Clinical factors associated with lithium response in bipolar disorders

Polygenic contributions to lithium augmentation outcomes in antidepressant non-responders with unipolar depression

Objective

Lithium augmentation (LA) is an effective treatment for patients with major depression after inadequate antidepressant response, but therapeutic outcomes vary considerably between individuals. Molecular studies could yield novel insights into treatment prediction to enable personalized therapy choices. Here, we investigated the effects of polygenic risk scores (PRS) for schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) on clinical outcomes following LA.

Methods

Recent GWAS summary statistics were used to construct disorder-specific PRS in lithium-augmented MDD patients who participated in a prospective study after poor response to at least one antidepressant drug. Depressive symptoms were assessed for four weeks or longer using the Hamilton Depression Rating Scale (HAMD). Hazard ratios (HR) of favorable outcomes, response (≥ 50% reduction in HAMD composite scores) and remission (HAMD ≤ 7), were estimated by Cox proportional hazards regression models adjusted for ancestry, demographic, and clinical covariates.

Results

In 193 patients, BIP-PRS was positively associated with both response (HR = 1.29, 95% CI = 1.02-1.63, p = 0.03, Nagelkerke R2 = 2.51%) and remission (HR = 1.52, 95% CI = 1.14-2.04, p = 0.004, Nagelkerke R2 = 4.53%) after LA. Our data further suggest that individuals who carry a lower polygenic burden for MDD tend to respond better to LA (HR = 0.81, 95% CI = 0.66-1.00, p = 0.048, Nagelkerke R2 = 1.99%). No associations were observed between SCZ-PRS and either clinical outcome (p > 0.05).

Conclusions

Our findings indicate that individuals at higher polygenic risk for BIP and lower polygenic risk for MDD are more likely to benefit from augmentation with lithium. If replicated, PRS may inform future efforts to establish clinical prediction models for LA outcomes in unipolar depression.

Predictors of valproic acid steady-state serum levels in adult and pediatric psychiatric inpatients: a comparative analysis

RATIONALE

Valproic acid (VPA) is commonly used as a second-line mood stabilizer or augmentative agent in severe mental illnesses. However, population pharmacokinetic studies specific to psychiatric populations are limited, and clinical predictors for the precision application of VPA remain undefined.

OBJECTIVES

To identify steady-state serum VPA level predictors in pediatric/adolescent and adult psychiatric inpatients.

METHODS

We analyzed data from 634 patients and 1,068 steady-state therapeutic drug monitoring (TDM) data points recorded from 2015 to 2021. Steady-state VPA levels were obtained after tapering during each hospitalization episode. Electronic patient records were screened for routine clinical parameters and co-medication. Generalized additive mixed models were employed to identify independent predictors.

RESULTS

Most TDM episodes involved patients with psychotic disorders, including schizophrenia (29.2%) and schizoaffective disorder (17.3%). Polypharmacy was common, with the most frequent combinations being VPA + quetiapine and VPA + promethazine. Age was significantly associated with VPA levels, with pediatric/adolescent patients (< 18 years) demonstrating higher dose-adjusted serum levels of VPA (β = 7.6±2.34, p < 0.001) after accounting for BMI. Women tended to have higher adjusted VPA serum levels than men (β = 5.08±1.62, p < 0.001). The formulation of VPA (Immediate-release vs. extended-release) showed no association with VPA levels. Co-administration of diazepam exhibited a dose-dependent decrease in VPA levels (F = 15.7, p < 0.001), suggesting a potential pharmacokinetic interaction.

CONCLUSIONS

This study highlights the utility of population-specific pharmacokinetic data for VPA in psychiatric populations. Age, gender, and co-administration of diazepam were identified as predictors of VPA levels. Further research is warranted to establish additional predictors and optimize the precision application of VPA in psychiatric patients.

Lithium-discontinuation-induced treatment refractoriness revisited

BACKGROUND

Lithium is effective in the long-term treatment of bipolar disorder. Concerns have been raised about non-responsiveness after discontinuation and resuming previously effective lithium prophylaxis. We reviewed the available literature on this so-called lithium-discontinuation-induced treatment refractoriness (LDITR).

RESULTS

We found 11 case reports and six cohort studies including 403 patients addressing LDITR, and one nation-wide register study providing some additional data on LDITR. Pooling all cohort studies, the percentages of non-responders during re-treatment with lithium ranged from 3.6 to 27.7%, with an average of 17.3%. Non-responsiveness was associated with longer duration of lithium treatment before discontinuation, longer duration of bipolar disorder before start of lithium, faster tapering off lithium, and longer duration of discontinuation.

CONCLUSIONS

There may be a subgroup in whom lithium discontinuation-induced treatment refractoriness exists. However, the vast majority of people respond when lithium is restarted. Moreover, it may be necessary to continue lithium beyond the first relapses to restore long-term prophylactic efficacy.

New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview

Over the last six decades, lithium has been considered the gold standard treatment for the long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well as suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways and biologic systems, the precise mechanism through which lithium stabilizes mood remains elusive. Furthermore, there is recent support for the therapeutic potential of lithium in other brain diseases. This review offers a comprehensive examination of contemporary understanding and predominant theories concerning the diverse mechanisms underlying lithium's effects. These findings are based on investigations utilizing cellular and animal models of neurodegenerative and psychiatric disorders. Recent studies have provided additional support for the significance of glycogen synthase kinase-3 (GSK3) inhibition as a crucial mechanism. Furthermore, research has shed more light on the interconnections between GSK3-mediated neuroprotective, antioxidant, and neuroplasticity processes. Moreover, recent advancements in animal and human models have provided valuable insights into how lithium-induced modifications at the homeostatic synaptic plasticity level may play a pivotal role in its clinical effectiveness. We focused on findings from translational studies suggesting that lithium may interface with microRNA expression. Finally, we are exploring the repurposing potential of lithium beyond bipolar disorder. These recent findings on the therapeutic mechanisms of lithium have provided important clues toward developing predictive models of response to lithium treatment and identifying new biologic targets. SIGNIFICANCE STATEMENT: Lithium is the drug of choice for the treatment of bipolar disorder, but its mechanism of action in stabilizing mood remains elusive. This review presents the latest evidence on lithium's various mechanisms of action. Recent evidence has strengthened glycogen synthase kinase-3 (GSK3) inhibition, changes at the level of homeostatic synaptic plasticity, and regulation of microRNA expression as key mechanisms, providing an intriguing perspective that may help bridge the mechanistic gap between molecular functions and its clinical efficacy as a mood stabilizer.

Type of cycle, temperament and childhood trauma are associated with lithium response in patients with bipolar disorders

BACKGROUND

Lithium stands as the gold standard in treating bipolar disorders (BD). Despite numerous clinical factors being associated with a favorable response to lithium, comprehensive studies examining the collective influence of clinical variables alongside psychopathological dimensions are lacking. Our study aims to enhance comprehension of lithium response in individuals with BD by integrating clinical variables with psychopathological traits and early adverse events.

