Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis

Andrew M. McIntosh; Lynsey S. Hall; Yanni Zeng; Mark J Adams; Jude Gibson; Eleanor Wigmore; Saskia 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

doi:10.1371/journal.pmed.1002090

Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis

Andrew M. McIntosh, Lynsey S. Hall, Yanni Zeng, Mark J Adams, Jude Gibson, Eleanor Wigmore, Saskia 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 ScollenWeihua Meng, Blair H. Smith, Lynne J. Hocking

Research output: Contribution to journal › Article › peer-review

Abstract

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 UK 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 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.
ConclusionsGenetic 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.

Original language	English
Article number	e1002090
Journal	PLoS Medicine
Volume	13
Issue number	8
DOIs	https://doi.org/10.1371/journal.pmed.1002090
Publication status	Published - 16 Aug 2016

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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
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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Stratifying Resilience and Depression Longitudinally
McIntosh, A. (Principal Investigator), Deary, I. (Co-investigator), Evans, K. (Co-investigator), Haley, C. (Co-investigator) & Porteous, D. (Co-investigator)
UK-based charities
1/01/15 → 30/06/21
Project: Research
RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I. (Principal Investigator), Gale, C. (Co-investigator), Holmes, M. (Co-investigator), Logie, P. (Co-investigator), Maclullich, A. (Co-investigator), Porteous, D. (Co-investigator), Seckl, J. (Co-investigator), Starr, J. (Co-investigator), Wardlaw, J. (Co-investigator) & Okely, J. (Researcher)
1/09/13 → 31/08/19
Project: Research
Generation Scotland
Porteous, D. (Principal Investigator)
UK central government bodies/local authorities, health and hospital authorities
1/04/11 → 31/03/14
Project: Research

Andrew McIntosh
- Deanery of Clinical Sciences - Chair of Biological Psychiatry
- Centre for Clinical Brain Sciences
- Edinburgh Neuroscience
Person: Academic: Research Active

Cite this

McIntosh, A. M., Hall, L. S., Zeng, Y., Adams, M. J., Gibson, J., Wigmore, E., Hagenaars, S., Davies, G., Fernandez-Pujals, A. M., Campbell, A. I., Clarke, T.-K., Hayward, C., Haley, C. S., Porteous, D. J., Deary, I. J., Smith, D. J., Nicholl, B. I., Hinds, D. A., Jones, A. V., ... Hocking, L. J. (2016). Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis. PLoS Medicine, 13(8), Article e1002090. https://doi.org/10.1371/journal.pmed.1002090

@article{8a0e3ab64b9947fa9d52761ea559bd93,

title = "Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis",

abstract = "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 UK 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 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. ConclusionsGenetic 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.",

author = "McIntosh, {Andrew M.} and Hall, {Lynsey S.} and Yanni Zeng and Adams, {Mark J} and Jude Gibson and Eleanor Wigmore and Saskia Hagenaars and Gail Davies and Fernandez-Pujals, {Ana Maria} and Campbell, {Archie I.} and Toni-Kim Clarke and Caroline Hayward and Haley, {Chris S.} and Porteous, {David J.} and Deary, {Ian J.} and Smith, {Daniel J} and Nicholl, {Barbara I.} and Hinds, {David A} and Jones, {Amy V} and Serena Scollen and Weihua Meng and Smith, {Blair H.} and Hocking, {Lynne J.}",

year = "2016",

month = aug,

day = "16",

doi = "10.1371/journal.pmed.1002090",

language = "English",

volume = "13",

journal = "PLoS Medicine",

issn = "1549-1277",

publisher = "Public Library of Science",

number = "8",

}

McIntosh, AM, Hall, LS, Zeng, Y, Adams, MJ, Gibson, J, Wigmore, E, Hagenaars, S, Davies, G, Fernandez-Pujals, AM, Campbell, AI, Clarke, T-K, Hayward, C , Haley, CS, Porteous, DJ, Deary, IJ, Smith, DJ, Nicholl, BI, Hinds, DA, Jones, AV, Scollen, S, Meng, W, Smith, BH & Hocking, LJ 2016, 'Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis', PLoS Medicine, vol. 13, no. 8, e1002090. https://doi.org/10.1371/journal.pmed.1002090

TY - JOUR

T1 - Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder

T2 - a family-based mixed-model analysis

AU - McIntosh, Andrew M.

AU - Hall, Lynsey S.

AU - Zeng, Yanni

AU - Adams, Mark J

AU - Gibson, Jude

AU - Wigmore, Eleanor

AU - Hagenaars, Saskia

AU - Davies, Gail

AU - Fernandez-Pujals, Ana Maria

AU - Campbell, Archie I.

AU - Clarke, Toni-Kim

AU - Hayward, Caroline

AU - Haley, Chris S.

AU - Porteous, David J.

AU - Deary, Ian J.

AU - Smith, Daniel J

AU - Nicholl, Barbara I.

AU - Hinds, David A

AU - Jones, Amy V

AU - Scollen, Serena

AU - Meng, Weihua

AU - Smith, Blair H.

AU - Hocking, Lynne J.

PY - 2016/8/16

Y1 - 2016/8/16

N2 - 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 UK 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 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. ConclusionsGenetic 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.

AB - 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 UK 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 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. ConclusionsGenetic 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.

U2 - 10.1371/journal.pmed.1002090

DO - 10.1371/journal.pmed.1002090

M3 - Article

SN - 1549-1277

VL - 13

JO - PLoS Medicine

JF - PLoS Medicine

IS - 8

M1 - e1002090

ER -

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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Stratifying Resilience and Depression Longitudinally

RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.

Generation Scotland

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Andrew McIntosh

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