Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) remains highly lethal globally, with complex pathogenic mechanisms. This study employs Mendelian randomization (MR) to investigate causal relationships between immune cells, serum metabolites, and HCC risk.

METHODS

A two-sample Mendelian randomization (2SMR) design was employed, based on large-scale genome-wide association studies (GWAS) databases, selecting single nucleotide polymorphisms (SNPs) strongly associated with immune cell features and plasma metabolites as genetic instrumental variables. The inverse variance weighted (IVW). method was primarily used for effect size estimation, with robustness verified through multiple sensitivity analysis methods including MR-Egger regression and weighted median method.

RESULTS

MR analysis revealed three immune cell subpopulations causally associated with HCC: CD127 on CD28 + CD4 + T cells (OR = 1.31, 95% CI: 1.15-1.49), unswitched memory B cell percentage (OR = 1.57, 95% CI: 1.23-2.01). Four causal serum metabolites were identified: 5-hydroxylysine (OR = 0.64), isobutyrylcarnitine (OR = 1.67), 1-stearoyl-GPC (OR = 0.27), and glycosyl-N-tricosanoyl-sphingadienine (OR = 0.32). For plasma metabolites, four metabolites were significantly associated with HCC risk: 5-hydroxylysine (OR = 0.64), isobutyrylcarnitine (OR = 1.67), 1-stearoyl-GPC (OR = 0.27), and glycosyl-N-tricosanoyl-sphingadienine (OR = 0.32).

CONCLUSION

This multi-omics approach provides evidence for causal relationships between specific immune populations, metabolites, and HCC risk, identifying potential biomarkers and therapeutic targets for HCC prevention and treatment.

MeSH

Cells, Carcinoma, Hepatocellular, Serum, Hydroxylysine, Multiple Chronic Conditions, Mendelian Randomization Analysis, Therapeutics, Random Allocation, Polymorphism, Single Nucleotide, Plasma