Causal inference between physical activity and chronic diseases: Insights from a two-sample Mendelian randomization study

Abstract

Chronic diseases are major causes of global death and disability, significantly impacting individual health and imposing economic burdens. This study aims to investigate the causal relationship between physical activity (PA) and the development of chronic diseases. Using a Mendelian randomization (MR) approach, we incorporated average PA and its subtypes (more than 450 ​000 participants) as exposure measures and eight chronic diseases as outcome measures. Data were obtained from the European Genome-Wide Association Study (GWAS). The primary causal analysis technique employed was the inverse variance weighting (IVW) method, with MR-Egger, weighted median, weighted mode, and simple mode used to validate the results. Sensitivity analyses were performed to assess heterogeneity and pleiotropy. The IVW approach results show that vigorous physical activity (VPA) is associated with a modest reduction in the risk of major coronary heart disease (OR ​= ​0.95, 95% CI: 0.91-0.99, p ​= ​0.01). The causal directions of the other four MR methods are consistent with this result and validated by sensitivity analysis. No substantial associations were found between other levels of PA and chronic disease. Our findings underscore the importance of VPA in preventive cardiology and suggest its potential role in public health initiatives. Further research should explore the impact of PA on different demographic groups and the dose-response relationship of VPA on heart health.

Keywords

Physical activity / Chronic diseases / Major coronary heart disease / Mendelian randomization / Causal inference

Ethical approval statement

All European GWAS countries incorporated in this secondary analysis received ethical approval from their respective institutions for data collection the collection of informed consent and no further ethical approval was required.

Data availability statement

The data employed in this study is freely accessible and can be downloaded from the UK Biobank at http://www.nealelab.is/uk-biobank and the NHGRI-EBI GWAS database at https://www.ebi.ac.uk/gwas/.

CRediT authorship contribution statement

Peng Qiu: Writing - original draft, Software, Methodology, Concep-tualization. Junyu Wu: Writing - original draft, Data curation. Min Li: Validation, Formal analysis. Zhiguang Zhao: Supervision. Qirong Wang: Writing - review & editing, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

We extend our gratitude to the UK Biobank and the NHGRI-EBI GWAS database for making their summary statistics publicly available for use in our study.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.smhs.2024.09.002.

References

[1] Yach D, Leeder SR, Bell J, Kistnasamy B. Global chronic diseases. Science. 2005; 307(5708):317. https://doi.org/10.1126/science.1108656.

[2] Bauer UE, Briss PA, Goodman RA, Bowman BA. Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA. Lancet. 2014; 384(9937):45-52. https://doi.org/10.1016/s0140-6736(14)60648-6.

[3] Noncommunicable diseases.https://www.who.int/news-room/fact-sheets/detail/no ncommunicable-diseases. Accessed June 26, 2024.

[4] Cardiovascular diseases (CVDs).https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds). Accessed June 26, 2024.

[5] GBD 2019 diseases and injuries collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019. Lancet. 2020; 396(10258):1204-1222. https://doi.org/10.1016/s0140-6736(20)30925-9.

[6] GBD 2019 risk factors collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019. Lancet. 2020; 396(10258):1223-1249. https://doi.org/10.1016/s0140-6736(20)30752-2.

[7] Garcia L, Pearce M, Abbas A, et al. Non-occupational physical activity and risk of cardiovascular disease, cancer and mortality outcomes: a dose-response meta-analysis of large prospective studies. Br J Sports Med. 2023; 57(15):979-989. https://doi.org/10.1136/bjsports-2022-105669.

[8] Spruit MA, Pitta F, McAuley E, ZuWallack RL, Nici L. Pulmonary rehabilitation and physical activity in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2015; 192(8):924-933. https://doi.org/10.1164/rccm.201505-0929CI.

[9] Piercy KL, Troiano RP, Ballard RM, et al. The physical activity guidelines for Americans. JAMA. 2018; 320(19):2020-2028. https://doi.org/10.1001/jama.2018.14854.

