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Background: Polygenic scores (PGSs) hold the potential to identify patients who respond favourably to specific psychiatric treatments. However, their biological interpretations remain unclear. In this study, we developed pathway-specific PGSs (PS PGS ) for lithium response and assessed their association with clinical lithium response in patients with bipolar disorder (BD). Methods: Using sets of genes involved in pathways affected by lithium, we developed nine PS PGSs and evaluated their associations with lithium response in the International Consortium on Lithium Genetics cohort (ConLi + Gen: N = 2367), validated in the combined PsyCourse (N = 105) and BipoLife (N = 102) cohorts. Lithium responsiveness was assessed using the Retrospective Assessment of the Lithium Response Phenotype Scale (ALDA scale), for categorical outcome (good vs poor response) and continuous ALDA total score. Logistic and linear regressions, adjusting for age, sex, chip type, and the first four genetic principal components, were used to test associations, after multiple testing corrections ( p <0.05). Results: Response to lithium was associated with PS PGS for acetylcholine, GABA, calcium channel signalling, mitochondria, circadian rhythm, and GSK pathways, R² ranging from 0.29% to 1.91%, with R² of 3.71% for the combined PS PGS. Associations for GABA PGS and CIR PGS were replicated. In decile-based stratified analysis, patients with the highest genetic loading (10 th decile) for acetylcholine pathway genetic variants were 3.03 times (95%CI: 1.95 - 4.69) more likely to have a good lithium response than the lowest decile (1 st decile). Conclusion: PS PGSs achieved predictive performance comparable with conventional genome-wide PGSs, with more biological interpretability and using a smaller list of genetic variants, facilitating further investigation into the interaction of variants and biological pathways underlying lithium response.
Pathway-Specific Polygenic Scores for Lithium Response for Predicting Clinical Lithium Treatment Response in Patients with Bipolar Disorder
Sharew, Nigussie T.;Clark, Scott R.;Papiol, Sergi;Heilbronner, Urs;Degenhardt, Franziska;Fullerton, Janice M.;Hou, Liping;Shekhtman, Tatyana;Adli, Mazda;Akula, Nirmala;Akiyama, Kazufumi;Ardau, Raffaella;Arias, Bárbara;Hasler, Roland;Richard-Lepouriel, Hélène;Perroud, Nader;Backlund, Lena;Bhattacharjee, Abesh Kumar;Bellivier, Frank;Benabarre, Antonio;Bengesser, Susanne;Biernacka, Joanna M.;Birner, Armin;Marie-Claire, Cynthia;Cervantes, Pablo;Chen, Hsi-Chung;Chillotti, Caterina;Cichon, Sven;Cruceanu, Cristiana;Czerski, Piotr M.;Dalkner, Nina;Del Zompo, Maria;DePaulo, J. Raymond;Étain, Bruno;Jamain, Stephane;Falkai, Peter;Forstner, Andreas J.;Frisen, Louise;Frye, Mark A.;Gard, Sébastien;Garnham, Julie S.;Goes, Fernando S.;Grigoroiu-Serbanescu, Maria;Fallgatter, Andreas J.;Stegmaier, Sophia;Ethofer, Thomas;Biere, Silvia;Petrova, Kristiyana;Schuster, Ceylan;Adorjan, Kristina;Budde, Monika;Heilbronner, Maria;Kalman, Janos L.;Kohshour, Mojtaba Oraki;Reich-Erkelenz, Daniela;Schaupp, Sabrina K.;Schulte, Eva C.;Senner, Fanny;Vogl, Thomas;Anghelescu, Ion-George;Arolt, Volker;Dannlowski, Udo;Dietrich, Detlef E.;Figge, Christian;Jäger, Markus;Lang, Fabian U.;Juckel, Georg;Konrad, Carsten;Reimer, Jens;Schmauß, Max;Schmitt, Andrea;Spitzer, Carsten;von Hagen, Martin;Wiltfang, Jens;Zimmermann, Jörg;Andlauer, Till