Genetic variants associated with response to lithium treatment in bipolar disorder: a genome-wide association study

Lithium alleviated spinal cord injury (SCI)-induced apoptosis and inflammation in rats via BDNF-AS/miR-9-5p axis

Spinal cord injury (SCI) is a major cause of paralysis, disability and even death in severe cases. Lithium has neuroprotective effects on SCI, while the underlying mechanisms remain obscure. In the present study, we established a SCI rat model, which subsequently received lithium treatment. Results displayed that lithium treatment improved the locomotor function recovery and reduced apoptosis by increasing anti-apoptotic molecule expression and decreasing pro-apoptotic factor expression in SCI rats. Furthermore, lithium treatment alleviated the inflammatory response by inactivating the nuclear factor-kappa B (NF-κB) pathway and inhibited the expression of lncRNA brain-derived neurotrophic factor antisense (BDNF-AS) in SCI rats. Subsequent researches indicated that miR-9-5p was targeted and regulated by BDNF-AS. Lithium treatment rescued the upregulation of BDNF-AS expression and downregulation of miR-9-5p expression induced by H₂O₂ in SH-SY5Y cells. BDNF-AS overexpression or miR-9-5p interference attenuated the anti-apoptotic and anti-inflammatory effects of lithium chloride in SH-SY5Y cells that was damaged by H₂O₂ induction, revealing that lithium might act through the BDNF-AS/miR-9-5p axis. In vivo studies showed that the injection of BDNF-AS adenovirus vector or miR-9-5p inhibitor reversed the effects of lithium on the histologic morphology of spinal cord, motor function, inflammatory reaction and apoptosis in SCI rats, which was consistent with the results of in vitro studies. In conclusion, our data demonstrated that lithium reduced SCI-induced apoptosis and inflammation in rats via the BDNF-AS/miR-9-5p axis.

Prediction of lithium response using genomic data

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen’s kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [− 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.

Has Bipolar Disorder become a predominantly female gender related condition? Analysis of recently published large sample studies

Bipolar Disorders (BD) are disabling and severe psychiatric disorders, commonly perceived as equally affecting both men and women. The prevalence of BD in the general population has been growing over the last decade, however, few epidemiological studies are available regarding BD gender distribution, leaving unanswered the question whether the often reported increment of BD diagnosis could be gender specific. In fact, BD in female patients can often be misdiagnosed as MDD, leaving such women non correctly treated for longer times than their male counterparts. From this perspective, we searched literature for large sample (> 1000 subjects) studies published in the last decade (2010 onward) on BD patients. We included ten large sample studies that reported the gender distribution of their samples, and we therefore analysed them. Our results show a higher preponderance of female patients in every sample and sub-sample of BDI and BDII, supporting our hypothesis of an increase in BD diagnosis in females. BD in women presents with higher rates of rapid cycling, depressive polarity and suicide attempts, characteristics of non inferior severity compared to males; prompt recognition and adequate treatment of BD is therefore crucial to reduce risks and improve quality of life of affected women. In this regard, our results could lead the way for national or international epidemiological studies with the aim of more accurately assessing gender-specific prevalence of BD.

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

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

Translational genomics and beyond in bipolar disorder

Genome-wide association studies (GWAS) have revealed multiple genomic loci conferring risk of bipolar disorder (BD), providing hints for its underlying pathobiology. However, there are still remaining questions to answer. For example, discordance exists between BD heritability estimated with earlier epidemiological evidence and that calculated based on common GWAS variations. Where is the "missing heritability"? How can we explain the biology of the disease based on genetic findings? In this review, we summarize the accomplishments and limitations of current BD GWAS, and discuss potential reasons for the "missing heritability." In addition, progresses of research for the biological mechanisms underlying BD genetic risk using brain tissues, reprogrammed cells, and model animals are reviewed. While our knowledge of BD genetic basis is significantly promoted by these efforts, the complexities of gene regulation in the genome, the spatial-temporal heterogeneity during brain development, and the limitations of different experimental models should always be considered. Notably, several genes have been widely studied given their relatively well-characterized involvement in BD (e.g., CACAN1C and ANK3), and findings of these genes are summarized to both outline possible biological mechanisms of BD and describe examples of translating GWAS discoveries into the pathophysiology.

Genomic perspectives on the circadian clock hypothesis of psychiatric disorders

Circadian rhythm disturbances are frequently described in psychiatric disorders such as major depressive disorder, bipolar disorder, and schizophrenia. Growing evidence suggests a biological connection between mental health and circadian rhythmicity, including the circadian influence on brain function and mood and the requirement for circadian entrainment by external factors, which is often impaired in mental illness. Mental (as well as physical) health is also adversely affected by circadian misalignment. The marked interindividual differences in this combined susceptibility, in addition to the phenotypic spectrum in traits related both to circadian rhythms and mental health, suggested the possibility of a shared genetic background and that circadian clock genes may also be candidate genes for psychiatric disorders. This hypothesis was further strengthened by observations in animal models where clock genes had been knocked out or mutated. The introduction of genome-wide association studies (GWAS) enabled hypothesis-free testing. GWAS analysis of chronotype confirmed the prominent role of circadian genes in these phenotypes and their extensive polygenicity. However, in GWAS on psychiatric traits, only one clock gene, ARNTL (BMAL1) was identified as one of the few loci differentiating bipolar disorder from schizophrenia, and macaque monkeys where the ARNTL gene has been knocked out display symptoms similar to schizophrenia. Another lesson from genomic analyses is that chronotype has an important genetic correlation with several psychiatric disorders and that this effect is unidirectional. We conclude that the effect of circadian disturbances on psychiatric disorders probably relates to modulation of rhythm parameters and extend beyond the core clock genes themselves.

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.

Review and Consensus on Pharmacogenomic Testing in Psychiatry

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

Lithium - past, present, future

OBJECTIVES

A narrative review of past, present, and future of lithium use in psychiatry.

METHODS

The most important references on the topic were reviewed with special emphasis on the author's works.

RESULTS

The history of medical and psychiatric use of lithium dates back to more than one and a half-century ago. However, modern psychiatric history began with the publication of John Cade, in 1949, showing a therapeutic effect of lithium in mania. Currently, lithium is a drug of choice as a mood-stabilizer for the maintenance treatment of the bipolar disorder. The second most important use of lithium is probably augmentation of antidepressants in treatment-resistant depression. In addition to its mood-stabilizing properties, lithium exerts anti-suicidal, immunomodulatory, and neuroprotective action. The drug may protect against dementia and some promising effects of lithium in neurodegenerative disorders have been observed.

