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Identification and characterization of genetic risk shared across 24 chronic pain conditions in the UK Biobank.

TLDR
A general factor explaining most of the shared genetic variance in all conditions and an additional musculoskeletal pain-selective factor are revealed, which identify common genetic risks and suggest neurobiological and psychosocial mechanisms of vulnerability to chronic pain.
Abstract
Chronic pain is attributable to both local and systemic pathology. To investigate the latter, we focused on genetic risk shared among 24 chronic pain conditions in the UK Biobank. We conducted genome-wide association studies (GWAS) on all conditions and estimated genetic correlations among them, using these to model a factor structure in Genomic SEM. This revealed a general factor explaining most of the shared genetic variance in all conditions and an additional musculoskeletal pain-selective factor. Network analyses revealed a large cluster of highly genetically inter-connected conditions, with arthropathic, back, and neck pain showing the highest centrality. Functional annotation (FUMA) showed organogenesis, metabolism, transcription, and DNA repair as associated pathways, with enrichment for associated genes exclusively in brain tissues. Cross-reference with previous GWAS showed genetic overlap with cognition, mood, and brain structure. In sum, our results identify common genetic risks and suggest neurobiological and psychosocial mechanisms of vulnerability to chronic pain.

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Posted ContentDOI

A shared genetic signature for common chronic pain conditions and its impact on biopsychosocial traits

TL;DR: A broad range of traits with genetic causal effects upon chronic pain are identified, which may inform development of novel diagnostic and therapeutic strategies, as well as provide convergent support for various existing approaches.
Posted ContentDOI

A Data-Driven Biopsychosocial Framework Determining the Spreading of Chronic Pain

TL;DR: Predictive models for the number of co-existing pain sites in the UK Biobank were derived and a common risk score was identified that classified different chronic pain conditions in cross-sectional data, predicted the development of chronic pain in pain-free individuals, and determined the spreading of chronicPain to multiple sites or its recovery nine years later.
Journal ArticleDOI

Shared Genetic Regulatory Networks Contribute to Neuropathic and Inflammatory Pain: Multi-Omics Systems Analysis

TL;DR: This study utilized multi-omics systematic analyses to investigate the shared genetic mechanisms of neuropathic pain and inflammatory pain, and revealed the significant overlap of the gene co-expression modules in NP and IP.
Posted ContentDOI

The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

TL;DR: In this article , a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel.
Posted ContentDOI

The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

TL;DR: In this paper , a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel.
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