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Abedini SS, Akhavantabasi S, Liang Y, Heng JIT, Alizadehsani R, Dehzangi I, Bauer DC, Alinejad-Rokny H. A critical review of the impact of candidate copy number variants on autism spectrum disorder. MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2024; 794:108509. [PMID: 38977176 DOI: 10.1016/j.mrrev.2024.108509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 04/14/2024] [Accepted: 07/02/2024] [Indexed: 07/10/2024]
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder (NDD) influenced by genetic, epigenetic, and environmental factors. Recent advancements in genomic analysis have shed light on numerous genes associated with ASD, highlighting the significant role of both common and rare genetic mutations, as well as copy number variations (CNVs), single nucleotide polymorphisms (SNPs) and unique de novo variants. These genetic variations disrupt neurodevelopmental pathways, contributing to the disorder's complexity. Notably, CNVs are present in 10 %-20 % of individuals with autism, with 3 %-7 % detectable through cytogenetic methods. While the role of submicroscopic CNVs in ASD has been recently studied, their association with genomic loci and genes has not been thoroughly explored. In this review, we focus on 47 CNV regions linked to ASD, encompassing 1632 genes, including protein-coding genes and long non-coding RNAs (lncRNAs), of which 659 show significant brain expression. Using a list of ASD-associated genes from SFARI, we detect 17 regions harboring at least one known ASD-related protein-coding gene. Of the remaining 30 regions, we identify 24 regions containing at least one protein-coding gene with brain-enriched expression and a nervous system phenotype in mouse mutants, and one lncRNA with both brain-enriched expression and upregulation in iPSC to neuron differentiation. This review not only expands our understanding of the genetic diversity associated with ASD but also underscores the potential of lncRNAs in contributing to its etiology. Additionally, the discovered CNVs will be a valuable resource for future diagnostic, therapeutic, and research endeavors aimed at prioritizing genetic variations in ASD.
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Affiliation(s)
- Seyedeh Sedigheh Abedini
- UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia; School of Biotechnology & Biomolecular Sciences, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Shiva Akhavantabasi
- Department of Molecular Biology and Genetics, Yeni Yuzyil University, Istanbul, Turkey; Ghiaseddin Jamshid Kashani University, Andisheh University Town, Danesh Blvd, 3441356611, Abyek, Qazvin, Iran
| | - Yuheng Liang
- UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Julian Ik-Tsen Heng
- Curtin Health Innovation Research Institute, Curtin University, Bentley 6845, Australia
| | - Roohallah Alizadehsani
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, Australia
| | - Iman Dehzangi
- Center for Computational and Integrative Biology, Rutgers University, Camden, NJ 08102, USA; Department of Computer Science, Rutgers University, Camden, NJ 08102, USA
| | - Denis C Bauer
- Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, Australia; Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, Australia
| | - Hamid Alinejad-Rokny
- UNSW BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia; Tyree Institute of Health Engineering (IHealthE), UNSW Sydney, Sydney, NSW 2052, Australia.
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Granata V, Fusco R, Coluccino S, Russo C, Grassi F, Tortora F, Conforti R, Caranci F. Preliminary data on artificial intelligence tool in magnetic resonance imaging assessment of degenerative pathologies of lumbar spine. LA RADIOLOGIA MEDICA 2024; 129:623-630. [PMID: 38349415 DOI: 10.1007/s11547-024-01791-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 01/15/2024] [Indexed: 04/17/2024]
Abstract
PURPOSE To evaluate the ability of an artificial intelligence (AI) tool in magnetic resonance imaging (MRI) assessment of degenerative pathologies of lumbar spine using radiologist evaluation as a gold standard. METHODS Patients with degenerative pathologies of lumbar spine, evaluated with MRI study, were enrolled in a retrospective study approved by local ethical committee. A comprehensive software solution (CoLumbo; SmartSoft Ltd., Varna, Bulgaria) designed to label the segments of the lumbar spine and to detect a broad spectrum of degenerative pathologies based on a convolutional neural network (CNN) was employed, utilizing an automatic segmentation. The AI tool efficacy was compared to data obtained by a senior neuroradiologist that employed a semiquantitative score. Chi-square test was used to assess the differences among groups, and Spearman's rank correlation coefficient was calculated between the grading assigned by radiologist and the grading obtained by software. Moreover, agreement was assessed between the value assigned by radiologist and software. RESULTS Ninety patients (58 men; 32 women) affected with degenerative pathologies of lumbar spine and aged from 60 to 81 years (mean 66 years) were analyzed. Significant correlations were observed between grading assigned by radiologist and the grading obtained by software for each localization. However, only when the localization was L2-L3, there was a good correlation with a coefficient value of 0.72. The best agreements were obtained in case of L1-L2 and L2-L3 localizations and were, respectively, of 81.1% and 72.2%. The lowest agreement of 51.1% was detected in case of L4-L5 locations. With regard canal stenosis and compression, the highest agreement was obtained for identification of in L5-S1 localization. CONCLUSIONS AI solution represents an efficacy and useful toll degenerative pathologies of lumbar spine to improve radiologist workflow.
