NIMH Data Archive - Data

Genomics

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¹ Numbers reported are subjects by age

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

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

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Electrophysiological Markers for Interventions in Phelan-McDermid Syndrome and Idiopathic Autism #3022

General
Experiments (0)
Shared Data
Publications (21)
Data Expected (14)
Associated Studies (11)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Electrophysiological Markers for Interventions in Phelan-McDermid Syndrome and Idiopathic Autism
Collection Investigators:	Alexander Kolevzon
Collection Description:	Recent work suggests that up to 2 percent of individuals with autism spectrum disorder ASD and intellectual disability ID have deletions or point mutations in the SHANK3 gene, resulting in Phelan-McDermid syndrome PMS, and approximately 85 percent of people with PMS meet criteria for ASD. SHANK3 codes for a master scaffolding protein that forms a key framework in the postsynaptic density of glutamatergic excitatory synapses and plays a critical role in synaptic function. SHANK3 and glutamate pathways are implicated in multiple forms of ASD and this convergence implies shared biochemical pathways with potentially overlapping therapeutic targets. Thus, targeting SHANK3 deficiency in PMS as a specific genetic cause of ASD allows us to inform treatment in broader idiopathic ASD iASD. Our ongoing studies provide in-depth phenotyping of PMS, pointing toward a specific clinical and electrophysiological EEG profile. However, the efficacy of potential EEG biomarkers as a measure of treatment response remains to be determined. Preliminary data using visual evoked potentials VEPs to examine cortical excitatory postsynaptic potentials demonstrate promising links to disease mechanisms in PMS and iASD. Biomarkers and novel clinical measures for evaluating response to intervention have also been piloted successfully at our site in cohorts of patients with PMS and iASD. We have identified a unique VEP profile of excitatory deficits in PMS markedly reduced P60-N75 amplitude that is also present in a subset of children with iASD. Here, we propose to extend this work to a larger sample in PMS and to parallel excitatory processes in the auditory domain, in order to stratify individuals with iASD and select those we predict will show response to IGF-1. We will enroll 150 children 60 PMS 90 iASD age 5-12 years, specifically recruiting intellectually disabled and minimally verbal children given the prominence of this profile in PMS and the critical need to address this group in broader ASD research. Our short-term goal is to show that select electrophysiological markers in PMS are relevant to iASD and predictive of treatment response. Our long-term goal is to optimize treatment selection in iASD by establishing biological signatures derived from PMS that are a useful for predicting treatment responders, and b responsive to intervention. The expected outcome of this study is to establish the feasibility of electrophysiological biomarkers for use in clinical trials in PMS and iASD and to define a biological profile that will mark a subset of patients with iASD likely to show neural and clinical response to IGF-1.
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	08/19/2018
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$1,457,785.00
Subjects Shared:	47
Collection DOI:	10.15154/wbgg-a193

{"values":[]}

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Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

Grant Information:

Project Number	Title	Start Date	Original End Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
R01NS105845-01	Electrophysiological Markers for Interventions in Phelan-McDermid Syndrome and Idiopathic Autism	05/15/2018	04/30/2023	04/30/2023	300	179	ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI	$1,457,785.00

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.

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ID	Name	Created Date	Status	Type
No records found.

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.

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Shared Data:

Title	Type	Number of Subjects
Aberrant Behavior Checklist (ABC) - Community	Clinical Assessments	39
Autism Diagnostic Interview, Revised (ADI-R)	Clinical Assessments	3
Autism Diagnostic Observation Schedule (ADOS)- Module 1	Clinical Assessments	2
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 1	Clinical Assessments	26
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 2	Clinical Assessments	6
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 3	Clinical Assessments	9
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Toddler Module	Clinical Assessments	3
DAS-II: Differential Ability Scales 2nd Ed. School Age	Clinical Assessments	1
DAS-II:Differential Ability Scales 2nd Ed. Early Years	Clinical Assessments	7
MacArthur-Bates CDI - Words and Gestures Form	Clinical Assessments	4
Mullen Scales of Early Learning	Clinical Assessments	25
Repetitive Behavior Scale - Revised (RBS-R)	Clinical Assessments	4
Sensory Profile Caregiver	Clinical Assessments	4
Vineland 3	Clinical Assessments	39
Wechsler Intelligence Scale for Children V	Clinical Assessments	1

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.

