Solving the mystery of HBV-related mixed cryoglobulinemia: potential biomarkers of disease progression

Abstract

Objectives: The biomarkers of an immunological dysregulation due to a chronic HBV infection are indeed understudied. If untreated, this condition may evolve into liver impairment co-occurring with extrahepatic involvements. Here, we aim to identify a new panel of biomarkers [including immunoglobulin G (IgG) subclasses, RF, and Free Light Chains (FLCs)] that may be useful and reliable for clinical evaluation of HBV-related cryoglobulinemia.

Methods: We retrospectively analysed clinical data from 44 HBV-positive patients. The patients were stratified (according to the presence/absence of mixed cryoglobulinemia) into two groups: 22 with cryoglobulins (CGs) and 22 without CGs. Samples from 20 healthy blood donors (HDs) were used as negative controls. Serum samples were tested for IgG subclasses, RF (-IgM, -IgG, and -IgA type), and FLCs.

Results: We detected a strikingly different distribution of serum IgG subclasses between HDs and HBV-positive patients, together with different RF isotypes; in addition, FLCs were significantly increased in HBV-positive patients compared with HDs, while no significant difference was shown between HBV-positive patients with/without mixed cryoglobulinemia.

Conclusion: The immune-inflammatory response triggered by HBV may be monitored by a peculiar profile of biomarkers. Our results open a new perspective in the precision medicine era; in these challenging times, they could also be employed to monitor the clinical course of those COVID-19 patients who are at high risk of HBV reactivation due to liver impairment and/or immunosuppressive therapies.

Keywords: HBV; IgG subclasses; free light chains; mixed cryoglobulinemia; rheumatoid factor; vasculitis.

Fig. 1

Box-plot analysis of the biomarkers serum levels for healthy donors (cyan) and HBV patients with and without cryoglobulins (gold) The presence of statistically significant differences is graphically shown using a grey plot background.

Fig. 2

Box-plot analysis of the biomarkers serum levels for HBV patients with (cyan) and without cryoglobulins (gold) A grey plot background graphically indicates the presence of statistically significant differences.

Fig. 3

ROC analysis of selected biomarkers, separately (a) and combining different biomarkers (b) according to a stepwise logistic regression in both directions

Fig. 4

Spearman’s correlation coefficients among different biomarkers in the three groups separately, namely healthy donors (a), patients with (b) and without (c) cryoglobulins The corresponding scatter plots for significant correlations are shown in panels d, e and f.