The potential of N-glycosylation profiles as biomarkers for monitoring the progression of Type II diabetes mellitus towards diabetic kidney disease

Lectin-mediated, time-efficient, and high-yield sorting of different morphologically intact nephron segments

The kidney is a highly complex organ equipped with a multitude of miniscule filter-tubule units called nephrons. Each nephron can be subdivided into multiple segments, each with its own morphology and physiological function. To date, conventional manual approaches to isolate specific nephron segments are very laborious, time-consuming, often limited to only a specific segment, and typically have low yield. Here, we describe a novel, unconventional method that is superior in many aspects to previous protocols by combining low-cost fluorophore-conjugated lectins or agglutinins (Flaggs) with flow sorting. This allows the simultaneous separation of different nephron segments with preserved 3D morphology from mouse or human samples in under 3 h. Using a 200-µm nozzle and 5 psi, glomeruli, proximal, or distal convoluted tubules are sorted with Cy3-labeled Sambucus Nigra agglutinin (SNA-Cy3), Fluorescein-labeled Lotus Tetragonolobus lectin (LTL-FITC), or Pacific Blue-labeled soybean agglutinin (SBA-PB), respectively. Connecting tubules and collecting ducts are sorted by double-positive SBA-PB and SNA-Cy3 signals, while thick ascending limb segments are characterized by the absence of any Flaggs labeling. From two mouse kidneys, this yields 37-521 ng protein/s or 0.71-16.71 ng RNA/s, depending on the specific nephron segment. The purity of sorted segments, as assessed by mRNA expression level profiling of 15 genes, is very high with a 96.1-fold median enrichment across all genes and sorted segments. In summary, our method represents a simple, straightforward, cost-effective, and widely applicable tool yielding high amounts of pure and morphologically largely intact renal tubule materials with the potential to propel nephron segment-specific research.

Water-stable hydrophilic metal organic framework composite for the recognition of N-glycopeptides during diabetes progression by mass spectrometry

A hydrophilic Al-MOFs composite was prepared using cheap and available reagents in water via a suitable large-scale production, an economical and environment-friendly method for capturing N-glycopeptides. The prepared Al-MOFs composite with high hydrolytically stable and hydrophilic 1D channels exhibits an ultralow detection limit (0.5 fmol/μL), and excellent reusability (at least 10 cycles) in the capture of N-glycopeptides from standard bio-samples. Interestingly, the Al-MOFs composite also shows remarkable performance in practical applications, where 300 N-glycopeptides ascribed to 124 glycoproteins were identified in 1 µL human serum and were successfully applied in profiling the differences of N-glycopeptides during diabetes progression. Moreover, 12 specific glycoproteins used as biomarkers to accurately distinguish the progression of diabetes are identified. The present work provides a potential commercial method for large-scale glycoproteomics research in complex clinical samples while offering new guidance for the precise diagnosis of diabetes progression.

Metabolomic Markers of Ultra-Processed Food and Incident CKD

BACKGROUND

High ultra-processed food consumption is associated with higher risk of CKD. However, there is no biomarker for ultra-processed food, and the mechanism through which ultra-processed food is associated with CKD is not clear. Metabolomics can provide objective biomarkers of ultra-processed food and provide important insights into the mechanisms by which ultra-processed food is associated with risk of incident CKD. Our objective was to identify serum metabolites associated with ultra-processed food consumption and investigate whether ultra-processed food-associated metabolites are prospectively associated with incident CKD.

METHODS

We used data from 3751 Black and White men and women (aged 45-64 years) in the Atherosclerosis Risk in Communities study. Dietary intake was assessed using a semiquantitative 66-item food frequency questionnaire, and ultra-processed food was classified using the NOVA classification system. Multivariable linear regression models were used to identify the association between 359 metabolites and ultra-processed food consumption. Cox proportional hazards models were used to investigate the prospective association of ultra-processed food-associated metabolites with incident CKD.

RESULTS

Twelve metabolites (saccharine, homostachydrine, stachydrine, N2, N2-dimethylguanosine, catechol sulfate, caffeine, 3-methyl-2-oxovalerate, theobromine, docosahexaenoate, glucose, mannose, and bradykinin) were significantly associated with ultra-processed food consumption after controlling for false discovery rate <0.05 and adjusting for sociodemographic factors, health behaviors, eGFR, and total energy intake. The 12 ultra-processed food-related metabolites significantly improved the prediction of ultra-processed food consumption (difference in C statistics: 0.069, P <1×10 -16 ). Higher levels of mannose, glucose, and N2, N2-dimethylguanosine were associated with higher risk of incident CKD after a median follow-up of 23 years.