F. M.;Fischer, Andre;Bermpohl, Felix;Ritter, Philipp;Matura, Silke;Gryaznova, Anna;Falkenberg, Irina;Yildiz, Cüneyt;Kircher, Tilo;Schmidt, Julia;Koch, Marius;Gade, Kathrin;Trost, Sarah;Haussleiter, Ida S.;Lambert, Martin;Rohenkohl, Anja C.;Kraft, Vivien;Grof, Paul;Hashimoto, Ryota;Hauser, Joanna;Herms, Stefan;Hoffmann, Per;Jiménez, Esther;Kahn, Jean-Pierre;Kassem, Layla;Kuo, Po-Hsiu;Kato, Tadafumi;Kelsoe, John;Kittel-Schneider, Sarah;Ferensztajn-Rochowiak, Ewa;König, Barbara;Kusumi, Ichiro;Laje, Gonzalo;Landén, Mikael;Lavebratt, Catharina;Leboyer, Marion;Leckband, Susan G.;Tortorella, Alfonso;Manchia, Mirko;Martinsson, Lina;McCarthy, Michael J.;McElroy, Susan;Colom, Francesc;Millischer, Vincent;Mitjans, Marina;Mondimore, Francis M.;Monteleone, Palmiero;Nievergelt, Caroline M.;Nöthen, Markus M.;Novák, Tomas;O'Donovan, Claire;Ozaki, Norio;Pfennig, Andrea;Pisanu, Claudia;Potash, James B.;Reif, Andreas;Reininghaus, Eva;Rouleau, Guy A.;Rybakowski, Janusz K.;Schalling, Martin;Schofield, Peter R.;Schweizer, Barbara W.;Severino, Giovanni;Shilling, Paul D.;Shimoda, Katzutaka;Simhandl, Christian;Slaney, Claire M.;Squassina, Alessio;Stamm, Thomas;Stopkova, Pavla;Maj, Mario;Turecki, Gustavo;Vieta, Eduard;Veeh, Julia;Viswanath, Biju;Witt, Stephanie H.;Wright, Adam;Zandi, Peter P.;Mitchell, Philip B.;Bauer, Michael;Alda, Martin;Rietschel, Marcella;McMahon, Francis J.;Schulze, Thomas G.;Baune, Bernhard T.;Schubert, Klaus Oliver;Amare, Azmeraw T.
2025
Abstract
Background: Polygenic scores (PGSs) hold the potential to identify patients who respond favourably to specific psychiatric treatments. However, their biological interpretations remain unclear. In this study, we developed pathway-specific PGSs (PS PGS ) for lithium response and assessed their association with clinical lithium response in patients with bipolar disorder (BD). Methods: Using sets of genes involved in pathways affected by lithium, we developed nine PS PGSs and evaluated their associations with lithium response in the International Consortium on Lithium Genetics cohort (ConLi + Gen: N = 2367), validated in the combined PsyCourse (N = 105) and BipoLife (N = 102) cohorts. Lithium responsiveness was assessed using the Retrospective Assessment of the Lithium Response Phenotype Scale (ALDA scale), for categorical outcome (good vs poor response) and continuous ALDA total score. Logistic and linear regressions, adjusting for age, sex, chip type, and the first four genetic principal components, were used to test associations, after multiple testing corrections ( p <0.05). Results: Response to lithium was associated with PS PGS for acetylcholine, GABA, calcium channel signalling, mitochondria, circadian rhythm, and GSK pathways, R² ranging from 0.29% to 1.91%, with R² of 3.71% for the combined PS PGS. Associations for GABA PGS and CIR PGS were replicated. In decile-based stratified analysis, patients with the highest genetic loading (10 th decile) for acetylcholine pathway genetic variants were 3.03 times (95%CI: 1.95 - 4.69) more likely to have a good lithium response than the lowest decile (1 st decile). Conclusion: PS PGSs achieved predictive performance comparable with conventional genome-wide PGSs, with more biological interpretability and using a smaller list of genetic variants, facilitating further investigation into the interaction of variants and biological pathways underlying lithium response.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1614074
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Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
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