Evidence mapPaperPMID 39621102Full record

ArticleDiabetologia2025

Metabolomics profiling in multi-ancestral individuals with type 2 diabetes in Singapore identified metabolites associated with renal function decline.

Yuqing Chen, Federico Torta, Hiromi W L Koh, Peter I Benke, Resham L Gurung, Jian-Jun Liu, Keven Ang, Yi-Ming Shao, Gek Cher Chan, Jason Chon-Jun Choo and 16 more

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Article in Diabetologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors.

Yuqing ChenSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore.
Federico TortaSingapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore, Republic of Singapore.
Hiromi W L KohInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore.
Peter I BenkeSingapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore, Republic of Singapore.
Resham L GurungClinical Research Unit, Khoo Teck Puat Hospital, Singapore, Republic of Singapore.
Jian-Jun LiuClinical Research Unit, Khoo Teck Puat Hospital, Singapore, Republic of Singapore.
Keven AngClinical Research Unit, Khoo Teck Puat Hospital, Singapore, Republic of Singapore.
Yi-Ming ShaoClinical Research Unit, Khoo Teck Puat Hospital, Singapore, Republic of Singapore.
Gek Cher ChanDivision of Nephrology, Department of Medicine, National University Hospital, Singapore, Republic of Singapore.
Jason Chon-Jun ChooDepartment of Renal Medicine, Singapore General Hospital, Singapore, Republic of Singapore.
Jianhong ChingCardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Republic of Singapore.
Jean-Paul KovalikCardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Republic of Singapore.
Tosha KalhanSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore.
Rajkumar DorajooGenome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore.
Chiea Chuen KhorGenome Institute of Singapore (GIS), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore.
Yun LiDepartment of Genetics, University of North Carolina, Chapel Hill, NC, USA.
Wern Ee TangNational Healthcare Group Polyclinics, Singapore, Republic of Singapore.
Darren E J SeahNational Healthcare Group Polyclinics, Singapore, Republic of Singapore.
Charumathi SabanayagamSingapore Eye Research Institute, Singapore National Eye Center, Singapore, Republic of Singapore.
Radoslaw M SobotaInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore.
Kavita VenkataramanSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore.
Thomas CoffmanCardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore, Republic of Singapore.
Markus R WenkSingapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore, Republic of Singapore.
Xueling SimSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore. ephsx@nus.edu.sg.ORCID http://orcid.org/0000-0002-1233-7642
Su-Chi LimSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore. lim.su.chi@ktph.com.sg.ORCID http://orcid.org/0000-0003-1742-5817
E Shyong TaiSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore. mdctes@nus.edu.sg.ORCID http://orcid.org/0000-0003-2929-8966

Funding

Alexandra Health Fund 20201Alexandra Health Fund 23201Alexandra Health Fund STAR grant 18203Biomedical Research Council MOH-001327-02Biomedical Research Council NMRC/OFLCG/001/2017National Medical Research Council MOH-00066National Medical Research Council MOH-000714 -01National Medical Research Council MOH-001327-02National Medical Research Council OFLCG/001/2017Singapore Ministry of Health's National Medical Research Council MOH-001327-02Singapore Ministry of Health's National Medical Research Council NMRC/OFLCG/001/2017
6 · The paper itself

Abstract

aims/hypothesisThis study aims to explore the association between plasma metabolites and chronic kidney disease progression in individuals with type 2 diabetes.

methodsWe performed a comprehensive metabolomic analysis in a prospective cohort study of 5144 multi-ancestral individuals with type 2 diabetes in Singapore, using eGFR slope as the primary outcome of kidney function decline. In addition, we performed genome-wide association studies on metabolites to assess how these metabolites could be genetically influenced by metabolite quantitative trait loci and performed colocalisation analysis to identify genes affecting both metabolites and kidney function.

resultsElevated levels of 61 lipids with long unsaturated fatty acid chains such as phosphatidylethanolamines, triacylglycerols, diacylglycerols, ceramides and deoxysphingolipids were prospectively associated with more rapid kidney function decline. In addition, elevated levels of seven amino acids and three lipids in the plasma were associated with a slower decline in eGFR. We also identified 15 metabolite quantitative trait loci associated with these metabolites, within which variants near TM6SF2, APOE and CPS1 could affect both metabolite levels and kidney functions. CONCLUSIONS/

interpretationOur study identified plasma metabolites associated with prospective renal function decline, offering insights into the underlying mechanism by which the metabolite abnormalities due to fatty acid oversupply might reflect impaired β-oxidation and associate with future chronic kidney disease progression in individuals with diabetes.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesKidneyRenal Insufficiency, ChronicAgedDisease ProgressionFemaleGenome-Wide Association StudyGlomerular Filtration RateHumansMaleMetabolomicsMiddle AgedProspective StudiesQuantitative Trait LociSingaporeChronic kidney diseaseEstimated glomerular filtration rate declineFatty acid oxidationGenome-wide association studyMendelian randomisationPlasma metabolitesType 2 diabetes

Identifiers

PMID39621102

What Socratic holds

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Registered trials

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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.