An Wenrong, Tang Kegong, Liu Juan, Zheng Wenfei, Li Guoxia, Xu Yunsheng
Second Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, 250001, Shandong, China.
Department of Pathology, Shandong Provincial Qianfoshan Hospital, The First Affiliated Hospital of Shandong First Medical University, Shandong Lung Cancer Institute, Shandong Institute of Nephrology, Jinan, 250014, Shandong, China.
Sci Rep. 2025 Jan 17;15(1):2301. doi: 10.1038/s41598-025-85825-2.
Obesity (OB) and atherosclerosis (AS) represent two highly prevalent and detrimental chronic diseases that are intricately linked. However, the shared genetic signatures and molecular pathways underlying these two conditions remain elusive. This study aimed to identify the shared diagnostic genes and the associated molecular mechanism between OB and AS. The microarray datasets of OB and AS were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis and the weighted gene co-expression network analysis (WGCNA) were conducted to identify the shared genes. Then least absolute shrinkage selection (LASSO) algorithm was used for diagnostic genes discovery. The diagnostic genes were validated using expression analysis and receiver operating characteristic (ROC) curves. Furthermore, Gene set enrichment analysis (GSEA) was used to investigate molecular pathways and immune infiltration related to the diagnostic genes. TF-gene and miRNA-gene networks were also constructed by utilizing the NetworkAnalyst tool. By intersecting the key module genes of WGCNA with DEGs in OB and AS, 56 shared genes with the same expression trend were identified. Using LASSO algorithm, we obtained two shared diagnostic genes, namely SAMSN1 and PHGDH. Validation confirmed their expression patterns and robust predictive abilities. GSEA revealed the crucial roles of SAMSN1 and PHGDH in disease-associated pathways. Additionally, higher immune cell infiltration expression was found in both diseases and strongly linked to the diagnostic genes. Finally, we constructed the TF-gene and miRNA-gene networks. We identified SAMSN1 and PHGDH as potential diagnostic genes for OB and AS. Our findings provide novel insights into the molecular underpinnings of the OB-AS link.
肥胖（OB）和动脉粥样硬化（AS）是两种高度普遍且有害的慢性疾病，它们紧密相连。然而，这两种疾病潜在的共同基因特征和分子途径仍不清楚。本研究旨在确定肥胖和动脉粥样硬化之间共同的诊断基因及相关分子机制。从基因表达综合数据库（GEO）获得肥胖和动脉粥样硬化的微阵列数据集。进行差异表达基因（DEG）分析和加权基因共表达网络分析（WGCNA）以确定共同基因。然后使用最小绝对收缩选择（LASSO）算法发现诊断基因。通过表达分析和受试者工作特征（ROC）曲线对诊断基因进行验证。此外，基因集富集分析（GSEA）用于研究与诊断基因相关的分子途径和免疫浸润。还利用NetworkAnalyst工具构建了转录因子-基因和miRNA-基因网络。通过将WGCNA的关键模块基因与肥胖和动脉粥样硬化中的DEG进行交叉分析，确定了56个具有相同表达趋势的共同基因。使用LASSO算法，我们获得了两个共同的诊断基因，即SAMSN1和PHGDH。验证证实了它们的表达模式和强大的预测能力。GSEA揭示了SAMSN1和PHGDH在疾病相关途径中的关键作用。此外，在这两种疾病中均发现较高的免疫细胞浸润表达，且与诊断基因密切相关。最后，我们构建了转录因子-基因和miRNA-基因网络。我们确定SAMSN1和PHGDH为肥胖和动脉粥样硬化的潜在诊断基因。我们的研究结果为肥胖-动脉粥样硬化联系的分子基础提供了新的见解。
