Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report

Phenotypic clustering of bipolar disorder supports stratification by lithium responsiveness over diagnostic subtypes

INTRODUCTION

The aim of this study was to determine whether the clinical profiles of bipolar disorder (BD) patients could be differentiated more clearly using the existing classification by diagnostic subtype or by lithium treatment responsiveness.

METHODS

We included adult patients with BD-I or II (N = 477 across four sites) who were treated with lithium as their principal mood stabilizer for at least 1 year. Treatment responsiveness was defined using the dichotomized Alda score. We performed hierarchical clustering on phenotypes defined by 40 features, covering demographics, clinical course, family history, suicide behaviour, and comorbid conditions. We then measured the amount of information that inferred clusters carried about (A) BD subtype and (B) lithium responsiveness using adjusted mutual information (AMI) scores. Detailed phenotypic profiles across clusters were then evaluated with univariate comparisons.

RESULTS

Two clusters were identified (n = 56 and n = 421), which captured significantly more information about lithium responsiveness (AMI range: 0.033 to 0.133) than BD subtype (AMI: 0.004 to 0.011). The smaller cluster had disproportionately more lithium responders (n = 47 [83.8%]) when compared to the larger cluster (103 [24.4%]; p = 0.006).

CONCLUSIONS

Phenotypes derived from detailed clinical data may carry more information about lithium responsiveness than the current classification of diagnostic subtype. These findings support lithium responsiveness as a valid approach to stratification in clinical samples.

Exploring the genetics of lithium response in bipolar disorders

BACKGROUND

Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II.

RESULTS

We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism.

CONCLUSIONS

Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Akt and AMPK activators rescue hyperexcitability in neurons from patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is a multifactorial psychiatric illness affecting ∼1% of the global adult population. Lithium (Li), is the most effective mood stabilizer for BD but works only for a subset of patients and its mechanism of action remains largely elusive.

METHODS

In the present study, we used iPSC-derived neurons from patients with BD who are responsive (LR) or not (LNR) to lithium. Combined electrophysiology, calcium imaging, biochemistry, transcriptomics, and phosphoproteomics were employed to provide mechanistic insights into neuronal hyperactivity in BD, investigate Li's mode of action, and identify alternative treatment strategies.

FINDINGS

We show a selective rescue of the neuronal hyperactivity phenotype by Li in LR neurons, correlated with changes to Na+ conductance. Whole transcriptome sequencing in BD neurons revealed altered gene expression pathways related to glutamate transmission, alterations in cell signalling and ion transport/channel activity. We found altered Akt signalling as a potential therapeutic effect of Li in LR neurons from patients with BD, and that Akt activation mimics Li effect in LR neurons. Furthermore, the increased neural network activity observed in both LR & LNR neurons from patients with BD were reversed by AMP-activated protein kinase (AMPK) activation.

INTERPRETATION

These results suggest potential for new treatment strategies in BD, such as Akt activators in LR cases, and the use of AMPK activators for LNR patients with BD.

FUNDING

Supported by funding from ERA PerMed, Bell Brain Canada Mental Research Program and Brain & Behavior Research Foundation.

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.

A pilot study examining the impact of lithium treatment and responsiveness on mnemonic discrimination in bipolar disorder

INTRODUCTION

Mnemonic discrimination (MD), the ability to discriminate new stimuli from similar memories, putatively involves dentate gyrus pattern separation. Since lithium may normalize dentate gyrus functioning in lithium-responsive bipolar disorder (BD), we hypothesized that lithium treatment would be associated with better MD in lithium-responsive BD patients.

METHODS

BD patients (N = 69; NResponders = 16 [23 %]) performed the Continuous Visual Memory Test (CVMT), which requires discriminating between novel and previously seen images. Before testing, all patients had prophylactic lithium responsiveness assessed over ≥1 year of therapy (with the Alda Score), although only thirty-eight patients were actively prescribed lithium at time of testing (55 %; 12/16 responders, 26/53 nonresponders). We then used computational modelling to extract patient-specific MD indices. Linear models were used to test how (A) lithium treatment, (B) lithium responsiveness via the continuous Alda score, and (C) their interaction, affected MD.

RESULTS

Superior MD performance was associated with lithium treatment exclusively in lithium-responsive patients (Lithium x AldaScore β = 0.257 [SE 0.078], p = 0.002). Consistent with prior literature, increased age was associated with worse MD (β = -0.03 [SE 0.01], p = 0.005).

LIMITATIONS

Secondary pilot analysis of retrospectively collected data in a cross-sectional design limits generalizability.

CONCLUSION

Our study is the first to examine MD performance in BD. Lithium is associated with better MD performance only in lithium responders, potentially due to lithium's effects on dentate gyrus granule cell excitability. Our results may influence the development of behavioural probes for dentate gyrus neuronal hyperexcitability in BD.

Longitudinal studies of bipolar patients and their families: translating findings to advance individualized risk prediction, treatment and research

BACKGROUND

Bipolar disorder is a broad diagnostic construct associated with significant phenotypic and genetic heterogeneity challenging progress in clinical practice and discovery research. Prospective studies of well-characterized patients and their family members have identified lithium responsive (LiR) and lithium non-responsive (LiNR) subtypes that hold promise for advancement.

