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 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 Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium

2019 ◽  
Vol 49 (07) ◽  
pp. 1218-1226 ◽  
Author(s):  
Renato Polimanti ◽  
Roseann E. Peterson ◽  
Jue-Sheng Ong ◽  
Stuart MacGregor ◽  
Alexis C. Edwards ◽  
...  
Keyword(s):  
Major Depression ◽  
Alcohol Dependence ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Causal Effect ◽  
Uk Biobank ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Genetic Mechanisms ◽  
Shared Genetic

AbstractBackgroundDespite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.MethodsLinkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).ResultsPositive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.ConclusionThis study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

scholarly journals The putative causal effect of type 2 diabetes in risk of cataract: a Mendelian randomization study in East Asian

2021 ◽  
Author(s):  
Haoyang Zhang ◽  
Xuehao Xiu ◽  
Angli Xue ◽  
Yuedong Yang ◽  
Yuanhao Yang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Correlation ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Population Based ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractBackgroundThe epidemiological association between type 2 diabetes and cataract has been well-established. However, it remains unclear whether the two diseases share a genetic basis, and if so, whether this reflects a causal relationship.MethodsWe utilized East Asian population-based genome-wide association studies (GWAS) summary statistics of type 2 diabetes (Ncase=36,614, Ncontrol=155,150) and cataract (Ncase=24,622, Ncontrol=187,831) to comprehensively investigate the shared genetics between the two diseases. We performed 1. linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (ρ-HESS) to estimate the genetic correlation and local genetic correlation between type 2 diabetes and cataract; 2. multiple Mendelian randomization (MR) analyses to infer the putative causality between type 2 diabetes and cataract; and 3. Summary-data-based Mendelian randomization (SMR) to identify candidate risk genes underling the causality.ResultsWe observed a strong genetic correlation (rg=0.58; p-value=5.60×10−6) between type 2 diabetes and cataract. Both ρ-HESS and multiple MR methods consistently showed a putative causal effect of type 2 diabetes on cataract, with estimated liability-scale MR odds ratios (ORs) at around 1.10 (95% confidence interval [CI] ranging from 1.06 to 1.17). In contrast, no evidence supports a causal effect of cataract on type 2 diabetes. SMR analysis identified two novel genes MIR4453HG (βSMR=−0.34, p-value=6.41×10−8) and KCNK17 (βSMR=−0.07, p-value=2.49×10−10), whose expression levels were likely involved in the putative causality of type 2 diabetes on cataract.ConclusionsOur results provided robust evidence supporting a causal effect of type 2 diabetes on the risk of cataract in East Asians, and posed new paths on guiding prevention and early-stage diagnosis of cataract in type 2 diabetes patients.Key MessagesWe utilized genome-wide association studies of type 2 diabetes and cataract in a large Japanese population-based cohort and find a strong genetic overlap underlying the two diseases.We performed multiple Mendelian randomization models and consistently disclosed a putative causal effect of type 2 diabetes on the development of cataract.We revealed two candidate genes MIR4453HG and KCNK17 whose expression levelss are likely relevant to the causality between type 2 diabetes and cataract.Our study provided theoretical fundament at the genetic level for improving early diagnosis, prevention and treatment of cataract in type 2 diabetes patients in clinical practice

scholarly journals Using multivariable Mendelian randomization to estimate the causal effect of bone mineral density on osteoarthritis risk, independent of body mass index

2021 ◽  
Author(s):  
April Hartley ◽  
Eleanor Sanderson ◽  
Raquel Granell ◽  
Lavinia Paternoster ◽  
Jie Zheng ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Body Mass Index ◽  
Genetic Correlation ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Mineral Density ◽  
Knee Oa ◽  
Causal Pathways ◽  
Causal Pathway ◽  
Shared Genetic

