Pathogenic Mechanism of the Lactylation-Related Gene DCBLD1 in Ulcerative Colitis: A Multi-Omics and Machine Learning Analysis.

IF 1.7 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Changan Chen, Yuping Yang, Tingmei Yang, Caiyuan Yu, Guixia Zhang, Lijiao Cui, Yu Zhou, Zhenkai Li, Zihang Hu, Yijie Weng
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引用次数: 0

Abstract

Background: The incidence of ulcerative colitis (UC) has been steadily increasing in recent years. Current treatments are only effective for some patients, highlighting the need to find novel therapeutic targets. Lactylation, a post-translational modification, remains poorly understood in UC. This study examines the role of the lactylation-related gene DCBLD1 in the pathogenesis of UC through multi-omics analysis.

Methods: Summary-data-based Mendelian Randomization (SMR) analysis identified DCBLD1 as a lactylation-related gene associated with UC risk. Single-cell RNA sequencing (scRNA-seq) examined DCBLD1 expression in UC and healthy intestinal tissues, coupled with cellular communication, metabolic pathway, KEGG enrichment, and GO annotations. Diagnostic models were built based on differential expression between DCBLD1+ and DCBLD1- epithelial cells. In addition, RNA sequencing (RNA-seq) was used for analysis. Ultimately, qPCR was performed to validate DCBLD1 expression.

Results: SMR demonstrated that DCBLD1 positively correlated with UC risk. scRNA-seq revealed that DCBLD1+ epithelial cells exhibited enhanced cellular communication and metabolic activity. Seventeen hub genes were screened for machine learning, yielding AUC values of 0.69 (CATboost), 0.63 (XGBoost), and 0.55 (NGboost) in the test set. RNA-seq confirmed the association of DCBLD1 with immune responses. qPCR confirmed elevated DCBLD1 expression in UC tissues versus controls.

Discussion: Intestinal epithelial cells expressing DCBLD1 may promote inflammation in UC by lactylation, regulating immunometabolism, and participating in immunological responses, all of which require further investigation in the future.

Conclusion: DCBLD1 may promote UC progression through lactylation, immune-metabolic regulation, and involvement in immune responses, serving as a potential therapeutic target.

乳酸酰化相关基因dbld1在溃疡性结肠炎中的致病机制:多组学和机器学习分析。
背景:近年来,溃疡性结肠炎(UC)的发病率稳步上升。目前的治疗方法只对一些患者有效,这突出了寻找新的治疗靶点的必要性。乳酸化,一种翻译后修饰,在UC中仍然知之甚少。本研究通过多组学分析探讨了乳酸化相关基因DCBLD1在UC发病机制中的作用。方法:基于汇总数据的孟德尔随机化(SMR)分析确定DCBLD1是与UC风险相关的乳酸化相关基因。单细胞RNA测序(scRNA-seq)检测了UC和健康肠道组织中的dccbld1表达,以及细胞通讯、代谢途径、KEGG富集和GO注释。基于DCBLD1+和DCBLD1-上皮细胞的差异表达建立诊断模型。此外,采用RNA测序(RNA-seq)进行分析。最后,采用qPCR验证dbld1的表达。结果:SMR显示DCBLD1与UC风险呈正相关。scRNA-seq显示DCBLD1+上皮细胞表现出增强的细胞通讯和代谢活性。17个hub基因被筛选用于机器学习,测试集中的AUC值为0.69 (CATboost), 0.63 (XGBoost)和0.55 (NGboost)。RNA-seq证实DCBLD1与免疫应答相关。与对照组相比,qPCR证实UC组织中DCBLD1表达升高。讨论:表达DCBLD1的肠上皮细胞可能通过乳酸化、调节免疫代谢、参与免疫应答等方式促进UC炎症,这些有待于进一步的研究。结论:dbld1可能通过乳酸化、免疫代谢调节和参与免疫反应来促进UC的进展,是潜在的治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.10
自引率
5.60%
发文量
327
审稿时长
7.5 months
期刊介绍: Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.
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