METHODS

We assessed 201 patients with BD for clinical characteristics, childhood trauma, temperament traits, impulsivity, and aggression. Lithium response was evaluated using the gold standard Alda scale, and predictors of lithium response were estimated through a multivariate model.

RESULTS

On the total sample, 61 (30.3%) patients were lithium responders according to the Alda scale. Comparatively, lithium responders, in contrast to non-responders, demonstrated a higher prevalence of the mania-depression-interval (MDI) cycle, a more frequent diagnosis of BD type I, and reported an earlier age of onset. They also exhibited less lifetime substance abuse, emotional, physical, and sexual abuse, while scoring higher on hyperthymic and irritable temperament scales. In multivariate analyses, only the MDI cycle (OR,3.47; 95%CI,1.61-7.50) hyperthymic (OR,1.20; 95%CI,1.02-1.41) and irritable temperament (OR,1.28; 95%CI,1.08-1.52) persisted as significant predictors of a positive response to lithium treatment, while emotional (OR,0.87; 95%CI,0.76-0.98) and physical abuse (OR,0.83; 95%CI,0.70-0.98) were predictors of non-response.

CONCLUSIONS

In evaluating lithium response in BD, our study highlights the importance of considering clinical variables alongside temperament and childhood adversities. The assessment of hyperthymic and irritable temperament, emotional and physical abuse together with the type of cycle is of particular importance. Furthermore, our findings underscore the significance of systematically assessing the type of cycle in patients with BD through the use of life charts.

Lithium prescription trends in psychiatric inpatient care 2014 to 2021: data from a Bavarian drug surveillance project

OBJECTIVES

Lithium (Li) remains one of the most valuable treatment options for mood disorders. However, current knowledge about prescription practices in Germany is limited. The objective of this study is to estimate the prevalence of current Li use over time and in selected diagnoses, highlighting clinically relevant aspects such as prescription rates in elderly patients, concomitant medications, important drug-drug interactions, and serious adverse events.

METHODS

We conducted a descriptive analysis of Li prescriptions, analyzing data from the ongoing Bavarian multicenter drug safety project Pharmaco-Epidemiology and Vigilance (Pharmako-EpiVig) from the years 2014-2021. Our study included 97,422 inpatients, 4543 of whom were prescribed Li.

RESULTS

The Li prescription rate in unipolar depression (UD) remained constant at 4.6% over the observational period. In bipolar disorder (BD), the prescription rate increased significantly from 28.8% in 2014 to 34.4% in 2019. Furthermore, 30.3% of patients with Li prescriptions did not have a diagnosis of BD or UD, and 15.3% of patients with schizoaffective disorder were prescribed Li. The majority (64%) of patients with Li prescriptions were prescribed five or more drugs. Most of the 178 high-priority drug-drug interactions were due to hydrochlorothiazide (N = 157) followed by olmesartan (N = 16).

CONCLUSION

Our study does not substantiate concerns about a decline in Li prescription. The decline in prescription rates observed in some diagnostic groups in 2020 and 2021 may be associated with the COVID-19 pandemic. The symptom-oriented use of Li beyond BD and UD is common. Polypharmacy and drug-drug interactions present a challenge in Li therapy. Old age and comorbid substance use disorder do not appear to be major deterrents for clinicians to initiate Li therapy.

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

INTRODUCTION

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.

AIM

To assess the neurochemical profile in DLPFC based on lithium response status among subjects with bipolar I disorder (BD-I) using in vivo MRS.

MATERIALS AND METHOD

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 3 T 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.

RESULTS

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 ± 0.20 mmol/l) compared to sub-optimal responders (0.25 ± 0.05 mmol/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.

CONCLUSION

The lithium responders exhibited elevated choline (GPC) in the left DLPFC compared to non-responders.

Lithium and Valproate in Bipolar Disorder: From International Evidence-based Guidelines to Clinical Predictors

Since decades, lithium and valproate remain the pharmacological cornerstone to treat bipolar disorder. Different response patterns occur according to the phases of illness. At same time, individual pretreatment variables may concur to determine a specific drug-response. Our narrative review focuses on these two key clinical aspects to summarize the state of art. Information from i) clinical trials and ii) the most relevant international guidelines is collected to assess the clinical and preclinical factors that may guide the use of lithium rather than valproate. Lithium may be effective in treating acute mania, and lithium efficacy is maximized when used to prevent both manic and depressive episodes. Lithium may be a better treatment choice in patients with: positive family history for bipolar disorder, mania-depression-interval pattern, few previous affective episodes/hospitalizations, high risk for suicide, no comorbidities. Valproate may be more effective as antimanic rather than prophylactic agent. Valproate might be a better choice in patients with many previous affective episodes/hospitalizations and psychiatric comorbidities. Finally, neither lithium nor valproate are suggested for the treatment of acute mixed states or bipolar depression. To consider clinical and preclinical factors may thus be useful to select the best treatment strategy.

Lithium response in bipolar disorder: Genetics, genomics, and beyond

Lithium is an effective mood stabilizer in bipolar disorder (BD). There is, however, high variability in treatment response to lithium and only 20-30% of individuals with BD are excellent responders. This subgroup has been shown to have specific phenotypic characteristics, and family studies have implicated genetics as an important factor. However, candidate gene studies did not find evidence for major effect genes. Genome-wide association studies (GWAS) have emphasized that lithium response is a polygenic trait. GWAS based on larger sample sizes and non-European ancestries are likely to shed light on the genomic architecture of this trait. Furthermore, induced pluripotent stem cells, transcriptomics, epigenetics, the integration of multiple omics data, and their combination with advanced machine learning techniques hold promise for the understanding of the complex biological underpinnings of lithium treatment response.

White matter characteristics in the early and late stages of bipolar disorder: A diffusion tensor imaging study

BACKGROUND

Bipolar disorder (BD) is characterized by recurrent mood episodes that may progress over time. Staging models may be used to follow the long-term course of BD. BD is associated with microstructural changes in white matter (WM). This study aims to compare the WM integrity within patients groups who are in different stages of BD and healthy controls and investigate whether WM integrity changes may be a biomarker that can be used in the clinical staging of BD.

METHODS

The study sample included euthymic 54 patients diagnosed with BD according to Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) and 27 healthy volunteers. Early-stage patients (n = 26) were determined as patients who have not had any mood episodes after the first manic episode, and late-stage patients (n = 28) determined as patients with recurrent mood episodes. MRI was performed using a 1.5 Tesla MR system and DTI sequences were acquired.

RESULTS

Region of interest (ROI) analyses showed that late-stage patients had significantly reduced fractional anisotropy (FA) in the right sagittal stratum and genu of the corpus callosum compared with healthy controls and early-stage patients. Regression models show that corpus callosum genu and right sagittal stratum FA values are predictive for the late-stage patient group.

LIMITATIONS

There are some limitations of the ROI method. The cross-sectional design is another limitation of this study.

