Psychiatric genetics and the future of personalized treatment

Innovation at the Intersection: Emerging Translational Research in Neurology and Psychiatry

Translational research in neurological and psychiatric diseases is a rapidly advancing field that promises to redefine our approach to these complex conditions [...].

Network-based drug repurposing for schizophrenia

Despite recent progress, the challenges in drug discovery for schizophrenia persist. However, computational drug repurposing has gained popularity as it leverages the wealth of expanding biomedical databases. Network analyses provide a comprehensive understanding of transcription factor (TF) regulatory effects through gene regulatory networks, which capture the interactions between TFs and target genes by integrating various lines of evidence. Using the PANDA algorithm, we examined the topological variances in TF-gene regulatory networks between individuals with schizophrenia and healthy controls. This algorithm incorporates binding motifs, protein interactions, and gene co-expression data. To identify these differences, we subtracted the edge weights of the healthy control network from those of the schizophrenia network. The resulting differential network was then analysed using the CLUEreg tool in the GRAND database. This tool employs differential network signatures to identify drugs that potentially target the gene signature associated with the disease. Our analysis utilised a large RNA-seq dataset comprising 532 post-mortem brain samples from the CommonMind project. We constructed co-expression gene regulatory networks for both schizophrenia cases and healthy control subjects, incorporating 15,831 genes and 413 overlapping TFs. Through drug repurposing, we identified 18 promising candidates for repurposing as potential treatments for schizophrenia. The analysis of TF-gene regulatory networks revealed that the TFs in schizophrenia predominantly regulate pathways associated with energy metabolism, immune response, cell adhesion, and thyroid hormone signalling. These pathways represent significant targets for therapeutic intervention. The identified drug repurposing candidates likely act through TF-targeted pathways. These promising candidates, particularly those with preclinical evidence such as rimonabant and kaempferol, warrant further investigation into their potential mechanisms of action and efficacy in alleviating the symptoms of schizophrenia.

Heart rate variability: Evaluating a potential biomarker of anxiety disorders

Establishing quantifiable biological markers associated with anxiety will increase the objectivity of phenotyping and enhance genetic research of anxiety disorders. Heart rate variability (HRV) is a physiological measure reflecting the dynamic relationship between the sympathetic and parasympathetic nervous systems, and is a promising target for further investigation. This review summarizes evidence evaluating HRV as a potential physiological biomarker of anxiety disorders by highlighting literature related to anxiety and HRV combined with investigations of endophenotypes, neuroimaging, treatment response, and genetics. Deficient HRV shows promise as an endophenotype of pathological anxiety and may serve as a noninvasive index of prefrontal cortical control over the amygdala, and potentially aid with treatment outcome prediction. We propose that the genetics of HRV can be used to enhance the understanding of the genetics of pathological anxiety for etiological investigations and treatment prediction. Given the anxiety-HRV link, strategies are offered to advance genetic analytical approaches, including the use of polygenic methods, wearable devices, and pharmacogenetic study designs. Overall, HRV shows promising support as a physiological biomarker of pathological anxiety, potentially in a transdiagnostic manner, with the heart-brain entwinement providing a novel approach to advance anxiety treatment development.

Mutation Burden Analysis of Six Common Mental Disorders in African Americans by Whole Genome Sequencing

Mental disorders present a global health concern, with limited treatment options. In today's medical practice, medications such as antidepressants are prescribed not only for depression, but also for conditions such as anxiety and attention deficit hyperactivity disorder (ADHD). Therefore, identifying gene targets for specific disorders is important and offers improved precision. In this study, we performed a genetic analysis of six common mental disorders, ADHD, anxiety, depression, delays in mental developments, intellectual disabilities (ID), and speech/language disorder in the ethnic minority of African Americans (AA) using whole genome sequencing (WGS). WGS data was generated from blood-derived DNA from 4178 AA individuals, including 1384 patients with the diagnosis of at least one mental disorder. Mutation burden analysis was applied based on rare and deleterious mutations in the AA population between cases and controls, and further analyzed in the context of patients with single mental disorder diagnosis. Certain genes uncovered demonstrated significant p values in mutation burden analysis. In addition, exclusive recurrences in specific type of disorder were scanned through gene-drug interaction databases to assess for availability of potential medications. We uncovered 15 genes harboring deleterious mutations, including HMGCR and UST for ADHD; FNTB for anxiety, XIRP2, NPPC, , STK33, PANX1 and NTS for depression; RUNX3, TACR1, and NDUFS7 for delays in mental developments; HPN for ID; COL6A3, DDB1, and NDUFA11 for speech/language disorder. Taken together, we have established critical insight into the development of new precision medicine approaches for mental disorders in African Americans.