METHOD

In this narrative review, relevant observations from published longitudinal studies of well-characterized bipolar patients and their families spanning six decades are highlighted. DSM diagnoses based on SADS-L interviews were decided in blind consensus reviews by expert clinicians. Genetic, neurobiological, and psychosocial factors were investigated in subsets of well-characterized probands and adult relatives. Systematic maintenance trials of lithium, antipsychotics, and lamotrigine were carried out. Clinical profiles that included detailed histories of the clinical course, symptom sets and disorders segregating in families were documented. Offspring of LiR and LiNR families were repeatedly assessed up to 20 years using KSADS-PL format interviews and DSM diagnoses and sub-threshold symptoms were decided by expert clinicians in blind consensus reviews using all available clinical and research data.

RESULTS

A characteristic clinical profile differentiated bipolar patients who responded to lithium stabilization from those who did not. The LiR subtype was characterized by a recurrent fully remitting course predominated by depressive episodes and a positive family history of episodic remitting mood disorders, and not schizophrenia. Response to lithium clustered in families and the characteristic clinical profile predicted lithium response, with the episodic remitting course being a strong correlate. There is accumulating evidence that genetic and neurobiological markers differ between LiR and LiNR subtypes. Further, offspring of bipolar parents subdivided by lithium response differed in developmental history, clinical antecedents and early course of mood disorders. Moreover, the nature of the emergent course bred true from parent to offspring, independent of the nature of emergent psychopathology.

CONCLUSIONS

Bipolar disorders are heterogeneous and response to long-term lithium is associated with a familial subtype with characteristic course, treatment response, family history and likely pathogenesis. Incorporating distinctive clinical profiles that index valid bipolar subtypes into routine practice and research will improve patient outcomes and advance the development and translation of novel treatment targets to improve prevention and early intervention.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we performed an exploratory study of the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. Overall, we observed relatively weak associations (p < 1 × 10-4) with BP phenotypes within immune-related genes. Network and functional enrichment analyses of the top findings from the association analyses of Li response variables showed an overrepresentation of pathways participating in cell adhesion and intercellular communication. These appeared to converge on the well-known Li-induced inhibition of GSK-3β. Association analyses of age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation suggested modest contributions of genes such as RTN4, XKR4, NRXN1, NRG1/3 and GRK5 to disease characteristics. PGS analyses returned weak associations (p < 0.05) between inflammation markers and the studied BP phenotypes. Our results suggest a modest relationship between immunity and clinical features in BP. More research is needed to assess the potential therapeutic relevance.

How effective are mood stabilizers in treating bipolar patients comorbid with cPTSD? Results from an observational study

BACKGROUND

Multiple traumatic experiences, particularly in childhood, may predict and be a risk factor for the development of complex post-traumatic stress disorder (cPTSD). Unfortunately, individuals with bipolar disorder (BP) are more likely to have suffered traumatic events than the general population. Consequently, cPTSD could be comorbid with BD, and this may negatively affect psychopathological manifestations. To date, no one has explored whether such comorbidity also affects the response to treatment with mood stabilizers in BD patients.

RESULTS

Here, a cross-sectional study was carried out by comparing the response to treatment, measured by the Alda scale, in a cohort of 344 patients diagnosed with BD type I and II, screened for the presence (or absence) of cPTSD using the International Trauma Questionnaire. The main result that emerged from the present study is the poorer response to mood stabilizers in BD patients with comorbid cPTSD compared with BD patients without cPTSD.

CONCLUSIONS

The results collected suggest the need for an add-on therapy focused on trauma in BD patients. This could represent an area of future interest in clinical research, capable of leading to more precise and quicker diagnoses as well as suggesting better tailored and more effective treatments.

Effectiveness of ultra-long-term lithium treatment: relevant factors and case series

BACKGROUND

The phenomenon of preventing the recurrences of mood disorders by the long-term lithium administration was discovered sixty years ago. Such a property of lithium has been unequivocally confirmed in subsequent years, and the procedure makes nowadays the gold standard for the pharmacological prophylaxis of bipolar disorder (BD). The efficacy of lithium prophylaxis surpasses other mood stabilizers, and the drug has the longest record as far as the duration of its administration is concerned. The continuation of lithium administration in case of good response could be a lifetime and last for several decades. The stability of lithium prophylactic efficacy in most patients is pretty steady. However, resuming lithium after its discontinuation may, in some patients, be less efficient.

MAIN BODY

In the article, the clinical and biological factors connected with the prophylactic efficacy of long-term lithium administration are listed. Next, the adverse and beneficial side effects of such longitudinal treatment are presented. The main problems of long-term lithium therapy, which could make an obstacle to lithium continuation, are connected with lithium's adverse effects on the kidney and, to lesser extent, on thyroid and parathyroid functions. In the paper, the management of these adversities is proposed. Finally, the case reports of three patients who have completed 50 years of lithium therapy are described.

CONCLUSIONS

The authors of the paper reckon that in the case of good response, lithium can be given indefinitely. Given the appropriate candidates for such therapy and successful management of the adverse effects, ultra-long term lithium therapy is possible and beneficial for such patients.

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.

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.

Exploring the genetics of lithium response in bipolar disorders

Background

Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II.

Results

We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism.

Conclusions

Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.

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 2,039 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.

Chronotype is associated with affective temperaments, clinical severity and worse treatment outcomes in bipolar disorders: results from a two-center, cross-sectional study

OBJECTIVE

The present study was aimed at investigating the clinical correlates of evening chronotype in a population of subjects suffering from bipolar disorders (BD).

METHODS

We assessed chronotype using the Morningness-Eveningness Questionnaire. We administered the brief Temperament Evaluation of Memphis, Pisa, and San Diego, the Barratt Impulsiveness Scale, and the Alda Scale to evaluate affective temperaments, impulsiveness, and response to mood stabilisers. We performed bivariate analyses and ran a logistic regression model to analyse clinical variables associated with evening chronotype.

