ArticleFrontiers in oncology2024
The role of blood metabolites in oral cancer: insights from a Mendelian randomization approach.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Plasma acylcarnitine dysregulation associated with CPT1-mediated metabolism contributes to oral carcinogenesis.Scientific reports · 2026Article
- Metabolomic analysis for diagnosis of oral squamous cell carcinoma using machine learning.Discover oncology · 2026Article
- Exploring Metabolic and Immunological Biomarkers for Oral Squamous Cell Carcinoma: Potential Targets for Precision Therapy.Biology · 2025Review
- Toxic effects of Helix aspersa snail egg hydrolyzates obtained by static in vitro digestion on Caco-2 colorectal adenocarcinoma cells.Scientific reports · 2025Article
- Metabolic reprogramming in saliva of mice treated with the environmental and tobacco carcinogen dibenzo[def, p]chrysene.Scientific reports · 2024Article
- Causal links of human serum metabolites on the risk of prostate cancer: insights from genome-wide Mendelian randomization, single-cell RNA sequencing, and metabolic pathway analysis.Frontiers in endocrinology · 2024Article
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Authors and funding
9 authors.
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Abstract
Aim: This research aimed to explore the causal impact of blood metabolites on oral cancer using a two-sample Mendelian randomization (MR) analysis. The study endeavored to identify potential biomarkers for oral cancer's clinical management. Materials and methods: Based on the large individual-level datasets from UK Biobank as well as GWAS summary datasets, we first constructed genetic risk scores (GRSs) of 486 human blood metabolites and evaluated the effect on oral cancer. Various statistical methods, including inverse variance weighted (IVW), MR-Egger, and weighted median, among others, were employed to analyze the potential causal relationship between blood metabolites and oral cancer. The sensitivity analyses were conducted using Cochran's Q tests, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. Results: 29 metabolites met the stringent selection criteria. Out of these, 14 metabolites demonstrated a positive association with oral cancer risk, while 15 metabolites indicated a protective effect against oral cancer. The IVW-derived estimates were significant, and the results were consistent across different statistical methodologies. Both the Cochran Q test and the MR-Egger intercept test indicated no heterogeneity and pleiotropy. Conclusion: This MR study offers evidence of the role specific blood metabolites play in oral cancer, pinpointing several with potential risk or protective effects. These findings could be helpful for new diagnostic tools and treatments for oral cancer. While the results are promising, additional research is necessary to fully validate and refine these conclusions. This study serves as a foundational step towards more comprehensive understandings in the future.
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