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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
39563223	Create Study	Investigating social orienting in children with Phelan-McDermid syndrome and ''idiopathic'' autism.	Journal of neurodevelopmental disorders	San José Cáceres, Antonia; Wilkinson, Emma; Cooke, Jennifer; Baskett, Victoria; Blackmore, Charlotte; Crawley, Daisy Victoria; Durkin, Allison; Halpern, Danielle; Núñez, María; Siper, Page; Murphy, Declan G; Foss-Feig, Jennifer; Kolevzon, Alexander; Loth, Eva	November 19, 2024	Not Determined
39257296	Create Study	Aortic Root Dilation and Genotype Associations in Phelan-McDermid Syndrome.	American journal of medical genetics. Part A	Gluckman, Jake; Levy, Tess; Friedman, Kate; Garces, Francesca; Filip-Dhima, Rajna; Quinlan, Aisling; Iannotti, Isabelle; Pekar, Margaret; Hernandez, Alexandra Lopez; Nava, Madison T; Kravets, Elijah; Siegel, Abigail; Bernstein, Jonathan A; Berry-Kravis, Elizabeth; Powell, Craig M; Soorya, Latha Valluripalli; Thurm, Audrey; Srivastava, Siddharth; Buxbaum, Joseph D; Sahin, Mustafa; Kolevzon, Alexander; Gelb, Bruce D; Developmental Synaptopathies Consortium	January 1, 2025	Not Determined
38766168	Create Study	Phenotypical divergence between self-reported and clinically ascertained autism.	Research square	Banker, Sarah; Schafer, Mathew; Harrington, Miles; Na, Soojung; Barkley, Sarah; Trayvick, Jadyn; Peters, Arabella; Thinakaran, Abigaël; Foss-Feig, Jennifer; Schiller, Daniela; Gu, Xiaosi	May 7, 2024	Not Determined
38730350	Create Study	Clinical, genetic, and cognitive correlates of seizure occurrences in Phelan-McDermid syndrome.	Journal of neurodevelopmental disorders	Levy, Tess; Gluckman, Jacob; Siper, Paige M; Halpern, Danielle; Zweifach, Jessica; Filip-Dhima, Rajna; Holder Jr, J Lloyd; Trelles, M Pilar; Johnson, Kristina; Bernstein, Jonathan A; Berry-Kravis, Elizabeth; Powell, Craig M; Soorya, Latha Valluripalli; Thurm, Audrey; Buxbaum, Joseph D; Sahin, Mustafa; Kolevzon, Alexander; Srivastava, Siddharth; Developmental Synaptopathies Consortium	May 10, 2024	Not Determined
37849292	Create Study	Gait Abnormalities in Children with Phelan-McDermid Syndrome.	Journal of child neurology	Frank, Yitzchak; Levy, Tess; Lozano, Reymundo; Friedman, Kate; Underwood, Slayton; Kostic, Ana; Walker, Hannah; Kolevzon, Alexander	December 1, 2023	Not Determined
37392087	Create Study	Updated consensus guidelines on the management of Phelan-McDermid syndrome.	American journal of medical genetics. Part A	Srivastava, Siddharth; Sahin, Mustafa; Buxbaum, Joseph D; Berry-Kravis, Elizabeth; Soorya, Latha Valluripalli; Thurm, Audrey; Bernstein, Jonathan A; Asante-Otoo, Afua; Bennett Jr, William E; Betancur, Catalina; Brickhouse, Tegwyn H; Passos Bueno, Maria Rita; Chopra, Maya; Christensen, Celanie K; Cully, Jennifer L; Dies, Kira; Friedman, Kate; Gummere, Brittany; Holder Jr, J Lloyd; Jimenez-Gomez, Andres; Kerins, Carolyn A; Khan, Omar; Kohlenberg, Teresa; Lacro, Ronald V; Levi, Lori A; Levy, Tess; Linnehan, Diane; Eva, Loth; Moshiree, Baharak; Neumeyer, Ann; Paul, Scott M; Phelan, Katy; Persico, Antonio; Rapaport, Robert; Rogers, Curtis; Saland, Jeffrey; Sethuram, Swathi; Shapiro, Janine; Tarr, Phillip I; White, Kerry M; Wickstrom, Jordan; Williams, Kent M; Winrow, Dana; Wishart, Brian; Kolevzon, Alexander	August 1, 2023	Not Determined
36276299	Create Study	Large 22q13.3 deletions perturb peripheral transcriptomic and metabolomic profiles in Phelan-McDermid syndrome.	HGG advances	Breen, Michael S; Fan, Xuanjia; Levy, Tess; Pollak, Rebecca M; Collins, Brett; Osman, Aya; Tocheva, Anna S; Sahin, Mustafa; Berry-Kravis, Elizabeth; Soorya, Latha; Thurm, Audrey; Powell, Craig M; Bernstein, Jonathan A; Kolevzon, Alexander; Buxbaum, Joseph D; Developmental Synaptopathies Consortium	January 12, 2023	Not Determined
