Skip to main content
SpringerLink
Log in

Metabolic Dysfunction-Associated Fatty Liver Disease in Newly Diagnosed, Treatment-Naive Hypertensive Patients and Its Association with Cardiorenal Risk Markers

  • Original article
  • Published:
High Blood Pressure & Cardiovascular Prevention Aims and scope Submit manuscript

Abstract

Introduction

Patients with arterial hypertension frequently present with comorbidities that are associated with increased cardiorenal risk, such as metabolic dysfunction-associated fatty liver disease (MAFLD).

Aims

Our study aimed to assess the prevalence and the association of MAFLD with cardiorenal risk markers in newly diagnosed, treatment-naïve hypertensive patients.

Methods

We recruited 281 individuals with new-onset hypertension who were not prescribed any medication. Medical history, clinical examination findings, and laboratory test results were recorded. Liver steatosis was assessed through fatty liver index (FLI) calculation. Patients with FLI ≥ 60 together with one main metabolic abnormality (type 2 diabetes mellitus or overweight/obesity) or at least two metabolic risk abnormalities (increased waist circumference, blood pressure, plasma triglycerides, presence of prediabetes or insulin resistance, decreased plasma high-density lipoprotein) fulfilled the diagnostic criteria for MAFLD.

Results

The prevalence of MAFLD in our study population was 28.7%. Individuals with MAFLD were more frequently male and had increased body mass index. Systolic, diastolic, and pulse pressure values were significantly higher in this group of patients. Moreover, lipid, renal, glucose, and inflammatory markers were considerably deranged in patients with MAFLD. After multivariate regression analysis, uric acid, ferritin, and apoE emerged as independent predictors of MAFLD. Area under receiver operating characteristics curve revealed that uric acid had the greatest diagnostic accuracy, with the ideal cutoff being ≥ 5.2 mg/dl (sensitivity: 77.6%, specificity: 76.3%).

Conclusion

MAFLD represents a common comorbidity in hypertensive patients and is associated with markers of cardiorenal risk. Uric acid may be indicative of MAFLD in particular.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16:223–37. https://doi.org/10.1038/s41581-019-0244-2.

    Article  CAS  Google Scholar 

  2. Bundy JD, Mills KT, Chen J, Li C, Greenland P, He J. Estimating the association of the 2017 and 2014 hypertension guidelines with cardiovascular events and deaths in US adults: an analysis of national data. JAMA Cardiol. 2018;3:572–81. https://doi.org/10.1001/jamacardio.2018.1240.

    Article  Google Scholar 

  3. Wang Z, Chen Z, Zhang L, Wang X, Hao G, Zhang Z, Shao L, Tian Y, Dong Y, Zheng C, Wang J, Zhu M, Weintraub WS, Gao R, China Hypertension Survey I. Status of hypertension in China: results from the China hypertension survey, 2012–2015. Circulation. 2018;137:2344–56. https://doi.org/10.1161/CIRCULATIONAHA.117.032380.

    Article  Google Scholar 

  4. Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, Zelber-Sagi S, Wai-Sun Wong V, Dufour JF, Schattenberg JM, Kawaguchi T, Arrese M, Valenti L, Shiha G, Tiribelli C, Yki-Jarvinen H, Fan JG, Gronbaek H, Yilmaz Y, Cortez-Pinto H, Oliveira CP, Bedossa P, Adams LA, Zheng MH, Fouad Y, Chan WK, Mendez-Sanchez N, Ahn SH, Castera L, Bugianesi E, Ratziu V, George J. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol. 2020;73:202–9. https://doi.org/10.1016/j.jhep.2020.03.039.

    Article  Google Scholar 

  5. von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, Initiative S. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007;335:806–8. https://doi.org/10.1136/bmj.39335.541782.AD.

    Article  Google Scholar 

  6. Stergiou GS, Palatini P, Parati G, O’Brien E, Januszewicz A, Lurbe E, Persu A, Mancia G, Kreutz R, European Society of Hypertension C, the European Society of Hypertension Working Group on Blood Pressure M, Cardiovascular V. 2021 European Society of Hypertension practice guidelines for office and out-of-office blood pressure measurement. J Hypertens. 2021;39:1293–302. https://doi.org/10.1097/HJH.0000000000002843.

