Human Gene最新文献

{"title":"Understanding the impact of cytokine gene polymorphisms (IL10 rs1800872 and TNF rs1800629) on COVID-19 severity: A comprehensive meta-analysis","authors":"Saranya Velmurugan ,&nbsp;Rashmi Pauline ,&nbsp;Langeswaran Kulanthaivel ,&nbsp;Gowtham Kumar Subbaraj","doi":"10.1016/j.humgen.2024.201308","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201308","url":null,"abstract":"<div><h3>Aim</h3><p>The anti-inflammatory and pro-inflammatory cytokine genes are linked to the severity and prognosis of individuals with respiratory and non-respiratory viral infections. The present investigation aimed to evaluate the association between the cytokine (<em>IL10</em> rs1800872 &amp; <em>TNF</em> rs1800629) gene polymorphisms and the severity of COVID-19 severity.</p></div><div><h3>Methods</h3><p>The PubMed, Elsevier, Science Direct, and EMBASE databases were utilized for a comprehensive literature review to find suitable case-control studies that investigate the relationship between the <em>IL10</em> rs1800872 and <em>TNF</em> rs1800629 gene polymorphisms and COVID-19 severity. The articles included in the investigation provided the genotypic data for analysis and meet the inclusion criteria. Each model was assessed with a 95% confidence interval (CI) and odds ratio (OR), with significance set at <em>p</em> &lt; 0.05 for <em>IL10</em> rs1800872 and <em>TNF</em> rs1800629 gene polymorphisms. MetaGenyo software was used to conduct a meta-analysis for assessing the statistical significance. The study quality was assessed using the Rob2 tool.</p></div><div><h3>Results</h3><p>Totally 3994 COVID-19 cases and 3504 controls in eleven studies were examined to identify the relationship between <em>IL10</em> rs1800872 &amp; <em>TNF</em> rs1800629 gene polymorphisms and the severity of COVID-19 in Asian and Caucasian populations. The findings revealed that there was a notable association between the <em>TNF</em> rs1800629 gene polymorphism and the COVID-19 severity, with a <em>p</em>-value &lt;0.05 indicating statistical significance. However, no association was found between the <em>IL10</em> rs1800872 gene polymorphism and the severity of COVID-19 with a <em>p</em>-value &gt;0.05 suggesting insignificance. Furthermore, the findings were confirmed with the funnel plot analysis, which demonstrated the statistical validity of the results.</p></div><div><h3>Conclusion</h3><p>The <em>TNF</em> rs1800629 gene polymorphism is a risk factor for the severity of COVID-19 and the <em>IL10</em> rs1800872 gene polymorphism does not have any association with the severity of COVID-19. Therefore, the <em>TNF</em> gene plays a role in the development of severe COVID-19 and it can be used as a biomarker for diagnosis of COVID-19.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201308"},"PeriodicalIF":0.5,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classify Alzheimer genes association using Naïve Bayes algorithm","authors":"Sushrutha Raj ,&nbsp;Anchal Vishnoi ,&nbsp;Alok Srivastava","doi":"10.1016/j.humgen.2024.201309","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201309","url":null,"abstract":"<div><h3>Background</h3><p>Alzheimer's disease, the most common form of dementia, accounts for 60–80% of cases and its prevalence is projected to increase as aging populations grow. By 2050, the number of individuals with Alzheimer's and dementia worldwide is expected to reach 152 million. Genetics plays a significant role, contributing to about 70% of the overall risk, underscoring the importance of understanding the genetic basis for developing targeted interventions. This study presents a system that combines text mining and machine learning techniques to identify and prioritize prospective candidate genes for Alzheimer's and further classifies them into three association classes with weights.</p></div><div><h3>Methods</h3><p>The machine learning-based classifier was trained over a meticulously curated gold standard dataset and then rigorously validated utilizing a 10-fold cross-validation method, demonstrating its consistency across all the folds of the data. This developed ensemble learning system categorizes PubMed abstracts into three distinct groups: Yes, No, and Ambiguous using text mining and a Bayesian classification algorithm. The system further predicts disease-gene associations over unknown disease-specific prediction data by using the developed classifier.