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Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease
OBJECTIVE: Observational studies show that higher hemoglobin A(1c) (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/o...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Diabetes Association
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609962/ https://www.ncbi.nlm.nih.gov/pubmed/30659074 http://dx.doi.org/10.2337/dc18-1712 |
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author | Leong, Aaron Chen, Ji Wheeler, Eleanor Hivert, Marie-France Liu, Ching-Ti Merino, Jordi Dupuis, Josée Tai, E Shyong Rotter, Jerome I. Florez, Jose C. Barroso, Inês Meigs, James B. |
author_facet | Leong, Aaron Chen, Ji Wheeler, Eleanor Hivert, Marie-France Liu, Ching-Ti Merino, Jordi Dupuis, Josée Tai, E Shyong Rotter, Jerome I. Florez, Jose C. Barroso, Inês Meigs, James B. |
author_sort | Leong, Aaron |
collection | PubMed |
description | OBJECTIVE: Observational studies show that higher hemoglobin A(1c) (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 (log(10) 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 meta-analyzed 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 × 10(−12)). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10(−9)) 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 × 10(−6)) 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, glycemia-independent factors. |
format | Online Article Text |
id | pubmed-6609962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-66099622020-07-01 Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease Leong, Aaron Chen, Ji Wheeler, Eleanor Hivert, Marie-France Liu, Ching-Ti Merino, Jordi Dupuis, Josée Tai, E Shyong Rotter, Jerome I. Florez, Jose C. Barroso, Inês Meigs, James B. Diabetes Care Epidemiology/Health Services Research OBJECTIVE: Observational studies show that higher hemoglobin A(1c) (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 (log(10) 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 meta-analyzed 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 × 10(−12)). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10(−9)) 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 × 10(−6)) 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, glycemia-independent factors. American Diabetes Association 2019-07 2019-01-19 /pmc/articles/PMC6609962/ /pubmed/30659074 http://dx.doi.org/10.2337/dc18-1712 Text en © 2019 by the American Diabetes Association. http://www.diabetesjournals.org/content/licenseReaders 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. |
spellingShingle | Epidemiology/Health Services Research Leong, Aaron Chen, Ji Wheeler, Eleanor Hivert, Marie-France Liu, Ching-Ti Merino, Jordi Dupuis, Josée Tai, E Shyong Rotter, Jerome I. Florez, Jose C. Barroso, Inês Meigs, James B. Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease |
title | Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease |
title_full | Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease |
title_fullStr | Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease |
title_full_unstemmed | Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease |
title_short | Mendelian Randomization Analysis of Hemoglobin A(1c) as a Risk Factor for Coronary Artery Disease |
title_sort | mendelian randomization analysis of hemoglobin a(1c) as a risk factor for coronary artery disease |
topic | Epidemiology/Health Services Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609962/ https://www.ncbi.nlm.nih.gov/pubmed/30659074 http://dx.doi.org/10.2337/dc18-1712 |
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