| Contributors: |
Amare, A. T.; Thalamuthu, A.; Schubert, K. O.; Fullerton, J. M.; Ahmed, M.; Hartmann, S.; Papiol, S.; Heilbronner, U.; Degenhardt, F.; Tekola-Ayele, F.; Hou, L.; Hsu, Y. -H.; Shekhtman, T.; Adli, M.; Akula, N.; Akiyama, K.; Ardau, R.; Arias, B.; Aubry, J. -M.; Hasler, R.; Richard-Lepouriel, H.; Perroud, N.; Backlund, L.; Bhattacharjee, A. K.; Bellivier, F.; Benabarre, A.; Bengesser, S.; Biernacka, J. M.; Birner, A.; Marie-Claire, C.; Cervantes, P.; Chen, H. -C.; Chillotti, C.; Cichon, S.; Cruceanu, C.; Czerski, P. M.; Dalkner, N.; Del Zompo, M.; Depaulo, J. R.; Etain, B.; Jamain, S.; Falkai, P.; Forstner, A. J.; Frisen, L.; Frye, M. A.; Gard, S.; Garnham, J. S.; Goes, F. S.; Grigoroiu-Serbanescu, M.; Fallgatter, A. J.; Stegmaier, S.; Ethofer, T.; Biere, S.; Petrova, K.; Schuster, C.; Adorjan, K.; Budde, M.; Heilbronner, M.; Kalman, J. L.; Kohshour, M. O.; Reich-Erkelenz, D.; Schaupp, S. K.; Schulte, E. C.; Senner, F.; Vogl, T.; Anghelescu, I. -G.; Arolt, V.; Dannlowski, U.; Dietrich, D.; Figge, C.; Jager, M.; Lang, F. U.; Juckel, G.; Konrad, C.; Reimer, J.; Schmauss, M.; Schmitt, A.; Spitzer, C.; von Hagen, M.; Wiltfang, J.; Zimmermann, J.; Andlauer, T. F. M.; Fischer, A.; Bermpohl, F.; Ritter, P.; Matura, S.; Gryaznova, A.; Falkenberg, I.; Yildiz, C.; Kircher, T.; Schmidt, J.; Koch, M.; Gade, K.; Trost, S.; Haussleiter, I. S.; Lambert, M.; Rohenkohl, A. C.; Kraft, V.; Grof, P.; Hashimoto, R. |
| Description: |
Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental healthdisorder 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 ... |