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	Illumina Infinium PsychArray BeadChip Assay	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

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Data Structures:

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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.

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Data Expected Item	Original Sharing Date	New Sharing Date

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Human Brain Collection Core genomics data in post-mortem brain of psychiatric disorders #3151

General
Experiments (21)
Shared Data
Publications (13)
Data Expected (6)
Associated Studies (13)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Human Brain Collection Core genomics data in post-mortem brain of psychiatric disorders
Collection Investigators:	Stefano Marenco
Collection Description:	This postmortem study examines molecular, genetic and epigenetic signatures in the brains of hundreds of subjects with or without mental disorders conducted by the DIRP NIMH Human Brain Collection Core (HBCC). The brain tissues are obtained under protocols approved by the CNS IRB (NCT00001260), with the permission of the next-of-kin (NOK) through the Offices of the Chief Medical Examiners (MEOs) in the District of Columbia, Northern Virginia and Central Virginia. Additional samples were obtained from the University of Maryland Brain and Tissue Bank (contracts NO1-HD-4-3368 & NO1-HD-4-3383) (http://www.medschool.umaryland.edu/btbank/) and the Stanley Medical Research Institute (http://www.stanleyresearch.org/brain-research/). Clinical characterization, neuropathological screening, toxicological analyses, and dissections of various brain regions were performed as previously described (Lipska et al. 2006). All patients met DSM-IV criteria for a lifetime Axis I diagnosis of psychiatric disorders including schizophrenia or schizoaffective disorder, bipolar disorder and major depression. Controls had no history of psychiatric diagnoses or addictions.
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	03/28/2019
NIH Research Initiative:	Neuro Bio Bank (NBB)
Collection Phase:	Enrolling
Blinded Clinical Trial:	No
Subjects Shared:	1,360

{"values":[]}

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Funding Sources:

Funding Source Name	Funding Source URL
NIH - Contract	None

Supporting Documentation:

File Name	File Type	Description	Audience
schema_crosswalk_Uploaded.xlsx	Other	This is a schema crosswalk table that will help mapping the subjects' pGUIDs existing in the current NDA collection and the subjects in Common Mind Consortium (CMC) to their corresponding HBCC internal subject identifier (or Brain Numbers).	Qualified Researchers
ExperimentID_1507_mapping_dataFileName_associated_with_brain_regions.xlsx	Other	For experiment name "RNA-Seq_dsACCC/STG" (ID =1507), the attached spreadsheet is useful to identify the brain regions (Dorsal anterior cingulate cortex (dACC) or superior temporal gyrus (STG)) used for generating sequencing read files (fastq).	Qualified Researchers
pseudoGUID to NBB ID Translation Table_110723.xlsx	Other	pseudoGUID to NBB ID Translation Table	Qualified Researchers

Grant Information:

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
1353	Microarray	07/18/2019	Approved	Omics
1354	Genotyping_HumanHap650Y	07/18/2019	Approved	Omics
1355	Genotyping_Human1MDuo	07/18/2019	Approved	Omics
1356	Genotyping_HumanOmni5-Quad	07/18/2019	Approved	Omics
1357	RNA-Seq_sgACC	07/18/2019	Approved	Omics
1359	WGS_HiSeq X	07/18/2019	Approved	Omics
1360	ChIP-seq_HiSeq_2500	07/18/2019	Approved	Omics
1361	RNA-Seq_DLPFC	07/19/2019	Approved	Omics
1507	RNA-Seq_dACC/STG	01/23/2020	Approved	Omics
1545	DNA_methylation_hippocampus	04/24/2020	Approved	Omics
1852	snRNAseq_controls_DLPFC/sgACC	09/30/2021	Approved	Omics
1965	DNA_methylation_DLPFC	03/10/2022	Approved	Omics
2056	RNA-Seq_ACC/Caudate	07/05/2022	Approved	Omics
2243	WGS_Novaseq_6000_linkedRead	05/02/2023	Approved	Omics
2271	RNA-Seq_Insula	06/13/2023	Approved	Omics
2369	WGS_at_MSSM	08/31/2023	Approved	Omics
2370	snRNA_brain_aging	09/18/2023	Approved	Omics
2443	DNA_methylation_ACC/Caudate	01/09/2024	Approved	Omics
2657	WGS_of_800_subjects_done_at_USU	07/30/2024	Approved	Omics
2669	Genotypes_SNParray_IlluminaGSA24	08/09/2024	Approved	Omics
2716	Relative expression of transcripts/genes using qPCR	10/25/2024	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
Drug Screen	Clinical Assessments	1324
Genomics Sample	Genomics	1360
Genomics Subject	Genomics	1360
Mortality Report	Clinical Assessments	1324
Psychosocial Interview	Clinical Assessments	1324

