The effect of BMI and type 2 diabetes on socioeconomic status: a two-sample multivariable Mendelian randomization study

OBJECTIVE To assess the independent causal effect of BMI and type 2 diabetes (T2D) on socioeconomic outcomes applying two-sample Mendelian randomization (MR) analysis. RESEARCH DESIGN AND METHODS We carried out univariate and multivariate two-sample MR to jointly assess the effect BMI and T2D on socioeconomic outcomes. We used overlapping genome-wide significant single nucleotide polymorphisms (SNPs) for BMI and T2D as instrumental variables. Their causal impact on household income and regional deprivation was assessed using summary-level data from the UK Biobank. RESULTS In the univariate analysis, higher BMI was related with lower income (marginal effect of 1-SD increase in BMI [β=-0.092 (95% CI: -0.138; -0.047)] and higher deprivation [β=0.051 (95% CI: 0.022; 0.079)]. In the multivariate MR, the effect of BMI controlling for diabetes was slightly lower for income and deprivation. Diabetes was not associated with these outcomes. CONCLUSIONS High BMI, but not diabetes, shows a causal link with socioeconomic outcomes.

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The effect of BMI and type 2 diabetes on socioeconomic status: a two-sample multivariable Mendelian randomization study

10.2337/figshare.13348040 ◽

2021 ◽

Author(s):

Sara Pedron ◽

Christoph F Kurz ◽

Lars Schwettmann ◽

Michael Laxy

Keyword(s):

Type 2 Diabetes ◽

Mendelian Randomization ◽

Causal Effect ◽

Univariate Analysis ◽

Causal Link ◽

Marginal Effect ◽

Nucleotide Polymorphisms ◽

Socioeconomic Outcomes ◽

The Uk

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Clustered Mendelian Randomization analyses identifies distinct and opposing pathways in the causal association between insulin-like growth factor-1 and type 2 diabetes mellitus

10.1101/2021.05.12.21257093 ◽

2021 ◽

Author(s):

Wenyi Wang ◽

Ephrem Baraki Tesfay ◽

Ko Willems van Dijk ◽

Andrzej Bartke ◽

Diana van Heemst ◽

...

Keyword(s):

Type 2 Diabetes ◽

Growth Factor ◽

Mendelian Randomization ◽

Causal Effect ◽

Proportional Hazard ◽

Uk Biobank ◽

Heterogeneous Distribution ◽

Cox Proportional Hazard ◽

The Uk

Aims/hypothesis: There is inconsistent evidence for the causal role of serum insulin-like growth factor-1 (IGF-1) concentration in the pathogenesis of type 2 diabetes. Here, we investigated the association between IGF-1 and type 2 diabetes using a combination of multivariable-adjusted and (clustered) Mendelian Randomization (MR) analyses in the UK Biobank. Methods: We conducted Cox proportional hazard analyses in 451,232 European-ancestry individuals of the UK Biobank (55.3% women, mean age at recruitment 56.6 years), among which 13,247 individuals developed type 2 diabetes during up to 12 years of follow-up. In addition, we conducted two-sample MR analyses based on independent SNPs associated with IGF-1. Given the heterogeneity between the causal estimates of individual instruments (P-value for Q statistic=4.03e-145), we also conducted clustered MR analyses. Biological pathway analyses of the identified clusters were performed by overrepresentation analyses. Results: In the Cox proportional hazard models, with IGF-1 concentrations stratified in quintiles, we observed that participants in the lowest quintile had the highest relative risk of type 2 diabetes (HR: 1.31; CI: 1.23-1.39). In contrast, in the two-sample MR analyses, higher genetically-influenced IGF-1 was associated with a higher risk of type 2 diabetes. Based on the heterogeneous distribution of causal effect estimates, six clusters associated either with a lower or a higher risk of type 2 diabetes were identified. The main clusters in which a higher IGF-1 was associated with a lower risk of type 2 diabetes consisted of instruments mapping to genes in the growth-hormone signaling pathway, whereas the main clusters in which a higher IGF-1 was associated with a higher risk of type 2 diabetes consisted of instruments mapping to genes in pathways related to amino acid metabolism and genomic integrity. Conclusion: The IGF-1 associated SNPs used as genetic instruments in MR analyses showed a heterogeneous distribution of causal effect estimates on the risk of type 2 diabetes. This was likely explained by differences in the underlying molecular pathways that increase IGF-1 concentration and differentially mediate the effects of IGF-1 on type 2 diabetes.

