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Cardiovascular Diabetology
Published in: Cardiovascular Diabetology 1/2024

Open Access 01-12-2024 | Atrial Fibrillation | Research

Associations of combined polygenic risk score and glycemic status with atrial fibrillation, coronary artery disease and ischemic stroke

Authors: Juntae Kim, Dongmin Kim, Han-Joon Bae, Byoung-Eun Park, Tae Soo Kang, Seong-Hoon Lim, Su Yeon Lee, Young Hak Chung, Ji Wung Ryu, Myung-Yong Lee, Pil-Sung Yang, Boyoung Joung

Published in: Cardiovascular Diabetology | Issue 1/2024

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Abstract

Background

It is unknown whether high hemoglobin A1c (HbA1c) is associated with increases in the risk of cardiovascular disease among individuals with elevated genetic susceptibility. We aimed to investigate the association between HbA1c and atrial fibrillation (AF), coronary artery disease (CAD), and ischemic stroke according to the polygenic risk score (PRS).

Methods

The UK Biobank cohort included 502,442 participants aged 40–70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. This study included 305,605 unrelated individuals with available PRS and assessed new-onset AF, CAD, and ischemic stroke. The participants were divided into tertiles based on the validated PRS for each outcome. Within each PRS tertiles, the risks of incident events associated with HbA1c levels were investigated and compared with HbA1c < 5.7% and low PRS. Data were analyzed from November 2022 to May 2023.

Results

Of 305,605 individuals, 161,605 (52.9%) were female, and the mean (SD) age was 56.6 (8.1) years. During a median follow-up of 11.9 (interquartile range 11.1–12.6) years, the incidences of AF, CAD, and ischemic stroke were 4.6, 2.9 and 1.1 per 100 person-years, respectively. Compared to individuals with HbA1c < 5.7% and low PRS, individuals with HbA1c ≥ 6.5% and high PRS had a 2.67-times higher risk for AF (hazard ratio [HR], 2.67; 95% confidence interval (CI), 2.43–2.94), 5.71-times higher risk for CAD (HR, 5.71; 95% CI, 5.14–6.33) and 2.94-times higher risk for ischemic stroke (HR, 2.94; 95% CI, 2.47–3.50). In the restricted cubic spline models, while a U-shaped trend was observed between HbA1c and the risk of AF, dose-dependent increases were observed between HbA1c and the risk of CAD and ischemic stroke regardless PRS tertile.

