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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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  • Lynsey S. Hall
  • Yanni Zeng
  • Mark J Adams
  • Jude Gibson
  • Ella Wigmore
  • Saskia Hagenaars
  • Ana Maria Fernandez-Pujals
  • Daniel J Smith
  • Barbara I. Nicholl
  • David A Hinds
  • Amy V Jones
  • Serena Scollen
  • Weihua Meng
  • Blair H. Smith
  • Lynne J. Hocking

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    Rights statement: Copyright: © 2016 McIntosh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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http://journals.plos.org/plosmedicine/article?id=info:doi/10.1371/journal.pmed.1002090
Original languageEnglish
Article numbere1002090
JournalPLOS Medicine
Volume13
Issue number8
DOIs
Publication statusPublished - 16 Aug 2016

Abstract

Background Chronic 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 UK Biobank study. Methods and Findings Using 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 0.5M 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%) which is significantly concordant in spouses (variance explained 18.7%, 95%CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (rho = 0.13, 95%CI 0.11 to 0.15, p = 2.72x10-68) and it shows a tendency to cluster within families for genetic reasons (genetic correlation rho = 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  = 6.18x10-2, 95%CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum  = 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  = 6.62x10-2, 95%CI 2.82 x10-2 to 9.76 x10-2, p = 4.3x10-4) and UK Biobank (maximum  = 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. Conclusions Genetic factors and chronic pain in a partner or spouse contribute substantially to the risk of chronic pain in the general population. Chronic pain is genetically correlated with MDD, has a polygenic architecture and is associated with polygenic risk of MDD.

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