CONCLUSIONS

We identified 12 serum metabolites associated with ultra-processed food consumption and three of them were positively associated with incident CKD. Mannose and N2, N2-dimethylguanosine are novel markers of CKD that may explain observed associations between ultra-processed food and CKD.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_03_08_CJN08480722.mp3.

Mass spectrometry-based N-glycosylation analysis in kidney disease

Kidney disease is a global health concern with an enormous expense. It is estimated that more than 10% of the population worldwide is affected by kidney disease and millions of patients would progress to death prematurely and unnecessarily. Although creatinine detection and renal biopsy are well-established tools for kidney disease diagnosis, they are limited by several inevitable defects. Therefore, diagnostic tools need to be upgraded, especially for the early stage of the disease and possible progression. As one of the most common post-translational modifications of proteins, N-glycosylation plays a vital role in renal structure and function. Deepening research on N-glycosylation in kidney disease provides new insights into the pathophysiology and paves the way for clinical application. In this study, we reviewed recent N-glycosylation studies on several kidney diseases. We also summarized the development of mass spectrometric methods in the field of N-glycoproteomics and N-glycomics.

Multi-block data integration analysis for identifying and validating targeted N-glycans as biomarkers for type II diabetes mellitus

Plasma N-glycan profiles have been shown to be defective in type II diabetes Mellitus (T2DM) and holds a promise to discovering biomarkers. The study comprised 232 T2DM patients and 219 healthy individuals. N-glycans were analysed by high-performance liquid chromatography. The multivariate integrative framework, DIABLO was employed for the statistical analysis. N-glycan groups (GPs 34, 32, 26, 31, 36 and 30) were significantly expressed in T2DM in component 1 and GPs 38 and 20 were related to T2DM in component 2. Four clusters were observed based on the correlation of the expressive signatures of the 39 N-glycans across T2DM and controls. Cluster A, B, C and D had 16, 16, 4 and 3 N-glycans respectively, of which 11, 8, 1 and 1 were found to express differently between controls and T2DM in a univariate analysis \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(p < 0.05)$$\end{document}(p<0.05). Multi-block analysis revealed that trigalactosylated (G3), triantennary (TRIA), high branching (HB) and trisialylated (S3) expressed significantly highly in T2DM than healthy controls. A bipartite relevance network revealed that HB, monogalactosylated (G1) and G3 were central in the network and observed more connections, highlighting their importance in discriminating between T2DM and healthy controls. Investigation of these N-glycans can enhance the understanding of T2DM.

Protein N-glycosylation aberrations and glycoproteomic network alterations in osteoarthritis and osteoarthritis with type 2 diabetes

Whether the relationship between type 2 diabetes mellitus (T2DM) and osteoarthritis (OA) can be solely attributed to the shared risk factors, such as obesity, remains controversial. Several studies have revealed the critical role of abnormal glycosylation in the pathogenesis of OA and T2DM. Therefore, we speculate that T2DM may contribute to the pathogenesis of OA through the intrinsic mechanisms of N-glycosylation aberrations. Using N-glycoproteomics, we compared the changes in N-glycosylated protein abundance in cartilage samples from patients with OA without and with T2DM (DM-OA), and from patients with traumatic joint injury (NC) as controls. We identified 847 N-glycosylation sites corresponding to 729 peptides fragments from 374 proteins. The number of N-glycosylated proteins in the DM-OA group tended to decrease compared with that in the OA and NC groups. We identified 22 upregulated and 1 down-regulated N-glycosylated peptides in the OA group compared to the NC group, while only fibronectin 1 (FN1) at position N1007, cartilage intermediate layer protein 1 (CILP) at N346, and collagen type VI alpha 1 chain (COL6A1) at N804, were also identified in the DM-OA group. Compared to the OA group, the downregulation of secreted protein acidic and rich in cysteine (SPARC) at N116, collagen type VI alpha 1 chain (COL6A2) at N785, and asporin (ASPN) at N282, and the upregulation of complement component C8 alpha chain (C8α) at N437, were the most remarkable alterations in the DM-OA group. The differentially expressed N-glycosylated proteins between the OA and DM-OA groups were mainly located extracellularly and enriched in the KEGG pathways involving PI3K/Akt signaling, focal adhesion, and ECM-receptor interaction. Their predicted protein–protein interactions were also depicted. We were thus able to show the general characteristics of N-glycosylation aberrations in OA and DM-OA. Moreover, the upregulated glycosylated complement C8α in the DM-OA group might augment membrane attack complex activity, thereby exacerbating cartilage destruction. Although further confirmation is required, our hypothesis proposes a possible explanation for the deduction that T2DM is an independent risk factor for OA.

