The Common and Unique Pattern of Microbiome Profiles among Saliva, Tissue, and Stool Samples in Patients with Crohn's Disease.

This study aimed to elucidate common and unique microbiome patterns in saliva, intestinal tissue biopsy, and stool samples from patients with Crohn's disease (CD). Saliva, tissue, and stool samples from patients with CD were prospectively collected. Quantitative and phylogenetic analyses of 16s rRNA sequencing data were performed with bioinformatical pipelines. A total of 30 patients were enrolled in this study. The composition of major microbial taxa was similar between tissue and stool samples. A total of 11 of the 20 most abundant microbiota were found in both samples. The microbial community in saliva was significantly distinct from that in tissue and stool. The major species of microbiota and their composition also differed significantly from those of tissue and stool samples. However, Streptococcus and Prevotella are common genera in saliva, tissue, and stool microbiome. The abundance of Streptococcus, Pantoea, and Actinomyces from the saliva sample group were significantly different, varying with the location of the inflammation. Saliva has a distinct microbial community compared with tissues and stools in patients with CD. Prevotella and Streptococcus, which are commonly observed in saliva, stool, and tissue, can be considered a potential biomarker related to the diagnosis or prognosis of CD.

Hepatic MIR20B promotes nonalcoholic fatty liver disease by suppressing PPARA.

Background: Non-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation and imbalances in lipid metabolism in the liver. Although nuclear receptors (NRs) play a crucial role in hepatic lipid metabolism, the underlying mechanisms of NR regulation in NAFLD remain largely unclear. Methods: Using network analysis and RNA-seq to determine the correlation between NRs and microRNA in human NAFLD patients, we revealed that MIR20B specifically targets PPARA. MIR20B mimic and anti-MIR20B were administered to human HepG2 and Huh-7 cells and mouse primary hepatocytes as well as high-fat diet (HFD)- or methionine-deficient diet (MCD)-fed mice to verify the specific function of MIR20B in NAFLD. We tested the inhibition of the therapeutic effect of a PPARα agonist, fenofibrate, by Mir20b and the synergic effect of combination of fenofibrate with anti-Mir20b in NAFLD mouse model. Results: We revealed that MIR20B specifically targets PPARA through miRNA regulatory network analysis of nuclear receptor genes in NAFLD. The expression of MIR20B was upregulated in free fatty acid (FA)-treated hepatocytes and the livers of both obesity-induced mice and NAFLD patients. Overexpression of MIR20B significantly increased hepatic lipid accumulation and triglyceride levels. Furthermore, MIR20B significantly reduced FA oxidation and mitochondrial biogenesis by targeting PPARA. In Mir20b-introduced mice, the effect of fenofibrate to ameliorate hepatic steatosis was significantly suppressed. Finally, inhibition of Mir20b significantly increased FA oxidation and uptake, resulting in improved insulin sensitivity and a decrease in NAFLD progression. Moreover, combination of fenofibrate and anti-Mir20b exhibited the synergic effect on improvement of NAFLD in MCD-fed mice. Conclusions: Taken together, our results demonstrate that the novel MIR20B targets PPARA, plays a significant role in hepatic lipid metabolism, and present an opportunity for the development of novel therapeutics for NAFLD. Funding: This research was funded by Korea Mouse Phenotyping Project (2016M3A9D5A01952411), the National Research Foundation of Korea (NRF) grant funded by the Korea government (2020R1F1A1061267, 2018R1A5A1024340, NRF-2021R1I1A2041463, 2020R1I1A1A01074940, 2016M3C9A394589324), and the Future-leading Project Research Fund (1.210034.01) of UNIST.

Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2.

Pathway-based analysis in genome-wide association study (GWAS) is being widely used to uncover novel multi-genic functional associations. Many of these pathway-based methods have been used to test the enrichment of the associated genes in the pathways, but exhibited low powers and were highly affected by free parameters. We present the novel method and software GSA-SNP2 for pathway enrichment analysis of GWAS P-value data. GSA-SNP2 provides high power, decent type I error control and fast computation by incorporating the random set model and SNP-count adjusted gene score. In a comparative study using simulated and real GWAS data, GSA-SNP2 exhibited high power and best prioritized gold standard positive pathways compared with six existing enrichment-based methods and two self-contained methods (alternative pathway analysis approach). Based on these results, the difference between pathway analysis approaches was investigated and the effects of the gene correlation structures on the pathway enrichment analysis were also discussed. In addition, GSA-SNP2 is able to visualize protein interaction networks within and across the significant pathways so that the user can prioritize the core subnetworks for further studies. GSA-SNP2 is freely available at https://sourceforge.net/projects/gsasnp2.