A Network Biology Approach to Understanding the Tissue-Specific Roles of Non-Coding RNAs in Arthritis - Ali, Shabana Amanda; Pastrello, Chiara; Kaur, Navdeep; Peffers, Mandy J.; Ormseth, Michelle J.; Jurisica, Igor (Frontiers in Endocrinology, 2021)
Discovery of noncoding RNAs continues to provide new insights into some of the key molecular drivers of musculoskeletal diseases. Among these, microRNAs have received widespread attention for their roles in osteoarthritis and rheumatoid arthritis. With evidence to suggest that long noncoding RNAs and circular RNAs function as competing endogenous RNAs to sponge microRNAs, the net effect on gene expression in specific disease contexts can be elusive. Studies to date have focused on elucidating individual long noncoding-microRNA-gene target axes and circular RNA-microRNA-gene target axes, with a paucity of data integrating experimentally validated effects of noncoding RNAs. To address this gap, we curated recent studies reporting noncoding RNA axes in chondrocytes from human osteoarthritis and in fibroblast-like synoviocytes from human rheumatoid arthritis. Using an integrative computational biology approach, we then combined the findings into cell- and disease-specific networks for in-depth interpretation. We highlight some challenges to data integration, including non-existent naming conventions and out-of-date databases for noncoding RNAs, and some successes exemplified by the International Molecular Exchange Consortium for protein interactions. In this perspective article, we suggest that data integration is a useful in silico approach for creating noncoding RNA networks in arthritis and prioritizing interactions for further in vitro and in vivo experimentation in translational research.