Introduction

Protein Induced by Vitamin K Absence or Antagonist-II (PIVKA-II) is regarded as a diagnostic marker for hepatocellular carcinoma (HCC). However, the optimal cut-off level for HCC diagnosis is not precisely defined, and it depends on the assay used as well as on the etiology and the stage of the underlying liver disease.^1,2

Aims & Methods

The aim of this study was to assess PIVKA-II levels in patients with different stages of chronic liver disease without signs of malignancy. Laboratory data of 69 patients were analyzed (69.5% male, median age 58 years). The serum PIVKA-II concentrations were determined using the Elecsys PIVKA-II immunoassay (Roche Diagnostics, Mannheim, Germany). The cut-off level set by the manufacturer was <31.2 μg /L. Patients were divided into three groups: decompensated cirrhosis (N=24), compensated cirrhosis (N=20), no signs of liver fibrosis (N=25). Kruskal-Wallis test with post-hoc analysis was used to compare the groups. Correlations between PIVKA-II levels, bilirubin, INR and MELD-Na score were described by Spearman`s rank correlation coefficients (ρ). The values P ≤ 0.05 were considered statistically significant.

Results

Concentrations of PIVKA-II were significantly higher in patients with decompensated cirrhosis (median 245 μg/L, IQR 102.5-485.5) when compared to patients with compensated cirrhosis (median 35.1 μg /L, IQR 17.4-342) and patients without signs of liver fibrosis (median 25.6 μg /L, 17.2-110) (P=0.0008). A statistically significant correlation was found between the concentrations of PIVKA-II and total bilirubin (ρ = 0.576 (95% CI: 0.326-0.750), P=0.0001), INR (ρ = 0.471 (95% CI:0.191-0.680), P=0.0019) and calculated MELD-Na score (ρ = 0.483 (95% CI:0.205-0.688), P=0.0155).

Conclusion

Elevated PIVKA-II concentrations, well beyond the cut-off levels proposed by the manufacturer, may be seen in benign liver disease. Correlations with bilirubin, INR and MELD-Na suggest that higher PIVKA-II concentrations can be expected in more severe forms of chronic liver disease.

References

1. Kim DY, Toan BN, Tan CK, Hasan I, Setiawan L, Yu ML et al. Utility of Combining PIVKA-II and AFP in the Surveillance and Monitoring of Hepatocellular Carcinoma in the Asia-Pacific Region. Clin Mol Hepatol. 2023 Jan 30.
2. Qian XJ, Wen ZM, Huang XM, Feng HJ, Lin SS, Liu YN et al. Better performance of PIVKA-II for detecting hepatocellular carcinoma in patients with chronic liver disease with normal total bilirubin. World J Gastroenterol. 2023 Feb 28;29(8):1359-1373.

Introduction

Hepatocellular carcinoma (HCC) is an end stage liver disease with increasing morbidity and mortality worldwide. Development of the disease is dependent on various genetic, dietary and environmental factors. While alcohol-related liver disease (ALD/MetALD) remains a major contributor, metabolic dysfunction-associated steatotic liver disease (MASLD) is becoming increasingly relevant in clinical practice. There is increasing evidence for the role of bacteria, for instance, such as Bifidobacterium and Blautia, which were considered protective, while Streptococcus has been associated with disease progression. However, little is known about the alteration of microRNAs (miRNAs) in liver diseases and its interrelationship with microbial environment in view of etiological factors.

Aims & Methods

This study aimed to elucidate gastrointestinal miRNA alterations and explore their relationship with microbiome composition in patients with different stages of liver disease in terms of disease etiology. Multi-omics analyses were performed in a subset of well characterized patients (n=59) with liver disease and healthy controls. Systematic characterization included clinical, laboratory, demographic and imaging characterization and dietary preferences. Patients subclassification included fibrosis stage (no fibrosis, fibrosis, liver cirrhosis(LC)) and etiology (MetALD/ALD vs. MASLD). Fecal miRNAs were extracted using the Qiagen miRNeasy Kit and profiled via Agilent miRNA microarray. Microbiome analyses were performed amplifying the V1-V2 region of the 16S rRNA gene following Illumina sequencing.

Results

For miRNA analysis stringent criteria were applied to identify high quality miRNA targets. From approximately 4,000 candidates filtering resulted in selection of 202 high-quality miRNAs with reliably measurable concentrations. 28 of these miRNAs showed significantly positive alterations in concentration in patients with liver disease and 7 miRNAs significant negative alterations. Specifically, miR-642a-3p, miR-5006, miR-6781, and miR-6849 were elevated in feces in patients with LC. In contrast, miR-6869, miR-4467, and miR-5001 were present in lower concentration in LC patients. Notably, miR-4467 also showed strong negative associations with liver-specific laboratory markers, including gamma-glutamyl transferase (GGT) (r=-0.34; p=0.026) and M65, a marker of apoptosis (r=-0.42; p=0.005). Cross-sectional comparison of miRNA and microbiome data revealed miRNA alterations associated with specific microbial signatures. MiR-6795-5p, which was associated with liver stiffness (r = 0.39, p = 0.01), also correlated positively with the abundance of Streptococcus, a genus linked to disease progression (r=0.29; p=0.047). Conversely, miR-6869, miR-4467, and miR-5001 showed positive correlations with the potentially protective genera Blautia and Bifidobacterium (miR-6869: r_{Bifidobacterium}=0.35; p_{Bifidobacterium}=0.012; r_Blautia=0.37; p_Blautia=0.008; miR-4467: r_Blautia=0.41; p_Blautia=0.002; miR-5001: r_Blautia=0.38; p_Blautia=0.006).

Conclusion

Multi-omics analysis reveals distinct alterations in fecal miRNAs and gut microbiota across different stages of liver disease. Changes in microbial composition were associated with shifts in miRNA profiles, suggesting a functional link in maintaining intestinal homeostasis. These findings highlight the potential of integrated microbiome–miRNA signatures as novel diagnostic and therapeutic targets. Further studies are warranted to validate these associations and explore their clinical applications.