Type 2 diabetes, glucose, insulin, BMI, and ischemic stroke subtypes: Mendelian randomization study.
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ABSTRACT: Objective
To implement a mendelian randomization (MR) approach to determine whether type 2 diabetes mellitus (T2D), fasting glucose, fasting insulin, and body mass index (BMI) are causally associated with specific ischemic stroke subtypes.Methods
MR estimates of the association between each possible risk factor and ischemic stroke subtypes were calculated with inverse-variance weighted (conventional) and weighted median approaches, and MR-Egger regression was used to explore pleiotropy. The number of single nucleotide polymorphisms (SNPs) used as instrumental variables was 49 for T2D, 36 for fasting glucose, 18 for fasting insulin, and 77 for BMI. Genome-wide association study data of SNP-stroke associations were derived from METASTROKE and the Stroke Genetics Network (n = 18,476 ischemic stroke cases and 37,296 controls).Results
Conventional MR analysis showed associations between genetically predicted T2D and large artery stroke (odds ratio [OR] 1.28, 95% confidence interval [CI] 1.16-1.40, p = 3.3 × 10-7) and small vessel stroke (OR 1.21, 95% CI 1.10-1.33, p = 8.9 × 10-5) but not cardioembolic stroke (OR 1.06, 95% CI 0.97-1.15, p = 0.17). The association of T2D with large artery stroke but not small vessel stroke was consistent in a sensitivity analysis using the weighted median method, and there was no evidence of pleiotropy. Genetically predicted fasting glucose and fasting insulin levels and BMI were not statistically significantly associated with any ischemic stroke subtype.Conclusions
This study provides support that T2D may be causally associated with large artery stroke.
SUBMITTER: Larsson SC
PROVIDER: S-EPMC5539736 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundType 2 diabetes (T2D) is a prevalent chronic disease associated with several comorbidities.ObjectivesThis study investigated whether the risk of T2D varied with genetically predicted insulin (INS), insulin receptor (INS-R), or insulin-like growth factor 1 receptor (IGF-1R) using genetic variants in a Mendelian randomization (MR) study.MethodsA 2-sample MR study was conducted using summary statistics from 2 genome-wide association studies (GWASs). Genetic predictors of the exposures (INS, INS-R, and IGF-1R) were obtained from a publicly available proteomics GWAS of the INTERVAL randomized controlled trial of blood donation in the United Kingdom. For T2D, the study leveraged the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium. The estimated associations of INS, INS-R, and IGF-1R proteins with T2D were based on independent single nucleotide polymorphisms (SNPs) strongly (P < 5 × 10-6) predicting each exposure. These SNPs were applied to publicly available genetic associations with T2D from the DIAMANTE case (n = 74,124) and control (n = 824,006) study of people of European descent. SNP-specific Wald estimates were meta-analyzed using inverse variance weighting with multiplicative random effects. Sensitivity analysis was conducted using the weighted median (WM) and MR-Egger.ResultsINS-R (based on 13 SNPs) was associated with a lower risk of T2D (OR: 0.95 per effect size; 95% CI: 0.92, 0.98; P = 0.001), with similar estimates from the WM and MR-Egger. Insulin (8 SNPs) and IGF-1R (10 SNPs) were not associated with T2D. However, 1 of the SNPs for INS-R was from the ABO blood group gene.ConclusionsThis study is consistent with a causally protective association of the INS-R with T2D. INS-R in RBCs regulates glycolysis and thus may affect their functionality and integrity. However, a pleiotropic effect via the blood group ABO gene cannot be excluded. The INS-R may be a target for intervention by repurposing existing therapeutics or otherwise to reduce the risk of T2D.
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