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
37037607	Study (2370)	Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing.	The Journal of neuroscience : the official journal of the Society for Neuroscience	Kim B, Kim D, Schulmann A, Patel Y, Caban-Rivera C, Kim P, Jambhale A, Johnson KR, Feng N, Xu Q, Kang SJ, Mandal A, Kelly M, Akula N, McMahon FJ, Lipska B, Marenco S, Auluck PK	May 10, 2023	Relevant
36694041	Study (2408)	Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Duncan L, Shen H, Schulmann A, Li T, Kolachana B, Mandal A, Feng N, Auluck P, Marenco S	April 2023	Relevant
36380233	Study (2395)	Mapping the cortico-striatal transcriptome in attention deficit hyperactivity disorder.	Molecular psychiatry	Sudre G, Gildea DE, Shastri GG, Sharp W, Jung B, Xu Q, Auluck PK, Elnitski L, Baxevanis AD, Marenco S, Shaw P	February 2023	Relevant
36163279	Study (2421)	Population-level variation in enhancer expression identifies disease mechanisms in the human brain.	Nature genetics	Dong, Pengfei; Hoffman, Gabriel E; Apontes, Pasha; Bendl, Jaroslav; Rahman, Samir; Fernando, Michael B; Zeng, Biao; Vicari, James M; Zhang, Wen; Girdhar, Kiran; Townsley, Kayla G; Misir, Ruth; CommonMind Consortium; Brennand, Kristen J; Haroutunian, Vahram; Voloudakis, Georgios; Fullard, John F; Roussos, Panos	October 2022	Relevant
33558674	Study (2397)	Deep transcriptome sequencing of subgenual anterior cingulate cortex reveals cross-diagnostic and diagnosis-specific RNA expression changes in major psychiatric disorders.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Akula N, Marenco S, Johnson K, Feng N, Zhu K, Schulmann A, Corona W, Jiang X, Cross J, England B, Nathan A, Detera-Wadleigh S, Xu Q, Auluck PK, An K, Kramer R, Apud J, Harris BT, Harker Rhodes C, Lipska BK, McMahon FJ	June 2021	Relevant
32533064	Study (2410)	Functional annotation of rare structural variation in the human brain.	Nature communications	Han, Lide; Zhao, Xuefang; Benton, Mary Lauren; Perumal, Thaneer; Collins, Ryan L; Hoffman, Gabriel E; Johnson, Jessica S; Sloofman, Laura; Wang, Harold Z; Stone, Matthew R; CommonMind Consortium; Brennand, Kristen J; Brand, Harrison; Sieberts, Solveig K; Marenco, Stefano; Peters, Mette A; Lipska, Barbara K; Roussos, Panos; Capra, John A; Talkowski, Michael; Ruderfer, Douglas M	June 12, 2020	Relevant
32485434	Study (2422)	Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortality.	Journal of psychiatric research	Jabbi M, Arasappan D, Eickhoff SB, Strakowski SM, Nemeroff CB, Hofmann HA	August 2020	Relevant
31746071	Study (2413)	Accelerated hippocampal biological aging in bipolar disorder.	Bipolar disorders	Fries GR, Bauer IE, Scaini G, Valvassori SS, Walss-Bass C, Soares JC, Quevedo J	August 2020	Relevant