35592263	Create Study	Neural Markers of Auditory Response and Habituation in Phelan-McDermid Syndrome.	Frontiers in neuroscience	Isenstein, Emily L; Grosman, Hannah E; Guillory, Sylvia B; Zhang, Yian; Barkley, Sarah; McLaughlin, Christopher S; Levy, Tess; Halpern, Danielle; Siper, Paige M; Buxbaum, Joseph D; Kolevzon, Alexander; Foss-Feig, Jennifer H	January 1, 2022	Not Determined
35395866	Create Study	Clinical trial of insulin-like growth factor-1 in Phelan-McDermid syndrome.	Molecular autism	Kolevzon, A; Breen, M S; Siper, P M; Halpern, D; Frank, Y; Rieger, H; Weismann, J; Trelles, M P; Lerman, B; Rapaport, R; Buxbaum, J D	April 8, 2022	Not Determined
35093163	Create Study	A proof-of-concept study of growth hormone in children with Phelan-McDermid syndrome.	Molecular autism	Sethuram, S; Levy, T; Foss-Feig, J; Halpern, D; Sandin, S; Siper, P M; Walker, H; Buxbaum, J D; Rapaport, R; Kolevzon, A	January 29, 2022	Not Determined
34863106	Create Study	Social visual attentional engagement and memory in Phelan-McDermid syndrome and autism spectrum disorder: a pilot eye tracking study.	Journal of neurodevelopmental disorders	Guillory, Sylvia B; Baskett, Victoria Z; Grosman, Hannah E; McLaughlin, Christopher S; Isenstein, Emily L; Wilkinson, Emma; Weissman, Jordana; Britvan, Bari; Trelles, M Pilar; Halpern, Danielle B; Buxbaum, Joseph D; Siper, Paige M; Wang, A Ting; Kolevzon, Alexander; Foss-Feig, Jennifer H	December 4, 2021	Not Determined
34559195	Create Study	Strong evidence for genotype-phenotype correlations in Phelan-McDermid syndrome: results from the developmental synaptopathies consortium.	Human molecular genetics	Levy, Tess; Foss-Feig, Jennifer H; Betancur, Catalina; Siper, Paige M; Trelles-Thorne, Maria Del Pilar; Halpern, Danielle; Frank, Yitzchak; Lozano, Reymundo; Layton, Christina; Britvan, Bari; Bernstein, Jonathan A; Buxbaum, Joseph D; Berry-Kravis, Elizabeth; Powell, Craig M; Srivastava, Siddharth; Sahin, Mustafa; Soorya, Latha; Thurm, Audrey; Kolevzon, Alexander; Developmental Synaptopathies Consortium	February 21, 2022	Not Determined
34521563	Create Study	Hippocampal contributions to social and cognitive deficits in autism spectrum disorder.	Trends in neurosciences	Banker, Sarah M; Gu, Xiaosi; Schiller, Daniela; Foss-Feig, Jennifer H	October 1, 2021	Not Determined
34303785	Create Study	Visual Evoked Potential Abnormalities in Phelan-McDermid Syndrome.	Journal of the American Academy of Child and Adolescent Psychiatry	Siper, Paige M; Rowe, Mikaela A; Guillory, Sylvia B; Rouhandeh, Audrey A; George-Jones, Julia L; Tavassoli, Teresa; Lurie, Stacey; Zweifach, Jessica; Weissman, Jordana; Foss-Feig, Jennifer; Halpern, Danielle; Trelles, M Pilar; Mulhern, Maureen S; Brittenham, Chloe; Gordon, James; Zemon, Vance; Buxbaum, Joseph D; Kolevzon, Alexander	April 1, 2022	Not Determined
34206779	Create Study	Sensory Reactivity Phenotype in Phelan-McDermid Syndrome Is Distinct from Idiopathic ASD.	Genes	Tavassoli, Teresa; Layton, Christina; Levy, Tess; Rowe, Mikaela; George-Jones, Julia; Zweifach, Jessica; Lurie, Stacey; Buxbaum, Joseph D; Kolevzon, Alexander; Siper, Paige M	June 26, 2021	Not Determined
33966481	Create Study	Reduced engagement of visual attention in children with autism spectrum disorder.	Autism : the international journal of research and practice	McLaughlin, Christopher S; Grosman, Hannah E; Guillory, Sylvia B; Isenstein, Emily L; Wilkinson, Emma; Trelles, Maria Del Pilar; Halpern, Danielle B; Siper, Paige M; Kolevzon, Alexander; Buxbaum, Joseph D; Wang, A Ting; Foss-Feig, Jennifer H	October 1, 2021	Not Determined
32406614	Create Study	Psychometric Study of the Social Responsiveness Scale in Phelan-McDermid Syndrome.	Autism research : official journal of the International Society for Autism Research	Gergoudis, Kellie; Weinberg, Alan; Templin, Jonathan; Farmer, Cristan; Durkin, Alison; Weissman, Jordana; Siper, Paige; Foss-Feig, Jennifer; Del Pilar Trelles, Maria; Bernstein, Jonathan A; Buxbaum, Joseph D; Berry-Kravis, Elizabeth; Powell, Craig M; Sahin, Mustafa; Soorya, Latha; Thurm, Audrey; Kolevzon, Alexander; Developmental Synaptopathies Consortium	August 1, 2020	Not Determined
