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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

Collection - Use Existing Experiment
To associate an experiment to the current collection, just select an axperiment from the table below then click the associate experiment button to persist your changes (saving the collection is not required). Note that once an experiment has been associated to two or more collections, the experiment will not longer be editable.

The table search feature is case insensitive and targets the experiment id, experiment name and experiment type columns. The experiment id is searched only when the search term entered is a number, and filtered using a startsWith comparison. When the search term is not numeric the experiment name is used to filter the results.
SelectExperiment IdExperiment NameExperiment Type
Created On
490Illumina Infinium PsychArray BeadChip AssayOmics07/07/2016
501PharmacoBOLD Resting StatefMRI07/27/2016
509ABC-CT Resting v2EEG08/18/2016
13Comparison of FI expression in Autistic and Neurotypical Homo SapiensOmics12/28/2010
18AGRE/Broad Affymetrix 5.0 Genotype ExperimentOmics01/06/2011
22Stitching PCR SequencingOmics02/14/2011
29Microarray family 03 (father, mother, sibling)Omics03/24/2011
37Standard paired-end sequencing of BCRsOmics04/19/2011
38Illumina Mate-Pair BCR sequencingOmics04/19/2011
39Custom Jumping LibrariesOmics04/19/2011
40Custom CapBPOmics04/19/2011
43Autism brain sample genotyping, IlluminaOmics05/16/2011
47ARRA Autism Sequencing Collaboration at Baylor. SOLiD 4 SystemOmics08/01/2011
53AGRE Omni1-quadOmics10/11/2011
59AGP genotypingOmics04/03/2012
60Ultradeep 454 sequencing of synaptic genes from postmortem cerebella of individuals with ASD and neurotypical controlsOmics06/23/2012
63Microemulsion PCR and Targeted Resequencing for Variant Detection in ASDOmics07/20/2012
76Whole Genome Sequencing in Autism FamiliesOmics01/03/2013
90Genotyped IAN SamplesOmics07/09/2013
91NJLAGS Axiom Genotyping ArrayOmics07/16/2013
93AGP genotyping (CNV)Omics09/06/2013
106Longitudinal Sleep Study. H20 200. Channel set 2EEG11/07/2013
107Longitudinal Sleep Study. H20 200. Channel set 3EEG11/07/2013
108Longitudinal Sleep Study. AURA 200EEG11/07/2013
105Longitudinal Sleep Study. H20 200. Channel set 1EEG11/07/2013
109Longitudinal Sleep Study. AURA 400EEG11/07/2013
116Gene Expression Analysis WG-6Omics01/07/2014
131Jeste Lab UCLA ACEii: Charlie Brown and Sesame Street - Project 1Eye Tracking02/27/2014
132Jeste Lab UCLA ACEii: Animacy - Project 1Eye Tracking02/27/2014
133Jeste Lab UCLA ACEii: Mom Stranger - Project 2Eye Tracking02/27/2014
134Jeste Lab UCLA ACEii: Face Emotion - Project 3Eye Tracking02/27/2014
151Candidate Gene Identification in familial AutismOmics06/09/2014
152NJLAGS Whole Genome SequencingOmics07/01/2014
154Math Autism Study - Vinod MenonfMRI07/15/2014
160syllable contrastEEG07/29/2014
167School-age naturalistic stimuliEye Tracking09/19/2014
44AGRE/Broad Affymetrix 5.0 Genotype ExperimentOmics06/27/2011
45Exome Sequencing of 20 Sporadic Cases of Autism Spectrum DisorderOmics07/15/2011
78MET GenotypesOmics03/18/2013
Collection - Add Experiment
Add Supporting Documentation
Select File

To add an existing Data Structure, enter its title in the search bar. If you need to request changes, select the indicator "No, it requires changes to meet research needs" after selecting the Structure, and upload the file with the request changes specific to the selected Data Structure. Your file should follow the Request Changes Procedure. If the Data Structure does not exist, select "Request New Data Structure" and upload the appropriate zip file.

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Your Collection is now in Data Analysis phase and exempt from biannual submissions. Analyzed data is still expected prior to publication or no later than the project end date.

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Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Autism Genetics, Phase II: Increasing Representation of Human Diversity
Daniel Geschwind 
Autism Spectrum Disorder (ASD) is a common, often devastating neuropsychiatric condition with largely unknown pathophysiology. Although ASD has a multifactorial etiology, it encompasses a large genetic component. The investigators in this proposal aim to continue and enhance our collaborative effort that has produced significant advances in our understanding of ASD over the last four years and generated highly successful, open data and biomaterials resources for the research community, the NIMH Genetics Initiative and the Autism Genetic Resource Exchange (AGRE). Our Network has met or exceeded our original aims. We have built patient resources for research, identified rare and common ASD susceptibility alleles, defined models of ASD genetic susceptibility, provided evidence for convergent pathophysiology, and led development of animal and cell culture models. Here we propose to take a major new direction, filling a significant gap in ASD research, by recruiting underserved subjects of self-reported African ancestry (African-American; AA), an important population that has not previously been well-represented in ASD genetics research. Our Network involves six research sites and the AGRE DCC, collaborating in a systematic, comprehensive investigation of ASD genetics in order to identify rare mutations, chromosomal abnormalities, and common variation contributing to ASD susceptibility in the AA population. Specifically, we will enrich existing resources by recruiting at least 600 AA probands and additional family members. Our recruitment plan includes an embedded health disparities project that will evaluate access to care for AAs with ASD and clarify factors influencing participation of AA individuals in genetic research. We will employ novel methods to define the ancestral origin of specific chromosomal segments and ascertain the background on which susceptibility alleles occur. We will perform follow up GWA on ASD-related endophenotypes or co-variates, such as language delay, sex and head circumference. In parallel, we will conduct whole exome sequencing (WES) and analysis of copy number variation (CNV) using 2.5M SNP arrays yielding high resolution molecular karyotypes and providing a resource on genome-wide CNV and coding sequence variation (SNV) in ASD. Gene expression profiling and network analysis will be used to prioritize variants. Genetic risk factors identified in the mostly European samples will be tested for association in the AA sample to determine whether these cohorts share the same genetic risk factors, using a sample size providing power to replicate previous associations and to identify rare, recurrent CNV and SNV. The observation of new forms or different population frequencies of ASD-related variation in this sample as well as the sharing of most CNV and SNV with other cohorts are both outcomes that will have great significance for future studies and clinical care. As has been our practice, our Network will make all phenotypic and genotype data accessible via the internet on a rolling basis, further enhancing the value of this resource to the community. In addition to the behavioral and genomic data in our NDA collection, whole-genome sequence generated for our cohort in collaboration with the Center for Common Disease Genomics (CCDG) can be found via dbGaP study accession number phs002042.v1.p1 and will be distributed through AnVIL (https://anvilproject.org/data).
NIMH Data Archive
Autism Centers of Excellence (ACE), NIMH Repository & Genomics Resource (NRGR)
Funding Completed
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NIH - Extramural None