RESULTS

In our sample (n = 178), subjects with an evening chronotype (n = 56, 31.5%) more often suffered from BD type I and reported higher prevalence of seasonality, antidepressant-induced mood switches, psychotic, aggressive, mixed, and anxiety features, and substance use disorders. The number of lifetime suicide attempts and mood episodes was higher in this subgroup. Depressive, cyclothymic, irritable, and anxious temperament scores were higher among evening-chronotype subjects, who also displayed greater levels of impulsiveness and worse treatment response. At the logistic regression, evening chronotype was associated with depressive and irritable temperaments.

CONCLUSIONS

Subjects with evening chronotype display higher clinical severity and worse BD course. Clinicians should evaluate the presence of evening chronotype in BD subjects, especially in those with irritable or depressive temperament.Key pointsEvening chronotype is a frequent clinical feature in subjects suffering from bipolar disorders (BD);Affective temperaments, particularly depressive and irritable, are associated with evening chronotype in BD;Evening chronotype underpins higher severity of the clinical picture in BD, as well as a worse response to mood stabiliser treatment;Circadian preferences should be systematically assessed in subjects suffering from BD, with particular attention to evening preference.

Differential characteristics of bipolar I and II disorders: a retrospective, cross-sectional evaluation of clinical features, illness course, and response to treatment

BACKGROUND

The distinction between bipolar I and bipolar II disorder and its treatment implications have been a matter of ongoing debate. The aim of this study was to examine differences between patients with bipolar I and II disorders with particular emphasis on the early phases of the disorders.

METHODS

808 subjects diagnosed with bipolar I (N = 587) or bipolar II disorder (N = 221) according to DSM-IV criteria were recruited between April 1994 and March 2022 from tertiary-level mood disorder clinics. Sociodemographic and clinical variables concerning psychiatric and medical comorbidities, family history, illness course, suicidal behavior, and response to treatment were compared between the bipolar disorder types.

RESULTS

Bipolar II disorder patients were more frequently women, older, married or widowed. Bipolar II disorder was associated with later "bipolar" presentation, higher age at first (hypo)mania and treatment, less frequent referral after a single episode, and more episodes before lithium treatment. A higher proportion of first-degree relatives of bipolar II patients were affected by major depression and anxiety disorders. The course of bipolar II disorder was typically characterized by depressive onset, early depressive episodes, multiple depressive recurrences, and depressive predominant polarity; less often by (hypo)mania or (hypo)mania-depression cycles at onset or during the early course. The lifetime clinical course was more frequently rated as chronic fluctuating than episodic. More patients with bipolar II disorder had a history of rapid cycling and/or high number of episodes. Mood stabilizers and antipsychotics were prescribed less frequently during the early course of bipolar II disorder, while antidepressants were more common. We found no differences in global functioning, lifetime suicide attempts, family history of suicide, age at onset of mood disorders and depressive episodes, and lithium response.

CONCLUSIONS

Differences between bipolar I and II disorders are not limited to the severity of (hypo)manic syndromes but include patterns of clinical course and family history. Caution in the use of potentially mood-destabilizing agents is warranted during the early course of bipolar II disorder.

The role of pharmacogenomics in precision psychiatry

The field of psychiatry is facing an important paradigm shift in the provision of clinical care and mental health service organization toward personalization and integration of multimodal data science. This approach, termed precision psychiatry, aims at identifying subgroups of patients more prone to the development of a certain phenotype, such as symptoms or severe mental disorders (risk detection), and/or to guide treatment selection. Pharmacogenomics and computational psychiatry are two fundamental tools of precision psychiatry, which have seen increasing levels of integration in clinical settings. Here we present a brief overview of these two applications of precision psychiatry in clinical settings.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers

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

Comparing measurements of lithium treatment efficacy in people with bipolar disorder: systematic review and meta-analysis

Background

Lithium has long been recognised as an effective treatment for bipolar disorder. Its relative efficacy has been measured with a diverse range of clinical outcomes, resulting in differences in efficacy reporting that have not been systematically reviewed.

Aims

We aimed to identify and compare the various measures of lithium efficacy employed in interventional studies for people with bipolar disorder.

Method

Database (PubMed, Web of Science) and hand searches were performed to identify studies that assessed a clinical response in patients with bipolar disorder who received lithium, up to the end of 2021. We included primary human interventional studies without excluding specific study designs, bipolar disorder subtypes, duration or dosage of lithium treatment. Continuous outcome effects were meta-analysed; binary outcomes were synthesised visually and narratively. The Cochrane risk-of-bias tool was used to assess study-level risk of bias.

Results

Seventy-one studies were included (N = 30 542 ). Approximately two-thirds of participants attained a clinically significant improvement in manic or depressive symptoms, and over 50% achieved remission. About a third required hospital admission (study length 2–12 years) and around 50% needed further treatment to stay well or had recurrence of symptoms; the latter two outcomes tended to be assessed over long-term maintenance periods.

Conclusions

An abundance of measurements have been used to assess lithium's clinical effects, across several study designs. Despite the resultant high heterogeneity, an overall picture of lithium's effects emerges that supports previous literature; between half and two-thirds of patients respond well to lithium across varying outcome measures, baseline mood states, study durations and bipolar disorder subtypes.

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

BACKGROUND

Response 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.

METHODS

We 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.

RESULTS

Polarity 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).

CONCLUSIONS

Combining clinical predictors and DNA methylation markers of Li response may have greater utility in clinical practice than relying on clinical characteristics alone.

Ancestry component as a major predictor of lithium response in the treatment of bipolar disorder

BACKGROUND

Bipolar Disorder (BD) represents the seventh major cause of disability life-years-adjusted. Lithium remains as a first-line treatment, but clinical improvement occurs only in 30 % of treated patients. Studies suggest that genetics plays a major role in shaping the individual response of BD patients to lithium.

METHODS

We used machine-learning techniques (Advance Recursive Partitioned Analysis, ARPA) to build a personalized prediction framework of BD lithium response using biological, clinical, and demographical data. Using the Alda scale, we classified 172 BD I-II patients as responders or non-responders to lithium treatment. ARPA methods were used to build individual prediction frameworks and to define variable importance. Two predictive models were evaluated: 1) demographic and clinical data, and 2) demographic, clinical and ancestry data. Model performance was assessed using Receiver Operating Characteristic (ROC) curves.

RESULTS

The predictive model including ancestry yield the best performance (sensibility = 84.6 %, specificity = 93.8 % and AUC = 89.2 %) compared to the model without ancestry (sensibility = 50 %, Specificity = 94.5 %, and AUC = 72.2 %). This ancestry component best predicted lithium individual response. Clinical variables such as disease duration, the number of depressive episodes, the total number of affective episodes, and the number of manic episodes were also important predictors.

CONCLUSION

Ancestry component is a major predictor and significantly improves the definition of individual Lithium response in BD patients. We provide classification trees with potential bench application in the clinical setting. While this prediction framework might be applied in specific populations, the used methodology might be of general use in precision and translational medicine.

Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using a support vector machine classifier

AIM

Bipolar disorder (BD) is a mood disorder with a high morbidity and death rate. Lithium (Li), a prominent mood stabilizer, is often used as a first-line treatment. However, clinical studies have shown that Li is fully effective in roughly 30% of BD patients. Our goal in this study was to use features derived from information theory to improve the prediction of the patient's response to Li as well as develop a diagnostic algorithm for the disorder.

METHODS

We have performed electrophysiological recordings in patient-derived dentate gyrus (DG) granule neurons (from a total of 9 subjects) for three groups: 3 control individuals, 3 BD patients who respond to Li treatment (LR), and 3 BD patients who do not respond to Li treatment (NR). The recordings were analyzed by the statistical tools of modern information theory. We used a Support Vector Machine (SVM) and Random forest (RF) classifiers with the basic electrophysiological features with additional information theory features.

RESULTS

Information theory features provided further knowledge about the distribution of the electrophysiological entities and the interactions between the different features, which improved classification schemes. These newly added features significantly improved our ability to distinguish the BD patients from the control individuals (an improvement from 60% to 74% accuracy) and LR from NR patients (an improvement from 81% to 99% accuracy).

CONCLUSION

The addition of Information theory-derived features provides further knowledge about the distribution of the parameters and their interactions, thus significantly improving the ability to discriminate and predict the LRs from the NRs and the patients from the controls.

Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.

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.

Analysis on in vitro effect of lithium on telomere length in lymphoblastoid cell lines from bipolar disorder patients with different clinical response to long-term lithium treatment

Background

It has been suggested that bipolar disorder (BD) is associated with clinical and biological features of accelerated aging. In our previous studies, we showed that long-term lithium treatment was correlated with longer leukocyte telomere length (LTL) in BD patients. A recent study explored the role of TL in BD using patients-derived lymphoblastoid cell lines (LCLs), showing that baseline TL was shorter in BD compared to controls and that lithium in vitro increased TL but only in BD. Here, we used the same cell system (LCLs) to explore if a 7-day treatment protocol with lithium chloride (LiCl) 1 mM was able to highlight differences in TL between BD patients clinically responders (Li-R; n = 15) or non-responders (Li-NR; n = 15) to lithium, and if BD differed from non-psychiatric controls (HC; n = 15).

Results

There was no difference in TL between BD patients and HC. Moreover, LiCl did not influence TL in the overall sample, and there was no difference between diagnostic or clinical response groups. Likewise, LiCl did not affect TL in neural precursor cells from healthy donors.

Conclusions

Our findings suggest that a 7-day lithium treatment protocol and the use of LCLs might not represent a suitable approach to deepen our understanding on the role of altered telomere dynamics in BD as previously suggested by studies in vivo.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-022-00418-8.

An ecological study of objective rest-activity markers of lithium response in bipolar-I-disorder

BACKGROUND

Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest-activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR).

METHODS

Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR).

RESULTS

Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06).

CONCLUSIONS

To our knowledge, this is the largest actigraphy study of rest-activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.

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.

Encore: Behavioural animal models of stress, depression and mood disorders

Animal studies over the past two decades have led to extensive advances in our understanding of pathogenesis of depressive and mood disorders. Among these, rodent behavioural models proved to be of highest informative value. Here, we present a comprehensive overview of the most popular behavioural models with respect to physiological, circuit, and molecular biological correlates. Behavioural stress paradigms and behavioural tests are assessed in terms of outcomes, strengths, weaknesses, and translational value, especially in the domain of pharmacological studies.

Circulating miRNAs as Potential Biomarkers for Patient Stratification in Bipolar Disorder: A Combined Review and Data Mining Approach

Bipolar disorder is a debilitating psychiatric condition that is shaped in a concerted interplay between hereditary and triggering risk factors. Profound depression and mania define the disorder, but high clinical heterogeneity among patients complicates diagnosis as well as pharmacological intervention. Identification of peripheral biomarkers that capture the genomic response to the exposome may thus progress the development of personalized treatment. MicroRNAs (miRNAs) play a prominent role in of post-transcriptional gene regulation in the context of brain development and mental health. They are coordinately modulated by multifarious effectors, and alteration in their expression profile has been reported in a variety of psychiatric conditions. Intriguingly, miRNAs can be released from CNS cells and enter circulatory bio-fluids where they remain remarkably stable. Hence, peripheral circulatory miRNAs may act as bio-indicators for the combination of genetic risk, environmental exposure, and/or treatment response. Here we provide a comprehensive literature search and data mining approach that summarize current experimental evidence supporting the applicability of miRNAs for patient stratification in bipolar disorder.

