转录组数据结合孟德尔随机化分析确定与椎间盘退变中线粒体和程序性细胞死亡相关的关键基因

IF 3.4 3区医学 Q1 ORTHOPEDICS

JOR Spine Pub Date : 2025-03-24 DOI:10.1002/jsp2.70057

Hongfei Nie, Xiao Hu, Jiaxiao Wang, Jia Wang, Xiaoqian Yu, Jun Li

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引用次数: 0

摘要

背景椎间盘退变（IDD）是导致颈腰椎疾病的主要原因，严重影响患者的生活质量。线粒体和细胞死亡与缺乏症有关，但关键的相关基因尚不清楚。方法用GSE70362检测IDD与对照的差异表达基因（DEGs）。线粒体相关基因（MRGs）和程序性细胞死亡相关基因（PCDRGs）与deg相交，发现DE-MRGs和DE-PCDRGs。加权基因共表达网络分析（Weighted gene co-expression network analysis， WGCNA）确定了关键模块基因，与deg的重叠揭示了候选基因。采用孟德尔随机化（MR）分析确定与缺乏症相关的基因。机器学习和表达验证进一步细化了关键基因，然后用这些基因构建一个nomogram来预测IDD风险。此外，还进行了基因集富集分析（GSEA）、免疫浸润和单细胞分析。结果共获得515个deg与224个关键模块基因相交，得到31个候选基因。bckdhb、BID、TNFAIP6、VRK1、CAB39L、tmtc1等6个基因与IDD存在因果关系。通过机器学习和验证进一步确定BID、TNFAIP6和TMTC1为关键基因。在这些基因的基础上形成了一种形态图。GSEA显示BID和TMTC1在n -聚糖生物合成中富集，TNFAIP6和TMTC1在氨基tRNA生物合成中富集，BID和TMTC1在核糖体途径中富集。激活的树突状细胞、CD56dim自然杀伤细胞、单核细胞和其他免疫细胞在IDD中升高，TNFAIP6与活化的树突状细胞密切相关。关键基因在降解样品中表达水平较高。结论BID、TMTC1和TNFAIP6是IDD中线粒体和细胞死亡相关的关键基因，为IDD的诊断和治疗提供了新的思路。

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Transcriptome Data Combined With Mendelian Randomization Analysis Identifies Key Genes Associated With Mitochondria and Programmed Cell Death in Intervertebral Disc Degeneration

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Transcriptome Data Combined With Mendelian Randomization Analysis Identifies Key Genes Associated With Mitochondria and Programmed Cell Death in Intervertebral Disc Degeneration

Background

Intervertebral disc degeneration (IDD) is a major cause of cervical and lumbar diseases, significantly impacting patients' quality of life. Mitochondria and cell death have been implicated in IDD, but the key related genes remain unknown.

Methods

Differentially expressed genes (DEGs) between IDD and control samples were identified using GSE70362. Mitochondria-related genes (MRGs) and programmed cell death-related genes (PCDRGs) were intersected with DEGs to find DE-MRGs and DE-PCDRGs. Weighted gene co-expression network analysis (WGCNA) identified key module genes, and the overlap with DEGs revealed candidate genes. Mendelian randomization (MR) analysis was used to determine genes causally linked to IDD. Machine learning and expression validation further refined key genes, which were then used to build a nomogram to predict IDD risk. Additionally, gene set enrichment analysis (GSEA), immune infiltration, and single-cell analysis were performed.

Results

A total of 515 DEGs were intersected with 224 key module genes, yielding 31 candidate genes. Six genes—BCKDHB, BID, TNFAIP6, VRK1, CAB39L, and TMTC1—showed a causal relationship with IDD. BID, TNFAIP6, and TMTC1 were further identified as key genes through machine learning and validation. A nomogram was developed based on these genes. GSEA revealed BID and TMTC1 were enriched in N-glycan biosynthesis, TNFAIP6 and TMTC1 in aminoacyl tRNA biosynthesis, and BID and TMTC1 in ribosomal pathways. Activated dendritic cells, CD56dim natural killer cells, monocytes, and other immune cells were elevated in IDD, with TNFAIP6 strongly correlating with activated dendritic cells. Key genes were expressed at higher levels in degraded samples.