NIMH Data Archive - Data

Genomics

Neuroimaging

Phenotype¹

New Trial
Clinical Trial

¹ Numbers reported are subjects by age

New Project
Grant/Project Number

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

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.

Select	Experiment Id	Experiment Name	Experiment Type	Created On

24	HI-NGS_R1	Omics	02/16/2011
475	MB1-10 (CHOP)	Omics	06/07/2016
490	Discovery and CRISPR validation of genetic factors associated with antipsychotic-induced weight gain and cardiometabolic risk	Omics	07/07/2016
501	PharmacoBOLD Resting State	fMRI	07/27/2016
506	PVPREF	Omics	08/05/2016
509	ABC-CT Resting v2	EEG	08/18/2016
13	Comparison of FI expression in Autistic and Neurotypical Homo Sapiens	Omics	12/28/2010
18	AGRE/Broad Affymetrix 5.0 Genotype Experiment	Omics	01/06/2011
22	Stitching PCR Sequencing	Omics	02/14/2011
26	ASD_Methylation	Omics	03/01/2011
29	Microarray family 03 (father, mother, sibling)	Omics	03/24/2011
37	Standard paired-end sequencing of BCRs	Omics	04/19/2011
38	Illumina Mate-Pair BCR sequencing	Omics	04/19/2011
39	Custom Jumping Libraries	Omics	04/19/2011
40	Custom CapBP	Omics	04/19/2011
41	Immunofluorescence	Omics	05/11/2011
43	Autism brain sample genotyping, Illumina	Omics	05/16/2011
47	ARRA Autism Sequencing Collaboration at Baylor. SOLiD 4 System	Omics	08/01/2011
53	AGRE Omni1-quad	Omics	10/11/2011
59	AGP genotyping	Omics	04/03/2012
60	Ultradeep 454 sequencing of synaptic genes from postmortem cerebella of individuals with ASD and neurotypical controls	Omics	06/23/2012
63	Microemulsion PCR and Targeted Resequencing for Variant Detection in ASD	Omics	07/20/2012
76	Whole Genome Sequencing in Autism Families	Omics	01/03/2013
519	Resting	fMRI	11/08/2016
90	Genotyped IAN Samples	Omics	07/09/2013
91	NJLAGS Axiom Genotyping Array	Omics	07/16/2013
93	AGP genotyping (CNV)	Omics	09/06/2013
106	Longitudinal Sleep Study. H20 200. Channel set 2	EEG	11/07/2013
107	Longitudinal Sleep Study. H20 200. Channel set 3	EEG	11/07/2013
108	Longitudinal Sleep Study. AURA 200	EEG	11/07/2013
105	Longitudinal Sleep Study. H20 200. Channel set 1	EEG	11/07/2013
109	Longitudinal Sleep Study. AURA 400	EEG	11/07/2013
116	Gene Expression Analysis WG-6	Omics	01/07/2014
131	Jeste Lab UCLA ACEii: Charlie Brown and Sesame Street - Project 1	Eye Tracking	02/27/2014
132	Jeste Lab UCLA ACEii: Animacy - Project 1	Eye Tracking	02/27/2014
133	Jeste Lab UCLA ACEii: Mom Stranger - Project 2	Eye Tracking	02/27/2014
134	Jeste Lab UCLA ACEii: Face Emotion - Project 3	Eye Tracking	02/27/2014
145	AGRE/FMR1_Illumina.JHU	Omics	04/14/2014
146	AGRE/MECP2_Sanger.JHU	Omics	04/14/2014
147	AGRE/MECP2_Junior.JHU	Omics	04/14/2014
151	Candidate Gene Identification in familial Autism	Omics	06/09/2014
152	NJLAGS Whole Genome Sequencing	Omics	07/01/2014
154	Math Autism Study - Vinod Menon	fMRI	07/15/2014
155	Resting	fMRI	07/25/2014
156	Speech	fMRI	07/25/2014
159	Emotion	fMRI	07/25/2014
160	syllable contrast	EEG	07/29/2014
167	School-age naturalistic stimuli	Eye Tracking	09/19/2014
44	AGRE/Broad Affymetrix 5.0 Genotype Experiment	Omics	06/27/2011
45	Exome Sequencing of 20 Sporadic Cases of Autism Spectrum Disorder	Omics	07/15/2011

Collection - Add Experiment

Add Supporting Documentation

Funding Source:
URL:

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.

Use/Modify Existing Data Structure

Request New Data Structure

Targeted Enrollment:

Initial Submission Date:

Initial Share Date:

Data Structure Search:

Data Structures:

Submit

Request Submission Exemption

Not Eligible

The Data Expected list for this Collection shows some raw data as missing. Contact the NDA Help Desk with any questions.

Please confirm that you will not be enrolling any more subjects and that all raw data has been collected and submitted.

Collection Updated

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.

