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The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth
Open accessAbstract
The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale study of child development that combines neuroimaging, diverse clinical and cognitive phenotypes, and genomics. Data from this rich resource is now publicly available through the Database of Genotypes and Phenotypes (dbGaP). Here we focus on the data from the PNC that is available through dbGaP and describe how users can access this data, which is evolving to be a significant resource for the broader neuroscience community for studies of normal and abnormal neurodevelopment.
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“The sample also completed the Wide Range Achievement Test (WRAT), which is a highly-reliable broad ability measure [67].”
From Global Ancestry and Cognitive Ability (2019) · cites this paper as [67]
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Why do many psychiatric disorders emerge during adolescence?
Paus, T., Keshavan, M., & Giedd, J. N. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2513 · Cited by 3,123 · cited 1×
“The PNC is a resource that responds to a paradigm shift in the field of psychiatric neuroscience, where major mental illnesses are increasingly conceptualized as disorders of development (Insel, 2010; Insel, 2009; Casey et al., 2014; Paus et al., 2008).”
Toward discovery science of human brain function
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“As previously emphasized (Biswal et al., 2010; Gorgolewski et al., 2013; Mennes et al., 2012; Milham, 2012; Nooner et al., 2012; Bis et al., 2012; Stein et al., 2012), large publicly available datasets are a prerequisite for the collaboration necessary to gain traction towards understanding complex…”
Functional impact of global rare copy number variation in autism spectrum disorders
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“Genotyping procedures are not discussed here, but the genotyping pipeline used at CAG has been previously described in detail (14,15) and further information can be accessed at www.”
Self-citationSatterthwaite, T. D., Elliott, M. A., Gerraty, R. T., Ruparel, K., Loughead, J., Calkins, M. E., Eickhoff, S. B., Hakonarson, H. H., Gur, R. C., Gur, R. E., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.08.052 · Cited by 1,982 · cited 2×
“…assessment, cognitive testing, and imaging procedures is provided in PNC manuscripts that have used these data types (Satterthwaite et al., 2012a; Satterthwaite et al., 2013a; Satterthwaite et al., in press; Satterthwaite et al., 2014b; Satterthwaite et al., 2014c; Roalf et al., 2014;…”
Self-citationInsel, T. R. (2010) · Nature · doi:10.1038/nature09552 · Cited by 1,783 · cited 1×
“The PNC is a resource that responds to a paradigm shift in the field of psychiatric neuroscience, where major mental illnesses are increasingly conceptualized as disorders of development (Insel, 2010; Insel, 2009; Casey et al., 2014; Paus et al., 2008).”
Autism genome-wide copy number variation reveals ubiquitin and neuronal genes
Glessner, J. T., Wang, K., Cai, G., Korvatska, O., Kim, C. E., Wood, S., Zhang, H., Estes, A., Brune, C. W., Bradfield, J. P., et al. (2009) · Nature · doi:10.1038/nature07953 · Cited by 1,421 · cited 2×
“Genotyping procedures are not discussed here, but the genotyping pipeline used at CAG has been previously described in detail (Pinto et al., 2010; Glessner et al., 2009) and further information can be accessed at www.”
Self-citationSex differences in the structural connectome of the human brain
Ingalhalikar, M., Smith, A., Parker, D., Satterthwaite, T. D., Elliott, M. A., Ruparel, K., Hakonarson, H., Gur, R. E., Gur, R. C., & Verma, R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316909110 · Cited by 1,223 · cited 2×
“Further information regarding clinical assessment, cognitive testing, and imaging procedures is provided in PNC manuscripts that have used these data types (Satterthwaite et al., 2012a; Satterthwaite et al., 2013a; Satterthwaite et al., in press; Satterthwaite et al., 2014b; Satterthwaite et al., 2014c; Roalf et al.,…”
Self-citationSatterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.063 · Cited by 1,125 · cited 2×
“…information regarding clinical assessment, cognitive testing, and imaging procedures is provided in PNC manuscripts that have used these data types (Satterthwaite et al., 2012a; Satterthwaite et al., 2013a; Satterthwaite et al., in press; Satterthwaite et al., 2014b; Satterthwaite et al.,…”
Self-citationThe NCBI dbGaP database of genotypes and phenotypes
Mailman, M. D., Feolo, M., Jin, Y., Kimura, M., Tryka, K. A., Bagoutdinov, R., Hao, L., Kiang, A., Paschall, J. E., Phan, L. D., et al. (2007) · Nature Genetics · doi:10.1038/ng1007-1181 · Cited by 1,100 · cited 2×
“As described in detail elsewhere (Mailman et al., 2007), dbGaP was created to be a general repository for sharing genetic and phenotypic data from large-scale studies in a secure manner.”
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“Individuals with a variety of clinical and subclinical psychiatric symptoms were included in the PNC dataset (57), potentially introducing noise to the relationship between age and differentiation (10-12).”