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Effect of metabolites levels on type 2 diabetes mellitus and glycemic traits: a Mendelian randomization study

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgab581 ◽

2021 ◽

Author(s):

Yue Sun ◽

Ya-Ke Lu ◽

Hao-Yu Gao ◽

Yu-Xiang Yan

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Mendelian Randomization ◽

Causal Effect ◽

Meta Analysis ◽

Significance Level ◽

Inverse Variance ◽

Meta Analyses

Abstract Objective To assess the causal associations of plasma levels of metabolites with type 2 diabetes mellitus (T2DM) and glycemic traits. Methods Two-sample mendelian randomization (MR) was conducted to assess the causal associations. Genetic variants strongly associated with metabolites at genome-wide significance level (P < 5 × 10 −8) were selected from public GWAS, and SNPs of Outcomes were obtained from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium for T2DM and from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) for the fasting glucose, insulin and HbA1c. The Wald ratio and inverse-variance weighted methods were used for analyses, and MR-Egger was used for sensitivity analysis. Results The β estimates per 1 SD increasement of arachidonic acid (AA) level was 0.16 (95% CI: 0.078, 0.242; P<0.001). Genetic predisposition to higher plasma AA levels were associated with higher FG levels (β 0.10 [95%CI: 0.064, 0.134], P<0.001), higher HbA1c levels (β 0.04 [95%CI: 0.027, 0.061]) and lower FI levels (β -0.025 [95%CI: -0.047, -0.002], P=0.033). Besides, 2-hydroxybutyric acid (2-HBA) might have positive causal effect on glycemic traits. Conclusions Our findings suggest that AA and 2-HBA may have the causal associations on T2DM and glycemic traits. It is beneficial for clarifying the pathogenesis of T2DM, which would be valuable for early identification and prevention for T2DM.

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Corrigendum: Exposing the Causal Effect of C-Reactive Protein on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study

Frontiers in Genetics ◽

10.3389/fgene.2019.00085 ◽

2019 ◽

Vol 10 ◽

Cited By ~ 1

Author(s):

Liang Cheng ◽

He Zhuang ◽

Shuo Yang ◽

Huijie Jiang ◽

Song Wang ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Mendelian Randomization ◽

Causal Effect ◽

C Reactive Protein ◽

Reactive Protein

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Exposing the Causal Effect of C-Reactive Protein on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study

Frontiers in Genetics ◽

10.3389/fgene.2018.00657 ◽

2018 ◽

Vol 9 ◽

Cited By ~ 37

Author(s):

Liang Cheng ◽

He Zhuang ◽

Shuo Yang ◽

Huijie Jiang ◽

Song Wang ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Mendelian Randomization ◽

Causal Effect ◽

C Reactive Protein ◽

Reactive Protein

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Pancreatic beta-cell function and type 2 diabetes risk: quantify the causal effect using a Mendelian randomization approach based on meta-analyses

Human Molecular Genetics ◽

10.1093/hmg/dds339 ◽

2012 ◽

Vol 21 (22) ◽

pp. 5010-5018 ◽

Cited By ~ 14

Author(s):

Yiqing Song ◽

Edwina Yeung ◽

Aiyi Liu ◽

Tyler J. VanderWeele ◽

Liwei Chen ◽

...

Keyword(s):

Type 2 Diabetes ◽

Beta Cell ◽

Beta Cell Function ◽

Cell Function ◽

Mendelian Randomization ◽

Causal Effect ◽

Pancreatic Beta Cell ◽

Meta Analyses ◽

Pancreatic Beta Cell Function

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

10.1101/2020.09.12.20193060 ◽

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.

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Roles of Cardiometabolic Factors in Mediating the Causal Effect of Type 2 Diabetes on Cardiovascular Diseases: A Two-Step, Two-Sample Multivariable Mendelian Randomization Study

10.21203/rs.3.rs-1019305/v1 ◽

2021 ◽

Author(s):

Ken Chen ◽

Zhenhuang Zhuang ◽

Chunli Shao ◽

Jilin Zheng ◽

Qing Zhou ◽

...

