Effects of Lithium Monotherapy for Bipolar Disorder on Gene Expression in Peripheral Lymphocytes

Lithium, Inflammation and Neuroinflammation with Emphasis on Bipolar Disorder-A Narrative Review

This narrative review examines lithium's effects on immune function, inflammation and cell survival, particularly in bipolar disorder (BD) in in vitro studies, animal models and clinical studies. In vitro studies show that high lithium concentrations (5 mM, beyond the therapeutic window) reduce interleukin (IL)-1β production in monocytes and enhance T-lymphocyte resistance, suggesting a protective role against cell death. Lithium modulates oxidative stress in lipopolysaccharide (LPS)-activated macrophages by inhibiting nuclear factor (NF)-ƙB activity and reducing nitric oxide production. At therapeutically relevant levels, lithium increased both pro-inflammatory [interferon (INF)-γ, IL-8 and tumor necrosis factor (TNF)-α)] and anti-inflammatory (IL-10) cytokines on whole blood supernatant culture in healthy volunteers, influencing the balance of pro- and anti-inflammatory responses. Animal models reveal lithium's potential to alleviate inflammatory diseases by reducing pro-inflammatory cytokines and enhancing anti-inflammatory responses. It also induces selective macrophage death in atherosclerotic plaques without harming other cells. In primary rat cerebellum cultures (ex vivo), lithium prevents neuronal loss and inhibits astroglial growth, impacting astrocytes and microglia. Clinical studies show that lithium alters cytokine profiles and reduces neuroinflammatory markers in BD patients. Chronic treatment decreases IL-2, IL-6, IL-10 and IFN-γ secretion from peripheral blood leukocytes. Lithium response correlates with TNF-α levels, with poor responders showing higher TNF-α. Overall, these findings elucidate lithium's diverse mechanisms in modulating immune responses, reducing inflammation and promoting cell survival, with significant implications for managing BD and other inflammation-related conditions. Yet, to better understand the drug's impact in BD and other inflammatory/neuroinflammatory conditions, further research is warranted to appreciate lithium's therapeutic potential and its role in immune regulation.

Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Common changes in rat cortical gene expression after valproate or lithium treatment particularly affect pre- and post-synaptic pathways that regulate four neurotransmitters systems

OBJECTIVES

We have postulated that common changes in gene expression after treatment with different therapeutic classes of psychotropic drugs contribute to their common therapeutic mechanisms of action.

METHODS

To test this hypothesis, we measured levels of cortical coding and non-coding RNA using GeneChip® Rat Exon 1.0 ST Array after treatment with vehicle (chow only), chow containing 1.8 g lithium carbonate/kg (n = 10) or chow containing 12 g sodium valproate/kg (n = 10) for 28 days. Differences in levels of RNA were identified using JMP Genomics 13 and the Panther Gene Ontology Classification System was used to identify potential consequences of RNA.

RESULTS

Compared to vehicle treatment, levels of cortical RNA for 543 and 583 coding and non-coding RNAs were different after treatment with valproate and lithium, respectively. Moreover, levels of 323 coding and non-coding RNAs were altered in a highly correlated way by treatment with valproate and lithium, changes that would impact on cholinergic, glutamatergic, serotonergic and dopaminergic neurotransmission as well as on voltage gated ion channels.

CONCLUSIONS

Our study suggests that treating with mood stabilisers cause many common changes in levels of RNA which will impact on CNS function, particularly affecting post-synaptic muscarinic receptor functioning and the release of multiple neurotransmitters.

