Skip to main content
Journal of Genetic Engineering and Biotechnology
Download PDF

Recognition of 7 genes signature (Cirrhosis Risk Score) in the diagnosed non-responders to DAAs therapy by intra-PBMCs nested HCV RNA PCR

Journal of Genetic Engineering and Biotechnology volume 21, Article number: 89 (2023) Cite this article

Abstract

Background and aims

Predictors of chronic HCV response to oral antiviral therapy (OAT) are related to host genetic variations. Single nucleotide polymorphisms (SNP) and alleles variations of host genes in association with hepatic fibro-cirrhotic changes have a distinct role in OAT outcomes. The current research evaluated the association of Cirrhosis-Risk-Scores (CRS) values, based on the correlation of seven genes signature-SNPs, with sonographic liver parenchymal changes in determining OAT outcomes.

Methods

All study subjects (n = 54) were recruited three months after completing OAT and classified into three groups. Group I (n = 21) had negative HCV PCR, group II (n = 17) showed positive solitary intra-PBMCs HCV infection, and group III(n = 16) was serum HCV RNA PCR-positive. All study-population were subjected to examination by hepatic-ultrasound (US), FIB-4-scoring, and screening for 7 gene-signature that addressed CRS values as low, intermediate, and high depending on gene SNPs identification.

Results

Group I showed a significant association with low CRS values compared to other groups (P < 0.001). Solitary intra- PBMCs HCV infection in group II was significantly combined with intermediate CRS values in comparison to groups I and III (P < 0.001). The high CRS values were significantly found in group III when compared to groups I and II (P < 0.01). On US imaging, low CRS values were common in normally appeared hepatic parenchyma (P < 0.001) and high CRS values were frequent in coarse-liver (P < 0.001), while bright-liver-tissues appearance was mainly detected in the intermediate CRS category (P = 0.09). On FIB-4 scoring, high CRS value were associated with hepatic fibro-cirrhosis compared to intermediate (P < 0.001) and low (P = 0.08) CRS-categories.

Conclusion

The current study concluded the association of (a) high CRS values with coarse liver in viral-RNA serologic relapse, (b) low CRS values with normal liver tissues in sustained virologic response (SVR), (c) intermediate CRS values with bright liver in solitary PBMCs relapse.

Introduction

There are conflicting reports regarding positive, negative, inconclusive, and denied association of certain gene SNPS and/or alleles with chronic HCV induced hepatic cirrhosis in different populations worldwide [1, 2]. On the other hand, direct-acting antivirals (DAAs) have markedly improved resistance to chronic HCV treatment and offered a unique chance to evaluate roles of host genetics that may participate in inducing hepatic fibro-cirrhotic changes as well as response to therapy [3, 4].

In chronic naive and post-treatment HCV RNA seropositive patients, evaluation of infection risk factors, as well as the correlation of infection courses with host immune-pathologic changes and treatment outcomes, are convenient tasks [5, 6]. On the other hand, diagnosing active chronic HCV infection in the RNA-seronegative population has been a challenge until developing cellular PCR that addressed intra-hepatocytes and intra-PBMCs RNA detection in both cryptogenic and occult viral infection [7, 8]. Grading of active hepatic tissues fibro-cirrhotic changes was addressed in chronic HCV infection in viremic patients and in solitary intracellular viral infections (who had negative serum viral RNA PCR) [6, 7]. Progressive fibro-cirrhotic liver tissues changes were found to be associated with solitary intra-bone marrow mononuclear cells (BMMCs) and intra-peripheral blood mononuclear cells (PBMCs) HCV infections with increasing hepatic-cirrhosis grades on the presence of HCV RNA viremia (positive serum PCR) [publication in progress].

The improving US resolution quality, the affordable overhead coast (reasonable machine price and the average screening time per patient), and the well-trained experienced operators’ availability make US screening more convenient and clinically applicable in both inpatient and outpatient clinics. Combining US image with Fibroscan in evaluation of hepatic parenchymal changes added more help in fibro-cirrhotic grading before and after treatment of chronic HCV infection. The results of both procedures (US and Fibroscan) in detecting and grading liver tissues changes are comparable to a considerable extent and enabled researchers to use one of them with satisfactory outcomes. The recognized absent hepatic tissue changes, bright liver parenchyma, and coarse hepatic surface by the US are respectively corresponding to normal (up to 5 kPa), up to moderate fibrosis (more than 5 but less than 15 kPa), and cirrhosis (≥ 15 kPa) by Fibroscan [9]. FIB-4 scoring is a biochemical-dependent scoring system that evaluates hepatic tissue changes and confirms the above-mentioned liver tissue grading by US [8, 10]. Sequelae of chronic HCV infection are variable among different hosts; they show no, slow, intermediate, and rapid progress in years or even decades to fibro-cirrhotic changes in liver tissues [11]. Several variables have been identified in cross-sectional and longitudinal studies that influence outcomes of chronic HCV infection. Environmental and host factors have major impacts on the progressive course of liver cirrhosis, while HCV genotype and blood loads of viral particles show minor effects [12, 13]. Host factors include male gender [14] and age of the subject at the time of infection [15], in addition to the presence of immunocompromising disorders and metabolic disease syndrome, particularly type II diabetes; all are associated with evident progressive liver disease [16, 17].

