Uric acid may serve as the sixth cardiometabolic criterion for defining MASLD

A multisociety Delphi consensus statement on new fatty liver disease nomenclatureJournal of HepatologyVol. 79Issue 6PreviewThe principal limitations of the terms NAFLD and NASH are the reliance on exclusionary confounder terms and the use of potentially stigmatising language. This study set out to determine if content experts and patient advocates were in favour of a change in nomenclature and/or definition. A modified Delphi process was led by three large pan-national liver associations. The consensus was defined a priori as a supermajority (67%) vote. An independent committee of experts external to the nomenclature process made the final recommendation on the acronym and its diagnostic criteria. Full-Text PDF Open Access The definition of MASLD (metabolic dysfunction-associated steatotic liver disease) incorporates five cardiometabolic criteria that emphasize the impact of metabolic disorders.[1]Rinella M.E. Lazarus J.V. Ratziu V. et al.A multisociety Delphi consensus statement on new fatty liver disease nomenclature.J Hepatol. 2023; 79: 1542-1556Abstract Full Text Full Text PDF PubMed Scopus (219) Google Scholar These criteria revolve around hypertension, hyperglycemia, and hyperlipidemia. However, we realize that hyperuricemia (HUA), known as the "fourth hyper",[2]Huang J. Ma Z.F. Zhang Y. et al.Geographical distribution of hyperuricemia in mainland China: a comprehensive systematic review and meta-analysis.Glob Health Res Pol. 2020; 5: 52Crossref PubMed Scopus (50) Google Scholar is not currently included. In today's society, the incidence of hyperuricemia is rapidly increasing due to high-purine diets and sugary beverages,[3]Dehlin M. Jacobsson L. Roddy E. Global epidemiology of gout: prevalence, incidence, treatment patterns and risk factors.Nat Rev Rheumatol. 2020; 16: 380-390Crossref PubMed Scopus (485) Google Scholar and a correlation between HUA and fatty liver has been reported.[4]Sun Q. Zhang T. Manji L. et al.Association between serum uric acid and non-alcoholic fatty liver disease: an updated systematic review and meta-analysis.Clin Epidemiol. 2023; 15: 683-693Crossref PubMed Scopus (3) Google Scholar In addition, serum uric acid levels can be easily obtained through routine checkups, unlike HOMA-IR (homeostasis model assessment of insulin resistance) and high-sensitivity C-reactive protein, which were required in the previous MAFLD (metabolic dysfunction-associated fatty liver disease) definition.[5]Eslam M. Newsome P.N. Sarin S.K. et al.A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement.J Hepatol. 2020; 73: 202-209Abstract Full Text Full Text PDF PubMed Scopus (2065) Google Scholar Regrettably, the new statement does not consider hyperuricemia as one of the cardiometabolic criteria for MASLD, and it remains unclear whether patients with HUA are covered by the MD (metabolic dysfunction with at least one of the cardiometabolic criteria for MASLD) category. Therefore, we conducted a study to investigate the feasibility of including HUA in the diagnosis of MASLD. This longitudinal study involved 16,152 patients who underwent a physical examination at a Chinese hospital from 2010 to 2014. All participants received a liver ultrasound to confirm the absence of fatty liver.[6]Sun D.Q. Wu S.J. Liu W.Y. et al.Association of low-density lipoprotein cholesterol within the normal range and NAFLD in the non-obese Chinese population: a cross-sectional and longitudinal study.BMJ Open. 2016; 6e013781Crossref Scopus (43) Google Scholar The mean age of the participants was 43.2 years. Those with excessive alcohol consumption (>140 g/week for men and >70 g/week for women), a history of viral hepatitis, autoimmune hepatitis, or other known causes of chronic liver disease, a BMI of ≥25 kg/m2, an LDL-c of >3.12 mmol/L, and those taking specific agents were excluded. Fatty liver was screened using liver ultrasound during follow-up periods. Within this cohort, the prevalence of the five cardiometabolic criteria that comprise MASLD were as follows: overweight (25.2%), hypertension (29.2%), hyperglycemia (13.9%), high triglyceride (TG, 19%), and low HDL-C (21.4%). The prevalence of HUA was 10.9%, with the majority (86.7%) having a comorbid MD, while a proportion (13.3%) did not have MD (Fig. S1A). During a mean follow-up period of 2.8±1.1 years, a total of 2,321 individuals developed fatty liver. Overweight, hypertension, hyperglycemia, high TG, low HDL-C, and hyperuricemia all increased the risk of non-alcoholic fatty liver disease (NAFLD). The incidence of NAFLD in the HUA group without MD (8.2%) was much higher than in the group without HUA/MD (2.9%, Fig. S1B). To eliminate the interactions between metabolic factors, the population was subdivided into the Only overweight group, Only hypertension group, Only hyperglycemia group, Only high TG group, Only low HDL-C group, and Only HUA group. Compared with the group without HUA/MD, the hazard ratio (HR) for the Only HUA group and NAFLD was 2.168 (95% CI 1.349, 3.485), which was higher than that for the Only hyperglycemia group and the Only low HDL-C group (Table 1). However, this study cannot guarantee that the Only HUA group will remain Only HUA or not develop other metabolic abnormalities during the follow-up period. Therefore, more studies are needed in the future to focus on the impact of dynamic changes in this