scholarly journals Shared Genetic Liability and Causal Associations Between Major Depressive Disorder and Cardiovascular Diseases

2021 ◽  
Vol 8 ◽  
Author(s):  
Fuquan Zhang ◽  
Hongbao Cao ◽  
Ancha Baranova
Keyword(s):  
Blood Pressure ◽  
Major Depressive Disorder ◽  
Cardiovascular Diseases ◽  
Mendelian Randomization ◽  
Genetic Variations ◽  
Major Depressive ◽  
Genetic Liability ◽  
Overlap Analysis ◽  
Randomization Analysis ◽  
Shared Genetic

Major depressive disorder (MDD) is phenotypically associated with cardiovascular diseases (CVD). We aim to investigate mechanisms underlying relationships between MDD and CVD in the context of shared genetic variations. Polygenic overlap analysis was used to test genetic correlation and to analyze shared genetic variations between MDD and seven cardiovascular outcomes (coronary artery disease (CAD), heart failure, atrial fibrillation, stroke, systolic blood pressure, diastolic blood pressure, and pulse pressure measurement). Mendelian randomization analysis was used to uncover causal relationships between MDD and cardiovascular traits. By cross-trait meta-analysis, we identified a set of genomic loci shared between the traits of MDD and stroke. Putative causal genes for MDD and stroke were prioritized by fine-mapping of transcriptome-wide associations. Polygenic overlap analysis pointed toward substantial genetic variation overlap between MDD and CVD. Mendelian randomization analysis indicated that genetic liability to MDD has a causal effect on CAD and stroke. Comparison of genome-wide genes shared by MDD and CVD suggests 20q12 as a pleiotropic region conferring risk for both MDD and CVD. Cross-trait meta-analyses and fine-mapping of transcriptome-wide association signals identified novel risk genes for MDD and stroke, including RPL31P12, BORSC7, PNPT11, and PGF. Many genetic variations associated with MDD and CVD outcomes are shared, thus, pointing that genetic liability to MDD may also confer risk for stroke and CAD. Presented results shed light on mechanistic connections between MDD and CVD phenotypes.

scholarly journals Shared genetic liability between major depressive disorder and osteoarthritis

2022 ◽  
Vol 11 (1) ◽  
pp. 12-22
Author(s):  
Fuquan Zhang ◽  
Shuquan Rao ◽  
Ancha Baranova
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genetic Correlation ◽  
Fine Mapping ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Major Depressive ◽  
Genetic Liability ◽  
Randomization Analysis ◽  
Shared Genetic

Aims Deciphering the genetic relationships between major depressive disorder (MDD) and osteoarthritis (OA) may facilitate an understanding of their biological mechanisms, as well as inform more effective treatment regimens. We aim to investigate the mechanisms underlying relationships between MDD and OA in the context of common genetic variations. Methods Linkage disequilibrium score regression was used to test the genetic correlation between MDD and OA. Polygenic analysis was performed to estimate shared genetic variations between the two diseases. Two-sample bidirectional Mendelian randomization analysis was used to investigate causal relationships between MDD and OA. Genomic loci shared between MDD and OA were identified using cross-trait meta-analysis. Fine-mapping of transcriptome-wide associations was used to prioritize putatively causal genes for the two diseases. Results MDD has a significant genetic correlation with OA (rg = 0.29) and the two diseases share a considerable proportion of causal variants. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on OA (bxy = 0.24) and genetic liability to OA conferred a causal effect on MDD (bxy = 0.20). Cross-trait meta-analyses identified 29 shared genomic loci between MDD and OA. Together with fine-mapping of transcriptome-wide association signals, our results suggest that Estrogen Receptor 1 ( ESR1), SRY-Box Transcription Factor 5 ( SOX5), and Glutathione Peroxidase 1 ( GPX1) may have therapeutic implications for both MDD and OA. Conclusion The study reveals substantial shared genetic liability between MDD and OA, which may confer risk for one another. Our findings provide a novel insight into phenotypic relationships between MDD and OA. Cite this article: Bone Joint Res 2022;11(1):12–22.

scholarly journals Shared Genetic Liability Between Major Depressive Disorder and Atopic Diseases

2021 ◽  
Vol 12 ◽  
Author(s):  
Hongbao Cao ◽  
Sheng Li ◽  
Ancha Baranova ◽  
Fuquan Zhang
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Fine Mapping ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Atopic Diseases ◽  
Major Depressive ◽  
Genetic Liability ◽  
Randomization Analysis ◽  
Shared Genetic

