A two-sample Mendelian randomization study on the relationship of body weight, body mass index, and waist circumference with cardiac arrest

doi:10.5847/wjem.j.1920-8642.2025.035

Abstract

Abstract:

BACKGROUND: This study aims to explore the causal relationship of body weight, body mass index (BMI), and waist circumference (WC) with the risk of cardiac arrest (CA) using two-sample Mendelian randomization (MR).
METHODS: Data were summarized using genome-wide association studies (GWAS). Two-sample MR analyses were performed using the inverse variance weighting (IVW) method, the weighted median method, and the MR-Egger analysis. Heterogeneity test and sensitivity analysis were performed using Cochran’s Q test and the leave-one-out method, respectively. The Steiger test was used to detect reverse causality. Bayesian model-averaged MR was used to identify the most influential risk factors.
RESULTS: A total of 13 GWAS data were collected for BMI, body weight and WC. IVW analyses showed a positive correlation of body weight, BMI, and WC with CA (all OR>1 and P<0.05), with MR-Egger and weighted median methods confirming the IVW findings. No horizontal pleiotropy or heterogeneity was observed. Sensitivity analysis indicated that no single nucleotide polymorphism (SNP) caused significant changes in overall causality. Bayesian model-averaged MR was also used to rank causality based on marginal inclusion probability (MIP), and the corresponding model-averaged causal estimate (MACE) were confirmed, which indicated that WC (GWAS ID: ukb-b-9405) was the highest-ranked risk factor (MIP=0.119, MACE=0.011); its posterior probability was 0.057. A total of 14 sex-specific GWAS data on weight, BMI, and WC were analyzed in relationship with CA, and the MR results showed no significant effects of sex-specific factors.
CONCLUSION: Body weight, BMI, and WC are causally associated with an increased risk of CA, with WC identified as the most important risk factor.

Key words: Body weight, Body mass index, Waist circumference, Cardiac arrest, Mendelian randomization

Tingting Xu, Shaokun Wang, Liqiang Zhao, Jiawen Wang, Jihong Xing. A two-sample Mendelian randomization study on the relationship of body weight, body mass index, and waist circumference with cardiac arrest[J]. World Journal of Emergency Medicine, 2025, 16(2): 129-135.

Figures/Tables 6

Table 1.

Table 2.

Results of Mendelian randomization analyses on the association of body weight, body mass index, and waist circumference with cardiac arrest

Exposure	GWAS ID	Method	Numbers of SNPs	β	P-value	OR (95% CI)
BMI	ebi-a-GCST90013974	IVW	327	0.308	0.004	1.361 (1.099-1.684)
		MR-Egger	327	0.025	0.933	1.025 (0.566-1.857)
		WM	327	0.219	0.263	1.245 (0.847-1.832)
BMI	ebi-a-GCST90018947	IVW	383	0.229	0.026	1.257 (1.026-1.540)
		MR-Egger	383	0.072	0.799	1.075 (0.615-1.879)
		WM	383	0.196	0.325	1.217 (0.822-1.802)
BMI	ebi-a-GCST90025994	IVW	340	0.412	0.0001	1.510 (1.216-1.876)
		MR-Egger	340	0.219	0.458	1.245 (0.696-2.227)
		WM	340	0.337	0.099	1.401 (0.938-2.094)
BMI	ebi-a-GCST90029007	IVW	441	0.278	0.005	1.321 (1.085-1.608)
		MR-Egger	441	0.243	0.380	1.275 (0.740-2.196)
		WM	441	0.319	0.074	1.376 (0.968-1.954)
BMI	ieu-b-40	IVW	461	0.314	0.002	1.369 (1.116-1.679)
		MR-Egger	461	0.387	0.177	1.473 (0.839-2.583)
		WM	461	0.047	0.802	1.048 (0.724-1.517)
BMI	ukb-a-248	IVW	278	0.312	0.002	1.367 (1.117-1.672)
		MR-Egger	278	0.094	0.761	1.098 (0.597-2.022)
		WM	278	0.205	0.264	1.228 (0.855-1.763)
BMI	ukb-b-19953	IVW	412	0.389	7.36e^-05	1.476 (1.217-1.790)
		MR-Egger	412	0.280	0.315	1.323 (0.766-2.287)
		WM	412	0.228	0.199	1.256 (0.886-1.799)
BMI	ukb-b-2303	IVW	408	0.363	0.0002	1.438 (1.183-1.748)
		MR-Egger	408	0.185	0.510	1.203 (0.693-2.088)
		WM	408	0.231	0.211	1.260 (0.876-1.814)
Weight	ukb-a-249	IVW	317	0.271	0.008	1.312 (1.070-1.608)
		MR-Egger	317	0.151	0.595	1.164 (0.664-2.038)
		WM	317	0.233	0.166	1.262 (0.907-1.758)
Weight	ukb-b-11842	IVW	468	0.282	0.004	1.326 (1.092-1.611)
		MR-Egger	468	0.107	0.681	1.113 (0.667-1.856)
		WM	468	0.264	0.109	1.302 (0.942-1.800)
Weight	ukb-b-12039	IVW	456	0.265	0.007	1.304 (1.072-1.586)
		MR-Egger	456	0.296	0.261	1.345 (0.802-2.254)
		WM	456	0.264	0.124	1.303 (0.929-1.827)
WC	ukb-a-382	IVW	206	0.308	0.027	1.360 (1.035-1.788)
		MR-Egger	206	0.725	0.104	2.065 (0.863-4.939)
		WM	206	0.250	0.268	1.284 (0.824-2.002)
WC	ukb-b-9405	IVW	342	0.375	0.003	1.455 (1.132-1.870)
		MR-Egger	342	0.421	0.265	1.523 (0.726-3.195)
		WM	342	0.279	0.213	1.322 (0.851-2.053)

