# Metabolite Profiles Preceding Progression to Diabetes Mellitus after Gestational Diabetes > **NIH NIH R01** · KAISER FOUNDATION RESEARCH INSTITUTE · 2021 · $608,175 ## Abstract PROJECT SUMMARY/ABSTRACT Metabolomics has emerged as a novel approach to identify alterations in metabolites to improve prediction of type 2 diabetes mellitus (DM) beyond blood glucose. Women with gestational diabetes mellitus (GDM) have an extremely high rate of conversion to diabetes within 5 to 10 years post-delivery. However, models for prediction of DM using clinical or metabolic measures are unavailable for this high-risk group. Oral glucose tolerance testing (OGTT) is recommended at 4 to 12 weeks postpartum, but the OGTT is burdensome for new mothers and uptake is low. The Study of Women Infant Feeding, and Type 2 Diabetes After GDM (SWIFT) R01HD050625 (Gunderson PI) enrolled 1,035 women with GDM in 2008 to 2011 and administered 2-hr 75 g research OGTTs and comprehensive assessments from 6-9 weeks postpartum (baseline) and annually through two years post-delivery. This prospective, well-characterized GDM cohort is uniquely positioned to address major gaps in our understanding of the pathophysiology and timing of transitions to DM following GDM pregnancy. Our research team conducted the first study to use a targeted metabolomics approach to identify and validate a metabolite profile predictive of DM among women with GDM. This study measured 182 metabolites previously linked with incident DM in adults to identify a metabolite profile consisting of 4 analyte isotypes [BCAAs, hexoses, PCaeC40:5, SM(OH)C14:1] with predictive ability (83%) that exceeded fasting glucose alone or 2-hr post-load glucose (72-73%). Although promising, we propose to refine this profile in the entire cohort, greatly expand the lipid metabolites and test its predictive ability with longer-term follow up. The overall study goal is to identify a metabolite profile from early postpartum plasma samples that is highly predictive of incident DM up to 8 years post-delivery in women with GDM. The SWIFT cohort is exceptional for its racial/ethnic diversity (75% minority), large size, longitudinal Biobank from multiple research OGTTs and detailed assessments from early through 2 years postpartum with high retention (83%), and ongoing surveillance via electronic health records (EHR) within a stable membership (84% remain members 5 years later). The timing is optimal for a 4th in-person research visit at ~8th year post- baseline to re-assess glucose tolerance and develop prediction tools. The specific aims are: Aim 1. To identify and refine metabolite profiles at 6-9 weeks postpartum (baseline) that better predict incident diabetes following GDM pregnancy; we hypothesize that metabolite profiles identified at 6-9 weeks postpartum will be highly predictive of DM during early (2-year) and later (8-year) follow up periods; Aim 2. To characterize the metabolic profiles at consecutive time points across follow up (baseline, 1 to 2 years, and 8 years) and evaluate their relationship to transitions in glucose tolerance; we hypothesize that distinct metabolite profiles will be strongly r... ## Key facts - **NIH application ID:** 10147058 - **Project number:** 5R01DK118409-04 - **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE - **Principal Investigator:** Erica Pauline Gunderson - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $608,175 - **Award type:** 5 - **Project period:** 2018-07-01 → 2024-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10147058 ## Citation > US National Institutes of Health, RePORTER application 10147058, Metabolite Profiles Preceding Progression to Diabetes Mellitus after Gestational Diabetes (5R01DK118409-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10147058. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*