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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

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Laminar dissection of cortical human brain gene expression in neuropsychiatric disorders #5229

General
Experiments (9)
Shared Data
Publications (50)
Data Expected (6)
Associated Studies (2)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Laminar dissection of cortical human brain gene expression in neuropsychiatric disorders
Collection Investigators:	Keri Martinowich
Collection Description:	Project Summary/Abstract The DLPFC is a true six layered neocortex, and neurons in different cortical layers show distinct expression patterns, morphology, physiology and patterns of connectivity. Converging evidence suggests that impairments in the formation or maintenance of synapses may be involved in schizophrenia and other neuropsychiatric disorders. Studies in the postmortem brains of subjects have pointed to specific cell types and revealed differences in neuronal and synaptic structure that are localized to specific layers, suggesting that genetic risk for schizophrenia may manifest with laminar specificity. Given the close relationship between brain structure and function, precisely assigning gene expression to the spatial coordinates of individual cell populations within this cortical cytoarchitecture would significantly advance our understanding of how dysregulation in these areas contributes to debilitating neuropsychiatric disorders. In this application, we propose to generate detailed spatial transcriptomics maps of the human DLPFC in patients with schizophrenia (SCZD), bipolar (BPD), major depressive (MDD) and autism spectrum (ASD) disorders, and contrast these laminar expression patterns to those derived from matched neurotypical controls (CONT). We will use the 10x Genomics Visium platform, which combines transcriptome-wide RNA sequencing with detailed high-resolution histology and immunofluorescence imaging, to generate these spatial transcriptomics profiles. We will combine these topographic and cell type-specific maps to implicate layer- and cell type-specific populations in psychiatric disorder genetic risk and illness state that will be validated using complementary quantitative in situ hybridization techniques. These layer-specific and cell type-specific expression profiles can refine the molecular causes and consequences of debilitating neuropsychiatric disorders that can be targeted for prevention and treatment.
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	04/30/2024
NIH Research Initiative:	PsychENCODE Consortium
Collection Phase:	Enrolling
Blinded Clinical Trial:	No
Total Funded Amount:	$5,663,491.00
Subjects Shared:	73
Collection DOI:	10.15154/6j1p-6q20

{"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
U01MH122849-01	Spatial registration of gene expression in the human brain	05/01/2020	04/30/2022	04/30/2024	Not Reported	Not Reported	LIEBER INSTITUTE, INC.	$1,747,260.00
R01MH126393-01	Laminar dissection of cortical human brain gene expression in neuropsychiatric disorders	06/23/2021	03/31/2026	09/30/2026	Not Reported	Not Reported	LIEBER INSTITUTE, INC.	$3,916,231.00

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
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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.

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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).

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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.
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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:
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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.
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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
2605	LIBD spatial DLPFC: snRNA-seq	05/09/2024	Approved	Omics
2606	LIBD spatial DLPFC: Visium	05/10/2024	Approved	Omics
2607	LIBD spatial DLPFC: genotyping	05/10/2024	Approved	Omics
2627	LIBD spatial HPC: snRNA-seq	07/01/2024	Approved	Omics
2628	LIBD spatial HPC: Visium	07/01/2024	Approved	Omics
2862	LIBD spatial DLPFC: Visium SCZ	02/20/2025	Approved	Omics
2863	LIBD spatial DLPFC: Visium MDD & BPD	02/20/2025	Approved	Omics
2864	LIBD spatial DLPFC: Visium ASD	02/20/2025	Approved	Omics
3045	LIBD spatial DLPFC: Xenium SCZ	08/11/2025	Approved	Omics

helpcenter.collection.experiments-tab

Collection - Experiments

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

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Experiment ID

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Shared Data:

Title	Type	Number of Subjects
Genomics Subject	Genomics	73
RNA Sequencing	Genomics	73
SNP Array	Genomics	10
Visium Image	Genomics	73

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.

