Unknown

Dataset Information

0

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


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.

SUBMITTER: Tsepilov YA 

PROVIDER: S-EPMC7316754 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Tsepilov Yakov A YA   Freidin Maxim B MB   Shadrina Alexandra S AS   Sharapov Sodbo Z SZ   Elgaeva Elizaveta E EE   Zundert Jan van JV   Karssen Lennart С LС   Suri Pradeep P   Williams Frances M K FMK   Aulchenko Yurii S YS  

Communications biology 20200625 1


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 (GI  ...[more]

Similar Datasets

| S-EPMC7141322 | biostudies-literature
| S-EPMC6250282 | biostudies-literature
| S-EPMC8072020 | biostudies-literature
| S-EPMC3831098 | biostudies-literature
| S-EPMC5026346 | biostudies-other
| S-EPMC9271637 | biostudies-literature
| S-EPMC8372387 | biostudies-literature
| S-EPMC7712753 | biostudies-literature
| S-EPMC6649665 | biostudies-literature
| S-EPMC9129062 | biostudies-literature