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

Genomic and neuroimaging approaches to bipolar disorder

BACKGROUND: To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder. AIMS: To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies. METHOD: We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings. RESULTS: ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder. CONCLUSIONS: The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder

Cognitive outcome and gamma noise power unrelated to neuregulin 1 and 3 variation in schizophrenia

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License.[Background]: Neuregulins are a family of signalling proteins that orchestrate a broad range of cellular responses. Four genes encoding Neuregulins 1-4 have been identified so far in vertebrates. Among them, Neuregulin 1 and Neuregulin 3 have been reported to contribute to an increased risk for developing schizophrenia. We hypothesized that three specific variants of these genes (rs6994992 and rs3924999 for Neuregulin 1 and rs10748842 for Neuregulin 3) that have been related to this illness may modify information processing capacity in the cortex, which would be reflected in electrophysiological parameters (P3b amplitude or gamma noise power) and/or cognitive performance. [Methods]: We obtained DNA from 31 patients with schizophrenia and 23 healthy controls and analyzed NRG1 rs6994992, NRG1 rs3924999 and NRG3 rs10748842 promoter polymorphisms by allelic discrimination with real-time polymerase chain reaction (PCR). We compared cognitive outcome, P300 amplitude parameters and an electroencephalographic measure of noise power in the gamma band between the groups dichotomized according to genotype. [Results]: Contrary to our hypothesis, we could not detect any significant influence of variation in Neuregulin 1/Neuregulin 3 polymorphisms on cognitive performance or electrophysiological parameters of patients with schizophrenia. [Conclusions]: Despite our findings, we cannot discard that other genetic variants and, more likely, interactions between those variants and with genetic variation related to different pathways may still influence cerebral processing in schizophrenia.Funding for this study was provided by the Instituto de Salud Carlos III Grants 080017 and 1102203 to VM, Gerencia Regional de Salud de Castilla y León GRS 249/A/08 and 613/A/11, a postdoctoral Marie Curie Intra European Fellowship within the 7th European Commission Framework Programme for Research and Innovation (330156-CODIP) to ÁD, a predoctoral research grant from the Consejería de Educación - Junta de Castilla y León and the European Social Fund to ÁD (EDU/1486/2008) and CC (EDU/1064/2009), a predoctoral scholarship from the University of Salamanca and Santander Bank to VS, and the FIS Grant PI 1000219 to RG.Peer Reviewe

Association of Insulin Resistance With Schizophrenia Polygenic Risk Score and Response to Antipsychotic Treatment

This study examines the association between insulin resistance, schizophrenia polygenic risk, and treatment outcomes in first-episode, antipsychotic-naive patients with schizophrenia.Funding/Support: This work was supported by grants from the Stanley Medical Research Institute (Dr Bahn)

Peripheral lymphocyte signaling pathway deficiencies predict treatment response in first-onset drug-naïve schizophrenia

Despite being a major cause of disability worldwide, the pathophysiology of schizophrenia and molecular basis of treatment response heterogeneity continue to be unresolved. Recent evidence suggests that multiple aspects of pathophysiology, including genetic risk factors, converge on key cell signaling pathways and that exploration of peripheral blood cells might represent a practical window into cell signaling alterations in the disease state. We employed multiplexed phospho-specific flow cytometry to examine cell signaling epitope expression in peripheral blood mononuclear cell (PBMC) subtypes in drug-naïve schizophrenia patients (n = 49) relative to controls (n = 61) and relate these changes to serum immune response proteins, schizophrenia polygenic risk scores and clinical effects of treatment, including drug response and side effects, over the longitudinal course of antipsychotic treatment. This revealed both previously characterized (Akt1) and novel cell signaling epitopes (IRF-7 (pS477/pS479), CrkL (pY207), Stat3 (pS727), Stat3 (pY705) and Stat5 (pY694)) across PBMC subtypes which were associated with schizophrenia at disease onset, and correlated with type I interferon-related serum molecules CD40 and CXCL11. Alterations in Akt1 and IRF-7 (pS477/pS479) were additionally associated with polygenic risk of schizophrenia. Finally, changes in Akt1, IRF-7 (pS477/pS479) and Stat3 (pS727) predicted development of metabolic and cardiovascular side effects following antipsychotic treatment, while IRF-7 (pS477/pS479) and Stat3 (pS727) predicted early improvements in general psychopathology scores measured using the Brief Psychiatric Rating Scale (BPRS). These findings suggest that peripheral blood cells can provide an accessible surrogate model for intracellular signaling alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic and cardiovascular side effects following antipsychotic therapy

