Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.1
3.5
Journals
Genes
Special Issues
Bioinformatics and Genetics of Human Diseases
share announcement

Bioinformatics and Genetics of Human Diseases

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (25 December 2022) | Viewed by 48967

Special Issue Editors

Prof. Dr. Jinchen Li

E-Mail Website
Guest Editor
Center of Medical Genetics, School of Life Sciences, Central South University, Changsha 410083, China
Interests: genetics and bioinformatics of neuropsychiatric disorders
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chao Chen

E-Mail Website
Co-Guest Editor
Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha 410083, China
Interests: multi-omics studies in brain diseases; network analysis; functional genomics; phenomics of human brain organoids
Dr. Mingbang Wang

E-Mail Website
Co-Guest Editor
South China Hospital of Shenzhen University, Shenzhen, China
Interests: pediatric disorders; perinatal risk; machine learning; gut microbiota; the role and mechanism of genetic and perinatal risk factors and their interactions in the occurrence of pediatric and psychiatric diseases; application of machine learning, deep learning and other artificial intelligence technology in metagenomics and metabolomics; the role of gut microbiota and metabolites in the perinatal period, newborns, children, and neuropsychiatric diseases

Special Issue Information

Dear Colleagues,

Thanks to rapid advances in high-throughput sequencing technology (i.e., whole-exome sequencing), the sharp increase in genome data and methodology have accelerated the identification of candidate genes and associated variants in human genetic diseases. However, the genetic causes in more than half of patients are still unclear. As a scientific community, we must confront these challenges and develop novel bioinformatics methods, tools, or databases to accelerate the prioritization of novel disease-associated variants and genes. We must also deeply investigate the genotype–phenotype correlations for specific genes, variants, or diseases with large sample sizes, assisting in precision medicine of complex human diseases. Recently, an increasing number of studies have demonstrated that human diseases involve noncoding variants, short tandem repeats, transposable elements and so on, providing novel insights for medical genetics in human diseases. In the current scenario of rapid progress, we believe more and more disease-associated variants will be prioritized by whole-genome sequencing and third-generation sequencing in the near future. Specifically, we believe that studies combining omics technologies (genomics, transcriptomics, epigenomics, proteomics, metabolomics, and metagenomics) with biotechnologies (molecular biology, cell biology, neurosciences, and animal model) will provide novel insights into the pathogenesis of human diseases. Researchers are invited to contribute original articles, new methods, or reviews that address current advances in bioinformatics and the genetics of human diseases. If you would like more information about the Special Issue, or have any other questions, please feel free to contact us.

Prof. Dr. Jinchen Li
Prof. Dr. Chao Chen
Dr. Mingbang Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). 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

  • human disease 
  • medical genetics 
  • bioinformatics 
  • candidate gene 
  • genetic variants 
  • multi-omics 
  • genomics 
  • sequencing 
  • regulation 
  • machine learning 
  • functional genomics

Published Papers (20 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review, Other

15 pages, 16198 KiB  
Article
High Level of GMFG Correlated to Poor Clinical Outcome and Promoted Cell Migration and Invasion through EMT Pathway in Triple-Negative Breast Cancer
by Yonglin Zhao, Xing Wei, Jia Li, Yan Diao, Changyou Shan, Weimiao Li, Shuqun Zhang and Fei Wu
Genes 2023, 14(6), 1157; https://doi.org/10.3390/genes14061157 - 26 May 2023
Viewed by 1528
Abstract
Triple-negative breast cancer (TNBC) has a very poor prognosis due to the disease’s lack of established targeted treatment options. Glia maturation factor γ (GMFG), a novel ADF/cofilin superfamily protein, has been reported to be differentially expressed in tumors, but its expression level in [...] Read more.
Triple-negative breast cancer (TNBC) has a very poor prognosis due to the disease’s lack of established targeted treatment options. Glia maturation factor γ (GMFG), a novel ADF/cofilin superfamily protein, has been reported to be differentially expressed in tumors, but its expression level in TNBC remains unknown. The question of whether GMFG correlates with the TNBC prognosis is also unclear. In this study, data from the Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), Human Protein Atlas (HPA), and Genotype-Tissue Expression (GTEx) databases were used to analyze the expression of GMFG in pan-cancer and the correlation between clinical factors. Gene Set Cancer Analysis (GSCA) and Gene Set Enrichment Analysis (GSEA) were also used to analyze the functional differences between the different expression levels and predict the downstream pathways. GMFG expression in breast cancer tissues, and its related biological functions, were further analyzed by immunohistochemistry (IHC), immunoblotting, RNAi, and function assay; we found that TNBC has a high expression of GMFG, and this higher expression was correlated with a poorer prognosis in TCGA and collected specimens of the TNBC. GMFG was also related to TNBC patients’ clinicopathological data, especially those with histological grade and axillary lymph node metastasis. In vitro, GMFG siRNA inhibited cell migration and invasion through the EMT pathway. The above data indicate that high expression of GMFG in TNBC is related to malignancy and that GMFG could be a biomarker for the detection of TNBC metastasis. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

