The druggable schizophrenia genome: from repurposing opportunities to unexplored drug targets

Genetic architecture of RNA editing, splicing and gene expression in schizophrenia

Genome wide association studies (GWAS) have been conducted over the past decades to investigate the underlying genetic origin of neuropsychiatric diseases, such as schizophrenia (SCZ). While these studies demonstrated the significance of disease-phenotype associations, there is a pressing need to fully characterize the functional relevance of disease-associated genetic variants. Functional genetic loci can affect transcriptional and post-transcriptional phenotypes that may contribute to disease pathology. Here, we investigate the associations between genetic variation and RNA editing, splicing, and overall gene expression through identification of quantitative trait loci (QTL) in the CommonMind Consortium SCZ cohort. We find that editing QTL (edQTL), splicing QTL (sQTL) and expression QTL (eQTL) possess both unique and common gene targets, which are involved in many disease-relevant pathways, including brain function and immune response. We identified two QTL that fall into all three QTL categories (seedQTL), one of which, rs146498205, targets the lincRNA gene, RP11-156P1.3. In addition, we observe that the RNA binding protein AKAP1, with known roles in neuronal regulation and mitochondrial function, had enriched binding sites among edQTL, including the seedQTL, rs146498205. We conduct colocalization with various brain disorders and find that all QTL have top colocalizations with SCZ and related neuropsychiatric diseases. Furthermore, we identify QTL within biologically relevant GWAS loci, such as in ELA2, an important tRNA processing gene associated with SCZ risk. This work presents the investigation of multiple QTL types in parallel and demonstrates how they target both distinct and overlapping SCZ-relevant genes and pathways.

IUPHAR review: Drug repurposing in Schizophrenia - An updated review of clinical trials

There is an urgent need for mechanistically novel and more efficacious treatments for schizophrenia, especially those targeting negative and cognitive symptoms with a more favorable side-effect profile. Drug repurposing-the process of identifying new therapeutic uses for already approved compounds-offers a promising approach to overcoming the lengthy, costly, and high-risk process of traditional CNS drug discovery. This review aims to update our previous findings on the clinical drug repurposing pipeline in schizophrenia. We examined studies conducted between 2018 and 2024, identifying 61 trials evaluating 40 unique repurposed drug candidates. These encompassed a broad range of pharmacological mechanisms, including immunomodulation, cognitive enhancement, and hormonal, metabolic, and neurotransmitter modulation. A notable development is the combination of the muscarinic modulators xanomeline, a compound with antipsychotic properties, and trospium, included to mitigate peripheral side effects, now approved by the FDA as the first antipsychotic drug in decades with a fundamentally novel mechanism of action. Moving beyond the traditional dopaminergic paradigm of schizophrenia, such findings highlight opportunities to improve treatment-resistant symptoms and alleviate adverse effects. Overall, the evolving drug repurposing landscape illustrates a significant shift in the rationale for schizophrenia drug development, highlighting the potential of in silico strategies, biomarker-based patient stratification, and personalized treatments that align with underlying pathophysiological processes.

Identification of Hub Genes Involved in Early-onset Schizophrenia: From Genetic Susceptibility to Predicted Regulated Gene Expression

BACKGROUND

Despite a high heritability of schizophrenia (SZ), only limited variance was attributed to gene loci or the polygenic risk score in genome-wide association studies (GWAS). Early-onset SZ, a more homogeneous SZ subtype, may aid in bridging the genotype-phenotype gap and the identification of its hub genes is critical for early intervention in clinical practice. We aimed to examine the gene expression risk score (GeRS) in patients from both multiplex and simplex families to identify hub genes for early-onset SZ, and perform enrichment analysis to understand the biological functions of the hub genes.

METHODS

Based on the GWAS genotype data from patients with SZ in multiplex families (223 early-onset and 372 late-onset) and those from simplex families (matched for sex and onset age), GeRSs for SZ (SZ-GeRSs) were estimated using the SNP-expression prediction model derived from existing brain tissues of patients with psychiatric disorders. Module-based SZ-GeRS was summed over genes from empirically derived gene clusters, network analysis was conducted to identify hub genes, and enrichment analysis was used for functional mapping.

RESULTS

Among the 13 modules from existing coexpression analyses of postmortem brains of patients with psychiatric disorders, the meta-analysis revealed that associations with early-onset SZ existed for the GeRS of module 10 in subset, M10sub-GeRS (adjusted odds ratio [aOR] = 1.38, 95% CI = 1.22-1.57), and six hub genes, M10hub-GeRS (aOR = 1.22, 95% CI = 1.07-1.39), after adjustment for covariates. Functional mapping of the genes revealed their enrichment in excitatory neurons and immune-regulatory pathways.

CONCLUSIONS

GeRS for SZ helps identify six hub genes for early-onset schizophrenia, and the enrichment analysis sheds light on their possible roles in the pathophysiology. These findings will enhance the understanding of SZ etiology and may contribute to early screening and personalized prevention efforts.

