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Epidemiology and Population Health

The causal role of elevated uric acid and waist circumference on the risk of metabolic syndrome components

Abstract

Background/objectives

Hyperuricemia has been found to cluster with multiple components of metabolic syndrome (MetS). It is unclear whether hyperuricemia is a downstream result of MetS or may play an upstream role in MetS development. Using the Mendelian randomization (MR) method, we examined the causal relationship between elevated uric acid and the various components of MetS with waist circumference as a positive control.

Subjects/methods

Data from 10k participants of Taiwan Biobank was used to carry out MR analysis with uric acid risk score (wGRS) and waist circumference wGRS as instrumental variables and components of MetS as the outcomes.

Results

We found that genetically increased serum uric acid corresponds to a significant increment of triglyceride (β = 0.065, p < 0.0001), systolic blood pressure (β = 1.047, p = 0.0005), diastolic blood pressure (β = 0.857, p < 0.0001), and mean arterial pressure (β = 0.920, p < 0.0001), but a significant reduction of high-density lipoprotein cholesterol (β = −0.020, p = 0.0014). Uric acid wGRS was not associated with fasting serum glucose, HbA1C, waist circumference, or BMI. On the other hand, waist circumference was causally associated with all the components of MetS including uric acid.

Conclusions

Our MR investigation shows that uric acid increment may augment the risk of MetS through increasing blood pressure and triglyceride levels and lowering HDL-C value but not through accumulating fat or hyperglycemia. High waist circumference may be a causal agent for all the components of MetS including hyperuricemia.

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Data availability

The data used in this study can be applied from TWB at https://www.twbiobank.org.tw/new_web_en/index.php.

References

  1. Thomas G, Sehgal AR, Kashyap SR, Srinivas TR, Kirwan JP, Navaneethan SD. Metabolic syndrome and kidney disease: a systematic review and meta-analysis. Clin J Am Soc Nephrol. 2011;6:2364–73.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Frisardi V, Solfrizzi V, Seripa D, Capurso C, Santamato A, Sancarlo D, et al. Metabolic-cognitive syndrome: a cross-talk between metabolic syndrome and Alzheimer’s disease. Ageing Res Rev. 2010;9:399–417.

    Article  PubMed  Google Scholar 

  3. Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract. 2014;2014:943162.

    PubMed  PubMed Central  Google Scholar 

  4. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5.

    Article  CAS  PubMed  Google Scholar 

  5. Paley CA, Johnson MI. Abdominal obesity and metabolic syndrome: exercise as medicine? BMC Sports Sci Med Rehabil. 2018;10:7.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Shen BJ, Todaro JF, Niaura R, McCaffery JM, Zhang J, Spiro A 3rd, et al. Are metabolic risk factors one unified syndrome? Modeling the structure of the metabolic syndrome X. Am J Epidemiol. 2003;157:701–11.

    Article  PubMed  Google Scholar 

  7. Maison P, Byrne CD, Hales CN, Day NE, Wareham NJ. Do different dimensions of the metabolic syndrome change together over time? Evidence supporting obesity as the central feature. Diabetes Care. 2001;24:1758–63.

    Article  CAS  PubMed  Google Scholar 

  8. Tsay YC, Chen CH, Pan WH. Ages at onset of 5 cardiometabolic diseases adjusting for nonsusceptibility: implications for the pathogenesis of metabolic syndrome. Am J Epidemiol. 2016;184:366–77.

    Article  PubMed  Google Scholar 

  9. Lee JJ, Ahn J, Hwang J, Han SW, Lee KN, Kim JB, et al. Relationship between uric acid and blood pressure in different age groups. Clin Hypertens. 2015;21:14.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Chu NF, Wang DJ, Liou SH, Shieh SM. Relationship between hyperuricemia and other cardiovascular disease risk factors among adult males in Taiwan. Eur J Epidemiol. 2000;16:13–7.

    Article  CAS  PubMed  Google Scholar 

  11. Bonora E, Targher G, Zenere MB, Saggiani F, Cacciatori V, Tosi F, et al. Relationship of uric acid concentration to cardiovascular risk factors in young men. Role of obesity and central fat distribution. The Verona Young Men Atherosclerosis Risk Factors Study. Int J Obes Relat Metab Disord. 1996;20:975–80.

    CAS  PubMed  Google Scholar 

  12. Chen LY, Zhu WH, Chen ZW, Dai HL, Ren JJ, Chen JH, et al. Relationship between hyperuricemia and metabolic syndrome. J Zhejiang Univ Sci B. 2007;8:593–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cicero AFG, Fogacci F, Giovannini M, Grandi E, Rosticci M, D’Addato S, et al. Serum uric acid predicts incident metabolic syndrome in the elderly in an analysis of the Brisighella Heart Study. Sci Rep. 2018;8:11529.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Chiang KM, Tsay YC, Vincent Ng TC, Yang HC, Huang YT, Chen CH, et al. Is hyperuricemia, an early-onset metabolic disorder, causally associated with cardiovascular disease events in Han Chinese? J Clin Med. 2019;8:1202.

