Sex Differences in Apolipoprotein E and Alzheimer Disease Pathology Across Ancestries

Xiaoyi Xu; Jiseon Kwon; Ruiqi Yan; Catherine Apio; Soomin Song; Gyujin Heo; Qijun Yang; Jigyasha Timsina; Menghan Liu; John Budde; Kaj Blennow; Henrik Zetterberg; Alberto Lleó; Agustin Ruiz; José Luis Molinuevo; Virginia Man-Yee Lee; Yuetiva Deming; Amanda J Heslegrave; Tim J Hohman; Pau Pastor; Elaine R Peskind; Marilyn S Albert; John C Morris; Taesung Park; Carlos Cruchaga; Yun Ju Sung

doi:10.1001/jamanetworkopen.2025.0562

. 2025 Mar 11;8(3):e250562. doi: 10.1001/jamanetworkopen.2025.0562

Sex Differences in Apolipoprotein E and Alzheimer Disease Pathology Across Ancestries

Xiaoyi Xu ^1,², Jiseon Kwon ^1,³, Ruiqi Yan ^1,², Catherine Apio ^1,^3,⁴, Soomin Song ^1,³, Gyujin Heo ^1,³, Qijun Yang ^1,⁵, Jigyasha Timsina ^1,³, Menghan Liu ^1,³, John Budde ^1,³, Kaj Blennow ⁶, Henrik Zetterberg ⁶, Alberto Lleó ⁷, Agustin Ruiz ⁸, José Luis Molinuevo ⁹, Virginia Man-Yee Lee ¹⁰, Yuetiva Deming ¹¹, Amanda J Heslegrave ¹², Tim J Hohman ¹³, Pau Pastor ¹⁴, Elaine R Peskind ¹⁵, Marilyn S Albert ¹⁶, John C Morris ^17,¹⁸, Taesung Park ^4,¹⁹, Carlos Cruchaga ^1,^3,²⁰, Yun Ju Sung ^1,^2,^3,^✉

¹NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, Missouri

²Division of Biostatistics, Washington University School of Medicine, St Louis, Missouri

³Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri

⁴Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea

⁵Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio

⁶Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden

⁷Sant Pau Memory Unit, Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain

⁸Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain

⁹BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain

¹⁰Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia

¹¹Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison

¹²Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom

¹³Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee

¹⁴University Hospital Germans Trias i Pujol and The Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain

¹⁵Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle

¹⁶Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland

¹⁷Department of Neurology, Washington University, St Louis, Missouri

¹⁸Knight Alzheimer’s Disease Research Center, Washington University, St Louis, Missouri

¹⁹Department of Statistics, Seoul National University, Seoul, Korea

²⁰Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, Missouri

Accepted for Publication: January 5, 2025.

Published: March 11, 2025. doi:10.1001/jamanetworkopen.2025.0562

^✉

Corresponding Author: Yun Ju Sung, PhD, Washington University School of Medicine in St Louis, 4444 Forest Park Ave, Room 5512, St Louis, MO 63108 (yunju@wustl.edu).

Author Contributions: Dr Sung had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Mss Xu, Kwon, and Yan contributed equally to this work as co–first authors.

Concept and design: Xu, Yan, Apio, Molinuevo, Lee, Morris, Cruchaga, Sung.

Acquisition, analysis, or interpretation of data: Xu, Kwon, Yan, Song, Heo, Yang, Timsina, Liu, Budde, Lleó, Ruiz Laza, Deming, Heslegrave, Hohman, Pastor, Peskind, Albert, Morris, Park, Cruchaga, Sung.

Drafting of the manuscript: Xu, Yan, Apio, Heo, Pastor, Sung.

Critical review of the manuscript for important intellectual content: Xu, Kwon, Yan, Apio, Song, Yang, Timsina, Liu, Budde, Lleó, Ruiz Laza, Molinuevo, Lee, Deming, Heslegrave, Hohman, Pastor, Peskind, Albert, Morris, Park, Cruchaga, Sung.

Statistical analysis: Xu, Kwon, Yan, Song, Yang, Liu, Morris, Park, Cruchaga, Sung.

Obtained funding: Ruiz Laza, Lee, Sung.

Administrative, technical, or material support: Xu, Apio, Liu, Budde, Lleó, Peskind, Albert, Morris, Sung.

Supervision: Molinuevo, Heslegrave, Pastor, Morris, Cruchaga, Sung.

Conflict of Interest Disclosures: Dr Lleó reported receiving personal fees from Lilly, Eisai, Almirall, Grifols, and Biogen and grants from Novo Nordisk outside the submitted work. Dr Ruiz Laza reported receiving grants from ISCIII, VLAIO, JPND, IMI2, Grifols, Caixabank, and Janssen during the conduct of the study, personal fees from Landsteiner Genmed, and nonfinancial support from Grifols outside the submitted work. Dr Molinuevo reported being a full-time employee of Lundbeck outside the submitted work. Dr Heslegrave reported receiving consulting fees from Quanterix Corp outside the submitted work. Dr Hohman reported receiving personal fees from the Alzheimer’s Association as an editor for Alzheimer & Dementia outside the submitted work. Dr Cruchaga reported receiving research support from GlaxoSmithKline and Eisai, being a member of the advisory board of Circular Genomics, and owning stock in this company outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported by grants RF1 AG074007 (Dr Sung), R01 AG044546 (Dr Cruchaga), P01 AG003991 (Dr Cruchaga), RF1 AG053303 (Dr Cruchaga), RF1 AG058501 (Dr Cruchaga), U01 AG058922 (Dr Cruchaga), P30 AG066444 (Dr Morris), P01 AG003991 (Dr Morris), and P01 AG026276 (Dr Morris) from the National Institutes of Health, the Chan Zuckerberg Initiative (Dr Cruchaga), the Michael J. Fox Foundation (Dr Cruchaga), and Alzheimer’s Association Zenith Fellows Award ZEN-22-848604 (Dr Cruchaga).

Data Sharing Statement: See Supplement 2.

Additional Contributions: We thank all the participants and their families as well as the involved cohorts, institutions, and their staff.

^✉

Corresponding author.

PMCID: PMC11897841 PMID: 40067298

Key Points

Question

How does the association of apolipoprotein E (APOE) with amyloid and tau pathology vary across different sex and ancestry groups?

Findings

In this cohort study of 4592 individuals, APOE-ε4 dosage was associated with more severe amyloid β1-42 pathology with sex × APOE-ε4 interaction in individuals of European ancestry. The association of APOE-ε4 with phosphorylated tau was stronger in women than in men, specifically among individuals of African ancestry, whereas for total tau, the sex difference was significant among individuals of African and European ancestries.

Meaning

These results highlight the importance of considering sex and ancestry when understanding the role of APOE in Alzheimer disease pathology, which may enhance insights into disease mechanisms.

This cohort study investigates the main and interactive associations of sex and apolipoprotein E with core cerebrospinal biomarkers in individuals of different ancestries.

Abstract

Importance

Age, sex, and apolipoprotein E (APOE) are the strongest risk factors for late-onset Alzheimer disease (AD). The role of APOE in AD varies with sex and ancestry. While the association of APOE with AD biomarkers also varies across sex and ancestry, no study has systematically investigated both sex-specific and ancestry differences of APOE on cerebrospinal fluid (CSF) biomarkers together, resulting in limited insights and generalizability.

Objective

To systematically investigate the association of sex and APOE-ε4 with 3 core CSF biomarkers across ancestries.

Design, Setting, and Participants

This cohort study examined 3 CSF biomarkers (amyloid β1-42 [Aβ42], phosphorylated tau 181 [p-tau], and total tau, in participants from 20 cohorts from July 1, 1985, to March 31, 2020. These individuals were grouped into African, Asian, and European ancestries based on genetic data. Data analyses were conducted from June 1, 2023, to November 10, 2024.

Exposure

Sex (male or female) and APOE-ε4.

Main Outcomes and Measures

The associations of sex and APOE-ε4 with biomarker levels were assessed within each ancestry group, adjusting for age. Meta-analyses were performed to identify these associations across ancestries. Sensitivity analyses were conducted to exclude the potential influence of the APOE-ε2 allele.

Results

This cohort study included 4592 individuals (mean [SD] age, 70.8 [10.2] years; 2425 [52.8%] female; 119 [2.6%] African, 52 [1.1%] Asian, and 4421 [96.3%] European). Higher APOE-ε4 dosage scores were associated with lower Aβ42 values (β [SE], −0.58 [0.02], P < .001), indicating more severe pathology; these associations were seen in men and women separately and jointly. The association with APOE-ε4 was statistically greater in men (β [SE], −0.63 [0.03]; P < .001) vs women (β [SE], −0.52 [0.03]; P < .001) of European ancestry (P = .01 for interaction). Women had higher levels of p-tau, indicating more severe neurofibrillary pathology. The association between APOE-ε4 dosage and p-tau was in the expected direction (higher APOE-ε4 dosage for higher p-tau values) in both sexes, but the difference between sexes was significant only in those of African ancestry (β [SE], 0.10 [0.18]; P = .57 for men; β [SE], 0.66 [0.17]; P < .001 for women; P = .03 for interaction). Women also had higher levels of total tau, indicating more neuronal damage. The association between APOE-ε4 dosage and total tau was stronger in women than in men in the African cohort (β [SE], 0.20 [0.22]; P = .36 for men and β [SE], 0.65 [0.22], P = .004 for women [P = .16 for interaction]) and European cohort (β [SE], 0.36 [0.03]; P < .001 in women and β [SE], 0.27 [0.03], P < .001 in men [P = .053 for interaction]); no significant associations were found in the Asian cohort. Sensitivity analysis excluding APOE-ε2 carriers yielded similar results.

Conclusions and Relevance

In this cohort study, the association of the APOE-ε4 risk allele with tau accumulation was higher in women than in men. These findings underscore the importance of considering sex differences in APOE-ε4’s association with AD biomarkers and tau pathology mechanisms in AD. Although this study provides robust evidence of complex interplay between sex and APOE-ε4 for European ancestry, further research is needed to fully understand other ancestry differences.

