Mood stabilizer treatment is central to the pharmacological management of patients with bipolar disorder. However, response to such agents is highly variable between individuals often resulting in a lengthy trial and error process of medication optimization that can last years. There is a great need for a better predictor of response which would guide physicians to the optimum medication in a more efficient fashion. Genetic differences likely explain a substantial portion of this variability. The goal of this project is to identify genetic variants that are associated with response to mood stabilizer medications that might ultimately be useful as a predictive test. Studies to date by our group have implicated two genes, NTRK2 and PDE11A as predicting response to lithium. In this project, we propose a two pronged approach: genes will first be sought in an exploratory fashion in a larger retrospective sample and then tested for replication in a smaller prospective sample. Larger samples are more easily obtainable in a retrospective study, however, prospective designs though more difficult, provide better and more quantitative data. Our 11 site consortium has recently completed collection of over 4,500 bipolar subjects for a large genetic study. 2,000 retrospective subjects will be collected from both recontact of these previous cases and recruitment of new retrospective cases. The prospective sample of 960 subjects will be collected through an eight site multicenter trial. Patients will be recruited, screened and stabilized first on lithium monotherapy over a 3 month period. After one month observation, they will enter the maintenance phase and followed for 2 years. The primary outcome measure will be time to relapse. Patients who fail lithium will be crossed over to valproic acid, those failing both drugs will enter the treatment as usual arm. Genomewide association will be performed on the retrospective sample and positive SNPs replicated in the prospective sample. Secondary analyses will include genomewide association ofthe prospective sample alone and in meta-analysis with the retrospective sample. These analyses will be guided in part by studies of lithium's mechanism of action in neuronal cells derived from induced pluripotent stem cells in turn derived from skin fibroblasts from lithium responders and non-responders.

Public Health Relevance

This multi-site collaborative project aims to identify genetic variants in individuals with bipolar disorder that predict response to lithium. We will do this with a combination of retrospective assessment of lithium response in 1600 individuals with BP disorder and analysis of genotype data, as well as a prospective study of 1000 BP individuals who begin an open trial with lithium. Our hypothesis is that genetic variants at several loci predict treatment outcomes with lithium.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZRG1-GGG-M (52))
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Senthil, Geetha
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University of California San Diego
Schools of Medicine
La Jolla
United States
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van den Hurk, Mark; Erwin, Jennifer A; Yeo, Gene W et al. (2018) Patch-Seq Protocol to Analyze the Electrophysiology, Morphology and Transcriptome of Whole Single Neurons Derived From Human Pluripotent Stem Cells. Front Mol Neurosci 11:261
Miller, Nathaniel D; Kelsoe, John R (2017) Unraveling the biology of bipolar disorder using induced pluripotent stem-derived neurons. Bipolar Disord 19:544-551
Oedegaard, Ketil J; Alda, Martin; Anand, Anit et al. (2016) The Pharmacogenomics of Bipolar Disorder study (PGBD): identification of genes for lithium response in a prospective sample. BMC Psychiatry 16:129
Gonçalves, J Tiago; Bloyd, Cooper W; Shtrahman, Matthew et al. (2016) In vivo imaging of dendritic pruning in dentate granule cells. Nat Neurosci 19:788-91
Tang, Xin; Kim, Julie; Zhou, Li et al. (2016) KCC2 rescues functional deficits in human neurons derived from patients with Rett syndrome. Proc Natl Acad Sci U S A 113:751-6
McCarthy, Michael J; Le Roux, Melissa J; Wei, Heather et al. (2016) Calcium channel genes associated with bipolar disorder modulate lithium's amplification of circadian rhythms. Neuropharmacology 101:439-48
Mertens, Jerome; Wang, Qiu-Wen; Kim, Yongsung et al. (2015) Differential responses to lithium in hyperexcitable neurons from patients with bipolar disorder. Nature 527:95-9
Nievergelt, Caroline M; Maihofer, Adam X; Mustapic, Maja et al. (2015) Genomic predictors of combat stress vulnerability and resilience in U.S. Marines: A genome-wide association study across multiple ancestries implicates PRTFDC1 as a potential PTSD gene. Psychoneuroendocrinology 51:459-71
Jacobsen, Kaya K; Nievergelt, Caroline M; Zayats, Tetyana et al. (2015) Genome wide association study identifies variants in NBEA associated with migraine in bipolar disorder. J Affect Disord 172:453-61
McCarthy, Michael J; Liang, Sherri; Spadoni, Andrea D et al. (2014) Whole brain expression of bipolar disorder associated genes: structural and genetic analyses. PLoS One 9:e100204

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