  15. Jalalzadeh M, Nurcheshmeh Z, Mohammadi R, Mousavinasab N, Ghadiani MH. The effect of allopurinol on lowering blood pressure in hemodialysis patients with hyperuricemia. J Res Med Sci. 2012;17:1039–46.

    PubMed  PubMed Central  Google Scholar 

  16. Feig DI, Soletsky B, Johnson RJ. Effect of allopurinol on blood pressure of adolescents with newly diagnosed essential hypertension: a randomized trial. JAMA. 2008;300:924–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Carnethon MR, Fortmann SP, Palaniappan L, Duncan BB, Schmidt MI, Chambless LE. Risk factors for progression to incident hyperinsulinemia: the Atherosclerosis Risk in Communities Study, 1987–1998. Am J Epidemiol. 2003;158:1058–67.

    Article  PubMed  Google Scholar 

  18. Kanbay M, Jensen T, Solak Y, Le M, Roncal-Jimenez C, Rivard C, et al. Uric acid in metabolic syndrome: from an innocent bystander to a central player. Eur J Intern Med. 2016;29:3–8.

    Article  CAS  PubMed  Google Scholar 

  19. Soltani Z, Rasheed K, Kapusta DR, Reisin E. Potential role of uric acid in metabolic syndrome, hypertension, kidney injury, and cardiovascular diseases: is it time for reappraisal? Curr Hypertens Rep. 2013;15:175–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chaudhary K, Malhotra K, Sowers J, Aroor A. Uric acid—key ingredient in the recipe for cardiorenal metabolic syndrome. Cardiorenal Med. 2013;3:208–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. 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;27:1133–63.

    Article  PubMed  Google Scholar 

  22. Chen CH, Yang JH, Chiang CW, Hsiung CN, Wu PE, Chang LC, et al. Population structure of Han Chinese in the modern Taiwanese population based on 10,000 participants in the Taiwan Biobank project. Hum Mol Genet. 2016;25:5321–31. https://doi.org/10.1093/hmg/ddw346.

  23. Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Magi R, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature. 2015;518:187–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lin E, Kuo PH, Liu YL, Yang AC, Tsai SJ. Detection of susceptibility loci on APOA5 and COLEC12 associated with metabolic syndrome using a genome-wide association study in a Taiwanese population. Oncotarget. 2017;8:93349–59.

    PubMed  PubMed Central  Google Scholar 

  25. Chen CH, Yang JH, Chiang CWK, Hsiung CN, Wu PE, Chang LC, et al. Population structure of Han Chinese in the modern Taiwanese population based on 10,000 participants in the Taiwan Biobank project. Hum Mol Genet. 2016;25:5321–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–5.

    Article  CAS  PubMed  Google Scholar 

  27. Cheng YC, Hsiao FC, Yeh EC, Lin WJ, Tang CY, Tseng HC, et al. VarioWatch: providing large-scale and comprehensive annotations on human genomic variants in the next generation sequencing era. Nucleic Acids Res. 2012;40(Web Server issue):W76–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Yavorska OO, Burgess S. Mendelian Randomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46:1734–9.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Riches PL, Wright AF, Ralston SH. Recent insights into the pathogenesis of hyperuricaemia and gout. Hum Mol Genet. 2009;18(R2):R177–84.

    Article  CAS  PubMed  Google Scholar 

  30. Mokry LE, Ross S, Timpson NJ, Sawcer S, Davey Smith G, Richards JB. Obesity and multiple sclerosis: a Mendelian Randomization Study. PLoS Med. 2016;13:e1002053.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Yuan H, Yu C, Li X, Sun L, Zhu X, Zhao C, et al. Serum uric acid levels and risk of metabolic syndrome: a dose-response meta-analysis of prospective studies. J Clin Endocrinol Metab. 2015;100:4198–207.

    Article  CAS  PubMed  Google Scholar 

  32. Liu Z, Que S, Zhou L, Zheng S. Dose-response relationship of serum uric acid with metabolic syndrome and non-alcoholic fatty liver disease incidence: a meta-analysis of prospective studies. Sci Rep. 2015;5:14325.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Perez-Pozo SE, Schold J, Nakagawa T, Sanchez-Lozada LG, Johnson RJ, Lillo JL. Excessive fructose intake induces the features of metabolic syndrome in healthy adult men: role of uric acid in the hypertensive response. Int J Obes. 2010;34:454–61.

