Public Release: 

Genetic and environmental risk factors for chronic pain


Both genetic factors and family environment contribute to risk for chronic pain, and contributions of many genes contribute to risk of both chronic pain and major depressive disorder (MDD), according to a new study published in PLOS Medicine. The research was conducted by Andrew McIntosh of the University of Edinburgh, and colleagues and utilized data from 23,960 individuals in the Generation Scotland: Scottish Family Health Study, as well as 112,151 individuals with genotyping and phenotypic data from the United Kingdom Biobank. They found that heritability accounted for 38.4% of the variation in chronic pain risk, and that shared environment with spouses accounted for 18.7% of the variation in susceptibility to chronic pain. They also found that chronic pain was correlated with depression. Finally, McIntosh and colleagues found evidence that polygenic risk contributes to chronic pain and MDD. Data from two independent genome wide association studies, Pfizer-23andMe and the Psychiatric Genomics Consortium Major Depressive Disorder Working Group, suggested that chronic pain risk arises through the combined effect of many different genetic risk factors and that the cumulative effects of genetic risk factors for depression increased an individual's chance of having chronic pain.

The researchers note that assortative mating (choosing a spouse who is similar to oneself) may be responsible for some of the spousal effects, and that these associations do not identify mechanisms through which the genes might be contribute chronic pain. Nevertheless, the study suggests strong genetic and environmental links in risk for MDD and chronic pain and that identifying the shared causal mechanisms may be relevant to finding new treatments.

The researchers say: "The answer to these key questions are likely to signpost new directions for therapeutic interventions and highlight the symptoms that are most amenable to treatment, as well as to prevention."


Research Article


This study was funded by Wellcome Trust Strategic Grant 104036/Z/14/Z. Generation Scotland is funded by the Chief Scientist Office [CZD/16/6] and the Scottish Funding Council [HR03006]. UK Biobank is funded by the Wellcome Trust, Medical Research Council, The Scottish Government and other funders. These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The analysis of pain data collected by 23andMe in collaboration with Pfizer and was funded by Pfizer. Employees of Pfizer and 23andMe are represented in the authorship.

Competing Interests:

AMM has received research funding from Pfizer, Janssen and Lilly in connection with other research. This funding had no role in the research presented in the current manuscript. DAH has received research funding from Pfizer for the current study. DAH is an employee of and owns stock options in 23andMe, Inc. WM has received research funding from Pfizer. BHS has received research funding from Pfizer and Napp Pharmaceuticals. LJH has received research funding from Pfizer. CHay has received research funding from Pfizer.


McIntosh AM, Hall LS, Zeng Y, Adams MJ, Gibson J, Wigmore E, et al. (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 Med 13(8): e1002090. doi:10.1371/journal.pmed.1002090

Author Affiliations:

Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, United Kingdom
Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
23andMe Inc., Mountain View, California, United States of America
Pfizer WRD, Human Genetics and Computational Biomedicine, Granta Park, Cambridge, United Kingdom
Division of Population Health Sciences, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
The Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom



Andrew M. McIntosh
University of Edinburgh,
United Kingdom

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.