Explicating miRNA-mediated regulation of inflammatory pathways in COPD, MS, and lung cancer using explainable artificial intelligence: insights from peripheral blood profiles.

IF 1.4
Nakul Tanwar, Yasha Hasija
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Abstract

Background: Chronic obstructive pulmonary disease (COPD), multiple sclerosis (MS), and lung cancer are linked by shared inflammatory pathways and immune dysregulation. miRNAs regulate these processes by influencing gene expression, yet their roles in the molecular mechanisms across neurological and respiratory systems are not fully understood.

Objective: This study aims to identify miRNAs and their target genes regulating inflammatory pathways, advancing the understanding of molecular genetics underlying COPD, MS, and lung cancer.

Methods: miRNA expression data (GSE61741) were analyzed using a Random Forest (RF) model optimized via Grid Search and validated with Stratified K-Fold cross-validation. Synthetic Minority Oversampling (SMOTE) addressed data imbalance, while SHapley Additive exPlanations (SHAP) identified key miRNAs. Functional enrichment and pathway analyses explored miRNA-gene interactions. Single-cell level analysis further validated the cell-specific roles of these genes. An independent dataset (GSE31568) was used for validation.

Results: Key miRNAs, including hsa-let-7c, hsa-miR-454, hsa-miR-92a, and hsa-miR-223, were identified as regulators of hallmark inflammatory genes such as CCL2, IL6, ITGB3, and MYC. These genes are critical for cytokine signaling, epithelial repair, and immune modulation. Single-cell analysis highlighted the role of inflammatory fibroblasts in localized inflammation and tissue remodeling. The RF model achieved an accuracy of 81.58%, validated at 82.55%. Pathway analysis emphasized cytokine-cytokine receptor interactions and shared pathways between neurological and respiratory diseases.

Conclusions: This study identifies miRNAs and their target genes as critical regulators of inflammation in COPD, MS, and lung cancer. Single-cell insights and pathway enrichment provide a comprehensive view of shared molecular mechanisms, contributing to biomarker discovery and therapeutic strategies for precision medicine in inflammatory diseases.

利用可解释的人工智能解释mirna介导的COPD、MS和肺癌炎症通路调节:来自外周血谱的见解
背景:慢性阻塞性肺疾病(COPD)、多发性硬化症(MS)和肺癌通过共同的炎症途径和免疫失调联系在一起。mirna通过影响基因表达来调节这些过程,但它们在神经系统和呼吸系统分子机制中的作用尚不完全清楚。目的:本研究旨在鉴定调节炎症通路的mirna及其靶基因,促进对COPD、MS和肺癌分子遗传学的理解。方法:使用随机森林(Random Forest, RF)模型分析miRNA表达数据(GSE61741),该模型通过网格搜索优化,并通过分层K-Fold交叉验证进行验证。合成少数派过采样(SMOTE)解决了数据不平衡问题,而SHapley加性解释(SHAP)确定了关键的mirna。功能富集和途径分析探讨了mirna与基因的相互作用。单细胞水平分析进一步证实了这些基因的细胞特异性作用。使用独立数据集(GSE31568)进行验证。结果:包括hsa-let-7c、hsa-miR-454、hsa-miR-92a和hsa-miR-223在内的关键mirna被确定为CCL2、IL6、ITGB3和MYC等标志性炎症基因的调节因子。这些基因对细胞因子信号传导、上皮修复和免疫调节至关重要。单细胞分析强调了炎症成纤维细胞在局部炎症和组织重塑中的作用。RF模型的准确率为81.58%,验证准确率为82.55%。通路分析强调细胞因子-细胞因子受体的相互作用和神经和呼吸系统疾病之间的共享通路。结论:本研究确定mirna及其靶基因是COPD、MS和肺癌炎症的关键调节因子。单细胞洞察和途径富集提供了共享分子机制的全面视图,有助于发现炎症疾病的生物标志物和精准医学治疗策略。
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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