Mick Correll

RATIONALE: Idiopathic pulmonary fibrosis (IPF) is an untreatable and often fatal lung disease that is increasing in prevalence and is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control gene expression and are likely to regulate the IPF transcriptome. OBJECTIVES: To identify methylation marks that modify gene expression in IPF lung. METHODS: We assessed DNA methylation (comprehensive high-throughput arrays for relative methylation arrays [CHARM]) and gene expression (Agilent gene expression arrays) in 94 patients with IPF and 67 control subjects, and performed integrative genomic analyses to define methylation-gene expression relationships in IPF lung. We validated methylation changes by a targeted analysis (Epityper), and performed functional validation of one of the genes identified by our analysis. MEASUREMENTS AND MAIN RESULTS: We identified 2,130 differentially methylated regions (DMRs; <5% false discovery rate), of which 738 are associated with significant changes in gene expression and enriched for expected inverse relationship between methylation and expression (P < 2.2 × 10(-16)). We validated 13/15 DMRs by targeted analysis of methylation. Methylation-expression quantitative trait loci (methyl-eQTL) identified methylation marks that control cis and trans gene expression, with an enrichment for cis relationships (P < 2.2 × 10(-16)). We found five trans methyl-eQTLs where a methylation change at a single DMR is associated with transcriptional changes in a substantial number of genes; four of these DMRs are near transcription factors (castor zinc finger 1 [CASZ1], FOXC1, MXD4, and ZDHHC4). We studied the in vitro effects of change in CASZ1 expression and validated its role in regulation of target genes in the methyl-eQTL. CONCLUSIONS: These results suggest that DNA methylation may be involved in the pathogenesis of IPF.

BACKGROUND: Oral pathology is a commonly reported extraintestinal manifestation of Crohn's disease (CD). The host-microbe interaction has been implicated in the pathogenesis of inflammatory bowel disease (IBD) in genetically susceptible hosts, yet limited information exists about oral microbes in IBD. We hypothesize that the microbiology of the oral cavity may differ in patients with IBD. Our laboratory has developed a 16S rRNA-based technique known as the Human Oral Microbe Identification Microarray (HOMIM) to study the oral microbiome of children and young adults with IBD. METHODS: Tongue and buccal mucosal brushings from healthy controls, CD, and ulcerative colitis (UC) patients were analyzed using HOMIM. Shannon Diversity Index (SDI) and Principal Component Analysis (PCA) were employed to compare population and phylum-level changes among our study groups. RESULTS: In all, 114 unique subjects from the Children's Hospital Boston were enrolled. Tongue samples from patients with CD showed a significant decrease in overall microbial diversity as compared with the same location in healthy controls (P = 0.015) with significant changes seen in Fusobacteria (P < 0.0002) and Firmicutes (P = 0.022). Tongue samples from patients with UC did not show a significant change in overall microbial diversity as compared with healthy controls (P = 0.418). CONCLUSIONS: As detected by HOMIM, we found a significant decrease in overall diversity in the oral microbiome of pediatric CD. Considering the proposed microbe-host interaction in IBD, the ease of visualization and direct oral mucosal sampling of the oral cavity, further study of the oral microbiome in IBD is of potential diagnostic and prognostic value.

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a 'basket' feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org.