Metabolite Profiles Preceding Progression to Diabetes Mellitus after Gestational Diabetes

项目摘要/摘要 代谢组学已经成为一种识别代谢物变化以提高预测能力的新方法 除血糖外，2型糖尿病(DM)的比例也较高。患有妊娠期糖尿病(GDM)的女性 产后5至10年内极高的糖尿病转化率。但是，模型用于 对于这一高危人群，无法使用临床或代谢指标预测糖尿病。口服葡萄糖 建议在产后4至12周进行耐力测试(OGTT)，但对于新生儿来说，OGTT是一种负担 母亲和接受率都很低。孕妇哺乳与妊娠期糖尿病后2型糖尿病的研究(SWIFT) R01HD050625(Gunderson Pi)在2008至2011年间招募了1,035名患有GDM的女性，并进行了2小时的治疗 产后6-9周75 g研究OGTT和综合评估(基线)和 每年至两年的产后。这个前瞻性的、特征良好的GDM队列是独一无二的 定位于解决我们对向DM过渡的病理生理学和时间安排方面的主要差距 在妊娠期糖尿病怀孕后。我们的研究团队进行了第一项使用靶向代谢组学的研究 在妊娠期糖尿病妇女中识别和验证预测糖尿病的代谢物分布的方法。本研究 测量182种先前与成人糖尿病发病相关的代谢物，以确定包括 在4种分析物同种类型[支链氨基酸、己糖、PCaeC40：5、SM(OH)C14：1]中，预测能力(83%)超过 单独空腹血糖或负荷后2小时血糖(72-73%)。尽管前景看好，但我们建议完善这一配置文件 在整个队列中，大大扩展脂代谢产物，并用更长期的随访检验其预测能力。 总体研究目标是从产后早期血浆样本中识别代谢物图谱， 对患有妊娠期糖尿病的妇女产后长达8年的糖尿病发病率具有很高的预测性。斯威夫特的队伍是 出类拔萃的是它的种族/民族多样性(75%的少数民族)，规模大，纵向生物库来自多个 研究产后早期到产后2年高滞留率的OGTT和详细评估 (83%)，并在稳定的成员中通过电子健康记录(EHR)进行持续监测(84% 5年后仍为成员)。这是在8年后进行第4次面对面研究访问的最佳时机 重新评估糖耐量和开发预测工具的基线。具体目标是：目标1.至 确定和改进产后6-9周的代谢物特征(基线)，以更好地预测糖尿病的发生 在GDM怀孕后，我们假设产后6-9周发现的代谢物图谱将是 糖尿病早期(2年)和后期(8年)的高度预测性；目标2。 连续时间点的代谢情况(基线、1至2年和8年)和 评估它们与糖耐量变化的关系；我们假设不同的代谢物特征 会随着时间的推移与葡萄糖耐量的稳定或恶化密切相关。探索性的目标是 在特定的种族/民族群体中开发出独特的代谢物特征，高度预测糖尿病的发生。

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 related to the stability or deterioration in glucose tolerance over time. An exploratory aim is to develop distinct metabolite profiles highly predictive of incident DM within specific race/ethnicity groups.