[10] Mueller S, Winzer EB, Duvinage A, et al. Effect of high-intensity interval training, moderate continuous training, or guideline-based physical activity advice on peak oxygen consumption in patients with heart failure with preserved ejection fraction: a randomized clinical trial. JAMA. 2021; 325(6):542-551. https://doi.org/10.1001/jama.2020.26812.

[11] Weston KS, Wisløff U, Coombes JS. High-intensity interval training in patients with lifestyle-induced cardiometabolic disease: a systematic review and meta-analysis. Br J Sports Med. 2014; 48(16):1227-1234. https://doi.org/10.1136/bjsports-2013-092576.

[12] Boyne P, Billinger SA, Reisman DS, et al. Optimal intensity and duration of walking rehabilitation in patients with chronic stroke: a randomized clinical trial. JAMA Neurol. 2023; 80(4):342-351. https://doi.org/10.1001/jamaneurol.2023.0033.

[13] Aldabayan YS, Ridsdale HA, Alrajeh AM, et al. Pulmonary rehabilitation, physical activity and aortic stiffness in COPD. Respir Res. 2019; 20(1):166. https://doi.org/10.1186/s12931-019-1135-6.

[14] Watson MC, Lloyd J. Physical activity: manifold benefits for health and wellbeing. BMJ. 2022;376:o815. https://doi.org/10.1136/bmj.o815.

[15] Arem H, Moore SC, Patel A, et al. Leisure time physical activity and mortality: a detailed pooled analysis of the dose-response relationship. JAMA Intern Med. 2015; 175(6):959-967. https://doi.org/10.1001/jamainternmed.2015.0533.

[16] Li J, Siegrist J. Physical activity and risk of cardiovascular disease-a meta-analysis of prospective cohort studies. Int J Environ Res Public Health. 2012; 9(2):391-407. https://doi.org/10.3390/ijerph9020391.

[17] Sekula P, Del Greco MF, Pattaro C, Köttgen A. Mendelian randomization as an approach to assess causality using observational data. J Am Soc Nephrol. 2016; 27(11):3253-3265. https://doi.org/10.1681/asn.2016010098.

[18] Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: a review. Res Synth Methods. 2019; 10(4):486-496. https://doi.org/10.1002/jrsm.1346.

[19] Zhuo C, Zhao J, Chen M, Lu Y. Physical activity and risks of cardiovascular diseases: a mendelian randomization study. Front Cardiovasc Med. 2021;8:722154. https://doi.org/10.3389/fcvm.2021.722154.

[20] Doherty A, Smith-Byrne K, Ferreira T, et al. GWAS identifies 14 loci for device-measured physical activity and sleep duration. Nat Commun. 2018; 9(1):5257. https://doi.org/10.1038/s41467-018-07743-4.

[21] Emdin CA, Khera AV, Kathiresan S. Mendelian randomization. JAMA. 2017; 318(19): 1925-1926. https://doi.org/10.1001/jama.2017.17219.

[22] Klimentidis YC, Raichlen DA, Bea J, et al. Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE. Int J Obes. 2018; 42(6):1161-1176. https://doi.org/10.1038/s41366-018-0120-3.

[23] Qi G, Dutta D, Leroux A, et al. Genome-wide association studies of 27 accelerometry-derived physical activity measurements identified novel loci and genetic mechanisms. Genet Epidemiol. 2022; 46(2):122-138. https://doi.org/10.1002/gepi.22441.

[24] Sudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015; 12(3):e1001779. https://doi.org/10.1371/journal.pmed.1001779.

[25] Vaucher J, Keating BJ, Lasserre AM, et al. Cannabis use and risk of schizophrenia: a Mendelian randomization study. Mol Psychiatry. 2018; 23(5):1287-1292. https://doi.org/10.1038/mp.2016.252.

[26] Prasad S, Sung B, Aggarwal BB. Age-associated chronic diseases require age-old medicine: role of chronic inflammation. Prev Med. 2012;54Suppl(Suppl):S29-S37. https://doi.org/10.1016/j.ypmed.2011.11.011.

[27] Larsson SC, Burgess S. Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies. BMC Med. 2021; 19(1):320. https://doi.org/10.1186/s12916-021-02188-x.