status on outcomes.Table 1Relationship between cardiometabolic risk factors and fatty liver.HR (95% CI)aAdjusted age and sex.p valueHR (95% CI)bAdjusted for age, sex, alanine aminotransferase, aspartate aminotransferase, total bilirubin, serum creatinine, and blood urea nitrogen.p valueHUA2.158 (1.951, 2.387)<0.0011.527 (1.374, 1.696)<0.001Cardiometabolic criteria Overweight5.253 (4.832, 5.711)<0.0014.058 (3.728, 4.417)<0.001 Hypertension2.190 (2.017, 2.378)<0.0011.719 (1.579, 1.871)<0.001 Hyperglycemia2.292 (2.084, 2.519)<0.0011.778 (1.613, 1.959)<0.001 High TG4.059 (3.740, 4.405)<0.0013.113 (2.864, 3.383)<0.001 Low HDL-C1.861 (1.694, 2.044)<0.0011.655 (1.506, 1.819)<0.001MD6.945 (6.004, 8.034)<0.0015.516 (4.761, 6.391)Without HUA/MDReferencesReferencesOnly overweight8.168 (6.711, 9.943)<0.0016.645 (5.455, 8.096)<0.001Only hypertension2.442 (1.902, 3.135)<0.0012.240 (1.744, 2.878)<0.001Only hyperglycemia2.296 (1.522, 3.464)<0.0012.130 (1.410, 3.215)<0.001Only high TG5.833 (4.523, 7.523)<0.0014.940 (3.829, 6.375)<0.001Only HDL-C1.207 (0.871, 1.673)0.2581.501 (1.083, 2.081)0.015Only HUA2.593 (1.615, 4.161)<0.0012.168 (1.349, 3.485)<0.001Without HUA/MDReferencesReferencesHUA/MD overlap10.597 (8.915, 12.598)<0.0016.925 (5.797, 8.273)<0.001Only MD6.821 (5.847, 7.958)<0.0015.623 (4.814, 6.569)<0.001HUA and/or MD7.269 (6.241, 8.466)<0.0015.731 (4.912, 6.686)<0.001CI, confidence interval; HR, hazard ratio; HUA, hyperuricemia; TG, triglyceride; MD, metabolic dysfunction with at least one of the cardiometabolic criteria for MASLD.The results were obtained by Cox regression.a Adjusted age and sex.b Adjusted for age, sex, alanine aminotransferase, aspartate aminotransferase, total bilirubin, serum creatinine, and blood urea nitrogen. Open table in a new tab CI, confidence interval; HR, hazard ratio; HUA, hyperuricemia; TG, triglyceride; MD, metabolic dysfunction with at least one of the cardiometabolic criteria for MASLD. The results were obtained by Cox regression. The available literature confirms that serum uric acid increases insulin resistance through multiple pathways, and in turn insulin resistance increases uric acid synthesis and inhibits its excretion, exacerbating the vicious cycle.[4]Sun Q. Zhang T. Manji L. et al.Association between serum uric acid and non-alcoholic fatty liver disease: an updated systematic review and meta-analysis.Clin Epidemiol. 2023; 15: 683-693Crossref PubMed Scopus (3) Google Scholar Our research also revealed that 86.7% of patients with HUA had comorbid MD. However, it is important to note that uric acid can directly induce hepatic steatosis through NLRP3-mediated inflammation,[7]Wan X. Xu C. Lin Y. et al.Uric acid regulates hepatic steatosis and insulin resistance through the NLRP3 inflammasome-dependent mechanism.J Hepatol. 2016; 64: 925-932Abstract Full Text Full Text PDF PubMed Scopus (190) Google Scholar and oxidative stress can impair energy metabolism in liver cells, leading to lipid accumulation.[8]Xu C. Hyperuricemia and non-alcoholic fatty liver disease: from bedside to bench and back.Hepatol Int. 2016; 10: 286-293Crossref PubMed Scopus (31) Google Scholar Individuals with HUA who do not have MD, comprising 13.3% of the population, are also at an increased risk of developing NAFLD, which supports this finding to some extent. This subgroup may not be individuals following a high-purine diet but those consuming sugary drinks. Fructose, found in sugary drinks, significantly contributes to uric acid synthesis and accumulation, thereby increasing the risk of NAFLD. Given the popularity of sugary drinks, this subgroup is expected to grow. It is worth noting that sugary beverages are trendy among younger individuals, and existing research suggests that being younger with NAFLD increases the risk of various diseases, including cancer.[9]Liu C. Liu T. Zhang Q. et al.New-onset age of non-alcoholic fatty liver disease and cancer risk.JAMA Netw Open. 2023; 6e2335511Crossref Scopus (1) Google Scholar Consequently, more attention needs to be paid to the effects of hyperuricemia on fatty liver disease. In conclusion, uric acid shows promise as the sixth cardiometabolic criterion for diagnosing MASLD. This additional criterion has the potential to enhance the accuracy and comprehensiveness of the identification of individuals at risk for MASLD and may facilitate the development of more effective diagnostic and management strategies. We anticipate that further studies can support the clinical application of this criterion. This study was supported by National Natural Science Foundation of China (Grant No. 82270909, No. 81974107). The authors declare no conflicts of interest. Please refer to the accompanying ICMJE disclosure forms for further details. Study concept and design: Tianshu Zeng, Wen Kong, and Linfeng He; Statistical analysis and interpretation: Linfeng He; Data acquisition and validation: Kangli Qiu, and Wenbin Zheng; All authors wrote and approved final manuscripts. The data used in this study are available in the "DATADRYAD" database (www.Datadryad.org). During the writing of this work, the authors used ChatGPT 3.5 in order to check grammar, spelling and optimize sentences to enhance the readability of the article. After using this tool/service, the authors reviewed and edited the content as necessary and take full responsibility for the content of the publication. 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