In-silico investigation of coding variants potentially affecting the functioning of the glutamatergic N-methyl-D-aspartate receptor in schizophrenia

Network-based analysis on the genes and their interactions reveals link between schizophrenia and Alzheimer's disease

Schizophrenia (SCZ) is a heterogeneous psychiatric disorder marked by impaired thinking, emotions, and behaviors. Studies have suggested a strong connection between SCZ and Alzheimer's disease (AD), however, controversies exist and the underlying mechanisms linking these two disorders remain largely unknown. Therefore, systematic studies of SCZ- and AD-related genes will provide valuable insights into the molecular features of these two diseases and their comorbidities. In this study, we obtained 331 SCZ-related genes, 650 AD-related genes, 65 shared genes between SCZ and AD. Enrichment analysis shown that these 65 shared genes were mainly involved in cognition, neural development, synaptic transmission, drug reactions, metabolic processes and immune related processes, suggesting a complex mechanism for the co-existence of SCZ and AD. In addition, we performed pathway enrichment analysis and found a total of 57 common pathways between SCZ and AD, which could be largely grouped into three modules: immune module, neurodevelopment module and cancer module. We eventually identified the potential disease-related genes whose interactions provide clues to the overlapping symptoms between SCZ and AD.

Schizophrenia as metabolic disease. What are the causes?

Schizophrenia (SZ) is a devastating neurodevelopmental disease with an accelerated ageing feature. The criteria of metabolic disease firmly fit with those of schizophrenia. Disturbances in energy and mitochondria are at the core of complex pathology. Genetic and environmental interaction creates changes in redox, inflammation, and apoptosis. All the factors behind schizophrenia interact in a cycle where it is difficult to discriminate between the cause and the effect. New technology and advances in the multi-dispensary fields could break this cycle in the future.

Targeting NMDA receptors in neuropsychiatric disorders by drug screening on human neurons derived from pluripotent stem cells

NMDA receptors (NMDARs), a prominent subtype of glutamatergic receptors, are implicated in the pathogenesis and development of neuropsychiatric disorders such as epilepsy, intellectual disability, autism spectrum disorder, and schizophrenia, and are therefore a potential therapeutic target in treating these disorders. Neurons derived from induced pluripotent stem cells (iPSCs) have provided the opportunity to investigate human NMDARs in their native environment. In this review, we describe the expression, function, and regulation of NMDARs in human iPSC-derived neurons and discuss approaches for utilizing human neurons for identifying potential drugs that target NMDARs in the treatment of neuropsychiatric disorders. A challenge in studying NMDARs in human iPSC-derived neurons is a predominance of those receptors containing the GluN2B subunit and low synaptic expression, suggesting a relatively immature phenotype of these neurons and delayed development of functional NMDARs. We outline potential approaches for improving neuronal maturation of human iPSC-derived neurons and accelerating the functional expression of NMDARs. Acceleration of functional expression of NMDARs in human iPSC-derived neurons will improve the modeling of neuropsychiatric disorders and facilitate the discovery and development of novel therapeutics targeting NMDARs for the treatment of these disorders.

Bioinformatics and Network-based Approaches for Determining Pathways, Signature Molecules, and Drug Substances connected to Genetic Basis of Schizophrenia etiology

Knowledge of heterogeneous etiology and pathophysiology of schizophrenia (SZP) is reasonably inadequate and non-deterministic due to its inherent complexity and underlying vast dynamics related to genetic mechanisms. The evolution of large-scale transcriptome-wide datasets and subsequent development of relevant, robust technologies for their analyses show promises toward elucidating the genetic basis of disease pathogenesis, its early risk prediction, and predicting drug molecule targets for therapeutic intervention. In this research, we have scrutinized the genetic basis of SZP through functional annotation and network-based system biology approaches. We have determined 96 overlapping differentially expressed genes (DEGs) from 2 microarray datasets and subsequently identified their interconnecting networks to reveal transcriptome signatures like hub proteins (FYN, RAD51, SOCS3, XIAP, AKAP13, PIK3C2A, CBX5, GATA3, EIF3K, and CDKN2B), transcription factors and miRNAs. In addition, we have employed gene set enrichment to highlight significant gene ontology (e.g., positive regulation of microglial cell activation) and relevant pathways (such as axon guidance and focal adhesion) interconnected to the genes associated with SZP. Finally, we have suggested candidate drug substances like Luteolin HL60 UP as a possible therapeutic target based on these key molecular signatures.

