Jimmy Potash

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203 Article
13 Review article
9 Comment/debate
7 Letter
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Correction: Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients (Translational Psychiatry, (2021), 11, 1, (606), 10.1038/s41398-021-01702-2)
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Dec 2022, In: Translational psychiatry. 12, 1, 278.
Research output: Contribution to journal › Comment/debate › peer-review

Open Access
Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders
Zhou, J., Chen, Q., Braun, P. R., Perzel Mandell, K. A., Jaffe, A. E., Tan, H. Y., Hyde, T. M., Kleinman, J. E., Potash, J. B., Shinozaki, G., Weinberger, D. R. & Han, S., Aug 23 2022, In: Proceedings of the National Academy of Sciences of the United States of America. 119, 34, e2206069119.
Research output: Contribution to journal › Article › peer-review

Open Access
Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Eating Disorders Working Group of the Psychiatric Genomics Consortium, German Borderline Genomics Consortium, MVP Suicide Exemplar Workgroup & VA Million Veteran Program, Feb 1 2022, In: Biological psychiatry. 91, 3, p. 313-327 15 p.
Research output: Contribution to journal › Article › peer-review

Open Access
Erratum: Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: Machine learning approach (The British Journal of Psychiatry (2022) (1–10) DOI: 10.1192/bjp.2022.28)
Cearns, M., Amare, A. T., Schubert, K. O., Thalamuthu, A., Frank, J., Streit, F., Adli, M., Akula, N., Akiyama, K., Ardau, R., Arias, B., Aubry, J. M., Backlund, L., Bhattacharjee, A. K., Bellivier, F., Benabarre, A., Bengesser, S., Biernacka, J. M., Birner, A., Brichant-Petitjean, C., & 97 othersCervantes, P., Chen, H. C., Chillotti, C., Cichon, S., Cruceanu, C., Czerski, P. M., Dalkner, N., Dayer, A., Degenhardt, F., Zompo, M. D., Depaulo, J. R., Étain, B., Falkai, P., Forstner, A. J., Frisen, L., Frye, M. A., Fullerton, J. M., Gard, S., Garnham, J. S., Goes, F. S., Grigoroiu-Serbanescu, M., Grof, P., Hashimoto, R., Hauser, J., Heilbronner, U., Herms, S., Hoffmann, P., Hofmann, A., Hou, L., Hsu, Y. H., Jamain, S., Jiménez, E., Kahn, J. P., Kassem, L., Kuo, P. H., Kato, T., Kelsoe, J., Kittel-Schneider, S., Kliwicki, S., König, B., Kusumi, I., Laje, G., Landén, M., Lavebratt, C., Leboyer, M., Leckband, S. G., Maj, M., Manchia, M., Martinsson, L., McCarthy, M. J., McElroy, S., Colom, F., Mitjans, M., Mondimore, F. M., Monteleone, P., Nievergelt, C. M., Nöthen, M. M., Novák, T., O'Donovan, C., Ozaki, N., Millischer, V., Papiol, S., Pfennig, A., Pisanu, C., Potash, J. B., Reif, A., Reininghaus, E., Rouleau, G. A., Rybakowski, J. K., Schalling, M., Schofield, P. R., Schweizer, B. W., Severino, G., Shekhtman, T., Shilling, P. D., Shimoda, K., Simhandl, C., Slaney, C. M., Squassina, A., Stamm, T., Stopkova, P., Tekolaayele, F., Tortorella, A., Turecki, G., Veeh, J., Vieta, E., Witt, S. H., Roberts, G., Zandi, P. P., Alda, M., Bauer, M., McMahon, F. J., Mitchell, P. B., Schulze, T. G., Rietschel, M., Clark, S. R. & Baune, B. T., Aug 1 2022, In: British Journal of Psychiatry. 221, 2, p. 494 1 p.
Research output: Contribution to journal › Comment/debate › peer-review

Open Access
Identifying the Common Genetic Basis of Antidepressant Response
GSRD Consortium & Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Apr 2022, In: Biological Psychiatry Global Open Science. 2, 2, p. 115-126 12 p.
Research output: Contribution to journal › Article › peer-review

Open Access

Jimmy Potash

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Correction: Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients (Translational Psychiatry, (2021), 11, 1, (606), 10.1038/s41398-021-01702-2)

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

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Erratum: Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: Machine learning approach (The British Journal of Psychiatry (2022) (1–10) DOI: 10.1192/bjp.2022.28)

Identifying the Common Genetic Basis of Antidepressant Response

Jimmy Potash

Fingerprint

Network

Research output

Correction: Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients (Translational Psychiatry, (2021), 11, 1, (606), 10.1038/s41398-021-01702-2)

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

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Erratum: Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: Machine learning approach (The British Journal of Psychiatry (2022) (1–10) DOI: 10.1192/bjp.2022.28)

Identifying the Common Genetic Basis of Antidepressant Response