[CMS] Error

[CMS]

Unable to change collection phase where targeted enrollment is less than 90%

You have requested to move the sharing dates for the following assessments:

Data Expected Item	Original Sharing Date	New Sharing Date

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Early Autism Risk Longitudinal Investigation (EARLI) Network #1600

General
Experiments (2)
Shared Data
Publications (42)
Data Expected (20)
Associated Studies (13)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Early Autism Risk Longitudinal Investigation (EARLI) Network
Collection Investigators:	Craig Newschaffer
Collection Description:	Descriptive data for EARLI (probands and sibling) ADOS, Vineland, SRS, SCQ
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	04/01/2008
NIH Research Initiative:	Autism Centers of Excellence (ACE)
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$6,483,811.00
Subjects Shared:	733
Collection DOI:	10.15154/2wv8-ad30

{"values":[]}

{"values":[["Typical Control",219],["Autism Spectrum Mildly Affected",54],["Sibling Control",31],["Autism Spectrum Affected",126],["Autism Spectrum Severely Affected",175],["Not Defined",463],["Neurological Control",13],["Parental Control",1]]}

Loading Chart...

Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

File Name	File Type	Description	Audience
Dietary History Questionnaire codebooks.zip	Other	Dietary History Codebooks Jan 15, 2017 submission	Qualified Researchers
EARLIFirstMaternalInterview_20170114.zip	Other	First Maternal Interview Data for Jan 15, 2017 submission	Qualified Researchers
EARLI_DietaryHistoryQuestionnaires_20170114.zip	Other	Dietary History Data Jan 15, 2017 submission	Qualified Researchers

Grant Information:

Project Number	Title	Start Date	Original End Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
R01ES016443-01	Early Autism Risk Longitudinal Investigation (EARLI) Network	04/01/2008	03/31/2013	03/31/2013	4315	763	DREXEL UNIVERSITY	$6,483,811.00

Clinical Trials:

helpcenter.collection.general-tab

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).

Glossary

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.

Contact NDA Help Desk

ID	Name	Created Date	Status	Type
347	EARLI Sperm DNAm	07/09/2015	Approved	Omics
924	EARLI Placenta WGBS	05/24/2018	Approved	Omics

helpcenter.collection.experiments-tab

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.

Glossary

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.

Contact NDA Help Desk

Shared Data:

Title	Type	Number of Subjects
Autism Diagnostic Observation Schedule (ADOS) - Module 4	Clinical Assessments	5
Autism Diagnostic Observation Schedule (ADOS)- Module 1	Clinical Assessments	91
Autism Diagnostic Observation Schedule (ADOS)- Module 2	Clinical Assessments	89
Autism Diagnostic Observation Schedule (ADOS)- Module 3	Clinical Assessments	55
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 1	Clinical Assessments	45
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 2	Clinical Assessments	89
Autism Observation Scale for Infants	Clinical Assessments	212
CSBS DP Infant-Toddler Checklist	Clinical Assessments	177
Child Behavior Checklist (CBCL) 1-5	Clinical Assessments	291
Child Behavior Checklist (CBCL) 6-18	Clinical Assessments	82
Depression Survey	Clinical Assessments	213
Dysmorphology Survey	Clinical Assessments	365
EARLI Intervention History	Clinical Assessments	190
Genomics Sample	Genomics	176
Genomics Subject	Genomics	176
Home Walk-Through Survey	Clinical Assessments	212
MacArthur-Bates CDI - Words and Gestures Form	Clinical Assessments	195
Mullen Scales of Early Learning	Clinical Assessments	245
Placental Morphology	Clinical Assessments	129
Research Subject	Clinical Assessments	403
Sensory Experiences Questionnaire	Clinical Assessments	204
Social Communication Questionnaire (SCQ) - Lifetime	Clinical Assessments	360
Social Responsiveness Scale (SRS)	Clinical Assessments	138
Stress Survey	Clinical Assessments	213
Vineland-II - Parent and Caregiver Rating Form (2005)	Clinical Assessments	403
Weekly Pregnancy Diary	Clinical Assessments	182

helpcenter.collection.shared-data-tab

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.

Glossary

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.

