• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用整合基因共表达网络分析确定家族性高胆固醇血症中的显著基因和功能富集通路。

Identifying significant genes and functionally enriched pathways in familial hypercholesterolemia using integrated gene co-expression network analysis.

作者信息

Awan Zuhier, Alrayes Nuha, Khan Zeenath, Almansouri Majid, Ibrahim Hussain Bima Abdulhadi, Almukadi Haifa, Ibrahim Kutbi Hussam, Jayasheela Shetty Preetha, Ahmad Shaik Noor, Banaganapalli Babajan

机构信息

Department of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.

Department of Genetics, Al Borg Diagnostics, Jeddah, Saudi Arabia.

出版信息

Saudi J Biol Sci. 2022 May;29(5):3287-3299. doi: 10.1016/j.sjbs.2022.02.002. Epub 2022 Feb 9.

DOI:10.1016/j.sjbs.2022.02.002
PMID:35844366
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9280244/
Abstract

Familial hypercholesterolemia (FH) is a monogenic lipid disorder which promotes atherosclerosis and cardiovascular diseases. Owing to the lack of sufficient published information, this study aims to identify the potential genetic biomarkers for FH by studying the global gene expression profile of blood cells. The microarray expression data of FH patients and controls was analyzed by different computational biology methods like differential expression analysis, protein network mapping, hub gene identification, functional enrichment of biological pathways, and immune cell restriction analysis. Our results showed the dysregulated expression of 115 genes connected to lipid homeostasis, immune responses, cell adhesion molecules, canonical Wnt signaling, mucin type O-glycan biosynthesis pathways in FH patients. The findings from expanded protein interaction network construction with known FH genes and subsequent Gene Ontology (GO) annotations have also supported the above findings, in addition to identifying the involvement of dysregulated thyroid hormone and ErbB signaling pathways in FH patients. The genes like were found to be enriched under all GO annotation categories. The subsequent phenotype ontology results have revealed , as key hub genes contributing to the inflammation underlying cardiovascular and immune response related phenotypes. Immune cell restriction findings show that above three genes are highly expressed by T-follicular helper CD4 T cells, naïve B cells, and monocytes, respectively. These findings not only provide a theoretical basis to understand the role of immune dysregulations underlying the atherosclerosis among FH patients but may also pave the way to develop genomic medicine for cardiovascular diseases.

摘要

家族性高胆固醇血症(FH)是一种单基因脂质紊乱疾病,可促进动脉粥样硬化和心血管疾病的发生。由于缺乏足够的已发表信息,本研究旨在通过研究血细胞的全基因表达谱来确定FH的潜在遗传生物标志物。采用差异表达分析、蛋白质网络映射、枢纽基因鉴定、生物通路功能富集和免疫细胞限制分析等不同的计算生物学方法,对FH患者和对照组的微阵列表达数据进行了分析。我们的结果显示,FH患者中115个与脂质稳态、免疫反应、细胞粘附分子、经典Wnt信号传导、粘蛋白型O-聚糖生物合成途径相关的基因表达失调。除了确定FH患者中甲状腺激素和ErbB信号通路失调的参与外,通过与已知FH基因构建扩展的蛋白质相互作用网络以及随后的基因本体(GO)注释得出的结果也支持了上述发现。发现 等基因在所有GO注释类别下均富集。随后的表型本体结果显示, 和 是导致心血管和免疫反应相关表型炎症的关键枢纽基因。免疫细胞限制分析结果表明,上述三个基因分别在T滤泡辅助性CD4 T细胞、初始B细胞和单核细胞中高表达。这些发现不仅为理解FH患者动脉粥样硬化背后免疫失调的作用提供了理论基础,也可能为开发心血管疾病的基因组医学铺平道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/d7e77283ecde/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/c87e70a922c8/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/806a95323b7c/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/c5a384524614/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/5ae4dc2f8972/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/bcf993ccf6c0/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/d7e77283ecde/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/c87e70a922c8/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/806a95323b7c/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/c5a384524614/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/5ae4dc2f8972/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/bcf993ccf6c0/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/732c/9280244/d7e77283ecde/gr6.jpg

