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The three-dimensional landscape of the genome in human brain tissue unveils regulatory mechanisms leading to schizophrenia risk
Open accessAbstract
Recent advances in our understanding of the genetic architecture of schizophrenia have shed light on the schizophrenia etiology. While common variation is one of the major genetic contributors, the majority of common variation reside in non-coding genome, posing a significant challenge in understanding the functional impact of this class of genetic variation. Functional genomic datasets that range from expression quantitative trait loci (eQTL) to chromatin interactions are critical to identify the potential target genes and functional consequences of non-coding variation. In this review, we discuss how three-dimensional chromatin landscape, identified by a technique called Hi-C, has facilitated the identification of potential target genes impacting schizophrenia risk. We outline key steps for Hi-C driven gene mapping, and compare Hi-C defined schizophrenia risk genes defined across developmental epochs and cell types, which offer rich insights into the temporal window and cellular etiology of schizophrenia. In contrast with a neurodevelopmental hypothesis in schizophrenia, Hi-C defined schizophrenia risk genes are postnatally enriched, suggesting that postnatal development is also important for schizophrenia pathogenesis. Moreover, Hi-C defined schizophrenia risk genes are highly expressed in excitatory neurons, highlighting excitatory neurons as a central cell type for schizophrenia. Further characterization of Hi-C defined schizophrenia risk genes demonstrated enrichment for genes that harbor loss-of-function variation in neurodevelopmental disorders, suggesting a shared genetic etiology between schizophrenia and neurodevelopmental disorders. Collectively, moving the search space from risk variants to the target genes lays a foundation to understand the neurobiological basis of schizophrenia.
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Previous work suggests a potential interplay between common and rare variation in the genetic architecture of brain disorders.
“Our previous work suggests a potential interplay between common and rare variation in the genetic architecture of brain disorders42.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [42]
Rare and common variation may impact the same biological pathways.
“These results collectively suggest that rare and common variation may impact same biological pathways42.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [42]
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A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
Biological insights from 108 schizophrenia-associated genetic loci
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) · Nature · doi:10.1038/nature13595 · Cited by 7,577
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352
Variance component model to account for sample structure in genome-wide association studies
Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.-Y., Freimer, N. B., Sabatti, C., & Eskin, E. (2010) · Nature Genetics · doi:10.1038/ng.548 · Cited by 2,817
Partitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604
Integrative approaches for large-scale transcriptome-wide association studies
Gusev, A., Ko, A., Shi, H., Bhatia, G., Chung, W., Penninx, B. W. J. H., Jansen, R., de Geus, E. J. C., Boomsma, D. I., Wright, F. A., et al. (2016) · Nature Genetics · doi:10.1038/ng.3506 · Cited by 2,479
Analysis of shared heritability in common disorders of the brain
The Brainstorm Consortium, Anttila, V., Bulik-Sullivan, B., Finucane, H. K., Walters, R. K., Bras, J., Duncan, L., Escott-Price, V., Falcone, G. J., Gormley, P., et al. (2018) · Science · doi:10.1126/science.aap8757 · Cited by 1,924
A gene-based association method for mapping traits using reference transcriptome data
Gamazon, E. R., Wheeler, H. E., Shah, K. P., Mozaffari, S. V., Aquino-Michaels, K., Carroll, R. J., Eyler, A. E., Denny, J. C., Nicolae, D. L., Cox, N. J., et al. (2015) · Nature Genetics · doi:10.1038/ng.3367 · Cited by 1,790
Chromatin architecture reorganization during stem cell differentiation
