{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T23:17:53Z","timestamp":1779923873939,"version":"3.53.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643682648","type":"print"},{"value":"9781643682655","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,6]]},"abstract":"<jats:p>Primary Immunodeficiencies (PIDs) are associated with more than 400 rare monogenic diseases affecting various biological functions (e.g., development, regulation of the immune response) with a heterogeneous clinical expression (from no symptom to severe manifestations). To better understand PIDs, the ATRACTion project aims to perform a multi-omics analysis of PIDs cases versus a control group patients, including single-cell transcriptomics, epigenetics, proteomics, metabolomics, metagenomics and lipidomics. In this study, our goal is to develop a common data model integrating clinical and omics data, which can be used to obtain standardized information necessary for characterization of PIDs patients and for further systematic analysis. For that purpose, we extend the OMOP Common Data Model (CDM) and propose a multi-omics ATRACTion OMOP-CDM to integrate multi-omics data. This model, available for the community, is customizable for other types of rare diseases (https:\/\/framagit.org\/imagine-plateforme-bdd\/pub-rhu4-atraction).<\/jats:p>","DOI":"10.3233\/shti220031","type":"book-chapter","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:29:53Z","timestamp":1654594193000},"source":"Crossref","is-referenced-by-count":1,"title":["A Multi-Omics Common Data Model for Primary Immunodeficiencies"],"prefix":"10.3233","author":[{"given":"M\u00e9lanie","family":"Buy","sequence":"first","affiliation":[{"name":"Universit\u00e9 de Paris, Imagine Institute, Data Science Platform, INSERM UMR 1163, F-75015, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"ATRACTion Members","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Digan","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris, Imagine Institute, Data Science Platform, INSERM UMR 1163, F-75015, Paris, France"},{"name":"Centre de Recherche des Cordeliers, INSERM, Universit\u00e9 de Paris, Sorbonne Universit\u00e9, F-75006, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyi","family":"Chen","sequence":"additional","affiliation":[{"name":"Centre de Recherche des Cordeliers, INSERM, Universit\u00e9 de Paris, Sorbonne Universit\u00e9, F-75006, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Husson","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris, Imagine Institute, Data Science Platform, INSERM UMR 1163, F-75015, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mickael","family":"M\u00e9nager","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris, Imagine Institute, Laboratory of Inflammatory Responses and Transcriptomic Networks in Diseases, Atip-Avenir Team, INSERM UMR 1163, F-75015 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fr\u00e9d\u00e9ric","family":"Rieux-Laucat","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris, Imagine Institute, Laboratory of Immunogenetics of Pediatric Autoimmune Diseases, INSERM UMR U1163, F-75015 Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Garcelon","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris, Imagine Institute, Data Science Platform, INSERM UMR 1163, F-75015, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2021: One World, One Health \u2013 Global Partnership for Digital Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220031","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:29:54Z","timestamp":1654594194000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220031"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,6]]},"ISBN":["9781643682648","9781643682655"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220031","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,6]]}}}