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 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 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 Causal Relationship Between Coffee Intake and Cardiometabolic Risks: Cross-Phenotype Association And Mendelian Randomization Analysis

2020 ◽  
Author(s):  
Xinpei Wang ◽  
Jinzhu Jia ◽  
Tao Huang
Keyword(s):  
Genetic Structure ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
P Value ◽  
Coffee Intake ◽  
Randomization Analysis ◽  
Cardiometabolic Traits ◽  
Shared Genetic

Abstract Background: Many epidemiological studies have shown that there is a significant association between coffee intake and cardiometabolic diseases, which may be due to the common genetic structure or causal relationship. Methods: We used linkage disequilibrium score regression analysis to calculate the genetic correlation between coffee intake and 23 cardiometabolic traits (diseases), and then used cross-phenotype association analysis to identify the shared genetic loci for the trait pairs with significant genetic correlation. Besides, a bi-directional Mendelian Randomization analysis was used to explore the causal relationship between coffee intake and 23 cardiometabolic traits (diseases).Results: Coffee intake has a significant genetic correlation (after Bonferroni correction) with body mass index (BMI) (Rg = 0.3713, P-value = 4.13ⅹ10-64), body fat percentage (BF%) (Rg = 0.2810, P-value = 1.81ⅹ10-13), type 2 diabetes (T2D) (unadjusted for BMI) (Rg = 0.1189, P-value = 8.80ⅹ10-6), heart failure (HF) (Rg = 0.2626, P-value = 6.00ⅹ10-9), atrial fibrillation (AF) (Rg = 0.1007, P-value = 4.30ⅹ10-5). There are 203, 18, 86, 13, 38 independent shared loci between coffee intake and BMI, BF%, T2D, HF, AF, respectively, among which 22, 2, 23, 4,13 loci do not achieve genome-wide significance in single trait GWAS. Coffee intake has significant causal effect on BMI (b = 0.0717, P-value = 2.33ⅹ10-5), T2D (unadjusted for BMI, OR = 1.27, P-value = 1.46ⅹ10-7), and intracerebral haemorrhage (ICH) (all types ICH: OR = 1.86, P-value = 3.37ⅹ10-4; deep ICH: OR = 2.12, P-value = 2.93ⅹ10-4 ). And BMI (b = 0.3694, P-value=3.64ⅹ10-154), BF% (b = 0.5500, P-value = 1.68ⅹ10-4), T2D (adjusted for BMI, b = -0.0252, P-value = 4.83ⅹ10-6) and triglycerides (TG) (b = -0.1209, P-value = 4.56ⅹ10-15) have significant causal effect on coffee intake.Conclusions: Our study identified the shared genetic structure and causal relationship between coffee intake and several cardiometabolic traits (diseases), providing a new insight into the mechanism of coffee intake and cardiometabolic traits (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.

scholarly journals Disentangling causal relationships between inflammatory markers and depression: a bidirectional Mendelian randomization analysis

2019 ◽  
Author(s):  
Christina Dardani ◽  
James Yarmolinsky ◽  
Jamie Robinson ◽  
Jie Zheng ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Interleukin 6 ◽  
Inflammatory Markers ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Reverse Direction ◽  
Causal Relationships ◽  
Limited Evidence ◽  
Major Depressive

AbstractBackgroundThe inflammatory markers C-reactive protein (CRP), interleukin-1 receptor antagonist (IL1-Ra), and interleukin-6 (IL-6) have been associated with depression risk in observational studies. The causal nature of these associations is unclear as conventional observational designs are susceptible to reverse causation and residual confounding. Bidirectional Mendelian randomization (MR) analysis uses genetic variants to proxy for risk factors to help elucidate the presence, magnitude, and direction of causal relationships between traits.MethodsWe performed bidirectional two-sample MR to examine causal associations between circulating CRP, IL1-Ra, and IL-6 and major depressive disorder (MDD) in 135,458 cases and 344,901 controls in the Psychiatric Genetics Consortium. Genetic instruments to proxy inflammatory markers and liability to MDD were constructed by obtaining single-nucleotide polymorphisms (SNPs) associated with these phenotypes in genome-wide association study meta-analyses. Wald ratios and inverse-variance weighted random-effects models were employed to generate causal effect estimates and various sensitivity analyses were performed to examine violations of MR assumptions.ResultsThere was evidence supporting a causal effect of circulating IL-6 on risk of MDD (per natural-log increase: OR 0.85, 95% CI: 0.75-0.96, P=0.007). Higher circulating levels of IL-6 as influenced by variants in the IL6R gene region represent lower cellular binding of IL-6 to its receptor and therefore the present results suggest that IL-6 increases the risk of MDD. We found limited evidence supporting a causal effect of CRP (1.06, 95% CI 0.93-1.22; P=0.36) or IL1-Ra (OR 0.95, 95% CI: 0.87-1.03, P=0.20) on risk of MDD. Reverse direction MR analyses suggested limited evidence for a causal effect of genetic liability to MDD on any of the inflammatory markers examined.ConclusionsThese findings support a causal role of IL-6-related pathways in development of major depressive disorder and suggest the possible efficacy of interleukin-6 inhibition as a therapeutic target for depression.

scholarly journals Investigating regions of shared genetic variation in attention deficit/hyperactivity disorder and major depressive disorder: a GWAS meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Victoria Powell ◽  
Joanna Martin ◽  
Anita Thapar ◽  
Frances Rice ◽  
Richard J. L. Anney
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genetic Correlation ◽  
Attention Deficit ◽  
Meta Analysis ◽  
Major Depressive ◽  
Hyperactivity Disorder ◽  
High Level ◽  
Genomic Regions

AbstractAttention deficit/hyperactivity disorder (ADHD) demonstrates a high level of comorbidity with major depressive disorder (MDD). One possible contributor to this is that the two disorders show high genetic correlation. However, the specific regions of the genome that may be responsible for this overlap are unclear. To identify variants associated with both ADHD and MDD, we performed a meta-analysis of GWAS of ADHD and MDD. All genome wide significant (p < 5 × 10–8) SNPs in the meta-analysis that were also strongly associated (p < 5 × 10–4) independently with each disorder were followed up. These putatively pleiotropic SNPs were tested for additional associations across a broad range of phenotypes. Fourteen linkage disequilibrium-independent SNPs were associated with each disorder separately (p < 5 × 10–4) and in the cross-disorder meta-analysis (p < 5 × 10–8). Nine of these SNPs had not been highlighted previously in either individual GWAS. Evidence supported nine of the fourteen SNPs acting as eQTL and two as brain eQTL. Index SNPs and their genomic regions demonstrated associations with other mental health phenotypes. Through conducting meta-analysis on ADHD and MDD only, our results build upon the previously observed genetic correlation between ADHD and MDD and reveal novel genomic regions that may be implicated in this overlap.

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