[28] Liangpunsakul S, Crabb DW, Qi R. Relationship among alcohol intake, body fat, and physical activity: a population-based study. Ann Epidemiol. 2010; 20(9):670-675. https://doi.org/10.1016/j.annepidem.2010.05.014.

[29] Kamat MA, Blackshaw JA, Young R, et al. PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019; 35(22): 4851-4853. https://doi.org/10.1093/bioinformatics/btz469.

[30] Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008; 27(8):1133-1163. https://doi.org/10.1002/sim.3034.

[31] Pierce BL, Ahsan H, Vanderweele TJ. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol. 2011; 40(3):740-752. https://doi.org/10.1093/ije/dyq151.

[32] Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013; 37(7): 658-665. https://doi.org/10.1002/gepi.21758.

[33] Greco MF, Minelli C, Sheehan NA, Thompson JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015; 34(21):2926-2940. https://doi.org/10.1002/sim.6522.

[34] Burgess S, Thompson SG. Mendelian Randomization.second ed. Chapman and Hall/CRC; 2021.

[35] Yin KJ, Huang JX, Wang P, et al. No genetic causal association between periodontitis and arthritis: a bidirectional two-sample Mendelian Randomization analysis. Front Immunol. 2022;13:808832. https://doi.org/10.3389/fimmu.2022.808832.

[36] Qiu P, Chen M, Lv S, Xie J, Wu J. The association between walking pace and hand grip strength with the risk of chronic obstructive pulmonary disease: a bidirectional Mendelian randomization study. BMC Pulm Med. 2023; 23(1):450. https://doi.org/10.1186/s12890-023-02759-z.

[37] Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015; 44(2):512-525. https://doi.org/10.1093/ije/dyv080.

[38] 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):304-314. https://doi.org/10.1002/gepi.21965.

[39] Hemani G, Tilling K,Davey Smith G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017; 13(11): e1007081. https://doi.org/10.1371/journal.pgen.1007081.

[40] Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018; 50(5):693-698. https://doi.org/10.1038/s41588-018-0099-7.

[41] Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG. Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants. Epidemiology. 2017; 28(1):30-42. https://doi.org/10.1097/ede.0000000000000559.

[42] The TwoSampleMR packages.https://github.com/MRCIEU/TwoSampleMR/releases/tag/0.5.6. Accessed October 1, 2023.

[43] The MRPRESSO packages.https://github.com/rondolab/MRPRESSO/blob/master/DESCRIPTION. Accessed October 1, 2023.

[44] Ekelund U, Tarp J, Steene-Johannessen J, et al. Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis. BMJ. 2019;366:l4570. https://doi.org/10.1136/bmj.l4570.

[45] Evenson KR, Wen F, Herring AH.Associations of accelerometry-assessed and self-reported physical activity and sedentary behavior with all-cause and cardiovascular mortality among US adults. Am J Epidemiol. 2016; 184(9):621-632. https://doi.org/10.1093/aje/kww070.

[46] Ekelund U, Brown WJ, Steene-Johannessen J, et al. Do the associations of sedentary behaviour with cardiovascular disease mortality and cancer mortality differ by physical activity level? A systematic review and harmonised meta-analysis of data from 850 060 participants. Br J Sports Med. 2019; 53(14):886-894. https://doi.org/10.1136/bjsports-2017-098963.

[47] Yu S, Patterson CC, Yarnell JW. Is vigorous physical activity contraindicated in subjects with coronary heart disease? Evidence from the Caerphilly study. Eur Heart J. 2008; 29(5):602-608. https://doi.org/10.1093/eurheartj/ehn012.

[48] Stewart RAH, Held C, Hadziosmanovic N, et al. Physical activity and mortality in patients with stable coronary heart disease. J Am Coll Cardiol. 2017; 70(14): 1689-1700. https://doi.org/10.1016/j.jacc.2017.08.017.

[49] Morris JN. Exercise in the prevention of coronary heart disease: today's best buy in public health. Med Sci Sports Exerc. 1994; 26(7):807-814.

