Lithium Response In Bipolar Disorder Research Articles

In-silico functional analyses identify TMPRSS15-mediated intestinal absorption of lithium as a modulator of lithium response in bipolar disorder

BackgroundThe therapeutic response to lithium in patients with bipolar disorder is highly variable and has a polygenic basis. Genome-wide association studies investigating lithium response have identified several relevant loci, though the precise mechanisms driving these associations are poorly understood. We aimed to prioritise the most likely effector gene and determine the mechanisms underlying an intergenic lithium response locus on chromosome 21 identified by the International Consortium on Lithium Genetics (ConLi+Gen). MethodsWe conducted in-silico functional analyses by integrating and synthesising information from several publicly available functional genetic datasets and databases including the Genotype-Tissue Expression (GTEx) project and HaploReg. ResultsThe findings from this study highlighted TMPRSS15 as the most likely effector gene at the ConLi+Gen lithium response locus. TMPRSS15 encodes enterokinase, a gastrointestinal enzyme responsible for converting trypsinogen into trypsin and thus aiding digestion. Convergent findings from gene-based lookups in human and mouse databases as well as co-expression network analyses of small intestinal RNA-seq data (GTEx) implicated TMPRSS15 in the regulation of intestinal nutrient absorption, including ions like sodium and potassium, which may extend to lithium. LimitationsAlthough the findings from this study indicated that TMPRSS15 was the most likely effector gene at the ConLi+Gen lithium response locus, the evidence was circumstantial. Thus, the conclusions from this study need to be validated in appropriately designed wet-lab studies. ConclusionsThe findings from this study are consistent with a model whereby TMPRSS15 impacts the efficacy of lithium treatment in patients with bipolar disorder by modulating intestinal lithium absorption.

Lithium response in bipolar disorder: Epigenome-wide DNA methylation signatures and epigenetic aging

Lithium (Li) is the first-line treatment for bipolar disorder (BD) even though only 30 % of BD patients are considered excellent responders. The mechanisms by which Li exerts its action are not clearly understood, but it has been suggested that specific epigenetic mechanisms, such as methylation processes, may play a role. In this regard, DNA methylation patterns can be used to estimate epigenetic age (EpiAge), which is accelerated in BD patients and reversed by Li treatment. Our first aim was to compare the DNA methylation profile in peripheral blood between BD patients categorized as excellent responders to Li (Ex-Rp) and non-responders (N-Rp). Secondly, EpiAge was estimated to detect differential age acceleration between the two groups.A total of 130 differentially methylated positions (DMPs) and 16 differentially methylated regions (DMRs) between Ex-Rp (n = 26) and N-Rp (n = 37) were identified (FDR adjusted p-value < 0.05). We found 122 genes mapping the DMPs and DMRs, nine of which (HOXB6, HOXB3, HOXB-AS3, TENM2, CACNA1B, ANK3, EEF2K, CYP1A1, and SORCS2) had previously been linked to Li response. We found genes related to the GSK3β pathway to be highly represented. Using FUMA, we found enrichment in Gene Ontology Cell Component for the synapse. Gene network analysis highlighted functions related to the cell cycle, nervous system development and function, and gene expression. No significant differences in age acceleration were found between Ex-Rp and N-Rp for any of the epigenetic clocks analysed.Our findings indicate that a specific methylation pattern could determine the response to Li in BD patients. We also found that a significant portion of the differentially methylated genes are closely associated with the GSK3β pathway, reinforcing the role of this system in Li response. Future longitudinal studies with larger samples will help to elucidate the epigenetic mechanisms underlying Li response.

