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878 results on '"Hamilton, Steven A."'

1. Comparison of Nested Geometry Treatments within GPU-Based Monte Carlo Neutron Transport Simulations of Fission Reactors

Author

Biondo, Elliott, Evans, Thomas, Johnson, Seth, and Hamilton, Steven

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Computational Geometry
Abstract

Monte Carlo (MC) neutron transport provides detailed estimates of radiological quantities within fission reactors. This method involves tracking individual neutrons through a computational geometry. CPU-based MC codes use multiple polymorphic tracker types with different tracking algorithms to exploit the repeated configurations of reactors, but virtual function calls have high overhead on the GPU. The Shift MC code was modified to support GPU-based tracking with three strategies: (1) dynamic polymorphism (DP) with virtual functions, (2) static polymorphism (SP), and (3) a single tracker (ST) type with tree-based acceleration. Results on the Frontier supercomputer show that the DP, SP, and ST methods achieve 77.8%, 91.2%, and 83.4% of the practical maximum tracking rate in the worst case, indicating that any of these methods can be used without incurring a significant performance penalty. The flexibility of the ST method is highlighted with a hexagonal-grid microreactor problem, performed without hexagonal-grid-specific tracking routines.

Published
2024

2. Advances in Touch Probes

Author

Barraud, Lilian, Walters, Casey, and Hamilton, Steven

Subjects
Machining -- Investigations -- Technology application, Lasers -- Technology application -- Investigations, Company legal issue, Laser, Technology application, Engineering and manufacturing industries, Metals, metalworking and machinery industries
Abstract

A combination of lasers, probes and software helps moldmakers automate in-process cutting tool and workpiece measurement. Automation is an essential part of machining and profitable manufacturing. Mold builders striving to [...]

Published
2024

9. Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Author

Cai, Na, Revez, Joana, Adams, Mark, Andlauer, Till, Breen, Gerome, Byrne, Enda, Clarke, Toni-Kim, Forstner, Andreas, Grabe, Hans, Hamilton, Steven, Levinson, Douglas, Lewis, Cathryn, Lewis, Glyn, Martin, Nicholas, Milaneschi, Yuri, Mors, Ole, Müller-Myhsok, Bertram, Penninx, Brenda, Perlis, Roy, Pistis, Giorgio, Potash, James, Preisig, Martin, Shi, Jianxin, Smoller, Jordan, Streit, Fabien, Tiemeier, Henning, Uher, Rudolf, Van der Auwera, Sandra, Viktorin, Alexander, Weissman, Myrna, Kendler, Kenneth, and Flint, Jonathan

Subjects
Adult, Aged, Bipolar Disorder, Depressive Disorder, Major, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Sensitivity and Specificity
Abstract

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Published
2020

10. Exascale applications: skin in the game

Author

Alexander, Francis, Almgren, Ann, Bell, John, Bhattacharjee, Amitava, Chen, Jacqueline, Colella, Phil, Daniel, David, DeSlippe, Jack, Diachin, Lori, Draeger, Erik, Dubey, Anshu, Dunning, Thom, Evans, Thomas, Foster, Ian, Francois, Marianne, Germann, Tim, Gordon, Mark, Habib, Salman, Halappanavar, Mahantesh, Hamilton, Steven, Hart, William, Huang, Zhenyu, Hungerford, Aimee, Kasen, Daniel, Kent, Paul RC, Kolev, Tzanio, Kothe, Douglas B, Kronfeld, Andreas, Luo, Ye, Mackenzie, Paul, McCallen, David, Messer, Bronson, Mniszewski, Sue, Oehmen, Chris, Perazzo, Amedeo, Perez, Danny, Richards, David, Rider, William J, Rieben, Rob, Roche, Kenneth, Siegel, Andrew, Sprague, Michael, Steefel, Carl, Stevens, Rick, Syamlal, Madhava, Taylor, Mark, Turner, John, Vay, Jean-Luc, Voter, Artur F, Windus, Theresa L, and Yelick, Katherine

Subjects
Information and Computing Sciences, Human-Centred Computing, Data Science, Affordable and Clean Energy, exascale, high-performance computing, computational science applications, numerical algorithms, machine learning, modelling and simulation, General Science & Technology
Abstract

As noted in Wikipedia, skin in the game refers to having 'incurred risk by being involved in achieving a goal', where 'skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

Published
2020

11. Spinnaker Software Quality Assurance FY23 Annual Report

Author

Slattery, Stuart, primary, Bement, Matt, additional, Bullerwell, Lance, additional, Chong, Kwitae, additional, Delchini, Marco, additional, Erwin, Taylor, additional, Glasby, Ryan, additional, Hall, Chris, additional, Hamilton, Steven, additional, Isner, Austin, additional, Karman, Steve, additional, Langford Jr, John, additional, Mutia, Pia, additional, Olshefski, Kris, additional, Sankaran, Ramanan, additional, Stefanski, Doug, additional, and Wise, Mike, additional

Published
2023
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12. Myasthenia Gravis

Author

Keung, Bonnie M., Hamilton, Steven R., Levin, Leonard, Section editor, Cestari, Dean, Section editor, Albert, Daniel M., editor, Miller, Joan W., editor, Azar, Dimitri T., editor, and Young, Lucy H., editor

Published
2022
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14. Assessment of the Lagrange Discrete Ordinates Equations for Three-Dimensional Neutron Transport

Author

Rowland, Kelly L, Ahrens, Cory D, Hamilton, Steven, and Slaybaugh, RN

Subjects
Engineering, Resources Engineering and Extractive Metallurgy, Quadrature, Lagrange, discrete ordinates, transport, Interdisciplinary Engineering, Energy, Resources engineering and extractive metallurgy
Abstract

The Lagrange Discrete Ordinates (LDO) equations, developed by Ahrens as an alternative to the traditional discrete ordinates formulation, have been implemented in Denovo, a three-dimensional radiation transport code developed by Oak Ridge National Laboratory. The LDO equations retain the formal structure of the classical discrete ordinates equations but treat particle scattering in a different way. Solutions of the LDO equations have an interpolatory structure such that the angular flux can be naturally evaluated at directions other than the discrete ordinates used in arriving at the solutions, and the ordinates themselves may be chosen in a strategic way for the problem under consideration. Of particular interest is that the LDO equations have been shown to mitigate ray effects at increased angular resolutions. In this paper we present scalar flux solutions of the LDO equations for a small number of test cases of interest and compare the results against flux solutions generated using standard quadrature types. The LDO equations’ flux solutions were found to be comparable to those resultant from the standard quadrature types in value; results from the LDO equations were also found to be commensurate with those of standard quadrature types when comparing the flux solutions in the context of the experimental benchmark test case examined.

Published
2019

15. Time Course of Changes in Peripheral Blood Gene Expression During Medication Treatment for Major Depressive Disorder.

Author

Cook, Ian, Congdon, Eliza, Hunter, Aimee, Hamilton, Steven, Leuchter, Andrew, Krantz, David, and Coppola, Giovanni

Subjects
antidepressant treatment, biomarkers, gene expression, neuroscience, predictive markers
Abstract

Changes in gene expression (GE) during antidepressant treatment may increase understanding of the action of antidepressant medications and serve as biomarkers of efficacy. GE changes in peripheral blood are desirable because they can be assessed easily on multiple occasions during treatment. We report here on GE changes in 68 individuals who were treated for 8 weeks with either escitalopram alone, or escitalopram followed by bupropion. GE changes were assessed after 1, 2, and 8 weeks of treatment, with significant changes observed in 156, 121, and 585 peripheral blood gene transcripts, respectively. Thirty-one transcript changes were shared between the 1- and 8-week time points (seven upregulated, 24 downregulated). Differences were detected between the escitalopram- and bupropion-treated subjects, although there was no significant association between GE changes and clinical outcome. A subset of 18 genes overlapped with those previously identified as differentially expressed in subjects with MDD compared with healthy control subjects. There was statistically significant overlap between genes differentially expressed in the current and previous studies, with 10 genes overlapping in at least two previous studies. There was no enrichment for genes overexpressed in nervous system cell types, but there was a trend toward enrichment for genes in the WNT/β-catenin pathway in the anterior thalamus; three genes in this pathway showed differential expression in the present and in three previous studies. Our dataset and other similar studies will provide an important source of information about potential biomarkers of recovery and for potential dysregulation of GE in MDD.

Published
2019

16. Time Course of Changes in Peripheral Blood Gene Expression During Medication Treatment for Major Depressive Disorder

Author

Cook, Ian A, Congdon, Eliza, Krantz, David E, Hunter, Aimee M, Coppola, Giovanni, Hamilton, Steven P, and Leuchter, Andrew F

Subjects
Biological Sciences, Genetics, Clinical Research, Depression, Neurosciences, Brain Disorders, Mental Health, Aetiology, 2.1 Biological and endogenous factors, biomarkers, predictive markers, neuroscience, gene expression, antidepressant treatment, Clinical Sciences, Law
Abstract

Changes in gene expression (GE) during antidepressant treatment may increase understanding of the action of antidepressant medications and serve as biomarkers of efficacy. GE changes in peripheral blood are desirable because they can be assessed easily on multiple occasions during treatment. We report here on GE changes in 68 individuals who were treated for 8 weeks with either escitalopram alone, or escitalopram followed by bupropion. GE changes were assessed after 1, 2, and 8 weeks of treatment, with significant changes observed in 156, 121, and 585 peripheral blood gene transcripts, respectively. Thirty-one transcript changes were shared between the 1- and 8-week time points (seven upregulated, 24 downregulated). Differences were detected between the escitalopram- and bupropion-treated subjects, although there was no significant association between GE changes and clinical outcome. A subset of 18 genes overlapped with those previously identified as differentially expressed in subjects with MDD compared with healthy control subjects. There was statistically significant overlap between genes differentially expressed in the current and previous studies, with 10 genes overlapping in at least two previous studies. There was no enrichment for genes overexpressed in nervous system cell types, but there was a trend toward enrichment for genes in the WNT/β-catenin pathway in the anterior thalamus; three genes in this pathway showed differential expression in the present and in three previous studies. Our dataset and other similar studies will provide an important source of information about potential biomarkers of recovery and for potential dysregulation of GE in MDD.

Published
2019

17. Identifying the Common Genetic Basis of Antidepressant Response

Author

Kasper, Siegfried, Zohar, Joseph, Souery, Daniel, Montgomery, Stuart, Albani, Diego, Forloni, Gianluigi, Ferentinos, Panagiotis, Rujescu, Dan, Mendlewicz, Julien, Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Foo, Jerome C., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Howard, David M., Ising, Marcus, Jansen, Rick, Jones, Ian, Jones, Lisa A., Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O’Reilly, Paul F., Oskarsson, Hogni, Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E.J.C., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, Nöthen, Markus M., O’Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., Pain, Oliver, Hodgson, Karen, Marshe, Victoria S., Campos, Adrian I., Carrillo-Roa, Tania, Cattaneo, Annamaria, Als, Thomas D., Dernovsek, Mojca Z., Fabbri, Chiara, Henigsberg, Neven, Hauser, Joanna, Kennedy, James L., Lenze, Eric J., Müller, Daniel J., Mulsant, Benoit H., Perroud, Nader, Rentería, Miguel E., Reynolds, Charles F., III, Wigmore, Eleanor M., Aitchison, Katherine J., Biernacka, Joanna M., Bondolfi, Guido, Kato, Masaki, Liu, Yu-Li, Serretti, Alessandro, Tsai, Shih-Jen, Turecki, Gustavo, and Weinshilboum, Richard

Published
2022
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18. Eigenvalue Solvers for Modeling Nuclear Reactors on Leadership Class Machines

Author

Slaybaugh, R. N., Ramirez-Zweiger, M., Pandya, Tara, Hamilton, Steven, and Evans, T. M.

Subjects
Computer Science - Numerical Analysis, Physics - Computational Physics
Abstract

Three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a Rayleigh Quotient Iteration (RQI) eigenvalue solver, and a multigrid in energy (MGE) preconditioner. The MG Krylov solver converges more quickly than Gauss Seidel and enables energy decomposition such that Denovo can scale to hundreds of thousands of cores. RQI should converge in fewer iterations than power iteration (PI) for large and challenging problems. RQI creates shifted systems that would not be tractable without the MG Krylov solver. It also creates ill-conditioned matrices. The MGE preconditioner reduces iteration count significantly when used with RQI and takes advantage of the new energy decomposition such that it can scale efficiently. Each individual method has been described before, but this is the first time they have been demonstrated to work together effectively. The combination of solvers enables the RQI eigenvalue solver to work better than the other available solvers for large reactors problems on leadership class machines. Using these methods together, RQI converged in fewer iterations and in less time than PI for a full pressurized water reactor core. These solvers also performed better than an Arnoldi eigenvalue solver for a reactor benchmark problem when energy decomposition is needed. The MG Krylov, MGE preconditioner, and RQI solver combination also scales well in energy. This solver set is a strong choice for very large and challenging problems., Comment: arXiv admin note: substantial text overlap with arXiv:1702.02111, arXiv:1612.00907

Published
2017
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19. Applying natural language processing to identify emergency department and observation encounters for worsening heart failure.