Table 2.

Table 3.

Table 4.

Table 5.

Table 6.

References 42

1	Myerburg RJ. Sudden cardiac death: interface between pathophysiology and epidemiology. Card Electrophysiol Clin. 2017; 9(4): 515-24. doi: S1877-9182(17)30089-8 pmid: 29173398
2	Kersten A. Resuscitation - practical implementation of guidelines and standards in the hospital. Dtsch Med Wochenschr. 2020; 145(8): 555-68.
3	Riva G, Ringh M, Jonsson M, Svensson L, Herlitz J, Claesson A, et al. Survival in out-of-hospital cardiac arrest after standard cardiopulmonary resuscitation or chest compressions only before arrival of emergency medical services: nationwide study during three guideline periods. Circulation. 2019; 139(23): 2600-9.
4	Perkins GD, Graesner JT, Semeraro F, Olasveengen T, Soar J, Lott C, et al. European Resuscitation Council guidelines 2021: executive summary. Resuscitation. 2021; 161: 1-60. doi: 10.1016/j.resuscitation.2021.02.003 pmid: 33773824
5	Hwang SO, Cha KC, Jung WJ, Roh YI, Kim TY, Chung SP, et al. 2020 Korean Guidelines for Cardiopulmonary Resuscitation. Part 2. Environment for cardiac arrest survival and the chain of survival. Clin Exp Emerg Med. 2021; 8(Suppl): S8-S14.
6	Koskinas KC, Van Craenenbroeck EM, Antoniades C, Blüher M, Gorter TM, Hanssen H, et al. Obesity and cardiovascular disease: an ESC clinical consensus statement. Eur J Prev Cardiol. 2025; 32(3):184-220.
7	Valenzuela PL, Carrera-Bastos P, Castillo-García A, Lieberman DE, Santos-Lozano A, Lucia A. Obesity and the risk of cardiometabolic diseases. Nat Rev Cardiol. 2023; 20(7): 475-94. doi: 10.1038/s41569-023-00847-5 pmid: 36927772
8	Hong Y, Ullah R, Wang JB, Fu JF. Trends of obesity and overweight among children and adolescents in China. World J Pediatr. 2023; 19(12):1115-26. doi: 10.1007/s12519-023-00709-7 pmid: 36920656
9	Sung CW, Huang CH, Chen WJ, Chang WT, Wang CH, Wu YW, et al. Obese cardiogenic arrest survivors with significant coronary artery disease had worse in-hospital mortality and neurological outcomes. Sci Rep. 2020; 10(1): 18638.
10	Geri G, Savary G, Legriel S, Dumas F, Merceron S, Varenne O, et al. Influence of body mass index on the prognosis of patients successfully resuscitated from out-of-hospital cardiac arrest treated by therapeutic hypothermia. Resuscitation. 2016; 109: 49-55. doi: S0300-9572(16)30470-1 pmid: 27743918
11	Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath CW Jr. Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med. 1999; 341(15): 1097-105.
12	Twig G, Yaniv G, Levine H, Leiba AD, Goldberger N, Derazne E, et al. Body-mass index in 2.3 million adolescents and cardiovascular death in adulthood. N Engl J Med. 2016; 374(25): 2430-40.
13	Jeong JH, Kim YG, Han KD, Roh SY, Lee HS, Choi YY, et al. Association of temporal change in body mass index with sudden cardiac arrest in diabetes mellitus. Cardiovasc Diabetol. 2024; 23(1): 46. doi: 10.1186/s12933-024-02130-4 pmid: 38281993
14	Matsushita Y, Nakagawa T, Shinohara M, Yamamoto S, Takahashi Y, Mizoue T, et al. How can waist circumference predict the body composition? Diabetol Metab Syndr. 2014; 6(1): 11. doi: 10.1186/1758-5996-6-11 pmid: 24472677
15	Coutinho T, Goel K, Corrêa de Sá D, Carter RE, Hodge DO, Kragelund C, et al. Combining body mass index with measures of central obesity in the assessment of mortality in subjects with coronary disease: role of “normal weight central obesity”. J Am Coll Cardiol. 2013; 61(5): 553-60. doi: 10.1016/j.jacc.2012.10.035 pmid: 23369419
16	Kim YG, Jeong JH, Roh SY, Han KD, Choi YY, Min K, et al. Obesity is indirectly associated with sudden cardiac arrest through various risk factors. J Clin Med. 2023; 12(5): 2068.
17	Nuttall FQ. Body mass index: obesity, BMI, and health: a critical review. Nutr Today. 2015; 50(3): 117-28. doi: 10.1097/NT.0000000000000092 pmid: 27340299
18	Busetto L, Bettini S, Makaronidis J, Roberts CA, Halford JCG, Batterham RL. Mechanisms of weight regain. Eur J Intern Med. 2021; 93: 3-7. doi: 10.1016/j.ejim.2021.01.002 pmid: 33461826
19	Nishida C, Ko GT, Kumanyika S. Body fat distribution and noncommunicable diseases in populations: overview of the 2008 WHO Expert Consultation on Waist Circumference and Waist-Hip Ratio. Eur J Clin Nutr. 2010; 64(1): 2-5. doi: 10.1038/ejcn.2009.139 pmid: 19935820
20	Long YW, Tang LH, Zhou YY, Zhao SS, Zhu H. Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study. BMC Med. 2023; 21(1): 66. doi: 10.1186/s12916-023-02761-6 pmid: 36810112