AbstractObjectivesObservational analyses suggest that high Bone Mineral Density (BMD) is a risk factor for osteoarthritis (OA); it’s unclear whether this represents a causal effect or shared aetiology and whether these relationships are body mass index (BMI)-independent. We performed bidirectional Mendelian randomization (MR) to uncover the causal pathways between BMD, BMI and OA.MethodsOne-sample (1S)MR estimates were generated by two-stage least-squares regression. Unweighted allele scores instrumented each exposure. Two-sample (2S)MR estimates were generated using inverse-variance weighted fixed-effects meta-analysis. Multivariable MR (MVMR), including BMD and BMI instruments in the same model, determined the BMI-independent causal pathway from BMD to OA. Latent causal variable (LCV) analysis, using weight-adjusted FN-BMD and hip/knee OA summary statistics, determined if genetic correlation explained the causal effect of BMD on OA.Results1SMR provided strong evidence for a causal effect of eBMD on hip and knee OA (ORhip =1.28[1.05,1.57],p=0.02, ORknee =1.40[1.20,1.63],p=3×10−5, OR per SD increase). 2SMR effect sizes were consistent in direction. Results suggested that the causal pathways between eBMD and OA were bidirectional (βhip=1.10[0.36,1.84],p=0.003, β knee =4.16[2.74,5.57],p=8×10−9, β=SD increase per doubling in risk). MVMR identified a BMI-independent causal pathway between eBMD and hip/knee OA. LCV suggested that genetic correlation (i.e. shared genetic aetiology) did not fully explain causal effects of BMD on hip/knee OA.ConclusionsThese results provide evidence for a BMI-independent causal effect of eBMD on OA. Despite evidence of bidirectional effects, the effect of BMD on OA did not appear to be fully explained by shared genetic aetiology, suggesting a direct action of bone on joint deterioration.

scholarly journals Dairy Intake and Body Composition and Cardiometabolic Traits among Adults: Mendelian Randomization Analysis of 182041 Individuals from 18 Studies

2019 ◽  
Vol 65 (6) ◽  
pp. 751-760 ◽  
Author(s):  
◽  
◽  
Tao Huang ◽  
Dianjianyi Sun ◽  
Yoriko Heianza ◽  
...  
Keyword(s):  
Body Composition ◽  
Lean Mass ◽  
Multiple Testing ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Inflammatory Factors ◽  
Dairy Intake ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis ◽  
Cardiometabolic Traits

Abstract BACKGROUND Associations between dairy intake and body composition and cardiometabolic traits have been inconsistently observed in epidemiological studies, and the causal relationship remains ill-defined. METHODS We performed Mendelian randomization analysis using an established genetic variant located upstream of the lactase gene (LCT-13910 C/T, rs4988235) associated with dairy intake as an instrumental variable (IV). The causal effects of dairy intake on body composition and cardiometabolic traits (lipids, glycemic traits, and inflammatory factors) were quantified by IV estimators among 182041 participants from 18 studies. RESULTS Each 1 serving/day higher dairy intake was associated with higher lean mass [β (SE) = 0.117 kg (0.035); P = 0.001], higher hemoglobin A1c [0.009% (0.002); P < 0.001], lower LDL [−0.014 mmol/L (0.006); P = 0.013], total cholesterol (TC) [−0.012 mmol/L (0.005); P = 0.023], and non-HDL [−0.012 mmol/L (0.005); P = 0.028]. The LCT-13910 C/T CT + TT genotype was associated with 0.214 more dairy servings/day (SE = 0.047; P < 0.001), 0.284 cm higher waist circumference (SE = 0.118; P = 0.017), 0.112 kg higher lean mass (SE = 0.027; P = 3.8 × 10−5), 0.032 mmol/L lower LDL (SE = 0.009; P = 0.001), and 0.032 mmol/L lower TC (SE = 0.010; P = 0.001). Genetically higher dairy intake was associated with increased lean mass [0.523 kg per serving/day (0.170); P = 0.002] after correction for multiple testing (0.05/18). However, we find that genetically higher dairy intake was not associated with lipids and glycemic traits. CONCLUSIONS The present study provides evidence to support a potential causal effect of higher dairy intake on increased lean mass among adults. Our findings suggest that the observational associations of dairy intake with lipids and glycemic traits may be the result of confounding.