Introduction

Alzheimer disease (AD) is the leading cause of dementia worldwide and represents a significant public health concern as a major expensive and burdensome disease.^1,2,3 The strongest risk factors for AD are advanced age, biological sex, and genetic variants.³ In particular, women are at a higher risk of developing AD and exhibit faster progression with more rapid cognitive decline after diagnosis compared with men.⁴ Among genetic variants, the apolipoprotein E (APOE) ε4 allele (APOE-ε4) is the largest genetic risk, explaining approximately 13% of phenotypic variance for late-onset AD.^5,6,7 The lifetime risk of AD is more than 50% for APOE-ε4/ε4 and 20% to 30% for APOE-ε3/ε4 carriers compared with APOE-ε2 or APOE-ε3 carriers.^8,9,10 These risks are reported to vary across ancestries.^11,12

Among the cerebrospinal fluid (CSF) biomarkers for AD are amyloid β1-42 (Aβ42) for cortical amyloid deposition, phosphorylated tau 181 (p-tau) for neurofibrillary pathological changes, and total tau for the intensity of neurodegeneration.¹³ Although p-tau is highly specific to AD, total tau serves as a broader marker of neurodegeneration, indicating neuronal damage across both AD and non-AD conditions.¹³ These 3 CSF biomarkers have significantly increased the diagnostic accuracy of AD in the mild cognitive impairment (MCI) stage^14,15 and sporadic AD with a combined sensitivity of greater than 95% and a specificity of greater than 85%.^{13,16,17,18,19} AD can be differentiated from other dementias by detecting lower concentrations of Aβ42 and higher concentrations of p-tau or total tau in CSF compared with age-matched control individuals.²⁰

To disentangle the interplay between sex and APOE with AD, several studies have examined the association of APOE with the underlying mechanism by considering these CSF or positron emission tomography (PET) biomarkers. While APOE-ε4 is associated with severe amyloid and tau pathology even in cognitively unimpaired individuals,²¹ its role often differs between men and women. Several studies, including the study by Hohman et al,²² reported that the role of APOE in p-tau and total tau was more pronounced in women. Other studies, including the study by Altmann et al,²³ also reported sex differences in the association of APOE-ε4 with Aβ42 in individuals with MCI. In addition, the role of APOE in AD pathology is known to vary across ancestries.^12,24,25,26 The levels of p-tau and total tau in African American individuals have been reported to be lower than those in European individuals,^12,24,25,26 with a potential ancestry × APOE-ε4 interaction in AD pathology.²⁷ This finding emphasizes the importance of considering ancestry in AD biomarker analyses. However, to our knowledge, no study has systematically investigated both sex- and ancestry-specific differences of the association between APOE-ε4 and CSF biomarkers together. Therefore, our study’s objective was to investigate the main and interactive associations of sex and APOE-ε4 with 3 core CSF biomarkers (Aβ42, p-tau, and total tau) across individuals of 3 ancestries.

Methods

Study Participants

The study considered individuals recruited from July 1, 1985, to March 31, 2020, from 20 cohorts: the Alzheimer Disease Neuroimaging Initiative²⁸; Australian Imaging, Biomarkers, and Lifestyle^29,30; Biomarkers of Cognitive Decline Among Normal Individuals³¹; Blennow et al¹³; Barcelona-1³²; Ace Alzheimer Center Barcelona, also known as Fundació ACE³³; Homburg, Germany³⁴; Hospital Sant Pau³⁵; London, England^36,37,38; Clinic de Barcelona³⁵; the Knight Alzheimer Disease Research Center^39,40; the Mayo Clinic Study of Aging⁴¹; National Alzheimer Coordinating Center⁴²; Skåne University Hospital⁴³; Wisconsin Alzheimer Disease Research Center⁴⁴; University of Pennsylvania^42,43; University of Washington⁴³; the Vanderbilt Memory and Aging Project⁴⁵; Mattsson et al,²⁰ and the Wisconsin Registry for Alzheimer’s Prevention.⁴⁶ The cohort-specific description and characteristics are presented in the eMethods and eTable 1 in Supplement 1. Written informed consent was obtained from all study participants. For those with substantial cognitive impairment, consent was obtained from a caregiver or legal guardian. The appropriate institutional review boards evaluated and approved the study protocols for all cohorts. The present study was approved by the Washington University School of Medicine institutional review board and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Ancestry Classification

From 20 cohorts, 4630 individuals with and without AD were considered. After excluding individuals with missing data on biomarkers, sex, age, or APOE genotype, 4592 remained (more details are presented in eFigure 1 in Supplement 1). To classify these individuals into ancestry, we performed principal component analysis by combining genomic data from these 4592 individuals and HapMap data. On the basis of the first 2 principal component analyses, individuals clustered near Europe were classified as having European ancestry (n = 4421) (eFigure 2 in Supplement 1). The remaining individuals were classified as having African (n = 119) or Asian (n = 52) ancestry.

CSF Biomarkers

This study examined 3 core CSF AD biomarkers: Aβ42, p-tau, and total tau. The CSF biomarker protein levels from the 20 cohorts were obtained using different platforms in each cohort. For details on specific laboratory procedures, see the original studies.^{20,28,29,30,31,32,33,35,39,40,41,42,43,45,46} To ensure comparability among the different cohorts and to reduce batch effects, we harmonized the CSF biomarker values across cohorts, as described previously.⁴⁷ Briefly, the CSF biomarker levels were log₁₀ transformed and z score normalized in each cohort. Any biomarker values outside 3 SDs from the mean were considered outliers and excluded from the analysis. The distribution of these CSF values before and after harmonization is presented in eFigure 3 in Supplement 1.

APOE Genotyping

The APOE haplotypes (ε2, ε3, and ε4) on chromosome 19 were determined using rs7412 and rs429358 genotypes. To capture the effect of the number of ε4 alleles, the APOE-ε4 dosage was coded as a continuous variable: 0 for individuals with no copy (ε2/ε2, ε2/ε3, and ε3/ε3), 1 for individuals with 1 copy (ε3/ε4 and ε2/ε4), and 2 for individuals with 2 copies (ε4/ε4).

Statistical Analysis

We combined harmonized data from all cohorts and split them into each ancestry. For each ancestry, we performed the following 4 regression analyses:

Y = α + β₁ × APOE-ε4 + β₂ × Sex + β₃ × Age (in both sexes);

Y = α + β₁ × APOE-ε4 + β₂ × Age (in men only);

Y = α + β₁ × APOE-ε4 + β₂ × Age (in women only); and

Y = α + β₁ × APOE-ε4 + β₂ × Sex + β₃ × Age + β₄ × APOE-ε4 × Sex (in both sexes).

Overall sex difference (β₁) and APOE-ε4 association (β₂) were obtained in model 1, considering both sexes. The sex-specific APOE-ε4 association (β₂) was obtained via models 2 and 3 (male specific in model 2; female specific in model 3). Finally, the interaction between APOE-ε4 allele and sex (β₄) was obtained via model 4 to test the difference between the sex-specific APOE-ε4 associations. Y was the normalized level of CSF Aβ42, p-tau, and total tau. Sex was coded as 0 for men and 1 for women. APOE-ε4 was the dosage (count) of the ε4 allele in APOE-ε4 genotype (0, 1, or 2). In addition, age at the time of the CSF draw was included as a covariate to adjust for the association of age with these CSF biomarkers.^48,49

To examine whether the resulting APOE-ε4 association was confounded by the known protective ε2 effect, we conducted 2 sensitivity analyses. The first sensitivity analysis considered only ε3/ε3 carriers for 0 (excluding ε2/ε2 and ε2/ε3). The second sensitivity analysis completely excluded any ε2 carriers, thereby considering 0 for ε3/ε3, 1 for ε3/ε4, and 2 for ε4/ε4. We then performed a meta-analysis to estimate their overall associations across the population using the inverse variance weighted method. Heterogeneity was assessed with the Cochran Q test⁵⁰ in all meta-analyses, and when P < .05, both the fixed-effect and random-effect models were reported.

All analyses were performed using R, version 4.3.1 (R Foundation for Statistical Computing). Meta-analysis was conducted using the meta R package.⁵¹ Forest plots for visualizing meta-analysis results were generated using the metafor R package.⁵² A 2-sided P < .05 was considered statistically significant. Data analyses were conducted from June 1, 2023, to November 10, 2024.

Results

Participant Characteristics

The characteristics of the 4592 participants examined in this study are summarized in Table 1. The mean (SD) age was 70.8 (10.2) years, reflecting an older population relevant to AD. Approximately half of the European and Asian participants (2171 [49.1%] and 27 [51.9%], respectively) were clinically diagnosed with AD, whereas 31.9% of African participants (n = 38) were diagnosed with AD. A total of 2425 participants (52.8%) were female, and 2167 (47.2%) were male. European and African ancestry had a slightly higher representation of women (74 [62.2%] in the African cohort, 22 [42.3%] in the Asian cohort, and 2329 [52.7%] in the European cohort). APOE-ε4 carriers were more prevalent in the European cohort compared with other ancestries (34.5% in African, 25.0% in Asian, and 41.0% in European), reflecting population differences in APOE allele frequencies. Although the median values of CSF biomarkers varied among the 3 ancestries, these values were not statistically different. Cohort-specific characteristics are presented in eTable 1 in Supplement 1 for demographic characteristics, eTable 2 in Supplement 1 for APOE genotypes, and eTable 3 in Supplement 1 for biomarker distributions.

Table 1. Participant Characteristics.

Characteristic	No. (%) of participants^a
Characteristic	European (n = 4421)	African (n = 119)	Asian (n = 52)
Age, mean (SD), y	71.0 (10.3)	69.0 (7.6)	69.0 (13.3)
Sex
Male	2092 (47.3)	45 (37.8)	30 (57.7)
Female	2329 (52.7)	74 (62.2)	22 (42.3)
Clinical diagnosis
AD	2171 (49.1)	38 (31.9)	27 (51.9)
Control	2250 (50.9)	81 (68.1)	25 (48.1)
APOE genotype
22	6 (0.1)	4 (3.4)	NA (0.0)
23	358 (8.1)	9 (7.6)	6 (11.5)
24	85 (1.9)	2 (1.7)	NA (0.0)
33	2243 (50.7)	65 (54.6)	33 (63.5)
34	1396 (31.6)	32 (26.9)	8 (15.4)
44	333 (7.5)	7 (5.9)	5 (9.6)
APOE-ε4 carrier
0	2607 (59.0)	78 (65.5)	39 (75.0)
1	1481 (33.5)	34 (28.6)	8 (15.4)
2	333 (7.5)	7 (5.9)	5 (9.6)
Aβ42, median (IQR), pg/mL	340 (183-639)	276 (192-726)	215 (157-266)
Phosphorylated tau, median (IQR), pg/mL	40 (25-65)	30 (23-45)	35 (23-54)
Total tau, median (IQR), pg/mL	179 (77-412)	116 (50-232)	63 (40-120)

Open in a new tab

Abbreviations: Aβ42, amyloid β1-42; AD, Alzheimer disease; APOE, apolipoprotein E.

