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

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Scientific articles

Exploring the realm of knowledge: Immerse yourself in the riches of scientific articles!

Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores

January 15, 2023

 | Publication

In this article, the authors observe that the genetic load for schizophrenia is associated with the highest clozapine dose in patients who suffer schizophrenia. It is noteworthy to mention that these researchers replicated this finding in 3 independent samples, the gold standard when it comes to validate the results of a genetic study.
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Polygenic risk scores of lithium response and treatment resistance in major depressive disorder

September 28, 2023

 | Publication

In this article, the authors describe an increased genetic load for lithium treatment response in patients who suffer treatment-resistant depression (TRD) when compared to depressive patients without TRD (they respond well to antidepressant pharmacological treatment). On the other hand, TRD and non-TRD patients did not show differences regarding the genetic load for antidepressant treatment response. Taken together, these results describe the existence of a genetic profile of lithium-sensitivity in TRD that could explain the efficacy of lithium to treat TRD.
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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

Genomic analyses

Proteomic / transcriptomic analyses

Cellular models

Clinical trial / Deep phenotyping

Machine Learning / Prediction

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The Psych-STRATA project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101057454.

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Genomic analyses

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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

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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

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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

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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

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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.