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Background: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II. [ABSTRACT FROM AUTHOR]

Background: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.Aims: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.Method: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.Results: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.Conclusions: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment. [ABSTRACT FROM AUTHOR]

Importance: Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ).Objectives: To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association.Design, Setting, and Participants: A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013. Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017.Main Outcomes and Measures: Treatment response to lithium was defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained.Results: Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 × 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95% CI, 1.42-8.41) at the first decile to 2.03 (95% CI, 0.86-4.81) at the ninth decile, compared with the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA antigen complex and inflammatory cytokines.Conclusions and Relevance: This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium. [ABSTRACT FROM AUTHOR]

Ketamine, depression, antidepressants, suicide, corrigendum, Esketamine Keywords: Esketamine; ketamine; depression; antidepressants; suicide; corrigendum EN Esketamine ketamine depression antidepressants suicide corrigendum 494 494 1 07/20/22 20220801 NES 220801 An incorrect author affiliation was published in the above article. [Extracted from the article]

Because of the important role of dopamine in neurotransmission, it would be useful to be able to image brain dopamine receptor-mediated signal transduction in animals and humans. Administering the D1–D2 receptor agonist apomorphine may allow us to do this, as the D2-like receptor is reported to be coupled to cytosolic phospholipase A2 activation and arachidonic acid (AA) release from membrane phospholipid. Unanesthetized adult rats were given intraperitoneally apomorphine (0.5 mg/kg) or saline, with or without pretreatment with 6 mg/kg intravenous raclopride, a D2/D3 receptor antagonist. [1–14C]AA was injected intravenously, then AA incorporation coefficients k*—brain radioactivity divided by integrated plasma radioactivity—markers of AA signaling, were measured using quantitative autoradiography in 62 brain regions. Apomorphine significantly elevated k* in 26 brain regions, including the frontal cortex, motor and somatosensory cortex, caudate-putamen, thalamic nuclei, and nucleus accumbens. Raclopride alone did not change baseline values of k*, but raclopride pretreatment prevented the apomorphine-induced increments in k*. A mixed D1–D2 receptor agonist, apomorphine, increased the AA signal by activating only D2-like receptors in brain circuits containing regions with high D2-like receptor densities. Thus, apomorphine might be used with positron emission tomography to image brain D2-like receptor-mediated AA signaling in humans in health and disease. [ABSTRACT FROM AUTHOR]

Focuses on a study which measured the signaling in response to dopamine D1 and D2 receptor agonists given acutely to unanesthetized rats using in vivo fatty acid method. Review of literature on dopamine receptors; Effects of drugs on AA incorporation coefficients for arachidonic acid; Association of D2 with activation of phospolipase A2 and the release of arachidonic acid.