Article(id=1198602002080035802, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198601997155922872, articleNumber=null, orderNo=null, doi=10.11855/j.issn.0577-7402.1011.2023.0912, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1651248000000, receivedDateStr=2022-04-30, revisedDate=null, revisedDateStr=null, acceptedDate=1657814400000, acceptedDateStr=2022-07-15, onlineDate=1763698586243, onlineDateStr=2025-11-21, pubDate=1719504000000, pubDateStr=2024-06-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763698586243, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763698586243, creator=13701087609, updateTime=1763698586243, updator=13701087609, issue=Issue{id=1198601997155922872, tenantId=1146029695717560320, journalId=1189873630562394117, year='2024', volume='49', issue='6', pageStart='611', pageEnd='732', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1763698585070, creator=13701087609, updateTime=1763698770557, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1198602775211901122, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198601997155922872, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1198602775211901123, tenantId=1146029695717560320, journalId=1189873630562394117, issueId=1198601997155922872, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=701, endPage=710, ext={EN=ArticleExt(id=1198602002818233324, articleId=1198602002080035802, tenantId=1146029695717560320, journalId=1189873630562394117, language=EN, title=Effect of IGFBP6 in unstable carotid atherosclerotic plaque: bioinformatics analysis and experimental validation, columnId=1190310110212751762, journalTitle=Medical Journal of Chinese People’s Liberation Army, columnName=Basic Research, runingTitle=null, highlight=null, articleAbstract=

Objective To investigate the differentially expressed genes (DEGs) and their molecular interactions in unstable carotid atherosclerotic plaques. Methods Gene expression datasets related to carotid atherosclerotic plaques (GSE41571, GSE118481, and E-MTAB-2055) were downloaded from Gene Expression Omnibus (GEO) and European Bioinformatics Institute (EBI) ArrayExpress databases. The co-regulated DEGs in at least two datasets of unstable carotid plaques were merged and analyzed using Gene Ontology Biological Process (GO-BP), Kyoto Encyclopedia of Genes and Genomes (KEGG), Protein-Protein Interaction (PPI) Networks and subnetwork analysis, relationships between miRNAs/transcription factors and target genes, and drug-gene interaction database. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) were used to detect the expression levels of some DEGs in carotid plaques and plasma from 58 patients with carotid atherosclerosis. Results GO enrichment analysis showed that DEGs in unstable carotid atherosclerotic plaques were mainly enriched in genes related to inflammatory response and extracellular matrix structure genes. KEGG enrichment analysis indicated that upregulated DEGs in unstable carotid plaques were enriched in extracellular matrix receptor (ECM-receptor) interaction, PI3K-Akt, Hippo and transforming growth factor-β (TGF-β) signaling pathways, while downregulated DEGs were primarily enriched in lysosomes, phagosomes, and chemokines processes. PPI network analysis suggested that COL1A2, COL4A2, insulin-like growth factor binding protein 6 (IGFBP6), COL4A5, C1QA, CXCL10, CXCL2, CXCR4, and CSF1R may play important roles in PPI networks. Prediction of drug-gene interactions revealed that CSF1R had the most drug interaction, CXCL2 was most antagonized by drugs, and IGFBP6 was most activated by drugs. qRT-PCR showed that the expression level of IGFBP6 in unstable carotid plaques group was significantly lower than that in stable carotid plaques group (P<0.001). ELISA results showed that plasma concentration of IGFBP6 in unstable carotid plaques group was significantly lower than that in stable carotid plaques group (P<0.0001). Receiver operating characteristic (ROC) suggested that the area under the curve (AUC) for plasma IGFBP6 levels to identify unstable plaques was 0.894 (95%CI 0.810-0.977), with a cutoff value of 142.08 ng/ml. Conclusion IGFBP6 may become an important biomarker for predicting unstable carotid atherosclerotic plaques.

, correspAuthors=Jin-Xia Fu, authorNote=null, correspAuthorsNote=
E-mail:
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目的 探讨不稳定颈动脉粥样硬化斑块的差异表达基因(DEGs)及其分子相互作用。方法 从基因表达数据库(GEO)和欧洲生物信息学研究所数据库下载颈动脉斑块患者的基因表达数据集GSE41571、GSE118481和E-MTAB-2055。采用基因本体生物学过程(GO-BP)富集分析、京都基因与基因组百科全书(KEGG)富集分析、蛋白-蛋白相互作用(PPI)网络、miRNAs/转录因子与靶基因的相互关系及药物-基因相互作用等方法,分析至少两个数据集中不稳定颈动脉斑块的共调控DEGs。采用定量实时PCR(qRT-PCR)和酶联免疫吸附试验(ELISA)检测颈动脉粥样硬化斑块患者58例的颈动脉斑块和血浆中部分DEGs的表达水平。结果 GO富集分析显示,不稳定颈动脉斑块的DEGs主要富集在与炎症反应相关的基因和细胞外基质结构基因; KEGG富集分析显示,不稳定颈动脉斑块中上调的DEGs富集于细胞外基质受体相互作用、PI3K-Akt、Hippo信号通路及转化生长因子-β(TGF-β)信号通路,下调的DEGs主要富集于溶酶体、吞噬体及趋化因子过程。PPI网络分析结果显示,COL1A2、COL4A2、胰岛素样生长因子结合蛋白6(IGFBP6)、COL4A5、C1QA、CXCL10、CXCL2、CXCR4和CSF1R等可能在PPI网络中起重要作用。药物-基因相互作用的预测显示,CSF1R的药物相互作用最多,CXCL2受药物拮抗程度最高,IGFBP6受药物激活程度最高。qRT-PCR检测结果显示,与稳定斑块组比较,不稳定斑块组IGFBP6表达水平明显降低(P<0.001)。ELISA法检测结果显示,不稳定斑块组血浆IGFBP6浓度明显低于稳定斑块组(P<0.0001)。受试者工作特征曲线分析结果显示,采用血浆IGFBP6水平鉴别不稳定斑块的曲线下面积为0.894(95%CI 0.810~0.977),截断值为142.08 ng/ml。结论 IGFBP6可能成为预测不稳定颈动脉斑块的重要生物标志物。

