Paget’s disease of bone (PDB) is the second most prevalent metabolic bone disorder worldwide, with a prevalence rate of 1.5%–8.3%. It is characterized by localized areas of accelerated, disorganized, and excessive bone production and turnover. Typically, PDB develops in the later stages of life, particularly in the late 50s, and affects men more frequently than women. PDB is a complex disease influenced by both genetic and environmental factors. PDB has a complex genetic basis involving multiple genes, with SQSTM1 being the gene most frequently associated with its development. Mutations affecting the UBA domain of SQSTM1 have been detected in both familial and sporadic PDB cases, and these mutations are often associated with severe clinical expression. Germline mutations in other genes such as TNFRSF11A, ZNF687 and PFN1, have also been associated with the development of the disease. Genetic association studies have also uncovered several PDB predisposing risk genes contributing to the disease pathology and severity. Epigenetic modifications of genes involved in bone remodelling and regulation, including RANKL, OPG, HDAC2, DNMT1, and SQSTM1, have been implicated in the development and progression of Paget’s disease of bone, providing insight into the molecular basis of the disease and potential targets for therapeutic intervention. Although PDB has a tendency to cluster within families, the variable severity of the disease across family members, coupled with decreasing incidence rates, indicates that environmental factors may also play a role in the pathophysiology of PDB. The precise nature of these environmental triggers and how they interact with genetic determinants remain poorly understood. Fortunately, majority of PDB patients can achieve long-term remission with an intravenous infusion of aminobisphosphonates, such as zoledronic acid. In this review, we discuss aspects like clinical characteristics, genetic foundation, and latest updates in PDB research.

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Background Myocardial infarction (MI) is the most prevalent coronary atherosclerotic heart disease caused by the complex molecular interactions between multiple genes and environment. Molecular exploration of gene expression changes in MI patients is very crucial not just to understand the molecular basis of disease development but also to identify potential therapeutic targets. Therefore, we aim to identify potential biomarkers for the disease development mechanisms and for prognosis of MI using extensive integrated biological network analysis. Methodology Gene expression datasets (GSE66360) generated from 51 healthy controls and 49 endothelial cell samples from patients experiencing acute MI were used to analyze the differentially expressed genes (DEG), protein-protein interactions (PPI), gene network-clusters to annotate the candidate pathways relevant to MI pathogenesis. Results Bioinformatic analysis revealed 810 DEGs, between control and MI samples, with 574 up- and 236 down- regulated genes. Their functional annotations with Gene Ontology (GO) has captured several MI targeting biological processes like immune response, inflammation and platelets degranulation. Most significantly DEGs enriched KEGG pathways are related to the following functions: Cytokine-cytokine receptor interaction, TNF and NFkB signaling. By constructing the PPI network using STRING and CytoHubba, seventeen hub and bottleneck genes were found, whose involvement in MI was further confirmed by DisGeNET data. Search in the Open Target Platform reveal unique bottleneck genes as potential target for MI. Conclusion Our integrative bioinformatics analysis of large-scale gene expression data has identified several potential genetic biomarkers associated with early stage MI providing a new insight into molecular mechanism underlying the disease.