Blood microRNA Signatures Serve as Potential Diagnostic Biomarkers for Hepatic Sinusoidal Obstruction Syndrome Caused by Gynura japonica Containing Pyrrolizidine Alkaloids

Abstract

Background and Aims: The Gynura japonica-induced hepatic sinusoidal obstruction syndrome (HSOS) is closely related to pyrrolizidine alkaloids (PAs), and its prevalence has been increasing worldwide in recent years. However, no effective therapy for PA-induced HSOS in clinics is available, partially due to the failure of quick diagnosis. This study aims to identify blood microRNA (miRNA) signatures as potential biomarkers for PA-induced HSOS in clinics. Methods: The microarray-based miRNA profiling was performed on blood samples of the discovery cohort, which consisted of nine patients with HSOS and nine healthy donors. Differentially expressed miRNAs were further confirmed using a validation cohort, which consisted of 20 independent patients with HSOS. In addition, the rat model was established through the oral administration of the total alkaloid extract from G. japonica to investigate the association of miRNA biomarkers with the progression of HSOS. Bioinformatic analyses, including GO and KEGG enrichment, receiver operating characteristics curve, and correlation analyses were conducted to evaluate the accuracy of the potential miRNA biomarkers. Results: Three miRNAs, namely miR-148a-3p, miR-362-5p, and miR-194-5p, were overexpressed in patients and rats with PA-induced HSOS. These miRNAs were positively related to the severity of liver injury and displayed considerable diagnostic accuracy for patients with HSOS with areas under the curve over 0.87. Conclusion: In summary, this study demonstrated that three miRNAs, hsa-miR-148a-3p, hsa-miR-362-5p, and hsa-miR-194-5p, might serve as potential biomarkers for PA-induced HSOS in clinics.

Keywords: Gynura japonica; biomarker; diagnosis; hepatic sinusoidal obstruction syndrome; microRNA; pyrrolizidine alkaloids.

FIGURE 1

Flowchart of the experimental design.

FIGURE 2

Screening of the differentially expressed miRNAs in patients with PA-induced HSOS. (A), Volcano plots of miRNAs by microarray analysis. The plots were constructed by plotting -log₁₀ (FDR adjusted-p value) on the y-axis and log₂ (Fold Change) on the x-axis. Red blots represent up-regulated differentially expressed miRNAs and gray blots represent miRNAs with no significant difference. (B), PCA score plot of unique differentially expressed miRNAs. (C), Levels of eight differentially expressed miRNAs in patients with PA-induced HSOS. Data were analyzed by Student’s t test and expressed as mean ± SD (n = 9 in healthy donors, n = 9 in cohort 1, and n = 20 in cohort 2). *p < 0.05, **p < 0.01, ***p < 0.001 vs. healthy donors.

FIGURE 3

ROC curve analysis for the discrimination between healthy donors and patients with PA-induced HSOS by the three miRNA biomarkers.

FIGURE 4

Gene enrichment and pathway analysis of miRNAs target genes. Co-expression networks of angiogenesis-associated genes and co-regulated miRNAs.

FIGURE 5

Time-dependent analysis in liver injury and plasma coagulation index levels in rats. Sprague-Dawley rats were orally administered TA at a dose of 120 mg/kg. The rats were euthanized at 0.04, 0.13, 0.5, 1, 2, and 7 days after the administration, and the blood was then collected for analysis. (A), Representative image of hematoxylin and eosin staining of livers (10×). Scale bar, 50 μm. (B), PPAs contents in serum. (C), Serum ALT and AST activities. (D), PT, FIB, and TT levels. (E), Expression levels of miR-148a-3p, miR-362-5p, and miR-194-5p. Data were analyzed by one-way ANOVA and expressed as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001 vs. CTRL group.