Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder

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.;Hauser J.;Herms S.;Hoffmann P.;Jimenez E.;Kahn J. -P.;Kassem L.;Kuo P. -H.;Kato T.;Kelsoe J.;Kittel-Schneider S.;Ferensztajn-Rochowiak E.;Konig B.;Kusumi I.;Laje G.;Landen M.;Lavebratt C.;Leboyer M.;Leckband S. G.;Tortorella A.;Manchia M.

Writing – Original Draft Preparation

;Martinsson L.;McCarthy M. J.;McElroy S.;Colom F.;Millischer V.;Mitjans M.;Mondimore F. M.;Monteleone P.;Nievergelt C. M.;Nothen M. M.;Novak T.;O'Donovan C.;Ozaki N.;Pfennig A.;Pisanu C.;Potash J. B.;Reif A.;Reininghaus E.;Rouleau G. A.;Rybakowski J. K.;Schalling M.;Schofield P. R.;Schweizer B. W.;Severino G.;Shilling P. D.;Shimoda K.;Simhandl C.;Slaney C. M.;Squassina A.;Stamm T.;Stopkova P.;Maj M.;Turecki G.;Vieta E.;Veeh J.;Witt S. H.;Wright A.;Zandi P. P.;Mitchell P. B.;Bauer M.;Alda M.;Rietschel M.;McMahon F. J.;Schulze T. G.;Clark S. R.;Baune B. T.

2023-01-01

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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 = 9.8 × 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.