Is Poor Lithium Response in Individuals with Bipolar Disorder Associated with Increased Degradation of Tryptophan along the Kynurenine Pathway? Results of an Exploratory Study

Bipolar disorder is associated with an inflammation-triggered elevated catabolism of tryptophan to the kynurenine pathway, which impacts psychiatric symptoms and outcomes. The data indicate that lithium exerts anti-inflammatory effects by inhibiting indoleamine-2,3-dioxygenase (IDO)-1 activity. This exploratory study aimed to investigate the tryptophan catabolism in individuals with bipolar disorder (n = 48) compared to healthy controls (n = 48), and the associations with the response to mood stabilizers such as lithium, valproate, or lamotrigine rated with the Retrospective Assessment of the Lithium Response Phenotype Scale (or the Alda scale). The results demonstrate an association of a poorer response to lithium with higher levels of kynurenine, kynurenine/tryptophan ratio as a proxy for IDO-1 activity, as well as quinolinic acid, which, overall, indicates a pro-inflammatory state with a higher degradation of tryptophan towards the neurotoxic branch. The treatment response to valproate and lamotrigine was not associated with the levels of the tryptophan metabolites. These findings support the anti-inflammatory properties of lithium. Furthermore, since quinolinic acid has neurotoxic features via the glutamatergic pathway, they also strengthen the assumption that the clinical drug response might be associated with biochemical processes. The relationship between the lithium response and the measurements of the tryptophan to the kynurenine pathway is of clinical relevance and may potentially bring advantages towards a personalized medicine approach to bipolar disorder that allows for the selection of the most effective mood-stabilizing drug.

Genetic polymorphisms influencing response to lithium in early-onset Bipolar disorder from south India

OBJECTIVES

Early-onset Bipolar disorder (EOBD), has a more malignant course with high recurrence risk and there is a need for population-specific pharmaco-genomic study.

METHODS

This study is a prospective and retrospective observational study. Both newly diagnosed patients and those on follow-up with a diagnosis of bipolar I disorder with onset before 18 years of age and on lithium prophylaxis as part of treatment-as-usual were recruited for the study. Response to treatment was assessed at the end of two years follow up using ALDA scale. Ten single nucleotide polymorphisms associated with treatment response based on previous studies were chosen for analysis.

RESULTS

Of 162 who had EOBD, sixty-four fulfilled inclusion criteria and fifty-seven completed the study. TT and TG genotypes of rs75222709 on AL157359.3 gene were found to be significantly different between non-responders(N = 43) and healthy controls (N = 220). The frequency of the GA genotype of the single nucleotide polymorphism rs17204573 of the RORA (Retinoic Acid related orphan receptor alpha) gene was significantly lower among subjects (27.3%, N = 54) as compared to controls (42.9%, OR:0.5, CI: 0.26-0.96, p value 0.035). However, the significance of both disappeared after Bonferroni correction. Among clinical factors female gender was significantly associated with lithium non-response.

CONCLUSION

Although conducting pharmaco-genomic studies with large sample size is a challenge for low and middle-income countries, future studies can help improve the long-term outcome of youth with EOBD.

Substance use disorders in bipolar disorders: Clinical correlates and treatment response to mood stabilizers

BACKGROUND

Substance use disorders (SUD) in bipolar disorders (BD) present relevant impact on psychopathological features and illness course. The present study was aimed at analyzing the clinical correlates of this comorbidity.

METHODS

In- and outpatients suffering from BD were recruited. Socio-demographic and clinical characteristics were collected. Subjects underwent a psychopathological assessment evaluating affective temperaments and impulsiveness. The appraisal of treatment response to mood stabilizers was conducted with the Alda Scale. Bivariate analyses were used to compare subjects suffering from BD with (SUD-BD) or without comorbid SUD (nSUD-BD) (p<0.05). A logistic regression model was performed to identify specific correlates of SUD in BD.

RESULTS

Among the 161 included subjects, 63 (39.1%) were diagnosed with comorbid SUD. SUD-BD subjects showed younger age at onset (p = 0.003) and higher prevalence of BD type I diagnosis (BDI) (p<0.001). Furthermore, lifetime mixed features (p<0.001), psychotic symptoms (p<0.001), suicide attempts (p = 0.002), aggression (p = 0.003), antidepressant-induced manic switch (p = 0.003), and poor treatment response (p<0.001) were more frequent in the SUD-BD subgroup. At the logistic regression, SUD revealed a positive association with BD type I diagnosis (Odds Ratio (OR) 4.77, 95% CI 1.66-13.71, p = 0.004) and mixed features (OR 2.54, 95% CI 1.17-5.53, p = 0.019).

LIMITATIONS

The cross-sectional study design and the relatively small sample size may limit the generalizability of the findings. The retrospective evaluation of comorbid SUD could have biased the outcome assessment.

CONCLUSIONS

Subjects with BD and SUD are characterized by higher clinical severity and require careful assessment of treatment response.

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.

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

INTRODUCTION

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).