The immunomodulatory effect of lithium as a mechanism of action in bipolar disorder

Bipolar disorder (BD) is a chronic mental disorder characterized by recurrent episodes of mania and depression alternating with periods of euthymia. Although environmental and genetic factors have been described, their pathogenesis is not fully understood. Much evidence suggests a role for inflammatory mediators and immune dysregulation in the development of BD. The first-line treatment in BD are mood-stabilizing agents, one of which is lithium (Li) salts. The Li mechanism of action is not fully understood, but it has been proposed that its robust immunomodulatory properties might be one of the mechanisms responsible for its effectiveness. In this article, the authors present the current knowledge about immune system changes accompanying BD, as well as the immunomodulatory effect of lithium. The results of studies describing connections between immune system changes and lithium effectiveness are often incoherent. Further research is needed to understand the connection between immune system modulation and the therapeutic action of lithium in BD.

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers

Bipolar disorder (BD) is a severe chronic disorder that represents one of the main causes of disability among young people. To date, no reliable biomarkers are available to inform the diagnosis of BD or clinical response to pharmacological treatment. Studies focused on coding and noncoding transcripts may provide information complementary to genome-wide association studies, allowing to correlate the dynamic evolution of different types of RNAs based on specific cell types and developmental stage with disease development or clinical course. In this narrative review, we summarize findings from human studies that evaluated the potential utility of messenger RNAs and noncoding transcripts, such as microRNAs, circular RNAs and long noncoding RNAs, as peripheral markers of BD and/or response to lithium and other mood stabilizers. The majority of available studies investigated specific targets or pathways, with large heterogeneity in the included type of cells or biofluids. However, a growing number of studies are using hypothesis-free designs, with some studies also integrating data on coding and noncoding RNAs measured in the same participants. Finally, studies conducted in neurons derived from induced-pluripotent stem cells or in brain organoids provide promising preliminary findings supporting the power and utility of these cellular models to investigate the molecular determinants of BD and clinical response.

Divergent Directionality of Immune Cell-Specific Protein Expression between Bipolar Lithium Responders and Non-Responders Revealed by Enhanced Flow Cytometry

Background and Objectives: There is no biomarker to predict lithium response. This study used CellPrint™ enhanced flow cytometry to study 28 proteins representing a spectrum of cellular pathways in monocytes and CD4⁺ lymphocytes before and after lithium treatment in patients with bipolar disorder (BD). Materials and Methods: Symptomatic patients with BD type I or II received lithium (serum level ≥ 0.6 mEq/L) for 16 weeks. Patients were assessed with standard rating scales and divided into two groups, responders (≥50% improvement from baseline) and non-responders. Twenty-eight intracellular proteins in CD4⁺ lymphocytes and monocytes were analyzed with CellPrint™, an enhanced flow cytometry procedure. Data were analyzed for differences in protein expression levels. Results: The intent-to-treat sample included 13 lithium-responders (12 blood samples before treatment and 9 after treatment) and 11 lithium-non-responders (11 blood samples before treatment and 4 after treatment). No significant differences in expression between the groups was observed prior to lithium treatment. After treatment, the majority of analytes increased expression in responders and decreased expression in non-responders. Significant increases were seen for PDEB4 and NR3C1 in responders. A significant decrease was seen for NR3C1 in non-responders. Conclusions: Lithium induced divergent directionality of protein expression depending on the whether the patient was a responder or non-responder, elucidating molecular characteristics of lithium responsiveness. A subsequent study with a larger sample size is warranted.

Multi-omic modeling of antidepressant response implicates dynamic immune and inflammatory changes in individuals who respond to treatment

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide, and is commonly treated with antidepressant drugs (AD). Although effective, many patients fail to respond to AD treatment, and accordingly identifying factors that can predict AD response would greatly improve treatment outcomes. In this study, we developed a machine learning tool to integrate multi-omic datasets (gene expression, DNA methylation, and genotyping) to identify biomarker profiles associated with AD response in a cohort of individuals with MDD.

