Cell Type-Specific Decomposition of Gingival Tissue Transcriptomes

Genome-wide transcriptomic analyses in whole tissues reflect the aggregate gene expression in heterogeneous cell populations comprising resident and migratory cells, and they are unable to identify cell type-specific information. We used a computational method (population-specific expression analysis [PSEA]) to decompose gene expression in gingival tissues into cell type-specific signatures for 8 cell types (epithelial cells, fibroblasts, endothelial cells, neutrophils, monocytes/macrophages, plasma cells, T cells, and B cells). We used a gene expression data set generated using microarrays from 120 persons (310 tissue samples; 241 periodontitis affected and 69 healthy). Decomposition of the whole-tissue transcriptomes identified differentially expressed genes in each of the cell types, which mapped to biologically relevant pathways, including dysregulation of Th17 cell differentiation, AGE-RAGE signaling, and epithelial-mesenchymal transition in epithelial cells. We validated selected PSEA-predicted, differentially expressed genes in purified gingival epithelial cells and B cells from an unrelated cohort (n = 15 persons), each of whom contributed with 1 periodontitis-affected and 1 healthy gingival tissue sample. Differential expression of these genes by quantitative reverse transcription polymerase chain reaction corroborated the PSEA predictions and pointed to dysregulation of biologically important pathways in periodontitis. Collectively, our results demonstrate the robustness of the PSEA in the decomposition of gingival tissue transcriptomes and its ability to identify differentially regulated transcripts in particular cellular constituents. These genes may serve as candidates for further investigation with respect to their roles in the pathogenesis of periodontitis.

Genomewide Study of Salivary MicroRNAs for Detection of Oral Cancer

MicroRNAs (miRNAs) in human saliva have recently demonstrated to be potential biomarkers for diagnosis purposes. However, lack of well-characterized/matched clinical groups and lack of suitable endogenous control (EC) for salivary extracellular miRNA detection and normalization are among the restrictions of applying salivary-based miRNA biomarker discovery. In the present study, we examined the differential expression pattern of miRNAs among 4 groups of subjects-including patients with oral squamous cell carcinoma (OSCC), patients with OSCC in remission (OSCC-R), patients with oral lichen planus, and healthy controls (HCs)-using a genomewide high-throughput miRNA microarray. First, we systematically screened 10 pooling samples and 34 individual samples of different groups to find a proper EC miRNA. We then investigated the genomewide expression patterns of differentially expressed miRNAs in saliva of different groups using NanoString nCounter miRNA expression assay and real-time quantitative polymerase chain reaction, followed by construction of receiver operating characteristic curves to determine the sensitivity and specificity of the assay. We identified miRNA-191 as a suitable EC miRNA with minimal intergroup and intragroup variability, and we used it for normalization. Of more than 700 miRNAs tested, 13 were identified as being significantly deregulated in saliva of OSCC patients compared to HCs: 11 miRNAs were underexpressed (miRNA-136, miRNA-147, miRNA-1250, miRNA-148a, miRNA-632, miRNA-646, miRNA668, miRNA-877, miRNA-503, miRNA-220a, miRNA-323-5p), and 2 miRNAs were overexpressed (miRNA-24, miRNA-27b). MiRNA-136 was underexpressed in both OSCC vs. HCs and OSCC vs. OSCC-R. MiRNA-27b levels were significantly higher in OSCC patients compared to those found in HCs, patients with OSCC-R, and patients with oral lichen planus and served as a characteristic biomarker of OSCC. Receiver operating characteristic curve analyses showed that miRNA-27b could be a valuable biomarker for distinguishing OSCC patients from the other groups. Our novel findings established a reliable EC miRNA for salivary-based diagnostic and indicate that the salivary miRNA profiles are discriminatory in OSCC patients.

The interleukin-1 family gene polymorphisms and Graves' disease

Genetic factors, including cytokine gene polymorphisms, are potential contributors to the pathogenesis of the Graves' disease (GD). We attempted in this study to determine the association between GD and the following polymorphisms in the interleukin-1 (IL-1) family genes: IL-1alpha (-889C/T), IL-1ss (-511C/T), IL-1ss (+3962C/T), IL-1R (Pst-1 1970C/T) and IL-1RA (Mspa-I 11100C/T). We studied 107 patients with an established diagnosis of GD and 140 healthy controls. Cytokine typing was performed by the polymerase chain reaction with sequence-specific primers assay. Genotype distributions among patients were in Hardy-Weinberg equilibrium for all polymorphisms. The frequency of the IL-1alpha -889T allele was significantly higher in patients than in controls (51.9% vs. 31.6%, OR=2.33, 95% CI=1.61-3.38; p<0.0001). The IL-1RA Msp-I 11100C allele was significantly more frequent in patients than in controls (50.0% vs. 22.9%, OR=3.38, 95% CI=2.29-4.97, p<0.0001). No significant associations were found for other polymorphisms. Although the IL-1 family has well-known roles in GD pathogenesis, the contributions of their genetic variations to the disease are unclear. In this study, we documented a highly significant association between GD and polymorphism in IL-1alpha and IL-1RA genes. Further studies in other populations are necessary to confirm our results.