ObjectivesDeciphering the genetic relationships between major depressive disorder (MDD) and atopic diseases (asthma, hay fever, and eczema) may facilitate understanding of their biological mechanisms as well as the development of novel treatment regimens. Here we tested the genetic correlation between MDD and atopic diseases by linkage disequilibrium score regression.MethodsA polygenic overlap analysis was performed to estimate shared genetic variations between the two diseases. Causal relationships between MDD and atopic diseases were investigated using two-sample bidirectional Mendelian randomization analysis. Genomic loci shared between MDD and atopic diseases were identified using cross-trait meta-analysis. Putative functional genes were evaluated by fine-mapping of transcriptome-wide associations.ResultsThe polygenic analysis revealed approximately 15.8 thousand variants causally influencing MDD and 0.9 thousand variants influencing atopic diseases. Among these variants, approximately 0.8 thousand were shared between the two diseases. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on atopic diseases (b = 0.22, p = 1.76 × 10-6), while genetic liability to atopic diseases confers a weak causal effect on MDD (b = 0.05, p = 7.57 × 10-3). Cross-trait meta-analyses of MDD and atopic diseases identified 18 shared genomic loci. Both fine-mapping of transcriptome-wide associations and analysis of existing literature suggest the estrogen receptor β-encoding gene ESR2 as one of the potential risk factors for both MDD and atopic diseases.ConclusionOur findings reveal shared genetic liability and causal links between MDD and atopic diseases, which shed light on the phenotypic relationship between MDD and atopic diseases.

scholarly journals Polygenic risk for severe psychopathology among Europeans is associated with major depressive disorder in Han Chinese women

2017 ◽  
Vol 48 (5) ◽  
pp. 777-789 ◽  
Author(s):  
A. C. Edwards ◽  
A. R. Docherty ◽  
A. Moscati ◽  
T. B. Bigdeli ◽  
R. E. Peterson ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Clinical Characteristics ◽  
Chinese Women ◽  
Well Being ◽  
Han Chinese ◽  
Major Depressive ◽  
Genetic Liability ◽  
Polygenic Risk ◽  
Shared Genetic

BackgroundPrevious studies have demonstrated that several major psychiatric disorders are influenced by shared genetic factors. This shared liability may influence clinical features of a given disorder (e.g. severity, age at onset). However, findings have largely been limited to European samples; little is known about the consistency of shared genetic liability across ethnicities.MethodThe relationship between polygenic risk for several major psychiatric diagnoses and major depressive disorder (MDD) was examined in a sample of unrelated Han Chinese women. Polygenic risk scores (PRSs) were generated using European discovery samples and tested in the China, Oxford, and VCU Experimental Research on Genetic Epidemiology [CONVERGE (maximumN= 10 502)], a sample ascertained for recurrent MDD. Genetic correlations between discovery phenotypes and MDD were also assessed. In addition, within-case characteristics were examined.ResultsEuropean-based polygenic risk for several major psychiatric disorder phenotypes was significantly associated with the MDD case status in CONVERGE. Risk for clinically significant indicators (neuroticism and subjective well-being) was also associated with case–control status. The variance accounted for by PRS for both psychopathology and for well-being was similar to estimates reported for within-ethnicity comparisons in European samples. However, European-based PRS were largely unassociated with CONVERGE family history, clinical characteristics, or comorbidity.ConclusionsThe shared genetic liability across severe forms of psychopathology is largely consistent across European and Han Chinese ethnicities, with little attenuation of genetic signal relative to within-ethnicity analyses. The overall absence of associations between PRS for other disorders and within-MDD variation suggests that clinical characteristics of MDD may arise due to contributions from ethnicity-specific factors and/or pathoplasticity.

Abstract P147: Genome Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases Using the UK Biobank Data

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Yanjun Guo ◽  
Wonil Chung ◽  
Zhilei Shan ◽  
Liming Liang
Keyword(s):  
Cardiovascular Diseases ◽  
Genetic Correlation ◽  
Multiple Testing ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Uk Biobank ◽  
Increased Risk ◽  
The Uk ◽  
Cardiovascular Traits ◽  
Shared Genetic

Background: Patients with RA have a 2-10 folds increased risk of cardiovascular diseases (CVD) and CVD accounts for almost 50% of the excess mortality in patients with RA when compared with general population, but the mechanisms underlying such associations are largely unknown. Methods: We examined the genetic correlation, causality, and shared genetic variants between RA (Ncase=6,756, Ncontrol=452,476) and CVD (Ncase=44,246, Ncontrol=414,986) using LD Score regression (LDSC), generalized summary-data-based Mendelian Randomization (GSMR), and cross-trait meta-analysis in the UK Biobank Data. Results: In the present study, RA was significantly genetically correlated with MI, angina, CHD, and CVD after correcting for multiple testing (Rg ranges from 0.40 to 0.43, P<0.05/5). Interestingly, when stratified by frequent usage of aspirin and paracetamol, we observed increased genetic correlation between RA and CVD for participants without aspirin usage ( Rg increased to 0.54 [95%CI: 0.54, 0.78] for angina; P value=6.69х10 -6 ), and for participants with usage of paracetamol ( Rg increased to 0.75 [95%CI: 0.20, 1.29] for MI; P value=8.90х10 -3 ). Cross-trait meta-analysis identified 9 independent loci that were shared between RA and at least one of the genetically correlated CVD traits including PTPN22 at chr1p13.2 , BCL2L11 at chr2q13 , and CCR3 at chr3p21.31 ( P single trait <1х10 -3 and P meta <5х10 -8 ) highlighting potential shared etiology between them which include accelerating atherosclerosis and upregulating oxidative stress and vascular permeability. Finally, Mendelian randomization analyses observed inconsistent instrumental effects and were unable to conclude the causality and directionality between RA and CVD. Conclusion: Our results supported positive genetic correlation between RA and multiple cardiovascular traits, and frequent usage of aspirin and paracetamol may modify their associations, but instrumental analyses were unable to conclude the causality and directionality between them.

