Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr;14(7):e038723.
doi: 10.1161/JAHA.124.038723. Epub 2025 Mar 27.

Exploration of the Interrelationship Between Serum Uric Acid, Gout, and Cardiac, Renal, and Metabolic Conditions in Middle Aged and Older People

Yingdong Han  1 , Menghui Yao  1 , He Zhao  1 , Xinxin Han  1 , Hong Di  1 , Tiange Xie  1 , Juan Wu  1 , Yibo Wang  1 , Yun Zhang  1 , Xuejun Zeng  1
Affiliations

Exploration of the Interrelationship Between Serum Uric Acid, Gout, and Cardiac, Renal, and Metabolic Conditions in Middle Aged and Older People

Yingdong Han et al. J Am Heart Assoc. 2025 Apr.

Abstract

Background: Cardiac, renal, and metabolic (CRM) conditions are major causes of morbidity and mortality globally. This study aims to explore the relationship between serum uric acid (SUA), hyperuricemia, gout, and CRM conditions in middle-aged and elderly populations.

Methods: Sample 1 included participants from CHARLS (China Health and Retirement Longitudinal Study, n=9341), and Sample 2 from NHANES (National Health and Nutrition Examination Survey, unweighted n=17 913; weighted n=115 646 390). Ordinal logistic regression, Cox regression, and restricted cubic spline analyses were used to assess the relationship between SUA, hyperuricemia, gout, and CRM conditions. A 2-sample Mendelian randomization analysis was conducted to explore causal associations between SUA and CRM conditions.

Results: In both samples, SUA, hyperuricemia, and gout were positively correlated with the risk of CRM conditions. Among participants with 3 or ≥1 CRM condition(s), SUA, asymptomatic hyperuricemia, and gout with poorly controlled hyperuricemia showed significant positive associations with all-cause mortality, whereas these associations were not observed in patients with gout with normal SUA levels. The restricted cubic spline analysis revealed a positive relationship between SUA levels and the risk of all-cause mortality in participants with ≥1 CRM condition(s), demonstrating a nonlinear dose-response relationship across both samples (P for nonlinearity <0.05). Mendelian randomization analysis indicated that SUA was causally associated with cardiovascular disease, chronic kidney disease, and diabetes.

Conclusions: Hyperuricemia and gout are strong predictors of increased prevalence and mortality of CRM conditions, emphasizing the importance of managing hyperuricemia and gout in these patients.

Keywords: Mendelian randomization; cardiac, renal, and metabolic conditions; gout; hyperuricemia; serum uric acid.

PubMed Disclaimer

Conflict of interest statement

None.

Figures

Figure 1
Figure 1. Kaplan–Meier survival curve for all‐cause mortality (months) in participants with 0 to 3 CRM conditions.
CRM indicates cardiac, renal, and metabolic.
Figure 2
Figure 2. Dose–response relationship between SUA level (mg/dL) and the risk of all‐cause mortality in participants with different CRM conditions from CHARLS.
A, 0 CRM conditions. B, ≥1 CRM condition. Data were adjusted for age, sex, residence, education, body mass index, hypertension, smoking status, estimated glomerular filtration rate, and triglyceride. CHARLS, China Health and Retirement Longitudinal Study; CRM, cardiac, renal, and metabolic; and HR, hazard ratio.
Figure 3
Figure 3. Dose–response relationship between SUA level (mg/dL) and the risk of all‐cause mortality in participants with different CRM conditions from NHANES.
A, 1 CRM condition. B, 2 CRM conditions. C, 3 CRM conditions. D, ≥1 CRM condition. Data were adjusted for age, sex, race, education, poverty, body mass index, hypertension, smoking status, estimated glomerular filtration rate, and triglyceride. CRM indicates cardiac, renal, and metabolic; HR, hazard ratio; and NHANES, National Health and Nutrition Examination Survey.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Ostrominski JW, Arnold SV, Butler J, Fonarow GC, Hirsch JS, Palli SR, Donato BMK, Parrinello CM, O'Connell T, Collins EB, et al. Prevalence and overlap of cardiac, renal, and metabolic conditions in US adults, 1999–2020. JAMA Cardiol. 2023;8:1050–1060. doi: 10.1001/jamacardio.2023.3241 - DOI - PMC - PubMed
    1. Kittelson KS, Junior AG, Fillmore N, da Silva Gomes R. Cardiovascular‐kidney‐metabolic syndrome ‐ an integrative review. Prog Cardiovasc Dis. 2024;87:26–36. doi: 10.1016/j.pcad.2024.10.012 - DOI - PMC - PubMed
    1. Ahmad FB, Anderson RN. The leading causes of death in the US for 2020. JAMA. 2021;325:1829–1830. doi: 10.1001/jama.2021.5469 - DOI - PMC - PubMed
    1. Ostrominski JW, Thierer J, Claggett BL, Miao ZM, Desai AS, Jhund PS, Kosiborod MN, Lam CSP, Inzucchi SE, Martinez FA, et al. Cardio‐renal‐metabolic overlap, outcomes, and Dapagliflozin in heart failure with mildly reduced or preserved ejection fraction. JACC Heart Fail. 2023;11:1491–1503. doi: 10.1016/j.jchf.2023.05.015 - DOI - PubMed
    1. Global burden of metabolic risk factors for chronic diseases C. Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: a comparative risk assessment. Lancet Diabetes Endocrinol. 2014;2:634–647. doi: 10.1016/S2213-8587(14)70102-0 - DOI - PMC - PubMed

MeSH terms

LinkOut - more resources