    Article  CAS  Google Scholar 

  7. Williams B, Mancia G, Spiering W, AgabitiRosei E, Azizi M, Burnier M, Clement DL, Coca A, de Simone G, Dominiczak A, Kahan T, Mahfoud F, Redon J, Ruilope L, Zanchetti A, Kerins M, Kjeldsen SE, Kreutz R, Laurent S, Lip GYH, McManus R, Narkiewicz K, Ruschitzka F, Schmieder RE, Shlyakhto E, Tsioufis C, Aboyans V, Desormais I, Group ESCSD. 2018 ESC/ESH guidelines for the management of arterial hypertension. Eur Heart J. 2018;39:3021–104. https://doi.org/10.1093/eurheartj/ehy339.

    Article  Google Scholar 

  8. Niiranen TJ, Kalesan B, Mitchell GF, Vasan RS. Relative contributions of pulse pressure and arterial stiffness to cardiovascular disease. Hypertension. 2019;73:712–7. https://doi.org/10.1161/HYPERTENSIONAHA.118.12289.

    Article  CAS  Google Scholar 

  9. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502.

    Article  CAS  Google Scholar 

  10. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–9. https://doi.org/10.1007/BF00280883.

    Article  CAS  Google Scholar 

  11. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab. 2000;85:2402–10. https://doi.org/10.1210/jcem.85.7.6661.

    Article  CAS  Google Scholar 

  12. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J, Ckd EPI. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–12. https://doi.org/10.7326/0003-4819-150-9-200905050-00006.

    Article  Google Scholar 

  13. Expert Panel on Detection E, Treatment of High Blood Cholesterol in A. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III). JAMA. 2001;285:2486–97. https://doi.org/10.1001/jama.285.19.2486

  14. Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, Tiribelli C. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol. 2006;6:33. https://doi.org/10.1186/1471-230X-6-33.

    Article  CAS  Google Scholar 

  15. Fluss R, Faraggi D, Reiser B. Estimation of the Youden Index and its associated cutoff point. Biom J. 2005;47:458–72. https://doi.org/10.1002/bimj.200410135.

    Article  Google Scholar 

  16. Theofilis P, Vordoni A, Kalaitzidis RG. Metabolic dysfunction-associated fatty liver disease in the National Health and Nutrition Examination Survey 2017–2020: epidemiology, clinical correlates, and the role of diagnostic scores. Metabolites. 2022;12:1070.

    Article  CAS  Google Scholar 

  17. Theofilis P, Vordoni A, Kalaitzidis RG. Interplay between metabolic dysfunction-associated fatty liver disease and chronic kidney disease: epidemiology, pathophysiologic mechanisms, and treatment considerations. World J Gastroenterol. 2022;28:5691–706.

    Article  CAS  Google Scholar 

  18. Mantovani A, Csermely A, Tilg H, Byrne CD, Targher G. Comparative effects of non-alcoholic fatty liver disease and metabolic dysfunction-associated fatty liver disease on risk of incident cardiovascular events: a meta-analysis of about 13 million individuals. Gut. 2022. https://doi.org/10.1136/gutjnl-2022-328224.

    Article  Google Scholar 

  19. Kim H, Lee CJ, Ahn SH, Lee KS, Lee BK, Baik SJ, Kim SU, Lee JI. MAFLD predicts the risk of cardiovascular disease better than NAFLD in asymptomatic subjects with health check-ups. Dig Dis Sci. 2022;67:4919–28. https://doi.org/10.1007/s10620-022-07508-6.

    Article  CAS  Google Scholar 

  20. Tanaka M, Mori K, Takahashi S, Higashiura Y, Ohnishi H, Hanawa N, Furuhashi M. Metabolic dysfunction-associated fatty liver disease predicts new onset of chronic kidney disease better than does fatty liver or nonalcoholic fatty liver disease. Nephrol Dial Transplant. 2022. https://doi.org/10.1093/ndt/gfac188.

    Article  Google Scholar 

  21. Quek J, Ng CH, Tang ASP, Chew N, Chan M, Khoo CM, Wei CP, Chin YH, Tay P, Lim G, Tan DJH, Lim WH, Chan KE, Teng M, Tan E, Tamaki N, Huang DQ, Siddiqui MS, Young DY, Noureddin M, Muthiah MD. Metabolic associated fatty liver disease increases the risk of systemic complications and mortality. A Meta-analysis and systematic review of 12,620,736 Individuals. Endocr Pract. 2022;28:667–72. https://doi.org/10.1016/j.eprac.2022.03.016.

