Prediction of lithium response using genomic data

Prediction of lithium response using genomic data

Abstract Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with...

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Auteurs principaux: William Stone, Abraham Nunes, Kazufumi Akiyama, Nirmala Akula, Raffaella Ardau, Jean-Michel Aubry, Lena Backlund, Michael Bauer, Frank Bellivier, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Cristiana Cruceanu, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, Andreas J. Forstner, Mark Frye, Janice M. Fullerton, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Liping Hou, Esther Jiménez, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Po-Hsiu Kuo, Ichiro Kusumi, Catharina Lavebratt, Mirko Manchia, Lina Martinsson, Manuel Mattheisen, Francis J. McMahon, Vincent Millischer, Philip B. Mitchell, Markus M. Nöthen, Claire O’Donovan, Norio Ozaki, Claudia Pisanu, Andreas Reif, Marcella Rietschel, Guy Rouleau, Janusz Rybakowski, Martin Schalling, Peter R. Schofield, Thomas G. Schulze, Giovanni Severino, Alessio Squassina, Julia Veeh, Eduard Vieta, Thomas Trappenberg, Martin Alda
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/3122c8062c9b4f39a9a4aa0e6220ae8c
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