31551426	Study (2414)	CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder.	Scientific data	Hoffman GE, Bendl J, Voloudakis G, Montgomery KS, Sloofman L, Wang YC, Shah HR, Hauberg ME, Johnson JS, Girdhar K, Song L, Fullard JF, Kramer R, Hahn CG, Gur R, Marenco S, Lipska BK, Lewis DA, Haroutunian V, Hemby S, Sullivan P, Akbarian S, Chess A, Buxbaum JD, Crawford GE, et al.	September 24, 2019	Relevant
30038276	Study (2419)	Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome.	Nature neuroscience	Girdhar, Kiran; Hoffman, Gabriel E; Jiang, Yan; Brown, Leanne; Kundakovic, Marija; Hauberg, Mads E; Francoeur, Nancy J; Wang, Ying-Chih; Shah, Hardik; Kavanagh, David H; Zharovsky, Elizabeth; Jacobov, Rivka; Wiseman, Jennifer R; Park, Royce; Johnson, Jessica S; Kassim, Bibi S; Sloofman, Laura; Mattei, Eugenio; Weng, Zhiping; Sieberts, Solveig K; Peters, Mette A; Harris, Brent T; Lipska, Barbara K; Sklar, Pamela; Roussos, Panos; Akbarian, Schahram	August 2018	Relevant
27668389	Study (2417)	Gene expression elucidates functional impact of polygenic risk for schizophrenia.	Nature neuroscience	Fromer, Menachem; Roussos, Panos; Sieberts, Solveig K; Johnson, Jessica S; Kavanagh, David H; Perumal, Thanneer M; Ruderfer, Douglas M; Oh, Edwin C; Topol, Aaron; Shah, Hardik R; Klei, Lambertus L; Kramer, Robin; Pinto, Dalila; Gümüş, Zeynep H; Cicek, A Ercument; Dang, Kristen K; Browne, Andrew; Lu, Cong; Xie, Lu; Readhead, Ben; Stahl, Eli A; Xiao, Jianqiu; Parvizi, Mahsa; Hamamsy, Tymor; Fullard, John F; Wang, Ying-Chih; Mahajan, Milind C; Derry, Jonathan M J; Dudley, Joel T; Hemby, Scott E; Logsdon, Benjamin A; Talbot, Konrad; Raj, Towfique; Bennett, David A; De Jager, Philip L; Zhu, Jun; Zhang, Bin; Sullivan, Patrick F; Chess, Andrew; Purcell, Shaun M; Shinobu, Leslie A; Mangravite, Lara M; Toyoshiba, Hiroyoshi; Gur, Raquel E; Hahn, Chang-Gyu; Lewis, David A; Haroutunian, Vahram; Peters, Mette A; Lipska, Barbara K; Buxbaum, Joseph D; Schadt, Eric E; Hirai, Keisuke; Roeder, Kathryn; Brennand, Kristen J; Katsanis, Nicholas; Domenici, Enrico; Devlin, Bernie; Sklar, Pamela	November 2016	Relevant
25206360	Study (2418)	DNA methylation changes in the postmortem dorsolateral prefrontal cortex of patients with schizophrenia.	Frontiers in genetics	Numata S, Ye T, Herman M, Lipska BK	2014	Relevant
22031444	Study (2372)	Temporal dynamics and genetic control of transcription in the human prefrontal cortex.	Nature	Colantuoni C, Lipska BK, Ye T, Hyde TM, Tao R, Leek JT, Colantuoni EA, Elkahloun AG, Herman MM, Weinberger DR, Kleinman JE	October 26, 2011	Relevant