Methylomic signature of lithium response in bipolar disorder

Introduction Bipolar disorder (BD) is a chronic and severe psychiatric disorder, characterized by the alternance of episodes of (hypo)-mania and major depression. Lithium (Li) is the first-line treatment for BD but unfortunately response to Li is highly variable: after at least two consecutive years of treatment, only a fraction of patients receiving Li will display significant improvement in the frequency and/or severity of mood recurrences. This interindividual variability of treatment response is difficult to predict, in the bipolar disorder context. This could be determined by genetic factors still misidentified by available genetic studies. In addition, no clinical or biological markers are available to reliably define eligibility criteria for a lithium treatment in bipolar disorder. A consequence is a long process of therapeutic trials (18-24 months) to phenotype Li response, delaying the stabilization.ObjectivesTo identify objective biomarkers of the prophylactic response to lithium in order to improve patient care and propose therapeutic alternatives to patients who do not respond to lithium.Methods Using a genome-wide methylomic approach, and then logistic regressions incorporating as covariates the different types of treatments, we were able to identify differentially methylated regions (DMRs) whose methylation difference between responders and non-responders was not impacted by co-prescribed treatments. Then, we used Methylation Specific High-Resolution Melting (MS-HRM), a PCR based method than can be implemented in any medical laboratory at low cost and with minimal equipment, to estimate methylation proportion of 9 DMRs in 61 samples of bipolar patients.Results In the sample of 61 individuals with BD, the 9 MS-HRM-measured DMRs combined with clinical variables (age, sex, cigarette smoking status, lifetime number of hospitalizations, age at onset of BD, polarity at onset, psychotic symptoms at onset, family history of BD, lifetime alcohol/cannabis misuse, panic disorders, Li prescribed as the first mood stabilizer (vs 2nd or 3rd choice)) correctly classified 83,6% of individuals as good or non-responders (n=61, prophylactic response phenotype defined using the “Alda” scale). Excluding the partial responders, the percentage of correctly classified individuals is as high as 100% (n=43, 18 non responders and 25 responders). The AUC are respectively AUC=0.913 and AUC=1.0.ConclusionsThe MS-HMR method allow to identify the response status of individuals with BD with 9 DMR. These DMRs discriminate good from non-responders and can be used in combination with clinical variables.Disclosure of InterestNone Declared

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Clinical, genetic, and epigenetic markers associated with lithium response in bipolar disorder

Clinical, genetic, and epigenetic markers associated with lithium response in bipolar disorder

Immunoglobulin genes expressed in lymphoblastoid cell lines discern and predict lithium response in bipolar disorder patients.

Bipolar disorder (BD) is a neuropsychiatric mood disorder manifested by recurrent episodes of mania and depression. More than half of BD patients are non-responsive to lithium, the first-line treatment drug, complicating BD clinical management. Given its unknown etiology, it is pertinent to understand the genetic signatures that lead to variability in lithium response. We discovered a set of differentially expressed genes (DEGs) from the lymphoblastoid cell lines (LCLs) of 10 controls and 19 BD patients belonging mainly to the immunoglobulin gene family that can be used as potential biomarkers to diagnose and treat BD. Importantly, we trained machine learning algorithms on our datasets that predicted the lithium response of BD subtypes with minimal errors, even when used on a different cohort of 24 BD patients acquired by a different laboratory.This proves the scalability of our methodology for predicting lithium response in BD and for a prompt and suitable decision on therapeutic interventions.

Methylomic biomarkers of lithium response in bipolar disorder: a clinical utility study

BackgroundResponse to lithium (Li) is highly variable in bipolar disorders (BD). Despite decades of research, no clinical predictor(s) of response to Li prophylaxis have been consistently identified. Recently, we developed epigenetic Methylation Specific High-Resolution Melting (MS-HRM) assays able to discriminate good responders (GR) from non-responders (NR) to Li in individuals with BD type 1 (BD-I). This study examined whether a combination of clinical and epigenetic markers can distinguish NR from other types of Li responders.MethodsWe recorded clinical variables that are potentially associated with Li response in 64 individuals with BD-I. MS-HRM assays were performed on DNA isolated from peripheral blood. We used backward stepwise logistic regression analyses, followed by receiver operating characteristic (ROC) curve analysis to estimate the performance of the clinical variables, alone then in combination with the epigenetic biomarkers, to identify GR and partial responders (PaR) vs NR.ResultsPolarity at onset, psychotic symptoms at onset and family history of BD classified correctly 70% of individuals according to their Li response (PaR + GR = 86%; NR = 35%). When combined with the epigenetic biomarkers, these three clinical variables plus alcohol misuse (and one DMR: Differentially Methylated Region) correctly classified 86% of individuals, improving the prediction of PaR + GR (93%) and of NR (70%). The ROC analysis demonstrated an improvement in the area under the curve from 0.75 (clinical variables alone) to 0.87 (combination of clinical and epigenetic markers).ConclusionsCombining clinical predictors and DNA methylation markers of Li response may have greater utility in clinical practice than relying on clinical characteristics alone.

