Genetic correlations between COVID-19 and a variety of traits and diseases

AbstractWe analyzed GWAS results released by COVID-19 Host Genetics Initiative, UK biobank and GWAS Catalog to explore the genetic overlap between COVID-19 and a broad spectrum of traits and diseases. We validate previously reported medical conditions and risk factors based on epidemiological studies, including but not limited to hypertension, type 2 diabetes and obesity. We also report novel traits associated with COVID-19, which have not been previously reported from epidemiological data, such as opioid use and educational attainment. Taken together, this study extends our understanding of the genetic basis of COVID-19, and provides target traits for further epidemiological studies.

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Vitamin D, adipose tissue, and obesity

Hormone Molecular Biology and Clinical Investigation ◽

10.1515/hmbci-2013-0027 ◽

2013 ◽

Vol 15 (3) ◽

Cited By ~ 6

Author(s):

Julie Marcotorchino ◽

Franck Tourniaire ◽

Jean-François Landrier

Keyword(s):

Type 2 Diabetes ◽

Vitamin D ◽

Adipose Tissue ◽

Cardiovascular Diseases ◽

Vitamin D Deficiency ◽

Epidemiological Studies ◽

The Relationship ◽

Diabetes And Obesity

AbstractEpidemiological studies have shown a link between vitamin D deficiency and numerous pathologies such as cancers, immunity diseases, cardiovascular diseases, hypertension, type 2 diabetes, and obesity. Recent studies in vitro and in animal models demonstrated an impact of vitamin D on adipose tissue and adipocyte biology. Such observations are of particular interest and provide mechanistic explanations on the relationship between vitamin D deficiency and obesity.

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Genome-wide association study of problematic opioid prescription use in 132,113 23andMe research participants of European ancestry

Molecular Psychiatry ◽

10.1038/s41380-021-01335-3 ◽

2021 ◽

Author(s):

Sandra Sanchez-Roige ◽

Pierre Fontanillas ◽

Mariela V. Jennings ◽

Sevim B. Bianchi ◽

Yuye Huang ◽

...

Keyword(s):

Association Study ◽

Risk Taking ◽

Genetic Basis ◽

Genome Wide Association Study ◽

Genetic Correlations ◽

Genome Wide Association ◽

European Ancestry ◽

Opioid Use ◽

Research Participants ◽

Genome Wide

AbstractThe growing prevalence of opioid use disorder (OUD) constitutes an urgent health crisis. Ample evidence indicates that risk for OUD is heritable. As a surrogate (or proxy) for OUD, we explored the genetic basis of using prescription opioids ‘not as prescribed’. We hypothesized that misuse of opiates might be a heritable risk factor for OUD. To test this hypothesis, we performed a genome-wide association study (GWAS) of problematic opioid use (POU) in 23andMe research participants of European ancestry (N = 132,113; 21% cases). We identified two genome-wide significant loci (rs3791033, an intronic variant of KDM4A; rs640561, an intergenic variant near LRRIQ3). POU showed positive genetic correlations with the two largest available GWAS of OUD and opioid dependence (rg = 0.64, 0.80, respectively). We also identified numerous additional genetic correlations with POU, including alcohol dependence (rg = 0.74), smoking initiation (rg = 0.63), pain relief medication intake (rg = 0.49), major depressive disorder (rg = 0.44), chronic pain (rg = 0.42), insomnia (rg = 0.39), and loneliness (rg = 0.28). Although POU was positively genetically correlated with risk-taking (rg = 0.38), conditioning POU on risk-taking did not substantially alter the magnitude or direction of these genetic correlations, suggesting that POU does not simply reflect a genetic tendency towards risky behavior. Lastly, we performed phenome- and lab-wide association analyses, which uncovered additional phenotypes that were associated with POU, including respiratory failure, insomnia, ischemic heart disease, and metabolic and blood-related biomarkers. We conclude that opioid misuse can be measured in population-based cohorts and provides a cost-effective complementary strategy for understanding the genetic basis of OUD.

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Genome-wide association study of problematic opioid prescription use in 132,113 23andMe research participants of European ancestry

10.1101/2021.06.03.21258260 ◽

2021 ◽

Author(s):

Sandra Sanchez-Roige ◽

Pierre Fontanillas ◽

Mariela V Jennings ◽

Sevim Bianchi ◽

Yuye Huang ◽

...

