Differences in Compositions of Gut Bacterial Populations and Bacteriophages in 5-11 Year-Olds Born Preterm Compared to Full Term.

Preterm infants are exposed to major perinatal, post-natal, and early infancy events that could impact on the gut microbiome. These events include infection, steroid and antibiotic exposure, parenteral nutrition, necrotizing enterocolitis, and stress. Studies have shown that there are differences in the gut microbiome during the early months of life in preterm infants. We hypothesized that differences in the gut microbial composition and metabolites in children born very preterm persist into mid-childhood. Participants were healthy prepubertal children aged 5-11 years who were born very preterm (≤32 weeks of gestation; n = 51) or at term (37-41 weeks; n = 50). We recorded the gestational age, birth weight, mode of feeding, mode of birth, age, sex, and the current height and weight of our cohort. We performed a multi'omics [i.e., 16S rRNA amplicon and shotgun metagenomic sequencing, SPME-GCMS (solid-phase microextraction followed by gas chromatography-mass spectrometry)] analysis to investigate the structure and function of the fecal microbiome (as a proxy of the gut microbiota) in our cross-sectional cohort. Children born very preterm were younger (7.8 vs. 8.3 years; p = 0.034), shorter [height-standard deviation score (SDS) 0.31 vs. 0.92; p = 0.0006) and leaner [BMI (body mass index) SDS -0.20 vs. 0.29; p < 0.0001] than the term group. Children born very preterm had higher fecal calprotectin levels, decreased fecal phage richness, lower plasma arginine, lower fecal branched-chain amino acids and higher fecal volatile (i.e., 3-methyl-butanoic acid, butyrolactone, butanoic acid and pentanoic acid) profiles. The bacterial microbiomes did not differ between preterm and term groups. We speculate that the observed very preterm-specific changes were established in early infancy and may impact on the capacity of the very preterm children to respond to environmental changes.

Physical Interactions and Expression Quantitative Traits Loci Identify Regulatory Connections for Obesity and Type 2 Diabetes Associated SNPs.

The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional [i.e., expression quantitative trait loci (eQTL)] outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g., AP3S2, ELP5, SVIP, IRS1, FADS2, WFS1, RBM6, HORMAD1, PYROXD2), which are enriched in tissues (e.g., adipose, skeletal muscle, pancreas) and biological processes and canonical pathways (e.g., lipid metabolism, leptin, and glucose-insulin signaling pathways) that are important for the pathogenesis of type 2 diabetes and obesity. Our discovery-based approach also identifies enrichment for eQTL SNP-gene interactions in tissues that are not classically associated with diabetes or obesity. We propose that the combinatorial action of active obesity and diabetes spatial eQTL SNPs on their gene pairs within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism.