The Association between Chronic Widespread Musculoskeletal Pain, Depression and Fatigue Is Genetically Mediated

• Published in: PloS one 2015-11, Vol.10 (11), p.e0140289
• Main Authors: Burri, Andrea, Ogata, Soshiro, Livshits, Gregory, Williams, Frances
• Format: Article
• Language: English
• Subjects: Activities of daily living; Adult; Aged; Aged, 80 and over; Analysis; Anxiety; Arthritis; Chronic fatigue syndrome; Chronic pain; Chronic Pain - blood; Chronic Pain - genetics; Chronic Pain - pathology; Complications and side effects; Correlation; Dehydroepiandrosterone; Depression (Mood disorder); Depression - blood; Depression - genetics; Depression - pathology; Development and progression; Dihydrotestosterone - blood; Environmental factors; Epidemiology; Etiology; Fatigue; Fatigue - blood; Fatigue - genetics; Fatigue - pathology; Female; Fibromyalgia; Gender differences; Gene-Environment Interaction; Genetic factors; Genetic Predisposition to Disease; Health care; Hormones; Hospitals; Humans; Male; Mental depression; Metabolism; Middle Aged; Musculoskeletal Pain - blood; Musculoskeletal Pain - genetics; Musculoskeletal Pain - pathology; Pain; Pain Measurement; Patient outcomes; Risk analysis; Risk Factors; Studies; Twins; Womens health
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0140289

Chronic widespread muscoloskeletal pain (CWP) is prevalent in the general population and associated with high health care costs, so understanding the risk factors for chronic pain is important for both those affected and for society. In the present study we investigated the underlying etiological structure of CWP to understand better the association between the major clinical features of fatigue, depression and dihydroepiandrosterone sulphate (DHEAS) using a multivariate twin design. Data were available in 463 UK female twin pairs including CWP status and information on depression, chronic fatigue and serum DHEAS levels. High to moderate heritabilities for all phenotypes were obtained (42.58% to 74.24%). The highest phenotypic correlation was observed between fatigue and CWP (r = 0.45), and the highest genetic correlation between CWP and fatigue (rg = 0.78). Structural equation modeling revealed the AE Cholesky model to provide the best model of the observed data. In this model, two additive genetic factors could be detected loading heavily on CWP-A2 explaining 40% of the variance and A3 20%. The factor loading heaviest on DHEAS showed only a small loading on the other phenotypes and none on fatigue at all. Furthermore, one distinct non-shared environmental factor loading specifically on CWP-but not on any of the other phenotypes-could be detected suggesting that the association between CWP and the other phenotypes is due only to genetic factors. Our results suggest that CWP and its associated features share a genetic predisposition but that they are relatively distinct in their environmental determinants.