32050889	Create Study	Psychiatric illness and regression in individuals with Phelan-McDermid syndrome.	Journal of neurodevelopmental disorders	Kohlenberg, Teresa M; Trelles, M Pilar; McLarney, Brittany; Betancur, Catalina; Thurm, Audrey; Kolevzon, Alexander	February 12, 2020	Not Determined
31879555	Create Study	Neuropsychiatric decompensation in adolescents and adults with Phelan-McDermid syndrome: a systematic review of the literature.	Molecular autism	Kolevzon, Alexander; Delaby, Elsa; Berry-Kravis, Elizabeth; Buxbaum, Joseph D; Betancur, Catalina	January 1, 2019	Not Determined
31655722	Create Study	Bilingualism in Autism Spectrum Disorder: Finding Meaning in Translation.	Journal of the American Academy of Child and Adolescent Psychiatry	Trelles, M Pilar; Castro, Karen	November 1, 2019	Not Determined
31521210	Create Study	Looking Under the Hood of Convergent Behavioral Deficits in Schizophrenia and Autism.	Biological psychiatry	Foss-Feig, Jennifer H	October 1, 2019	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
Research Subject and Pedigree	150	01/15/2019	77	05/15/2019	0	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	80	01/15/2020	62	05/15/2020	25	Approved
ABC Community	150	01/15/2020	97	05/15/2020	39	Approved
ADOS	150	01/15/2020	89	05/15/2020	45	Approved
ADI-R	150	01/15/2020	95	05/15/2020	3	Approved
Wechsler Abbreviated Scale of Intelligence (WASI)	5	01/15/2020	0	05/15/2020	0	Approved
Wechsler Intelligence Scale for Children	20	01/15/2020	9	05/15/2020	1	Approved
DAS-II: Differential Ability Scales	20	01/15/2020	12	05/15/2020	8	Approved
MacArthur Bates Communicative Development Inventory	64	01/15/2020	91	05/15/2020	4	Approved
Repetitive Behavior Scale - Revised (RBS-R)	67	01/15/2020	94	05/15/2020	4	Approved
Wechsler Preschool Primary Scale Intelligence (WPPSI)	5	01/15/2020	1	05/15/2020	0	Approved
Stanford Binet	20	01/15/2020	18	05/15/2020	0	Approved
Sensory Profile	63	01/15/2020	90	05/15/2020	4	Approved
Vineland (Parent and Caregiver)	150	01/15/2020	94	05/15/2020	39	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.	38/17423	Secondary Analysis	Shared
Examining Diagnostic Trends and Gender Differences in the ADOS-II	10.15154/jxd2-vw05	Approximately 3–4 boys for every girl meet the clinical criteria for autism in studies of community diagnostic patterns and studies of autism using samples of convenience. However, girls with autism have been hypothesized to be underdiagnosed, possibly because they may present with differing symptom profiles as compared to boys. This secondary data analysis used the National Database of Autism Research (NDAR) to examine how gender and symptom profiles are associated with one another in a gold standard assessment of autism symptoms, the Autism Diagnostic Observation Schedule II (ADOS-II; Lord, C., Luyster, R., Guthrie, W., & Pickles A. (2012a). Patterns of developmental trajectories in toddlers with autism spectrum disorder. Journal of Consulting and Clinical Psychology, 80(3):477–489. https://doi.org/10.1037/a0027214. Epub 2012 Apr 16. PMID: 22506796, PMCID: PMC3365612). ADOS-II scores from 6183 children ages 6–14 years from 78 different studies in the NDAR indicated that gender was a significant predictor of total algorithm, restrictive and repetitive behavioral, and social communicative difficulties composite severity scores. These findings suggest that gender differences in ADOS scores are common in many samples and may reflect on current diagnostic practices.	25/5615	Secondary Analysis	Shared
