System-Level Analysis of Alzheimer’s Disease Prioritizes Candidate Genes for Neurodegeneration - Brabec, Jeffrey L.; Lara, Montana Kay; Tyler, Anna L.; Mahoney, J. Matthew (Frontiers in Genetics, 2021)
Alzheimer’s Disease (AD) is a debilitating neurodegenerative disorder that affects memory and emotional regulation through the atrophy of neural tissues that support these functions. In particular, hippocampal and amygdalar volume are dramatically lower in patients with AD compared to age-matched controls. However, there is significant heterogeneity across patients about how strongly affected these brain regions are by AD, suggesting that risk for atrophy is a genetically complex trait. To identify candidate genes for hippocampal and amygdalar atrophy, we developed a novel strategy to integrate gene associations from two genome-wide association studies: a large case-control meta-GWAS and a comparatively small imaging GWAS that directly measured hippocampal volume (HV) and amygdalar volume (AV). Using meta-GWAS gene associations, we trained machine learning classifiers to rank all genes in the genome by their functional connectivity to AD-associated genes in hippocampus- and amygdala-specific gene networks. Using imaging GWAS, we ranked genes by their statistical association to low HV and AV. We then integrated functional association to AD with genetic association to low HV or AV into a combined score for a specific association to AD-induced neural atrophy. High ranking genes by our method included a combination of genes that have previously been associated to AD through GWAS, including APOE, TOMM40, and NECTIN2, along with potentially novel genetic associations, including IQSEC1, PFN1, HDAC3, and PAK2. Our top-ranking genes are highly enriched for AD-associated processes that broadly implicate a loss of synaptic integrity and excitotoxicity as major components of the genetic risk for hippocampal and amygdalar atrophy in AD.