CONCLUSIONS

WM integrity of corpus callosum genu and right sagittal stratum may be a biomarker for clinical staging of BD. Identifying stage-specific biomarkers may help us predict the neuroprogressive course of BD. Longitudinal studies would be required to detect stage-specific biomarkers.

The pharmacotherapeutic management of comorbid bipolar disorder and alcohol use disorder

INTRODUCTION

Comorbidity of bipolar disorder (BD) and alcohol use disorder (AUD) is very frequent resulting in detrimental outcomes, including increased mortality. Diagnosis of AUD in BD and vice versa is often delayed as symptoms of one disorder mimic and obscure the other one. Evidence for pharmacotherapies for people with comorbid BD and AUD remains limited, and further proof-of-concept studies are urgently needed.

AREAS COVERED

This paper explores the currently available pharmacotherapies for AUD, BD and their usefulness for comorbid BD and AUD. It also covers to some degree the epidemiology, diagnosis, and potential common neurobiological traits of comorbid BD and AUD.

EXPERT OPINION

The authors conclude that more controlled studies are needed before evidence-based guidance can be drawn up for clinician's use. Since there are no relevant pharmacological interactions, approved medications for AUD can also be used safely in BD. For mood stabilization, lithium should be considered first in adherent persons with BD and comorbid AUD. Alternatives include valproate, lamotrigine, and some atypical antipsychotics, with partial D2/D3 receptor agonism possibly being beneficial in AUD, too.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach

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.

Perceived helpfulness of bipolar disorder treatment: Findings from the World Health Organization World Mental Health Surveys

OBJECTIVES

To examine patterns and predictors of perceived treatment helpfulness for mania/hypomania and associated depression in the WHO World Mental Health Surveys.

METHODS

Face-to-face interviews with community samples across 15 countries found n = 2,178 who received lifetime mania/hypomania treatment and n = 624 with lifetime mania/hypomania who received lifetime major depression treatment. These respondents were asked whether treatment was ever helpful and, if so, the number of professionals seen before receiving helpful treatment. Patterns and predictors of treatment helpfulness were examined separately for mania/hypomania and depression.

RESULTS

63.1% (mania/hypomania) and 65.1% (depression) of patients reported ever receiving helpful treatment. However, only 24.5-22.5% were helped by the first professional seen, which means that the others needed to persist in help seeking after initial unhelpful treatments in order to find helpful treatment. Projections find only 22.9% (mania/hypomania) and 43.3% (depression) would persist through a series of unhelpful treatments but that the proportion helped would increase substantially if persistence increased. Few patient-level significant predictors of helpful treatment emerged and none consistently either across the two components (i.e., provider-level helpfulness and persistence after earlier unhelpful treatment) or for both mania/hypomania and depression. Although prevalence of treatment was higher in high-income than low/middle-income countries, proportional helpfulness among treated cases was nearly identical in the two groups of countries.

CONCLUSIONS

Probability of patients with mania/hypomania and associated depression obtaining helpful treatment might increase substantially if persistence in help-seeking increased after initially unhelpful treatments, although this could require seeing numerous additional treatment providers. In addition to investigating reasons for initial treatments not being helpful, messages reinforcing the importance of persistence should be emphasized to patients.

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 MD and 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 MD were more likely to respond well to lithium, compared to those patients 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.

Can actigraphy be used to define lithium response dimensions in bipolar disorders?

BACKGROUND

Actigraphy is commonly used in case-control studies to explore sleep-wake patterns and circadian rhythmicity in bipolar disorders (BD). However, there is limited ecological research regarding actigraphy parameters associated with response to lithium (Li_Resp).

METHODS

Outpatients with BD-I (n=70) and BD-II (n=20) who were all prescribed prophylactic Li undertook 21 consecutive days of actigraphy recording. The Retrospective Assessment of Response to Lithium Scale (also referred as the Alda scale) was rated on a 0-10 continuum. We used principal component analysis (PCA) to summarize interrelationships among clinical and actigraphic variables and Li_Resp.

RESULTS

PCA demonstrated the existence of a Li_Resp dimension (accounting for >20% explained variance) characterized by 5 markers of circadian timing and rhythmicity. Replication of the PCA, using the resampling procedure, confirmed this model was robust for the BD-I but not for BD-II (which showed weaker associations between Li_Resp and sleep variables). These circadian rhythm markers identified by PCA correctly classified 64% (95% Confidence Intervals: 52-76%; p<0.03) of all BD cases as Li responders or non-responders.

LIMITATIONS

Although we attempted to minimize risk of statistical error, the small BD-II subsample may have undermined the ability of PCA to identify a robust Li_Resp dimension for this subtype.

CONCLUSIONS

Our findings are compatible with circadian models of BD and with putative mechanisms of action of Li. If confirmed in prospective studies, the study offers support for use of actigraphy as a relevant method for real time objective monitoring of Li_Resp, with few concerns regarding reliability and validity.

Socio-demographic and clinical predictors of outcome to long-term treatment with lithium in bipolar disorders: a systematic review of the contemporary literature and recommendations from the ISBD/IGSLI Task Force on treatment with lithium

Objective

To identify possible socio-demographic and clinical factors associated with Good Outcome (GO) as compared with Poor Outcome (PO) in adult patients diagnosed with Bipolar Disorder (BD) who received long-term treatment with lithium.

Methods

A comprehensive search of major electronic databases was performed to identify relevant studies that included adults patients (18 years or older) with a diagnosis of BD and reported sociodemographic and/or clinical variables associated with treatment response and/or with illness outcome during long-term treatment to lithium (> = 6 months). The quality of the studies was scored using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies from the National Institute of Health.

Results

Following review, 34 publications (from 31 independent datasets) were eligible for inclusion in this review. Most of them (n = 25) used a retrospective design. Only 11 studies were graded as good or borderline good quality. Forty-three potential predictors of outcome to lithium were identified. Four factors were associated with PO to lithium: alcohol use disorder; personality disorders; higher lifetime number of hospital admissions and rapid cycling pattern. Two factors were associated with GO in patients treated with lithium: good social support and episodic evolution of BD. However, when the synthesis of findings was limited to the highest (good or borderline good) quality studies (11 studies), only higher lifetime number of hospitalization admissions remained associated with PO to lithium and no associations remained for GO to lithium.

Conclusion

Despite decades of research on lithium and its clinical use, besides lifetime number of hospital admissions, no factor being consistently associated with GO or PO to lithium was identified. Hence, there remains a substantial gap in our understanding of predictors of outcome of lithium treatment indicating there is a need of high quality research on large representative samples.

Defining phenotypes of long-term lithium and valproate response, including combination therapy: a modified application of the Alda scale in patients with bipolar disorders

BACKGROUND

When evaluating the long-term treatment response to mood stabilizers using the Alda scale, mood stabilizer combination therapy is typically considered a confounding factor, and patients receiving combination therapy are excluded from the analysis. However, this may result in bias if those under combination therapy are worse treatment responders. This study aims to explore whether the Alda scale is applicable to patients taking lithium and valproate combination therapy. We compared long-term treatment response in patients receiving monotherapy and combination therapy of the two drugs, and investigated clinical correlates of the responses to each drug.

