Metabolomic profiles associated with subtypes of prediabetes among Mexican Americans in Starr County, Texas, USA

Abstract

Aims/hypothesis: To understand the complex metabolic changes that occur long before the diagnosis of type 2 diabetes, we investigated differences in metabolomic profiles in plasma between prediabetic and normoglycaemic individuals for subtypes of prediabetes defined by fasting glucose, 2 h glucose and HbA_1c measures.

Methods: Untargeted metabolomics data were obtained from 155 plasma samples from 127 Mexican American individuals from Starr County, TX, USA. None had type 2 diabetes at the time of sample collection and 69 had prediabetes by at least one criterion. We tested statistical associations of amino acids and other metabolites with each subtype of prediabetes.

Results: We identified distinctive differences in amino acid profiles between prediabetic and normoglycaemic individuals, with further differences in amino acid levels among subtypes of prediabetes. When testing all named metabolites, several fatty acids were also significantly associated with 2 h glucose levels. Multivariate discriminative analyses show that untargeted metabolomic data have considerable potential for identifying metabolic differences among subtypes of prediabetes.

Conclusions/interpretation: People with each subtype of prediabetes have a distinctive metabolomic signature, beyond the well-known differences in branched-chain amino acids.

Data availability: Metabolomics data are available through the NCBI database of Genotypes and Phenotypes (dbGaP, accession number phs001166; www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001166.v1.p1).

Keywords: Amino acids; Impaired fasting glucose; Impaired glucose tolerance; Metabolomics; Mexican Americans; Prediabetes; Type 2 diabetes.

Fig. 1

Mean normalised amino acid levels of prediabetes and normoglycaemia by (a) any of the three criteria, (b) fasting blood glucose, (c) 2 h glucose and (d) HbA_1c levels. Arg, arginine; Gln, glutamine; Ile, isoleucine; Leuc, leucine; Lys, lysine; Phe, phenylalanine; Pro, proline; Thr, threonine; Trp, tryptophan; Tyr, tyrosine; Val, valine; Glu, glucose. Data are expressed as means ± SEM

Fig. 2

LDAs between normoglycaemic and prediabetic individuals defined by three criteria. Linear discriminant (LD)1 was projected by using fasting glucose (FG)-based prediabetes status as class labels, and LD2 and LD3 by using 2 h glucose (2hG) and HbA_1c, respectively. (a–c) LDA was performed on 12 amino acid measures with missing rates of less than 30%, coloured by prediabetes status by (a) fasting glucose, (b) 2 h glucose and (c) HbA_1c. (d–f) LDA was performed on 63 metabolites selected by LASSO regression on 151 known metabolites with missing rates of less than 30%, coloured by prediabetes status by (d) fasting glucose, (e) 2 h glucose and (f) HbA_1c. (g–i) LDA was performed on 118 metabolites selected by LASSO regression on 3560 metabolites including unknown metabolites, coloured by prediabetes status by (g) fasting glucose, (h) 2 h glucose and (i) HbA_1c

Fig. 3

Correlation between tryptophan and kynurenine levels in normoglycaemic and prediabetic groups. *p<0.05, **p<0.001.