CONCLUSION

Given the clinical and biological properties of lithium, this drug is presently greatly underutilized in mood disorders. Therefore, the efforts should be undertaken for challenging a skepticism about the use of lithium and optimizing its long-term administration. In such a way, more patients with mood disorders can become the beneficiaries of lithium's therapeutic action. KEY POINTS Lithium is a drug of choice as a mood-stabiliser for the maintenance treatment of bipolar disorder. Augmentation of antidepressants by lithium is one of the best strategies in treatment-resistant depression. Lithium exerts anti-suicidal, immunomodulatory, and neuroprotective action and may protect against dementia. Despite the evidence for the efficacy and added favourable properties, lithium is greatly underutilised in mood disorders. Challenging a scepticism about the use of lithium and optimising its long-term administration can make more patients with mood disorders the beneficiaries of lithium's therapeutic action.

Trends in prescriptions of lithium and other medications for patients with bipolar disorder in office-based practices in the United States: 1996-2015

BACKGROUND

Studies have shown that rates of lithium use for bipolar disorder in the United States declined through the 1990s as other mood stabilizing anticonvulsants and second-generation antipsychotics (SGAs) became more popular. We examined trends of medications for bipolar disorder from 1996 to 2015.

METHODS

Twenty years of data from the National Ambulatory Medical Care Survey (NAMCS) were used. Weighted percentages of reported use of lithium, anticonvulsants, SGAs and antidepressants were calculated over two-year intervals. Logistic regression was used to examine factors related to polytherapy.

RESULTS

Reported use of lithium declined from 38.1% (95%CI: 29.8% - 46.3%) in 1996-97 to 14.3% (95%CI: 10.6% - 18.1%) in 2006-07 and has remained stable since. During this time, reports of SGAs more than doubled. SGAs and/or anticonvulsants were reported in 75.4% (95%CI: 69.5% - 81.3%) of visits with bipolar diagnoses in 2014-15. Polytherapy increased by approximately 3% every two years and in 2014-15 occurred in over 30% of visits. Antidepressants were reported in 40-50% of visits, but their reported use without other mood stabilizers decreased from 18.2% (95%CI: 11.7% - 24.8%) in 1998-99 to 7.5% (95%CI: 4.2% - 10.9%) in 2014-15.

LIMITATIONS

The sample had limited power to study the effect of individual medications or the potential for differing effects in certain sub-groups of patients.

CONCLUSIONS

This study further documents the declining use of lithium for bipolar disorder, and corresponding increase in use of anticonvulsants and SGAs, despite the fact that lithium is typically recommended as a first line therapy for bipolar disorder.

Positional cloning and comprehensive mutation analysis of a Japanese family with lithium-responsive bipolar disorder identifies a novel DOCK5 mutation

Bipolar disorder (BD) is a severe psychiatric disorder characterized by the recurrence of depressive and manic episodes. Its heritability is high, and many linkage and association studies have been performed. Although various linkage regions and candidate genes have been reported, few have shown sufficient reproducibility, and none have identified the pathogenic genes based on the results of the linkage analysis. To find functional variants that are expected to be rare and have strong genetic effects, we recruited ten healthy individuals, two individuals with unknown status, and six patients with BD or recurrent major depressive disorder (MDD) from a Japanese family consisting of 21 members. We performed a genome-wide linkage analysis using a 100K single-nucleotide polymorphism (SNP) array and microsatellite markers to narrow linkage regions within this family. Subsequently, we performed whole-exome sequencing for two patients with BD to identify genetic mutations in the narrowed linkage regions. Then, we performed co-segregation analysis for DNA variants obtained from the results of the exome sequencing. Finally, we identified a rare heterozygous mutation in exon 31 of DOCK5 (c.3170A>G, p.E1057G). Convergent functional genomics analysis revealed that DOCK5 was listed as one of the biomarkers for mood state and suicidality. Although DOCK5 is still a functionally unknown gene, our findings highlight the possibility of a pathological relationship between BD and DOCK5.

Investigation of the impact of an ADCY2 polymorphism as a predictive biomarker in bipolar disorder, suicide tendency and response to lithium carbonate therapy: the first report from Iran

High rates of mortality due to both suicide and medical comorbidities in bipolar patients can be decreased through the administration of lithium, which affects the cerebral endothelium as well as neurons. To investigate the role of ADCY2 in risk of bipolar disorder, we genotyped the ADCY2 rs2290910 in bipolar patients and healthy controls using amplification refractory mutation system PCR. This polymorphism was associated with risk of bipolar disorder (odds ratio [OR]: 0.430; 95% CI: 0.296-0.624; p = 0.001). The C allele was more frequent in suicide ideation group compared other groups (OR: 2.7; 95% CI: 1.386-5.302; p = 0.004). The T allele was more frequent in suicide attempt group compared with suicide ideation group (OR: 0.238; 95% CI: 0.111-0.509; p = 0.001).

Na+/K+-ATPase and lipid peroxidation in forebrain cortex and hippocampus of sleep-deprived rats treated with therapeutic lithium concentration for different periods of time

Lithium (Li) is a typical mood stabilizer and the first choice for treatment of bipolar disorder (BD). Despite an extensive clinical use of Li, its mechanisms of action remain widely different and debated. In this work, we studied the time-course of the therapeutic Li effects on ouabain-sensitive Na⁺/K⁺-ATPase in forebrain cortex and hippocampus of rats exposed to 3-day sleep deprivation (SD). We also monitored lipid peroxidation as malondialdehyde (MDA) production. In samples of plasma collected from all experimental groups of animals, Li concentrations were followed by ICP-MS. The acute (1 day), short-term (7 days) and chronic (28 days) treatment of rats with Li resulted in large decrease of Na⁺/K⁺-ATPase activity in both brain parts. At the same time, SD of control, Li-untreated rats increased Na⁺/K⁺-ATPase along with increased production of MDA. The SD-induced increase of Na⁺/K⁺-ATPase and MDA was attenuated in Li-treated rats. While SD results in a positive change of Na⁺/K⁺-ATPase, the inhibitory effect of Li treatment may be interpreted as a pharmacological mechanism causing a normalization of the stress-induced shift and return the Na⁺/K⁺-ATPase back to control level. We conclude that SD alone up-regulates Na⁺/K⁺-ATPase together with increased peroxidative damage of lipids. Chronic treatment of rats with Li before SD, protects the brain tissue against this type of damage and decreases Na⁺/K⁺-ATPase level back to control level.

