title: Detection of significant pathways in osteoporosis based on graph clustering.
abstract: Osteoporosis is the most common and serious skeletal disorder among the             elderly, characterized by a low bone mineral density (BMD). Low bone mass in the             elderly is highly dependent on their peak bone mass (PBM) as young adults. Circulating             monocytes serve as early progenitors of osteoclasts and produce significant molecules             for bone metabolism. An improved understanding of the biology and genetics of             osteoclast differentiation at the pathway level is likely to be beneficial for             the development of novel targeted approaches for osteoporosis. The objective of             this study was to explore gene expression profiles comprehensively by grouping             individual differentially expressed genes (DEGs) into gene sets and pathways using             the graph clustering approach and Gene Ontology (GO) term enrichment analysis.             The results indicated that the DEGs between high and low PBM samples were grouped             into nine gene sets. The genes in clusters 1 and 8 (including GBP1, STAT1, CXCL10             and EIF2AK2) may be associated with osteoclast differentiation by the immune system             response. The genes in clusters 2, 7 and 9 (including SOCS3, SOD2, ATF3, ADM EGR2             and BCL2A1) may be associated with osteoclast differentiation by responses to             various stimuli. This study provides a number of candidate genes that warrant             further investigation, including DDX60, HERC5, RSAD2, SIGLEC1, CMPK2, MX1, SEPING1,             EPSTI1, C9orf72, PHLDA2, PFKFB3, PLEKHG2, ANKRD28, IL1RN and RNF19B.
authors.affiliation: Department of Orthopedics, Fengxian Central Hospital, Shanghai                     201400, P.R. China.
authors.forename: Haijun
authors.initials: H
authors.lastname: Xiao
authors.forename: Liancheng
authors.initials: L
authors.lastname: Shan
authors.forename: Haiming
authors.initials: H
authors.lastname: Zhu
authors.forename: Feng
authors.initials: F
authors.lastname: Xue
mesh_terms: D015519:Bone Density; D016000:Cluster Analysis; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D009000:Monocytes / Q000166:cytology / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis; D010024:Osteoporosis / Q000235:genetics* / Q000378:metabolism / Q000473:pathology