Gender Differences: Confirmatory Factor Analysis of the ADOS-II	10.15154/4sxe-qh09	Purpose Recent research has suggested that autism may present differently in girls compared to boys, encouraging the exploration of a sex-differential diagnostic criteria. Gender differences in diagnostic assessments have been shown on the ADOS-II, such that, on average, females score significantly lower than males on all scales and are less likely to show atypicality on most items related to social communicative difficulties. Yet, gender differences in the latent structure of instruments like the ADOS-II have not been examined systematically. Methods As such, this secondary data analysis examined 4,100 youth diagnosed with autism (Mage = 9.9, 813 female & 3287 male) examined item response trends by gender on the ADOS-II Module 3. Results Multi-Group Confirmatory Factor Analysis results show that the factor loadings of four ADOS-II items differ across the genders. One SCD item and one RRB item are strongly related to the latent factor in the female group, while two RRB items have larger factor loadings in the male group. Conclusion The assumption of an identical latent factor structure for the ADOS-II Module 3 for males and females might not be justifiable. Possible diagnostic implications are discussed.	25/5615	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.	5/3517	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.	1/3382	Secondary Analysis	Shared
Imbalanced social-communicative and restricted repetitive behavior subtypes in autism spectrum disorder exhibit different neural circuitry	10.15154/1524418	Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.	3/1708	Secondary Analysis	Shared
Word Learning and Word Features	10.15154/1526346	Vocabulary composition and word-learning biases are closely interrelated in typical development. Learning new words involves attending to certain properties to facilitate word learning. Such word-learning biases are influenced by perceptually and conceptually salient word features, including high imageability, concreteness, and iconicity. This study examined the association of vocabulary knowledge and word features in young children with ASD (n = 280) and typically developing (TD) toddlers (n = 1,054). Secondary analyses were conducted using data from the National Database for Autism Research and the Wordbank database. Expressive vocabulary was measured using the MacArthur-Bates Communicative Development Inventory. Although the trajectories for concreteness, iconicity, and imageability are similar between children with ASD and TD toddlers, divergences were observed. Differences in imageability are seen early but resolve to a common trajectory; differences in iconicity are small but consistent; and differences in concreteness only emerge after both groups reach a simultaneous peak, before converging again. This study reports unique information about the nonlinear growth patterns associated with each word feature for and distinctions in these growth patterns between the groups.	1/280	Primary Analysis	Shared
Examining the Shape Bias in Young Autistic Children: A Vocabulary Composition Analysis	10.15154/wjfb-vy71	Shape is a salient object property and one of the first that children use to categorize objects under one label. Colunga and Sims (2017) suggest that noun vocabulary composition and word learning biases are closely interrelated in typical development. The current study examined the association between noun vocabulary knowledge and perceptual word features, specifically shape and material features. Participants included 249 autistic children and 1,245 non-autistic toddlers who were matched on expressive noun vocabulary size and gender. Nouns were categorized using the Samuelson and Smith (1999) noun feature database. A simple group comparison revealed no group differences in shape bias; both groups evidenced developing noun vocabularies that favored shape+solid and nonsolid+material nouns. However, the trajectory of evidence of shape bias as a function of vocabulary size differed between the groups, with autistic children demonstrating a reduced shape-bias initially. Future work should examine how children’s learning biases shift over development and whether the shape bias promotes lexical development to the same degree across groups.	3/249	Secondary Analysis	Shared
