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

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

RATIONALE

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers

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

Effect of pharmacogenomic testing on pediatric mental health outcome: a 6-month follow-up

Aim: This retrospective, case-control study evaluated the effect of pharmacogenomic testing (PGT) on the management of pediatrics with anxiety, major depressive disorder (MDD) and attention-deficit/hyperactivity disorder (ADHD). Methods: The authors examined psychiatric diagnoses, medication histories, CYP450 profiles, SLC6A4, HTR2A, COMT and MTHFR. Results: The authors found no difference in clinical improvement between the two groups. However, the number of medication changes was significantly larger after PGT. The treatment response in MDD and anxiety was not different between the groups, while ADHD treatment response was substantially improved in PGT and correlated with COMT status. Conclusion: PGT had some value with ADHD with doubtful benefit for MDD or anxiety disorders. Accordingly, pediatric indications must be weighed against cost, utility and clinician experience. Limitations included sample size and selection bias.

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.

An individualized medication model of sodium valproate for patients with bipolar disorder based on machine learning and deep learning techniques

Valproic acid/sodium valproate (VPA) is a widely used anticonvulsant drug for maintenance treatment of bipolar disorders. In order to balance the efficacy and adverse events of VPA treatment, an individualized dose regimen is necessary. This study aimed to establish an individualized medication model of VPA for patients with bipolar disorder based on machine learning and deep learning techniques. The sequential forward selection (SFS) algorithm was applied for selecting a feature subset, and random forest was used for interpolating missing values. Then, we compared nine models using XGBoost, LightGBM, CatBoost, random forest, GBDT, SVM, logistic regression, ANN, and TabNet, and CatBoost was chosen to establish the individualized medication model with the best performance (accuracy = 0.85, AUC = 0.91, sensitivity = 0.85, and specificity = 0.83). Three important variables that correlated with VPA daily dose included VPA TDM value, antipsychotics, and indirect bilirubin. SHapley Additive exPlanations was applied to visually interpret their impacts on VPA daily dose. Last, the confusion matrix presented that predicting a daily dose of 0.5 g VPA had a precision of 55.56% and recall rate of 83.33%, and predicting a daily dose of 1 g VPA had a precision of 95.83% and a recall rate of 85.19%. In conclusion, the individualized medication model of VPA for patients with bipolar disorder based on CatBoost had a good prediction ability, which provides guidance for clinicians to propose the optimal medication regimen.

Stress exposure and well-being: correlates of meeting criteria for bipolar disorder, borderline personality disorder, or both

PURPOSE

Bipolar and borderline personality disorders share similar features, are challenging to differentiate and sometimes co-occur in the same individual. This paper compares people with bipolar, borderline, both or neither, analyzing sociodemographic characteristics, lifetime exposure to stressors, and emotional, social, and physical wellbeing to illuminate differences in life experiences associated with expressing symptoms consistent with bipolar, borderline, or both.

METHODS

Data were analyzed from the 2012-13 National Epidemiological Survey on Alcohol and Related Conditions (NESARC-III), N = 36,309. Survey participants were classified as bipolar (N = 488, 1.3%), borderline (N = 1758, 4.8%), both (N = 388, 1.1%), or neither (N = 33,675, 92.8%). Differences between these groups regarding demographics, adverse childhood experiences, recent stressors, lifetime trauma, psychiatric co-morbidities, and emotional, social, and physical wellbeing were assessed with the adjusted Wald F test.

RESULTS

People with bipolar were more likely to also have borderline (44.3%) than the reverse (18.1%). People with both disorders were least advantaged socioeconomically, most exposed to stressors and traumas across the life course, and had the worst wellbeing emotionally, socially, and physically. Differences between people with both disorders vs. borderline only were smaller than between people with borderline vs. bipolar, although bipolar disorder was associated with considerable hardship relative to having neither disorder.

CONCLUSION

Borderline personality disorder alone or in combination with bipolar is associated with worse economic, social, and health outcomes than bipolar alone. Borderline can resolve with evidence-based treatment, and it is critical to correctly differentiate between the two conditions, so people with borderline and/or bipolar have the optimum chance for recovery.

