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Article: Prediction of osteoporosis candidate genes by computational disease-gene identification strategy

TitlePrediction of osteoporosis candidate genes by computational disease-gene identification strategy
Authors
KeywordsBioinformatics
Bone mineral density
Candidate gene
Genetics
Osteoporosis
Issue Date2008
PublisherNature Publishing Group. The Journal's web site is located at http://www.nature.com/jhg/index.html
Citation
Journal Of Human Genetics, 2008, v. 53 n. 7, p. 644-655 How to Cite?
AbstractOsteoporosis is a complex disease with a strong genetic component. To date, more than 20 genome-wide linkage scans across multiple populations have been launched to hunt for osteoporosis susceptibility genes. Some significant or suggestive chromosomal regions of linkage to bone mineral density have been identified and replicated in genome-wide linkage screens. However, identification of key candidate genes within these confirmed regions is challenging. We used five freely available bioinformatics tools (Prioritizer, GeneSeeker, PROSPECTR and SUSPECTS, Disease Gene Prediction, and Endeavor) to analyze the 13 well-replicated osteoporosis susceptibility loci: 1p36, 1q21-25, 2p22-24, 3p14-25, 4q25-34, 6p21, 7p14-21, 11q14-25, 12q23-24, 13q14-34, 20p12, 2q24-32, and 5q12-21. Pathways and regulatory network analyses were performed using the Ingenuity Pathways Analysis (IPA) software. We identified a subset of most likely candidate osteoporosis susceptibility genes that are largely involved in transforming growth factor (TGF)-β signaling, granulocyte-macrophage colony-stimulating factor (GM-CSF) signaling, axonal guidance signaling, peroxisome proliferator-activated receptor (PPAR) signaling, and Wnt/β-catenin signaling pathway. Six nonoverlapping networks were generated by IPA 5.0 from 88 out of the 91 candidate genes. The list of most likely candidate genes and the associated pathway identified will assist researchers in prioritizing candidate disease genes for further empirical analysis and understanding the pathogenesis of osteoporosis. © 2008 The Japan Society of Human Genetics and Springer.
Persistent Identifierhttp://hdl.handle.net/10722/68325
ISSN
2015 Impact Factor: 2.487
2015 SCImago Journal Rankings: 1.416
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHuang, QYen_HK
dc.contributor.authorLi, GHYen_HK
dc.contributor.authorCheung, WMWen_HK
dc.contributor.authorSong, YQen_HK
dc.contributor.authorKung, AWCen_HK
dc.date.accessioned2010-09-06T06:03:30Z-
dc.date.available2010-09-06T06:03:30Z-
dc.date.issued2008en_HK
dc.identifier.citationJournal Of Human Genetics, 2008, v. 53 n. 7, p. 644-655en_HK
dc.identifier.issn1434-5161en_HK
dc.identifier.urihttp://hdl.handle.net/10722/68325-
dc.description.abstractOsteoporosis is a complex disease with a strong genetic component. To date, more than 20 genome-wide linkage scans across multiple populations have been launched to hunt for osteoporosis susceptibility genes. Some significant or suggestive chromosomal regions of linkage to bone mineral density have been identified and replicated in genome-wide linkage screens. However, identification of key candidate genes within these confirmed regions is challenging. We used five freely available bioinformatics tools (Prioritizer, GeneSeeker, PROSPECTR and SUSPECTS, Disease Gene Prediction, and Endeavor) to analyze the 13 well-replicated osteoporosis susceptibility loci: 1p36, 1q21-25, 2p22-24, 3p14-25, 4q25-34, 6p21, 7p14-21, 11q14-25, 12q23-24, 13q14-34, 20p12, 2q24-32, and 5q12-21. Pathways and regulatory network analyses were performed using the Ingenuity Pathways Analysis (IPA) software. We identified a subset of most likely candidate osteoporosis susceptibility genes that are largely involved in transforming growth factor (TGF)-β signaling, granulocyte-macrophage colony-stimulating factor (GM-CSF) signaling, axonal guidance signaling, peroxisome proliferator-activated receptor (PPAR) signaling, and Wnt/β-catenin signaling pathway. Six nonoverlapping networks were generated by IPA 5.0 from 88 out of the 91 candidate genes. The list of most likely candidate genes and the associated pathway identified will assist researchers in prioritizing candidate disease genes for further empirical analysis and understanding the pathogenesis of osteoporosis. © 2008 The Japan Society of Human Genetics and Springer.en_HK
dc.languageengen_HK
dc.publisherNature Publishing Group. The Journal's web site is located at http://www.nature.com/jhg/index.htmlen_HK
dc.relation.ispartofJournal of Human Geneticsen_HK
dc.subjectBioinformaticsen_HK
dc.subjectBone mineral densityen_HK
dc.subjectCandidate geneen_HK
dc.subjectGeneticsen_HK
dc.subjectOsteoporosisen_HK
dc.subject.meshBone Density - geneticsen_HK
dc.subject.meshComputational Biology - methodsen_HK
dc.subject.meshGenetic Linkageen_HK
dc.subject.meshGenetic Predisposition to Diseaseen_HK
dc.subject.meshHumansen_HK
dc.subject.meshOsteoporosis - geneticsen_HK
dc.subject.meshPredictive Value of Testsen_HK
dc.titlePrediction of osteoporosis candidate genes by computational disease-gene identification strategyen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1434-5161&volume=53&spage=644&epage=655&date=2008&atitle=Prediction+of+osteoporosis+candidate+genes+by+computational+disease-gene+identification+strategyen_HK
dc.identifier.emailHuang, QY: qyhuang@hotmail.comen_HK
dc.identifier.emailSong, YQ: songy@hku.hken_HK
dc.identifier.emailKung, AWC: awckung@hku.hken_HK
dc.identifier.authorityHuang, QY=rp00521en_HK
dc.identifier.authoritySong, YQ=rp00488en_HK
dc.identifier.authorityKung, AWC=rp00368en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10038-008-0295-xen_HK
dc.identifier.pmid18463784-
dc.identifier.scopuseid_2-s2.0-46149084172en_HK
dc.identifier.hkuros145103en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-46149084172&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume53en_HK
dc.identifier.issue7en_HK
dc.identifier.spage644en_HK
dc.identifier.epage655en_HK
dc.identifier.isiWOS:000257208200009-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridHuang, QY=7403630787en_HK
dc.identifier.scopusauthoridLi, GHY=35080710200en_HK
dc.identifier.scopusauthoridCheung, WMW=7202743069en_HK
dc.identifier.scopusauthoridSong, YQ=7404921212en_HK
dc.identifier.scopusauthoridKung, AWC=7102322339en_HK

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