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Updated: Sep 10, 2025

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
Genome-wide Cox regression analysis identifies 134 novel risk loci for disability development: the Canadian
Huiping Zheng1, Tao Sun2,3, Xiaojun Wang2,3
1School of Statistics, Renmin University of China, Beijing, China.
Background:
Disability significantly affects the well-being of older adults and imposes substantial personal and social burdens. Although genetic effects play a role in disability, large-scale genome-wide association studies (GWAS) of disability development remain scarce.
Methods:
We performed the first Cox proportional hazards GWAS on disability development on 8421 individuals aged more than 65 years from the Canadian Longitudinal Study on Aging (CLSA). Disability was defined as the inability to perform daily activities, as measured by the activities of daily living (ADL) scale. A polygenic hazard score (PHS) was developed and incorporated into the predictive model, along with demographic and environmental factors.
Results:
The study observed a 16.28% incidence of disability over a mean follow-up duration of 4.64 years (SD = 1.95). The Cox-GWAS identified six genome-wide significant variants (P < 5E-08) and 134 independent single nucleotide polymorphisms (SNPs) with suggestive significance level (P < 1E - 05). Replication in the UK Biobank (UKB) confirmed that rs589819, rs56294014, and rs143714258 remained nominally significant and exhibited consistent effect directions. Post-GWAS analyses, including transcriptome-wide association studies TWAS, gene set, and tissue--enrichment analyses, revealed genetic pathways related to inflammation regulation, neurogenesis, and metabolic processes. Incorporating PHS with demographic and environmental factors improves the prediction performance in both CLSA and UKB.
Conclusion:
This study is among the first genome-wide Cox regression analyses to uncover novel genetic loci and biological pathways involved in disability development in older adults. These findings provide a foundation for predictive modeling and targeted prevention strategies.
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