MATERIALS AND METHODS

Individuals with MDD (N = 111) were treated for 8 weeks with antidepressants and were separated into responders and non-responders based on the Montgomery-Åsberg Depression Rating Scale (MADRS). Using peripheral blood samples, we performed RNA-sequencing, assessed DNA methylation using the Illumina EPIC array, and performed genotyping using the Illumina PsychArray. To address this rich multi-omic dataset with high dimensional features, we developed integrative Geneset-Embedded non-negative Matrix factorization (iGEM), a non-negative matrix factorization (NMF) based model, supplemented with auxiliary information regarding gene sets and gene-methylation relationships. In particular, we factorize the subjects by features (i.e., gene expression or DNA methylation) into subjects-by-factors and factors-by-features. We define the factors as the meta-phenotypes as they represent integrated composite scores of the molecular measurements for each subject.

RESULTS

Using our model, we identified a number of meta-phenotypes which were related to AD response. By integrating geneset information into the model, we were able to relate these meta-phenotypes to biological processes, including a meta-phenotype related to immune and inflammatory functions as well as other genes related to depression or AD response. The meta-phenotype identified several genes including immune interleukin 1 receptor like 1 (IL1RL1) and interleukin 5 receptor (IL5) subunit alpha (IL5RA), AKT/PIK3 pathway related phosphoinositide-3-kinase regulatory subunit 6 (PIK3R6), and sphingomyelin phosphodiesterase 3 (SMPD3), which has been identified as a target of AD treatment.

CONCLUSIONS

The derived meta-phenotypes and associated biological functions represent both biomarkers to predict response, as well as potential new treatment targets. Our method is applicable to other diseases with multi-omic data, and the software is open source and available on Github (https://github.com/li-lab-mcgill/iGEM).

Transcriptional biomarkers of response to pharmacological treatments in severe mental disorders: A systematic review

Variation in the expression level and activity of genes involved in drug disposition and action in tissues of pharmacological importance have been increasingly investigated in patients treated with psychotropic drugs. Findings are promising, but reliable predictive biomarkers of response have yet to be identified. Here we conducted a PRISMA-compliant systematic search of PubMed, Scopus and PsycInfo up to 12 September 2020 for studies investigating RNA expression levels in cells or biofluids from patients with major depressive disorder, schizophrenia or bipolar disorder characterized for response to psychotropic drugs (antidepressants, antipsychotics or mood stabilizers) or adverse effects. Among 5497 retrieved studies, 123 (63 on antidepressants, 33 on antipsychotics and 27 on mood stabilizers) met inclusion criteria. Studies were either focused on mRNAs (n = 96), microRNAs (n = 19) or long non-coding RNAs (n = 1), with only a minority investigating both mRNAs and microRNAs levels (n = 7). The most replicated results include genes playing a role in inflammation (antidepressants), neurotransmission (antidepressants and antipsychotics) or mitochondrial function (mood stabilizers). Compared to those investigating response to antidepressants, studies focused on antipsychotics or mood stabilizers more often showed lower sample size and lacked replication. Strengths and limitations of available studies are presented and discussed in light of the specific designs, methodology and clinical characterization of included patients for transcriptomic compared to DNA-based studies. Finally, future directions of transcriptomics of psychopharmacological interventions in psychiatric disorders are discussed.

Dose-dependent transcriptional effects of lithium and adverse effect burden in a psychiatric cohort

Lithium is the first-line treatment for bipolar disorder (BD), but there is a large variation in response rate and adverse effects. Although the molecular effects of lithium have been studied extensively, the specific mechanisms of action remain unclear. In particular, the molecular changes underlying lithium adverse effects are little known. Multiple linear regression analyses of lithium serum concentrations and global gene expression levels in whole blood were carried out using a large case-control sample (n = 1450). Self-reported adverse effects of lithium were assessed with the "Udvalg for Kliniske Undersøgelser" (UKU) adverse effect rating scale, and regression analysis was used to identify significant associations between lithium-related genes and six of the most common adverse effects. Serum concentrations of lithium were significantly associated with the expression levels of 52 genes (FDR < 0.01), largely replicating previous results. We found 32 up-regulated genes and 20 down-regulated genes in lithium users compared to non-users. The down-regulated gene set was enriched for several processes related to the translational machinery. Two adverse effects were significantly associated (p < 0.01) with three or more lithium-associated genes: tremor (FAM13A-AS1, FAR2, ITGAX, RWDD1, and STARD10) and xerostomia (ANKRD13A, FAR2, RPS8, and RWDD1). The adverse effect association with the largest effect was between CAMK1D expression and nausea/vomiting. These results suggest putative transcriptional mechanisms that may predict lithium adverse effects, and could thus have a large potential for informing clinical practice.