, correspAuthors=付金霞, authorNote=null, correspAuthorsNote=
付金霞,E-mail:
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李玉岩,主治医师,主要从事神经病学方面的研究

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李玉岩,主治医师,主要从事神经病学方面的研究

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李玉岩,主治医师,主要从事神经病学方面的研究

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DEGs. 差异表达基因;A. 与GSE41571数据集中稳定斑块比较,在不稳定斑块中鉴定出DEGs 1519个,包括上调662个、下调857个;B. 在GSE118481数据集中筛选出DEGs 730个,其中上调458个、下调272个;C. 在E-MTAB-2055数据集中鉴定出DEGs 1130个,其中上调601个,下调529个;D. 合并3个数据集后,确定14个上调的DEGs;E. 合并3个数据集后,确定2个下调的DEGs

, figureFileSmall=snrl2hXSvWnZD2K2SaWUlw==, figureFileBig=U23D7hrmYoZyPK4fDRAgaw==, tableContent=null), ArticleFig(id=1198602013413044566, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Fig.2, caption=Functional enrichment analysis results of differentially expressed genes in carotid atherosclerotic plaque, figureFileSmall=fKgy4OStD3hoCz+3mRrJIw==, figureFileBig=lTEzXd2/G8trWkefKHqcXw==, tableContent=null), ArticleFig(id=1198602013593399643, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=图2, caption=颈动脉粥样硬化斑块差异表达基因的功能富集分析结果

GO. 基因本体论;KEGG. 京都基因和基因组百科全书;A-B. GO富集分析;C-D. KEGG通路富集分析;单个点的大小代表富集程度;颜色深度代表P

, figureFileSmall=fKgy4OStD3hoCz+3mRrJIw==, figureFileBig=lTEzXd2/G8trWkefKHqcXw==, tableContent=null), ArticleFig(id=1198602013706645850, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Fig. 3, caption=The analysis on PPI network and sub-network module of differentially expressed genes in carotid atherosclerotic plaque, figureFileSmall=Vru/Osnrq5KxG5mfRjYkaw==, figureFileBig=l85/BK8syFW8zNSbBiJEkw==, tableContent=null), ArticleFig(id=1198602013794726243, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=图3, caption=颈动脉粥样硬化斑块差异表达基因的PPI网络和子网络模块分析

紫色圆圈代表上调的差异表达基因,绿色菱形块代表下调的差异表达基因;节点大小代表某种蛋白质的蛋白质-蛋白质相互作用对的数目;两个节点之间的连线表示两种蛋白质的相互作用;PPI. 蛋白-蛋白相互作用;A. PPI网络的构建;B. PPI子网络模块分析

, figureFileSmall=Vru/Osnrq5KxG5mfRjYkaw==, figureFileBig=l85/BK8syFW8zNSbBiJEkw==, tableContent=null), ArticleFig(id=1198602013895389542, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Fig.4, caption=Drug-gene interaction network of differentially expressed genes in carotid atherosclerotic plaque, figureFileSmall=k224rdb7WwJBaQDy17G+xA==, figureFileBig=biMXsJ5wUH+69bX0mz23Uw==, tableContent=null), ArticleFig(id=1198602013979275626, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=图4, caption=颈动脉粥样硬化斑块差异基因的药物-基因相互作用网络

紫色矩形表示上调的差异表达基因;绿色矩形表示下调的差异表达基因;灰色矩形表示药物

, figureFileSmall=k224rdb7WwJBaQDy17G+xA==, figureFileBig=biMXsJ5wUH+69bX0mz23Uw==, tableContent=null), ArticleFig(id=1198602014084133229, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Fig.5, caption=The mRNA expression of CSF1R, CXCL2, and IGFBP6 in two groups of patients with carotid atherosclerotic plaque, figureFileSmall=wLL7nIbX9iO3eRd2YVyGlg==, figureFileBig=dRUKqNzSHTcipPwSyDG6QQ==, tableContent=null), ArticleFig(id=1198602014155436401, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=图5, caption=两组颈动脉粥样硬化斑块中3个候选基因CSF1RCXCL2IGFBP6 mRNA表达水平

CSF1R. 集落刺激因子1受体基因;CXCL2. 趋化因子配体2基因;IGFBP6. 胰岛素样生长因子结合蛋白6基因;***P<0.001

, figureFileSmall=wLL7nIbX9iO3eRd2YVyGlg==, figureFileBig=dRUKqNzSHTcipPwSyDG6QQ==, tableContent=null), ArticleFig(id=1198602014230933875, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Fig.6, caption=Prediction of unstable carotid plaques by plasma level of IGFBP6 protein, figureFileSmall=46iK78JhWF6zY7yMyNzJdQ==, figureFileBig=w10TGleyvt0Wxgcuu+DpSQ==, tableContent=null), ArticleFig(id=1198602014365151607, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=图6, caption=血浆IGFBP6水平预测颈动脉不稳定斑块

IGFBP6. 胰岛素样生长因子结合蛋白6;ROC. 受试者工作特征曲线;A. 两组血浆IGFBP6水平比较;B. ROC曲线;****P<0.0001

, figureFileSmall=46iK78JhWF6zY7yMyNzJdQ==, figureFileBig=w10TGleyvt0Wxgcuu+DpSQ==, tableContent=null), ArticleFig(id=1198602017351496059, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Tab.1, caption=

