Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity
We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete inform...
| Autores: | ; ; ; ; ; ; |
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| Tipo de documento: | Artigo |
| Estado: | Published version |
| Data de publicação: | 2016 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositório: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/104559 |
| Acesso em linha: | https://hdl.handle.net/2445/104559 |
| Nível de acesso: | Acesso aberto |
| Palavra-chave: | Neurosi obsessiva Neuropsicologia Genètica humana Ressonància magnètica Diagnòstic per la imatge Farmacogenètica Obsessive-compulsive disorder Neuropsychology Human genetics Magnetic resonance Diagnostic imaging Pharmacogenetics |
| _version_ | 1878732160792264704 |
|---|---|
| author | Mas Herrero, Sergi |
| author2 | Gassó Astorga, Patricia Morer Liñán, Astrid Calvo, Anna Bargalló Alabart, Núria Lafuente, Amàlia, 1952-2022 Lázaro García, Luisa |
| author2_role | author author author author author author |
| author_browse | Bargalló Alabart, Núria Calvo, Anna Gassó Astorga, Patricia Lafuente, Amàlia, 1952-2022 Lázaro García, Luisa Mas Herrero, Sergi Morer Liñán, Astrid |
| author_facet | Mas Herrero, Sergi Gassó Astorga, Patricia Morer Liñán, Astrid Calvo, Anna Bargalló Alabart, Núria Lafuente, Amàlia, 1952-2022 Lázaro García, Luisa |
| author_role | author |
| collection | Recercat. Dipósit de la Recerca de Catalunya |
| description | We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the train- ing set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our under- standing of the neurobiological basis of the disorder. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ES_3dbccb294a8a1982e9dfc2eb3cd9b5b7 |
| institution | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| instname_str | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:recercat.cat:2445/104559 |
| publishDate | 2016 |
| publishDateSort | 2016 |
| publisher | Public Library of Science (PLoS) |
| publisherStr | Public Library of Science (PLoS) |
| reponame_str | Recercat. Dipósit de la Recerca de Catalunya |
| spelling | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity Mas Herrero, Sergi Gassó Astorga, Patricia Morer Liñán, Astrid Calvo, Anna Bargalló Alabart, Núria Lafuente, Amàlia, 1952-2022 Lázaro García, Luisa Neurosi obsessiva Neuropsicologia Genètica humana Ressonància magnètica Diagnòstic per la imatge Farmacogenètica Obsessive-compulsive disorder Neuropsychology Human genetics Magnetic resonance Diagnostic imaging Pharmacogenetics We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the train- ing set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our under- standing of the neurobiological basis of the disorder. Public Library of Science (PLoS) https://hdl.handle.net/2445/104559 |
| spellingShingle | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity Mas Herrero, Sergi Neurosi obsessiva Neuropsicologia Genètica humana Ressonància magnètica Diagnòstic per la imatge Farmacogenètica Obsessive-compulsive disorder Neuropsychology Human genetics Magnetic resonance Diagnostic imaging Pharmacogenetics |
| status_str | publishedVersion |
| title | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity |
| title_full | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity |
| title_fullStr | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity |
| title_full_unstemmed | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity |
| title_short | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity |
| title_sort | Integrating genetic, neuropsychological and neuroimaging data to model early-onset obsessive compulsive disorder severity |
| topic | Neurosi obsessiva Neuropsicologia Genètica humana Ressonància magnètica Diagnòstic per la imatge Farmacogenètica Obsessive-compulsive disorder Neuropsychology Human genetics Magnetic resonance Diagnostic imaging Pharmacogenetics |
| topic_facet | Neurosi obsessiva Neuropsicologia Genètica humana Ressonància magnètica Diagnòstic per la imatge Farmacogenètica Obsessive-compulsive disorder Neuropsychology Human genetics Magnetic resonance Diagnostic imaging Pharmacogenetics |
| url | https://hdl.handle.net/2445/104559 |