Evidence map›Paper›PMID 40794353›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2025

Metabolomic and lipidomic profiling of plasma in kidney stone patients: identification of potential biomarkers and therapeutic targets.

Ziyu Fang, Shenglan Gong, Ling Li, Shuwei Zhang, Wei He, Yuchen Gao, Yonghan Peng, Meng Shu, Yiying Jia, Bangyu Zou and 6 more

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Ziyu FangDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Shenglan GongDepartment of Hematology, Changhai hospital of Shanghai, Navy Medical University, Shanghai, 200433, China.
Ling LiDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Shuwei ZhangDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Wei HeDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Yuchen GaoDepartment of College of Arts, Sciences, and Engineering, The University of Rochester, Rochester, NY, 14627, USA.
Yonghan PengDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Meng ShuDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Yiying JiaDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Bangyu ZouDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Shaoxiong MingDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Min LiuDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Hao DongDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China.
Chenghua YangDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China. Chenghua-yang@qq.com.
Xu GaoDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China. gaoxu.changhai@foxmail.com.
Xiaofeng GaoDepartment of Urology, Changhai hospital of Shanghai, Navy Medical University, Changhai road, YangPu District, Shanghai, 200433, P.R. China. gxfdoc@sina.com.

Funding

National Key Research and Development Program of China 2020YFC2002704
6 · The paper itself

Abstract

backgroundKidney stone are among the most common urologic diseases characterized with metabolic disorder. Biomarker for kidney stone detection and the metabolic variables in kidney stone development have attracted increasing attention.

methodsTo explore the metabolomic and lipidomic characteristics of plasma in patients with kidney stones, we collected plasma samples from 200 participants, including 100 kidney stone patients and 100 healthy controls. We designated 59 patients with clearly defined stone compositions alongside matched healthy individuals as the training set (n = 118), while the remaining 41 patients with unclear stone compositions were paired with healthy individuals and served as the test set (n = 82).

resultsA total of 333 and 270 metabolites were significantly altered in kidney stone patients under positive and negative ion modes, respectively, compared to healthy controls. KEGG analysis indicated that pathways such as Arginine and proline metabolism, Citrate cycle (TCA cycle), Alanine, aspartate and glutamate metabolism and phenylalanine metabolism, were closely associated with kidney stone formation. Moreover, a total of 416 lipids were significantly changed in the Kidney stone group and the control group. Using Lasso model, a panel of integrated 4 metabolites and 4 lipids showed effective discrimination between Kidney stone group and the control group. Among these metabolites, Isorhamnetin has the potential to effectively reduced oxalate-induecd acute kidney injury, hence lowering the likelihood of stone formation.

conclusionsThese findings offer novel insights into the metabolic and lipidomic alterations associated with kidney stones, providing potential biomarkers for early diagnosis and therapeutic targets for intervention.

Indexed as

BiomarkersKidney CalculiLipidomicsLipidsMetabolomicsAdultCase-Control StudiesFemaleHumansMaleMetabolomeMiddle AgedBiomarkersLipidsInflammationIsorhamnetinKidney stoneLipidomicsMetabolomics

Identifiers

PMID40794353
PMCPMC12343701

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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 OpenQuestion graph.