Dixon, J. R., Jung, I., Selvaraj, S., Shen, Y., Antosiewicz-Bourget, J. E., Lee, A. Y., Ye, Z., Kim, A., Rajagopal, N., Xie, W., et al. (2015) · Nature · doi:10.1038/nature14222 · Cited by 1,646
GERAD1 Consortium, Pardiñas, A. F., CRESTAR Consortium, Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., Legge, S. E., Bishop, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0059-2 · Cited by 1,552
Self-citationPrevalence and architecture of de novo mutations in developmental disorders
Study, D. D. D. (2017) · Nature · doi:10.1038/nature21062 · Cited by 1,480
Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci
Sanders, S. J., He, X., Willsey, A. J., Ercan-Sencicek, A. G., Samocha, K. E., Cicek, A. E., Murtha, M. T., Bal, V. H., Bishop, S. L., Dong, S., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.016 · Cited by 1,430
A survey of human brain transcriptome diversity at the single cell level
Darmanis, S., Sloan, S. A., Zhang, Y., Enge, M., Caneda, C., Shuer, L. M., Hayden Gephart, M. G., Barres, B. A., & Quake, S. R. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1507125112 · Cited by 1,401
Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq
Arnold, C. D., Gerlach, D., Stelzer, C., Boryń, Ł. M., Rath, M., & Stark, A. (2013) · Science · doi:10.1126/science.1232542 · Cited by 1,125
Gene expression elucidates functional impact of polygenic risk for schizophrenia
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., Ruderfer, D. M., Oh, E. C., Topol, A., Shah, H. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4399 · Cited by 1,091
Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects
Marshall, C. R., Howrigan, D. P., Merico, D., Thiruvahindrapuram, B., Wu, W., Greer, D. S., Antaki, D., Shetty, A., Holmans, P. A., Pinto, D., et al. (2017) · Nature Genetics · doi:10.1038/ng.3725 · Cited by 1,058
Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039
Self-citationMapping long-range promoter contacts in human cells with high-resolution capture Hi-C
Mifsud, B., Tavares-Cadete, F., Young, A. N., Sugar, R., Schoenfelder, S., Ferreira, L., Wingett, S. W., Andrews, S., Grey, W., Ewels, P. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3286 · Cited by 990
Comprehensive functional genomic resource and integrative model for the human brain
Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F. C. P., Clarke, D., Gu, M., Emani, P., Yang, Y. T., et al. (2018) · Science · doi:10.1126/science.aat8464 · Cited by 965
Self-citationNeuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
Lake, B. B., Ai, R., Kaeser, G. E., Salathia, N. S., Yung, Y. C., Liu, R., Wildberg, A., Gao, D., Fung, H.-L., Chen, S., et al. (2016) · Science · doi:10.1126/science.aaf1204 · Cited by 957
A compendium of chromatin contact maps reveals spatially active regions in the human genome
Schmitt, A. D., Hu, M., Jung, I., Xu, Z., Qiu, Y., Tan, C. L., Li, Y., Lin, S., Lin, Y., Barr, C. L., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.10.061 · Cited by 866
FINEMAP: efficient variable selection using summary data from genome-wide association studies
Benner, C., Spencer, C. C. A., Havulinna, A. S., Salomaa, V., Ripatti, S., & Pirinen, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw018 · Cited by 815
Beyond GWASs: Illuminating the Dark Road from Association to Function
Edwards, S. L., Beesley, J., French, J. D., & Dunning, A. M. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.10.012 · Cited by 784
Melnikov, A., Murugan, A., Zhang, X., Tesileanu, T., Wang, L., Rogov, P., Feizi, S., Gnirke, A., Callan, C. G., Kinney, J. B., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2137 · Cited by 711
Colocalization of GWAS and eQTL Signals Detects Target Genes
Hormozdiari, F., van de Bunt, M., Segrè, A. V., Li, X., Joo, J. W. J., Bilow, M., Sul, J. H., Sankararaman, S., Pasaniuc, B., & Eskin, E. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.10.003 · Cited by 697
Autistic-like social behaviour in Shank2-mutant mice improved by restoring NMDA receptor function
Won, H., Lee, H.-R., Gee, H. Y., Mah, W., Kim, J.-I., Lee, J., Ha, S., Chung, C., Jung, E. S., Cho, Y. S., et al. (2012) · Nature · doi:10.1038/nature11208 · Cited by 695
Self-citationPostnatal neurodevelopmental disorders: meeting at the synapse?