Primer sequences for qRT-PCR

, figureFileSmall=null, figureFileBig=null, tableContent=
基因引物序列(5'-3')
CSF1R正义:GGGAATCCCAGTGATAGAGCC
反义:TTGGAAGGTAGCGTTGTTGGT
CXCL2正义:CCAACCACCAGGCTACAGG
反义:GCGTCACACTCAAGCTCTG
IGFBP6正义:GAATCCTAAGGAGAGTAAACCCC
反义:CTGGATTCCTCTGTTGGTCTC
GAPDH正义:TGCACCACCAACTGCTTAGC
反义:GGCATGGACTGTGGTCATGAC
), ArticleFig(id=1198602017443770752, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=表1, caption=

qRT-PCR引物序列

, figureFileSmall=null, figureFileBig=null, tableContent=
基因引物序列(5'-3')
CSF1R正义:GGGAATCCCAGTGATAGAGCC
反义:TTGGAAGGTAGCGTTGTTGGT
CXCL2正义:CCAACCACCAGGCTACAGG
反义:GCGTCACACTCAAGCTCTG
IGFBP6正义:GAATCCTAAGGAGAGTAAACCCC
反义:CTGGATTCCTCTGTTGGTCTC
GAPDH正义:TGCACCACCAACTGCTTAGC
反义:GGCATGGACTGTGGTCATGAC
), ArticleFig(id=1198602017548628357, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Tab.2, caption=

Subnetworks of PPI networks of differentially expressed genes in carotid atherosclerotic plaque

, figureFileSmall=null, figureFileBig=null, tableContent=
模块 A模块 B模块 C
节点描述程度节点描述程度节点描述程度
COL1A2下调14ADCY3上调12TYROBP上调17
COL4A2下调12CXCR4上调11CSF1R上调10
COL4A5下调11FPR1上调11CD14上调9
IGFBP6下调11CXCL10上调9CD163上调7
COL16A1下调10CXCL16上调8C1QA上调7
COL13A1下调9C1QA上调8C1QB上调6
COL21A1下调8CXCL2上调7C1QC上调5
COL12A1下调7CSF1R上调6
), ArticleFig(id=1198602017682846088, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=表2, caption=

颈动脉粥样硬化斑块差异表达基因的蛋白-蛋白相互作用网络中的子网络

, figureFileSmall=null, figureFileBig=null, tableContent=
模块 A模块 B模块 C
节点描述程度节点描述程度节点描述程度
COL1A2下调14ADCY3上调12TYROBP上调17
COL4A2下调12CXCR4上调11CSF1R上调10
COL4A5下调11FPR1上调11CD14上调9
IGFBP6下调11CXCL10上调9CD163上调7
COL16A1下调10CXCL16上调8C1QA上调7
COL13A1下调9C1QA上调8C1QB上调6
COL21A1下调8CXCL2上调7C1QC上调5
COL12A1下调7CSF1R上调6
), ArticleFig(id=1198602017779315085, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Tab.3, caption=

KEGG and Go-BP enrichment analysis of differentially expressed genes in PPI network module in carotid atherosclerotic plaque (top 5)

, figureFileSmall=null, figureFileBig=null, tableContent=
项目模块KEGG 通路/BP-top 5数量P
KEGG模块Ahsa04512:ECM—受体相互作用31.59E-02
hsa04510:黏着斑24.06E-02
模块Bhsa04062:趋化因子信号通路71.42E-05
hsa04060:细胞因子—细胞因子受体相互作用43.31E-05
模块Chsa05020:朊病毒疾病34.54E-04
hsa04610:补体和凝血级联31.77E-03
hsa05322:系统性红斑狼疮33.61E-03
BP模块AGO:0007155—细胞黏附76.16E-07
GO:0022610—生物黏附68.72E-07
GO:0030198—细胞外基质组织52.32E-06
GO:0043062—细胞外结构组织46.04E-05
GO:0030199—胶原原纤维组织38.31E-04
模块BGO:0006952—反射反应82.62E-10
GO:0006954—炎症反应72.46E-10
GO:0002526—急性炎症反应73.52E-09
GO:0009611—伤人反应62.23E-08
GO:0006958—补体激活,经典途径94.82E-07
模块CGO:0006952—防御反应61.10E-06
GO:0006954—炎症反应54.72E-06
GO:0002526—急性炎症反应47.26E-06
GO:0009611—对伤害的反应53.28E-05
GO:0006958—补体激活,经典途径36.62E-05
), ArticleFig(id=1198602017917727122, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=表3, caption=

颈动脉粥样硬化斑块PPI子网络模块中差异表达基因的KEGG和GO-BP富集分析(前5位)

, figureFileSmall=null, figureFileBig=null, tableContent=
项目模块KEGG 通路/BP-top 5数量P
KEGG模块Ahsa04512:ECM—受体相互作用31.59E-02
hsa04510:黏着斑24.06E-02
模块Bhsa04062:趋化因子信号通路71.42E-05
hsa04060:细胞因子—细胞因子受体相互作用43.31E-05
模块Chsa05020:朊病毒疾病34.54E-04
hsa04610:补体和凝血级联31.77E-03
hsa05322:系统性红斑狼疮33.61E-03
BP模块AGO:0007155—细胞黏附76.16E-07
GO:0022610—生物黏附68.72E-07
GO:0030198—细胞外基质组织52.32E-06
GO:0043062—细胞外结构组织46.04E-05
GO:0030199—胶原原纤维组织38.31E-04
模块BGO:0006952—反射反应82.62E-10
GO:0006954—炎症反应72.46E-10
GO:0002526—急性炎症反应73.52E-09
GO:0009611—伤人反应62.23E-08
GO:0006958—补体激活,经典途径94.82E-07
模块CGO:0006952—防御反应61.10E-06
GO:0006954—炎症反应54.72E-06
GO:0002526—急性炎症反应47.26E-06
GO:0009611—对伤害的反应53.28E-05
GO:0006958—补体激活,经典途径36.62E-05
), ArticleFig(id=1198602018022584724, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=EN, label=Tab.4, caption=

