(2019-2.1.7-ERA-NET-2020-00005) Támogató: Nemzeti Kutatási, Fejlesztési és Innovációs
Hivatal
Depression is a highly prevalent and debilitating condition, yet we still lack both
in-depth knowledge concerning its etiopathology and sufficiently efficacious treatment
options. With approximately one third of patients resistant to currently available
antidepressants there is a pressing need for a better understanding of depression,
identifying subgroups within the highly heterogeneous illness category and to understand
the divergent underlying biology of such subtypes, to help develop and personalise
treatments. The TRAJECTOME project aims to address such challenges by (1) identifying
depression-related multimorbidity subgroups and shared molecular pathways based on
temporal disease profiles from healthcare systems and biobank data using machine learning
approaches, and by (2) characterising these subgroups from multiple aspects including
genetic variants, metabolic processes, lifestyle and environmental factors. Following
the identification of multimorbidity trajectories, a disease burden score related
to depression and adjusted for multimorbidity was established summarising the current
state of the patient to weigh the molecular mechanisms associated with depression.
In addition, the role of genetic and environmental factors, and also their interactions
were identified for all subgroups. The project also attempted to identify potential
metabolomic markers for the early diagnostics of these multimorbidity conditions.
Finally, we prioritized molecular drug candidates matching the multimorbidity pathways
indicated for the individual subgroups which would potentially offer personalised
treatment simultaneously for the observable multimorbid conditions yet minimising
polypharmacy and related side effects. The present paper overviews the TRAJECTOME
project including its aims, tasks, procedures and accomplishments. (Neuropsychopharmacol
Hung 2023; 25(4): 183-193)
