent MCSA study³⁶ reported that while the prevalence of cardiovascular conditions was higher in males, cardiovascular conditions had stronger associations with cognitive decline in females as compared to males. Similarly, we observed that being male significantly mitigated dyslipidemia's negative effect over time in z-scores of global cognition, attention and visuospatial skills as compared to females. Thus, the potential impact of sex differences should be evaluated in future studies. The relationship between sex, cardiovascular risk and AD is complex. Even though previous studies reported a higher prevalence of cardiovascular risk factors in males compared to females,^36,37 the prevalence of AD is higher in females than in males.^2,38 While one should generally note the possibility of attrition bias, the follow-up time and baseline age in the current study were not significantly different between males and females (see Supplemental Table 1). Therefore, in our study attrition does not seem to be higher in males. Thus, the observed sex-differences may be due to a combination of biological and sociocultural factors. For example, previous studies reported a higher tau burden in females than males.³⁹ One hypothesis is that hormonal changes, such as the loss of estrogen after menopause, may accelerate amyloid and tau accumulation.^39,40 Additionally, sociocultural factors, including differences in educational and occupational attainment as well as caregiving-related stress and lower physical activity could potentially play a role.⁴¹

When considering age, several studies reported that lipid-levels measured in mid-life were associated with cognitive decline in later life.³³ In contrast, previous studies reported that lipid levels measured in late-life were not associated with increased risk of MCI, AD or all-cause dementia.³⁴ We observed that individuals with dyslipidemia and higher age declined statistically significantly faster over time in z-scores of attention. However, it should be noted that the effect size was small and there were no significant three-way interactions among dyslipidemia, age, and time since baseline in predicting longitudinal z-scores of any other domain (i.e., memory, language, visuospatial skills or global cognition).

Furthermore, when it comes to the relationship between statin use and cognitive outcomes, the previous literature suggests that statin use in late life in individuals at vascular risk does not prevent cognitive decline or dementia.⁴² Thus, the potential role of lifestyle interventions in middle age in reducing dyslipidemia and vascular risk and their effect on cognitive outcomes should be explored in future studies.

Only few studies examined interactions between APOE ɛ4 carrier status and dyslipidemia on increased dementia risk and most of them did not report significant interactions.¹¹ However, investigators from the aforementioned ARIC study reported stronger associations between elevated lipid levels and accelerated decline in a test assessing verbal memory in APOE ɛ4 carriers.¹² In our analysis, we observed that APOE ɛ4 carrier status did not modify the effect of dyslipidemia on cognitive z-scores.

Additionally, it should be noted that dyslipidemia is often associated with other cardiovascular risk factors including obesity, diabetes, hypertension and smoking.⁴³ Since cardiovascular risk factors often co-occur the term “metabolic syndrome” has been introduced. Even though the exact definition of “metabolic syndrome” has been inconsistent, the core features typically include: abdominal obesity, insulin resistance, dyslipidemia, and hypertension.⁴⁴ Previously, ARIC investigators observed that individuals with metabolic syndrome had an increased risk for long-term cardiovascular outcomes, even in the absence of diabetes or existing cardiovascular disease.⁴⁵ Insulin resistance plays a crucial role in the development of dyslipidemia.⁴³ Furthermore, brain insulin resistance is associated with AD.⁴⁶ However, it remains uncertain whether insulin resistance is mechanistically associated with AD. Thus, future research should examine mechanisms underlying the associations between insulin resistance, dyslipidemia and cognitive decline.

Our study has several strengths, including that the cognitive assessments were conducted at a center that has well-established expertise in the field of brain aging and MCI. Further strengths are the high number of study participants, population-based cohort study and a relatively long median follow-up time of more than six years. Our study also has limitations. Due to the nature of an observational study, causality cannot be drawn from our study findings. Furthermore, dyslipidemia was defined based on physician diagnosis or treatment abstracted from medical records, rather than individual lipid parameters. Notably, the prevalence of dyslipidemia in the current study is consistent with that reported in prior MCSA publications basing the diagnosis of dyslipidemia on established laboratory criteria (i.e., one or more of the following: triglycerides ≥150 mg/dL, total cholesterol >200 mg/d, or HDL cholesterol <40 mg/dL for men or <50 mg/dL for women), or the use of lipid-lowering medications.⁴⁷ While this approach reflects clinical practice, it does not allow us to determine the effect of specific lipid parameters (such as elevated triglycerides, total cholesterol, LDL cholesterol or low HDL cholesterol) on cognitive trajectories. Therefore, future studies examining specific lipid parameters and their relative contributions on cognitive trajectories could provide further insight and possibly clarify the observed heterogeneity across studies. Additionally, when interpreting our study findings, one should consider potential confounders such as diet and physical activity. Furthermore, it should be noted that the study population is highly educated and includes mostly White and non-Hispanic or Latino participants. Thus, although data from Olmsted County have shown generalizability to the population of Minnesota and the Upper Midwest,⁴⁸ the generalizability of our findings to other racial and ethnicity groups and geographical locations might be limited.