21	Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan NA, Thompson JR. 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. 2016; 45(6): 1961-74. doi: 10.1093/ije/dyw220 pmid: 27616674
22	Burgess S, Thompson SG; CRP CHD Genetics Collaboration. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011; 40(3): 755-64. doi: 10.1093/ije/dyr036 pmid: 21414999
23	Staley JR, Blackshaw J, Kamat MA, Ellis S, Surendran P, Sun BB, et al. PhenoScanner: a database of human genotype-phenotype associations. Bioinformatics. 2016; 32(20): 3207-9.
24	Lee CH, Cook S, Lee JS, Han B. Comparison of two meta-analysis methods: inverse-variance-weighted average and weighted sum of Z-scores. Genomics Inform. 2016; 14(4): 173-80.
25	Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016; 40(4): 304-14. doi: 10.1002/gepi.21965 pmid: 27061298
26	Cohen JF, Chalumeau M, Cohen R, Korevaar DA, Khoshnood B, Bossuyt PMM. Cochran’s Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy. J Clin Epidemiol. 2015; 68(3): 299-306.
27	Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017; 32(5): 377-89. doi: 10.1007/s10654-017-0255-x pmid: 28527048
28	Lord J, Jermy B, Green R, Wong A, Xu J, Legido-Quigley C, et al. Mendelian randomization identifies blood metabolites previously linked to midlife cognition as causal candidates in Alzheimer’s disease. Proc Natl Acad Sci USA. 2021; 118(16): e2009808118.
29	Zuber V, Colijn JM, Klaver C, Burgess S. Selecting likely causal risk factors from high-throughput experiments using multivariable Mendelian randomization. Nat Commun. 2020; 11(1): 29. doi: 10.1038/s41467-019-13870-3 pmid: 31911605
30	Mi JR, Jiang LJ, Liu ZY, Wu X, Zhao N, Wang YZ, et al. Identification of blood metabolites linked to the risk of cholelithiasis: a comprehensive Mendelian randomization study. Hepatol Int. 2022; 16(6): 1484-93. doi: 10.1007/s12072-022-10360-5 pmid: 35704268
31	Hu YL, Tan P, Wang JT, Zeng J, Li Q, Yan SJ, et al. Mendelian randomization study to investigate the causal relationship between plasma homocysteine and chronic obstructive pulmonary disease. World J Emerg Med. 2023; 14(5): 367-71. doi: 10.5847/wjem.j.1920-8642.2023.078 pmid: 37908800
32	Global BMI Mortality Collaboration, Di Angelantonio E, Bhupathiraju ShN, Wormser D, Gao P, Kaptoge S, et al. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 2016; 388(10046): 776-86. doi: 10.1016/S0140-6736(16)30175-1 pmid: 27423262
33	Paratz ED, Ashokkumar S, van Heusden A, Smith K, Zentner D, Morgan N, et al. Obesity in young sudden cardiac death: rates, clinical features, and insights into people with body mass index >50kg/m2. Am J Prev Cardiol. 2022; 11: 100369.
34	Cavalera M, Wang JH, Frangogiannis NG. Obesity, metabolic dysfunction, and cardiac fibrosis: pathophysiological pathways, molecular mechanisms, and therapeutic opportunities. Transl Res. 2014; 164(4): 323-35. doi: 10.1016/j.trsl.2014.05.001 pmid: 24880146
35	Esposito K, Nicoletti G, Marzano S, Gualdiero P, Carusone C, Marfella R, et al. Autonomic dysfunction associates with prolongation of QT intervals and blunted night BP in obese women with visceral obesity. J Endocrinol Invest. 2002; 25(11): RC32-5. doi: 10.1007/BF03344061 pmid: 12553548
36	Tudorancea I, Șerban IL, Șerban DN, Costache-Enache II, Cătălin C, Naum AG, et al. Sympathetic nervous system inhibition enhances cardiac metabolism and improves hemodynamics and glucose-insulin dynamics in obese and lean rat models. Sci Rep. 2025; 15(1): 503.
37	Koparkar G, Biswas DA. Adiposity and cardiac defects: pathophysiology and etiology. Cureus. 2023; 15(1): e34026.
38	Ouchi N, Parker JL, Lugus JJ, Walsh K. Adipokines in inflammation and metabolic disease. Nat Rev Immunol. 2011; 11(2): 85-97. doi: 10.1038/nri2921 pmid: 21252989
39	Ren J, Wu NN, Wang SY, Sowers JR, Zhang YM. Obesity cardiomyopathy: evidence, mechanisms, and therapeutic implications. Physiol Rev. 2021; 101(4): 1745-807.
40	Cerhan JR, Moore SC, Jacobs EJ, Kitahara CM, Rosenberg PS, Adami HO, et al. A pooled analysis of waist circumference and mortality in 650, 000 adults. Mayo Clin Proc. 2014; 89(3): 335-45.
41	Li X, Katashima M, Yasumasu T, Li KJ. Visceral fat area, waist circumference and metabolic risk factors in abdominally obese Chinese adults. Biomed Environ Sci. 2012; 25(2): 141-8. pmid: 22998819
42	Chavda MP, Pakavakis A, Ernest D. Does obesity influence the outcome of the patients following a cardiac arrest? Indian J Crit Care Med. 2020; 24(11):1077-80.

