Integrating rare pathogenic variant prioritization with gene-based association analysis to identify novel genes and relevant multimodal traits for Alzheimer's disease

Introduction: Increasing evidence has highlighted rare variants in Alzheimer's disease (AD). However, insufficient sample sizes, especially in underrepresented ethnic groups, hinder their investigation. Additionally, their impact on endophenotypes remains largely unexplored.

Methods: We prioritized rare likely-deleterious variants based on whole-genome sequencing data from a Chinese AD cohort (n = 988). Gene-based optimal sequence kernel association tests were conducted between AD cases and normal controls to identify AD-related genes. Network clustering, endophenotype association, and cellular experiments were conducted to evaluate their functional consequences.

Results: We identified 11 novel AD candidate genes, which captured AD-related pathways and enhanced AD risk prediction performance. Key genes (RABEP1, VIPR1, RPL3L, and CABIN1) were linked to cognitive decline and brain atrophy. Experiments showed RABEP1 p.R845W inducing endocytosis dysregulation and exacerbating toxic amyloid β accumulation, underscoring its therapeutic potential.

Discussion: Our findings highlighted the contributions of rare variants to AD and provided novel insights into AD therapeutics.

Highlights: Identified 11 novel AD candidate genes in a Chinese AD cohort. Correlated candidate genes with AD-related cognitive and brain imaging traits. Indicated RABEP1 p.R845W as a critical AD contributor in the endocytic pathway.