    Article  Google Scholar 

  22. Morishita A, Tadokoro T, Fujihara S, Iwama H, Oura K, Fujita K, Tani J, Takuma K, Nakahara M, Shi T, Haba R, Okano K, Nishiyama A, Ono M, Himoto T, Masaki T. Ipragliflozin attenuates non-alcoholic steatohepatitis development in an animal model. PLoS ONE. 2022;17:e0261310. https://doi.org/10.1371/journal.pone.0261310.

    Article  CAS  Google Scholar 

  23. Akuta N, Kawamura Y, Fujiyama S, Saito S, Muraishi N, Sezaki H, Hosaka T, Kobayashi M, Kobayashi M, Arase Y, Ikeda K, Suzuki F, Suzuki Y, Kumada H. Favorable impact of long-term SGLT2 inhibitor for NAFLD complicated by diabetes mellitus: a 5-year follow-up study. Hepatol Commun. 2022;6:2286–97. https://doi.org/10.1002/hep4.2005.

    Article  CAS  Google Scholar 

  24. Takahashi H, Kessoku T, Kawanaka M, Nonaka M, Hyogo H, Fujii H, Nakajima T, Imajo K, Tanaka K, Kubotsu Y, Isoda H, Oeda S, Kurai O, Yoneda M, Ono M, Kitajima Y, Tajiri R, Takamori A, Kawaguchi A, Aishima S, Kage M, Nakajima A, Eguchi Y, Anzai K. Ipragliflozin improves the hepatic outcomes of patients with diabetes with NAFLD. Hepatol Commun. 2022;6:120–32. https://doi.org/10.1002/hep4.1696.

    Article  CAS  Google Scholar 

  25. Li X, Wu X, Jia Y, Fu J, Zhang L, Jiang T, Liu J, Wang G. Liraglutide decreases liver fat content and serum fibroblast growth factor 21 levels in newly diagnosed overweight patients with type 2 diabetes and nonalcoholic fatty liver disease. J Diabetes Res. 2021;2021:3715026. https://doi.org/10.1155/2021/3715026.

    Article  CAS  Google Scholar 

  26. Morieri ML, Targher G, Lapolla A, D’Ambrosio M, Tadiotto F, Rigato M, Frison V, Paccagnella A, Simioni N, Avogaro A, Fadini GP. Changes in markers of hepatic steatosis and fibrosis in patients with type 2 diabetes during treatment with glucagon-like peptide-1 receptor agonists. A multicenter retrospective longitudinal study. Nutr Metab Cardiovasc Dis. 2021;31:3474–83. https://doi.org/10.1016/j.numecd.2021.08.049.

    Article  CAS  Google Scholar 

  27. Jianping W, Xuelian Z, Anjiang W, Haiying X. Efficacy and safety of glucagon-like peptide-1 receptor agonists in the treatment of metabolic associated fatty liver disease: a systematic review and meta-analysis. J Clin Gastroenterol. 2021;55:586–93. https://doi.org/10.1097/MCG.0000000000001556.

    Article  CAS  Google Scholar 

  28. Dutta D, Kumar M, Shivaprasad KS, Kumar A, Sharma M. Impact of semaglutide on biochemical and radiologic measures of metabolic-dysfunction associated fatty liver disease across the spectrum of glycaemia: a meta-analysis. Diabetes Metab Syndr. 2022;16:102539. https://doi.org/10.1016/j.dsx.2022.102539.

    Article  Google Scholar 

  29. Saha M, Manna K, Das SK. Melatonin suppresses NLRP3 inflammasome activation via TLR4/NF-kappaB and P2X7R signaling in high-fat diet-induced murine NASH model. J Inflamm Res. 2022;15:3235–58. https://doi.org/10.2147/JIR.S343236.

    Article  Google Scholar 

  30. Pakravan H, Ahmadian M, Fani A, Aghaee D, Brumanad S, Pakzad B. The effects of melatonin in patients with nonalcoholic fatty liver disease: a randomized controlled trial. Adv Biomed Res. 2017;6:40. https://doi.org/10.4103/2277-9175.204593.

    Article  CAS  Google Scholar 

  31. Akhavan Rezayat A, Ghasemi Nour M, Bondarsahebi Y, Hozhabrossadati SA, Amirkhanlou F, Akhavan Rezayat S, Kiani M, Imani B. The effects of melatonin therapy on the treatment of patients with Non-alcoholic steatohepatitis: a systematic review and Meta-analysis on clinical trial studies. Eur J Pharmacol. 2021;905:174154. https://doi.org/10.1016/j.ejphar.2021.174154.

    Article  CAS  Google Scholar 

  32. Liu J, Ayada I, Zhang X, Wang L, Li Y, Wen T, Ma Z, Bruno MJ, de Knegt RJ, Cao W, Peppelenbosch MP, Ghanbari M, Li Z, Pan Q. Estimating global prevalence of metabolic dysfunction-associated fatty liver disease in overweight or obese adults. Clin Gastroenterol Hepatol. 2022;20:e573–82. https://doi.org/10.1016/j.cgh.2021.02.030.

    Article  Google Scholar 

  33. Ruiz-Manriquez J, Olivas-Martinez A, Chávez-García LC, Fernández-Ramírez A, Moctezuma-Velazquez C, Kauffman-Ortega E, Castro-Narro G, Astudillo-García F, Escalona-Nandez I, Aguilar-Salinas CA, Navarro-Alvarez N, Torre A. Prevalence of metabolic-associated fatty liver disease in Mexico and development of a screening tool: the MAFLD-S score. Gastro Hep Adv. 2022;1:352–8. https://doi.org/10.1016/j.gastha.2021.12.011.

    Article  Google Scholar 

  34. Theofilis P, Vordoni A, Nakas N, Kalaitzidis RG. Endothelial dysfunction in nonalcoholic fatty liver disease: a systematic review and meta-analysis. Life (Basel). 2022;12:718. https://doi.org/10.3390/life12050718.

    Article  Google Scholar 

  35. Masarone M, Rosato V, Dallio M, Gravina AG, Aglitti A, Loguercio C, Federico A, Persico M. Role of oxidative stress in pathophysiology of nonalcoholic fatty liver disease. Oxid Med Cell Longev. 2018;2018:9547613. https://doi.org/10.1155/2018/9547613.

    Article  CAS  Google Scholar 

  36. Tan X, Liu Y, Long J, Chen S, Liao G, Wu S, Li C, Wang L, Ling W, Zhu H. Trimethylamine N-oxide aggravates liver steatosis through modulation of bile acid metabolism and inhibition of farnesoid X receptor signaling in nonalcoholic fatty liver disease. Mol Nutr Food Res. 2019;63:e1900257. https://doi.org/10.1002/mnfr.201900257.

    Article  CAS  Google Scholar 

  37. Rodrigo R, Gonzalez J, Paoletto F. The role of oxidative stress in the pathophysiology of hypertension. Hypertens Res. 2011;34:431–40. https://doi.org/10.1038/hr.2010.264.

    Article  CAS  Google Scholar 

  38. Theofilis P, Sagris M, Oikonomou E, Antonopoulos AS, Siasos G, Tsioufis C, Tousoulis D. Inflammatory mechanisms contributing to endothelial dysfunction. Biomedicines. 2021;9:781. https://doi.org/10.3390/biomedicines9070781.

    Article  CAS  Google Scholar 

  39. Avery EG, Bartolomaeus H, Maifeld A, Marko L, Wiig H, Wilck N, Rosshart SP, Forslund SK, Muller DN. The gut microbiome in hypertension: recent advances and future perspectives. Circ Res. 2021;128:934–50. https://doi.org/10.1161/CIRCRESAHA.121.318065.

    Article  CAS  Google Scholar 

  40. Oikonomou E, Leopoulou M, Theofilis P, Antonopoulos AS, Siasos G, Latsios G, Mystakidi VC, Antoniades C, Tousoulis D. A link between inflammation and thrombosis in atherosclerotic cardiovascular diseases: clinical and therapeutic implications. Atherosclerosis. 2020;309:16–26. https://doi.org/10.1016/j.atherosclerosis.2020.07.027.