Overview of the Knowledge Management Center for Illuminating the Druggable Genome

The Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) project aims to aggregate, update, and articulate protein-centric data knowledge for the entire human proteome, with emphasis on the understudied proteins from the three IDG protein families. KMC collates and analyzes data from over 70 resources to compile the Target Central Resource Database (TCRD), which is the web-based informatics platform (Pharos). These data include experimental, computational, and text-mined information on protein structures, compound interactions, and disease and phenotype associations. Based on this knowledge, proteins are classified into different Target Development Levels (TDLs) for identification of understudied targets. Additional work by the KMC focuses on enriching target knowledge and producing DrugCentral and other data visualization tools for expanding investigation of understudied targets.

Large-Scale Mendelian Randomization Study Reveals Circulating Blood-based Proteomic Biomarkers for Psychopathology and Cognitive Task Performance

Background

Research on peripheral (e.g., blood-based) biomarkers for psychiatric illness has typically been low-throughput in terms of both the number of subjects and the range of assays performed. Moreover, traditional case-control studies examining blood-based biomarkers are subject to potential confounds of treatment and other exposures common to patients with psychiatric illnesses. Our research addresses these challenges by leveraging large-scale, high-throughput proteomics data and Mendelian Randomization (MR) to examine the causal impact of circulating proteins on psychiatric phenotypes and cognitive task performance.

Methods

We utilized plasma proteomics data from the UK Biobank (3,072 proteins assayed in 34,557 European-ancestry individuals) and deCODE Genetics (4,719 proteins measured across 35,559 Icelandic individuals). Significant proteomic quantitative trait loci (both cis-pQTLs and trans-pQTLs) served as MR instruments, with the most recent GWAS for schizophrenia, bipolar disorder, major depressive disorder, and cognitive task performance (all excluding overlapping UK Biobank participants) as phenotypic outcomes.

Results

MR revealed 109 Bonferroni-corrected causal associations (44 novel) involving 88 proteins across the four phenotypes. Several immune-related proteins, including interleukins and complement factors, stood out as pleiotropic across multiple outcome phenotypes. Drug target enrichment analysis identified several novel potential pharmacologic repurposing opportunities, including anti-inflammatory agents for schizophrenia and bipolar disorder and duloxetine for cognitive performance.

Conclusions

Identification of causal effects for these circulating proteins suggests potential biomarkers for these conditions and offers insights for developing innovative therapeutic strategies. The findings also indicate substantial evidence for the pleiotropic effects of many proteins across different phenotypes, shedding light on the shared etiology among psychiatric conditions and cognitive ability.

Challenges, unmet needs and future directions - a critical evaluation of the clinical trial landscape in schizophrenia research

INTRODUCTION

Developing novel antipsychotic mechanisms of action and repurposing established compounds for the treatment of schizophrenia is of utmost importance to improve relevant symptom domains and to improve the risk/benefit ratio of antipsychotic compounds. Novel trial design concepts, pathophysiology-based targeted treatment approaches, or even the return to old values may improve schizophrenia outcomes in the future.

AREAS COVERED

In this review of the clinical trial landscape in schizophrenia, we present an overview of the challenges and gaps in current clinical trials and elaborate on potential solutions to improve the outcomes of people with schizophrenia.

EXPERT OPINION

The classic parallel group design may limit substantial advantages in drug approval or repurposing. Collaborative approaches between regulatory authorities, industry, academia, and funding agencies are needed to overcome barriers in clinical schizophrenia research to allow for meaningful outcome improvements for the patients.

New "drugs and targets" in the GWAS era of bipolar disorder

OBJECTIVE

Due to the phenotypic heterogeneity and etiological complexity of bipolar disorder (BD), many patients do not respond well to the current medications, and developing novel effective treatment is necessary. Whether any BD genome-wide association study (GWAS) risk genes were targets of existing drugs or novel drugs that can be repurposed in the clinical treatment of BD is a hot topic in the GWAS era of BD.

METHODS

A list of 425 protein-coding BD risk genes was distilled through the BD GWAS, and 4479 protein-coding druggable targets were retrieved from the druggable genome. The overlapped genes/targets were subjected to further analyses in DrugBank, Pharos, and DGIdb datasets in terms of their FDA status, mechanism of action and primary indication, to identify their potential for repurposing.

RESULTS

We identified 58 BD GWAS risk genes grouped as the druggable targets, and several genes were given higher priority. These BD risk genes were targets of antipsychotics, antidepressants, antiepileptics, calcium channel antagonists, as well as anxiolytics and analgesics, either existing clinically-approved drugs for BD or the drugs than can be repurposed for treatment of BD in the future. Those genes were also likely relevant to BD pathophysiology, as many of them encode ion channel, ion transporter or neurotransmitter receptor, or the mice manipulating those genes are likely to mimic the phenotypes manifest in BD patients.

CONCLUSIONS

This study identifies several targets that may facilitate the discovery of novel treatments in BD, and implies the value of conducting GWAS into clinical translation.

Genomics of Obsessive-Compulsive Disorder and Related Disorders: What the Clinician Needs to Know

A wealth of evidence has shown that genetics plays a major role in susceptibility to obsessive-compulsive disorder (OCD) and all of its related disorders. Several large-scale, collaborative efforts using modern genomic methods are beginning to reveal the genetic architecture of these traits and identify long-sought risk genes. In this article, we summarize current OCD and related disorder genomic knowledge and explain how to communicate this information to patients and their families. The article concludes with a discussion of how genomic discovery in OCD and related disorders can inform our understanding of disease etiology and provide novel targets for therapeutic development.