BackgroundObesity is frequently complicated by comorbid conditions, yet how excess adipose contributes is poorly understood. Although adipocytes in obese individuals induce systemic inflammation via secreted cytokines, another potential mediator has recently been identified (i.e. adipocyte-derived exosomes). We hypothesized that adipocyte-derived exosomes contain mediators capable of activating end-organ inflammatory and fibrotic signaling pathways.MethodsWe developed techniques to quantify and characterize exosomes shed by adipocytes from 7 obese (age: 12–17.5 years, BMI: 33–50 kg/m2) and 5 lean (age: 11–19 years, BMI: 22–25 kg/m2) subjects.ResultsAbundant exosomal miRNAs, but no mRNAs, were detected. Comparison of obese vs. lean visceral adipose donors detected 55 differentially-expressed miRNAs (p<0.05; fold change≥|1.2|). qRT-PCR confirmed downregulation of miR-148b (ratio = 0.2 [95% confidence interval = 0.1, 0.6]) and miR-4269 (0.3 [0.1, 0.8]), and upregulation of miR-23b (6.2 [2.2, 17.8]) and miR-4429 (3.8 [1.1 to 13.4]). Pathways analysis identified TGF-β signaling and Wnt/ β-catenin signaling among the top canonical pathways expected to be altered with visceral adiposity based on projected mRNA targets for the 55 differentially expressed miRNAs. A select mRNA target was validated in vitro.ConclusionThese data show that visceral adipocytes shed exosomal-mediators predicted to regulate key end-organ inflammatory and fibrotic signaling pathways.

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BackgroundEpigenetic changes in visceral adipose tissue (VAT) with obesity and their effects on gene expression are poorly understood, especially during emergent obesity in youth. The current study tested the hypothesis that methylation and gene expression profiles of key growth factor and inflammatory pathways are altered in VAT from obese compared to non-obese youth.MethodsVAT samples from adolescent females grouped as Lean (L; n = 15; age = 15 ± 3 years, BMI = 21.9 ± 3.0 kg/m2) or Obese (Ob; n = 15, age = 16 ± 2 years, BMI = 45.8 ± 9.8 kg/m2) were collected. Global methylation (n = 20) and gene expression (N = 30) patterns were profiled via microarray and interrogated for differences between groups by ANCOVA (p < 0.05), followed by biological pathway analyses.ResultsOverlapping differences in methylation and gene expression in 317 genes were found in VAT from obese compared to lean groups. PI3K/AKT Signaling (p = 1.83 × 10−6; 11/121 molecules in dataset/pathway) was significantly overrepresented in Ob VAT according to pathway analysis. Upregulations in the PI3K/AKT signaling pathway mRNAs TFAM (p = 0.03; fold change = 1.8) and PPP2R5C (p = 0.03, FC = 2.6) were confirmed via qRT-PCR.ConclusionOur analyses show obesity-related differences in DNA methylation and gene expression in visceral adipose tissue of adolescent females. Specifically, we identified methylation site/gene expression pairs differentially regulated and mapped these differences to pathways including PI3K/AKT signaling, suggesting that PI3K/AKT signaling pathway dysfunction in obesity may be driven in part by changes in DNA methylation.

Background: Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5x human stool samples and 2x mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. Results: A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. Conclusion: This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.