Identification of novel genetic variants and biomarkers for cognitive decline in Alzheimer’s disease

Abstract

AbstractBackgroundAlzheimer’s disease (AD) is a complex, multifactorial disease that is incurable in the aging population. The success of genome‐wide association studies (GWAS), as a cross sectional design, to identify novel genetic risk factors for AD in recent years is well known; however, case‐control studies are less likely to uncover genetic factors that influence other aspects of the disease, such as progression and onset.MethodIn order to identify common and rare genetic variants associated with rates of cognitive decline in AD, we aim at systematically analyzing the largest collection of longitudinal and GWAS data (N = 7,241), across non‐Hispanic white individuals from multicenter cohorts (Knight‐ADRC, ADNI, NACC, and GSK) with at least 1.5 years of follow up after being diagnosed with AD. We also aim at exploring if genetic risk factors, alone or interacting with other genetic factors, are associated rate of cognitive decline in patients with AD when aggregated together into a single Polygenic Risk Score (PRS). Furthermore, external proteomics data will be combined with the genetics data for Mendelian Randomization (MR) analyses in order to discover causal biomarkers for cognitive decline and AD risk.ResultPreliminary results found a suggestive signal in chr21 (min P = 8.7e‐8) approaching close to the genome‐wide significance threshold. Moreover, some other suggestive signals were detected in chr2 (min P = 3.8e‐06) and chr1 (min P = 3.7e‐06) that warrant further investigation. Further results and key findings of the post‐GWAS analyses will be presented during the AAIC meeting.ConclusionWe have leveraged these datasets to generate prediction models for rate of cognitive decline in AD. The identification of AD‐specific genetic variants and biomarkers will enable the characterization of appropriate therapeutic targets for slowing or halting the AD progression.