METHODS

Thirty-four subjects with BD who had been taking lithium for ≥2 years 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 (10 µg) and change in protein expression was determined using Western blot.

RESULTS

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 5 min 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%) 5 mins post-insulin in non-responders.

CONCLUSIONS

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.

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.

Mitochondrial DNA Copy Number Is Associated With Treatment Response and Cognitive Function in Euthymic Bipolar Patients Receiving Valproate

BACKGROUND

Bipolar disorder (BD) is associated with cognitive impairment and mitochondrial dysfunction. However, the associations among mitochondrial DNA copy number (MCN), treatment response, and cognitive function remain elusive in BD patients.

METHODS

Sixty euthymic BD patients receiving valproate (VPA) and 66 healthy controls from the community were recruited. The indices of metabolic syndrome (MetS) were measured. Quantitative polymerase chain reaction analysis of blood leukocytes was used to measure the MCN. Cognitive function was measured by calculating perseverative errors and completed categories on the Wisconsin Card Sorting Test (WCST). The VPA treatment response was measured using the Alda scale.

RESULTS

BD patients had significantly higher MCN, triglyceride, and C-reactive protein (CRP) levels, waist circumference, and worse performance on the WCST than the controls. Regression models showed that BD itself and the VPA concentration exerted significant effects on increased MCN levels. Moreover, the receiver operating characteristic curve analysis showed that an MCN of 2.05 distinguished VPA responders from nonresponders, with an area under the curve of 0.705 and a sensitivity and specificity of 0.529 and 0.816, respectively. An MCN level ≥2.05 was associated with 5.39 higher odds of being a VPA responder (P = .006). BD patients who were stratified into the high-MCN group had a higher VPA response rate, better WCST performance, lower CRP level, and less MetS.

CONCLUSIONS

The study suggests a link between the peripheral MCN and cognitive function in BD patients. As an inflammatory status, MetS might modulate this association.

Sex Differences in Bipolar Disorders: Impact on Psychopathological Features and Treatment Response

INTRODUCTION

Sex differences were demonstrated in bipolar disorders (BD) concerning epidemiological, clinical, and psychopathological characteristics, but consensus is lacking. Moreover, data concerning the influence of sex on treatment response in BD is contrasting. The present cross-sectional study aimed to analyze sex differences in a population of BD subjects, with specific focus on psychopathological features and treatment response.

MATERIALS AND METHODS

Subjects diagnosed with BD according to the Diagnostic and Statistical Manual of Mental Disorders, 5th version (DSM-5) were recruited. Socio-demographic and clinical characteristics were collected. The Hamilton Rating Scale for Depression, the Mania Rating Scale (MRS), the brief version of the Temperament Evaluation of Memphis, Pisa and San Diego-Münster version (briefTEMPS-M), and the Barratt Impulsiveness Scale-11 items (BIS-11) were used for psychopathological assessment. Treatment response was appraised with the Alda Scale. We performed bivariate analyses to compare socio-demographic, clinical, and psychopathological characteristics between men and women (p < 0.05). A logistic regression was run to analyze features that were significantly associated with female sex.

RESULTS

Among the recruited 219 BD subjects, 119 (54.3%) were females. Women had a lower scholarity (p = 0.015) and were less frequently employed (p = 0.001). As for psychopathological features, a higher MRS total score (p < 0.001) was detected among women, as well as higher BIS-11 total score (p = 0.040), and briefTEMPS-M score for anxious temperament (p = 0.006). Men showed higher prevalence of DSM-5 mixed features (p = 0.025), particularly during a depressive episode (p = 0.014). Women reported longer duration of untreated illness (DUI) (p < 0.001). There were no sex differences in the Alda Scale total score when considering the whole sample, but this was significantly higher among men (p = 0.030) when evaluating subjects treated with anticonvulsants. At the logistic regression, female sex was positively associated with longer DUI (p < 0.001; OR 1.106, 95% CI 1.050-1.165) and higher MRS total score (p < 0.001; OR 1.085, 95% CI 1.044-1.128) and negatively associated with employment (p = 0.003; OR 0.359, 95% CI 0.185-0.698) and DSM-5 mixed features (p = 0.006; OR 0.391, 95% CI 0.200-0.762).

CONCLUSIONS

The clinical presentation of BD may differ depending on sex. The severity of BD should not be neglected among women, who may also display worse treatment response to anticonvulsants.

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.

Association study of BDNF Val66Met gene polymorphism with bipolar disorder and lithium treatment response in Indian population

BACKGROUND

The association of the Val66Met (rs6265) polymorphism in the brain-derived neurotrophic factor (BDNF) gene with bipolar disorder (BD) and response to lithium treatment has been suggested, though inconsistently. The considerable diversity of allele frequency across different populations contributes to this. There is no data from South Asia till date. Hence, we examined the association of this polymorphism in BD cases from India, and its association with lithium treatment response.

METHODS

BD patients (N = 301) were recruited from the clinical services of National Institute of Mental Health and Neurosciences (NIMHANS), India. Lithium treatment response for 190 BD subjects was assessed using Alda scale by NIMH life charts. Patients with total score ⩾7 were defined as lithium responders (N = 115) and patients with score <7 were defined as lithium non-responders (N = 75). Healthy controls (N = 484) with no lifetime history of neuropsychiatric illness or a family history of mental illness were recruited as control set. Genotyping was performed by TaqMan genotyping assay.

RESULTS

Genotype and allele frequency of BDNF Val66Met SNP was significantly different (χ2 = 7.78, p = 0.02) in cases compared to controls, and the Val(G) allele was more frequent (χ2 = 7.08, p = 0.008) in BD patients. However, no significant difference is noted in genotype or allele frequencies of this polymorphism between the lithium responders and non-responders.