</p></div><div><h3>Results</h3><p>With an average accuracy of 87.33% and confidence level of 90.10% +/− 0.142, the protocol effectively extracted 2031 associated genes, of which 1162, 489 and 1439 belong to positive, negative and ambiguous classes respectively at the threshold of 0.9. In comparison between the established disease gene databases, our system identified 915 positive genes that had not been previously reported. One can use these positive genes for in-depth understanding and ambiguous genes for further exploration of their association with Alzheimer's disease.</p></div><div><h3>Conclusions</h3><p>The system's ability to generate accurate predictions demonstrates its robustness and provides valuable insights into the genetic factors of Alzheimer's disease. Consequently, this study contributes to existing knowledge and paves the way for future research in this field.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201309"},"PeriodicalIF":0.5,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analysis reveals an association of CAPN10 SNP 44 polymorphism with type 2 diabetes mellitus in Middle Eastern populations","authors":"Kali Charan Mishra ,&nbsp;Suraj Kumar ,&nbsp;Aman Kumar Jha ,&nbsp;Anupama ,&nbsp;Atanu Banerjee ,&nbsp;Shushovan Banik ,&nbsp;Parul Banerjee","doi":"10.1016/j.humgen.2024.201305","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201305","url":null,"abstract":"<div><p>The calpain-10 gene (CAPN10) was the first gene identified to be associated with Type 2 diabetes mellitus. Several polymorphic loci of the calpain-10 gene (CAPN10) have been implicated in the etiology of Type 2 diabetes mellitus. However, the results have been conflicting. Keeping this in view, the present study was aimed at doing a meta-analysis to dig out the association of CAPN SNP 44 (rs2975760) polymorphism with type 2 diabetes mellitus, given that the role of polymorphism at this particular locus is lesser studied than the rest and therefore shrouded in speculations.</p><p>Preferred Reporting Items for Systematic Reviews and Meta-analyses PRISMA and the published PROSPERO research protocol was followed for the present study. A total of thirteen studies were included for pooling of data. All statistical analyses were done on R studio (version 4.2.3). The meta-analysis has lead to the conclusion that the genotype ‘CC' has significantly low odds of occurrence in the type 2 diabetes mellitus patients in the Middle Eastern Populations. Therefore, we postulate that the minor allele ‘C' must be playing a protective role against type 2 diabetes mellitus. However, the question of how the ‘CC' genotype must be affecting the incidence of T2DM only the Middle Eastern populations remains to be answered.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201305"},"PeriodicalIF":0.5,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The molecular evidence behind the adjunct use of anticoagulants and chemotherapy in pancreatic cancer treatment: A new role for anticoagulants?","authors":"Ghena Lababidi ,&nbsp;Noura Wahoud ,&nbsp;Lina Ghandour ,&nbsp;Nour Moukalled ,&nbsp;Rami Mahfouz","doi":"10.1016/j.humgen.2024.201307","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201307","url":null,"abstract":"<div><p>Pancreatic cancers include highly aggressive forms of neoplasms, with limited treatment options and high mortality rates. Recent studies have highlighted various molecular pathways underlying the dynamic modification of the coagulation cascade by pancreatic cancer cells, promoting the development of thromboembolic events and possibly contributing to tumor progression. As such, the use of anticoagulants as adjuncts to chemotherapy in the treatment of pancreatic neoplasms has become a topic of interest. A literature review of over 115 articles was conducted. The primary objective was to highlight the molecular pathways implicated in both pancreatic cancer and the coagulation cascade, as well as the influence of anti-coagulants on cancer related thromboembolic events and their potential use as anti-metastatic medications. Available data suggests significant reduction in thromboembolic events following adjunct treatment with anticoagulants, though an impact on overall survival remains poorly characterized. Several anti-coagulants were found to have prominent anti-metastatic effects, and in animal models improved overall survival and decreased tumor growth margins. Gene pathways such as Protease-Activated Receptor-1 (PAR-1) and Kirsten rat sarcoma viral oncogene (KRAS) are also heavily upregulated in the context of pancreatic cancer and further modified by anti-coagulant use. Further studies are needed to characterize the risks and efficacy of this treatment option in humans.