GWAS; chronic back pain; low back pain; polygenic risk score; Medicine (miscellaneous)
Abstract :
[en] Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.56 and OR = 1.24 per SD, 95% CI: 1.22-1.26), but individuals from the 99th percentile of PRS distribution had a nearly two-fold increased risk of CBP (OR = 1.82, 95% CI: 1.60-2.06). We validated the PRS on an independent TwinsUK sample, obtaining a similar magnitude of effect. The PRS was significantly associated with various ICD-10 and OPCS-4 diagnostic codes, including chronic ischemic heart disease (OR = 1.1, p-value = 4.8 × 10-15), obesity, metabolism-related traits, spine disorders, disc degeneration, and arthritis-related disorders. PRS and environment interaction analysis with twelve known CBP risk factors revealed no significant results, suggesting that the magnitude of G × E interactions with studied factors is small. The limited predictive ability of the PRS that we developed is likely explained by the complexity, heterogeneity, and polygenicity of CBP, for which sample sizes of a few hundred thousand are insufficient to estimate small genetic effects robustly.
Disciplines :
Genetics & genetic processes
Author, co-author :
Tsepilov, Yakov A ; Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk 630090, Russia ; Kurchatov Genomics Center, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
Elgaeva, Elizaveta E ; Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk 630090, Russia ; Department of Natural Sciences, Novosibirsk State University, Novosibirsk 630090, Russia
Nostaeva, Arina ; Université de Liège - ULiège > Département de gestion vétérinaire des Ressources Animales (DRA) > Génomique animale ; Department of Natural Sciences, Novosibirsk State University, Novosibirsk 630090, Russia
Compte, Roger; Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London SE1 7EH, UK
Kuznetsov, Ivan A ; Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
Karssen, Lennart C ; PolyOmica, 5237 PA s-Hertogenbosch, The Netherlands
Freidin, Maxim B ; Department of Biology, School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK
Suri, Pradeep; Division of Rehabilitation Care Services, VA Puget Sound Health Care System, Seattle, WA 98208, USA ; Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, WA 98208, USA ; Department of Rehabilitation Medicine, University of Washington, Seattle, WA 98208, USA ; Clinical Learning, Evidence, and Research (CLEAR) Center, University of Washington, Seattle, WA 98208, USA
Williams, Frances M K ; Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London SE1 7EH, UK
Aulchenko, Yurii S; Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk 630090, Russia ; PolyOmica, 5237 PA s-Hertogenbosch, The Netherlands
Language :
English
Title :
Development and Replication of a Genome-Wide Polygenic Risk Score for Chronic Back Pain.
Versus Arthritis RSF - Russian Science Foundation UW - University of Washington
Funding text :
The work of R.C. has been supported by funding from Versus Arthritis (Grant Number 22467) and Marie Skłodowska Curie International Training Network (ITN) “disc4all” (H2020-MSCA-ITN-ETN-2020 GA: 9557). Tsepilov and Elgaeva were supported by the Russian Science Foundation (RSF) grant No. 22-15-20037 and Government of the Novosibirsk region. Suri is an employee of the VA Puget Sound Health Care System and is Director of the University of Washington Clinical Learning, Ev-idence and Research (CLEAR) Center Resource Core, which is funded by NIAMS/NIH P30AR072572. The contents of this work do not represent the views of the US Department of Veterans Affairs, the National Institutes of Health, or the US Government. The data analysis was performed using computational resources of the “Bioinformatics” Joint Computational Center supported by the budget project No. FWNR-2022-0020.
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