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 Sex differences in the risk of cataract associated with type 2 diabetes: a Mendelian randomization study

2021 ◽  
Author(s):  
Haoyang Zhang ◽  
Xuehao Xiu ◽  
Yuedong Yang ◽  
Yuanhao Yang ◽  
Huiying Zhao
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
East Asian ◽  
P Value ◽  
East Asians ◽  
Confident Interval ◽  
Significant Genetic Correlation

Type 2 diabetes (T2D) is a recognized risk factor for developing cataract. However, it is unclear if the shared genetic variance and potential genetic causal relationship between T2D and cataract are different for males and females. We evaluated sex-specific genetic correlation (rg) and putative genetic causality between the two diseases by using linkage disequilibrium score regression (LDSC) and six Mendelian randomization (MR) approaches after lever-aging large-scale population-based genome-wide association studies (GWAS) summary of T2D and cataract. Application of LDSC found a significant genetic correlation between T2D and cataract in East Asian males (rg=0.68, 95% confident interval [CI]=0.17 to 1, p-value=8.60e-3) but a non-significant genetic correlation in East Asian females (rg=0.25, CI= -0.02 to 0.52, p-value=8.38e-2). MR analyses indicated a consistently stronger (paired t-test |t|=5.87, p-value=2.04e-3) causal effect of T2D on cataract in East Asian males (liability OR=1.20 to 1.41, p-value=5.86e-27 to 6.60e-6) than in females (liability OR=1.12 to 1.21, p-value=2.02e-14 to 1.82e-2). In Europeans, the LDSC analysis suggested a close significant genetic correlation between the two diseases in males (rg=0.20, 95% confident interval [CI]=0.08 to 0.32, p-value=7.00e-4) and females (rg=0.17, CI= 0.05 to 0.29, p-value=4.90e-3); but the MR analyses provided weak evidences on a causal relationship between the two diseases in both sexes. These results presented the first evidence on sex difference of the casual relationship between cataract and T2D in East Asians, and supported a potential genetic heterogeneity of the shared genetics underlying T2D and cataract between East Asians and Europeans in both sexes.

scholarly journals No Causal Association Between Adiponectin and the Risk of Rheumatoid Arthritis: A Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Hanzhu Chen ◽  
Shuai Mi ◽  
Jiahao Zhu ◽  
Weidong Jin ◽  
Yasong Li ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Genetic Correlation ◽  
Causal Relationship ◽  
Large Scale ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Reverse Direction ◽  
Genome Wide Association Studies

Background: Accumulating evidence from observational studies suggested that circulating adiponectin levels are associated with the risk of rheumatoid arthritis (RA), but the causality remains unknown. We aimed to assess the causal relationship of adiponectin with RA risk.Methods: Based on summary statistics from large-scale genome-wide association studies (GWAS), we quantified the genetic correlation between adiponectin and RA. Then bidirectional Mendelian randomization (MR) analysis was performed to assess the causal relationship. Twenty single-nucleotide polymorphisms (SNPs) associated with adiponectin were selected as instrumental variables from a recent GWAS (n = 67,739). We applied theses SNPs to a large-scale GWAS for RA (14,361 cases and 43,923 controls) with replication using RA data from the FinnGen consortium (6,236 cases and 147,221 controls) and the UK Biobank (5,201 cases and 457,732 controls). The inverse-variance weighted (IVW) and multiple pleiotropy-robust methods were used for two-sample MR analyses.Results: Our analyses showed no significant genetic correlation between circulating adiponectin levels and RA [rG = 0.127, 95% confidence interval (CI): –0.012 to 0.266, P = 0.074]. In MR analyses, genetically predicted adiponectin levels were not significantly associated with the RA risk (odds ratio: 0.98, 95% CI: 0.88–1.09, P = 0.669). In the reverse direction analysis, there is little evidence supporting an association of genetic susceptibility to RA with adiponectin (β: 0.007, 95% CI: –0.003 to 0.018, P = 0.177). Replication analyses and sensitivity analyses using different models yielded consistent results.Conclusions: Our findings provided no evidence to support the causal effect of adiponectin levels on RA risk and of RA on circulating adiponectin levels.

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