scholarly journals Potential Genetic Overlap Between Insomnia and Sleep Symptoms in Major Depressive Disorder: A Polygenic Risk Score Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Lindsay M. Melhuish Beaupre ◽  
Arun K. Tiwari ◽  
Vanessa F. Gonçalves ◽  
Clement C. Zai ◽  
Victoria S. Marshe ◽  
...  

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.

Thyroid ◽  
2019 ◽  
Vol 29 (12) ◽  
pp. 1713-1722 ◽  
Author(s):  
Kwan Woo Choi ◽  
Yuwon Kim ◽  
Maurizio Fava ◽  
David Mischoulon ◽  
Eun Jin Na ◽  
...  

2017 ◽  
Vol 92 ◽  
pp. 119-123 ◽  
Author(s):  
Fernanda Pedrotti Moreira ◽  
Karen Jansen ◽  
Taiane de Azevedo Cardoso ◽  
Thaíse Campos Mondin ◽  
Pedro Vieira da Silva Magalhães ◽  
...  

1996 ◽  
Vol 168 (S30) ◽  
pp. 17-30 ◽  
Author(s):  
R. C. Kessler ◽  
C. B. Nelson ◽  
K. A. McGonagle ◽  
J. Liu ◽  
M. Swartz ◽  
...  

General population data are presented on the prevalence and correlates of comorbidity between DSM–III–R major depressive disorder (MDD) and other DSM–III–R disorders. The data come from the US National Comorbidity Survey, a large general population survey of persons aged 15–54 years in the non-institutionalised civilian population. Diagnoses are based on a modified version of the Composite International Diagnostic Interview (CIDI). The analysis shows that most cases of lifetime MDD are secondary, in the sense that they occur in people with a prior history of another DSM–III–R disorder. Anxiety disorders are the most common primary disorders. The time-lagged effects of most primary disorders on the risk of subsequent MDD continue for many years without change in magnitude. Secondary MDD is, in general, more persistent and severe than pure or primary MDD. This has special public health significance because lifetime prevalence of secondary MDD has increased in recent cohorts, while the prevalence of pure and primary depression has remained unchanged.


2021 ◽  
Vol 15 ◽  
Author(s):  
Jiaqi Zhou ◽  
Miao Li ◽  
Xueying Wang ◽  
Yuwen He ◽  
Yan Xia ◽  
...  

Pharmacotherapy is the most common treatment for schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). Pharmacogenetic studies have achieved results with limited clinical utility. DNA methylation (DNAm), an epigenetic modification, has been proposed to be involved in both the pathology and drug treatment of these disorders. Emerging data indicates that DNAm could be used as a predictor of drug response for psychiatric disorders. In this study, we performed a systematic review to evaluate the reproducibility of published changes of drug response-related DNAm in SCZ, BD and MDD. A total of 37 publications were included. Since the studies involved patients of different treatment stages, we partitioned them into three groups based on their primary focuses: (1) medication-induced DNAm changes (n = 8); (2) the relationship between DNAm and clinical improvement (n = 24); and (3) comparison of DNAm status across different medications (n = 14). We found that only BDNF was consistent with the DNAm changes detected in four independent studies for MDD. It was positively correlated with clinical improvement in MDD. To develop better predictive DNAm factors for drug response, we also discussed future research strategies, including experimental, analytical procedures and statistical criteria. Our review shows promising possibilities for using BDNF DNAm as a predictor of antidepressant treatment response for MDD, while more pharmacoepigenetic studies are needed for treatments of various diseases. Future research should take advantage of a system-wide analysis with a strict and standard analytical procedure.


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