The Purinergic System as a Target for the Development of Treatments for Bipolar Disorder

The neurobiological and neurochemical mechanisms underlying the pathophysiology of bipolar disorder are complex and not yet fully understood. From circadian disruption to neuroinflammation, many pathways and signaling molecules are important contributors to bipolar disorder development, some specific to a disease subtype or a cycling episode. Pharmacological agents for bipolar disorder have shown only partial efficacy, including mood stabilizers and antipsychotics. The purinergic hypothesis for bipolar disorder emerges in this scenario as a promising target for further research and drug development, given its role in neurotransmission and neuroinflammation that results in behavioral and mood regulation. Here, we review the basic concepts of purinergic signaling in the central nervous system and its contribution to bipolar disorder pathophysiology. Allopurinol and novel P2X7 receptor antagonists are promising candidates for treating bipolar disorder. We further explore currently available pharmacotherapies and the emerging new purinergic targets for drug development in bipolar disorder.

Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect

BACKGROUND

Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.

METHODS

We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.

RESULTS

While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.

CONCLUSIONS

These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.

Does Lithium Deserve a Place in the Treatment Against COVID-19? A Preliminary Observational Study in Six Patients, Case Report

Lithium has shown the capacity to: a) inhibit the replication of several types of viruses, some of which are similar to the SARS-CoV-2 virus, b) increase the immune response by reducing lymphopenia, and c) reduce inflammation by preventing or reducing the cytokine storm. In the present study, we have treated six patients with severe COVID-19 infection with lithium carbonate. We found that lithium carbonate significantly reduced plasma reactive C-Protein levels, increased lymphocyte numbers and decreased the neutrophil-lymphocyte ratio, improving both inflammatory activity and the immune response in these patients. We propose that lithium carbonate may deserve a place in the treatment against COVID-19.

Exploring lithium's transcriptional mechanisms of action in bipolar disorder: a multi-step study

Lithium has been the first-line treatment for bipolar disorder (BD) for more than six decades. Although the molecular effects of lithium have been studied extensively and gene expression changes are generally believed to be involved, the specific mechanisms of action that mediate mood regulation are still not known. In this study, a multi-step approach was used to explore the transcriptional changes that may underlie lithium's therapeutic efficacy. First, we identified genes that are associated both with lithium exposure and with BD, and second, we performed differential expression analysis of these genes in brain tissue samples from BD patients (n = 42) and healthy controls (n = 42). To identify genes that are regulated by lithium exposure, we used high-sensitivity RNA-sequencing of corpus callosum (CC) tissue samples from lithium-treated (n = 8) and non-treated (n = 9) rats. We found that lithium exposure significantly affected 1108 genes (FDR < 0.05), 702 up-regulated and 406 down-regulated. These genes were mostly enriched for molecular functions related to signal transduction, including well-established lithium-related pathways such as mTOR and Wnt signaling. To identify genes with differential expression in BD, we performed expression quantitative trait loci (eQTL) analysis on BD-associated genetic variants from the most recent genome-wide association study (GWAS) using three different gene expression databases. We found 307 unique eQTL genes regulated by BD-associated variants, of which 12 were also significantly modulated by lithium treatment in rats. Two of these showed differential expression in the CC of BD cases: RPS23 was significantly down-regulated (p = 0.0036, fc = 0.80), while GRIN2A showed suggestive evidence of down-regulation in BD (p = 0.056, fc = 0.65). Crucially, GRIN2A was also significantly up-regulated by lithium in the rat brains (p = 2.2e-5, fc = 1.6), which suggests that modulation of GRIN2A expression may be a part of the therapeutic effect of the drug. These results indicate that the recent upsurge in research on this central component of the glutamatergic system, as a target of novel therapeutic agents for affective disorders, is warranted and should be intensified.