Riley, S., Cheng, A., Wang, Y.-W., Shen, X.-L., Dhamala, E., Zhao, Y.-Z., Holmes, A. J., Constable, R., & Yip, S. W. (2026) · Imaging neuroscience · doi:10.1162/imag.a.1287
“Similar improvements were observed across other common performance metrics (e.g., Spearman’s ρ , root mean squared error, coefficient of determination, Supplementary Tables S2 - S4), as well as for prediction of IQ in an independent cohort of youth in the Philadelphia Neurodevelopmental Cohort ( Satterthwaite et al.,…”
InfluentialLi, X.-X., Zhang, G.-M., Qu, G., Orlichenko, A., Ding, Z.-M., Wilson, T. W., Stephen, J., Calhoun, V., & Wang, Y.-P. (2026) · bioRxiv · doi:10.64898/2026.05.16.725673
“The PNC was designed to characterize the interactions among brain imaging, behavior, and genetics in a diverse sample of adolescents [33].”
Kikidis, G., Raio, A., Sportelli, L., Antonucci, L., Bertolino, A., Rampino, A., Selvaggi, P., Weinberger, D. R., & Pergola, G. (2026) · bioRxiv · doi:10.64898/2026.05.19.726222
Mapping Individualized Developmental Imbalance in Youth and Its Association with Psychopathology
Hu, Q.-Y., Milecki, L., Jafrasteh, B., Pohl, K., Kuceyeski, A., & Zhao, Q.-Y. (2026) · bioRxiv · doi:10.64898/2026.05.09.724052
“1): HCP-D [31] ( n = 509; 271 females; age 8–21 years), PNC [33, 36] ( n = 1,159; 623 females; age 8–23 years), and HBN [32] ( n = 1,159; 472 females; age 5– 21 years) [31-34 , 36].”
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“Recruitment procedures, sample characteristics, clinical, cognitive, and imaging protocols are described in detail by Satterthwaite et al (2016).”
Testing for Network Specificity in Brain‐Behavior Associations Using Ordinal Dominance Curves
Hillman, N., Weinstein, S. M., Bagautdinova, J., Sun, K. Y., Cieslak, M., Salo, T., Yong Fan, A., Keller, A. S., Alexander‐Bloch, A. F., Vandekar, S., et al. (2026) · Human Brain Mapping · doi:10.1002/hbm.70493
“The PNC is a community-based sample of 8–21 year-olds designed to integrate multimodal neuroimaging, cognitive and clinical phenotypes, and genetics in order to elucidate the relationship be-tween neurodevelopment and psychiatric disorders (Satterthwaite et al. 2016).”
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King, A. P. J., Langenecker, S. A., Gorka, S. M., Turner, J. A., Wang, L., Wastler, H. M., Gonzalez, M. R., Christian, L. M., Keck, C., Olsen, R., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-099525
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“While we also demonstrated the utility of our approach to predict a small number of additional phenotypes from HCP, and to also predict IQ using data from the Philadelphia Neurodevelopmental Cohort, further testing of the robustness of our approach to other datasets – including those acquired without harmonized acquis…”
InfluentialPatel, B., & Habeeb, Z. (2025) · Machine Learning for Computational Science and Engineering · doi:10.1007/s44379-025-00038-8
“The [12].”
Sariyanidi, E., Herrington, J., Yankowitz, L., Chaudhari, P., Satterthwaite, T., Zampella, C., Schultz, R., Shinohara, R., & Tunç, B. (2025) · bioRxiv · doi:10.1101/2025.08.02.668286
“3 compares the connectivity matrices obtained with Pearson’s r (i.e., correlation matrix) and the concurrence coefficient (i.e., concurrence matrix) on a version of the Philadelphia Neurodevelopmental Cohort dataset [39] that was pre-processed as in prior work [40].”
Self-citationGraph Learning Based Functional Connectivity Estimation with Application to Brain Age Prediction
Bai, K., & Li, X. (2024) · 2024 6th International Conference on Frontier Technologies of Information and Computer (ICFTIC) · doi:10.1109/icftic64248.2024.10912904
“The dataset utilized in this investigation originates from the Philadelphia Neurodevelopmental Cohort[13-14], a significant joint endeavor in applied genomics between the Children’s Hospital of Philadelphia and the University of Pennsylvania’s Brain Behavioral Laboratory.”
