Characterizing metabolic variability during pregnancy to understand pathways of in-utero overnutrition: an integrative analysis of metabolomics and lifestyle data

表征妊娠期间的代谢变异性以了解子宫内营养过剩的途径：代谢组学和生活方式数据的综合分析

• 批准号: 10425090
• 负责人: Ellen Cross Francis
• 金额: $ 9.44万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-09 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10425090
• 关键词: 5 year old; 8 year old; Address; Amino Acids; Behavioral; Biochemical; Biological; Biological Assay; Biological Markers; Biology; Birth; Blood; Blood Pressure; Body mass index; Cardiometabolic Disease; Child; Childhood; Chorionic villi; Clinical; Complex; Data; Development; Developmental Biology; Diabetes Mellitus; Diet; Environment; Epidemiology; Exposure to; FRAP1 gene; Fasting; Fatty Acids; Fatty acid glycerol esters; Fetal Development; Gestational Diabetes; Glucose; Health; Heterogeneity; Hyperglycemia; Infant; Instruction; Insulin; Insulin Signaling Pathway; Interruption; Knowledge; Lead; Life; Life Style; Lipids; Mediating; Mentors; Metabolic; Metabolic Diseases; Metabolic Pathway; Metabolism; Mothers; Obesity; Overnutrition; Participant; Pathology; Pathway interactions; Perinatal; Phase; Phenotype; Phosphorylation; Physical activity; Physiological Adaptation; Placenta; Placental Biology; Plasma; Pregnancy; Pregnant Women; Prevention strategy; Principal Component Analysis; Process; Proteins; Research; Research Personnel; Resource Allocation; Resources; Risk; Role; Sampling; Serum; Severities; Signal Pathway; Signal Transduction; Subgroup; Techniques; Testing; Tissues; Training; Triglycerides; Woman; Youth; adipokines; cardiometabolic risk; career; circulating biomarkers; cohort; detection of nutrient; disorder risk; early-onset obesity; fetal; fetal programming; high dimensionality; improved; in utero; lifestyle data; lifestyle intervention; maternal condition; maternal obesity; metabolic profile; metabolomics; modifiable behavior; novel; obesity risk; obstetrical complication; offspring; offspring obesity; phenotypic data; prenatal; prepregnancy; programs; response; risk stratification; symposium

PROJECT SUMMARY/ABSTRACT Maternal-fetal resource allocation is governed by complex maternal physiological adaptations; however, conditions such as obesity and Gestational Diabetes Mellitus (GDM) are associated with a suboptimal adaptive response to pregnancy resulting in under- or overnutrition in utero. In utero overnutrition (i.e., fetal over- nourishment by excess exposure to maternal fuels) is a concern given the earlier onset of obesity and cardiometabolic disease in youth. Moreover, higher glycemia and adiposity, even below thresholds of clinical GDM and obesity, have detrimental effects on offspring health. Such metabolic heterogeneity is noteworthy as it influences target tissues involved in fetal development, such as the placenta. Characterizing metabolic variability in pregnant women and assessing associations with offspring metabolic health will reveal nuances in maternal phenotypes that contribute to metabolic disease risk in offspring. However, the associations of maternal metabolic heterogeneity with maternal fuels (e.g., glucose, insulin, lipids) and modifiable behaviors are unclear. Moreover, it is unknown if placental signaling, which is implicated in fetal programming, reflects metabolic heterogeneity assessed via circulating biomarkers during pregnancy. Dr. Ellen Francis’ proposal addresses these knowledge gaps by integrating low- and high-dimensional observational data and applying advanced statistical techniques to test the hypothesis that distinct maternal metabolic subgroups correspond to differences in placental signaling pathways, and that the maternal subgroups and placental pathways are involved in programming of offspring metabolic risk. This proposal will use existing samples of fasting maternal blood during pregnancy (N=1410), placental villus tissue, and collect new metabolomics in offspring at 4-8 years of age. Through didactic instruction and mentored training, Dr. Francis will obtain training in the analysis of ‘omics data within a lifecourse epidemiological framework to characterize metabolic variability in pregnancy and generate metabolic subgroups related to adiposity and maternal fuels. She will advance her understanding of placental and developmental biology (fetal programing) by receiving extensive hands-on-training (inclusion in lab and bench training, and conference and seminar attendance) from mentors with expertise in placental and perinatal biology. In the independent phase, she will use training gained in the mentored phase to assess if maternal metabolic subgroups are reflected in placental nutrient sensing pathways, generate metabolomics data in offspring and create offspring metabolic profiles. She will then assess whether maternal metabolic subgroups are associated with offspring metabolic profiles in childhood, and the extent to which these associations are mediated by placental nutrient sensing pathways. Findings from these complementary studies will improve our understanding of metabolic pathways involved in fetal development, contribute to knowledge of how maternal metabolic variability influences metabolic risk in offspring, and could reveal key cellular and behavioral targets for prevention strategies, while assisting Dr. Francis’ to establish a career as an independent investigator.

项目总结/摘要 母胎资源分配受到复杂的母体生理适应的支配;然而， 诸如肥胖症和妊娠糖尿病（GDM）的病症与次优的适应性 对妊娠的反应导致子宫内营养不足或营养过剩。子宫内营养过剩（即，胎儿过度- 由于肥胖症发病较早， 年轻人的心脏代谢疾病。此外，更高的肥胖和肥胖，甚至低于临床阈值， GDM和肥胖对后代健康有不利影响。这种代谢异质性值得注意， 它影响与胎儿发育有关的靶组织，如胎盘。表征代谢 孕妇的变异性和评估与后代代谢健康的关联将揭示 导致后代代谢疾病风险的母体表型。然而，产妇的协会 母体燃料的代谢异质性（例如，葡萄糖、胰岛素、脂质）和可改变的行为尚不清楚。 此外，还不清楚与胎儿编程有关的胎盘信号是否反映了代谢 通过妊娠期间循环生物标志物评估异质性。Ellen弗朗西斯博士的提案 通过整合低维和高维观测数据并应用先进的 检验不同母体代谢亚组对应于差异的假设的统计技术 在胎盘信号通路中，母体亚群和胎盘通路参与了 后代代谢风险的规划。该提案将使用现有的空腹产妇血液样本， 妊娠（N=1410），胎盘绒毛组织，并在4-8岁的后代中收集新的代谢组学。 通过教学指导和指导培训，弗朗西斯博士将获得“组学数据分析”方面的培训 在生命过程流行病学框架内，以表征妊娠期代谢变异性， 与肥胖和母体燃料相关的代谢亚组。她将进一步了解胎盘 和发育生物学（胎儿编程）通过接受广泛的实践培训（包括在实验室和 在胎盘和围产期方面具有专业知识的导师提供的长凳培训以及会议和研讨会出席情况） 生物学在独立阶段，她将使用在指导阶段获得的培训来评估是否有产妇 代谢亚组反映在胎盘营养感应途径中，产生代谢组学数据， 并创建后代代谢谱。然后她将评估母体代谢亚组是否 与儿童时期的后代代谢谱有关，以及这些关联的程度 由胎盘营养感应途径介导。这些补充研究的结果将改善我们的 了解参与胎儿发育的代谢途径，有助于了解母亲如何 代谢变异性影响后代的代谢风险，并可能揭示关键的细胞和行为目标 为预防策略，同时协助博士弗朗西斯'建立一个职业生涯作为一个独立的调查员。