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Comorbidity Network Analyses of Global Rheumatoid Arthritis and Type 2 Diabetes Reveal IL2 & IL6 as Common Role Players

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 12108))

Abstract

Comorbidities are associated with harder clinical management, worse health outcomes and an overall increase in healthcare expenditure. Here, we present a novel method of finding the common key genes and pathways via comorbidity network analyses. Essentially, we deployed data from the RAvariome database and Type 2 Diabetes Knowledge Portal for mutually exclusive interpopulation RA and T2D susceptibility genes, respectively. Protein interactomes (PIN) are built by mapping direct interactions between the above gene products and their interacting partners, along with a comorbid network combining both RA and T2D PIN. Network centrality analyses of all PIN projected 18 overlapping proteins with IL-6 and IL-2 being the common key role players found in the comorbid PIN, despite being exclusive to our curated RA susceptible gene list. Subsequent pathway analyses revealed the involvement of cellular senescence, MAPK and AGE-RAGE signalling in diabetic complications. We conclude that RA and T2D susceptible genes do not necessarily translate into indispensable proteins in their induced individual or comorbid diseased networks, but those of RA can outcompete T2D susceptible genes despite the much larger T2D component in the comorbid network. Our method is a unique approach to find key genes/proteins and implicated pathways in disease comorbidities.

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Contributions

RM constructed the interactome and compiled the implicated proteins and pathways. LTO wrote the manuscript and corrected the analysis. CL checked and corrected the manuscript and headed the project. The authors declare no conflicts of interest.

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Correspondence to Chandrajit Lahiri .

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Liew, T.O., Mishra, R., Lahiri, C. (2020). Comorbidity Network Analyses of Global Rheumatoid Arthritis and Type 2 Diabetes Reveal IL2 & IL6 as Common Role Players. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham. https://doi.org/10.1007/978-3-030-45385-5_21

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  • DOI: https://doi.org/10.1007/978-3-030-45385-5_21

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