Mood-Stabilizing Antiepileptic Treatment Response in Bipolar Disorder: A Genome-Wide Association Study

Several antiepileptic drugs (AEDs) have US Food and Drug Administration (FDA) approval for use as mood stabilizers in bipolar disorder (BD), but not all BD patients respond to these AED mood stabilizers (AED‐MSs). To identify genetic polymorphisms that contribute to the variability in AED‐MS response, we performed a discovery genome‐wide association study (GWAS) of 199 BD patients from the Mayo Clinic Bipolar Disorder Biobank. Most of these patients had been treated with the AED‐MS valproate/divalproex and/or lamotrigine. AED‐MS response was assessed using the Alda scale, which quantifies clinical improvement while accounting for potential confounding factors. We identified two genome‐wide significant single‐nucleotide polymorphism (SNP) signals that mapped to the THSD7A (rs78835388, P = 7.1E‐09) and SLC35F3 (rs114872993, P = 3.2E‐08) genes. We also identified two genes with statistically significant gene‐level associations: ABCC1 (P = 6.7E‐07; top SNP rs875740, P = 2.0E‐6), and DISP1 (P = 8.9E‐07; top SNP rs34701716, P = 8.9E‐07). THSD7A SNPs were previously found to be associated with risk for several psychiatric disorders, including BD. Both THSD7A and SLC35F3 are expressed in excitatory/glutamatergic and inhibitory/γ‐aminobutyric acidergic (GABAergic) neurons, which are targets of AED‐MSs. ABCC1 is involved in the transport of valproate and lamotrigine metabolites, and the SNPs in ABCC1 and DISP1 with the strongest evidence of association in our GWAS are strong splicing quantitative trait loci in the human gut, suggesting a possible influence on drug absorption. In conclusion, our pharmacogenomic study identified novel genetic loci that appear to contribute to AED‐MS treatment response, and may facilitate precision medicine in BD.

Insights into the genomics of affective disorders

Affective disorders, or mood disorders, are a group of neuropsychiatric illnesses that are characterized by a disturbance of mood or affect. Most genetic research in this field to date has focused on bipolar disorder and major depression. Symptoms of major depression include a depressed mood, reduced energy, and a loss of interest and enjoyment. Bipolar disorder is characterized by the occurrence of (hypo)manic episodes, which generally alternate with periods of depression. Formal and molecular genetic studies have demonstrated that affective disorders are multifactorial diseases, in which both genetic and environmental factors contribute to disease development. Twin and family studies have generated heritability estimates of 58–85 % for bipolar disorder and 40 % for major depression.

Large genome-wide association studies have provided important insights into the genetics of affective disorders via the identification of a number of common genetic risk factors. Based on these studies, the estimated overall contribution of common variants to the phenotypic variability (single-nucleotide polymorphism [SNP]-based heritability) is 17–23 % for bipolar disorder and 9 % for major depression. Bioinformatic analyses suggest that the associated loci and implicated genes converge into specific pathways, including calcium signaling. Research suggests that rare copy number variants make a lower contribution to the development of affective disorders than to other psychiatric diseases, such as schizophrenia or the autism spectrum disorders, which would be compatible with their less pronounced negative impact on reproduction. However, the identification of rare sequence variants remains in its infancy, as available next-generation sequencing studies have been conducted in limited samples. Future research strategies will include the enlargement of genomic data sets via innovative recruitment strategies; functional analyses of known associated loci; and the development of new, etiologically based disease models. Researchers hope that deeper insights into the biological causes of affective disorders will eventually lead to improved diagnostics and disease prediction, as well as to the development of new preventative, diagnostic, and therapeutic strategies. Pharmacogenetics and the application of polygenic risk scores represent promising initial approaches to the future translation of genomic findings into psychiatric clinical practice.

Correlations between immune and metabolic serum markers and schizophrenia/bipolar disorder polygenic risk score in first-episode psychosis

AIMS

There is a strong interest in identifying the biological mechanisms involved in the genetic risk for psychotic disorders. In this study, we evaluated the correlation between serum concentrations of specific molecular markers and the genetic component for schizophrenia and bipolar disorder.

METHODS

We analysed the association between the polygenic risk score (PRS) and the serum levels of different inflammatory/metabolic markers in a sample of 81 first-episode psychosis patients (FEP) with a diagnosis of schizophrenia or bipolar disorder and 33 controls.

RESULTS

A positive correlation of schizophrenia and bipolar disorder PRS with the inflammatory marker C-C Motif Chemokine Ligand 4 serum concentration (ρ = 0.42, P = 1.56 × 10^-04 and ρ = 0.40, P = 1.65 × 10^-03 , respectively) and a negative correlation with the serum ghrelin content (ρ = - 0.35, P = 4.27 × 10^-03 and ρ = - 0.45, P = 6.05 × 10^-04 , respectively) were observed.

CONCLUSION

These findings provide new insight into the biological underpinnings of the PRS component, thus supporting a role of the genetic liability on the inflammatory and metabolic alterations that characterize psychosis onset.

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.

Potential pharmacogenomic targets in bipolar disorder: considerations for current testing and the development of decision support tools to individualize treatment selection

Background

Treatment in bipolar disorder (BD) is commonly applied as a multimodal therapy based on decision algorithms that lack an integrative understanding of molecular mechanisms or a biomarker associated clinical outcome measure. Pharmacogenetics/genomics study the individual genetic variation associated with drug response. This selective review of pharmacogenomics and pharmacogenomic testing (PGT) in BD will focus on candidate genes and genome wide association studies of pharmacokinetic drug metabolism and pharmacodynamic drug response/adverse event, and the potential role of decision support tools that incorporate multiple genotype/phenotype drug recommendations.

Main body

We searched PubMed from January 2013 to May 2019, to identify studies reporting on BD and pharmacogenetics, pharmacogenomics and PGT. Studies were selected considering their contribution to the field. We summarize our findings in: targeted candidate genes of pharmacokinetic and pharmacodynamic pathways, genome-wide association studies and, PGT platforms, related to BD treatment. This field has grown from studies of metabolizing enzymes (i.e., pharmacokinetics) and drug transporters (i.e., pharmacodynamics), to untargeted investigations across the entire genome with the potential to merge genomic data with additional biological information.