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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.
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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

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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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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
41757081	Create Study	Mapping spatially organized molecular and genetic signatures of schizophrenia across multiple scales in human prefrontal cortex.	bioRxiv : the preprint server for biology	Kwon, Sang Ho; Guo, Boyi; Fang, Cindy; Tippani, Madhavi; Bach, Svitlana V; Miller, Ryan A; Maguire, Sarah E; Iatrou, Artemis; Pertea, Geo; Eagles, Nicholas J; Valentine, Madeline R; Oh, Seyun; Jajoo, Aarti; Balakundi, Vijetha; Du, Yufeng; Nguyen, Annie B; Zhang, Ruth; Kaipa, Uma M; Divecha, Heena R; Lobana, Jashandeep S; Kleinman, Joel E; Han, Shizhong; Daskalakis, Nikolaos P; Hyde, Thomas M; Collado-Torres, Leonardo; Page, Stephanie C; Maynard, Kristen R; Hicks, Stephanie C; Martinowich, Keri	February 16, 2026	Not Determined
41394650	Create Study	High cell-type specificity of eQTLs revealed by single-nucleus analyses of brain and blood.	bioRxiv : the preprint server for biology	Vochteloo, Martijn; Kooijmans, Anoek; Bakker, Joost; Oelen, Roy; Niewold, Jelmer; Kaptijn, Dan; Bonder, Marc Jan; van der Wijst, Monique; Huang, Yunfeng; Bryois, Julien; Tsai, Ellen A; Franke, Lude; Westra, Harm-Jan	November 28, 2025	Not Determined
41332620	Create Study	Orchestrating Spatial Transcriptomics Analysis with Bioconductor.	bioRxiv : the preprint server for biology	Crowell, Helena L; Dong, Yixing; Billato, Ilaria; Cai, Peiying; Emons, Martin; Gunz, Samuel; Guo, Boyi; Li, Mengbo; Mahmoud, Alexandru; Manukyan, Artür; Pagès, Hervé; Panwar, Pratibha; Rao, Shreya; Sargeant, Callum J; Kern, Lori Shepherd; Ramos, Marcel; Sun, Jieran; Totty, Michael; Carey, Vincent J; Chen, Yunshun; Collado-Torres, Leonardo; Ghazanfar, Shila; Hansen, Kasper D; Martinowich, Keri; Maynard, Kristen R; Patrick, Ellis; Righelli, Dario; Risso, Davide; Tiberi, Simone; Waldron, Levi; Gottardo, Raphael; Robinson, Mark D; Hicks, Stephanie C; Weber, Lukas M	November 21, 2025	Not Determined
40739059	Create Study	An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.	Nature neuroscience	Thompson, Jacqueline R; Nelson, Erik D; Tippani, Madhavi; Ramnauth, Anthony D; Divecha, Heena R; Miller, Ryan A; Eagles, Nicholas J; Pattie, Elizabeth A; Kwon, Sang Ho; Bach, Svitlana V; Kaipa, Uma M; Yao, Jianing; Hou, Christine; Kleinman, Joel E; Collado-Torres, Leonardo; Han, Shizhong; Maynard, Kristen R; Hyde, Thomas M; Martinowich, Keri; Page, Stephanie C; Hicks, Stephanie C	September 1, 2025	Not Determined
40515599	Create Study	Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon.	Biostatistics (Oxford, England)	Shah, Kinnary; Guo, Boyi; Hicks, Stephanie C	December 31, 2025	Not Determined
40481362	Create Study	SpotSweeper: spatially aware quality control for spatial transcriptomics.	Nature methods	Totty, Michael; Hicks, Stephanie C; Guo, Boyi	July 1, 2025	Not Determined