METHODS

The study subjects consisted of 102 patients with bipolar I (BD-I) or bipolar II (BD-II) disorder who had been undergoing maintenance treatment with lithium and/or valproate for more than 2 years at a single specialized bipolar disorder clinic. Long-term treatment response was measured using the Alda scale and compared among the lithium monotherapy group, the valproate monotherapy group, and the mood stabilizer combination group. Clinical correlates of long-term treatment response were evaluated in lithium users and valproate users separately.

RESULTS

There were no significant differences in terms of baseline illness characteristics among groups. The combination group showed the worst treatment response for all the response measurements applied. This group also had the higher rate of 'poor responder' with a statistically significant difference compared to valproate group. Older age at onset and (hypo)manic episode at onset showed significant positive associations with total Alda score in lithium users, while comorbid anxiety disorders, obsessive-compulsive disorder and mixed episode showed significant negative associations in valproate users.

CONCLUSIONS

The combination group had poorer long-term treatment response but did not show distinct clinical characteristics compared to the monotherapy groups. When exploring the long-term effects of mood stabilizers, excluding patients undergoing combination treatment could result in bias because they may represent a poor response group. The long-term treatment responses of lithium and valproate had different clinical correlates.

Neurocognitive predictors of long-term clinical course in bipolar disorder

OBJECTIVE

The aim of this study was to estimate whether neurocognitive deficits are predictors of the long-term clinical course of patients with bipolar disorder.

METHODS

A total of 76 outpatients with bipolar disorder performed a neurocognitive assessment at baseline and were followed for a period of at least 48 months. The clinical course during the follow-up period was documented by two measures: (1) number of affective episodes and (2) time spent ill.

RESULTS

Patients had lower performance than controls in the domains of verbal memory and executive functions, and they were followed-up for a mean period of 70.73 months. Global cognitive deficits (performance 1.5 standard deviations below the mean in two or more cognitive domain) were independent predictors of both hypo/manic episode density and time spent with hypo/manic symptoms during follow-up. On the contrary, no neurocognitive measure showed a relationship with depressive morbidity during follow-up.

CONCLUSION

Our findings suggest that cognitive deficits could be useful for predicting hypo/manic morbidity in the long-term clinical course. Theoretical and clinical implications of these findings are discussed.

A DNA methylation signature discriminates between excellent and non-response to lithium in patients with bipolar disorder type 1

Lithium (Li) is the cornerstone maintenance treatment for bipolar disorders (BD), but response rates are highly variable. To date, no clinical or biological marker is available to reliably define eligibility criteria for a maintenance treatment with Li. We examined whether the prophylactic response to Li (assessed retrospectively) is associated with distinct blood DNA methylation profiles. Bisulfite-treated total blood DNA samples from individuals with BD type 1 (15 excellent-responders (LiERs) versus 11 non-responders (LiNRs)) were used for targeted enrichment of CpG rich genomic regions followed by high-resolution next-generation sequencing to identify differentially methylated regions (DMRs). After controlling for potential confounders we identified 111 DMRs that significantly differ between LiERs and LiNRs with a significant enrichment in neuronal cell components. Logistic regression and receiver operating curves identified a combination of 7 DMRs with a good discriminatory power for response to Li (Area Under the Curve 0.806). Annotated genes associated with these DMRs include Eukaryotic Translation Initiation Factor 2B Subunit Epsilon (EIF2B5), Von Willebrand Factor A Domain Containing 5B2 (VWA5B2), Ral GTPase Activating Protein Catalytic Alpha Subunit 1 (RALGAPA1). Although preliminary and deserving replication, these results suggest that biomarkers of response to Li may be identified through peripheral epigenetic measures.

A Physiological Instability Displayed in Hippocampal Neurons Derived From Lithium-Nonresponsive Bipolar Disorder Patients

BACKGROUND

We recently reported a hyperexcitability phenotype displayed in dentate gyrus granule neurons derived from patients with bipolar disorder (BD) as well as a hyperexcitability that appeared only in CA3 pyramidal hippocampal neurons that were derived from patients with BD who responded to lithium treatment (lithium responders) and not in CA3 pyramidal hippocampal neurons that were derived from patients with BD who did not respond to lithium (nonresponders).

METHODS

Here we used our measurements of currents in neurons derived from 4 control subjects, 3 patients with BD who were lithium responders, and 3 patients with BD who were nonresponders. We changed the conductances of simulated dentate gyrus and CA3 hippocampal neurons according to our measurements to derive a numerical simulation for BD neurons.

RESULTS

The computationally simulated BD dentate gyrus neurons had a hyperexcitability phenotype similar to the experimental results. Only the simulated BD CA3 neurons derived from lithium responder patients were hyperexcitable. Interestingly, our computational model captured a physiological instability intrinsic to hippocampal neurons that were derived from nonresponder patients that we also observed when re-examining our experimental results. This instability was caused by a drastic reduction in the sodium current, accompanied by an increase in the amplitude of several potassium currents. These baseline alterations caused nonresponder BD hippocampal neurons to drastically shift their excitability with small changes to their sodium currents, alternating between hyperexcitable and hypoexcitable states.

CONCLUSIONS

Our computational model of BD hippocampal neurons that was based on our measurements reproduced the experimental phenotypes of hyperexcitability and physiological instability. We hypothesize that the physiological instability phenotype strongly contributes to affective lability in patients with BD.

Can network analysis shed light on predictors of lithium response in bipolar I disorder?

OBJECTIVE

To undertake a large-scale clinical study of predictors of lithium (Li) response in bipolar I disorder (BD-I) and apply contemporary multivariate approaches to account for inter-relationships between putative predictors.

METHODS

We used network analysis to estimate the number and strength of connections between potential predictors of good Li response (measured by a new scoring algorithm for the Retrospective Assessment of Response to Lithium Scale) in 900 individuals with BD-I recruited to the Consortium of Lithium Genetics.

RESULTS

After accounting for co-associations between potential predictors, the most important factors associated with the good Li response phenotype were panic disorder, manic predominant polarity, manic first episode, age at onset between 15-32 years and family history of BD. Factors most strongly linked to poor outcome were comorbid obsessive-compulsive disorder, alcohol and/or substance misuse, and/or psychosis (symptoms or syndromes).

CONCLUSIONS

Network analysis can offer important additional insights to prospective studies of predictors of Li treatment outcomes. It appears to especially help in further clarifying the role of family history of BD (i.e. its direct and indirect associations) and highlighting the positive and negative associations of different subtypes of anxiety disorders with Li response, particularly the little-known negative association between Li response and obsessive-compulsive disorder.

An examination of the quality and performance of the Alda scale for classifying lithium response phenotypes

OBJECTIVES

The Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale) is the most widely used clinical measure of lithium response phenotypes. We assess its performance against recommended psychometric and clinimetric standards.

METHODS

We used data from the Consortium for Lithium Genetics and a French study of lithium response phenotypes (combined sample >2500) to assess reproducibility, responsiveness, validity, and interpretability of the A scale (assessing change in illness activity), the B scale, and its items (assessing confounders of response) and the previously established response categories derived from the Total Score for the Alda scale.

RESULTS

The key findings are that the B scale is vulnerable to error measurement. For example, some items contribute little to overall performance of the Alda scale (eg, B2) and that the B scale does not reliably assess a single construct (uncertainty in response). Machine learning models indicate that it may be more useful to employ an algorithm for combining the ratings of individual B items in a sequence that clarifies the noise to signal ratio instead of using a composite score.

CONCLUSIONS

This study highlights three important topics. First, empirical approaches can help determine which aspects of the performance of any scale can be improved. Second, the B scale of the Alda is best applied as a multidimensional index (identifying several independent confounders of the assessment of response). Third, an integrated science approach to precision psychiatry is vital, otherwise phenotypic misclassifications will undermine the reliability and validity of findings from genetics and biomarker studies.

Predicted Cellular and Molecular Actions of Lithium in the Treatment of Bipolar Disorder: An In Silico Study

BACKGROUND

Lithium remains the first-line treatment for bipolar disorder (BD), but patients respond to it variably. While a myriad of studies have attributed many genes and signaling pathways to lithium responsiveness, a comprehensive study with an integrated conclusion is still lacking.

OBJECTIVE

We aim to present an integrated mechanism for the therapeutic actions of lithium in BD.

METHODS

First, a list of lithium responsiveness-associated genes (LRAGs) was collected by searching in the literature. Thereafter, gene set enrichment analysis together with gene-gene interaction network analysis was performed, in order to find the cellular and molecular events related to the LRAGs.

RESULTS

Gene set enrichment analyses showed that the chromosomal regions 3p26, 4p21, 5q34 and 7p13 could be novel associated loci for lithium responsiveness in BD. Also, expression pattern analysis of the LRAGs showed their enrichment in adulthood stages and different cell lineages of brain, blood and immune system. Most of the LRAGs exhibited enriched expression in central parts of human brain, suggesting major contribution of these parts in lithium responsiveness. Beside the prediction of several biological processes and signaling pathways related to lithium responsiveness, an interaction network between these processes was constructed that was found to be regulated by a set of microRNAs. Proteins of the network were mainly classified as transcription factors and kinases, which also highlighted the crucial role of glycogen synthase kinase 3β (GSK3β) in lithium responsiveness.

CONCLUSIONS

The predicted cellular and molecular events in this study could be considered as mechanisms and also determinants of lithium responsiveness in BD.

Evaluation of 2D:4D digit ratio in bipolar 1 disorder patients and its relationship with treatment response

BACKGROUND

The role of sex steroids in bipolar disorder (BD) has been demonstrated in adults. We aimed to evaluate the 2D:4D ratio, which indirectly reflects prenatal sex steroids, in BD. Another purpose of this study was to determine the relationship between clinical features, especially lithium response, and digit ratio.

METHODS

The study included 74 patients with bipolar 1 disorder and 74 healthy individuals matched according to age, gender, and educational status. The digit ratio was calculated by dividing the index finger (2D) length by the ring finger (4D) length in both hands. A lithium response scale was used to evaluate the lithium response history.

RESULTS

There was no difference in 2D:4D ratio between the patients and controls in either right or left hands. The digit ratio was not different between groups with and without suicide attempts. The 2D:4D ratio in the patient group was lower in individuals unresponsive to lithium therapy than in partial and good responders for both right and left hands.

DISCUSSION

According to the results of our study, the 2D:4D ratio in the BD group was not different from healthy controls but was lower in patients unresponsive to lithium. In this respect, the 2D:4D ratio can be considered as a biomarker for lithium response in BD. In large-sample studies, the 2D:4D ratio should be investigated for pathophysiology and treatment response of BD.

Prediction of lithium response using clinical data

OBJECTIVE

Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical markers.

METHOD

Our data are the largest existing sample of direct interview-based clinical data from lithium-treated patients (n = 1266, 34.7% responders), collected across seven sites, internationally. We trained a random forest model to classify LR-as defined by the previously validated Alda scale-against 180 clinical predictors.

RESULTS

Under appropriate cross-validation procedures, LR was predictable in the pooled sample with an area under the receiver operating characteristic curve of 0.80 (95% CI 0.78-0.82) and a Cohen kappa of 0.46 (0.4-0.51). The model demonstrated a particularly low false-positive rate (specificity 0.91 [0.88-0.92]). Features related to clinical course and the absence of rapid cycling appeared consistently informative.

CONCLUSION

Clinical data can inform out-of-sample LR prediction to a potentially clinically relevant degree. Despite the relevance of clinical course and the absence of rapid cycling, there was substantial between-site heterogeneity with respect to feature importance. Future work must focus on improving classification of true positives, better characterizing between- and within-site heterogeneity, and further testing such models on new external datasets.

Clinical correlates associated with the long-term response of bipolar disorder patients to lithium, valproate or lamotrigine: A retrospective study

Background

Although mood stabilizers such as lithium (LIT), valproate (VAL), and lamotrigine (LMT) appear to be efficacious treatments for bipolar disorder (BD) in research settings, the long-term response to these mood stabilizers in clinical practice is highly variable among individuals. Thus, the present study examined the characteristics associated with good or insufficient responses to long-term treatment with LIT, VAL, or LMT for BD.

Methods

This study retrospectively analyzed the medical records of patients who visited an outpatient clinic with a diagnosis of BD I or II. Data from patients who were treated with one of three mood stabilizing medications (LIT, VAL, or LMT) for more than 6 months were selected, and the long-term treatment responses were evaluated using the Alda scale. For the purposes of this study, two response categories were formed: insufficient response (ISR), including non-response or poor response (Alda total score ≤ 6), and good response (GR; Alda total score ≥ 7).

Results

Of the 645 patients included in the present study, 172 were prescribed LIT, 320 were prescribed VAL, and 153 were prescribed LMT for at least 6 months. A binary logistic regression analysis revealed that a diagnosis of BD II (odds ratio [OR], 8.868; 95% confidence interval [CI], 1.123–70.046; p = 0.038), comorbid alcohol/substance use disorder (OR, 4.238; 95% CI, 1.154–15.566; p = 0.030), and a history of mixed episodes (OR, 4.363; 95% CI, 1.191–15.985; p = 0.026) were significant predictors of LIT-ISR. Additionally, a depressive-predominant polarity significantly predicted LMT-GR (OR, 8.586; 95% CI, 2.767–26.644; p < 0.001).

Conclusion

The present findings demonstrated that patients with a diagnosis of BD II, a comorbid alcohol/substance problem, or a history of mixed episodes were not likely to respond to LIT treatment. Additionally, LMT might be a better treatment choice for patients with a depressive-predominant polarity.

