# 5/5 - Biomarkers/Biotypes, Course of Early Psychosis and Specialty Services (BICEPS)

> **NIH NIH R01** · UNIVERSITY OF GEORGIA · 2024 · $302,000

## Abstract

PROJECT SUMMARY
There is increasing evidence that early intervention for psychosis in coordinated specialty care
(CSC) services improves outcomes and lives. The outcome of early course psychosis (EP) is
heterogeneous, ranging from early full recovery to treatment resistance and functional decline
from the onset of illness. This heterogeneity limits our ability to predict individual level outcomes
needed for treatment planning and for tailoring the type, duration and intensity of therapeutic
interventions. Biomarkers as well as clinical and demographic features, early in the illness can
predict outcome, but taken individually, their prognostic value is limited. Our Bipolar-
Schizophrenia Network for Intermediate Phenotypes (BSNIP) consortium has recently developed,
replicated and validated a biomarker (EEG, eye movement testing, and neurocognition) based
categorization (Biotypes 1, 2 and 3) in a trans-diagnostic sample of cases with idiopathic
psychosis (schizophrenia, schizoaffective disorder, or bipolar disorder with psychosis), ranging
from 18-35 years of age. In this study, we will leverage this categorization, along with clinical and
biomarker data to predict illness trajectory and outcome during follow-up at 1, 6 and 12 months in
320 EP patients across CSC clinics at the five B-SNIP sites. First, we will characterize outcome
trajectories and Biotype structure in EP. Our available data indicate the Biotype structure will be
the same in EP as in our large sample. Second, we will investigate the predictive value of the nine
bio-factors and the three Biotypes identified by B-SNIP for symptomatic and functional outcome.
We predict that the EP population will manifest distinct outcome clinical trajectories (good,
intermediate and poor) and will have a Biotype structure similar to that seen in chronic psychosis
subjects, i.e., Biotypes 1, 2 and 3) (hypothesis 1). Biotype-3, and Biotye-2 cases, will have the
best outcomes (defined both categorically, and dimensionally, using symptomatic, cognitive and
functional measures); Biotype-1 will have the worst outcomes to CSC treatment, across all target
time points (hypothesis 2). Notably, Biotype-1 and Biotype-2 cases will have the same level of
cognition function at baseline. Finally, we will investigate the predictive value of clinical (such as
diagnosis, illness duration, substance abuse, and treatment adherence), and biomarker (including
neuroimaging) features in a multi-variate model and will develop a feasible biomarker battery and
predictive algorithm for application in community CSC sites nation-wide. We will thus provide to
the field a means for predicting success of EP cases in CSC treatment to improve clinical practice
and to enhance efficient use of available treatment resources.

## Key facts

- **NIH application ID:** 10880352
- **Project number:** 5R01MH127172-03
- **Recipient organization:** UNIVERSITY OF GEORGIA
- **Principal Investigator:** BRETT A CLEMENTZ
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $302,000
- **Award type:** 5
- **Project period:** 2022-08-15 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10880352

## Citation

> US National Institutes of Health, RePORTER application 10880352, 5/5 - Biomarkers/Biotypes, Course of Early Psychosis and Specialty Services (BICEPS) (5R01MH127172-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10880352. Licensed CC0.

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