Integrative analysis of lithium treatment associated effects on brain structure and peripheral gene expression reveals novel molecular insights into mechanism of action

Lithium is a highly effective medication for bipolar disorder, but its mechanism of action remains unknown. In this study, brain MRI scans and blood samples for gene expression (total of 110 scans and 109 blood samples) were collected from 21 bipolar subjects before and after 2 and 8 weeks of lithium monotherapy and at the same time-points from untreated 16 healthy controls. We used linear mixed-effects models to identify brain structural features and genes with expression changed after lithium treatment, with correction for multiple testing, and correlated their concurrent changes to identify molecular pathways associated with lithium effects. There are significant increases in gray matter fraction, global cortical thickness, and the frontal and parietal cortices after 8 weeks of lithium treatment (corrected p < 0.05). Volume increases were also seen for putamen, hippocampus, thalamic nuclei, and thalamic substructures. Several genes showed significant expression changes, and 14 gene pathways were identified for the present integration analysis. Of these, nine pathways had significant correlations with structural changes (FDR < 0.05). Three neurotrophy-related pathways (GDNF family of ligands, NFAT immune-response, and p53-signaling pathway) correlated with structural changes in multiple regions. Mediation analysis showed that the sphingomyelin metabolism pathway is associated with HAM-D change (p < 0.01), and this effect is mediated via the volume of mediodorsal thalamus (p < 0.03). In summary, the integration of lithium effects on brain structural and peripheral gene expression changes revealed effects on several neurotrophic molecular pathways, which provides further insights into the mechanism of lithium action.

Genomics of Lithium Action and Response

(Reprinted with permission from Neurotherapeutics (2017) 14:582-587).

Gene expression changes related to immune processes associate with cognitive endophenotypes of schizophrenia

Schizophrenia is a heterogeneous disorder characterized by a spectrum of symptoms and many different underlying causes. Thus, instead of using the broad diagnosis, intermediate phenotypes can be used to possibly decrease the underlying complexity of the disorder. Alongside the classical symptoms of delusions and hallucinations, cognitive deficits are a core feature of schizophrenia. To increase our understanding of the biological processes related to these cognitive deficits, we performed a genome-wide gene expression analysis. A battery of 14 neuropsychological tests was administered to 844 individuals from a Finnish familial schizophrenia cohort. We grouped the applied neuropsychological tests into five factors for further analysis. Cognitive endophenotypes, whole blood mRNA, genotype, and medication use data were studied from 47 individuals. Expression level of several RNA probes were significantly associated with cognitive performance. The factor representing Verbal Working Memory was associated with altered expression levels of 11 probes, of which one probe was also associated with a specific sub-measure of this factor (WMS-R Digit span backward). While, the factor Processing speed was related to one probe, which additionally associated among 55 probes with a specific sub-measure of this factor (WAIS-R Digit symbol). Two probes were associated with the measure recognition memory performance. Enrichment analysis of these differentially expressed probes highlighted immunological processes. Our findings are in line with genome-wide genetic discoveries made in schizophrenia, suggesting that immunological processes may be of biological interest for future drug design towards schizophrenia and the cognitive dysfunctions that underlie it.

