Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions

Yakov A. Tsepilov, Maxim B. Freidin, Alexandra S. Shadrina, Sodbo Z. Sharapov, Elizaveta E. Elgaeva, Jan van Zundert, Lennart Karssen, Pradeep Suri, Frances M.K. Williams, Yurii S. Aulchenko

Research output: Contribution to journalArticlepeer-review

Abstract

Chronic musculoskeletal pain affects all aspects of human life. However, mechanisms of its genetic control remain poorly understood. Genetic studies of pain are complicated by the high complexity and heterogeneity of pain phenotypes. Here, we apply principal component analysis to reduce phenotype heterogeneity of chronic musculoskeletal pain at four locations: the back, neck/shoulder, hip, and knee. Using matrices of genetic covariances, we constructed four genetically independent phenotypes (GIPs) with the leading GIP (GIP1) explaining 78.4% of the genetic variance of the analyzed conditions, and GIP2–4 explain progressively less. We identified and replicated five GIP1-associated loci and one GIP2-associated locus and prioritized the most likely causal genes. For GIP1, we showed enrichment with multiple nervous system-related terms and genetic correlations with anthropometric, sociodemographic, psychiatric/personality traits and osteoarthritis. We suggest that GIP1 represents a biopsychological component of chronic musculoskeletal pain, related to physiological and psychological aspects and reflecting pain perception and processing.

Original languageEnglish
Article number329
Number of pages13
JournalCommunications Biology
Volume3
Issue number1
DOIs
Publication statusPublished - 25 Jun 2020

Keywords

  • EXTRACELLULAR-MATRIX PROTEIN-1
  • OSTEOARTHRITIS SUSCEPTIBILITY
  • GDF5
  • METAANALYSIS
  • PREVALENCE
  • DEPRESSION
  • EXPRESSION
  • VARIANTS
  • GWAS
  • SNP

Fingerprint Dive into the research topics of 'Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions'. Together they form a unique fingerprint.

Cite this