Contact NDA Help Desk

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 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 ID	Study	Title	Journal	Authors	Date	Status
40869759	Create Study	Testing the Development of a Diet-Based Bisphenol a Score to Facilitate Studies on Child Neurodevelopment: A Pilot Project.	International journal of environmental research and public health	Patti, Marisa A; Kivumbi, Apollo; Rando, Juliette; Song, Ashley; Croen, Lisa A; Schmidt, Rebecca J; Volk, Heather E; Lyall, Kristen	July 25, 2025	Not Determined
40331055	Create Study	The association of prenatal ambient air pollution with placental epigenetic gestational age at birth.	Environmental epidemiology (Philadelphia, Pa.)	He, Zhengting; Song, Ashley Y; Schrott, Rose; Feinberg, Jason I; Bakulski, Kelly M; Benke, Kelly S; Croen, Lisa A; Hertz-Picciotto, Irva; Schmidt, Rebecca J; Lyall, Kristen; Newschaffer, Craig J; Fallin, M Daniele; Volk, Heather E; Ladd-Acosta, Christine	June 1, 2025	Not Determined
39235189	Create Study	Characterizing self-reported physical activity before and during a subsequent pregnancy among parents in a familial autism cohort.	Autism : the international journal of research and practice	G Bragg, Megan; Vesey, Olivia; Chavarro, Jorge E; Hart, Jaime E; Tabb, Loni Philip; Weisskopf, Marc G; Croen, Lisa A; Fallin, Daniele; Hertz-Picciotto, Irva; Newschaffer, Craig; Schmidt, Rebecca J; Volk, Heather; Lyall, Kristen	January 1, 2025	Not Determined
38436527	Create Study	Gestational thyroid hormones and autism-related traits in the EARLI and HOME studies.	Autism research : official journal of the International Society for Autism Research	Zhong, Caichen; Rando, Juliette; Patti, Marisa A; Braun, Joseph M; Chen, Aimin; Xu, Yingying; Lanphear, Bruce P; Yolton, Kimberly; Croen, Lisa A; Fallin, M Daniele; Hertz-Picciotto, Irva; Newschaffer, Craig J; Lyall, Kristen	April 1, 2024	Not Determined
38317694	Create Study	Prenatal Metal Exposures and Child Social Responsiveness Scale Scores in 2 Prospective Studies.	Environmental health insights	Yu, Emma X; Dou, John F; Volk, Heather E; Bakulski, Kelly M; Benke, Kelly; Hertz-Picciotto, Irva; Schmidt, Rebecca J; Newschaffer, Craig J; Feinberg, Jason I; Daniels, Jason; Fallin, Margaret Daniele; Ladd-Acosta, Christine; Hamra, Ghassan B	January 1, 2024	Not Determined
38045240	Create Study	Exposure to heavy metals in utero and autism spectrum disorder at age 3: A meta-analysis of two longitudinal cohorts of siblings of children with autism.	medRxiv : the preprint server for health sciences	Dou, John F; Schmidt, Rebecca J; Volk, Heather E; Nitta, Manon M; Feinberg, Jason I; Newschaffer, Craig J; Croen, Lisa A; Hertz-Picciotto, Irva; Fallin, M Daniele; Bakulski, Kelly M	December 5, 2023	Not Determined
37820223	Create Study	A Mixture of Urinary Phthalate Metabolite Concentrations During Pregnancy and Offspring Social Responsiveness Scale Scores.	Epidemiology (Cambridge, Mass.)	Yu, Emma X; Braun, Joseph M; Lyall, Kristen; Hertz-Picciotto, Irva; Fallin, M Daniele; Croen, Lisa A; Chen, Aimin; Xu, Yingying; Yolton, Kimberly; Newschaffer, Craig J; Hamra, Ghassan B	January 1, 2024	Not Determined
37661110	Create Study	Reply to E Ciappio et al.	The American journal of clinical nutrition	Sauder, Katherine A; Couzens, G Lance; Bailey, Regan L; Hockett, Christine W; Switkowski, Karen M; Lyall, Kristen; Kerver, Jean M; Dabelea, Dana; Maldonado, Luis E; O'Connor, Thomas G; Deoni, Sean Cl; Glueck, Deborah H; Catellier, Diane J; program collaborators for Environmental influences on Child Health Outcomes	September 1, 2023	Not Determined