The Rapidly Expanding Nexus of Immunoglobulin G N-Glycomics, Suboptimal Health Status, and Precision Medicine

Immunoglobulin G is a prevalent glycoprotein, whose downstream immune responses are partially mediated by the N-glycans within the fragment crystallisable domain. Collectively termed the N-glycome, it is considered a complex intermediate phenotype: an amalgamation of genetic predisposition, environmental exposure, and health behaviours over the life-course. Thus, the immunoglobulin G N-glycome may provide an indication of health status on the spectrum from health to disease and infirmary. Although variability exists within and between populations, composition of the immunoglobulin G N-glycome remains stable over short periods of time. This underscores the potential of harnessing the immunoglobulin G N-glycome as an ideal tool for preclinical disease risk prediction, stratification, and prognosis through the development of precise dynamic biomarkers.

Plasma protein N-glycosylation is associated with cardiovascular disease, nephropathy, and retinopathy in type 2 diabetes

INTRODUCTION

Although associations of total plasma N-glycome (TPNG) with type 2 diabetes have been reported, little is known on the role of TPNG in type 2 diabetes complications, a major cause of type 2 diabetes-related morbidity and mortality. Here, we assessed TPNG in relation to type 2 diabetes complications in subsamples of two Dutch cohorts using mass spectrometry (n=1815 in DiaGene and n=1518 in Hoorn Diabetes Care System).

RESEARCH DESIGN AND METHODS

Blood plasma samples and technical replicates were pipetted into 96-well plates in a randomized manner. Peptide:N-glycosidase F (PNGase F) was used to release N-glycans, whereafter sialic acids were derivatized for stabilization and linkage differentiation. After total area normalization, 68 individual glycan compositions were quantified in total and were used to calculate 45 derived traits which reflect structural features of glycosylation. Associations of glycan features with prevalent and incident microvascular or macrovascular complications were tested in logistic and Cox regression in both independent cohorts and the results were meta-analyzed.

RESULTS

Our results demonstrated similarities between incident and prevalent complications. The strongest association for prevalent cardiovascular disease was a high level of bisection on a group of diantennary glycans (A2FS0B; OR=1.38, p=1.34×10^-11), while for prevalent nephropathy the increase in 2,6-sialylation on triantennary glycans was most pronounced (A3E; OR=1.28, p=9.70×10^-6). Several other TPNG features, including fucosylation, galactosylation, and sialylation, firmly demonstrated associations with prevalent and incident complications of type 2 diabetes.

CONCLUSIONS

These findings may provide a glance on how TPNG patterns change before complications emerge, paving the way for future studies on prediction biomarkers and potentially disease mechanisms.

Novel Urinary Glycan Biomarkers Predict Cardiovascular Events in Patients With Type 2 Diabetes: A Multicenter Prospective Study With 5-Year Follow Up (U-CARE Study 2)

Background: Although various biomarkers predict cardiovascular event (CVE) in patients with diabetes, the relationship of urinary glycan profile with CVE in patients with diabetes remains unclear.

Methods: Among 680 patients with type 2 diabetes, we examined the baseline urinary glycan signals binding to 45 lectins with different specificities. Primary outcome was defined as CVE including cardiovascular disease, stroke, and peripheral arterial disease.

