IgA nephropathy (IgAN), the most common primary glomerular disease worldwide, is characterized by glomerular deposition of IgA1-containing immune complexes. The IgA1 hinge region (HR) has up to six clustered O-glycans consisting of Ser/Thr-linked N-acetylgalactosamine usually with β1,3-linked galactose and variable sialylation. Circulating levels of IgA1 with abnormally O-glycosylated HR, termed galactose-deficient IgA1 (Gd-IgA1), are increased in patients with IgAN. Current evidence suggests that IgAN is induced by multiple sequential pathogenic steps, and production of aberrantly glycosylated IgA1 is considered the initial step. Thus, the mechanisms of biosynthesis of aberrantly glycosylated IgA1 and the involvement of aberrant glycoforms of IgA1 in disease development have been studied. Furthermore, Gd-IgA1 represents an attractive biomarker for IgAN, and its clinical significance is still being evaluated. To elucidate the pathogenesis of IgAN, it is important to deconvolute the biosynthetic origins of Gd-IgA1 and characterize the pathogenic IgA1 HR O-glycoform(s), including the glycan structures and their sites of attachment. These efforts will likely lead to development of new biomarkers. Here, we review the IgA1 HR O-glycosylation in general and the role of aberrantly glycosylated IgA1 in the pathogenesis of IgAN in particular.

A common renal disease, immunoglobulin A (IgA) nephropathy (IgAN), is associated with glomerular deposition of IgA1-containing immune complexes. IgA1 hinge region (HR) has up to six clustered O-glycans consisting of Ser/Thr-linked N-acetylgalactosamine with β1,3-linked galactose and variable sialylation. IgA1 glycoforms with some galactose-deficient (Gd) HR O-glycans play a key role in IgAN pathogenesis. The clustered and variable O-glycans make the IgA1 glycomic analysis challenging and better approaches are needed. Here, we report a comprehensive analytical workflow for IgA1 HR O-glycoform analysis. We combined an automated quantitative analysis of the HR O-glycopeptide profiles with sequential deglycosylation to remove all but Gd O-glycans from the HR. The workflow was tested using serum IgA1 from healthy subjects. Twelve variants of glycopeptides corresponding to the HR with three to six O-glycans were detected; nine glycopeptides carried up to three Gd O-glycans. Sites with Gd O-glycans were unambiguously identified by electron-transfer/higher-energy collision dissociation tandem mass spectrometry. Extracted ion chromatograms of isomeric glycoforms enabled quantitative assignment of Gd sites. The most frequent Gd site was T²³⁶, followed by S²³⁰, T²³³, T²²⁸, and S²³². The new workflow for quantitative profiling of IgA1 HR O-glycoforms with site-specific resolution will enable identification of pathogenic IgA1 HR O-glycoforms in IgAN.

Patients with IgA nephropathy (IgAN) have elevated circulating levels of IgA1 with some O-glycans consisting of galactose (Gal)-deficient N-acetylgalactosamine (GalNAc) with or without N-acetylneuraminic acid (NeuAc). We have analyzed O-glycosylation heterogeneity of naturally asialo-IgA1 (Ale) myeloma protein that mimics Gal-deficient IgA1 (Gd-IgA1) of patients with IgAN, except that IgA1 O-glycans of IgAN patients are frequently sialylated. Specifically, serum IgA1 of healthy controls has more α2,3-sialylated O-glycans (NeuAc attached to Gal) than α2,6-sialylated O-glycans (NeuAc attached to GalNAc). As IgA1-producing cells from IgAN patients have an increased activity of α2,6-sialyltransferase (ST6GalNAc), we hypothesize that such activity may promote premature sialylation of GalNAc and, thus, production of Gd-IgA1, as sialylation of GalNAc prevents subsequent Gal attachment. Distribution of NeuAc in IgA1 O-glycans may play an important role in the pathogenesis of IgAN. To better understand biological functions of NeuAc in IgA1, we established protocols for enzymatic sialylation leading to α2,3- or α2,6-sialylation of IgA1 O-glycans. Sialylation of Gal-deficient asialo-IgA1 (Ale) myeloma protein by an ST6GalNAc enzyme generated sialylated IgA1 that mimics the Gal-deficient IgA1 glycoforms in patients with IgAN, characterized by α2,6-sialylated Gal-deficient GalNAc. In contrast, sialylation of the same myeloma protein by an α2,3-sialyltransferase yielded IgA1 typical for healthy controls, characterized by α2,3-sialylated Gal. The GalNAc-specific lectin from Helix aspersa (HAA) is used to measure levels of Gd-IgA1. We assessed HAA binding to IgA1 sialylated at Gal or GalNAc. As expected, α2,6-sialylation of IgA1 markedly decreased reactivity with HAA. Notably, α2,3-sialylation also decreased reactivity with HAA. Neuraminidase treatment recovered the original HAA reactivity in both instances. These results suggest that binding of a GalNAc-specific lectin is modulated by sialylation of GalNAc as well as Gal in the clustered IgA1 O-glycans. Thus, enzymatic sialylation offers a useful model to test the role of NeuAc in reactivities of the clustered O-glycans with lectins.

