Loading...

Login
Reset Password

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.

Warning Notice

This is a U.S. Government computer system, which may be accessed and used only for authorized Government business by authorized personnel. Unauthorized access or use of this computer system may subject violators to criminal, civil, and/or administrative action. All information on this computer system may be intercepted, recorded, read, copied, and disclosed by and to authorized personnel for official purposes, including criminal investigations. Such information includes sensitive data encrypted to comply with confidentiality and privacy requirements. Access or use of this computer system by any person, whether authorized or unauthorized, constitutes consent to these terms. There is no right of privacy in this system.

You have logged in with a temporary password. Please update your password. Passwords must contain 8 or more characters and must contain at least 3 of the following types of characters:

Subscribe to our mailing list

Mailing List(s)
Email Format

You are now leaving the National Database for Autism Research (NDAR) web site to go to:

Click on the address above if the page does not change within 10 seconds.

Disclaimer

NDAR is not responsible for the content of this external site and does not monitor other web sites for accuracy.

Accept Terms
Selected Filters
No filters selected

The filters you have selected from various query interfaces will be stored here, in the 'Filter Cart'. The database will be queried using filters added to your 'Filter Cart', when multiple filters are defined, each will be executed using 'AND' logic, so with each filter that is applied the result set gets smaller.

From the 'Filter Cart' you can inspect each of the filters that have been defined, and you also have the option to remove filters. The 'Filter Cart' itself will display the number of filters applied along with the number of subjects that are identified by the combination of those filters. For example a GUID filter with two subjects, followed by a GUID filter for just one of those subjects would return only data for the subject that is in both GUID filters.

If you have a question about the filter cart, or underlying filters please contact the help desk at The NDA Help Desk

Description
Value Range
Notes
Data Structures with shared data
No filters have been selected
Switch User

1 Numbers reported are subjects by age
New Trial
New Project

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

Please select an experiment type below

help.associateExperiment
help.associateExperiment
SelectExperiment IdExperiment NameExperiment Type
  • Select One
  • EEG
  • EGG
  • Eye Tracking
  • Omics
  • fMRI
Created On
911Resting StatefMRI04/20/2018
910Modified Monetary Incentive Delay fMRI04/20/2018
908Resting State Pre-Stress Visit 1fMRI04/20/2018
907Montreal Imaging Stress Task Visit 1fMRI04/18/2018
9062-back Post-Stress Visit 1fMRI04/18/2018
9051-back Post-Stress Visit 1fMRI04/18/2018
9040-back Post-Stress Visit 1fMRI04/18/2018
9032-back Pre-Stress Visit 1fMRI04/18/2018
9021-back Pre-Stress Visit 1fMRI04/18/2018
9010-back Pre-Stress Visit 1fMRI04/18/2018
900DTIfMRI04/11/2018
899Investigating a Neurobehavioral Mechanism of Paranoia - Resting State ScansfMRI04/06/2018
898FAST-POMAfMRI04/03/2018
897parvizi_eeg_109EEG03/19/2018
896parvizi_eeg_107EEG03/19/2018
895parvizi_eeg_106EEG03/19/2018
894Dot ProbeEye Tracking03/07/2018
893Startle Habituation and Shock Sensitivity EvaluationEEG03/03/2018
892NPU EEG Task EEG03/03/2018
891Duke ACE ETEye Tracking03/02/2018
888Emotion 1.1 Determining context effects during potential threatfMRI02/26/2018
886RestfMRI02/14/2018
885SARTfMRI02/14/2018
884Plasma metabolic profileOmics02/05/2018
878Social Challenge AssessmentEye Tracking01/26/2018
877PRV-005-EEGEEG01/22/2018
876Mixed Anti and Pro (vgs) saccade mixed blocked (EyeTracking)Eye Tracking01/22/2018
875Attention modulation taskEye Tracking01/17/2018
874ruthldopa resting 17 and 18fMRI01/16/2018
873ruthldopa resting 15 and 16fMRI01/16/2018
872ruthldopa resting 13 and 14fMRI01/16/2018
871ruthldopa resting 11 and 12fMRI01/16/2018
870Resting State fMRIfMRI01/12/2018
869cyberballfMRI01/12/2018
868MDD_PilotfMRI01/12/2018
867Velten Mood Induction State-ItemfMRI01/12/2018
866Emotional Hemifield Task (EHT)EEG01/12/2018
865Genome EditingOmics01/12/2018
864parvizi_eeg_118EEG01/12/2018
863parvizi_eeg_117EEG01/12/2018
862parvizi_eeg_116EEG01/12/2018
861parvizi_eeg_115EEG01/12/2018
860parvizi_eeg_114EEG01/12/2018
859parvizi_eeg_113EEG01/12/2018
858PRV-003-EEGEEG01/12/2018
857PRV-004-EEGEEG01/12/2018
856PRV-007-EEGEEG01/12/2018
855Regulating Emotional Responses to Visual Images Across the Affective Instability SpectrumfMRI01/12/2018
854PRV-002-EEGEEG01/12/2018
853R61 Ezogabine Resting State FMRIfMRI01/11/2018
Collection - Add Experiment
Add Supporting Documentation
Select File