Author

Hamilton, Steven A., Ambrosy, Andrew P., Parikh, Rishi V., Tan, Thida C., Fitzpatrick, Jesse K., Avula, Harshith R., Sandhu, Alexander T., Ku, Ivy A., Go, Alan S., Sax, Dana, and Bhatt, Ankeet S.

Subjects
NATURAL language processing, EMERGENCY room visits, VENTRICULAR ejection fraction, HEART failure, HOSPITAL emergency services
Abstract

Aims: Worsening heart failure (WHF) events occurring in non‐inpatient settings are becoming increasingly recognized, with implications for prognostication. We evaluate the performance of a natural language processing (NLP)‐based approach compared with traditional diagnostic coding for non‐inpatient clinical encounters and left ventricular ejection fraction (LVEF). Methods and results: We compared characteristics for encounters that did vs. did not meet WHF criteria, stratified by care setting [i.e. emergency department (ED) and observation stay]. Overall, 8407 (22%) encounters met NLP‐based criteria for WHF (3909 ED visits and 4498 observation stays). The use of an NLP‐derived definition adjudicated 3983 (12%) of non‐primary HF diagnoses as meeting consensus definitions for WHF. The most common diagnosis indicated in these encounters was dyspnoea. Results were primarily driven by observation stays, in which 2205 (23%) encounters with a secondary HF diagnosis met the WHF definition by NLP. Conclusions: The use of standard claims‐based adjudication for primary diagnosis in the non‐inpatient setting may lead to misclassification of WHF events in the ED and overestimate observation stays. Primary diagnoses alone may underestimate the burden of WHF in non‐hospitalized settings. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Eigenvalue Solvers for Modeling Nuclear Reactors on Leadership Class Machines

Author

Slaybaugh, RN, Ramirez-Zweiger, M, Pandya, Tara, Hamilton, Steven, and Evans, TM

Subjects
Affordable and Clean Energy, Eigenvalue, Rayleigh quotient, preconditioning, cs.NA, physics.comp-ph, Interdisciplinary Engineering, Energy
Abstract

Three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a Rayleigh quotient iteration (RQI) eigenvalue solver, and a multigrid in energy (MGE) preconditioner. The MG Krylov solver converges more quickly than Gauss Seidel and enables energy decomposition such that Denovo can scale to hundreds of thousands of cores. RQI should converge in fewer iterations than power iteration (PI) for large and challenging problems. RQI creates shifted systems that would not be tractable without the MG Krylov solver. It also creates ill-conditioned matrices. The MGE preconditioner reduces iteration count significantly when used with RQI and takes advantage of the new energy decomposition such that it can scale efficiently. Each individual method has been described before, but this is the first time they have been demonstrated to work together effectively. The combination of solvers enables the RQI eigenvalue solver to work better than the other available solvers for large reactors problems on leadership-class machines. Using these methods together, RQI converged in fewer iterations and in less time than PI for a full pressurized water reactor core. These solvers also performed better than an Arnoldi eigenvalue solver for a reactor benchmark problem when energy decomposition is needed. The MG Krylov, MGE preconditioner, and RQI solver combination also scales well in energy. This solver set is a strong choice for very large and challenging problems.

Published
2018

22. The association between genetically determined ABO blood types and major depressive disorder

Author

Garvert, Linda, Baune, Bernhard T, Berger, Klaus, Boomsma, Dorret I, Breen, Gerome, Greinacher, Andreas, Hamilton, Steven P, Levinson, Douglas F, Lewis, Cathryn M, Lucae, Susanne, Magnusson, Patrik K E, Martin, Nicholas G, McIntosh, Andrew M, Mors, Ole, Müller-Myhsok, Bertram, Penninx, Brenda W J H, Perlis, Roy H, Pistis, Giorgio, Potash, James B, Preisig, Martin, Rietschel, Marcella, Shi, Jianxin, Smoller, Jordan W, Tiemeier, Henning, Uher, Rudolf, Völker, Uwe, Völzke, Henry, Weissman, Myrna M, Grabe, Hans J, and Van der Auwera, Sandra

Published
2021
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24. The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

Author

Byrne, Enda M., Forstner, Andreas J., Holmans, Peter A., de Leeuw, Christiaan A., Mattheisen, Manuel, McQuillin, Andrew, Whitehead Pavlides, Jennifer M., Pers, Tune H., Ripke, Stephan, Stahl, Eli A., Steinberg, Stacy, Trubetskoy, Vassily, Trzaskowski, Maciej, Wang, Yunpeng, Abbott, Liam, Abdellaoui, Abdel, Adams, Mark J., Adolfsson, Annelie Nordin, Agerbo, Esben, Akil, Huda, Albani, Diego, Alliey-Rodriguez, Ney, Als, Thomas D., Andlauer, Till F.M., Anjorin, Adebayo, Antilla, Verneri, Van der Auwera, Sandra, Awasthi, Swapnil, Bacanu, Silviu-Alin, Badner, Judith A., Bækvad-Hansen, Marie, Barchas, Jack D., Bass, Nicholas, Bauer, Michael, Beekman, Aartjan T.F., Belliveau, Richard, Bergen, Sarah E., Bigdeli, Tim B., Binder, Elisabeth B., Bøen, Erlend, Boks, Marco, Boocock, James, Budde, Monika, Bunney, William, Burmeister, Margit, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Byerley, William, Cai, Na, Casas, Miquel, Castelao, Enrique, Cerrato, Felecia, Cervantes, Pablo, Chambert, Kimberly, Charney, Alexander W., Chen, Danfeng, Christensen, Jane Hvarregaard, Churchhouse, Claire, St Clair, David, Clarke, Toni-Kim, Colodro-Conde, Lucía, Coryell, William, Couvy-Duchesne, Baptiste, Craig, David W., Crawford, Gregory E., Cruceanu, Cristiana, Czerski, Piotr M., Dale, Anders M., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Del-Favero, Jurgen, DePaulo, J Raymond, Derks, Eske M., Direk, Nese, Djurovic, Srdjan, Dobbyn, Amanda L., Dolan, Conor V., Dumont, Ashley, Dunn, Erin C., Eley, Thalia C., Elvsåshagen, Torbjørn, Escott-Price, Valentina, Fan, Chun Chieh, Finucane, Hilary K., Fischer, Sascha B., Flickinger, Matthew, Foo, Jerome C., Foroud, Tatiana M., Forty, Liz, Frank, Josef, Fraser, Christine, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Gage, Diane, Garnham, Julie, Giambartolomei, Claudia, Goes, Fernando S., Goldstein, Jaqueline, Gordon, Scott D., Gordon-Smith, Katherine, Green, Elaine K., Green, Melissa J., Greenwood, Tiffany A., Grove, Jakob, Guan, Weihua, Hall, Lynsey S., Hamshere, Marian L., Hansen, Christine Søholm, Hansen, Thomas F., Hautzinger, Martin, Heilbronner, Urs, van Hemert, Albert M., Herms, Stefan, Hickie, Ian B., Hipolito, Maria, Hoffmann, Per, Holland, Dominic, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Huckins, Laura, Ising, Marcus, Jamain, Stéphane, Jansen, Rick, Johnson, Jessica S., de Jong, Simone, Jorgenson, Eric, Juréus, Anders, Kandaswamy, Radhika, Karlsson, Robert, Kennedy, James L., Hassan Kiadeh, Farnush Farhadi, Kittel-Schneider, Sarah, Knowles, James A., Kogevinas, Manolis, Kohane, Isaac S., Koller, Anna C., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kupka, Ralph, Kutalik, Zoltán, Lavebratt, Catharina, Lawrence, Jacob, Lawson, William B., Leber, Markus, Lee, Phil H., Levy, Shawn E., Li, Jun Z., Li, Yihan, Lind, Penelope A., Liu, Chunyu, Olde Loohuis, Loes M., Maaser, Anna, MacIntyre, Donald J., MacKinnon, Dean F., Mahon, Pamela B., Maier, Wolfgang, Maier, Robert M., Marchini, Jonathan, Martinsson, Lina, Mbarek, Hamdi, McCarroll, Steve, McGrath, Patrick, McGuffin, Peter, McInnis, Melvin G., McKay, James D., Medeiros, Helena, Medland, Sarah E., Mehta, Divya, Meng, Fan, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mirza, Saira Saeed, Mondimore, Francis M., Montgomery, Grant W., Morris, Derek W., Mostafavi, Sara, Mühleisen, Thomas W., Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nguyen, Hoang, Nievergelt, Caroline M., Nivard, Michel G., Nwulia, Evaristus A., Nyholt, Dale R., O'Donovan, Claire, O'Reilly, Paul F., Ori, Anil P.S., Oruc, Lilijana, Ösby, Urban, Oskarsson, Hogni, Painter, Jodie N., Parra, José Guzman, Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Perry, Amy, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pfennig, Andrea, Pistis, Giorgio, Purcell, Shaun M., Quiroz, Jorge A., Qvist, Per, Regeer, Eline J., Reif, Andreas, Reinbold, Céline S., Rice, John P., Riley, Brien P., Rivas, Fabio, Rivera, Margarita, Roussos, Panos, Ruderfer, Douglas M., Ryu, Euijung, Sánchez-Mora, Cristina, Schatzberg, Alan F., Scheftner, William A., Schoevers, Robert, Schork, Nicholas J., Schulte, Eva C., Shehktman, Tatyana, Shen, Ling, Shi, Jianxin, Shilling, Paul D., Shyn, Stanley I., Sigurdsson, Engilbert, Slaney, Claire, Smeland, Olav B., Smit, Johannes H., Smith, Daniel J., Sobell, Janet L., Spijker, Anne T., Steffens, Michael, Strauss, John S., Streit, Fabian, Strohmaier, Jana, Szelinger, Szabolcs, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Robert C., Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Uitterlinden, André G., Umbricht, Daniel, Vedder, Helmut, Viktorin, Alexander, Visscher, Peter M., Wang, Weiqing, Watson, Stanley J., Webb, Bradley T., Weickert, Cynthia Shannon, Weickert, Thomas W., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Xu, Wei, Yang, Jian, Young, Allan H., Zandi, Peter, Zhang, Peng, Zhang, Futao, Zollner, Sebastian, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Arolt, Volker, Backlund, Lena, Baune, Bernhard T., Bellivier, Frank, Berger, Klaus, Berrettini, Wade H., Biernacka, Joanna M., Blackwood, Douglas H.R., Boehnke, Michael, Boomsma, Dorret I., Corvin, Aiden, Craddock, Nicholas, Daly, Mark J., Dannlowski, Udo, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Etain, Bruno, Frye, Mark, Fullerton, Janice M., Gershon, Elliot S., de Geus, E.J.C., Gill, Michael, Goes, Fernando, Grabe, Hans J., Grigoroiu-Serbanescu, Maria, Hamilton, Steven P., Hauser, Joanna, Hayward, Caroline, Heath, Andrew C., Hougaard, David M., Hultman, Christina M., Jones, Ian, Jones, Lisa A., Kahn, René S., Kendler, Kenneth S., Kirov, George, Kloiber, Stefan, Landén, Mikael, Leboyer, Marion, Lewis, Glyn, Li, Qingqin S., Lissowska, Jolanta, Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., Mayoral, Fermin, McElroy, Susan L., McIntosh, Andrew M., McMahon, Francis J., Melle, Ingrid, Metspalu, Andres, Mitchell, Philip B., Morken, Gunnar, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Myers, Richard M., Neale, Benjamin M., Nimgaonkar, Vishwajit, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Oedegaard, Ketil J., Owen, Michael J., Paciga, Sara A., Pato, Carlos, Pato, Michele T., Pedersen, Nancy L., Penninx, Brenda W.J. H., Perlis, Roy H., Porteous, David J., Posthuma, Danielle, Potash, James B., Preisig, Martin, Ramos-Quiroga, Josep Antoni, Ribasés, Marta, Rietschel, Marcella, Rouleau, Guy A., Schaefer, Catherine, Schalling, Martin, Schofield, Peter R., Schulze, Thomas G., Serretti, Alessandro, Smoller, Jordan W., Stefansson, Hreinn, Stefansson, Kari, Stordal, Eystein, Tiemeier, Henning, Turecki, Gustavo, Uher, Rudolf, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Andreassen, Ole A., Børglum, Anders D., Cichon, Sven, Edenberg, Howard J., Di Florio, Arianna, Kelsoe, John, Levinson, Douglas F., Lewis, Cathryn M., Nurnberger, John I., Ophoff, Roel A., Scott, Laura J., Sklar, Pamela, Sullivan, Patrick F., Wray, Naomi R., Coleman, Jonathan R.I., Gaspar, Héléna A., Bryois, Julien, and Breen, Gerome

Published
2020
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27. Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression

Author

Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Foo, Jerome C., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Howard, David M., Ising, Marcus, Jansen, Rick, Jones, Ian, Jones, Lisa A., Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O'Reilly, Paul F., Oskarsson, Hogni, Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, Andrés G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, EJC., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela AF., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., Glanville, Kylie P., Hanscombe, Ken B., Euesden, Jack, Choi, Shing Wan, Purves, Kirstin L., Blackwood, Douglas H.R., and de Geus, Eco J.C.