21 pages, 6313 KiB  
Article
An Aggrephagy-Related LncRNA Signature for the Prognosis of Pancreatic Adenocarcinoma
by Xueyuan Huang, Hao Chi, Siqi Gou, Xiyuan Guo, Lin Li, Gaoge Peng, Jinhao Zhang, Jiayu Xu, Siji Nian and Qing Yuan
Genes 2023, 14(1), 124; https://doi.org/10.3390/genes14010124 - 02 Jan 2023
Cited by 14 | Viewed by 2166
Abstract
Pancreatic adenocarcinoma (PAAD) is a common, highly malignant, and aggressive gastrointestinal tumor. The conventional treatment of PAAD shows poor results, and patients have poor prognosis. The synthesis and degradation of proteins are essential for the occurrence and development of tumors. Aggrephagy is a [...] Read more.
Pancreatic adenocarcinoma (PAAD) is a common, highly malignant, and aggressive gastrointestinal tumor. The conventional treatment of PAAD shows poor results, and patients have poor prognosis. The synthesis and degradation of proteins are essential for the occurrence and development of tumors. Aggrephagy is a type of autophagy that selectively degrades aggregated proteins. It decreases the formation of aggregates by degrading proteins, thus reducing the harm to cells. By breaking down proteins, it decreases the formation of aggregates; thus, minimizing damage to cells. For evaluating the response to immunotherapy and prognosis in PAAD patients, in this study, we developed a reliable signature based on aggrephagy-related genes (ARGs). We obtained 298 AGGLncRNAs. Based on the results of one-way Cox and LASSO analyses, the lncRNA signature was constructed. In the risk model, the prognosis of patients in the low-risk group was noticeably better than that of the patients in the high-risk group. Additionally, the ROC curves and nomograms validated the capacity of the risk model to predict the prognosis of PAAD. The patients in the low-risk and high-risk groups showed considerable variations in functional enrichment and immunological analysis. Regarding drug sensitivity, the low-risk and high-risk groups had different half-maximal inhibitory concentrations (IC50). Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

13 pages, 5395 KiB  
Article
Identification of an Amino Acid Metabolism-Related Gene Signature for Predicting Prognosis in Lung Adenocarcinoma
by Wuguang Chang, Hongmu Li, Chun Wu, Leqi Zhong, Tengfei Zhu, Zenghao Chang, Wei Ou and Siyu Wang
Genes 2022, 13(12), 2295; https://doi.org/10.3390/genes13122295 - 06 Dec 2022
Cited by 1 | Viewed by 1605
Abstract
Dysregulation of amino acid metabolism (AAM) is an important factor in cancer progression. This study intended to study the prognostic value of AAM-related genes in lung adenocarcinoma (LUAD). Methods: The mRNA expression profiles of LUAD datasets from The Cancer Genome Atlas (TCGA) and [...] Read more.
Dysregulation of amino acid metabolism (AAM) is an important factor in cancer progression. This study intended to study the prognostic value of AAM-related genes in lung adenocarcinoma (LUAD). Methods: The mRNA expression profiles of LUAD datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were applied as the training and validation sets. After identifying the differentially expressed AAM-related genes, an AAM-related gene signature (AAMRGS) was constructed and validated. Additionally, we systematically analyzed the differences in immune cell infiltration, biological pathways, immunotherapy response, and drug sensitivity between the two AAMRGS subgroups. Results: The prognosis-related signature was constructed on the grounds of key AAM-related genes. LUAD patients were divided into AAMRGS-high and -low groups. Patients in the two subgroups differed in prognosis, tumor microenvironment (TME), biological pathways, and sensitivity to chemotherapy and immunotherapy. The area under the receiver operating characteristics (ROC) and calibration curves showed good predictive ability for the nomogram. Analysis of immune cell infiltration revealed that the TME of the AAMRGS-low group was in a state of immune activation. Conclusion: We constructed an AAMRGS that could effectively predict prognosis and guide treatment strategies for patients with LUAD. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

14 pages, 5712 KiB  
Article
Development and Validation of a Prognostic Model for Esophageal Adenocarcinoma Based on Necroptosis-Related Genes
by Suhong Zhang, Shuang Liu, Zheng Lin, Juwei Zhang, Zhifeng Lin, Haiyin Fang and Zhijian Hu
Genes 2022, 13(12), 2243; https://doi.org/10.3390/genes13122243 - 29 Nov 2022
Viewed by 1373
Abstract
Necroptosis is a newly developed cell death pathway that differs from necrosis and apoptosis; however, the potential mechanism of necroptosis-related genes in EAC and whether they are associated with the prognosis of EAC patients remain unclear. We obtained 159 NRGs from the Kyoto [...] Read more.
Necroptosis is a newly developed cell death pathway that differs from necrosis and apoptosis; however, the potential mechanism of necroptosis-related genes in EAC and whether they are associated with the prognosis of EAC patients remain unclear. We obtained 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and performed differential expression analysis of the NRGs in 9 normal samples and 78 EAC tumor samples derived from The Cancer Genome Atlas (TCGA). Finally, we screened 38 differentially expressed NRGs (DE-NRGs). The results of the GO and KEGG analyses indicated that the DE-NRGs were mainly enriched in the functions and pathways associated with necroptosis. Protein interaction network (PPI) analysis revealed that TNF, CASP1, and IL-1B were the core genes of the network. A risk score model based on four DE-NRGs was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) regression, and the results showed that the higher the risk score, the worse the survival. The model achieved more efficient diagnosis compared with the clinicopathological variables, with an area under the receiver operating characteristic (ROC) curve of 0.885. The prognostic value of this model was further validated using Gene Expression Omnibus (GEO) datasets. Gene set enrichment analyses (GSEA) demonstrated that several metabolism-related pathways were activated in the high-risk population. Single-sample GSEA (ssGSEA) provided further confirmation that this prognostic model was remarkably associated with the immune status of EAC patients. Finally, the nomogram map exhibited a certain prognostic prediction efficiency, with a C-index of 0.792 and good consistency. Thus, the prognostic model based on four NRGs could better predict the prognosis of EAC and help to elucidate the mechanism of necroptosis-related genes in EAC, which can provide guidance for the target prediction and clinical treatment of EAC patients. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