The available texts describe the association of liver tissue fibro-cirrhosis progression in chronic HCV infection with many single-nucleotide polymorphisms (SNP) in the genes encoding for IFN, TNF, interleukin-10, low-density lipoprotein, factor V Leiden, and the monocyte chemotactic protein 2 [13, 18,19,20]. In 2007, Huang et al. [21] addressed seven gene variant signatures known as cirrhosis risk scores (CRS) that are elaborated in association with hepatic cirrhosis in chronic HCV infection. High CRS scores that are derived from logarithms based on a constellation of seven SNPs showed a positive predictive value of 82% to 96% in diagnosing liver cirrhosis. A longitudinal study (follow-up for at least 60 months) was conducted to evaluate the prognostic value of the CRS seven-gene signature in chronically infected HCV patients who presented with no to minimal hepatic fibro-cirrhotic changes. The study concluded that host genetics, as defined by CRS, predicted hepatic fibrosis occurrence and progression in males with initially mild chronic HCV infection. The study expressed the probability of the CRS seven-gene signature to become a useful indicator for prognostic evaluation and may be for treatment decisions [22, 23]. Evaluation of host CRS seven gene signature in chronic HCV induced hepatic fibro-cirrhotic changes of SVR in addition to post-treatment serum and solitary cellular viral relapses is the target of the current research.

Methods and subjects

Patients

This study was carried out et al.-Azhar university hospitals on 54 patients who received HCV treatment (400 mg Sofosbuvir plus 60 mg Daclatasvir) with or without ribavirin (up to 1200 mg according to body weight). All patients were submitted to both serum and PBMCs HCV SRT-PCR 3 months after completing OAT. Patients were classified into three groups: (a) group I: 21 patients who had negative serum and PBMCs SRT-PRCs, (b) group II: 17 patients had positive solitary PBMCs-PCR, negative serum SRT-PCR, (c) group III: 16 patients presented with positive serum HCV-RNA and intra-PBMCs -RNA by SRT-PCR.

Ethics

The authors have no conflicts of interest related to this research. All procedures performed in the current work that involved human participants were in accordance with the ethical standards of the institution and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the current study.

Detection of HCV RNA in serum and PBMCs by SRT-PCR

Extraction of RNA from PBMCs

Peripheral blood (200 μL) was diluted with 10 mL of freshly prepared red blood cell alkaline buffer (38.8 mmol/L NH4Cl, 2.5 mmol/L K2HCO3, 1 mmol/L EDTA pH 8.0). After 10 min incubation at room temperature, the nucleated cells were washed with the same buffer and lysed in 500 mL anti-nuclease solution (4 mol/L guanidinium isothiocyanate containing 25 mmol/L sodium citrate, 0.5 sarcosyl and 0.1 mol/L ß-mercaptoethanol). A single step method previously described [24, 25] and subsequently modified [26] was fused to extract RNA.

Detection of both sense and antisense strands of HCV RNA

Briefly, the reaction mixture (50 μL) contained 400 ng of cellular RNA, RT-PCR bead (HVD), 50 pmol from each of the primers (1CH, P2, and 2CH) for amplification of the sense strand, or 50 pmol from P2 and 75 pmol from 2CH for antisense strand and 20 U of AMV reverse transcriptase. The mixture was incubated at 42 °C for 1 h and denatured for 15 min at 94 °C. Amplification of cDNA First-round PCR was performed in a thermal cycler for 30 cycles (94 °C for 1 min, 55 °C for 1 min, and 72 °C for 1 min). Nested PCR amplification was like the first-round PCR except for using 10 μL from the first PCR and two nested primers (P3 and P4) and 2 U Taq DNA polymerase. To assure the specificity of the assay two controls were employed: C1, ddH2O instead of RNA in the cDNA synthesis reaction to exclude RNA contamination; C2, PCR step with only F1 or R1 to exclude mixed primer contamination. In all conditions, the two controls provided negative amplification; special attention was paid to heat inactivating the reverse transcriptase at 95 °C for 1 h to reduce false detection of the antisense strand before adding the forward strand. Primer sequences used included below Primers used for PCR. Primer Sequences: 1CH 5-ggtgcacggtctacgagacctc-3′; 2CH 5 aactcatgtcttcacgcagaa-3; P2 5-tgctcatggtgcacggtcta-3′ P3; 5-ctttcgcgacccaacactac-3′; P4 5-agagccatagtggtctgcgg-3’ [6, 26].