^{^a}

Unless otherwise indicated. Mean (SD) for Aβ42, phosphorylated tau, and total tau biomarkers, as well as the median (IQR) for log₁₀-transformed Aβ42, phosphorylated tau, and total tau values, were calculated based on samples stratified by ancestry.

Sex Differences in CSF Biomarker Levels

We first examined sex differences in CSF biomarkers before examining the APOE association in model 1. For CSF Aβ42 levels, no significant sex association was observed, indicating similar levels in men and women across all 3 ancestries (β [SE], 0.27 [0.19]; P = .14 for African; β [SE], −0.28 [0.32]; P = .004 for Asian; and β [SE], −0.00 [0.03]; P = .92 for European ancestry), with no evidence of heterogeneity (eTables 4 and 5 in Supplement 1).

For CSF p-tau, women had significantly higher levels than men in both the European and African ancestry cohorts (β [SE], 0.08 [0.03]; P = .007 in the European cohort; β [SE], 0.45 [0.17]; P = .001 in the African cohort) (eTable 4 in Supplement 1). A similar finding was observed for Asian ancestry (β [SE], 0.60 [0.32]; P = .431), but it was not significant due to the small sample size. This was consistent across all 3 ancestries, although the ancestry-specific effect size showed evidence of heterogeneity (European individuals having a smaller effect size compared with African and Asian individuals; P = .048 for heterogeneity).

For CSF total tau, women consistently had higher levels than men in the European and African cohorts, but the effect size was not significant in the Asian cohort (β [SE], 0.55 [0.21]; P = .009 in the African cohort; β [SE], 0.60 [0.35]; P = .360 in the Asian cohort; and β [SE], 0.12 [0.03]; P < .001 in the European cohort) (eTable 4 in Supplement 1). In the meta-analysis, the overall sex difference across 3 ancestries was significant (β [SE], 0.12 [0.03]; P < .001), with no evidence of heterogeneity (P = .06 for heterogeneity).

Association of APOE-ε4 With CSF Biomarker Levels

For all 3 biomarkers, we observed a significant association with APOE-ε4 (Table 2). Relative to the European cohort (β [SE], −0.57 [0.02]; P < .001), this APOE-ε4 association was somewhat stronger in African and Asian ancestries (β [SE], −0.75 [0.14]; P < .001 in the African cohort; β [SD], −0.69 [0.23]; P = .004 in the Asian cohort) (eFigure 4 in Supplement 1), although statistical significance was reduced due to relatively fewer samples. The overall APOE-ε4 association remained significant in the meta-analysis (β [SE], −0.58 [0.02]; P < .001) with no evidence of heterogeneity.

Table 2. APOE-ε4 Effect Within and Across Ancestry^a.

Trait	European		African		Asian		Meta-analysis across ancestries
Trait	β (SE)	P value	β (SE)	P value	β (SE)	P value	β (SE)	P value
Aβ42
Both sexes	−0.57 (0.02)	<.001	−0.75 (0.14)	<.001	−0.69 (0.23)	.004	−0.58 (0.02)	<.001
Male	−0.63 (0.03)	<.001	−0.81 (0.23)	.001	0.34 (0.61)	.58	−0.63 (0.03)	<.001
Female	−0.52 (0.03)	<.001	−0.66 (0.17)	<.001	−0.86 (0.22)	<.001	−0.53 (0.03)	<.001
Sex × APOE-ε4 interaction	0.11 (0.04)	.01	0.17 (0.28)	.55	−1.24 (0.62)	.049	0.11 (0.04)	.01
Phosphorylated tau
Both sexes	0.35 (0.02)	<.001	0.44 (0.13)	<.001	0.18 (0.23)	.43	0.35 (0.02)	<.001
Male	0.33 (0.03)	<.001	0.10 (0.18)	.57	−0.69 (0.49)	.17	0.32 (0.03)	<.001
Female	0.37 (0.03)	<.001	0.66 (0.17)	<.001	0.34 (0.30)	.27	0.38 (0.03)	<.001
Sex × APOE-ε4 interaction	0.03 (0.05)	.48	0.55 (0.26)	.03	1.04 (0.63)	.11	0.34 (0.26)	.19
Tau
Both sexes	0.32 (0.02)	<.001	0.46 (0.16)	.004	0.25 (0.27)	.36	0.32 (0.02)	<.001
Male	0.27 (0.03)	<.001	0.20 (0.22)	.36	−0.90 (0.56)	.12	0.27 (0.03)	<.001
Female	0.36 (0.03)	<.001	0.65 (0.22)	.004	0.48 (0.34)	.18	0.37 (0.03)	<.001
Sex × APOE-ε4 interaction	0.09 (0.05)	.053	0.46 (0.32)	.16	1.32 (0.73)	.08	0.10 (0.05)	.03

Open in a new tab

Abbreviations: Aβ42, amyloid β1-42; APOE, apolipoprotein E.

^{^a}

APOE-ε4 evaluates the main effect of the APOE-ε4 allele on cerebrospinal fluid biomarkers from model 1. Values for male participants focus on the association of APOE-ε4 in male participants from model 2. Values for female participants focus on the association of APOE-ε4 in female participants from model 3. Interaction values focus on the interaction between sex and APOE-ε4 on cerebrospinal fluid biomarkers from model 4.

APOE-ε4 carriers had higher tau levels, with significant associations seen in the European and African cohorts for p-tau (β [SE], 0.35 [0.02]; P < .001 in the European cohort; β [SE], 0.44 [0.13]; P < .001 in the African cohort) as well as for total tau (β [SE], 0.32 [0.02]; P < .001 in the European cohort and β [SE], 0.46 [0.16]; P = .004 for the African cohort). In the Asian cohort, there was no significant association for p-tau or total tau due to the small sample size. A meta-analysis confirmed an overall significant association of APOE-ε4 with both p-tau and total tau values (β [SE], 0.35 [0.02]; P < .001 for p-tau and 0.32 [0.02]; P < .001 for total tau).

Sex-Specific APOE-ε4 Association

To examine the APOE-ε4 association in more detail, we analyzed men and women separately using models 2 and 3 and then confirmed sex differences through the significance of the interaction term in model 4. The association of APOE-ε4 with Aβ42 was more pronounced in European men (β [SE], −0.63 [0.03]; P < .001) compared with women (β [SE], −0.52 [0.03]; P < .001) (Figure, A and eFigure 5 in Supplement 1), with a statistically significant difference (P = .01 for interaction) (Table 2). A similar trend was observed in African ancestry. In Asian ancestry, the APOE-ε4 association was only observed in women, whereas the result for men was not in the expected direction due to a very small sample of APOE-ε4 carriers (n = 3). A meta-analysis confirmed a significant interaction between sex and APOE-ε4 on Aβ42 (β [SE], 0.11 [0.04]; P = .01 for interaction) (eFigure 6 in Supplement 1).

For p-tau, the association with APOE-ε4 differed between men and women only in individuals of African ancestry (Figure, B). In the European ancestry cohort, the association with APOE-ε4 was somewhat higher in women (β [SE], 0.37 [0.03] in women; β [SE], 0.33 [0.03] in men) but not significantly different (P = .48 for interaction). In the African ancestry cohort, the APOE-ε4 association was observed in women (β [SE], 0.66 [0.17]; P < .001) but not men (β [SE], 0.10 [0.18]; P = .57), with a significant difference (P = .03 for interaction). In the Asian ancestry cohort, the APOE-ε4 association was not significant in either sex (eFigure 7 in Supplement 1). Due to this heterogeneity in differences across ancestries (P = .04 for heterogeneity), no overall interaction was observed.

For total tau, the APOE-ε4 association was stronger in women for all 3 ancestries. In the European ancestry cohort, this difference (β [SE], 0.36 [0.03]; P < .001 in women; β [SE], 0.27 [0.03]; P < .001 in men) was not significant (P = .053 for interaction). In the African ancestry cohort, the APOE-ε4 association was observed in women (β [SE], 0.65 [0.22]; P = .004) but not men (β [SE], 0.20 [0.22]; P = .36), although this difference was not statistically significant (P = .16 for interaction). In the Asian ancestry cohort, no significant associations were found. Although the magnitudes of these associations were somewhat different, there was no evidence of heterogeneity across ancestries (P = .13 for heterogeneity). A meta-analysis confirmed a significant overall interaction between sex and APOE-ε4 on total tau (β [SE], 0.10 [0.05]; P = .03 for interaction).

Sensitivity Analysis

Our analysis included APOE-ε2 carriers in the reference group (APOE-ε4 dosage = 0) as well as APOE-ε4 dosage 1 group. To examine whether our results were influenced by inclusion of any APOE-ε2 carriers, we conducted 2 sets of sensitivity analyses. The first sensitivity analysis that included only ε3/ε3 carriers as the reference group (coded as 0; excluding ε2/ε2 and ε2/ε3) was highly similar to the primary analysis (eTable 6 in Supplement 1). The second sensitivity analysis that completely excluded any ε2 carriers (0 for ε3/ε3, 1 for ε3/ε4, and 2 for ε4/ε4) was also similar, with a slight difference in their P values due to reduced sample size (eTable 7 in Supplement 1). In particular, the sex × APOE-ε4 interaction on Aβ in the European cohort was identical across the 3 sets (β [SE], 0.11 [0.04]) (Table 2; eTables 6 and 7 in Supplement 1). We observed consistent interactions for total tau in the European cohort (β [SE], 0.09 [0.05]) and a similar interaction for p-tau in the African cohort (β [SE], 0.55 [0.26] in the primary analysis and first sensitivity analysis and 0.54 [0.28] in the second sensitivity analysis). These analyses demonstrated that the inclusion of APOE-ε2 did not alter the observed sex differences.

