An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response

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• dc.contributor.author Baune, Bernhard T.
• dc.contributor.author Domínguez Barragán, Jorge
• dc.contributor.author Donlo, Chus
• dc.contributor.author Martínez de Lagrán Cabredo, María
• dc.contributor.author Mayer, Miguel Ángel, 1960-
• dc.contributor.author Perera Bel, Júlia
• dc.contributor.author Sierra, Cesar
• dc.contributor.author Sanz, Ferran
• dc.contributor.author Dierssen, Mara
• dc.date.accessioned 2024-03-19T07:32:34Z
• dc.date.available 2024-03-19T07:32:34Z
• dc.date.issued 2024
• dc.description.abstract Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance.
• dc.format.mimetype application/pdf
• dc.identifier.citation Baune BT, Minelli A, Carpiniello B, Contu M, Domínguez Barragán J, Donlo C, et al. An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response. Front Psychiatry. 2024 Jan 16;14:1279688. DOI: 10.3389/fpsyt.2023.1279688
• dc.identifier.doi http://dx.doi.org/10.3389/fpsyt.2023.1279688
• dc.identifier.issn 1664-0640
• dc.identifier.uri http://hdl.handle.net/10230/59478
• dc.language.iso eng
• dc.publisher Frontiers
• dc.relation.ispartof Front Psychiatry. 2024 Jan 16;14:1279688
• dc.rights © 2024 Baune, Minelli, Carpiniello, Contu, Domínguez Barragán, Donlo, Ferensztajn-Rochowiak, Glaser, Kelch, Kobelska, Kolasa, Kopeć, Martínez de Lagrán Cabredo, Martini, Mayer, Menesello, Paribello, Perera Bel, Perusi, Pinna, Pinna, Pisanu, Sierra, Stonner, Wahner, Xicota, Zang, Gennarelli, Manchia, Squassina, Potier, Rybakowski, Sanz and Dierssen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Antidepressant treatment response
• dc.subject.keyword Genomics
• dc.subject.keyword Major depressive disorder (MDD)
• dc.subject.keyword Patient empowerment
• dc.subject.keyword Predictive algorithm
• dc.subject.keyword Shared decision making (SDM)
• dc.subject.keyword Transcriptomics
• dc.subject.keyword Treatment resistant depression (TRD)
• dc.title An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion