Pharmacogenomics of antiepileptic drug mood stabilizer treatment response in bipolar disorder: A MoStGen Consortium study.
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Ho Ada Man-Choi, Coombes Brandon J, Batzler Anthony, Pazdernik Vanessa K, Pendegraft Richard S, Skime Michelle, Bendjemaa Narjes, Carpiniello Bernardo, Contu Martina, Dalkner Nina, Fellendorf Frederike T, Fico Giovanna, Fullerton Claudio D, Gardea-Resendez Manuel, Gonzalez-Garza Sarai, Jaafari Nematollah, Jiménez Esther, Kebir Oussama, Legrand Adrien, Luna-Garza Sofia, Meloni Anna, Millet Bruno, Mouaffak Fayçal, Nunes Abraham, O'Donovan Claire, Paribello Pasquale, Pinna Marco, Pisanu Claudia, Pomarol-Clotet Edith, Romo-Nava Francisco, Sánchez Raúl F, Scott Katie, Squassina Alessio, Vilella Elisabet, Serretti Alessandro, Prieto Miguel L, Reininghaus Eva Z, Bengesser Susanne A, Cuellar-Barboza Alfredo B, Krebs Marie-Odile, Chaumette Boris, Vieta Eduard, Manchia Mirko, McElroy Susan L, Alda Martin, Frye Mark A, Biernacka Joanna M
Аннотация
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.