Examination of Genetic Risk Factors for Alzheimer’s Disease in a Cohort of Familial Longevity: the Long Life Family Study

Abstract

AbstractBackgroundGenetic risk factors have been explored extensively for late onset Alzheimer’s Disease (LOAD). The largest meta‐analysis GWAS studies to date (Bellenguez et al., 2022) identified 83 single nucleotide polymorphisms (SNPs) associated with LOAD in the general population. The Long Life Family Study (LLFS) is aimed to identify factors associated with familial longevity and healthy aging by examining US and Danish families. Our earlier studies have shown that LLFS families are at lower risk of several age‐related diseases, including LOAD. Here, we will: (1) compare allele frequencies and effect sizes of the identified meta‐GWAS variants against those in LLFS; and (2) assess whether a polygenic risk score (PRS) based on meta‐GWAS variants differs between LOAD vs. cognitively healthy in LLFS.MethodWe examined LLFS participants who were Non‐Hispanic Whites, had available cognitive and whole genome sequencing (WGS) (n = 4,220). Allele frequencies were estimated based on founders only. Association analyses were performed via logistic regression using Wald test and adjusting for sex, age, site, education, first principal components, and the genetic relationship matrix. PRS was calculated using a weighted formula, and to account for family structure, means for each status per family were obtained.ResultIndependent of LOAD status, 13 SNPs had significantly different allele frequencies between the two studies. Minor allele frequencies of 10 of the SNPs were lower in LLFS when compared with Bellenguez et al. When examining the relations between LOAD and the 77 available SNPs, only five variants appeared to be associated in LLFS. The direction of association differed for two of the SNPs. Lastly, estimated PRS scores did not differ by LOAD status (affected vs unaffected: ‐0.059 vs. ‐0.054, respectively).ConclusionHere we show that variants associated with LOAD in the general population were not necessarily associated with LOAD in in the LLFS cohort, a cohort ascertained for familial healthy aging. When estimating disease risk using genetic markers, as expected, ascertainment needs to be taken into consideration.