Over-representation of potential SP4 target genes within schizophrenia-risk genes

SRSF3 suppresses RCC tumorigenesis and progression via regulating SP4 alternative splicing

Abnormal alternative splicing (AS) caused by dysregulated expression of splicing factors plays a crucial role in tumorigenesis and progression. The serine/arginine-rich (SR) RNA-binding protein family is a major class of splicing factors regulating AS. However, their roles and mechanisms in renal cell carcinoma (RCC) development and progression are not fully understood. Here, we found that SR splicing factor 3 (SRSF3) was an important splicing factor affecting RCC progression. SRSF3 was downregulated in RCC tissues and its low level was associated with decreased overall survival time of RCC patients. SRSF3 overexpression suppressed RCC cell malignancy. Mechanistically, the binding of SRSF3 to SP4 exon 3 led to the inclusion of SP4 exon 3 and the increase of long SP4 isoform (L-SP4) level in RCC cells. L-SP4, but not S-SP4 overexpression suppressed RCC cell malignancy. Meanwhile, L-SP4 participated in SRSF3-mediated anti-proliferation by transcriptionally promoting SMAD4 expression. Taken together, our findings provide new insights into the anticancer mechanism of SRSF3, suggesting that SRSF3 may serve as a novel potential therapeutic target for RCC.

Human stem cell-based models to study synaptic dysfunction and cognition in schizophrenia: A narrative review

Cognitive impairment is the strongest predictor of functional outcomes in schizophrenia and is hypothesized to result from synaptic dysfunction. However, targeting synaptic plasticity and cognitive deficits in patients remains a significant clinical challenge. A comprehensive understanding of synaptic plasticity and the molecular basis of learning and memory in a disease context can provide specific targets for the development of novel therapeutics targeting cognitive impairments in schizophrenia. Here, we describe the role of synaptic plasticity in cognition, summarize evidence for synaptic dysfunction in schizophrenia and demonstrate the use of patient derived induced-pluripotent stem cells for studying synaptic plasticity in vitro. Lastly, we discuss current advances and future technologies for bridging basic science research of synaptic dysfunction with clinical and translational research that can be used to predict treatment response and develop novel therapeutics.

Genetic Diversity in Schizophrenia: Developmental Implications of Ultra-Rare, Protein-Truncating Mutations

The genetic basis of schizophrenia (SZ) remains elusive despite its characterization as a highly heritable disorder. This incomplete understanding has led to stagnation in therapeutics and treatment, leaving many suffering with insufficient relief from symptoms. However, recent large-cohort genome- and exome-wide association studies have provided insights into the underlying genetic machinery. The scale of these studies allows for the identification of ultra-rare mutations that confer substantial disease risk, guiding clinicians and researchers toward general classes of genes that are central to SZ etiology. One such large-scale collaboration effort by the Schizophrenia Exome Sequencing Meta-Analysis consortium identified ten, high-risk, ultra-rare, protein-truncating variants, providing the clearest picture to date of the dysfunctional gene products that substantially increase risk for SZ. While genetic studies of SZ provide valuable information regarding "what" genes are linked with the disorder, it is an open question as to "when" during brain development these genetic mutations impose deleterious effects. To shed light on this unresolved aspect of SZ etiology, we queried the BrainSpan developmental mRNA expression database for these ten high-risk genes and discovered three general expression trajectories throughout pre- and postnatal brain development. The elusiveness of SZ etiology, we infer, is not only borne out of the genetic heterogeneity across clinical cases, but also in our incomplete understanding of how genetic mutations perturb neurodevelopment during multiple critical periods. We contextualize this notion within the National Institute of Mental Health's Research Domain Criteria framework and emphasize the utility of considering both genetic variables and developmental context in future studies.

Efficacy of the combination of water aerobics and metacognitive training on psychological and physical health variables and their relationship with SP1 and SP4 biomarkers in people with psychosis: a study protocol

Background

Metacognitive Training (MCT) is widely used and effective in reducing positive symptoms in psychosis. Physical exercise, such as Water Aerobics (WA), improves general health, quality of life and symptoms as a low impact activity that allows social interactions. Preliminary results suggest a relationship between dopamine and psychotic symptoms, through SP transcription factors, SP1 and SP4 biomarkers. The aims of the project are to evaluate the efficacy of a combined intervention (WA and MCT) for psychosis to improve psychotic symptoms, physical health, and transcription levels of SP biomarkers.

Materials and methods

This is a unicentric randomized controlled trial of three parallel intervention groups: MCT, WA and combined intervention. The estimated sample will be 48 patients with a psychotic spectrum disorder diagnosis. The assessment will be performed at baseline and at 2-months' follow-up. Instruments used in the assessment will include clinical, cognitive, metacognitive, social cognitive and psychosocial variables.

Discussion

This will be the first study investigating the impact of the combination of MCT and WA in psychosis. Moreover, it will be the first study analyzing changes in the transcriptional biomarkers SP1 and SP4 after interventions. The results of this study may have clinical implications contributing to the improvement of treatment selection.

Clinical trial registration

https://clinicaltrials.gov/, identifier: NCT05455593.

Psychosis superspectrum II: neurobiology, treatment, and implications

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Genetic overlap between schizophrenia and cognitive performance

Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.

