Pharmacogenomic aspects of bipolar disorder: An update

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

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

Transcriptomics and miRNomics data integration in lymphoblastoid cells highlights the key role of immune-related functions in lithium treatment response in Bipolar disorder

BACKGROUND

Bipolar Disorder (BD) is a complex mental disease characterized by recurrent episodes of mania and depression. Lithium (Li) represents the mainstay of BD pharmacotherapy, despite the narrow therapeutic index and the high variability in treatment response. However, although several studies have been conducted, the molecular mechanisms underlying Li therapeutic effects remain unclear.

METHODS

In order to identify molecular signatures and biological pathways associated with Li treatment response, we conducted transcriptome and miRNome microarray analyses on lymphoblastoid cell lines (LCLs) from 20 patients diagnosed with BD classified as Li responders (n = 11) or non-responders (n = 9).

RESULTS

We found 335 mRNAs and 77 microRNAs (miRNAs) significantly modulated in BD responders versus non-responders. Interestingly, pathway and network analyses on these differentially expressed molecules suggested a modulatory effect of Li on several immune-related functions. Indeed, among the functional molecular nodes, we found NF-κB and TNF. Moreover, networks related to these molecules resulted overall inhibited in BD responder patients, suggesting anti-inflammatory properties of Li. From the integrative analysis between transcriptomics and miRNomics data carried out using miRComb R package on the same samples from patients diagnosed with BD, we found 97 significantly and negatively correlated mRNA-miRNA pairs, mainly involved in inflammatory/immune response.

CONCLUSIONS

Our results highlight that Li exerts modulatory effects on immune-related functions and that epigenetic mechanisms, especially miRNAs, can influence the modulation of different genes and pathways involved in Li response. Moreover, our data suggest the potentiality to integrate data coming from different high-throughput approaches as a tool to prioritize genes and pathways.

Chronic Lithium Treatment Affects Anxious Behaviors and theExpression of Serotonergic Genes in Midbrain Raphe Nuclei of Defeated Male Mice

There is experimental evidence that chronic social defeat stress is accompanied by the development of an anxiety, development of a depression-like state, and downregulation of serotonergic genes in midbrain raphe nuclei of male mice. Our study was aimed at investigating the effects of chronic lithium chloride (LiCl) administration on anxiety behavior and the expression of serotonergic genes in midbrain raphe nuclei of the affected mice. A pronounced anxiety-like state in male mice was induced by chronic social defeat stress in daily agonistic interactions. After 6 days of this stress, defeated mice were chronically treated with saline or LiCl (100 mg/kg, i.p., 2 weeks) during the continuing agonistic interactions. Anxiety was assessed by behavioral tests. RT-PCR was used to determine Tph2, Htr1a, Htr5b, and Slc6a4 mRNA expression. The results revealed anxiolytic-like effects of LiCl on social communication in the partition test and anxiogenic-like effects in both elevated plus-maze and social interaction tests. Chronic LiCl treatment upregulated serotonergic genes in midbrain raphe nuclei. Thus, LiCl effects depend on the treatment mode, psycho-emotional state of the animal, and experimental context (tests). It is assumed that increased expression of serotonergic genes is accompanied by serotonergic system activation and, as a side effect, by higher anxiety.

Mini review: Recent advances on epigenetic effects of lithium

Lithium (Li) remains the first line long-term treatment of bipolar disorders notwithstanding a high inter-individual variability of response. Significant research effort has been undertaken to understand the molecular mechanisms underlying Li cellular and clinical effects in order to identify predictive biomarkers of response. Li response has been shown to be partly heritable, however mechanisms that do not rely on DNA variants could also be involved. In recent years, modulation of epigenetic marks in relation with the level of Li response has appeared increasingly plausible. Recent results in this field of research have provided new insights into the molecular processes involved in Li effects. In this review, we examined the literature investigating the involvement of three epigenetic mechanisms (DNA methylation, noncoding RNAs and histone modifications) in Li clinical efficacy in bipolar disorder.

The Genetics of Response to and Side Effects of Lithium Treatment in Bipolar Disorder: Future Research Perspectives

Although the mood stabilizer lithium is a first-line treatment in bipolar disorder, a substantial number of patients do not benefit from it and experience side effects. No clinical tool is available for predicting lithium response or the occurrence of side effects in everyday clinical practice. Multiple genetic research efforts have been performed in this field because lithium response and side effects are considered to be multifactorial endophenotypes. Available results from linkage and segregation, candidate-gene, and genome-wide association studies indicate a role of genetic factors in determining response and side effects. For example, candidate-gene studies often report GSK3β, brain-derived neurotrophic factor, and SLC6A4 as being involved in lithium response, and the latest genome-wide association study found a genome-wide significant association of treatment response with a locus on chromosome 21 coding for two long non-coding RNAs. Although research results are promising, they are limited mainly by a lack of replicability and, despite the collaboration of consortia, insufficient sample sizes. The need for larger sample sizes and "multi-omics" approaches is apparent, and such approaches are crucial for choosing the best treatment options for patients with bipolar disorder. In this article, we delineate the mechanisms of action of lithium and summarize the results of genetic research on lithium response and side effects.