Published
2020
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29. A Parallel Multi-Domain Solution Methodology Applied to Nonlinear Thermal Transport Problems in Nuclear Fuel Pins

Author

Philip, Bobby, Berrill, Mark A., Allu, Srikanth, Hamilton, Steven P., Sampath, Rahul S., Clarno, Kevin T., and Dilts, Gary A

Subjects
Physics - Computational Physics
Abstract

This paper describes an efficient and nonlinearly consistent parallel solution methodology for solving coupled nonlinear thermal transport problems that occur in nuclear reactor applications over hundreds of individual 3D physical subdomains. Efficiency is obtained by leveraging knowledge of the physical domains, the physics on individual domains, and the couplings between them for preconditioning within a Jacobian Free Newton Krylov method. Details of the computational infrastructure that enabled this work, namely the open source Advanced Multi-Physics (AMP) package developed by the authors is described. Details of verification and validation experiments, and parallel performance analysis in weak and strong scaling studies demonstrating the achieved efficiency of the algorithm are presented. Furthermore, numerical experiments demonstrate that the preconditioner developed is independent of the number of fuel subdomains in a fuel rod, which is particularly important when simulating different types of fuel rods. Finally, we demonstrate the power of the coupling methodology by considering problems with couplings between surface and volume physics and coupling of nonlinear thermal transport in fuel rods to an external radiation transport code.

Published
2014
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30. A TALE OF TWO WAGE SUBSIDIES: THE AMERICAN AND AUSTRALIAN FISCAL RESPONSES TO C0VID-19.

Author

Hamilton, Steven

Subjects
COVID-19 -- Economic aspects, Tax expenditures -- Comparative analysis -- Research, Employment subsidies -- Comparative analysis -- Research
Abstract

I. INTRODUCTION As of July 2020, almost six million people are confirmed to have had COVID-19, leading to more than half a million deaths. (1) In addition to sparking the [...], In July 2020, C0VID-19 had been suppressed in Australia but continued to spread across the United States. Both countries instituted lock-downs and fiscal support, but Australia experienced a milder recession, highlighting the role of public health measures in protecting the economy. Cash stimulus is less useful than in a normal recession, justifying wage subsidies encouraging businesses to retain workers. The Australian wage subsidy, delivered via the tax authority, was better targeted, more generous, more accessible, but slower than the American wage subsidy delivered via banks. The experience highlights the need for investments in IRS infrastructure to better prepare for future crises. Keywords: COVID-19, wage subsidy, fiscal stimulus JEL Codes: D04, J08, E62

Published
2020
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31. NPAS1 represses the generation of specific subtypes of cortical interneurons.

Author

Stanco, Amelia, Pla, Ramón, Vogt, Daniel, Chen, Yiran, Mandal, Shyamali, Walker, Jamie, Hunt, Robert F, Lindtner, Susan, Erdman, Carolyn A, Pieper, Andrew A, Hamilton, Steven P, Xu, Duan, Baraban, Scott C, and Rubenstein, John LR

Subjects
Cerebral Cortex, Interneurons, Cells, Cultured, Animals, Mice, Inbred C57BL, Animals, Newborn, Mice, Transgenic, Humans, Mice, Glutamate Decarboxylase, Nerve Tissue Proteins, Transcription Factors, Autistic Disorder, Age Factors, Cell Proliferation, MAP Kinase Signaling System, Gene Expression Regulation, Developmental, Polymorphism, Single Nucleotide, Female, Male, Basic Helix-Loop-Helix Transcription Factors, Embryo, Mammalian, LIM-Homeodomain Proteins, Genetics, Stem Cell Research - Nonembryonic - Non-Human, Stem Cell Research, Underpinning research, 1.1 Normal biological development and functioning, Neurosciences, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Little is known about genetic mechanisms that regulate the ratio of cortical excitatory and inhibitory neurons. We show that NPAS1 and NPAS3 transcription factors (TFs) are expressed in progenitor domains of the mouse basal ganglia (subpallium, MGE, and CGE). NPAS1(-/-) mutants had increased proliferation, ERK signaling, and expression of Arx in the MGE and CGE. NPAS1(-/-) mutants also had increased neocortical inhibition (sIPSC and mIPSC) and generated an excess of somatostatin(+) (SST) (MGE-derived) and vasoactive intestinal polypeptide(+) (VIP) (CGE-derived) neocortical interneurons, but had a normal density of parvalbumin(+) (PV) (MGE-derived) interneurons. In contrast, NPAS3(-/-) mutants showed decreased proliferation and ERK signaling in progenitors of the ganglionic eminences and had fewer SST(+) and VIP(+) interneurons. NPAS1 repressed activity of an Arx enhancer, and Arx overexpression resulted in increased proliferation of CGE progenitors. These results provide insights into genetic regulation of cortical interneuron numbers and cortical inhibitory tone.

Published
2014

34. Association of Whole-Genome and NETRIN1 Signaling Pathway–Derived Polygenic Risk Scores for Major Depressive Disorder and White Matter Microstructure in the UK Biobank

Author

Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Blackwood, Douglas H.R., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Ising, Marcus, Jansen, Rick, Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O'Reilly, Paul F., Oskarsson, Hogni, Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E.J.C., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Sathirapongsasuti, J. Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, Wilson, Catherine H., Barbu, Miruna C., Zeng, Yanni, Shen, Xueyi, Cox, Simon R., Gibson, Jude, Johnstone, Mandy, Haley, Chris S., Lawrie, Stephen M., and Whalley, Heather C.

