Assessment of complementarity of WGCNA and NERI results for identification of modules associated to schizophrenia spectrum disorders

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dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorFELTRIN, Arthur Sant'Anna
dc.contributor.authorTAHIRA, Ana Carolina
dc.contributor.authorSIMOES, Sergio Nery
dc.contributor.authorBRENTANI, Helena
dc.contributor.authorMARTINS JR., David Correa
dc.date.accessioned2019-02-21T17:27:25Z
dc.date.available2019-02-21T17:27:25Z
dc.date.issued2019
dc.description.abstractPsychiatric disorders involve both changes in multiple genes as well different types of variations. As such, gene co-expression networks allowed the comparison of different stages and parts of the brain contributing to an integrated view of genetic variation. Two methods based on co-expression networks presents appealing results: Weighted Gene Correlation Network Analysis (WGCNA) and Network-Medicine Relative Importance (NERI). By selecting two different gene expression databases related to schizophrenia, we evaluated the biological modules selected by both WGCNA and NERI along these databases as well combining both WGCNA and NERI results (WGCNA-NERI). Also we conducted a enrichment analysis for the identification of partial biological function of each result (as well a replication analysis). To appraise the accuracy of whether both algorithms (as well our approach, WGCNA-NERI) were pointing to genes related to schizophrenia and its complex genetic architecture we conducted the MSET analysis, based on a reference gene list of schizophrenia database (SZDB) related to DNA Methylation, Exome, GWAS as well as copy number variation mutation studies. The WGCNA results were more associated with inflammatory pathways and immune system response; NERI obtained genes related with cellular regulation, embryological pathways e cellular growth factors. Only NERI were able to provide a statistical meaningful results to the MSET analysis (for Methylation and de novo mutations data). However, combining WGCNA and NERI provided a much more larger overlap in these two categories and additionally on Transcriptome database. Our study suggests that using both methods in combination is better for establishing a group of modules and pathways related to a complex disease than using each method individually. NERI is available at: https://bitbucket.org/sergionery/neri.eng
dc.description.indexMEDLINEeng
dc.description.sponsorshipFAPESP - Sao Paulo Research Foundation [2014/10488-3, 2011/50761-2, 2015/01587-0, 2014/00041-1, 2011/04956-6]
dc.description.sponsorshipCNPq - National Council for Scientific and Technological Development [304955/2014-0]
dc.description.sponsorshipCAPES - Coordination for the Improvement of Higher Education Personnel [1750212, 88881.187975/2018-01]
dc.description.sponsorshipNAP eScience -PRP- USP
dc.description.sponsorshipUFABC - Federal University of ABC
dc.identifier.citationPLOS ONE, v.14, n.1, article ID e0210431, 22p, 2019
dc.identifier.doi10.1371/journal.pone.0210431
dc.identifier.issn1932-6203
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/30896
dc.language.isoeng
dc.publisherPUBLIC LIBRARY SCIENCEeng
dc.relation.ispartofPlos One
dc.rightsopenAccesseng
dc.rights.holderCopyright PUBLIC LIBRARY SCIENCEeng
dc.subject.othernetwork biologyeng
dc.subject.othergene networkseng
dc.subject.otherneurogenesiseng
dc.subject.otherpathwayseng
dc.subject.otherslc6a3eng
dc.subject.othereef2eng
dc.subject.wosMultidisciplinary Scienceseng
dc.titleAssessment of complementarity of WGCNA and NERI results for identification of modules associated to schizophrenia spectrum disorderseng
dc.typearticleeng
dc.type.categoryoriginal articleeng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.author.externalFELTRIN, Arthur Sant'Anna:Fed Univ ABC UFABC, Ctr Math Computat & Cognit, Santo Andre, SP, Brazil
hcfmusp.author.externalSIMOES, Sergio Nery:Fed Inst Educ Sci & Technol Espirito Santo, Serra, ES, Brazil
hcfmusp.author.externalMARTINS JR., David Correa:Fed Univ ABC UFABC, Ctr Math Computat & Cognit, Santo Andre, SP, Brazil
hcfmusp.citation.scopus20
hcfmusp.contributor.author-fmusphcANA CAROLINA TAHIRA
hcfmusp.contributor.author-fmusphcHELENA PAULA BRENTANI
hcfmusp.description.articlenumbere0210431
hcfmusp.description.issue1
hcfmusp.description.volume14
hcfmusp.origemWOS
hcfmusp.origem.pubmed30645614
hcfmusp.origem.scopus2-s2.0-85060023534
hcfmusp.origem.wosWOS:000455810200029
hcfmusp.publisher.citySAN FRANCISCOeng
hcfmusp.publisher.countryUSAeng
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