Glycans on circulating antibodies (Abs) participate in cell--cell  and cell--pathogen interactions , direct Ab functionality, and immune functions regulation . Higher levels of Ab galactosylation and lower levels of fucosylation have been associated with higher antibody-dependent cell-mediated cytotoxicity (ADCC) [4–6], whereas Ab sialylation and galactosylation have been linked to strong anti-inflammatory responses [7–10].
HIV and hepatitis C virus (HCV) mono-infection lead to immune activation and gradual loss of immune function [11–13]. Antiretroviral therapy (ART) partially restores these effects in HIV [14,15]. HIV/HCV co-infection is common, with HIV and HCV affecting each other [16–18].
We evaluated how IgG glycosylation and immune profile patterns are modulated in single or dual infections using samples from HCV and ART-suppressed HIV, and HIV/HCV individuals.
Fourteen HCV patients and 27 ART-suppressed HIV/HCV patients untreated for HCV were evaluated for IgG glycans, and clinical/immune variables. Inclusion criteria are shown in Supplemental Table 1, https://links.lww.com/QAD/B747. IgG glycans data were also available from 23 ART-suppressed chronically HIV patients (historic HIV: CD4+ T-cell count >400 cells/μl, HIV RNA <500 copies/ml for ≥6 months, <50 copies/ml at study entry). Informed consent was obtained from all participants. The study protocol and informed consent procedures were approved by the Institutional Review Boards of the authors’ institutions.
IgG isolation and N-glycan analysis
Bulk IgG was purified from cryopreserved plasma using Pierce Protein G Spin Plates (ThermoFisher Scientific, Waltham, Massachusetts, USA). N-glycans were released using peptide-N-glycosidase F (PNGase F) and labeled with 8-aminopyrene-1,3,6-trisulfonic acid (APTS) using the GlycanAssure APTS Kit (ThermoFisher Scientific). Labelled N-glycans were analyzed using a 3500 Genetic Analyzer capillary electrophoresis system. Relative abundance of N-glycan structures was quantified by calculating the area under the curve (AUC) of each glycan structure divided by total glycans using the Applied Biosystems GlycanAssure Data Analysis Software Version 2.0 (Supplemental Figure 1, https://links.lww.com/QAD/B744).
Clinical and immune variable assessment
Clinical parameters [complete blood count with differential, CD4+ count, HCV and HIV viral load, alanine aminotransferase (ALT), and aspartate aminotransferase (AST)] were assessed by Quest Diagnostics (New Jersey, USA).
Flow cytometry was performed on fresh blood as previously described [19,20]. Combinations of fluorochrome-conjugated monoclonal Abs targeted activation/exhaustion, costimulatory and apoptosis markers as shown in Supplemental Table 2, https://links.lww.com/QAD/B748. All Abs were from Becton Dickinson Biosciences (San Diego, California, USA) except blood dendritic cells antigen (BDCA) 2-allophycocyanin (APC), BDCA4-APC and IgG1-APC (Miltenyi Biotec, San Diego, California, USA). T cells were defined as CD3+CD8−, CD3+CD8+, dendritic cells  as BDCA2+BDCA4+ (plasmacytoid DC, PDC), and CD19-BDCA1+CD11c+ (myeloid DC, MDC)], monocytes as CD14+, and natural killer (NK) cells as CD3−CD56dimCD16−, CD3−CD56dimCD16+, CD3−CD56bright, and CD3−CD56−CD16+[22–25].
Natural killer function assessment
Constitutive and in-vitro IFN-α-induced natural killer cell-mediated cytotoxicity were measured using a standard 51Cr release assay with fresh PBMC serving as effectors against the 51Cr-labelled erythroblastoid MHC-null cell line K562 [20,26]. Effectors and K562 targets were cultured in triplicate for each effector/target ratio (E/T: 50 : 1, 25 : 1, 12.5 : 1, and 6.25 : 1). Results were expressed for each condition as AUC.
NK function in individual NK subsets (i.e. Lin3-CD56-CD16+, Lin3−CD56dimCD16−, Lin3-CD56dimCD16+, and Lin3-CD56bright with Lin3 consisting of CD3+, CD14+, CD19+, and CD20+) was assessed using flow cytometry as previously described  by measuring constitutive and target-induced cytokine production (IFN-γ) in the presence or absence of IFN-α stimulation and K562 cells.