Published
2019
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35. Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs

Author

Merzari, Elia, primary, Hamilton, Steven, additional, Evans, Thomas, additional, Min, Misun, additional, Fischer, Paul, additional, Kerkemeier, Stefan, additional, Fang, Jun, additional, Romano, Paul, additional, Lan, Yu-Hsiang, additional, Phillips, Malachi, additional, Biondo, Elliott, additional, Royston, Katherine, additional, Warburton, Tim, additional, Chalmers, Noel, additional, and Rathnayake, Thilina, additional

Published
2023
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36. Frontier: Exploring Exascale

Author

Atchley, Scott, primary, Zimmer, Christopher, additional, Lange, John, additional, Bernholdt, David, additional, Melesse Vergara, Veronica, additional, Beck, Thomas, additional, Brim, Michael, additional, Budiardja, Reuben, additional, Chandrasekaran, Sunita, additional, Eisenbach, Markus, additional, Evans, Thomas, additional, Ezell, Matthew, additional, Frontiere, Nicholas, additional, Georgiadou, Antigoni, additional, Glenski, Joe, additional, Grete, Philipp, additional, Hamilton, Steven, additional, Holmen, John, additional, Huebl, Axel, additional, Jacobson, Daniel, additional, Joubert, Wayne, additional, Mcmahon, Kim, additional, Merzari, Elia, additional, Moore, Stan, additional, Myers, Andrew, additional, Nichols, Stephen, additional, Oral, Sarp, additional, Papatheodore, Thomas, additional, Perez, Danny, additional, Rogers, David M., additional, Schneider, Evan, additional, Vay, Jean-Luc, additional, and Yeung, P. K., additional

Published
2023
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37. Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction

Author

Parikh, Rishi V., primary, Go, Alan S., additional, Bhatt, Ankeet S., additional, Tan, Thida C., additional, Allen, Amanda R., additional, Feng, Kent Y., additional, Hamilton, Steven A., additional, Tai, Andrew S., additional, Fitzpatrick, Jesse K., additional, Lee, Keane K., additional, Adatya, Sirtaz, additional, Avula, Harshith R., additional, Sax, Dana R., additional, Shen, Xian, additional, Cristino, Joaquim, additional, Sandhu, Alexander T., additional, Heidenreich, Paul A., additional, and Ambrosy, Andrew P., additional

Published
2023
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40. Does Childhood Trauma Moderate Polygenic Risk for Depression? A Meta-analysis of 5765 Subjects From the Psychiatric Genomics Consortium

Author

Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Blackwood, Douglas H.R., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Farnush, Kiadeh, Farhadi Hassan, Finucane, Hilary K., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hicki, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Ising, Marcus, Jansen, Rick, Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O’Reilly, Paul F., Oskarsson, Hogni, Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E.J.C., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., Henders, Anjali K., Heat, Andrew C., Fisher, Helen L., Air, Tracy A., Martin, Nick G., and Nelson, Elliot N.

Published
2018
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42. A genome-wide association study of a sustained pattern of antidepressant response

Author

Hunter, Aimee M, Leuchter, Andrew F, Power, Robert A, Muthén, Bengt, McGrath, Patrick J, Lewis, Cathryn M, Cook, Ian A, Garriock, Holly A, McGuffin, Peter, Uher, Rudolf, and Hamilton, Steven P

Subjects
Brain Disorders, Clinical Trials and Supportive Activities, Human Genome, Clinical Research, Genetics, Mental Health, Prevention, Depression, Aetiology, 2.1 Biological and endogenous factors, Mental health, Antidepressive Agents, Clinical Trials as Topic, Confidence Intervals, Depressive Disorder, Major, Genome-Wide Association Study, Genotype, Humans, Odds Ratio, Pharmacogenetics, Polymorphism, Single Nucleotide, Antidepressant, STAR*D, GENDEP, Growth mixture modeling, Citalopram, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Genome-wide association studies (GWAS) have failed to replicate common genetic variants associated with antidepressant response, as defined using a single endpoint. Genetic influences may be discernible by examining individual variation between sustained versus unsustained patterns of response, which may distinguish medication effects from non-specific, or placebo responses to active medication. We conducted a GWAS among 1116 subjects with Major Depressive Disorder from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial who were characterized using Growth Mixture Modeling as showing a sustained versus unsustained pattern of clinical response over 12 weeks of treatment with citalopram. Replication analyses examined 585 subjects from the Genome-based Therapeutic Drugs for Depression (GENDEP) trial. The strongest association with sustained as opposed to unsustained response in STAR*D involved a single nucleotide polymorphism (SNP; rs10492002) within the acyl-CoA synthetase short-chain family member 3 gene (ACSS3, p-value=4.5×10(-6), odds ratio=0.61). No SNPs met our threshold for genome-wide significance. SNP data were available in GENDEP for 18 of the top 25 SNPs in STAR*D. The most replicable association was with SNP rs7816924 (p=0.008, OR=1.58); no SNP met the replication p-value threshold of 0.003. Joint analysis of these 18 SNPs resulted in the strongest signal coming from rs7816924 (p=2.11×10(-7)), which resides in chondroitin sulfate N-acetylgalactosaminyltransferase 1 gene (CSGALNACT1). An exploratory genetic pathway analysis revealed evidence for an involvement of the KEGG pathway of long-term potentiation (FDR=.02). Results suggest novel genetic associations to sustained response.

Published
2013

43. A pilot study evaluating genetic and environmental factors for postpartum depression.

Author

El-Ibiary, Shareen Y, Hamilton, Steven P, Abel, Rebecca, Erdman, Carolyn A, Robertson, Patricia A, and Finley, Patrick R

Subjects
Mental Health, Genetic Testing, Depression, Genetics, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, HTR2A, Perinatal depression, gene-environment interaction, postpartum, serotonin
Abstract

ObjectiveTo assess the influence of genetic and environmental risk factors upon postpartum depression.DesignCase-control, prospective study.SettingThe University of California at San Francisco Obstetric and Gynecology Clinic.ParticipantsMothers screened for postpartum depression six weeks after delivery with the Edinburgh Postnatal Depression Scale and recruited as cases and controls.MeasurementsEligible subjects completed a series of assessments and a structured clinical interview to confirm diagnosis of depression. Deoxyribonucleic acid was obtained for genotyping of 81 single nucleotide polymorphisms in 12 genes hypothesized to be postpartum depression-related.ResultsTwenty-four cases and 24 controls were eligible for analysis. Three single necleotide polymorphisms in the serotonin 2A receptor (HTR2A) gene were associated with postpartum depression. The strongest association at a functional promoter polymorphism (rs6311), a functional promoter single nucleotide polymorphisms (p=0.002, odds ratio 0.25, 95% confidence interval:0.10-0.63), was a finding robust to population stratification. Gene-wide association was significant for HTR2A (permuted p=0.008), but not when corrected for all 12 genes. Analysis of demographic and psychosocial risk factors identified distressed relationship, unplanned pregnancy, and a previous history of depression as significant predictive variables (p≤0.05).ConclusionsThis pilot data suggests deoxyribonucleic acid variations in HTR2A may be associated with postpartum depression. Psychosocial variables were also identified as risk factors. The relative influence of these variables on the manifestation of postpartum depression is yet to be determined.

