Bioinformatic Analysis of Coronary Disease Associated SNPs and Genes to Identify Proteins Potentially Involved in the Pathogenesis of Atherosclerosis

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dc.contributor.authorMao, Chunhongen
dc.contributor.authorHoward, Timothy D.en
dc.contributor.authorSullivan, Danen
dc.contributor.authorFu, Zongmingen
dc.contributor.authorYu, Guoqiangen
dc.contributor.authorParker, Sarah J.en
dc.contributor.authorWill, Rebeccaen
dc.contributor.authorVander Heide, Richard S.en
dc.contributor.authorWang, Yueen
dc.contributor.authorHixson, Jamesen
dc.contributor.authorVan Eyk, Jenniferen
dc.contributor.authorHerrington, David M.en
dc.date.accessioned2018-07-13T14:10:36Zen
dc.date.available2018-07-13T14:10:36Zen
dc.date.issued2017-03-04en
dc.description.abstractFactors that contribute to the onset of atherosclerosis may be elucidated by bioinformatic techniques applied to multiple sources of genomic and proteomic data. The results of genome wide association studies, such as the CardioGramPlusC4D study, expression data, such as that available from expression quantitative trait loci (eQTL) databases, along with protein interaction and pathway data available in Ingenuity Pathway Analysis (IPA), constitute a substantial set of data amenable to bioinformatics analysis. This study used bioinformatic analyses of recent genome wide association data to identify a seed set of genes likely associated with atherosclerosis. The set was expanded to include protein interaction candidates to create a network of proteins possibly influencing the onset and progression of atherosclerosis. Local average connectivity (LAC), eigenvector centrality, and betweenness metrics were calculated for the interaction network to identify top gene and protein candidates for a better understanding of the atherosclerotic disease process. The top ranking genes included some known to be involved with cardiovascular disease (APOA1, APOA5, APOB, APOC1, APOC2, APOE, CDKN1A, CXCL12, SCARB1, SMARCA4 and TERT), and others that are less obvious and require further investigation (TP53, MYC, PPARG, YWHAQ, RB1, AR, ESR1, EGFR, UBC and YWHAZ). Collectively these data help define a more focused set of genes that likely play a pivotal role in the pathogenesis of atherosclerosis and are therefore natural targets for novel therapeutic interventions.en
dc.description.sponsorshipNational Institutes of Healthen
dc.description.sponsorshipNIH: R01HL111362en
dc.identifier.doihttps://doi.org/10.14302/issn.2326-0793.jpgr-17-1447en
dc.identifier.issue1en
dc.identifier.urihttp://hdl.handle.net/10919/83953en
dc.identifier.volume2en
dc.language.isoen_USen
dc.publisherOpen Access Puben
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectBioinformaticsen
dc.subjectCoronary diseaseen
dc.subjectAtherosclerosisen
dc.subjectSNPsen
dc.subjectGenomicsen
dc.titleBioinformatic Analysis of Coronary Disease Associated SNPs and Genes to Identify Proteins Potentially Involved in the Pathogenesis of Atherosclerosisen
dc.title.serialJournal of Proteomics and Genomics Researchen
dc.typeArticle - Refereeden

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