Leveraging Gene-Level Prediction as Informative Covariate in Hypothesis Weighting Improves Power for Rare Variant Association Studies

Gene-based rare variant association studies (RVASs) have low power due to the infrequency of rare variants and the large multiple testing burden. To correct for multiple testing, traditional false discovery rate (FDR) procedures which depend solely on P-values are often used. Recently, Independent Hypothesis Weighting (IHW) was developed to improve the detection power while maintaining FDR control by leveraging prior information for each hypothesis. Here, we present a framework to increase power of gene-based RVASs by incorporating prior information using IHW. We first build supervised machine learning models to assign each gene a prediction score that measures its disease risk, using the input of multiple biological features, fed with high-confidence risk genes and local background genes selected near GWAS significant loci as the training set. Then we use the prediction scores as covariates to prioritize RVAS results via IHW. We demonstrate the effectiveness of this framework through applications to RVASs in schizophrenia and autism spectrum disorder. We found sizeable improvements in the number of significant associations compared to traditional FDR approaches, and independent evidence supporting the relevance of the genes identified by our framework but not traditional FDR, demonstrating the potential of our framework to improve power of gene-based RVASs.

Glutamate transporter-1 link astrocytes with heightened aggressive behavior induced by steroid abuse in male CF1 mice

The astrocytic glutamate transporter GLT-1 performs glutamate uptake thereby mediating NMDAr responses in neurons. Ceftriaxone (CEF) upregulates astrocytic GLT-1 expression/activity, which could counteract excessive glutamate levels and aggressive behavior induced by anabolic synthetic steroids such as nandrolone decanoate (ND). Here, adult male CF-1 mice were allocated to oil (VEH), ND, CEF, and ND/CEF groups. Mice were subcutaneously (s.c.) injected with ND (15 mg/kg) or VEH for 19 days, and received intraperitoneal (i.p.) injections of CEF (200 mg/kg) or saline for 5 days. The ND/CEF group received ND for 19 days plus coadministration of CEF in the last 5 days. On the 19th day, the aggressive phenotypes were evaluated through the resident-intruder test. After 24 h, cerebrospinal fluid was collected to measure glutamate levels, and the pre-frontal cortex was used to assess GLT-1, pGluN2B^Tyr1472, and pGluN2A^Tyr1246 by Western blot. Synaptosomes from the left brain hemisphere was used to evaluate mitochondrial function including complex II-succinate dehydrogenase (SDH), Ca²⁺ handling, membrane potential (ΔѰ_m), and H₂O₂ production. ND decreased the latency for the first attack and increased the number of attacks by the resident mice against the intruder, mechanistically associated with an increase in glutamate levels and pGluN2B^Tyr1472 but not pGluN2A^Tyr1244, and GLT-1 downregulation. The abnormalities in mitochondrial Ca²⁺ influx, SDH, ΔѰ_m, and H₂O₂ implies in deficient energy support to the synaptic machinery. The ND/CEF group displayed a decreased aggressive behavior, normalization of glutamate and pGluN2B^Tyr1472levels, and mitochondrial function at synaptic terminals. In conclusion, the pharmacological modulation of GLT-1 highlights its relevance as an astrocytic target against highly impulsive and aggressive phenotypes.

Do damaging variants of SLC6A9, the gene for the glycine transporter 1 (GlyT-1), protect against schizophrenia?

The aim of the investigation was to test whether genetic variants predicted to impair the functionality of SLC6A9, which codes for the GlyT-1 glycine transporter, are protective against schizophrenia. In an exome sequenced sample of 4225 schizophrenia cases and 5834 controls, variants occurring in SLC6A9 were annotated and weights were assigned using GENEVARASSOC. Genotype counts were compared using SCOREASSOC. Variants predicted to be deleterious by SIFT and damaging by PolyPhen were examined. Genotypes at 1:44466494-G/A seemed likely to be erroneous. If these were ignored then there were 15 damaging variants in controls and five in cases. The results are consistent with the hypothesis that variants which damage SLC6A9 are protective against schizophrenia but a larger sample would be required to confirm this.

Weighted burden analysis of exome-sequenced late-onset Alzheimer's cases and controls provides further evidence for a role for PSEN1 and suggests involvement of the PI3K/Akt/GSK-3β and WNT signalling pathways

Previous studies have implicated common and rare genetic variants as risk factors for late-onset Alzheimer's disease (LOAD). Here, weighted burden analysis was applied to over 10,000 exome-sequenced subjects from the Alzheimer's Disease Sequencing Project. Analyses were carried out to investigate whether rare variants predicted to have a functional effect within a gene were more commonly seen in cases or in controls. Confirmatory results were obtained for TREM2, ABCA7, and SORL1. Additional support was provided for PSEN1 (p = 0.0002), which previously had been only weakly implicated in LOAD. There was suggestive evidence that functional variants in PIK3R1, WNT7A, C1R, and EXOC5 might increase risk and that variants in TIAF1 and/or NDRG2 might have a protective effect. Overall, there was strong evidence (p = 5 × 10-6 ) that variants in tyrosine phosphatase genes reduce the risk of developing LOAD. Because PIK3R1 variants are expected to impair PI3K/Akt/GSK-3β signalling while variants in tyrosine phosphatase genes would enhance it, these findings are in line with those from animal models, suggesting that this pathway is protective against Alzheimer's disease.

A possible role for sarcosine in the management of schizophrenia

Sarcosine, which is freely sold as a dietary supplement, has pharmacological activity to boost functioning of the glutamatergic N-methyl-d-aspartate receptor (NMDAR) and hence it is a biologically rational treatment for schizophrenia. The small number of studies carried out to date provide some evidence for its efficacy and psychiatrists could consider suggesting its use to their patients.

A general statistic to test an optimally weighted combination of common and/or rare variants

Both genome-wide association study and next-generation sequencing data analyses are widely employed to identify disease susceptible common and/or rare genetic variants. Rare variants generally have large effects though they are hard to detect due to their low frequencies. Currently, many existing statistical methods for rare variants association studies employ a weighted combination scheme, which usually puts subjective weights or suboptimal weights based on some adhoc assumptions (e.g., ignoring dependence between rare variants). In this study, we analytically derived optimal weights for both common and rare variants and proposed a general and novel approach to test association between an optimally weighted combination of variants (G-TOW) in a gene or pathway for a continuous or dichotomous trait while easily adjusting for covariates. Results of the simulation studies show that G-TOW has properly controlled type I error rates and it is the most powerful test among the methods we compared when testing effects of either both rare and common variants or rare variants only. We also illustrate the effectiveness of G-TOW using the Genetic Analysis Workshop 17 (GAW17) data. Additionally, we applied G-TOW and other competitive methods to test disease-associated genes in real data of schizophrenia. The G-TOW has successfully verified genes FYN and VPS39 which are associated with schizophrenia reported in existing publications. Both of these genes are missed by the weighted sum statistic and the sequence kernel association test. Simulation study and real data analysis indicate that G-TOW is a powerful test.

Can N-Methyl-D-Aspartate Receptor Hypofunction in Schizophrenia Be Localized to an Individual Cell Type?

Hypofunction of N-methyl-D-aspartate glutamate receptors (NMDARs), whether caused by endogenous factors like auto-antibodies or mutations, or by pharmacological or genetic manipulations, produces a wide variety of deficits which overlap with-but do not precisely match-the symptom spectrum of schizophrenia. In order to understand how NMDAR hypofunction leads to different components of the syndrome, it is necessary to take into account which neuronal subtypes are particularly affected by it in terms of detrimental functional alterations. We provide a comprehensive overview detailing findings in rodent models with cell type-specific knockout of NMDARs. Regarding inhibitory cortical cells, an emerging model suggests that NMDAR hypofunction in parvalbumin (PV) positive interneurons is a potential risk factor for this disease. PV interneurons display a selective vulnerability resulting from a combination of genetic, cellular, and environmental factors that produce pathological multi-level positive feedback loops. Central to this are two antioxidant mechanisms-NMDAR activity and perineuronal nets-which are themselves impaired by oxidative stress, amplifying disinhibition. However, NMDAR hypofunction in excitatory pyramidal cells also produces a range of schizophrenia-related deficits, in particular maladaptive learning and memory recall. Furthermore, NMDAR blockade in the thalamus disturbs thalamocortical communication, and NMDAR ablation in dopaminergic neurons may provoke over-generalization in associative learning, which could relate to the positive symptom domain. Therefore, NMDAR hypofunction can produce schizophrenia-related effects through an action on various different circuits and cell types.