Pharmacogenetics of Carbamazepine and Valproate: Focus on Polymorphisms of Drug Metabolizing Enzymes and Transporters

Pharmacogenomics can identify polymorphisms in genes involved in drug pharmacokinetics and pharmacodynamics determining differences in efficacy and safety and causing inter-individual variability in drug response. Therefore, pharmacogenomics can help clinicians in optimizing therapy based on patient's genotype, also in psychiatric and neurological settings. However, pharmacogenetic screenings for psychotropic drugs are not routinely employed in diagnosis and monitoring of patients treated with mood stabilizers, such as carbamazepine and valproate, because their benefit in clinical practice is still controversial. In this review, we summarize the current knowledge on pharmacogenetic biomarkers of these anticonvulsant drugs.

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.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

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.

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.

Pharmacogenetics in the clinical analysis laboratory: clinical practice, research, and drug development pipeline

Introduction: Over the last decade, the spread of next-generation sequencing technology along with the rising cost in health management in national health systems has led to widespread use/abuse of pharmacogenetic tests (PGx) in the practice of many clinical disciplines. However, given their clinical significance, it is important to standardize these tests for having an interaction with the clinical analysis laboratory (CAL), in which a PGx service can meet these requirements. Areas covered: A diagnostic test must meet the criteria of reproducibility and validity for its utility in the clinical routine. This present review mainly describes the utility of introducing PGx tests in the CAL routine to produce correct results useful for setting up personalized drug treatments. Expert opinion: With a PGx service, CALs can provide the right tool to help clinicians to make better choices about different categories of drugs and their dosage and to manage the economic impact both in hospital-based settings and in National Health Services, throughout electronic health records. Advances in PGx also allow a new approach for pharmaceutical companies in order to improve drug development and clinical trials. As a result, CALs can achieve a powerful source of epidemiological, clinical, and research findings from PGx tests.

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.

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.

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

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

Pharmacogenetics in Psychiatry

Mental illness represents a major health issue both at the individual and at the socioeconomical level. This is partly due to the current suboptimal treatment options: existing psychotropic medications, including antidepressants, antipsychotics, and mood stabilizers, are effective only in a subset of patients or produce partial response and they are often associated with debilitating side effects that discourage adherence. Pharmacogenetics is the study of how genetic information impacts on drug response/side effects with the goal to provide tailored treatments, thereby maximizing efficacy and tolerability. The first pharmacogenetic studies focused on candidate genes, previously known to be relevant to the pharmacokinetics and pharmacodynamics of psychotropic drugs. Results were mainly inconclusive, but some replicated candidates were identified and included as pharmacogenetic biomarkers in drug labeling and in some commercial kits. With the advent of the genomic revolution, it became possible to study the genetic variation on an unprecedented scale, throughout the whole genome with no need of a priori hypothesis. This may lead to the personalized prescription of existing medications and potentially to the development of innovative ones, thanks to new insights into the genetics of mental illness. Promising findings were obtained, but methods for the generation and analysis of genome-wide and sequencing data are still in evolution. Future pharmacogenetic tests may consist of hundreds/thousands of polymorphisms throughout the genome or selected pathways in order to take into account the complex interactions across variants in a number of genes.

Bipolar disorders

Bipolar disorders are chronic and recurrent disorders that affect >1% of the global population. Bipolar disorders are leading causes of disability in young people as they can lead to cognitive and functional impairment and increased mortality, particularly from suicide and cardiovascular disease. Psychiatric and nonpsychiatric medical comorbidities are common in patients and might also contribute to increased mortality. Bipolar disorders are some of the most heritable psychiatric disorders, although a model with gene-environment interactions is believed to best explain the aetiology. Early and accurate diagnosis is difficult in clinical practice as the onset of bipolar disorder is commonly characterized by nonspecific symptoms, mood lability or a depressive episode, which can be similar in presentation to unipolar depression. Moreover, patients and their families do not always understand the significance of their symptoms, especially with hypomanic or manic symptoms. As specific biomarkers for bipolar disorders are not yet available, careful clinical assessment remains the cornerstone of diagnosis. The detection of hypomanic symptoms and longtudinal clinical assessment are crucial to differentiate a bipolar disorder from other conditions. Optimal early treatment of patients with evidence-based medication (typically mood stabilizers and antipsychotics) and psychosocial strategies is necessary.

Recent trends on the role of epigenomics, metabolomics and noncoding RNAs in rationalizing mood stabilizing treatment

Mood stabilizers are the cornerstone in treatment of mood disorders, but their use is characterized by high interindividual variability. This feature has stimulated intensive research to identify predictive biomarkers of response and disentangle the molecular bases of their clinical efficacy. Nevertheless, findings from studies conducted so far have only explained a small proportion of the observed variability, suggesting that factors other than DNA variants could be involved. A growing body of research has been focusing on the role of epigenetics and metabolomics in response to mood stabilizers, especially lithium salts. Studies from these approaches have provided new insights into the molecular networks and processes involved in the mechanism of action of mood stabilizers, promoting a systems-level multiomics synergy. In this article, we reviewed the literature investigating the involvement of epigenetic mechanisms, noncoding RNAs and metabolomic modifications in bipolar disorder and the mechanism of action and clinical efficacy of mood stabilizers.