Molecular mechanisms of schizophrenia: Insights from human genetics

Schizophrenia is a debilitating psychiatric disorder that affects millions of people worldwide; however, its etiology is poorly understood at the molecular and neurobiological levels. A particularly important advance in recent years is the discovery of rare genetic variants associated with a greatly increased risk of developing schizophrenia. These primarily loss-of-function variants are found in genes that overlap with those implicated by common variants and are involved in the regulation of glutamate signaling, synaptic function, DNA transcription, and chromatin remodeling. Animal models harboring mutations in these large-effect schizophrenia risk genes show promise in providing additional insights into the molecular mechanisms of the disease.

Children with Early-Onset Psychosis Have Increased Burden of Rare GRIN2A Variants

BACKGROUND

Children and adolescents with early-onset psychosis (EOP) have more rare genetic variants than individuals with adult-onset forms of the illness, implying that fewer EOP participants are needed for genetic discovery. The Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) study predicted that 10 genes with ultra-rare variation were linked to adult-onset schizophrenia. We hypothesized that rare variants predicted "High" and "Moderate" by the Variant Effect Predictor Algorithm (abbreviated as VEPHMI) in these 10 genes would be enriched in our EOP cohort.

METHODS

We compared rare VEPHMI variants in individuals with EOP (N = 34) with race- and sex-matched controls (N = 34) using the sequence kernel association test (SKAT).

RESULTS

GRIN2A variants were significantly increased in the EOP cohort (p = 0.004), with seven individuals (20% of the EOP cohort) carrying a rare VEPHMI variant. The EOP cohort was then compared to three additional control cohorts. GRIN2A variants were significantly increased in the EOP cohort for two of the additional control sets (p = 0.02 and p = 0.02), and trending towards significance for the third (p = 0.06).

CONCLUSION

Despite a small sample size, GRIN2A VEPHMI variant burden was increased in a cohort of individuals with EOP in comparison to controls. GRIN2A variants have been associated with a range of neuropsychiatric disorders including adult-onset psychotic spectrum disorder and childhood-onset schizophrenia. This study supports the role of GRIN2A in EOP and emphasizes its role in neuropsychiatric disorders.

Development of cross-species translational paradigms for psychiatric research in the Research Domain Criteria era

The past 30 years of IBNS has included research attempting to treat the cognitive and behavioral deficits observed in people with psychiatric conditions. Early work utilized drugs identified from tests thought to be cognition-relevant, however the high failure rate crossing the translational-species barrier led to focus on developing valid cross-species translational tests. The face, predictive, and neurobiological validities used to assess animal models of psychiatry can be used to validate these tests. Clinical sensitivity is another important aspect however, for if the clinical population targeted for treatment does not exhibit task deficits, then why develop treatments? This review covers some work validating cross-species translational tests and suggests future directions. Also covered is the contribution IBNS made to fostering such research and my role in IBNS, making it more available to all including fostering mentor/mentee programs plus spearheading diversity and inclusivity initiatives. All science needs support and IBNS has supported research recreating the behavioral abnormalities that define psychiatric conditions with the aim to improve the lives of people with such conditions.

[An analysis of the relationship between genetic factors and the risk of schizophrenia]

The etiology and pathogenesis of schizophrenia remain poorly understood, but it has been established that the contribution of heredity to the development of the disease is about 80-85%. Over the past decade, significant progress has been made in the search for specific genetic variants associated with the development of schizophrenia. The review discusses the results of modern large-scale studies aimed at searching for genetic associations with schizophrenia: genome-wide association studies (GWAS) and the search for rare variants (mutations or copy number variations, CNV), including the use of whole exome sequencing. We synthesize data on currently known genes that are significantly associated with schizophrenia and discuss their biological functions in order to identify the main molecular pathways involved in the pathophysiology of schizophrenia.

Mining comorbidities of opioid use disorder from FDA adverse event reporting system and patient electronic health records

BACKGROUND

Opioid use disorder (OUD) has become an urgent health problem. People with OUD often experience comorbid medical conditions. Systematical approaches to identifying co-occurring conditions of OUD can facilitate a deeper understanding of OUD mechanisms and drug discovery. This study presents an integrated approach combining data mining, network construction and ranking, and hypothesis-driven case-control studies using patient electronic health records (EHRs).

METHODS

First, we mined comorbidities from the US Food and Drug Administration Adverse Event Reporting System (FAERS) of 12 million unique case reports using frequent pattern-growth algorithm. The performance of OUD comorbidity mining was measured by precision and recall using manually curated known OUD comorbidities. We then constructed a disease comorbidity network using mined association rules and further prioritized OUD comorbidities. Last, novel OUD comorbidities were independently tested using EHRs of 75 million unique patients.

RESULTS

The OUD comorbidities from association rules mining achieves a precision of 38.7% and a recall of 78.2 Based on the mined rules, the global DCN was constructed with 1916 nodes and 32,175 edges. The network-based OUD ranking result shows that 43 of 55 known OUD comorbidities were in the first decile with a precision of 78.2%. Hypothyroidism and type 2 diabetes were two top-ranked novel OUD comorbidities identified by data mining and network ranking algorithms. Based on EHR-based case-control studies, we showed that patients with OUD had significantly increased risk for hyperthyroidism (AOR = 1.46, 95% CI 1.43-1.49, p value < 0.001), hypothyroidism (AOR = 1.45, 95% CI 1.42-1.48, p value < 0.001), type 2-diabetes (AOR = 1.28, 95% CI 1.26-1.29, p value < 0.001), compared with individuals without OUD.

CONCLUSION

Our study developed an integrated approach for identifying and validating novel OUD comorbidities from health records of 87 million unique patients (12 million for discovery and 75 million for validation), which can offer new opportunities for OUD mechanism understanding, drug discovery, and multi-component service delivery for co-occurring medical conditions among patients with OUD.