In conclusion, here we report that individuals with dyslipidemia who were cognitively unimpaired at baseline showed faster decline in global and domain-specific cognitive z-scores over time relative to individuals without dyslipidemia. The effect of dyslipidemia on cognitive trajectories may be sex-influenced, i.e., greater in females as compared to males. More research is needed to examine whether, for example, lifestyle interventions addressing dyslipidemia and cardiovascular risk in mid-life decrease the rate of cognitive decline.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251385255 - Supplemental material for The longitudinal association between dyslipidemia and cognitive trajectory

Supplemental material, sj-docx-1-alz-10.1177_13872877251385255 for The longitudinal association between dyslipidemia and cognitive trajectory by Anna Pink, Janina Krell-Roesch, Jeremy A Syrjanen, Maria Vassilaki, Julie A Fields, Bernhard Iglseder, Elmar Aigner, Walter K Kremers, Clifford R Jack Jr., Susan B Racette, Ronald C Petersen and Yonas E Geda in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

The authors would like to thank Dr David S. Knopman for constructive feedback of the manuscript.

ORCID iDs

Anna Pink

Janina Krell-Roesch

Jeremy A Syrjanen

Maria Vassilaki

Bernhard Iglseder

Elmar Aigner

Susan B Racette

Ethical considerations

The MCSA was approved by the Mayo Clinic and Olmsted Medical Center institutional review boards. These boards also authorized the sharing of anonymized data.

Consent to participate

Informed consent for participation was obtained from every participant.

Consent for publication

Not applicable.

Author contribution(s)

Anna Pink: Investigation; Methodology; Writing – original draft.

Janina Krell-Roesch: Investigation; Writing – review & editing.

Jeremy A Syrjanen: Formal analysis; Investigation; Methodology; Writing – review & editing.

Maria Vassilaki: Investigation; Methodology; Supervision; Writing – review & editing.

Julie A Fields: Writing – review & editing.

Bernhard Iglseder: Supervision; Writing – review & editing.

Elmar Aigner: Supervision; Writing – review & editing.

Walter K Kremers: Formal analysis; Investigation; Methodology; Writing – review & editing.

Susan B Racette: Writing – review & editing.

Ronald C Petersen: Funding acquisition; Resources; Writing – review & editing.

Yonas E Geda: Investigation; Methodology; Resources; Supervision; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Support for this research was provided by NIH grants: National Institute on Aging (R01 AG057708, U01 AG006786, P30 AG062677, R37 AG011378, R01 AG041851); the Robert H. and Clarice Smith and Abigail Van Buren Alzheimer's Disease Research Program; the GHR Foundation; the Alexander Family Alzheimer's Disease Research Professorship of the Mayo Clinic; the Liston Award; the Schuler Foundation; the Mayo Foundation for Medical Education and Research; the Arizona Alzheimer's Consortium; the Barrow Neurological Foundation; and used the resources of the Rochester Epidemiology Project (REP) medical records linkage system, which is supported by the National Institute on Aging (AG 058738), by the Mayo Clinic Research Committee, and by fees paid annually by REP users.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: J.K.-R. receives funding from the NIH and Roche. Dr. Kremers receives research funding from NIH. Dr. Fields serves as a consultant for Medtronic, Inc. and receives research support from the NIH. Dr. Racette receives funding from the NIH and Barrow Neurological Foundation and serves on the Scientific Advisory Board for Pritikin Intensive Cardiac Rehab. Dr. Petersen has consulted for Roche, Inc.; Genentech, Inc.; Eli Lilly, Inc.; Nestle, Inc. and Eisai, Inc.; a DSMB for Genentech, Inc. and receives royalties from Oxford University Press for Mild Cognitive Impairment and from UpToDate. His research funding is from NIH/NIA. Dr. Vassilaki receives research funding from NIH and has equity ownership in Amgen, Johnson and Johnson, and Merck. Dr. Geda receives funding from Roche, served on the Lundbeck advisory board, and receives research funding from the NIH. The remaining authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The data used in this study is available to qualified researchers upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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