Discussion

This study, to our knowledge, is the first to evaluate the main and interactive associations of sex and APOE-ε4 dosage with 3 CSF biomarkers across African, Asian, and European ancestries. This study harmonized CSF biomarkers of 4592 participants recruited from 20 cohorts and performed ancestry-specific analyses and meta-analysis, providing robust evidence of complex interplay among sex, ancestry, and APOE-ε4 in these AD biomarkers. First, for CSF Aβ42, a higher APOE-ε4 dosage score was associated with lower values, indicating more severe Aβ pathology, in men and women separately and jointly. The male and female APOE-ε4 associations were statistically different in those of European ancestry. Second, for CSF p-tau, women had higher levels, indicating more severe neurofibrillary pathology. Although the association between APOE-ε4 dosage and p-tau was in the expected direction (higher APOE-ε4 dosage for higher p-tau values) in both sexes, the association was statistically different only in those of African ancestry. Third, for CSF total tau, women had higher levels, indicating more neuronal damage. Moreover, the association between APOE-ε4 dosage and total tau was stronger in women than men in both the African and European cohorts.

Several studies have investigated the association of sex and APOE-ε4 with Aβ and tau pathology. Altmann et al²³ reported the sex × APOE-ε4 interactions for Aβ in healthy individuals and interaction for p-tau and total tau in individuals with MCI, suggesting that interaction between sex and APOE depends on cognition status. Hohman et al²² reported significant sex × APOE-ε4 interactions for p-tau and total tau, among which interaction remained significant for total tau in Aβ-positive individuals. Although our finding for sex × APOE-ε4 interactions on Aβ is different from that of Hohman et al,²² it is in line with the finding of Altmann et al.²³ In addition, Saunders et al⁵³ observed high negative correlation between Aβ and p-tau, with more pronounced sex differences, in APOE-ε4 carriers, whereas correlation in noncarriers was opposite. In contrast, multiple studies presented sex differences in the association of APOE-ε4 dosage with tau accumulation, regardless of amyloid levels, in individuals with MCI and AD,⁵⁴ reporting higher tau load only in women via positron emission tomography⁵⁵ or via CSF biomarkers.⁵⁶ Our findings of higher p-tau and total tau levels in female APOE-ε4 carriers are consistent with these studies. These studies, together with ours, demonstrate a complex presentation of sex × APOE-ε4 interactions for AD pathology and the resulting cognition status.

Previous studies highlighted significant variation in the effect of APOE-ε4 on AD risk across different ethnic and racial groups, underscoring the importance of ancestry in AD studies.^11,12,57 A recent study reported these ethnic variations for AD risk between European and African ancestry in large scale.¹² The association of APOE genotype with AD neuropathology also differs by ancestry, with African individuals often exhibiting lower amyloid burden and attenuated APOE-ε4 risk compared with individuals of European ancestry.⁵⁸ These ancestry differences in the association of APOE-ε4 with amyloid pathology appear to be confounded by age.⁵⁹ Racial disparities in APOE-ε4 were also reported for tau pathology. African American participants were reported to exhibit lower CSF p-tau and total tau levels compared with White individuals,²⁷ even when they had similar cognitive scores.²⁶ Although one study reported these ancestry differences via genetically derived ancestry information,⁶⁰ another study noted these ancestry differences only with self-reported race (and not in genetic ancestry).⁶¹ Because self-reported African individuals often exhibit a continuum of African ancestry with a large admixture with European ancestry,⁶⁰ inconsistencies between these 2 studies may be due to their sample selection differences. In our study, relatively lower p-tau and total tau levels were noticeable in men of African ancestry, which may have resulted in sex differences in their APOE-ε4 effects on p-tau levels.

Recent findings have expanded the sex differences in APOE-ε2 and their role in AD risk and cognitive decline. The protective APOE-ε2 effect was reported for amyloid and regional tau burden.²¹ One study reported the association of APOE-ε2 with a slower cognitive decline more in men, suggesting sex-specific protective effects.⁶² Another study reported the protective effect of APOE-ε2 on late-life cognition in women but not men.⁶³ This APOE-ε2 effect on AD is reported to vary across populations because it is shown to be most protective in European populations followed by African populations, with no association in Asian and Hispanic populations.¹² Among cognitively unimpaired individuals, the protective effect of APOE-ε2 on baseline executive function was reported to be female specific in European individuals but male specific in African individuals.⁶⁴ Although our study focused on APOE-ε4, we performed 2 sets of sensitivity analyses that examined the potential influence of any APOE-ε2 carriers. Both sets of analysis had highly consistent outcomes with the primary analysis, indicating that the inclusion of APOE-ε2 carriers does not substantially alter observed sex differences in APOE-ε4 association and the interplay with sex and ancestry.

There are several potential mechanisms underlying a direct or regulatory association of APOE-ε4 expression with CSF biomarkers and AD risk. The most prevailing explanation is through regulation of sex hormones or through sex chromosome. In women, changes in sex hormones in menopause may contribute to AD pathology and cognitive impairment.⁸ For example, estrogen loss in menopausal women may be one explanation for a more pronounced sex difference in APOE-ε4 associations with AD between the ages of 55 and 70 years.⁶⁵ Estradiol has been shown to increase CSF tau accumulation while simultaneously reducing neuronal Aβ generation and preventing tau phosphorylation, indicating a multifaceted role in tau and amyloid regulation.^66,67 APOE expression may also regulate the estrogen receptor α polymorphisms, which are associated with faster cognitive decline in female patients with AD.⁶⁸ Beyond estradiol, testosterone also plays a key role in the greater CSF p-tau level in female APOE-ε4 carriers.⁶⁹ In addition, sex-specific effects of APOE-ε4 in AD may be influenced by X chromosome mechanisms, in which differences in gene expression related to sex hormones could affect how AD develops in men and women.⁷⁰

Limitations

This study has several limitations. First, African and Asian ancestries had smaller sample sizes due to underrepresentation of CSF samples in non-European populations. Although the magnitude of sex × APOE-ε4 interaction on all 3 biomarkers was more pronounced in African and Asian ancestries (compared with those of European ancestry), statistical significance was often not reached due to the limited sample sizes. Although our results indicate lower p-tau and total tau levels in African individuals compared with European individuals, often this led to a lack of sex differences. In addition, the results in Asian men were somewhat unexpected, which appears to be affected by a limited sample size in APOE-ε4 carriers. Given the increasing global AD risk, the generalizability of CSF biomarkers in these populations is critical for disease prevention, warranting a follow-up study. Second, interplay between sex and APOE-ε4 on the cascade of amyloid pathology and tau pathology is known to be complex, often exhibiting more pronounced sex differences in certain age ranges. To disentangle our findings (in particular, the presence of sex × APOE-ε4 interaction on Aβ and absence on p-tau), more detailed follow-up study may be needed. Third, although this study performed the sensitivity analysis for the inclusion of APOE-ε2, the main scope of this study was to examine the risk effect of APOE-ε4. Additional research is needed to investigate the protective effects of APOE-ε2 on these CSF biomarkers.

Conclusions

In this study, we report sex differences observed in the association of the APOE-ε4 allele with amyloid and tau pathology in individuals of African, Asian, and European ancestry based on harmonized CSF biomarkers. This study highlights the importance of accounting for sex in examining APOE-ε4’s influence for understanding underlying amyloid and tau pathology in AD. Although we provided robust evidence of complex interplay between sex and APOE-ε4 for European ancestry, further research is needed to fully understand some ancestry differences.

Supplement 1.

eTable 1. Demographic Distribution by Study Cohort

eTable 2. Distribution of APOE Genotypes Across Cohorts

eTable 3. Distribution of CSF Biomarkers (Aβ42, pTau, and Tau) by Study Cohort

eTable 4. Sex Effect in Each Ancestry and Across Ancestry (via Meta-Analysis)

eTable 5. Heterogeneity Test

eTable 6. Sensitivity Analysis With ε3/ε3 as Reference

eTable 7. Sensitivity Analysis Excluding APOE-ε2/ε4 Heterozygotes

eFigure 1. Flowchart

eFigure 2. Genetically Derived Ancestry Information

eFigure 3. Histogram of CSF Biomarkers Before and After Harmonization

eFigure 4. Sex and APOE-ε4 Effect Across Both Sexes

eFigure 5. Sex-Specific APOE-ε4 Effects

eFigure 6. Interaction Effect Between Sex and APOE-ε4

eFigure 7. Sex-Stratified APOE-ε4 Effect in Asian Ancestry

eMethods. Cohort Description

jamanetwopen-e250562-s001.pdf^{(1.2MB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e250562-s002.pdf^{(13KB, pdf)}