Published
2013

44. Variation in genes related to cochlear biology is strongly associated with adult-onset deafness in border collies.

Author

Yokoyama, Jennifer S, Lam, Ernest T, Ruhe, Alison L, Erdman, Carolyn A, Robertson, Kathryn R, Webb, Aubrey A, Williams, D Colette, Chang, Melanie L, Hytönen, Marjo K, Lohi, Hannes, Hamilton, Steven P, and Neff, Mark W

Subjects
Cochlea, Animals, Dogs, Humans, Deafness, Cochlear Diseases, Genetic Predisposition to Disease, Endopeptidases, Ubiquitin-Protein Ligases, Carrier Proteins, DNA-Binding Proteins, NF-kappa B, Chromosome Mapping, Aging, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Ubiquitin-Specific Proteases, Polymorphism, Single Nucleotide, Developmental Biology, Genetics
Abstract

Domestic dogs can suffer from hearing losses that can have profound impacts on working ability and quality of life. We have identified a type of adult-onset hearing loss in Border Collies that appears to have a genetic cause, with an earlier age of onset (3-5 years) than typically expected for aging dogs (8-10 years). Studying this complex trait within pure breeds of dog may greatly increase our ability to identify genomic regions associated with risk of hearing impairment in dogs and in humans. We performed a genome-wide association study (GWAS) to detect loci underlying adult-onset deafness in a sample of 20 affected and 28 control Border Collies. We identified a region on canine chromosome 6 that demonstrates extended support for association surrounding SNP Chr6.25819273 (p-value = 1.09 × 10(-13)). To further localize disease-associated variants, targeted next-generation sequencing (NGS) of one affected and two unaffected dogs was performed. Through additional validation based on targeted genotyping of additional cases (n = 23 total) and controls (n = 101 total) and an independent replication cohort of 16 cases and 265 controls, we identified variants in USP31 that were strongly associated with adult-onset deafness in Border Collies, suggesting the involvement of the NF-κB pathway. We found additional support for involvement of RBBP6, which is critical for cochlear development. These findings highlight the utility of GWAS-guided fine-mapping of genetic loci using targeted NGS to study hereditary disorders of the domestic dog that may be analogous to human disorders.

Published
2012

46. Association between regulator of G protein signaling 9-2 and body weight.

Author

Waugh, Jeffrey L, Celver, Jeremy, Sharma, Meenakshi, Dufresne, Robert L, Terzi, Dimitra, Risch, S Craig, Fairbrother, William G, Neve, Rachael L, Kane, John P, Malloy, Mary J, Pullinger, Clive R, Gu, Harvest F, Tsatsanis, Christos, Hamilton, Steven P, Gold, Stephen J, Zachariou, Venetia, and Kovoor, Abraham

Subjects
Nucleus Accumbens, Adipose Tissue, Adipocytes, Animals, Mice, Knockout, Humans, Mice, Rats, Body Weight, Weight Loss, RGS Proteins, Body Mass Index, Motor Activity, RNA Splicing, Sequence Deletion, Base Sequence, Genes, Reporter, Introns, Molecular Sequence Data, Female, Male, Intra-Abdominal Fat, Genetic Association Studies, Genes, Reporter, Knockout, General Science & Technology
Abstract

Regulator of G protein signaling 9-2 (RGS9-2) is a protein that is highly enriched in the striatum, a brain region that mediates motivation, movement and reward responses. We identified a naturally occurring 5 nucleotide deletion polymorphism in the human RGS9 gene and found that the mean body mass index (BMI) of individuals with the deletion was significantly higher than those without. A splicing reporter minigene assay demonstrated that the deletion had the potential to significantly decrease the levels of correctly spliced RGS9 gene product. We measured the weights of rats after virally transduced overexpression of RGS9-2 or the structurally related RGS proteins, RGS7, or RGS11, in the nucleus accumbens (NAc) and observed a reduction in body weight after overexpression of RGS9-2 but not RGS7 or 11. Conversely, we found that the RGS9 knockout mice were heavier than their wild-type littermates and had significantly higher percentages of abdominal fat. The constituent adipocytes were found to have a mean cross-sectional area that was more than double that of corresponding cells from wild-type mice. However, food intake and locomotion were not significantly different between the two strains. These studies with humans, rats and mice implicate RGS9-2 as a factor in regulating body weight.

Published
2011

47. Biomarkers to Predict Antidepressant Response

Author

Leuchter, Andrew F, Cook, Ian A, Hamilton, Steven P, Narr, Katherine L, Toga, Arthur, Hunter, Aimee M, Faull, Kym, Whitelegge, Julian, Andrews, Anne M, Loo, Joseph, Way, Baldwin, Nelson, Stanley F, Horvath, Steven, and Lebowitz, Barry D

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Mental Health, Serious Mental Illness, Clinical Research, Clinical Trials and Supportive Activities, Depression, Brain Disorders, Good Health and Well Being, Antidepressive Agents, Biomarkers, Depressive Disorder, Humans, Predictive Value of Tests, Treatment Outcome, Major depression, Predicting treatment response, Brain imaging, Magnetic resonance imaging, Quantitative electroencephalography, Cordance, Antidepressant Treatment Response (ATR) Index, Positron emission tomography, Pharmacogenomics, Proteomics, Metabolomics, Neurosciences, Psychiatry, Clinical sciences, Applied and developmental psychology, Clinical and health psychology
Abstract

During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection.