[50] Ahmadi MN, Clare PJ, Katzmarzyk PT, Del Pozo Cruz B, Lee IM, Stamatakis E. Vigorous physical activity, incident heart disease, and cancer: how little is enough? Eur Heart J. 2022; 43(46):4801-4814. https://doi.org/10.1093/eurheartj/ehac572.

[51] Islam H, Gibala MJ, Little JP. Exercise snacks: a novel strategy to improve cardiometabolic health. Exerc Sport Sci Rev. 2022; 50(1):31-37. https://doi.org/10.1249/jes.0000000000000275.

[52] Blodgett JM, Ahmadi MN, Atkin AJ, et al. Device-measured physical activity and cardiometabolic health: the prospective physical activity, sitting, and sleep (ProPASS) consortium. Eur Heart J. 2024;45(6):458-471. https://doi.org/10.1093/eurheartj/ehad717.

[53] Arnett DK, Blumenthal RS, Albert MA, et al. ACC/AHA guideline on the primary prevention of cardiovascular disease: executive summary: a report of the American college of Cardiology/American heart association task force on clinical practice guidelines. Circulation. 2019; 140(11):e563-e595. https://doi.org/10.1161/cir.0000000000000677.

[54] Bielemann RM, Ramires VV, Gigante DP, Hallal PC, Horta BL. Longitudinal and cross-sectional associations of physical activity with triglyceride and HDLc levels in young male adults. J Phys Act Health. 2014;11(4):784-789. https://doi.org/10.1123/jpah.2012-0175.

[55] Izadi MR, Ghardashi Afousi A, Asvadi Fard M, Babaee Bigi MA. High-intensity interval training lowers blood pressure and improves apelin and NOx plasma levels in older treated hypertensive individuals. J Physiol Biochem. 2018;74(1):47-55. https://doi.org/10.1007/s13105-017-0602-0.

[56] Clark T, Morey R, Jones MD, et al. High-intensity interval training for reducing blood pressure: a randomized trial vs. moderate-intensity continuous training in males with overweight or obesity. Hypertens Res. 2020;43(5):396-403. https://doi.org/10.1038/s41440-019-0392-6.

[57] Cruz R, Koch S, Matsuda M, et al. Air pollution and high-intensity interval exercise: implications to anti-inflammatory balance, metabolome and cardiovascular responses. Sci Total Environ. 2022;809:151094. https://doi.org/10.1016/j.scitotenv.2021.151094.

[58] Martín-Ventura JL, Madrigal-Matute J, Mu~noz-Garcia B, et al. Increased CD74 expression in human atherosclerotic plaques: contribution to inflammatory responses in vascular cells. Cardiovasc Res. 2009;83(3):586-594. https://doi.org/10.1093/cvr/cvp141.

[59] Ayubi N, Halip MF, Komaini A, et al. Citrus limon tiene el potential de reducir el estrés oxidativo y la inflamación después de la actividad física/ejercicio: revisión sistemática (citrus limon has the potential to reduce oxidative stress and inflammation after physical activity/exercise: systematic review). Retos. 2024;51: 1168-1173. https://doi.org/10.47197/retos.v51.10154.

[60] Gusti Handayani S, Ayubi N, Komaini A, et al. Los ácidos grasos poliinsaturados n-3 (PUFA) y el ejercicio físico tienen el potential de reducir la intensi-dad del dolor en mujeres con dismenorrea primaria: systematic review (N-3 polyunsaturated fatty acids (PUFAs) and physical exercise have the potential to reduce pain intensity in women with primary dysmenorrhea: systematic review). Retos. 2023;48:106-112. https://doi.org/10.47197/retos.v48.96629.

[61] Riddell MC, Gallen IW, Smart CE, et al. Exercise management in type 1 diabetes: a consensus statement. Lancet Diabetes Endocrinol. 2017;5(5):377-390. https://doi.org/10.1016/s2213-8587(17)30014-1.

[62] Qian J, Xiao Q, Walkup MP, et al. Association of timing of moderate-to-vigorous physical activity with changes in glycemic control over 4 years in adults with type 2 diabetes from the look ahead trial. Diabetes Care. 2023;46(7):1417-1424. https://doi.org/10.2337/dc22-2413.