相似文献

1
Identifying significant genes and functionally enriched pathways in familial hypercholesterolemia using integrated gene co-expression network analysis.利用整合基因共表达网络分析确定家族性高胆固醇血症中的显著基因和功能富集通路。
Saudi J Biol Sci. 2022 May;29(5):3287-3299. doi: 10.1016/j.sjbs.2022.02.002. Epub 2022 Feb 9.
2
Analysis of Differentially Expressed Genes and Molecular Pathways in Familial Hypercholesterolemia Involved in Atherosclerosis: A Systematic and Bioinformatics Approach.家族性高胆固醇血症中参与动脉粥样硬化的差异表达基因和分子通路分析:一种系统和生物信息学方法
Front Genet. 2020 Jul 15;11:734. doi: 10.3389/fgene.2020.00734. eCollection 2020.
3
Investigation of the underlying genes and mechanism of familial hypercholesterolemia through bioinformatics analysis.通过生物信息学分析研究家族性高胆固醇血症的潜在基因和机制。
BMC Cardiovasc Disord. 2020 Sep 16;20(1):419. doi: 10.1186/s12872-020-01701-z.
4
Bioinformatics analyses of gene expression profile identify key genes and functional pathways involved in cutaneous lupus erythematosus.基于基因表达谱的生物信息学分析鉴定出参与皮肤红斑狼疮的关键基因和功能途径。
Clin Rheumatol. 2022 Feb;41(2):437-452. doi: 10.1007/s10067-021-05913-2. Epub 2021 Sep 23.
5
Prediction of genetic risk factors of atherosclerosis using various bioinformatic tools.使用各种生物信息学工具预测动脉粥样硬化的遗传风险因素。
Genet Mol Res. 2016 Apr 4;15(2):gmr7347. doi: 10.4238/gmr.15027347.
6
An integrative bioinformatics analysis of microarray data for identifying hub genes as diagnostic biomarkers of preeclampsia.基于基因芯片数据的综合生物信息学分析,以识别先兆子痫的诊断生物标志物的枢纽基因。
Biosci Rep. 2019 Sep 3;39(9). doi: 10.1042/BSR20190187. Print 2019 Sep 30.
7
The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.通过高通量数据的生物信息学分析鉴定肝细胞癌中的关键基因和信号通路。
Med Oncol. 2017 Jun;34(6):101. doi: 10.1007/s12032-017-0963-9. Epub 2017 Apr 21.
8
[Gene expression analysis of familial hypercholesterolemia].[家族性高胆固醇血症的基因表达分析]
Mol Biol (Mosk). 2014 Jan-Feb;48(1):185-92.
9
Identification of differentially expressed genes and signaling pathways in papillary thyroid cancer: a study based on integrated microarray and bioinformatics analysis.甲状腺乳头状癌中差异表达基因及信号通路的鉴定:一项基于整合微阵列和生物信息学分析的研究
Gland Surg. 2021 Feb;10(2):629-644. doi: 10.21037/gs-20-673.
10
Weighted gene co-expression network analysis revealed key biomarkers associated with the diagnosis of hypertrophic cardiomyopathy.加权基因共表达网络分析揭示了与肥厚型心肌病诊断相关的关键生物标志物。
Hereditas. 2020 Oct 24;157(1):42. doi: 10.1186/s41065-020-00155-9.

引用本文的文献

1
A computational framework for identifying cytoskeletal genes associated with age-related diseases.一种用于识别与年龄相关疾病相关的细胞骨架基因的计算框架。
Sci Rep. 2025 Apr 26;15(1):14590. doi: 10.1038/s41598-025-97363-y.
2
Artificial Intelligence in Cardiology and Atherosclerosis in the Context of Precision Medicine: A Scoping Review.精准医学背景下心脏病学与动脉粥样硬化领域的人工智能:一项范围综述
Appl Bionics Biomech. 2024 Apr 30;2024:2991243. doi: 10.1155/2024/2991243. eCollection 2024.
3
Identification of Plasma Exosomes hsa_circ_0001360 and hsa_circ_0000038 as Key Biomarkers of Coronary Heart Disease.