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

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

Activating SIRT-1 Signalling with the Mitochondrial-CoQ10 Activator Solanesol Improves Neurobehavioral and Neurochemical Defects in Ouabain-Induced Experimental Model of Bipolar Disorder

Bipolar disorder (BD) is a chronic mental illness characterized by mood fluctuations that range from depressive lows to manic highs. Several studies have linked the downregulation of SIRT-1 (silent mating type information regulation-2 homologs) signaling to the onset of BD and other neurological dysfunctions. This research aimed to look into the neuroprotective potential of Solanesol (SNL) in rats given ICV-Ouabain injections, focusing on its effect on SIRT-1 signaling activation in the brain. Ouabain, found in hypothalamic and medullary neurons, is an endogenous inhibitor of brain Na⁺/K⁺ ATPase. The inhibition of brain Na⁺/K⁺ ATPase by Ouabain may also result in changes in neurotransmission within the central nervous system. SNL is a Solanaceae family active phytoconstituent produced from the plant Nicotiana tabacum. SNL is used as a precursor for the production of CoQ10 (Coenzyme Q10), a powerful antioxidant and neuroprotective compound. In the current study, lithium (Li), an important mood stabilizer drug, was used as a control. This study looked at the neuroprotective potential of SNL at dosages of 40 and 80 mg/kg in ICV-OUA injections that caused BD-like neurobehavioral and neurochemical defects in Wistar rats. Wistar rats were placed into eight groups (n = 6) and administered 1 mM/0.5 µL ICV-OUA injections for three days. Neurochemical assessments were done in rat brain homogenates, CSF, and blood plasma samples at the end of the experiment protocol schedule. Long-term SNL and lithium administration have been shown to decrease the number of rearing and crossings and reduce time spent in the center, locomotor activities, and immobility time. Solansesol treatment gradually raises the amount of Na⁺/K⁺ ATPase, limiting the severity of behavioural symptoms. These findings also revealed that SNL increases the levels of SIRT-1 in CSF, blood plasma, and brain homogenate samples. Moreover, in rat brain homogenates and blood plasma samples, SNL modulates apoptotic markers such as Caspase-3, Bax (pro-apoptotic), and Bcl-2 (anti-apoptotic). Mitochondrial-ETC complex enzymes, including complex-I, II, IV, V, and CoQ10, were also restored following long-term SNL treatment. Furthermore, SNL lowered inflammatory cytokines (TNF-α, IL-1β) levels while restoring neurotransmitter levels (serotonin, dopamine, glutamate, and acetylcholine) and decreasing oxidative stress markers. Histological examinations also validated Solanesol’s protective effect. As a result, our findings suggest that SNL, as a SIRT-1 signalling activator, may be a promising therapeutic approach for BD-like neurological dysfunctions.

Prefrontal cortical thickness and clinical characteristics of long-term treatment response to valproate in bipolar disorder

Valproate compositions are frequently used to treat bipolar disorder (BD); however, 87% of patients do not report full response in the long-term. There is scarce information about the clinical features and brain structural characteristics of long-term treatment response (LTTR) to this medication. In this study, we aim to evaluate the clinical characteristics and prefrontal cortical thickness (CT) of LTTR to valproate in BD. We evaluated 30 BD outpatients on valproate treatment, and 20 controls with a 3T T1-weighted 3D brain scan and Alda's scale for LTTR. An analysis of covariance was used to evaluate CT measures and a logistic regression was conducted to predict the full response (FR) using clinical features and CT measures. Patients with an insufficient response (IR) reported thinner right frontal eye fields, anterior and dorsolateral prefrontal cortexes compared with controls. FR patients presented thicker right dorsolateral prefrontal cortex than IR and no differences with controls. Patients with mixed features presented increased odds of achieving FR, while CT measures reported non-significant results. This is the first study to report mixed features as a clinical predictor of valproate LTTR. Our findings also suggest better preservation of the right prefrontal cortex of subjects with FR to valproate.

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.