Comparison of baseline data of two groups of the patients with carotid atherosclerotic plaque

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临床特征

稳定斑块组

(n=30)

不稳定斑块组

(n=28)

年龄(岁, $\bar{x}±s$)66.8±2.167.3±1.9
男[例(%)]25(83.3)23(82.1)
吸烟[例(%)]17(56.7)15(53.6)
高血压病[例(%)]15(50.0)13(46.4)
糖尿病[例(%)]6(20.0)9(32.1)
卒中[例(%)]9(30.0)8(28.6)
冠心病[例(%)]5(16.7)4(14.3)
短暂性脑缺血发作[例(%)]6(20.0)5(17.9)
阿司匹林治疗[例(%)]13(43.3)10(35.7)
他汀类治疗[例(%)]11(36.7)11(39.3)
氯吡格雷治疗[例(%)]3(10.0)2(7.1)
Beta受体阻断剂治疗[例(%)]3(10.0)4(14.3)
钙通道阻滞剂治疗[例(%)]10(33.3)9(32.1)
体重(kg, $\bar{x}±s$)71.5±2.272.1±1.9
肌酐(μmol/L, $\bar{x}±s$)79.1±3.281.3±3.9
三酰甘油(mmol/L, $\bar{x}±s$)1.5±0.21.7±0.3
总胆固醇(mmol/L, $\bar{x}±s$)4.1±0.23.9±0.2
高密度脂蛋白胆固醇(mmol/L, $\bar{x}±s$)1.10±0.031.10±0.02
低密度脂蛋白胆固醇(mmol/L, $\bar{x}±s$)2.4±0.12.2±0.1
), ArticleFig(id=1198602018106470808, tenantId=1146029695717560320, journalId=1189873630562394117, articleId=1198602002080035802, language=CN, label=表4, caption=

两组颈动脉粥样硬化斑块患者基线特征比较

, figureFileSmall=null, figureFileBig=null, tableContent=
临床特征

稳定斑块组

(n=30)

不稳定斑块组

(n=28)

年龄(岁, $\bar{x}±s$)66.8±2.167.3±1.9
男[例(%)]25(83.3)23(82.1)
吸烟[例(%)]17(56.7)15(53.6)
高血压病[例(%)]15(50.0)13(46.4)
糖尿病[例(%)]6(20.0)9(32.1)
卒中[例(%)]9(30.0)8(28.6)
冠心病[例(%)]5(16.7)4(14.3)
短暂性脑缺血发作[例(%)]6(20.0)5(17.9)
阿司匹林治疗[例(%)]13(43.3)10(35.7)
他汀类治疗[例(%)]11(36.7)11(39.3)
氯吡格雷治疗[例(%)]3(10.0)2(7.1)
Beta受体阻断剂治疗[例(%)]3(10.0)4(14.3)
钙通道阻滞剂治疗[例(%)]10(33.3)9(32.1)
体重(kg, $\bar{x}±s$)71.5±2.272.1±1.9
肌酐(μmol/L, $\bar{x}±s$)79.1±3.281.3±3.9
三酰甘油(mmol/L, $\bar{x}±s$)1.5±0.21.7±0.3
总胆固醇(mmol/L, $\bar{x}±s$)4.1±0.23.9±0.2
高密度脂蛋白胆固醇(mmol/L, $\bar{x}±s$)1.10±0.031.10±0.02
低密度脂蛋白胆固醇(mmol/L, $\bar{x}±s$)2.4±0.12.2±0.1
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IGFBP6在不稳定颈动脉斑块中的作用:生物信息学分析与实验验证
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李玉岩 1 , 梁莹莹 2 , 周洁信 1 , 车飞 1 , 付金霞 1, *
解放军医学杂志 | 基础研究 2024,49(6): 701-710
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解放军医学杂志 | 基础研究 2024, 49(6): 701-710
IGFBP6在不稳定颈动脉斑块中的作用:生物信息学分析与实验验证
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李玉岩1, 梁莹莹2, 周洁信1, 车飞1, 付金霞1, *
作者信息
  • 1齐齐哈尔医学院附属第二医院神经内科,黑龙江齐齐哈尔 161006
  • 2齐齐哈尔医学院附属第二医院心血管内科,黑龙江齐齐哈尔 161006
  • 李玉岩,主治医师,主要从事神经病学方面的研究

通讯作者:

付金霞,E-mail:
Effect of IGFBP6 in unstable carotid atherosclerotic plaque: bioinformatics analysis and experimental validation
Yu-Yan Li1, Ying-Ying Liang2, Jie-Xin Zhou1, Fei Che1, Jin-Xia Fu1, *
Affiliations
  • 1Department of Neurology, the Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
  • 2Department of Cardiovascular Medicine, the Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
出版时间: 2024-06-28 doi: 10.11855/j.issn.0577-7402.1011.2023.0912
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目的 探讨不稳定颈动脉粥样硬化斑块的差异表达基因(DEGs)及其分子相互作用。方法 从基因表达数据库(GEO)和欧洲生物信息学研究所数据库下载颈动脉斑块患者的基因表达数据集GSE41571、GSE118481和E-MTAB-2055。采用基因本体生物学过程(GO-BP)富集分析、京都基因与基因组百科全书(KEGG)富集分析、蛋白-蛋白相互作用(PPI)网络、miRNAs/转录因子与靶基因的相互关系及药物-基因相互作用等方法,分析至少两个数据集中不稳定颈动脉斑块的共调控DEGs。采用定量实时PCR(qRT-PCR)和酶联免疫吸附试验(ELISA)检测颈动脉粥样硬化斑块患者58例的颈动脉斑块和血浆中部分DEGs的表达水平。结果 GO富集分析显示,不稳定颈动脉斑块的DEGs主要富集在与炎症反应相关的基因和细胞外基质结构基因; KEGG富集分析显示,不稳定颈动脉斑块中上调的DEGs富集于细胞外基质受体相互作用、PI3K-Akt、Hippo信号通路及转化生长因子-β(TGF-β)信号通路,下调的DEGs主要富集于溶酶体、吞噬体及趋化因子过程。PPI网络分析结果显示,COL1A2、COL4A2、胰岛素样生长因子结合蛋白6(IGFBP6)、COL4A5、C1QA、CXCL10、CXCL2、CXCR4和CSF1R等可能在PPI网络中起重要作用。药物-基因相互作用的预测显示,CSF1R的药物相互作用最多,CXCL2受药物拮抗程度最高,IGFBP6受药物激活程度最高。qRT-PCR检测结果显示,与稳定斑块组比较,不稳定斑块组IGFBP6表达水平明显降低(P<0.001)。ELISA法检测结果显示,不稳定斑块组血浆IGFBP6浓度明显低于稳定斑块组(P<0.0001)。受试者工作特征曲线分析结果显示,采用血浆IGFBP6水平鉴别不稳定斑块的曲线下面积为0.894(95%CI 0.810~0.977),截断值为142.08 ng/ml。结论 IGFBP6可能成为预测不稳定颈动脉斑块的重要生物标志物。

动脉粥样硬化  /  卒中  /  生物信息学  /  胰岛素样生长因子结合蛋白6

Objective To investigate the differentially expressed genes (DEGs) and their molecular interactions in unstable carotid atherosclerotic plaques. Methods Gene expression datasets related to carotid atherosclerotic plaques (GSE41571, GSE118481, and E-MTAB-2055) were downloaded from Gene Expression Omnibus (GEO) and European Bioinformatics Institute (EBI) ArrayExpress databases. The co-regulated DEGs in at least two datasets of unstable carotid plaques were merged and analyzed using Gene Ontology Biological Process (GO-BP), Kyoto Encyclopedia of Genes and Genomes (KEGG), Protein-Protein Interaction (PPI) Networks and subnetwork analysis, relationships between miRNAs/transcription factors and target genes, and drug-gene interaction database. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) were used to detect the expression levels of some DEGs in carotid plaques and plasma from 58 patients with carotid atherosclerosis. Results GO enrichment analysis showed that DEGs in unstable carotid atherosclerotic plaques were mainly enriched in genes related to inflammatory response and extracellular matrix structure genes. KEGG enrichment analysis indicated that upregulated DEGs in unstable carotid plaques were enriched in extracellular matrix receptor (ECM-receptor) interaction, PI3K-Akt, Hippo and transforming growth factor-β (TGF-β) signaling pathways, while downregulated DEGs were primarily enriched in lysosomes, phagosomes, and chemokines processes. PPI network analysis suggested that COL1A2, COL4A2, insulin-like growth factor binding protein 6 (IGFBP6), COL4A5, C1QA, CXCL10, CXCL2, CXCR4, and CSF1R may play important roles in PPI networks. Prediction of drug-gene interactions revealed that CSF1R had the most drug interaction, CXCL2 was most antagonized by drugs, and IGFBP6 was most activated by drugs. qRT-PCR showed that the expression level of IGFBP6 in unstable carotid plaques group was significantly lower than that in stable carotid plaques group (P<0.001). ELISA results showed that plasma concentration of IGFBP6 in unstable carotid plaques group was significantly lower than that in stable carotid plaques group (P<0.0001). Receiver operating characteristic (ROC) suggested that the area under the curve (AUC) for plasma IGFBP6 levels to identify unstable plaques was 0.894 (95%CI 0.810-0.977), with a cutoff value of 142.08 ng/ml. Conclusion IGFBP6 may become an important biomarker for predicting unstable carotid atherosclerotic plaques.

