identification-classification-position-specific-gabaa-receptor

Identification and Classification of Position-specific GABA<sub>A</sub> Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Understanding the effects of functionally unknown variants in epilepsy associated genes is crucial for elucidating disease pathophysiology and developing ...

Üsküdar University

GABA(A) receptors (GABA(A)Rs) are hetero-pentameric chloride channels and the primary sites for fast synaptic inhibition. We have expressed recombinant γ2 and δ subunits of GABA(A)Rs in cultured hippocampal neurons to analyze the membrane targeting of synaptic and extra-synaptic GABA(A)Rs, a phenomenon not well understood. Our data demonstrate that the synaptic targeting of γ2-containing GABA(A)Rs (γ2-GABA(A)Rs) does not depend on the cytoplasmic loop of γ2 subunit, in parallel with previous findings, showing that the synaptic localization of γ2-GABA(A)Rs requires the TM4 domain of γ2 rather than the large cytoplasmic loop. On the other hand, we showed here that the extrasynaptic targeting of the δ-containing GABA(A)Rs (δ-GABA(A)Rs) depends on the cytoplasmic loop of δ subunit via an active or a passive mechanism. We also show that the amino acid sequences of δ loop is highly conserved across the whole span of vertebrate evolution suggesting an active role of δ loop in extra-synaptic targeting of corresponding receptor subtypes.

Cytoplasmic domain of δ subunit is important for the extra-synaptic targeting of GABAA receptor subtypes.

The majority of neuropsychiatric disorders show a strong degree of heritability, yet little is known about molecular factors involved in the pathophysiology of diseases like schizophrenia. After a brief historical introduction into the current understanding of neuropsychiatric disorders, the aim of this study is to discuss imaging genetics as a strategy to explore the pathophysiology of neuropsychiatric disorders. The candidate gene approach of imaging genetics is used for validation/replication studies of genes, whereas the hypothesis-free, noncandidate gene approach appears to be a tool for gene discovery. Besides, integration of environmental factors into neuroimaging begins to converge on neuroimaging studies of genetic variation. In the light of data from other avenues such as animal experimentation, these developments show a model of interdisciplinary research, which may lead to identifying markers for neuropsychiatric disorders.

Genes, brains, and behavior: imaging genetics for neuropsychiatric disorders.

Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research.

Imaging genetics of schizophrenia in the post-GWAS era.

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ.

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges.

Editorial: The inflammation markers in schizophrenia and bipolar disorder: Do we have promising results?

Critical for brain development, neurodevelopmental and network disorders, the GABRA1 gene encodes for the α1 subunit, an abundantly and developmentally expressed subunit of heteropentameric gamma-aminobutyric acid A receptors (GABARs) mediating primary inhibition in the brain. Mutations of the GABAR subunit genes including GABRA1 gene are associated with epilepsy, a group of syndromes, characterized by unprovoked seizures and diagnosed by integrative approach, that involves genetic testing. Despite the diagnostic use of genetic testing, a large fraction of the GABAR subunit gene variants including the variants of GABRA1 gene is not known in terms of their molecular consequence, a challenge for precision and personalized medicine. Addressing this, one hundred thirty-seven GABRA1 gene variants of unknown clinical significance have been extracted from the ClinVar database and computationally analyzed for pathogenicity. Eight variants (L49H, P59L, W97R, D99G, G152S, V270G, T294R, P305L) are predicted as pathogenic and mapped to the α1 subunit's extracellular domain (ECD), transmembrane domains (TMDs) and extracellular linker. This is followed by the integration with relevant data for cellular pathology and severity of the epilepsy syndromes retrieved from the literature. Our results suggest that the pathogenic variants in the ECD of GABRA1 (L49H, P59L, W97R, D99G, G152S) will probably manifest decreased surface expression and reduced current with mild epilepsy phenotypes while V270G, T294R in the TMDs and P305L in the linker between the second and the third TMDs will likely cause reduced cell current with severe epilepsy phenotypes. The results presented in this study provides insights for clinical genetics and wet lab experimentation.

Pathogenic variants of human GABRA1 gene associated with epilepsy: A computational approach.

Wikipedia, the open crowdsourced encyclopedia that anyone can edit, ranks among the top ten most-visited websites globally. Its integration into university curriculum as an innovative educational tool is a slowly growing trend; however, many higher education institutions have yet to fully grasp its potential. In response, a specific optional module for Wikipedia editing, designed for the selected undergraduate science courses at the School of Advanced Studies, Russia, was implemented as an optional extra credit service-learning activity, a teaching methodology combining meaningful service to the community with curriculum-based learning. Students who chose to participate and those who preferred not to participate in the activity were invited to participate in a research project to explore their perspectives and experiences. In total, five sessions of focus group discussions were conducted with participants (12 females and 2 males) in one set and non-participants (5 females and 4 males) in another to identify students' perspectives on themes such as their interest in science, reasons for their choices, and their expectations before the activity while post-experience focus group discussions were used to identify the perspectives of participant students on themes, encompassing contribution of the service-learning activity, acquisition of new skills, and the development of prosocial behaviors. Students' opinions on integrating social responsibility topics into the curriculum were also explored. The results extracted from these focus group discussions, analyzed through consensual coding, revealed factors promoting student participation, like interest in the subject, novelty of the activity, and grade improvement opportunities, as well as factors deterring participation, such as concerns about academic benefits, workload, and time constraints. Furthermore, the results demonstrated that Wikipedia editing serves as a novel teaching methodology, promoting student learning and development in digital literacy and information literacy, which are among the twenty-first-century skills. Interestingly, at the same time, not all students could address the value of contributing to open, crowdsourced knowledge for public service or interpret this activity as an academic service-learning. These suggest that Wikipedia editing is an innovative teaching approach, fostering students' learning and development while also indicating its potential to enhance students' understanding of responsible citizenship and public service in the digital age.

Wikipedia as an academic service-learning tool in science and technology: higher education case from Siberia.

The primary objective of this study is to address the challenge posed by the increasing number of variants of unknown clinical significance (VUS) within the GABRD gene, which encodes the δ subunit of γ-Aminobutyric acid type A receptors. The focus is on predicting the most pathogenic GABRD VUS to enhance precision medicine and improve our understanding of relevant pathophysiology.

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy.

This chapter primarily focuses on the progress in depression precision medicine with specific emphasis on the integrative approaches that include artificial intelligence and other data, tools, and technologies. After the description of the concept of precision medicine and a comparative introduction to depression precision medicine with cancer and epilepsy, new avenues of depression precision medicine derived from integrated artificial intelligence and other sources will be presented. Additionally, less advanced areas, such as comorbidity between depression and cancer, will be examined.

Ayla Arslan

Department of Molecular Biology and Genetics,
Faculty of Engineering and Natural Sciences,
Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences

Üsküdar University

Identification and Classification of Position-specific GABA_A Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Ayla Arslan

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Molecular Biology and Genetics,Faculty of Engineering and Natural Sciences,Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences

Üsküdar University

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Department of Molecular Biology and Genetics,
Faculty of Engineering and Natural Sciences,
Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences

Identification and Classification of Position-specific GABA_A Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons