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Osteoporosis is the most common and serious skeletal disorder among theelderly, characterized by a low bone mineral density (BMD). Low bone mass in theelderly is highly dependent on their peak bone mass (PBM) as young adults. Circulatingmonocytes serve as early progenitors of osteoclasts and produce significant moleculesfor bone metabolism. An improved understanding of the biology and genetics ofosteoclast differentiation at the pathway level is likely to be beneficial forthe development of novel targeted approaches for osteoporosis. The objective ofthis study was to explore gene expression profiles comprehensively by groupingindividual differentially expressed genes (DEGs) into gene sets and pathways usingthe graph clustering approach and Gene Ontology (GO) term enrichment analysis.The results indicated that the DEGs between high and low PBM samples were groupedinto nine gene sets. The genes in clusters 1 and 8 (including GBP1, STAT1, CXCL10and EIF2AK2) may be associated with osteoclast differentiation by the immune systemresponse. The genes in clusters 2, 7 and 9 (including SOCS3, SOD2, ATF3, ADM EGR2and BCL2A1) may be associated with osteoclast differentiation by responses tovarious stimuli. This study provides a number of candidate genes that warrantfurther investigation, including DDX60, HERC5, RSAD2, SIGLEC1, CMPK2, MX1, SEPING1,EPSTI1, C9orf72, PHLDA2, PFKFB3, PLEKHG2, ANKRD28, IL1RN and RNF19B.

Detection of significant pathways in osteoporosis based on graph clustering