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201307"},"PeriodicalIF":0.5,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141541559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico identification of differentially expressed microRNAs in thyroid cancer","authors":"Hasan Onur Caglar ,&nbsp;Abdulmelik Aytatli ,&nbsp;Omer Faruk Karatas","doi":"10.1016/j.humgen.2024.201306","DOIUrl":"10.1016/j.humgen.2024.201306","url":null,"abstract":"<div><h3>Background</h3><p>Abnormal expression of microRNAs is one of the crucial features contributing to the thyroid cancer (TC) progression. However, a comprehensive identification of the dysregulated microRNA profile and the associated molecular pathways that underlie the TC pathogenesis has not been completely provided. In the current study, bioinformatic analysis tools and microarray datasets were used to evaluate the biological roles of differentially expressed microRNAs and their targets in TC.</p></div><div><h3>Methods</h3><p>GEO2R was used to identify differentially expressed microRNAs in TC samples. The mRNA targets of these microRNAs were predicted using different databases. DAVID and Reactome databases were used to perform gene ontology and pathway enrichment analyses of target genes. Then, the protein-protein interaction networks were constructed among them through the STRING database. MCODE was applied to screen hub genes. The prognostic values of hub genes were examined in TCGA THCA dataset using GEPIA2 platform. The relationship between hub genes and the ERBB2 protein was revealed using GeneMANIA.</p></div><div><h3>Results</h3><p>We found a significant decrease in five microRNAs and a significant increase in five others in TC samples. Target genes of upregulated and downregulated microRNAs in TC were associated with ERBB2 signaling and ion exchanger pathways, respectively. <em>CUX2</em> and <em>DCUN1D4</em>, the targets of upregulated microRNAs, were downregulated, whereas <em>AP1S1</em>, the target of downregulated microRNAs, were overexpressed in TCGA THCA samples. EZR and CUL5 were mediators for the interaction of ERBB2 with CUX2 or DCUN1D4, respectively.</p></div><div><h3>Conclusion</h3><p>We suggest that <em>CUX2</em>/<em>DCUN1D4</em> and <em>AP1S1</em> may act as tumor suppressor and oncogene in TC onset and progression, respectively.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201306"},"PeriodicalIF":0.7,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141409065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of interleukin-1 gene polymorphisms on the severity of COVID-19","authors":"Shrikant Verma ,&nbsp;Sushma Verma ,&nbsp;Sheeba Afreen ,&nbsp;Zeba Siddiqi ,&nbsp;Faizan Haider Khan ,&nbsp;Mohammad Abbas ,&nbsp;Farzana Mahdi","doi":"10.1016/j.humgen.2024.201303","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201303","url":null,"abstract":"<div><p>The severity of Coronavirus Disease 2019 (COVID-19) has been closely linked to an exacerbated proinflammatory response and cytokine storm. Interleukin-1 (IL-1), a pivotal proinflammatory cytokine, plays a crucial role in the development of acute respiratory distress syndrome (ARDS) and multiorgan dysfunction. Single nucleotide polymorphisms within the <em>IL-1</em> gene have been shown to modulate IL-1 cytokine levels. This study aimed to investigate the association of <em>IL-1</em> gene polymorphisms (<em>IL-1</em> + 3953C &gt; T, <em>IL-1β</em> -511 T &gt; C, and IL-1Ra) with the severity of COVID-19. Genotyping of <em>IL-1</em> gene polymorphisms (<em>IL-1</em> + 3953C &gt; T, <em>IL-1β</em> -511 T &gt; C) were performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), while <em>IL-1Ra</em> genotyping was done by Random Amplification of Polymorphic DNA (RAPD). PCR-RFLP data were validated through Sanger sequencing (SeqStudio Genetic Analyzer). Data analysis was carried out by SPSS-v21 and SHesis (online version). The frequency of the T allele of the <em>IL-1</em> + 3953C &gt; T polymorphism was found to be higher in mild cases as compared to severe cases, demonstrating a significant protective effect against COVID-19 severity (<em>P</em> = 0.001). However, no significant associations were observed for <em>IL-1β</em> -511 T &gt; C and <em>IL-1Ra</em> polymorphisms (<em>P</em> &gt; 0.05). In haplotype analysis (between <em>IL-1</em> + 3953C &gt; T, and <em>IL-1β</em> -511 T &gt; C gene polymorphisms), individual with CT haplotype showed a higher risk of severity (OR = 1.8, <em>P</em> = 0.001), while individuals with TT haplotype showed significant protection against severity (P = 0.001). Our findings suggest that the T allele of <em>IL-1β</em> + 3953C &gt; T polymorphism may confer protective effect against the severity of COVID-19.