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.

Neural progenitor cells derived from lithium responsive and non-responsive bipolar disorder patients exhibit distinct sensitivity to cell death following methamphetamine

Bipolar disorder (BD) is characterized by manic and depressive mood episodes and loss of brain gray matter. Lithium has antimanic and neuroprotective properties, but only 30% BD patients respond to lithium pharmacotherapy. Dopamine signaling has been implicated in BD and may contribute to lithium response. Methamphetamine (METH) stimulates dopamine release and models the clinical features of mania but has never been used to study cell death in BD patient neurons. We used BD patient derived neuronal progenitor cells (NPCs) to determine whether the vulnerability to cell death differed in samples from lithium responder (Li-R) and non-responder (Li-NR) BD patients and healthy controls following METH exposure in vitro. We hypothesized that NPCs from Li-R and Li-NR would differ in vulnerability to METH, dopamine signaling and neuroprotection from lithium. Following METH, NPCs from controls and Li-NR showed significantly greater cell loss compared to Li-R. Pre-treatment of NPCs with the D1 dopamine receptor antagonist SCH 23390 reversed the neurotoxic effects of METH. In Li-R NPCs, expression of phosho-ERK1/2 was significantly increased. In Li-NR NPCs, phospho-AKT, D1 and D2 dopamine receptor proteins were significantly increased. Pre-treatment of NPCs with lithium before METH reversed the neurotoxic effects of METH in control NPCs, whereas Li-NR showed less protective benefit. Li-R cells showed decreased levels of cell death after METH and comparatively high viability, and lithium treatment did not increase viability any further. This novel NPC model of mania reveals differences in cell death that could help identify mechanisms of lithium response in BD.

Elevated choline in dorsolateral prefrontal cortex of lithium responders with bipolar I disorder.

Response to lithium maintenance varies widely across patients with bipolar disorder (BD). The studies on neurochemical correlates of long-term lithium response in BD remain scant. To assess the neurochemical profile in DLPFC based on lithium response status among subjects with bipolar I disorder (BD-I) using in vivo MRS. This was an observational study of 40 right-handed, euthymic adult participants with DSM-5 BD-I on long-term lithium maintenance with no psychiatric comorbidities (MINI 7.0). Using Alda Lithium Response Scale (LRS), a cut-off ≥7 for excellent lithium response, the sample was grouped into study group I for responders and group II for non-responders. All participants were assessed using NIMH Life Chart Method and IGSLI typical/atypical features scale. 1H-MRS was carried out on a 3T MR scanner (Achieva, Phillips) using a 32-channel head coil, with a voxel placed at the left DLPFC. LC model was used to measure absolute concentrations of neurochemicals and their ratios in relation to creatine. Group I (n=20) was comparable to Group II (n=20) with respect to demographic and illness profile. The GPC/Cr+PCr ratio was significantly higher (p=0.028) among excellent lithium responders (0.32±0.20mmol/l) compared to sub-optimal responders (0.25±0.05mmol/l). Choline-containing compounds reflect alterations in cell membrane synthesis or myelin turnover, and are a marker of overall cell density. No significant alterations were detected in NAA, glutamate, glutamine, myo-inositol and creatine. The lithium responders exhibited elevated choline (GPC) in the left DLPFC compared to non-responders.

Discovering proteomics predictors for lithium response in bipolar disorder: a 6-month follow-up study

Discovering proteomics predictors for lithium response in bipolar disorder: a 6-month follow-up study

Genetic and Epigenetic Markers of Lithium Response.

The mood stabilizer lithium represents a cornerstone in the long term treatment of bipolar disorder (BD), although with substantial interindividual variability in clinical response. This variability appears to be modulated by genetics, which has been significantly investigated in the last two decades with some promising findings. In addition, recently, the interest in the role of epigenetics has grown significantly, since the exploration of these mechanisms might allow the elucidation of the gene–environment interactions and explanation of missing heritability. In this article, we provide an overview of the most relevant findings regarding the pharmacogenomics and pharmacoepigenomics of lithium response in BD. We describe the most replicated findings among candidate gene studies, results from genome-wide association studies (GWAS) as well as post-GWAS approaches supporting an association between high genetic load for schizophrenia, major depressive disorder or attention deficit/hyperactivity disorder and poor lithium response. Next, we describe results from studies investigating epigenetic mechanisms, such as changes in methylation or noncoding RNA levels, which play a relevant role as regulators of gene expression. Finally, we discuss challenges related to the search for the molecular determinants of lithium response and potential future research directions to pave the path towards a biomarker guided approach in lithium treatment.