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	1,166	01/15/2020	1,691	05/15/2020	1,360	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
Genomics/omics	1,166	10/28/2019	1,692	11/15/2019	1,360	Approved
Drug Screen	1,325	07/15/2021	1,358	11/15/2021	1,324	Approved
Psychosocial Interview	1,325	07/15/2021	1,324	11/15/2021	1,324	Approved
Mortality Report	1,325	07/15/2021	1,358	11/15/2021	1,324	Approved
Ancestry and SCZ Polygenic Risk Score	1,402	04/13/2023	1,402	05/01/2023	0	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	AbstractFilter by Abstract	Collection/Study SubjectsFilter by Collection/Study Subjects	Data UsageFilter by Data Usage	StateFilter by State
Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.	, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.	1402/1402	Primary Analysis	Shared
Gene expression elucidates functional impact of polygenic risk for schizophrenia.	Over 100 genetic loci harbor schizophrenia-associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of people with schizophrenia (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ∼20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Altering expression of FURIN, TSNARE1 or CNTN4 changed neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yielded abnormal migration. Of 693 genes showing significant case-versus-control differential expression, their fold changes were ≤ 1.33, and an independent cohort yielded similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show that schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.	867/867	Primary Analysis	Shared
Temporal dynamics and genetic control of transcription in the human prefrontal cortex.	Previous investigations have combined transcriptional and genetic analyses in human cell lines, but few have applied these techniques to human neural tissue. To gain a global molecular perspective on the role of the human genome in cortical development, function and ageing, we explore the temporal dynamics and genetic control of transcription in human prefrontal cortex in an extensive series of post-mortem brains from fetal development through ageing. We discover a wave of gene expression changes occurring during fetal development which are reversed in early postnatal life. One half-century later in life, this pattern of reversals is mirrored in ageing and in neurodegeneration. Although we identify thousands of robust associations of individual genetic polymorphisms with gene expression, we also demonstrate that there is no association between the total extent of genetic differences between subjects and the global similarity of their transcriptional profiles. Hence, the human genome produces a consistent molecular architecture in the prefrontal cortex, despite millions of genetic differences across individuals and races. To enable further discovery, this entire data set is freely available (from Gene Expression Omnibus: accession GSE30272; and dbGaP: accession phs000417.v1.p1) and can also be interrogated via a biologist-friendly stand-alone application (http://www.libd.org/braincloud).	803/803	Primary Analysis	Shared
Functional annotation of rare structural variation in the human brain.	Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. Here, we integrate SVs with RNA-sequencing from human post-mortem brains to quantify their dosage and regulatory effects. We show that genic and regulatory SVs exist at significantly lower frequencies than intergenic SVs. Functional impact of copy number variants (CNVs) stems from both the proportion of genic and regulatory content altered and loss-of-function intolerance of the gene. We train a linear model to predict expression effects of rare CNVs and use it to annotate regulatory disruption of CNVs from 14,891 independent genome-sequenced individuals. Pathogenic deletions implicated in neurodevelopmental disorders show significantly more extreme regulatory disruption scores and if rank ordered would be prioritized higher than using frequency or length alone. This work shows the deleteriousness of regulatory SVs, particularly those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs.	425/425	Primary Analysis	Shared
CommonMind Consortium provides transcriptomic and epigenomic data for Schizophrenia and Bipolar Disorder.	Schizophrenia and bipolar disorder are serious mental illnesses that affect more than 2% of adults. While large-scale genetics studies have identified genomic regions associated with disease risk, less is known about the molecular mechanisms by which risk alleles with small effects lead to schizophrenia and bipolar disorder. In order to fill this gap between genetics and disease phenotype, we have undertaken a multi-cohort genomics study of postmortem brains from controls, individuals with schizophrenia and bipolar disorder. Here we present a public resource of functional genomic data from the dorsolateral prefrontal cortex (DLPFC; Brodmann areas 9 and 46) of 986 individuals from 4 separate brain banks, including 353 diagnosed with schizophrenia and 120 with bipolar disorder. The genomic data include RNA-seq and SNP genotypes on 980 individuals, and ATAC-seq on 269 individuals, of which 264 are a subset of individuals with RNA-seq. We have performed extensive preprocessing and quality control on these data so that the research community can take advantage of this public resource available on the Synapse platform at http://CommonMind.org .	382/382	Primary Analysis	Shared