Exposure	GWAS ID	Sample size	Number of SNPs	Year
BMI	ieu-b-40	681,275	2,336,260	2018
BMI	ebi-a-GCST90029007	532,396	11,973,091	2018
BMI	ukb-b-19953	461460	9,851,867	2018
BMI	ebi-a-GCST90025994	457756	4,238,669	2021
BMI	ukb-b-2303	454,884	9,851,867	2018
BMI	ebi-a-GCST90013974	407,609	10,783,680	2021
BMI	ebi-a-GCST90018947	359,983	19,066,885	2021
BMI	ukb-a-248	336,107	10,894,596	2017
Body weight	ukb-b-11842	461,632	9,851,867	2018
Body weight	ukb-b-12039	454,893	9,851,867	2018
Body weight	ukb-a-249	336,227	10,894,596	2017
WC	ukb-a-382	336,639	10,894,596	2017
WC	ukb-b-9405	462,166	9,851,867	2018

[1]	Wachira Wongtanasarasin, Daniel K. Nishijima, Wanrudee Isaranuwatchai, Jeffrey S. Hoch. Real-world cost-effectiveness of targeted temperature management in out-of-hospital cardiac arrest survivors: results from an academic medical center [J]. World Journal of Emergency Medicine, 2025, 16(1): 28-34.
[2]	Subi Abudurexiti, Shihai Xu, Zhangping Sun, Yi Jiang, Ping Gong. Glucose metabolic reprogramming-related parameters for the prediction of 28-day neurological prognosis and all-cause mortality in patients after cardiac arrest: a prospective single-center observational study [J]. World Journal of Emergency Medicine, 2024, 15(3): 197-203.
[3]	Rashed Alremeithi, Quincy K. Tran, Megan T. Quintana, Soroush Shahamatdar, Ali Pourmand. Approach to traumatic cardiac arrest in the emergency department: a narrative literature review for emergency providers [J]. World Journal of Emergency Medicine, 2024, 15(1): 3-9.
[4]	Jing Yang, Hanqi Tang, Shihuan Shao, Feng Xu, Yangyang Fu, Shengyong Xu, Chen Li, Yan Li, Yang Liu, Joseph Harold Walline, Huadong Zhu, Yuguo Chen, Xuezhong Yu, Jun Xu. A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study [J]. World Journal of Emergency Medicine, 2024, 15(1): 16-22.
[5]	Yanlan Hu, Ping Tan, Juntao Wang, Jun Zeng, Quan Li, Shijiao Yan, Wenjie Hao, Lanfen He, Xingyue Song, Caihong Zhang, Chuanzhu Lyu. Mendelian randomization study to investigate the causal relationship between plasma homocysteine and chronic obstructive pulmonary disease [J]. World Journal of Emergency Medicine, 2023, 14(5): 367-371.
[6]	Gannan Wang, Zhe Wang, Yi Zhu, Zhongman Zhang, Wei Li, Xufeng Chen, Yong Mei. The neuro-prognostic value of the ion shift index in cardiac arrest patients following extracorporeal cardiopulmonary resuscitation [J]. World Journal of Emergency Medicine, 2023, 14(5): 354-359.