Genetic Variations Associated with Long-Term Treatment Response in Bipolar Depression

Several pharmacogenetic-based decision support tools for psychoactive medication selection are available. However, the scientific evidence of the gene-drug pairs analyzed is mainly based on pharmacogenetic studies in patients with major depression or schizophrenia, and their clinical utility is mostly assessed in major depression. This study aimed at evaluating the impact of individual genes, with pharmacogenetic relevance in other psychiatric conditions, in the response to treatment in bipolar depression. Seventy-six patients diagnosed with bipolar disorder and an index major depressive episode were included in an observational retrospective study. Sociodemographic and clinical data were collected, and all patients were genotyped using a commercial multigene pharmacogenomic-based tool (Neuropharmagen^®, AB-Biotics S.A., Barcelona, Spain). Multiple linear regression was used to identify pharmacogenetic and clinical predictors of efficacy and tolerability of medications. The pharmacogenetic variables response to serotonin-norepinephrine reuptake inhibitors (SNRIs) (ABCB1) and reduced metabolism of quetiapine (CYP3A4) predicted patient response to these medications, respectively. ABCB1 was also linked to the tolerability of SNRIs. An mTOR-related multigenic predictor was also associated with a lower number of adverse effects when including switch and autolytical ideation. Our results suggest that the predictors identified could be useful to guide the pharmacological treatment in bipolar disorder. Additional clinical studies are necessary to confirm these findings.

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.

Increasing engagement in pharmacology and pharmacogenetics education using games and online resources: The PharmacoloGenius mobile app

Mobile applications represent useful instruments to convey information and engage the users even during traveling, thanks to the wide diffusion of smartphones, tablets, smartwatches, and similar devices. As such, they have high potential as learning tools that can act complementary to traditional teaching approaches. In the field of pharmacology, mobile applications are increasingly being used to improve adherence of patients or to help them report suspect adverse drug reactions. However, they have been scarcely applied to pharmacology education. In this article, we present PharmacoloGenius, a free Android mobile application integrating resources useful for students as well as healthcare professionals or researchers to expand knowledge on pharmacological topics. We gave particular emphasis to pharmacogenetics, as it is a fundamental tool to achieve personalized treatment. The application offers original games such as pharmacological trivia based on textbooks or special "journal club" trivia based on research articles conveying the state of the art on specific topics. Additionally, the app offers a curated list of online resources to study pharmacology and pharmacogenetics (e.g., free online courses, videos, and databases) as well as updated news on conferences, grants, and opportunities for pharmacologists. In conclusion, PharmacoloGenius aims to be a useful instrument for people interested in expanding their knowledge on pharmacology in an engaging way.

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.

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.

Clinical, genetic, and brain imaging predictors of risk for bipolar disorder in high-risk individuals

Introduction: Early detection and intervention in bipolar disorder (BD) might reduce illness severity, slow its progression, and, in specific cases, even ward off the full-blown disorder. Therefore, identifying at-risk individuals and targeting them promptly before the illness onset is of the utmost importance. In the last decades, there has been a significant effort aimed at identifying genetic and molecular factors able to modulate risk and pharmacological outcomes.Areas covered: We performed a narrative review of articles aimed at identifying clinical, genetics, molecular, and brain imaging markers of BD specifically focusing on samples of individuals at high-risk for BD. Special emphasis was put on studies applying an integrative design, e.g. studies combining different markers such as genetic and brain imaging.Expert opinion: Findings from studies in risk individuals are still too sparse to allow drawing definite conclusions. However, the high potentiality of longitudinal studies in individuals considered at risk to develop BD supports the need for more efforts. Future investigations should focus on more homogeneous subpopulations and evaluate the cross-linking between clinical, genetic, and brain morphostructural/functional neuroimaging characteristics as predictors of risk for 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.

Evidence that genes involved in hedgehog signaling are associated with both bipolar disorder and high BMI

Patients with bipolar disorder (BD) show higher frequency of obesity and type 2 diabetes (T2D), but the underlying genetic determinants and molecular pathways are not well studied. Using large publicly available datasets, we (1) conducted a gene-based analysis using MAGMA to identify genes associated with BD and body mass index (BMI) or T2D and investigated their functional enrichment; and (2) performed two meta-analyses between BD and BMI, as well as BD and T2D using Metasoft. Target druggability was assessed using the Drug Gene Interaction Database (DGIdb). We identified 518 and 390 genes significantly associated with BD and BMI or BD and T2D, respectively. A total of 52 and 12 genes, respectively, were significant after multiple testing correction. Pathway analyses conducted on nominally significant targets showed that genes associated with BD and BMI were enriched for the Neuronal cell body Gene Ontology (GO) term (p = 1.0E-04; false discovery rate (FDR) = 0.025) and different pathways, including the Signaling by Hedgehog pathway (p = 4.8E-05, FDR = 0.02), while genes associated with BD and T2D showed no specific enrichment. The meta-analysis between BD and BMI identified 64 relevant single nucleotide polymorphisms (SNPs). While the majority of these were located in intergenic regions or in a locus on chromosome 16 near and in the NPIPL1 and SH2B1 genes (best SNP: rs4788101, p = 2.1E-24), five were located in the ETV5 gene (best SNP: rs1516725, p = 1E-24), which was previously associated with both BD and obesity, and one in the RPGRIP1L gene (rs1477199, p = 5.7E-09), which was also included in the Signaling by Hedgehog pathway. The meta-analysis between BD and T2D identified six significant SNPs, three of which were located in ALAS1 (best SNP: rs352165, p = 3.4E-08). Thirteen SNPs associated with BD and BMI, and one with BD and T2D, were located in genes which are part of the druggable genome. Our results support the hypothesis of shared genetic determinants between BD and BMI and point to genes involved in Hedgehog signaling as promising targets.

