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: 10913646
• 负责人: Ellen Cross Francis
• 金额: $ 24.9万
• 依托单位: RUTGERS BIOMEDICAL AND HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10913646
• 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; Cholesterol; Chorionic villi; Clinical; Complex; Data; Development; Developmental Biology; Diabetes Mellitus; Diet; Environment; 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; Life; Life Cycle Stages; Life Style; Life course epidemiology; 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; response; risk stratification; symposium; 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; Cholesterol; Chorionic villi; Clinical; Complex; Data; Development; Developmental Biology; Diabetes Mellitus; Diet; Environment; 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; Life; Life Cycle Stages; Life Style; Life course epidemiology; 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; 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.

项目摘要/摘要 孕产妇资源分配受孕产妇生理适应的控制；然而， 肥胖和妊娠糖尿病（GDM）等疾病与次优的自适应有关 对妊娠的反应导致子宫内养营不足。在子宫营养不良中（即胎儿过度 - 考虑到肥胖的早期发作和 年轻人的心脏代谢疾病。此外，较高的血糖和肥胖，甚至低于临床阈值 GDM和肥胖症对后代健康有不利影响。这种代谢异质性值得注意 它影响胎儿发育中涉及的目标时机，例如PLAPETA。特征代谢 孕妇的变异性并评估与后代代谢健康的关联将揭示细微差别 在后代有助于代谢疾病风险的母体表型。但是，孕产妇的关联 尚不清楚与母体燃料（例如葡萄糖，胰岛素，脂质）和可修改行为的代谢异质性。 此外，未知是否在胎儿编程中实施的lopenal信号反映了代谢 通过怀孕期间通过循环生物标志物评估的异质性。艾伦·弗朗西斯（Ellen Francis）博士的提议讲话 这些知识差距通过整合低维和高维观测数据并应用高级 统计技术来检验以下假设，即不同的Mater代谢亚组对应于差异 在位置信号通路中 编程后代代谢风险。该提案将在期间使用现有禁食的遗产样本 怀孕（n = 1410），斑点绒毛组织，并在4-8岁的后代收集新的代谢组学。 通过教学教学和修补培训，弗朗西斯博士将获得培训，以分析“ OMICS数据” 在生命的流行病学框架内，以表征怀孕的代谢变异性并产生 与肥胖和母体燃料有关的代谢亚组。她会提高对placenal的理解 通过接受广泛的动手培训（包括在实验室和 具有专业知识的导师和围产期 生物学。在独立阶段，她将使用在重要阶段获得的培训来评估孕产妇的 代谢亚组反映在胎盘养分传感途径中，生成代谢组学数据 后代并创建后代代谢概况。然后，她将评估母体代谢子群 与童年时代的代谢特征以及这些关联的程度有关 由胎盘营养感应途径介导。这些完整研究的发现将改善我们的 了解胎儿发育中涉及的代谢途径的理解有助于了解母体 代谢可变性会影响后代的代谢风险，并且可能揭示关键细胞和行为目标 为了预防策略，同时协助弗朗西斯博士确立了独立研究者的职业。