Serum N-glycan Research Articles

Identification of serum N-glycans signatures in three major gastrointestinal cancers by high-throughput N-glycome profiling

BackgroundAlternative N-glycosylation of serum proteins has been observed in colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC) and gastric cancer (GC), while comparative study among those three cancers has not been reported before. We aimed to identify serum N-glycans signatures and introduce a discriminative model across the gastrointestinal cancers.MethodsThe study population was initially screened according to the exclusion criteria process. Serum N-glycans profiling was characterized by a high-throughput assay based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Diagnostic model was built by random forest, and unsupervised machine learning was performed to illustrate the differentiation between the three major gastrointestinal (GI) cancers.ResultsWe have found that three major gastrointestinal cancers strongly associated with significantly decreased mannosylation and mono-galactosylation, as well as increased sialylation of serum glycoproteins. A highly accurate discriminative power (> 0.90) for those gastrointestinal cancers was obtained with serum N-glycome based predictive model. Additionally, serum N-glycome profile exhibited distinct distributions across GI cancers, and several altered N-glycans were hyper-regulated in each specific disease.ConclusionsSerum N-glycome profile was differentially expressed in three major gastrointestinal cancers, providing a new clinical tool for cancer diagnosis and throwing a light upon the disease-specific molecular signatures.

N-glycan as new potential biomarker for predicting treatment response in patients with type 2 diabetes mellitus.

To investigate the N-glycans related to the metformin efficacy in patients with type 2 diabetes mellitus (T2DM). We enrolled 141healthy controls and 195 newly diagnosed T2DM patients treated with metformin for 3 months. Serum N-glycan profile was determined by DNA sequencer - assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). The N-glycan model was established by logistic regression analysis. Receiver operating characteristic curve (ROC) analysis was used to analyze the predictive power of the N-glycan model for metformin efficacy. The abundances of several N-glycans in serum of T2DM patients at baseline were significantly different from those of healthy controls and tended to recover the N-glycan of controls after 3 months treatment. Serum N-glycans changes were more significant in the good response group (FPG <7 mmol/L) after metformin treatment. In addition, the abundance of peak9 at baseline had an opposite tendency between HbA1c increased and decreased groups post-treatment, which could be a biomarker for predicting metformin efficacy. Peak9 combined with other 11 N-glycans at baseline was used to establish the predictive model to distinguish non-response from response patients (AUROC = 0.780, sensitivity = 70.6% and specificity = 77.5%). Serum N-glycans may have potential value as biomarkers for indicating the efficacy of metformin.

Pregnancy-related changes in the canine serum N-glycosylation pattern studied by Rapifluor HILIC-UPLC-FLR-MS

Canine reproduction differs from that of many other domestic animals, and increased knowledge on biochemical changes during canine pregnancy is important for investigations of infertility or subfertility. The total glycosylation pattern, i.e., the glycome, of body fluids reflects cellular status in health and disease. The aim of the present pilot study was to investigate pregnancy-related changes of the serum N-glycome in bitches. A method based on Rapifluor HILIC-UPLC-FLR-MS was optimized and applied for analysis and quantification of N-glycans in canine serum. Serum samples from six pregnant and five non-pregnant bitches, collected at four well-defined time points, were included. The levels of sialylated and galactosylated complex glycans were significantly elevated in serum from pregnant bitches, consistent with previous reports on human pregnancy. The levels of fucosylated and agalactosylated glycans decreased significantly in pregnant dogs. In non-pregnant dogs, the glycosylation pattern did not change during the cycle. Pregnancy is an inflammatory state, but our findings during canine pregnancy are quite the opposite to changes that have previously been described for dogs with a known parasitic infection. Evaluation of the canine glycome may thus be valuable in studies of canine pregnancy, possibly differing inflammatory changes related to pregnancy to those caused by an infection.

Serum N-Glycan Changes in Rats Chronically Exposed to Glyphosate-Based Herbicides.