King, A., Langenecker, S., Gorka, S., Turner, J., Wang, L., Wastler, H., Carpenter, L., Keck, C., Olsen, R., Kim, H., et al. (2024) · medRxiv · doi:10.1101/2024.11.19.24316679
“…Understanding of Recovery after Trauma (AURORA) study (McLean et al., 2020), the Philadelphia Neurodevelopmental Cohort (PNC) (Calkins et al., 2015, Satterthwaite et al., 2016), the Tulsa 1000 study (Victor et al., 2018), and the Texas Resilience Against Depression (T-RAD) (Trivedi et al., 2020)…”
Dafflon, J., Moraczewski, D., Earl, E., Nielson, D. M., Loewinger, G., Mcclure, P., Thomas, A. G., & Pereira, F. (2024) · arXiv.org · doi:10.48550/arxiv.2405.00255
“We selected 39 summary scores from cognitive tasks from the PNC dataset (Satterthwaite et al., 2016; Gur et al., 2010; Roalf et al., 2014).”
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He, Q.-F., Keding, T. J., Zhang, Q., Miao, J.-C., Herringa, R., Lu, Q.-S., Travers, B., & Li, J. J. (2022) · medRxiv · doi:10.1101/2022.12.12.22283356
“We conducted standard quality control and 238 imputation, excluding SNPs with call rate <95%, minor allele frequency <5%, Hardy-Weinberg 239 equilibrium p<1*10 (32,39).”
BackgroundMethodCai, B., Zhou, Z.-X., Zhang, A.-Y., Zhang, G.-M., Xiao, L., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2022) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2022.109539
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Self-citationLinking Brain Age to Psychopathology in Adolescence.
Kempton, M. (2021) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2021.02.005
Angelis, F. D., Wendt, F. R., Pathak, G., Tylee, D., Goswami, A., Gelernter, J., & Polimanti, R. (2020) · medRxiv · doi:10.1101/2020.10.22.20217596
“; https://doi.org/10.1101/2020.10.22.20217596doi: medRxiv preprint 5 (Satterthwaite et al., 2016).”
InfluentialInvoluntary Retrieval in Episodic Memory
Bian, Z.-X. (2020) · doi:10.23977/iceipi2020025
“Meanwhile, researchers argued that for patients with MDD and PTSD, the cognitive control regions, including DLPFC and inferior frontal gyrus (IFG), presented decreased connectivity with amygdala (Satterthwaite et al., 2016).”
BackgroundFang, J., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2018) · IEEE International Symposium on Biomedical Imaging · doi:10.1109/isbi.2018.8363512
“It is available in the dbGaP database[4], and contains resting-state fMRI for children aged from 8 to 22 years.”
MethodInfluentialCoupled Dimensionality-Reduction Model for Imaging Genomics
Zillé, P., & Wang, Y.-P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67675-3_22 · Cited by 1
Mehta, C., Malins, J. G., Noble, K., & Gruen, J. (2017) · bioRxiv · doi:10.1101/160424
“Raw neuroimaging scans, neuropsychological assessments, genotypes, and demographic information collected by the PNC study were obtained from dbGAP [43].”
MethodVenkataraman, A., Rekik, I., Kim, M., & Chung, A. W. (2019) · CNI@MICCAI · doi:10.1007/978-3-030-32391-2
“The permutation test is perhaps the most widely used nonparametric test procedure in sciences [8,19,21,24,27].”
BackgroundMethodInfluentialGao, S., Mishne, G., & Scheinost, D. (2018) · doi:10.32470/ccn.2018.1139-0
“For both datasets, 268 timecourses of fMRI data were extracted using a whole-brain, functional atlas (Shen et al., 2013).”
Method
Metadata
- Authors
- Satterthwaite, T. D., Connolly, J. J., Ruparel, K., Calkins, M. E., Jackson, C., Elliott, M. A., Roalf, D. R., Hopson, R., Prabhakaran, K., Behr, M., Qiu, H., Mentch, F. D., Chiavacci, R., Sleiman, P. M. A., Gur, R. C., Hakonarson, H., & Gur, R. E.
- Affiliations
- University of Pennsylvania (US)
- Children's Hospital of Philadelphia (US)
- Philadelphia VA Medical Center (US)
- Corresponding author
- Satterthwaite, Theodore D.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 124
- Issue
- Pt B
- Pages
- 1115-1119
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4591095
- OpenAlex
- W2030561475
- Cited by
- 335
- References
- 44
- Citations by year
- 2026: 23 · 2025: 27 · 2024: 36 · 2023: 22 · 2022: 33 · 2021: 46 · 2020: 37 · 2019: 40 · 2018: 31 · 2017: 26 · 2016: 11
- FWCI
- 14.02
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (MH089983, MH089924, MH019112, U01HG006830, K23MH098130, K01MH102609, K08MH79364)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- Philadelphia Neurodevelopmental Cohort, brain development, child development, neuroimaging, genomics, clinical phenotype, cognitive phenotypes, public data, dbGaP, data access
- MeSH terms
- Adolescent, Brain, Child, Child Development, Developmental Disabilities, Cognition, Female, Humans, Male, Nervous System, Internet, Genomics, Information Dissemination, Neuroimaging
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