11 pages, 1184 KiB  
Article
Inferring bona fide Differentially Expressed Genes and Their Variants Associated with Vitamin K Deficiency Using a Systems Genetics Approach
by Shalini Rajagopal, Akanksha Sharma, Anita Simlot, Praveen Mathur, Sudhir Mehta, Sumita Mehta, Jalaja Naravula, Krishna Mohan Medicherla, Anil Kumar, Uma Kanga, Renuka Suravajhala, Ramji Kumar Bhandari, Bipin G. Nair, P. B. Kavi Kishor and Prashanth Suravajhala
Genes 2022, 13(11), 2078; https://doi.org/10.3390/genes13112078 - 09 Nov 2022
Cited by 2 | Viewed by 2336
Abstract
Systems genetics is key for integrating a large number of variants associated with diseases. Vitamin K (VK) is one of the scarcely studied disease conditions. In this work, we ascertained the differentially expressed genes (DEGs) and variants associated with individual subpopulations of VK [...] Read more.
Systems genetics is key for integrating a large number of variants associated with diseases. Vitamin K (VK) is one of the scarcely studied disease conditions. In this work, we ascertained the differentially expressed genes (DEGs) and variants associated with individual subpopulations of VK disease phenotypes, viz., myocardial infarction, renal failure and prostate cancer. We sought to ask whether or not any DEGs harbor pathogenic variants common in these conditions, attempt to bridge the gap in finding characteristic biomarkers and discuss the role of long noncoding RNAs (lncRNAs) in the biogenesis of VK deficiencies. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

22 pages, 13459 KiB  
Article
Identifying Prognostic Biomarkers Related to m6A Modification and Immune Infiltration in Renal Cell Carcinoma
by Junjie Ye, Peng Li, Huijiang Zhang, Qi Wu and Dongrong Yang
Genes 2022, 13(11), 2059; https://doi.org/10.3390/genes13112059 - 07 Nov 2022
Cited by 2 | Viewed by 1748
Abstract
Background: Renal cell carcinoma (RCC) is the largest category of kidney tumors and usually does not have a good prognosis. N6-methyladenosine(m6A) and immune infiltration have received increased attention because of their great influence on the clinical outcome and prognosis of cancer patients. Methods: [...] Read more.
Background: Renal cell carcinoma (RCC) is the largest category of kidney tumors and usually does not have a good prognosis. N6-methyladenosine(m6A) and immune infiltration have received increased attention because of their great influence on the clinical outcome and prognosis of cancer patients. Methods: We identified hub genes through multi-dimensional screening, including DEGs, PPI analysis, LASSO regression, and random forest. Meanwhile, GO/KEGG enrichment, cMAP analysis, prognostic analysis, m6A prediction, and immune infiltration analysis were performed to understand the potential mechanism and screen therapeutic drugs. Results: We screened 275 downregulated and 185 upregulated genes using three GEO datasets and the TCGA dataset. In total, 82 candidate hub genes were selected using STRING and Cytoscape. Enrichment analysis illustrated that the top 3 biological process terms and top 1 KEGG term were related to immunity. cMAP analysis showed some antagonistic molecules can be candidate drugs for the treatment of RCC. Then, six hub genes (ERBB2, CASR, P2RY8, CAT, PLAUR, and TIMP1) with strong predictive values for prognosis and clinicopathological features were selected. Meanwhile, P2RY8, ERBB2, CAT, and TIMP1 may obtain m6A modification by binding METTL3 or METTL14. On the other hand, differential expression of CAT, ERBB2, P2RY8, PLAUR, and TIMP1 affects the infiltration of the majority of immune cells. Conclusions: We identified six hub genes through multi-dimensional screening. They all possess strong predictive value for prognosis and clinicopathological features. Meanwhile, hub genes may regulate the progression of RCC via an m6A- and immunity-dependent mechanism. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

21 pages, 5018 KiB  
Article
Integration of lncRNAs, Protein-Coding Genes and Pathology Images for Detecting Metastatic Melanoma
by Shuai Liu, Yusi Fan, Kewei Li, Haotian Zhang, Xi Wang, Ruofei Ju, Lan Huang, Meiyu Duan and Fengfeng Zhou
Genes 2022, 13(10), 1916; https://doi.org/10.3390/genes13101916 - 21 Oct 2022
Cited by 1 | Viewed by 1616
Abstract
Melanoma is a lethal skin disease that develops from moles. This study aimed to integrate multimodal data to predict metastatic melanoma, which is highly aggressive and difficult to treat. The proposed EnsembleSKCM method evaluated the prediction performances of long noncoding RNAs (lncRNAs), protein-coding [...] Read more.
Melanoma is a lethal skin disease that develops from moles. This study aimed to integrate multimodal data to predict metastatic melanoma, which is highly aggressive and difficult to treat. The proposed EnsembleSKCM method evaluated the prediction performances of long noncoding RNAs (lncRNAs), protein-coding messenger genes (mRNAs) and pathology images (images) for metastatic melanoma. Feature selection was used to screen for metastatic biomarkers in the lncRNA and mRNA datasets. The integrated EnsembleSKCM model was built based on the weighted results of the lncRNA-, mRNA- and image-based models. EnsembleSKCM achieved 0.9444 in the prediction accuracy of metastatic melanoma and outperformed the single-modal prediction models based on the lncRNA, mRNA and image data. The experimental data suggest the importance of integrating the complementary information from the three data modalities. WGCNA was used to analyze the relationship of molecular-level features and image features, and the results show connections between them. Another cohort was used to validate our prediction. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

18 pages, 23308 KiB  
Article
Systematic Analysis of Immune Infiltration and Predicting Prognosis in Clear Cell Renal Cell Carcinoma Based on the Inflammation Signature
by Yuke Zhang, Chunliu Shi, Yue Chen, Hongwei Wang, Feng Chen and Ping Han
Genes 2022, 13(10), 1897; https://doi.org/10.3390/genes13101897 - 19 Oct 2022
Cited by 2 | Viewed by 1591
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most frequent kind of kidney malignancy. Inflammation is a physiological response of the immune system to harmful stimuli. Notably, the role inflammation plays in ccRCC is still unknown. In this study, consensus clustering analysis sorted [...] Read more.
Clear cell renal cell carcinoma (ccRCC) is the most frequent kind of kidney malignancy. Inflammation is a physiological response of the immune system to harmful stimuli. Notably, the role inflammation plays in ccRCC is still unknown. In this study, consensus clustering analysis sorted the ccRCC specimens from the TCGA dataset into C1 and C2 clusters. The C2 cluster comprised ccRCC specimens with a high TNM stage and tumor grade. These specimens were characterized by the activation of the inflammatory response and an immunosuppressive microenvironment. A seven-gene inflammation-related risk signature was designed employing the LASSO and Cox regression analyses for the inflammation-related genes. The ccRCC specimens were classified into two groups with high and low risk by calculating the risk scores. The specimens in the group with high risk showed a poor prognosis and were positively correlated with immune inhibitory factors. Moreover, a nomogram was created by incorporating inflammation-related risk signatures and clinical characteristics. The ROC and DCA curves indicated a satisfactory efficiency of the nomogram for predicting the survival outcomes. Furthermore, we identified the potential therapeutic drug molecules through CMap analysis. The findings of our study may act as a guide for further research on new prognostic biomarkers and therapies. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

15 pages, 5525 KiB  
Article
Identification and Analysis of Immune-Related Gene Signature in Hepatocellular Carcinoma
by Bingbing Shen, Guanqi Zhang, Yunxun Liu, Jianguo Wang and Jianxin Jiang
Genes 2022, 13(10), 1834; https://doi.org/10.3390/genes13101834 - 11 Oct 2022
Cited by 9 | Viewed by 2662
Abstract
Background: Hepatocellular carcinoma (HCC) originates from the hepatocytes and accounts for 90% of liver cancer. The study intends to identify novel prognostic biomarkers for predicting the prognosis of HCC patients based on TCGA and GSE14520 cohorts. Methods: Differential analysis was employed to obtain [...] Read more.
Background: Hepatocellular carcinoma (HCC) originates from the hepatocytes and accounts for 90% of liver cancer. The study intends to identify novel prognostic biomarkers for predicting the prognosis of HCC patients based on TCGA and GSE14520 cohorts. Methods: Differential analysis was employed to obtain the DEGs (Differentially Expressed Genes) of the TCGA-LIHC-TPM cohort. The lasso regression analysis was applied to build the prognosis model through using the TCGA cohort as the training group and the GSE14520 cohort as the testing group. Next, based on the prognosis model, we performed the following analyses: the survival analysis, the independent prognosis analysis, the clinical feature analysis, the mutation analysis, the immune cell infiltration analysis, the tumor microenvironment analysis, and the drug sensitivity analysis. Finally, the survival time of HCC patients was predicted by constructing nomograms. Results: Through the lasso regression analysis, we obtained a prognosis model of ten genes including BIRC5 (baculoviral IAP repeat containing 5), CDK4 (cyclin-dependent kinase 4), DCK (deoxycytidine kinase), HSPA4 (heat shock protein family A member 4), HSP90AA1 (heat shock protein 90 α family class A member 1), PSMD2 (Proteasome 26S Subunit Ubiquitin Receptor, Non-ATPase 2), IL1RN (interleukin 1 receptor antagonist), PGF (placental growth factor), SPP1 (secreted phosphoprotein 1), and STC2 (stanniocalcin 2). First, we found that the risk score is an independent prognosis factor and is related to the clinical features of HCC patients, covering AFP (α-fetoprotein) and stage. Second, we observed that the p53 mutation was the most obvious mutation between the high-risk and low-risk groups. Third, we also discovered that the risk score is related to some immune cells, covering B cells, T cells, dendritic, macrophages, neutrophils, etc. Fourth, the high-risk group possesses a lower TIDE score, a higher expression of immune checkpoints, and higher ESTIMATE score. Finally, nomograms include the clinical features and risk signatures, displaying the clinical utility of the signature in the survival prediction of HCC patients. Conclusions: Through the comprehensive analysis, we constructed an immune-related prognosis model to predict the survival of HCC patients. In addition to predicting the survival time of HCC patients, this model significantly correlates with the tumor microenvironment. Furthermore, we concluded that these ten immune-related genes (BIRC5, CDK4, DCK, HSPA4, HSP90AA1, PSMD2, IL1RN, PGF, SPP1, and STC2) serve as novel targets for antitumor immunity. Therefore, this study plays a significant role in exploring the clinical application of immune-related genes. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

9 pages, 669 KiB  
Article
An Analysis of Phenotype and Genotype in a Large Cohort of Chinese Children with Angelman Syndrome
by Xiaonan Du, Ji Wang, Shuang Li, Yu Ma, Tianqi Wang, Bingbing Wu, Yuanfeng Zhou, Lifei Yu and Yi Wang
Genes 2022, 13(8), 1447; https://doi.org/10.3390/genes13081447 - 14 Aug 2022
Cited by 3 | Viewed by 1974
Abstract
Angelman syndrome (AS) is a neurodevelopmental genetic disorder, but there has been limited analysis of a large cohort of Chinese children with Angelman syndrome. This study aims to assess the phenotype and genotype of Chinese children with Angelman syndrome. We retrospectively analyzed data [...] Read more.
Angelman syndrome (AS) is a neurodevelopmental genetic disorder, but there has been limited analysis of a large cohort of Chinese children with Angelman syndrome. This study aims to assess the phenotype and genotype of Chinese children with Angelman syndrome. We retrospectively analyzed data through a detailed online survey combined with an on-site study. Furthermore, phenotype analysis stratified by deletion and non-deletion groups was carried out. The responses of family members of 695 individuals with AS revealed that 577 patients (83.02%) had maternal deletions, 65 patients (9.35%) carried UBE3A mutations, 31 (4.46%) patients had UPD15pat (one patient with UPD15pat constituted by a mosaic), 10 patients (1.44%) had imprinting defects and 12 (1.58%) patients only showed abnormal methylation without further detection. We identified 50 different pathogenic variants in this cohort, although 18 of these variants were unreported. Recurrent variant c.2507_2510del (p.K836Rfs*4) was found in 7 patients. In the deletion group, patients were diagnosed at an earlier age, had a more severe clinical phenotype, a higher rate of epilepsy with more multiple seizure types, and more frequently combined medication. Strabismus and sleep disturbances were both common in deletion and non-deletion groups. The top three resources invested in caring for AS children are: daily involvement in patient care, rehabilitation cost, and anti-epileptic treatment. Our study showed the genetic composition of Chinese children with 83.02% of maternal deletions, and the mutation spectrum for UBE3A variants was expanded. Developmental outcomes are associated with genotype, and this was confirmed by deletion patients having a worse clinical phenotype and complex epilepsy. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Graphical abstract

17 pages, 3640 KiB  
Article
The Identification by Exome Sequencing of Candidate Genes in BRCA-Negative Tunisian Patients at a High Risk of Hereditary Breast/Ovarian Cancer
by Dorra BenAyed-Guerfali, Chamseddine Kifagi, Wala BenKridis-Rejeb, Nihel Ammous-Boukhris, Wajdi Ayedi, Afef Khanfir, Jamel Daoud and Raja Mokdad-Gargouri
Genes 2022, 13(8), 1296; https://doi.org/10.3390/genes13081296 - 22 Jul 2022
Cited by 3 | Viewed by 2720
Abstract
(1) Background: Germline variants in BRCA1/BRCA2 genes explain about 20% of hereditary breast/ovarian cancer (HBOC) cases. In the present paper, we aim to identify genetic determinants in BRCA-negative families from the South of Tunisia. (2) Methods: Exome Sequencing (ES) was performed on [...] Read more.
(1) Background: Germline variants in BRCA1/BRCA2 genes explain about 20% of hereditary breast/ovarian cancer (HBOC) cases. In the present paper, we aim to identify genetic determinants in BRCA-negative families from the South of Tunisia. (2) Methods: Exome Sequencing (ES) was performed on the lymphocyte DNA of patients negative for BRCA mutations from each Tunisian family with a high risk of HBOC. (3) Results: We focus on the canonical genes associated with HBOC and identified missense variants in DNA damage response genes, such as ATM, RAD52, and RAD54; however, no variants in PALB2, Chek2, and TP53 genes were found. To identify novel candidate genes, we selected variants harboring a loss of function and identified 17 stop-gain and 11 frameshift variants in genes not commonly known to be predisposed to HBOC. Then, we focus on rare and high-impact genes shared by at least 3 unrelated patients from each family and selected 16 gene variants. Through combined data analysis from MCODE with gene ontology and KEGG pathways, a short list of eight candidate genes (ATM, EP300, LAMA1, LAMC2, TNNI3, MYLK, COL11A2, and LAMB3) was created. The impact of the 24 selected genes on survival was analyzed using the TCGA data resulting in a selection of five candidate genes (EP300, KMT2C, RHPN2, HSPG2, and CCR3) that showed a significant association with survival. (4) Conclusions: We identify novel candidate genes predisposed to HBOC that need to be validated in larger cohorts and investigated by analyzing the co-segregation of selected variants in affected families and the locus-specific loss of heterozygosity to highlight their relevance for HBOC risk. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

11 pages, 591 KiB  
Article
Identifying Rare Genetic Variants of Immune Mediators as Risk Factors for Autism Spectrum Disorder
by Chunquan Cai, Zhaoqing Yin, Aiping Liu, Hui Wang, Shujuan Zeng, Zhangxing Wang, Huixian Qiu, Shijun Li, Jiaxiu Zhou and Mingbang Wang
Genes 2022, 13(6), 1098; https://doi.org/10.3390/genes13061098 - 20 Jun 2022
Cited by 5 | Viewed by 2291
Abstract
Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies [...] Read more.
Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies have shown that ASD is more common in children with folate receptor autoantibodies. We also found that children with ASD have abnormal gut immune function, which was characterized by a significant increase in the content of immunoglobulin A and an increase in gut-microbiota-associated epitope diversity. These studies suggest that the immune mechanism plays an important role in the occurrence of ASD. The present study aims to systematically assess gene mutations in immune mediators in patients with ASD. We collected genetic samples from 72 children with ASD (2–12 years old) and 107 healthy controls without ASD (20–78 years old). We used our previously-designed immune gene panel, which can capture cytokine and receptor genes, the coding regions of MHC genes, and genes of innate immunity. Target region sequencing (500×) and bioinformatics analytical methods were used to identify variants in immune response genes associated with patients with ASD. A total of 4 rare variants were found to be associated with ASD, including HLA-B: p.A93G, HLA-DQB1: p.S229N, LILRB2: p.R322H, and LILRB2: c.956-4C>T. These variants were present in 44.44% (32/72) of the ASD patients and were detected in 3.74% (4/107) of the healthy controls. We expect these genetic variants will serve as new targets for the clinical genetic assessment of ASD, and our findings suggest that immune abnormalities in children with ASD may have a genetic basis. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

14 pages, 1415 KiB  
Article
Clinical Targeted Panel Sequencing Analysis in Clinical Evaluation of Children with Autism Spectrum Disorder in China
by Chunchun Hu, Linlin He, Huiping Li, Yanhua Ding, Kaifeng Zhang, Dongyun Li, Guoqing Zhu, Bingbing Wu, Xiu Xu and Qiong Xu
Genes 2022, 13(6), 1010; https://doi.org/10.3390/genes13061010 - 02 Jun 2022
Cited by 2 | Viewed by 2151
Abstract
Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder in which genetics play a major role. Molecular diagnosis may lead to a more accurate prognosis, improved clinical management, and potential treatment of the condition. Both copy number variations (CNVs) and single nucleotide variations [...] Read more.
Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder in which genetics play a major role. Molecular diagnosis may lead to a more accurate prognosis, improved clinical management, and potential treatment of the condition. Both copy number variations (CNVs) and single nucleotide variations (SNVs) have been reported to contribute to the genetic etiology of ASD. The effectiveness and validity of clinical targeted panel sequencing (CTPS) designed to analyze both CNVs and SNVs can be evaluated in different ASD cohorts. CTPS was performed on 573 patients with the diagnosis of ASD. Medical records of positive CTPS cases were further reviewed and analyzed. Additional medical examinations were performed for a group of selective cases. Positive molecular findings were confirmed by orthogonal methods. The overall positive rate was 19.16% (109/569) in our cohort. About 13.89% (79/569) and 4.40% (25/569) of cases had SNVs only and CNVs only findings, respectively, while 0.9% (5/569) of cases had both SNV and CNV findings. For cases with SNVs findings, the SHANK3 gene has the greatest number of reportable variants, followed by gene MYT1L. Patients with MYT1L variants share common and specific clinical characteristics. We found a child with compound heterozygous SLC26A4 variants had an enlarged vestibular aqueduct syndrome and autistic phenotype. Our results showed that CTPS is an effective molecular diagnostic tool for ASD. Thorough clinical and genetic evaluation of ASD can lead to more accurate diagnosis and better management of the condition. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

10 pages, 626 KiB  
Article
Genetic Variants Involved in the Crystallization Pathway Are Associated with Calcium Nephrolithiasis in the Chinese Han Population
by Lujia Wang, Xiaoling Lin, Zijian Zhou, Yuanyuan Yang, Peng Gao and Zhong Wu
Genes 2022, 13(6), 943; https://doi.org/10.3390/genes13060943 - 25 May 2022
Viewed by 1634
Abstract
A genome-wide association analysis study (GWAS) in the Japanese population identified 14 significant loci associated with nephrolithiasis. Besides 4 novel loci related to metabolic traits, the 10 remaining loci were associated with kidney or electrolyte-related traits. We aimed to replicate the association of [...] Read more.
A genome-wide association analysis study (GWAS) in the Japanese population identified 14 significant loci associated with nephrolithiasis. Besides 4 novel loci related to metabolic traits, the 10 remaining loci were associated with kidney or electrolyte-related traits. We aimed to replicate the association of these loci with calcium nephrolithiasis in the Chinese Han population. A case–control association analysis was conducted involving 691 calcium nephrolithiasis patients and 1008 control subjects. We were able to genotype a total of 11 single-nucleotide polymorphisms (SNPs) previously identified as being correlated with nephrolithiasis in the Japanese population. SNP rs35747824 at PDILT was related to calcium nephrolithiasis in the Chinese Han population (p = 4.346 × 10−3, OR = 1.292). Moreover, four SNPs at four loci, rs6667242 at ALPL (p = 0.02999, OR = 0.8331), rs1544935 at KCNK5 (p = 0.01341, OR = 0.7804), rs7328064 at DGKH (p = 0.007452, OR = 1.211) and rs13041834 at BCAS1 (p = 0.03897, OR = 0.8409), were suggestively associated with calcium nephrolithiasis. Our results demonstrated that the genetic variants at 1p36.12, 6p21.2, 13q14.11, 16p12.3 and 20q13.2 are associated with calcium nephrolithiasis in the Chinese Han population. Furthermore, our study highlights the importance of genetic variance associated with the crystallization pathway in Chinese patients with calcium nephrolithiasis. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

11 pages, 1668 KiB  
Article
Rare Variant Analysis and Molecular Dynamics Simulation in Alzheimer’s Disease Identifies Exonic Variants in FLG
by Weixue Xiong, Jiahui Cai, Ruijia Li, Canhong Wen, Haizhu Tan and on behalf of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Database
Genes 2022, 13(5), 838; https://doi.org/10.3390/genes13050838 - 07 May 2022
Cited by 4 | Viewed by 2275
Abstract
Background: Although an increasing number of common variants contributing to Alzheimer’s disease (AD) are uncovered by genome-wide association studies, they can only explain less than half of the heritability of AD. Rare variant association studies (RVAS) has become an increasingly important area to [...] Read more.
Background: Although an increasing number of common variants contributing to Alzheimer’s disease (AD) are uncovered by genome-wide association studies, they can only explain less than half of the heritability of AD. Rare variant association studies (RVAS) has become an increasingly important area to explain the risk or trait variability of AD. Method: To investigate the potential rare variants that cause AD, we screened 70,209 rare variants from two cohorts of a 175 AD cohort and a 214 cognitively normal cohort from the Alzheimer’s Disease Neuroimaging Initiative database. MIRARE, a novel RVAS method, was performed on 232 non-synonymous variants selected by ANNOVAR annotation. Molecular docking and molecular dynamics (MD) simulation were adopted to verify the interaction between the chosen functional variants and BACE1. Results: MIRAGE analysis revealed significant associations between AD and six potential pathogenic genes, including PREX2, FLG, DHX16, NID2, ZnF585B and ZnF875. Only interactions between FLG (including wild type and rs3120654(SER742TYR)) and BACE1 were verified by molecular docking and MD simulation. The interaction of FLG(SER742TYR) with BACE1 was greater than that of wildtype FLG with BACE1. Conclusions: According to the literature search, bio-informatics analysis, and molecular docking and MD simulation, we find non-synonymous rare variants in six genes, especially FLG(rs3120654), that may play key roles in AD. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

16 pages, 1868 KiB  
Article
Computational Saturation Mutagenesis to Investigate the Effects of Neurexin-1 Mutations on AlphaFold Structure
by Raina Rhoades, Brianna Henry, Dominique Prichett, Yayin Fang and Shaolei Teng
Genes 2022, 13(5), 789; https://doi.org/10.3390/genes13050789 - 28 Apr 2022
Cited by 4 | Viewed by 2863
Abstract
Neurexin-1 (NRXN1) is a membrane protein essential in synapse formation and cell signaling as a cell-adhesion molecule and cell-surface receptor. NRXN1 and its binding partner neuroligin have been associated with deficits in cognition. Recent genetics research has linked NRXN1 missense mutations to increased [...] Read more.
Neurexin-1 (NRXN1) is a membrane protein essential in synapse formation and cell signaling as a cell-adhesion molecule and cell-surface receptor. NRXN1 and its binding partner neuroligin have been associated with deficits in cognition. Recent genetics research has linked NRXN1 missense mutations to increased risk for brain disorders, including schizophrenia (SCZ) and autism spectrum disorder (ASD). Investigation of the structure–function relationship in NRXN1 has proven difficult due to a lack of the experimental full-length membrane protein structure. AlphaFold, a deep learning-based predictor, succeeds in high-quality protein structure prediction and offers a solution for membrane protein model construction. In the study, we applied a computational saturation mutagenesis method to analyze the systemic effects of missense mutations on protein functions in a human NRXN1 structure predicted from AlphaFold and an experimental Bos taurus structure. The folding energy changes were calculated to estimate the effects of the 29,540 mutations of AlphaFold model on protein stability. The comparative study on the experimental and computationally predicted structures shows that these energy changes are highly correlated, demonstrating the reliability of the AlphaFold structure for the downstream bioinformatics analysis. The energy calculation revealed that some target mutations associated with SCZ and ASD could make the protein unstable. The study can provide helpful information for characterizing the disease-causing mutations and elucidating the molecular mechanisms by which the variations cause SCZ and ASD. This methodology could provide the bioinformatics protocol to investigate the effects of target mutations on multiple AlphaFold structures. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

12 pages, 1461 KiB  
Article
ProGeo-Neo v2.0: A One-Stop Software for Neoantigen Prediction and Filtering Based on the Proteogenomics Strategy
by Chunyu Liu, Yu Zhang, Xingxing Jian, Xiaoxiu Tan, Manman Lu, Jian Ouyang, Zhenhao Liu, Yuyu Li, Linfeng Xu, Lanming Chen, Yong Lin and Lu Xie
Genes 2022, 13(5), 783; https://doi.org/10.3390/genes13050783 - 28 Apr 2022
Cited by 9 | Viewed by 2567
Abstract
A proteogenomics-based neoantigen prediction pipeline, namely ProGeo-neo, was previously developed by our team to predict neoantigens, allowing the identification of class-I major histocompatibility complex (MHC) binding peptides based on single-nucleotide variation (SNV) mutations. To improve it, we here present an updated pipeline, i.e., [...] Read more.
A proteogenomics-based neoantigen prediction pipeline, namely ProGeo-neo, was previously developed by our team to predict neoantigens, allowing the identification of class-I major histocompatibility complex (MHC) binding peptides based on single-nucleotide variation (SNV) mutations. To improve it, we here present an updated pipeline, i.e., ProGeo-neo v2.0, in which a one-stop software solution was proposed to identify neoantigens based on the paired tumor-normal whole genome sequencing (WGS)/whole exome sequencing (WES) data in FASTQ format. Preferably, in ProGeo-neo v2.0, several new features are provided. In addition to the identification of MHC-I neoantigens, the new version supports the prediction of MHC class II-restricted neoantigens, i.e., peptides up to 30-mer in length. Moreover, the source of neoantigens has been expanded, allowing more candidate neoantigens to be identified, such as in-frame insertion-deletion (indels) mutations, frameshift mutations, and gene fusion analysis. In addition, we propose two more efficient screening approaches, including an in-group authentic neoantigen peptides database and two more stringent thresholds. The range of candidate peptides was effectively narrowed down to those that are more likely to elicit an immune response, providing a more meaningful reference for subsequent experimental validation. Compared to ProGeo-neo, the ProGeo-neo v2.0 performed well based on the same dataset, including updated functionality and improved accuracy. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

18 pages, 11430 KiB  
Article
Integrated Analysis of RNA Binding Protein-Related lncRNA Prognostic Signature for Breast Cancer Patients
by Shaohua Xu, Jiahui Xie, Yanjie Zhou, Hui Liu, Yirong Wang and Zhaoyong Li
Genes 2022, 13(2), 345; https://doi.org/10.3390/genes13020345 - 14 Feb 2022
Cited by 7 | Viewed by 2802
Abstract
Long non-coding RNAs (lncRNAs) have been well known for their multiple functions in the tumorigenesis, development, and prognosis of breast cancer (BC). Mechanistically, their production, function, or stability can be regulated by RNA binding proteins (RBPs), which were also involved in the carcinogenesis [...] Read more.
Long non-coding RNAs (lncRNAs) have been well known for their multiple functions in the tumorigenesis, development, and prognosis of breast cancer (BC). Mechanistically, their production, function, or stability can be regulated by RNA binding proteins (RBPs), which were also involved in the carcinogenesis and progression of BC. However, the roles and clinical implications of RBP-related lncRNAs in BC remain largely unknown. Therefore, we herein aim to construct a prognostic signature with RBP-relevant lncRNAs for the prognostic evaluation of BC patients. Firstly, based on the RNA sequencing data of female BC patients from The Cancer Genome Atlas (TCGA) database, we screened out 377 differentially expressed lncRNAs related to RBPs. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were then performed to establish a prognostic signature composed of 12-RBP-related lncRNAs. Furthermore, we divided the BC patients into high- and low-risk groups by the prognostic signature and found the overall survival (OS) of patients in the high-risk group was significantly shorter than that of the low-risk group. Moreover, the 12-lncRNA signature exhibited independence in evaluating the prognosis of BC patients. Additionally, a functional enrichment analysis revealed that the prognostic signature was associated with some cancer-relevant pathways, including cell cycle and immunity. In summary, our 12-lncRNA signature may provide a theoretical reference for the prognostic evaluation or clinical treatment of BC patients. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

Review

Jump to: Research, Other

12 pages, 521 KiB  
Review
Pathogenesis of Choledochal Cyst: Insights from Genomics and Transcriptomics
by Yongqin Ye, Vincent Chi Hang Lui and Paul Kwong Hang Tam
Genes 2022, 13(6), 1030; https://doi.org/10.3390/genes13061030 - 08 Jun 2022
Cited by 6 | Viewed by 3517
Abstract
Choledochal cysts (CC) is characterized by extra- and/or intra-hepatic b\ile duct dilations. There are two main theories, “pancreaticobiliary maljunction” and “congenital stenosis of bile ducts” proposed for the pathogenesis of CC. Although family cases or CC associated with other anomalies have been reported, [...] Read more.
Choledochal cysts (CC) is characterized by extra- and/or intra-hepatic b\ile duct dilations. There are two main theories, “pancreaticobiliary maljunction” and “congenital stenosis of bile ducts” proposed for the pathogenesis of CC. Although family cases or CC associated with other anomalies have been reported, the molecular pathogenesis of CC is still poorly understood. Recent advances in transcriptomics and genomics analysis platforms have unveiled key expression signatures/genes/signaling pathways in the pathogenesis of human diseases including CC. This review summarizes insights from genomics and transcriptomics studies into the pathogenesis of CC, with the aim to improve (i) our understanding of its underlying complex pathomechanisms, and (ii) clinical management of different subtypes of CC, in particular their associated hepatic fibrotic change and their risk of malignancy transformation. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

Other

Jump to: Research, Review

11 pages, 2632 KiB  
Case Report
Clinical and Genetic Studies of the First Monozygotic Twins with Pfeiffer Syndrome
by Piranit N. Kantaputra, Salita Angkurawaranon, Krit Khwanngern, Chumpol Ngamphiw, Worrachet Intachai, Ploy Adisornkanj, Sissades Tongsima, Bjorn Olsen, Nuntigar Sonsuwan and Kamornwan Katanyuwong
Genes 2022, 13(10), 1850; https://doi.org/10.3390/genes13101850 - 13 Oct 2022
Viewed by 4885
Abstract
Objective: To report the clinical and radiographic findings and molecular etiology of the first monozygotic twins affected with Pfeiffer syndrome. Methods: Clinical and radiographic examination and whole exome sequencing were performed on two monozygotic twins with Pfeiffer syndrome. Results: An acceptor splice site [...] Read more.
Objective: To report the clinical and radiographic findings and molecular etiology of the first monozygotic twins affected with Pfeiffer syndrome. Methods: Clinical and radiographic examination and whole exome sequencing were performed on two monozygotic twins with Pfeiffer syndrome. Results: An acceptor splice site mutation in FGFR2 (c.940-2A>G) was detected in both twins. The father and both twins shared the same haplotype, indicating that the mutant allele was from their father’s chromosome who suffered severe upper airway obstruction and subsequent obstructive sleep apnea. Hypertrophy of nasal turbinates appears to be a newly recognized finding of Pfeiffer syndrome. Increased intracranial pressure in both twins were corrected early by fronto-orbital advancement with skull expansion and open osteotomy, in order to prevent the more severe consequences of increased intracranial pressure, including hydrocephalus, the bulging of the anterior fontanelle, and the diastasis of suture. Conclusions: Both twins carried a FGFR2 mutation and were discordant for lambdoid synostosis. Midface hypoplasia, narrow nasal cavities, and hypertrophic nasal turbinates resulted in severe upper airway obstruction and subsequent obstructive sleep apnea in both twins. Hypertrophy of the nasal turbinates appears to be a newly recognized finding of Pfeiffer syndrome. Fronto-orbital advancement with skull expansion and open osteotomy was performed to treat increased intracranial pressure in both twins. This is the first report of monozygotic twins with Pfeiffer syndrome. Full article
(This article belongs to the Special Issue Bioinformatics and Genetics of Human Diseases)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-20
Back to TopTop