Keyword(s):

Blood Pressure ◽

Type 2 Diabetes ◽

Blood Lipids ◽

Mendelian Randomization ◽

Causal Effect ◽

Density Lipoprotein ◽

Mediation Effect ◽

Mediation Effects ◽

Cardiometabolic Factors

Abstract ObjectivesTo investigate the roles of cardiometabolic factors (including blood pressure, blood lipids, thyroid function, body mass, and insulin sensitivity) in mediating the causal effect of type 2 diabetes (T2DM) on cardiovascular disease (CVD) outcomes. DesignTwo-step, two-sample multivariable Mendelian randomization (MVMR) study.SettingInternational genome-wide association study (GWAS) consortia data.ExposureT2DM, blood pressure: systolic blood pressure (SBP), diastolic blood pressure (DBP); blood lipids: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), triglycerides (TG); thyroid function: hyperthyroidism, hypothyroidism; body mass index (BMI), waist-hip-ratio (WHR), and insulin sensitivity. Main outcomesCVD including coronary heart disease (CHD), myocardial infarction (MI) and stroke.MethodsSummary-level data for exposures and main outcomes were extracted from GWAS consortia. We used two-sample MR to illustrate the causal effect of T2DM on CVD subtypes and regression-based MVMR to quantify the possible mediation effects of cardiometabolic factors on CVD.ResultsEach additional unit of log odds of T2DM increased 16% risk of CHD [OR: 1.16, 95% confidence interval (CI): 1.12-1.21], 15% risk of MI (OR: 1.15, 95%CI: 1.10-1.20), and 10% risk of stroke (OR: 1.10, 95%CI: 1.06-1.13). In mediation analysis, SBP, DBP and TG were found as main mediators, while the mediation effects of other cardiometabolic factors were not significant. The proportion of total effect of T2DM on CHD mediated by SBP, DBP and TG was 16% (95%CI: 8%-24%), 7% (95%CI: 1%-13%) and 10% (95%CI: 2%-18%), respectively. Mediation effect of SBP and DBP on MI and stroke, TG on MI was also prominent, while mediation effect of TG on stroke was not significant. Combined mediation effect of all three mediators accounted for 29%, 26% and 13% of total effect of T2DM on CHD, MI and stroke, respectively.ConclusionSBP, DBP and TG mediate a substantial proportion of the causal effect of T2DM on CVD and thus interventions on these factors might reduce considerable excess risk of CVD among T2DM patients.

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Alcohol use and cardiometabolic risk in the UK Biobank: a Mendelian randomization study

10.1101/2020.11.10.376400 ◽

2020 ◽

Author(s):

Joanna Lankester ◽

Daniela Zanetti ◽

Erik Ingelsson ◽

Themistocles L. Assimes

Keyword(s):

Type 2 Diabetes ◽

Alcohol Consumption ◽

Alcohol Use ◽

Mendelian Randomization ◽

Lower Amount ◽

Cardiometabolic Health ◽

Uk Biobank ◽

The Uk ◽

Cardiometabolic Traits

AbstractObservational studies suggest alcohol use promotes the development of some adverse cardiometabolic traits but protects against others including outcomes related to coronary artery disease. We used Mendelian randomization to explore causal relationships between the degree of alcohol consumption and several cardiometabolic traits in the UK Biobank. We found carriers of the ADH1B Arg47His variant (rs1229984) reported a 26% lower amount of alcohol consumption compared to non-carriers. In our one-sample, two-stage least squares analyses of the UK Biobank using rs1229984 as an instrument, one additional drink/day was associated with statistically significant elevated level of systolic blood pressure (3.0 mmHg), body mass index (0.87 kg/m^2), waist circumference (1.3 cm), body fat percentage (1.7%), low-density lipoprotein levels in blood (0.16 mmol/L), and the risk of myocardial infarction (OR=1.50), stroke (OR=1.52), any cardiovascular disease (OR=1.43), and all-cause mortality (OR=1.41). Conversely, increasing use of alcohol was associated with reduced levels of triglycerides (−0.059 mmol/L) and HbA1C (−0.42 mmol/mol) in the blood, the latter possibly a consequence of a statistically elevated mean corpuscular volume among ADH1B Arg47His carriers. Stratifications by sex and smoking revealed a pattern of more harm of alcohol use among men compared to women, but no consistent difference by smoking status. Men had an increased risk of heart failure (OR = 1.76), atrial fibrillation (OR = 1.35), and type 2 diabetes (OR = 1.31) per additional drink/day. Using summary statistics from external datasets in 2-sample analyses for replication, we found causal associations between alcohol and obesity, stroke, ischemic stroke, and type 2 diabetes. Our results are consistent with an overall harmful effect of alcohol on cardiometabolic health at all levels of use and suggest that even moderate alcohol use should not be promoted as a part of a healthy diet and lifestyle.

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