Convergence and Divergence in the Genetics of Psychiatric Disorders From Pathways to Developmental Stages

In the past decade, the identification of susceptibility genes for psychiatric disorders has become routine, but understanding the biology underlying these discoveries has proven extremely difficult. The large number of potential risk genes and the genetic overlap between disorders are major obstacles for studying the etiology of these conditions. Systems biology approaches relying on gene ontologies, gene coexpression, and protein-protein interactions are used to identify convergence of the genes in relation to biological processes, cell types, brain areas, and developmental stages. Across psychiatric disorders, there is a clear enrichment for genes expressed in the brain and especially in the cortex, but a higher resolution is vastly dependent on sample size and statistical power. There is indication that susceptibility genes tend to be expressed in the brain during periods preceding the typical onset of the disorders. Thus, the role of genes in prenatal brain development is more pronounced for childhood-onset disorders, such as autism spectrum disorder and attention-deficit/hyperactivity disorder, but is much less so for bipolar disorder and depression. One of the most consistent findings across multiple disorders and classes of genetic variants is the role of genes intolerant to mutations in psychiatric disorders, yet this association is more pronounced for disorders with a clear neurodevelopmental component. Notwithstanding, a detailed understanding of the neurobiology of psychiatric disorders is still lacking. It is possible that it will only be revealed by studying the risk genes at the level of the development and function of neuronal networks and circuits.

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.

Enhancing cognition through pharmacological and environmental interventions: Examples from preclinical models of neurodevelopmental disorders

In this review we discuss the role of environmental and pharmacological treatments to enhance cognition with special regards to neurodevelopmental related disorders and aging. How the environment influences brain structure and function, and the interactions between rearing conditions and gene expression, are fundamental questions that are still poorly understood. We propose a model that can explain some of the discrepancies in findings for effects of environmental enrichment on outcome measures. Evidence of a direct causal correlation of nootropics and treatments that enhanced cognition also will be presented, and possible molecular mechanisms that include neurotrophin signaling and downstream pathways underlying these processes are discussed. Finally we review recent findings achieved with a wide set of behavioral and cognitive tasks that have translational validity to humans, and should be useful for future work on devising appropriate therapies. As will be discussed, the collective findings suggest that a combinational therapeutic approach of environmental enrichment and nootropics could be particularly successful for improving learning and memory in both developmental disorders and normal aging.

GWAS of Behavioral Traits

Over the past decade, genome-wide association studies (GWAS) have evolved into a powerful tool to investigate genetic risk factors for human diseases via a hypothesis-free scan of the genome. The success of GWAS for psychiatric disorders and behavioral traits have been somewhat mixed, partly owing to the complexity and heterogeneity of these traits. Significant progress has been made in the last few years in the development and implementation of complex statistical methods and algorithms incorporating GWAS. Such advanced statistical methods applied to GWAS hits in combination with incorporation of different layers of genomics data have catapulted the search for novel genes for behavioral traits and improved our understanding of the complex polygenic architecture of these traits.This chapter will give a brief overview on GWAS and statistical methods currently used in GWAS. The chapter will focus on reviewing the current literature and highlight some of the most important GWAS on psychiatric and other behavioral traits and will conclude with a discussion on future directions.

