| Title: | Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions |
| Journal: | Communications Biology |
| Published: | 25 Jun 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32587327/ |
| DOI: | https://doi.org/10.1038/s42003-020-1051-9 |
| URL: | https://www.nature.com/articles/s42003-020-1051-9.pdf |
| Citations: | 49 (22 in last 2 years) as of 8 Aug 2024 |
Publication 3208
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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.</p>
10 Authors
- Yakov A. Tsepilov
- Maxim B. Freidin
- Alexandra S. Shadrina
- Sodbo Z. Sharapov
- Elizaveta E. Elgaeva
- Jan van Zundert
- Lennart С. Karssen
- Pradeep Suri
- Frances M. K. Williams
- Yurii S. Aulchenko
1 Application
| Application ID | Title |
|---|---|
| 18219 | Genetic and epidemiological analyses of low back pain |
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