Conclusions

The complexity of BD genetics and, the heterogeneity in BD drug-related phenotypes, are important considerations for the design and interpretation of BD PGT. The clinical applicability of PGT in psychiatry is in its infancy and is far from reaching the robust impact it has in other medical disciplines. Nonetheless, promising findings are discovered with increasing frequency with remarkable relevance in neuroscience, pharmacology and biology.

Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action

Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substantial burden on society, the research activity in BD is much smaller than its economic impact appears to demand. There is a consensus that the accurate identification of the underlying pathophysiology for BD is fundamental to realize major health benefits through better treatment and preventive regimens. However, to achieve these goals requires coordinated action and innovative approaches to boost the discovery of the neurobiological underpinnings of BD, and rapid translation of research findings into development and testing of better and more specific treatments. To this end, we here propose that only a large-scale coordinated action can be successful in integrating international big-data approaches with real-world clinical interventions. This could be achieved through the creation of a Global Bipolar Disorder Foundation, which could bring government, industry and philanthropy together in common cause. A global initiative for BD research would come at a highly opportune time given the seminal advances promised for our understanding of the genetic and brain basis of the disease and the obvious areas of unmet clinical need. Such an endeavour would embrace the principles of open science and see the strong involvement of user groups and integration of dissemination and public involvement with the research programs. We believe the time is right for a step change in our approach to understanding, treating and even preventing BD effectively.

Orphan G Protein Coupled Receptors in Affective Disorders

G protein coupled receptors (GPCRs) are the main mediators of signal transduction in the central nervous system. Therefore, it is not surprising that many GPCRs have long been investigated for their role in the development of anxiety and mood disorders, as well as in the mechanism of action of antidepressant therapies. Importantly, the endogenous ligands for a large group of GPCRs have not yet been identified and are therefore known as orphan GPCRs (oGPCRs). Nonetheless, growing evidence from animal studies, together with genome wide association studies (GWAS) and post-mortem transcriptomic analysis in patients, pointed at many oGPCRs as potential pharmacological targets. Among these discoveries, we summarize in this review how emotional behaviors are modulated by the following oGPCRs: ADGRB2 (BAI2), ADGRG1 (GPR56), GPR3, GPR26, GPR37, GPR50, GPR52, GPR61, GPR62, GPR88, GPR135, GPR158, and GPRC5B.

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.

The black sheep of the family- whole-exome sequencing in family of lithium response discordant bipolar monozygotic twins

Twin studies are among the most promising strategies for studying heritable disorders, including bipolar disorder (BD). The aim of the present study was to identify distinguishing genes between monozygotic (MZ) twins with different BD phenotype and compare them to their non-affected siblings. Whole-exome sequencing (WES) can identify rare and structural variants that could detect the polygenetic burden of complex disorders. WES was performed on a family composed of two MZ twins with BD, their unaffected brother and unaffected parents. The twins have a discordant response to lithium and distinct course of illness. Following WES, six genes of particular interest emerged: Neurofibromin type 1 (NF1), Biorientation of chromosomes in cell division 1 (BOD1), Golgi-associated gamma adaptin ear-containing ARF binding protein 3 (GGA3), Disrupted in schizophrenia 1 (DISC1), Neuromedin U receptor 2 (NMUR2), and Huntingtin interacting protein 1-related (HIP1R). Interestingly, many of these influence glutamatergic pathways and thus the findings may have therapeutical implications. These results may provide important insights to unveil genetic underpinnings of BD and the response to lithium.

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.

Genomics and the future of psychopharmacology: MicroRNAs offer novel therapeutics

MicroRNAs (miRNAs) are short, noncoding RNAs functioning as regulators of the transcription of protein-coding genes in eukaryotes. During the last two decades, studies on miRNAs indicate that they have potential as diagnostic and prognostic biomarkers for a wide range of cancers. Research interest in miRNAs has moved to embrace further medical disciplines, including neuropsychiatric disorders, comparing miRNA expression and mRNA targets between patient and control blood samples and postmortem brain tissues, as well as in animal models of neuropsychiatric disorders. This manuscript reviews recent findings on miRNAs implicated in the pathology of mood disorders, schizophrenia, and autism, as well as their diagnostic potential, and their potential as tentative targets for future therapeutics. The plausible contribution of X chromosome miRNAs to the larger prevalence of major depression among women is also evaluated.


Modeling the complex genetic architectures of brain disease

The genetic architecture of each individual comprises common and rare variants that, acting alone and in combination, confer risk of disease. The cell-type-specific and/or context-dependent functional consequences of the risk variants linked to brain disease must be resolved. Coupling human induced pluripotent stem cell (hiPSC)-based technology with CRISPR-based genome engineering facilitates precise isogenic comparisons of variants across genetic backgrounds. Although functional-validation studies are typically performed on one variant in isolation and in one cell type at a time, complex genetic diseases require multiplexed gene perturbations to interrogate combinations of genes and resolve physiologically relevant disease biology. Our aim is to discuss advances at the intersection of genomics, hiPSCs and CRISPR. A better understanding of the molecular mechanisms underlying disease risk will improve genetic diagnosis, drive phenotypic drug discovery and pave the way toward precision medicine.

Lithium effects on serine-threonine kinases activity: High throughput kinomic profiling of lymphoblastoid cell lines from excellent-responders and non-responders bipolar patients

Objectives: Lithium is the leading mood stabiliser for maintenance treatment in bipolar disorder (BD). However, response to lithium is heterogeneous with more than 60% of patients experiencing partial or no response. In vitro and in vivo molecular studies have reported the implication of kinases in the pathophysiology of BD.Methods: Since kinases are putative targets for lithium therapeutic action, we conducted the first pilot study using kinase array technology to evaluate the global serine/threonine kinases (STK) profiles in cell lines from BD I subtype patients classified as lithium excellent-responders (ER) and non-responder (NR) to lithium treatment.Results: We found significant differences in the basal STK profiles between ER and NR to lithium. We also tested lithium influence on the global STK profile and found no significant difference between ER vs NR cell lines.Conclusions: The results obtained in this exploratory study suggest that multiplex kinase activity profiling could provide a complementary approach in the study of biomarkers of therapeutic response in BD.

Lithium treatment in the era of personalized medicine

In 1949, an Australian psychiatrist, John Cade, reported on the antimanic efficacy of lithium carbonate, which is regarded as an introduction of lithium into contemporary psychiatry. Since the 1960s, lithium has been a precursor of mood stabilizers and has become first-choice drug for the prevention of affective episodes in mood disorders. For nearly four decades, lithium has also been used for the augmentation of antidepressant drugs in treatment-resistant depression. The knowledge of clinical and biological factors connected with the capability of long-term lithium treatment to prevent manic and depressive recurrences makes an important element of the personalized medicine of mood disorders. Excellent prophylactic lithium responders can be characterized by distinct mood episodes, with full remissions between them, the absence of other psychiatric morbidity, and the family history of bipolar illness. In recent years, many other clinical and biological factors connected with such a response have been identified, helping to select the best candidates for lithium prophylaxis. The antisuicidal effect of lithium during its long-term administration has been demonstrated and should also be taken into account as the element of personalized medicine for the pharmacological prophylaxis of patients with mood disorders. Several studies pertaining to personalized medicine were also dedicated to lithium treatment of acute mood episodes. Lithium still has a value in the treatment of mania and bipolar depression. However, it seems that the more important indication would be the augmentation of antidepressant drugs in treatment-resistant depression. The factors connected with the efficacy of lithium in these conditions are reviewed.

The genetics of bipolar disorder

Bipolar disorder (BD) is one of the most heritable mental illnesses, but the elucidation of its genetic basis has proven to be a very challenging endeavor. Genome-Wide Association Studies (GWAS) have transformed our understanding of BD, providing the first reproducible evidence of specific genetic markers and a highly polygenic architecture that overlaps with that of schizophrenia, major depression, and other disorders. Individual GWAS markers appear to confer little risk, but common variants together account for about 25% of the heritability of BD. A few higher-risk associations have also been identified, such as a rare copy number variant on chromosome 16p11.2. Large scale next-generation sequencing studies are actively searching for other alleles that confer substantial risk. As our understanding of the genetics of BD improves, there is growing optimism that some clear biological pathways will emerge, providing a basis for future studies aimed at molecular diagnosis and novel therapeutics.

Prediction of lithium treatment response in bipolar depression using 5-HTT and 5-HT1A PET

BACKGROUND

Lithium, one of the few effective treatments for bipolar depression (BPD), has been hypothesized to work by enhancing serotonergic transmission. Despite preclinical evidence, it is unknown whether lithium acts via the serotonergic system. Here we examined the potential of serotonin transporter (5-HTT) or serotonin 1A receptor (5-HT_1A) pre-treatment binding to predict lithium treatment response and remission. We hypothesized that lower pre-treatment 5-HTT and higher pre-treatment 5-HT_1A binding would predict better clinical response. Additional analyses investigated group differences between BPD and healthy controls and the relationship between change in binding pre- to post-treatment and clinical response. Twenty-seven medication-free patients with BPD currently in a depressive episode received positron emission tomography (PET) scans using 5-HTT tracer [¹¹C]DASB, a subset also received a PET scan using 5-HT_1A tracer [¹¹C]-CUMI-101 before and after 8 weeks of lithium monotherapy. Metabolite-corrected arterial input functions were used to estimate binding potential, proportional to receptor availability. Fourteen patients with BPD with both [¹¹C]DASB and [¹¹C]-CUMI-101 pre-treatment scans and 8 weeks of post-treatment clinical scores were included in the prediction analysis examining the potential of either pre-treatment 5-HTT or 5-HT1A or the combination of both to predict post-treatment clinical scores.

RESULTS

We found lower pre-treatment 5-HTT binding (p = 0.003) and lower 5-HT_1A binding (p = 0.035) were both significantly associated with improved clinical response. Pre-treatment 5-HTT predicted remission with 71% accuracy (77% specificity, 60% sensitivity), while 5-HT_1A binding was able to predict remission with 85% accuracy (87% sensitivity, 80% specificity). The combined prediction analysis using both 5-HTT and 5-HT_1A was able to predict remission with 84.6% accuracy (87.5% specificity, 60% sensitivity). Additional analyses BPD and controls pre- or post-treatment, and the change in binding were not significant and unrelated to treatment response (p > 0.05).

CONCLUSIONS

Our findings suggest that while lithium may not act directly via 5-HTT or 5-HT_1A to ameliorate depressive symptoms, pre-treatment binding may be a potential biomarker for successful treatment of BPD with lithium.

CLINICAL TRIAL REGISTRATION

PET and MRI Brain Imaging of Bipolar Disorder Identifier: NCT01880957; URL: https://clinicaltrials.gov/ct2/show/NCT01880957.

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.

Asymmetrical reliability of the Alda score favours a dichotomous representation of lithium responsiveness

The Alda score is commonly used to quantify lithium responsiveness in bipolar disorder. Most often, this score is dichotomized into “responder” and “non-responder” categories, respectively. This practice is often criticized as inappropriate, since continuous variables are thought to invariably be “more informative” than their dichotomizations. We therefore investigated the degree of informativeness across raw and dichotomized versions of the Alda score, using data from a published study of the scale’s inter-rater reliability (n = 59 raters of 12 standardized vignettes each). After learning a generative model for the relationship between observed and ground truth scores (the latter defined by a consensus rating of the 12 vignettes), we show that the dichotomized scale is more robust to inter-rater disagreement than the raw 0-10 scale. Further theoretical analysis shows that when a measure’s reliability is stronger at one extreme of the continuum—a scenario which has received little-to-no statistical attention, but which likely occurs for the Alda score ≥ 7—dichotomization of a continuous variable may be more informative concerning its ground truth value, particularly in the presence of noise. Our study suggests that research employing the Alda score of lithium responsiveness should continue using the dichotomous definition, particularly when data are sampled across multiple raters.

Quantifying the level of difficulty to treat major depressive disorder with antidepressants: Treatment Resistance to Antidepressants Evaluation Scale

BACKGROUND

The present study aimed to develop a new scale to evaluate the level of difficulty in treating major depressive disorder with antidepressants based on the lifetime treatment profile.

