Polygenic risk score for disability and insights into disability-related molecular mechanisms.

Published

Journal Article

Late life disability is a highly devastating condition affecting 20% or more of persons aged 65 years and older in the USA; it is an important determinant of acute medical and long-term care costs which represent a growing burden on national economies. Disability is a multifactorial trait that contributes substantially to decline of health/wellbeing. Accordingly, gaining insights into the genetics of disability could help in identifying molecular mechanisms of this devastating condition and age-related processes contributing to a large fraction of specific geriatric conditions, concordantly with geroscience. We performed a genome-wide association study of disability in a sample of 24,068 subjects from five studies with 12,550 disabled individuals. We identified 30 promising disability-associated polymorphisms in 19 loci at p < 10-4; four of them attained suggestive significance, p < 10-5. In contrast, polygenic risk scores aggregating effects of minor alleles of independent SNPs that were adversely or beneficially associated with disability showed highly significant associations in meta-analysis, p = 3.13 × 10-45 and p = 5.60 × 10-23, respectively, and were replicated in each study. The analysis of genetic pathways, related diseases, and biological functions supported the connections of genes for the identified SNPs with disabling and age-related conditions primarily through oxidative/nitrosative stress, inflammatory response, and ciliary signaling. We identified musculoskeletal system development, maintenance, and regeneration as important components of gene functions. The beneficial and adverse gene sets may be differently implicated in the development of musculoskeletal-related disability with the beneficial set characterized, e.g., by regulation of chondrocyte proliferation and bone formation, and the adverse set by inflammation and bone loss.

Full Text

Duke Authors

Cited Authors

  • Kulminski, AM; Kang, C; Kolpakov, SA; Loika, Y; Nazarian, A; Yashin, AI; Stallard, E; Culminskaya, I

Published Date

  • December 2019

Published In

Volume / Issue

  • 41 / 6

Start / End Page

  • 881 - 893

PubMed ID

  • 31707593

Pubmed Central ID

  • 31707593

Electronic International Standard Serial Number (EISSN)

  • 2509-2723

International Standard Serial Number (ISSN)

  • 2509-2715

Digital Object Identifier (DOI)

  • 10.1007/s11357-019-00125-8

Language

  • eng