Christina Ellervik1,2,3, Carolina Roselli4, Ingrid E Christophersen5,6, Alvaro Alonso7, Maik Pietzner8,9, Collen M Sitlani10, Stella Trompet11,12, Dan E Arking13, Bastiaan Geelhoed14, Xiuqing Guo15,16,17, Marcus E Kleber18, Henry J Lin15,16,17, Honghuang Lin19,20, Peter MacFarlane21, Elizabeth Selvin22, Christian Shaffer23, Albert V Smith24,25, Niek Verweij14, Stefan Weiss9,26, Anne R Cappola27, Marcus Dörr9,28, Vilmundur Gudnason25,29, Susan Heckbert30, Simon Mooijaart12,31, Winfried März18,32, Bruce M Psaty33,34, Paul M Ridker2,35,36, Dan Roden23, David J Stott37, Henry Völzke9,38, Emelia J Benjamin19,20,39, Graciela Delgado18, Patrick Ellinor2,40,41, Georg Homuth42, Anna Köttgen22,43, Johan W Jukema11,44,45, Steven A Lubitz46, Samia Mora2,35,36, Michiel Rienstra14, Jerome I Rotter15,16,17, M Benjamin Shoemaker23, Nona Sotoodehnia10, Kent D Taylor15,16,17, Pim van der Harst14, Christine M Albert2,35,36, Daniel I Chasman2,4,36. 1. Department of Laboratory Medicine, Boston Children's Hospital, Boston, Massachusetts. 2. Harvard Medical School, Boston, Massachusetts. 3. Division of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. 4. Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts. 5. Department of Medical Genetics, Oslo University Hospital, Oslo, Norway. 6. Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway. 7. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia. 8. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. 9. DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany. 10. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle. 11. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands. 12. Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands. 13. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland. 14. University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. 15. Division of Genomic Outcomes, Institute for Translational Genomics and Population Sciences, Torrance, California. 16. Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-University of California, Los Angeles Medical Center, Torrance. 17. Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles. 18. Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany. 19. Department of Medicine, Boston University School of Medicine, Boston, Massachusetts. 20. National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts. 21. Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom. 22. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. 23. Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee. 24. School of Public Health, Department of Biostatistics, University of Michigan, Ann Arbor. 25. Icelandic Heart Association, Kopavogur, Iceland. 26. Interfaculty Institute for Genetics and Functional Genomics, University Medicine and University Greifswald, Greifswald, Germany. 27. Smilow Center for Translational Research, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia. 28. Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany. 29. Faculty of Medicine, University of Iceland, Reykjavik, Iceland. 30. Department of Epidemiology, University of Washington, Seattle. 31. Institute for Evidence-Based Medicine in Old Age, Leiden, the Netherlands. 32. Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany. 33. Cardiovascular Health Research Unit, Department of Medicine, Epidemiology, and Health Services, University of Washington, Seattle. 34. Kaiser Permanente Washington Health Research Institute, Seattle. 35. Division of Cardiovascular, Brigham and Women's Hospital, Boston, Massachusetts. 36. Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts. 37. Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom. 38. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. 39. Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts. 40. Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, Massachusetts. 41. Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, Massachusetts. 42. University Medicine Greifswald, Interfaculty Institute for Genetics and Functional Genomics, Greifswald, Germany. 43. Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany. 44. Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, the Netherlands. 45. Interuniversity Cardiology Institute of the Netherlands, Utrecht, the Netherlands. 46. Cardiovascular Research Center, Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston.