METHODS

In addition to evaluating the difficulty of treatment with antidepressants (A subscale), the Treatment Resistance to Antidepressants Evaluation Scale (TRADES) is comprised of a subscale to account for the attributes that compromise the efficacy of treatment (B subscale). One hundred and six participants aged 18 to 65 years with remitted major depressive disorder were enrolled. Eligible cases were those with at least 2 years from disease onset until the scoring date of the TRADES (the index date), with a complete treatment record. Various psychosocial and clinical features, such as neuroticism, harm avoidance, and utilization of psychiatric services, were used to validate the TRADES.

RESULTS

The mean duration of the course before and after the index date were 5.5 ± 3.5 and 3.1 ± 1.7 years, respectively. In a multiple regression analysis, the final total scores of the TRADES independently correlated with higher levels of neuroticism and harm avoidance. Total scores were also associated with a higher utilization of psychiatric outpatient and admission services before the index date. Furthermore, it is thought that total scores could predict a higher number of visits to psychiatric outpatient, emergency, and admission services following the index date.

CONCLUSIONS

The TRADES has acceptable validity and could help to quantify the level of treatment difficulty with antidepressants in major depressive disorder.

Further evidence for the association between LRP8 and schizophrenia

Previous studies (including genome-wide association study (GWAS) and candidate gene studies) have revealed the important roles of genetic risk factors in schizophrenia, and RELN has been identified as a risk gene for this illness. We recently found that the low-density lipoprotein receptor-related protein 8 (LRP8), a receptor of Reelin (the protein encoded by RELN), was significantly associated with schizophrenia and bipolar disorder in European populations. To further enhance our understanding of its role in the risk of psychiatric illnesses, we conducted meta-analyses of a higher density of single nucleotide polymorphisms (SNPs, N=173) in LRP8 to understand their associations with schizophrenia in much larger samples (39,400 cases and 50,357 controls) from populations of European, Chinese and African American ancestries. The significant risk SNPs then underwent further analyses to understand their correlations with bipolar disorder and anxiety disorders, as well as LRP8 expression. We observed that rs5177 in the 3' untranslated region (3'UTR) of LRP8 was associated with schizophrenia and other psychiatric disorders, and rs5177 was also associated with LRP8 mRNA expression. These data further support LRP8 as a schizophrenia susceptibility gene, and suggest that this variant is likely a risk locus in general populations.

Whole Genome Expression Analyses of miRNAs and mRNAs Suggest the Involvement of miR-320a and miR-155-3p and their Targeted Genes in Lithium Response in Bipolar Disorder

Lithium is the mainstay in the maintenance of bipolar disorder (BD) and the most efficacious pharmacological treatment in suicide prevention. Nevertheless, its use is hampered by a high interindividual variability and important side effects. Genetic and epigenetic factors have been suggested to modulate lithium response, but findings so far have not allowed identifying molecular targets with predictive value. In this study we used next generation sequencing to measure genome-wide miRNA expression in lymphoblastoid cell lines from BD patients excellent responders (ER, n = 12) and non-responders (NR, n = 12) to lithium. These data were integrated with microarray genome-wide expression data to identify pairs of miRNA/mRNA inversely and significantly correlated. Significant pairs were prioritized based on strength of association and in-silico miRNA target prediction analyses to select candidates for validation with qRT-PCR. Thirty-one miRNAs were differentially expressed in ER vs. NR and inversely correlated with 418 genes differentially expressed between the two groups. A total of 331 of these correlations were also predicted by in-silico algorithms. miR-320a and miR-155-3p, as well as three of their targeted genes (CAPNS1 (Calpain Small Subunit 1) and RGS16 (Regulator of G Protein Signaling 16) for miR-320, SP4 (Sp4 Transcription Factor) for miR-155-3p) were validated. These miRNAs and mRNAs were previously implicated in psychiatric disorders (miR-320a and SP4), key processes of the central nervous system (CAPNS1, RGS16, SP4) or pathways involved in mental illnesses (miR-155-3p). Using an integrated approach, we identified miRNAs and their targeted genes potentially involved in lithium response in BD.

Coding and Non-Coding RNA Abnormalities in Bipolar Disorder

The molecular mechanisms underlying bipolar disorder (BPD) have remained largely unknown. Postmortem brain tissue studies comparing BPD patients with healthy controls have produced a heterogeneous array of potentially implicated protein-coding RNAs. We hypothesized that dysregulation of not only coding, but multiple classes of RNA (coding RNA, long non-coding (lnc) RNA, circular (circ) RNA, and/or alternative splicing) underlie the pathogenesis of BPD. Using non-polyadenylated libraries we performed RNA sequencing in postmortem human medial frontal gyrus tissue from BPD patients and healthy controls. Twenty genes, some of which not previously implicated in BPD, were differentially expressed (DE). PCR validation and replication confirmed the implication of these DE genes. Functional in silico analyses identified enrichment of angiogenesis, vascular system development and histone H3-K4 demethylation. In addition, ten lncRNA transcripts were differentially expressed. Furthermore, an overall increased number of alternative splicing events in BPD was detected, as well as an increase in the number of genes carrying alternative splicing events. Finally, a large reservoir of circRNAs populating brain tissue not affected by BPD is described, while in BPD altered levels of two circular transcripts, cNEBL and cEPHA3, are reported. cEPHA3, hitherto unlinked to BPD, is implicated in developmental processes in the central nervous system. Although we did not perform replication analyses of non-coding RNA findings, our findings hint that RNA dysregulation in BPD is not limited to coding regions, opening avenues for future pharmacological investigations and biomarker research.

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.