40393810	Create Study	Spatial domain detection using contrastive self-supervised learning for spatial multi-omics technologies.	Genome research	Yao, Jianing; Yu, Jinglun; Caffo, Brian; Page, Stephanie C; Martinowich, Keri; Hicks, Stephanie C	July 1, 2025	Not Determined
40009515	Create Study	Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation.	Cell reports	Ramnauth, Anthony D; Tippani, Madhavi; Divecha, Heena R; Papariello, Alexis R; Miller, Ryan A; Nelson, Erik D; Thompson, Jacqueline R; Pattie, Elizabeth A; Kleinman, Joel E; Maynard, Kristen R; Collado-Torres, Leonardo; Hyde, Thomas M; Martinowich, Keri; Hicks, Stephanie C; Page, Stephanie C	February 18, 2025	Not Determined
39935130	Create Study	Integrating Spatially-Resolved Transcriptomics Data Across Tissues and Individuals: Challenges and Opportunities.	Small methods	Guo, Boyi; Ling, Wodan; Kwon, Sang Ho; Panwar, Pratibha; Ghazanfar, Shila; Martinowich, Keri; Hicks, Stephanie C	May 1, 2025	Not Determined
39574747	Create Study	Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon.	bioRxiv : the preprint server for biology	Shah, Kinnary; Guo, Boyi; Hicks, Stephanie C	November 8, 2024	Not Determined
39329069	Create Study	Influence of Alzheimer''s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex.	GEN biotechnology	Kwon, Sang Ho; Parthiban, Sowmya; Tippani, Madhavi; Divecha, Heena R; Eagles, Nicholas J; Lobana, Jashandeep S; Williams, Stephen R; Mak, Michelle; Bharadwaj, Rahul A; Kleinman, Joel E; Hyde, Thomas M; Page, Stephanie C; Hicks, Stephanie C; Martinowich, Keri; Maynard, Kristen R; Collado-Torres, Leonardo	October 1, 2023	Not Determined
39130195	Create Study	Integrating spatially-resolved transcriptomics data across tissues and individuals: challenges and opportunities.	ArXiv	Guo, Boyi; Ling, Wodan; Kwon, Sang Ho; Panwar, Pratibha; Ghazanfar, Shila; Martinowich, Keri; Hicks, Stephanie C	August 1, 2024	Not Determined
39107272	Create Study	Single-cell multiomics analysis reveals cell/tissue-specific associations in bipolar disorder.	Translational psychiatry	Wei, Wenming; Cheng, Bolun; Yang, Xuena; Chu, Xiaoge; He, Dan; Qin, Xiaoyue; Zhang, Na; Zhao, Yijing; Shi, Sirong; Cai, Qingqing; Hui, Jingni; Wen, Yan; Liu, Huan; Jia, Yumeng; Zhang, Feng	August 6, 2024	Not Determined
38913688	Create Study	The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons.	Molecular biology and evolution	Morales-Vicente, David A; Tahira, Ana C; Woellner-Santos, Daisy; Amaral, Murilo S; Berzoti-Coelho, Maria G; Verjovski-Almeida, Sergio	July 3, 2024	Not Determined
38895212	Create Study	SpotSweeper: spatially-aware quality control for spatial transcriptomics.	bioRxiv : the preprint server for biology	Totty, Michael; Hicks, Stephanie C; Guo, Boyi	June 9, 2024	Not Determined
38781390	Create Study	Massively parallel characterization of regulatory elements in the developing human cortex.	Science (New York, N.Y.)	Deng, Chengyu; Whalen, Sean; Steyert, Marilyn; Ziffra, Ryan; Przytycki, Pawel F; Inoue, Fumitaka; Pereira, Daniela A; Capauto, Davide; Norton, Scott; Vaccarino, Flora M; PsychENCODE Consortium‡; Pollen, Alex A; Nowakowski, Tomasz J; Ahituv, Nadav; Pollard, Katherine S; PsychENCODE Consortium	May 24, 2024	Not Determined
