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14 results on '"Braun, Patricia R."'

4. List of contributors

Author

Abdolmaleky, Hamid Mostafavi, primary, Akbarian, Schahram, additional, Ambrosini, Alexander, additional, Avramopoulos, Dimitrios, additional, Bendersky, Cari J., additional, Bendl, Jaroslav, additional, Bérubé, Nathalie G., additional, Bhat, Unis Ahmad, additional, Borreggine, Kristin, additional, Braun, Patricia R., additional, Brennand, Kristen J., additional, Castro, Amanda, additional, Chakravarty, Sumana, additional, Chang, Connie, additional, Cohen, Sophie, additional, Coppedè, Fabio, additional, Dahrendorff, Jan, additional, Dunn, Jeffrey T., additional, Eberwine, James H., additional, Elia, Josephine, additional, Fang, Gang, additional, Fels, Samuel, additional, Fernando, Michael B., additional, Franklin, Tamara Brook, additional, Fries, Gabriel R., additional, Frizzola, Meg, additional, Fullard, John F., additional, Ganguly, Sebanti, additional, Gapp, Katharina, additional, Garcia, Meilin Fernandez, additional, Gatta, Eleonora, additional, Grayson, Dennis R., additional, Gropman, Andrea L., additional, Guidotti, Alessandro, additional, Gupta, Praveer, additional, Hakonarson, Hakon, additional, Hunter, Richard G., additional, Imamura, Takuya, additional, Izaki, Yumiko, additional, Jakub, Taryn, additional, Keung, Crystal, additional, Kramer, Jamie M., additional, Kumar, Arvind, additional, Kundakovic, Marija, additional, Labonté, Benoit, additional, LaMarca, Elizabeth A., additional, Lee, Richard S., additional, Lima, Camila N.C., additional, Lutz, Pierre-Eric, additional, Matt, Stephanie M., additional, Milian, Allison A., additional, Miyashiro, Kevin Y., additional, Murgatroyd, Chris, additional, Nakashima, Kinichi, additional, Paul, Bidisha, additional, Peedicayil, Jacob, additional, Pinjari, Omar F., additional, Poddar, Karuna, additional, Potash, James B., additional, Powell, Samuel K., additional, Quesnel, Katerine, additional, Rayfield, Jessica, additional, Reddy, R. Gajendra, additional, Richter, Troy A., additional, Roth, Eric D., additional, Roth, Tania L., additional, Roussos, Panos, additional, Ruzicka, W. Brad, additional, Salarda, Erika M., additional, Santhosh, Samuel, additional, Saudagar, Vikram, additional, Stoccoro, Andrea, additional, Syed, Shariful A., additional, Thiagalingam, Sam, additional, Tollefsbol, Trygve O., additional, Turecki, Gustavo, additional, Uddin, Monica, additional, Uesaka, Masahiro, additional, Walker, Deena, additional, Yamamoto, Naoki, additional, Yost, Oliver, additional, and Zannas, Anthony S., additional

Published
2021
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8. Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders

Author

Zhou, Jiyun, primary, Chen, Qiang, additional, Braun, Patricia R., additional, Perzel Mandell, Kira A., additional, Jaffe, Andrew E., additional, Tan, Hao Yang, additional, Hyde, Thomas M., additional, Kleinman, Joel E., additional, Potash, James B., additional, Shinozaki, Gen, additional, Weinberger, Daniel R., additional, and Han, Shizhong, additional

Published
2022
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10. Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.

Author

Jiyun Zhou, Qiang Chen, Braun, Patricia R., Perzel Mandell, Kira A., Jaffe, Andrew E., Hao Yang Tan, Hyde, Thomas M., Kleinman, Joel E., Potash, James B., Gen Shinozaki, Weinberger, Daniel R., and Shizhong Han

Subjects
DNA methylation, DEEP learning, GENETICS, LOCUS (Genetics), MENTAL illness
Abstract

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits. [ABSTRACT FROM AUTHOR]

Published
2022
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12. Genome‐wide DNA methylation investigation of glucocorticoid exposure within buccal samples

Author

Braun, Patricia R., primary, Tanaka‐Sahker, Mai, additional, Chan, Aubrey C., additional, Jellison, Sydney S., additional, Klisares, Mason J., additional, Hing, Benjamin W., additional, Shabbir, Yaseen, additional, Gaul, Lindsey N., additional, Nagahama, Yasunori, additional, Robles, Julian, additional, Heinzman, Jonathan T., additional, Sabbagh, Sayeh, additional, Cramer, Ellyn M., additional, Duncan, Gabrielle N., additional, Yuki, Kumi, additional, Close, Liesl N., additional, Dlouhy, Brian J., additional, Howard, Matthew A., additional, Kawasaki, Hiroto, additional, Stein, Kyle M., additional, Potash, James B., additional, and Shinozaki, Gen, additional

Published
2019
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13. Epigenetics of Delirium and Aging: Potential Role of DNA Methylation Change on Cytokine Genes in Glia and Blood Along With Aging

Author

Shinozaki, Gen, primary, Braun, Patricia R., additional, Hing, Benjamin W. Q., additional, Ratanatharathorn, Andrew, additional, Klisares, Mason J., additional, Duncan, Gabrielle N., additional, Jellison, Sydney S., additional, Heinzman, Jonathan T., additional, Nagahama, Yasunori, additional, Close, Liesl, additional, Sabbagh, Sayeh, additional, Dlouhy, Brian J., additional, Howard, Matthew A., additional, Kawasaki, Hiroto, additional, and Cho, Hyunkeun R., additional

Published
2018
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14. Investigation of differential HDAC4methylation patterns in eating disorders

Author

Subramanian, Subha, Braun, Patricia R., Han, Shizhong, and Potash, James B.

Abstract

Supplemental Digital Content is available in the text.The objective of this study was to investigate the relationship between methylation patterns of the histone deacetylase 4 gene and eating disorders in a site previously associated with anorexia nervosa (AN). Women with AN (N=28) or bulimia nervosa (BN) (N=19) were age-matched and sex-matched to controls (N=45). We obtained saliva-derived DNA and use bisulfite pyrosequencing to examine region-specific methylation differences between cases and controls. The region assayed includes 15 CpGs. We found no significant association between the previously implicated CpG and either AN or BN. We found that three CpGs were nominally associated with AN (P=0.02–0.03); the largest difference was a 9% hypermethylation in AN. One CpG was nominally associated with BN (P=0.04), with 4% hypomethylation. None of these results remained significant after correction for multiple testing. We did not replicate previous findings, though through expanded coverage, we identified additional CpGs that were nominally associated with eating disorders.

Published
2018
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