Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium’s possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10−12, R2 = 1.9%) and continuous (P = 6.4 × 10−9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10−4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
Research in developmental disabilities Amsterdam [u.a.] : Elsevier Science, 1987 Volume 112 (2021), Artikel 103931, insgesamt ca. 2 Seiten Online-Ressource
von Heiner Götz Rudolf Claessen ; Maria Narres ; Tatjana Kvitkina ; Adrian Wilk ; Heiko Friedel ; Christian Günster ; Falk Hoffmann ; Michael Koch ; Karin Jandeleit-Dahm ; Andrea Icks
von Daniel Thomas-Rüddel ; Peter Hoffmann ; Daniel Schwarzkopf ; Christian Scheer ; Friedhelm Bach ; Marcus Komann ; Herwig Gerlach ; Manfred Weiss ; Matthias Lindner ; Hendrik Rüddel ; Philipp Simon ; Sven-Olaf Kuhn ; Reinhard Wetzker ; Michael Bauer ; Konrad Reinhart ; Frank Bloos ; Anja Diers ; Florian Jelschen ; Andreas Weyland
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