Occult HCV Infection (OCI) Diagnosis in Cirrhotic and Non-cirrhotic Naïve Patients by Intra-PBMC Nested Viral RNA PCR

Abstract

Background and Aims: Occult HCV infections (OCIs) include IgG antibody seronegative cryptogenic (COCIs), as well as seropositive secondary naïve (SNOCIs) and experienced (SEOCIs) cases. We used peripheral-blood-mononuclear-cell (PBMC)-PCR to evaluate COCIs and SNOCIs prevalence, serum HCV spontaneous disappearance (SCSD) in naïve cirrhotics and non-cirrhotics, intra-PBMC HCV-RNA strands in relation to cirrhosis density in naïve non-viremia cases, and HCV-RNA seroconversion after 1 year of solitary naïve intra-PBMC infection. Methods: The anti-HCV IgG antibody-positive naïve-patients (n = 785) were classified into viremic (n = 673) and non-viremic [n = 112, including non-cirrhotics (n = 55) and cirrhotics (n = 57)], and 62 controls without evidence of HCV-infection. Controls and post-HCV non-viremia cases (n = 62+112 = 174) were submitted to hepatic Fibroscan-Elastography evaluation. All subjects (n = 847) were screened for intra-PBMC HCV-RNA sense and antisense strands by nested-PCR. Results: Naïve-OCI cases (4.84%) that were diagnosed by PBMC-PCR significantly raised the total numbers of HCV-infection to 714 (p = 0.01). The percent positivity of SNOCIs (34.82%) was significantly higher than for asymptomatic-COCIs (3.125%, p = 0.0001). Comparing PBMC-PCR with single-step-reverse-transcription (SRT)-PCR for identification of SCSD in naïve IgG antibody-positive non-viremia patients (n = 112) revealed a decline in SCSD prevalence by PBMC-PCR (from 14.27% to 9.3%), regardless of presence of hepatic cirrhosis (p = 0.03). SCSD was found to be higher by PBMC-PCR in non-cirrhotics compared to cirrhotics (p = 0.0001), with an insignificant difference when using SRT-PCR (p = 0.45). Intra-PBMC HCV-RNA infection was significantly more frequent in cirrhotics compared to both non-cirrhotics and controls (p < 0.0005). An increased hepatic fibrosis density was recognized in intra-PBMC HCV-RNA infection with sense (p = 0.0001) or antisense strand (p = 0.003). HCV-RNA seroconversion was associated with intra-PBMC infection when both sense and antisense strands were detected (p = 0.047). Conclusions: Intracellular HCV-RNA evaluation is crucial for diagnosing OCIs and addressing relapse probability.

Keywords: Cirrhosis; Naïve; OCIs; PBMCs.

Fig. 1.. Advantages of combined serum and PBMCs (B and C) screening over solitary serum screening for HCV infection (A) by PCR.

PBMC testing of non-viremic subjects detected an extra 41 (4.84%) and 39 (4.97%) infections upon adding (B) or subtracting (C) controls, respectively. The higher numbers of HCV diagnosis obtained by detecting intracellular RNA strands significantly raised the overall frequencies of HCV diagnosis by PBMCs compared to SRT-PCR (p = 0.011 for panel B and p = 0.0029 for panel C). As noted in panel C, the frequency of SNOCIs (39/785, 4.968%) is significantly lower than the frequency among patients with negative PCR (73/785, 9.3%) (p = 0.001).

Fig. 2.. SCSD of HCV RNA genomic materials from IgG antibody-positive and PCR negative populations in relation to hepatic cirrhosis.

SCSD of HCV RNA as diagnosed by A) SRT-PCR and B) PBMC-PCR. A) Insignificant difference was found when cirrhotic and non-cirrhotic naïve patients were compared (Fisher’s exact 1-tailed, p = 0.446). B) Significant difference was found when non-cirrhotic and cirrhotic naïve patients were compared (Fisher’s exact 1-tailed, p = 0.0001).

Fig. 3.. Relative quantification of hepatic fibrosis per RNA seronegative subject in relation to intra-PBMC HCV-infection.

Intracellular RNA was significantly associated with liver fibrosis upon comparison of currently infected groups with the post-HCV PCR negative group (Fisher’s exact 2-tailed, p = 0.00001 and p = 0.0028, respectively, for intra-PBMC sense and antisense strands). Hepatic fibrosis was almost equally distributed among patients who presented with intra-PBMC HCV RNA antisense or sense strand infection (Fisher’s exact 1-tailed, p = 0.68). Fisher’s exact 1-tailed p < 0.00001 was found upon comparing controls with each of the other three groups. Dotted line, cutoff point; solid line, mean kPa values per group. Data cutoff point = mean+3SD of controls KPa values.