Zoghbi, H. Y. (2003) · Science · doi:10.1126/science.1089071 · Cited by 691
Genetic identification of brain cell types underlying schizophrenia
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Skene, N. G., Bryois, J., Bakken, T. E., Breen, G., Crowley, J. J., Gaspar, H. A., Giusti-Rodriguez, P., Hodge, R. D., Miller, J. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0129-5 · Cited by 651
Hilker, R., Helenius, D., Fagerlund, B., Skytthe, A., Christensen, K., Werge, T. M., Nordentoft, M., & Glenthøj, B. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.08.017 · Cited by 615
A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens
Gasperini, M., Hill, A. J., McFaline-Figueroa, J. L., Martin, B., Kim, S., Zhang, M. D., Jackson, D., Leith, A., Schreiber, J., Noble, W. S., et al. (2019) · Cell · doi:10.1016/j.cell.2018.11.029 · Cited by 613
Chromosome conformation elucidates regulatory relationships in developing human brain
Won, H., de la Torre-Ubieta, L., Stein, J. L., Parikshak, N. N., Huang, J., Opland, C. K., Gandal, M. J., Sutton, G. J., Hormozdiari, F., Lu, D., et al. (2016) · Nature · doi:10.1038/nature19847 · Cited by 584
Self-citationThe dopamine hypothesis of schizophrenia: focus on the dopamine receptor
Snyder, S. H. (1976) · American Journal of Psychiatry · doi:10.1176/ajp.133.2.197 · Cited by 557
Gulsuner, S., Walsh, T., Watts, A. C., Lee, M. K., Thornton, A. M., Casadei, S., Rippey, C., Shahin, H., Braff, D., Cadenhead, K. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.049 · Cited by 536
Neurodevelopmental hypothesis of schizophrenia
Owen, M. J., O'Donovan, M. C., Thapar, A., & Craddock, N. (2011) · British Journal of Psychiatry · doi:10.1192/bjp.bp.110.084384 · Cited by 500
Mumbach, M. R., Satpathy, A. T., Boyle, E. A., Dai, C., Gowen, B. G., Cho, S. W., Nguyen, M. L., Rubin, A. J., Granja, J. M., Kazane, K. R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3963 · Cited by 490
Identifying Causal Variants at Loci with Multiple Signals of Association
Hormozdiari, F., Kostem, E., Kang, E. Y., Pasaniuc, B., & Eskin, E. (2014) · Genetics · doi:10.1534/genetics.114.167908 · Cited by 465
Enhancer-promoter interactions are encoded by complex genomic signatures on looping chromatin
Whalen, S., Truty, R. M., & Pollard, K. S. (2016) · Nature Genetics · doi:10.1038/ng.3539 · Cited by 456
Study, S. S., Singh, T., Study, I., Study, D., UK10 K Consortium, Kurki, M. I., Curtis, D., Purcell, S. M., Crooks, L., McRae, J., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4267 · Cited by 452
Akbarian, S., Liu, C., Knowles, J. A., Vaccarino, F. M., Farnham, P. J., Crawford, G. E., Jaffe, A. E., Pinto, D., Dracheva, S., Geschwind, D. H., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4156 · Cited by 451
Self-citationThe Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis
de la Torre-Ubieta, L., Stein, J. L., Won, H., Opland, C. K., Liang, D., Lu, D., & Geschwind, D. H. (2018) · Cell · doi:10.1016/j.cell.2017.12.014 · Cited by 353
Self-citationCommon genetic variants contribute to risk of rare severe neurodevelopmental disorders
Niemi, M. E. K., Martin, H. C., Rice, D. L., Gallone, G., Gordon, S., Kelemen, M., McAloney, K., McRae, J., Radford, E. J., Yu, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0566-4 · Cited by 340
Schizophrenia: a tale of two critical periods for prefrontal cortical development
Selemon, L. D., & Zecevic, N. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.115 · Cited by 336