References

1.Scheltens P, De Strooper B, Kivipelto M, et al. Alzheimer’s disease. Lancet. 2021;397(10284):1577-1590. doi: 10.1016/S0140-6736(20)32205-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer’s disease. Lancet. 2011;377(9770):1019-1031. doi: 10.1016/S0140-6736(10)61349-9 [DOI] [PubMed] [Google Scholar]
3.Gatz M, Reynolds CA, Fratiglioni L, et al. Role of genes and environments for explaining Alzheimer disease. Arch Gen Psychiatry. 2006;63(2):168-174. doi: 10.1001/archpsyc.63.2.168 [DOI] [PubMed] [Google Scholar]
4.GBD 2016 Neurology Collaborators . Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):459-480. doi: 10.1016/S1474-4422(18)30499-X [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Skillbäck T, Delsing L, Synnergren J, et al. CSF/serum albumin ratio in dementias: a cross-sectional study on 1861 patients. Neurobiol Aging. 2017;59:1-9. doi: 10.1016/j.neurobiolaging.2017.06.028 [DOI] [PubMed] [Google Scholar]
6.Verghese PB, Castellano JM, Holtzman DM. Apolipoprotein E in Alzheimer’s disease and other neurological disorders. Lancet Neurol. 2011;10(3):241-252. doi: 10.1016/S1474-4422(10)70325-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Ridge PG, Mukherjee S, Crane PK, Kauwe JS; Alzheimer’s Disease Genetics Consortium . Alzheimer’s disease: analyzing the missing heritability. PLoS One. 2013;8(11):e79771. doi: 10.1371/journal.pone.0079771 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Lopez-Lee C, Torres ERS, Carling G, Gan L. Mechanisms of sex differences in Alzheimer’s disease. Neuron. 2024;112(8):1208-1221. doi: 10.1016/j.neuron.2024.01.024 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Scheltens P, Blennow K, Breteler MM, et al. Alzheimer’s disease. Lancet. 2016;388(10043):505-517. doi: 10.1016/S0140-6736(15)01124-1 [DOI] [PubMed] [Google Scholar]
10.Fortea J, Pegueroles J, Alcolea D, et al. APOE4 homozygosity represents a distinct genetic form of Alzheimer’s disease. Nat Med. 2024;30(5):1284-1291. doi: 10.1038/s41591-024-02931-w [DOI] [PubMed] [Google Scholar]
11.Farrer LA, Cupples LA, Haines JL, et al. ; APOE and Alzheimer Disease Meta Analysis Consortium . Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. JAMA. 1997;278(16):1349-1356. doi: 10.1001/jama.1997.03550160069041 [DOI] [PubMed] [Google Scholar]
12.Belloy ME, Andrews SJ, Le Guen Y, et al. APOE genotype and Alzheimer disease risk across age, sex, and population ancestry. JAMA Neurol. 2023;80(12):1284-1294. doi: 10.1001/jamaneurol.2023.3599 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Blennow K, Hampel H, Weiner M, Zetterberg H. Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol. 2010;6(3):131-144. doi: 10.1038/nrneurol.2010.4 [DOI] [PubMed] [Google Scholar]
14.Shaw LM, Vanderstichele H, Knapik-Czajka M, et al. ; Alzheimer’s Disease Neuroimaging Initiative . Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol. 2009;65(4):403-413. doi: 10.1002/ana.21610 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Visser PJ, Verhey F, Knol DL, et al. Prevalence and prognostic value of CSF markers of Alzheimer’s disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the DESCRIPA study: a prospective cohort study. Lancet Neurol. 2009;8(7):619-627. doi: 10.1016/S1474-4422(09)70139-5 [DOI] [PubMed] [Google Scholar]
16.Welge V, Fiege O, Lewczuk P, et al. Combined CSF tau, p-tau181 and amyloid-beta 38/40/42 for diagnosing Alzheimer’s disease. J Neural Transm (Vienna). 2009;116(2):203-212. doi: 10.1007/s00702-008-0177-6 [DOI] [PubMed] [Google Scholar]
17.Blennow K. CSF biomarkers for mild cognitive impairment. J Intern Med. 2004;256(3):224-234. doi: 10.1111/j.1365-2796.2004.01368.x [DOI] [PubMed] [Google Scholar]
18.Blennow K. CSF biomarkers for Alzheimer’s disease: use in early diagnosis and evaluation of drug treatment. Expert Rev Mol Diagn. 2005;5(5):661-672. doi: 10.1586/14737159.5.5.661 [DOI] [PubMed] [Google Scholar]
19.Marksteiner J, Hinterhuber H, Humpel C. Cerebrospinal fluid biomarkers for diagnosis of Alzheimer’s disease: beta-amyloid(1-42), tau, phospho-tau-181 and total protein. Drugs Today (Barc). 2007;43(6):423-431. doi: 10.1358/dot.2007.43.6.1067341 [DOI] [PubMed] [Google Scholar]
20.Mattsson N, Zetterberg H, Hansson O, et al. CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA. 2009;302(4):385-393. doi: 10.1001/jama.2009.1064 [DOI] [PubMed] [Google Scholar]
21.Young CB, Johns E, Kennedy G, et al. ; Alzheimer’s Disease Neuroimaging Initiative; A4 Study Team . APOE effects on regional tau in preclinical Alzheimer’s disease. Mol Neurodegener. 2023;18(1):1. doi: 10.1186/s13024-022-00590-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Hohman TJ, Dumitrescu L, Barnes LL, et al. ; Alzheimer’s Disease Genetics Consortium and the Alzheimer’s Disease Neuroimaging Initiative . Sex-specific association of apolipoprotein E with cerebrospinal fluid levels of tau. JAMA Neurol. 2018;75(8):989-998. doi: 10.1001/jamaneurol.2018.0821 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Altmann A, Tian L, Henderson VW, Greicius MD; Alzheimer’s Disease Neuroimaging Initiative Investigators . Sex modifies the APOE-related risk of developing Alzheimer disease. Ann Neurol. 2014;75(4):563-573. doi: 10.1002/ana.24135 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Garatachea N, Emanuele E, Calero M, et al. ApoE gene and exceptional longevity: insights from three independent cohorts. Exp Gerontol. 2014;53:16-23. doi: 10.1016/j.exger.2014.02.004 [DOI] [PubMed] [Google Scholar]
25.Deters K, Napolioni V, Greicius M, Mormino B. African ancestry moderates the effect of ApoE4 on cognitive decline. Alzheimer’s & Dementia. 2018;14:P1027-P1028. doi: 10.1212/WNL.0000000000011599 [DOI] [Google Scholar]
26.Howell JC, Watts KD, Parker MW, et al. Race modifies the relationship between cognition and Alzheimer’s disease cerebrospinal fluid biomarkers. Alzheimers Res Ther. 2017;9(1):88. doi: 10.1186/s13195-017-0315-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Morris JC, Schindler SE, McCue LM, et al. Assessment of racial disparities in biomarkers for Alzheimer disease. JAMA Neurol. 2019;76(3):264-273. doi: 10.1001/jamaneurol.2018.4249 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Swaminathan S, Shen L, Risacher SL, et al. ; Alzheimer’s Disease Neuroimaging Initiative . Amyloid pathway-based candidate gene analysis of [(11)C]PiB-PET in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Brain Imaging Behav. 2012;6(1):1-15. doi: 10.1007/s11682-011-9136-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Ellis KA, Bush AI, Darby D, et al. ; AIBL Research Group . The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer’s disease. Int Psychogeriatr. 2009;21(4):672-687. doi: 10.1017/S1041610209009405 [DOI] [PubMed] [Google Scholar]
30.Fowler C, Rainey-Smith SR, Bird S, et al. ; the AIBL investigators . Fifteen years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study: progress and observations from 2,359 older adults spanning the spectrum from cognitive normality to Alzheimer’s disease. J Alzheimers Dis Rep. 2021;5(1):443-468. doi: 10.3233/ADR-210005 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Albert M, Soldan A, Gottesman R, et al. Cognitive changes preceding clinical symptom onset of mild cognitive impairment and relationship to ApoE genotype. Curr Alzheimer Res. 2014;11(8):773-784. doi: 10.2174/156720501108140910121920 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Álvarez I, Diez-Fairen M, Aguilar M, et al. Added value of cerebrospinal fluid multimarker analysis in diagnosis and progression of dementia. Eur J Neurol. 2021;28(4):1142-1152. doi: 10.1111/ene.14658 [DOI] [PubMed] [Google Scholar]
33.de Rojas I, Moreno-Grau S, Tesi N, et al. ; EADB contributors; GR@ACE study group; DEGESCO consortium; IGAP (ADGC, CHARGE, EADI, GERAD); PGC-ALZ consortia . Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores. Nat Commun. 2021;12(1):3417. doi: 10.1038/s41467-021-22491-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Riemenschneider M, Wagenpfeil S, Diehl J, et al. Tau and Aβ42 protein in CSF of patients with frontotemporal degeneration. Neurology. 2002;58(11):1622-1628. doi: 10.1212/WNL.58.11.1622 [DOI] [PubMed] [Google Scholar]
35.Deming Y, Filipello F, Cignarella F, et al. The MS4A gene cluster is a key modulator of soluble TREM2 and Alzheimer’s disease risk. Sci Transl Med. 2019;11(505):eaau2291. doi: 10.1126/scitranslmed.aau2291 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Voyle N, Patel H, Folarin A, et al. ; EDAR and DESCRIPA study groups and the Alzheimer’s Disease Neuroimaging Initiative . Genetic risk as a marker of amyloid-β and tau burden in cerebrospinal fluid. J Alzheimers Dis. 2017;55(4):1417-1427. doi: 10.3233/JAD-160707 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Visser PJ, Verhey FR, Boada M, et al. Development of screening guidelines and clinical criteria for predementia Alzheimer’s disease: the DESCRIPA study. Neuroepidemiology. 2008;30(4):254-265. doi: 10.1159/000135644 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.MacDonald SWS, Thorvaldsson V, Johansson B, Bäckman L. O3-02-02: identifying factors that moderate the onset and rate of prodromal cognitive impairment in dementia. Alzheimers Dement. 2010;6(4 suppl):S127-S127. doi: 10.1016/j.jalz.2010.05.398 [DOI] [Google Scholar]
39.Deming Y, Li Z, Kapoor M, et al. ; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer Disease Genetic Consortium (ADGC) . Genome-wide association study identifies four novel loci associated with Alzheimer’s endophenotypes and disease modifiers. Acta Neuropathol. 2017;133(5):839-856. doi: 10.1007/s00401-017-1685-y [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Morris JC, Roe CM, Xiong C, et al. APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol. 2010;67(1):122-131. doi: 10.1002/ana.21843 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Ramanan VK, Wang X, Przybelski SA, et al. Variants in PPP2R2B and IGF2BP3 are associated with higher tau deposition. Brain Commun. 2020;2(2):fcaa159. doi: 10.1093/braincomms/fcaa159 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Beekly DL, Ramos EM, Lee WW, et al. ; NIA Alzheimer’s Disease Centers . The National Alzheimer’s Coordinating Center (NACC) database: the Uniform Data Set. Alzheimer Dis Assoc Disord. 2007;21(3):249-258. doi: 10.1097/WAD.0b013e318142774e [DOI] [PubMed] [Google Scholar]
43.Deming Y, Dumitrescu L, Barnes LL, et al. ; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer Disease Genetics Consortium (ADGC) . Sex-specific genetic predictors of Alzheimer’s disease biomarkers. Acta Neuropathol. 2018;136(6):857-872. doi: 10.1007/s00401-018-1881-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Al-Hakim AK, Zagorska A, Chapman L, Deak M, Peggie M, Alessi DR. Control of AMPK-related kinases by USP9X and atypical Lys(29)/Lys(33)-linked polyubiquitin chains. Biochem J. 2008;411(2):249-260. doi: 10.1042/BJ20080067 [DOI] [PubMed] [Google Scholar]
45.Jefferson AL, Gifford KA, Acosta LM, et al. The Vanderbilt Memory & Aging Project: study design and baseline cohort overview. J Alzheimers Dis. 2016;52(2):539-559. doi: 10.3233/JAD-150914 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Berman SE, Koscik RL, Clark LR, et al. Use of the Quick Dementia Rating System (QDRS) as an initial screening measure in a longitudinal cohort at risk for Alzheimer’s disease. J Alzheimers Dis Rep. 2017;1(1):9-13. doi: 10.3233/ADR-170004 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Timsina J, Ali M, Do A, et al. Harmonization of CSF and imaging biomarkers in Alzheimer’s disease: need and practical applications for genetics studies and preclinical classification. Neurobiol Dis. 2024;190:106373. doi: 10.1016/j.nbd.2023.106373 [DOI] [PubMed] [Google Scholar]
48.Sjögren M, Vanderstichele H, Agren H, et al. Tau and Aβ42 in cerebrospinal fluid from healthy adults 21-93 years of age: establishment of reference values. Clin Chem. 2001;47(10):1776-1781. doi: 10.1093/clinchem/47.10.1776 [DOI] [PubMed] [Google Scholar]
49.Popp J, Lewczuk P, Frommann I, et al. Cerebrospinal fluid markers for Alzheimer’s disease over the lifespan: effects of age and the APOEε4 genotype. J Alzheimers Dis. 2010;22(2):459-468. doi: 10.3233/JAD-2010-100561 [DOI] [PubMed] [Google Scholar]
50.Cochran WG. The comparison of percentages in matched samples. Biometrika. 1950;37(3-4):256-266. doi: 10.1093/biomet/37.3-4.256 [DOI] [PubMed] [Google Scholar]
51.Balduzzi S, Rücker G, Schwarzer G. How to perform a meta-analysis with R: a practical tutorial. Evid Based Ment Health. 2019;22(4):153-160. doi: 10.1136/ebmental-2019-300117 [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Viechtbauer W. Conducting meta-analyses in R with the metafor Package. J Stat Software. 2010;36(3):1-48. doi: 10.18637/jss.v036.i03 [DOI] [Google Scholar]
53.Saunders TS, Jenkins N, Blennow K, Ritchie C, Muniz-Terrera G. Interactions between apolipoprotein E, sex, and amyloid-beta on cerebrospinal fluid p-tau levels in the European prevention of Alzheimer’s dementia longitudinal cohort study (EPAD LCS). EBioMedicine. 2022;83:104241. doi: 10.1016/j.ebiom.2022.104241 [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Yan S, Zheng C, Paranjpe MD, et al. Sex modifies APOE ε4 dose effect on brain tau deposition in cognitively impaired individuals. Brain. 2021;144(10):3201-3211. doi: 10.1093/brain/awab160 [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Wang YT, Pascoal TA, Therriault J, et al. ; Alzheimer’s Disease Neuroimaging Initiative . Interactive rather than independent effect of APOE and sex potentiates tau deposition in women. Brain Commun. 2021;3(2):fcab126. doi: 10.1093/braincomms/fcab126 [DOI] [PMC free article] [PubMed] [Google Scholar]
56.Liu M, Paranjpe MD, Zhou X, et al. Sex modulates the ApoE ε4 effect on brain tau deposition measured by ¹⁸F-AV-1451 PET in individuals with mild cognitive impairment. Theranostics. 2019;9(17):4959-4970. doi: 10.7150/thno.35366 [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Qin W, Li W, Wang Q, et al. Race-related association between APOE genotype and Alzheimer’s disease: a systematic review and meta-analysis. J Alzheimers Dis. 2021;83(2):897-906. doi: 10.3233/JAD-210549 [DOI] [PubMed] [Google Scholar]
58.Naslavsky MS, Suemoto CK, Brito LA, et al. Global and local ancestry modulate APOE association with Alzheimer’s neuropathology and cognitive outcomes in an admixed sample. Mol Psychiatry. 2022;27(11):4800-4808. doi: 10.1038/s41380-022-01729-x [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Royse SK, Snitz BE, Hill AV, et al. Apolipoprotein E and Alzheimer’s disease pathology in African American older adults. Neurobiol Aging. 2024;139:11-19. doi: 10.1016/j.neurobiolaging.2024.03.005 [DOI] [PubMed] [Google Scholar]
60.Deters KD, Napolioni V, Sperling RA, et al. Amyloid PET imaging in self-identified non-Hispanic Black participants of the Anti-Amyloid in Asymptomatic Alzheimer’s Disease (A4) Study. Neurology. 2021;96(11):e1491-e1500. doi: 10.1212/WNL.0000000000011599 [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Hajjar I, Yang Z, Okafor M, et al. Association of plasma and cerebrospinal fluid Alzheimer disease biomarkers with race and the role of genetic ancestry, vascular comorbidities, and neighborhood factors. JAMA Netw Open. 2022;5(10):e2235068. doi: 10.1001/jamanetworkopen.2022.35068 [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Wood ME, Xiong LY, Wong YY, et al. ; ADNI and Prevent-AD Research Groups . Sex differences in associations between APOE ε2 and longitudinal cognitive decline. Alzheimers Dement. 2023;19(10):4651-4661. doi: 10.1002/alz.13036 [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Nichols E, Brickman AM, Casaletto KB, et al. AD and non-AD mediators of the pathway between the APOE genotype and cognition. Alzheimers Dement. 2023;19(6):2508-2519. doi: 10.1002/alz.12885 [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Walters S, Contreras AG, Eissman JM, et al. ; Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Genetics Consortium, and Alzheimer’s Disease Sequencing Project . Associations of sex, race, and apolipoprotein E alleles with multiple domains of cognition among older adults. JAMA Neurol. 2023;80(9):929-939. doi: 10.1001/jamaneurol.2023.2169 [DOI] [PMC free article] [PubMed] [Google Scholar]
65.Neu SC, Pa J, Kukull W, et al. Apolipoprotein E genotype and sex risk factors for Alzheimer disease: a meta-analysis. JAMA Neurol. 2017;74(10):1178-1189. doi: 10.1001/jamaneurol.2017.2188 [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Alvarez-de-la-Rosa M, Silva I, Nilsen J, et al. Estradiol prevents neural tau hyperphosphorylation characteristic of Alzheimer’s disease. Ann N Y Acad Sci. 2005;1052:210-224. doi: 10.1196/annals.1347.016 [DOI] [PubMed] [Google Scholar]
67.Xu H, Gouras GK, Greenfield JP, et al. Estrogen reduces neuronal generation of Alzheimer β-amyloid peptides. Nat Med. 1998;4(4):447-451. doi: 10.1038/nm0498-447 [DOI] [PubMed] [Google Scholar]
68.Corbo RM, Gambina G, Ruggeri M, Scacchi R. Association of estrogen receptor α (ESR1) Pvu II and Xba I polymorphisms with sporadic Alzheimer’s disease and their effect on apolipoprotein E concentrations. Dement Geriatr Cogn Disord. 2006;22(1):67-72. doi: 10.1159/000093315 [DOI] [PubMed] [Google Scholar]
69.Sundermann EE, Panizzon MS, Chen X, Andrews M, Galasko D, Banks SJ; Alzheimer’s Disease Neuroimaging Initiative . Sex differences in Alzheimer’s-related Tau biomarkers and a mediating effect of testosterone. Biol Sex Differ. 2020;11(1):33. doi: 10.1186/s13293-020-00310-x [DOI] [PMC free article] [PubMed] [Google Scholar]
70.Belloy ME, Le Guen Y, Stewart I, et al. Role of the X chromosome in Alzheimer disease genetics. JAMA Neurol. 2024;81(10):1032-1042. doi: 10.1001/jamaneurol.2024.2843 [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.

Supplementary Materials

Supplement 1.

eTable 1. Demographic Distribution by Study Cohort

eTable 2. Distribution of APOE Genotypes Across Cohorts

eTable 3. Distribution of CSF Biomarkers (Aβ42, pTau, and Tau) by Study Cohort

eTable 4. Sex Effect in Each Ancestry and Across Ancestry (via Meta-Analysis)

eTable 5. Heterogeneity Test

eTable 6. Sensitivity Analysis With ε3/ε3 as Reference

eTable 7. Sensitivity Analysis Excluding APOE-ε2/ε4 Heterozygotes

eFigure 1. Flowchart

eFigure 2. Genetically Derived Ancestry Information

eFigure 3. Histogram of CSF Biomarkers Before and After Harmonization

eFigure 4. Sex and APOE-ε4 Effect Across Both Sexes

eFigure 5. Sex-Specific APOE-ε4 Effects

eFigure 6. Interaction Effect Between Sex and APOE-ε4

eFigure 7. Sex-Stratified APOE-ε4 Effect in Asian Ancestry

eMethods. Cohort Description

jamanetwopen-e250562-s001.pdf^{(1.2MB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e250562-s002.pdf^{(13KB, pdf)}

[zoi250047r1] 1.Scheltens P, De Strooper B, Kivipelto M, et al. Alzheimer’s disease. Lancet. 2021;397(10284):1577-1590. doi: 10.1016/S0140-6736(20)32205-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r2] 2.Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer’s disease. Lancet. 2011;377(9770):1019-1031. doi: 10.1016/S0140-6736(10)61349-9 [DOI] [PubMed] [Google Scholar]

[zoi250047r3] 3.Gatz M, Reynolds CA, Fratiglioni L, et al. Role of genes and environments for explaining Alzheimer disease. Arch Gen Psychiatry. 2006;63(2):168-174. doi: 10.1001/archpsyc.63.2.168 [DOI] [PubMed] [Google Scholar]

[zoi250047r4] 4.GBD 2016 Neurology Collaborators . Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):459-480. doi: 10.1016/S1474-4422(18)30499-X [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r5] 5.Skillbäck T, Delsing L, Synnergren J, et al. CSF/serum albumin ratio in dementias: a cross-sectional study on 1861 patients. Neurobiol Aging. 2017;59:1-9. doi: 10.1016/j.neurobiolaging.2017.06.028 [DOI] [PubMed] [Google Scholar]

