Familial Contributions to Self-Reported Sleep and Pain in Female Twins

Polygenic evidence and overlapped brain functional connectivities for the association between chronic pain and sleep disturbance

Chronic pain and sleep disturbance are highly comorbid disorders, which leads to barriers to treatment and significant healthcare costs. Understanding the underlying genetic and neural mechanisms of the interplay between sleep disturbance and chronic pain is likely to lead to better treatment. In this study, we combined 1206 participants with phenotype data, resting-state functional magnetic resonance imaging (rfMRI) data and genotype data from the Human Connectome Project and two large sample size genome-wide association studies (GWASs) summary data from published studies to identify the genetic and neural bases for the association between pain and sleep disturbance. Pittsburgh sleep quality index (PSQI) score was used for sleep disturbance, pain intensity was measured by Pain Intensity Survey. The result showed chronic pain was significantly correlated with sleep disturbance (r = 0.171, p-value < 0.001). Their genetic correlation was r_g = 0.598 using linkage disequilibrium (LD) score regression analysis. Polygenic score (PGS) association analysis showed PGS of chronic pain was significantly associated with sleep and vice versa. Nine shared functional connectivity (FCs) were identified involving prefrontal cortex, temporal cortex, precentral/postcentral cortex, anterior cingulate cortex, fusiform gyrus and hippocampus. All these FCs mediated the effect of sleep disturbance on pain and seven FCs mediated the effect of pain on sleep disturbance. The chronic pain PGS was positively associated with the FC between middle temporal gyrus and hippocampus, which further mediated the effect of chronic pain PGS on PSQI score. Mendelian randomization analysis implied a possible causal relationship from chronic pain to sleep disturbance was stronger than that of sleep disturbance to chronic pain. The results provided genetic and neural evidence for the association between pain and sleep disturbance, which may inform future treatment approaches for comorbid chronic pain states and sleep disturbance.

Genetic and Environmental Influences on Sleep, Pain, and Depression Symptoms in a Community Sample of Twins

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.