38781388	Create Study	Single-cell multi-cohort dissection of the schizophrenia transcriptome.	Science (New York, N.Y.)	Ruzicka, W Brad; Mohammadi, Shahin; Fullard, John F; Davila-Velderrain, Jose; Subburaju, Sivan; Tso, Daniel Reed; Hourihan, Makayla; Jiang, Shan; Lee, Hao-Chih; Bendl, Jaroslav; PsychENCODE Consortium§; Voloudakis, Georgios; Haroutunian, Vahram; Hoffman, Gabriel E; Roussos, Panos; Kellis, Manolis; PsychENCODE Consortium	May 24, 2024	Not Determined
38781370	Create Study	A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex.	Science (New York, N.Y.)	Huuki-Myers, Louise A; Spangler, Abby; Eagles, Nicholas J; Montgomery, Kelsey D; Kwon, Sang Ho; Guo, Boyi; Grant-Peters, Melissa; Divecha, Heena R; Tippani, Madhavi; Sriworarat, Chaichontat; Nguyen, Annie B; Ravichandran, Prashanthi; Tran, Matthew N; Seyedian, Arta; PsychENCODE Consortium†; Hyde, Thomas M; Kleinman, Joel E; Battle, Alexis; Page, Stephanie C; Ryten, Mina; Hicks, Stephanie C; Martinowich, Keri; Collado-Torres, Leonardo; Maynard, Kristen R; PsychENCODE Consortium	May 24, 2024	Not Determined
38781369	Create Study	Single-cell genomics and regulatory networks for 388 human brains.	Science (New York, N.Y.)	Emani, Prashant S; Liu, Jason J; Clarke, Declan; Jensen, Matthew; Warrell, Jonathan; Gupta, Chirag; Meng, Ran; Lee, Che Yu; Xu, Siwei; Dursun, Cagatay; Lou, Shaoke; Chen, Yuhang; Chu, Zhiyuan; Galeev, Timur; Hwang, Ahyeon; Li, Yunyang; Ni, Pengyu; Zhou, Xiao; PsychENCODE Consortium‡; Bakken, Trygve E; Bendl, Jaroslav; Bicks, Lucy; Chatterjee, Tanima; Cheng, Lijun; Cheng, Yuyan; Dai, Yi; Duan, Ziheng; Flaherty, Mary; Fullard, John F; Gancz, Michael; Garrido-Martín, Diego; Gaynor-Gillett, Sophia; Grundman, Jennifer; Hawken, Natalie; Henry, Ella; Hoffman, Gabriel E; Huang, Ao; Jiang, Yunzhe; Jin, Ting; Jorstad, Nikolas L; Kawaguchi, Riki; Khullar, Saniya; Liu, Jianyin; Liu, Junhao; Liu, Shuang; Ma, Shaojie; Margolis, Michael; Mazariegos, Samantha; Moore, Jill; Moran, Jennifer R; Nguyen, Eric; Phalke, Nishigandha; Pjanic, Milos; Pratt, Henry; Quintero, Diana; Rajagopalan, Ananya S; Riesenmy, Tiernon R; Shedd, Nicole; Shi, Manman; Spector, Megan; Terwilliger, Rosemarie; Travaglini, Kyle J; Wamsley, Brie; Wang, Gaoyuan; Xia, Yan; Xiao, Shaohua; Yang, Andrew C; Zheng, Suchen; Gandal, Michael J; Lee, Donghoon; Lein, Ed S; Roussos, Panos; Sestan, Nenad; Weng, Zhiping; White, Kevin P; Won, Hyejung; Girgenti, Matthew J; Zhang, Jing; Wang, Daifeng; Geschwind, Daniel; Gerstein, Mark; PsychENCODE Consortium	May 24, 2024	Not Determined
38781368	Create Study	Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain.	Science (New York, N.Y.)	Wen, Cindy; Margolis, Michael; Dai, Rujia; Zhang, Pan; Przytycki, Pawel F; Vo, Daniel D; Bhattacharya, Arjun; Matoba, Nana; Tang, Miao; Jiao, Chuan; Kim, Minsoo; Tsai, Ellen; Hoh, Celine; Aygün, Nil; Walker, Rebecca L; Chatzinakos, Christos; Clarke, Declan; Pratt, Henry; PsychENCODE Consortium†; Peters, Mette A; Gerstein, Mark; Daskalakis, Nikolaos P; Weng, Zhiping; Jaffe, Andrew E; Kleinman, Joel E; Hyde, Thomas M; Weinberger, Daniel R; Bray, Nicholas J; Sestan, Nenad; Geschwind, Daniel H; Roeder, Kathryn; Gusev, Alexander; Pasaniuc, Bogdan; Stein, Jason L; Love, Michael I; Pollard, Katherine S; Liu, Chunyu; Gandal, Michael J; PsychENCODE Consortium	May 24, 2024	Not Determined
