MOM2CHild Study: Leveraging systems biology toward discoveries in Maternal Obesity, Milk, and Translation To Child Health

项目总结 母乳喂养是美国公共卫生服务和美国儿科学会建议的 优化婴幼儿营养与健康。母乳喂养开始接近85%的美国母亲，但意义重大 关于我们对母乳和哺乳作为一个生物系统的理解，仍然存在差距。这些差距 削弱我们识别可能损害母乳喂养或降低牛奶质量的影响的能力。肥胖是 持续的公共卫生流行病影响到至少29%的孕妇和19%的儿童 青少年。母亲肥胖不仅影响怀孕，还会缩短母乳喂养持续时间和 排他性。反过来，在大多数研究中，母乳喂养减少与儿童肥胖症的风险更大有关， 然而，对残留混淆的担忧削弱了人们对这些发现的信心。此外，许多小的 研究报告称，母亲肥胖与牛奶成分的变化(特别是瘦素， 炎性细胞因子、脂肪酸、寡糖和多肽)与儿童肥胖或肥胖有关。许多 这些变化可能是不健康的，并通过各种方式导致儿童肥胖症。令人信服地定义 母体肥胖及其相关炎症和合并症对母乳、哺乳期和乳汁的影响 儿童健康，需要一种系统的方法，利用下一代技术和大型 一群人。在这里，我们提出了MOM2CHild研究，它利用系统生物学来发现 母体肥胖、牛奶和儿童健康的转化。MOM2CHild将使用来自 流行和印记出生队列，这是根据与CDC和NIAID的合作协议提供资金的， 分别进行了分析。这些队列招募怀孕的辛辛那提母亲，并跟踪孩子到两年。占上风 已完成对245对母婴的随访。Imprint将完成1370名母婴的入学 到2023年。这两个队列都是由同一个团队设计和制定的，涉及全面的 调查问卷和健康数据库以及样本收集，包括牛奶和其他样本。标准化 研究母亲的母乳采集是在第2周和第6周进行的。 资助广泛地表征母乳成分，但样本已经仔细收集和 为此目的而存入银行。在MOM2CHild下，我们将使用来自盛行和 印记队列，并应用代谢组学、脂肪酸图谱、蛋白质组学、糖组学和微生物组学 分析，得到最先进的统计和机器学习的支持：1)广泛地表征 母体肥胖、炎症和代谢失调对牛奶成分的影响 生物学方法；2)确定母亲肥胖、炎症和代谢失调对 哺乳成功；以及3)确定母乳喂养和母乳成分变化对 儿童肥胖/肥胖、炎症和代谢物到2岁。我们的团队在科学上是很有资格的 我们的目标符合NICHD Begin倡议和RFA-HD-22-020，需要在这些领域取得成功。

PROJECT SUMMARY Breastfeeding is recommended by the U.S. Public Health Service and American Academy of Pediatrics to optimize infant nutrition and health. Breastfeeding initiation is approaching 85% of U.S. mothers, yet significant gaps remain regarding our understanding of human milk and lactation as a biologic system. These gaps undermine our ability to identify influences that may impair breastfeeding or reduce quality of milk. Obesity is an ongoing public health epidemic that affects at least 29% of pregnant women and 19% of children and adolescents. Maternal obesity influences not only pregnancy but also reduces breastfeeding duration and exclusivity. In turn, reduced breastfeeding is associated with greater risk of childhood obesity in most studies, though concerns about residual confounding undermine confidence in these findings. In addition, many small studies have reported that maternal obesity is associated with shifts in milk components (notably, leptin, inflammatory cytokines, fatty acids, oligosaccharides, and peptides) associated child adiposity or obesity. Many of these shifts could be unhealthy and contribute to child adiposity by various means. To convincingly define the impact of maternal obesity and its associated inflammation and co-morbidities on human milk, lactation and child health, a systems approach is needed, drawing on the power of next generation technologies and large cohorts. Here, we propose the MOM2CHild Study, which leverages systems biology towards discoveries in maternal obesity, milk, and translation to child health. MOM2CHild will use data and samples from the PREVAIL and IMPRINT birth cohorts, which are funded under cooperative agreements with CDC and NIAID, respectively. These cohorts enroll Cincinnati mothers in pregnancy and follow children to >2 years. PREVAIL has completed follow-up of 245 mother-infant pairs. IMPRINT will complete enrollment of 1,370 mother-infant pairs by 2023. Both cohorts were designed and enacted by the same team, involve comprehensive questionnaire and health databases and sample collection, including milk and other samples. Standardized human milk collections from study mothers are undertaken at weeks 2 and 6. Neither cohort was originally funded to extensively characterize human milk components, but samples have been carefully collected and banked for that purpose. Under MOM2CHild, we will use the wealth of data and samples from PREVAIL and IMPRINT cohorts, and apply metabolomics, fatty acid profiling, proteomics, glycomics, and microbiome analysis, supported by state-of-the-art statistical and machine learning to: 1) Extensively characterize the impact of maternal obesity, inflammation and metabolic dysregulation on milk composition using a systems biology approach; 2) Identify the impact of maternal obesity, inflammation and metabolic dysregulation on lactation success; and 3) Determine the impact of breastfeeding and variation in human milk composition on child adiposity/obesity, inflammation, and metabolome to age 2. Our team is well-qualified in the scientific domains needed to succeed in our aims, which align with the NICHD BEGIN initiative and RFA-HD-22-020.