Identification of Novel Urinary Biomarkers for Predicting Renal Prognosis in Patients With Type 2 Diabetes by Glycan Profiling in a Multicenter Prospective Cohort Study: U-CARE Study 1

Shared Genetic Architectures between Coronary Artery Disease and Type 2 Diabetes Mellitus in East Asian and European Populations

Coronary artery disease (CAD) is a common comorbidity of type 2 diabetes mellitus (T2DM). However, the pathophysiology connecting these two phenotypes remains to be further understood. Combined analysis in multi-ethnic populations can help contribute to deepening our understanding of biological mechanisms caused by shared genetic loci. We applied genetic correlation analysis and then performed conditional and joint association analyses in Chinese, Japanese, and European populations to identify the genetic variants jointly associated with CAD and T2DM. Next, the associations between genes and the two traits were also explored. Finally, fine-mapping and functional enrichment analysis were employed to identify the potential causal variants and pathways. Genetic correlation results indicated significant genetic overlap between CAD and T2DM in the three populations. Over 10,000 shared signals were identified, and 587 were shared by East Asian and European populations. Fifty-six novel shared genes were found to have significant effects on both CAD and T2DM. Most loci were fine-mapped to plausible causal variant sets. Several similarities and differences of the involved genes in GO terms and KEGG pathways were revealed across East Asian and European populations. These findings highlight the importance of immunoregulation, neuroregulation, heart development, and the regulation of glucose metabolism in shared etiological mechanisms between CAD and T2DM.

Plasma angiotensin-converting enzyme 2 (ACE2) is a marker for renal outcome of diabetic kidney disease (DKD) (U-CARE study 3)

INTRODUCTION

ACE cleaves angiotensin I (Ang I) to angiotensin II (Ang II) inducing vasoconstriction via Ang II type 1 (AT1) receptor, while ACE2 cleaves Ang II to Ang (1-7) causing vasodilatation by acting on the Mas receptor. In diabetic kidney disease (DKD), it is still unclear whether plasma or urine ACE2 levels predict renal outcomes or not.

RESEARCH DESIGN AND METHODS

Among 777 participants with diabetes enrolled in the Urinary biomarker for Continuous And Rapid progression of diabetic nEphropathy study, the 296 patients followed up for 9 years were investigated. Plasma and urinary ACE2 levels were measured by the ELISA. The primary end point was a composite of a decrease of estimated glomerular filtration rate (eGFR) by at least 30% from baseline or initiation of hemodialysis or peritoneal dialysis. The secondary end points were a 30% increase or a 30% decrease in albumin-to-creatinine ratio from baseline to 1 year.

RESULTS

The cumulative incidence of the renal composite outcome was significantly higher in group 1 with lowest tertile of plasma ACE2 (p=0.040). Group 2 with middle and highest tertile was associated with better renal outcomes in the crude Cox regression model adjusted by age and sex (HR 0.56, 95% CI 0.31 to 0.99, p=0.047). Plasma ACE2 levels demonstrated a significant association with 30% decrease in ACR (OR 1.46, 95% CI 1.044 to 2.035, p=0.027) after adjusting for age, sex, systolic blood pressure, hemoglobin A1c, and eGFR.

CONCLUSIONS

Higher baseline plasma ACE2 levels in DKD were protective for development and progression of albuminuria and associated with fewer renal end points, suggesting plasma ACE2 may be used as a prognosis marker of DKD.

TRIAL REGISTRATION NUMBER

UMIN000011525.

Network pharmacology combined with Mendelian randomization analysis to identify the key targets of renin-angiotensin-aldosterone system inhibitors in the treatment of diabetic nephropathy

Background

Diabetic Nephropathy (DN) is one of the microvascular complications of diabetes. The potential targets of renin-angiotensin-aldosterone system (RAAS) inhibitors for the treatment of DN need to be explored.

Methods

The GSE96804 and GSE1009 datasets, 729 RAAS inhibitors-related targets and 6,039 DN-related genes were derived from the public database and overlapped with the differentially expressed genes (DN vs. normal) in GSE96804 to obtain the candidate targets. Next, key targets were screened via the Mendelian randomization analysis and expression analysis. The diagnostic nomogram was constructed and assessed in GSE96804. Additionally, enrichment analysis was conducted and a 'core active ingredient-key target-disease pathway' network was established. Finally, molecular docking was performed.