37604382	Create Study	Identifying Foods That Optimize Intake of Key Micronutrients During Pregnancy.	The Journal of nutrition	Sauder, Katherine A; Cohen, Catherine C; Mueller, Noel T; Hockett, Christine W; Switkowski, Karen M; Maldonado, Luis E; Lyall, Kristen; Kerver, Jean M; Dabelea, Dana; O'Connor, Thomas G; Glueck, Deborah H; Melough, Melissa M; Couzens, G Lance; Catellier, Diane J; program collaborators for Environmental influences on Child Health Outcomes; ECHO Components—Coordinating Center; Smith, P B; Newby, K L; Benjamin, D K; Data Analysis Center; ECHO Awardees and Cohorts	October 1, 2023	Not Determined
37407168	Create Study	Reply to H Wang and M Chichlowski.	The American journal of clinical nutrition	Sauder, Katherine A; Couzens, Lance; Bailey, Regan L; Hockett, Christine W; Switkowski, Karen M; Lyall, Kristen; Kerver, Jean M; Dabelea, Dana; Maldonado, Luis E; O'Connor, Thomas G; Deoni, Sean Cl; Glueck, Deborah H; Catellier, Diane J; program collaborators for Environmental Influences on Child Health Outcomes	July 1, 2023	Not Determined
37140384	Create Study	Prepregnancy BMI, gestational weight gain, and susceptibility to autism-related traits: the EARLI and HOME studies.	Obesity (Silver Spring, Md.)	Patti, Marisa A; Croen, Lisa A; Chen, Aimin; Fallin, M Daniele; Khoury, Jane; Lyall, Kristen; Newschaffer, Craig; Hertz-Picciotto, Irva; Schmidt, Rebecca J; Yolton, Kimberly; Braun, Joseph M	May 1, 2023	Not Determined
37116678	Create Study	Associations of prenatal exposure to a mixture of persistent organic pollutants with social traits and cognitive and adaptive function in early childhood: Findings from the EARLI study.	Environmental research	Song, Ashley Y; Kauffman, Elizabeth M; Hamra, Ghassan B; Dickerson, Aisha S; Croen, Lisa A; Hertz-Picciotto, Irva; Schmidt, Rebecca J; Newschaffer, Craig J; Fallin, M Daniele; Lyall, Kristen; Volk, Heather E	July 15, 2023	Not Determined
37100868	Create Study	Epigenetic changes in sperm are associated with paternal and child quantitative autistic traits in an autism-enriched cohort.	Molecular psychiatry	Feinberg, Jason I; Schrott, Rose; Ladd-Acosta, Christine; Newschaffer, Craig J; Hertz-Picciotto, Irva; Croen, Lisa A; Daniele Fallin, M; Feinberg, Andrew P; Volk, Heather E	January 1, 2024	Not Determined
37019542	Create Study	Selecting a dietary supplement with appropriate dosing for 6 key nutrients in pregnancy.	The American journal of clinical nutrition	Sauder, Katherine A; Couzens, G Lance; Bailey, Regan L; Hockett, Christine W; Switkowski, Karen M; Lyall, Kristen; Kerver, Jean M; Dabelea, Dana; Maldonado, Luis E; O'Connor, Thomas G; Deoni, Sean Cl; Glueck, Deborah H; Catellier, Diane J; program collaborators for Environmental influences on Child Health Outcomes	April 1, 2023	Not Determined
36189953	Create Study	Associations between accelerated parental biologic age, autism spectrum disorder, social traits, and developmental and cognitive outcomes in their children.	Autism research : official journal of the International Society for Autism Research	Song, Ashley Y; Bakulski, Kelly; Feinberg, Jason I; Newschaffer, Craig; Croen, Lisa A; Hertz-Picciotto, Irva; Schmidt, Rebecca J; Farzadegan, Homayoon; Lyall, Kristen; Fallin, M Daniele; Volk, Heather E; Ladd-Acosta, Christine	December 1, 2022	Not Determined
35918756	Create Study	Prenatal vitamin intake in first month of pregnancy and DNA methylation in cord blood and placenta in two prospective cohorts.	Epigenetics & chromatin	Dou, John F; Middleton, Lauren Y M; Zhu, Yihui; Benke, Kelly S; Feinberg, Jason I; Croen, Lisa A; Hertz-Picciotto, Irva; Newschaffer, Craig J; LaSalle, Janine M; Fallin, Daniele; Schmidt, Rebecca J; Bakulski, Kelly M	August 2, 2022	Not Determined
35870502	Create Study	The associations between prenatal phthalate exposure measured in child meconium and cognitive functioning of 12-month-old children in two cohorts at elevated risk for adverse neurodevelopment.	Environmental research	Mathew, Leny; Snyder, Nathaniel W; Lyall, Kristen; Lee, Brian K; McClure, Leslie A; Elliott, Amy J; Newschaffer, Craig J; program collaborators for Environmental influences on Child Health Outcomes	November 1, 2022	Not Determined