R01MH100027-06 Autism Genetics, Phase II: Increasing Representation of Human Diversity 03/25/2013 02/28/2018 3360 1870 UNIVERSITY OF CALIFORNIA LOS ANGELES $3,168,451.00


NDA Help Center

Collection - General Tab

Fields available for edit on the top portion of the page include:

  • Collection Title
  • Investigators
  • Collection Description
  • Collection Phase
  • Funding Source
  • Clinical Trials

Collection Phase: The current status of a research project submitting data to an NDA Collection, based on the timing of the award and/or the data that have been submitted.

  • Pre-Enrollment: The default entry made when the NDA Collection is created.
  • Enrolling: Data have been submitted to the NDA Collection or the NDA Data Expected initial submission date has been reached for at least one data structure category in the NDA Collection.
  • Data Analysis: Subject level data collection for the research project is completed and has been submitted to the NDA Collection. The NDA Collection owner or the NDA Help Desk may set this phase when they’ve confirmed data submission is complete and submitted subject counts match at least 90% of the target enrollment numbers in the NDA Data Expected. Data submission reminders will be turned off for the NDA Collection.
  • Funding Completed: The NIH grant award (or awards) associated with the NDA Collection has reached its end date. NDA Collections in Funding Completed phase are assigned a subphase to indicate the status of data submission.
    • The Data Expected Subphase indicates that NDA expects more data will be submitted
    • The Closeout Subphase indicates the data submission is complete.
    • The Sharing Not Met Subphase indicates that data submission was not completed as expected.

Blinded Clinical Trial Status:

  • This status is set by a Collection Owner and indicates the research project is a double blinded clinical trial. When selected, the public view of Data Expected will show the Data Expected items and the Submission Dates, but the targeted enrollment and subjects submitted counts will not be displayed.
  • Targeted enrollment and subjects submitted counts are visible only to NDA Administrators and to the NDA Collection or as the NDA Collection Owner.
  • When an NDA Collection that is flagged Blinded Clinical Trial reaches the maximum data sharing date for that Data Repository (see https://nda.nih.gov/nda/sharing-regimen.html), the embargo on Data Expected information is released.

Funding Source

The organization(s) responsible for providing the funding is listed here.

Supporting Documentation

Users with Submission privileges, as well as Collection Owners, Program Officers, and those with Administrator privileges, may upload and attach supporting documentation. By default, supporting documentation is shared to the general public, however, the option is also available to limit this information to qualified researchers only.

Grant Information

Identifiable details are displayed about the Project of which the Collection was derived from. You may click in the Project Number to view a full report of the Project captured by the NIH.

Clinical Trials

Any data that is collected to support or further the research of clinical studies will be available here. Collection Owners and those with Administrator privileges may add new clinical trials.

Frequently Asked Questions

  • How does the NIMH Data Archive (NDA) determine which Permission Group data are submitted into?
    During Collection creation, NDA staff determine the appropriate Permission Group based on the type of data to be submitted, the type of access that will be available to data access users, and the information provided by the Program Officer during grant award.
  • How do I know when a NDA Collection has been created?
    When a Collection is created by NDA staff, an email notification will automatically be sent to the PI(s) of the grant(s) associated with the Collection to notify them.
  • Is a single grant number ever associated with more than one Collection?
    The NDA system does not allow for a single grant to be associated with more than one Collection; therefore, a single grant will not be listed in the Grant Information section of a Collection for more than one Collection.
  • Why is there sometimes more than one grant included in a Collection?
    In general, each Collection is associated with only one grant; however, multiple grants may be associated if the grant has multiple competing segments for the same grant number or if multiple different grants are all working on the same project and it makes sense to hold the data in one Collection (e.g., Cooperative Agreements).


