Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.

Central Institute of Mental Health Medical Faculty Mannheim Heidelberg University Mannheim Baden Württemberg Germany

Centre for Human Genetics University of Marburg Marburg Germany

Centro Lucio Bini Cagliari e Roma Cagliari Italy

Charité Universitätsmedizin Berlin Berlin Germany

Charité University Medical Center Campus Charité Mitte Institute for Social Medicine Epidemiology and Health Economics Berlin Germany

Department of Adult Psychiatry Poznan University of Medical Sciences Poznan Poland

Department of Biomedical Sciences Section of Neuroscience and Clinical Pharmacology University of Cagliari Cagliari Italy

Department of Biomedicine University of Basel Basel Switzerland

Department of Medical Sciences and Public Health Section of Psychiatry University of Cagliari Cagliari Italy

Department of Mental Health Poznan University of Medical Sciences Poznan Poland

Department of Pharmacology Dalhousie University Halifax Nova Scotia Canada

Department of Psychiatric Nursing Poznan University of Medical Sciences Poznan Poland

Department of Psychiatry Charles University Prague Czech Republic

Department of Psychiatry Dalhousie University Halifax NS Canada

Department of Psychiatry McGill University Health Centre Montreal Québec Canada

Department of Psychiatry University of Toronto Toronto Ontario Canada

Department of Psychiatry University of Wurzburg Wurzburg Germany

Faculty of Computer Science Dalhousie University Halifax NS Canada

Harvard Medical School and McLean Hospital Boston MA USA

Institute of Human Genetics University of Bonn School of Medicine and University Hospital Bonn Bonn Germany

Institute of Psychiatric Phenomics and Genomics Munich Germany

Montreal Neurological Institute McGill University Montreal QC Canada

Mood Disorders Center of Ottawa Ottawa Ontario Canada

National Institute of Mental Health Bethesda MD USA

Unit of Clinical Pharmacology and San Giovanni di Dio Hospital University Hospital of Cagliari Cagliari Italy

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