Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis.
| Title: | Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis. |
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| Authors: | Andrew M McIntosh, Lynsey S Hall, Yanni Zeng, Mark J Adams, Jude Gibson, Eleanor Wigmore, Saskia P Hagenaars, Gail Davies, Ana Maria Fernandez-Pujals, Archie I Campbell, Toni-Kim Clarke, Caroline Hayward, Chris S Haley, David J Porteous, Ian J Deary, Daniel J Smith, Barbara I Nicholl, David A Hinds, Amy V Jones, Serena Scollen, Weihua Meng, Blair H Smith, Lynne J Hocking |
| Source: | PLoS Medicine, Vol 13, Iss 8, p e1002090 (2016) |
| Publisher Information: | Public Library of Science (PLoS), 2016. |
| Publication Year: | 2016 |
| Collection: | LCC:Medicine |
| Subject Terms: | Medicine |
| More Details: | BackgroundChronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study.Methods and findingsUsing family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with chronic pain in both GS:SFHS (maximum β = 6.18x10-2, 95% CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 5.68 x 10-2, 95% CI 4.70x10-2 to 6.65x10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum β = 6.62x10-2, 95% CI 2.82 x10-2 to 9.76 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 2.56x10-2, 95% CI 1.62x10-2 to 3.63x10-2, p < 3x10-4). Limitations of the current study include the possibility that spouse effects may be due to assortative mating and the relatively small polygenic risk score effect sizes.ConclusionsGenetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1549-1277 1549-1676 |
| Relation: | https://doaj.org/toc/1549-1277; https://doaj.org/toc/1549-1676 |
| DOI: | 10.1371/journal.pmed.1002090 |
| Access URL: | https://doaj.org/article/8f71b918dc974bb39e192772bb999d22 |
| Accession Number: | edsdoj.8f71b918dc974bb39e192772bb999d22 |
| Database: | Directory of Open Access Journals |
| ISSN: | 15491277 15491676 |
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| DOI: | 10.1371/journal.pmed.1002090 |
| Published in: | PLoS Medicine |
| Language: | English |