Genetic risk shared across 24 chronic pain conditions: identification and characterization with genomic structural equation modeling.

ABSTRACT:

Abstract

Chronic pain conditions frequently co-occur, suggesting common risks and paths to prevention and treatment. Previous studies have reported genetic correlations among specific groups of pain conditions and reported genetic risk for within-individual multisite pain counts (≤7). Here, we identified genetic risk for multiple distinct pain disorders across individuals using 24 chronic pain conditions and genomic structural equation modeling (Genomic SEM). First, we ran individual genome-wide association studies (GWASs) on all 24 conditions in the UK Biobank ( N ≤ 436,000) and estimated their pairwise genetic correlations. Then we used these correlations to model their genetic factor structure in Genomic SEM, using both hypothesis- and data-driven exploratory approaches. A compl

SUBMITTER: Zorina-Lichtenwalter K 

PROVIDER: S-EPMC10524350 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature