Neurobiological Markers as Predictors of Later Functional Outcome in First Episode Psychosis

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PROJECT SUMMARY Due to the COVID-19 pandemic, the parent R01 project experienced significant delays and interruptions in the last year of award, resulting in substantial components (Aim 2) of the investment being at risk. Also, the principal investigator’s grants are ending with no additional funding. This supplement will thus provide a critical resource to: i) complete the proposed longitudinal cohort data collection in order to achieve the proposed project goals; ii) extend the science of parent R01 project beyond the initial follow-up period to include the early-stage illness period; iii) provide much needed salary support of the principal investigator. NIMH priority research area: Examine Mental Illness Trajectories Across the Lifespan. Scope of the Parent Project (MH109687): to characterize bio-classes of first episode of psychosis patients (FEP) using an expanded biomarker panel and to investigate the role of bio-classes as predictors of later functional outcomes. Specific Aim 1: To bio-classify FEP patients into distinct homogeneous sub-groups (bio-classes) using a constellation of biomarkers and phenotypes at baseline. Specific Aim 2a: To investigate whether baseline bio-classes are associated with and predictive of later functional outcomes over a two-year follow-up period and collect comprehensive biomarker, clinical, and functional outcome measures at each time point. Specific Aim 2b: To examine differences between bio-classes and DSM classification in associations with later functional outcomes and recovery trajectories over two-years. Contribution of the requested supplement: Although the 2-year follow-up data was not collected due to the COVID-19 disruption, we predict that baseline bio-classes will continue to be significantly associated with and predictive of later functional outcomes throughout the early-stage illness beyond the initial proposed 2 years. Therefore, we propose a Modified Specific Aim 2a: To investigate whether baseline bio-classes are associated with and predictive of later functional outcomes during early-stage illness. We will bring back FEP patients (N=58) who have already enrolled in the study with baseline data and collect follow-up data. The follow-up period will thus be extended within 4 years of illness onset. We predict that machine learning clustering analyses will parse out heterogeneity of patients making reliable bio-class classifications and predictions. Specific Aim 2b will remain unchanged.