38781356	Create Study	Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms.	Science (New York, N.Y.)	Patowary, Ashok; Zhang, Pan; Jops, Connor; Vuong, Celine K; Ge, Xinzhou; Hou, Kangcheng; Kim, Minsoo; Gong, Naihua; Margolis, Michael; Vo, Daniel; Wang, Xusheng; Liu, Chunyu; Pasaniuc, Bogdan; Li, Jingyi Jessica; Gandal, Michael J; de la Torre-Ubieta, Luis	May 24, 2024	Not Determined
38781336	Create Study	Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data.	Science advances	Dai, Rujia; Chu, Tianyao; Zhang, Ming; Wang, Xuan; Jourdon, Alexandre; Wu, Feinan; Mariani, Jessica; Vaccarino, Flora M; Lee, Donghoon; Fullard, John F; Hoffman, Gabriel E; Roussos, Panos; Wang, Yue; Wang, Xusheng; Pinto, Dalila; Wang, Sidney H; Zhang, Chunling; PsychENCODE consortium; Chen, Chao; Liu, Chunyu	May 24, 2024	Not Determined
38781333	Create Study	Brain cell-type shifts in Alzheimer''s disease, autism, and schizophrenia interrogated using methylomics and genetics.	Science advances	Yap, Chloe X; Vo, Daniel D; Heffel, Matthew G; Bhattacharya, Arjun; Wen, Cindy; Yang, Yuanhao; Kemper, Kathryn E; Zeng, Jian; Zheng, Zhili; Zhu, Zhihong; Hannon, Eilis; Vellame, Dorothea Seiler; Franklin, Alice; Caggiano, Christa; Wamsley, Brie; Geschwind, Daniel H; Zaitlen, Noah; Gusev, Alexander; Pasaniuc, Bogdan; Mill, Jonathan; Luo, Chongyuan; Gandal, Michael J	May 24, 2024	Not Determined
38712198	Create Study	An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.	bioRxiv : the preprint server for biology	Thompson, Jacqueline R; Nelson, Erik D; Tippani, Madhavi; Ramnauth, Anthony D; Divecha, Heena R; Miller, Ryan A; Eagles, Nicholas J; Pattie, Elizabeth A; Kwon, Sang Ho; Bach, Svitlana V; Kaipa, Uma M; Yao, Jianing; Hou, Christine; Kleinman, Joel E; Collado-Torres, Leonardo; Han, Shizhong; Maynard, Kristen R; Hyde, Thomas M; Martinowich, Keri; Page, Stephanie C; Hicks, Stephanie C	December 11, 2024	Not Determined
38562822	Create Study	Single-cell genomics and regulatory networks for 388 human brains.	bioRxiv : the preprint server for biology	Emani, Prashant S; Liu, Jason J; Clarke, Declan; Jensen, Matthew; Warrell, Jonathan; Gupta, Chirag; Meng, Ran; Lee, Che Yu; Xu, Siwei; Dursun, Cagatay; Lou, Shaoke; Chen, Yuhang; Chu, Zhiyuan; Galeev, Timur; Hwang, Ahyeon; Li, Yunyang; Ni, Pengyu; Zhou, Xiao; PsychENCODE Consortium; Bakken, Trygve E; Bendl, Jaroslav; Bicks, Lucy; Chatterjee, Tanima; Cheng, Lijun; Cheng, Yuyan; Dai, Yi; Duan, Ziheng; Flaherty, Mary; Fullard, John F; Gancz, Michael; Garrido-Martín, Diego; Gaynor-Gillett, Sophia; Grundman, Jennifer; Hawken, Natalie; Henry, Ella; Hoffman, Gabriel E; Huang, Ao; Jiang, Yunzhe; Jin, Ting; Jorstad, Nikolas L; Kawaguchi, Riki; Khullar, Saniya; Liu, Jianyin; Liu, Junhao; Liu, Shuang; Ma, Shaojie; Margolis, Michael; Mazariegos, Samantha; Moore, Jill; Moran, Jennifer R; Nguyen, Eric; Phalke, Nishigandha; Pjanic, Milos; Pratt, Henry; Quintero, Diana; Rajagopalan, Ananya S; Riesenmy, Tiernon R; Shedd, Nicole; Shi, Manman; Spector, Megan; Terwilliger, Rosemarie; Travaglini, Kyle J; Wamsley, Brie; Wang, Gaoyuan; Xia, Yan; Xiao, Shaohua; Yang, Andrew C; Zheng, Suchen; Gandal, Michael J; Lee, Donghoon; Lein, Ed S; Roussos, Panos; Sestan, Nenad; Weng, Zhiping; White, Kevin P; Won, Hyejung; Girgenti, Matthew J; Zhang, Jing; Wang, Daifeng; Geschwind, Daniel; Gerstein, Mark	March 30, 2024	Not 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	73	01/15/2022	73	05/15/2022	73	Approved
