Bioinformatic Prediction of Neuropathic Pain Signaling Pathways in Rheumatoid Arthritis after high throughput miRNA analysis

Abstract

microRNAs (miRNAs) are a special subgroup of RNAs which work to prevent the expression of genes at the post‐transcriptional level by “silencing” them. That is, gene expression is prevented. This ultimately affects the pathways that they are a part of and the products produced by these pathways. Due to the ability of miRNA to bind to any base pair complementary to its own thus inhibiting expression of the sequence it is bound to, they are often involved in multiple cellular pathways. The relation between a specific clinical outcome and an exact pathway that a miRNA is involved is hard to establish because of the sheer number of potential pathways one miRNA could be involved in. Bioinformatic predictions are useful because they allow us to identify the most probable pathway. That is, through the careful analysis of miRNA’s targets and the prediction of the targets’ interactions in biological mechanisms. In this project, we predicted the pathways related to deregulation of miR‐223‐3p and miR‐16‐5p. Both miRNAs were correlated with neuropathy‐related clinical measures (neuropathic pain (ID Pain) and the Toronto Clinical Neuropathy Score (TCNS) respectively (Pearson Coeff.ID Pain=0.556, p=0.014) and (Pearson Coeff.TCNS= −0.5, p=0.02)). To predict possible neuropathic pain signalling pathways in people afflicted with rheumatoid arthritis, we used the miRDB database. We identified 1,485 targets and selected targets with scores of 60+ to carry out a gene ontology analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Conducted through DAVID Software from the Laboratory of Human Retrovirology and Immunoinformatics, KEGG identified 72 pathways as the most likely affected by deregulation of miR‐223‐3p and miR‐16‐5p. Several pathways on this list including the FoxO, neurotrophin and sphingolipid signalling pathways are related to pain and neuropathic outcomes. Future studies will have to determine whether both miRNAs affect these pathways directly and in relationship to RA.Support or Funding InformationSupport for student stipends, supplies, and/or equipment used in this research was supplied by the Program for Research Initiatives in Science and Math (PRISM) at John Jay College. PRISM is funded by the Title V program within the U.S. Department of Education; the PAESMEM program through the National Science Foundation; and New York State’s Graduate Research and Technology Initiative and NYS Education Department CSTEP program.