atherosclerosis  /  apoplexy  /  bioinformatics  /  insulin-like growth factor binding protein 6
李玉岩, 梁莹莹, 周洁信, 车飞, 付金霞. IGFBP6在不稳定颈动脉斑块中的作用:生物信息学分析与实验验证. 解放军医学杂志, 2024 , 49 (6) : 701 -710 . DOI: 10.11855/j.issn.0577-7402.1011.2023.0912
Yu-Yan Li, Ying-Ying Liang, Jie-Xin Zhou, Fei Che, Jin-Xia Fu. Effect of IGFBP6 in unstable carotid atherosclerotic plaque: bioinformatics analysis and experimental validation[J]. Medical Journal of Chinese People’s Liberation Army, 2024 , 49 (6) : 701 -710 . DOI: 10.11855/j.issn.0577-7402.1011.2023.0912
在发达国家,卒中是导致死亡的第三大原因,也是致残的主要原因之一[1]。颈动脉粥样硬化斑块是缺血性脑卒中的主要原因之一[2]。晚期颈动脉粥样硬化可能发展为有破裂倾向的不稳定斑块,这是局部血栓或栓子的主要来源[3]。预防不稳定斑块的形成对于卒中的预防非常重要[4]。不稳定斑块具有明显的特征,如纤维帽含量减少、坏死核增加、斑块内出血等。纤维帽与坏死核之间的平衡可能被受损的愈伤组织行为和加重的炎性免疫反应所干扰[5]。有研究显示,诸多基因与不稳定斑块的形成有关,如YKL-40[6]和干扰素调节因子基因[7]。然而,目前尚缺乏对不稳定斑块形成的全面和多效性的理解。阐明与易损斑块形成相关的生物学过程和途径,有可能揭示预防卒中的药物靶点。本研究采用差异表达基因(differentially expressed genes,DEGs)筛选、基因本体生物学过程(gene ontology biological process,GO-BP)富集分析、京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)富集分析、蛋白-蛋白相互作用(protein-protein interaction,PPI)分析、转录因子(transcription factor,TF)/miRNA与DEG相互作用关系预测及药物-基因相互作用研究,分析颈动脉斑块患者的基因表达谱数据集,并利用在颈动脉内膜切除术中获得的人类颈动脉斑块验证PPI网络中共调节的DEGs和Hub基因,旨在探索预测不稳定斑块的基因标记,并作为抑制不稳定斑块形成的潜在靶点。
从基因表达数据库(GEO,http://www.ncbi.nlm.nih.gov/GEO)和欧洲生物信息学研究所(EBI,https://www.EBI.ac.uk)数据库下载颈动脉粥样硬化斑块患者基因的芯片数据集。芯片数据的纳入标准:(1)由过去10年发表的稳定和不稳定颈动脉斑块患者的基因表达谱组成;(2)稳定和不稳定斑块根据临床(有症状或无症状)或组织学标准定义[8];(3)原始数据。排除动物样本、血清或血浆样本及糖尿病患者的数据集。
GSE41571和GSE118481下载于GEO数据库,E-MTAB-2055下载于EBI数据库。GSE41571含有5个破裂的颈动脉斑块和6个稳定的颈动脉斑块,在GPL5175[HuEx-1_0-st]Affymetrix人外显子1.0ST阵列[transcript(gene)version]平台上进行检测。以A-MEXP-931-Illumina Affymetrix Human Exon 1.0 ST Array为平台,对E-MTAB-2055中25个破裂斑块和22个稳定斑块进行检测。GSE118481包括10个临床不稳定和6个稳定的颈动脉粥样硬化斑块,在GPL10558 Illumina Human HT-12 V4.0表达珠芯片平台上进行检测。3个数据集的图谱构建均得到了当地研究伦理委员会的授权。
基因数据集下载后,采用R包[9]中的affy(版本1.50.0,http://www.bioconductor.org/packages/release/bioc/html/affy.html)和芯片数据线性模型(LIMMA)包[10](版本3.10.3,http://www.bio-conductor.org/packages/2.9/bioc/html/LIMMA.html)读取GSE41571的原始数据,用LIMMA软件包[10]读取E-MTAB-2055和GSE118481。采用稳健多阵列平均值(robustmulti-arrayaverage,RMA)(背景校正,归一化和表达计算)方法处理3个数据集,根据平台提供的注释模式对探针进行注释,放弃不匹配的探针,当多个探针匹配到一个基因符号时,该基因的最终表达定义为多个探针的平均值。
使用LIMMA包(版本3.30.3)确定DEGs。对于芯片数据,采用经典贝叶斯方法建立线性模型。使用Benjamini-Hochberg方法调整P值,然后计算P值的错误发现率(FDR)。DEGs定义为FDR<0.05、|log2倍数变化(FC)|>0.585的基因。共调节DEGs是至少两个数据集的交集,用在线绘图工具VENNY[11](2.1.0版,http://bioinfogp.cnb.csic.es/tools/venny/index.html)进行选择。
通过在线工具数据库Database for Annotation,Visualization,and Integrated Discovery (DAVID)[12](6.8版,https://david-d.ncifcrf.gov/)进行共调控DEGs的GO-BP[13]和KEGG[14]富集分析。利用Cytoscape®软件(3.2.0版,http://www.cytoscape.org/)的ClueGO插件(2.2.6版,http://www.apps.cytoscape.org/)[15]可视化GO-BP和KEGG富集的上调和下调DEGs,阈值如下:富集基因数≥2和P<0.05。