  • Administrator Privilege
    A privilege provided to a user associated with an NDA Collection or NDA Study whereby that user can perform a full range of actions including providing privileges to other users.
  • Collection Owner
    Generally, the Collection Owner is the contact PI listed on a grant. Only one NDA user is listed as the Collection owner. Most automated emails are primarily sent to the Collection Owner.
  • Collection Phase
    The Collection Phase provides information on data submission as opposed to grant/project completion so while the Collection phase and grant/project phase may be closely related they are often different. Collection users with Administrative Privileges are encouraged to edit the Collection Phase. The Program Officer as listed in eRA (for NIH funded grants) may also edit this field. Changes must be saved by clicking the Save button at the bottom of the page. This field is sortable alphabetically in ascending or descending order. Collection Phase options include:
    • Pre-Enrollment: A grant/project has started, but has not yet enrolled subjects.
    • Enrolling: A grant/project has begun enrolling subjects. Data submission is likely ongoing at this point.
    • Data Analysis: A grant/project has completed enrolling subjects and has completed all data submissions.
    • Funding Completed: A grant/project has reached the project end date.
  • Collection Title
    An editable field with the title of the Collection, which is often the title of the grant associated with the Collection.
  • Grant
    Provides the grant number(s) for the grant(s) associated with the Collection. The field is a hyperlink so clicking on the Grant number will direct the user to the grant information in the NIH Research Portfolio Online Reporting Tools (RePORT) page.
  • Supporting Documentation
    Various documents and materials to enable efficient use of the data by investigators unfamiliar with the project and may include the research protocol, questionnaires, and study manuals.
  • NIH Research Initiative
    NDA Collections may be organized by scientific similarity into NIH Research Initiatives, to facilitate query tool user experience. NIH Research Initiatives map to one or multiple Funding Opportunity Announcements.
  • Permission Group
    Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.
  • Planned Enrollment
    Number of human subject participants to be enrolled in an NIH-funded clinical research study. The data is provided in competing applications and annual progress reports.
  • Actual Enrollment
    Number of human subjects enrolled in an NIH-funded clinical research study. The data is provided in annual progress reports.
  • NDA Collection
    A virtual container and organization structure for data and associated documentation from one grant or one large project/consortium. It contains tools for tracking data submission and allows investigators to define a wide array of other elements that provide context for the data, including all general information regarding the data and source project, experimental parameters used to collect any event-based data contained in the Collection, methods, and other supporting documentation. They also allow investigators to link underlying data to an NDA Study, defining populations and subpopulations specific to research aims.
  • Data Use Limitations
    Data Use Limitations (DULs) describe the appropriate secondary use of a dataset and are based on the original informed consent of a research participant. NDA only accepts consent-based data use limitations defined by the NIH Office of Science Policy.
  • Total Subjects Shared
    The total number of unique subjects for whom data have been shared and are available for users with permission to access data.
IDNameCreated DateStatusType
3262013-489 targeted linkage peaks06/12/2015ApprovedOmics
474Single All AGRE, MBV33-10 (CHOP)06/07/2016ApprovedOmics
475MB1-10 (CHOP)06/07/2016ApprovedOmics
517Exomes 2014-407_UCLA; 2014-207_UCSF; 2016-912311/05/2016ApprovedOmics
1712Whole-genome sequence (CCDG)03/15/2021ApprovedOmics
1830Illumina Global Screening Array08/02/2021ApprovedOmics
1980Whole-exome sequence: Kapa HyperPrep, SeqCAP EZ Human Exome v303/24/2022ApprovedOmics

NDA Help Center

Collection - Experiments

The number of Experiments included is displayed in parentheses next to the tab name. You may download all experiments associated with the Collection via the Download button. You may view individual experiments by clicking the Experiment Name and add them to the Filter Cart via the Add to Cart button.

Collection Owners, Program Officers, and users with Submission or Administrative Privileges for the Collection may create or edit an Experiment.

Please note: The creation of an NDA Experiment does not necessarily mean that data collected, according to the defined Experiment, has been submitted or shared.

Frequently Asked Questions

  • Can an Experiment be associated with more than one Collection?

    Yes -see the “Copy” button in the bottom left when viewing an experiment. There are two actions that can be performed via this button:

    1. Copy the experiment with intent for modifications.
    2. Associate the experiment to the collection. No modifications can be made to the experiment.


  • Experiment Status
    An Experiment must be Approved before data using the associated Experiment_ID may be uploaded.
  • Experiment ID
    The ID number automatically generated by NDA which must be included in the appropriate file when uploading data to link the Experiment Definition to the subject record.
ACE Family Medical History Clinical Assessments 452
ACE Subject Physical Exam Clinical Assessments 445
Diagnostic Odyssey Instrument Clinical Assessments 479
Genomics Genetic Test Genomics 185
Genomics Sample Genomics 4483
Genomics Subject Genomics 4483
Mullen Scales of Early Learning Clinical Assessments 20
Peabody Picture Vocabulary Test, Fourth Edition-Form A Clinical Assessments 89
Ravens Coloured Progressive Matrices (CPM) Clinical Assessments 275
Ravens Standard Progressive Matrices Clinical Assessments 499
Research Subject Clinical Assessments 1571
SRS-2. Adult, Preschool and School Age Clinical Assessments 974
Social Communication Questionnaire (SCQ) - Current Form Clinical Assessments 51
Social Communication Questionnaire (SCQ) - Lifetime Clinical Assessments 478
Vineland-II - Survey Form (2005) Clinical Assessments 445

NDA Help Center

Collection - Shared Data

This tab provides a quick overview of the Data Structure title, Data Type, and Number of Subjects that are currently Shared for the Collection. The information presented in this tab is automatically generated by NDA and cannot be edited. If no information is visible on this tab, this would indicate the Collection does not have shared data or the data is private.

The shared data is available to other researchers who have permission to access data in the Collection's designated Permission Group(s). Use the Download button to get all shared data from the Collection to the Filter Cart.

Frequently Asked Questions

  • How will I know if another researcher uses data that I shared through the NIMH Data Archive (NDA)?
    To see what data your project have submitted are being used by a study, simply go the Associated Studies tab of your collection. Alternatively, you may review an NDA Study Attribution Report available on the General tab.
  • Can I get a supplement to share data from a completed research project?
    Often it becomes more difficult to organize and format data electronically after the project has been completed and the information needed to create a GUID may not be available; however, you may still contact a program staff member at the appropriate funding institution for more information.
  • Can I get a supplement to share data from a research project that is still ongoing?
    Unlike completed projects where researchers may not have the information needed to create a GUID and/or where the effort needed to organize and format data becomes prohibitive, ongoing projects have more of an opportunity to overcome these challenges. Please contact a program staff member at the appropriate funding institution for more information.


  • Data Structure
    A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points. Data structures that have been defined in the NDA Data Dictionary are available at https://nda.nih.gov/general-query.html?q=query=data-structure
  • Data Type
    A grouping of data by similar characteristics such as Clinical Assessments, Omics, or Neurosignal data.
  • Shared
    The term 'Shared' generally means available to others; however, there are some slightly different meanings based on what is Shared. A Shared NDA Study is viewable and searchable publicly regardless of the user's role or whether the user has an NDA account. A Shared NDA Study does not necessarily mean that data used in the NDA Study have been shared as this is independently determined. Data are shared according the schedule defined in a Collection's Data Expected Tab and/or in accordance with data sharing expectations in the NDA Data Sharing Terms and Conditions. Additionally, Supporting Documentation uploaded to a Collection may be shared independent of whether data are shared.

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


Publications relevant to NDA 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
38699304Create StudyContribution of autosomal rare and de novo variants to sex differences in autism.medRxiv : the preprint server for health sciencesKoko, Mahmoud; Kyle Satterstrom, F; Autism Sequencing Consortium; APEX consortium; Warrier, Varun; Martin, HilaryApril 16, 2024Not Determined
37506195Create StudyThe contributions of rare inherited and polygenic risk to ASD in multiplex families.Proceedings of the National Academy of Sciences of the United States of AmericaCirnigliaro, Matilde; Chang, Timothy S; Arteaga, Stephanie A; Pérez-Cano, Laura; Ruzzo, Elizabeth K; Gordon, Aaron; Bicks, Lucy K; Jung, Jae-Yoon; Lowe, Jennifer K; Wall, Dennis P; Geschwind, Daniel HAugust 1, 2023Not Determined
37196781Create StudyProspects for Leveling the Playing Field for Black Children With Autism.Journal of the American Academy of Child and Adolescent PsychiatryConstantino, John N; Abbacchi, Anna M; May, Brandon K; Klaiman, Cheryl; Zhang, Yi; Lowe, Jennifer K; Marrus, Natasha; Klin, Ami; Geschwind, Daniel HSeptember 1, 2023Not Determined
37101120Create StudyPriors, population sizes, and power in genome-wide hypothesis tests.BMC bioinformaticsCai, Jitong; Zhan, Jianan; Arking, Dan E; Bader, Joel SApril 26, 2023Not Determined
36829214Create StudySex differences in friendships and loneliness in autistic and non-autistic children across development.Molecular autismLibster, Natalie; Knox, Azia; Engin, Selin; Geschwind, Daniel; Parish-Morris, Julia; Kasari, ConnieFebruary 24, 2023Not Determined
36566252Create StudyPersonal victimization experiences of autistic and non-autistic children.Molecular autismLibster, Natalie; Knox, Azia; Engin, Selin; Geschwind, Daniel; Parish-Morris, Julia; Kasari, ConnieDecember 24, 2022Not Determined
36517753Create StudySocial attention during object engagement: toward a cross-species measure of preferential social orienting.Journal of neurodevelopmental disordersWeichselbaum, Claire; Hendrix, Nicole; Albright, Jordan; Dougherty, Joseph D; Botteron, Kelly N; Constantino, John N; Marrus, NatashaDecember 14, 2022Not Determined
36311265Create StudyWhole-exome sequencing in 415,422 individuals identifies rare variants associated with mitochondrial DNA copy number.HGG advancesPillalamarri, Vamsee; Shi, Wen; Say, Conrad; Yang, Stephanie; Lane, John; Guallar, Eliseo; Pankratz, Nathan; Arking, Dan EJanuary 12, 2023Not Determined
36280734Create StudyStatistical and functional convergence of common and rare genetic influences on autism at chromosome 16p.Nature geneticsWeiner, Daniel J; Ling, Emi; Erdin, Serkan; Tai, Derek J C; Yadav, Rachita; Grove, Jakob; Fu, Jack M; Nadig, Ajay; Carey, Caitlin E; Baya, Nikolas; Bybjerg-Grauholm, Jonas; iPSYCH Consortium; ASD Working Group of the Psychiatric Genomics Consortium; ADHD Working Group of the Psychiatric Genomics Consortium; Berretta, Sabina; Macosko, Evan Z; Sebat, Jonathan; O'Connor, Luke J; Hougaard, David M; Børglum, Anders D; Talkowski, Michael E; McCarroll, Steven A; Robinson, Elise BNovember 1, 2022Not Determined
36183905Create StudyChallenges and opportunities for precision medicine in neurodevelopmental disorders.Advanced drug delivery reviewsChen, George T; Geschwind, Daniel HDecember 1, 2022Not Determined
35982160Create StudyRare coding variation provides insight into the genetic architecture and phenotypic context of autism.Nature geneticsFu, Jack M; Satterstrom, F Kyle; Peng, Minshi; Brand, Harrison; Collins, Ryan L; Dong, Shan; Wamsley, Brie; Klei, Lambertus; Wang, Lily; Hao, Stephanie P; Stevens, Christine R; Cusick, Caroline; Babadi, Mehrtash; Banks, Eric; Collins, Brett; Dodge, Sheila; Gabriel, Stacey B; Gauthier, Laura; Lee, Samuel K; Liang, Lindsay; Ljungdahl, Alicia; Mahjani, Behrang; Sloofman, Laura; Smirnov, Andrey N; Barbosa, Mafalda; Betancur, Catalina; Brusco, Alfredo; Chung, Brian H Y; Cook, Edwin H; Cuccaro, Michael L; Domenici, Enrico; Ferrero, Giovanni Battista; Gargus, J Jay; Herman, Gail E; Hertz-Picciotto, Irva; Maciel, Patricia; Manoach, Dara S; Passos-Bueno, Maria Rita; Persico, Antonio M; Renieri, Alessandra; Sutcliffe, James S; Tassone, Flora; Trabetti, Elisabetta; Campos, Gabriele; Cardaropoli, Simona; Carli, Diana; Chan, Marcus C Y; Fallerini, Chiara; Giorgio, Elisa; Girardi, Ana Cristina; Hansen-Kiss, Emily; Lee, So Lun; Lintas, Carla; Ludena, Yunin; Nguyen, Rachel; Pavinato, Lisa; Pericak-Vance, Margaret; Pessah, Isaac N; Schmidt, Rebecca J; Smith, Moyra; Costa, Claudia I S; Trajkova, Slavica; Wang, Jaqueline Y T; Yu, Mullin H C; Autism Sequencing Consortium (ASC); Broad Institute Center for Common Disease Genomics (Broad-CCDG); iPSYCH-BROAD Consortium; Cutler, David J; De Rubeis, Silvia; Buxbaum, Joseph D; Daly, Mark J; Devlin, Bernie; Roeder, Kathryn; Sanders, Stephan J; Talkowski, Michael ESeptember 1, 2022Not Determined
35591888Create StudyA bioinformatics pipeline for estimating mitochondrial DNA copy number and heteroplasmy levels from whole genome sequencing data.NAR genomics and bioinformaticsBattle, Stephanie L; Puiu, Daniela; TOPMed mtDNA Working Group; Verlouw, Joost; Broer, Linda; Boerwinkle, Eric; Taylor, Kent D; Rotter, Jerome I; Rich, Stephan S; Grove, Megan L; Pankratz, Nathan; Fetterman, Jessica L; Liu, Chunyu; Arking, Dan EJune 1, 2022Not Determined
34932941Create StudyOxytocin normalizes altered circuit connectivity for social rescue of the Cntnap2 knockout mouse.NeuronChoe, Katrina Y; Bethlehem, Richard A I; Safrin, Martin; Dong, Hongmei; Salman, Elena; Li, Ying; Grinevich, Valery; Golshani, Peyman; DeNardo, Laura A; Peñagarikano, Olga; Harris, Neil G; Geschwind, Daniel HMarch 2, 2022Not Determined