NIH Data Use Limitations	1	01/15/2022	0	05/15/2022	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
SNP Array	10	05/03/2024	10	09/03/2024	10	Approved
RNA Sequencing	73	05/03/2024	73	09/03/2024	73	Approved
Visium Images	73	05/03/2024	73	09/03/2024	73	Approved
Xenium Experiment	24	08/19/2025	24	12/19/2025	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	DOIFilter by DOI	AbstractFilter by Abstract	Collection/Study SubjectsFilter by Collection/Study Subjects	Data UsageFilter by Data Usage	StateFilter by State
An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.	10.15154/cnb4-v250	The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.	10/10	Primary Analysis	Shared
LIBD spatial DLPFC	10.15154/7893-6778	The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Post-mortem human brain tissue was obtained at the time of autopsy with informed consent from the legal next of kin, through the Maryland Department of Health IRB protocol #12–24, and from the Western Michigan University Homer Stryker MD School of Medicine, Department of Pathology, the Department of Pathology, University of North Dakota School of Medicine and Health Sciences, and the County of Santa Clara Medical Examiner-Coroner Office in San Jose, CA, all under the WCG protocol #20111080. Tissue blocks from the anterior (Ant), middle (Mid) and posterior (Post) positions along the rostral-caudal axis of human DLPFC were microdissected from the post-mortem brains of 10 adult neurotypical control donors (n=10 Ant, n=10 Mid, n=10 Post DLPFC blocks), resulting in a total of 30 tissue blocks. Each tissue block was dissected from Brodmann Area 46 in a plane perpendicular to the pial surface to capture L1-6 and the WM. All 30 tissue blocks were subjected to quality control (H&E and RNAscope) and Visium H&E experiments, while snRNA-seq and Visium Spatial Proteogenomics (SPG) were performed on only a subset of tissue blocks (19 and 4 tissue blocks, respectively). All assays were performed on cryosections taken from the same tissue block to ensure similar proportions of white matter and gray matter and consistent cell type representation (Fig S1). Briefly, ~50µm of tissue was trimmed from the tissue block to achieve a flat surface. Next, several ~10µm sections were collected for quality control (RNAscope, H&E) and Visium H&E experiments. Blocks were stored at -80℃ until completion of these assays. Next, blocks were placed back on the cryostat, trimmed, and ~1mm thickness of tissue was collected for snRNA-seq. At the same time, ~2mm thickness of tissue was sectioned and banked for future assays. Blocks were stored at -80℃ until completion of these assays. Finally, four tissue blocks were placed back on the cryostat and trimmed again to obtain a flat surface prior to collecting a ~10µm Visium-SPG tissue section.	10/10	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.

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