Systems Genetics: A Novel Approach to Dissect the Genetic Basis of Osteoporosis

Farber, Charles R.

doi:10.1007/s11914-012-0112-5

Cited by 13 publications

(13 citation statements)

References 64 publications

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“…Also, novel transcripts, gene fusion, and alternative splicing may not be detected because of the dependence on commercial chips. To address these issues, transcriptome sequencing (RNA-seq) could be an attractive alternative [71]. …”

Section: Gene Expression Studiesmentioning

confidence: 99%

“…Most of the genetic variants or genomic regions that have so far been identified by GWASs of osteoporosis-related traits have been intronic or intergenic [71]. These variants or regions could be transcription factor binding sites that regulate or affect gene expression [71], but precisely how they might influence bone mass awaits further investigation.…”

Section: Implications For Pathogenesismentioning

confidence: 99%

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Genome-wide approaches for identifying genetic risk factors for osteoporosis

Liu

Zhang

et al. 2013

Genome Medicine

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Osteoporosis, the most common type of bone disease worldwide, is clinically characterized by low bone mineral density (BMD) and increased susceptibility to fracture. Multiple genetic and environmental factors and gene-environment interactions have been implicated in its pathogenesis. Osteoporosis has strong genetic determination, with the heritability of BMD estimated to be as high as 60%. More than 80 genes or genetic variants have been implicated in risk of osteoporosis by hypothesis-free genome-wide studies. However, these genes or genetic variants can only explain a small portion of BMD variation, suggesting that many other genes or genetic variants underlying osteoporosis risk await discovery. Here, we review recent progress in genome-wide studies of osteoporosis and discuss their implications for medicine and the major challenges in the field.

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Section: Gene Expression Studiesmentioning

confidence: 99%

Section: Implications For Pathogenesismentioning

confidence: 99%

Genome-wide approaches for identifying genetic risk factors for osteoporosis

Liu

Zhang

et al. 2013

Genome Medicine

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“…Linkage analysis [30][31][32] has been successful in identifying numerous quantitative trait loci involved in BMD regulation, but these findings have not been replicated between linkage studies and most of the genetic variables resulting from linkage signals remain to be identified. However, until now, identification of genes influencing osteoporosis by linkage analysis proved difficult with few successes [33], and positional cloning of genes underlying the associated trait loci appears intricate. Furthermore, meta-analysis of 11,842 subjects from nine linkage studies found no loci were associated with BMD [34].…”

Section: A Linkage Analysismentioning

confidence: 99%

“…GWAS is a powerful tool to investigate the genetic architecture of polygenic disorders arising from nucleotide polymorphisms and have been successful in identifying osteoporosis predisposition genes [29,48,49]. GWASs have recently identified nearly 100 independent associations for osteoporosis susceptibility traits [33]. GWAS has a major advantage over the CGAS by offering the possibility to identify novel susceptibility genes and pathways.…”

Section: Genome Wide Association Studies (Gwas)mentioning

confidence: 99%

Searching for the Molecular Pathways Regulating Bone Mineral Density in the Proteome and RNA Interference Era

Saad¹

2013

J Orth Rheumatol

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Osteoporosis is a polygenic disorder associated with low bone mineral density and deterioration of bone microarchitecture with increased chance of bone fractures. Although bone matrix mineralization and osteoporosis are closely related, the mineralization of bone matrix is almost a forgotten aspect in osteoporosis research. The complex processes of bone matrix mineralization and bone remodeling are tightly regulated by several transcription factors and signal transduction pathways. However, signal transduction pathways occurring at a protein level that depends not only on mRNA transcriptional regulation but also on a multitude of translational and posttranslational controls. Furthermore, proteomics allow a discerning view of complex molecular pathways, provides an efficient method to determine protein candidates, and elucidates signal transduction pathways that regulate bone mineral density and accelerates the discovery of osteoporosis causative genes. RNA interference is a powerful tool for rapid analysis of gene functions. Therefore, strategies to combine proteomics with RNA interference and transgenic RNAi would greatly improve the efficiency of gene discovery and divulge the molecular pathways involved in osteoporosis pathophysiology. In this review, current methods employed to identify genes involved in osteoporosis, which include linkage analysis, candidate gene association studies, genome wide association studies, transcriptome microarray, and proteomics are evaluated, and a new strategy is proposed.

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“…As an emerging and novel approach, systems genetics has been applied to complex diseases from a systems-level perspective to determine how genetic variations perturb cellular systems and ultimately disease (12). In a systems genetics study, data from genome, transcriptome, epigenome, proteome, metabolome, and interactome will be analyzed using a suite of analytical approaches including GWAS and network analysis (13).…”

mentioning

confidence: 99%

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

Zhang

et al. 2014

The Journal of Clinical Endocrinology & Metabolism

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Context:To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods:First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results:In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value Ͻ.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion:We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis.

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Systems Genetics: A Novel Approach to Dissect the Genetic Basis of Osteoporosis

Cited by 13 publications

References 64 publications

Genome-wide approaches for identifying genetic risk factors for osteoporosis

Genome-wide approaches for identifying genetic risk factors for osteoporosis

Searching for the Molecular Pathways Regulating Bone Mineral Density in the Proteome and RNA Interference Era

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

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