TY - JOUR
T1 - Pharmacogenomics of antiepileptic drug mood stabilizer treatment response in bipolar disorder
T2 - A MoStGen Consortium study
AU - Ho, Ada Man Choi
AU - Coombes, Brandon J.
AU - Batzler, Anthony
AU - Pazdernik, Vanessa K.
AU - Pendegraft, Richard S.
AU - Skime, Michelle
AU - Bendjemaa, Narjes
AU - Carpiniello, Bernardo
AU - Contu, Martina
AU - Dalkner, Nina
AU - Fellendorf, Frederike T.
AU - Fico, Giovanna
AU - Fullerton, Claudio D.
AU - Gardea-Resendez, Manuel
AU - Gonzalez-Garza, Sarai
AU - Jaafari, Nematollah
AU - Jiménez, Esther
AU - Kebir, Oussama
AU - Legrand, Adrien
AU - Luna-Garza, Sofia
AU - Meloni, Anna
AU - Millet, Bruno
AU - Mouaffak, Fayçal
AU - Nunes, Abraham
AU - O’Donovan, Claire
AU - Paribello, Pasquale
AU - Pinna, Marco
AU - Pisanu, Claudia
AU - Pomarol-Clotet, Edith
AU - Romo-Nava, Francisco
AU - Sánchez, Raúl F.
AU - Scott, Katie
AU - Squassina, Alessio
AU - Vilella, Elisabet
AU - Serretti, Alessandro
AU - Prieto, Miguel L.
AU - Reininghaus, Eva Z.
AU - Bengesser, Susanne A.
AU - Cuellar-Barboza, Alfredo B.
AU - Krebs, Marie Odile
AU - Chaumette, Boris
AU - Vieta, Eduard
AU - Manchia, Mirko
AU - McElroy, Susan L.
AU - Alda, Martin
AU - Frye, Mark A.
AU - Biernacka, Joanna M.
N1 - Publisher Copyright:
© The Author(s) 2026.
PY - 2026
Y1 - 2026
N2 - Identifying biological and clinical factors associated with response to mood-stabilizing medications is critical for improving bipolar disorder (BD) treatment. The Mood Stabilizer Genomics (MoStGen) Consortium was established to investigate pharmacogenomic and clinical predictors of response to treatment of BD with antiepileptic drug mood stabilizers (AMS). Here we present the first pharmacogenomic analyses of AMS treatment outcomes based on MoStGen Consortium data, including 917 individuals across contributing sites. We performed genome-wide association analyses in subcohorts followed by meta-analyses, with AMS treatment response measured quantitatively using the Alda scale. Medication-stratified analyses were performed for valproic acid (VPA) and lamotrigine (LTG) treatment response. Additionally, polygenic score (PGS) analyses were used to evaluate the overall genetic contribution to AMS response across cohorts and to test whether genetic liability for various neuropsychiatric illnesses impacts AMS response. We detected genome-wide significant associations with LTG treatment response for SNPs in the gene ROBO2 (top SNP: rs985123, p = 1.9E-10) and for POLR1E at the gene-level (p = 2.53E-06). No significant associations were found for overall AMS or VPA treatment response. Leave-one-out PGS analyses provided significant evidence for a polygenic signal for AMS treatment response. Furthermore, the epilepsy PGS was nominally significantly associated with AMS response (p = 0.024), suggesting higher genetic liability to epilepsy predicts a better response to treatment with AMS. These findings provide insights into the genetic contribution to AMS treatment outcomes, and in particular LTG response, and may contribute to the development of more precise treatments for BD.
AB - Identifying biological and clinical factors associated with response to mood-stabilizing medications is critical for improving bipolar disorder (BD) treatment. The Mood Stabilizer Genomics (MoStGen) Consortium was established to investigate pharmacogenomic and clinical predictors of response to treatment of BD with antiepileptic drug mood stabilizers (AMS). Here we present the first pharmacogenomic analyses of AMS treatment outcomes based on MoStGen Consortium data, including 917 individuals across contributing sites. We performed genome-wide association analyses in subcohorts followed by meta-analyses, with AMS treatment response measured quantitatively using the Alda scale. Medication-stratified analyses were performed for valproic acid (VPA) and lamotrigine (LTG) treatment response. Additionally, polygenic score (PGS) analyses were used to evaluate the overall genetic contribution to AMS response across cohorts and to test whether genetic liability for various neuropsychiatric illnesses impacts AMS response. We detected genome-wide significant associations with LTG treatment response for SNPs in the gene ROBO2 (top SNP: rs985123, p = 1.9E-10) and for POLR1E at the gene-level (p = 2.53E-06). No significant associations were found for overall AMS or VPA treatment response. Leave-one-out PGS analyses provided significant evidence for a polygenic signal for AMS treatment response. Furthermore, the epilepsy PGS was nominally significantly associated with AMS response (p = 0.024), suggesting higher genetic liability to epilepsy predicts a better response to treatment with AMS. These findings provide insights into the genetic contribution to AMS treatment outcomes, and in particular LTG response, and may contribute to the development of more precise treatments for BD.
UR - https://www.scopus.com/pages/publications/105030554643
U2 - 10.1038/s41380-026-03478-7
DO - 10.1038/s41380-026-03478-7
M3 - Article
AN - SCOPUS:105030554643
SN - 1359-4184
JO - Molecular Psychiatry
JF - Molecular Psychiatry
ER -