The link between bipolarity and substance use: A controlled clinic based study

OBJECTIVES

Because of high rates of co-occurrence, common familial risk, and phenotypic similarities, we conjectured that substance use and bipolar disorder might have a common substrate of origin in bipolarity and that they might lie on a continuum of bipolarity. Thus it was aimed to investigate the association between bipolarity and substance use through a controlled, clinic based study.

METHODS

Cross sectional assessment and comparison of bipolarity as trait in four groups, namely the substance use disorder (SUD), bipolar disorder (BPAD), dual diagnosis (DD), and the healthy control (HC) groups. Bipolar spectrum diagnostic scale (BSDS) was used. The quality of life in these four groups was also assessed using WHOQOL-Bref scale.

RESULTS

The mean Bipolar spectrum diagnostic scale (BSDS) score in SUD was 11.0 ± 5.3 which was more than that of HC (6.2 ± 3.9) and lesser than that in BPAD (18.4 ± 4.2) and DD (20.6 ± 3.6). Differences among all four groups were statistically significant. SUD group was found to have significantly higher score than healthy control. The BSDS score of DD and BPAD groups were higher than those of SUD but the difference between BPAD and DD was non-significant.

DISCUSSION

The results showed a potential association between substance dependence and bipolarity. Mood dysregulation appears to be the link between the two. The gradient of bipolarity detected by BSDS screener suggests a continuum model between substance use and bipolar disorder. However, this is a clinic based study and only male patients have been taken for study.

Prospective cohort study of early biosignatures of response to lithium in bipolar-I-disorders: overview of the H2020-funded R-LiNK initiative

Background

Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need.

Structure

The H2020-funded Response to Lithium Network (R-LiNK; http://www.r-link.eu.com/) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants’ response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence.

Conclusions

The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment.

Electronic supplementary material

The online version of this article (10.1186/s40345-019-0156-x) contains supplementary material, which is available to authorized users.

Bipolar disorder and the endocannabinoid system

OBJECTIVE

Bipolar disorder (BD) is a debilitating, lifelong neuropsychiatric illness characterised by unsteady mood states which vacillate from (hypo)mania to depression. Despite the availability of pharmaceutical agents which can be effective in ameliorating the acute affective symptoms and prevent episodic relapse, BD is inadequately treated in a subset of patients. The endocannabinoid system (ECS) is known to exert neuromodulatory effects on other neurotransmitter systems critical in governing emotions. Several studies ranging from clinical to molecular, as well as anecdotal evidence, have placed a spotlight on the potential role of the ECS in the pathophysiology of BD. In this perspective, we present advantages and disadvantages of cannabis use in the management of illness course of BD and provide mechanistic insights into how this system might contribute to the pathophysiology of BD.

RESULTS

We highlight the putative role of selective cannabinoid receptor 2 (CB2) agonists in BD and briefly discuss findings which provide a rationale for targeting the ECS to assuage the symptoms of BD. Further, data encourage basic and clinical studies to determine how cannabis and cannabinoids (CBs) can affect mood and to investigate emerging CB-based options as probable treatment approaches.

CONCLUSION

The probable role of the ECS has been almost neglected in BD; however, from data available which suggest a role of ECS in mood control, it is justified to support conducting comprehensive studies to determine whether ECS manipulation could positively affect BD. Based on the limited available data, we suggest that activation of CB2 may stabilise mood in this disorder.

A systematic review and meta-analysis of clinical predictors of lithium response in bipolar disorder

OBJECTIVE

To determine clinical predictors of lithium response in bipolar disorder.

METHODS

Systematic review of studies examining clinical predictors of lithium response was conducted. Meta-analyses were performed when ≥2 studies examined the same potential predictor.

RESULTS

A total of 71 studies, including over 12 000 patients, identified six predictors of good response: mania-depression-interval sequence [odds ratio (OR): 4.27; 95% CI: 2.61, 6.97; P < 0.001], absence of rapid cycling (OR for rapid cycling: 0.30; 95% CI: 0.17, 0.53; P < 0.001), absence of psychotic symptoms (OR for psychotic symptoms: 0.52; 95% CI: 0.34, 0.79; P = 0.002), family history of bipolar disorder (OR: 1.61; 95% CI: 1.03, 2.52; P = 0.036), shorter prelithium illness duration [standardised mean difference (SMD): -0.26; 95% CI: -0.41, -0.12; P < 0.001] and later age of onset (SMD: 0.17; 95% CI: 0.02, 0.36; P = 0.029). Additionally, higher body mass index was associated with poor response in two studies (SMD: -0.61; 95% CI: -0.90, -0.32; P < 0.001). There was weak evidence for number of episodes prior to lithium treatment (SMD: -0.42; 95% CI: -0.84, -0.01; P = 0.046), number of hospitalisations before lithium (SMD: -0.40; 95% CI: -0.81, 0.01; P = 0.055) and family history of lithium response (OR: 10.28; 95% CI: 0.66, 161.26; P = 0.097).

CONCLUSIONS

The relative importance of these clinical characteristics should be interpreted with caution because of potential biases and confounding.

Treatment of substance use disorders with co-occurring severe mental health disorders

PURPOSE OF REVIEW

To provide an update of treatment for substance use in patients with co-occurring substance use disorders (SUD) and mental health disorders (dual diagnosis) with a focus on both pharmacological and psychosocial interventions.

RECENT FINDINGS

A total of 1435 abstracts were identified, of which we selectively reviewed 43 for this narrative review. There is emerging evidence, both clinical and neurobiological, that clozapine is a more efficacious antipsychotic in treatment of individuals with schizophrenia and SUD. The use of depot atypical antipsychotic paliperidone palmitate in this population is also promising. Although valproate remains the treatment of choice in individuals with bipolar disorder and SUD, present evidence suggests that lithium and quetiapine may not be effective in this population. Naltrexone is the most effective anticraving agent in individuals with severe mental illness (SMI) and comorbid alcohol use disorders. The use of opioid substitution therapy in individuals with SMI and comorbid opioid use disorders is also associated with favorable outcomes. Varenicline shows promise in patients with SMI who smoke tobacco. Psychosocial interventions should be instituted early in the course of treatment. They should ideally be high intensity and based on established therapies used for SUD.

SUMMARY

The paucity of systematic studies in individuals with co-occurring mental health disorders and SUD remains a concern, given the enormous burden that they pose. However, there are a number of studies which have evaluated interventions, both psychosocial and pharmacological, which show promise and can guide clinical practice. VIDEO ABSTRACT: http://links.lww.com/YCO/A49.

Prediction of Response to Drug Therapy in Psychiatric Disorders

Reprinted with permission from Open Biol. 8: 180031. The Royal Society.

Comparing the effect of the novel ionic cocrystal of lithium salicylate proline (LISPRO) with lithium carbonate and lithium salicylate on memory and behavior in female APPswe/PS1dE9 Alzheimer's mice

Alzheimer's disease (AD) is characterized by progressive decline of cognition and associated neuropsychiatric signs including weight loss, anxiety, depression, agitation, and aggression, which is particularly pronounced in the female gender. Previously, we have shown that a novel ionic co-crystal of lithium salicylate proline (LISPRO) is an improved lithium formulation compared to the carbonate or salicylate form of lithium in terms of safety and efficacy in reducing AD pathology in Alzheimer's mice. The current study is designed to compare the prophylactic effects of LISPRO, lithium carbonate (LC), and lithium salicylate (LS) on cognitive and noncognitive impairments in female transgenic APPswe/PS1dE9 AD mice. Female APPswe/PS1dE9 mice at 4 months of age were orally treated with low-dose LISPRO, LS, or LC for 9 months at 2.25 mmol lithium/kg/day followed by determination of body weight, growth of internal organs, and cognitive and noncognitive behavior. No significant differences in body or internal organ weight, anxiety or locomotor activity were found between lithium treated and untreated APPswe/PS1dE9 cohorts. LISPRO, LC, and LS prevented spatial cognitive decline, as determined by Morris water maze and depression as determined by tail suspension test. In addition, LISPRO treatment was superior in preventing associative memory decline determined by contextual fear conditioning and reducing irritability determined by touch escape test in comparison with LC and LS. In conclusion, low-dose LISPRO, LC, and LS treatment prevent spatial cognitive decline and depression-like behavior, while LISPRO prevented hippocampal-dependent associative memory decline and irritability in APPswe/PS1dE9 mice.

Prediction of response to drug therapy in psychiatric disorders

Personalized medicine has become increasingly relevant to many medical fields, promising more efficient drug therapies and earlier intervention. The development of personalized medicine is coupled with the identification of biomarkers and classification algorithms that help predict the responses of different patients to different drugs. In the last 10 years, the Food and Drug Administration (FDA) has approved several genetically pre-screened drugs labelled as pharmacogenomics in the fields of oncology, pulmonary medicine, gastroenterology, haematology, neurology, rheumatology and even psychiatry. Clinicians have long cautioned that what may appear to be similar patient-reported symptoms may actually arise from different biological causes. With growing populations being diagnosed with different psychiatric conditions, it is critical for scientists and clinicians to develop precision medication tailored to individual conditions. Genome-wide association studies have highlighted the complicated nature of psychiatric disorders such as schizophrenia, bipolar disorder, major depression and autism spectrum disorder. Following these studies, association studies are needed to look for genomic markers of responsiveness to available drugs of individual patients within the population of a specific disorder. In addition to GWAS, the advent of new technologies such as brain imaging, cell reprogramming, sequencing and gene editing has given us the opportunity to look for more biomarkers that characterize a therapeutic response to a drug and to use all these biomarkers for determining treatment options. In this review, we discuss studies that were performed to find biomarkers of responsiveness to different available drugs for four brain disorders: bipolar disorder, schizophrenia, major depression and autism spectrum disorder. We provide recommendations for using an integrated method that will use available techniques for a better prediction of the most suitable drug.

Clinical factors associated with lithium treatment response in bipolar disorder patients from India

BACKGROUND

Bipolar Disorder (BD) is a chronic and disabling psychiatric illness with waxing and waning course. Lithium is the mainstay of treatment for Bipolar disorder (BD). There is limited literature on the clinical markers of Lithium treatment response from south Asia.

METHODS

Two hundred and ten individuals with BD I and a history of at least 6 months of treatment with Lithium were recruited from the outpatient services of the National Institute of Mental Health and Neurosciences (NIMHANS) after obtaining informed consent. A diagnosis of BD I was made according to the DSM-IV criteria. The characterization of response to lithium prophylaxis was done using NIMH Retrospective Life Chart and "Retrospective Criteria of Long Term Treatment Response in Research Subjects with Bipolar Disorder" scale.

RESULTS

There were 132 (62.86%) good responders and 78 (37.14%) non-responders. Good responders were noted to have less number of hospitalizations and more onset episode of depression than non-responders. Using continuous phenotype, Lithium response was inversely correlated with total number of episodes, number of episodes of mania/ depression, number of hospitalisations and presence of suicide attempt. Multivariate analysis only revealed number of episodes and hospitalization to be associated with Lithium response.

CONCLUSION

Our Lithium response rates were higher than what have been reported in the few previous studies. Illness severity was the only factor associated with Lithium response. There is a need to examine this question in larger prospective samples and to focus on biological/ molecular markers of treatment response.

The Role of Pharmacogenomics in Bipolar Disorder: Moving Towards Precision Medicine

Bipolar disorder (BD) is a common and disabling psychiatric condition with a severe socioeconomic impact. BD is treated with mood stabilizers, among which lithium represents the first-line treatment. Lithium alone or in combination is effective in 60% of chronically treated patients, but response remains heterogenous and a large number of patients require a change in therapy after several weeks or months. Many studies have so far tried to identify molecular and genetic markers that could help us to predict response to mood stabilizers or the risk for adverse drug reactions. Pharmacogenetic studies in BD have been for the most part focused on lithium, but the complexity and variability of the response phenotype, together with the unclear mechanism of action of lithium, limited the power of these studies to identify robust biomarkers. Recent pharmacogenomic studies on lithium response have provided promising findings, suggesting that the integration of genome-wide investigations with deep phenotyping, in silico analyses and machine learning could lead us closer to personalized treatments for BD. Nevertheless, to date none of the genes suggested by pharmacogenetic studies on mood stabilizers have been included in any of the genetic tests approved by the Food and Drug Administration (FDA) for drug efficacy. On the other hand, genetic information has been included in drug labels to test for the safety of carbamazepine and valproate. In this review, we will outline available studies investigating the pharmacogenetics and pharmacogenomics of lithium and other mood stabilizers, with a specific focus on the limitations of these studies and potential strategies to overcome them. We will also discuss FDA-approved pharmacogenetic tests for treatments commonly used in the management of BD.

The identification of biomarkers predicting acute and maintenance lithium treatment response in bipolar disorder: A plea for further research attention

The prediction of acute and maintenance lithium treatment response carries major clinical and neurobiological implications, warranting systematic review. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) compliant review searched major electronic databases from inception until December 2017 for studies documenting a clinical diagnosis of bipolar disorder (BD) made according to the mainstream diagnostic manuals and confirmed by a structured interview. Eligible studies allowed a quantitative comparison of endpoint vs baseline mean values of a given biomarker, regardless of the mood phase of patients with BD, and the disorder was assessed for severity using validated rating tool(s). Owing to the purposely applied stringent selection criteria, 16 acute and 12 maintenance studies could be included. The anticipated publication bias limited the chances of reportable generalizable findings, hindering a side-by-side comparison of different records across varying biomarkers and subsequent meta-analyses. The PRISMA approach was nonetheless preferred; it aimed at enhancing the homogeneity of the included results and minimizing the chances of "apples and oranges" with respect to the present research theme. The present critical review confirms the need for future research to specifically assess either pretreatment and/or posttreatment putative biomarkers of patients with BD and treated with lithium.