利用Search Tool for the Retrieval of Interacting Genes/Proteins (STRING)(版本10.0,http://string-db.org/)[16]数据库预测共调控DEGs编码蛋白的PPI,PPI阈值≥0.7(高置信度),利用Cytoscape软件构建PPI网络并进行可视化,选择连接度>12的Hub基因进行实验验证。
单个基因往往与其他基因相互作用,以利于它们发挥调控作用。来自同一模块的编码蛋白倾向于充当一个模块来完成相同的生物学角色和功能。Cytoscape中的multi-contrast delayed enhancement插件[17](版本1.4.2,http://apps.cytoscape.org/apps/mcode)对阈值得分>5的聚类较明显的PPI网络进行子网分析。采用DAVID[14]进行每个子网模块的GO和KEGG富集分析。
采用Web-Gestalt[18](http://www.webgestalt.org/option.php)预测TFs或miRNAs,通过过表达富集分析(http://amp.pharm.mssm.edu/enrichr/)预测TF或miRNA与显著聚类模块中所有靶向DEGs之间的相互作用关系(富集基因计数≥2且P<0.05),利用Cytoscape软件构建miRNAs或TFs靶向调控网络并进行可视化。
为了探索药物开发中优先靶向的基因,使用药物-基因相互作用数据库[19](http://www.dgidb.org/)中潜在靶向于共调控DEGs和调控网络中的基因的药物,所有的药物-基因相互作用都被设定为“all default”,并使用Cytoscape软件构建药物-基因相互作用网络。
选择2016年6月-2018年6月本院收治的颈动脉狭窄且接受颈动脉内膜剥脱术治疗的患者58例。术中获取动脉粥样硬化斑块及血浆,将完整的斑块切成两部分,一部分保存在4%多聚甲醛溶液中用于组织学和免疫组化检测,另一部分冷冻在液氮中提取RNA。根据组织学标准将斑块分为稳定或不稳定斑块。组织学特征采用美国心脏协会的半定量分级标准进行分析。本研究通过齐齐哈尔医学院附属第二医院伦理委员会批准(编号:2018LL-006),所有患者同意参加该研究。
用Trizol(Qiagen,德国)从10~50 μg菌斑中提取总RNA,用miScript反转录试剂盒(Qiagen,德国)反转录成cDNA。用miScript SYBR Green PCR试剂盒(Qiagen,德国)进行qRT-PCR。用RT-PCR方法在Light Cycler480Ⅱ(Roche Diagnostics Ltd,Rotkreuz,Switzerland)上检测基因表达,在95 ℃下反应10 min,然后分别在95 ℃反应10 s,60 ℃反应15 s,72 ℃反应20 s,共40个循环。基因表达归一化为参考基因(GADPH)。用于实验验证的候选基因纳入标准:(1)在PPI网络中连接度>12的Hub基因;(2)在3个数据集中均上调或下调的基因。排除标准:(1)候选基因与动脉粥样硬化的关联没有文献报道;(2)不稳定颈动脉斑块的生物标志物或重要靶点的基因。PCR引物序列见表1
采用ELISA试剂盒(Cloud Clone Corp.,美国)检测颈动脉粥样硬化患者血浆中IGFBP6水平。
采用SPSS 20.0软件进行统计分析。Kolmogorov-Smirnov正态性检验确定为正态分布的计量资料以$\bar{x}±s$表示。对稳定斑块与不稳定斑块的基因表达及ELISA检测结果比较采用t检验。两组人口学和危险因素的差异比较,分别对枚举数据和测量数据进行χ2检验或不配对t检验。应用受试者工作特征(ROC)曲线分析IGFBP6及其相关指标预测不稳定斑块的敏感度和特异度。曲线下面积(AUC)以95%可信区间(CI)计算。根据约登指数确定最佳截断值。P<0.05为差异有统计学意义。
GSE41571中,在不稳定斑块中鉴定出DEGs 1575个,其中上调680个、下调895个。GSE118481中,共筛选到DEGs 760个,其中上调471个、下调289个。E-MTAB-2055数据集中,共鉴定出DEGs 1186个,其中上调619个、下调567个。在3个数据集中,获得共同差异上调基因14个,共同差异下调基因2个(图1)。
考虑到3个数据集差异基因交集较少,本研究选择数据集两两交集的综合,汇总为共同DEGs 231个和下调DEGs 205个,并进行GO和KEGG富集分析。选取前10条路径,采用气泡图显示GO富集分析结果。GO分子功能(molecular function,MF)分析显示,共上调的DEGs主要富集在细胞外基质结构成分、糖胺聚糖结合、含硫化合物结合等功能过程;共下调的DEGs主要富集于趋化因子活性及免疫球蛋白结合等通路。选取前20条路径,采用气泡图显示KEGG富集分析结果。KEGG富集分析结果显示,共上调的DEGs富集于ECM受体相互作用、PI3K-Akt信号通路、Hippo信号通路及转化生长因子-β(transforming grouth factor-β,TGF-β)信号通路;共下调的DEGs主要富集于溶酶体、吞噬体以及趋化因子信号通路(图2)。
在PPI调控网络中共鉴定出189个节点和368个相互作用(图3)。此外,PPI网络进一步筛选出3个子网络模块,即模块A、B和C。模块A包含9个下调节点(如IGFBP6、COL1A2、COL4A2和COL4A5等);模块B包含8个上调节点[如C1QA、CXCL1、CXCL2、CXCR4和集落刺激因子1受体(colony-stimulating factor 1 receptor,CSF1R)]等;模块C包含7个上调节点(如C1QA、CXCL10、CXCL2、CXCR4和CSF1R等)。3个模块中的基因及连通度见表2。此外,模块A中的节点富集于两条KEGG通路(ECM-受体相互作用和黏着斑);模块B中的节点富集于两条通路(趋化因子信号通路和细胞因子-细胞因子受体相互作用);模块C中的节点富集于三条通路(防御素应激、炎症应激和经典补体激活通路,表3)。
通过Dgidb数据库鉴定出药物-基因相互作用对103对,包括上调的靶基因4个、下调的靶基因3个和药物96种(图4)。在药物-基因相互作用网络中,CSF1R受药物抑制程度最高,CXCL2受药物拮抗程度最高,IGFBP6受药物激活程度最高。
根据斑块的组织学状态,分为稳定斑块组30例和不稳定斑块组28例;两组患者的基线人口学特征、组织学指标及短暂性脑缺血发作、黑蒙和卒中发生率比较差异均无统计学意义(P>0.05,表4)。
选择CSF1RCXCL2IGFBP6作为实验验证的候选基因。qRT-PCR检测结果显示,与稳定斑块组比较,不稳定斑块组IGFBP6表达水平明显降低(P<0.001),CSF1RCXCL2表达水平差异均无统计学意义(P>0.05,图5)。
ELISA法检测结果显示,不稳定斑块组血浆IGFBP6水平明显低于稳定斑块组[(113 041±3710) pg/ml vs. (157 359±6152) pg/ml,P<0.0001,图6A]。ROC分析结果显示,采用血浆IGFBP6水平鉴别不稳定斑块的AUC为0.894(95%CI 0.810~0.977),最佳临界值为142.08 ng/ml,敏感度为1.000,特异度为0.655(图6B)。
颈动脉粥样硬化是脑卒中的主要病理基础。动脉粥样硬化斑块破裂形成的栓子是脑血管闭塞的主要原因。卒中可能是可预防的,识别有卒中风险患者的生物标志物及动脉粥样硬化和不稳定斑块的可能治疗靶点,对于预防脑血管和心血管不良事件至关重要[20]。基因表达谱分析如芯片分析和RNA测序,可用来探索DEG和参与动脉粥样硬化的分子机制。测序技术结合生物信息学分析,可用来定义DEG和生物学过程及转录因子、微小RNA(microRNA,miRNA)和蛋白质的复杂相互作用的关系[21]。Wang等[22]通过生物信息学分析,发现差异表达的Ⅲ型胶原α1链(COL3A1)、Ⅰ型胶原α2链(COL1A2)、天冬氨酸(ASPN)和前血小板基础蛋白可能在不稳定斑块的形成中起关键作用。一项基于显微射线的研究显示,趋化因子(C-C基元)配体19[chemokine (C-C motif) ligand 19,CCL19]在不稳定颈动脉斑块中表达上调。
为了确定颈动脉粥样硬化潜在的生物标志物,本研究利用多种生物信息学方法分析了来自GEO和EBI数据库的3个数据集(包括人类颈动脉脉粥样硬化不稳定斑块40例和稳定斑块34例)中的共调节DEGs。通过使用多数据集的合并分析,避免了单个数据集分析中存在的个体偏差。本研究通过排除标准消除了部分因素的影响,如糖尿病、跨物种差异及非斑块样本,并通过检测颈动脉脉粥样硬化不稳定斑块的临床标本验证上述共调节DEGs。
本研究在不稳定斑块中鉴定出231个共上调基因和205个共下调基因。表达上调的基因可能参与信号转导、先天性免疫反应和炎症反应等生物学过程,提示斑块的易损性是由免疫-炎症反应调控的复杂过程。这与斑块破裂很大程度上是由未解决的免疫-炎症反应所触发的证据一致[23-24]。而下调的DEGs主要富集在细胞黏附和ECM组织中。细胞黏附的减少可抑制内皮修复细胞的迁移,从而干扰受损内皮的修复[25]。细胞黏附相关基因的下调可能是导致不稳定斑块形成的原因。此外,ECM的组织对于维持纤维冠的稳定性必不可少,本研究结果显示,参与ECM组织的下调基因(如COL1A2COL12A1)与冠状动脉粥样硬化中纤维冠的含量下降有关[26]。因此,减轻炎症和免疫反应,增强细胞黏附和ECM的组织可能是稳定颈动脉斑块的策略。
本研究差异基因PPI网络及子网络分析结果显示,PPI网络大致可分为3个蛋白模块,进一步的药物-基因相互作用预测显示,CSF1R受药物抑制程度最高,CXCL2受药物拮抗程度最高,IGFBP6受药物激活程度最高。CSF1R具有最多的药物-基因相互作用对,可能是药物开发的优先靶点。集落刺激因子1(CSF1)/CSF1R轴在单核细胞-巨噬细胞系统的存活和分化中起至关重要的作用,可促进肿瘤相关巨噬细胞的激活[25]。CSF1抑制剂,包括CSF1R及其配体的抑制剂,已被开发为抗肿瘤和抗炎剂[26]。斑块中的巨噬细胞通过增加炎症反应和产生蛋白水解基质降解酶,在破坏斑块稳定方面也起重要作用。使用CSF1R抑制剂(已被用于癌症治疗)来稳定斑块是一个有吸引力的方法。
qRT-PCR检测结果显示,稳定斑块与不稳定斑块中CSF1RCXCL2表达差异不明显,仅IGFBP6表达在不稳定斑块中明显低于稳定斑块。IGFBP6属于可与胰岛素样生长因子结合的家族蛋白,可参与多种疾病,包括癌症和自身免疫性疾病[27];IGFBP6在Ⅰ型和Ⅱ型糖尿病中的表达下调[28]。糖尿病和晚期糖基化终产物与易损斑块表型相关[26]。以上结果提示糖尿病与易损斑块形成有关。此外,IGFBP6与内皮细胞和巨噬细胞共定位,提示IGFBP6可能在参与不稳定斑块的内皮细胞和巨噬细胞的活动中起关键作用。ELISA分析显示,不稳定斑块患者血浆IGFBP6浓度低于稳定斑块患者。此外,基于ROC和AUC,若血浆IGFBP6值<142.08 ng/ml,提示颈动脉粥样硬化斑块在组织学检查中更易被归类为不稳定斑块。该临界值敏感度较高,特异度较低,可拓宽IGFBP6在非选择性人群筛选中的应用。因此,IGFBP6可能是预测易损斑块的生物标志物,也是不稳定斑块形成的重要分子;能否作为不稳定斑块的临床监测指标,尚待进一步的大样本试验验证。
总之,IGFBP6在不稳定颈动脉粥样硬化斑块和血浆中表达下调,可能成为预测不稳定颈动脉斑块的生物标志物。
  • 齐齐哈尔市科技计划创新激励项目(CSFGG-2020148)
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doi: 10.11855/j.issn.0577-7402.1011.2023.0912
  • 接收时间:2022-04-30
  • 首发时间:2025-11-21
  • 出版时间:2024-06-28
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  • 收稿日期:2022-04-30
  • 录用日期:2022-07-15
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Innovation Incentive Projects of Qiqihar Science and Technology Plan(CSFGG-2020148)
齐齐哈尔市科技计划创新激励项目(CSFGG-2020148)
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    1齐齐哈尔医学院附属第二医院神经内科,黑龙江齐齐哈尔 161006
    2齐齐哈尔医学院附属第二医院心血管内科,黑龙江齐齐哈尔 161006

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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