Modeling Vocabulary Growth in Autistic and Non-Autistic Children	10.15154/q64a-9k34	We assessed the goodness of fit of three models of vocabulary growth, with varying sensitivity to the structure of the environment and the learner’s internal state, to estimated vocabulary growth trajectories in autistic and non-autistic children. We first computed word-level acquisition norms that indicate the vocabulary size at which individual words tend to be learned by each group. We then evaluated how well network growth models based on natural language co-occurrence structure and word associations account for variance in the autistic and non-autistic acquisition norms. In addition to replicating key observations from prior work and observing that the growth models explained similar amounts of variance in each group, we found that autistic vocabulary growth also exhibits growth consistent with “the lure of the associates” model. Thus, both groups leverage semantic structure in the learning environment for vocabulary development, but autistic vocabulary growth is also strongly influenced by existing vocabulary knowledge.	2/247	Secondary Analysis	Shared
Semantic modeling 2023	10.15154/1528994	Although it is well documented that children with ASD are slower to develop their lexicons, we still have a limited understanding of the structure of early lexical knowledge in children with ASD. The current study uses network analysis and differential item functioning anlaysis to examine the structure of semantic knowledge, which may provide insight into the learning processes that influence early word learning.	4/208	Secondary Analysis	Shared
Semantic Network Modeling in Young Autistic Children	10.15154/z865-cy61	Background: Most young autistic children have delayed vocabulary growth relative to their non-autistic peers. Additionally, previous studies have revealed that autistic children are less likely to encode associated features of novel objects, suggesting inefficient encoding or different processes for acquiring semantic information about words. Recent network analyses of vocabulary growth revealed important relationships between early vocabulary acquisition and the structure of the sematic environment. Methods: We studied the expressive vocabularies of 970 non-autistic toddlers (Mage = 20.82 months) and 194 autistic children (Mage = 54.58 months) in two studies. The groups were vocabulary-matched (words produced: MAutistic = 213.60, MNon-autistic = 213.72). In study 1, we estimated their trajectories of semantic development using network analyses. Network structure was based on child-oriented adult-generated word associations. We compared child semantic networks according to indegree, average shortest path length, and clustering coefficient (features that holistically contribute to well-connected network structure). Then, in study 2, we attempted to relate vocabulary-level effects to word-level learning biases. Results: Study 1 revealed that autistic and non-autistic children are sensitive to the structure of their semantic environment. Both groups demonstrated nonlinear vocabulary trajectories that differed from random acquisition networks. Despite similarities, group differences were observed for each network metric. Differences were most pronounced for clustering coefficient (how closely connected groups of words are), with earlier peaks for autistic children. Study 2 demonstrated that many words differ in their expected vocabulary size of acquisition. Conclusions: Group differences at the vocabulary- and word-levels indicate that, although autistic children are learning from their semantic environment, they may be processing their semantic environment differently. These deviations indicate that autistic children have distinctive learning biases that may align with core autism features.	4/194	Secondary Analysis	Shared

* Data not on individual level

helpcenter.collection.associated-studies-tab

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.

Glossary

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.

Contact NDA Help Desk

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