# Molecular Profiling of Schizophrenia

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $1,389,214

## Abstract

Project Summary
Complex diseases such as schizophrenia (SCZ) result from multifactorial genetic and environmental
perturbations that cause pleiotropic changes in molecular networks, resulting in disease. The goal of our
project is to move our CommonMind Consortium (CMC) data generation to the next level, focusing on cell-type
specific data generation including transcriptomics, epigenomics, proteomics, and integrated analyses, from
critical regions implicated in SCZ to improve our ability to identify and refine genetic risk factors for SCZ. We
will characterize cell-type specific transcriptome and epigenome components in our post-mortem CMC SCZ
and control cohort and in new control autopsy specimens. In 50 SCZ cases and 50 controls from the CMC, we
will 1.) perform RNA, sequencing, 2.) ATACseq, and 3.) Hi-C in nuclei isolated from pools of glutamatergic
neurons, GABAergic neurons, and oligodendrocytes isolated from the prefrontal cortex. In the same samples
we characterize proteins of post-synaptic density proteins by liquid chromatography (LC)-selective reaction
monitoring (SRM)-mass spectrometer (MS) quantitative proteomic analyses. In order to uncover how many
distinct types of cells are present in various brain regions of control individuals we will use nanofluidics and
bar-coding (Drop-seq) from freshly autopsied, never frozen or fixed control specimens. Integrative analyses will
be pursued that will combine genetic, gene expression, epigenomic and proteomic data to identify novel SCZ
genes. Finally, we will continue to maintain and upgrade our community workspace that provides for the rapid
dissemination and open evaluation of data, analyses, and outcomes derived from the CMC. We will continue to
make all data available to the research community through the Sage Bionetworks Synapse Platform. There is a
deep need to more cell-type specific information on the transcriptional and epigenetic landscape in the human
brain, and in particular in neurons and glia and to integrate this information with human SCZ genetics. We have
assembled the critical key personnel, sample resources, technological know-how, and analytic strategies to be
able to provide both useful maps for the field, as well as begin to unravel SCZ biology.

## Key facts

- **NIH application ID:** 9847993
- **Project number:** 5R01MH110921-04
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Andrew J Chess
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,389,214
- **Award type:** 5
- **Project period:** 2016-09-07 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9847993

## Citation

> US National Institutes of Health, RePORTER application 9847993, Molecular Profiling of Schizophrenia (5R01MH110921-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9847993. Licensed CC0.

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