Sialylation of antibodies in kidney recipients with de novo donor specific antibody, with or without antibody mediated rejection

The role of antibody glycosylation in autoimmune and alloimmune kidney diseases

Immunoglobulin glycosylation is a pivotal mechanism that drives the diversification of antibody functions. The composition of the IgG glycome is influenced by environmental factors, genetic traits and inflammatory contexts. Differential IgG glycosylation has been shown to intricately modulate IgG effector functions and has a role in the initiation and progression of various diseases. Analysis of IgG glycosylation is therefore a promising tool for predicting disease severity. Several autoimmune and alloimmune disorders, including critical and potentially life-threatening conditions such as systemic lupus erythematosus, anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis and antibody-mediated kidney graft rejection, are driven by immunoglobulin. In certain IgG-driven kidney diseases, including primary membranous nephropathy, IgA nephropathy and lupus nephritis, particular glycome characteristics can enhance in situ complement activation and the recruitment of innate immune cells, resulting in more severe kidney damage. Hypofucosylation, hypogalactosylation and hyposialylation are the most common IgG glycosylation traits identified in these diseases. Modulating IgG glycosylation could therefore be a promising therapeutic strategy for regulating the immune mechanisms that underlie IgG-driven kidney diseases and potentially reduce the burden of immunosuppressive drugs in affected patients.

Sensitization in transplantation: Assessment of Risk 2022 Working Group Meeting Report

The Sensitization in Transplantation: Assessment of Risk workgroup is a collaborative effort of the American Society of Transplantation and the American Society of Histocompatibility and Immunogenetics that aims at providing recommendations for clinical testing, highlights gaps in current knowledge, and proposes areas for further research to enhance histocompatibility testing in support of solid organ transplantation. This report provides updates on topics discussed by the previous Sensitization in Transplantation: Assessment of Risk working groups and introduces 2 areas of exploration: non-human leukocyte antigen antibodies and utilization of human leukocyte antigen antibody testing measurement to evaluate the efficacy of antibody-removal therapies.

Afucosylation of HLA-specific IgG1 as a potential predictor of antibody pathogenicity in kidney transplantation

Antibody-mediated rejection (AMR) is the leading cause of graft failure. While donor-specific antibodies (DSAs) are associated with a higher risk of AMR, not all patients with DSAs develop rejection, suggesting that the characteristics of alloantibodies determining their pathogenicity remain undefined. Using human leukocyte antigen (HLA)-A2-specific antibodies as a model, we apply systems serology tools to investigate qualitative features of immunoglobulin G (IgG) alloantibodies including Fc-glycosylation patterns and FcγR-binding properties. Levels of afucosylated anti-A2 antibodies are elevated in seropositive patients, especially those with AMR, suggesting potential cytotoxicity via FcγRIII-mediated mechanisms. Afucosylation of both glycoengineered monoclonal and naturally glycovariant polyclonal serum IgG specific to HLA-A2 drives potentiated binding to, slower dissociation from, and enhanced signaling through FcγRIII, a receptor widely expressed on innate effector cells, and greater cytotoxicity against HLA-A2+ cells mediated by natural killer (NK) cells. Collectively, these results suggest that afucosylated DSA may be a biomarker of AMR and contribute to pathogenesis.

Machine learning diagnosis by immunoglobulin N-glycan signature for precision diagnosis of urological diseases