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Affiliation(s)
- Vincenza Granata
- Division of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", Naples, Italy
| | | | - Simone Coluccino
- Division of Radiology, "Università degli Studi della Campania Luigi Vanvitelli", Naples, Italy
| | - Carmela Russo
- Unit of Neuroradiology, Department of Neurosciences, Santobono-Pausilipon Children's Hospital, Naples, Italy
| | - Francesca Grassi
- Division of Radiology, "Università degli Studi della Campania Luigi Vanvitelli", Naples, Italy
| | - Fabio Tortora
- Neuroradiology Unit, Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Renata Conforti
- Division of Radiology, "Università degli Studi della Campania Luigi Vanvitelli", Naples, Italy
| | - Ferdinando Caranci
- Division of Radiology, "Università degli Studi della Campania Luigi Vanvitelli", Naples, Italy
- Unit of Neuroradiology, Department of Neurosciences, Santobono-Pausilipon Children's Hospital, Naples, Italy
- Neuroradiology Unit, Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Via della Signora 2, 20122, Milan, Italy
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Wang ZB, Qu J, Yang ZY, Liu DY, Jiang SL, Zhang Y, Yang ZQ, Mao XY, Liu ZQ. Integrated Analysis of Expression Profile and Potential Pathogenic Mechanism of Temporal Lobe Epilepsy With Hippocampal Sclerosis. Front Neurosci 2022; 16:892022. [PMID: 35784838 PMCID: PMC9243442 DOI: 10.3389/fnins.2022.892022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/24/2022] [Indexed: 11/13/2022] Open
Abstract
Objective To investigate the potential pathogenic mechanism of temporal lobe epilepsy with hippocampal sclerosis (TLE+HS) by analyzing the expression profiles of microRNA/ mRNA/ lncRNA/ DNA methylation in brain tissues. Methods Brain tissues of six patients with TLE+HS and nine of normal temporal or parietal cortices (NTP) of patients undergoing internal decompression for traumatic brain injury (TBI) were collected. The total RNA was dephosphorylated, labeled, and hybridized to the Agilent Human miRNA Microarray, Release 19.0, 8 × 60K. The cDNA was labeled and hybridized to the Agilent LncRNA+mRNA Human Gene Expression Microarray V3.0,4 × 180K. For methylation detection, the DNA was labeled and hybridized to the Illumina 450K Infinium Methylation BeadChip. The raw data was extracted from hybridized images using Agilent Feature Extraction, and quantile normalization was performed using the Agilent GeneSpring. P-value < 0.05 and absolute fold change >2 were considered the threshold of differential expression data. Data analyses were performed using R and Bioconductor. BrainSpan database was used to screen for signatures that were not differentially expressed in normal human hippocampus and cortex (data from BrainSpan), but differentially expressed in TLE+HS’ hippocampus and NTP’ cortex (data from our cohort). The strategy “Guilt by association” was used to predict the prospective roles of each important hub mRNA, miRNA, or lncRNA. Results A significantly negative correlation (r < −0.5) was found between 116 pairs of microRNA/mRNA, differentially expressed in six patients with TLE+HS and nine of NTP. We examined this regulation network’s intersection with target gene prediction results and built a lncRNA-microRNA-Gene regulatory network with structural, and functional significance. Meanwhile, we found that the disorder of FGFR3, hsa-miR-486-5p, and lnc-KCNH5-1 plays a key vital role in developing TLE+HS.
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Affiliation(s)
- Zhi-Bin Wang
- Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacology, Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Central South University, Changsha, China
| | - Jian Qu
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhuan-Yi Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Ding-Yang Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Shi-Long Jiang
- Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacology, Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Central South University, Changsha, China
| | - Ying Zhang
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, China
| | - Zhi-Quan Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
- Zhi-Quan Yang,
| | - Xiao-Yuan Mao
- Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacology, Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Central South University, Changsha, China
- Xiao-Yuan Mao,
| | - Zhao-Qian Liu
- Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Institute of Clinical Pharmacology, Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Central South University, Changsha, China
- *Correspondence: Zhao-Qian Liu,
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Ahmadi M, Herting A, Mueffelmann B, Woermann FG, Abou Jamra R, Bien CG, Polster T, Brandt C. Hypochondroplasia and temporal lobe epilepsy - A series of 4 cases. Epilepsy Behav 2022; 126:108479. [PMID: 34922328 DOI: 10.1016/j.yebeh.2021.108479] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/26/2021] [Accepted: 11/27/2021] [Indexed: 11/03/2022]
Abstract
Hypochondroplasia is a skeletal dysplasia syndrome with an autosomal dominant inheritance. It may be associated with temporal lobe epilepsy. We present a series of four patients (two female, two male) with hypochondroplasia who presented at our center with drug refractory epilepsy. Clinical details and EEG and MRI findings led to a diagnosis of temporal lobe epilepsy in all four cases. The MRI findings indicate the epilepsy in hypochondroplasia may be associated with bilateral temporal lobe dysgenesis.
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Affiliation(s)
- Mehdi Ahmadi
- Dept. of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Campus Bielefeld-Bethel, Maraweg 21, 33617 Bielefeld, Germany.
| | - Arne Herting
- Dept. of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Campus Bielefeld-Bethel, Maraweg 21, 33617 Bielefeld, Germany.
| | - Birgitt Mueffelmann
- Dept. of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Campus Bielefeld-Bethel, Maraweg 21, 33617 Bielefeld, Germany.
| | | | - Rami Abou Jamra
- Institute of Human Genetics, University Medical Center Leipzig, Leipzig, Germany.
| | - Christian G Bien
- Dept. of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Campus Bielefeld-Bethel, Maraweg 21, 33617 Bielefeld, Germany.
| | - Tilman Polster
- Dept. of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Campus Bielefeld-Bethel, Maraweg 21, 33617 Bielefeld, Germany.
| | - Christian Brandt
- Dept. of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Campus Bielefeld-Bethel, Maraweg 21, 33617 Bielefeld, Germany.
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