Identification of potential biomarkers and drug targets for meningioma by Mendelian randomisation analysis

Abstract

Background: Meningiomas exhibit high levels of heterogeneity in terms of grade, treatment, and molecular background, and there are no effective therapeutic drug treatment options. Consequently, there is an urgent need to identify new biomarkers and therapeutic targets to improve the molecular typing and prognosis of patients. Methods: This study used summary-data-based Mendelian randomisation and Bayesian co-localisation analysis based on pooled data to investigate the causal relationship between quantitative trait loci for gene expression levels in the blood and brain, and meningioma. The use of a replication cohort ensured the robustness of the results. The identified genes were further analysed using single-cell expression analysis to detect specific cell types with enriched expression and to identify potential biomarkers and targets. Results: In the primary dataset, 12 genes were identified that were significantly associated with meningioma risk. HEterogeneity In Dependent Instruments testing, co-localisation analysis, and replicating cohorts were used to ensure the robustness of the results. The expression of tetratricopeptide repeat domain 28 (TTC28) (OR = 2.03; 95 % CI = 1.60–2.57) and HscB mitochondrial iron-sulfur cluster cochaperone(HscB) (OR = 1.12; 95 % CI = 1.06–1.17) showed a significant causal relationship with meningioma risk. These genes are primarily expressed in the fibroblasts and macrophages of meningioma tissues and are considered potential therapeutic targets and biomarkers. Conclusions: This study identified several genes significantly associated with meningioma risk and provides new insights that will aid in the development of biomarkers and therapeutics for meningioma.