Correlation of ultrasonography (US) image with FIB-4 score

Chronic HCV induced parenchymal changes of the liver were examined by US image and were correlated with FIB-4 scoring system in all study populations. US images were classified into undetectable, bright, and coarse hepatic parenchyma. These three categories were correlated with the corresponding values of the FIB-4 score. The latter was calculated according to an equation that depends on liver function tests, platelets count and age of the patient: (Age X AST)/(platelet count) X [√ (square root) ALT]. The FIB-4 score ranges were segregated as follows: (a) low: < 1.45 corresponds to F0-F1, (b) intermediate: 1.45–3.25 equals to F2–F3, (c) high: > 3.25 is the same as F4 [10].

CRS genotyping (7 gene screening)

The 7 gene SNPs identified previously by Huang et al. [21] were genotyped using real-time PCR protocol based on the pre-validated TaqMan MGBTM probe for allele discrimination assay (Applied Bio systems). Briefly, 1.25 μL of a × 40 combined primer and probe mix (ABI/Life Technologies, USA) was added to 12.5 μL of 2 × TaqMan® Universal PCR master mix (ABI/Life Technologies, USA) in a 25-μL final volume of DNase/RNase free water (Invitrogen/ Life Technologies, USA) & template. The cycle conditions were 95 °C for 10 min, 95 °C for 15 s, and 60 °C for 1 min. The last two steps were repeated 40 times. The PCR run was performed on Rotor-Gene real-time PCR system (Qiagen, Santa Clarita, CA). Allelic discrimination plots were produced in Statistical Package for The Social Sciences.

Table 1 illustrates that each SNP can take the value 0 or 1 based on the obtained genotype, and then, each value has two probabilities (assuming that the patient can be cirrhotic or non-cirrhotic). Each SNP was calculated independently of other SNPs. The values obtained from Table 1 were substituted in the following Naive Bayes formula:

Table 1 CRS algorithm deduced by Huang et al.
Full size table
$${\left(\mathrm{CRS}\right)}=\frac{0.626\;\mathrm{ X\;p}\left(\mathrm{s}/\mathrm{ cirrhosis}\right)}{0.626\;\mathrm{ x\;p }\left(\frac{\mathrm{s}}{\mathrm{cirrhosis}}\right)+0.374\;\mathrm{ x\;p }(\frac{\mathrm{s}}{\mathrm{no}}\mathrm{cirrhosis})}$$

Statistics

The collected data were analyzed using appropriate tests. Continuous variables were expressed in mean and standard deviation, while ordinal and nominal categorical data were described as number and percentage. The Statistical Program for Social Science (SPSS) version 18.0 was used to analyze the current data. A one-way analysis of variance (ANOVA) when comparing between more than two means. Chi-square (X2) test of significance was used to compare proportions between two qualitative parameters. P value < 0.05 was considered significant.

Results

Outcomes of DAAs therapy in relation to HCV-PCR results in the studied populations

Table 2 showed the outcomes of DAAs treatment (SOF + DAC versus SOF + DAC + RBA) in the studied population. There was a significant success of the SOF Plus DAC regimen without relapse in group I compared to groups II and III (P < 0.001). The difference in success rates on using the same regimen was insignificant on comparing group II with III (P = 0.42).

Table 2 Comparison of DAAs therapeutic regimens outcomes in all study population
Full size table

Grading of cirrhosis risk score (CRS) in relation to HCV-PCR results after DAAs therapy in all study groups

The cirrhosis risk score (CRS) grading results were demonstrated in Table 3. The CRS had significant frequencies of low grades (< 0.5) in post-treatment negative HCV-PCR populations (group I) in comparison to cases with either solitary positive cellular viral-RNA PCR (group II) or positive serum PCR (group III) (P < 0.001). On the other hand, the intermediate CRS values (ranging from 0.5 to 0.7) showed significant association with solitary HCV intracellular infection (group II) compared to positive serum viral PCR group III (P < 0.005), but insignificant changes in comparison with infection-free group I (P = 0.36). Viremic patients with positive HCV-RNA serology in group III showed a significant association with high CRS values (> 0.7) when compared with either SVR group I (P < 0.001) or solitary intracellular HCV infection in group II (P < 0.001). At the same time, solitary intracellular HCV infection showed a significant association with high CRS values in comparison with infection-free subjects in group I (P < 0.001).

Table 3 Comparison of CRS score values (low, intermediate, and high) among the three studied groups
Full size table

Association of various CRS values with hepatic parenchymal changes as defined by FIB-4 score

As illustrated in Table 4, the intermediate values of CRS were frequently associated with normal ranges of FIB-4 scores compared to both low (P = 0.06) and high CRS values (P = 0.005). On the other hand, high CRS values were seen more often in hepatic fibro-cirrhotic changes compared to normal (P = 0.08) and intermediate (P < 0.001) CRS values.

Table 4 Correlation of cirrhosis risk score (CRS) values with grades of liver tissue changes by FIB-4-Scores
Full size table

Correlation of CRS values with liver parenchymal fibro-cirrhotic changes as recognized by ultrasound (US)

Table 5 addressed the association of low, intermediate, and high CRS values with normal, fibrotic, and cirrhotic liver parenchyma defined by the US. Over 90% of low CRS values were present in populations with normal US images; P = 0.06 and < 0.001 on comparison with intermediate and high CRS values respectively. There was also a significant association of intermediate CRS values with normal liver image by the US compared to the same association with high CRS values P < 0.001). The early hepatic fibro-cirrhotic changes (bright liver by the US) were equally distributed within the three categories of CRS values (P > 0.05). On the other hand, high CRS values were significantly associated with liver cirrhosis by the US in comparison with either low or intermediate CRS values (P < 0.001).

Table 5 Association of CRS score values with grades of hepatic parenchymal changes by US imaging in all groups
Full size table

Discussion

The studied population in the current research are recruited three months after completing oral antiviral therapy (OAT) for 12 weeks. All study populations are tested by both serum and PBMCs HCV-PCR as well as screening by both hepatic US and FIB-4 scoring system. They are segregated into subjects with sustained virologic response (SVR) (group I), solitary intracellular HCV-RNA infection with negative serum viral PCR (group II), and patients with positive serum HCV-PCR (group III). Association of oral antiviral therapy (OAT) outcomes and seven gene signatures (SNPs dependent) presented as cirrhosis risk score (CRS) values with different grades of hepatic parenchymal changes is tested in the currently studied small numbers of populations as a pilot study. CRS scores are categorized into low (< 0.5), intermediate (from 0.5 to 0.7), and high (> 0.7) values. The association of each CRS category with normal, bright, and coarse liver parenchyma in SVR, solitary intracellular HCV infection and viral RNA seropositive patients is addressed by the illustrated research above.

Outcomes of OAT in association with specific host genes variants results in chronic HCV infection are still debatable because of variation in the diagnostic procedures used to address SVR, probabilities of viral relapses, and differentiation of resistance to OAT from actual HCV-RNA serologic relapse [8, 27, 28]. Post-treatment persistence of intracellular HCV infection is considered viral relapse and/or resistance to antiviral therapy as it is followed later by viral RNA seroconversion [6, 29,30,31]. Different patterns of SNPs distribution are identified when specific human genes are sequenced, which effectively play distinct roles in determining treatment outcomes that have been based solely on screening for serum HCV-PCR [1, 4, 21, 22]. However, pending cases of serologic HCV relapse are expected when negative serum HCV-PCR is associated with the positive intracellular viral infection. Genotyping of these cases (pending HCV serologic relapse) to address SNPs during host genes sequencings are targeted in the current research. Correlating host genes typing results of the pending relapse populations with hepatic fibro-cirrhosis grades showed the dominance of persistent solitary intracellular HCV infection in intermediate CRS values. The stationary status of bright hepatic parenchyma with a lacking ability to progress into cirrhosis or regress back to normal liver tissues is explained by not only the relationship to duration of infection but also to variations in host genetic constituent. So, the bias of a hidden intracellular viral infection that would end up with both unexpected serologic relapse and upgrading of hepatic fibro-cirrhotic changes [6, 29,30,31] can be minimized by the appropriate management of solitary intra-cellular HCV infection.

In addition, the broad-spectrum use of ultra-sonographic (US) images worldwide in intra-abdominal solid organs evaluation is attributed to the improving high-quality resolution because of advanced technology, affordable cost on comparing reasonable machine price with the average screening time per patient, and availability of the well-trained experienced operators. These advantages make the US screening procedure one of the most convenient and attractive methods to implement everywhere for liver tissue screening before and after OAT. Adding scanning of hepatic parenchyma by fibroscan to the US image has refined the differentiation of cirrhosis from fatty infiltration in addition to fine grading of both conditions. Fortunately, results from both imaging procedures (US and Fibroscan) in detecting and grading hepatic parenchymal changes are conclusively comparable to the degree that enable researchers to use them either complimentary or singular with dependable satisfactory outcomes. The reported no hepatic tissue changes, bright hepatic parenchyma, and coarse liver surface by US are respectively corresponding to normal [up to 5 kPa], mild to moderate fibrosis (> 5 but < 15 kPa), and cirrhosis (15 kPa or above) by Fibroscan [9]. The FIB-4 scoring system is a biochemical dependent evaluation of hepatic parenchymal changes that is usually used to confirm the above-mentioned liver tissue changes by the US [10]. Accordingly, the use of US in the evaluation of hepatic parenchymal changes in the current research is justified upfront in literature by data from Fibroscan grading and currently by the results from the FIB-4 scoring system. Therefore, the convenience of affordability and reliability of the US image is much appreciated at baseline and follow-up evaluation of hepatic parenchymal changes on the application of well-defined interventions that require correlation with various host-related immunogenetic factors.

The Association of CRS changes in chronic HCV infection with hepatic parenchymal fibro-cirrhotic changes is demonstrated in several studies [21, 32]. Moreover, the high CRS score [33]. The current research studies the relationship between various CRS values (low, intermediate, and high) and outcomes of OAT in chronic HCV infection. Fortunately, in this study, OAT outcomes are defined as SVR when both serum and cellular HCV PCR are negative, while viral relapses are diagnosed when viral RNA and/or its remnant are found in either serum and/or PBMCs [6, 29,30,31]. So, probabilities of the unpredictable infectious agents such as hidden intracellular viral genomic materials (pending viral relapse) to bias the currently elaborated data and their subsequent conclusions are wearing thin. It is obvious in the current data set that proving hepatic tissue fibro-cirrhotic changes by liver US and/or FIB-4 score calculation is crucial to interpret the association of various levels of CRS values with (a) complete elimination of HCV particles from serum and cells, (b) persistent intracellular viral infection without serologic relapse, (c) fully blown HCV serologic relapse. It is currently reported that (1) SVR, as indicated by viral infection-free serum and cells, are associated with low values of CRS (< 0.5) when liver tissues appear normal by US. (2) Serologic relapse with positive serum HCV-PCR is associated with high CRS-values (> 0.7) when live tissues are cirrhotic (coarse by US). Both findings are in full agreement with the previous studies [21, 34]. The association of intermediate values of CRS with solitary intracellular HCV-RNA detection in the early fibrotic liver (bright appearance by the US) is a novel finding that is supported by IL28B gene sequencing in previous studies from our lab [35]. The interpretation of this finding may be related to variations in the genetic construction of the host that plays a significant role in HCV infection outcomes. However, clearance of post-OAT intracellular HCV remaining antigenic positive or replicative negative strands by the continuation of OAT therapy for a longer duration than the anticipated time in the primary therapeutic protocol [36] may indicate the iatrogenic origin of this phenomenon. Extension of this study should be performed on larger sample size to prove this finding.

Conclusion

The current study addressed the following: (a) high CRS values are present in liver cirrhosis (coarse liver by the US) when serum HCV-PCR is positive, (b) low CRS values are found in normally appeared liver tissues by the US when both serum and cellular HCV PCR are negative, (c) Intermediate CRS values are recognized more often in early fibrotic changes (bright liver by the US) in association with solitary intra-PBMCs HCV-RNA infection. So, we recommend correlating cirrhosis risk score (CRS) values with ultrasonographic patterns of hepatic parenchyma before oral antiviral therapy (OAT) as predictors for treatment outcomes in chronic HCV infection.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Abbreviations

CHIKV:

Chikungunya virus

OAT:

Oral antiviral therapy

CRS:

Cirrhosis Risk Score

HCV:

Hepatitis C virus

DAAs:

Direct-acting antivirals

US:

Ultrasound

PBMCs:

Peripheral blood mononuclear cells

FIB-4:

Fibrosis scoring system

IFN:

Interferon

TNF:

Tumor necrosis factor

SVR:

Sustained-virologic-response

PCR:

Polymerase chain reaction

SNPs:

Single-nucleotide polymorphisms

References

  1. Falleti E, Bitetto D, Fabris C, Cussigh A, Fornasiere E, Cmet S et al (2011) Role of interleukin 28B rs12979860 C/T polymorphism on the histological outcome of chronic hepatitis C: Relationship with gender and viral genotype. J Clin Immunol 31:891–899. https://doi.org/10.1007/s10875-011-9547-1

    Article  Google Scholar 

  2. Marabita F, Aghemo A, de Nicola S, Rumi MG, Cheroni C, Scavelli R et al (2011) Genetic variation in the interleukin-28B gene is not associated with fibrosis progression in patients with chronic hepatitis C and known date of infection. Hepatology 54:1127–1134. https://doi.org/10.1002/hep.24503

    Article  Google Scholar 

  3. Papastergiou V. Current status and emerging challenges in the treatment of hepatitis C virus genotypes 4 to 6. World J Clin Cases 2015;3:210. https://doi.org/10.12998/wjcc.v3.i3.210

  4. Coppola N. Role of genetic polymorphisms in hepatitis C virus chronic infection. World J Clin Cases 2015;3:807. https://doi.org/10.12998/wjcc.v3.i9.807

  5. ABD ALLA MDA, EL-DESSOUKY YMM, ABDEL-HAMID MR, ZAIN EL-DEEN ANA. Prevalence of HCV infection among health care employee at Al Azhar University hospitals in Cairo, Egypt. J Egypt Soc Parasitol 2017;47:459–66. https://doi.org/10.21608/jesp.2017.77516

  6. Abd Alla MDA, El Awady MK, Dawood RM, Elhawary MA, Al-Azhari SS, Galal ASGM (2018) Hepatitis C virus serologic relapse after treatment with direct-acting antivirals is dependent on viral RNA levels in peripheral blood mononuclear cells and the grade of liver cirrhosis. Arch Virol 163:2765–2774. https://doi.org/10.1007/s00705-018-3922-7

    Article  Google Scholar 

  7. Dawood RM, el-Meguid MA, Ibrahim MK, Bader El Din NG, Barakat A, El-Wakeel K, et al. Dysregulation of fibrosis related genes in HCV induced liver disease. Gene 2018;664:58–69. https://doi.org/10.1016/j.gene.2018.04.032

  8. Abd Alla MDA, Dawood RM, Rashed HAEH, Farrag G, Ammar IAE, Mahmoud MMAH et al (2021) Treatment of hepatitis C virus infection with direct-acting antivirals plus ribavirin eliminates viral RNA from peripheral blood mononuclear cells and reduces virologic relapse in diverse hepatic parenchymal changes. Arch Virol 166:1071–1081. https://doi.org/10.1007/s00705-021-04969-4

    Article  Google Scholar 

  9. de Lédinghen V, Vergniol J (2008) Transient elastography (FibroScan). Gastroenterol Clin Biol 32:58–67. https://doi.org/10.1016/S0399-8320(08)73994-0

    Article  Google Scholar 

  10. Wahab E, Fathy T, Saber S, Ahmad H. Hepatic Elastography and FIB-4 Score Versus Liver Biopsy for Assessment of Liver fibrosis in Chronic Hcv Patients. Zagazig Univ Med J 2017;21:1–11. https://doi.org/10.21608/zumj.2017.41211

  11. Poynard T, Bedossa P, Opolon P (1997) Natural history of liver fibrosis progression in patients with chronic hepatitis C. Lancet 349:825–832. https://doi.org/10.1016/S0140-6736(96)07642-8

    Article  Google Scholar 

  12. Alberti A, Chemello L, Benvegnù L (1999) Natural history of hepatitis C. J Hepatol 31:17–24. https://doi.org/10.1016/S0168-8278(99)80369-9

    Article  Google Scholar 

  13. Missiha SB, Ostrowski M, Heathcote EJ (2008) Disease progression in chronic hepatitis C: modifiable and nonmodifiable factors. Gastroenterology 134:1699–1714. https://doi.org/10.1053/j.gastro.2008.02.069

    Article  Google Scholar 

  14. Wright M, Goldin R, Fabre A, Lloyd J, Thomas H, Trepo C et al (2003) Measurement and determinants of the natural history of liver fibrosis in hepatitis C virus infection: A cross sectional and longitudinal study. Gut 52:574–579. https://doi.org/10.1136/gut.52.4.574