Methylomic Biomarkers of Lithium Response in Bipolar Disorder: A Proof of Transferability Study.

Response to lithium (Li) is highly variable in bipolar disorders (BD) and no clinical or biological predictors of long-term response have been validated to date. Using a genome-wide methylomic approach (SeqCapEpi), we previously identified seven differentially methylated regions (DMRs) that discriminated good from non-responders (prophylactic response phenotype defined using the “Alda” scale). This study is a proof of transferability from bench to bedside of this epigenetic signature. For this purpose, we used Methylation Specific High-Resolution Melting (MS-HRM), a PCR based method that can be implemented in any medical laboratory at low cost and with minimal equipment. In 23 individuals with BD, MS-HRM measures of three out of seven DMRs were technically feasible and consistencies between SeqCapEpi and MS-HRM-measures were moderate to high. In an extended sample of individuals with BD (n = 70), the three MS-HRM-measured DMRs mainly predicted nonresponse, with AUC between 0.70–0.80 according to different definitions of the phenotype (Alda- or machine-learning-based definitions). Classification tree analyses further suggested that the MS-HRM-measured DMRs correctly classified up to 84% of individuals as good or non-responders. This study suggested that epigenetic biomarkers, identified in a retrospective sample, accurately discriminate non-responders from responders to Li and may be transferrable to routine practice.

Correction of depression-associated circadian rhythm abnormalities is associated with lithium response in bipolar disorder.

Bipolar disorder (BD) is characterized by episodes of depression and mania and disrupted circadian rhythms. Lithium is an effective therapy for BD, but only 30%-40% of patients are fully responsive. Preclinical models show that lithium alters circadian rhythms. However, it is unknown if the circadian rhythm effects of lithium are essential to its therapeutic properties. In secondary analyses of a multi-center, prospective, trial of lithium for BD, we examined the relationship between circadian rhythms and therapeutic response to lithium. Using standardized instruments, we measured morningness, diurnal changes in mood, sleep, and energy (circadian rhythm disturbances) in a cross-sectional study of 386 BD subjects with varying lithium exposure histories. Next, we tracked symptoms of depression and mania prospectively over 12weeks in a subset of 88 BD patients initiating treatment with lithium. Total, circadian, and affective mood symptoms were scored separately and analyzed. Subjects with no prior lithium exposure had the most circadian disruption, while patients stable on lithium monotherapy had the least. Patients who were stable on lithium with another drug or unstable on lithium showed intermediate levels of disruption. Treatment with lithium for 12weeks yielded significant reductions in total and affective depression symptoms. Lithium responders (Li-Rs) showed improvement in circadian symptoms of depression, but non-responders did not. There was no difference between Li-Rs and nonresponders in affective, circadian, or total symptoms of mania. Exposure to lithium is associated with reduced circadian disruption. Lithium response at 12weeks was selectively associated with the reduction of circadian depressive symptoms. We conclude that stabilization of circadian rhythms may be an important feature of lithium's therapeutic effects. NCT0127253.

P.0112 Evaluation of circadian rhythm parameters and NR1D1 single nucleotide polymorphism relationship to predict lithium response in bipolar disorder

P.0112 Evaluation of circadian rhythm parameters and NR1D1 single nucleotide polymorphism relationship to predict lithium response in bipolar disorder

Dynamic insulin-stimulated mTOR/GSK3 signaling in peripheral immune cells: Preliminary evidence for an association with lithium response in bipolar disorder.

