# 3/5 Biomarkers/Biotypes, Course of Early Psychosis and Specialty Services (BICEPS)

> **NIH NIH R01** · YALE UNIVERSITY · 2023 · $321,767

## 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
We predict that the EP population
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.
Biotypes identified by B-SNIP for symptomatic and functional outcome. will
manifest distinct outcome clinical trajectories (good, intermediate and poor) and will have a
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:** 10683286
- **Project number:** 5R01MH127158-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** GODFREY D PEARLSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $321,767
- **Award type:** 5
- **Project period:** 2022-08-15 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10683286

## Citation

> US National Institutes of Health, RePORTER application 10683286, 3/5 Biomarkers/Biotypes, Course of Early Psychosis and Specialty Services (BICEPS) (5R01MH127158-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10683286. Licensed CC0.

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