    Article  Google Scholar 

  15. Minola E, Prati D, Suter F, Maggiolo F, Caprioli F, Sonzogni A et al (2002) Age at infection affects the long-term outcome of transfusion-associated chronic hepatitis C. Blood 99:4588–4591. https://doi.org/10.1182/blood-2001-12-0192

    Article  Google Scholar 

  16. Hui JM, Sud A, Farrell GC, Bandara P, Byth K, Kench JG et al (2003) Insulin resistance is associated with chronic hepatitis C and virus infection fibrosis progression. Gastroenterology 125:1695–1704. https://doi.org/10.1053/j.gastro.2003.08.032

    Article  Google Scholar 

  17. McCaughan GW, George J (2004) fibrosis progression in chronic hepatitis C virus infection. Gut 53:318–321. https://doi.org/10.1136/gut.2003.026393

    Article  Google Scholar 

  18. Bataller R, North KE, Brenner DA (2003) Genetic polymorphisms and the progression of liver fibrosis: a critical appraisal. Hepatology 37:493–503. https://doi.org/10.1053/jhep.2003.50127

    Article  Google Scholar 

  19. Powell EE, Edwards-Smith CJ, Hay JL, Clouston AD, Crawford DH, Shorthouse C et al (2000) Host genetic factors influence disease progression in chronic hepatitis C. Hepatology 31:828–833. https://doi.org/10.1053/he.2000.6253

    Article  Google Scholar 

  20. Dawood RM, El-Meguid MA, Salum GM, El Awady MK (2020) Key Players of Hepatic fibrosis. J Interf Cytokine Res 40:472–489. https://doi.org/10.1089/jir.2020.0059

    Article  Google Scholar 

  21. Huang H, Shiffman ML, Friedman S, Venkatesh R, Bzowej N, Abar OT et al (2007) A 7 gene signature identifies the risk of developing cirrhosis in patients with chronic hepatitis C. Hepatology 46:297–306. https://doi.org/10.1002/hep.21695

    Article  Google Scholar 

  22. Marcolongo M, Young B, Dal Pero F, Fattovich G, Peraro L, Guido M et al (2009) A seven-gene signature (cirrhosis risk score) predicts liver fibrosis progression in patients with initially mild chronic hepatitis C. Hepatology 50:1038–1044. https://doi.org/10.1002/hep.23111

    Article  Google Scholar 

  23. Dawood RM, Salum GM, El-Meguid MA, Elsayed A, Yosry A, Abdelaziz A, et al. Development of a gene signature for predicting cirrhosis risk score of chronic liver disease associated with HCV infection in Egyptians. Microb Pathog 2021;153:104805. https://doi.org/10.1016/j.micpath.2021.104805

  24. Chomczynski P, Sacchi N (1987) Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Anal Biochem 162:156–159. https://doi.org/10.1016/0003-2697(87)90021-2

    Article  Google Scholar 

  25. Löhr HF, Goergen B, Meyer zum Büschenfelde KH, Gerken G. HCV replication in mononuclear cells stimulates anti-HCV-secreting B cells and reflects nonresponsiveness to interferon-alpha. J Med Virol 1995;46:314–20. https://doi.org/10.1002/jmv.1890460405

  26. Abd Alla MDA, Awady MK El. Hepatitis C virus RNA strands detection in peripheral blood mononuclear cells legitimizes virus eradication in negative serum pcr naïve and post-treatment patients. J Clin Transl Hepatol 2017;5:1–8. https://doi.org/10.14218/JCTH.2016.00054

  27. Goniewicz M, Włoszczak-Szubzda A, Niemcewicz M, Witt M, Marciniak-Niemcewicz A, Jarosz MJ (2012) Injuries caused by sharp instruments among healthcare workers - international and Polish perspectives. Ann Agric Environ Med 19:523–527

    Google Scholar 

  28. El-awady MK, Rahman MMA, Ismail SM. HEPATITIS AND HEPATOCELLULAR CARCINOMA Prediction of relapse after interferon therapy in hepatitis C virus-infected patients by the use of triple assay 2003

  29. Alla MDAA, Elibiary SA, Wu GY, El-Awady MK. Occult hcv infection (OCI) diagnosis in cirrhotic and non-cirrhotic naïve patients by intra-pbmc nested viral RNA PCR. J Clin Transl Hepatol 2017;5:319–26. https://doi.org/10.14218/JCTH.2017.00034

  30. Hanno AFF, Mohiedeen KM, Alshayeb AF, Deghedy A (2014) HCV RNA in peripheral blood mononuclear cells (PBMCs) as a predictor of the response to antiviral therapy in chronic hepatitis C. Alexandria J Med 50:317–322. https://doi.org/10.1016/j.ajme.2013.05.004

