Using multi-trait polygenic scores to predict lithium responsiveness in patients with bipolar disorder.
The British journal of psychiatry : the journal of mental science
Authors:
Nigussie T Sharew, Scott R Clark, Simon Hartmann, Sergi Papiol, Urs Heilbronner, Franziska Degenhardt, Janice M Fullerton, Liping Hou, Tatyana Shekhtman, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Fasil Tekola-Ayele, Carla Gallo, Roland Hasler, Hélène Richard-Lepouriel, Nader Perroud, Lena Backlund, Abesh K Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M Biernacka, Armin Birner, Cynthia Marie-Claire, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceana, Piotr M Czerski, Nina Dalkner, Maria Del Zompo, J Raymond DePaulo, Bruno Étain, Stéphane Jamain, Peter Falkai, Andreas J Forstner, Louise Frisen, Mark A Frye, Sebastien Gard, Julie S Garnham, Fernando S Goes, Maria Grigoroiu-Serbanescu, Andreas J Fallgatter, Sophia Stegmaier, Thomas Ethofer, Silvia Biere, Kristiyana Petrova, Ceylan Schuster, Kristina Adorjan, Monika Budde, Maria Heilbronner, Janos L Kalman, Mojtaba O Kohshour, Daniela Reich-Erkelenz, Sabrina K Schaupp, Eva C Schulte, Fanny Senner, Thomas Vogl, Ion-George Anghelescu, Volker Arolt, Udo Dannlowski, Detlef E Dietrich, Christian Figge, Markus Jäger, Fabian U Lang, Georg Juckel, Carsten Konrad, Jens Reimer, Max Schmauß, Andrea Schmitt, Carsten Spitzer, Martin Von Hagen, Jens Wiltfang, Jörg Zimmermann, Till F M Andlauer, Andre Fischer, Felix Bermpohl, Philipp Ritter, Silke Matura, Anna Gryaznova, Irina Falkenberg, Cüneyt Yildiz, Tilo Kircher, Julia Schmidt, Marius Koch, Kathrin Gade, Sarah Trost, Ida S Haussleiter, Martin Lambert, Anja C Rohenkohl, Vivien Kraft, Paul Grof, Ryota Hashimoto, Joanna Hauser, Stefan Herms, Per Hoffman, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Ewa Ferensztajn-Rochowiak, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G Leckband, Alfonso Tortorella, Mirko Manchia, Lina Martinsson, Michael J McCarthy, Susan L McElroy, Francesc Colom, Vincent Millischer, Marina Mitjans, Francis M Mondimore, Palmiero Monteleone, Caroline M Nievergelt, Markus M Nöthen, Tomas Novak, Claire O'Donovan, Norio Ozaki, Andrea Pfennig, Claudia Pisanu, James B Potash, Andrea Reif, Eva Reininghaus, Guy A Rouleau, Janus K Rybakowski, Martin Schalling, Peter R Schofield, Barbara W Schweizer, Giovanni Severino, Paul D Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Mario Maj, Gustavo Turecki, Eduard Vieta, Julia Veeh, Biju Viswanath, Stephanie H Witt, Adam Wright, Peter P Zandi, Philip B Mitchell, Michael Bauer, Martin Alda, Marcella Rietschel, Francis J McMahon, Thomas G Schulze, Bernhard T Baune, K Oliver Schubert, Azmeraw T Amare
BACKGROUND: The predictive power of polygenic scores (PGSs) for lithium treatment response in bipolar disorder remains limited.
AIMS: To enhance the prediction of lithium responsiveness by developing a multi-trait PGS (mt-PGS) combining genetic information from multiple phenotypes implicated in lithium response and/or bipolar disorder aetiology.
METHOD: We analysed data collected from bipolar disorder patients who had received lithium treatment for at least 6 months and participated in the International Consortium on Lithium Genetics study ( = 2367). The Alda scale was used to assess lithium responsiveness, and treatment outcome was defined as continuous total Alda score (0-10) and categorical outcome (favourable ≥7 versus unfavourable response). PGSs were calculated for 60 phenotypes grouped into 5 clinical-biological clusters: psychiatric and behavioural (#23 phenotypes), cardiometabolic (#17), autoimmune/inflammatory (#5), neurocognitive (#8) and renal function (#7). We applied cross-validated machine learning regression approaches in both outcomes within each cluster, with the selected features from each cluster subsequently combined to construct the final mt-PGS models. Model performance was assessed using explained variance () for the continuous outcome, and both McFadden's pseudo- and standard classification model parameters for the categorical outcome.
RESULTS: mt-PGS explained between 5.70% (continuous outcome) and 9.11% (categorical outcome) of the interindividual variability in lithium responsiveness. Classification accuracy (area under the curve) for the categorical outcome was 68.24% (95% CI: 64.98-71.66), with a Brier score of 0.257. Of the 5 clusters, the PGSs for psychiatric and behavioural phenotypes were most strongly associated with lithium responsiveness, accounting for 3.67-6.52% of its variability.
CONCLUSIONS: By integrating PGSs for multiple relevant phenotypes, predictive accuracy for lithium response improved substantially compared with single-trait methods. Future research incorporating larger, more diverse populations and combining genetic scores with clinical data holds promise for further enhancing prediction and advancing clinical implementation.