# Discovery and analysis of brain circuits and cell types affected in autism and schizophrenia

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $752,885

## Abstract

PROJECT SUMMARY
There is now unequivocal evidence that the behavioral and cognitive phenotypes associated with
psychiatric disorders are mediated by perturbations to specific brain circuits, i.e. sets of strongly
anatomically and functionally connected brain structures. However, there are currently no
unbiased computational approaches to implicate disease-related circuits, in a brain-wide fashion
and at a high spatial resolution, and then to connect abnormalities in these circuits to specific
patient phenotypes. The main goal of the proposal is to develop and optimize a computational
approach which will make it possible, for the first time and at an unprecedented resolution, to
discover functional brain circuits involved in mental disorders. The proposed approach is based
on synergistic analyses of genetics data, ultra-high-resolution expression and brain-wide
connectome data – available for the same mouse strain, and in a common coordinate system. An
important virtue of the approach is that it is based exclusively on genome- and brain-wide data
and therefore is not biased towards any prior hypothesis about disorders' etiology. We specifically
propose Aim 1. Identify brain circuits and associated cell types primarily affected by genetic
insults in autism spectrum disorder (ASD) and schizophrenia (SCZ). We will develop data-driven
computational approaches to identify genetic biases towards anatomically connected functional
brain circuits. Aim 2. Experimentally test the identified circuits in several mouse models of ASD
and SCZ. Functional circuits identified by the computational approach will be tested using two
independent mouse models of ASD and two models of SCZ. The dynamics of the circuits will be
explored using multi-site photometric imaging. Aim 3. Correlate mutation biases towards brain
regions, circuits, and cell types with specific ASD phenotypes. Using extensive and deep
phenotypic human data together with genetic data from the same patient cohorts, we will
correlate mutation biases towards brain cell types and circuits with multiple specific ASD
phenotypes.

## Key facts

- **NIH application ID:** 10897914
- **Project number:** 5R01MH124923-05
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** JOSEPH A GOGOS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $752,885
- **Award type:** 5
- **Project period:** 2020-09-15 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10897914

## Citation

> US National Institutes of Health, RePORTER application 10897914, Discovery and analysis of brain circuits and cell types affected in autism and schizophrenia (5R01MH124923-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10897914. Licensed CC0.

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