Bioinformatics approach to identify the impacts of microgravity on the development of bone and joint diseases

• Published in: Informatics in medicine unlocked 2023, Vol.38, p.101211, Article 101211
• Main Authors: Akhtar, Mst Rashida, Mondal, Md Nazrul Islam, Rana, Humayan Kabir
• Format: Article
• Language: English
• Subjects: Microgravity; Osteoarthritis; Osteomalacia and osteosarcoma; Osteoporosis
• ISSN: 2352-9148; 2352-9148
• DOI: 10.1016/j.imu.2023.101211

Experiencing long-term weightlessness during prolonged spaceflight in microgravity environments causes enormous changes in human physiology. Past space missions have revealed that low gravity in space is a serious threat to the development of several human diseases, especially bone and joint diseases (BJDs), which have been identified as the major obstacle to long-term space missions. Hence, before sending humans to Mars or long duration spaceflight, it is truly essential to investigate the association of microgravity (MG) on the development of BJDs, however, these are not clearly understood. To investigate this problem, we developed a computational model to detect the changes in gene expression as potential impacts of MG exposure that may influence the progression of BJDs. We explored gene expression microarray data from tissues affected by MG and BJDs, including Osteoporosis (OP), Osteoarithritis (OA), Osteomalacia (OM), and Osteosarcoma (OS). We constructed gene-disease association networks, identified significant signaling and ontological pathways, and clustered the protein-protein interactions (PPIs) network using neighborhood-based benchmarking and multilayer network topology. We checked the validity of our study using receiver operating characteristic (ROC) and gold benchmark databases, including OMIM, dbGaP, and DisGeNET. We observed that MG exposure altered the expression of many genes, and these genes are also expressed differentially in OP, OA, OM, and OS (21, 19, 19, and 21 respectively). We found five significant biomarker hub proteins (EGFR, CCNB2, Skp2, VDR and SMAD3) from PPIs analysis by evaluating the degree of centrality. The ROC analysis showed an area under the curve (AUC) of 0.844 where the higher value of AUC indicates the result is more significant. Hence, these gene-disease association networks, signaling and ontological pathways, PPIs network of the altered genes and the ROC curve of the findings imply that MG may have significant impacts on the development of BJDs. This computational model-based investigation identified a strong cohesion between MG and BJDs that ensures the credible presence of a group of genes and gene products in BJDs. The outcome of this study would be useful in lab-based research to develop potential therapeutic targets for the treatment of long-term MG exposure.