# From Manic Symptoms to Bipolar Disorder: Neural-behavioral Markers Using Two Analytic Models

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $741,587

## Abstract

PROJECT SUMMARY
Bipolar disorder (BD) is a devastating neuropsychiatric illness that affects 2-5% of youth and causes morbidity,
functional impairment, and suicide. Prodromal manic symptoms without manic episodes usually emerge before
BD types I and II (BD-I/II) develop, but less than 60% of youth with manic symptoms will develop BD-I/II. The
uncertainty of diagnosis and illness progression results in potentially detrimental interventions and 7-10 years
delay appropriate treatments. It is thus imperative that objective biomarkers of risk for conversion to BD-I/II are
identified and tested in youth before the peak onset of illness. Given that neural measures of structure and
function associated with emotion and reward processing, in combination with clinical and behavior measures,
can improve prediction of psychiatric outcomes in youth, this project will investigate brain-behavior relations in
the most severely ill youth during inpatient stays and aims to build a predictive model of BD. We aim to use two
distinct analytic models to test our hypotheses. First a general linear model (GLM) with a machine learning (ML)
model of regularized regression with cross validation and second a whole brain ML pattern recognition model.
We will first identify neural and behavioral markers of BD-I/II in circuitry associated with emotion and reward
processing. We hypothesize that decreased activity and connectivity in prefrontal, amygdala, and striatal regions
and behavioral measures showing less sleep, lower activity, and poorer mood and cognition will distinguish BD-
I/II from clinically matched youth without mania and healthy. Next, we will identify using ML a whole brain neural
classifier of BD-I/II relative to clinically matched inpatients without mania. Aim 2 is to, after two years, identify
and quantify the neural and behavioral measures that predict conversion to BD-I/II, and to test individual
conversion in an independent group of high symptomatic risk adolescents. Aim 3 is to identify brain-behavior
associations for app development. Training samples include mid-/post- pubertal adolescents aged 13-17 years
recruited from the nation’s only specialized inpatient unit for adolescents with BD and the general adolescent
unit at our hospital; 70 well-characterized adolescents with BD-I/II, a clinically matched group of 70 inpatient
youth without mania. Testing sample is an independent group of 180 adolescents with manic symptoms without
BD-I/II. 60 healthy controls will be recruited. The project includes emotion and reward processing neural function
and structure, clinical and behavioral measures including sleep and activity with actigraphy, computerized
cognitive measures, and self-reports during inpatient evaluation and for two weeks post discharge. At two-year
follow up, clinical assessments will confirm diagnoses. This is the first study to employ a multimodal assessment
of behavior and mood symptoms combined with multimodal imaging methods to comprehensive...

## Key facts

- **NIH application ID:** 9860596
- **Project number:** 1R01MH121451-01
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Michele A Bertocci
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $741,587
- **Award type:** 1
- **Project period:** 2020-03-01 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9860596

## Citation

> US National Institutes of Health, RePORTER application 9860596, From Manic Symptoms to Bipolar Disorder: Neural-behavioral Markers Using Two Analytic Models (1R01MH121451-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9860596. Licensed CC0.

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