Towards an early identification of depression through a process of physiological signals and metabolomic biomarkers

The main diagnostic methods for depression are based on subjective measures. Autonomic nervous system (ANS) changes in depression may affect physiological signals. These signals can be noninvasively measured and provide objective data which may aid in the diagnosis and monitoring of the disease. The main objective of the project is to investigate autonomic nervous system biomarkers in depression which may aid in the quantitative diagnosis and monitoring of the disease. Specific objectives: 1) Recording of a database of ambulatory MDD patients, and controls, during basal conditions, and subject to a cognitive stressor. This database will include physiological signals, biochemicalmarkers, metabolomics, clinical variables. 2) Development of signal processing techniques to robustly derive physiological indices related to ANS activity in MDD patients. 3) Analysis of the correlations between: i) physiological indices and depression severity; ii) stress level and depression severity; iii) biochemical markers and depression severity; iv) metabolomics profile and depression severity. 4) Design and validation of prediction models for depression severity assessment based on  physiological signals, biochemical markers, metabolomics fingerprint and psychometric tests.