Mendelian randomization analysis of inflammatory biomarkers and hepatocellular carcinoma risk: genetic causality and single-cell transcriptomics - GuangXin Shao; Xiao Yun; Hongyue Xie; Beicheng Sun (Discover Oncology)
Abstract Background The causal relationship between inflammatory biomarkers and hepatocellular carcinoma (HCC) risk remains unclear. This study aimed to investigate the causal associations between various inflammation-related biomarkers and HCC risk using Mendelian randomization (MR) analysis, complemented by single-cell transcriptomic validation. Methods We conducted comprehensive MR analyses using multiple statistical approaches including MR Egger, weighted median, inverse variance weighted, weighted mode, and simple mode methods to evaluate causal relationships between inflammatory biomarkers and HCC risk. Over 20–30 single nucleotide polymorphisms (SNPs) were employed as instrumental variables for each biomarker. Single-cell RNA sequencing data from four HCC samples (BT1306, BT1307, scrSOL004, scrSOL006) were analyzed to validate findings through cellular heterogeneity analysis, cell-cell communication networks, and pathway enrichment analysis. Results MR analysis identified differential causal effects of inflammatory biomarkers on HCC risk. Protective factors included CCL7 (OR: 0.524–0.714), CCL11 (OR: 0.660–0.752), IFN-gamma (OR: 0.657), NT-3 (OR: 0.520), and TWEAK_TNFSF12 (OR: 0.804), suggesting these factors may reduce HCC risk through immune modulation. Conversely, risk factors comprised CASP-8 (OR: 1.530), CD5 (OR: 2.079), FGF-21 (OR: 2.052), and CCL2 (OR: 2.440), with CCL2 showing the strongest pathogenic association. Single-cell analysis successfully identified 29 distinct cell subpopulations and revealed complex intercellular communication networks involving MIF, MK, and ncWNT signaling pathways. CCL2 and CCL8 demonstrated significant positive correlation (r = 0.4362, p < 0.001) across multiple cell types, with fibroblasts and malignant cells serving as central communication hubs. Conclusions This study provides robust genetic evidence for causal relationships between specific inflammatory biomarkers and HCC risk through MR analysis.