Development of a Novel Hydroxylamine-Based Stable Isotope Labeling Reagent for Profiling Aldehyde Metabolic Biomarkers in Diabetes Using LC-MS/MS and Machine Learning

Abstract

Aldehyde compounds are significantly associated with diabetes mellitus. The metabolic profile of aldehydes can enhance understanding of the mechanisms underlying development of diabetes. This study employed a pair of stable isotope labeling (SIL) reagents, N-((1-phenyl-1H-1,2,3-triazol-4-yl)methyl)hydroxylamine (PTMH) and N-((1-(phenyl-d5)-1H-1,2,3-triazol-4-yl)methyl)hydroxylamine (PTMH-d5), for aldehyde profiling, address challenges related to selectivity, isomer formation, and transamination that occur with conventional labels, such as hydrazide or amine reagents. The metabolic profiling of 28 aldehydes on the serum samples of patients with type 2 diabetes mellitus (T2DM, n = 39) and gestational diabetes mellitus (GDM, n = 37) was carried out using PTMH/PTMH-d5. Furthermore, comparative metabolomic analyses of T2DM and GDM against healthy controls were performed. Moreover, advanced informatics approaches, including PCA, ROC, and PLS-DA, were employed for statistical evaluation. A machine learning classification model was also developed. The results revealed that 4-hydroxyhexenal, methylglyoxal, and trans-2-pentenal may serve as potential biomarkers for T2DM, whereas 4-hydroxyhexenal, methylglyoxal, heptanal, 5-hydroxymethylfurfural, and trans-2-octenal can be employed as potential biomarkers for GDM. The established model demonstrated significant potential as a prototype for early and accurate diagnosis of T2DM and GDM and may be translated into routine clinical diagnostics.