The Database Of Risk Factors & Molecular Mechanism Researches Of Osteoporosis

Osteoporosis(OP)is a chronic complex disease,mainly happened in the elderly.Osteoporosis seriously affects the quality of life(QOL)of patients and brings heavy burden to their family and society.Therefore,it is crucial to find out and analyze the potential risk factors,and to explore the pathogenesis of osteoporosis.The content of this study is divided into two aspects:In the first part,we constructed an integrated database of risk factors for osteoporosis,formed as OPAR-base.Through screening 1772 articles from PubMed,we found detailed information about 441 risk factors from the elected 370 original documents.Our data include the risk factors,protective factors and impact factors,which were divided into three categories,i.e.genetic factors,epidemiological factors and environmental factors.In the second part of the thesis,we investigated the underlying molecular mechanism of osteoporosis from the perspective of system biology.We analyzed the osteoporosis-associated microarray data from different sources,and performed gene differential expression analysis,pathway enrichment analysis,WGCNA and GO biological function analysis on functional genes.Finally,we mapped the DEGs(Differentially expressed genes)to specific co-expression modules and removed the outlying nodes,to describe and analyze the pathology of osteoporosis process.For each data set,we obtained a OP specific submodule.In addition,we have verified the reliability of our study by using network topology analysis,GO enrichment analysis,TF enrichment analysis,etc.Results are as follows.Many significantly enriched transcription factors have been reported playing important roles in the process of osteoporosis,e.g.USP18,FOXG1,STAT6,TP53.What's more,relevant biological processes(BP)and molecular functions(MF)have been significantly enriched in our submodules,e.g.negative regulation of myeloid cell differentiation,aging,small GTPase mediated signal transduction.This study not only provides researchers with convenient query platform about risk factors of OP,but also makes up for the deficiency of gene differential expression analysis without considering the interaction between genes,and remedies the limitations of the traditional co-expression analysis which completely ignores non-DEGs.This study provides a solid data base as well as new methods and ideas for the prevention,diagnosis and treatment of osteoporosis,and has important clinical value.