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.

Association between Copy Number Variation and Response to Social Skills Training in Autism Spectrum Disorder

Challenges in social communication and interaction are core features of autism spectrum disorder (ASD) for which social skills group training (SSGT) is a commonly used intervention. SSGT has shown modest and heterogeneous effects. One of the major genetic risk factors in ASD is rare copy number variation (CNV). However, limited information exists whether CNV profiles could be used to aid intervention decisions. Here, we analyzed the rare genic CNV carrier status for 207 children, of which 105 received SSGT and 102 standard care as part of a randomized clinical trial for SSGT. We found that being a carrier of rare genic CNV did not have an impact on the SSGT outcome measured by the parent-report Social Responsiveness Scale (SRS). However, when stratifying by pathogenicity and size of the CNVs, we identified that carriers of clinically significant and large genic CNVs (>500 kb) showed inferior SRS outcomes at post-intervention (P = 0.047 and P = 0.036, respectively) and follow-up (P = 0.008 and P = 0.072, respectively) when adjusting for standard care effects. Our study provides preliminary evidence that carriers of clinically significant and large genic CNVs might not benefit as much from SSGT as non-carriers. Our results indicate that genetic information might help guide the modifications of interventions in ASD.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Biomarkers for bipolar disorder: current status and challenges ahead

INTRODUCTION

Bipolar disorder (BD) is a chronic psychiatric disorder marked by clinical and pathophysiological heterogeneity. There is a high expectation that personalized approaches can improve the management of patients with BD. For that, identification and validation of potential biomarkers are fundamental. Areas covered: This manuscript will critically review the current status of different biomarkers for BD, including peripheral, genetic, neuroimaging, and neurophysiological candidates, discussing the challenges to move the field forward. Expert commentary: There are no lab or complementary tests currently recommended for the diagnosis or management of patients with BD. Panels composed by multiple biomarkers will probably contribute to stratifying patients according to their clinical stage, therapeutic response, and prognosis.

Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?

Clinical practice guidelines identify lithium as a first line treatment for mood stabilization and reduction of suicidality in bipolar disorders (BD); however, most individuals show sub-optimal response. Identifying biomarkers for lithium response could enable personalization of treatment and refine criteria for stratification of BD cases into treatment-relevant subgroups. Existing systematic reviews identify potential biomarkers of lithium response, but none directly address the conceptual issues that need to be addressed to enhance translation of research into precision prescribing of lithium. For example, although clinical syndrome subtyping of BD has not led to customized individual treatments, we emphasize the importance of assessing clinical response phenotypes in biomarker research. Also, we highlight the need to give greater consideration to the quality of prospective longitudinal monitoring of illness activity and the differentiation of non-response from partial or non-adherence with medication. It is unlikely that there is a single biomarker for lithium response or tolerability, so this review argues that more research should be directed toward the exploration of biosignatures. Importantly, we emphasize that an integrative science approach may improve the likelihood of discovering the optimal combination of clinical factors and multimodal biomarkers (e.g., blood omics, neuroimaging, and actigraphy derived-markers). This strategy could uncover a valid lithium response phenotype and facilitate development of a composite prediction algorithm. Lastly, this narrative review discusses how these strategies could improve eligibility criteria for lithium treatment in BD, and highlights barriers to translation to clinical practice including the often-overlooked issue of the cost-effectiveness of introducing biomarker tests in psychiatry.