CONCLUSIONS

The Val(G) allele of BDNF Val66Met polymorphism is associated with risk of BD in this sample, but it is not related to response to lithium.

Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi⁺Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

Long-term lithium therapy and risk of chronic kidney disease in bipolar disorder: A historical cohort study

AIMS

Long-term lithium therapy (LTLT) has been associated with kidney insufficiency in bipolar disorder (BD). We aimed to investigate the risk factors of chronic kidney disease (CKD) development and progression among BD patients receiving LTLT.

METHODS

We included adult patients with BD on LTLT (≥1 year) who were enrolled in the Mayo Clinic Bipolar Biobank, Rochester, Minnesota. We reviewed electronic medical records to extract information related to lithium therapy and kidney-related data to assess changes in the estimated glomerular filtration rate (eGFR). CKD severity was assessed based on eGFR.

RESULTS

Among 154 patients who received LTLT, 41 patients (27%) developed CKD, of whom 20 (49%) patients continued lithium (continuers) and 19 (46%) discontinued it (discontinuers). The median time to stage 3 CKD development was 21.7 years from the start of Li treatment. Type-2 diabetes mellitus and benzodiazepine use were independent predictors for CKD development in the survival analysis, after controlling for age. The subsequent CKD progression rate did not differ between continuers and discontinuers (mean GFR 48.6 vs. 44.1, p = 0.13) at the end of follow-up duration (mean duration: 3.5 ± 4.4 years for continuers and 4.9 ± 5.3 years for discontinuers).

CONCLUSION

CKD was observed in one fourth of patients with BD receiving LTLT. There was no significant difference in the progression of CKD among Li continuers versus discontinuers, at the mean follow-up duration of 4.2 years, after the CKD diagnosis. Progression of CKD could be influenced by existing comorbidities and may not necessarily be due to lithium alone.

Duration of untreated illness and bipolar disorder: time for a new definition? Results from a cross-sectional study

BACKGROUND

We primarily aimed to explore the associations between duration of untreated illness (DUI), treatment response, and functioning in a cohort of patients with bipolar disorder (BD).

METHODS

261 participants with BD were recruited. DUI was defined as months from the first affective episode to the start of a mood-stabilizer. The functioning assessment short test (FAST) scores and treatment response scores for lithium, valproate, or lamotrigine according to the Alda Scale Total Score (TS) were compared between patients with short (<24 months) or long DUI. Differences in FAST scores among good (GR; TS≥7), poor (PR; TS=2-6), or non-responders (NR; TS<2) to each mood-stabilizer were analyzed. Linear regression was computed using the FAST global score as the dependent variable.

RESULTS

DUI and FAST scores showed no statistically significant correlation. Patients with a longer DUI showed poorer response to lithium (Z=-3.196; p<0.001), but not to valproate or lamotrigine. Response to lithium (β=-1.814; p<0.001), number of hospitalizations (β=0.237; p<0.001), and illness duration (β=0.160; p=0.028) were associated with FAST total scores. GR to lithium was associated with better global functioning compared to PR or NR [H=27.631; p<0.001].

LIMITATIONS

The retrospective design could expose our data to a recall bias. Also, only few patients were on valproate or lamotrigine treatment.

CONCLUSIONS

Poor functioning in BD could be the result of multiple affective relapses, rather than a direct effect of DUI. A timely diagnosis with subsequent effective prophylactic treatment, such as lithium, may prevent poor functional outcomes in real-world patients with BD.

A Comparison of Different Approaches to Clinical Phenotyping of Lithium Response: A Proof of Principle Study Employing Genetic Variants of Three Candidate Circadian Genes

Optimal classification of the response to lithium (Li) is crucial in genetic and biomarker research. This proof of concept study aims at exploring whether different approaches to phenotyping the response to Li may influence the likelihood of detecting associations between the response and genetic markers. We operationalized Li response phenotypes using the Retrospective Assessment of Response to Lithium Scale (i.e., the Alda scale) in a sample of 164 cases with bipolar disorder (BD). Three phenotypes were defined using the established approaches, whilst two phenotypes were generated by machine learning algorithms. We examined whether these five different Li response phenotypes showed different levels of statistically significant associations with polymorphisms of three candidate circadian genes (RORA, TIMELESS and PPARGC1A), which were selected for this study because they were plausibly linked with the response to Li. The three original and two revised Alda ratings showed low levels of discordance (misclassification rates: 8–12%). However, the significance of associations with circadian genes differed when examining previously recommended categorical and continuous phenotypes versus machine-learning derived phenotypes. Findings using machine learning approaches identified more putative signals of the Li response. Established approaches to Li response phenotyping are easy to use but may lead to a significant loss of data (excluding partial responders) due to recent attempts to improve the reliability of the original rating system. While machine learning approaches require additional modeling to generate Li response phenotypes, they may offer a more nuanced approach, which, in turn, would enhance the probability of identifying significant signals in genetic studies.

Genetics and antiepileptic mood stabilizer treatment response in bipolar disorder: what do we know?

Antiepileptic mood stabilizers (AED-MS) are often used to treat bipolar disorder (BD). Similar to other mood disorder medications, AED-MS treatment response varies between patients. Identification of biomarkers associated with treatment response may ultimately help with the delivery of individualized treatment and lead to improved treatment efficacy. Here, we conducted a narrative review of the current knowledge of the pharmacogenomics of AED-MS (valproic acid, lamotrigine and carbamazepine) treatment response in BD, including genetic contributions to AED-MS pharmacokinetics. Genes involved in neurotransmitter systems and drug transport have been shown to be associated with AED-MS treatment response. As more studies are conducted, and experimental and analytical methods advance, knowledge of AED-MS pharmacogenomics is expected to grow and contribute to precision medicine in BD.

Development and validation of a risk calculator for major mood disorders among the offspring of bipolar parents using information collected in routine clinical practice

BACKGROUND

Family history is a significant risk factor for bipolar disorders (BD), but the magnitude of risk varies considerably between individuals within and across families. Accurate risk estimation may increase motivation to reduce modifiable risk exposures and identify individuals appropriate for monitoring over the peak risk period. Our objective was to develop and independently replicate an individual risk calculator for bipolar spectrum disorders among the offspring of BD parents using data collected in routine clinical practice.

METHODS

Data from the longitudinal Canadian High-Risk Offspring cohort study collected from 1996 to 2020 informed the development of a 5 and 10-year risk calculator using parametric time-to-event models with a cure fraction and a generalized gamma distribution. The calculator was then externally validated using data from the Lausanne-Geneva High-Risk Offspring cohort study collected from 1996 to 2020. A time-varying C-index by age in years was used to estimate the probability that the model correctly classified risk. Bias corrected estimates and 95% confidence limits were derived using a jackknife resampling approach.

FINDINGS

The primary outcome was age of onset of a major mood disorder. The risk calculator was most accurate at classifying risk in mid to late adolescence in the Canadian cohort (n = 285), and a similar pattern was replicated in the Swiss cohort (n = 128). Specifically, the time-varying C-index indicated that there was approximately a 70% chance that the model would correctly predict which of two 15-year-olds would be more likely to develop the outcome in the future. External validation within a smaller Swiss cohort showed mixed results.

INTERPRETATION

Findings suggest that this model may be a useful clinical tool in routine practice for improved individualized risk estimation of bipolar spectrum disorders among the adolescent offspring of a BD parent; however, risk estimation in younger high-risk offspring is less accurate, perhaps reflecting the evolving nature of psychopathology in early childhood. Based on external validation with a Swiss cohort, the risk calculator may not be as predictive in more heterogenous high-risk populations.

FUNDING

The Canadian High-Risk Study has been funded by consecutive operating grants from the Canadian Institutes for Health Research, currently CIHR PJT Grant 152796 he Lausanne-Geneva high-risk study was and is supported by five grants from the Swiss National Foundation (#3200-040,677, #32003B-105,969, #32003B-118,326, #3200-049,746 and #3200-061,974), three grants from the Swiss National Foundation for the National Centres of Competence in Research project "The Synaptic Bases of Mental Diseases" (#125,759, #158,776, and #51NF40 - 185,897), and a grant from GlaxoSmithKline Clinical Genetics.

Childhood maltreatment and clinical response to mood stabilizers in patients with bipolar disorder

OBJECTIVE

The association between childhood maltreatment (CM) and clinical response to mood stabilizers has been scarcely investigated in bipolar disorder (BD). Therefore, we assessed whether CM affects the response to lithium or anticonvulsant treatments in BD patients.

METHODS

A retrospective assessment of clinical response to mood stabilizers was conducted in 97 euthymic patients with BD by means of the Alda scale. History of CM was investigated through the Childhood Trauma Questionnaire.

RESULTS

Thirty-seven patients (24 with a history of CM and 13 without CM) were on stable lithium treatment while sixty (35 with a history of CM and 25 without CM) were on stable anticonvulsant treatment. Clinical response to drug treatment did not differ between BD with CM and those without CM in the whole sample as well as in the anticonvulsant-treated subgroup. In the lithium-treated subgroup, a significant negative correlation emerged between childhood physical abuse and clinical response and patients with CM showed a significantly reduced Alda score.

CONCLUSIONS

In BD patients, CM did not influence the clinical response to anticonvulsant mood stabilizers whereas it was associated with a poorer response to lithium with childhood physical abuse playing a major role in this effect.

Deficient LEF1 expression is associated with lithium resistance and hyperexcitability in neurons derived from bipolar disorder patients

Bipolar disorder (BD) is a psychiatric condition characterized by depressive and manic episodes that affect 2% of the world population. The first-line long-term treatment for mood stabilization is lithium (Li). Induced pluripotent stem cell modeling of BD using hippocampal dentate gyrus-like neurons derived from Li-responsive (LR) and Li-non-responsive (NR) patients previously showed neuronal hyperexcitability. Li treatment reversed hyperexcitability only on the LR neurons. In this study we searched for specific targets of Li resistance in NR neurons and found that the activity of Wnt/β-catenin signaling pathway was severely affected, with a significant decrease in expression of LEF1. Li targets the Wnt/β-catenin signaling pathway by inhibiting GSK-3β and releasing β-catenin that forms a nuclear complex with TCF/LEF1, activating the Wnt/β-catenin transcription program. Therefore, we propose that downregulation of LEF1 may account for Li resistance in NR neurons. Our results show that valproic acid (VPA), a drug used to treat NR patients that also acts downstream of GSK-3β, upregulated LEF1 and Wnt/β-catenin gene targets, increased transcriptional activity of complex β-catenin/TCF/LEF1, and reduced excitability in NR neurons. In addition, decreasing LEF1 expression in control neurons using shLEF1 caused hyperexcitability, confirming that the impact of VPA on excitability in NR neurons was connected to changes in LEF1 and in the Wnt/β-catenin pathway. Our results suggest that LEF1 may be a useful target for the discovery of new drugs for BD treatment.

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.