Strategic Plan Objective Detail
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Question 3: Long-term Objective B  

$49,905,587.13
Fiscal Year: 2009

Green dot: Objective has greater than or equal to the recommended funding.3LB. Identify genetic risk factors in at least 50% of people with ASD by 2014. IACC Recommended Budget: $33,900,000 over 6 years.

Download 2009 Question 3: Long-term Objective B projects (EXCEL)
Note: Initial Sort is by Principal Investigator. Sorting by other columns is available by clicking on the desired column header.
Project Title Principal Investigator Institution
Identifying autism susceptibility genes by high-throughput chip resequencing Zwick, Michael Emory University
Comprehensive genetic variation detection to assess the role of the X chromosome in autism Warren, Stephen Emory University
Simons Simplex Collection Site Ledbetter, David Emory University
Dense mapping of candidate regions linked to autistic disorder Gregersen, Peter Feinstein Institute for Medical Research
Research Center for the Study of Gene Structure and Function (supplement) Raab, Jennifer Hunter College
Illumina, Inc. No PI listed Illumina, Inc.
Understanding glutamate signaling defects in autism spectrum disorders Wang, Tao Johns Hopkins University
Integrative genetic analysis of autistic brains Arking, Dan Johns Hopkins University School of Medicine
The role of contactin-associated protein-like 2 (CNTNAP2) and other novel genes in autism Chakravarti, Aravinda Johns Hopkins University School of Medicine
Investigation of genes involved in synaptic plasticity in Iranian families with ASD Santangelo, Susan Massachusetts General Hospital
Comprehensive follow-up of novel autism genetic discoveries Daly, Mark Massachusetts General Hospital
A recurrent genetic cause of autism Gusella, James Massachusetts General Hospital
Genes disrupted by balanced genomic rearrangements in autism spectrum disorders Gusella, James Massachusetts General Hospital
Role of TSC/mTOR signaling pathway in autism and autism spectrum disorders Ramesh, Vijaya Massachusetts General Hospital
Genome-wide analyses of DNA methylation in autism Chess, Andrew Massachusetts General Hospital
The role of the neurexin 1 gene in susceptibility to autism Gusella, James Massachusetts General Hospital/Harvard Medical School
Autism Genome Project Buxbaum, Joseph Mount Sinai School of Medicine
Computational tools to analyze SNP data from patients with mental illness Downey, Thomas Partek, Inc.
Autism and SNPs in the IGF pathway Levine, Arnold Princeton University
Identification of aberrantly methylated genes in autism: The role of advanced paternal age Gingrich, Jay Research Foundation for Mental Hygiene, Inc.
Rutgers, The State University of New Jersey Contract Rutgers, The State University of New Jersey
Identification and functional assessment of autism susceptibility genes Brzustowicz, Linda Rutgers, The State University of New Jersey - New Brunswick
Behavioral and genetic biomarker development for autism and related disorders Brzustowicz, Linda Rutgers, The State University of New Jersey - New Brunswick
The impact of autism specific genomic variations on microRNA gene expression profile Scherer, Stephen The Hospital for Sick Children
Identification and functional assessment of autism susceptibility genes Vieland, Veronica The Research Institute at Nationwide Children's Hospital

Objective Cumulative Funding Table

IACC Strategic Plan Objective 2008 2009 2010 2011 2012 Total
Identify genetic risk factors in at least 50% of people with ASD by 2014.

IACC Recommended Budget: $33,900,000 over 6 years
3.8
$37,043,410
83 projects

3.L.B
$49,905,587
79 projects

3.L.B
$34,432,884
60 projects

3.L.B
$25,383,346
59 projects

3.L.B
$23,041,231
74 projects

$169,806,458
3.L.B. Funding: The recommended budget was met. Significantly more than the recommended minimum budget was allocated to projects specific to this objective.

Progress: Further work is needed to identify genetic risk factors in at least 50% of people. Currently, whole exome analysis predicts that a genetic risk factor can be identified for 20% of people; inclusion of CNV data might push this toward 30%.

Remaining Gaps, Needs, and Opportunities: The initial budget recommendation for this objective was made based on the assumption that GWAS studies would provide risk factor identification, but sequencing has proven more fruitful. Since this technique is more expensive, a higher budget will be required to meet the goal of 50%.