Published
2010

48. Polygenic risk prediction: why and when out-of-sample prediction R2 can exceed SNP-based heritability

Author

Wang, Xiaotong, primary, Walker, Alicia, additional, Revez, Joana A., additional, Ni, Guiyan, additional, Adams, Mark J., additional, McIntosh, Andrew M., additional, Visscher, Peter M., additional, Wray, Naomi R., additional, Ripke, Stephan, additional, Mattheisen, Manuel, additional, Trzaskowski, Maciej, additional, Byrne, Enda M., additional, Abdellaoui, Abdel, additional, Agerbo, Esben, additional, Air, Tracy M., additional, Andlauer, Till F.M., additional, Bacanu, Silviu-Alin, additional, Bækvad-Hansen, Marie, additional, Beekman, Aartjan T.F., additional, Bigdeli, Tim B., additional, Binder, Elisabeth B., additional, Bryois, Julien, additional, Buttenschøn, Henriette N., additional, Bybjerg-Grauholm, Jonas, additional, Cai, Na, additional, Castelao, Enrique, additional, Christensen, Jane Hvarregaard, additional, Clarke, Toni-Kim, additional, Coleman, Jonathan R.I., additional, Colodro-Conde, Lucía, additional, Couvy-Duchesne, Baptiste, additional, Craddock, Nick, additional, Crawford, Gregory E., additional, Davies, Gail, additional, Degenhardt, Franziska, additional, Derks, Eske M., additional, Direk, Nese, additional, Dolan, Conor V., additional, Dunn, Erin C., additional, Eley, Thalia C., additional, Escott-Price, Valentina, additional, Kiadeh, Farnush Farhadi Hassan, additional, Finucane, Hilary K., additional, Foo, Jerome C., additional, Forstner, Andreas J., additional, Frank, Josef, additional, Gaspar, Héléna A., additional, Gill, Michael, additional, Goes, Fernando S., additional, Gordon, Scott D., additional, Grove, Jakob, additional, Hall, Lynsey S., additional, Søholm Hansen, Christine, additional, Hansen, Thomas F., additional, Herms, Stefan, additional, Hickie, Ian B., additional, Hoffmann, Per, additional, Homuth, Georg, additional, Horn, Carsten, additional, Hottenga, Jouke-Jan, additional, Hougaard, David M., additional, Howard, David M., additional, Ising, Marcus, additional, Jansen, Rick, additional, Jones, Ian, additional, Jones, Lisa A., additional, Jorgenson, Eric, additional, Knowles, James A., additional, Kohane, Isaac S., additional, Kraft, Julia, additional, Kretzschmar, Warren W., additional, Kutalik, Zoltán, additional, Li, Yihan, additional, Lind, Penelope A., additional, MacIntyre, Donald J., additional, MacKinnon, Dean F., additional, Maier, Robert M., additional, Maier, Wolfgang, additional, Marchini, Jonathan, additional, Mbarek, Hamdi, additional, McGrath, Patrick, additional, McGuffin, Peter, additional, Medland, Sarah E., additional, Mehta, Divya, additional, Middeldorp, Christel M., additional, Mihailov, Evelin, additional, Milaneschi, Yuri, additional, Milani, Lili, additional, Mondimore, Francis M., additional, Montgomery, Grant W., additional, Mostafavi, Sara, additional, Mullins, Niamh, additional, Nauck, Matthias, additional, Ng, Bernard, additional, Nivard, Michel G., additional, Nyholt, Dale R., additional, O'Reilly, Paul F., additional, Oskarsson, Hogni, additional, Owen, Michael J., additional, Painter, Jodie N., additional, Bøcker Pedersen, Carsten, additional, Giørtz Pedersen, Marianne, additional, Peterson, Roseann E., additional, Peyrot, Wouter J., additional, Pistis, Giorgio, additional, Posthuma, Danielle, additional, Quiroz, Jorge A., additional, Qvist, Per, additional, Rice, John P., additional, Riley, Brien P., additional, Rivera, Margarita, additional, Saeed Mirza, Saira, additional, Schoevers, Robert, additional, Schulte, Eva C., additional, Shen, Ling, additional, Shi, Jianxin, additional, Shyn, Stanley I., additional, Sigurdsson, Engilbert, additional, Sinnamon, Grant C.B., additional, Smit, Johannes H., additional, Smith, Daniel J., additional, Stefansson, Hreinn, additional, Steinberg, Stacy, additional, Streit, Fabian, additional, Strohmaier, Jana, additional, Tansey, Katherine E., additional, Teismann, Henning, additional, Teumer, Alexander, additional, Thompson, Wesley, additional, Thomson, Pippa A., additional, Thorgeirsson, Thorgeir E., additional, Traylor, Matthew, additional, Treutlein, Jens, additional, Trubetskoy, Vassily, additional, Uitterlinden, André G., additional, Umbricht, Daniel, additional, Van der Auwera, Sandra, additional, van Hemert, Albert M., additional, Viktorin, Alexander, additional, Wang, Yunpeng, additional, Webb, Bradley T., additional, Weinsheimer, Shantel Marie, additional, Wellmann, Jürgen, additional, Willemsen, Gonneke, additional, Witt, Stephanie H., additional, Wu, Yang, additional, Xi, Hualin S., additional, Yang, Jian, additional, Zhang, Futao, additional, Arolt, Volker, additional, Baune, Bernhard T., additional, Berger, Klaus, additional, Boomsma, Dorret I., additional, Cichon, Sven, additional, Dannlowski, Udo, additional, de Geus, E.J.C., additional, DePaulo, J. Raymond, additional, Domenici, Enrico, additional, Domschke, Katharina, additional, Esko, Tõnu, additional, Grabe, Hans J., additional, Hamilton, Steven P., additional, Hayward, Caroline, additional, Heath, Andrew C., additional, Kendler, Kenneth S., additional, Kloiber, Stefan, additional, Lewis, Glyn, additional, Li, Qingqin S., additional, Lucae, Susanne, additional, Madden, Pamela A.F., additional, Magnusson, Patrik K., additional, Martin, Nicholas G., additional, Metspalu, Andres, additional, Mors, Ole, additional, Bo Mortensen, Preben, additional, Müller-Myhsok, Bertram, additional, Nordentoft, Merete, additional, Nöthen, Markus M., additional, O'Donovan, Michael C., additional, Paciga, Sara A., additional, Pedersen, Nancy L., additional, Penninx, Brenda W.J.H., additional, Perlis, Roy H., additional, Porteous, David J., additional, Potash, James B., additional, Preisig, Martin, additional, Rietschel, Marcella, additional, Schaefer, Catherine, additional, Schulze, Thomas G., additional, Smoller, Jordan W., additional, Stefansson, Kari, additional, Tiemeier, Henning, additional, Uher, Rudolf, additional, Völzke, Henry, additional, Weissman, Myrna M., additional, Werge, Thomas, additional, Lewis, Cathryn M., additional, Levinson, Douglas F., additional, Breen, Gerome, additional, Børglum, Anders D., additional, and Sullivan, Patrick F., additional

Published
2023
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49. The ABCB1 transporter gene and antidepressant response.

Author

Peters, Eric J, Reus, Victor, and Hamilton, Steven P

Abstract

P-glycoprotein, encoded by the ABCB1 gene, may modulate the brain concentration of several antidepressants. Functional genetic variation is thought to exist in this gene, and here we review several studies that have attempted to associate this variation with clinical response to antidepressant treatment.

Published
2009

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