Expected Impact

The following outcomes will directly result from the activity of the PRECISESADS consortium:

• Identification of biomarkers for clinical use (diagnosis, prognosis, response to drugs) for SAD patients.
• Identification of clusters of biomarkers that characterize groups of SADs patients.
• Reclassification of SADs based on meaningful clinical biomarkers.
• Crucial scientific insights on the interplay between different clinical features among SADs.
• Development of a protocol for patient management.

These outcomes will directly result in the following impacts:

• Impact on SAD classification and patient stratification. One of the major goals of the PRECISESADS consortium is the generate a novel classification of SAD patients based on state-of-the-art OMICS data and integrated systems biology analysis but with the possibility of yielding a minimum number of easy-to-use/inexpensive biomarkers that can be transferred to the clinical practice for fast and inexpensive detection and patient stratification.
• Impact on generation of robust biomarkers for clinical use. Integrated bioinformatics will result in the generation of a robust set of biomarkers associated with general and specific clinical features of SADs. Clusters of biomarkers will not only be used for the re-classification of SADs, stratification of SAD patients but also will be potentially used for other related disorders sharing clinical features with SADs.
• Impact on the knowledge regarding the interplay between different regulatory factors during SAD onset, progression and response to drugs.
• Impact on the generation of a state-of-the art technological/analytical platform for testing new compounds or compounds in clinical trials. Molecular profiling of SADs patients and identification of relevant biomarkers for the clusters will facilitate patient stratification for clinical trials based on the molecular mechanisms targeted by the intervention to be tested. Parallel profiling of commonly used preclinical disease models and determination of their “goodness of fit” to the identified patient clusters will improve rational selection of the most appropriate animal models for the discovery of new drugs for treatment of SADs. Taken together, these aspects will contribute to improving probability of success for development of new treatments and thereby to improvements in therapeutic options for SADs patients