[zoi250047r6] 6.Verghese PB, Castellano JM, Holtzman DM. Apolipoprotein E in Alzheimer’s disease and other neurological disorders. Lancet Neurol. 2011;10(3):241-252. doi: 10.1016/S1474-4422(10)70325-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r7] 7.Ridge PG, Mukherjee S, Crane PK, Kauwe JS; Alzheimer’s Disease Genetics Consortium . Alzheimer’s disease: analyzing the missing heritability. PLoS One. 2013;8(11):e79771. doi: 10.1371/journal.pone.0079771 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r8] 8.Lopez-Lee C, Torres ERS, Carling G, Gan L. Mechanisms of sex differences in Alzheimer’s disease. Neuron. 2024;112(8):1208-1221. doi: 10.1016/j.neuron.2024.01.024 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r9] 9.Scheltens P, Blennow K, Breteler MM, et al. Alzheimer’s disease. Lancet. 2016;388(10043):505-517. doi: 10.1016/S0140-6736(15)01124-1 [DOI] [PubMed] [Google Scholar]

[zoi250047r10] 10.Fortea J, Pegueroles J, Alcolea D, et al. APOE4 homozygosity represents a distinct genetic form of Alzheimer’s disease. Nat Med. 2024;30(5):1284-1291. doi: 10.1038/s41591-024-02931-w [DOI] [PubMed] [Google Scholar]

[zoi250047r11] 11.Farrer LA, Cupples LA, Haines JL, et al. ; APOE and Alzheimer Disease Meta Analysis Consortium . Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. JAMA. 1997;278(16):1349-1356. doi: 10.1001/jama.1997.03550160069041 [DOI] [PubMed] [Google Scholar]

[zoi250047r12] 12.Belloy ME, Andrews SJ, Le Guen Y, et al. APOE genotype and Alzheimer disease risk across age, sex, and population ancestry. JAMA Neurol. 2023;80(12):1284-1294. doi: 10.1001/jamaneurol.2023.3599 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r13] 13.Blennow K, Hampel H, Weiner M, Zetterberg H. Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol. 2010;6(3):131-144. doi: 10.1038/nrneurol.2010.4 [DOI] [PubMed] [Google Scholar]

[zoi250047r14] 14.Shaw LM, Vanderstichele H, Knapik-Czajka M, et al. ; Alzheimer’s Disease Neuroimaging Initiative . Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol. 2009;65(4):403-413. doi: 10.1002/ana.21610 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r15] 15.Visser PJ, Verhey F, Knol DL, et al. Prevalence and prognostic value of CSF markers of Alzheimer’s disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the DESCRIPA study: a prospective cohort study. Lancet Neurol. 2009;8(7):619-627. doi: 10.1016/S1474-4422(09)70139-5 [DOI] [PubMed] [Google Scholar]

[zoi250047r16] 16.Welge V, Fiege O, Lewczuk P, et al. Combined CSF tau, p-tau181 and amyloid-beta 38/40/42 for diagnosing Alzheimer’s disease. J Neural Transm (Vienna). 2009;116(2):203-212. doi: 10.1007/s00702-008-0177-6 [DOI] [PubMed] [Google Scholar]

[zoi250047r17] 17.Blennow K. CSF biomarkers for mild cognitive impairment. J Intern Med. 2004;256(3):224-234. doi: 10.1111/j.1365-2796.2004.01368.x [DOI] [PubMed] [Google Scholar]

[zoi250047r18] 18.Blennow K. CSF biomarkers for Alzheimer’s disease: use in early diagnosis and evaluation of drug treatment. Expert Rev Mol Diagn. 2005;5(5):661-672. doi: 10.1586/14737159.5.5.661 [DOI] [PubMed] [Google Scholar]

[zoi250047r19] 19.Marksteiner J, Hinterhuber H, Humpel C. Cerebrospinal fluid biomarkers for diagnosis of Alzheimer’s disease: beta-amyloid(1-42), tau, phospho-tau-181 and total protein. Drugs Today (Barc). 2007;43(6):423-431. doi: 10.1358/dot.2007.43.6.1067341 [DOI] [PubMed] [Google Scholar]

[zoi250047r20] 20.Mattsson N, Zetterberg H, Hansson O, et al. CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA. 2009;302(4):385-393. doi: 10.1001/jama.2009.1064 [DOI] [PubMed] [Google Scholar]

[zoi250047r21] 21.Young CB, Johns E, Kennedy G, et al. ; Alzheimer’s Disease Neuroimaging Initiative; A4 Study Team . APOE effects on regional tau in preclinical Alzheimer’s disease. Mol Neurodegener. 2023;18(1):1. doi: 10.1186/s13024-022-00590-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r22] 22.Hohman TJ, Dumitrescu L, Barnes LL, et al. ; Alzheimer’s Disease Genetics Consortium and the Alzheimer’s Disease Neuroimaging Initiative . Sex-specific association of apolipoprotein E with cerebrospinal fluid levels of tau. JAMA Neurol. 2018;75(8):989-998. doi: 10.1001/jamaneurol.2018.0821 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r23] 23.Altmann A, Tian L, Henderson VW, Greicius MD; Alzheimer’s Disease Neuroimaging Initiative Investigators . Sex modifies the APOE-related risk of developing Alzheimer disease. Ann Neurol. 2014;75(4):563-573. doi: 10.1002/ana.24135 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r24] 24.Garatachea N, Emanuele E, Calero M, et al. ApoE gene and exceptional longevity: insights from three independent cohorts. Exp Gerontol. 2014;53:16-23. doi: 10.1016/j.exger.2014.02.004 [DOI] [PubMed] [Google Scholar]

[zoi250047r25] 25.Deters K, Napolioni V, Greicius M, Mormino B. African ancestry moderates the effect of ApoE4 on cognitive decline. Alzheimer’s & Dementia. 2018;14:P1027-P1028. doi: 10.1212/WNL.0000000000011599 [DOI] [Google Scholar]

[zoi250047r26] 26.Howell JC, Watts KD, Parker MW, et al. Race modifies the relationship between cognition and Alzheimer’s disease cerebrospinal fluid biomarkers. Alzheimers Res Ther. 2017;9(1):88. doi: 10.1186/s13195-017-0315-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r27] 27.Morris JC, Schindler SE, McCue LM, et al. Assessment of racial disparities in biomarkers for Alzheimer disease. JAMA Neurol. 2019;76(3):264-273. doi: 10.1001/jamaneurol.2018.4249 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r28] 28.Swaminathan S, Shen L, Risacher SL, et al. ; Alzheimer’s Disease Neuroimaging Initiative . Amyloid pathway-based candidate gene analysis of [(11)C]PiB-PET in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Brain Imaging Behav. 2012;6(1):1-15. doi: 10.1007/s11682-011-9136-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r29] 29.Ellis KA, Bush AI, Darby D, et al. ; AIBL Research Group . The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer’s disease. Int Psychogeriatr. 2009;21(4):672-687. doi: 10.1017/S1041610209009405 [DOI] [PubMed] [Google Scholar]

[zoi250047r30] 30.Fowler C, Rainey-Smith SR, Bird S, et al. ; the AIBL investigators . Fifteen years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study: progress and observations from 2,359 older adults spanning the spectrum from cognitive normality to Alzheimer’s disease. J Alzheimers Dis Rep. 2021;5(1):443-468. doi: 10.3233/ADR-210005 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r31] 31.Albert M, Soldan A, Gottesman R, et al. Cognitive changes preceding clinical symptom onset of mild cognitive impairment and relationship to ApoE genotype. Curr Alzheimer Res. 2014;11(8):773-784. doi: 10.2174/156720501108140910121920 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r32] 32.Álvarez I, Diez-Fairen M, Aguilar M, et al. Added value of cerebrospinal fluid multimarker analysis in diagnosis and progression of dementia. Eur J Neurol. 2021;28(4):1142-1152. doi: 10.1111/ene.14658 [DOI] [PubMed] [Google Scholar]

[zoi250047r33] 33.de Rojas I, Moreno-Grau S, Tesi N, et al. ; EADB contributors; GR@ACE study group; DEGESCO consortium; IGAP (ADGC, CHARGE, EADI, GERAD); PGC-ALZ consortia . Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores. Nat Commun. 2021;12(1):3417. doi: 10.1038/s41467-021-22491-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r34] 34.Riemenschneider M, Wagenpfeil S, Diehl J, et al. Tau and Aβ42 protein in CSF of patients with frontotemporal degeneration. Neurology. 2002;58(11):1622-1628. doi: 10.1212/WNL.58.11.1622 [DOI] [PubMed] [Google Scholar]

[zoi250047r35] 35.Deming Y, Filipello F, Cignarella F, et al. The MS4A gene cluster is a key modulator of soluble TREM2 and Alzheimer’s disease risk. Sci Transl Med. 2019;11(505):eaau2291. doi: 10.1126/scitranslmed.aau2291 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r36] 36.Voyle N, Patel H, Folarin A, et al. ; EDAR and DESCRIPA study groups and the Alzheimer’s Disease Neuroimaging Initiative . Genetic risk as a marker of amyloid-β and tau burden in cerebrospinal fluid. J Alzheimers Dis. 2017;55(4):1417-1427. doi: 10.3233/JAD-160707 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r37] 37.Visser PJ, Verhey FR, Boada M, et al. Development of screening guidelines and clinical criteria for predementia Alzheimer’s disease: the DESCRIPA study. Neuroepidemiology. 2008;30(4):254-265. doi: 10.1159/000135644 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r38] 38.MacDonald SWS, Thorvaldsson V, Johansson B, Bäckman L. O3-02-02: identifying factors that moderate the onset and rate of prodromal cognitive impairment in dementia. Alzheimers Dement. 2010;6(4 suppl):S127-S127. doi: 10.1016/j.jalz.2010.05.398 [DOI] [Google Scholar]

[zoi250047r39] 39.Deming Y, Li Z, Kapoor M, et al. ; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer Disease Genetic Consortium (ADGC) . Genome-wide association study identifies four novel loci associated with Alzheimer’s endophenotypes and disease modifiers. Acta Neuropathol. 2017;133(5):839-856. doi: 10.1007/s00401-017-1685-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r40] 40.Morris JC, Roe CM, Xiong C, et al. APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol. 2010;67(1):122-131. doi: 10.1002/ana.21843 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r41] 41.Ramanan VK, Wang X, Przybelski SA, et al. Variants in PPP2R2B and IGF2BP3 are associated with higher tau deposition. Brain Commun. 2020;2(2):fcaa159. doi: 10.1093/braincomms/fcaa159 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r42] 42.Beekly DL, Ramos EM, Lee WW, et al. ; NIA Alzheimer’s Disease Centers . The National Alzheimer’s Coordinating Center (NACC) database: the Uniform Data Set. Alzheimer Dis Assoc Disord. 2007;21(3):249-258. doi: 10.1097/WAD.0b013e318142774e [DOI] [PubMed] [Google Scholar]