Early diagnosis of urological diseases is often difficult due to the lack of specific biomarkers. More powerful and less invasive biomarkers that can be used simultaneously to identify urological diseases could improve patient outcomes. The aim of this study was to evaluate a urological disease‐specific scoring system established with a machine learning (ML) approach using Ig N‐glycan signatures. Immunoglobulin N‐glycan signatures were analyzed by capillary electrophoresis from 1312 serum subjects with hormone‐sensitive prostate cancer (n = 234), castration‐resistant prostate cancer (n = 94), renal cell carcinoma (n = 100), upper urinary tract urothelial cancer (n = 105), bladder cancer (n = 176), germ cell tumors (n = 73), benign prostatic hyperplasia (n = 95), urosepsis (n = 145), and urinary tract infection (n = 21) as well as healthy volunteers (n = 269). Immunoglobulin N‐glycan signature data were used in a supervised‐ML model to establish a scoring system that gave the probability of the presence of a urological disease. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). The supervised‐ML urologic disease‐specific scores clearly discriminated the urological diseases (AUC 0.78–1.00) and found a distinct N‐glycan pattern that contributed to detect each disease. Limitations included the retrospective and limited pathological information regarding urological diseases. The supervised‐ML urological disease‐specific scoring system based on Ig N‐glycan signatures showed excellent diagnostic ability for nine urological diseases using a one‐time serum collection and could be a promising approach for the diagnosis of urological diseases.

IgG3 donor-specific antibodies with a proinflammatory glycosylation profile may be associated with the risk of antibody-mediated rejection after kidney transplantation

The pathogenicity of de novo donor-specific antibodies (dnDSA) varies according to their characteristics. While their MFI, complement-fixing ability, and IgG3 subclass are associated with ABMR occurrence and graft loss, they are not fully predictive of outcomes. We investigated the role of the Fc glycosylation of IgG3 dnDSA in ABMR occurrence using mass spectrometry after isolation by single HLA antigen beads. Between 2014 and 2018, we enrolled 54 patients who developed dnDSA (ABMR- n = 24; ABMR+ n = 30) in two French transplant centers. Fucosylation, galactosylation, GlcNAc bisection, and sialylation of IgG3 dnDSA were compared between ABMR+ and ABMR- patients. IgG3 dnDSA from ABMR+ patients exhibited significantly lower sialylation (7.5% vs. 10.5%, p < .001) and higher GlcNAc bisection (20.6% vs. 17.4%, p = .008). Fucosylation and galactosylation were similar in both groups. DSA glycosylation was not correlated with DSA MFI. In a multivariate analysis, low IgG3 sialylation, high IgG3%, time from transplantation to kidney biopsy, and tacrolimus-free regimen were independent predictive factors of ABMR. We conclude that a proinflammatory glycosylation profile of IgG3 dnDSA is associated with a risk of ABMR occurrence. Further studies are needed to confirm the clinical interest of DSA glycosylation and to clarify its role in determining the risk of ABMR and graft survival.

N-glycan signature of serum immunoglobulins as a diagnostic biomarker of urothelial carcinomas

Discriminating between urothelial carcinoma (UC), including bladder cancer (BCa) and upper urinary tract UC (UTUC), is often challenging. Thus, the current study evaluated the diagnostic performance of N-glycosylation signatures of immunoglobulins (Igs) for detecting UC, including BCa and UTUC. N-glycosylation signatures of Igs from serum samples of the training cohort, including 104 BCa, 68 UTUC, 10 urinary tract infection, and 5 cystitis cases, as well as 62 healthy volunteers, were measured retrospectively using automated capillary-electrophoresis-based N-glycomics. UTUC or BCa scores were then established through discriminant analysis using N-glycan signatures of Igs. Diagnostic performance was evaluated using the area under receiver operating characteristics curve (AUC) and decision curve analyses (DCA). Our result showed that BCa and UTUC scores for discriminating BCa (AUC: 0.977) and UTUC (AUC: 0.867), respectively, provided significantly better clinical performance compared to urine cytology, gross hematuria, or clinical T1 cases. DCA revealed that adding BCa and UTUC scores to gross hematuria status was the best combination for detecting UC and avoiding the need for more intervention without overlooking UC (risk threshold: 13%-93%). The UC nomogram based on the combination of gross hematuria, UTUC score, and BCa score could detect UC with an AUC of 0.891, indicating significantly better performance compared to gross hematuria status in the validation cohort (251 patients). The limitations of this study include its small sample size and retrospective nature. The UC nomogram based on gross hematuria and N-glycosylation signatures of Igs can be a promising approach for the diagnosis of UC.

Serum N-glycan profiling can predict biopsy-proven graft rejection after living kidney transplantation

BACKGROUND

To evaluate whether serum N-glycan profile can be used as a diagnostic marker of graft rejection after living-donor kidney transplants (KT).

METHODS

We retrospectively examined 174 KT recipients at five medical centers. N-Glycan levels were analyzed in postoperative serum samples using glycoblotting combined with mass spectrometry. We developed an integrated score to predict graft rejection based on a combination of age, gender, immunological risk factors, and serum N-glycan levels at post-KT day D1 and D7. Rejection-free survival rates stratified by the sum of integrated scores (D1 + D7) were evaluated using Kaplan-Meier curves.

RESULTS

Of 174, 52 showed graft rejection (Rejection-pos. group) and 122 recipients did not show graft rejection (Rejection-neg. group). The integrated scores were significantly higher in the Rejection-pos. group than those of the Rejection-neg. group. Area-under-curve (AUC) value of integrated scores at post-KT D1, and D7 were 0.84 and 0.84, respectively. The sum of integrated scores (D1 + D7) ≥ 0.50 identified graft rejection with 81% sensitivity and 80% specificity; with an AUC value of 0.87. Recipients with higher sum of integrated scores (D1 + D7 ≥ 0.5) had significantly shorter rejection-free survival than those with lower scores.

CONCLUSION

Evaluation of serum N-glycosylation profiles can identify recipients who are prone to rejection.

Aberrant N-Glycosylation Profile of Serum Immunoglobulins is a Diagnostic Biomarker of Urothelial Carcinomas

The aim of this study to determine whether the aberrant N-glycosylated serum immunoglobulins (Igs) can be applied as a diagnostic marker of urothelial carcinoma (UC). Between 2009 and 2016, we randomly obtained serum available from 237 UC and also 96 prostate cancer as other cancer controls from our serum bank and also obtained-from 339 healthy volunteers (HV)-controls obtained from community-dwelling volunteers in Iwaki Health Promotion Project. A total of 32 types of N-glycan levels on Igs were determined by high-throughput N-glycomics and analyzed by multivariable discriminant analysis. We found five UC-associated aberrant N-glycans changes on Igs and also found that asialo-bisecting GlcNAc type N-glycan on Igs were significantly accumulated in UC patients. The diagnostic N-glycan Score (dNGScore) established by combination of five N-glycans on Igs discriminated UC patients from HV and prostate cancer (PC) patients with 92.8% sensitivity and 97.2% specificity. The area under the curve (AUC) for of the dNGScore was 0.969 for UC detection that was much superior to that of urine cytology (AUC, 0.707) and hematuria (AUC, 0.892). Furthermore, dNGScore can detect hematuria and urine cytology negative patients. The dNGscore based on aberrant N-glycosylation signatures of Igs were found to be promising diagnostic biomarkers of UCs.

Donor-Recipient Matching Based on Predicted Indirectly Recognizable HLA Epitopes Independently Predicts the Incidence of De Novo Donor-Specific HLA Antibodies Following Renal Transplantation

De novo donor-specific HLA antibodies (dnDSA) are recognized as a risk factor for premature allograft failure. Determinants of DSA specificity are generated via the indirect allorecognition pathway. Here, we present supportive data for the relevance of predicted indirectly recognizable HLA epitopes (PIRCHE) to predict dnDSA following kidney transplantation. A total of 2787 consecutive kidney transplants performed between 1995 and 2015 without preformed DSA have been analyzed. De novo DSA were detected by single antigen bead assay. HLA epitope mismatches were determined by the HLAMatchmaker and PIRCHE approach and correlated in uni- and multivariate analyses with 10-year allograft survival and incidence of dnDSA. The PIRCHE-II score moderately predicted allograft survival. However, the predictive value of elevated PIRCHE-II scores >9 for the incidence of dnDSA was statistically significant (p < 0.001). In a multivariate Cox regression analysis adjusted for antigen mismatch and HLAMatchmaker epitopes, the PIRCHE-II score could be identified as an independent risk factor for dnDSA. The PIRCHE-II score independently from the antigen mismatch and HLAMatchmaker epitopes could be revealed as being a strong predictor for dnDSA. PIRCHE may help to identify acceptable mismatches with decreased risk of dnDSA and thus improve long-term renal allograft survival.

