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Zusammenfassung:
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 x 10(-)(12), R-2 = 1.9%) and continuous (P = 6.4 x 10(-)(9), R-2 = 2.6%) outcomes. Compared to bipolar patients in the 1(st) decile of the risk distribution, individuals in the 10(th) 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 x 10(-)(4), R-2 = 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.
