Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions. / Tsepilov, Yakov A.; Freidin, Maxim B.; Shadrina, Alexandra S. и др.
в: Communications Biology, Том 3, № 1, 329, 25.06.2020.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Analysis of genetically independent phenotypes identifies shared genetic factors associated with chronic musculoskeletal pain conditions
AU - Tsepilov, Yakov A.
AU - Freidin, Maxim B.
AU - Shadrina, Alexandra S.
AU - Sharapov, Sodbo Z.
AU - Elgaeva, Elizaveta E.
AU - Zundert, Jan van
AU - Karssen, Lennart
AU - Suri, Pradeep
AU - Williams, Frances M.K.
AU - Aulchenko, Yurii S.
PY - 2020/6/25
Y1 - 2020/6/25
N2 - 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.
AB - 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.
KW - EXTRACELLULAR-MATRIX PROTEIN-1
KW - OSTEOARTHRITIS SUSCEPTIBILITY
KW - GDF5
KW - METAANALYSIS
KW - PREVALENCE
KW - DEPRESSION
KW - EXPRESSION
KW - VARIANTS
KW - GWAS
KW - SNP
UR - http://www.scopus.com/inward/record.url?scp=85087062025&partnerID=8YFLogxK
U2 - 10.1038/s42003-020-1051-9
DO - 10.1038/s42003-020-1051-9
M3 - Article
C2 - 32587327
AN - SCOPUS:85087062025
VL - 3
JO - Communications Biology
JF - Communications Biology
SN - 2399-3642
IS - 1
M1 - 329
ER -
ID: 24615306