Given the growing body of evidence that many (if not the vast majority) of chronic, non-communicable disease have their origins in fetal life, understanding the in utero factors that impact fetal metabolism and development are among the most important public health issues of our time. During the initial grant period, we generated and published considerable data which (together with others work) collectively suggest that fetal (re)programming of metabolic and developmental gene expression pathways occur via stable modification of not only the epigenome, but the metagenome (e.g., the microbial community genetic repertoire). In the current renewal, we propose a series of experiments that will considerably advance these findings. Why study the microbiome in our non-human primate model? Employing our non-human primate model, we were the first to demonstrate that a high fat diet, and not obesity per se, drives both maternal and offspring microbial dysbiosis. For several years we have developed and employed metagenomics to characterize the early human developmental microbiome, and observed variation in its community membership and their function by virtue of multiple factors. However, given the inherent confounding of human cohorts, it remains unknown what the relative impact of maternal diet is on the early offspring microbiome, and whether this is driven by host epigenomic modifications. Moreover, how this leads to lifelong metabolic disease is unknown. Based on our published and preliminary data from the initial grant period, our central hypothesis is that under conditions of maternal high fat diet exposure in gestation and lactation, the offspring hepatic and hypothalamic epigenome and the establishing microbiome undergo a series of highly predictive modifications. These modifications result in meaningful functional alterations to the offspring metabolome as well as transcriptome, resulting in both metabolic disturbances as well as behavioral modifications. While these offspring modifications are not readily modifiable with an improved diet post-weaning, reversion of the dams onto control diet just prior to pregnancy is largely restorative to her offspring. In order to prove this hypothesis, we will execute four essential aims in our primate cohort. The net result of the completion of these aims will be to first establish the conserved alterations to the fetal and juvenile gut and oral microbiome, alongside full spectral metabolomics, to identify the stable and lasting metabolic (both host and bacterial) footprint of maternal high fat diet exposure. By integrating our existing epigenomics data with the derived metagenomics data, we will be able predict how these microbiome and metabolome variations in turn influence fetal and offspring metabolic outcomes and phenotypic traits. After having spent over a decade establishing and molecular characterizing the current NHP model, we are uniquely poised to now undertake complex integration of our derived unique data sets in studies which are scientifically rigorous, feasible, justifiable, and of likely long-term significance and high translational impact.
Over the last decade have developed a non-human primate model of obesity, now in its ninth year, to study the root molecular causes rendering risk of offspring metabolic disease following maternal high fat diet exposure. In the first period of this grant, we have shown that it is maternal high fat diet (HFD) consumption (rather than maternal obesity per se) which drives fetal metabolic reprogramming, and concomitantly modifies the fetal histone code as well as persistent alterations to the offspring microbiome as far out as three years of age, and note that the ensuant dysbiosis is not corrected with a healthy post-weaning diet. As a result of this work, we are now uniquely poised to apply metagenomics with advanced analytical approaches to decipher the molecular means by which the primate epigenome and its metagenome are modified by a maternal HFD, and how these changes result in lifelong risk of metabolic disease in the offspring.
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