35807909	Create Study	Maternal Dietary Patterns during Pregnancy and Child Autism-Related Traits: Results from Two US Cohorts.	Nutrients	Vecchione, Rachel; Wang, Siwen; Rando, Juliette; Chavarro, Jorge E; Croen, Lisa A; Fallin, M Daniele; Hertz-Picciotto, Irva; Newschaffer, Craig J; Schmidt, Rebecca J; Lyall, Kristen	June 30, 2022	Not Determined
35764940	Create Study	Placental morphology in association with autism-related traits in the EARLI study.	BMC pregnancy and childbirth	Zhong, Caichen; Shah, Ruchit; Rando, Juliette; Park, Bo; Girardi, Theresa; Walker, Cheryl K; Croen, Lisa A; Fallin, M Daniele; Hertz-Picciotto, Irva; Lee, Brian K; Schmidt, Rebecca J; Volk, Heather E; Newschaffer, Craig J; Salafia, Carolyn M; Lyall, Kristen	June 28, 2022	Not Determined
35678944	Create Study	Examining associations between prenatal biomarkers of oxidative stress and ASD-related outcomes using quantile regression.	Journal of autism and developmental disorders	Carey, Meghan E; Rando, Juliette; Melnyk, Stepan; James, S Jill; Snyder, Nathaniel; Salafia, Carolyn; Croen, Lisa A; Fallin, M Daniele; Hertz-Picciotto, Irva; Volk, Heather; Newschaffer, Craig; Lyall, Kristen	August 1, 2023	Not Determined
35261202	Create Study	Prenatal exposure to pesticide residues in the diet in association with child autism-related traits: Results from the EARLI study.	Autism research : official journal of the International Society for Autism Research	Joyce, Emily E; Chavarro, Jorge E; Rando, Juliette; Song, Ashley Y; Croen, Lisa A; Fallin, M Daniele; Hertz-Picciotto, Irva; Schmidt, Rebecca J; Volk, Heather; Newschaffer, Craig J; Lyall, Kristen	May 1, 2022	Not Determined
34494118	Create Study	Disparities in Risks of Inadequate and Excessive Intake of Micronutrients during Pregnancy.	The Journal of nutrition	Sauder, Katherine A; Harte, Robyn N; Ringham, Brandy M; Guenther, Patricia M; Bailey, Regan L; Alshawabkeh, Akram; Cordero, José F; Dunlop, Anne L; Ferranti, Erin P; Elliott, Amy J; Mitchell, Diane C; Hedderson, Monique M; Avalos, Lyndsay A; Zhu, Yeyi; Breton, Carrie V; Chatzi, Leda; Ran, Jin; Hertz-Picciotto, Irva; Karagas, Margaret R; Sayarath, Vicki; Hoover, Joseph; MacKenzie, Debra; Lyall, Kristen; Schmidt, Rebecca J; O'Connor, Thomas G; Barrett, Emily S; Switkowski, Karen M; Comstock, Sarah S; Kerver, Jean M; Trasande, Leonardo; Tylavsky, Frances A; Wright, Rosalind J; Kannan, Srimathi; Mueller, Noel T; Catellier, Diane J; Glueck, Deborah H; Dabelea, Dana; Program Collaborators for Environmental influences on Child Health Outcomes (ECHO)	November 2, 2021	Not Determined
34280640	Create Study	Prenatal phthalate exposure measurement: A comparison of metabolites quantified in prenatal maternal urine and newborn''s meconium.	The Science of the total environment	Mathew, Leny; Snyder, Nathaniel W; Lyall, Kristen; Lee, Brian K; McClure, Leslie A; Elliott, Amy J; Newschaffer, Craig J	November 20, 2021	Not Determined
34110557	Create Study	The Association of Prenatal Vitamins and Folic Acid Supplement Intake with Odds of Autism Spectrum Disorder in a High-Risk Sibling Cohort, the Early Autism Risk Longitudinal Investigation (EARLI).	Journal of autism and developmental disorders	Brieger, Katharine K; Bakulski, Kelly M; Pearce, Celeste L; Baylin, Ana; Dou, John F; Feinberg, Jason I; Croen, Lisa A; Hertz-Picciotto, Irva; Newschaffer, Craig J; Fallin, M Daniele; Schmidt, Rebecca J	June 1, 2022	Not Determined
33794742	Create Study	Maternal blood metal concentrations and whole blood DNA methylation during pregnancy in the Early Autism Risk Longitudinal Investigation (EARLI).	Epigenetics	Aung, Max T; M Bakulski, Kelly; Feinberg, Jason I; F Dou, John; D Meeker, John; Mukherjee, Bhramar; Loch-Caruso, Rita; Ladd-Acosta, Christine; Volk, Heather E; Croen, Lisa A; Hertz-Picciotto, Irva; Newschaffer, Craig J; Fallin, M Daniele	March 1, 2022	Not Determined

