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Abstract:
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=9.8x10(-) (12), R-2=1.9%) and continuous (P=6.4x10(-) (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=3.9x10(-) (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.
