PDF(Pubmed)
Abstract：
Laparoscopic sleeve gastrectomy (LSG) is a sustainable technique that effectively treats morbid obesity. However, the molecular mechanisms underlying the improvement of metabolic health following this process warrants more investigation. This study investigates LSG-related molecules and uses bulk RNA-sequencing high-throughput analysis to unravel their regulatory mechanisms.
Peripheral blood mononuclear cells (PBMC) were collected from ten obese patients with BMI ≥ 32.5 kg/m2 in the Department of General Surgery of Kunming First People\'s Hospital. After LSG, patients were followed up for one month, and blood samples were retaken. Blood samples from ten patients before and after LSG and bulk RNA-Seq data were analyzed in this study. LSG-associated gene expression was detected by weighted gene coexpression network analysis (WGCNA) and differential analysis. Subsequently, essential signature genes were identified using logistic least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were utilized to reveal the potential functions of the target genes. Furthermore, the Pearson correlation of signature genes with leptin and lipocalin was also explored. Finally, we constructed a robust endogenous RNA (ceRNA) network based on miRWalk and starBase databases.
We identified 18 overlapping genes from 91 hub genes, and 165 differentially expressed mRNAs (DE-mRNA), which were revealed to be significantly associated with immune cells, immune response, inflammatory response, lipid storage, and localization upon functional enrichment analysis. Three signature genes, IRF1, NFKBIA, and YRDC, were identified from the 18 overlapping genes by LASSO and SVM-REF algorithms. The logistic regression model based on the three signature genes highlighted how robustly they discriminated between samples. ssGSEA indicated these genes to be involved in lipid metabolism and degradation pathways. Moreover, leptin levels were significantly reduced in patients undergoing LSG, and NFKBIA significantly negatively correlated with leptin. Finally, we identified how the long non-coding RNA (lncRNA) ATP2B1-AS1 regulated the expression of the signature genes by competitively binding to six microRNAs (miRNAs), which were hsa-miR-6509-5p, hsa-miR-330-5P, hsa-miR-154-5P, hsa-miR-145-5P, hsa-miR4726-5P and hsa-miR-134-5P.
This study identified three critical regulatory genes significantly differentiated between patients before and after LSG treatment and highlighted their potentially crucial role after bariatric surgery. This provides novel insights to increase our understanding of the underlying mechanisms of weight loss and associated metabolic improvement after bariatric surgery.
Peripheral blood mononuclear cells (PBMC) were collected from ten obese patients with BMI ≥ 32.5 kg/m2 in the Department of General Surgery of Kunming First People\'s Hospital. After LSG, patients were followed up for one month, and blood samples were retaken. Blood samples from ten patients before and after LSG and bulk RNA-Seq data were analyzed in this study. LSG-associated gene expression was detected by weighted gene coexpression network analysis (WGCNA) and differential analysis. Subsequently, essential signature genes were identified using logistic least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were utilized to reveal the potential functions of the target genes. Furthermore, the Pearson correlation of signature genes with leptin and lipocalin was also explored. Finally, we constructed a robust endogenous RNA (ceRNA) network based on miRWalk and starBase databases.
We identified 18 overlapping genes from 91 hub genes, and 165 differentially expressed mRNAs (DE-mRNA), which were revealed to be significantly associated with immune cells, immune response, inflammatory response, lipid storage, and localization upon functional enrichment analysis. Three signature genes, IRF1, NFKBIA, and YRDC, were identified from the 18 overlapping genes by LASSO and SVM-REF algorithms. The logistic regression model based on the three signature genes highlighted how robustly they discriminated between samples. ssGSEA indicated these genes to be involved in lipid metabolism and degradation pathways. Moreover, leptin levels were significantly reduced in patients undergoing LSG, and NFKBIA significantly negatively correlated with leptin. Finally, we identified how the long non-coding RNA (lncRNA) ATP2B1-AS1 regulated the expression of the signature genes by competitively binding to six microRNAs (miRNAs), which were hsa-miR-6509-5p, hsa-miR-330-5P, hsa-miR-154-5P, hsa-miR-145-5P, hsa-miR4726-5P and hsa-miR-134-5P.
This study identified three critical regulatory genes significantly differentiated between patients before and after LSG treatment and highlighted their potentially crucial role after bariatric surgery. This provides novel insights to increase our understanding of the underlying mechanisms of weight loss and associated metabolic improvement after bariatric surgery.