Conclusions

Our results suggest that the nature of the dose-dependent relationship between HbA1c levels and cardiovascular disease in individuals with different PRS is outcome-specific. This adds to the evidence that PRS may play a role together with glycemic status in the development of cardiovascular disease.
Appendix
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Literature
1.
Murray CJ, Barber RM, Foreman KJ, et al. Global, regional, and national disability-adjusted life years (DALYs) for 306 Diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition. The Lancet. 2015;386(10009):2145–91.CrossRef
2.
Morrish N, Wang S-L, Stevens L, Fuller J, Keen H, Group WMS. Mortality and causes of death in the WHO multinational study of Vascular Disease in Diabetes. Diabetologia. 2001;44:14–S21.CrossRef
3.
Rao Kondapally Seshasai S, Kaptoge S, Thompson A, et al. Diabetes Mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829–41.PubMedPubMedCentralCrossRef
4.
Khaw KT, Wareham N, Bingham S, Luben R, Welch A, Day N. Association of hemoglobin A1c with Cardiovascular Disease and mortality in adults: the European prospective investigation into cancer in Norfolk. Ann Intern Med. 2004;141(6):413–20.PubMedCrossRef
5.
Cavender MA, Scirica BM, Raz I, et al. Cardiovascular outcomes of patients in SAVOR-TIMI 53 by Baseline Hemoglobin A1c. Am J Med. 2016;129(3):340e341–348.CrossRef
6.
Lee WL, Cheung AM, Cape D, Zinman B. Impact of Diabetes on coronary artery Disease in women and men: a meta-analysis of prospective studies. Diabetes Care. 2000;23(7):962–8.PubMedCrossRef
7.
Mitsios JP, Ekinci EI, Mitsios GP, Churilov L, Thijs V. Relationship between glycated hemoglobin and Stroke risk: a systematic review and Meta-analysis. J Am Heart Assoc 2018;7(11).
8.
Kim D, Yang PS, Jang E, et al. 10-year nationwide trends of the incidence, prevalence, and adverse outcomes of non-valvular atrial fibrillation nationwide health insurance data covering the entire Korean population. Am Heart J. 2018;202:20–6.PubMedCrossRef
9.
Kim D, Yang PS, Jang E, et al. Increasing trends in hospital care burden of atrial fibrillation in Korea, 2006 through 2015. Heart. 2018;104(24):2010–7.PubMedCrossRef
10.
Kim D, Yang PS, You SC, et al. Treatment timing and the effects of rhythm control strategy in patients with atrial fibrillation: nationwide cohort study. BMJ. 2021;373:n991.PubMedPubMedCentralCrossRef
11.
Lee SS, Ae Kong K, Kim D, et al. Clinical implication of an impaired fasting glucose and prehypertension related to new onset atrial fibrillation in a healthy Asian population without underlying Disease: a nationwide cohort study in Korea. Eur Heart J. 2017;38(34):2599–607.PubMedCrossRef
12.
Lim YM, Yang PS, Jang E, et al. Body Mass Index variability and long-term risk of New-Onset Atrial Fibrillation in the General Population: a Korean Nationwide Cohort Study. Mayo Clin Proc. 2019;94(2):225–35.PubMedCrossRef
13.
Kim J, Kim D, Jang E et al. Associations of high-normal blood pressure and impaired fasting glucose with atrial fibrillation. Heart 2023.
14.
15.
Liou YS, Yang FY, Chen HY, Jong GP. Antihyperglycemic Drugs use and new-onset atrial fibrillation: a population-based nested case control study. PLoS ONE. 2018;13(8):e0197245.PubMedPubMedCentralCrossRef
16.
Nichols GA, Reinier K, Chugh SS. Independent contribution of Diabetes to increased prevalence and incidence of atrial fibrillation. Diabetes Care. 2009;32(10):1851–6.PubMedPubMedCentralCrossRef
17.
Schoen T, Pradhan AD, Albert CM, Conen D. Type 2 Diabetes Mellitus and risk of incident atrial fibrillation in women. J Am Coll Cardiol. 2012;60(15):1421–8.PubMedPubMedCentralCrossRef
18.
Qi W, Zhang N, Korantzopoulos P, et al. Serum glycated hemoglobin level as a predictor of atrial fibrillation: a systematic review with meta-analysis and meta-regression. PLoS ONE. 2017;12(3):e0170955.PubMedPubMedCentralCrossRef
19.
Harati H, Zanetti D, Rao A, et al. No evidence of a causal association of type 2 Diabetes and glucose metabolism with atrial fibrillation. Diabetologia. 2019;62(5):800–4.PubMedPubMedCentralCrossRef
20.
Zhao H, Liu M, Chen Z, Mei K, Yu P, Xie L. Dose-response analysis between hemoglobin A1c and risk of atrial fibrillation in patients with and without known Diabetes. PLoS ONE. 2020;15(2):e0227262.PubMedPubMedCentralCrossRef
21.
22.
Nelson CP, Goel A, Butterworth AS, et al. Association analyses based on false discovery rate implicate new loci for coronary artery Disease. Nat Genet. 2017;49(9):1385–91.PubMedCrossRef
23.
Bevan S, Traylor M, Adib-Samii P, et al. Genetic heritability of ischemic Stroke and the contribution of previously reported candidate gene and genomewide associations. Stroke. 2012;43(12):3161–7.PubMedCrossRef
24.
Polygenic Risk Score Task Force of the International Common Disease A. Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps. Nat Med. 2021;27(11):1876–84.CrossRef
25.
Thompson DJ, Wells D, Selzam S, et al. UK Biobank release and systematic evaluation of optimised polygenic risk scores for 53 Diseases and quantitative traits. MedRxiv. 2022. 2022.2006. 2016.22276246.
26.
Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of Sociodemographic and Health-related characteristics of UK Biobank participants with those of the General Population. Am J Epidemiol. 2017;186(9):1026–34.PubMedPubMedCentralCrossRef
27.
Elliott P, Peakman TC, Biobank UK. The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int J Epidemiol. 2008;37(2):234–44.PubMedCrossRef
28.
Geistanger A, Arends S, Berding C, et al. Statistical methods for monitoring the relationship between the IFCC reference measurement procedure for hemoglobin A1c and the designated comparison methods in the United States, Japan, and Sweden. Clin Chem. 2008;54(8):1379–85.PubMedCrossRef
29.
American Diabetes Association Professional Practice C. 2. Classification and diagnosis of Diabetes: standards of Medical Care in Diabetes-2022. Diabetes Care. 2022;45(Suppl 1):17–S38.CrossRef
30.
31.
Selvin E, Coresh J, Shahar E, Zhang L, Steffes M, Sharrett AR. Glycaemia (haemoglobin A1c) and incident ischaemic Stroke: the Atherosclerosis risk in communities (ARIC) Study. Lancet Neurol. 2005;4(12):821–6.PubMedCrossRef
32.
Donnellan E, Aagaard P, Kanj M, et al. Association between Pre-ablation Glycemic Control and outcomes among patients with Diabetes undergoing Atrial Fibrillation ablation. JACC Clin Electrophysiol. 2019;5(8):897–903.PubMedCrossRef
33.
Ashburner JM, Go AS, Chang Y, et al. Effect of Diabetes and Glycemic Control on ischemic Stroke risk in AF patients: ATRIA Study. J Am Coll Cardiol. 2016;67(3):239–47.PubMedPubMedCentralCrossRef
34.
Patti G, Lucerna M, Cavallari I, et al. Insulin-requiring Versus Noninsulin-requiring Diabetes and thromboembolic risk in patients with Atrial Fibrillation: PREFER in AF. J Am Coll Cardiol. 2017;69(4):409–19.PubMedCrossRef
35.
Zhang L, Li X, Wolfe CDA, O’Connell MDL, Wang Y. Diabetes as an Independent risk factor for Stroke recurrence in ischemic Stroke patients: an updated Meta-analysis. Neuroepidemiology. 2021;55(6):427–35.PubMedCrossRef
36.
Cerecedo-Lopez CD, Cantu-Aldana A, Patel NJ, Aziz-Sultan MA, Frerichs KU, Du R. Insulin in the management of Acute ischemic Stroke: a systematic review and Meta-analysis. World Neurosurg. 2020;136:e514–34.PubMedCrossRef
37.
Malmberg K, Ryden L, Wedel H, et al. Intense metabolic control by means of insulin in patients with Diabetes Mellitus and acute Myocardial Infarction (DIGAMI 2): effects on mortality and morbidity. Eur Heart J. 2005;26(7):650–61.PubMedCrossRef
38.
Shahim B, De Bacquer D, De Backer G, et al. The Prognostic Value of Fasting plasma glucose, two-hour postload glucose, and HbA(1c) in patients with coronary artery Disease: a Report from EUROASPIRE IV: a Survey from the European Society of Cardiology. Diabetes Care. 2017;40(9):1233–40.PubMedPubMedCentralCrossRef
39.
Leong A, Chen J, Wheeler E, et al. Mendelian randomization analysis of Hemoglobin A(1c) as a risk factor for coronary artery Disease. Diabetes Care. 2019;42(7):1202–8.PubMedPubMedCentralCrossRef
40.
Larsson SC, Scott RA, Traylor M, et al. Type 2 Diabetes, glucose, insulin, BMI, and ischemic Stroke subtypes: mendelian randomization study. Neurology. 2017;89(5):454–60.PubMedPubMedCentralCrossRef
41.
Strawbridge RJ, van Zuydam NR. Shared Genetic Contribution of type 2 Diabetes and Cardiovascular Disease: implications for prognosis and treatment. Curr Diab Rep. 2018;18(8):59.PubMedPubMedCentralCrossRef
42.
Natarajan P, Young R, Stitziel NO, et al. Polygenic risk score identifies Subgroup with higher burden of Atherosclerosis and greater relative benefit from statin therapy in the primary Prevention setting. Circulation. 2017;135(22):2091–101.PubMedPubMedCentralCrossRef
43.
44.
Wang A, Green JB, Halperin JL, Piccini JP. Sr. Atrial Fibrillation and Diabetes Mellitus: JACC Review topic of the Week. J Am Coll Cardiol. 2019;74(8):1107–15.PubMedCrossRef
45.
Chatterjee NA, Giulianini F, Geelhoed B, et al. Genetic Obesity and the risk of Atrial Fibrillation: causal estimates from mendelian randomization. Circulation. 2017;135(8):741–54.PubMedCrossRef
46.
47.
Carson AP, Fox CS, McGuire DK, et al. Low hemoglobin A1c and risk of all-cause mortality among US adults without Diabetes. Circ Cardiovasc Qual Outcomes. 2010;3(6):661–7.PubMedPubMedCentralCrossRef
48.
Raghavan S, Vassy JL, Ho YL, et al. Diabetes Mellitus-Related all-cause and Cardiovascular Mortality in a national cohort of adults. J Am Heart Assoc. 2019;8(4):e011295.PubMedPubMedCentralCrossRef
49.
Radin MS. Pitfalls in hemoglobin A1c measurement: when results may be misleading. J Gen Intern Med. 2014;29(2):388–94.PubMedCrossRef
Metadata
Title
Associations of combined polygenic risk score and glycemic status with atrial fibrillation, coronary artery disease and ischemic stroke
Authors
Juntae Kim
Dongmin Kim
Han-Joon Bae
Byoung-Eun Park
Tae Soo Kang
Seong-Hoon Lim
Su Yeon Lee
Young Hak Chung
Ji Wung Ryu
Myung-Yong Lee
Pil-Sung Yang
Boyoung Joung
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Cardiovascular Diabetology / Issue 1/2024
Electronic ISSN: 1475-2840
DOI
https://doi.org/10.1186/s12933-023-02021-0

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