helpcenter.collection.publications-tab

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).

Glossary

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.

Contact NDA Help Desk

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 Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Genomics/omics	763	07/15/2009	176	11/15/2009	176	Approved
Research Subject and Pedigree	763	07/15/2009	466	11/15/2009	466	Approved

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 Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Mullen Scales of Early Learning	200	07/15/2009	245	11/15/2009	245	Approved
ADOS	124	07/15/2009	340	11/15/2009	340	Approved
Social Responsiveness Scale (SRS)	334	07/15/2009	138	11/15/2009	138	Approved
Sensory Experiences Questionnaire (SEQ)	302	07/15/2009	204	11/15/2009	204	Approved
Social Communication Questionnaire (SCQ)	173	07/15/2009	360	11/15/2009	360	Approved
Child Behavior Checklist (CBCL)	173	07/15/2009	373	11/15/2009	373	Approved
Enviromental Evaluation	173	07/15/2009	212	11/15/2009	212	Approved
Autism Observation Scale for Infants (AOSI)	191	07/15/2009	212	11/15/2009	212	Approved
Communication and Symbolic Behavior Scales (CSBS)	229	07/15/2009	177	11/15/2009	177	Approved
Diet/Food Diary/Log	215	07/15/2009	0	11/15/2009	0	Approved
MacArthur Bates Communicative Development Inventory	226	07/15/2009	195	11/15/2009	195	Approved
Intervention History	194	07/15/2009	190	11/15/2009	190	Approved
Physical Exam	129	07/15/2009	129	11/15/2009	129	Approved
Depression Questionnaire	130	07/15/2009	213	11/15/2009	213	Approved
Stress Questionnaires	167	07/15/2009	213	11/15/2009	213	Approved
Exposure Diary	302	07/15/2009	182	11/15/2009	182	Approved
Dysmorphology Survey	227	07/15/2009	365	11/15/2009	365	Approved
Vineland (Parent and Caregiver)	194	07/15/2009	403	11/15/2009	403	Approved

Structure not yet defined

No Status history for this Data Expected has been recorded yet

helpcenter.collection.data-expected-tab

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.

Glossary

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.

Contact NDA Help Desk

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 NameFilter by Study Name	DOIFilter by DOI	AbstractFilter by Abstract	Collection/Study SubjectsFilter by Collection/Study Subjects	Data UsageFilter by Data Usage	StateFilter by State
Examining the validity of the use of ratio IQs in psychological assessments	10.15154/1522624	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.	245/17423	Secondary Analysis	Shared
The importance of low IQ to early diagnosis of autism	10.15154/1528140	Some 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.	242/6323	Secondary Analysis	Shared
Prognostic early snapshot stratification of autism based on adaptive functioning	10.15154/0z1c-1d37	A 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.	148/3517	Secondary Analysis	Shared
Investigating autism etiology and heterogeneity by decision tree algorithm	10.15154/1518655	Autism 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.	134/3382	Secondary Analysis	Shared
Psychometric Analysis of the Social Communication Questionnaire Using an Item-Response Theory Framework: Implications for the Use of the Lifetime and Current Forms	10.15154/1158938	The Social Communication Questionnaire (SCQ) was developed as a screener of Autism Spectrum Disorder (ASD). To date, the majority of the SCQ utility studies focused on its external validity (e.g., ROC curve analyses), but very few have addressed the internal validity issues. With samples consisting of 2,134 individuals available from the National Database for Autism Research (NDAR), the current study examined the factor structure, item-level characteristics, and measurement equivalence of the SCQ forms (i.e., Lifetime form and Current form) using both the classical true score theory and the item response theory (IRT). While our findings indicate sufficient psychometric properties of the SCQ Lifetime form, measurement issues emerged with respect to the SCQ Current form. These issues include lower internal consistencies, a weaker factor structure, lower item discriminations, significant pseudo-guessing effects, and subscale-level measurement bias. Thus, we caution researchers and clinicians about the use of the SCQ Current form. In particular, it seems inappropriate to use the Current form as an alternative to the Lifetime form among children younger than 5 years old or under other special situations (e.g., teacher-report data), although such practices were advised by the publisher of the SCQ. Instead, we recommend modifying the wording of the Lifetime form items rather than switching to the Current form where a 3-month timeframe is specified for responding to SCQ items. Future studies may consider investigating the association between the temporality of certain behaviors and the individual’s potential for being diagnosed with ASD, as well as the age neutrality of the SCQ.	192/2054	Secondary Analysis	Shared
Unravelling the Collective Diagnostic Power Behind the Features in the Autism Diagnostic Observation Schedule	10.15154/1421921	Background: Autism is a group of heterogeneous disorders defined by deficits in social interaction and communication. Typically, diagnosis depends on the results of a behavioural examination called the Autism Diagnostic Observation Schedule (ADOS). Unfortunately, administration of the ADOS exam is time-consuming and requires a significant amount of expert intervention, leading to delays in diagnosis and access to early intervention programs. The diagnostic power of each feature in the ADOS exam is currently unknown. Our hypothesis is that certain features could be removed from the exam without a significant reduction in diagnostic accuracy, sensitivity or specificity. Objective: Determine the smallest subset of predictive features in ADOS module-1 (an exam variant for patients with minimal verbal skills). Methodology: ADOS module-1 datasets were acquired from the Autism Genetic Resource Exchange and the National Database for Autism Research. The datasets contained 2572 samples with the following labels: autism (1763), autism spectrum (513), and non-autism (296). The datasets were used as input to 4 different cost-sensitive classifiers in Weka (functional trees, LADTree, logistic model trees, and PART). For each classifier, a 10-fold cross validation was preformed and the number of predictive features, accuracy, sensitivity, and specificity was recorded. Results & Conclusion: Each classifier resulted in a reduction of the number of ADOS features required for autism diagnosis. The LADtree classifier was able to obtain the largest reduction, utilizing only 10 of 29 ADOS module-1 features (96.8% accuracy, 96.9% sensitivity, and 95.9% specificity). Overall, these results are a step towards a more efficient behavioural exam for autism diagnosis.	91/1832	Secondary Analysis	Shared
Sensorimotor variability distinguishes early features of cognition in toddlers with autism	10.15154/qfej-cf04	The potential role of early sensorimotor features to atypical human cognition in autistic children has received surprisingly little attention given that appropriate movements are a crucial element that connects us to other people. Crucially it is sensorimotor function prior to the development of autism which would be of most interest in terms of establishing causal links. We examined movements acquired during natural sleep in over 200 toddlers recruited for neuroimaging studies, months before they were diagnosed with Autism Spectrum Disorder (ASD) or were ascertained as typically developing. We show there are significant correlations between objective, quantitative features of the distribution of head speed in the scanner (coefficient of variance and skewness) and subsequent cognitive abilities (intelligence quotient, IQ) in these children. Relative to higher-IQ ASD toddlers, those with lower-IQ had significantly altered sensorimotor features. Remarkably, we found that higher cognitive abilities in autistic toddlers confer resilience to atypical movement, as sensorimotor features in higher-IQ ASD toddlers were indistinguishable from those of typically developing healthy control toddlers. In a second set of analyses, we examined general motor skills assessed using observational instruments during wakefulness in an independent sample of over 1,000 infants and toddlers who received ASD diagnoses by 3-4 years. We detected significantly lower motor scores for lower-IQ vs. higher IQ autistic children, at 6, 12, 18, 24, and 30 months. We suggest that the altered movement patterns may affect key autistic behaviors in those with lower intelligence by affecting sensorimotor learning mechanisms. Atypical sensorimotor functioning is a novel, key feature in lower-IQ early childhood autism.	58/1078	Secondary Analysis	Shared
Automated Autism Diagnosis using Phenotypic and Genotypic Attributes: Phase I	10.15154/1343559	The ultimate goal of this project is to develop a predictive system that can automate the diagnosis process for autism using phenotypic and genotypic attributes for classification. At this time, only a first phase is being pursued: starting with scores from Autism Diagnostic Observation Schedule (ADOS) reports, use data-mining techniques to select the smallest set of the most informative evaluation points that can lead to similar behavioral diagnoses as using all report features. The effort began in March, 2016 after data access to NDAR was granted. This report describes the results from that date through the end of December 2016.	40/1045	Secondary Analysis	Shared