Pro-inflammatory State in Monoclonal Gammopathy of Undetermined Significance and in Multiple Myeloma Is Characterized by Low Sialylation of Pathogen-Specific and Other Monoclonal Immunoglobulins

Multiple myeloma (MM) and its pre-cancerous stage monoclonal gammopathy of undetermined significance (MGUS) allow to study immune responses and the chronology of inflammation in the context of blood malignancies. Both diseases are characterized by the production of a monoclonal immunoglobulin (mc Ig) which for subsets of MGUS and MM patients targets pathogens known to cause latent infection, a major cause of inflammation. Inflammation may influence the structure of both polyclonal (pc) Ig and mc Ig produced by malignant plasma cells via the sialylation of Ig Fc fragment. Here, we characterized the sialylation of purified mc and pc IgGs from 148 MGUS and MM patients, in comparison to pc IgGs from 46 healthy volunteers. The inflammatory state of patients was assessed by the quantification in serum of 40 inflammation-linked cytokines, using Luminex technology. While pc IgGs from MGUS and MM patients showed heterogeneity in sialylation level, mc IgGs from both MGUS and MM patients exhibited a very low level of sialylation. Furthermore, mc IgGs from MM patients were less sialylated than mc IgGs from MGUS patients (p < 0.01), and mc IgGs found to target an infectious pathogen showed a lower level of sialylation than mc IgGs of undetermined specificity (p = 0.048). Regarding inflammation, 14 cytokines were similarly elevated with a p value < 0.0001 in MGUS and in MM compared to healthy controls. MM differed from MGUS by higher levels of HGF, IL-11, RANTES and SDF-1-α (p < 0.05). MGUS and MM patients presenting with hyposialylated pc IgGs had significantly higher levels of HGF, IL-6, tumor necrosis factor-α, TGF-β1, IL-17, and IL-33 compared to patients with hyper-sialylated pc IgGs (p < 0.05). In MGUS and in MM, the degree of sialylation of mc and pc IgGs and the levels of four cytokines important for the anti-microbial response were correlated, either positively (IFN-α2, IL-13) or negatively (IL-17, IL-33). Thus in MGUS as in MM, hyposialylation of mc IgGs is concomitant with increased levels of cytokines that play a major role in inflammation and anti-microbial response, which implies that infection, inflammation, and abnormal immune response contribute to the pathogenesis of MGUS and MM.

Serum Aberrant N-Glycan Profile as a Marker Associated with Early Antibody-Mediated Rejection in Patients Receiving a Living Donor Kidney Transplant

We determined if the serum N-glycan profile can be used as a diagnostic marker of antibody-mediated rejection (ABMR) in living donor kidney transplant (LKTx) recipients. Glycoblotting, combined with mass spectrometry, was used to retrospectively examine N-glycan levels in the postoperative sera of 197 LKTx recipients of whom 16 recipients had ABMR with or without T-cell-mediated rejection (TCMR), 40 recipients had TCMR, and 141 recipients had no adverse events. Multivariate discriminant analysis for prediction of ABMR was performed by inputting an ABMR event as an explanatory variable and sex, age, and serum N-glycan level as objective variables. The N-glycan score was calculated by multiplying the level of candidate objective variables by objective function values. The ABMR predictive performance of the N-glycan score was assessed by receiver operator characteristic curve and Kaplan-Meier curve analyses. The N-glycan score discriminated ABMR with 81.25% sensitivity, 87.85% specificity, and an area under the curve (AUC) of 0.892 that was far superior to that of preformed donor-specific antibody status (AUC, 0.761). Recipients with N-glycan-positive scores >0.8770 had significantly shorter ABMR survival than that of recipients with N-glycan-negative scores. Although the limitations of our study includ its small sample size and retrospective nature, the serum N-glycan score may contribute to prediction of ABMR.

Clinical implications of serum N-glycan profiling as a diagnostic and prognostic biomarker in germ-cell tumors

Serum biomarker monitoring is essential for management of germ‐cell tumors (GCT). However, not all GCT are positive for conventional tumor markers. We examined whether serum N‐glycan‐based biomarkers can be applied for detection and prognosis in patients with GCT. We performed a comprehensive N‐glycan structural analysis of sera from 54 untreated GCT patients and 103 age‐adjusted healthy volunteers using glycoblotting methods and mass spectrometry. Candidate N‐glycans were selected from those with the highest association; cutoff concentration values were established, and an N‐glycan score was created based on the number of positive N‐glycans present. The validity of this score for diagnosis and prognosis was analyzed using a receiver operating characteristic (ROC) curve. We identified five candidate N‐glycans significantly associated with GCT patients. The accuracy of the N‐glycan score for GCT was significant with an area‐under‐the‐curve (AUC) value of 0.87. Diagnostically, the N‐glycan score detected 10 of 12 (83%) patients with negative conventional tumor markers. Prognostically, the N‐glycan score comprised four candidate N‐glycans. The predictive value of the prognostic N‐glycan score was significant, with an AUC value of 0.89. A high value prognostic N‐glycan score was significantly associated with poor prognosis. Finally, to identify a potential carrier protein, immunoglobulin (Ig) fractions of sera were subjected to N‐glycan analysis and compared to whole sera. Candidate N‐glycans in Ig‐fractions were significantly decreased; therefore, the carrier protein for candidate N‐glycans is likely not an immunoglobulin. In summary, our newly developed N‐glycan score seems to be a practical diagnostic and prognostic method for GCT.

Significance of Serum N-glycan Profiling as a Diagnostic Biomarker in Urothelial Carcinoma

BACKGROUND

The clinical diagnosis of urothelial carcinoma (UC) relies on invasive methods in patients with hematuria. Although more sensitive and noninvasive screening methods are required, a specific serum biomarker for UC is lacking.

OBJECTIVE

To examine whether serum glycan-based biomarkers can be applied to UC detection.

DESIGN, SETTING, AND PARTICIPANTS

Between April 1994 and June 2016, serum N-glycan concentrations were retrospectively measured in 212 patients with UC before treatment (UC group) and 212 pair-matched controls using glycoblotting and mass spectrometry.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

N-glycan levels were compared between the groups using receiver operating characteristic curves to select candidate N-glycans. We created an N-glycan score based on the combination of candidate N-glycans. The specificity and sensitivity of the candidate N-glycan score were evaluated using receiver operating characteristic curves.

RESULTS AND LIMITATIONS

The N-glycan score was calculated using six N-glycans (m/z 1566, m/z 1687, m/z 1769, m/z 1871, m/z 2011, and m/z 2337) that were significantly associated with UC. The median N-glycan score was significantly higher in the UC group than in the pair-matched control group (5.0 vs 1.0, p<0.001). The N-glycan score correctly classified UC patients with a sensitivity, specificity, and area under the curve of 93%, 81%, and 0.95, respectively. The limitations of our study included its retrospective nature and nonclinical setting.

CONCLUSIONS

Serum N-glycan content has the potential to be a specific and sensitive novel serum biomarker that may improve the accuracy of the detection for UC and reduce unnecessary invasive screening. Validation of this test in a large-scale prospective study is needed.

PATIENT SUMMARY

Combination of serum N-glycan (N-glycan score) is a novel serum marker for urothelial carcinoma that is expressed by 93% of patients and thus is far more sensitive than classic urine cytology. Validation in a large patient cohort is needed.