Epigenome-wide association study identifies Vogt-Koyanagi-Harada disease-associated DNA methylation loci in Chinese.

DNA methylation is one of the important epigenetic mechanisms for modulating gene expression. By performing a genome-wide methylation association analysis of whole peripheral blood from 60 Vogt-Koyanagi-Harada disease (VKH) patients and 60 healthy controls, we depicted the global DNA methylation status of VKH disease. Further pyrosequencing validation in 160 patients and 159 controls identified 3 aberrant CpG sites in HLA gene regions including cg04026937 and cg18052547 (located in HLA-DRB1 region), and cg13778567 (HLA-DQA1).

Integrated multi-omics profiling of nonfunctioning pituitary adenomas.

Purpose: Genetic and epigenetic alterations are involved in pituitary adenoma pathogenesis, however the molecular basis of proliferative nonfunctioning pituitary adenomas (NFPAs) remains unclear. Here, we analyzed integrated multi-omics profiling including copy number variation (CNV), DNA methylation and gene expression of 8 NFPAs.

Methods: We collected 4 highly proliferative (hpNFPA, Ki-67 ≥ 3) and 4 lowly proliferative (Ki-67 ≤ 1) NFPAs, and comprehensively assessed CNV, DNA methylation, and gene expression by Illumina HumanMethylation450 BeadChip and Affymetrix GeneChip PrimeView Human Gene Expression Array.

Gut metagenomics-derived genes as potential biomarkers of Parkinson's disease.

Identification of the gut microbiome compositions associated with disease has become a research focus worldwide. Emerging evidence has revealed the presence of gut microbiota dysbiosis in Parkinson's disease. In this study, we aimed to identify the gut microbiome associated with Parkinson's disease and subsequently to screen and to validate potential diagnostic biomarkers of Parkinson's disease.

CoreProbe: A Novel Algorithm for Estimating Relative Abundance Based on Metagenomic Reads.

With the rapid development of high-throughput sequencing technology, the analysis of metagenomic sequencing data and the accurate and efficient estimation of relative microbial abundance have become important ways to explore the microbial composition and function of microbes. In addition, the accuracy and efficiency of the relative microbial abundance estimation are closely related to the algorithm and the selection of the reference sequence for sequence alignment. We introduced the microbial core genome as the reference sequence for potential microbes in a metagenomic sample, and we constructed a finite mixture and latent Dirichlet models and used the Gibbs sampling algorithm to estimate the relative abundance of microorganisms.

Integrated metagenomic data analysis demonstrates that a loss of diversity in oral microbiota is associated with periodontitis.

Background: Periodontitis is an inflammatory disease affecting the tissues supporting teeth (periodontium). Integrative analysis of metagenomic samples from multiple periodontitis studies is a powerful way to examine microbiota diversity and interactions within host oral cavity.

Methods: A total of 43 subjects were recruited to participate in two previous studies profiling the microbial community of human subgingival plaque samples using shotgun metagenomic sequencing.