The skeletal muscle hypertrophic response to resistance exercise training (RT) is highly variable across individuals. The molecular underpinnings of this heterogeneity are unclear. This study investigated transcriptional networks linked to RT-induced muscle hypertrophy, classified as 1) predictive of hypertrophy, 2) responsive to RT independent of muscle hypertrophy, or 3) plastic with hypertrophy. Older adults (n = 31, 18 F/13 M, 70 ± 4 yr) underwent 14-wk RT (3 days/wk, alternating high-low-high intensity). Muscle hypertrophy was assessed by pre- to post-RT change in mid-thigh muscle cross-sectional area (CSA) [computed tomography (CT), primary outcome] and thigh lean mass [dual-energy X-ray absorptiometry (DXA), secondary outcome]. Transcriptome-wide poly-A RNA-seq was performed on vastus lateralis tissue collected pre- (n = 31) and post-RT (n = 22). Prediction networks (using only baseline RNA-seq) were identified by weighted gene correlation network analysis (WGCNA). To identify Plasticity networks, WGCNA change indices for paired samples were calculated and correlated to changes in muscle size outcomes. Pathway-level information extractor (PLIER) was applied to identify Response networks and link genes to biological annotation. Prediction networks (n = 6) confirmed transcripts previously connected to resistance/aerobic training adaptations in the MetaMEx database while revealing novel member genes that should fuel future research to understand the influence of baseline muscle gene expression on hypertrophy. Response networks (n = 6) indicated RT-induced increase in aerobic metabolism and reduced expression of genes associated with spliceosome biology and type-I myofibers. A single exploratory Plasticity network was identified. Findings support that interindividual differences in baseline gene expression may contribute more than RT-induced changes in gene networks to muscle hypertrophic response heterogeneity. Code/Data: https://github.com/kallavin/MASTERS_manuscript/tree/master.

Vertical sleeve gastrectomy (VSG) is a surgical weight loss procedure that resects 80% of the stomach, creating a tube linking the esophagus to the duodenum. Because of the efficacy and relative simplicity of VSG, it is preferred in the United States, with VSG currently at >61% of bariatric surgeries performed. Surprisingly, there has never been a complete molecular characterization of the human stomach greater curvature's fundus and corpus. Here we compare and contrast the molecular makeup of these regions. We performed a prospective cohort study to obtain gastric tissue samples from patients undergoing elective VSG. Paired fundus and corpus samples were obtained. Whole genome transcriptome analysis was performed by RNA sequencing (N = 10), with key findings validated by qPCR (N = 24). Participants were primarily female (95.8%) and White (79.15%). Mean body mass index, body weight, and age were 46.1 kg/m2, 121.6 kg, and 43.29 yr, respectively. Overall, 432 gene transcripts were significantly different between the fundus and the corpus (P < 0.05). A significant correlation was found between the RNA sequencing dataset and qPCR validation, demonstrating robust gene expression differences between the fundus and the corpus. Significant genes included progastricsin, acidic chitinase, and gastokine 1 and 2 in both the fundus and the corpus. Of the very highly expressed genes in both regions, 87% were present in both the stomach's fundus and corpus, indicating substantial overlap. Despite significant overlap in the greater curvature gene signature, regional differences exist within the fundus and the corpus. Given that the mechanism of VSG is partly unresolved, the potential that the resected tissue may express genes that influence long-term body weight regulation is unknown and could influence VSG outcomes.

Mice have provided critical mechanistic understandings of clinical traits underlying metabolic syndrome (MetSyn) and susceptibility to MetSyn in mice is known to vary among inbred strains. We investigated the diet- and strain-dependent effects on metabolic traits in the eight Collaborative Cross (CC) founder strains (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Liver transcriptomics analysis showed that both atherogenic diet and host genetics have profound effects on the liver transcriptome, which may be related to differences in metabolic traits observed between strains. We found strain differences in circulating trimethylamine N-oxide (TMAO) concentration and liver triglyceride content, both of which are traits associated with metabolic diseases. Using a network approach, we identified a module of transcripts associated with TMAO and liver triglyceride content, which was enriched in functional pathways. Interrogation of the module related to metabolic traits identified NADPH oxidase 4 (Nox4), a gene for a key enzyme in the production of reactive oxygen species, which showed a strong association with plasma TMAO and liver triglyceride. Interestingly, Nox4 was identified as the highest expressed in the C57BL/6J and NZO/HILtJ strains and the lowest expressed in the CAST/EiJ strain. Based on these results, we suggest that there may be genetic variation in the contribution of Nox4 to the regulation of plasma TMAO and liver triglyceride content. In summary, we show that liver transcriptomic analysis identified diet- or strain-specific pathways for metabolic traits in the Collaborative Cross (CC) founder strains.