| Literature DB >> 34696438 |
Mohamed E Ali1, Hamada M Halby1, Mamdouh Yones Ali1, Elham Ahmed Hassan2, Mohamed A El-Mokhtar3, Ibrahim M Sayed3, Marwa M Thabet4, Magdy Fouad5, Ahmed M El-Ashmawy6, Zainab Gaber Mahran2.
Abstract
Direct-acting antivirals (DAAs) are used for hepatitis C virus (HCV) treatment. However, treatment failure and hepatocellular carcinoma (HCC) development following treatment was reported. In this study, we assessed the role of serum vitamin D, interleukin 13 (IL-13), and microRNA-135a in the prediction of treatment failure with DAA and HCC development among Egyptian HCV-infected patients. A total of 950 patients with HCV-related chronic liver disease underwent DAA treatment. Before DAAs, serum vitamin D and IL-13 were determined by ELISA, and gene expression of miRNA-135a was assessed in serum by real-time PCR. The predictive abilities of these markers were determined using the receiver operating characteristic (ROC) curve. Sustained virological response (SVR) was achieved in 92.6% of HCV-infected patients (responders). High viral load, IL-13, miRNA-135a, and low vitamin D levels were associated with treatment failure and HCC development. HCC development was recorded in non-responders, but not in the responders (35.7% vs. 0% p < 0.001). In conclusion: serum IL-13, Vitamin D, and miRNA-135a could be potential biomarkers in monitoring DAA treatment and HCC prediction. DAAs-induced SVR may decrease the incidence of HCC.Entities:
Keywords: HCC; HCV; IL-13; miRNA-135a; prognostic marker; vit D
Mesh:
Substances:
Year: 2021 PMID: 34696438 PMCID: PMC8539757 DOI: 10.3390/v13102008
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.048
Sociodemographic and clinical characteristics of the study population.
| Responders | Non Responders | Controls | |||
|---|---|---|---|---|---|
| Age | 47.83 ± 9.78 | 50.14 ± 9.5 | 49.62 ± 9.024 | 0.082 | 0.0549 |
| Sex M/F | 418/462 (47.5/52.5) | 33/37 (47.1/52.9) | 30/20 (60/40) | 0.224 | 0.99 |
| Smoking | 286 (32.5) | 20 (28.6) | 0 | <0.001 | 0.51 |
| Comorbidities | 528 (60) | 57 (81.4) | 0 | <0.001 | <0.001 |
| Severity of liver disease | 748 (85) | 26 (37.1) | 0 | <0.001 | <0.001 |
| HCC incidence | 0 | 25 (35.7) | 0 | <0.001 | <0.001 |
| IL-13 (pg/mL) | 102 ± 20.6 | 308.9 ± 113.4 | 75.2 ± 4.8 | <0.001 | <0.001 |
| miRNA-135a (fold change) | 2.1 ± 0.9 | 4.6 ± 0.7 | 1.2 ± 0.25 | <0.001 | <0.001 |
| VIT D (ng/mL) | 32.2 (2.5–71) | 12.65 (2–45) | 44.1 (30–70) | <0.001 | <0.001 |
| HCV-RNA (IU/mL) | 4.7 × 105 | 9.6 × 106 | - | - | <0.001 |
Values are presented as mean ± standard deviation (range), median (minimum-maximum) or n (%) unless otherwise indicated. p-value < 0.05 means significant. For comparison between the groups one-way ANOVA analysis or Kruskal–Wallis and Mann–Whitney or Student’s t-test is used to compare between the two groups. HCC: hepatocellular carcinoma. IL-13: Interleukin 13. Vit D: Vitamin D. Comorbidities: Hypertension, DM.
Figure 1Comparison between laboratory parameters in different patients’ groups. Comparing the laboratory parameters between the cirrhotic and non-cirrhotic patients according to the therapy response (a): IL-13. (b): miRNA-135a. (c): Vit D. Responders are represented as light grey and non-responders are represented by dark grey.
Comparison between non-responders with and without HCC.
| Non Responders without HCC | Non Responders with HCC | ||
|---|---|---|---|
| Age (years) | 49.71 ± 9.37 (32–71) | 50.92 ± 9.798 (34–69) | 0.49 |
| Sex M/F | 23/22 (51.1/48.9) | 10/15(40/60) | 0.45 |
| Smoking | 12 (26.7 %) | 8 (32 %) | 0.78 |
| Comorbidities | 34 (75.6 %) | 23 (92 %) | 0.116 |
| IL-13 (pg/mL) | 262.8 ± 106.3 | 391.8 ± 71.5 | <0.001 |
| miRNA-135a (fold change) | 4.5 ± 0.8 (2.7–6.7) | 4.8 ± 0.5 (3.7–5.67) | 0.0426 |
| VIT D (ng/mL) | 14.7 (2–45) | 11.97 (2–41) | 0.13 |
| HCV-RNA (IU/mL) | 4.6 × 106 | 1.8 × 107 | 0.002 |
Values are presented as mean ± standard deviation (range), median (minimum − maximum) or n (%) unless otherwise indicated. p-value < 0.05 means significant. for comparison as determined by Mann–Whitney tests or Student’s t-test.
Diagnostic accuracy of IL-13, miRNA-135a, and vit D to predict treatment failure and HCC with the best predictive cut offs.
| AUC (95%CI) | SE | SP | +LR | |
|---|---|---|---|---|
| (a) For prediction of DAA treatment failure | ||||
| IL-13 (>135.9 pg/mL) | 0.999 (0.998–1) | 100 | 96.1 | 25.9 |
| miRNA135a (>3.562-fold change) | 0.978 (0.968–0.989) | 97.14 | 91.59 | 11.7 |
| Vit D (<21.13 ng/mL) | 0.851 (0.807–0.895) | 82.9 | 82.7 | 4.8 |
| (b) For prediction of HCC development | ||||
| IL-13 (>249 pg/mL) | 0.992 (0.987–0.997) | 100 | 98.4 | 61.7 |
| miRNA135a (>3.66 fold change) | 0.976 (0.964–0.989) | 100 | 88.96 | 9.06 |
| Vit D (<21.04 ng/mL) | 0.872 (0.809–0.935) | 92 | 79.9 | 4.6 |
| (c) For prediction of DAA treatment failure in non-cirrhotic patients | ||||
| IL-13 (>135.9 pg/mL) | 0.998 (0.995–1.000) | 100 | 96.9 | 32.5 |
| mRNA135a (>3.562-fold change) | 0.967 (0.950–0.983) | 96.2 | 91.7 | 11.6 |
| Vit D (<24.11 ng/mL) | 0.861 (0.780–0.942) | 84.6 | 83.7 | 5.2 |
| (d) For prediction of DAA treatment failure in cirrhotic patients | ||||
| Il-13 (>166.3 pg/mL) | 1 (0.979–1.000) | 100 | 100 | - |
| mRNA135a (>3.643 fold change) | 0.985 (0.971–1.000) | 97.73 | 92.42 | 12.9 |
| Vit D (<22.5 ng/mL) | 0.657 (0.573–0.742) | 86.4 | 50 | 1.7 |
| (e) For prediction of HCC development in cirrhotic patients | ||||
| Il-13 (>232.5 pg/mL) | 0.949 (0.9184–0.9798) | 100 | 90.1 | 10.1 |
| mRNA135a (>3.643 fold change) | 0.936 (0.900–0.972) | 100 | 81.46 | 5.4 |
| Vit D (<22.5 ng/mL) | 0.6575 (0.558–0.757) | 92 | 46.4 | 1.7 |
AUC: area under the curve; CI: confidence interval; +LR: positive likelihood ratio, SE: sensitivity; SP: specificity.
Figure 2Diagnostic accuracy of IL-13, miRNA-135a and vit D to predict treatment failure and HCC with the best predictive cut offs. (a) ROC analysis to discriminate between responders and non-responders using IL-13, miRNA-135a, and vit D. (b) ROC analysis to predict the development of HCC among HCV-infected patients using IL-13, miRNA-135a, and vit D. ROC curves to predict DAA therapy failure in non cirrhotic (c) and cirrhotic patients (d) using the previous mentioned markers. (e) ROC curve to predict the development of HCC among cirrhotic patients.