Marianna Gasperi1, Matthew Herbert, Ellen Schur, Dedra Buchwald, Niloofar Afari. 1. From the Department of Psychiatry (Gasperi, Afari), University of California, San Diego, California; VA Center of Excellence for Stress and Mental Health (Gasperi, Herbert, Afari), San Diego, California; VA San Diego Healthcare System (Herbert, Afari), San Diego, California; Department of Medicine (Schur), University of Washington, Seattle, Washington; and Elson S Floyd College of Medicine (Buchwald), Washington State University, Spokane, Washington.
Abstract
OBJECTIVE: We used quantitative genetic methods to evaluate whether sleep quality, pain, and depression symptoms share a common genetic diathesis, to estimate the genetic and environmental sources of covariance among these symptoms, and to test for possible causal relationships. METHODS: A community sample of 400 twins from the University of Washington Twin Registry completed standardized self-report questionnaires. We used biometric modeling to assess genetic and environmental contribution to the association between sleep quality measured by the Pittsburgh Sleep Quality Index, pain measured by the Brief Pain Inventory, and depression symptoms measured by the Brief Symptom Inventory. Trivariate Cholesky structural equation models were used to decompose correlations among the phenotypes. RESULTS: Heritability was estimated at 37% (95% confidence interval = 20%-51%) for sleep quality, 25% (9%-41%) for pain, and 39% (22%-53%) for depression. Nonshared environmental influences accounted for the remaining variance. The genetic correlation between sleep quality and pain had an rg value of .69 (95% confidence interval [CI] = 0.33-0.97), rg value of .56 (95% CI = 0.55-0.98) between pain and depression, and rg value of .61 (95% CI = 0.44-0.88) between depression and sleep quality. Nonshared environmental overlap was present between pain and sleep quality as well as depression and sleep quality. CONCLUSIONS: The link between sleep quality, pain, and depression was primarily explained by shared genetic influences. The genetic factors influencing sleep quality and pain were highly correlated even when accounting for depression. Findings support the hypothesis of a genetic link between depression and pain as well as potential causality for the association of sleep quality with pain and depression.
OBJECTIVE: We used quantitative genetic methods to evaluate whether sleep quality, pain, and depression symptoms share a common genetic diathesis, to estimate the genetic and environmental sources of covariance among these symptoms, and to test for possible causal relationships. METHODS: A community sample of 400 twins from the University of Washington Twin Registry completed standardized self-report questionnaires. We used biometric modeling to assess genetic and environmental contribution to the association between sleep quality measured by the Pittsburgh Sleep Quality Index, pain measured by the Brief Pain Inventory, and depression symptoms measured by the Brief Symptom Inventory. Trivariate Cholesky structural equation models were used to decompose correlations among the phenotypes. RESULTS: Heritability was estimated at 37% (95% confidence interval = 20%-51%) for sleep quality, 25% (9%-41%) for pain, and 39% (22%-53%) for depression. Nonshared environmental influences accounted for the remaining variance. The genetic correlation between sleep quality and pain had an rg value of .69 (95% confidence interval [CI] = 0.33-0.97), rg value of .56 (95% CI = 0.55-0.98) between pain and depression, and rg value of .61 (95% CI = 0.44-0.88) between depression and sleep quality. Nonshared environmental overlap was present between pain and sleep quality as well as depression and sleep quality. CONCLUSIONS: The link between sleep quality, pain, and depression was primarily explained by shared genetic influences. The genetic factors influencing sleep quality and pain were highly correlated even when accounting for depression. Findings support the hypothesis of a genetic link between depression and pain as well as potential causality for the association of sleep quality with pain and depression.
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