ArticleJournal of personalized medicine2024
Identifying Proteins and Amino Acids Associated with Liver Cancer Risk: A Study Utilizing Mendelian Randomization and Bulk RNA Sequencing Analysis.
Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Blood-based obesity biomarkers and their relevance for disease risk.Nature reviews. Endocrinology · 2026Review
- Advancing liver cancer diagnosis and treatment with multi-omics approaches: a systematic review.Discover oncology · 2025Review
- Association between metabolites and hepatocellular carcinoma: findings from a two-sample Mendelian randomization study.Journal of liver cancer · 2025Article
- Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPrimary liver cancer (PLC) ranks third in terms of fatality rate among all malignant tumors worldwide. Proteomics and metabolomics have become widely utilized in identifying causes and diagnostic indicators of PLC. Nevertheless, in studies aiming to identify proteins/metabolites that experienced significant changes before PLC, the potential impact of reverse causation and confounding variables still needs to be fully addressed.
methodsThis study thoroughly investigated the causal relationship between 4719 blood proteins, 21 amino acids, and the risk of PLC using the Mendelian randomization (MR) method. In addition, through a comprehensive analysis of the TCGA-LIHC cohort and GEO databases, we evaluated the differentially expressed genes (DEGs) related to serine metabolism in diagnosing and predicting the prognosis of patients with PLC.
resultsA total of 63 proteins have been identified as connected to the risk of PLC. Additionally, there has been confirmation of a positive cause-effect between PLC and the concentration of serine. The integration of findings from both MR analyses determined that the protein associated with PLC risk exhibited a significant correlation with serine metabolism. Upon careful analysis of the TCGA-LIHC cohort, it was found that eight DEGs are linked to serine metabolism. After thoroughly validating the GEO database, two DEGs, TDO2 and MICB, emerged as potential biomarkers for diagnosing PLC.
conclusionsTwo proteins involved in serine metabolism, MICB and TDO2, are causally linked to the risk of PLC and could potentially be used as diagnostic indicators.
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Registered trials
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