Singh, T., Walters, J. T. R., Johnstone, M., Curtis, D., Suvisaari, J., Torniainen, M., Rees, E., Iyegbe, C., Blackwood, D., McIntosh, A. M., et al. (2017) · Nature Genetics · doi:10.1038/ng.3903 · Cited by 231
Cao, Q., Anyansi, C., Hu, X. S., Xu, L., Xiong, L., Tang, W., Mok, M. T. S., Cheng, C., Fan, X., Gerstein, M., et al. (2017) · Nature Genetics · doi:10.1038/ng.3950 · Cited by 220
Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk
Rajarajan, P., Borrman, T., Liao, W., Schrode, N., Flaherty, E., Casiño, C., Powell, S., Yashaswini, C., LaMarca, E. A., Kassim, B., et al. (2018) · Science · doi:10.1126/science.aat4311 · Cited by 219
Self-citationGlutamatergic Synaptic Dysregulation in Schizophrenia: Therapeutic Implications
Coyle, J. T., Basu, A., Benneyworth, M., Balu, D., & Konopaske, G. (2012) · Handbook of Experimental Pharmacology · doi:10.1007/978-3-642-25758-2_10 · Cited by 180
Narrowing the Boundaries of the Genetic Architecture of Schizophrenia
Wray, N. R., & Visscher, P. M. (2009) · Schizophrenia Bulletin · doi:10.1093/schbul/sbp137 · Cited by 106
Enhancer Domains Predict Gene Pathogenicity and Inform Gene Discovery in Complex Disease
Wang, X., & Goldstein, D. B. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.01.012 · Cited by 106
Forloni, G., Bertani, I., Calella, A. M., Thaler, F., & Invernizzi, R. W. (2000) · Annals of Neurology · doi:10.1002/1531-8249(200005)47:5 · Cited by 82
Xi, W., & Beer, M. A. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1006625 · Cited by 68
Most chromatin interactions are not in linkage disequilibriumPreprint
Whalen, S., & Pollard, K. S. (2019) · Genome Research · doi:10.1101/gr.238022.118 · Cited by 35
Enhancer redundancy predicts gene pathogenicity and informs complex disease gene discoveryPreprint
Wang, X., & Goldstein, D. (2018) · bioRxiv · doi:10.1101/459123 · Cited by 13
Most regulatory interactions are not in linkage disequilibriumPreprint
Whalen, S., & Pollard, K. S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/272245 · Cited by 8
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Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
Lee, P. H., Anttila, V., Won, H., Feng, Y.-C. A., Rosenthal, J., Zhu, Z., Tucker-Drob, E. M., Nivard, M. G., Grotzinger, A. D., Posthuma, D., et al. (2019) · Cell · doi:10.1016/j.cell.2019.11.020 · Cited by 1,381
Self-citationSey, N. Y. A., Hu, B., Mah, W., Fauni, H., McAfee, J. C., Rajarajan, P., Brennand, K. J., Akbarian, S., & Won, H. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0603-0 · Cited by 297
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Metadata
- Authors
- Mah, W., & Won, H.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Won, Hyejung
- ORCID
- Won, Hyejung
- Venue
- Schizophrenia Research
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 217
- Pages
- 17-25
- ISSN
- 0920-9964 (ISSN-L)
- PMC
- PMC6748876
- OpenAlex
- W2921156692
- Cited by
- 38
- References
- 56
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1 · 2023: 6 · 2022: 6 · 2021: 6 · 2020: 10
- FWCI
- 1.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Schizophrenia Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (R00MH113823)
- NARSAD
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- schizophrenia, 3D genome organization
- MeSH terms
- Brain, Chromatin, Humans, Schizophrenia, Genome, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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