Korean-UK consortium to predict treatment response in major depression using mechanistic early response markers
Lead Research Organisation:
University of Nottingham
Department Name: UNLISTED
Abstract
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Technical Summary
"Major depressive disorder (MDD) is a leading cause of disability severely affecting mental health, resulting in premature death, and causing massive socio-economic burden. About half of MDD patients do not respond to their initial treatment, and ~30% are considered treatment resistant. The exact pathophysiology of depression and mechanisms of action (MOA) of various antidepressant therapies remain elusive. There is an urgent need to better understand and individually predict treatment response to improve outcomes by offering early adjunctive or alternative interventions to those unlikely to respond to standard treatment.
To overcome current limitations a comprehensive approach is needed to combine the predictive power of multimodal biomarkers and digital phenotyping that depict the multifaceted aspects of depression including neuroimaging, inflammation, and digital physiological phenotyping. This will be made possible by developing an inter-institutional strategic alliance building on the thriving interdisciplinary partnership between well-established centres of excellence in Seoul, Korea (KU, Brain Convergence Research Centre) and the Nottingham, UK (Biomedical Research Centre).
In this MRC-NRF funded partnership building project, we will lay the foundations and providing proof of concept support for the multi-stage development of a precise, personalised predictive model for antidepressant treatment response based on dynamic responses of existing and new digital phenotypes, inflammation, and brain imaging markers.
During the 12 months consortium building, we will (i) establish a joint platform for standardised collection of digital phenotyping, brain imaging and inflammatory biomarkers with potential to indicate MOA; (ii) pilot early (~2 weeks) biomarker responsiveness to standard antidepressant pharmacotherapy to assess feasibility of multi-omics data collection, determine sensitivity to mechanisms of actions and provide proof of concept for associations with future (12 weeks) response; and (iii) develop a prospective trial design as next stage of the consortial research activity based on pilot findings, systematic reviews and as appropriate use of Mendelian randomization (MR) technique to ascertain putative causal inference of novel treatment targets. These activities including the pilot studies are expected to demonstrate feasibility to detect treatment response across multiple MOA after two weeks of antidepressant therapy, and to provide support for predictive candidate biomarkers for treatment response beyond 3 months. Based on these preliminary findings, we will seek additional funding to support the development, refinement and validation of a cloud-based AI enabled prediction of individual treatment response. Developing further funding applications is an explicit objective during the consortium building to boost the long-term sustainability and growth of our strategic partnership. "
To overcome current limitations a comprehensive approach is needed to combine the predictive power of multimodal biomarkers and digital phenotyping that depict the multifaceted aspects of depression including neuroimaging, inflammation, and digital physiological phenotyping. This will be made possible by developing an inter-institutional strategic alliance building on the thriving interdisciplinary partnership between well-established centres of excellence in Seoul, Korea (KU, Brain Convergence Research Centre) and the Nottingham, UK (Biomedical Research Centre).
In this MRC-NRF funded partnership building project, we will lay the foundations and providing proof of concept support for the multi-stage development of a precise, personalised predictive model for antidepressant treatment response based on dynamic responses of existing and new digital phenotypes, inflammation, and brain imaging markers.
During the 12 months consortium building, we will (i) establish a joint platform for standardised collection of digital phenotyping, brain imaging and inflammatory biomarkers with potential to indicate MOA; (ii) pilot early (~2 weeks) biomarker responsiveness to standard antidepressant pharmacotherapy to assess feasibility of multi-omics data collection, determine sensitivity to mechanisms of actions and provide proof of concept for associations with future (12 weeks) response; and (iii) develop a prospective trial design as next stage of the consortial research activity based on pilot findings, systematic reviews and as appropriate use of Mendelian randomization (MR) technique to ascertain putative causal inference of novel treatment targets. These activities including the pilot studies are expected to demonstrate feasibility to detect treatment response across multiple MOA after two weeks of antidepressant therapy, and to provide support for predictive candidate biomarkers for treatment response beyond 3 months. Based on these preliminary findings, we will seek additional funding to support the development, refinement and validation of a cloud-based AI enabled prediction of individual treatment response. Developing further funding applications is an explicit objective during the consortium building to boost the long-term sustainability and growth of our strategic partnership. "