34859289Create StudyGenome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation.Human geneticsLongchamps, R J; Yang, S Y; Castellani, C A; Shi, W; Lane, J; Grove, M L; Bartz, T M; Sarnowski, C; Liu, C; Burrows, K; Guyatt, A L; Gaunt, T R; Kacprowski, T; Yang, J; De Jager, P L; Yu, L; Bergman, A; Xia, R; Fornage, M; Feitosa, M F; Wojczynski, M K; Kraja, A T; Province, M A; Amin, N; Rivadeneira, F; Tiemeier, H; Uitterlinden, A G; Broer, L; Van Meurs, J B J; Van Duijn, C M; Raffield, L M; Lange, L; Rich, S S; Lemaitre, R N; Goodarzi, M O; Sitlani, C M; Mak, A C Y; Bennett, D A; Rodriguez, S; Murabito, J M; Lunetta, K L; Sotoodehnia, N; Atzmon, G; Ye, K; Barzilai, N; Brody, J A; Psaty, B M; Taylor, K D; Rotter, J I; Boerwinkle, E; Pankratz, N; Arking, D EJanuary 1, 2022Not Determined
34663447Create StudyComprehensive multi-omics integration identifies differentially active enhancers during human brain development with clinical relevance.Genome medicineYousefi, Soheil; Deng, Ruizhi; Lanko, Kristina; Salsench, Eva Medico; Nikoncuk, Anita; van der Linde, Herma C; Perenthaler, Elena; van Ham, Tjakko J; Mulugeta, Eskeatnaf; Barakat, Tahsin StefanOctober 19, 2021Not Determined
34553489Create StudyRethinking autism spectrum disorder assessment for children during COVID-19 and beyond.Autism research : official journal of the International Society for Autism ResearchZwaigenbaum, Lonnie; Bishop, Somer; Stone, Wendy L; Ibanez, Lisa; Halladay, Alycia; Goldman, Sylvie; Kelly, Amy; Klaiman, Cheryl; Lai, Meng-Chuan; Miller, Meghan; Saulnier, Celine; Siper, Paige; Sohl, Kristin; Warren, Zachary; Wetherby, AmyNovember 1, 2021Not Determined
34313757Create StudyThree decades of ASD genetics: building a foundation for neurobiological understanding and treatment.Human molecular geneticsEyring, Katherine W; Geschwind, Daniel HOctober 1, 2021Not Determined
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23933821Create StudyGenetic relationship between five psychiatric disorders estimated from genome-wide SNPs.Nature geneticsCross-Disorder Group of the Psychiatric Genomics Consortium; Lee, S Hong; Ripke, Stephan; Neale, Benjamin M; Faraone, Stephen V; Purcell, Shaun M; Perlis, Roy H; Mowry, Bryan J; Thapar, Anita; Goddard, Michael E; Witte, John S; Absher, Devin; Agartz, Ingrid; Akil, Huda; Amin, Farooq; Andreassen, Ole A; Anjorin, Adebayo; Anney, Richard; Anttila, Verneri; Arking, Dan E; Asherson, Philip; Azevedo, Maria H; Backlund, Lena; Badner, Judith A; Bailey, Anthony J; Banaschewski, Tobias; Barchas, Jack D; Barnes, Michael R; Barrett, Thomas B; Bass, Nicholas; Battaglia, Agatino; Bauer, Michael; Bayés, Mònica; Bellivier, Frank; Bergen, Sarah E; Berrettini, Wade; Betancur, Catalina; Bettecken, Thomas; Biederman, Joseph; Binder, Elisabeth B; Black, Donald W; Blackwood, Douglas H R; Bloss, Cinnamon S; Boehnke, Michael; Boomsma, Dorret I; Breen, Gerome; Breuer, René; Bruggeman, Richard; Cormican, Paul; Buccola, Nancy G; Buitelaar, Jan K; Bunney, William E; Buxbaum, Joseph D; Byerley, William F; Byrne, Enda M; Caesar, Sian; Cahn, Wiepke; Cantor, Rita M; Casas, Miguel; Chakravarti, Aravinda; Chambert, Kimberly; Choudhury, Khalid; Cichon, Sven; Cloninger, C Robert; Collier, David A; Cook, Edwin H; Coon, Hilary; Cormand, Bru; Corvin, Aiden; Coryell, William H; Craig, David W; Craig, Ian W; Crosbie, Jennifer; Cuccaro, Michael L; Curtis, David; Czamara, Darina; Datta, Susmita; Dawson, Geraldine; Day, Richard; De Geus, Eco J; Degenhardt, Franziska; Djurovic, Srdjan; Donohoe, Gary J; Doyle, Alysa E; Duan, Jubao; Dudbridge, Frank; Duketis, Eftichia; Ebstein, Richard P; Edenberg, Howard J; Elia, Josephine; Ennis, Sean; Etain, Bruno; Fanous, Ayman; Farmer, Anne E; Ferrier, I Nicol; Flickinger, Matthew; Fombonne, Eric; Foroud, Tatiana; Frank, Josef; Franke, Barbara; Fraser, Christine; Freedman, Robert; Freimer, Nelson B; Freitag, Christine M; Friedl, Marion; Frisén, Louise; Gallagher, Louise; Gejman, Pablo V; Georgieva, Lyudmila; Gershon, Elliot S; Geschwind, Daniel H; Giegling, Ina; Gill, Michael; Gordon, Scott D; Gordon-Smith, Katherine; Green, Elaine K; Greenwood, Tiffany A; Grice, Dorothy E; Gross, Magdalena; Grozeva, Detelina; Guan, Weihua; Gurling, Hugh; De Haan, Lieuwe; Haines, Jonathan L; Hakonarson, Hakon; Hallmayer, Joachim; Hamilton, Steven P; Hamshere, Marian L; Hansen, Thomas F; Hartmann, Annette M; Hautzinger, Martin; Heath, Andrew C; Henders, Anjali K; Herms, Stefan; Hickie, Ian B; Hipolito, Maria; Hoefels, Susanne; Holmans, Peter A; Holsboer, Florian; Hoogendijk, Witte J; Hottenga, Jouke-Jan; Hultman, Christina M; Hus, Vanessa; Ingason, Andrés; Ising, Marcus; Jamain, Stéphane; Jones, Edward G; Jones, Ian; Jones, Lisa; Tzeng, Jung-Ying; Kähler, Anna K; Kahn, René S; Kandaswamy, Radhika; Keller, Matthew C; Kennedy, James L; Kenny, Elaine; Kent, Lindsey; Kim, Yunjung; Kirov, George K; Klauck, Sabine M; Klei, Lambertus; Knowles, James A; Kohli, Martin A; Koller, Daniel L; Konte, Bettina; Korszun, Ania; Krabbendam, Lydia; Krasucki, Robert; Kuntsi, Jonna; Kwan, Phoenix; Landén, Mikael; Långström, Niklas; Lathrop, Mark; Lawrence, Jacob; Lawson, William B; Leboyer, Marion; Ledbetter, David H; Lee, Phil H; Lencz, Todd; Lesch, Klaus-Peter; Levinson, Douglas F; Lewis, Cathryn M; Li, Jun; Lichtenstein, Paul; Lieberman, Jeffrey A; Lin, Dan-Yu; Linszen, Don H; Liu, Chunyu; Lohoff, Falk W; Loo, Sandra K; Lord, Catherine; Lowe, Jennifer K; Lucae, Susanne; MacIntyre, Donald J; Madden, Pamela A F; Maestrini, Elena; Magnusson, Patrik K E; Mahon, Pamela B; Maier, Wolfgang; Malhotra, Anil K; Mane, Shrikant M; Martin, Christa L; Martin, Nicholas G; Mattheisen, Manuel; M (see original citation for additional authors)September 2013Not Relevant
23722009Create StudyMapping connectivity in the developing brain.International journal of developmental neuroscience : the official journal of the International Society for Developmental NeuroscienceDennis, Emily L; Thompson, Paul MNovember 2013Not Relevant
23453885Create StudyIdentification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis.Lancet (London, England)Cross-Disorder Group of the Psychiatric Genomics ConsortiumApril 20, 2013Not Determined

NDA Help Center

Collection - Publications

The number of Publications is displayed in parentheses next to the tab name. Clicking on any of the Publication Titles will open the Publication in a new internet browsing tab.

Collection Owners, Program Officers, and users with Submission or Administrative Privileges for the Collection may mark a publication as either Relevant or Not Relevant in the Status column.

Frequently Asked Questions

  • How can I determine if a publication is relevant?
    Publications are considered relevant to a collection when the data shared is directly related to the project or collection.
  • Where does the NDA get the publications?
    PubMed, an online library containing journals, articles, and medical research. Sponsored by NiH and National Library of Medicine (NLM).


  • Create Study
    A link to the Create an NDA Study page that can be clicked to start creating an NDA Study with information such as the title, journal and authors automatically populated.
  • Not Determined Publication
    Indicates that the publication has not yet been reviewed and/or marked as Relevant or Not Relevant so it has not been determined whether an NDA Study is expected.
  • Not Relevant Publication
    A publication that is not based on data related to the aims of the grant/project associated with the Collection or not based on any data such as a review article and, therefore, an NDA Study is not expected to be created.
  • PubMed
    PubMed provides citation information for biomedical and life sciences publications and is managed by the U.S. National Institutes of Health's National Library of Medicine.
  • PubMed ID
    The PUBMed ID is the unique ID number for the publication as recorded in the PubMed database.
  • Relevant Publication
    A publication that is based on data related to the aims of the grant/project associated with the Collection and, therefore, an NDA Study is expected to be created.
Data Expected List: Mandatory Data Structures

These data structures are mandatory for your NDA Collection. Please update the Targeted Enrollment number to accurately represent the number of subjects you expect to submit for the entire study.

For NIMH HIV-related research that involves human research participants: Select the dictionary or dictionaries most appropriate for your research. If your research does not require all three data dictionaries, just ignore the ones you do not need. There is no need to delete extra data dictionaries from your NDA Collection. You can adjust the Targeted Enrollment column in the Data Expected tab to “0” for those unnecessary data dictionaries. At least one of the three data dictionaries must have a non-zero value.

Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Research Subject and Pedigree info icon
To create your project's Data Expected list, use the "+New Data Expected" to add or request existing structures and to request new Data Structures that are not in the NDA Data Dictionary.

If the Structure you need already exists, locate it and specify your dates and enrollment when adding it to your Data Expected list. If you require changes to the Structure you need, select the indicator stating "No, it requires changes to meet research needs," and upload a file containing your requested changes.

If the structure you need is not yet defined in the Data Dictionary, you can select "Upload Definition" and attach the necessary materials to request its creation.

When selecting the expected dates for your data, make sure to follow the standard Data Sharing Regimen and choose dates within the date ranges that correspond to your project start and end dates.