Keyword(s):

Association Study ◽

Risk Taking ◽

Genetic Basis ◽

Genome Wide Association Study ◽

Genetic Correlations ◽

Genome Wide Association ◽

European Ancestry ◽

Opioid Use ◽

Research Participants ◽

Genome Wide

Rates of opioid use disorder (OUD) constitute an urgent health crisis. Ample evidence indicates that risk for OUD is heritable. As a surrogate (or proxy) for OUD, we explored the genetic basis of using opioids "not as prescribed". We hypothesized that misuse of opiates might be a heritable risk factor for OUD. To test this hypothesis, we performed a genome-wide association study (GWAS) of problematic opioid use (POU; "ever taking opioid prescriptions not as prescribed") in 132,113 23andMe research participants of European ancestry (Ncases=27,805). Our GWAS identified two genome-wide significant loci (rs3791033, an intronic variant of KDM4A; rs640561, an intergenic variant near LRRIQ3). POU showed a positive genetic correlation with opioid dependence and OUD, as measured in the largest available GWAS (rg=0.57-0.80). We also identified numerous additional genetic correlations with POU, including alcohol dependence (rg=0.74), smoking initiation (rg=0.63), pain relief medication intake (rg=0.49), major depressive disorder (rg=0.44), chronic pain (rg=0.42), insomnia (rg=0.39), and loneliness (rg=0.28). Although POU was positively genetically correlated with risk-taking (rg=0.38), conditioning POU on risk-taking did not substantially alter the magnitude or direction of these genetic correlations, suggesting that POU does not simply reflect a general tendency for risky behavior. We conclude that opioid misuse can be measured in population-based cohorts and provides a cost-effective complementary strategy for understanding the genetic basis of OUD.

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Genetics

10.1093/med/9780198789284.003.0004 ◽

2018 ◽

Author(s):

Carol Kan ◽

Ma-Li Wong

Keyword(s):

Complex Traits ◽

Association Studies ◽

Genetic Correlations ◽

Twin Studies ◽

Epidemiological Studies ◽

Environment Interaction ◽

Genome Wide Association Studies ◽

Small Magnitude ◽

Gene Environment ◽

Genetic Overlap

An association between type 2 diabetes mellitus (T2DM) and depression has been reported in epidemiological studies. Finding a genetic overlap between T2DM and depression will provide evidence to support a common biological pathway to both disorders. Genetic correlations observed from twin studies indicate that a small magnitude of the variance in liability can be attributed to genetic factors. However, no genetic overlap has been observed between T2DM and depression in genome-wide association studies using both the polygenic score and the linkage disequilibrium score regression approaches. Clarifying the shared heritability between these two complex traits is an important next step towards better therapy and treatment. Another area that needs to be explored is gene–environment interaction, since genotypes can affect an individual’s responses to the environment and environment can differentially affect genotypes expression.

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Characterization of the genetic relationship between the domains of sleep and circadian-related behaviors with substance use phenotypes

10.1101/2021.12.09.21267547 ◽

2021 ◽

Author(s):

Alexander S. Hatoum ◽

Evan A. Winiger ◽

Claire L. Morrison ◽

Emma C. Johnson ◽

Arpana Agrawal

Keyword(s):

Substance Use ◽

Sleep Duration ◽

Tobacco Use ◽

Genetic Correlations ◽

Opioid Use Disorder ◽

Opioid Use ◽

Related Activity ◽

Genetic Overlap ◽

Activity Measures ◽

Genetic Clusters

AbstractSleep problems and substance use frequently cooccur. While substance use can often manifest as specific sleep deficits, genetic pleiotropy could also explain part of the relationship between sleep and substance use. Here we assess the genetic overlap between substance use behaviors and both sleep and circadian-related activity measures by deriving genetic clusters between these domains and testing processes of causality vs. horizontal pleiotropy using the largest publicly available genome-wide summary statistics of substance use behaviors (N= 79,729 - 632,802) and sleep/activity phenotypes/endophenotypes to date (N=85,502 - 449,734). We found 31 genetic correlations between substance use and sleep/activity measures after Bonferroni correction. Two specific genetic clusters explained our patterns of overlap. Genes associated with tobacco use severity (age of first regular tobacco use and smoking cessation) share overlap with elements of sleep health (sleep duration, sleep efficiency, and chronotype). Substance consumption (drinks per day and cigarettes per day) and problematic substance use behaviors (cannabis use disorder, opioid use disorder, and problematic alcohol use) clustered strongly with problematic measures of sleep (insomnia, self-reported short sleep duration, increased number of sleep episodes, increased sleep duration variability, diurnal inactivity) as well as measures of circadian-related activity (L5, M10, and sleep midpoint). Latent causal variable analyses determined that horizontal pleiotropy (rather than causality) underlies a majority of the associations between substance use and sleep/circadian related measures, except one plausible genetically causal relationship for opioid use disorder on self-reported long sleep duration. Results indeed show significant genetic overlap between substance use and sleep/circadian-related activity measures.

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