Dataset Information

No Evidence of a Causal Relationship between Plasma Homocysteine and Type 2 Diabetes: A Mendelian Randomization Study.

ABSTRACT: BACKGROUND:Several observational studies have shown an association between increased circulating homocysteine and risk of type 2 diabetes (T2D). We aimed to assess whether this relation is causal using genetic data from large populations of individuals of European descent. METHODS:We investigated the association between homocysteine concentrations and blood glucose, plasma insulin, T2D in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) cohort (n?=?1,016). A score of five previously published single nucleotide polymorphisms (SNPs) from genes involved in homocysteine metabolism were utilized as genetic instrument for homocysteine concentrations. The effect estimate of this genetic score with T2D was determined using results from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (including 34,840 cases and 114,981 controls). Further, the effects of the genetic score with fasting glucose and insulin were determined using results from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) (up to 38,238 non-diabetic participants). RESULTS:The genetic score provided a strong instrument for homocysteine concentrations (P?=?2.7?×?10(-143), F?=?650). In the PIVUS cohort, we found an association of homocysteine with fasting insulin [??=?0.056 (95% CI 0.021, 0.090), P?=?0.001], but not with incident diabetes. We did not find any evidence of a causal effect of homocysteine on fasting glucose, fasting insulin, or T2D (P?>?0.05 for all analyses) when using data from DIAGRAM or MAGIC studies. CONCLUSION:No evidence of a causal relationship of levels of plasma homocysteine with fasting glucose, fasting insulin, or T2D was observed.

SUBMITTER: Kumar J

PROVIDER: S-EPMC4671343 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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No Evidence of a Causal Relationship between Plasma Homocysteine and Type 2 Diabetes: A Mendelian Randomization Study.

Kumar Jitender J Ingelsson Erik E Lind Lars L Fall Tove T

Frontiers in cardiovascular medicine 20150305

<h4>Background</h4>Several observational studies have shown an association between increased circulating homocysteine and risk of type 2 diabetes (T2D). We aimed to assess whether this relation is causal using genetic data from large populations of individuals of European descent.<h4>Methods</h4>We investigated the association between homocysteine concentrations and blood glucose, plasma insulin, T2D in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) cohort (n = 1,016 ...[more]

PMID: 26664883

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Project description:BackgroundsMany studies have shown particulate matter has emerged as one of the major environmental risk factors for diabetes; however, studies on the causal relationship between particulate matter 2.5 (PM2.5) and diabetes based on genetic approaches are scarce. The study estimated the causal relationship between diabetes and PM2.5 using two sample mendelian randomization (TSMR).MethodsWe collected genetic data from European ancestry publicly available genome wide association studies (GWAS) summary data through the MR-BASE repository. The IEU GWAS information output PM2.5 from the Single nucleotide polymorphisms (SNPs) GWAS pipeline using pheasant-derived variables (Consortium = MRC-IEU, sample size: 423,796). The annual relationship of PM2.5 (2010) were modeled for each address using a Land Use Regression model developed as part of the European Study of Cohorts for Air Pollution Effects. Diabetes GWAS information (Consortium = MRC-IEU, sample size: 461,578) were used, and the genetic variants were used as the instrumental variables (IVs). We performed three representative Mendelian Randomization (MR) methods: Inverse Variance Weighted regression (IVW), Egger, and weighted median for causal relationship using genetic variants. Furthermore, we used a novel method called MR Mixture to identify outlier SNPs.ResultsFrom the IVW method, we revealed the causal relationship between PM2.5 and diabetes (Odds ratio [OR]: 1.041, 95% CI: 1.008-1.076, P = 0.016), and the finding was substantiated by the absence of any directional horizontal pleiotropy through MR-Egger regression (β = 0.016, P = 0.687). From the IVW fixed-effect method (i.e., one of the MR machine learning mixture methods), we excluded outlier SNP (rs1537371) and showed the best predictive model (AUC = 0.72) with a causal relationship between PM2.5 and diabetes (OR: 1.028, 95% CI: 1.006-1.049, P = 0.012).ConclusionWe identified the hypothesis that there is a causal relationship between PM2.5 and diabetes in the European population, using MR methods.

Project description:Type 2 diabetes (T2D) frequently co-occurs with respiratory system diseases such as chronic obstructive pulmonary disease (COPD), bronchial asthma, lung cancer, interstitial lung disease, and pulmonary tuberculosis. Although a potential association is noted between these conditions, the available research is limited. To investigate the causal relationship between patients with T2D and respiratory system diseases using two-sample Mendelian randomization analysis. Causal relationships were inferred using a two-sample Mendelian randomization (MR) analysis based on publicly available genome-wide association studies. We employed the variance inverse-weighted method as the primary analytical approach based on three key assumptions underlying MR analysis. To bolster the robustness and reliability of our results, we utilized MR Egger's intercept test to detect potential pleiotropy, Cochran's Q test to assess heterogeneity, funnel plots to visualize potential bias, and "leave-one-out" sensitivity analysis to ensure that our findings were not unduly influenced by any single genetic variant. The inverse variance weighted (IVW) analysis indicated a causal relationship between T2D and COPD [Odds Ratio (OR) = 0.87; 95% Confidence Interval (CI) = 0.82-0.96; p < 0.05]. No significant heterogeneity or pleiotropy were observed through their respective tests (p > 0.05), and the statistical power calculations indicated that the results were reliable. The IVW analysis showed a negative causal relationship between T2D and bronchial asthma [OR = 0.85; 95% CI = 0.81-0.89; p < 0.05]. However, the IVW under the random-effects model indicated heterogeneity (p < 0.05), suggesting instability in the results and requiring cautious interpretation. The study found a positive causal relationship between T2D and pulmonary tuberculosis (OR = 1.24, 95% CI = 1.05-1.45, p < 0.05). However, they exhibited pleiotropy (p < 0.05), indicating their instability. No correlation between T2D and interstitial lung disease or lung cancer was observed. T2D is negatively associated with COPD, suggesting that T2D may reduce the risk of developing COPD. A negative causal relationship between T2D and bronchial asthma has been observed, but the results exhibit heterogeneity. There is a positive causal relationship between T2D and pulmonary tuberculosis, yet the findings suggest the presence of pleiotropy. No significant causal relationship between T2D and lung cancer or interstitial lung disease was observed.

Dataset Information

No Evidence of a Causal Relationship between Plasma Homocysteine and Type 2 Diabetes: A Mendelian Randomization Study.

Publications

No Evidence of a Causal Relationship between Plasma Homocysteine and Type 2 Diabetes: A Mendelian Randomization Study.

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