A key mechanism of lithium is the inhibition of glycogen synthase kinase-3β (GSK3β) and activation of mammalian target of rapamycin (mTOR), two contributors to insulin signaling. We explored the relationship between these markers and clinical response to lithium in bipolar disorder (BD). Thirty-four subjects with BD who had been taking lithium for ≥2years and had a maintenance lithium Alda score defined as either high (≥7; n=20) or low (≤2; n=14) were included in the study. Baseline protein expression of GSK3β and mTOR (total and phosphorylated (p)) was obtained from a buffy coat. Peripheral blood mononuclear cells (PBMCs) from a subset of each group (n=11) were stimulated with insulin (10µg) and change in protein expression was determined using Western blot. In buffy coat samples, significantly higher levels of pmTOR were present in subjects with an Alda score ≤2 (lithium non-responsive), relative to those with scores ≥7 (lithium-responsive). No differences were observed for pGSK3β. In contrast, functional PBMC responses to 5min of insulin stimulation demonstrated robust increases in pGSK3β (87.05±43.41%) and pmTOR (105.7±66.48%) in the lithium responsive group only. This contrasted observed decreases in pGSK3β (34.08±16.12%) and pmTOR (37.84±14.39%) 5mins post-insulin in non-responders. Dynamic increases in pmTOR and pGSK3β post-insulin stimulation may reflect an immunometabolic state that facilitates lithium response. Further prospective analyses are needed to replicate and extend these preliminary findings and further investigate the role of insulin signaling in lithium response in BD.

A 7 Tesla Amygdalar-Hippocampal Shape Analysis of Lithium Response in Bipolar Disorder

Research to discover clinically useful predictors of lithium response in patients with bipolar disorder has largely found them to be elusive. We demonstrate here that detailed neuroimaging may have the potential to fill this important gap in mood disorder therapeutics. Lithium treatment and bipolar disorder have both been shown to affect anatomy of the hippocampi and amygdalae but there is no consensus on the nature of their effects. We aimed to investigate structural surface anatomy changes in amygdala and hippocampus correlated with treatment response in bipolar disorder. Patients with bipolar disorder (N = 14) underwent lithium treatment, were classified by response status at acute and long-term time points, and scanned with 7 Tesla structural MRI. Large Deformation Diffeomorphic Metric Mapping was applied to detect local differences in hippocampal and amygdalar anatomy between lithium responders and non-responders. Anatomy was also compared to 21 healthy comparison participants. A patch of the ventral surface of the left hippocampus was found to be significantly atrophied in non-responders as compared to responders at the acute time point and was associated at a trend-level with long-term response status. We did not detect an association between response status and surface anatomy of the right hippocampus or amygdala. To the best of our knowledge, this is the first shape analysis of hippocampus and amygdala in bipolar disorder using 7 Tesla MRI. These results can inform future work investigating possible neuroimaging predictors of lithium response in bipolar disorder.

Lithium response in bipolar disorder correlates with improved cell viability of patient derived cell lines

Lithium is an effective, well-established treatment for bipolar disorder (BD). However, the mechanisms of its action, and reasons for variations in clinical response, are unclear. We used neural precursor cells (NPCs) and lymphoblastoid cell lines (LCLs), from BD patients characterized for clinical response to lithium (using the “Alda scale” and “NIMH Retrospective Life chart method”), to interrogate cellular phenotypes related to both disease and clinical lithium response. NPCs from two biologically related BD patients who differed in their clinical response to lithium were compared with healthy controls. RNA-Seq and analysis, mitochondrial membrane potential (MMP), cell viability, and cell proliferation parameters were assessed, with and without in vitro lithium. These parameters were also examined in LCLs from 25 BD patients (16 lithium responders and 9 non-responders), and 12 controls. MMP was lower in both NPCs and LCLs from BD; but it was reversed with in vitro lithium only in LCLs, and this was unrelated to clinical lithium response. The higher cell proliferation observed in BD was unaffected by in vitro lithium. Cell death was greater in BD. However, LCLs from clinical lithium responders could be rescued by addition of in vitro lithium. In vitro lithium also enhanced BCL2 and GSK3B expression in these cells. Our findings indicate cellular phenotypes related to the disease (MMP, cell proliferation) in both NPCs and LCLs; and those related to clinical lithium response (cell viability, BCL2/GSK3B expression) in LCLs.

Ethnicity as a Major Predictor of Lithium Response in Bipolar Disorder

Lithium response in Bipolar Disorder (BD) has shown to have a genetic basis. However, few studies have explored the effect of ethnicity in predicting lithium response. The aim of this study was to test the hypothesis whether ethnicity plays a role in defining the outcome of lithium treatment in BD.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MDand lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MDwere more likely to respond well to lithium, compared to thosepatients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.