A Stratified Treatment Algorithm in Psychiatry: A program on stratified pharmacogenomics in severe mental illness

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Learn more about Psych-STRATA

This is a graphic abstract of the project that will help you to understand our research process. Click in each process box to find a graphic description. If you are interested in learning more contact info@psych-strata.eu

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Genomic analyses

Genomic analysis will compare the DNA sequence of patients with and without treatment resistance using large samples. This approach will allow the identification of differences in DNA that increase the risk for treatment resistance.

Proteomic / transcriptomic analyses

RNA-based transcriptomic analyses will measure expressed genes and proteomic analysis will quantify the proteins after epigenetic modifications that circulate in the blood in patients with and without treatment resistance. This approach will allow the identification of biomarker signatures that could be associated with an increased risk of treatment resistance.

Cellular models

Using induced pluripotent stem cell (iPSC) technology, neurons of patients with or without treatment resistance will be differentiated in laboratory cell cultures. This experimental setup will allow the analysis of the effects of treatments on the transcriptome (RNA) and metabolome of these differentiated neurons as well as the genetics of treatment response. Such analyses will eventually lead to the identification of further candidate biomarkers related to treatment resistance.

Clinical trial / Deep phenotyping

A clinical study will be conducted, comparing patients that receive intensified treatment to those that receive treatment as usual. The efficacy of the intensified treatment option will be studied. Likewise, the patients included in this clinical study will be thoroughly assessed regarding their clinical severity, cognitive function, and several measures obtained using digital tools and blood-based markers. This approach will allow the delineation of a behavioural and biomarker profile that is associated with treatment resistance.

Machine Learning / Prediction

The biological and behavioral information collected in the different phases of Psych-STRATA will be combined using sophisticated statistical models (machine learning). The final goal is the development of predictive models of treatment resistance that will assist physicians to decide which patients are eligible for intensified treatment very early on.