    Article  CAS  Google Scholar 

  41. Theofilis P, Sagris M, Antonopoulos AS, Oikonomou E, Tsioufis C, Tousoulis D. Inflammatory mediators of platelet activation: focus on atherosclerosis and COVID-19. Int J Mol Sci. 2021;22:11170. https://doi.org/10.3390/ijms222011170.

    Article  CAS  Google Scholar 

  42. Sagris M, Theofilis P, Antonopoulos AS, Oikonomou E, Paschaliori C, Galiatsatos N, Tsioufis K, Tousoulis D. Inflammation in coronary microvascular dysfunction. Int J Mol Sci. 2021;22:13471. https://doi.org/10.3390/ijms222413471.

    Article  CAS  Google Scholar 

  43. Sagris M, Theofilis P, Antonopoulos AS, Tsioufis C, Oikonomou E, Antoniades C, Crea F, Kaski JC, Tousoulis D. Inflammatory mechanisms in COVID-19 and atherosclerosis: current pharmaceutical perspectives. Int J Mol Sci. 2021;22:6607. https://doi.org/10.3390/ijms22126607.

    Article  CAS  Google Scholar 

  44. Suarez-Ortegon MF, McLachlan S, Fernandez-Real JM, Tuomainen TP, Aregbesola A, Wild SH. Serum ferritin and incident cardiometabolic diseases in Scottish adults. Cardiovasc Diabetol. 2022;21:26. https://doi.org/10.1186/s12933-022-01450-7.

    Article  CAS  Google Scholar 

  45. Kang HT, Linton JA, Kwon SK, Park BJ, Lee JH. Ferritin level is positively associated with chronic kidney disease in Korean men, based on the 2010–2012 Korean National Health and Nutrition Examination Survey. Int J Environ Res Public Health. 2016. https://doi.org/10.3390/ijerph13111058.

    Article  Google Scholar 

  46. Wu YH, Wang SY, Li MX, He H, Yin WJ, Guo YH, Zhang HQ, Sun ZM, Zhang D, Wang X, Sun SY, Tang SX, Du R, Zhang CH. Serum ferritin independently predicts the incidence of chronic kidney disease in patients with type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2020;13:99–105. https://doi.org/10.2147/DMSO.S228335.

    Article  CAS  Google Scholar 

  47. Fibrinogen Studies C, Danesh J, Lewington S, Thompson SG, Lowe GD, Collins R, Kostis JB, Wilson AC, Folsom AR, Wu K, Benderly M, Goldbourt U, Willeit J, Kiechl S, Yarnell JW, Sweetnam PM, Elwood PC, Cushman M, Psaty BM, Tracy RP, Tybjaerg-Hansen A, Haverkate F, de Maat MP, Fowkes FG, Lee AJ, Smith FB, Salomaa V, Harald K, Rasi R, Vahtera E, Jousilahti P, Pekkanen J, D’Agostino R, Kannel WB, Wilson PW, Tofler G, Arocha-Pinango CL, Rodriguez-Larralde A, Nagy E, Mijares M, Espinosa R, Rodriquez-Roa E, Ryder E, Diez-Ewald MP, Campos G, Fernandez V, Torres E, Marchioli R, Valagussa F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Cremer P, Nagel D, Curb JD, Rodriguez B, Yano K, Salonen JT, Nyyssonen K, Tuomainen TP, Hedblad B, Lind P, Loewel H, Koenig W, Meade TW, Cooper JA, De Stavola B, Knottenbelt C, Miller GJ, Cooper JA, Bauer KA, Rosenberg RD, Sato S, Kitamura A, Naito Y, Palosuo T, Ducimetiere P, Amouyel P, Arveiler D, Evans AE, Ferrieres J, Juhan-Vague I, Bingham A, Schulte H, Assmann G, Cantin B, Lamarche B, Despres JP, Dagenais GR, Tunstall-Pedoe H, Woodward M, Ben-Shlomo Y, Davey Smith G, Palmieri V, Yeh JL, Rudnicka A, Ridker P, Rodeghiero F, Tosetto A, Shepherd J, Ford I, Robertson M, Brunner E, Shipley M, Feskens EJ, Kromhout D, Dickinson A, Ireland B, Juzwishin K, Kaptoge S, Lewington S, Memon A, Sarwar N, Walker M, Wheeler J, White I, Wood A. Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality: an individual participant meta-analysis. JAMA. 2005;294:1799–809. https://doi.org/10.1001/jama.294.14.1799.

