Integrative Analysis Of Genomics And Transcriptome Data To Identify Potential Functional Genes And Causal Variants Of BMDs In Females

BackgroundOsteoporosis is a common chronic disease characterized by a decrease in bone mass and compromised bone strength,resulting inthe consequent increased risk in fragility and susceptibility to fractures.Osteoporosis has become a serious public health problem,especially in the middle-aged and older women.Because of the difficulty in measuring bone strength,the diagnostic standard for osteoporosis is bone mineral density(BMD).The heritability of BMD variation ranges from 0.5 to 0.85.However,Genomic studies,including all the GWAS studies(Genome-wide association studies),only explain less than 6%of the risk for osteoporosis.A number of studies have suggested that the missing heritability may be the result of other genomic mechanisms,such as gene-gene interactions.However,two-locus interactions explain only a minority of missing heritability.Network-assisted analysis through gene-gene interactions,an emerging approach,improves disease gene detection power and provides new insights for the missing heritability of diseases.In addition,integrative analysis of genomics and transcriptome data can make up for the inadequacy of genomics studies because it can provide functional information of the associated genes of disease.Further,we performed a statistical approach to fine mapping for the identification of causal variants for BMD.Using this fine mapping approach,we will gain a better understanding of the mechanism of the genetic variants contributing to BMD.Our present work also provided novel therapeutic clues for the treatment of osteoporosis.Objective(1)To identify genes and modules which are associated with BMD in females.(2)To investigative the functional implications of the identified genes and modules on the regulation of BMD.(3)To identify causal variants for BMD,we performed a statistical approach to fine mapping of the potential functional genes.Material and MethodsThe GWAS dataset used in the study was the largest dataset for BMD in the field.The gene expression dataset used in the study was also the largest dataset for BMD all over the world.To identify novel heritability for osteoporosis,we performed a network-assisted analysis using WGCNA(Weighted Gene Co-expression Network Analysis).In addition,We performed GO and pathway enrichment analysis for the genes in the significant module by using DAVID(Database for Annotation Visualization and Integrated Discovery).ES(Enrichment Score)?3.0 is considered the threshold for nominal significance in enrichment analyses.Finally,we summarized these results and explained the functional implications of the identified genes and modules on the regulation of BMD.ResultsIn the first step,we obtained the genome-wide adjusted P-value of genes by using ProxyGeneLD.By combining the two gene lists(gene list for GWAS data and gene list for transcriptome data)and excluding non-and lowly expressed genes,we identified probes representing 1574 GWAS nominally significant genes and applied the WGCNA package to compile the network.These 1574 genes were divided into 12 modules.Out of the 12 modules,significant correlation relationship was present in the yellow module(P-value<0.05).Thus,we obtained a module(the yellow module)associated with BMD.Further,we performed gene annotation and gene enrichment analysis.Significant enrichments were observed for GO term contractile fiber part(ES = 3.57,FDR = 0.06),which implies a close connection between muscle and bone.Conclusion(1)In summary,our study demonstrated the effectiveness of using integrative analysis of GWAS data jointly with gene expression data.The findings highlighted a module as well as genes playing important roles in the regulation of bone mass in females,affording novel insights into the genetic basis of osteoporosis,which may provide several clues for the functional implications of the identified genes of osteoporosis in females.(2)Our present work performed a statistical approach to fine mapping of the potential functional genes associated with BMD,which identified several causal variants of BMD.Further,our results also provided novel clues for the functional mechanistic experiments in osteoporosis studies.