The GROWTH Study, Glycemia Range and Offspring Weight and adiposity in response To Human milk

摘要 妊娠期母体代谢是代谢性疾病发育起源的关键因素。 暴露于母体高血糖和肥胖的后代有肥胖和紊乱的发病率增加， 葡萄糖代谢哺乳期也是方案拟订的一个关键窗口期。泌乳开始于 妊娠后半期，因此母乳（HM）的生物合成易受母体代谢的影响。 母乳营养素的个体间差异揭示了母体代谢对乳汁生物合成的影响。一 关于HM组成是否改变了被编程的后代的发育途径， 在子宫里包括妊娠期糖尿病（GDM）和肥胖症在内的母体代谢状态改变了HM的营养状况， 包括乳脂肪酸（FA）。我们的研究确定了改变HM亚油酸和二高-γ-亚麻酸 在母体糖尿病、高血糖症和肥胖症的情况下， 与婴儿成长的关系。然而，母体代谢在整个范围内的任何影响， 对HM组成和后代编程的影响尚未在详细的背景下进行评估。 子宫内暴露的特征分析。我们的目标是了解HM对母体代谢的易感性 影响后代的新陈代谢，确定干预措施，以减轻不利的发展规划。这 该提案的目的是确定孕妇怀孕对HM成分的影响， HM营养素对后代肥胖的影响。转化科学的方法将决定如何产妇 乳腺癌改变乳腺上皮细胞的基因表达，以及HM如何在不同的 母亲的乳房调节婴儿的肥胖。我们的总体假设是， 和病理范围影响HM组成，这反过来又影响后代的代谢程序， 反映在儿童早期肥胖症上。利用GO MOM的详细代谢表型 队列，我们将在450名妇女的队列中进行产后1、2和6个月的前瞻性HM分析， 在怀孕期间和怀孕后将母体脂肪酸联系起来，重点关注已知可调节后代的HM脂质 肥胖症（目标1）。将使用转录组学评价表达HM中脱落的乳腺上皮细胞 （子目标1）。为了重现性，将HM脂质与招募女性的单独验证队列进行比较 关于GDM我们将测量后代的身体组成，以辨别在1个月，2个月，6个月和2年的肥胖， 儿童饮食（目标2）。将人婴儿前脂肪细胞株暴露于收集的人乳脂质 并按母体脂肪含量的四分位数分组，以确定改变婴儿脂肪细胞发育的机制 (Aim 3）。完成这些目标将定义具有全面代谢的妊娠队列中的HM组成 在整个妊娠期和哺乳期，在BMI和BMI范围内进行分析。子代生长和 转化研究将促进对哺乳期暴露如何改变子宫内编程的理解。这 将进一步揭示干预措施，以减少不利的后代代谢健康的风险领域。

ABSTRACT Maternal metabolism during pregnancy is a key contributor to developmental origins of metabolic disease. Offspring exposed to maternal hyperglycemia and obesity have increased rates of obesity and disordered glucose metabolism. The lactation period is also a critical window for programming. Lactogenesis initiates in the second half of gestation, thus human milk (HM) biosynthesis is susceptible maternal metabolism. Interindividual variation in HM nutrients reveals the influence of maternal metabolism on milk biosynthesis. A knowledge gap exists as to whether HM composition alters developmental pathways of offspring programmed in utero. Maternal metabolic states including gestational diabietes (GDM) and obesity alter HM nutrient profiles, including milk fatty acids (FA). Our studies identified altered HM linoleic acid and dihomo-gamma-linolenic acid (DGLA) in conditions of maternal diabetes, hyperglycemia, and obesity, as well as HM palmitic acid and DGLA associations with infant growth. However, any impact of maternal metabolism across the entire range of glycemia on both HM composition and offspring programming has not been evaluated in context of detailed profiling of in utero exposures. Our goal is to understand how HM susceptibility to maternal metabolism impacts offspring metabolism, identifying interventions to mitigate adverse developmental programming. This proposal’s objective is to determine the impact of maternal glycemia in pregnancy on HM composition and effects of HM nutrients on offspring adiposity. Translational science approaches will determine how maternal glycemia alters mammary gland epithelial cell gene expression and how HM lipids across the range of maternal glycemia regulate infant adipoctyes. Our overarching hypothesis is that maternal glycemia in normal and pathologic ranges impacts HM composition, which in turn influences offspring metabolic programming as reflected by early childhood adiposity. Capitalizing on the detailed metabolic phenotyping of the GO MOMs cohort, we will conduct prospective HM profiling at 1, 2 and 6 months post-partum in a cohort of 450 women to associate maternal glycemia during and after pregnancy, focusing on HM lipids known to regulate offspring adiposity (Aim 1). Mammary epithelial cells shed in expressed HM will be evaluated using transcriptomics (SubAim 1). For reproducibility, HM lipids will be compared to a separate validation cohort enrolling women with GDM. We will measure offspring body composition to discern adiposity at months 1, 2, and 6 and 2 years, accounting for childhood diet (Aim 2). A human infant preadipocyte strain will be exposed to HM lipids collected and grouped by quartiles of maternal glycemia to determine mechanisms altering infant adipocyte development (Aim 3). Completing the aims will define HM composition in a pregnancy cohort with comprehensive metabolic profiling throughout pregnancy and lactation across the range of glycemia and BMI. Offspring growth and translational studies will advance understanding of how lactation exposures modify in utero programming. This will further the field by revealing interventions to reduce risk of adverse offspring metabolic health.