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NDAR provides a single access to de-identified autism research data. For permission to download data, you will need an NDAR account with approved access to NDAR or a connected repository (AGRE, IAN, or the ATP). For NDAR access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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Format should be in the following format: Activity Code, Institute Abbreviation, and Serial Number. Grant Type, Support Year, and Suffix should be excluded. For example, grant 1R01MH123456-01A1 should be entered R01MH123456

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Shared

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General

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For clinical trials, the option to link to the clinical trial in clinicaltrials.gov is optionally provided.

Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Rapid Phenotyping for Rare Variant Discovery in Autism
Stanley Nelson 
The project proposed here is to use the combined power of web based recruiting, web-implemented and validated phenotypic measurements, and distributed blood collection to establish a cost-effective recruitment of affected children with ASD. Based on our preliminary analysis where we assessed the accuracy of a web-based approach to autism phenotyping implemented within the Interactive Autism Network (IAN), we have set up a protocol in IAN to recruit from already registered and newly registered families, consent them electronically and instruct them for blood collection at one of the 1,600 contracted blood draw sites near their home. This recruitment procedure is already initiated in collaboration with IAN and we expect that the planned recruitment of 1,000 families per year will be readily met in the first three year of the funding period. Throughout the recruitment process, we will carefully monitor the IAN population to ensure that there is no significant phenotype shifts observed. At the same time, we will also perform targeted sequencing on a subset of the collected samples to search for rare risk variants and rare CNVs within a gene set that is enriched for genes associated with autism from previous studies. Although the sample size proposed here is still not large enough to detect all rare risk variants, this additional genetic information will be used to validate genetic findings associated with autism. We would hope to eventually establish an environment in which all affected childrens genetic makeup is known, relative to a comprehensive set of genetic risk factors, so that deeper phenotypic efforts can be applied to individuals with known genetic risk factors. All of the samples collected and the sequence data will be shared with other investigators, substantially increasing the sample size available for autism genetic studies.
NDAR
Enrolling
Shared
$3,051,030.00
3,598
4800
2693
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NIH - Extramural None


R01NS073871-01 Rapid Phenotyping for Rare Variant Discovery in Autism 09/01/2011 08/31/2016 4800 2693 UNIVERSITY OF CALIFORNIA LOS ANGELES $3,051,030.00

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Experiments

To create a new Omics, eye tracking, fMRI, or EEG experiment, press the "+ New Experiment" button. Once an experiment is created, then raw files for these types of experiments should be provided, associating the experiment – through Experiment_ID – with the metadata defined in the experiments interface.

IDNameCreated DateStatusType
90Genotyped IAN Samples07/09/2013ApprovedOmics

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Shared Data

Data structures with the number of subjects submitted and shared are provided.

Genomics Sample Genomics 208
Genomics Subject Genomics 208
Research Subject Clinical Assessments 3294

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Publications

Publications relevant to NDAR data are listed below. Most displayed publications have been associated with the grant within Pubmed. Use the "+ New Publication" button to add new publications. Publications relevant/not relevant to data expected are categorized. Relevant publications are then linked to the underlying data by selecting the Create Study link. Study provides the ability to define cohorts, assign subjects, define outcome measures and lists the study type, data analysis and results. Analyzed data and results are expected in this way.

PubMed IDStudyTitleJournalAuthorsDateStatus
24808022Create StudyPDE5 inhibition alleviates functional muscle ischemia in boys with Duchenne muscular dystrophy.NeurologyNelson MD, Rader F, Tang X, Tavyev J, Nelson SF, Miceli MC, Elashoff RM, Sweeney HL, Victor RGJune 10, 2014Not Relevant
24501278Create StudyExome sequencing identifies de novo gain of function missense mutation in KCND2 in identical twins with autism and seizures that slows potassium channel inactivation.Human molecular geneticsLee H, Lin MC, Kornblum HI, Papazian DM, Nelson SFJuly 1, 2014Not Determined
22371046Create StudyAutism recurrence in half siblings: strong support for genetic mechanisms of transmission in ASD.Molecular psychiatryConstantino JN, Todorov A, Hilton C, Law P, Zhang Y, Molloy E, Fitzgerald R, Geschwind DFebruary 2013Not Determined
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Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.
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Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Research Subject and Pedigree info iconApproved
genomics/omics info iconApproved
Structure not yet defined

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Associated Studies

Studies that have been defined using data from a Collection are important criteria to determine the value of data shared. The number of subjects column displays the counts from this Collection that are included in a Study, out of the total number of subjects in that study. The Data Use column represents whether or not the study is a primary analysis of the data or a secondary analysis. State indicates whether the study is private or shared with the research community.

Study Name Description Number of Subjects
Collection / Total
Data Use State
Rare Inherited and De Novo CNVs Reveal Complex Contributions to ASD Risk in Multiplex families NOTE: NOT ALL DATA HAS BEEN UPLOADED FOR THIS STUDY. Rare mutations, including copy-number variants (CNVs), contribute significantly to autism spectrum disorder (ASD) risk. Although their importance has been established in families with only one affected child (simplex families), the contribution of both de novo and inherited CNVs to ASD in families with multiple affected individuals (multiplex families) is less well understood. We analyzed 1,532 families from the Autism Genetic Resource Exchange (AGRE) to assess the impact of de novo and rare CNVs on ASD risk in multiplex families. We observed a higher burden of large, rare CNVs, including inherited events, in individuals with ASD than in their unaffected siblings (odds ratio [OR] = 1.7), but the rate of de novo events was significantly lower than in simplex families. In previously characterized ASD risk loci, we identified 49 CNVs, comprising 24 inherited events, 19 de novo events, and 6 events of unknown inheritance, a significant enrichment in affected versus control individuals (OR = 3.3). In 21 of the 30 families (71%) in whom at least one affected sibling harbored an established ASD major risk CNV, including five families harboring inherited CNVs, the CNV was not shared by all affected siblings, indicating that other risk factors are contributing. We also identified a rare risk locus for ASD and language delay at chromosomal region 2q24 (implicating NR4A2) and another lower-penetrance locus involving inherited deletions and duplications of WWOX. The genetic architecture in multiplex families differs from that in simplex families and is complex, warranting more complete genetic characterization of larger multiplex ASD cohorts. 7 / 5288 Primary Analysis Shared
* Data not on individual level
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