Genetic Studies of Mood Disorders and Comorbidities

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (25 August 2021) | Viewed by 10035

Special Issue Editor


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Guest Editor
1. Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Glasgow G12 8RZ, UK
2. Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, 17177 Stockholm, Sweden
Interests: schizophrenia; bipolar disorder; major depressive disorder; psychiatric endophenotyes; cardiovascular disease; metabolic disease

Special Issue Information

Dear Colleagues,

Individuals with severe mental illness (such as schizophrenia, bipolar disorder and major depressive disorder) carry increased risk of developing many physical diseases, which contributes to the mortality rate being 2–3 times higher in such patients compared to the general public. Cardiometabolic diseases (such as obesity, type 2 diabetes and coronary artery disease) are particularly prevalent, with reductions in life expectancy of up to 25 years due to cardiovascular diseases. Traditionally, the increased disease risk has been attributed to the increased burden of risk factors, such as sedentary lifestyle, smoking, substance abuse and socioeconomic factors. Genetic studies have begun to challenge this assumption, with recent studies suggesting common biological mechanisms underlying physical and psychiatric illness.

In this Special Issue, we aim to highlight some of the ways in which genetics and genomics can be used to investigate the relationship between physical and psychiatric illness as well as to provide an update on some recent findings in this area.

Dr. Rona Strawbridge
Guest Editor

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Keywords

  • Psychiatric illness
  • Psychiatric endophenotypes
  • Cardiovascular disease
  • Obesity
  • Type 2 diabetes
  • Other psychiatric comorbidities

Published Papers (3 papers)

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Research

16 pages, 2202 KiB  
Article
GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia
by Yi-Sian Lin, Chia-Chun Wang and Cho-Yi Chen
Genes 2021, 12(10), 1506; https://doi.org/10.3390/genes12101506 - 26 Sep 2021
Cited by 7 | Viewed by 3801
Abstract
Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent, and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity [...] Read more.
Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent, and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understanding their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together, these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms. Full article
(This article belongs to the Special Issue Genetic Studies of Mood Disorders and Comorbidities)
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27 pages, 7297 KiB  
Article
Genetic Variation in the ASTN2 Locus in Cardiovascular, Metabolic and Psychiatric Traits: Evidence for Pleiotropy Rather Than Shared Biology
by Olivia Burt, Keira J. A. Johnston, Nicholas Graham, Breda Cullen, Donald M. Lyall, Laura M. Lyall, Jill P. Pell, Joey Ward, Daniel J. Smith and Rona J. Strawbridge
Genes 2021, 12(8), 1194; https://doi.org/10.3390/genes12081194 - 31 Jul 2021
Cited by 5 | Viewed by 2183
Abstract
Background: The link between cardiometabolic and psychiatric illness has long been attributed to human behaviour, however recent research highlights shared biological mechanisms. The ASTN2 locus has been previously implicated in psychiatric and cardiometabolic traits, therefore this study aimed to systematically investigate the genetic [...] Read more.
Background: The link between cardiometabolic and psychiatric illness has long been attributed to human behaviour, however recent research highlights shared biological mechanisms. The ASTN2 locus has been previously implicated in psychiatric and cardiometabolic traits, therefore this study aimed to systematically investigate the genetic architecture of ASTN2 in relation to a wide range of relevant traits. Methods: Baseline questionnaire, assessment and genetic data of 402111 unrelated white British ancestry individuals from the UK Biobank was analysed. Genetic association analyses were conducted using PLINK 1.07, assuming an additive genetic model and adjusting for age, sex, genotyping chip, and population structure. Conditional analyses and linkage disequilibrium assessment were used to determine whether cardiometabolic and psychiatric signals were independent. Results: Associations between genetic variants in the ASTN2 locus and blood pressure, total and central obesity, neuroticism, anhedonia and mood instability were identified. All analyses support the independence of the cardiometabolic traits from the psychiatric traits. In silico analyses provide support for the central obesity signal acting through ASTN2, however most of the other signals are likely acting through other genes in the locus. Conclusions: Our systematic analysis demonstrates that ASTN2 has pleiotropic effects on cardiometabolic and psychiatric traits, rather than contributing to shared pathology. Full article
(This article belongs to the Special Issue Genetic Studies of Mood Disorders and Comorbidities)
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13 pages, 1338 KiB  
Article
A Causal Web between Chronotype and Metabolic Health Traits
by John A. Williams, Dominic Russ, Laura Bravo-Merodio, Victor Roth Cardoso, Samantha C. Pendleton, Furqan Aziz, Animesh Acharjee and Georgios V. Gkoutos
Genes 2021, 12(7), 1029; https://doi.org/10.3390/genes12071029 - 01 Jul 2021
Cited by 2 | Viewed by 3278
Abstract
Observational and experimental evidence has linked chronotype to both psychological and cardiometabolic traits. Recent Mendelian randomization (MR) studies have investigated direct links between chronotype and several of these traits, often in isolation of outside potential mediating or moderating traits. We mined the EpiGraphDB [...] Read more.
Observational and experimental evidence has linked chronotype to both psychological and cardiometabolic traits. Recent Mendelian randomization (MR) studies have investigated direct links between chronotype and several of these traits, often in isolation of outside potential mediating or moderating traits. We mined the EpiGraphDB MR database for calculated chronotype–trait associations (p-value < 5 × 10−8). We then re-analyzed those relevant to metabolic or mental health and investigated for statistical evidence of horizontal pleiotropy. Analyses passing multiple testing correction were then investigated for confounders, colliders, intermediates, and reverse intermediates using the EpiGraphDB database, creating multiple chronotype–trait interactions among each of the the traits studied. We revealed 10 significant chronotype–exposure associations (false discovery rate < 0.05) exposed to 111 potential previously known confounders, 52 intermediates, 18 reverse intermediates, and 31 colliders. Chronotype–lipid causal associations collided with treatment and diabetes effects; chronotype–bipolar associations were mediated by breast cancer; and chronotype–alcohol intake associations were impacted by confounders and intermediate variables including known zeitgebers and molecular traits. We have reported the influence of chronotype on several cardiometabolic and behavioural traits, and identified potential confounding variables not reported on in studies while discovering new associations to drugs and disease. Full article
(This article belongs to the Special Issue Genetic Studies of Mood Disorders and Comorbidities)
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