The functional variant rs334558 of GSK3B is associated with remission in patients with depressive disorders

Purpose

GSK3B and AKT1 genes have been implicated in the pathogenesis of a number of psychiatric and neurological disorders. Furthermore, their genetic variants are associated with response to antidepressant pharmacotherapy. As the evidence is still incomplete and inconsistent, continuing efforts to investigate the role of these two genes in the pathogenesis and treatment of brain disorders is necessary. The aim of our study was thus to evaluate the association of variants of these two genes with depressive disorders and drug treatment response.

Patients and methods

In the present study, 222 patients with a depressive disorder who underwent pharmacological antidepressant treatment were divided into remitters and non-remitters following a 28-day course of pharmacotherapy. The association of a depressive disorder and remission rates with polymorphisms rs334558 in the GSK3B gene and rs1130214 and rs3730358 in the AKT1 gene was evaluated with a chi-square test.

Results

Neither of the studied genetic variants was associated with a depressive disorder. Furthermore, frequencies of alleles and genotypes for rs1130214 and rs3730358 were not different in the groups of remitters and non-remitters. However, the activating allele T of the functional polymorphism rs334558 was significantly associated with remission, when all types of antidepressant drugs were included. This association continued as a trend when only patients taking selective serotonin reuptake inhibitors were considered.

Conclusion

The present study provides support that the functional polymorphism rs334558 of GSK3B may play a role as a useful genetic and pharmacogenetic biomarker in the framework of personalized medicine approach.

Social inequality, scientific inequality, and the future of mental illness

BACKGROUND

Despite five decades of increasingly elegant studies aimed at advancing the pathophysiology and treatment of mental illness, the results have not met expectations. Diagnoses are still based on observation, the clinical history, and an outmoded diagnostic system that stresses the historic goal of disease specificity. Psychotropic drugs are still based on molecular targets developed decades ago, with no increase in efficacy. Numerous biomarkers have been proposed, but none have the requisite degree of sensitivity and specificity, and therefore have no usefulness in the clinic. The obvious lack of progress in psychiatry needs exploration.

METHODS

The historical goals of psychiatry are reviewed, including parity with medicine, a focus on diagnostic reliability rather than validity, and an emphasis on reductionism at the expense of socioeconomic issues. Data are used from Thomas Picketty and others to argue that our failure to advance clinical care may rest in part on the rise in social and economic inequality that began in the 1970s, and in part on our inability to move beyond the medical model of specificity of disease and treatment.

RESULTS

It is demonstrated herein that the historical goal of specificity of disease and treatment has not only impeded the advance of diagnosis and treatment of mental illness, but, in combination with a rapid increase in socioeconomic inequality, has led to poorer outcomes and rising mortality rates in a number of disorders, including schizophrenia, anxiety, and depression.

CONCLUSIONS

It is proposed that Psychiatry should recognize the fact of socioeconomic inequality and its effects on mental disorders. The medical model, with its emphasis on diagnostic and treatment specificity, may not be appropriate for investigation of the brain, given its complexity. The rise of scientific inequality, with billions allocated to connectomics and genetics, may shift attention away from the need for improvements in clinical care. Unfortunately, the future prospects of those suffering from mental illness appear dim.

New drug developments in psychosis: Challenges, opportunities and strategies

All currently approved drugs for schizophrenia work mainly by dopaminergic antagonism. While they are efficacious for psychotic symptoms, their efficacy is limited for negative symptoms and cognitive deficits which underlie the substantive disability in this illness. Recent insights into the biological basis of schizophrenia, especially in relation to non-dopaminergic mechanisms, have raised the efforts to find novel and effective drug targets, though with relatively little success thus far. Potential impediments to novel drug discovery include the continued use of symptom based disease definitions which leads to etiological and pathophysiological heterogeneity, lack of valid preclinical models for drug testing, and design limitations in clinical trials. These roadblocks can be addressed by (i) characterizing trans-diagnostic, translational pathophysiological dimensions as potential treatment targets, (ii) efficiency, accountability and, transparency in approaches to the clinical trials process, and (iii) leveraging recent advances in genetics and in vitro phenotypes. Accomplishing these goals is urgent given the significant unmet needs in the pharmacological treatment of schizophrenia. As this happens, it is imperative that clinicians employ optimal dosing, measurement-based care, and other best practices in utilizing existing treatments to optimize outcomes for their patients today.

