PDF(Pubmed)
Abstract：
UNASSIGNED: Atherosclerosis (AS) is a major contributor to cerebrovascular and cardiovascular events. There is growing evidence that ankylosing spondylitis is closely linked to AS, often co-occurring with it; however, the shared pathogenic mechanisms between the two conditions are not well understood. This study employs bioinformatics approaches to identify common biomarkers and pathways between AS and ankylosing spondylitis.
UNASSIGNED: Gene expression datasets for AS (GSE100927, GSE28829, GSE155512) and ankylosing spondylitis (GSE73754, GSE25101) were obtained from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) and module genes for AS and ankylosing spondylitis were identified using the Limma R package and weighted gene co-expression network analysis (WGCNA) techniques, respectively. The machine learning algorithm SVM-RFE was applied to pinpoint promising biomarkers, which were then validated in terms of their expression levels and diagnostic efficacy in AS and ankylosing spondylitis, using two separate GEO datasets. Furthermore, the interaction of the key biomarker with the immune microenvironment was investigated via the CIBERSORT algorithm, single-cell analysis was used to identify the locations of common diagnostic markers.
UNASSIGNED: The dataset GSE100927 contains 524 DEGs associated with AS, whereas dataset GSE73754 includes 1,384 genes categorized into modules specific to ankylosing spondylitis. Analysis of these datasets revealed an overlap of 71 genes between the DEGs of AS and the modular genes of ankylosing spondylitis. Utilizing the SVM-RFE algorithm, 15 and 24 central diagnostic genes were identified in datasets GSE100927 and GSE73754, respectively. Further validation of six key genes using external datasets confirmed ST8SIA4 as a common diagnostic marker for both conditions. Notably, ST8SIA4 is upregulated in samples from both diseases. Additionally, ROC analysis confirmed the robust diagnostic utility of ST8SIA4. Moreover, analysis through CIBERSORT suggested an association of the ST8SIA4 gene with the immune microenvironment in both disease contexts. Single-cell analysis revealed that ST8SIA4 is primarily expressed in Macrophages, Monocytes, T cells, and CMPs.
UNASSIGNED: This study investigates the role of ST8SIA4 as a common diagnostic gene and the involvement of the lysosomal pathway in both AS and ankylosing spondylitis. The findings may yield potential diagnostic biomarkers and offer new insights into the shared pathogenic mechanisms underlying these conditions.
UNASSIGNED: Gene expression datasets for AS (GSE100927, GSE28829, GSE155512) and ankylosing spondylitis (GSE73754, GSE25101) were obtained from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) and module genes for AS and ankylosing spondylitis were identified using the Limma R package and weighted gene co-expression network analysis (WGCNA) techniques, respectively. The machine learning algorithm SVM-RFE was applied to pinpoint promising biomarkers, which were then validated in terms of their expression levels and diagnostic efficacy in AS and ankylosing spondylitis, using two separate GEO datasets. Furthermore, the interaction of the key biomarker with the immune microenvironment was investigated via the CIBERSORT algorithm, single-cell analysis was used to identify the locations of common diagnostic markers.
UNASSIGNED: The dataset GSE100927 contains 524 DEGs associated with AS, whereas dataset GSE73754 includes 1,384 genes categorized into modules specific to ankylosing spondylitis. Analysis of these datasets revealed an overlap of 71 genes between the DEGs of AS and the modular genes of ankylosing spondylitis. Utilizing the SVM-RFE algorithm, 15 and 24 central diagnostic genes were identified in datasets GSE100927 and GSE73754, respectively. Further validation of six key genes using external datasets confirmed ST8SIA4 as a common diagnostic marker for both conditions. Notably, ST8SIA4 is upregulated in samples from both diseases. Additionally, ROC analysis confirmed the robust diagnostic utility of ST8SIA4. Moreover, analysis through CIBERSORT suggested an association of the ST8SIA4 gene with the immune microenvironment in both disease contexts. Single-cell analysis revealed that ST8SIA4 is primarily expressed in Macrophages, Monocytes, T cells, and CMPs.
UNASSIGNED: This study investigates the role of ST8SIA4 as a common diagnostic gene and the involvement of the lysosomal pathway in both AS and ankylosing spondylitis. The findings may yield potential diagnostic biomarkers and offer new insights into the shared pathogenic mechanisms underlying these conditions.
摘要：
动脉粥样硬化(AS)是脑血管和心血管事件的主要原因。越来越多的证据表明强直性脊柱炎与AS密切相关，经常与它同时发生；然而，这两种疾病之间的共同致病机制还没有得到很好的理解。这项研究采用生物信息学方法来鉴定AS和强直性脊柱炎之间的常见生物标志物和通路。
■AS(GSE100927,GSE28829,GSE155512)和强直性脊柱炎(GSE73754,GSE25101)的基因表达数据集从基因表达综合(GEO)获得。使用LimmaR包和加权基因共表达网络分析（WGCNA）技术鉴定AS和强直性脊柱炎的差异表达基因（DEGs）和模块基因，分别。机器学习算法SVM-RFE被用来确定有希望的生物标志物，然后根据它们在AS和强直性脊柱炎中的表达水平和诊断功效进行验证，使用两个单独的GEO数据集。此外，通过CIBERSORT算法研究了关键生物标志物与免疫微环境的相互作用，使用单细胞分析来确定常见诊断标志物的位置.
■数据集GSE100927包含524个与AS关联的DEG，而数据集GSE73754包括1,384个基因,这些基因被分类为强直性脊柱炎特有的模块.对这些数据集的分析显示，AS的DEG和强直性脊柱炎的模块化基因之间有71个基因重叠。利用SVM-RFE算法，在数据集GSE100927和GSE73754中分别鉴定了15个和24个中心诊断基因。使用外部数据集对六个关键基因的进一步验证证实ST8SIA4是两种情况的常见诊断标记。值得注意的是,ST8SIA4在来自两种疾病的样品中上调。此外,ROC分析证实了ST8SIA4的稳健诊断效用。此外，通过CIBERSORT的分析表明,在两种疾病背景下,ST8SIA4基因与免疫微环境均有关联.单细胞分析显示，ST8SIA4主要在巨噬细胞中表达，单核细胞,T细胞,和CMPs。
■本研究调查了ST8SIA4作为常见诊断基因的作用以及溶酶体途径在AS和强直性脊柱炎中的作用。这些发现可能会产生潜在的诊断生物标志物，并为这些疾病的共同致病机制提供新的见解。
■AS(GSE100927,GSE28829,GSE155512)和强直性脊柱炎(GSE73754,GSE25101)的基因表达数据集从基因表达综合(GEO)获得。使用LimmaR包和加权基因共表达网络分析（WGCNA）技术鉴定AS和强直性脊柱炎的差异表达基因（DEGs）和模块基因，分别。机器学习算法SVM-RFE被用来确定有希望的生物标志物，然后根据它们在AS和强直性脊柱炎中的表达水平和诊断功效进行验证，使用两个单独的GEO数据集。此外，通过CIBERSORT算法研究了关键生物标志物与免疫微环境的相互作用，使用单细胞分析来确定常见诊断标志物的位置.
■数据集GSE100927包含524个与AS关联的DEG，而数据集GSE73754包括1,384个基因,这些基因被分类为强直性脊柱炎特有的模块.对这些数据集的分析显示，AS的DEG和强直性脊柱炎的模块化基因之间有71个基因重叠。利用SVM-RFE算法，在数据集GSE100927和GSE73754中分别鉴定了15个和24个中心诊断基因。使用外部数据集对六个关键基因的进一步验证证实ST8SIA4是两种情况的常见诊断标记。值得注意的是,ST8SIA4在来自两种疾病的样品中上调。此外,ROC分析证实了ST8SIA4的稳健诊断效用。此外，通过CIBERSORT的分析表明,在两种疾病背景下,ST8SIA4基因与免疫微环境均有关联.单细胞分析显示，ST8SIA4主要在巨噬细胞中表达，单核细胞,T细胞,和CMPs。
■本研究调查了ST8SIA4作为常见诊断基因的作用以及溶酶体途径在AS和强直性脊柱炎中的作用。这些发现可能会产生潜在的诊断生物标志物，并为这些疾病的共同致病机制提供新的见解。