Anti-endothelial cell antibodies (AECA) are frequently detected in patients with systemic lupus erythematosus (SLE), but their pathological role remains unclear. We recently developed a solubilized cell surface protein capture enzyme-linked immunosorbent assay (CSP-ELISA) to detect antibodies against membrane proteins involved in autoimmune reactions. In this study, sera from 51 patients with biopsy-proven lupus nephritis (LN), 25 with SLE without renal involvement (non-LN SLE), 42 disease control (DC) subjects, and 80 healthy control (HC) subjects were tested for IgG- and IgA-AECA for human umbilical vein endothelial cells (HUVEC) and human glomerular EC (HGEC) by using CSP-ELISA. IgG- and IgA-AECA titers were significantly higher in LN and non-LN SLE patients than in the DC or HC (P < 0.001) groups. IgG- and IgA-AECA titers for HUVEC corresponded well with those for HGEC. The IgA-AECA level correlated with the SLE disease activity index and with histological evidence of active lesions (cellular proliferations, hyaline thrombi and wire loops, leukocytic infiltration, and fibrinoid necrosis) in LN patients (P < 0.001). The sensitivity of IgA-AECA as a diagnostic test for histological evidence of active lesions in LN patients was 0.92, with a specificity of 0.70. The significant correlation of IgA-AECA with glomerular hypercellularity indicates that IgA-AECA are associated with endothelial damage in LN.

Introduction: Protein glycosylation influences characteristics such as folding, stability, protein interactions, and solubility. Therefore, glycan moieties of therapeutic proteins and proteins that are likely associated with disease pathogenesis should be analyzed in-depth, including glycan heterogeneity and modification sites. Recent advances in analytical methods and instrumentation have enabled comprehensive characterization of highly complex glycosylated proteins. Area covered: The following aspects should be considered when analyzing glycosylated proteins: sample preparation, chromatographic separation, mass spectrometry (MS) and fragmentation methods, and bioinformatics, such as software solutions for data analyses. Notably, analysis of glycoproteins with heavily sialylated glycans or multiple glycosylation sites requires special considerations. Here, we discuss recent methodological advances in MS that provide detailed characterization of heterogeneous glycoproteins. Expert opinion: As characterization of complex glycosylated proteins is still analytically challenging, the function or pathophysiological significance of these proteins is not fully understood. To reproducibly produce desired forms of therapeutic glycoproteins or to fully elucidate disease-specific patterns of protein glycosylation, a highly reproducible and robust analytical platform(s) should be established. In addition to advances in MS instrumentation, optimization of analytical and bioinformatics methods and utilization of glycoprotein/glycopeptide standards is desirable. Ultimately, we envision that an automated high-throughput MS analysis will provide additional power to clinical studies and precision medicine.

Favipiravir is an antiviral that is being evaluated for the treatment of COVID-19. Use of favipiravir is associated with elevation of serum uric acid levels. Risk factors for the occurrence of hyperuricemia are unclear. Specimens from COVID-19 patients who received 10 days of favipiravir in a previous clinical trial (jRCTs041190120) were used. Serum favipiravir concentrations were measured by LC-MS. Factors associated with the development of hyperuricemia were investigated using logistic regression analysis. Optimal cut-off values for the baseline serum uric acid levels and steady-state serum favipiravir concentrations in predicting the occurrence of hyperuricemia were determined by ROC curve analysis. Among the 66 COVID-19 patients who were treated with favipiravir for 10 days, the steady-state serum favipiravir concentrations were significantly correlated with serum uric acid levels. High baseline serum uric acid levels and steady-state serum favipiravir concentrations during therapy were factors associated with the development of hyperuricemia. The cut‑off baseline serum uric acid level and steady-state serum favipiravir concentration during favipiravir administration determined to predict hyperuricemia were 3.7 mg/dL and 46.14 μg/mL, respectively. Patients with high baseline serum uric acid levels or who achieved high steady-state serum favipiravir concentrations during therapy were susceptible to hyperuricemia.