Abstract
Importance: Increased free thyroxine (FT4) and decreased thyrotropin are associated with increased risk of atrial fibrillation (AF) in observational studies, but direct involvement is unclear. Objective: To evaluate the potential direct involvement of thyroid traits on AF. Design, Setting, and Participants: Study-level mendelian randomization (MR) included 11 studies, and summary-level MR included 55 114 AF cases and 482 295 referents, all of European ancestry. Exposures: Genomewide significant variants were used as instruments for standardized FT4 and thyrotropin levels within the reference range, standardized triiodothyronine (FT3):FT4 ratio, hypothyroidism, standardized thyroid peroxidase antibody levels, and hyperthyroidism. Mendelian randomization used genetic risk scores in study-level analysis or individual single-nucleotide polymorphisms in 2-sample MR for the summary-level data. Main Outcomes and Measures: Prevalent and incident AF. Results: The study-level analysis included 7679 individuals with AF and 49 233 referents (mean age [standard error], 62 [3] years; 15 859 men [29.7%]). In study-level random-effects meta-analysis, the pooled hazard ratio of FT4 levels (nanograms per deciliter) for incident AF was 1.55 (95% CI, 1.09-2.20; P = .02; I2 = 76%) and the pooled odds ratio (OR) for prevalent AF was 2.80 (95% CI, 1.41-5.54; P = .003; I2 = 64%) in multivariable-adjusted analyses. The FT4 genetic risk score was associated with an increase in FT4 by 0.082 SD (standard error, 0.007; P < .001) but not with incident AF (risk ratio, 0.84; 95% CI, 0.62-1.14; P = .27) or prevalent AF (OR, 1.32; 95% CI, 0.64-2.73; P = .46). Similarly, in summary-level inverse-variance weighted random-effects MR, gene-based FT4 within the reference range was not associated with AF (OR, 1.01; 95% CI, 0.89-1.14; P = .88). However, gene-based increased FT3:FT4 ratio, increased thyrotropin within the reference range, and hypothyroidism were associated with AF with inverse-variance weighted random-effects OR of 1.33 (95% CI, 1.08-1.63; P = .006), 0.88 (95% CI, 0.84-0.92; P < .001), and 0.94 (95% CI, 0.90-0.99; P = .009), respectively, and robust to tests of horizontal pleiotropy. However, the subset of hypothyroidism single-nucleotide polymorphisms involved in autoimmunity and thyroid peroxidase antibodies levels were not associated with AF. Gene-based hyperthyroidism was associated with AF with MR-Egger OR of 1.31 (95% CI, 1.05-1.63; P = .02) with evidence of horizontal pleiotropy (P = .045). Conclusions and Relevance: Genetically increased FT3:FT4 ratio and hyperthyroidism, but not FT4 within the reference range, were associated with increased AF, and increased thyrotropin within the reference range and hypothyroidism were associated with decreased AF, supporting a pathway involving the pituitary-thyroid-cardiac axis.
Importance: Increased free thyroxine (FT4) and decreased thyrotropin are associated with increased risk of atrial fibrillation (AF) in observational studies, but direct involvement is unclear. Objective: To evaluate the potential direct involvement of thyroid traits on AF. Design, Setting, and Participants: Study-level mendelian randomization (MR) included 11 studies, and summary-level MR included 55 114 AF cases and 482 295 referents, all of European ancestry. Exposures: Genomewide significant variants were used as instruments for standardized FT4 and thyrotropin levels within the reference range, standardized triiodothyronine (FT3):FT4 ratio, hypothyroidism, standardized thyroid peroxidase antibody levels, and hyperthyroidism. Mendelian randomization used genetic risk scores in study-level analysis or individual single-nucleotide polymorphisms in 2-sample MR for the summary-level data. Main Outcomes and Measures: Prevalent and incident AF. Results: The study-level analysis included 7679 individuals with AF and 49 233 referents (mean age [standard error], 62 [3] years; 15 859 men [29.7%]). In study-level random-effects meta-analysis, the pooled hazard ratio of FT4 levels (nanograms per deciliter) for incident AF was 1.55 (95% CI, 1.09-2.20; P = .02; I2 = 76%) and the pooled odds ratio (OR) for prevalent AF was 2.80 (95% CI, 1.41-5.54; P = .003; I2 = 64%) in multivariable-adjusted analyses. The FT4 genetic risk score was associated with an increase in FT4 by 0.082 SD (standard error, 0.007; P < .001) but not with incident AF (risk ratio, 0.84; 95% CI, 0.62-1.14; P = .27) or prevalent AF (OR, 1.32; 95% CI, 0.64-2.73; P = .46). Similarly, in summary-level inverse-variance weighted random-effects MR, gene-based FT4 within the reference range was not associated with AF (OR, 1.01; 95% CI, 0.89-1.14; P = .88). However, gene-based increased FT3:FT4 ratio, increased thyrotropin within the reference range, and hypothyroidism were associated with AF with inverse-variance weighted random-effects OR of 1.33 (95% CI, 1.08-1.63; P = .006), 0.88 (95% CI, 0.84-0.92; P < .001), and 0.94 (95% CI, 0.90-0.99; P = .009), respectively, and robust to tests of horizontal pleiotropy. However, the subset of hypothyroidism single-nucleotide polymorphisms involved in autoimmunity and thyroid peroxidase antibodies levels were not associated with AF. Gene-based hyperthyroidism was associated with AF with MR-Egger OR of 1.31 (95% CI, 1.05-1.63; P = .02) with evidence of horizontal pleiotropy (P = .045). Conclusions and Relevance: Genetically increased FT3:FT4 ratio and hyperthyroidism, but not FT4 within the reference range, were associated with increased AF, and increased thyrotropin within the reference range and hypothyroidism were associated with decreased AF, supporting a pathway involving the pituitary-thyroid-cardiac axis.
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