Results: During approximately a 5-year follow-up period, 62 patients reached the endpoint. Cox proportional hazards analysis revealed that urinary glycan signals binding to two lectins were significantly associated with the outcome after adjustment for known indicators of CVE and for false discovery rate, as well as increased model fitness. Hazard ratios for these lectins (+1 SD for the glycan index) were UDA (recognizing glycan: mixture of Man5 to Man9): 1.78 (95% CI: 1.24–2.55, P = 0.002) and Calsepa [High-Man (Man2–6)]: 1.56 (1.19–2.04, P = 0.001). Common glycan binding to these lectins was high-mannose type of N-glycans. Moreover, adding glycan index for UDA to a model including known confounders improved the outcome prediction [Difference of Harrel's C-index: 0.028 (95% CI: 0.001–0.055, P = 0.044), net reclassification improvement at 5-year risk increased by 0.368 (0.045–0.692, P = 0.026), and the Akaike information criterion and Bayesian information criterion decreased from 725.7 to 716.5, and 761.8 to 757.2, respectively].

Conclusion: The urinary excretion of high-mannose glycan may be a valuable biomarker for improving prediction of CVE in patients with type 2 diabetes, and provides the rationale to explore the mechanism underlying abnormal N-glycosylation occurring in patients with diabetes at higher risk of CVE.

Trial Registration: This study was registered with the University Hospital Medical Information Network on June 26, 2012 (Clinical trial number: UMIN000011525, URL: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000013482).

COVID-19 and Preparing Planetary Health for Future Ecological Crises: Hopes from Glycomics for Vaccine Innovation

A key lesson emerging from COVID-19 is that pandemic proofing planetary health against future ecological crises calls for systems science and preventive medicine innovations. With greater proximity of the human and animal natural habitats in the 21st century, it is also noteworthy that zoonotic infections such as COVID-19 that jump from animals to humans are increasingly plausible in the coming decades. In this context, glycomics technologies and the third alphabet of life, the sugar code, offer veritable prospects to move omics systems science from discovery to diverse applications of relevance to global public health and preventive medicine. In this expert review, we discuss the science of glycomics, its importance in vaccine development, and the recent progress toward discoveries on the sugar code that can help prevent future infectious outbreaks that are looming on the horizon in the 21st century. Glycomics offers veritable prospects to boost planetary health, not to mention the global scientific capacity for vaccine innovation against novel and existing infectious agents.

Glycosylation Profiling as a Biomarker of Suboptimal Health Status for Chronic Disease Stratification

WHO defines health as "a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity." We coined and defined suboptimal health status (SHS) as a subclinical, reversible stage of the pre-chronic disease. SHS is a physical state between health and disease, characterized by health complaints, general weakness, chronic fatigue, and low energy levels. We have developed an instrument to measure SHS, Suboptimal Health Status Questionnaire-25 (SHSQ-25), a self-reported survey assessing five health components that has been validated in various ethnical populations. Our studies suggest that SHS is associated with the major components of cardiovascular health and the early onset of metabolic diseases. Besides subjective measure of health (SHS), glycans are conceived as objective biomarkers of SHS. Glycans are complex and branching carbohydrate moieties attached to proteins, participating in inflammatory regulation and chronic disease pathogenesis. We have been investigating the role of glycans and SHS in multiple cardiometabolic diseases in different ethnical populations (African, Chinese, and Caucasian). Here we present case studies to prove that a combination of subjective health measure (SHS) with objective health measure (glycans) represents a window of opportunity to halt or reverse the progression of chronic diseases.

Protein Glycosylation in Diabetes

Diabetes mellitus is a group of metabolic disorders characterized by the presence of hyperglycaemia. Due to its high prevalence and substantial heterogeneity, many studies have been investigating markers that could identify predisposition for the disease development, differentiate between the various subtypes, establish early diagnosis, predict complications or represent novel therapeutic targets. N-glycans, complex oligosaccharide molecules covalently linked to proteins, emerged as potential markers and functional effectors of various diabetes subtypes, appearing to have the capacity to meet these requirements. For instance, it has been shown that N-glycome changes in patients with type 2 diabetes and that N-glycans can even identify individuals with an increased risk for its development. Moreover, genome-wide association studies identified glycosyltransferase genes as candidate causal genes for both type 1 and type 2 diabetes. N-glycans have also been suggested to have a major role in preventing the impairment of glucose-stimulated insulin secretion by modulating cell surface expression of glucose transporters. In this chapter we aimed to describe four major diabetes subtypes: type 1, type 2, gestational and monogenic diabetes, giving an overview of suggested role for N-glycosylation in their development, diagnosis and management.

