We are submitting Integrated Multiscale Networks in Schizophrenia in response to RFA-MH-16-300. Schizophrenia (SCZ) is a generally devastating neuropsychiatric illness with considerable morbidity, mortality, and personal and societal cost. Genetic factors have been strongly implicated via family and twin data, and more recently directly through genome-wide association studies (GWAS) and sequencing studies. The primary objective of our project is to develop and apply advanced integrative methods for computational and functional analysis of networks, including but not limited to Bayesian network reconstruction and prediction algorithms of variant causality to identify key drivers of SCZ pathology for potential therapeutic intervention. To achieve this in Aim 1 we will construct single tissue and multi- tissue probabilistic causal network by applying a novel top-down and bottom-up or hypothesis-driven probabilistic causal network approaches in RNA sequencing key drivers of networks, novel pathways, and new mechanisms in SCZ pathology data from the CommonMind consortium, incorporating prior information.
In Aim 2 we will use network models derived in Aim 1 in order to improve the predictive SCZ networks that could be used to identify SCZ-relevant transcription-based features that can be useful in therapeutic screening. Finally, in Aim 3 we will use modified RNA and cellular models to validate the network models, key drivers and investigate their phenotype effects.

Public Health Relevance

In the United States, over a million people have schizophrenia. The costs are staggering in human and financial terms. We propose to develop methods for integrating a broad range of genomic data into a novel, flexible and extensible computing platform. We will develop integrated networks that cover many aspects of disease biology in order to understand what the key pathways are and develop knowledge of how best to change them to healthy networks.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH109897-03
Application #
9455794
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Arguello, Alexander
Project Start
2016-05-01
Project End
2021-02-28
Budget Start
2018-03-12
Budget End
2019-02-28
Support Year
3
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Psychiatry
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
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