Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

1202 Diabetes Care Volume 42, July 2019 Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease Aaron Leong,1,2,3 Ji Chen,4 Eleanor Wheeler,4 Marie-France Hivert,1,2 Ching-Ti Liu,5 Jordi Merino,1,2,3 Josée Dupuis,5 E Shyong Tai,6 Jerome I. Rotter,7 Jose C. Florez,1,2,3 Inês Barroso,4 and James B. Meigs1,2,3 EPIDEMIOLOGY/HEALTH SERVICES RESEARCH Diabetes Care 2019;42:1202–1208 | https://doi.org/10.2337/dc18-1712 OBJECTIVE Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors. RESEARCH DESIGN AND METHODS To examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ‡6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and metaanalyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD. RESULTS Genetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 3 10212). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 3 1029) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 3 1026) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02). CONCLUSIONS Genetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemiaindependent factors. Hemoglobin A1c (A1C) is a convenient test used to diagnose diabetes, monitor glycemic control, and assess risk of diabetes-related complications, including coronary artery disease (CAD). Epidemiologic studies have shown in people without diabetes that A1C is strongly associated with CAD risk, even after accounting for fasting glucose 1 Massachusetts General Hospital, Boston, MA Harvard Medical School, Boston, MA 3 Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 4 Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, U.K. 5 Department of Biostatistics, Boston University School of Public Health, Boston, MA 6 Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 7 Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 2 Corresponding author: Aaron Leong, asleong@ mgh.harvard.edu Received 10 August 2018 and accepted 18 December 2018 This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/suppl/ doi:10.2337/dc18-1712/-/DC1. © 2019 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at http://www.diabetesjournals .org/content/license. See accompanying articles, pp. 1159 and 1284. care.diabetesjournals.org Leong and Associates and other clinical risk factors (1,2). Mendelian randomization (MR) can be used to assess the causal association between A1C and CAD risk through the application of an instrumental variable analysis with A1C-associated genetic variants. As genetic variants are randomized at birth and have effects that are potentially lifelong, MR studies are less vulnerable to unmeasured and residual confounding than traditional epidemiologic studies where biomarker measures may not be reliably measured or only reflect a brief snapshot in time (3). Previous MR studies have shown that genetically increased A1C is associated with higher CAD risk (4–6). However, a major challenge has been the examination of the underlying mechanisms linking A1C and CAD risk. As A1C is not a direct measurement of glycemia but rather a measure of the proportion of glycated hemoglobin in the blood, nonglycemic determinants of A1C that are intrinsic to the erythrocyte (7–10) may also influence CAD risk independently of glycemia. Here, we undertook a series of MR analyses to determine whether the association between A1C and CAD risk was driven by glycemic or erythrocytic factors, or both, through subsets of genetic variants previously classified by their probable biological categories (glycemic or erythrocytic). As some genetic determinants of A1C may act through changes in hemoglobin (Hb) levels, we performed additional MR analyses to test whether Hb and other erythrocytic traits were also associated with A1C and CAD risk. RESEARCH DESIGN AND METHODS A1C Candidate Instrument Selection and Classification as Either Glycemic or Erythrocytic Genome-wide association studies (GWAS) data sets used in the MR analyses are summarized in Table 1. We extracted association summary statistics from a large-scale transethnic meta-analysis GWAS on A1C in individuals without diabetes (the Meta-Analyses of Glucose and Insulin-Related Traits Consortium [MAGIC]) (11). As GWAS data sets were overwhelmingly European, we drew a set of distinct variants reaching genomewide (GW) significance in the transethnic analysis (log10 Bayes factor $6; n = 159,940, European-ancestry linkage disequilibrium r2 , 0.05) and excluded those with P . 5 3 1025 in European samples (n = 123,665) (Supplementary Fig. 1). Previous work has classified these variants as “glycemic” or “erythrocytic” (Supplementary Table 1) (11). We performed separate MR analyses restricting instruments to A1C variants classified as “glycemic” or “erythrocytic” to test the hypothesis that variation in A1C altered CAD risk through glycemic or erythrocytic factors, respectively. A1C variants that were not associated with glycemic or erythrocytic traits were excluded from these subanalyses. MR Analysis Using CAD GWAS Summary Data To estimate the causal association of A1C on CAD, we performed a two-sample MR using summary data from the Coronary Artery Disease Genome-Wide Replication and Meta-analysis Plus Coronary Artery Disease Genetics (CARDIoGRAMplusC4D; n = 60,801 case subjects/123,504 control subjects) GWAS (12). The ca (...truncated)