Fibrinogen Fucosylation as a Prognostic Marker of End-Stage Renal Disease in Patients on Peritoneal Dialysis

Glycosylation may strongly affect protein structure and functions. A high risk of cardiovascular complications seen in patients with end-stage renal disease (ESRD) is, at least partly associated with delayed clot formation, increased clot strength, and delayed cloth lysis. Taking into consideration that fibrinogen mediates these processes, we isolated fibrinogen from the plasma from patients with ESRD on peritoneal dialysis (ESRD-PD), and examined glycosylation of native fibrinogen and its subunits by lectin-based microarray and lectin blotting. Compared to healthy controls, fibrinogen from patients had increased levels of A2BG2 and decreased levels of FA2 glycan. The distribution of glycans on individual chains was also affected, with the γ chain, responsible for physiological functions of fibrinogen (such as coagulation and platelet aggregation), being most prone to these alterations. Increased levels of multi-antennary N-glycans in ESRD-PD patients were also associated with the type of dialysis solutions, whereas an increase in the fucosylation levels was strongly related to the peritoneal membrane damage. Consequently, investigation of fibrinogen glycans can offer better insight into fibrinogen-related complications observed in ESRD-PD patients and, additionally, contribute to prognosis, choice of personalised therapy, determination of peritoneal membrane damage, and the length of utilization of peritoneum for dialysis.

Association of the IgG N-glycome with the course of kidney function in type 2 diabetes

INTRODUCTION

Inflammatory processes are thought to be involved in kidney function decline in individuals with type 2 diabetes. Glycosylation of immunoglobulin G (IgG) is an important post-translation process affecting the inflammatory potential of IgG. We investigated the prospective relationship between IgG N-glycosylation patterns and kidney function in type 2 diabetes.

RESEARCH DESIGN AND METHODS

In the DiaGene study, an all-lines-of-care case-control study (n=1886) with mean prospective follow-up of 7.0 years, the association between 58 IgG N-glycan profiles and estimated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) per year and during total follow-up was analyzed. Models were adjusted for clinical variables and multiple comparisons.

RESULTS

Eleven traits were significantly associated with eGFR change per year. Bisecting GlcNAc in fucosylated and fucosylated disialylated structures and monosialylation of fucosylated digalactosylated structures were associated with a faster decrease of eGFR. Fucosylation of neutral and monogalactosylated structures was associated with less eGFR decline per year. No significant associations between IgG glycans and ACR were found.

CONCLUSIONS

In type 2 diabetes, we found IgG N-glycosylation patterns associated with a faster decline of kidney function, reflecting a pro-inflammatory state of IgG. eGFR, but not ACR, was associated with IgG glycans, which suggests these associations may represent renal macroangiopathy rather than microvascular disease.

Next-Generation (Glycomic) Biomarkers for Cardiometabolic Health: A Community-Based Study of Immunoglobulin G N-Glycans in a Chinese Han Population

Cardiovascular disease is a common complex trait that calls for next-generation biomarkers for precision diagnostics and therapeutics. The most common type of post-translational protein modification involves glycosylation. Glycans participate in key intercellular and intracellular functions, such as protein quality control, cell adhesion, cell-cell recognition, signal transduction, cell proliferation, and cell differentiation. In this context, immunoglobulin G (IgG) N-glycans affect the anti-inflammatory and proinflammatory responses of IgG, and are associated with cardiometabolic risk factors such as aging, central obesity, dyslipidemia, and hyperglycemia. Yet, the role of such glycomic biomarkers requires evaluation in diverse world populations. We report here original observations on association of IgG N-glycan biosignatures with 15 cardiometabolic risk factors in a community-based cross-sectional study conducted in 701 Chinese Han participants. After controlling for age and sex, we found that the 16, 21, and 18 IgG N-glycan traits were significantly different in participants with and without metabolic syndrome, hypertriglyceridemic waist phenotype, or abdominal obesity, respectively. The canonical correlation analysis showed that IgG N-glycan profiles were significantly associated with cardiometabolic risk factors (r = 0.469, p < 0.001). Classification models based on IgG N-glycan traits were able to differentiate participants with (1) metabolic syndrome, (2) hypertriglyceridemic waist phenotype, or (3) abdominal obesity from controls, with an area under receiver operating characteristic curves (AUC) of 0.632 (95% confidence interval [CI], 0.574-0.691, p < 0.001), 0.659 (95% CI, 0.587-0.730, p < 0.001), and 0.610 (95% CI, 0.565-0.656, p < 0.001), respectively. These new data suggest that IgG N-glycans may play an important role in cardiometabolic disease pathogenesis by regulating the proinflammatory or anti-inflammatory responses of IgG. Looking into the future, IgG N-glycan biosignatures warrant further research in other world population samples with a view to applications in clinical cardiology and public health practice.