Oxytocin and Anxiety Disorders

In the present chapter, we review the literature focusing on oxytocin (OT)-centered research in anxiety spectrum conditions, comprising separation anxiety disorder, specific phobias, social anxiety disorder (SAD), panic disorder, generalized anxiety disorder, and anxiety-related endophenotypes (e.g., trust behavior, behavioral inhibition, neuroticism, and state/trait anxiety). OT receptor gene (OXTR) polymorphisms have been implicated in gene-environment interactions with attachment style and childhood maltreatment and to influence clinical outcomes, including SAD intensity and limbic responsiveness. Epigenetic OXTR DNA methylation patterns have emerged as a link between categorical, dimensional, neuroendocrinological, and neuroimaging SAD correlates, highlighting them as potential peripheral surrogates of the central oxytocinergic tone. A pathophysiological framework of OT integrating the dynamic nature of epigenetic biomarkers and the summarized genetic and peripheral evidence is proposed. Finally, we emphasize opportunities and challenges of OT as a key network node of social interaction and fear learning in social contexts. In conjunction with multi-level investigations incorporating a dimensional understanding of social affiliation and avoidance in anxiety spectrum disorders, these concepts will help to promote research for diagnostic, state, and treatment response biomarkers of the OT system, advancing towards indicated preventive interventions and personalized treatment approaches.

Toward a Global Roadmap for Precision Medicine in Psychiatry: Challenges and Opportunities

Mental disorders represent a major public health burden worldwide. This is likely to rise in the next decade, with the highest increases predicted to occur in low- and middle-income countries. Current psychotropic medication treatment guidelines focus on uniform approaches to the treatment of heterogeneous disorders and achieve only partial therapeutic success. Developing a global precision medicine approach in psychiatry appears attractive, given the value of this approach in other fields of medicine, such as oncology and infectious diseases. In this horizon scanning analysis, we review the salient opportunities and challenges for precision medicine in psychiatry over the next decade. Variants within numerous genes involved in a range of pathways have been implicated in psychotropic drug response and might ultimately be used to guide choice of pharmacotherapy. Multipronged approaches such as multi-omics (genomics, proteomics, metabolomics) analyses and systems diagnostics together with high-throughput sequencing and genotyping technologies hold promise for identifying precise and targeted treatments in mental disorders. To date, however, the vast majority of pharmacogenomics work has been undertaken in high-income countries on a relatively small proportion of the global population, and many other challenges face the field. Opportunities and challenges for establishing a global roadmap for precision medicine in psychiatry are discussed in this article.

Novel developments in genetic and epigenetic mechanisms of anxiety

PURPOSE OF REVIEW

The present review aims to deliver a systematic overview of current developments and trends in (epi)genetics of anxiety and to identify upcoming challenges and opportunities.

RECENT FINDINGS

Genes related to peptide and hormone signaling have been suggested for anxiety-related phenotypes, e.g., the NPSR1 gene, which has been associated predominantly with panic disorder in women, and shown to interact with environmental factors and to influence psychometric, neurophysiological, and neuroimaging correlates of anxiety. Similar multi-level results have been reported for genetic and epigenetic variation in the OXTR gene, especially in social anxiety disorder (SAD), and for CRHR1 gene variation in women with panic disorder. Variants in RGS2 and ASIC1 genes were linked to panic disorder, with the latter also being implicated in SAD treatment response. Finally, monoaminergic 'risk' genes (SLC6A4, MAOA, HTR1A) were related to SAD, generalized anxiety disorder and women with panic disorder, anxiety traits and response to psychopharmacological and psychotherapeutic interventions.

SUMMARY

Converging evidence for potential genetic and epigenetic risk markers has been gathered and future studies call for independent replications and multi-level integration of dimensional approaches, environmental factors, and biological readouts, while considering sex-specific substratification. Particularly, epigenetic variation appears promising for disease course and treatment response predictions.

The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders

Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories-posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders-for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene-environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research.