    Article  Google Scholar 

  48. Emerging Risk Factors C, Kaptoge S, Di Angelantonio E, Pennells L, Wood AM, White IR, Gao P, Walker M, Thompson A, Sarwar N, Caslake M, Butterworth AS, Amouyel P, Assmann G, Bakker SJ, Barr EL, Barrett-Connor E, Benjamin EJ, Bjorkelund C, Brenner H, Brunner E, Clarke R, Cooper JA, Cremer P, Cushman M, Dagenais GR, D’Agostino RB Sr, Dankner R, Davey-Smith G, Deeg D, Dekker JM, Engstrom G, Folsom AR, Fowkes FG, Gallacher J, Gaziano JM, Giampaoli S, Gillum RF, Hofman A, Howard BV, Ingelsson E, Iso H, Jorgensen T, Kiechl S, Kitamura A, Kiyohara Y, Koenig W, Kromhout D, Kuller LH, Lawlor DA, Meade TW, Nissinen A, Nordestgaard BG, Onat A, Panagiotakos DB, Psaty BM, Rodriguez B, Rosengren A, Salomaa V, Kauhanen J, Salonen JT, Shaffer JA, Shea S, Ford I, Stehouwer CD, Strandberg TE, Tipping RW, Tosetto A, Wassertheil-Smoller S, Wennberg P, Westendorp RG, Whincup PH, Wilhelmsen L, Woodward M, Lowe GD, Wareham NJ, Khaw KT, Sattar N, Packard CJ, Gudnason V, Ridker PM, Pepys MB, Thompson SG, Danesh J. C-reactive protein, fibrinogen, and cardiovascular disease prediction. N Engl J Med. 2012;367:1310–20. https://doi.org/10.1056/NEJMoa1107477.

    Article  Google Scholar 

  49. Shlipak MG, Fried LF, Crump C, Bleyer AJ, Manolio TA, Tracy RP, Furberg CD, Psaty BM. Elevations of inflammatory and procoagulant biomarkers in elderly persons with renal insufficiency. Circulation. 2003;107:87–92. https://doi.org/10.1161/01.cir.0000042700.48769.59.

    Article  CAS  Google Scholar 

  50. Goicoechea M, de Vinuesa SG, Gomez-Campdera F, Aragoncillo I, Verdalles U, Mosse A, Luno J. Serum fibrinogen levels are an independent predictor of mortality in patients with chronic kidney disease (CKD) stages 3 and 4. Kidney Int Suppl. 2008. https://doi.org/10.1038/ki.2008.519.

    Article  Google Scholar 

  51. Huang MJ, Wei RB, Wang Y, Su TY, Di P, Li QP, Yang X, Li P, Chen XM. Blood coagulation system in patients with chronic kidney disease: a prospective observational study. BMJ Open. 2017;7:e014294. https://doi.org/10.1136/bmjopen-2016-014294.

    Article  Google Scholar 

  52. Hagstrom E, Steg PG, Szarek M, Bhatt DL, Bittner VA, Danchin N, Diaz R, Goodman SG, Harrington RA, Jukema JW, Liberopoulos E, Marx N, McGinniss J, Manvelian G, Pordy R, Scemama M, White HD, Zeiher AM, Schwartz GG, Investigators OO. Apolipoprotein B, residual cardiovascular risk after acute coronary syndrome, and effects of alirocumab. Circulation. 2022;146:657–72. https://doi.org/10.1161/CIRCULATIONAHA.121.057807.

    Article  CAS  Google Scholar 

  53. Walldius G, de Faire U, Alfredsson L, Leander K, Westerholm P, Malmstrom H, Ivert T, Hammar N. Long-term risk of a major cardiovascular event by apoB, apoA-1, and the apoB/apoA-1 ratio-Experience from the Swedish AMORIS cohort: a cohort study. PLoS Med. 2021;18:e1003853. https://doi.org/10.1371/journal.pmed.1003853.

    Article  CAS  Google Scholar 

  54. Kronenberg F, Mora S, Stroes ESG, Ference BA, Arsenault BJ, Berglund L, Dweck MR, Koschinsky M, Lambert G, Mach F, McNeal CJ, Moriarty PM, Natarajan P, Nordestgaard BG, Parhofer KG, Virani SS, von Eckardstein A, Watts GF, Stock JK, Ray KK, Tokgozoglu LS, Catapano AL. Lipoprotein(a) in atherosclerotic cardiovascular disease and aortic stenosis: a European Atherosclerosis Society consensus statement. Eur Heart J. 2022. https://doi.org/10.1093/eurheartj/ehac361.

    Article  Google Scholar 

  55. Goek ON, Kottgen A, Hoogeveen RC, Ballantyne CM, Coresh J, Astor BC. Association of apolipoprotein A1 and B with kidney function and chronic kidney disease in two multiethnic population samples. Nephrol Dial Transplant. 2012;27:2839–47. https://doi.org/10.1093/ndt/gfr795.

    Article  CAS  Google Scholar 

  56. Hopewell JC, Haynes R, Baigent C. The role of lipoprotein (a) in chronic kidney disease. J Lipid Res. 2018;59:577–85. https://doi.org/10.1194/jlr.R083626.

    Article  CAS  Google Scholar 

  57. Sofat R, Cooper JA, Kumari M, Casas JP, Mitchell JP, Acharya J, Thom S, Hughes AD, Humphries SE, Hingorani AD. Circulating apolipoprotein E concentration and cardiovascular disease risk: meta-analysis of results from three studies. PLoS Med. 2016;13:e1002146. https://doi.org/10.1371/journal.pmed.1002146.

    Article  CAS  Google Scholar 

  58. Cicero AFG, Fogacci F, Giovannini M, Grandi E, Rosticci M, D’Addato S, Borghi C. Serum uric acid predicts incident metabolic syndrome in the elderly in an analysis of the Brisighella Heart Study. Sci Rep. 2018;8:11529. https://doi.org/10.1038/s41598-018-29955-w.

    Article  CAS  Google Scholar 

  59. Pugliese NR, Mengozzi A, Virdis A, Casiglia E, Tikhonoff V, Cicero AFG, Ungar A, Rivasi G, Salvetti M, Barbagallo CM, Bombelli M, Dell’Oro R, Bruno B, Lippa L, D’Elia L, Verdecchia P, Mallamaci F, Cirillo M, Rattazzi M, Cirillo P, Gesualdo L, Mazza A, Giannattasio C, Maloberti A, Volpe M, Tocci G, Georgiopoulos G, Iaccarino G, Nazzaro P, Parati G, Palatini P, Galletti F, Ferri C, Desideri G, Viazzi F, Pontremoli R, Muiesan ML, Grassi G, Masi S, Borghi C, Working Group on Uric A, Cardiovascular Risk of the Italian Society of H. The importance of including uric acid in the definition of metabolic syndrome when assessing the mortality risk. Clin Res Cardiol. 2021;110:1073–82. https://doi.org/10.1007/s00392-021-01815-0.

    Article  CAS  Google Scholar 

  60. Theofilis P, Tsimihodimos V, Vordoni A, Kalaitzidis RG. Serum uric acid levels and cardiometabolic profile in middle-aged, treatment-naive hypertensive patients. High Blood Press Cardiovasc Prev. 2022;29:367–74. https://doi.org/10.1007/s40292-022-00522-9.

    Article  CAS  Google Scholar 

  61. Virdis A, Masi S, Casiglia E, Tikhonoff V, Cicero AFG, Ungar A, Rivasi G, Salvetti M, Barbagallo CM, Bombelli M, Dell’Oro R, Bruno B, Lippa L, D’Elia L, Verdecchia P, Mallamaci F, Cirillo M, Rattazzi M, Cirillo P, Gesualdo L, Mazza A, Giannattasio C, Maloberti A, Volpe M, Tocci G, Georgiopoulos G, Iaccarino G, Nazzaro P, Parati G, Palatini P, Galletti F, Ferri C, Desideri G, Viazzi F, Pontremoli R, Muiesan ML, Grassi G, Borghi C, from the Working Group on Uric A, Cardiovascular Risk of the Italian Society of H. Identification of the uric acid thresholds predicting an increased total and cardiovascular mortality over 20 years. Hypertension. 2020;75:302–8. https://doi.org/10.1161/HYPERTENSIONAHA.119.13643.