Please enter the name of the data structure to search or if your definition does not exist, please upload that definition so that it can be appropriately defined for submission. Multiple data structures may be associated with a single Data Expected entry. Please add only one data structure per assessment.

submission.dialog.title

submission.exemption.missing.data.header
submission.exemption.missing.data

submission.exemption.analyzed.data.header
submission.exemption.analyzed.data

submission.dialog.c.confirm
submission.type.c.confirm

submission.dialog.c.error
submission.c.error

You have requested to move the sharing dates for the following assessments:
Data Expected Item Original Sharing Date New Sharing Date

Please provide a reason for this change, which will be sent to the Program Officers listed within this collection:

Explanation must be between 20 and 200 bytes in length.

Please press Save or Cancel
communication.email.address.dialog.header
communication.email.address
Shared

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

General

Title, investigators, and Collection Description may be edited along with the Collection Phase. For Collection Phase, the options Pre-enrollment, Enrollment, and Completed can be chosen allowing the Collection Owner to indicate the stage of data collection.

Funding Source

The ability to associate the funding source for the project is provided. For NIH funded grants, linkage to Project Reporter information (e.g. R01MH123456) is supported. Projects funded by others, including the URL of the project, are listed. Non NIH funded projects will become available here to link that data with the appropriate funding agency.

Supporting Documentation

Any documents related to the project may be uploaded clarifying the data or acquisition methods used may be uploaded and made available here. The default is to share these documents to the general public. An option to share only to qualified Researchers is also an option.

Clinical Trials

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
Deep sequencing of autism candidate genes in 2000 families from the Simons Simplex Collection (SSC)
Michael Wigler 
343 families from the Simons Simplex Collection. Each family includes father, mother, a proband and an unaffected sibling.
NDAR
Funding Completed
Shared
$2,779,842.00
4,558
0
0
Loading Chart...
NIH - Extramural None

sequencing_files_readme_col_1936.pdf Background Readme for sequencing files Qualified Researchers

RC2MH090028-01 Deep sequencing of autism candidate genes in 2000 families from the Simons Simple 09/30/2009 08/31/2011 Not Reported Not Reported COLD SPRING HARBOR LABORATORY $2,779,842.00

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
66SSC samples exome sequencing08/03/2012ApprovedOmics
170Whole genome sequencing of 8 SSC samples10/22/2014ApprovedOmics

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 4651
Genomics Subject Genomics 4645
Research Subject Clinical Assessments 1360

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

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
22542183Study (318)De novo gene disruptions in children on the autistic spectrum.NeuronIossifov I, Ronemus M, Levy D, Wang Z, Hakker I, Rosenbaum J, Yamrom B, Lee YH, Narzisi G, Leotta A, Kendall J, Grabowska E, Ma B, Marks S, Rodgers L, Stepansky A, Troge J, Andrews P, Bekritsky M, Pradhan K, Ghiban E, Kramer M, Parla J, Demeter R, Fulton LL, et al.April 26, 2012Relevant
help.tab.dataexpected

Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.
help.tab.dataexpected.addnew
Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Research Subject and Pedigree info iconApproved
genomics/omics info iconApproved
Structure not yet defined

