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. 2015 May 28:6:7060.
doi: 10.1038/ncomms8060.

A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease

Omar S Ahmad  1 , John A Morris  2 , Muhammad Mujammami  1 , Vincenzo Forgetta  1 , Aaron Leong  3 , Rui Li  4 , Maxime Turgeon  5 , Celia M T Greenwood  5 , George Thanassoulis  6 , James B Meigs  3 , Robert Sladek  6 , J Brent Richards  7
Affiliations

A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease

Omar S Ahmad et al. Nat Commun. .

Abstract

In observational studies, type-2 diabetes (T2D) is associated with an increased risk of coronary heart disease (CHD), yet interventional trials have shown no clear effect of glucose-lowering on CHD. Confounding may have therefore influenced these observational estimates. Here we use Mendelian randomization to obtain unconfounded estimates of the influence of T2D and fasting glucose (FG) on CHD risk. Using multiple genetic variants associated with T2D and FG, we find that risk of T2D increases CHD risk (odds ratio (OR)=1.11 (1.05-1.17), per unit increase in odds of T2D, P=8.8 × 10(-5); using data from 34,840/114,981 T2D cases/controls and 63,746/130,681 CHD cases/controls). FG in non-diabetic individuals tends to increase CHD risk (OR=1.15 (1.00-1.32), per mmol·per l, P=0.05; 133,010 non-diabetic individuals and 63,746/130,681 CHD cases/controls). These findings provide evidence supporting a causal relationship between T2D and CHD and suggest that long-term trials may be required to discern the effects of T2D therapies on CHD risk.

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Figures

Figure 1
Figure 1. Selection and validation of T2D SNPs used as instruments in the Mendelian randomization analysis of the effect of T2D on CHD risk.
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Figure 2
Figure 2. The Mendelian randomization estimate of the effect of T2D on CHD using a random-effects model.
For each of the 26 non-pleiotropic SNPs (Table 1), the Forest plot shows the estimate of the effect of genetically increased T2D risk on CHD risk, as assessed for each SNP. Also shown for each SNP is the 95% confidence interval (black line segment) of the estimate and the inverse-variance weight (% proportional to the size of the grey square) in the random-effects meta-analysis.
Figure 3
Figure 3. Mendelian randomization estimate of genetically increased T2D risk on CHD risk: subgroup analysis by physiologic cluster, computed using a random-effects model.
Shown for each SNP is mean value (black sqaure), the 95% confidence interval (black line segment) of the estimate and the inverse-variance weight (% proportional to the size of the grey square) in the random-effects meta-analysis (blue diamond). Of five biologically distinct clusters of genetic variants, only two clusters contained enough significant, non-pleiotropic variants for further analysis: (a) the cluster of variants influencing beta-cell function; and (b) the cluster unclassified variants.
Figure 4
Figure 4. Selection and validation of fasting glucose SNPs used as instruments in the Mendelian randomization analysis of the effect of fasting glucose on CHD risk.
Figure 5
Figure 5. The Mendelian randomization estimate of the effect of fasting glucose on CHD using a random-effects model.
For each of the 24 non-pleiotropic SNPs (Table 4), the Forest plot shows the estimate of the effect of the Fasting Glucose risk allele upon CHD risk, as assessed for each SNP, the 95% confidence interval (black line segment) of the estimate and the inverse-variance weight (proportional to the size of the grey square) in the random-effects meta-analysis (blue diamond).
See this image and copyright information in PMC

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