Multi-Omics Integration Reveals Mitochondrial Gene Regulation as a Determinant of Tuberculosis Susceptibility: A Mendelian Randomization Approach

多组学整合揭示线粒体基因调控是结核病易感性的决定因素:孟德尔随机化方法

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Abstract

Background/Objectives: Mitochondrial dysfunction has been implicated in the pathogenesis of tuberculosis (TB). Despite emerging evidence of the importance of mitochondrial gene regulation in the immune response, the specific role of mitochondrial-related genes in TB susceptibility remains to be fully elucidated. Methods: We employed a multi-omics approach integrating genetic, methylation, and protein-level data. Mendelian randomization (MR) and colocalization analyses were conducted to explore causal associations between mitochondrial gene features-expression quantitative trait loci (eQTL), methylation quantitative trait loci (mQTL), and protein quantitative trait loci (pQTL)-and TB susceptibility. Data were obtained from the FinnGen cohort and validated using independent datasets. Results: Our analyses identified several key mitochondrial genes (e.g., ACSF3, AK3, LYRM4, and PDHB) significantly associated with TB susceptibility. Random forest analysis and gene set enrichment analysis (GSEA) supported the predictive power of these genes. Furthermore, we observed significant correlations between mitochondrial gene expression and immune cell infiltration in TB patients, suggesting a role of these genes in modulating immune responses during infection. Receiver operating characteristic (ROC) analysis confirmed strong predictive accuracy for the identified feature genes, with area under the curve (AUC) values exceeding 0.7. Conclusions: This study demonstrates that mitochondrial-related gene regulation influences TB susceptibility across genetic, methylation, and protein levels. The integration of multi-omics data provides valuable insight into the molecular mechanisms underlying TB, highlighting the potential of mitochondrial genes as biomarkers and therapeutic targets.

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