AUTHOR=Melhuish Beaupre Lindsay M. , Tiwari Arun K. , Gonçalves Vanessa F. , Zai Clement C. , Marshe Victoria S. , Lewis Cathryn M. , Martin Nicholas G. , McIntosh Andrew M. , Adams Mark J. , Baune Bernhard T. , Levinson Doug F. , Boomsma Dorret I. , Penninx Brenda W. J. H. , Breen Gerome , Hamilton Steve , Awasthi Swapnil , Ripke Stephan , Jones Lisa , Jones Ian , Byrne Enda M. , Hickie Ian B. , Potash James P. , Shi Jianxin , Weissman Myrna M. , Milaneschi Yuri , Shyn Stanley I. , Geus Eco J. C. de , Willemsen Gonneke , Brown Gregory M. , Kennedy James L. , Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
TITLE=Potential Genetic Overlap Between Insomnia and Sleep Symptoms in Major Depressive Disorder: A Polygenic Risk Score Analysis
JOURNAL=Frontiers in Psychiatry
VOLUME=12
YEAR=2021
URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.734077
DOI=10.3389/fpsyt.2021.734077
ISSN=1664-0640
ABSTRACT=Background: The prevalence of insomnia and hypersomnia in depressed individuals is substantially higher than that found in the general population. Unfortunately, these concurrent sleep problems can have profound effects on the disease course. Although the full biology of sleep remains to be elucidated, a recent genome-wide association (GWAS) of insomnia, and other sleep traits in over 1 million individuals was recently published and provides many promising hits for genetics of insomnia in a population-based sample.
Methods: Using data from the largest available GWAS of insomnia and other sleep traits, we sought to test if sleep variable PRS scores derived from population-based studies predicted sleep variables in samples of depressed cases [Psychiatric Genomics Consortium - Major Depressive Disorder subjects (PGC MDD)]. A leave-one-out analysis was performed to determine the effects that each individual study had on our results.
Results: The only significant finding was for insomnia, where p-value threshold, p = 0.05 was associated with insomnia in our PGC MDD sample (R2 = 1.75−3, p = 0.006).
Conclusion: Our results reveal that <1% of variance is explained by the variants that cover the two significant p-value thresholds, which is in line with the fact that depression and insomnia are both polygenic disorders. To the best of our knowledge, this is the first study to investigate genetic overlap between the general population and a depression sample for insomnia, which has important treatment implications, such as leading to novel drug targets in future research efforts.