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

Lithium is the first-line treatment for bipolar affective disorder (BPAD) but two-thirds of patients respond only partially or not at all. The reasons for this high variability in lithium response are not well understood. Transcriptome-wide profiling, which tests the interface between genes and the environment, represents a viable means of exploring the molecular mechanisms underlying lithium response variability. Thus, in the present study we performed co-expression network analyses of whole-blood-derived RNA-seq data from n = 50 lithium-treated BPAD patients. Lithium response was assessed using the well-validated ALDA scale, which we used to define both a continuous and a dichotomous measure. We identified a nominally significant correlation between a co-expression module comprising 46 genes and lithium response represented as a continuous (i.e., scale ranging 0-10) phenotype (cor = -0.299, p = 0.035). Forty-three of these 46 genes had reduced mRNA expression levels in better lithium responders relative to poorer responders, and the central regulators of this module were all mitochondrially-encoded (MT-ND1, MT-ATP6, MT-CYB). Accordingly, enrichment analyses indicated that genes involved in mitochondrial functioning were heavily over-represented in this module, specifically highlighting the electron transport chain (ETC) and oxidative phosphorylation (OXPHOS) as affected processes. Disrupted ETC and OXPHOS activity have previously been implicated in the pathophysiology of BPAD. Our data adds to previous evidence suggesting that a normalisation of these processes could be central to lithium's mode of action, and could underlie a favourable therapeutic response.

Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder

This study developed potential blood-based biomarker tests for diagnosing and differentiating schizophrenia (SZ), bipolar disorder type I (BD), and normal control (NC) subjects using mRNA gene expression signatures. A total of 90 subjects (n = 30 each for the three groups of subjects) provided blood samples at two visits. The Affymetrix exon microarray was used to profile the expression of over 1.4 million probesets. We selected potential biomarker panels using the temporal stability of the probesets and also back-tested them at two different visits for each subject. The 18-gene biomarker panels, using logistic regression modeling, correctly differentiated the three groups of subjects with high accuracy across the two different clinical visits (83-88% accuracy). The results are also consistent with the actual data and the "leave-one-out" analyses, indicating that the models should be predictive when applied to independent data cohorts. Many of the SZ and BD subjects were taking antipsychotic and mood stabilizer medications at the time of blood draw, raising the possibility that these drugs could have affected some of the differential transcription signatures. Using an independent Illumina data set of gene expression data from antipsychotic medication-free SZ subjects, the 18-gene biomarker panels produced a receiver operating characteristic curve accuracy greater than 0.866 in patients that were less than 30 years of age and medication free. We confirmed select transcripts by quantitative PCR and the nCounter® System. The episodic nature of psychiatric disorders might lead to highly variable results depending on when blood is collected in relation to the severity of the disease/symptoms. We have found stable trait gene panel markers for lifelong psychiatric disorders that may have diagnostic utility in younger undiagnosed subjects where there is a critical unmet need. The study requires replication in subjects for ultimate proof of the utility of the differential diagnosis.

Proliferation and apoptosis of T lymphocytes in patients with bipolar disorder

The aim of the study was to evaluate proliferation capacity and susceptibility to apoptosis of T lymphocytes of patients with bipolar disorder (BD) and to investigate in vitro influence of two standard mood stabilizers: lithium and valproic acid on these parameters using flow cytometry. Our results show that T lymphocytes of BD patients, especially those treated with lithium, have reduced proliferation capacity compared to healthy people. In vitro studies showed that valproic acid reduces the number of cell divisions and percentages of proliferating cells regardless of health status but mainly in very high dose, while lithium has no significant influence on proliferation capacity of patients’ T lymphocytes. Lymphocytes of BD patients are also more prone to apoptosis compared with healthy individuals which is related to high expression of Bax, a pro-apoptotic protein. In vitro lithium protected patients’ lymphocytes from apoptosis proportionally to dose used. Valproic acid protected lymphocytes of patients from apoptosis mainly in therapeutic concentration. Our results show that mood stabilizers used to prevent relapses of the disease have anti-apoptotic effect on T lymphocytes of BD patients but they are not able to improve their proliferation capacity.