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

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 NameAbstractCollection/Study SubjectsData UsageState
Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk LociAnalysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1).4111/9975Secondary AnalysisShared
The contribution of de novo coding mutations to autism spectrum disorderWhole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females. PLEASE NOTE: Additional data on these subjects, unrelated to this publication exist in other NDAR Studies. These data include realigned BAM files, unfiltered SNV/InDel variant calls (made by GATK and FreeBayes), and CNVs. Please see this news item for more details: https://ndar.nih.gov/ndarpublicweb/aboutNDAR.html#news_item_201 4558/9456Secondary AnalysisShared
Recurrent de novo mutations implicate novel genes underlying simplex autism risk.Autism spectrum disorder (ASD) has a strong but complex genetic component. Here we report on the resequencing of 64 candidate neurodevelopmental disorder risk genes in 5,979 individuals: 3,486 probands and 2,493 unaffected siblings. We find a strong burden of de novo point mutations for these genes and specifically implicate nine genes. These include CHD2 and SYNGAP1, genes previously reported in related disorders, and novel genes TRIP12 and PAX5. We also show that mutation carriers generally have lower IQs and enrichment for seizures. These data begin to distinguish genetically distinct subtypes of autism important for aetiological classification and future therapeutics.1888/6400Primary AnalysisShared
The evolution and population diversity of human-specific segmental duplicationsSegmental duplications contribute to human evolution, adaptation and genomic instability but are often poorly characterized. We investigate the evolution, genetic variation and coding potential of human-specific segmental duplications (HSDs). We identify 218 HSDs based on analysis of 322 deeply sequenced archaic and contemporary hominid genomes. We sequence 550 human and nonhuman primate genomic clones to reconstruct the evolution of the largest, most complex regions with protein-coding potential (n=80 genes/33 gene families). We show that HSDs are non-randomly organized, associate preferentially with ancestral ape duplications termed “core duplicons”, and evolved primarily in an interspersed inverted orientation. In addition to Homo sapiens-specific gene expansions (e.g., TCAF1/2), we highlight ten gene families (e.g., ARHGAP11B and SRGAP2C) where copy number never returns to the ancestral state, there is evidence of mRNA splicing, and no common gene-disruptive mutations are observed in the general population. Such duplicates are candidates for the evolution of human-specific adaptive traits. 743/6360Primary AnalysisShared
Mitochondrial DNA mutations in Autism Spectrum DisorderMitochondrial dysfunction is frequently observed in Autism Spectrum Disorders (ASD). Thus, variations in the mitochondrial DNA (mtDNA) sequences may contribute to increased ASD risks. In the current study, we evaluated mtDNA variations, including homoplasmy and heteroplasmy, in 903 ASD individuals along with their mothers and non-ASD siblings by using off-target reads from whole-exome sequencing data sets of Simons Foundation Autism Research Initiative (SFARI) Simons Collection available on NDAR. We found that heteroplasmic mutations in ASD individuals were enriched at non-polymorphic mtDNA sites (P = 0.0015) compared to their non-ASD siblings, which were more likely to confer deleterious effects than heteroplasmies at polymorphic mtDNA sites. Accordingly, we observed a ~1.5-fold enrichment of nonsynonymous mutations as well as a ~2.2-fold enrichment of predicted pathogenic mutations (P < 0.003) in ASD individuals compared to their non-ASD siblings. Our genetic findings substantiate pathogenic mtDNA mutations as a potential cause for ASD and synergize with recent work calling attention to their unique metabolic phenotypes for diagnosis and treatment of ASD.2709/2709Secondary AnalysisShared
Transmission disequilibrium of small CNVs in simplex autism.Cohorts: 411 ASD Quads from Simons Simplex Collection 177 Quads from Sanders et al. (PubMed ID: 22495306) 166 Quads from I. Iossifov et al. (PubMed ID: 22542183) 71 Quads from O'Roak et al. (PubMed ID: 22495309) Publication Abstract: We searched for disruptive, genic rare copy-number variants (CNVs) among 411 families affected by sporadic autism spectrum disorder (ASD) from the Simons Simplex Collection by using available exome sequence data and CoNIFER (Copy Number Inference from Exome Reads). Compared to high-density SNP microarrays, our approach yielded ¿2× more smaller genic rare CNVs. We found that affected probands inherited more CNVs than did their siblings (453 versus 394, p = 0.004; odds ratio [OR] = 1.19) and that the probands' CNVs affected more genes (921 versus 726, p = 0.02; OR = 1.30). These smaller CNVs (median size 18 kb) were transmitted preferentially from the mother (136 maternal versus 100 paternal, p = 0.02), although this bias occurred irrespective of affected status. The excess burden of inherited CNVs among probands was driven primarily by sibling pairs with discordant social-behavior phenotypes (p < 0.0002, measured by Social Responsiveness Scale [SRS] score), which contrasts with families where the phenotypes were more closely matched or less extreme (p > 0.5). Finally, we found enrichment of brain-expressed genes unique to probands, especially in the SRS-discordant group (p = 0.0035). In a combined model, our inherited CNVs, de novo CNVs, and de novo single-nucleotide variants all independently contributed to the risk of autism (p < 0.05). Taken together, these results suggest that small transmitted rare CNVs play a role in the etiology of simplex autism. Importantly, the small size of these variants aids in the identification of specific genes as additional risk factors associated with ASD. 462/1644Secondary AnalysisShared
De Novo Gene Disruptions in Children on the Autistic SpectrumPublic Abstract: Exome sequencing of 343 families, each with a single child on the autism spectrum and at least one unaffected sibling, reveal de novo small indels and point substitutions, which come mostly from the paternal line in an age-dependent manner. We do not see significantly greater numbers of de novo missense mutations in affected versus unaffected children, but gene-disrupting mutations (nonsense, splice site, and frame shifts) are twice as frequent, 59 to 28. Based on this differential and the number of recurrent and total targets of gene disruption found in our and similar studies, we estimate between 350 and 400 autism susceptibility genes. Many of the disrupted genes in these studies are associated with the fragile X protein, FMRP, reinforcing links between autism and synaptic plasticity. We find FMRP-associated genes are under greater purifying selection than the remainder of genes and suggest they are especially dosage-sensitive targets of cognitive disorders.1372/1372Primary AnalysisShared
* Data not on individual level
Return
Edit