Hadi Harati1, Daniela Zanetti2, Abhiram Rao3, Stefan Gustafsson4, Marco Perez2, Erik Ingelsson2,5,6, Joshua W Knowles7,8,9. 1. Department of Medicine, Division of Endocrinology, Stanford University School of Medicine, Stanford, CA, USA. 2. Department of Medicine, Division of Cardiovascular Medicine, Falk Cardiovascular Research Center, Stanford University School of Medicine, 300 Pasteur Drive, CV 273, Stanford, CA, 94305, USA. 3. Department of Bioengineering, Stanford University, Stanford, CA, USA. 4. Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. 5. Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA. 6. Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA. 7. Department of Medicine, Division of Cardiovascular Medicine, Falk Cardiovascular Research Center, Stanford University School of Medicine, 300 Pasteur Drive, CV 273, Stanford, CA, 94305, USA. knowlej@stanford.edu. 8. Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA. knowlej@stanford.edu. 9. Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA. knowlej@stanford.edu.
Abstract
AIMS/HYPOTHESIS: Several epidemiological studies have shown an increased risk of atrial fibrillation in individuals with type 2 diabetes or milder forms of dysglycaemia. We aimed to assess whether this relation is causal using a Mendelian randomisation approach. METHODS: Two-sample Mendelian randomisation was used to obtain estimates of the influence of type 2 diabetes, fasting blood glucose (FBG), and HbA1c on the risk of atrial fibrillation. Instrumental variables were constructed using available summary statistics from meta-analyses of genome-wide association studies (GWAS) for type 2 diabetes and associated phenotypes. Pleiotropic SNPs were excluded from the analyses. The most recent GWAS meta-analysis summary statistics for atrial fibrillation, which included over 1 million individuals (approximately 60,000 individuals with atrial fibrillation) was used for outcome analysis. RESULTS: Neither type 2 diabetes (OR 1.01 [95% CI 0.98, 1.03]; p = 0.37), nor FBG (OR 0.95 [95% CI 0.82, 1.09] per mmol/l; p = 0.49) or HbA1c (OR 1.01 [95% CI, 0.85, 1.17] per mmol/mol [%]; p = 0.88) were associated with atrial fibrillation in Mendelian randomisation analyses. We had >80% statistical power to detect ORs of 1.08, 1.06 and 1.09 or larger for type 2 diabetes, FBG and HbA1c, respectively, for associations with atrial fibrillation. CONCLUSIONS/ INTERPRETATION: This Mendelian randomisation analysis does not support a causal role of clinical significance between genetically programmed type 2 diabetes, FBG or HbA1c and development of atrial fibrillation. These data suggest that drug treatment to reduce dysglycaemia is unlikely to be an effective strategy for atrial fibrillation prevention. DATA AVAILABILITY: The datasets analysed during the current study are available from the following repository: Nielsen JB, Thorolfsdottir RB, Fritsche LG, et al (2018) GWAS summary statistics for AF (N=60,620 AF cases and 970,216 controls). Center for Statistical Genetics: http://csg.sph.umich.edu/willer/public/afib2018/nielsen-thorolfsdottir-willer-NG2018-AFib-gwas-summary-statistics.tbl.gz.
AIMS/HYPOTHESIS: Several epidemiological studies have shown an increased risk of atrial fibrillation in individuals with type 2 diabetes or milder forms of dysglycaemia. We aimed to assess whether this relation is causal using a Mendelian randomisation approach. METHODS: Two-sample Mendelian randomisation was used to obtain estimates of the influence of type 2 diabetes, fasting blood glucose (FBG), and HbA1c on the risk of atrial fibrillation. Instrumental variables were constructed using available summary statistics from meta-analyses of genome-wide association studies (GWAS) for type 2 diabetes and associated phenotypes. Pleiotropic SNPs were excluded from the analyses. The most recent GWAS meta-analysis summary statistics for atrial fibrillation, which included over 1 million individuals (approximately 60,000 individuals with atrial fibrillation) was used for outcome analysis. RESULTS: Neither type 2 diabetes (OR 1.01 [95% CI 0.98, 1.03]; p = 0.37), nor FBG (OR 0.95 [95% CI 0.82, 1.09] per mmol/l; p = 0.49) or HbA1c (OR 1.01 [95% CI, 0.85, 1.17] per mmol/mol [%]; p = 0.88) were associated with atrial fibrillation in Mendelian randomisation analyses. We had >80% statistical power to detect ORs of 1.08, 1.06 and 1.09 or larger for type 2 diabetes, FBG and HbA1c, respectively, for associations with atrial fibrillation. CONCLUSIONS/ INTERPRETATION: This Mendelian randomisation analysis does not support a causal role of clinical significance between genetically programmed type 2 diabetes, FBG or HbA1c and development of atrial fibrillation. These data suggest that drug treatment to reduce dysglycaemia is unlikely to be an effective strategy for atrial fibrillation prevention. DATA AVAILABILITY: The datasets analysed during the current study are available from the following repository: Nielsen JB, Thorolfsdottir RB, Fritsche LG, et al (2018) GWAS summary statistics for AF (N=60,620 AF cases and 970,216 controls). Center for Statistical Genetics: http://csg.sph.umich.edu/willer/public/afib2018/nielsen-thorolfsdottir-willer-NG2018-AFib-gwas-summary-statistics.tbl.gz.
Entities:
Keywords:
Atrial fibrillation; Genome-wide association; Mendelian randomisation; Type 2 diabetes
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