摘要：
■腹腔镜袖状胃切除术（LSG）是一种可持续的技术，可有效治疗病态肥胖。然而,此过程后代谢健康改善的分子机制值得更多研究。这项研究调查了LSG相关分子，并使用批量RNA测序高通量分析来解开它们的调控机制。
■收集10例BMI≥32.5kg/m2的肥胖患者的外周血单个核细胞(PBMC)。在LSG之后,患者随访一个月,并重新采集了血液样本.在本研究中分析了来自LSG之前和之后的10名患者的血液样品和大量RNA-Seq数据。通过加权基因共表达网络分析（WGCNA）和差异分析检测LSG相关基因的表达。随后，使用逻辑最小绝对收缩和选择算子(LASSO)和支持向量机-递归特征消除(SVM-RFE)算法鉴定基本特征基因.基因本体论（GO），京都基因和基因组百科全书（KEGG），和单样本基因集富集分析（ssGSEA）用于揭示目标基因的潜在功能。此外，还探讨了标记基因与瘦素和脂质运载蛋白的Pearson相关性.最后,我们基于miRWalk和starBase数据库构建了一个强大的内源性RNA（ceRNA）网络。
■我们从91个hub基因中鉴定出18个重叠基因，和165个差异表达的mRNA（DE-mRNA），被发现与免疫细胞显著相关，免疫反应，炎症反应，脂质储存，和功能富集分析的定位。三个特征基因，IRF1,NFKBIA,YRDC,通过LASSO和SVM-REF算法从18个重叠基因中鉴定。基于三个标记基因的逻辑回归模型强调了它们在样品之间的区分能力。ssGSEA表明这些基因参与脂质代谢和降解途径。此外，LSG患者的瘦素水平显着降低，NFKBIA与瘦素呈显著负相关。最后,我们确定了长的非编码RNA（lncRNA）ATP2B1-AS1如何通过竞争性结合六个microRNAs（miRNA）来调节签名基因的表达，是hsa-miR-6509-5p，hsa-miR-330-5P,hsa-miR-154-5P,hsa-miR-145-5P,hsa-miR4726-5P和hsa-miR-134-5P。
这项研究确定了在LSG治疗前后患者之间有显著差异的三个关键调节基因，并强调了它们在减肥手术后的潜在关键作用。这提供了新的见解，以增加我们对减肥手术后体重减轻和相关代谢改善的潜在机制的理解。
■收集10例BMI≥32.5kg/m2的肥胖患者的外周血单个核细胞(PBMC)。在LSG之后,患者随访一个月,并重新采集了血液样本.在本研究中分析了来自LSG之前和之后的10名患者的血液样品和大量RNA-Seq数据。通过加权基因共表达网络分析（WGCNA）和差异分析检测LSG相关基因的表达。随后，使用逻辑最小绝对收缩和选择算子(LASSO)和支持向量机-递归特征消除(SVM-RFE)算法鉴定基本特征基因.基因本体论（GO），京都基因和基因组百科全书（KEGG），和单样本基因集富集分析（ssGSEA）用于揭示目标基因的潜在功能。此外，还探讨了标记基因与瘦素和脂质运载蛋白的Pearson相关性.最后,我们基于miRWalk和starBase数据库构建了一个强大的内源性RNA（ceRNA）网络。
■我们从91个hub基因中鉴定出18个重叠基因，和165个差异表达的mRNA（DE-mRNA），被发现与免疫细胞显著相关，免疫反应，炎症反应，脂质储存，和功能富集分析的定位。三个特征基因，IRF1,NFKBIA,YRDC,通过LASSO和SVM-REF算法从18个重叠基因中鉴定。基于三个标记基因的逻辑回归模型强调了它们在样品之间的区分能力。ssGSEA表明这些基因参与脂质代谢和降解途径。此外，LSG患者的瘦素水平显着降低，NFKBIA与瘦素呈显著负相关。最后,我们确定了长的非编码RNA（lncRNA）ATP2B1-AS1如何通过竞争性结合六个microRNAs（miRNA）来调节签名基因的表达，是hsa-miR-6509-5p，hsa-miR-330-5P,hsa-miR-154-5P,hsa-miR-145-5P,hsa-miR4726-5P和hsa-miR-134-5P。
这项研究确定了在LSG治疗前后患者之间有显著差异的三个关键调节基因，并强调了它们在减肥手术后的潜在关键作用。这提供了新的见解，以增加我们对减肥手术后体重减轻和相关代谢改善的潜在机制的理解。
