Plasma metabolome and lipidome associations with type 2 diabetes and diabetic nephropathy

Yan Ming Tan, Yan Gao, Guoshou Teo, Hiromi W.L. Koh, E. Shyong Tai, Chin Meng Khoo, Kwok Pui Choi, Lei Zhou, Hyungwon Choi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)

Abstract

We conducted untargeted metabolomics analysis of plasma samples from a cross-sectional case–control study with 30 healthy controls, 30 patients with diabetes mellitus and normal renal function (DM-N), and 30 early diabetic nephropathy (DKD) patients using liquid chromatography-mass spectrometry (LC-MS). We employed two different modes of MS acquisition on a high-resolution MS instrument for identification and semi-quantification, and analyzed data using an advanced multivariate method for prioritizing differentially abundant metabolites. We obtained semi-quantification data for 1088 unique compounds (~55% lipids), excluding compounds that may be either exogenous compounds or treated as medication. Supervised classification analysis over a confounding-free partial correlation network shows that prostaglandins, phospholipids, nucleotides, sugars, and glycans are elevated in the DM-N and DKD patients, whereas glutamine, phenylacetylglutamine, 3-indoxyl sulfate, acetylphenylalanine, xanthine, dimethyluric acid, and asymmetric dimethylarginine are increased in DKD compared to DM-N. The data recapitulate the well-established plasma metabolome changes associated with DM-N and suggest uremic solutes and oxidative stress markers as the compounds indicating early renal function decline in DM patients.

Original languageEnglish
Article number228
JournalMetabolites
Volume11
Issue number4
DOIs
Publication statusPublished - Apr 2021
Externally publishedYes

Keywords

  • Data independent acquisition
  • Diabetic nephropathy
  • Oxidative stress
  • Phospholipids
  • Prostaglandins
  • Uremic toxins

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology

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