Please visit the Completing Your Data Expected Tutorial for more information.
Data Expected List: Data Structures per Research Aims

These data structures are specific to your research aims and should list all data structures in which data will be collected and submitted for this NDA Collection. Please update the Targeted Enrollment number to accurately represent the number of subjects you expect to submit for the entire study.

Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Mullen Scales of Early Learning info icon
Ravens Coloured Progressive Matrices (CPM) info icon
Genomics/omics info icon
ADOS info icon
ADI-R info icon
Medical History info icon
Social Responsiveness Scale (SRS) info icon
Genetic Test info icon
Social Communication Questionnaire (SCQ) info icon
Demographics info icon
DAS-II: Differential Ability Scales info icon
Peabody Picture Vocabulary Test, Fourth Edition info icon
Physical Exam info icon
EHCI Diagnostic Odyssey Instrument info icon
Vineland (Parent and Caregiver) info icon
Ravens Standard Progressive Matrices (SPM) info icon
Structure not yet defined
No Status history for this Data Expected has been recorded yet

NDA Help Center

Collection - Data Expected

The Data Expected tab displays the list of all data that NDA expects to receive in association with the Collection as defined by the contributing researcher, as well as the dates for the expected initial upload of the data, and when it is first expected to be shared, or with the research community. Above the primary table of Data Expected, any publications determined to be relevant to the data within the Collection are also displayed - members of the contributing research group can use these to define NDA Studies, connecting those papers to underlying data in NDA.

The tab is used both as a reference for those accessing shared data, providing information on what is expected and when it will be shared, and as the primary tracking mechanism for contributing projects. It is used by both contributing primary researchers, secondary researchers, and NIH Program and Grants Management staff.

Researchers who are starting their project need to update their Data Expected list to include all the Data Structures they are collecting under their grant and set their initial submission and sharing schedule according to the NDA Data Sharing Regimen.

To add existing Data Structures from the Data Dictionary, to request new Data Structure that are not in the Dictionary, or to request changes to existing Data Structures, click "+New Data Expected".

For step-by-step instructions on how to add existing Data Structures, request changes to an existing Structure, or request a new Data Structure, please visit the Completing Your Data Expected Tutorial.

If you are a contributing researcher creating this list for the first time, or making changes to the list as your project progress, please note the following:

  • Although items you add to the list and changes you make are displayed, they are not committed to the system until you Save the entire page using the "Save" button at the bottom of your screen. Please Save after every change to ensure none of your work is lost.
  • If you attempt to add a new structure, the title you provide must be unique - if another structure exists with the same name your change will fail.
  • Adding a new structure to this list is the only way to request the creation of a new Data Dictionary definition.

Frequently Asked Questions

  • What is an NDA Data Structure?
    An NDA Data Structure is comprised of multiple Data Elements to make up an electronic definition of an assessment, measure, questionnaire, etc will have a corresponding Data Structure.
  • What is the NDA Data Dictionary?
    The NDA Data Dictionary is comprised of electronic definitions known as Data Structures.


  • Analyzed Data
    Data specific to the primary aims of the research being conducted (e.g. outcome measures, other dependent variables, observations, laboratory results, analyzed images, volumetric data, etc.) including processed images.
  • Data Item
    Items listed on the Data Expected list in the Collection which may be an individual and discrete Data Structure, Data Structure Category, or Data Structure Group.
  • Data Structure
    A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points. Data structures that have been defined in the NDA Data Dictionary are available at https://nda.nih.gov/general-query.html?q=query=data-structure
  • Data Structure Category
    An NDA term describing the affiliation of a Data Structure to a Category, which may be disease/disorder or diagnosis related (Depression, ADHD, Psychosis), specific to data type (MRI, eye tracking, omics), or type of data (physical exam, IQ).
  • Data Structure Group
    A Data Item listed on the Data Expected tab of a Collection that indicates a group of Data Structures (e.g., ADOS or SCID) for which data may be submitted instead of a specific Data Structure identified by version, module, edition, etc. For example, the ADOS Data Structure Category includes every ADOS Data Structure such as ADOS Module 1, ADOS Module 2, ADOS Module 1 - 2nd Edition, etc. The SCID Data Structure Group includes every SCID Data Structure such as SCID Mania, SCID V Mania, SCID PTSD, SCID-V Diagnosis, and more.
  • Evaluated Data
    A new Data Structure category, Evaluated Data is analyzed data resulting from the use of computational pipelines in the Cloud and can be uploaded directly back to a miNDAR database. Evaluated Data is expected to be listed as a Data Item in the Collection's Data Expected Tab.
  • Imaging Data
    Imaging+ is an NDA term which encompasses all imaging related data including, but not limited to, images (DTI, MRI, PET, Structural, Spectroscopy, etc.) as well as neurosignal data (EEG, fMRI, MEG, EGG, eye tracking, etc.) and Evaluated Data.
  • Initial Share Date
    Initial Submission and Initial Share dates should be populated according to the NDA Data Sharing Terms and Conditions. Any modifications to these will go through the approval processes outlined above. Data will be shared with authorized users upon publication (via an NDA Study) or 1-2 years after the grant end date specified on the first Notice of Award, as defined in the applicable Data Sharing Terms and Conditions.
  • Initial Submission Date
    Initial Submission and Initial Share dates should be populated according to these NDA Data Sharing Terms and Conditions. Any modifications to these will go through the approval processes outlined above. Data for all subjects is not expected on the Initial Submission Date and modifications may be made as necessary based on the project's conduct.
  • Research Subject and Pedigree
    An NDA created Data Structure used to convey basic information about the subject such as demographics, pedigree (links family GUIDs), diagnosis/phenotype, and sample location that are critical to allow for easier querying of shared data.
  • Submission Cycle
    The NDA has two Submission Cycles per year - January 15 and July 15.
  • Submission Exemption
    An interface to notify NDA that data may not be submitted during the upcoming/current submission cycle.