SCN11A mRNA levels in female bipolar disorder PBMCs as tentative biomarker for distinct patient sub-phenotypes

Bipolar disorder (BD) is a complex neuropsychiatric disorder characterized by recurrent mania and depression episodes and requiring lifelong treatment with mood stabilizing drugs. Several lines of evidence, including with BD patient iPSC-derived neurons, suggest that neuronal hyperexcitability may underlie the key clinical symptoms of BD. Indeed, higher mRNA levels of SCN11A, coding for the voltage-gated sodium channel Na_V 1.9 implicated in nociception, were detected in iPSC-derived neurons from BD patients, and were normalized by in vitro lithium. Here we studied SCN11A expression in peripheral blood mononuclear cells (PBMCs) from well-phenotyped female BD patients and controls and evaluated their association with several clinical sub-phenotypes. We observed higher mRNA levels of SCN11A in PBMCs from female BD patients with no records of alcohol dependence (p = .0050), no records of psychosis (p = .0097), or no records of suicide attempts (p = .0409). A trend was observed for higher SCN11A expression (FD = 1.91; p = .052) in BD PBMCs compared with controls. Datamining of published postmortem gene expression datasets indicated higher SCN11A expression in dorsolateral prefrontal cortex and orbitofrontal cortex tissues from BD patients compared with controls. Higher phenotype-associated expression levels in PBMC from BD patients were also observed for ID2 (alcohol dependence, suicide attempts) and HDGFRP3 (seasonal BD pattern). Our findings suggest that higher PBMC SCN11A expression levels may be associated with certain behavioral BD sub-phenotypes, including lack of alcohol dependence and psychosis, among BD patients. The Na_V 1.9 voltage-gated sodium channel thus deserves consideration as a tentative phenotype modifier in BD.

The Emergent Course of Bipolar Disorder: Observations Over Two Decades From the Canadian High-Risk Offspring Cohort

OBJECTIVE

The authors sought to describe the emergent course of bipolar disorder in offspring of affected parents subgrouped by parental response to lithium prophylaxis.

METHODS

Parent bipolar disorder was confirmed by the best-estimate procedure and lithium response by research protocol. High-risk offspring (N=279) and control subjects (N=87) were blindly assessed, annually on average, with the Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime version or the Schedule for Affective Disorders and Schizophrenia-Lifetime version. DSM-IV diagnoses were confirmed using the best-estimate procedure in blind consensus reviews. Cumulative incidence and median age at onset were determined for lifetime syndrome- and symptom-level data. Mixed models assessed the association between parent and offspring course. A multistate model was used to estimate the clinical trajectory into bipolar disorder.

RESULTS

The cumulative incidence of bipolar disorder was 24.5%, and the median age at onset was 20.7 years (range, 12.4 to 30.3). The clinical course of the affected parent was associated with that of the affected child. Depressive episodes predominated during the early bipolar course, especially among offspring of lithium responders. Childhood sleep and anxiety disorders significantly predicted 1.6-fold and 1.8-fold increases in risk of mood disorder, respectively, and depressive and manic symptoms predicted 2.7-fold and 2.3-fold increases in risk, respectively. The best-fit model of emerging bipolar disorder was a progressive sequence from nonspecific childhood antecedents to adolescent depression to index manic or hypomanic episode. Subthreshold sleep symptoms were significantly associated with transition from well to non-mood disorder, and psychotic symptoms in mood episodes were significantly associated with transition from unipolar to bipolar disorder.

CONCLUSIONS

Bipolar disorder in individuals at familial risk typically unfolds in a progressive clinical sequence. Childhood sleep and anxiety disorders are important predictors, as are clinically significant mood symptoms and psychotic symptoms in depressive episodes.

Research Domain Criteria: Strengths, Weaknesses, and Potential Alternatives for Future Psychiatric Research

The Research Domain Criteria (RDoC) paradigm was launched 10 years ago as a superior approach for investigation of mental illness. RDoC conceptualizes normal human behavior, emotion, and cognition as dimensional, with mental illnesses as dimensional extremes. We suggest that RDoC may have value for understanding normal human psychology and some conditions plausibly construed as extremes of normal variation. By contrast, for the most serious of mental illnesses, including dementia, autism, schizophrenia, and bipolar disorder, we argue that RDoC is conceptually flawed. RDoC conflates variation along dimensional axes of normal function with quantitative measurements of disease phenotypes and with the occurrence of diseases in overlapping clusters or spectra. This moves away from the disease model of major mental illness. Further, RDoC imposes a top-down approach to research. We argue that progress in major mental illness research will be more rapid with a bottom-up approach, starting with the discovery of etiological factors, proceeding to investigation of pathogenic pathways, including use of cell and animal models, and leading to a refined nosology and novel, targeted treatments.

Predictive modeling for response to lithium and quetiapine in bipolar disorder

OBJECTIVES

Lithium and quetiapine are known to be effective treatments for bipolar disorder. However, little information is available to inform prediction of response to these medications. Machine-learning methods can identify predictors of response by examining variables simultaneously. Further evaluation of models on a test sample can estimate how well these models would generalize to other samples.

METHODS

Data (N = 482) were drawn from a randomized clinical trial of outpatients with bipolar I or II disorder who received adjunctive personalized treatment plus either lithium or quetiapine. Elastic net regularization (ENR) was used to generate models for lithium and quetiapine; these models were evaluated on a test set.

RESULTS

Predictions from the lithium model explained 17.4% of the variance in actual observed scores of patients who received lithium in the test set, while predictions from the quetiapine model explained 32.1% of the variance of patients that received quetiapine. Of the baseline variables selected, those with the largest parameter estimates were: severity of mania; attention-deficit/hyperactivity disorder (ADHD) comorbidity; nonsuicidal self-injurious behavior; employment; and comorbidity with each of two anxiety disorders (social phobia/society anxiety and agoraphobia). Predictive accuracy of the ENR model outperformed the simple and basic theoretical models.

CONCLUSION

ENR is an effective approach for building optimal and generalizable models. Variables identified through this methodology can inform future research on predictors of response to lithium and quetiapine, as well as future modeling efforts of treatment choice in bipolar disorder.

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.

Twenty years of Lithium pharmacogenetics: A systematic review

Lithium is among the best proven treatments for patients diagnosed with Bipolar Disorder, however response to Lithium appears to be considerably variable among individuals and it has been suggested that this inconstancy in Lithium response could be genetically determined. Starting from this perspective, in the last few decades, a number of pharmacogenetic studies have attempted to identify genetic variants, which might be associated with response to Lithium in bipolar patients, in order to develop a pharmacogenetics test to tailor treatment on patients, identifying who will benefit the most from therapy with Lithium. Within this context, authors have critically reviewed pharmacogenetic studies of Lithium response in bipolar disorder, suggesting strategies for future work in this field. Computerized searches of PubMed and Embase databases, for studies published between 1998 and January 2018, was performed: 1162 studies were identified but only 37 relevant papers were selected for detailed review. Despite some interesting preliminary findings, the pharmacogenetics of Lithium and the development of a specific pharmacogenetics test in bipolar disorder appears to be a field still in its infancy, even though the advent of genome-wide association studies holds particular promise for future studies, which should include larger samples.

Personalized and precision medicine as informants for treatment management of bipolar disorder

DSM-5 diagnostic categories, defined by a set of psychopathological symptoms are heterogeneous conditions that may include different biological entities, with distinct etiopathogenesis, different courses and requiring different treatment management. For bipolar disorder the major evidences for this lack of validity are the long paths before a proper diagnosis, the inconsistence of treatment guidelines, the long phases of pharmacological adjustment and the low average of long-term treatment response rates. Personalized medicine for mental disorders aims to couple established clinical-pathological indexes with new molecular profiling to create diagnostic, prognostic and therapeutic strategies precisely tailored to each patient. Regarding bipolar disorder, the clinical history and presentation are still the most reliable markers in stratifying patients and guiding therapeutic management, despite the research goes to great lengths to develop new neuropsychological or biological markers that can reliably predict individual therapy effectiveness. We provide an overview of the advancements in personalized medicine in bipolar disorder, with particular attention to how psychopathology, age at onset, comorbidity, course and staging, genetic and epigenetic, imaging and biomarkers can influence treatment management and provide an integration to the conventional treatment guidelines. This approach may offer a new and rational path for the development of treatments for targeted subgroups of patients with bipolar disorder.

RNA sequencing of bipolar disorder lymphoblastoid cell lines implicates the neurotrophic factor HRP-3 in lithium's clinical efficacy

Objectives: Lithium remains the oldest and most effective treatment for mood stabilisation in bipolar disorder (BD), even though at least half of patients are only partially responsive or do not respond. This study aimed to identify biomarkers associated with lithium response in BD, based on comparing RNA sequencing information derived from lymphoblastoid cell lines (LCLs) of lithium-responsive (LR) versus lithium non-responsive (LNR) BD patients, to assess gene expression variations that might bear on treatment outcome. Methods: RNA sequencing was carried out on 24 LCLs from female BD patients (12 LR and 12 LNR) followed by qPCR validation in two additional independent cohorts (41 and 17 BD patients, respectively). Results: Fifty-six genes showed nominal differential expression comparing LR and LNR (FC ≥ |1.3|, P ≤ 0.01). The differential expression of HDGFRP3 and ID2 was validated by qPCR in the independent cohorts. Conclusions: We observed higher expression levels of HDGFRP3 and ID2 in BD patients who favourably respond to lithium. Both of these genes are involved in neurogenesis, and HDGFRP3 has been suggested to be a neurotrophic factor. Additional studies in larger BD cohorts are needed to confirm the potential of HDGFRP3 and ID2 expression levels in blood cells as tentative favourable lithium response biomarkers.

Genomics of Lithium Action and Response

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

Decreased need for sleep as an endophenotype of bipolar disorder: an actigraphy study

Reports of subjective sleep impairments have been replicated in adults with bipolar disorder (BD), young BD patients, and even children of parents with BD. Furthermore, circadian rhythm alterations are a core feature of BD. Despite the impairment in circadian rhythms and altered sleep included in various heuristic developmental models of BD, thus far, biomarkers have not been sufficiently objectively validated. Thus, here, we assessed the rest-activity circadian rhythmicity and sleep macrostructure using actigraphy in a sample of unaffected child and adolescent offspring of bipolar parents (BO; n = 43; 21 females; 11.0 ± 3.2 years) and controls (n = 42; 17 females; 11.1 ± 3.4 years) comparable in sex (p = .4) and age (p = .7). All participants wore a MotionWatch 8 (Camntech, Cambridge, UK) actigraph on their nondominant wrist for ≥ 14 days and completed sleep diaries. Psychopathology was assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia and by subjective scales. The main areas of interest were rest-activity circadian rhythmicity, chronotype and sleep macrostructure. Subgroup analyses (child and adolescent subgroups) were conducted to identify physiological differences in sleep between these age groups. The BO and controls did not differ in the presence of current mood (p = .5) and anxiety (p = .6) disorders. The BO had shorter sleep time on free days (p = .007; effect size, Cohen´s d = 0.56), lower sleep efficiency on free days (p = .01; d = 0.47), lower prolongation of time in bed on free days (p = .046; d = 0.41), and lower social jet lag (p = .04; d = 0.5) than the controls. A longer sleep time on school days (p < .001; d = 0.21), lower prolongation of sleep time between school and free days (p = .008; d = 0.74), and larger difference in sleep onset latency between school days and free days (p = .009; d = 0.52) were observed in the adolescent BO than in the controls. The child BO had poorer sleep quality on free days than the controls (p = .02; d = 0.96). In all cases, the results remained significant after controlling for subthreshold mood and anxiety symptoms. The BO had less variable rest-activity rhythm than controls (p = .04; d = 0.32). No other significant differences between the BO and controls were observed in the rest-activity circadian rhythmicity and chronotype. The results showed decreased physiological catch-up sleep on free days in the BO, which may indicate a decreased need for sleep in this population. Thus, the decreased need for sleep observed in the unaffected BO may represent an endophenotype of BD.

Lithium-induced gene expression alterations in two peripheral cell models of bipolar disorder

Objectives: The aim of our study was to investigate molecular mechanisms of lithium action by studying the gene expression profile of peripheral cell models generated from bipolar patients (BD) and healthy controls (HC). Methods: EBV-immortalised lymphoblastoid cells (LCLs) and fibroblast cells from BD and HC were incubated with either lithium chloride or plain medium for 3 weeks. We first conducted a microarray gene expression study. The most promising differentially regulated genes in terms of lithium-associated or disorder-associated pathways were then replicated by quantitative real-time PCR (qRT-PCR). Results: The pooled microarray analysis showed 459 genes to be differentially regulated in BD compared to HC and 58 due to lithium treatment in LCLs, and 295 genes to be differentially regulated in BD compared to HC and five due to lithium treatment in fibroblasts. After correction for multiple comparison, EPHB1 disorder × treatment interactions remained significant in LCLs validated by qRT-PCR. In the control group, lithium influenced the expression of ANP32E, PLEKHA2, KCNK1, PRKCH, ST3GAL6 and AIF1. In bipolar and control fibroblast cells lithium treatment decreased FGF9 expression. Conclusions: The differentially regulated genes in our study add evidence for the relevance of inflammation, neuronal/glial development, phosphatidylinositol second-messenger pathway and ion channels in the mode of action of lithium.