title: Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.
abstract: Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD.
authors.affiliation: Center for Public Health Genomics, Department of Medicine, Division of Cardiology and Biochemistry and Molecular Biology, University of Virginia, Charlottesville, VA 22908, USA. crf2s@virginia.edu
authors.forename: Charles R
authors.initials: CR
authors.lastname: Farber
mesh_terms: D000328:Adult; D015519:Bone Density / Q000235:genetics*; D016000:Cluster Analysis; D005260:Female; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks / Q000235:genetics*; D055106:Genome-Wide Association Study; D006801:Humans; D009000:Monocytes / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D014158:Transcription, Genetic