    Article  CAS  Google Scholar 

  34. Keenan T, Zhao W, Rasheed A, Ho WK, Malik R, Felix JF, et al. Causal assessment of serum urate levels in cardiometabolic diseases through a Mendelian randomization study. J Am Coll Cardiol. 2016;67:407–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Martinez-Quintana E, Tugores A, Rodriguez-Gonzalez F. Serum uric acid levels and cardiovascular disease: the Gordian knot. J Thorac Dis. 2016;8:E1462–6.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sluijs I, Holmes MV, van der Schouw YT, Beulens JW, Asselbergs FW, Huerta JM, et al. A Mendelian randomization study of circulating uric acid and type 2 Diabetes. Diabetes. 2015;64:3028–36.

    Article  CAS  PubMed  Google Scholar 

  37. Pfister R, Barnes D, Luben R, Forouhi NG, Bochud M, Khaw KT, et al. No evidence for a causal link between uric acid and type 2 diabetes: a Mendelian randomisation approach. Diabetologia. 2011;54:2561–9.

    Article  CAS  PubMed  Google Scholar 

  38. Khosla UM, Zharikov S, Finch JL, Nakagawa T, Roncal C, Mu W, et al. Hyperuricemia induces endothelial dysfunction. Kidney Int. 2005;67:1739–42.

    Article  PubMed  Google Scholar 

  39. Nakagawa T, Hu H, Zharikov S, Tuttle KR, Short RA, Glushakova O, et al. A causal role for uric acid in fructose-induced metabolic syndrome. Am J Physiol Renal Physiol. 2006;290:F625–31.

    Article  CAS  PubMed  Google Scholar 

  40. Cai W, Duan XM, Liu Y, Yu J, Tang YL, Liu ZL, et al. Uric acid induces endothelial dysfunction by activating the HMGB1/RAGE signaling pathway. Biomed Res Int. 2017;2017:4391920.

    PubMed  PubMed Central  Google Scholar 

  41. Lanaspa MA, Sanchez-Lozada LG, Choi YJ, Cicerchi C, Kanbay M, Roncal-Jimenez CA, et al. Uric acid induces hepatic steatosis by generation of mitochondrial oxidative stress: potential role in fructose-dependent and -independent fatty liver. J Biol Chem. 2012;287:40732–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Haase CL, Tybjaerg-Hansen A, Nordestgaard BG, Frikke-Schmidt R. HDL cholesterol and risk of type 2 diabetes: a Mendelian randomization study. Diabetes. 2015;64:3328–33.

    Article  CAS  PubMed  Google Scholar 

  43. Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet. 2012;380:572–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Khera AV, Kathiresan S. Genetics of coronary artery disease: discovery, biology and clinical translation. Nat Rev Genet. 2017;18:331–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Roberts R. A genetic basis for coronary artery disease. Trends Cardiovasc Med. 2015;25:171–8.

    Article  CAS  PubMed  Google Scholar 

  46. Wu Z, Lou Y, Qiu X, Liu Y, Lu L, Chen Q, et al. Association of cholesteryl ester transfer protein (CETP) gene polymorphism, high density lipoprotein cholesterol and risk of coronary artery disease: a meta-analysis using a Mendelian randomization approach. BMC Med Genet. 2014;15:118.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Pierce BL, VanderWeele TJ. The effect of non-differential measurement error on bias, precision and power in Mendelian randomization studies. Int J Epidemiol. 2012;41:1383–93.

    Article  PubMed  Google Scholar 

  48. Bochud M, Rousson V. Usefulness of Mendelian randomization in observational epidemiology. Int J Environ Res Public Health. 2010;7:711–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Smith GD, Timpson N, Ebrahim S. Strengthening causal inference in cardiovascular epidemiology through Mendelian randomization. Ann Med. 2008;40:524–41.

    Article  PubMed  Google Scholar 

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Acknowledgements

Data analyzed in this article were collected by the TWB research project (AS-550) sponsored by Multidisciplinary Health Cloud Research Program: Technology Development and Application of Big Health Data, Academia Sinica, Taipei, Taiwan. The TWB directed by Dr. Fu-Tong Liu and Dr. Chen-Yang Shen was carried out by the Institute of Biomedical Sciences of Academia Sinica which is also responsible for data distribution. The assistance provided by the institute and all of those who contribute to the formation and data collection of the TWB is greatly appreciated. The views expressed herein are solely those of the authors.

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WHP, KMC, and MIB conceived and coordinated the investigation. MIB and KMC were responsible for the data analysis. MIB wrote the paper. WHP undertook revisions and HCY and YTH contributed intellectually to the development of this paper.

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Correspondence to Wen-Harn Pan.

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Biradar, M.I., Chiang, KM., Yang, HC. et al. The causal role of elevated uric acid and waist circumference on the risk of metabolic syndrome components. Int J Obes 44, 865–874 (2020). https://doi.org/10.1038/s41366-019-0487-9

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