[7]	Guang-qi Guo, Yan-nan Ma, Shuang Xu, Hong-rong Zhang, Peng Sun. Effect of post-rewarming fever after targeted temperature management in cardiac arrest patients: a systematic review and meta-analysis [J]. World Journal of Emergency Medicine, 2023, 14(3): 217-223.
[8]	Gan-nan Wang, Zhong-man Zhang, Wen Chen, Xiao-quan Xu, Jin-song Zhang. Timing of brain computed tomography for predicting neurological prognosis in comatose cardiac arrest survivors: a retrospective observational study [J]. World Journal of Emergency Medicine, 2022, 13(5): 349-354.
[9]	Shi-jiao Yan, Mei Chen, Jing Wen, Wen-ning Fu, Xing-yue Song, Huan-jun Chen, Ri-xing Wang, Mei-ling Chen, Xiao-tong Han, Chuan-zhu Lyu. Global research trends in cardiac arrest research: a visual analysis of the literature based on CiteSpace [J]. World Journal of Emergency Medicine, 2022, 13(4): 290-296.
[10]	Hong-li Xiao, Lian-xing Zhao, Jun Yang, Nan Tong, Le An, Guo-xing Wang, Miao-rong Xie, Chun-sheng Li. Increasing angiotensin-converting enzyme (ACE) 2/ACE axes ratio alleviates early pulmonary vascular remodeling in a porcine model of acute pulmonary embolism with cardiac arrest [J]. World Journal of Emergency Medicine, 2022, 13(3): 208-214.
[11]	Chao-yu Lei, Heng-wei Qin, Xue-jie Dong, Jia-lin You, Lin Zhang. Layperson’s performance on an unconversant type of AED device: A prospective crossover simulation experimental study [J]. World Journal of Emergency Medicine, 2022, 13(2): 98-105.
[12]	Ji-yang Ling, Chun-sheng Li, Yun Zhang, Xiao-li Yuan, Bo Liu, Yong Liang, Qiang Zhang. Protective effect of extracorporeal membrane pulmonary oxygenation combined with cardiopulmonary resuscitation on post-resuscitation lung injury [J]. World Journal of Emergency Medicine, 2021, 12(4): 303-308.
[13]	Wei-jing Shao, Ting-ting Shu, Shuang Xu, Li-cai Liang, Jehane Michael Le Grange, Yu-ran Zhou, He Huang, Yu Cai, Qing Zhang, Peng Sun. Left-sided vagus nerve stimulation improves cardiopulmonary resuscitation outcomes in rats as effectively as right-sided vagus nerve stimulation [J]. World Journal of Emergency Medicine, 2021, 12(4): 309-316.
[14]	Xue-jie Dong, Lin Zhang, Yue-lin Yu, Shu-xiao Shi, Xiao-chen Yang, Xiao-qian Zhang, Shuang Tian, Helge Myklebust, Guo-hong Li, Zhi-jie Zheng. The general public’s ability to operate automated external defibrillator: A controlled simulation study [J]. World Journal of Emergency Medicine, 2020, 11(4): 238-245.
[15]	Ye-cheng Liu, Yan-meng Qi, Hui Zhang, Joseph Walline, Hua-dong Zhu. A survey of ventilation strategies during cardiopulmonary resuscitation [J]. World Journal of Emergency Medicine, 2019, 10(4): 222-227.