System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data

Detalhes bibliográficos
Autor(a) principal: Asif, Muhammad
Data de Publicação: 2014
Tipo de documento: Relatório
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.18/2945
Resumo: BioSys-PhD, Biological Systems: Functional and Integrative Genomics
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spelling System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical dataPerturbações do Desenvolvimento Infantil e Saúde MentalAutism Spectrum DisorderBioSys-PhD, Biological Systems: Functional and Integrative GenomicsAutism spectrum disorder (ASD) is a neurodevelopmental disorder of well known complexity. ASD is characterized by impaired social interaction and communication and by stereotyped behaviors, and a high heterogeneity in clinical and genetic presentation. It is hypothesized that such complex heterogeneous phenotypic behaviors are associated with genetic factors. To dissect the complex correlations between phenotype and genotype in ASD, in the current study we will use powerful machine learning and data mining algorithms, like decision trees. We will integrate clinical information (from the diagnostic instruments ADI-R: Autism Diagnostic Interview-Revised and ADOS: Autism Diagnostic Observation Schedule, as well as adaptive behavior scale VABS: Vineland Adaptive Behavior Scale and cognitive scales adapted to age and cognitive level) and genetic data (Copy Number Variants, CNVs) of 3000 ASD individuals with ASD. Data on this patient cohort was obtained by the Autism Genome Project international consortium, which included 335 Portuguese patients from our dataset. This analysis will identify autism behavior associations with genetic risk factors, and eventually allow categorization of patients and prognosis according to genotype. We will initially assess the effect of deletion and duplication events and de novo and transmitted CNVs in disease clinical presentation, and progress to analyze the association of CNVs containing candidate genes for ASD with disease phenotype. So far, the etiology of autism is not well understood due to interactions between multiple factors. Genetic, metabolic, gastrointestinal, immunological and neurobiological factors have been associated with ASD etiology. Therefore, we will use a system biology based approach for ASD analysis, which will integrate genetic, miRNA, neurobiology and clinical data to determine how multiple factors can influence the autism heterogeneity. This work will improve the accuracy of data mining techniques, by building specialized classifiers based on a machine learning approach), and by applying semantic enrichment analysis. These classifiers will help in rapid diagnosis of ASD. Moreover, we will provide a framework for autism analysis with knowledge graph based data organization. This framework will enlist classifiers, feature selection and cross validation methods for ASD analysis. We will also provide a comparative and testing phase to cross check the accuracy of framework. ASD is a complex disorder, therefore enhanced understanding of associations at multiple levels (genetic, miRNA, neurobiology, clinical and behavioral), will be useful to assist in ASD diagnosis and prognosis.Muhammad Asif, Doctoral Research Fellow for Fundação para a Ciência e Tecnologia do Ministério da Ciência, Tecnologia e Ensino Superior SFRH/BD/52485/2014Moura, AstridCouto, Francisco M.Repositório Científico do Instituto Nacional de SaúdeAsif, Muhammad2015-02-20T14:39:40Z2014-122014-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/reportapplication/pdfhttp://hdl.handle.net/10400.18/2945enginfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-20T15:39:31Zoai:repositorio.insa.pt:10400.18/2945Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:37:52.954090Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
title System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
spellingShingle System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
Asif, Muhammad
Perturbações do Desenvolvimento Infantil e Saúde Mental
Autism Spectrum Disorder
title_short System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
title_full System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
title_fullStr System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
title_full_unstemmed System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
title_sort System medicine approach to improve diagnosis and prognosis in Autism Spectrum Disorders (ASD), based on extensive genomic, biochemical and clinical data
author Asif, Muhammad
author_facet Asif, Muhammad
author_role author
dc.contributor.none.fl_str_mv Moura, Astrid
Couto, Francisco M.
Repositório Científico do Instituto Nacional de Saúde
dc.contributor.author.fl_str_mv Asif, Muhammad
dc.subject.por.fl_str_mv Perturbações do Desenvolvimento Infantil e Saúde Mental
Autism Spectrum Disorder
topic Perturbações do Desenvolvimento Infantil e Saúde Mental
Autism Spectrum Disorder
description BioSys-PhD, Biological Systems: Functional and Integrative Genomics
publishDate 2014
dc.date.none.fl_str_mv 2014-12
2014-12-01T00:00:00Z
2015-02-20T14:39:40Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/report
format report
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.18/2945
url http://hdl.handle.net/10400.18/2945
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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