Association of PIK3CG gene polymorphisms with attention-deficit/hyperactivity disorder: A case-control study

Attention-deficit/hyperactivity disorder (ADHD) is a complicated neurodevelopmental disorder with high heritability. This study explores the association of PIK3CG gene single nucleotide polymorphisms (rs1129293, rs12536620, rs12667819, rs17847825, rs2230460) with ADHD in children and the relation of interaction between SNPs and environmental factors, including blood lead levels (BLLs) and feeding style. A case-control study was conducted with children aged 6-18years old, consisting of 389 children newly diagnosed with ADHD via the DSM-IV at the Wuhan Women and Children Medical Care Center, and 393 control participants were healthy children for physical examination during the same period. All participants were tested using the Chinese Wechsler Intelligence Scale for Children and Parent Symptom Questionnaire (PSQ). Furthermore, a self-designed questionnaire was used to investigate the general situation and related environmental factors, and the BLLs were measured by atomic absorption spectrophotometry. The genotyping was performed using Sequenom MassArray. In our study, PIK3CG gene rs12667819 was consistently shown to be associated with ADHD risk in dominant model (OR=1.656, 95% CI=1.229-2.232), ADHD-I type (OR=2.278, 95% CI=1.666-4.632), and symptom scores. Moreover, rs12536620 has been observed to be related to ADHD-C type and symptom scores. Intriguingly, gene-environmental interactions analysis consistently revealed the potential interactions of rs12667819 collaborating with blood lead (P_mul=0.045) and feeding style (P_mul=0.041) to modify ADHD risk. Expression quantitative trait loci analysis suggested that rs12667819 may mediate PIK3CG gene expression. Therefore, our results suggest that selected PIK3CG gene variants may have a significant effect on ADHD risk.

Association between Lithium Use and Melanoma Risk and Mortality: A Population-Based Study

Laboratory studies show that lithium, an activator of the Wnt/ß-catenin signaling pathway, slows melanoma progression, but to our knowledge no published epidemiologic studies have explored this association. We conducted a retrospective cohort study of adult white Kaiser Permanente Northern California members (n = 2,213,848) from 1997-2012 to examine the association between lithium use and melanoma risk. Lithium exposure (n = 11,317) was assessed from pharmacy databases, serum lithium levels were obtained from electronic laboratory databases, and incident cutaneous melanomas (n = 14,056) were identified from an established cancer registry. In addition to examining melanoma incidence, melanoma hazard ratios and 95% confidence intervals for lithium exposure were estimated using Cox proportional hazards models, adjusted for potential confounders. Melanoma incidence per 100,000 person-years among lithium-exposed individuals was 67.4, compared with 92.5 in unexposed individuals (P = 0.027). Lithium-exposed individuals had a 32% lower risk of melanoma (hazard ratio = 0.68, 95% confidence interval = 0.51-0.90) in unadjusted analysis, but the estimate was attenuated and nonsignificant in adjusted analysis (adjusted hazard ratio = 0.77, 95% confidence interval = 0.58-1.02). No lithium-exposed individuals presented with thick (>4 mm) or advanced-stage melanoma at diagnosis. Among melanoma patients, lithium-exposed individuals were less likely to suffer melanoma-associated mortality (rate = 4.68/1,000 person-years) compared with the unexposed (rate = 7.21/1,000 person-years). Our findings suggest that lithium may reduce melanoma risk and associated mortality.

Genomics of Lithium Action and Response

Lithium is the most successful mood stabilizer treatment for bipolar disorder. However, unlike conventional drugs that are designed to interact with a specific molecular target, the actions of lithium are distributed across many biological processes and pathways. Treatment response is subject to genetic variation between individuals and similar genetic variation may dictate susceptibility to side effects. Transcriptomic, genomic, and cell-model research strategies have all been deployed in the search for the genetic factors and biological systems that mediate the interaction between genetics and the therapeutic actions of lithium. In this review, recent findings from genome-wide studies and patient cell lines will be summarized and discussed from a standpoint that genuine progress is being made to define clinically useful mechanisms of this treatment, to place it in the context of bipolar disorder pathology, and to move towards a time when the prescription of lithium is targeted to those individuals who will derive the greatest benefit.