    Article  CAS  Google Scholar 

  62. Son YB, Yang JH, Kim MG, Jo SK, Cho WY, Oh SW. The effect of baseline serum uric acid on chronic kidney disease in normotensive, normoglycemic, and non-obese individuals: a health checkup cohort study. PLoS ONE. 2021;16:e0244106. https://doi.org/10.1371/journal.pone.0244106.

    Article  CAS  Google Scholar 

  63. Srivastava A, Kaze AD, McMullan CJ, Isakova T, Waikar SS. Uric Acid and the risks of kidney failure and death in individuals with CKD. Am J Kidney Dis. 2018;71:362–70. https://doi.org/10.1053/j.ajkd.2017.08.017.

    Article  CAS  Google Scholar 

  64. Yu H, Zhao L, Liu L, Li Y, Sun J, Liu Y. Relationship between serum uric acid level and nonalcoholic fatty liver disease in type 2 diabetes patients. Medicine (Baltimore). 2021;100:e26946. https://doi.org/10.1097/MD.0000000000026946.

    Article  CAS  Google Scholar 

  65. Bao T, Ying Z, Gong L, Du J, Ji G, Li Z, Gao W, Jiang X, Yang H, Huang Y, Tang H. Association between serum uric acid and nonalcoholic fatty liver disease in nonobese postmenopausal women: a cross-sectional study. Sci Rep. 2020;10:10072. https://doi.org/10.1038/s41598-020-66931-9.

    Article  CAS  Google Scholar 

  66. Wei F, Li J, Chen C, Zhang K, Cao L, Wang X, Ma J, Feng S, Li WD. Higher serum uric acid level predicts non-alcoholic fatty liver disease: a 4-year prospective cohort study. Front Endocrinol (Lausanne). 2020;11:179. https://doi.org/10.3389/fendo.2020.00179.

    Article  Google Scholar 

  67. Oral A, Sahin T, Turker F, Kocak E. Relationship between serum uric acid levels and nonalcoholic fatty liver disease in non-obese patients. Medicina (Kaunas). 2019. https://doi.org/10.3390/medicina55090600.

    Article  Google Scholar 

  68. Xing Y, Chen J, Liu J, Song G, Ma H. Relationship between serum uric acid-to-creatinine ratio and the risk of metabolic-associated fatty liver disease in patients with type 2 diabetes mellitus. Diabetes Metab Syndr Obes. 2022;15:257–67. https://doi.org/10.2147/DMSO.S350468.

    Article  CAS  Google Scholar 

  69. Theofilis P, Vordoni A, Kalaitzidis RG. Metabolic dysfunction-associated fatty liver disease in the National Health and Nutrition Examination Survey 2017–2020: epidemiology, clinical correlates, and the role of diagnostic scores. Metabolites. 2022. https://doi.org/10.3390/metabo12111070.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Nephrology “G. Papadakis”, General Hospital of Nikaia-Piraeus “Agios Panteleimon”, 18454, Piraeus, Nikaia, Greece

    Panagiotis Theofilis, Aikaterini Vordoni & Rigas G. Kalaitzidis

  2. Department of Internal Medicine, University of Ioannina, Ioannina, Greece

    Vasilis Tsimihodimos

Authors
  1. Panagiotis Theofilis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aikaterini Vordoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vasilis Tsimihodimos
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rigas G. Kalaitzidis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rigas G. Kalaitzidis.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Research involving human participants

The study was approved by the Ethics Committee of the Ioannina University Hospital and was carried out according to the Declaration of Helsinki (1989).

Informed consent

All individuals were informed about the aims of the study and provided written informed consent.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

Author contributions

PT interpreted the results and drafted the manuscript. VT conceived and designed the study and revised the manuscript. AV interpreted the results and revised the manuscript. RGK conceived and designed the study, acquired the data, interpreted the results and drafted the manuscript.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Theofilis, P., Vordoni, A., Tsimihodimos, V. et al. Metabolic Dysfunction-Associated Fatty Liver Disease in Newly Diagnosed, Treatment-Naive Hypertensive Patients and Its Association with Cardiorenal Risk Markers. High Blood Press Cardiovasc Prev 30, 63–72 (2023). https://doi.org/10.1007/s40292-023-00558-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40292-023-00558-5

Keywords

Search

Navigation