Population-level variation in enhancer expression identifies disease mechanisms in the human brain.	Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding population-level variation in enhancer function in the human brain. Besides regulating tissue-specific and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. By jointly analyzing large-scale cell-type-specific transcriptome and regulome data, we cataloged 30,795 neuronal and 23,265 non-neuronal candidate transcribed enhancers. Examination of the transcriptome in 1,382 brain samples identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified expression quantitative trait loci (eQTLs) for both genes and enhancers and found that enhancer eQTLs mediate a substantial fraction of neuropsychiatric trait heritability. Inclusion of enhancer eQTLs in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the gene-enhancer regulome and genetic mechanisms in the human cortex in both healthy and diseased states.	329/329	Primary Analysis	Shared
Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome.	Risk variants for schizophrenia affect more than 100 genomic loci, yet cell- and tissue-specific roles underlying disease liability remain poorly characterized. We have generated for two cortical areas implicated in psychosis, the dorsolateral prefrontal cortex and anterior cingulate cortex, 157 reference maps from neuronal, neuron-depleted and bulk tissue chromatin for two histone marks associated with active promoters and enhancers, H3-trimethyl-Lys4 (H3K4me3) and H3-acetyl-Lys27 (H3K27ac). Differences between neuronal and neuron-depleted chromatin states were the major axis of variation in histone modification profiles, followed by substantial variability across subjects and cortical areas. Thousands of significant histone quantitative trait loci were identified in neuronal and neuron-depleted samples. Risk variants for schizophrenia, depressive symptoms and neuroticism were significantly over-represented in neuronal H3K4me3 and H3K27ac landscapes. Our Resource, sponsored by PsychENCODE and CommonMind, highlights the critical role of cell-type-specific signatures at regulatory and disease-associated noncoding sequences in the human frontal lobe.	312/312	Primary Analysis	Shared
DNA methylation changes in the postmortem dorsolateral prefrontal cortex of patients with schizophrenia.	BACKGROUND: Schizophrenia is a complex psychiatric disorder with a lifetime morbidity rate of 0.5-1.0%. The pathophysiology of schizophrenia still remains obscure. Accumulating evidence indicates that DNA methylation, which is the addition of a methyl group to the cytosine in a CpG dinucleotide, might play an important role in the pathogenesis of schizophrenia. METHODS: To gain further insight into the molecular mechanisms underlying schizophrenia, a genome-wide DNA methylation profiling (27,578 CpG dinucleotides spanning 14,495 genes) of the human dorsolateral prefrontal cortex (DLPFC) was conducted in a large cohort (n = 216) of well characterized specimens from individuals with schizophrenia and non-psychiatric controls, combined with an analysis of genetic variance at ~880,000 SNPs. RESULTS: Aberrant DNA methylation in schizophrenia was identified at 107 CpG sites at 5% Bonferroni correction (p < 1.99 × 10(-6)). Of these significantly altered sites, hyper-DNA methylation was observed at 79 sites (73.8%), mostly in the CpG islands (CGIs) and in the regions flanking CGIs (CGI: 31 sites; CGI shore: 35 sites; CGI shelf: 3 sites). Furthermore, a large number of cis-methylation quantitative trait loci (mQTL) were identified, including associations with risk SNPs implicated in schizophrenia. CONCLUSIONS: These results suggest that altered DNA methylation might be involved in the pathophysiology and/or treatment of schizophrenia, and that a combination of epigenetic and genetic approaches will be useful to understanding the molecular mechanism of this complex disorder.	220/220	Primary Analysis	Shared
Deep transcriptome sequencing of subgenual anterior cingulate cortex reveals cross-diagnostic and diagnosis-specific RNA expression changes in major psychiatric disorders.	Despite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case-control comparisons detected modest expression differences that were correlated across disorders. Case-case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.	200/200	Primary Analysis	Shared
Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortality.	Suicidal behaviors are strongly linked with mood disorders, but the specific neurobiological and functional gene-expression correlates for this linkage remain elusive. We performed neuroimaging-guided RNA-sequencing in two studies to test the hypothesis that imaging-localized gray matter volume (GMV) loss in mood disorders, harbors gene-expression changes associated with disease morbidity and related suicide mortality in an independent postmortem cohort. To do so, first, we conducted study 1 using an anatomical likelihood estimation (ALE) MRI meta-analysis including a total of 47 voxel-based morphometry (VBM) publications (i.e. 26 control versus (vs) major depressive disorder (MDD) studies, and 21 control vs bipolar disorder (BD) studies) in 2387 (living) participants. Study 1 meta-analysis identified a selective anterior insula cortex (AIC) GMV loss in mood disorders. We then used this results to guide study 2 postmortem tissue dissection and RNA-Sequencing of 100 independent donor brain samples with a life-time history of MDD (N = 30), BD (N = 37) and control (N = 33). In study 2, exploratory factor-analysis identified a higher-order factor representing number of Axis-1 diagnoses (e.g. substance use disorders/psychosis/anxiety, etc.), referred to here as morbidity and suicide-completion referred to as mortality. Comparisons of case-vs-control, and factor-analysis defined higher-order-factor contrast variables revealed that the imaging-identified AIC GMV loss sub-region harbors differential gene-expression changes in high morbidity-&-mortality versus low morbidity-&-mortality cohorts in immune, inflammasome, and neurodevelopmental pathways. Weighted gene co-expression network analysis further identified co-activated gene modules for psychiatric morbidity and mortality outcomes. These results provide evidence that AIC anatomical signature for mood disorders are possible correlates for gene-expression abnormalities in mood morbidity and suicide mortality.	100/100	Primary Analysis	Shared
Accelerated hippocampal biological aging in bipolar disorder.	Evidence suggests accelerated aging mechanisms in bipolar disorder (BD), including DNA methylation (DNAm) aging in blood. However, it is unknown whether such mechanisms are also evident in the brain, in particular in association with other biological clocks. To investigate this, we interrogated genome-wide DNAm in postmortem hippocampus from 32 BD-I patients and 32 non-psychiatric controls group-matched for age and sex from the NIMH Human Brain Collection Core. DNAm age and epigenetic aging acceleration were estimated using the Horvath method. Telomere length (TL) and mitochondrial DNA (mtDNA) copy number were quantified by real-time PCR. Between-group differences were assessed by linear regression and univariate general linear models with age, sex, race, postmortem interval, tissue pH, smoking, and body mass index included as co-variates. Groups did not differ for epigenetic aging acceleration when considering the entire sample. However, after splitting the sample by the median age, an epigenetic aging acceleration was detected in patients compared to controls among older subjects (P = .042). While TL did not differ between groups, a reduction in mtDNA copy number was observed in patients compared to controls (P = .047). In addition, significant correlations were observed between epigenetic aging acceleration and TL (r = -.337, P = .006), as well as between TL and mtDNA copy number (r = .274, P = .028). Hippocampal aging may underlie neurocognitive dysfunctions observed in BD patients. Moreover, our results suggest a complex cross-talk between biological clocks in hippocampus that may underlie clinical manifestations of premature aging in BD.	64/64	Primary Analysis	Shared
Mapping the cortico-striatal transcriptome in attention deficit hyperactivity disorder.	Despite advances in identifying rare and common genetic variants conferring risk for ADHD, the lack of a transcriptomic understanding of cortico-striatal brain circuitry has stymied a molecular mechanistic understanding of this disorder. To address this gap, we mapped the transcriptome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from 60 individuals with and without ADHD. Significant differential expression of genes was found in the anterior cingulate cortex and, to a lesser extent, the caudate. Significant downregulation emerged of neurotransmitter gene pathways, particularly glutamatergic, in keeping with models that implicate these neurotransmitters in ADHD. Consistent with the genetic overlap between mental disorders, correlations were found between the cortico-striatal transcriptomic changes seen in ADHD and those seen in other neurodevelopmental and mood disorders. This transcriptomic evidence points to cortico-striatal neurotransmitter anomalies in the pathogenesis of ADHD, consistent with current models of the disorder.	60/60	Primary Analysis	Shared
Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing.	Dysfunction of the subgenual anterior cingulate cortex has been implicated in mood disorders, particularly major depressive disorder, and the dorsolateral PFC, a subsection of the PFC involved in executive functioning, has been implicated in schizophrenia. Understanding the cellular composition of these regions is critical to elucidating the neurobiology underlying psychiatric and neurologic disorders. We studied cell type diversity of the subgenual anterior cingulate cortex and dorsolateral PFC of humans with no neuropsychiatric illness using a clustering analysis of single-nuclei RNA-sequencing data. Defining the transcriptomic profile of cellular subpopulations in these cortical regions is a first step to demystifying the cellular and molecular pathways involved in psychiatric disorders.	8/8	Primary 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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