    Article  Google Scholar 

  31. Elzahaby Aaliabde, Soliman GMM, Korany MA, Eltiby DM, EL Awady MK. Association between post treatment existence of HCV/RNA positive strand and/or negative strand in the PBMNCS and HCV relapse. J Egypt Soc Parasitol 2017;47:323–30. https://doi.org/10.21608/jesp.2017.77783

  32. Dawood RM, Salum GM, Abd El-Meguid M, Shemis M, Abdel Aziz AO, El Awady MK. Recipient interleukin 6 gene polymorphism and expression predict HCV recurrence post liver transplantation. Gene 2020;754:144887. https://doi.org/10.1016/j.gene.2020.144887

  33. Dawood RM, El-Meguid MA, Shousha HI, Elsayed A, Nabeel MM, Yosry A, et al. Seven gene signature explores the impact of DAAs on the appearance of hepatocellular carcinoma in HCV infected patients. Heliyon 2022;8:e10119. https://doi.org/10.1016/j.heliyon.2022.e10119

  34. Abd el-Meguid M, Dawood RM, Mokhles MA, El Awady MK. Extrahepatic upregulation of transforming growth factor beta 2 in HCV genotype 4-induced liver fibrosis. J Interf Cytokine Res 2018;38:341–7. https://doi.org/10.1089/jir.2018.0045

  35. Abd Alla M, altambouly ahmed, Abd Alla M, AbuFarrag G, Ammar I, El-Awady M. Evaluation of IL28B gene sequence variations in the diagnosed null-response to DAAs therapy by intra PBMCs nested HCV RNA PCR. Al-Azhar Int Med J 2021;0:0–0. https://doi.org/10.21608/aimj.2021.40774.1313

  36. Abd Alla MDA, Elibiary SA, Elshaboury RH, Wu GY, Dawood RM, El Awady MK. HCV therapy follow-up fractionation (CTF2) by intra-PBMC nested RNA PCR recognizes early virologic response and relapse. J Clin Transl Hepatol 2018;6:147–54. https://doi.org/10.14218/JCTH.2017.00077

Download references

Funding

Department of Hepatology, Gastroenterology, and Infectious Diseases; Faculty of Medicine et al.-Azhar University; Cairo, Egypt. The institutes have no conflict of interest.

Author information

Authors and Affiliations

  1. Horus Specialized Hospital, General Authority of Health Care, Waburat Armant, Egypt

    Al-Shazly Gaber Mohamed Galal

  2. Department of Microbial Biotechnology, National Research Center, Cairo, Egypt

    Reham M. Dawood & Mostafa K. El Awady

  3. Department of Hepatology, Gastroenterology and Infectious Diseases, Faculty of Medicine, Al-Azhar University, Cairo, Egypt

    Yasser Mohamed Mohamed El-Dessouky, Mohamed Mahmoud Abdel-Halim Mahmoud & Mohamed Darwish Ahmed Abd Alla

Authors
  1. Al-Shazly Gaber Mohamed Galal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reham M. Dawood
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mostafa K. El Awady
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yasser Mohamed Mohamed El-Dessouky
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mohamed Mahmoud Abdel-Halim Mahmoud
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mohamed Darwish Ahmed Abd Alla
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Study design, data analysis, and interpretation: MDA. Drafting of the manuscript: MDA and AG. Critical revision of the manuscript for important intellectual content: RMD, YME, and MMAM. Administrative, technical, and material support: RMA, YME, and AGMG. Study supervision: MDA and MKE. Recruiting patients: MMAM and AGMG. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mohamed Darwish Ahmed Abd Alla.

Ethics declarations

Ethics approval and consent to participate

The authors have no conflicts of interest related to this research. All procedures performed in the current work that involved human participants were in accordance with the ethical standards of the institutional and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the current study. This article does not contain any studies with animals performed by any of the authors. Ethical approval certificate Registration number: Trop.Med._17Med.Research_Inf.GIT.Liv.Dis._0000017.

Consent for publication

Not applicable.

Competing interests

All authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Galal, AS.G.M., Dawood, R.M., Awady, M.K.E. et al. Recognition of 7 genes signature (Cirrhosis Risk Score) in the diagnosed non-responders to DAAs therapy by intra-PBMCs nested HCV RNA PCR. J Genet Eng Biotechnol 21, 89 (2023). https://doi.org/10.1186/s43141-023-00544-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43141-023-00544-3

Keywords