Revising the Social Communication Questionnaire scoring procedures for Autism Spectrum Disorder and potential Social Communication Disorder	10.15154/1195993	In analyzing data from the National Database for Autism Research, we examine revising the Social Communication Questionnaire (SCQ), a commonly used screening instrument for Autism Spectrum Disorder. A combination of Item Response Theory and Mokken scaling techniques were utilized to achieve this and abbreviated scoring of the SCQ is suggested. The psychometric sensitivity of this abbreviated SCQ was examined via bootstrapped Receiver Operator Characteristic (ROC) curve analyses. Additionally, we examined the sensitivity of the abbreviated and total scaled SCQ as it relates to a potential diagnosis of Social (Pragmatic) Communication Disorder (SCD). As SCD is a new disorder introduced with the fifth edition of the Diagnostic and Statistical Manual (DSM-5), we identified individuals with potential diagnosis of SCD among individuals with ASD via mixture modeling techniques using the same NDAR data. These analyses revealed two classes or clusters of individuals when considering the two core areas of impairment among individuals with ASD: social communication and restricted, repetitive patterns of behavior.	64/889	Secondary Analysis	Shared
The Sensitivity and Specificity of the Social Communication Questionnaire for Autism Spectrum Disorder with Respect to Age	10.15154/1195992	Scientific Abstract The Social Communication Questionnaire (SCQ) assesses communication skills and social functioning in screening for symptoms of autism-spectrum disorder (ASD). The SCQ is recommended for individuals between 4 to 40 years with a cutoff score of 15 for referral. Mixed findings have been reported regarding the recommended cutoff score’s ability to accurately classify an individual as at-risk for ASD (sensitivity) versus an individual as not at-risk for ASD (specificity). Based on a sample from the National Database for Autism Research (n=344; age: 1.58 to 25.92 years old), the present study examined the SCQ’s sensitivity versus specificity across a range of ages. We recommend that the cutoff scores for the SCQ be re-evaluated with age as a consideration. Lay Abstract The age neutrality of the Social Communication Questionnaire (SCQ) was examined as a common screener for ASD. Mixed findings have been reported regarding the recommended cutoff score’s ability to accurately classify an individual as at-risk for ASD (sensitivity) versus accurately classifying an individual as not at-risk for ASD (specificity). With a sample from the National Database for Autism Research, the present study examined the SCQ’s sensitivity versus specificity. Analyses indicated that the actual sensitivity and specificity scores were lower than initially reported by the creators of the SCQ.	62/339	Secondary Analysis	Shared
Does Anxiety Mediate the Relationship between Sensory Hyperresponsiveness and Restricted, Repetitive Behaviors during Early Development?	10.15154/1528765	Sensory hyperresponsiveness, anxiety, and restricted, repetitive behaviors are known to be associated with one another, especially in autistic youth, and may be important to the development and presentation of autism over time. Few studies, however, have studied the nature of this three-way relationship prospectively, or in young children at elevated likelihood for autism. The goals of the current study were to gain greater insight into the development of autism from a symptom level before a diagnosis can be made, and specifically, to examine the relationship between sensory hyperresponsiveness, anxiety, and restricted, repetitive behaviors across time during early development in children at elevated likelihood for autism. Extant longitudinal data for a group of children at elevated likelihood for autism (N = 147) were used to conduct path analyses for two mediation model configurations, which included measures of sensory hyperresponsiveness at baseline, and anxiety and restricted and repetitive behaviors at follow-up. Results did not indicate mediating effects for either model; however, higher levels of sensory hyperresponsiveness at baseline were significantly associated with higher levels of anxiety symptoms at follow-up (b = 0.09, SE = 0.04, β = 0.24, p = 0.005, 95% CIs [0.07, 0.40]). Findings suggest that sensory hyperresponsiveness during early development later predicts anxiety symptoms in children at elevated likelihood for autism, which is consistent with prior findings in both autistic (Green et al., 2012) and non-autistic children (Carpenter et al., 2019). Although we are unable to determine whether this is a unidirectional or bidirectional relationship in the current study given the lack of concurrent data on anxiety symptoms at baseline, this result adds to emerging research suggesting that sensory hyperresponsiveness may be a risk factor for later developing anxiety.	159/159	Secondary Analysis	Shared
Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort	10.15154/1195994	Epigenetic mechanisms such as altered DNA methylation have been suggested to play a role in autism, beginning with the classical association of Prader-Willi syndrome, an imprinting disorder, with autistic features. Here we tested for the relationship of paternal sperm DNA methylation with autism risk in offspring, examining an enriched-risk cohort of fathers of autistic children. We examined genome-wide DNA methylation (DNAm) in paternal semen biosamples obtained from an autism spectrum disorder (ASD) enriched-risk pregnancy cohort, the Early Autism Risk Longitudinal Investigation (EARLI) cohort, to estimate associations between sperm DNAm and prospective ASD development, using a 12-month ASD symptoms assessment, the Autism Observation Scale for Infants (AOSI). We analysed methylation data from 44 sperm samples run on the CHARM 3.0 array, which contains over 4 million probes (over 7 million CpG sites), including 30 samples also run on the Illumina Infinium HumanMethylation450 (450K) BeadChip platform (∼485 000 CpG sites). We also examined associated regions in an independent sample of post-mortem human brain ASD and control samples for which Illumina 450K DNA methylation data were available. Using region-based statistical approaches, we identified 193 differentially methylated regions (DMRs) in paternal sperm with a family-wise empirical P-value [family-wise error rate (FWER)] <0.05 associated with performance on the Autism Observational Scale for Infants (AOSI) at 12 months of age in offspring. The DMRs clustered near genes involved in developmental processes, including many genes in the SNORD family, within the Prader-Willi syndrome gene cluster. These results were consistent among the 75 probes on the Illumina 450K array that cover AOSI-associated DMRs from CHARM. Further, 18 of 75 (24%) 450K array probes showed consistent differences in the cerebellums of autistic individuals compared with controls. These data suggest that epigenetic differences in paternal sperm may contribute to autism risk in offspring, and provide evidence that directionally consistent, potentially related epigenetic mechanisms may be operating in the cerebellum of individuals with autism.	44/44	Primary Analysis	Shared
Placental gross shape differences in a high autism risk cohort and the general population.	10.15154/1421920	A growing body of evidence suggests that prenatal environment is important in Autism Spectrum Disorder (ASD) etiology. In this study, we compare placental shape features in younger siblings of children with ASD, who themselves are at high ASD risk, to a sample of low risk peers. Digital photographs of the fetal placenta surface and of the sliced placental disk from 129 high ASD risk newborns and from 267 newborns in the National Children’s Study Vanguard pilot were analysed to extract comparable measures of placental chorionic surface shape, umbilical cord displacement and disk thickness. Placental thickness measures were moderately higher in siblings of ASD cases. The placentas of ASD-case siblings were also rounder and more regular in perimeter than general population placentas. After stratification by sex, these across-group differences persisted for both sexes but were more pronounced in females. No significant differences were observed in cord insertion measures. Variations in placental shape features are generally considered to reflect flexibility in placental growth in response to changes in intrauterine environment as the placenta establishes and matures. Reduced placental shape variability observed in high ASD risk siblings compared to low-risk controls may indicate restricted ability to compensate for intrauterine changes.	30/30	Primary Analysis	Shared

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