Predictors of recurrence during long-term treatment of bipolar I and II disorders. A 4 year prospective naturalistic study

BACKGROUND

Despite the large number of treatments available for bipolar disorder (BD), more than one half of patients have a recurrence within 2 years, and over 90% experience at least one additional affective episode during their lifetime.

METHODS

The aim of this study was to test the impact of a number of demographic and clinical features on the risk to recurrence in a real- word representative sample of 266 outpatients with BD-I or II treated in a naturalistic setting during a 4-years-follow-up period.

RESULTS

We found that the number of episodes per year after study entry, compared to the number of episodes per year before study entry,significantly decreased and that about one third of patients had no recurrences during the observation period. The length of follow-up and the number of previous episodes, mainly depressive, predicted the risk of recurrence, while female gender, higher age at intake, and a higher frequency of past mixed episodes predicted a higher frequency of recurrences.

LIMITATIONS

The study had some limitations to consider: i.e. the risk of poor reliability of information on the previous course of illness or the naturalistic treatment during the follow-up.

CONCLUSIONS

Our study suggests that (a) an evidence-based long-term treatment, with regular follow-up visits could improve the course of disease and prognosis; (b) clinicians should carefully consider the presence of a high number of mixed episodes, to provide more targeted treatment strategies; (c) an appropriate use of antidepressants in selected patients did not worsen the course of illness.

Distinct lithium-induced gene expression effects in lymphoblastoid cell lines from patients with bipolar disorder

Lithium is the most commonly prescribed medication for the treatment of bipolar disorder (BD), yet the mechanisms underlying its beneficial effects are still unclear. We aimed to compare the effects of lithium treatment in lymphoblastoid cell lines (LCLs) from BD patients and controls. LCLs were generated from sixty-two BD patients (based on DSM-IV) and seventeen healthy controls matched for age, sex, and ethnicity. Patients were recruited from outpatient clinics from February 2012 to October 2014. LCLs were treated with 1mM lithium for 7 days followed by microarray gene expression assay and validation by real-time quantitative PCR. Baseline differences between groups, as well as differences between vehicle- and lithium-treated cells within each group were analyzed. The biological significance of differentially expressed genes was examined by pathway enrichment analysis. No significant differences in baseline gene expression (adjusted p-value < 0.05) were detected between groups. Lithium treatment of LCLs from controls did not lead to any significant differences. However, lithium altered the expression of 236 genes in LCLs from patients; those genes were enriched for signaling pathways related to apoptosis. Among those genes, the alterations in the expression of PIK3CG, SERP1 and UPP1 were validated by real-time PCR. A significant correlation was also found between circadian functioning and CEBPG and FGF2 expression levels. In summary, our results suggest that lithium treatment induces expression changes in genes associated with the apoptosis pathway in BD LCLs. The more pronounced effects of lithium in patients compared to controls suggest a disease-specific effect of this drug.

Sociodemographic and Clinical Predictors of Response in Manic Episodes: A Naturalistic, Prospective, Cohort Study

BACKGROUND

Response to treatment of a manic episode is dependent on several sociodemographic and clinical factors as reported by researchers from other countries. The prescription of mood stabilizers and/or antipsychotics for manic episode depends on these factors. There is a lack of availability of data from India on this topic. Hence, this study was planned to identify the predictors of pharmacological response.

MATERIALS AND METHODS

Forty-two patients with a diagnosis of bipolar affective disorder current episode manic were enrolled and assessed for sociodemographic variables and clinical variables such as age of onset, family history, comorbidities, index episode, and number of past episodes. They were divided into four groups depending on the treatment they were receiving, namely, lithium with an antipsychotic (n = 25), lithium with divalproex and an antipsychotic (n = 8), divalproex with an antipsychotic (n = 5), and the miscellaneous group (n = 4). The primary outcome measure was improvement in the Young Mania Rating Scale score and secondary outcome measure was duration of ward stay.

RESULTS

There was a significant improvement in all the treatment modalities and it was comparable. There was no significant impact of any sociodemographic or clinical variable on treatment outcome except that females had significantly better response than males. There was nearly significant shorter duration of hospitalization in the lithium and antipsychotics groups compared to divalproex group.

CONCLUSION

All treatment modalities are equally efficacious in the management of manic episode in short term. However, lithium and antipsychotics tend to produce early response than divalproex. Other sociodemographic and clinical predictors were not significantly associated with response.

Childhood trauma and mixed episodes are associated with poor response to lithium in bipolar disorders

OBJECTIVES

Reliable predictors of response to lithium are still lacking in bipolar disorders (BDs). However, childhood trauma has been hypothesized to be associated with poor response to lithium.

METHODS

We included 148 patients with BD, euthymic when retrospectively and clinically assessed for response to lithium and childhood trauma using reliable scales.

RESULTS

According to the 'Alda scale', the sample consisted in 20.3% of excellent responders, 49.3% of partial responders and 30.4% of non-responders to lithium. A higher level of physical abuse significantly correlated with a lower level of response to lithium (P = 0.009). As compared to patients not exposed to any abuse, patients with at least two trauma abuses (emotional, physical or sexual) were more at risk of belonging to the non-responders group (OR = 4.91 95% CI (1.01-27.02)). Among investigated clinical variables, lifetime presence of mixed episodes and alcohol misuse were associated with non-response to lithium. Multivariate analyses demonstrated that physical abuse and mixed episodes were independently associated with poor response to lithium (P = 0.005 and P = 0.013 respectively).

CONCLUSIONS

Childhood physical abuse might be involved in a poor future response to lithium prophylaxis, this effect being independent of the association between clinical expression of BD and poor response to lithium.

Cross-validation of clinical characteristics and treatment patterns associated with phenotypes for lithium response defined by the Alda scale

BACKGROUND

It is increasingly recognised that reliable and valid assessments of lithium response are needed in order to target more efficiently the use of this medication in bipolar disorders (BD) and to identify genotypes, endophenotypes and biomarkers of response.

METHODS

In a large, multi-centre, clinically representative sample of 300 cases of BD, we assess external clinical validators of lithium response phenotypes as defined using three different recommended approaches to scoring the Alda lithium response scale. The scale comprises an A scale (rating lithium response) and a B scale (assessing confounders).

RESULTS

Analysis of the two continuous scoring methods (A scale score minus the B scale score, or A scale score in those with a low B scale score) demonstrated that 21-23% of the explained variance in lithium response was accounted for by a positive family history of BD I and the early introduction of lithium. Categorical definitions of response suggest poor response is also associated with a positive history of alcohol and/or substance use comorbidities. High B scale scores were significantly associated with longer duration of illness prior to receiving lithium and the presence of psychotic symptoms.

LIMITATIONS

The original sample was not recruited specifically to study lithium response. The Alda scale is designed to assess response retrospectively.

CONCLUSIONS

This cross-validation study identifies different clinical phenotypes of lithium response when defined by continuous or categorical measures. Future clinical, genetic and biomarker studies should report both the findings and the method employed to assess lithium response according to the Alda scale.