Evidence mapPaperPMID 41225494Full record

ArticleNutrition journal2025

Associations of urinary phytoestrogen biomarkers with uric acid and hyperuricemia, and the mediating role of kidney function.

Min Luan, Youping Tian, Xianfeng Wu, Kuangyang Chen, Cheng Hu

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Article in Nutrition journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Min LuanShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Youping TianNational Management Office of Neonatal Screening Project for Congenital Heart Disease (CHD), Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
Xianfeng WuDepartment of Nephrology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Kuangyang ChenDepartment of Endocrinology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Cheng HuShanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. alfredhc@sjtu.edu.cn.

Funding

a three-year action plan for strengthening the construction of the public health system in Shanghai GWVI-11.2-YQ24Shanghai Sixth People's Hospital Grant Award ynqn202425the National Natural Science Foundation of China 82404275
6 · The paper itself

Abstract

backgroundHyperuricemia is increasingly acknowledged as a major public health issue. Current evidence on the effects of urinary phytoestrogen biomarkers on hyperuricemia is limited. Moreover, the potential mediation effect of kidney function was not assessed.

methodsThis study included 2,793 adults aged 20–79 years from the National Health and Nutrition Examination Surveys (NHANES 2007–2010). We used traditional regression and Bayesian kernel machine regression (BKMR) models to assess the associations of urinary phytoestrogen biomarkers with serum uric acid and hyperuricemia risk, and the mediation effect model to evaluate the role of kidney function in their associations. Estimated glomerular filtration rate (eGFR) was calculated for assessing kidney function.

resultsMost phytoestrogen biomarkers were inversely associated with serum uric acid and hyperuricemia risk, with mean changes in the estimates ranging from − 0.06 to -0.12 mg/dl and odds ratios ranging from 0.80 to 0.90. The BKMR model demonstrated that higher urinary concentrations of phytoestrogen mixtures were associated with lower serum uric acid and hyperuricemia risk, and identified that equol (EQU) and enterolactone (ENT) were the two most important contributors to the overall inverse associations. The BKMR model further confirmed that EQU and ENT were independently associated with lower serum uric acid and hyperuricemia risk. Causal mediation analysis indicated eGFR mediated the associations of EQU and ENT with hyperuricemia risk, with the proportion of mediation ranging from 9.64 to 11.60% (all P < 0.05), respectively.

conclusionsUrinary phytoestrogen biomarkers were inversely associated with serum uric acid levels and the risk of hyperuricemia, with EQU and ENT identified as the major contributing metabolites. These findings provide preliminary evidence that renal function may partially mediate the associations of EQU and ENT with uric acid concentrations and hyperuricemia risk.

Indexed as

HyperuricemiaKidneyPhytoestrogensUric AcidAdultAgedBayes TheoremBiomarkersCross-Sectional StudiesFemaleGlomerular Filtration RateHumansMaleMiddle AgedNutrition SurveysYoung AdultBiomarkersPhytoestrogensUric AcidHyperuricemiaKidney functionNHANESPhytoestrogen biomarkerUric acid

Identifiers

PMID41225494
PMCPMC12613696

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.