Acute effects of single and repeated electroconvulsive therapy on plasma catecholamines and blood pressure in major depressive disorder

1990 ◽  
Vol 34 (2) ◽  
pp. 127-137 ◽  
Author(s):  
J.John Mann ◽  
Alan Z.A. Manevitz ◽  
Jaw-Sy Chen ◽  
Katherine S. Johnson ◽  
Erica F. Adelsheimer ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Electroconvulsive Therapy ◽  
Plasma Catecholamines ◽  
Acute Effects ◽  
Major Depressive

scholarly journals Major depressive disorder but not bipolar disorder and schizophrenia is a causal factor for type 2 diabetes as determined by Mendelian randomization

2020 ◽  
Author(s):  
Heejin Jin ◽  
Jeewon Lee ◽  
Oh Sohee ◽  
Sanghun Lee ◽  
Sungho Won
Keyword(s):  
Type 2 Diabetes ◽  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Reverse Causality ◽  
Major Depressive ◽  
Mr Study

Objective: In many epidemiologic studies, type 2 diabetes has been reported to be associated with severe mental illness (SMI) such as schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD). However, the relationship between SMI and type 2 diabetes is bi-directional, and the causal relationship remains unclear due to various confounders. Therefore, a Mendelian randomization (MR) study is necessary to identify the causality between them. Research Design and Methods: We conducted a two−sample MR study to identify the causal effect of SMI on type 2 diabetes using the inverse-variance weighted (IVW), MR−Egger, MR− Egger with a simulation extrapolation, weighted median approach, and MR-Pleiotropy RESidual Sum and Outlier methods. The most appropriate method was selected according to the instrument variables assumption. Results: We found that MDD had a significant causal effect on type 2 diabetes from the results obtained using the IVW method (Odds ratio (OR): 1.191, 95% CI: 1.036−1.372, P = 0.014); however, this was not observed for BPD (IVW, OR: 1.006, 95% CI: 0.918−1.104, P = 0.892) or SCZ (IVW, OR: 1.016, 95% CI: 0.974−1.059, P = 0.463). The absence of reverse-causality between MDD and type 2 diabetes was also demonstrated from bidirectional MR studies. Conclusions: These results clearly reveal important knowledge on the causal role of MDD in the risk of type 2 diabetes without a residual confounding, whereas the causality of BPD and SCZ was not shown. Therefore, careful attention should be paid to MDD patients in type 2 diabetes prevention and treatment.

scholarly journals Genetic and Environmental Contributions to The Association Between Violent Victimization and Major Depressive Disorder

2017 ◽  
Author(s):  
Nicholas Kavish ◽  
Eric J. Connolly ◽  
Brian B. Boutwell
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Violent Victimization ◽  
Major Depressive ◽  
Biometric Analysis ◽  
Sibling Pairs ◽  
Increased Risk ◽  
The Life Course ◽  
Shared Genetic ◽  
Half Sibling

AbstractResearch suggests victims of violent crime are more likely to suffer from major depressive disorder (MDD) compared to non-victims. Less research has utilized longitudinal data to evaluate the directionality of this relationship or examined the genetic and environmental contributions to this association across the life course. The current study evaluated 473 full-sibling pairs and 209 half-sibling pairs (N = 1,364) from the National Longitudinal Survey of Youth (Mage = 20.14, SD = 3.94). Cross-lagged models were used to examine the directionality of effects between violent victimization and MDD over time. Biometric liability models were used to examine genetic and environmental influences on single and chronic violent victimization and MDD. Violent victimization was associated with increases in MDD during late adolescence, but MDD was more associated with increased risk for violent victimization across young adulthood. Biometric analysis indicated that 20% and 30% of the association between MDD and single and chronic victimization, respectively, was accounted for by common genetic influences. Results from the current study suggest individuals who exhibit symptoms of MDD are at higher risk for chronic victimization rather than developing MDD as a result of victimization. Shared genetic liability accounted for between 20 to 30% of this longitudinal relationship.

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