Data were described as medians, and interquartile ranges. The Kruskal--Wallis test with post-hoc two by two comparisons with Wilcoxon rank sum test was used for group comparisons and Spearman's correlation test for associations within each group. Unadjusted P values that were less than 0.05 along with multiple testing adjusted P values were assessed. Multiple testing adjustment was applied using the Benjamini and Hochberg False discovery rate (FDR) method, with a cutoff of 10%. FDR adjusted P-values that were less than 0.1 are reported. Fisher's exact test was used to test the null hypothesis that there is no significant difference in race and sex amongst groups. To evaluate if age, race or sex would affect the observed significant differences amongst groups, a linear regression model was applied using glycans and clinical/immune variables as dependent variables, and including study group, age, race, or sex as independent variables. To evaluate if age, race or sex would affect the observed significant associations within each group, a linear regression model was applied using glycans as dependent variables, and including clinical/immune variables, age, race, or sex as independent variables, and the interaction term between clinical/immune variables and race or sex. R version 3.5.0 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria) was used.
Study participants’ demographic and clinical characteristics are described in Supplemental Table 3, https://links.lww.com/QAD/B749. A significant difference was found amongst groups for sex and race. CD4+ T-cell count and age were higher in HCV when compared with HIV/HCV and HIV, whereas no difference was found for these variables between HIV/HCV and HIV.
Hepatitis C virus decreases the levels of pro-antibody-dependent cell-mediated cytotoxicity-associated glycans
Comparison of 27 IgG glycans and 144 clinical/immune variables amongst groups showed a difference after multiple testing adjustment in the expression levels of 9/27 IgG glycans (Fig. 1) and 8/144 immune variables (Supplemental Figure 2, https://links.lww.com/QAD/B745). Assessment of the effect of age, race, or sex on these differences showed an effect in 4/9 IgG glycans (Fig. 1) and 1/8 immune variables (Supplemental Figure 2, https://links.lww.com/QAD/B745).
Briefly, comparison of IgG glycans amongst HCV, HIV/HCV, and historic HIV showed lower levels of the pro-ADCC-associated nonfucosylated glycans (nonfucosylated mono-sialylated A1, or di-sialylated A2) or mono-galactosylated G1 along with higher levels of the anti-ADCC-associated fucosyated glycans (e.g. total fucosylated, fucosylated G1Fp) in HCV when compared with HIV/HCV or HIV. Interestingly, the same differences were observed for these glycan levels between HIV/HCV and HIV supporting retained modulation of glycans levels by HCV in the context of HIV co-infection (Fig. 1a and b).
A difference was also detected between HCV and HIV for inflammation-associated glycans as shown by the lower levels of anti-inflammatory glycans (e.g. total galactosylated, total di-galactosylated G2, total sialylated) and the higher levels of the pro-inflammatory agalactosylated G0 glycans in HCV when compared with HIV (Fig. 1c and d). No difference was detected for these glycan levels between HCV and HIV/HCV.
As documented in Supplemental Figure 2, https://links.lww.com/QAD/B745, markers of immune activation [e.g. CD3+CD8+CD38+ percentage (%) of CD8+ T cells], exhaustion [e.g. CD3+CD8+ B and T-lymphocyte attenuator (BTLA)+CD160+ % of CD8+ T cells], and apoptosis [e.g. tumor necrosis factor-alpha-related apoptosis-inducing ligand (TRAIL)+ % of monocytes] were higher in HIV/HCV when compared with HCV. In contrast, no significant difference was observed for plasma levels of the biomarkers of liver status ALT and AST.
Association of glycans with liver status and immune variables
Correlation of IgG glycans with clinical/immune variables within each group, resulted after multiple testing adjustment in 21 associations in HCV and 2 associations in HIV/HCV (Table 1, Supplemental Figure 3, https://links.lww.com/QAD/B746). Assessment of the effect of age, race, or sex on the observed associations showed an effect of age in 4/21 associations observed in HCV (Table 1).
Briefly, in HCV consistent with an expected association of liver status or immune activation with inflammation, liver status (i.e. AST) was negatively associated with the anti-inflammatory total galactosylated glycans, total di-galactosylated G2 glycans, and total sialylated glycans, and positively associated with the pro-inflammatory agalactosylated G0 glycans. In addition, the frequencies of CD3+CD8+HLA-DR+ and of effector terminal CD8+ T cells were negatively associated with anti-inflammatory (i.e. total galactosylated, total di-galactosylated G2, total sialylated), and positively associated with pro-inflammatory (i.e. agalactosylated G0) glycans. Finally, consistent with the previously described lower activation potential of CD8+ T cells expressing BTLA and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), these markers were positively associated with anti-inflammatory (i.e. total galactosylated, total di-galactosylated G2, and total sialylated), and negatively associated with pro-inflammatory (i.e. agalactosylated G0) glycans.
