利用机器学习方法识别儿童、青少年和成人鼻咽部和外周血中与 COVID-19 相关的基因特征。

IF 3.8 4区 医学 Q2 GENETICS & HEREDITY Current gene therapy Pub Date : 2024-09-27 DOI:10.2174/0115665232316769240912061652
YuSheng Bao, JingXin Ren, Lei Chen, Wei Guo, KaiYan Feng, Tao Huang, Yu-Dong Cai
{"title":"利用机器学习方法识别儿童、青少年和成人鼻咽部和外周血中与 COVID-19 相关的基因特征。","authors":"YuSheng Bao, JingXin Ren, Lei Chen, Wei Guo, KaiYan Feng, Tao Huang, Yu-Dong Cai","doi":"10.2174/0115665232316769240912061652","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Significant variations in immune profiles across different age groups manifest distinct clinical symptoms and prognoses in Coronavirus Disease 2019 (COVID-19) patients. Predominantly, severe COVID-19 cases that require hospitalization occur in the elderly, with the risk of severe illness escalating with age among young adults, children, and adolescents.</p><p><strong>Objective: </strong>This study aimed to delineate the unique immune characteristics of COVID-19 across various age groups and evaluate the feasibility of detecting COVID-19-induced immune alterations through peripheral blood analysis.</p><p><strong>Methods: </strong>By employing a machine learning approach, we analyzed gene expression data from nasopharyngeal and peripheral blood samples of COVID-19 patients across different age brackets. Nasopharyngeal data reflected the immune response to COVID-19 in the upper respiratory tract, while peripheral blood samples provided insights into the overall immune system status. Both datasets encompassed COVID-19 patients and healthy controls, with patients divided into children, adolescents, and adult age groups. The analysis included the expression levels of 62,703 genes per patient. Then, 9 feature-sequencing methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, random forest, ridge regression, adaptive boosting, categorical boosting, extremely randomized trees, and extreme gradient boosting) were employed to evaluate the association of the genes with COVID-19. Key genes were then utilized to develop efficient classification models.</p><p><strong>Results: </strong>The findings identified specific markers: insulin-like growth factor binding protein 3 (downregulated in the peripheral blood of COVID-19 patients), interferon alpha-inducible protein 27 (upregulated), and SERPING1 (upregulated in nasopharyngeal tissues). In addition, fibulin-2 was downregulated in adolescent patients, but upregulated in the other groups, while epoxide hydrolase 3 was upregulated in healthy controls, but downregulated in children and adolescents.</p><p><strong>Conclusion: </strong>This study offers valuable insights into the local and systemic immune responses of COVID-19 patients across age groups, aiding in identifying potential therapeutic targets and formulating personalized treatment strategies.</p>","PeriodicalId":10798,"journal":{"name":"Current gene therapy","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Gene Signatures Associated with COVID-19 across Children, Adolescents, and Adults in the Nasopharynx and Peripheral Blood by Using a Machine Learning Approach.\",\"authors\":\"YuSheng Bao, JingXin Ren, Lei Chen, Wei Guo, KaiYan Feng, Tao Huang, Yu-Dong Cai\",\"doi\":\"10.2174/0115665232316769240912061652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Significant variations in immune profiles across different age groups manifest distinct clinical symptoms and prognoses in Coronavirus Disease 2019 (COVID-19) patients. Predominantly, severe COVID-19 cases that require hospitalization occur in the elderly, with the risk of severe illness escalating with age among young adults, children, and adolescents.</p><p><strong>Objective: </strong>This study aimed to delineate the unique immune characteristics of COVID-19 across various age groups and evaluate the feasibility of detecting COVID-19-induced immune alterations through peripheral blood analysis.</p><p><strong>Methods: </strong>By employing a machine learning approach, we analyzed gene expression data from nasopharyngeal and peripheral blood samples of COVID-19 patients across different age brackets. Nasopharyngeal data reflected the immune response to COVID-19 in the upper respiratory tract, while peripheral blood samples provided insights into the overall immune system status. Both datasets encompassed COVID-19 patients and healthy controls, with patients divided into children, adolescents, and adult age groups. The analysis included the expression levels of 62,703 genes per patient. Then, 9 feature-sequencing methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, random forest, ridge regression, adaptive boosting, categorical boosting, extremely randomized trees, and extreme gradient boosting) were employed to evaluate the association of the genes with COVID-19. Key genes were then utilized to develop efficient classification models.</p><p><strong>Results: </strong>The findings identified specific markers: insulin-like growth factor binding protein 3 (downregulated in the peripheral blood of COVID-19 patients), interferon alpha-inducible protein 27 (upregulated), and SERPING1 (upregulated in nasopharyngeal tissues). In addition, fibulin-2 was downregulated in adolescent patients, but upregulated in the other groups, while epoxide hydrolase 3 was upregulated in healthy controls, but downregulated in children and adolescents.</p><p><strong>Conclusion: </strong>This study offers valuable insights into the local and systemic immune responses of COVID-19 patients across age groups, aiding in identifying potential therapeutic targets and formulating personalized treatment strategies.</p>\",\"PeriodicalId\":10798,\"journal\":{\"name\":\"Current gene therapy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current gene therapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/0115665232316769240912061652\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current gene therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115665232316769240912061652","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0

摘要

背景:冠状病毒病 2019(COVID-19)患者的临床症状和预后在不同年龄段的免疫特征方面存在显著差异。需要住院治疗的 COVID-19 重症病例主要发生在老年人身上,而在青壮年、儿童和青少年中,重症风险随着年龄的增长而上升:本研究旨在描述不同年龄组 COVID-19 的独特免疫特征,并评估通过外周血分析检测 COVID-19 引起的免疫改变的可行性:通过采用机器学习方法,我们分析了不同年龄段COVID-19患者鼻咽和外周血样本的基因表达数据。鼻咽部数据反映了上呼吸道对 COVID-19 的免疫反应,而外周血样本则提供了对整体免疫系统状态的洞察。这两个数据集包括 COVID-19 患者和健康对照组,患者分为儿童、青少年和成人三个年龄组。分析包括每位患者 62703 个基因的表达水平。然后,采用 9 种特征测序方法(最小绝对收缩和选择算子、轻梯度提升机、蒙特卡洛特征选择、随机森林、脊回归、自适应提升、分类提升、极端随机树和极端梯度提升)来评估基因与 COVID-19 的关联。然后利用关键基因开发出高效的分类模型:结果:研究结果确定了特定的标记:胰岛素样生长因子结合蛋白 3(在 COVID-19 患者外周血中下调)、干扰素α诱导蛋白 27(上调)和 SERPING1(在鼻咽组织中上调)。此外,青少年患者的纤维素-2 下调,而其他组别则上调;健康对照组的环氧化物水解酶 3 上调,而儿童和青少年则下调:本研究为了解不同年龄组 COVID-19 患者的局部和全身免疫反应提供了宝贵的信息,有助于确定潜在的治疗靶点和制定个性化的治疗策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Identification of Gene Signatures Associated with COVID-19 across Children, Adolescents, and Adults in the Nasopharynx and Peripheral Blood by Using a Machine Learning Approach.

Background: Significant variations in immune profiles across different age groups manifest distinct clinical symptoms and prognoses in Coronavirus Disease 2019 (COVID-19) patients. Predominantly, severe COVID-19 cases that require hospitalization occur in the elderly, with the risk of severe illness escalating with age among young adults, children, and adolescents.

Objective: This study aimed to delineate the unique immune characteristics of COVID-19 across various age groups and evaluate the feasibility of detecting COVID-19-induced immune alterations through peripheral blood analysis.

Methods: By employing a machine learning approach, we analyzed gene expression data from nasopharyngeal and peripheral blood samples of COVID-19 patients across different age brackets. Nasopharyngeal data reflected the immune response to COVID-19 in the upper respiratory tract, while peripheral blood samples provided insights into the overall immune system status. Both datasets encompassed COVID-19 patients and healthy controls, with patients divided into children, adolescents, and adult age groups. The analysis included the expression levels of 62,703 genes per patient. Then, 9 feature-sequencing methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, random forest, ridge regression, adaptive boosting, categorical boosting, extremely randomized trees, and extreme gradient boosting) were employed to evaluate the association of the genes with COVID-19. Key genes were then utilized to develop efficient classification models.

Results: The findings identified specific markers: insulin-like growth factor binding protein 3 (downregulated in the peripheral blood of COVID-19 patients), interferon alpha-inducible protein 27 (upregulated), and SERPING1 (upregulated in nasopharyngeal tissues). In addition, fibulin-2 was downregulated in adolescent patients, but upregulated in the other groups, while epoxide hydrolase 3 was upregulated in healthy controls, but downregulated in children and adolescents.

Conclusion: This study offers valuable insights into the local and systemic immune responses of COVID-19 patients across age groups, aiding in identifying potential therapeutic targets and formulating personalized treatment strategies.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Current gene therapy
Current gene therapy 医学-遗传学
CiteScore
6.70
自引率
2.80%
发文量
46
期刊介绍: Current Gene Therapy is a bi-monthly peer-reviewed journal aimed at academic and industrial scientists with an interest in major topics concerning basic research and clinical applications of gene and cell therapy of diseases. Cell therapy manuscripts can also include application in diseases when cells have been genetically modified. Current Gene Therapy publishes full-length/mini reviews and original research on the latest developments in gene transfer and gene expression analysis, vector development, cellular genetic engineering, animal models and human clinical applications of gene and cell therapy for the treatment of diseases. Current Gene Therapy publishes reviews and original research containing experimental data on gene and cell therapy. The journal also includes manuscripts on technological advances, ethical and regulatory considerations of gene and cell therapy. Reviews should provide the reader with a comprehensive assessment of any area of experimental biology applied to molecular medicine that is not only of significance within a particular field of gene therapy and cell therapy but also of interest to investigators in other fields. Authors are encouraged to provide their own assessment and vision for future advances. Reviews are also welcome on late breaking discoveries on which substantial literature has not yet been amassed. Such reviews provide a forum for sharply focused topics of recent experimental investigations in gene therapy primarily to make these results accessible to both clinical and basic researchers. Manuscripts containing experimental data should be original data, not previously published.
期刊最新文献
Immune Modulation Strategies in Gene Therapy: Overcoming Immune Barriers and Enhancing Efficacy. Identification of Gene Signatures Associated with COVID-19 across Children, Adolescents, and Adults in the Nasopharynx and Peripheral Blood by Using a Machine Learning Approach. Pan-Cancer Single-Cell Analysis Revealing the Heterogeneity of Cancer-Associated Fibroblasts in Skin Tumors. Target and Gene-Based Therapeutic Strategies against Pancreatic Cancer: Current and Future Prospects. Characteristics of Oxidative Phosphorylation-Related Subtypes and Construction of a Prognostic Signature in Ovarian Cancer
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1