The mediating role of atrial fibrillation in causal associations between risk factors and stroke: a Mendelian randomization study
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
OBJECTIVES: Atrial fibrillation (AF) contributes to stroke development and progression. We aimed to quantify the mediating role of AF in the causal associations between a wide range of risk factors and stroke via a Mendelian randomization (MR) framework. METHODS: We assessed the associations of 108 traits with stroke and its subtypes in a 2-sample univariable MR approach, then conducted a bidirectional MR analysis between these 108 traits and AF to evaluate the presence and direction of their causal associations. Finally, to further investigate the extent to which AF mediated the effects of eligible traits on stroke, we applied multivariable and 2-step MR techniques in a mediation analysis where outcomes were restricted to stroke types causally affected by AF (any stroke [AS], any ischemic stroke [AIS], and cardioembolic stroke [CES]). RESULTS: Among 108 traits, 42 were putatively causal for at least 1 stroke type; of these 42 traits, 20 that had no bidirectional relationship with AF were retained. Finally, 33 associations of 15 eligible traits were examined in the mediation analysis. The mediation analyses for AS, AIS, and CES each included 11 eligible traits. After AF adjustment, the direct effects of all traits on CES were attenuated to null (all p> 0.05), while the associations with AS and AIS persisted for most traits (AF-mediated proportion: from 6.6% [95% confidence interval, 2.7 to 0.6] to 52.0% [95% confidence interval, 39.8 to 64.3]). CONCLUSIONS: The causal associations between all eligible traits and CES were largely mediated through AF, while most traits affected AS and AIS independently of AF.
Abstract
OBJECTIVES: Atrial fibrillation (AF) contributes to stroke development and progression. We aimed to quantify the mediating role of AF in the causal associations between a wide range of risk factors and stroke via a Mendelian randomization (MR) framework. METHODS: We assessed the associations of 108 traits with stroke and its subtypes in a 2-sample univariable MR approach, then conducted a bidirectional MR analysis between these 108 traits and AF to evaluate the presence and direction of their causal associations. Finally, to further investigate the extent to which AF mediated the effects of eligible traits on stroke, we applied multivariable and 2-step MR techniques in a mediation analysis where outcomes were restricted to stroke types causally affected by AF (any stroke [AS], any ischemic stroke [AIS], and cardioembolic stroke [CES]). RESULTS: Among 108 traits, 42 were putatively causal for at least 1 stroke type; of these 42 traits, 20 that had no bidirectional relationship with AF were retained. Finally, 33 associations of 15 eligible traits were examined in the mediation analysis. The mediation analyses for AS, AIS, and CES each included 11 eligible traits. After AF adjustment, the direct effects of all traits on CES were attenuated to null (all p> 0.05), while the associations with AS and AIS persisted for most traits (AF-mediated proportion: from 6.6% [95% confidence interval, 2.7 to 0.6] to 52.0% [95% confidence interval, 39.8 to 64.3]). CONCLUSIONS: The causal associations between all eligible traits and CES were largely mediated through AF, while most traits affected AS and AIS independently of AF.
참고문헌 (42)
- Wolf PA, "Atrial fibrillation as an independent risk factor for stroke : the Framingham Study", Stroke, 22, pp.983~988 (1991)[DOI]
- Hindricks G, "2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery(EACTS) : the Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology(ESC)Developed with the special contribution of the European Heart Rhythm Association(EHRA)of the ESC", Eur Heart J, 42, pp.373~498 (2021)[DOI]
- Tu HT, "Pathophysiological determinants of worse stroke outcome in atrial fibrillation", Cerebrovasc Dis, 30, pp.389~395 (2010)[DOI]
- Tu HT, "Worse stroke outcome in atrial fibrillation is explained by more severe hypoperfusion, infarct growth, and hemorrhagic transformation", Int J Stroke, 10, pp.534~540 (2015)[DOI]
- Alkhouli M, "Burden of atrial fibrillation-associated ischemic stroke in the United States", JACC Clin Electrophysiol, 4, pp.618~625 (2018)[DOI]
- Sposato LA, "Diagnosis of atrial fibrillation after stroke and transient ischaemic attack : a systematic review and meta-analysis", Lancet Neurol, 14, pp.377~387 (2015)[DOI]
- Schnabel RB, "Searching for atrial fibrillation poststroke : a white paper of the AF-SCREEN International Collaboration", Circulation, 140, pp.1834~1850 (2019)[DOI]
- Sposato LA, "Poststroke atrial fibrillation: cause or consequence? Critical review of current views", Neurology, 82, pp.1180~1186 (2014)[DOI]
- Davey Smith G, "Mendelian randomization : genetic anchors for causal inference in epidemiological studies", Hum Mol Genet, 23, pp.R89~R98 (2014)[DOI]
- Sanderson E, "Multivariable Mendelian randomization and mediation", Cold Spring Harb Perspect Med, 11, pp.a038984~ (2021)[DOI]
- Marouli E, "Thyroid function affects the risk of stroke via atrial fibrillation : a Mendelian randomization study", J Clin Endocrinol Metab, 105, pp.2634~2641 (2020)[DOI]
- Frerich S, "Cardiac risk factors for stroke : a comprehensive Mendelian randomization study", Stroke, 53, pp.e130~e135 (2022)[DOI]
- Wang Q, "A phenome-wide bidirectional Mendelian randomization analysis of atrial fibrillation", Int J Epidemiol, 51, pp.1153~1166 (2022)[DOI]
- Tsao CW, "Heart disease and stroke statistics-2022 update : a report from the American Heart Association", Circulation, 145, pp.e153~e639 (2022)[DOI]
- Kornej J, "Epidemiology of atrial fibrillation in the 21st century : novel methods and new insights", Circ Res, 127, pp.4~20 (2020)[DOI]
- Lawlor DA, "Commentary : two-sample Mendelian randomization : opportunities and challenges", Int J Epidemiol, 45, pp.908~915 (2016)[DOI]
- Sanderson E, "An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings", Int J Epidemiol, 48, pp.713~727 (2019)[DOI]
- Relton CL, "Two-step epigenetic Mendelian randomization : a strategy for establishing the causal role of epigenetic processes in pathways to disease", Int J Epidemiol, 41, pp.161~176 (2012)[DOI]
- Skrivankova VW, "Strengthening the reporting of observational studies in epidemiology using Mendelian randomization : the STROBE-MR statement", JAMA, 326, pp.1614~1621 (2021)[DOI]
- Georgakis MK, "Mendelian randomization studies in stroke : exploration of risk factors and drug targets with human genetic data", Stroke, 52, pp.2992~3003 (2021)[DOI]
- Acosta JN, "Mendelian randomization in stroke : a powerful approach to causal inference and drug target validation", Front Genet, 12, pp.683082~ (2021)[DOI]
- Yengo L, "Meta-analysis of genome-wide association studies for height and body mass index in~700000 individuals of European ancestry", Hum Mol Genet, 27, pp.3641~3649 (2018)[DOI]
- Stanzick KJ, "Discovery and prioritization of variants and genes for kidney function in >1. 2 million individuals", Nat Commun, 12, pp.4350~ (2021)[DOI]
- O’Seaghdha CM, "Meta-analysis of genome-wide association studies identifies six new Loci for serum calcium concentrations", PLoS Genet, 9, pp.e1003796~ (2013)[DOI]
- Meyer TE, "Genome-wide association studies of serum magnesium, potassium, and sodium concentrations identify six Loci influencing serum magnesium levels", PLoS Genet, 6, pp.e1001045~ (2010)[DOI]
- Nielsen JB, "Biobank-driven genomic discovery yields new insight into atrial fibrillation biology", Nat Genet, 50, pp.1234~1239 (2018)[DOI]
- Malik R, "Multiancestry genome-wide association study of 520, 000 subjects identifies 32 loci associated with stroke and stroke subtypes", Nat Genet, 50, pp.524~537 (2018)[DOI]
- Adams HP Jr, "Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in acute stroke treatment", Stroke, 24, pp.35~41 (1993)[DOI]
- Burgess S, "Mendelian randomization analysis with multiple genetic variants using summarized data", Genet Epidemiol, 37, pp.658~665 (2013)[DOI]
- Bowden J, "Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator", Genet Epidemiol, 40, pp.304~314 (2016)[DOI]
- Bowden J, "Mendelian randomization with invalid instruments : effect estimation and bias detection through Egger regression", Int J Epidemiol, 44, pp.512~525 (2015)[DOI]
- Bowden J, "Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression : the role of the I2 statistic", Int J Epidemiol, 45, pp.1961~1974 (2016)[DOI]
- Bowden J, "Improving the accuracy of two-sample summary-data Mendelian randomization : moving beyond the NOME assumption", Int J Epidemiol, 48, pp.728~742 (2019)[DOI]
- Benjamini Y, "Controlling the false discovery rate : a practical and powerful approach to multiple testing", J R Stat Soc Ser B Methodol, 57, pp.289~300 (1995)[DOI]
- Hemani G, "The MR-Base platform supports systematic causal inference across the human phenome", Elife, 7, pp.e34408~ (2018)[DOI]
- Sanderson E, "Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization", Stat Med, 40, pp.5434~5452 (2021)[DOI]
- O’Donnell MJ, "Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries(the INTERSTROKE study) : a case-control study", Lancet, 376, pp.112~123 (2010)[DOI]
- Carter AR, "Understanding the consequences of education inequality on cardiovascular disease : mendelian randomisation study", BMJ, 365, pp.l1855~ (2019)[DOI]
- Staley JR, "Semiparametric methods for estimation of a nonlinear exposure-outcome relationship using instrumental variables with application to Mendelian randomization", Genet Epidemiol, 41, pp.341~352 (2017)[DOI]
- Hemani G, "Evaluating the potential role of pleiotropy in Mendelian randomization studies", Hum Mol Genet, 27, pp.R195~R208 (2018)[DOI]
- Burgess S, "Bias due to participant overlap in two-sample Mendelian randomization", Genet Epidemiol, 40, pp.597~608 (2016)[DOI]
- Carter AR, "Mendelian randomisation for mediation analysis : current methods and challenges for implementation", Eur J Epidemiol, 36, pp.465~478 (2021)[DOI]