Type 2 Diabetes Mellitus is Associated with the Immunoglobulin G N-Glycome through Putative Proinflammatory Mechanisms in an Australian Population

Type 2 diabetes mellitus (T2DM) is a common complex trait arising from interactions among multiple environmental, genomic, and postgenomic factors. We report here the first attempt to investigate the association between immunoglobulin G (IgG) N-glycan patterns, T2DM, and their clinical risk factors in an Australian population. N-glycosylation of proteins is one of the most frequently observed co- and post-translational modifications, reflecting, importantly, the real-time status of the interplay between the genomic and postgenomic factors. In a community-based case-control study, 849 participants (217 cases and 632 controls) were recruited from an urban community in Busselton, Western Australia. We applied the ultraperformance liquid chromatography method to analyze the composition of IgG N-glycans. We then conducted Spearman's correlation analyses to explore the association between glycan biomarker candidates and clinical risk factors. We performed area under the curve (AUC) analysis of the receiver operating characteristic curves by fivefold cross-validation for clinical risk factors, IgG glycans, and their combination. Two directly measured and four derived glycan peaks were significantly associated with T2DM, after correction for extensive clinical confounders and false discovery rate, thus suggesting that IgG N-glycan traits are highly correlated with T2DM clinical risk factors. Moreover, adding the IgG glycan profiles to fasting blood glucose in the logistic regression model increased the AUC from 0.799 to 0.859. The AUC for IgG glycans alone was 0.623 with a 95% confidence interval 0.580-0.666. In addition, our study provided new evidence of diversity in T2DM complex trait by IgG N-glycan stratification. Six IgG glycan traits were firmly associated with T2DM, which reflects an increased proinflammatory and biological aging status. In summary, our study reports novel associations between the IgG N-glycome and T2DM in an Australian population and the putative role of proinflammatory mechanisms. Furthermore, IgG N-glycomic alterations offer future prospects as inflammatory biomarker candidates for T2DM diagnosis, and monitoring of T2DM progression to cardiovascular disease or renal failure.

Inhibition of core fucosylation limits progression of diabetic kidney disease

BACKGROUND

FUT8-mediated core fucosylation, which transfers a fucose residue from GDP-fucose to core-GlcNAc of the N-linked type glycoproteins, is crucial for signaling receptors function. Core fucosylation is involved in various biological processes such as cell proliferation, apoptosis, differentiation and immune regulation. Our previous studies demonstrated that inhibiting core fucosylation prevented renal interstitial fibrosis of UUO murine models, but its role in the development of diabetic kidney disease (DKD) remains unclear. This study aimed to clarify the protective effects and molecular mechanisms during the progress of DKD by inhibiting core fucosylation in vivo.

METHODS

Core fucosylation was examined in streptozotocin (STZ)-induced diabetic mouse model. Then a new Fut8 mutation mouse model in which exon 7 of Fut8 gene is deleted was constructed for diabetes induction. Metabolic and renal parameters were measured. Renal structure, fibrosis, and podocyte injury were assessed, and underlying mechanisms were investigated.

RESULTS

The levels of fasting blood glucose, glycated hemoglobin, kidney-weight-to- body-weight (KW/BW) and urine albumin-to-creatinine (ACR) were increased at 16 weeks post injection. KW/BW and urine ACR were decreased significantly by inhibiting core fucosylation. The renal pathology, fibrosis, and podocyte injury were mitigated significantly by inhibiting core fucosylation. The protective effects of inhibiting core fucosylation were mediated by downregulated of the phosphorylation of Smad2/3 and extracellular signal-regulated kinase (ERK).

CONCLUSIONS

Our results indicate that FUT8-based treatment might be a promising intervention strategy in therapeutic paradigm of DKD.