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201303"},"PeriodicalIF":0.7,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141325312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between IL6 rs1800795, IL10 rs1800871 and 1,800,872 polymorphisms with periodontitis","authors":"Israa Allawi Hussein Al-Hussein ,&nbsp;Fatemeh Keshavarzi ,&nbsp;Balkeas Abd Ali Abd Aun Jwad ,&nbsp;Mardin Maroofi Naghadehi ,&nbsp;Kawther Mohammed Ali Hasan","doi":"10.1016/j.humgen.2024.201302","DOIUrl":"10.1016/j.humgen.2024.201302","url":null,"abstract":"<div><h3>Background</h3><p>The components of oral microorganisms are important for stimulating the production of pro-inflammatory cytokines, making it essential to understand this relationship. The purpose of this research was to investigate the relationship between polymorphisms of Interleukin 10 (IL-10) and Interleukin 6(IL-6) and candidiasis-type tooth decay.</p></div><div><h3>Methods</h3><p>Two hundred and forty individuals, including120 patients and 120 controls provided saliva and blood samples in accordance with ethical standards. Saliva samples were cultured on SDA and PDA to detect fungi, which were then identified using confirmatory tests. Additionally, blood samples were assayed to detect IL6 rs1800795, IL10 rs1800871 and rs1800872 genotypes. The relationship between these polymorphisms and candidiasis-type tooth decay was then investigated using the SPSS statistical program.</p></div><div><h3>Results</h3><p>Six types of dental caries were identified: <em>Candida albicans</em> (<em>C.albicans</em>) (75.25%), <em>C. parapsilosis</em>(20.58%), <em>C. glabrata</em> (4.54%), <em>C. krusei</em> (9.8%), <em>Rhodotorula</em> spp. (4.54%) and <em>Penicillium</em> spp. (5.44%). The allelic distribution of IL6 (−147 G/C) SNP (rs1800795) showed no statistically significant difference(<em>P</em> values for G/C and CC genotypes, respectively, <em>p</em> = 0.57 and <em>p</em> = 0.42). In addition, the presence The C allele increases the probability of contracting the disease by 1.3 times compared to the healthy group. But these effects are not statistically significant (<em>P</em> = 0.67). The rs1800871 T/C, it has no effect on the occurrence of the disease (OR = 0.37, 95% CI = 0.8–1.2). However, the C/C genotype increases the probability of tooth decay by 6 times (OR = 6, 95%, CI = 1.8–19.0, <em>p</em> = 0.01) and the C allele increases the likelihood of developing dental caries by 3.5 times (OR = 3.5, 95%, CI = 1.6–7.4) compared to the healthy group (<em>p</em> = 0.017).Also, the rs1800872 polymorphism, the A/C genotype does not have an effect on the incidence of the disease (OR = 0.44, 95% CI =0.1–1.97, <em>p</em> &gt; 0.2) while the C/C genotype is more likely to suffer from caries. Caries increases 2.7 times compared to the AA genotype (OR = 2.7, 95% CI = 0.8–8.5, <em>p</em> = 0.09), and the C allele compared to the A allele increases the probability of periodontitis up to 2.4 times (OR = 2.4, 95% CI = 0.9–5.9, <em>p</em> = 0.05).</p></div><div><h3>Conclusion</h3><p>There may be a correlation between IL6 rs1800795, IL10 rs1800871 and 1,800,872 polymorphisms with periodontitis. However, further investigation with a larger sample size is needed to explore this relationship.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201302"},"PeriodicalIF":0.5,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141411812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diversity of SARS-CoV-2 genome among various strains identified in Lucknow, Uttar Pradesh","authors":"Biswajit Sahoo ,&nbsp;Pramod Kumar Maurya ,&nbsp;Ratnesh Kumar Tripathi ,&nbsp;Jyotsna Agarwal ,&nbsp;Swasti Tiwari","doi":"10.1016/j.humgen.2024.201304","DOIUrl":"10.1016/j.humgen.2024.201304","url":null,"abstract":"<div><p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a significant challenge worldwide. Rapid genome sequencing of SARS-CoV-2 is going on across the globe to detect mutations and genomic modifications in SARS-CoV-2. In this study, we have sequenced 23 SARS-CoV-2-positive samples collected during the first pandemic from the state of Uttar Pradesh, India. We observed a range of already reported mutations (2−22), including D614G, L452R, Q613H, Q677H, and T1027I in the S gene; S194L in the N gene; and Q57H, L106F, and T175I in the ORF3. A few unreported mutations, such as P309S in the ORF1ab gene, T379I in the N gene, and L52F and V77I in the ORF3a gene, were also detected. Phylogenetic genome analysis showed similarity with other SARS-CoV-2 viruses reported from Uttar Pradesh. The observed mutations may be associated with SARS-CoV-2 virus pathogenicity or disease severity.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201304"},"PeriodicalIF":0.5,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141414944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico analysis on frequency and distribution of microsatellites in genes associated with spinal cord astrocytoma","authors":"Tahir Shehzad Ahmed ,&nbsp;Kashif Mahmood ,&nbsp;Muhammad Sabtain Nazish Ali Khattak ,&nbsp;Azizullah Noor ,&nbsp;Huiying Liang ,&nbsp;Siddiq Ur Rahman","doi":"10.1016/j.humgen.2024.201301","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201301","url":null,"abstract":"<div><p>Microsatellites, also called short tandem repeats (STRs) or simple sequence repeats (SSRs) are short DNA sequence segments consisting of tandemly repeated motifs. SSRs are regarded as one of the most effective tools for genetic research. In this study, we conducted an in silico analysis to investigate the presence, distribution, and characteristics of SSRs within the genes associated with spinal cord astrocytoma. The aim of this study was to identify SSRs in coding and non-coding regions, analyze their correlation with gene parameters, and determine the GC content in the gene sequences. The results revealed that the widespread presence of SSRs within the genes is associated with spinal cord astrocytoma (SCA). The distribution of SSR motifs varied among the analyzed genes, and certain motifs were common across multiple genes. Additionally, we observed a strong positive correlation between the total number of SSRs and gene size, indicating that larger genes tend to have a higher number of microsatellites. Furthermore, we identified SSRs in both coding and non-coding regions of the genes. The incidence of SSRs and cSSRs differed among genes, suggesting potential functional implications for gene expression and regulation. Our study provides valuable insights into the genetic diversity within the astrocytoma genes and highlights the potential significance of SSRs in gene regulation. In conclusion, this study contributes to a better understanding of the role of microsatellites within the genes associated with spinal cord astrocytoma. The observed patterns of SSR distribution and characteristics suggest their potential functional relevance in the development and progression of astrocytoma.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201301"},"PeriodicalIF":0.7,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141291694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of cellular heterogeneity in recurrent pediatric glioblastoma: Machine learning-enhanced single-cell RNA-Seq unveils regulatory signatures","authors":"Shikha Suman ,&nbsp;Anurag Kulshrestha","doi":"10.1016/j.humgen.2024.201300","DOIUrl":"https://doi.org/10.1016/j.humgen.2024.201300","url":null,"abstract":"<div><p>The most common oncologic cause of mortality in children is pediatric glioblastoma, an extremely dangerous brain tumor. The tumor progress is almost inevitable and recurs after first-line standard care. Because surgical resection is often more effective when tumors are localized and smaller, early identification and action may be essential to assure favourable outcomes for the recurring disease. This study aims to employ single-cell RNA-Sequencing data (scRNA-Seq data) for clustering and explainable Artificial intelligence framework to find gene biomarkers and signature cell types for the diagnosis and prognosis of reoccurring pediatric glioblastoma. Distinct cell types and statistically significant DEGs were found using scRNA-Seq data retrieved from the Gene Expression Omnibus database. Random forest (RF) and extreme gradient boosting (XGBoost) machine learning (ML) classifiers were constructed to select genes significantly contributing to the disease using Shapley (SHAP) values, an explainable artificial intelligence (EAI) framework. Potential biomarkers were chosen based on the shared genes among statistically discovered DEGs and SHAP-based relevance. B cells, macrophages, CD8+ T cells, T cells, and NK cells were identified as distinct cell types, which played an essential role in disease recurrence. Also, five significant genes, namely HMGB2, H2AFZ, HIST1H4C, KIAA0101, and DUT, were screened and in silico validated through survival analysis and feature plot, hence, proposed as biomarkers for recurring pediatric glioblastoma. Utilising these five genes may improve disease prognosis and provide a crucial understanding of the molecular causes of recurrent pediatric glioblastoma.</p></div>","PeriodicalId":29686,"journal":{"name":"Human Gene","volume":"41 ","pages":"Article 201300"},"PeriodicalIF":0.7,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141243825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}