Proteomics for blood biomarker exploration of severe mental illness: pitfalls of the past and potential for the future

Recent improvements in high-throughput proteomic approaches are likely to constitute an essential advance in biomarker discovery, holding promise for improved personalized care and drug development. These methodologies have been applied to study multivariate protein patterns and provide valuable data of peripheral tissues. To highlight findings of the last decade for three of the most common psychiatric disorders, namely schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), we queried PubMed. Here we delve into the findings from thirty studies, which used proteomics and multiplex immunoassay approaches for peripheral blood biomarker exploration. In an explorative approach, we ran enrichment analyses in peripheral blood according to these results and ascertained the overlap between proteomic findings and genetic loci identified in genome-wide association studies (GWAS). The studies we appraised demonstrate that proteomics for psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results constraining the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges for the implementation of proteomic signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of proteomics in mental disease diagnostics, future research will need large, well-defined cohorts in combination with state-of-the-art technologies

Pathway sensor-based functional genomics screening identifies modulators of neuronal activity

Neuronal signal transduction shapes brain function and malfunction may cause mental disorders. Despite the existence of functional genomics screens for proliferation and toxicity, neuronal signalling has been difficult to address so far. To overcome this limitation, we developed a pooled screening assay which combines barcoded activity reporters with pooled genetic perturbation in a dual-expression adeno-associated virus (AAV) library. With this approach, termed pathScreener, we comprehensively dissect signalling pathways in postmitotic neurons. This overcomes several limitations of lentiviral-based screens. By applying first a barcoded and multiplexed reporter assay, termed cisProfiler, we identified the synaptic-activity responsive element (SARE) as top performance sensor of neuronal activity. Next, we targeted more than 4,400 genes and screened for modulatory effects on SARE activity in primary cortical neurons. We identified with high replicability many known genes involved in glutamatergic synapse-to-nucleus signalling of which a subset was validated in orthogonal assays. Several others have not yet been associated with the regulation of neuronal activity such as the hedgehog signalling members Ptch2 and Ift57. This assay thus enhances the toolbox for analysing regulatory processes during neuronal signalling and may help identifying novel targets for brain disorders

Drug discovery for psychiatric disorders using high-content single-cell screening of signaling network responses ex vivo

There is a paucity of efficacious new compounds to treat neuropsychiatric disorders. We present a novel approach to neuropsychiatric drug discovery based on high-content characterization of druggable signaling network responses at the single-cell level in patient-derived lymphocytes ex vivo. Primary T lymphocytes showed functional responses encompassing neuropsychiatric medications and central nervous system ligands at established (e.g., GSK-3?) and emerging (e.g., CrkL) drug targets. Clinical application of the platform to schizophrenia patients over the course of antipsychotic treatment revealed therapeutic targets within the phospholipase C?1-calcium signaling pathway. Compound library screening against the target phenotype identified subsets of L-type calcium channel blockers and corticosteroids as novel therapeutically relevant drug classes with corresponding activity in neuronal cells. The screening results were validated by predicting in vivo efficacy in an independent schizophrenia cohort. The approach has the potential to discern new drug targets and accelerate drug discovery and personalized medicine for neuropsychiatric conditions

Exploring cellular markers of metabolic syndrome in peripheral blood mononuclear cells across the neuropsychiatric spectrum

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy.This work was supported by grants from the Stanley Medical Research Institute (SMRI); the Engineering and Physical Sciences Research Council UK (EPSRC); the Dutch Government-funded Virgo consortium (ref. FES0908); the Netherlands Genomics Initiative (ref. 050-060-452); the European Union FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (ref. 286334, PSYCH-AID project); SAF2016-76046-R and SAF2013-46292-R (MINECO) and PI16/00156 (isciii and FEDER)

The Future of Diagnosis in Clinical Neurosciences: Comparing Multiple Sclerosis and Schizophrenia

The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries