Cross‐Ancestry Meta‐Analysis of APOE‐ε4 Stratified GWAS of Longitudinal Cognitive Decline in Older Adults
Authors: Contreras Alex G. , Walters Skylar , Eissman Jaclyn M. , Archer Derek B. , Regelson Alexandra N. , Durant Alaina , Mukherjee Shubhabrata , Lee Michael L. , Choi Seo‐Eun , Scollard Phoebe , Trittschuh Emily H. , Mez Jesse , Bush William S. , Kunkle Brian W. , Naj Adam C. , Gifford Katherine A. , Bilgel Murat , Kuzma Amanda B , Cuccaro Michael L. , Cruchaga Carlos , Pericak‐Vance Margaret A , Farrer Lindsay A. , Wang Li‐San , Schellenberg Gerard D. , Mayeux Richard , Haines Jonathan L. , Jefferson Angela L. , Kukull Walter A. , Keene C. Dirk , Saykin Andrew J. , Thompson Paul M. , Martin Eden R. , Albert Marilyn S. , Johnson Sterling C. , Engelman Corinne D. , Ferrucci Luigi , Bennett David A. , Barnes Lisa L. , Schneider Julie A. , Resnick Susan M. , Sperling Reisa A , Crane Paul K. , Dumitrescu Logan C. , Hohman Timothy J. 
Published: January 2025

Background

The Apolipoprotein E ε4 (APOE‐ε4) allele is common in the population, but acts as the strongest genetic risk factor for late‐onset Alzheimer’s disease (AD). Despite the strength of the association, there is notable heterogeneity in the population including a strong modifying effect of genetic ancestry, with the APOE‐ε4 allele showing a stronger association among individuals of European ancestry (EUR) compared to individuals of African ancestry (AFR). Given this heterogeneity, we sought to identify genetic modifiers of APOE‐ε4 related to cognitive decline leveraging APOE‐ε4 stratified and interaction genome‐wide association analyses (GWAS).

Method

We leveraged a comprehensive harmonized cognitive dataset from nine well‐characterized aging and AD cohorts, representing African and European ancestries (total of 32,751 individuals, including 10,969 EUR ε4 carriers, 18,385 EUR non‐carriers, 1,495 AFR ε4 carriers, and 1,902 AFR non‐carriers). We then conducted APOE stratified and interaction GWAS and post GWAS analyses on longitudinal composite measures of memory, executive function, and language. To capture longitudinal cognitive trajectories, linear mixed effects models were employed, focusing on the rate of cognitive decline over time. Post GWAS analysis included eQTL analysis, gene‐set/pathway‐set analysis, and an assessment of genetic correlations.

Result

We identified novel loci for baseline executive function performance including two that are specific to APOE‐ε4 carriers (rs28609108 on chromosome 9 and rs2959641 on chromosome 15) and one that is specific to non‐carriers (rs73072750 on chromosome 7). The effect sizes of these three loci remained consistent when subset by ancestry, achieving statistical significance in EUR, and nominal significance in AFR. Post GWAS eQTL analyses implicate the glutamate receptor subunit gene (GRIN3A) among APOE‐ε4 carriers, while the integrin gene (ITGB8). Additionally, both GRIN3A and ITGB8 have been previously implicated in AD/cognition GWAS, underscoring their relevance in the context of APOE‐ε4.

Conclusion

Our study has shed light on several novel genetic factors that relate to late‐life cognitive performance in an APOE‐specific manner. These findings enrich our understanding of the genetic landscape influencing cognitive decline. Further research is imperative to unravel how these genetic variations affect biological processes and the potential in guiding therapeutic strategies.