[zoi250047r43] 43.Deming Y, Dumitrescu L, Barnes LL, et al. ; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer Disease Genetics Consortium (ADGC) . Sex-specific genetic predictors of Alzheimer’s disease biomarkers. Acta Neuropathol. 2018;136(6):857-872. doi: 10.1007/s00401-018-1881-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r44] 44.Al-Hakim AK, Zagorska A, Chapman L, Deak M, Peggie M, Alessi DR. Control of AMPK-related kinases by USP9X and atypical Lys(29)/Lys(33)-linked polyubiquitin chains. Biochem J. 2008;411(2):249-260. doi: 10.1042/BJ20080067 [DOI] [PubMed] [Google Scholar]

[zoi250047r45] 45.Jefferson AL, Gifford KA, Acosta LM, et al. The Vanderbilt Memory & Aging Project: study design and baseline cohort overview. J Alzheimers Dis. 2016;52(2):539-559. doi: 10.3233/JAD-150914 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r46] 46.Berman SE, Koscik RL, Clark LR, et al. Use of the Quick Dementia Rating System (QDRS) as an initial screening measure in a longitudinal cohort at risk for Alzheimer’s disease. J Alzheimers Dis Rep. 2017;1(1):9-13. doi: 10.3233/ADR-170004 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r47] 47.Timsina J, Ali M, Do A, et al. Harmonization of CSF and imaging biomarkers in Alzheimer’s disease: need and practical applications for genetics studies and preclinical classification. Neurobiol Dis. 2024;190:106373. doi: 10.1016/j.nbd.2023.106373 [DOI] [PubMed] [Google Scholar]

[zoi250047r48] 48.Sjögren M, Vanderstichele H, Agren H, et al. Tau and Aβ42 in cerebrospinal fluid from healthy adults 21-93 years of age: establishment of reference values. Clin Chem. 2001;47(10):1776-1781. doi: 10.1093/clinchem/47.10.1776 [DOI] [PubMed] [Google Scholar]

[zoi250047r49] 49.Popp J, Lewczuk P, Frommann I, et al. Cerebrospinal fluid markers for Alzheimer’s disease over the lifespan: effects of age and the APOEε4 genotype. J Alzheimers Dis. 2010;22(2):459-468. doi: 10.3233/JAD-2010-100561 [DOI] [PubMed] [Google Scholar]

[zoi250047r50] 50.Cochran WG. The comparison of percentages in matched samples. Biometrika. 1950;37(3-4):256-266. doi: 10.1093/biomet/37.3-4.256 [DOI] [PubMed] [Google Scholar]

[zoi250047r51] 51.Balduzzi S, Rücker G, Schwarzer G. How to perform a meta-analysis with R: a practical tutorial. Evid Based Ment Health. 2019;22(4):153-160. doi: 10.1136/ebmental-2019-300117 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r52] 52.Viechtbauer W. Conducting meta-analyses in R with the metafor Package. J Stat Software. 2010;36(3):1-48. doi: 10.18637/jss.v036.i03 [DOI] [Google Scholar]

[zoi250047r53] 53.Saunders TS, Jenkins N, Blennow K, Ritchie C, Muniz-Terrera G. Interactions between apolipoprotein E, sex, and amyloid-beta on cerebrospinal fluid p-tau levels in the European prevention of Alzheimer’s dementia longitudinal cohort study (EPAD LCS). EBioMedicine. 2022;83:104241. doi: 10.1016/j.ebiom.2022.104241 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r54] 54.Yan S, Zheng C, Paranjpe MD, et al. Sex modifies APOE ε4 dose effect on brain tau deposition in cognitively impaired individuals. Brain. 2021;144(10):3201-3211. doi: 10.1093/brain/awab160 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r55] 55.Wang YT, Pascoal TA, Therriault J, et al. ; Alzheimer’s Disease Neuroimaging Initiative . Interactive rather than independent effect of APOE and sex potentiates tau deposition in women. Brain Commun. 2021;3(2):fcab126. doi: 10.1093/braincomms/fcab126 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r56] 56.Liu M, Paranjpe MD, Zhou X, et al. Sex modulates the ApoE ε4 effect on brain tau deposition measured by ¹⁸F-AV-1451 PET in individuals with mild cognitive impairment. Theranostics. 2019;9(17):4959-4970. doi: 10.7150/thno.35366 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r57] 57.Qin W, Li W, Wang Q, et al. Race-related association between APOE genotype and Alzheimer’s disease: a systematic review and meta-analysis. J Alzheimers Dis. 2021;83(2):897-906. doi: 10.3233/JAD-210549 [DOI] [PubMed] [Google Scholar]

[zoi250047r58] 58.Naslavsky MS, Suemoto CK, Brito LA, et al. Global and local ancestry modulate APOE association with Alzheimer’s neuropathology and cognitive outcomes in an admixed sample. Mol Psychiatry. 2022;27(11):4800-4808. doi: 10.1038/s41380-022-01729-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r59] 59.Royse SK, Snitz BE, Hill AV, et al. Apolipoprotein E and Alzheimer’s disease pathology in African American older adults. Neurobiol Aging. 2024;139:11-19. doi: 10.1016/j.neurobiolaging.2024.03.005 [DOI] [PubMed] [Google Scholar]

[zoi250047r60] 60.Deters KD, Napolioni V, Sperling RA, et al. Amyloid PET imaging in self-identified non-Hispanic Black participants of the Anti-Amyloid in Asymptomatic Alzheimer’s Disease (A4) Study. Neurology. 2021;96(11):e1491-e1500. doi: 10.1212/WNL.0000000000011599 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r61] 61.Hajjar I, Yang Z, Okafor M, et al. Association of plasma and cerebrospinal fluid Alzheimer disease biomarkers with race and the role of genetic ancestry, vascular comorbidities, and neighborhood factors. JAMA Netw Open. 2022;5(10):e2235068. doi: 10.1001/jamanetworkopen.2022.35068 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r62] 62.Wood ME, Xiong LY, Wong YY, et al. ; ADNI and Prevent-AD Research Groups . Sex differences in associations between APOE ε2 and longitudinal cognitive decline. Alzheimers Dement. 2023;19(10):4651-4661. doi: 10.1002/alz.13036 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r63] 63.Nichols E, Brickman AM, Casaletto KB, et al. AD and non-AD mediators of the pathway between the APOE genotype and cognition. Alzheimers Dement. 2023;19(6):2508-2519. doi: 10.1002/alz.12885 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r64] 64.Walters S, Contreras AG, Eissman JM, et al. ; Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Genetics Consortium, and Alzheimer’s Disease Sequencing Project . Associations of sex, race, and apolipoprotein E alleles with multiple domains of cognition among older adults. JAMA Neurol. 2023;80(9):929-939. doi: 10.1001/jamaneurol.2023.2169 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r65] 65.Neu SC, Pa J, Kukull W, et al. Apolipoprotein E genotype and sex risk factors for Alzheimer disease: a meta-analysis. JAMA Neurol. 2017;74(10):1178-1189. doi: 10.1001/jamaneurol.2017.2188 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r66] 66.Alvarez-de-la-Rosa M, Silva I, Nilsen J, et al. Estradiol prevents neural tau hyperphosphorylation characteristic of Alzheimer’s disease. Ann N Y Acad Sci. 2005;1052:210-224. doi: 10.1196/annals.1347.016 [DOI] [PubMed] [Google Scholar]

[zoi250047r67] 67.Xu H, Gouras GK, Greenfield JP, et al. Estrogen reduces neuronal generation of Alzheimer β-amyloid peptides. Nat Med. 1998;4(4):447-451. doi: 10.1038/nm0498-447 [DOI] [PubMed] [Google Scholar]

[zoi250047r68] 68.Corbo RM, Gambina G, Ruggeri M, Scacchi R. Association of estrogen receptor α (ESR1) Pvu II and Xba I polymorphisms with sporadic Alzheimer’s disease and their effect on apolipoprotein E concentrations. Dement Geriatr Cogn Disord. 2006;22(1):67-72. doi: 10.1159/000093315 [DOI] [PubMed] [Google Scholar]

[zoi250047r69] 69.Sundermann EE, Panizzon MS, Chen X, Andrews M, Galasko D, Banks SJ; Alzheimer’s Disease Neuroimaging Initiative . Sex differences in Alzheimer’s-related Tau biomarkers and a mediating effect of testosterone. Biol Sex Differ. 2020;11(1):33. doi: 10.1186/s13293-020-00310-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi250047r70] 70.Belloy ME, Le Guen Y, Stewart I, et al. Role of the X chromosome in Alzheimer disease genetics. JAMA Neurol. 2024;81(10):1032-1042. doi: 10.1001/jamaneurol.2024.2843 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Sex Differences in Apolipoprotein E and Alzheimer Disease Pathology Across Ancestries

Xiaoyi Xu, MS

Jiseon Kwon, MS

Ruiqi Yan, MS

Catherine Apio, MS

Soomin Song, MS

Gyujin Heo, MS

Qijun Yang, MS

Jigyasha Timsina, MS

Menghan Liu, MS

John Budde, BS

Kaj Blennow, MD, PhD

Henrik Zetterberg, MD, PhD

Alberto Lleó, MD, PhD

Agustin Ruiz, PhD

José Luis Molinuevo, MD

Virginia Man-Yee Lee, PhD

Yuetiva Deming, PhD

Amanda J Heslegrave, PhD

Tim J Hohman, PhD

Pau Pastor, MD, PhD

Elaine R Peskind, MD

Marilyn S Albert, PhD

John C Morris, MD

Taesung Park, PhD

Carlos Cruchaga, PhD

Yun Ju Sung, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposure

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Participants

Ancestry Classification

CSF Biomarkers

APOE Genotyping

Statistical Analysis

Results

Participant Characteristics

Table 1. Participant Characteristics.

Sex Differences in CSF Biomarker Levels

Association of APOE-ε4 With CSF Biomarker Levels

Table 2. APOE-ε4 Effect Within and Across Ancestrya.

Sex-Specific APOE-ε4 Association

Figure. Sex-Specific APOE-ε4 Associations With Cerebrospinal Fluid Biomarkers in Individuals of European and African Ancestry.

Sensitivity Analysis

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 2. APOE-ε4 Effect Within and Across Ancestry^a.