Ding Yunfa, Deng Anxia, Yu Hao, Zhang Hongbing, Qi Tengfei, He Jipei, He Chenjun, Jie Hou, Wang Zihao, Wu Liangpin
Jinsha Zhou Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asian, Department of Cardiology, the First Affiliated Hospital of Xinjiang Medical University, Clinical Medical Research Institute of Xinjiang Medical University, Urumqi, China; Xinjiang Key Laboratory of Medical Animal Model Research, Urumqi, China.
Comput Biol Med. 2025 Jan;184:109365. doi: 10.1016/j.compbiomed.2024.109365. Epub 2024 Nov 14.
The focus of this study is on identifying a potential association between Crohn's disease (CD), a chronic inflammatory bowel condition, and metabolic syndrome (Mets), characterized by a cluster of metabolic abnormalities, including high blood pressure, abnormal lipid levels, and overweight. While the link between CD and MetS has been suggested in the medical community, the underlying molecular mechanisms remain largely unexplored.
Using microarray data from the Gene Expression Omnibus (GEO) database, we conducted a differential gene expression analysis and applied Weighted Gene Co-expression Network Analysis (WGCNA) to identify genes shared between CD and MetS. To further elucidate the functions of these shared genes, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and constructed protein-protein interaction (PPI) networks. For key gene screening, we used Random Forest and Least Absolute Shrinkage and Selection Operator (LASSO) regression and constructed a diagnostic prediction model with the Extreme Gradient Boosting (XGBoost) algorithm. Additionally, CIBERSORT and Gene Set Variation Analysis (GSVA) were employed to examine the relationships between these genes and immune cell infiltration, as well as metabolic pathways. Mendelian randomization and colocalization analyses were also conducted to explore causal links between genes and disease. Lastly, single-cell RNA sequencing (scRNA-seq) was used to validate the functionality of these key genes.
Through the use of the limma R package and WGCNA, we identified 1767 co-expressed genes common to both CD and MetS, which are notably enriched in pathways related to immune responses and metabolic regulation. After thorough analysis, 34 key genes were highlighted, demonstrating their potential utility in prognostic models. These genes were closely linked to tissue immune responses and metabolic functions. Subsequent scRNA-seq analysis confirmed the strong diagnostic potential of PIM2 and PBX2, with especially prominent expression in T and B cells.
This study identifies shared regulatory genes between CD and MetS, advancing the development of precise diagnostic tools. In particular, PIM2 and PBX2 were found to be positively associated with hypoxia and hemoglobin metabolism pathways, suggesting their involvement in the modulation of cellular processes. These findings improve our understanding of the molecular mechanisms underlying the comorbidity of CD and MetS, offering novel targets for integrated therapeutic interventions.
本研究的重点是确定克罗恩病（一种慢性炎症性肠病）与代谢综合征（以包括高血压、血脂异常和超重在内的一系列代谢异常为特征）之间的潜在关联。虽然医学界已提出克罗恩病与代谢综合征之间存在联系，但其潜在分子机制在很大程度上仍未得到探索。
利用基因表达综合数据库（GEO）中的微阵列数据，我们进行了差异基因表达分析，并应用加权基因共表达网络分析（WGCNA）来识别克罗恩病和代谢综合征之间共有的基因。为了进一步阐明这些共有基因的功能，我们进行了基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析，并构建了蛋白质 - 蛋白质相互作用（PPI）网络。对于关键基因筛选，我们使用随机森林和最小绝对收缩与选择算子（LASSO）回归，并使用极端梯度提升（XGBoost）算法构建诊断预测模型。此外，采用CIBERSORT和基因集变异分析（GSVA）来研究这些基因与免疫细胞浸润以及代谢途径之间的关系。还进行了孟德尔随机化和共定位分析以探索基因与疾病之间的因果联系。最后，使用单细胞RNA测序（scRNA - seq）来验证这些关键基因的功能。
通过使用limma R包和WGCNA，我们确定了1767个克罗恩病和代谢综合征共有的共表达基因，这些基因在与免疫反应和代谢调节相关的通路中显著富集。经过深入分析，突出了34个关键基因，证明了它们在预后模型中的潜在效用。这些基因与组织免疫反应和代谢功能密切相关。随后的scRNA - seq分析证实了PIM2和PBX2具有很强的诊断潜力，在T细胞和B细胞中表达尤为突出。
本研究确定了克罗恩病和代谢综合征之间共有的调控基因，推动了精确诊断工具的开发。特别是，发现PIM2和PBX2与缺氧和血红蛋白代谢途径呈正相关，表明它们参与细胞过程的调节。这些发现增进了我们对克罗恩病和代谢综合征合并症潜在分子机制的理解，为综合治疗干预提供了新的靶点。
