Analysis of the microRNA Profile of Coal-Burning Endemic Fluorosis Using Deep Sequencing and Bioinformatic Approaches.

MicroRNAs (miRNAs) differentially expressed in plasma were identified using microRNA sequencing (miRNA-seq), and five miRNAs were selected for validation. Potential target genes of these five miRNAs were predicted using the miRWalk3.0 database, and the overlapping portions were analyzed using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Comparison of the cases and controls revealed 127 known differentially expressed miRNAs. A total of 44 and 83 miRNAs were upregulated and downregulated, respectively. Through target gene prediction of five miRNAs, we obtained 1360 target genes. GO enrichment analysis showed that the target genes of these dysregulated miRNAs were related with secretion, protein binding, and cell growth. The KEGG pathway analysis showed that pathways in cancer, calcium signaling, and rat sarcoma (Ras) signaling, etc. were likely regulated by these five miRNAs. These findings highlight the distinct expression patterns of miRNAs in coal-burning endemic fluorosis.