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. 2025 Mar;68(3):557-575.
doi: 10.1007/s00125-024-06324-z. Epub 2024 Dec 2.

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

Yuqing Chen  1 , Federico Torta  2   3 , Hiromi W L Koh  4 , Peter I Benke  2 , Resham L Gurung  5 , Jian-Jun Liu  5 , Keven Ang  5 , Yi-Ming Shao  5 , Gek Cher Chan  6   7 , Jason Chon-Jun Choo  8 , Jianhong Ching  9   10 , Jean-Paul Kovalik  9 , Tosha Kalhan  1 , Rajkumar Dorajoo  11 , Chiea Chuen Khor  11 , Yun Li  12   13   14 , Wern Ee Tang  15 , Darren E J Seah  15 , Charumathi Sabanayagam  16   17 , Radoslaw M Sobota  4 , Kavita Venkataraman  1 , Thomas Coffman  9 , Markus R Wenk  2   18 , Xueling Sim  19 , Su-Chi Lim  20   21   22   23 , E Shyong Tai  24   25
Affiliations

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

Yuqing Chen et al. Diabetologia. 2025 Mar.

Abstract

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

Methods: We 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.

Results: Elevated 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/interpretation: Our 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.

Keywords: Chronic kidney disease; Estimated glomerular filtration rate decline; Fatty acid oxidation; Genome-wide association study; Mendelian randomisation; Plasma metabolites; Type 2 diabetes.

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Conflict of interest statement

Acknowledgements: We thank all of the participants, study team and investigators of the Diabetic Cohort (DC), the Diabetic Nephropathy (DN) cohort and the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D) for their contributions to research. Data availability: Summary statistics of all metabolites profiled are provided in the ESM tables. Summary statistics of the GWAS on metabolites are available in the GWAS Catalog. Data from this study may be requested through the authors via an application process and shared through an institutional data-sharing agreement. Funding: This research is supported by the Singapore Ministry of Health’s National Medical Research Council under its Open Fund Large Collaborative Grant (NMRC/OFLCG/001/2017 and MOH-001327-02). The Diabetic Cohort (DC) is supported by individual research and clinical scientist award schemes from the National Medical Research Council (NMRC) and the Biomedical Research Council (BMRC) of Singapore, and infrastructure funding from the Singapore Ministry of Health (Population Health Metrics and Analytics [PHMA]), National University of Singapore and National University Health System, Singapore. The Diabetic Nephropathy (DN) cohort is supported by the Alexandra Health Fund (STAR grants 18203, 20201 and 23201). The Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D) is supported by NMRC grants (MOH-00066, MOH-000714 -01, MOH-001327-02 and OFLCG/001/2017) and the Alexandra Health Fund (STAR grants 18203 and 20201). Authors’ relationships and activities: The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: YC, FT, MRW, XS, SCL and EST conceived and designed the study. YC, HWLK and RLG analysed the data. YC, FT, XS, SCL and EST drafted the manuscript. All authors contributed to the writing of the article, provided support for the analysis and interpretation of results, critically revised the article and approved the final article. XS, SCL and EST are responsible for the integrity of the work as a whole.

References

    1. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY (2004) Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 351(13):1296–1305. https://doi.org/10.1056/NEJMoa041031 - DOI - PubMed
    1. Magliano DJ, Boyko EJ, IDF Diabetes Atlas 10th edition scientific committee (2021) IDF Diabetes Atlas 2021. Available from: https://diabetesatlas.org/data/en/ . Accessed 19 Sept 2024
    1. Tong LL, Adler SG (2022) Diabetic kidney disease treatment: new perspectives. Kidney Res Clin Pract 41(Suppl 2):S63–S73. https://doi.org/10.23876/j.krcp.21.288 - DOI - PubMed - PMC
    1. Kume S, Maegawa H (2020) Lipotoxicity, nutrient-sensing signals, and autophagy in diabetic nephropathy. JMA J 3(2):87–94. https://doi.org/10.31662/jmaj.2020-0005 - DOI - PubMed - PMC
    1. Liu JJ, Ghosh S, Kovalik JP et al (2017) Profiling of plasma metabolites suggests altered mitochondrial fuel usage and remodeling of sphingolipid metabolism in individuals with type 2 diabetes and kidney disease. Kidney Int Rep 2(3):470–480. https://doi.org/10.1016/j.ekir.2016.12.003 - DOI - PubMed

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