Abstract
Developing type 2 diabetes (T2D) can increase patient risk of developing other common diseases and exacerbate their severity, including diseases that affect bone and joints. Such comorbidity interactions are hard to study in detail by traditional endocrinological methods. Thus, we developed tissue transcript analytical approaches to identify common pathways through which these diseases can interact. We examined RNAseq and microarray transcript datasets from studies of T2D and chronic bone and joint diseases, namely rheumatoid arthritis (RA), osteoarthritis (OA), juvenile idiopathic arthritis (JIA) and low peak bone density, a key osteoporosis (OP) determinant. These datasets contained data from affected individuals and matched controls. Differentially expressed genes (DEGs) for each condition were compared with T2D DEG. Overlapping DEGs (i.e., those common to T2D and a bone or joint condition) were subjected to gene enrichment by pathway analyses and by gene ontology methods, and the results were evaluated by using SNP-disease linkage (dbGaP) and gene-disease association (OMIM) databases that indicate gene involvement in pathologies. By examining gene targets of transcription factors (TFs) and microRNA (miRNAs), we also constructed DEG-TF and DEG-miRNA interactions networks for analysis. We identified strong candidate genes in common pathways, notably including SYK, UCP3, ROR1, PPARG, BUB1, AKT2, ADCY2 and CCR5. The DEG-TF network and DEG-miRNA interactions network analyses revealed a number of TFs (GATA2, FOXC1, USF2, YY1, E2F1, JUN, RELA, CREB1, TFAP2A, NFB1) and miRNAs (mir-335-5p, mir-16-5p, mir-26b-5p, mir-124-3p, mir-218-5p, mir-98-5p, mir-29b-3p, mir-3135b, mir-29c-3p, mir-1-1) that can regulate the identified DEGs at the transcriptional and post-transcriptional levels. Thus this data-driven approach has enabled identification and validation of regulatory factors and cell pathways by which T2D may influence bone and joint conditions, which may suggest new ways to interfere with the pathogenic processes involved.
Highlights
Type 2 diabetes (T2D) affects hundreds of millions of people and has become an enormous clinical problem with seriousThe associate editor coordinating the review of this manuscript and approving it for publication was Derek Abbott .attendant vascular disease issues, including heart disease, strokes, retinopathy and peripheral ischemia
Differentially expressed genes (DEGs) were defined as genes with false discovery rate (FDR) under 0.05 and more than log 2-fold increase or decrease in gene expression The numbers of unfiltered DEG that were identified were, respectively, 1290 for T2D, 393 for OP, 2013 for OA, 833 for rheumatoid arthritis (RA) and 1003 for the juvenile idiopathic arthritis (JIA) datasets
To identify statistically significant associations between T2D and the other conditions, we constructed an up- and down-regulation diseasome relationship network that was centerd on T2D where two diseases are comorbid when one or more DEGs associated with both diseases are found. 2 particular significant genes, PLAU and GJA1, are commonly up-regulated in T2D, OA and JIA, while 2 significant genes (BIRC3 and MX1, respectively an anti-apoptosis factor and a poorly understood interferon induced gene) are commonly up-regulated in T2D, FIGURE 2
Summary
Type 2 diabetes (T2D) affects hundreds of millions of people and has become an enormous clinical problem with seriousThe associate editor coordinating the review of this manuscript and approving it for publication was Derek Abbott .attendant vascular disease issues, including heart disease, strokes, retinopathy and peripheral ischemia. The high incidence of T2D and its tendency to affect the function of many organs makes it important to determine how T2D interacts with co-morbidities, i.e., other diseases suffered by the same individual at the same time [1]. In addition there are the local cellular effects of insulin resistance itself These affect diseases of bone and joints, the commonest of which include osteoporosis, osteoarthritis and inflammatory types of arthritis such as rheumatoid arthritis (RA) [3]. This approach may identify important pathways that are relevant to a range of other diseases
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
