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Advances of Psychiatric Genetics

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 8200

Special Issue Editors

Department of Medical Genetics, Medical School, University of Pécs, 7624 Pécs, Hungary
Interests: molecular genetics and genomics; next generation sequencing; rare diseases; genetic testing; neurocutaneous syndromes; copy number variations
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Medical Genetics, Medical School, University of Pécs, 7624 Pécs, Hungary
Interests: autism spectrum disorders; genomic disorders; epilepsy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

People with mental illness make up a large group of patients with increasing prevalence. Despite the extensive research, the etiology and molecular pathogenesis of psychiatric disorders are still poorly understood. It is clear from recent genomic studies that the genetic architecture of psychiatric disorders is highly polygenic and comprises all forms of genetic variations, such as common and rare SNVs, small insertions and deletions, de novo and inherited CNVs and chromosomal translocations. Moreover, epigenetic and environmental factors also play a crucial role in the development of these diseases.

Thanks to the new sophisticated technologies, such as whole-exome and whole-genome sequencing, more and more genomic data are available for psychiatric disorders. This gives promise to understand the biological mechanisms and develop novel therapeutic methods.

There are a number of rare disorders with psychiatric symptoms. The exploration of candidate genes and related biological pathways involved in the pathogenesis of these rare disorders is supposed to contribute to discovering the complex nature of mental disorders.

The aim of this Special Issue is to collect original and review articles which describe recent findings related to the genetic defects and pathomechanisms underlying mental illness. Pure clinical studies are out of the scope of this Special Issue; however, clinical submissions with biomolecular experiments are welcome.

Dr. Judit Bene
Dr. Hadzsiev Kinga
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mental disorders
  • schizophrenia
  • bipolar disorder
  • obsessive-compulsive disorder
  • major depression disorder
  • anxiety disorders
  • autism spectrum disorders
  • attention deficit hyperactivity disorder
  • rare disorders
  • WES
  • WGS
  • aCGH

Published Papers (3 papers)

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Research

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13 pages, 1876 KiB  
Article
Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters
by Yichuan Liu, Hui-Qi Qu, Xiao Chang, Lifeng Tian, Jingchun Qu, Joseph Glessner, Patrick M. A. Sleiman and Hakon Hakonarson
Int. J. Mol. Sci. 2021, 22(7), 3364; https://doi.org/10.3390/ijms22073364 - 25 Mar 2021
Cited by 4 | Viewed by 2159
Abstract
RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA [...] Read more.
RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels. Full article
(This article belongs to the Special Issue Advances of Psychiatric Genetics)
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Review

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19 pages, 2641 KiB  
Review
Copy Number Variations in Neuropsychiatric Disorders
by Gergely Büki, Kinga Hadzsiev and Judit Bene
Int. J. Mol. Sci. 2023, 24(18), 13671; https://doi.org/10.3390/ijms241813671 - 5 Sep 2023
Viewed by 2726
Abstract
Neuropsychiatric disorders are complex conditions that represent a significant global health burden with complex and multifactorial etiologies. Technological advances in recent years have improved our understanding of the genetic architecture of the major neuropsychiatric disorders and the genetic loci involved. Previous studies mainly [...] Read more.
Neuropsychiatric disorders are complex conditions that represent a significant global health burden with complex and multifactorial etiologies. Technological advances in recent years have improved our understanding of the genetic architecture of the major neuropsychiatric disorders and the genetic loci involved. Previous studies mainly investigated genome-wide significant SNPs to elucidate the cross-disorder and disorder-specific genetic basis of neuropsychiatric disorders. Although copy number variations represent a major source of genetic variations, they are known risk factors in developing a variety of human disorders, including certain neuropsychiatric diseases. In this review, we demonstrate the current understanding of CNVs contributing to liability for schizophrenia, bipolar disorder, and major depressive disorder. Full article
(This article belongs to the Special Issue Advances of Psychiatric Genetics)
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12 pages, 803 KiB  
Review
New Insights into TETs in Psychiatric Disorders
by Wenxia Zhan, Yi Li, Jie Yuan, Na Zhi, Yiyuan Huang, Yingqi Liu, Ming Zhang, Shengxi Wu and Xianghui Zhao
Int. J. Mol. Sci. 2022, 23(9), 4909; https://doi.org/10.3390/ijms23094909 - 28 Apr 2022
Cited by 4 | Viewed by 2242
Abstract
Psychiatric disorders are complex and heterogeneous disorders arising from the interaction of multiple factors based on neurobiology, genetics, culture, and life experience. Increasing evidence indicates that sustained abnormalities are maintained by epigenetic modifications in specific brain regions. Over the past decade, the critical, [...] Read more.
Psychiatric disorders are complex and heterogeneous disorders arising from the interaction of multiple factors based on neurobiology, genetics, culture, and life experience. Increasing evidence indicates that sustained abnormalities are maintained by epigenetic modifications in specific brain regions. Over the past decade, the critical, non-redundant roles of the ten-eleven translocation (TET) family of dioxygenase enzymes have been identified in the brain during developmental and postnatal stages. Specifically, TET-mediated active demethylation, involving the iterative oxidation of 5-methylcytosine to 5-hydroxymethylcytosine and subsequent oxidative derivatives, is dynamically regulated in response to environmental stimuli such as neuronal activity, learning and memory processes, and stressor exposure. Here, we review the progress of studies designed to provide a better understanding of how profiles of TET proteins and 5hmC are powerful mechanisms by which to explain neuronal plasticity and long-term behaviors, and impact transcriptional programs operative in the brain that contribute to psychiatric disorders. Full article
(This article belongs to the Special Issue Advances of Psychiatric Genetics)
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