本文引用的文献

1
[Analysis of the Differential Expression of circRNA in Acute Myeloid Leukemia by GEO Database].利用GEO数据库分析急性髓系白血病中circRNA的差异表达
Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2021 Dec;29(6):1719-1726. doi: 10.19746/j.cnki.issn.1009-2137.2021.06.005.
2
Saudi Familial Hypercholesterolemia Patients With Rare Stop Gain Variant Showed Variable Clinical Phenotype and Resistance to Multiple Drug Regimen.患有罕见终止密码子获得性变异的沙特家族性高胆固醇血症患者表现出可变的临床表型和对多种药物治疗方案的耐药性。
Front Med (Lausanne). 2021 Jun 25;8:694668. doi: 10.3389/fmed.2021.694668. eCollection 2021.
3
Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection.
鉴定血浆外泌体hsa_circ_0001360和hsa_circ_0000038作为冠心病的关键生物标志物
Cardiol Res Pract. 2024 Mar 26;2024:5557143. doi: 10.1155/2024/5557143. eCollection 2024.
4
Network pharmacology based anti-diabetic attributes of bioactive compounds from L through computational approach.基于网络药理学的从L中提取的生物活性化合物的抗糖尿病特性的计算方法研究。
Saudi J Biol Sci. 2023 Sep;30(9):103766. doi: 10.1016/j.sjbs.2023.103766. Epub 2023 Aug 6.
5
Rare variant burden analysis from exomes of three consanguineous families reveals and as potential key proteins in inflammatory bowel disease pathogenesis.对三个近亲家庭的外显子组进行罕见变异负担分析,发现[具体蛋白质名称1]和[具体蛋白质名称2]是炎症性肠病发病机制中的潜在关键蛋白。
Front Med (Lausanne). 2023 May 5;10:1164305. doi: 10.3389/fmed.2023.1164305. eCollection 2023.
6
Exome Sequencing Identifies the Extremely Rare and Variants in Early Onset Inflammatory Bowel Disease Patients.外显子组测序鉴定早发性炎症性肠病患者中的极其罕见变异。
Front Pediatr. 2022 May 26;10:895074. doi: 10.3389/fped.2022.895074. eCollection 2022.
肺转录组学数据的多层次系统生物学分析鉴定了 SARS-CoV-2 感染的关键 miRNAs 和潜在的 miRNA 靶基因。
Comput Biol Med. 2021 Aug;135:104570. doi: 10.1016/j.compbiomed.2021.104570. Epub 2021 Jun 12.
4
Familial Hypercholesterolemia in the Arabian Gulf Region: Clinical results of the Gulf FH Registry.阿拉伯海湾地区的家族性高胆固醇血症:海湾 FH 注册研究的临床结果。
PLoS One. 2021 Jun 4;16(6):e0251560. doi: 10.1371/journal.pone.0251560. eCollection 2021.
5
Gene Set Knowledge Discovery with Enrichr.基因集知识发现与 Enrichr
Curr Protoc. 2021 Mar;1(3):e90. doi: 10.1002/cpz1.90.
6
Role of PI3K in the Progression and Regression of Atherosclerosis.PI3K在动脉粥样硬化进展与消退中的作用
Front Pharmacol. 2021 Mar 9;12:632378. doi: 10.3389/fphar.2021.632378. eCollection 2021.
7
Appyters: Turning Jupyter Notebooks into data-driven web apps.Appyters:将Jupyter笔记本转变为数据驱动的网络应用程序。
Patterns (N Y). 2021 Mar 4;2(3):100213. doi: 10.1016/j.patter.2021.100213. eCollection 2021 Mar 12.
8
Molecular differential analysis of uterine leiomyomas and leiomyosarcomas through weighted gene network and pathway tracing approaches.通过加权基因网络和通路追踪方法对子宫平滑肌瘤和平滑肌肉瘤进行分子差异分析。
Syst Biol Reprod Med. 2021 Jun;67(3):209-220. doi: 10.1080/19396368.2021.1876179. Epub 2021 Mar 8.
9
CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer.CIBERSORT 分析 TCGA 和 METABRIC 数据,确定三阴性乳腺癌中具有更好预后的亚组。
Sci Rep. 2021 Feb 25;11(1):4691. doi: 10.1038/s41598-021-83913-7.
10
Exploring celiac disease candidate pathways by global gene expression profiling and gene network cluster analysis.通过全基因表达谱分析和基因网络聚类分析探索乳糜泻候选途径。
Sci Rep. 2020 Oct 1;10(1):16290. doi: 10.1038/s41598-020-73288-6.