Glyphosate, the active ingredient in many herbicides, has been widely used in agriculture since the 1970s. Despite initial beliefs in its safety for humans and animals due to the absence of the shikimate pathway, recent studies have raised concerns about its potential health effects. This study aimed to identify glycomic changes indicative of glyphosate-induced toxicity. Specifically, the study focused on profiling N-glycosylation, a protein post-translational modification increasingly recognized for its involvement in various disorders, including neurological conditions. A comprehensive analysis of rat serum N-glycomics following chronic exposure to glyphosate-based herbicides (GBH) was conducted using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results revealed significant changes in the N-glycan profile, particularly in sialylated and sialofucosylated N-glycans. The analysis of N-glycans across gender subgroups provided insights into gender-specific responses to GBH exposure, with the male rats exhibiting a higher susceptibility to these N-glycan changes compared to females. The validation of significantly altered N-glycans using parallel reaction monitoring (PRM) confirmed their expression patterns. This study provides novel insights into the impact of chronic GBH exposure on serum N-glycan composition, with implications for assessing glyphosate toxicity and its potential neurological implications.

A novel model based on serum N-glycan markers for evaluating stage of liver necroinflammation in treatment-naïve chronic hepatitis B patients.

This study aimed to establish a novel noninvasive model based on the serum N-glycan spectrum for providing an objective value for determining the stage of liver necroinflammation related to chronic hepatitis B (CHB) patients. N-glycan profiles of the sera of 295 treatment-naïve CHB patients were analyzed. N-glycan profiles were tested for different liver necroinflammation stages using DNA sequence-assisted fluorophore-assisted carbohydrate electrophoresis. A serum N-glycan model named N-glycan-LI(NGLI) using support vector machine was selected to evaluate the classification of liver necroinflammation (G < 2 and G ≥ 2). The area under the receiver operating characteristic curves (AUROCs) was 0.898 (training set, n = 236) and 0.911 (validation set, n = 59) regardless of the stage of liver fibrosis (AUROC = 0.886 and 0.926, respectively, in S < 2 and S ≥ 2 group). The NGLI correspondingly had the highest specificity (SP) of 90.79% and negative predictive value of 92.00% in an inactive stage (including immune-tolerant [IT] and inactive-carrier [IC] stage), had the highest positive predictive value of 95.18% in stage immune-active, and had the highest SPof 93.94% in grey zone IT + IC. N-glycan profiles appear to correlate well with hepatic necroinflammation in CHB when compared with liver biopsy. The newly developed model appears to reliably predict liver damage in naïve-treatment patients with CHB.

Dose–response relationship between serum N-glycan markers and liver fibrosis in chronic hepatitis B

BackgroundEvaluation of liver fibrosis played a monumental role in the diagnosis and monitoring of chronic hepatitis B (CHB). We aimed to explore the value of serum N-glycan markers in liver fibrosis.MethodsThis multi-center (33 hospitals) study recruited 760 treatment-naïve CHB patients who underwent liver biopsy. Serum N-glycan markers were analyzed by DNA sequencer-assisted fluorophore-assisted with capillary electrophoresis (DSA-FACE) technology. First, we explore the relationship between 12 serum N-glycan markers and the fibrosis stage. Then, we developed a Px score for diagnosing significant fibrosis using the LASSO regression. Next, we compared the diagnostic performances between Px, LSM, APRI, and FIB-4. Finally, we explored the relationships between glycosyltransferase gene and liver fibrosis with RNA-transcriptome sequencing.ResultsWe included 622 CHB participants: male-dominated (69.6%); median age 42.0 (IQR 34.0–50.0); 287 with normal ALT; 73.0% with significant fibrosis. P5(NA2), P8(NA3), and P10(NA4) were opposite to the degree of fibrosis, while other profiles (except for P0[NGA2]) increased with the degree of fibrosis. Seven profiles (P1[NGA2F], P2[NGA2FB], P3[NG1A2F], P4[NG1A2F], P7[NA2FB], P8[NA3], and P9[NA3Fb]) were selected into Px score. Px score was associated with an increased risk of significant fibrosis (for per Px score increase, the risk of significant fibrosis was increased by 3.54 times (OR = 4.54 [2.63–7.82]) in the fully-adjusted generalized linear model. p for trend was <0.001. The diagnostic performance of the Px score was superior to others. Glycosyltransferase genes were overexpressed in liver fibrosis, and glycosylation and glycosyltransferase-related pathways were significantly enriched.ConclusionsSerum N-glycan markers were positively correlated with liver fibrosis. Px score had good performance in distinguishing significant fibrosis.

High sensitivity profiling of N-glycans from mouse serum using fluorescent imidazolium tags by HILIC electrospray ionisation spectrometry

N-linked glycosylation is a ubiquitous protein post-translational modification in which aberrant glycan biosynthesis has been linked to severe conditions like cancer. Accurate qualitative and quantitative analysis of N-glycans are crucial for investigating their physiological functions. Owing to the intrinsic absence of chromophores and high polarity of the glycans, current detection methods are restricted to liquid chromatography and mass spectrometry. Herein, we describe three new imidazolium-based glycan tags: 2’GITag, 3’GITag, and 4’GITag, that significantly improve both the limit of detection and limit of quantification of derivatized oligosaccharides, in terms of fluorescence intensity and ionisation efficiency. Our top-performing derivatisation agent, 4’GITag, shifted the detection sensitivity range from high femtomole to sub-femtomole levels in ESI-MS compared to traditional glycan label, 2AB, enabling the identification of 24 N-glycans in mouse serum, including those bearing sialic acids. Additionally, 4’GITag stabilized Na-salt forms of sialic acids, simplifying the simultaneous analysis of neutral and negative charged N-glycans significantly, avoiding the need for complex derivatisation procedures typically required for the detection of sialylated species. Overall, the favorable performance of imidazolium tags in the derivatisation and sensitive profiling of glycans has the potential for labeling tissue or live cells to explore disease biomarkers and for developing new targeted therapeutic strategies.

D-mannose as a new therapy for fucokinase deficiency-related congenital disorder of glycosylation (FCSK-CDG)

IntroductionFucokinase deficiency-related congenital disorder of glycosylation (FCSK-CDG) is a rare autosomal recessive inborn error of metabolism characterized by a decreased flux through the salvage pathway of GDP-fucose biosynthesis due to a block in the recycling of L-fucose that exits the lysosome. FCSK-CDG has been described in 5 individuals to date in the medical literature, with a phenotype comprising global developmental delays/intellectual disability, hypotonia, abnormal myelination, posterior ocular disease, growth and feeding failure, immune deficiency, and chronic diarrhea, without clear therapeutic recommendations. Patient and methodsIn a so far unreported FCSK-CDG patient, we studied proteomics and glycoproteomics in vitro in patient-derived fibroblasts and also performed in vivo glycomics, before and after treatment with either D-Mannose or L-Fucose. ResultsWe observed a marked increase in fucosylation after D-mannose supplementation in fibroblasts compared to treatment with L-Fucose. The patient was then treated with D-mannose at 850 mg/kg/d, with resolution of the chronic diarrhea, resolution of oral aversion, improved weight gain, and observed developmental gains. Serum N-glycan profiles showed an improvement in the abundance of fucosylated glycans after treatment. No treatment-attributed adverse effects were observed. ConclusionD-mannose is a promising new treatment for FCSK-CDG.

Serum N-glycomic profiling identifies candidate biomarker panels for assessing coronary artery stenosis severity

Stenosis severity may escalate over the course of coronary artery disease (CAD), increasing the risk of death for the patient. Conventionally, the assessment of stenosis degree relies on invasive coronary angiography (ICA), an invasive examination unsuitable for patients in poor physical condition or those with contrast allergies and one that imposes a psychological burden on patients. Although abnormal serum N-glycan profiles have exhibited robust associations with various cardiovascular diseases, including CAD, their potential in diagnosing CAD stenosis remains to be determined. In this study, we performed a comprehensive analysis of serum N-glycome from 132 patients who underwent ICA and 27 healthy controls using MALDI-TOF-mass spectrometry. The patients who underwent ICA examination were categorized into four groups based on stenosis severity: no/mild/moderate/severe stenosis. Twenty-seven N-glycans were directly quantified, and 47 derived glycan traits were obtained. Notably, among these 74 glycan features, 18 exhibited variations across the study groups. Using a combination of least absolute shrinkage and selection operator and logistic regression analyses, we developed five diagnostic models for recognizing stenosis degree. Our results suggested that alterations in serum N-glycosylation modifications might be valuable for identifying stenosis degree and monitoring disease progression in individuals with CAD. It is expected to offer a noninvasive alternative for those who could not undergo ICA because of various reasons. However, the diagnostic potential of serum N-glycan panels as biomarkers requires multicenter, large cohort validation in the future.

N-glycan biosignatures as a potential diagnostic biomarker for early-stage pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of less than 10%, owing to its late-stage diagnosis. Early detection of pancreatic cancer (PC) can significantly increase survival rates. To identify the serum biomarker signatures associated with early-stage PDAC by serum N-glycan analysis. An extensive patient cohort was used to determine a biomarker signature, including patients with PDAC that was well-defined at an early stage (stages I and II). The biomarker signature was derived from a case-control study using a case-cohort design consisting of 29 patients with stage I, 22 with stage II, 4 with stage III, 16 with stage IV PDAC, and 88 controls. We used multiparametric analysis to identify early-stage PDAC N-glycan signatures and developed an N-glycan signature-based diagnosis model called the "Glyco-model". The biomarker signature was created to discriminate samples derived from patients with PC from those of controls, with a receiver operating characteristic area under the curve of 0.86. In addition, the biomarker signature combined with cancer antigen 19-9 could discriminate patients with PDAC from controls, with a receiver operating characteristic area under the curve of 0.919. Glyco-model demonstrated favorable diagnostic performance in all stages of PC. The diagnostic sensitivity for stage I PDAC was 89.66%. In a prospective validation study, this serum biomarker signature may offer a viable method for detecting early-stage PDAC.

Unlocking the diagnostic potential: N-Glycan profiling for distinguishing breast cancer patients from healthy individuals

Chest sickness is now the most broadly perceived dangerous development, addressing 12.5% of all new yearly harmful development cases all over the planet. Around 13% (around 1 out of 8) of U.S. women will cultivate prominent chest illness all through their lives. In 2022, a normal 287,850 new occurrences of prominent chest illness should be examined in women in the U.S., close to 51,400 new examples of easy chest dangerous development. The exploration directed a review where N-glycans were gotten from the serum of bosom disease patients and solid people, and their general overflow contrasts were used for primer bosom malignant growth determination. Through Fractional Least Squares Discriminant Examination (PLS-DA), the creator had the option to successfully recognize bosom malignant growth patients from the sound populace, demonstrating the capability of N-glycan profiles in segregating between bosom disease and non-bosom disease people. This examination denotes a promising step towards the improvement of expected demonstrative and prognostic markers for bosom disease, giving likely biomarkers to beginning-phase bosom malignant growth patients. The discoveries of this study might hold critical pertinence in the field of bosom disease determination and treatment. This exploration will utilize work area and trial. Past assessment found that the level of serum N-glycan A2G1(6)FB, a biantennary N-glycan containing focus fucose and bisecting GlcNAc developments was higher in chest-threatening development patients than in those without chest illness. Additionally, A2G1(6)FB was recognizable in chest dangerous development patients with starting stage and could be a precise marker. Hence, concurrent utilization of IgG blood tests and customary biomarkers could work on the exactness of bosom disease determination, recommending that IgG blood tests might be a solid biomarker for beginning phase bosom malignant growth patients.

Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

BackgroundOvarian cancer (OC) is one of the most common gynecological tumors with high morbidity and mortality. Altered serum N-glycome has been observed in many diseases, while the association between serum protein N-glycosylation and OC progression remains unclear, particularly for the onset of carcinogenesis from benign neoplasms to cancer.MethodsHerein, a mass spectrometry based high-throughput technique was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasms and different stages of OC. To elucidate the alterations of glycan features in OC progression, an orthogonal strategy with lectin-based ELISA was performed.ResultsIt was observed that the initiation and development of OC was associated with increased high-mannosylationand agalactosylation, concurrently with decreased total sialylation of serum, each of which gained at least moderately accurate merits. The most important individual N-glycans in each glycan group was H7N2, H3N5 and H5N4S2F1, respectively. Notably, serum N-glycome could be used to accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared to CA125 and HE4. Furthermore, bioinformatics analysis based discriminative model verified the diagnostic performance of serum N-glycome for OC in two independent sets.ConclusionsThese findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.

P1042 Serum N-glycan Biomarkers Predict Patient Response to Biologics for Crohn’s Disease

Abstract Background Several therapeutic antibodies are approved to treat Crohn’s Disease (CD), for example, Vedolizumab (anti-α4β7), Ustekinumab (targets IL-12 and IL-23), Adalimumab and Infliximab (anti-TNF). Glycosylation alterations have been associated with CD, but have not been thoroughly investigated as potential predictors of disease remission¹. A comparison of serum N-glycan profiles between responders and non-responders prior to each therapy was used to detect potential biomarkers to response. The N-glycan composition after treatment was used to distinguish the different mechanisms of the biologics. In addition, a comparison of glycomic profiles across the different therapies could highlight the distinct biological pathways involved in response. Methods Serum samples, before (t1) and after (t2) treatment, were taken from 166 patients, containing the four sub-cohorts of patients under different biologics with CD. Treatment response, observed in 100 patients, was assessed by a combination of clinical and endoscopic outcomes. Firstly, the Serum N-glycans were detected by hydrophilic interaction liquid chromatography to produce a 62-peak chromatogram. Followed by quantifying the relative area of 62 glycan peaks via HappyTools². Logistic regression was used to determine which glycan peaks at t1 are predictive of response (p-value &amp;lt;0.05) and which are markers of response (p-value&amp;lt;0.05). 5 fold cross-validation tested on a variety of classifiers was used to derive the optimal predictor of response. The glycomic profiles across the four biologics, at both t1 and t2, were compared through the Kruskal test. The significant peaks (p-value &amp;lt; 0.05) were then combined to generate a multiclass model to predict response in each therapeutic. Results The N-glycan classification models for all four sub-cohorts under different biologics, Ustekinumab (0.78 AUC), Adalimumab (0.82 AUC), Infliximab (0.75 AUC), Vedolizumab (0.75 AUC), performed moderately well at predicting therapy response prior to treatment(figure 1A). In turn, patients could be identified as responders after treatment by N-glycan based classification models, Ustekinumab (0.70 AUC), Adalimumab (0.86 AUC), Infliximab (0.85 AUC), Vedolizumab (0.84 AUC). Prior to treatment, patients who responded were strongly distinguished by the therapy type (0.96 AUC) through a combination of 13 significant glycan peaks (figure 1B). Conclusion This study has demonstrated multiple N-glycans are potential predictors of biological response, with the possibility to guide clinicians in the most appropriate form of treatment. These results require the integration of mass spectrometry and validation by larger cohorts.

Serum-based Comprehensive N-Glycans Profiling Analysis in Different Gastric Disease Stages by Porous Graphitic Carbon Liquid Chromatography-Mass Spectrometry Associated With Potential Marker Discovery.

N-glycans are potential serum biomarkers due to their aberrant structure and abundance alteration during disease progression. Few studies have been associated with relative quantitative N-glycans profiling during different gastric disease stages. In this study, we conducted an investigation on the profiling of N-glycans in patients with gastric disease, as well as in healthy controls. In this study, the porous graphitization carbon chromatography-high resolution Fourier transform mass spectrometry (PGC-FTMS) method was applied to assess comprehensive N-glycans profiling in patients at different stages of gastric disease, including gastritis, atrophic gastritis, gastric ulcer, gastric polyps, and gastric cancer. A total of 45 N-glycans (relative abundance >0.1%) were detected, and 9 N-glycans were found to be potential biomarkers for gastric disease detection. Along with the progression of gastric disease, the abundance of sialylated N-glycans increased, while that of core-fucosylated N-glycans decreased. Multivariate statistical analysis demonstrated that N-glycans profiling between gastritis and healthy controls had significant differences. The characteristic N-glycans distinguished gastric cancer from healthy controls, which had strong clinical diagnostic value. The relative quantitative profile of N-glycans in different gastric disease stages was revealed and serum N-glycans are proposed for distinguishing gastric disease stages in clinical application.

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Protein glycosylation is associated with the pathogenesis of various cancers. The utilization of certain glycans in cancer diagnosis models holds promise, yet their accuracy is not always guaranteed. Here, we investigated the utility of deep learning techniques, specifically random forests combined with transfer learning, in enhancing serum glycome's discriminative power for cancer diagnosis (including ovarian cancer, non-small cell lung cancer, gastric cancer, and esophageal cancer). We started with ovarian cancer and demonstrated that transfer learning can achieve superior performance in data-disadvantaged cohorts (AUROC >0.9), outperforming the approach of PLS-DA. We identified a serum glycan-biomarker panel including 18 serum N-glycans and 4 glycan derived traits, most of which were featured with sialylation. Furthermore, we validated advantage of the transfer learning scheme across other cancer groups. These findings highlighted the superiority of transfer learning in improving the performance of glycans-based cancer diagnosis model and identifying cancer biomarkers, providing a new high-fidelity cancer diagnosis venue.

Comprehensive serum N-glycan profiling identifies a biomarker panel for early diagnosis of non-small-cell lung cancer.

Aberrant serum N-glycan profiles have been observed in multiple cancers including non-small-cell lung cancer (NSCLC), yet the potential of N-glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N-glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI-TOF-MS. The levels of serum N-glycans and N-glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N-glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N-glycan structures were identified in human serum. Compared with healthy controls, 29 serum N-glycans were increased or decreased in NSCLC patients. N-glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N-glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early-stage patients from healthy controls (AUC=0.88). In conclusion, our work highlights the abnormal N-glycan profiles in NSCLC and provides supports potential application of N-glycan biomarker panel in clinical NSCLC detection.

Novel Three-Dimensional Hierarchical Porous Carbon Probe for the Discovery of N-Glycan Biomarkers and Early Hepatocellular Carcinoma Detection.

Due to the highly heterogeneous nature of hepatocellular carcinoma (HCC), the accurate diagnosis of HCC during the early phase of development is still a challenging task. Therefore, the further development of novel diagnostic methods by discovering new biomarkers is required to improve the rate of HCC diagnosis in the early phase. In this work, an oxygen-modified three-dimensional interconnected porous carbon probe is designed and fabricated to profile the differences of N-glycans in human serum from health controls (H) and patients with hepatic dysfunction (HD) and HCC for the discovery of new biomarkers with HCC development. Excitingly, we discovered that the expression levels of 12 serum N-glycans were gradually increased from H to patients with HD and eventually to patients with HCC. Moreover, two machine learning models established based on these 12 serum N-glycans reached a satisfactory accuracy for predicting HCC development where the receiver operating characteristic curve arrived above 0.95 for distinguishing healthy controls and patients with liver diseases (HD or HCC) and the ROC curve arrived at 0.85 for distinguishing HD and HCC. Our work not only developed a new method for the large-scale characterization of serum N-glycans but also provided valuable guidance for accurate and highly sensitive diagnosis of early liver cancer development in a non-invasive manner.

Total serum N-glycans mark visceral leishmaniasis in human infections with Leishmania infantum

Visceral leishmaniasis (VL) is a clinical form of leishmaniasis with high mortality rates when not treated. Diagnosis suffers from invasive techniques and sub-optimal sensitivities. The current (affordable) treatment with pentavalent antimony as advised by the WHO is possibly harmful to the patient. There is need for an improved diagnosis to prevent possibly unnecessary treatment. N-glycan analysis may aid in diagnosis. We evaluated the N-glycan profiles from active VL, asymptomatic infections (ASYMP) and controls from non-endemic (NC) and endemic (EC) areas. Active VL has a distinct N-glycome profile that associates with disease severity. Our study suggests that the observed glycan signatures could be a valuable additive to diagnosis and assist in identifying possible markers of disease and understanding the pathogenesis of VL. Further studies are warranted to assess a possible future role of blood glycome analysis in active VL diagnosis and should aim at disease specificity.

Serum N-Glycosylation RPLC-FD-MS Assay to Assess Colorectal Cancer Surgical Interventions.

A newly developed analytical strategy was applied to profile the total serum N-glycome of 64 colorectal cancer (CRC) patients before and after surgical intervention. In this cohort, it was previously found that serum N-glycome alterations in CRC were associated with patient survival. Here, fluorescent labeling of serum N-glycans was applied using procainamide and followed by sialic acid derivatization specific for α2,6- and α2,3-linkage types via ethyl esterification and amidation, respectively. This strategy allowed efficient separation of specific positional isomers on reversed-phase liquid chromatography-fluorescence detection-mass spectrometry (RPLC-FD-MS) and complemented the previous glycomics data based on matrix-assisted laser desorption/ionization (MALDI)-MS that did not include such separations. The results from comparing pre-operative CRC to post-operative samples were in agreement with studies that identified a decrease in di-antennary structures with core fucosylation and an increase in sialylated tri- and tetra-antennary N-glycans in CRC patient sera. Pre-operative abundances of N-glycans showed good performance for the classification of adenocarcinoma and led to the revisit of the previous MALDI-MS dataset with regard to histological and clinical data. This strategy has the potential to monitor patient profiles before, during, and after clinical events such as treatment, therapy, or surgery and should also be further explored.

Human complement component C3 N-glycome changes in type 1 diabetes complications.

Changes in N-glycosylation have been described in numerous diseases and are being considered as biomarkers of ongoing pathological condition. Previous studies demonstrated the interrelation of N-glycosylation and type 1 diabetes (T1D), particularly linking serum N-glycan changes with complications accompanying the disease. Moreover, the role of complement component C3 in diabetic nephropathy and retinopathy has been implicated, and C3 N-glycome was found to be altered in young T1D patients. Therefore, we investigated associations between C3 N-glycan profiles and albuminuria and retinopathy accompanying T1D, as well as glycosylation connection with other known T1D complication risk factors. Complement component C3 N-glycosylation profiles have been analyzed from 189 serum samples of T1D patients (median age 46) recruited at a Croatian hospital centre. Using our recently developed high-throughput method, relative abundances of all six of the C3 glycopeptides have been determined. Assessment of C3 N-glycome interconnection with T1D complications, hypertension, smoking status, estimated glomerular filtration rate (eGFR), glycaemic control and duration of the disease was done using linear modelling. Significant changes of C3 N-glycome in severe albuminuria accompanying type 1 diabetes were observed, as well as in T1D subjects with hypertension. All except one of the C3 glycopeptides proved to be associated with measured HbA1c levels. One of the glycoforms was shown to be changed in non-proliferative T1D retinopathy. Smoking and eGFR showed no effect on C3 N-glycome. Furthermore, C3 N-glycosylation profile was shown to be independent of disease duration. This study empowered the role of C3 N-glycosylation in T1D, showing value in distinguishing subjects with different diabetic complications. Being independent of the disease duration, these changes may be associated with the disease onset, making C3 N-glycome a potential novel marker of the disease progression and severity.