Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose

Jordi Merino, Aaron Leong, Ching Ti Liu, Bianca Porneala, Geoffrey A. Walford, Marcin von Grotthuss, Thomas J. Wang, Jason Flannick, Josée Dupuis, Daniel Levy, Robert E. Gerszten, Jose C. Florez, James B. Meigs

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

Aims/hypothesis: Identifying the metabolite profile of individuals with normal fasting glucose (NFG [<5.55 mmol/l]) who progressed to type 2 diabetes may give novel insights into early type 2 diabetes disease interception and detection. Methods: We conducted a population-based prospective study among 1150 Framingham Heart Study Offspring cohort participants, age 40–65 years, with NFG. Plasma metabolites were profiled by LC-MS/MS. Penalised regression models were used to select measured metabolites for type 2 diabetes incidence classification (training dataset) and to internally validate the discriminatory capability of selected metabolites beyond conventional type 2 diabetes risk factors (testing dataset). Results: Over a follow-up period of 20 years, 95 individuals with NFG developed type 2 diabetes. Nineteen metabolites were selected repeatedly in the training dataset for type 2 diabetes incidence classification and were found to improve type 2 diabetes risk prediction beyond conventional type 2 diabetes risk factors (AUC was 0.81 for risk factors vs 0.90 for risk factors + metabolites, p = 1.1 × 10−4). Using pathway enrichment analysis, the nitrogen metabolism pathway, which includes three prioritised metabolites (glycine, taurine and phenylalanine), was significantly enriched for association with type 2 diabetes risk at the false discovery rate of 5% (p = 0.047). In adjusted Cox proportional hazard models, the type 2 diabetes risk per 1 SD increase in glycine, taurine and phenylalanine was 0.65 (95% CI 0.54, 0.78), 0.73 (95% CI 0.59, 0.9) and 1.35 (95% CI 1.11, 1.65), respectively. Mendelian randomisation demonstrated a similar relationship for type 2 diabetes risk per 1 SD genetically increased glycine (OR 0.89 [95% CI 0.8, 0.99]) and phenylalanine (OR 1.6 [95% CI 1.08, 2.4]). Conclusions/interpretation: In individuals with NFG, information from a discrete set of 19 metabolites improved prediction of type 2 diabetes beyond conventional risk factors. In addition, the nitrogen metabolism pathway and its components emerged as a potential effector of earliest stages of type 2 diabetes pathophysiology.

Original languageEnglish (US)
Pages (from-to)1315-1324
Number of pages10
JournalDiabetologia
Volume61
Issue number6
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

Keywords

  • Metabolomics
  • Normoglycaemia
  • Type 2 diabetes pathophysiology
  • Type 2 diabetes prediction

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

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