Consistent with an expected association of direct NK cytotoxicity with ADCC or inflammation, in HCV IFN-α-induced NK cytotoxicity was negatively associated with the anti-ADDC total fucosylated glycans, while constitutive NK cytotoxicity was positively associated with the anti-inflammatory total galactosylated and total di-galactosylated G2 glycans. In agreement with this finding, in HIV/HCV CD56dimCD16– NK cells were positively associated with the anti-inflammatory total di-galactosylated G2 glycans, and negatively with the anti-ADDC total fucosylated glycans.
We evaluated the modulation of IgG glycosylation in single and dual infections using samples from HIV and HCV, and HIV/HCV. We show that HCV modulates IgG glycosylation in HIV/HCV by decreasing the levels of glycans that are associated with higher NK-mediated ADCC compared with HIV. We also show that in HCV, inflammation-modulating IgG glycans are associated with biomarkers of liver status, and immune activation/exhaustion.
We confirmed data from us  and others [27,28] suggesting a greater T-cell dysfunction (e.g. activation/exhaustion) in co-infection with HIV despite ART-mediated suppression. Importantly, in HCV, the correlations found between AST and IgG glycans suggest that IgG glycans can signal for inflammation and liver damage. The lack of significant difference in the levels of biomarkers of liver status between HCV and HIV/HCV, despite a difference in activation, could be attributed to independent factors driving liver damage or immune activation in HIV/HCV or to the exclusion of individuals with established noncompensated liver cirrhosis.
Lower fucosylation and higher antibody galactosylation have been associated with higher ADCC [4–6]. Our results support these data as in HCV and HIV/HCV NK cytotoxicity or NK cell subsets frequency, respectively, were positively associated with the pro-ADCC-associated di-galactosylated glycans, and negatively associated with the anti-ADCC-associated fucosylated glycans suggesting an association between these glycans and NK function. Comparison of IgG glycosylation between these groups showed higher levels of fucosylated glycans in HCV and higher levels of nonfucosylated glycans in HIV/HCV. Furthermore, higher levels of nonfucosylated and lower levels of fucosylated glycans were observed in HIV when compared with HCV or HIV/HCV. These findings suggest that suppressive ART could result in higher ADCC in HIV. This in turn could account for higher ADCC in HIV/HCV when compared with HCV, although co-infection with HCV could restrict this beneficial effect.
Usage of fresh samples eliminated any influence of cryopreservation on the cell subsets and functions studied. Although our study suggests modulation of ADCC-associated glycans, the lack of a specific HCV antigen that could be used to test ADCC necessitated the usage of direct NK cytotoxicity as a surrogate marker of NK function. Due to the small sample size, our study did not address the possible confounding effects of different antiretroviral drug combinations on IgG glycomic signatures.
Overall, our data suggest that ART-suppressed HIV/HCV co-infection may restrict the beneficial effect of ART-mediated immune reconstitution by decreasing the levels of glycans that are associated with higher NK-mediated ADCC, and increasing the levels of glycans that are associated with higher inflammation and immune activation; in contrast to HIV/HCV, IgG glycan profiles may be more informative in HCV where we found an association between levels of ADCC or inflammation-associated IgG glycans and markers of liver status, NK cytotoxicity, or immune activation/exhaustion. Future studies should validate our findings in other mono and dual infections.
We thank the study participants and their providers.
L.B.G., M.D., B.N.R., M.F., and A.S. performed experimental work. K.M., J.R.K. J.M.J., and K.M.L. selected and recruited patients. X.Y. and Q.L. performed the statistical analysis. E.P., L.A., M.A.-M., and L.J.M. designed the study, evaluated the results, and wrote the manuscript. We also acknowledge technical support for this work by Griffin Reynolds, Natalie Opsitnick, Charity Calloway, Jocelin Joseph, and Maxwell Pistilli. All participants have read and approved the manuscript.
Conflicts of interest
This work was supported by a grant to L.J.M. by the National Institutes of Health (NIH) (R01AI073219), the Philadelphia Foundation (Robert I. Jacobs Fund), Ken Nimblett and The Summerhill Trust. Glycomic analysis were supported by funds to M.A.-M.: NIH grants (R01 DK123733, R01 AG062383, R21 AI143385, R21 AI129636, and R21 NS106970) and The Foundation for AIDS Research (amfAR) impact grant # 109840-65-RGR. This publication was also made possible through core services and support from the Penn Center for AIDS Research (Grant P30 AI 045008), and the BEAT-HIV Delaney Collaboratory, supported by NIH UM1AI126620, co-funded by NIAID, NIMH, NINDS, and NIDA. The funding sources had no involvement in the study design; collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
There are no conflicts of interest.
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