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
Examining the validity of the use of ratio IQs in psychological assessments IQ tests are amongst the most used psychological assessments, both in research and clinical settings. For participants who cannot complete IQ tests normed for their age, ratio IQ scores (RIQ) are routinely computed and used as a proxy of IQ, especially in large research databases to avoid missing data points. However, because it has never been scientifically validated, this practice is questionable. In the era of big data, it is important to examine the validity of this widely used practice. In this paper, we use the case of autism to examine the differences between standard full-scale IQ (FSIQ) and RIQ. Data was extracted from four databases in which ages, FSIQ scores and subtests raw scores were available for autistic participants between 2 and 17 years old. The IQ tests included were the MSEL (N=12033), DAS-II early years (N=1270), DAS-II school age (N=2848), WISC-IV (N=471) and WISC-V (N=129). RIQs were computed for each participant as well as the discrepancy (DSC) between RIQ and FSIQ. We performed two linear regressions to respectively assess the effect of FSIQ and of age on the DSC for each IQ test, followed by additional analyses comparing age subgroups as well as FSIQ subgroups on DSC. Participants at the extremes of the FSIQ distribution tended to have a greater DSC than participants with average FSIQ. Furthermore, age significantly predicted the DSC, with RIQ superior to FSIQ for younger participants while the opposite was found for older participants. These results question the validity of this widely used alternative scoring method, especially for individuals at the extremes of the normal distribution, with whom RIQs are most often employed.20/17423Secondary AnalysisShared
The importance of low IQ to early diagnosis of autismSome individuals can flexibly adapt to life’s changing demands while others, in particular those with Autism Spectrum Disorder (ASD), find it challenging. The origin of early individual differences in cognitive abilities, the putative tools with which to navigate novel information in life, including in infants later diagnosed with ASD remains unexplored. Moreover, the role of intelligence quotient (IQ) vis-à-vis core features of autism remains debated. We systematically investigate the contribution of early IQ in future autism outcomes in an extremely large, population-based study of 8,000 newborns, infants, and toddlers from the US between 2 and 68 months with over 15,000 cross-sectional and longitudinal assessments, and for whom autism outcomes are ascertained or ruled out by about 2-4 years. This population is representative of subjects involved in the National Institutes of Health (NIH)-funded research, mainly on atypical development, in the US. Analyses using predetermined age bins showed that IQ scores are consistently lower in ASD relative to TD at all ages (p<0.001), and IQ significantly correlates with calibrated severity scores (total CSS, as well as non-verbal and verbal CSS) on the ADOS. Note, VIQ is no better than the full-scale IQ to predict ASD cases. These findings raise new, compelling questions about potential atypical brain circuitry affecting performance in both verbal and nonverbal abilities and that precede an ASD diagnosis. This study is the first to establish prospectively that low early IQ is a major feature of ASD in early childhood. 2/6323Secondary AnalysisShared
Prognostic early snapshot stratification of autism based on adaptive functioningA major goal of precision medicine is to predict prognosis based on individualized information at the earliest possible points in development. Using early snapshots of adaptive functioning and unsupervised data- driven discovery methods, we uncover highly stable early autism subtypes that yield information relevant to later prognosis. Data from the National Institute of Mental Health Data Archive (NDA) (n = 1,098) was used to uncover three early subtypes (<72 months) that generalize with 96% accuracy. Outcome data from NDA (n = 2,561; mean age, 13 years) also reproducibly clusters into three subtypes with 99% generalization accuracy. Early snapshot subtypes predict developmental trajectories in non-verbal cognitive, language and motor domains and are predictive of membership in different adaptive functioning outcome subtypes. Robust and prognosis- relevant subtyping of autism based on early snapshots of adaptive functioning may aid future research work via prediction of these subtypes with our reproducible stratification model.214/3517Secondary AnalysisShared
Investigating autism etiology and heterogeneity by decision tree algorithmAutism spectrum disorder (ASD) is a neurodevelopmental disorder that causes deficits in cognition, communication and social skills. ASD, however, is a highly heterogeneous disorder. This heterogeneity has made identifying the etiology of ASD a particularly difficult challenge, as patients exhibit a wide spectrum of symptoms without any unifying genetic or environmental factors to account for the disorder. For better understanding of ASD, it is paramount to identify potential genetic and environmental risk factors that are comorbid with it. Identifying such factors is of great importance to determine potential causes for the disorder, and understand its heterogeneity. Existing large-scale datasets offer an opportunity for computer scientists to undertake this task by utilizing machine learning to reliably and efficiently obtain insight about potential ASD risk factors, which would in turn assist in guiding research in the field. In this study, decision tree algorithms were utilized to analyze related factors in datasets obtained from the National Database for Autism Research (NDAR) consisting of nearly 3000 individuals. We were able to identify 15 medical conditions that were highly associated with ASD diagnoses in patients; furthermore, we extended our analysis to the family medical history of patients and we report six potentially hereditary medical conditions associated with ASD. Associations reported had a 90% accuracy. Meanwhile, gender comparisons highlighted conditions that were unique to each gender and others that overlapped. Those findings were validated by the academic literature, thus opening the way for new directions for the use of decision tree algorithms to further understand the etiology of autism. 5/3382Secondary AnalysisShared
* Data not on individual level

NDA Help Center

Collection - Associated Studies

Clicking on the Study Title will open the study details in a new internet browser tab. The Abstract is available for viewing, providing the background explanation of the study, as provided by the Collection Owner.

Primary v. Secondary Analysis: The Data Usage column will have one of these two choices. An associated study that is listed as being used for Primary Analysis indicates at least some and potentially all of the data used was originally collected by the creator of the NDA Study. Secondary Analysis indicates the Study owner was not involved in the collection of data, and may be used as supporting data.

Private v. Shared State: Studies that remain private indicate the associated study is only available to users who are able to access the collection. A shared study is accessible to the general public.

Frequently Asked Questions

  • How do I associate a study to my collection?
    Studies are associated to the Collection automatically when the data is defined in the Study.


  • Associated Studies Tab
    A tab in a Collection that lists the NDA Studies that have been created using data from that Collection including both Primary and Secondary Analysis NDA Studies.