ARRA Investments in Genetics of Mental Disorders
Public Health Burden
Mental disorders affect most of us over the course of a lifetime and rank high among causes of disability. Genes exert a significant influence on risk for disorders such as autism, schizophrenia, and bipolar disorder. Studies are revealing a complex interplay of genetic and environmental contributions. A disorder might result from the interaction of combined, small effects of many different genetic variations, diverse single gene mutations and/or experience-triggered chemical modification of gene expression. Advances in genetic research afford an unprecedented opportunity to define how genes confer risk, potentially yielding new diagnostic and therapeutic targets.
Researchers are making great strides in profiling the genome of mental disorders. Using robots that perform high throughput genetic screening, sequencing, and other advanced technologies, they are pinpointing molecules that confer risk. ARRA genomics projects will:
Collect and analyze the first whole-genome sequence data from a large sample of patients with schizophrenia and bipolar disorder, laying a foundation for future genetic research on these disorders.
Genetically screen for activators of a protein that is associated with resilience to deleterious effects of chronic stress and shows therapeutic promise for depression.
Genetically engineer an animal model of depression that mirrors human features of the disorder. The model will help identify molecular targets for treatment.
Explore how a specific genetic risk factor for schizophrenia influences neuron function; this project will generate a novel cell line derived from individuals with the disorder.
Genomics Resources and Infrastructure
To make the most of burgeoning genetics information, data sharing infrastructure is being created for the research community. These ARRA projects will:
Create a web-based atlas of gene expression patterns in the developing human brain that will help to pinpoint activity of gene variants that may contribute to mental disorders. It will show which genes are expressed in particular brain regions at specific time points.
Assemble behavioral, cognitive, emotional, and genomic profiles of 10,000 children and adolescents to create a dataset to serve as a resource for investigating the contributions of genes to aspects of brain function, and ultimately, health and disease.
Genetic Biomarkers for Disease
Biomarkers, like cholesterol levels for heart disease, can predict risk for a disorder and guide diagnosis and treatment. These can include mutations or other variations in genes, transcripts, and proteins. ARRA initiatives seeking such genetic biomarkers related to mental illness will:
Identify and validate inherited aspects of specific behaviors, such as language disability, that signal genetic risk for autism.
Study cellular abnormalities in DiGeorge syndrome to reveal potential biomarkers and identify targets for improving treatments for this and other schizophrenia-related disorders.
Epigenetic mechanisms – ways that the environment influences genes to control their function –likely play a key role in mental illnesses. Evidence suggests that this complex interplay between genes and the environment changes over the lifespan. To improve identification of the genetic and environmental factors associated with mental illness, ARRA projects will:
Examine the heritability of chemical modifications to the genome associated with schizophrenia and how these changes relate to cognitive deficits in people with schizophrenia and their families.
Conduct a genome-wide analysis of biochemical factors that influence autism-associated genes to control their function, in boys with autism and their families.
-- Whole genome sequencing of bipolar disorder and schizophrenia -- Sklar, Pamela
, Compound Screening, Nestler, Eric J
-- Modeling Core Behavioral, Neuroendocrine and Molecular Features of Depression -- Sibille, Etienne L
-- iPS Cell-Derived Neurons Carrying an allelic series of CNTNAP2 structural mutations -- Karayiorgou, Maria
Transcriptional Atlas of Human Brain Development -- Knowles, James A (contact); Levitt, Pat R; Fischl, Bruce; Geschwind, Daniel H; Hawrylycz, Michael; Lein, Ed; Sestan, Nenad
- Hakonarson, Hakon (PA)
-- Behavioral and Genetic Biomarker Development for Autism and Related Disorders -- Brzustowicz, Linda M
-- Schizophrenia biomarkers discerned by cellular networks in DiGeorge syndrome -- Pearce, Bradley D
-- Family-based Genome-wide Methylation Scan in Schizophrenia -- Feinberg, Andrew; Gur Raquel R; Nimgaonkar, Vishwajit Laxmikant; Perry, Rodney T; Braff, David L
-- Epigenetic Marks as Peripheral Biomarkers of Autism -- Warren, Stephen T.
Page Last Updated on June 30, 2018
Turning Discovery Into Health