Charting the genetic architecture of Alzheimer’s disease across APOE*4 and sex

Abstract

AbstractBackgroundAPOE*4 status and sex (and their interaction) are among the strongest risk factors for late‐onset Alzheimer’s disease (AD). We thus sought to perform large‐scale, stratified genome‐wide association study (GWAS) of AD to chart the role of common genetic variation in AD sexual dimorphism and heterogeneity of APOE*4‐related AD risk.MethodThe study overview and GWAS models are shown in Figure.1A. SNP‐array AD GWAS datasets primarily composing the ADGC, together with whole‐genome sequencing (WGS) from ADSP (NG00067.v7), provided case‐control diagnoses for phase‐1. The UK Biobank provided subjects with ICD codes and family history of AD status for phase‐2. Subjects were of European ancestry. Linear mixed model regressions were performed (LMM‐BOLT v.2.3.4) on AD outcome measures, adjusting for sex, APOE*4/APOE*2 dosage, genetic principal components, and array/batch/center. GWAS hits (P<5e‐*8) were evaluated for interactions effects (meta‐regression for phase1+2 meta‐analyses) and assessed in functional follow‐up analyses. The effect of stratification on genetic risk scores (GRS) predictive performance on AD risk was also evaluated.ResultStratified AD GWAS identified 28 loci/variants, including 5 known lead variants in known AD loci, 6 novel independent variants in known AD loci, and 17 novel loci (Figure.1B). 13 out of 17 novel loci showed varying degrees of functional support, with 4 also showing evidence for QTL colocalization (Figure.2). Many implicated genes showed prior support or effects relevant to AD: MARCHF10 was recently implicated as a risk gene for all‐cause dementia; EMP2 is a regulator of cell membrane composition, cell‐matrix adhesion, and blood vessel endothelial cell migration; SLIT2 binds APP, and EYA4 and TBC1D9 have respectively been implicated in brain tau deposition and MAPT haplotype‐stratified GWAS. Nonetheless, most novel hits were low/uncommon frequency variants and QTL colocalization evidence was limited. Further, there appeared to be no predictive benefit for stratified GRS analyses (Figure.3).ConclusionWe identified novel loci/variants differentially associated with AD risk across APOE*4 and/or sex. Yet, we inferred relatively limited evidence for stratified effects (propensity for low frequency hits and no benefit for stratified GRS). Overall, our findings contribute to our understanding of the genetic etiology of AD, which in turn contributes to advance personalized genetic medicine.