Results

In total, 60 candidate targets were derived, in which CTSC and PDE5A were screened as the key targets and had a causal association with DN as the protective factors (P < 0.05, OR < 1). Further, a nomogram exhibited pretty prediction efficiency. It is indicated that Benadryl hydrochloride might play a role in the DN by affecting the pathways of 'cytokine cytokine receptor interaction', etc. targeting the CTSC. Moreover, PDE5A might be involved in 'ECM receptor interaction', etc. for the effect of NSAID, captopril, chlordiazepoxide on DN. Molecular docking analysis showed a good binding ability of benadryl hydrochloride and CTSC, NSAID and PDE5A. PTGS2, ITGA4, and ANPEP are causally associated with acute kidney injury.

Conclusion

CTSC and PDE5A were identified as key targets for RAAS inhibitors in the treatment of DN, which might provide some clinical significance in helping to diagnose and treat DN. Among the targets of RAAS inhibitors, PTGS2, ITGA4 and ANPEP have a causal relationship with acute kidney injury, which is worthy of further clinical research.

Urinary growth differentiation factor 15 predicts renal function decline in diabetic kidney disease

Sensitive biomarkers can enhance the diagnosis, prognosis, and surveillance of chronic kidney disease (CKD), such as diabetic kidney disease (DKD). Plasma growth differentiation factor 15 (GDF15) levels are a novel biomarker for mitochondria-associated diseases; however, it may not be a useful indicator for CKD as its levels increase with declining renal function. This study explores urinary GDF15's potential as a marker for CKD. The plasma and urinary GDF15 as well as 15 uremic toxins were measured in 103 patients with CKD. The relationship between the urinary GDF15-creatinine ratio and the uremic toxins and other clinical characteristics was investigated. Urinary GDF15-creatinine ratios were less related to renal function and uremic toxin levels compared to plasma GDF15. Additionally, the ratios were significantly higher in patients with CKD patients with diabetes (p = 0.0012) and reduced with statin treatment. In a different retrospective DKD cohort study (U-CARE, n = 342), multiple and logistic regression analyses revealed that the baseline urinary GDF15-creatinine ratios predicted a decline in estimated glomerular filtration rate (eGFR) over 2 years. Compared to the plasma GDF15 level, the urinary GDF15-creatinine ratio is less dependent on renal function and sensitively fluctuates with diabetes and statin treatment. It may serve as a good prognostic marker for renal function decline in patients with DKD similar to the urine albumin-creatinine ratio.

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.

Analysis of inflammatory cytokines and estimated glomerular filtration rate decline in Japanese patients with diabetic kidney disease: a pilot study

Background: It is important to identify additional prognostic factors for diabetic kidney disease. Materials & methods: Baseline levels of ten cytokines (APRIL/TNFSF13, BAFF/TNFSF13B, chitinase 3-like 1, LIGHT/TNFSF14, TWEAK/TNFSF12, gp130/sIL-6Rβ, sCD163, sIL-6Rα, sTNF-R1, sTNF-R2) were measured in two cohorts of diabetic patients. In one cohort (n = 777), 156 individuals were randomly sampled after stratification and their plasma samples were analyzed; in the other cohort (n = 69), serum samples were analyzed in all the individuals. The levels of cytokines between rapid (estimated glomerular filtration rate decline >5 ml/min/1.73 m²/year) and non-rapid decliners were compared. Results: Multivariate analysis demonstrated significantly high levels of LIGHT/TNFSF14, TWEAK/TNFSF12 and sTNF-R2 in rapid decliners. Conclusion: These three cytokines can be potential biomarkers for the progression of diabetic kidney disease.

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).

Novel urinary glycan profiling by lectin array serves as the biomarkers for predicting renal prognosis in patients with IgA nephropathy

In IgA nephropathy (IgAN), IgA1 molecules are characterized by galactose deficiency in O-glycans. Here, we investigated the association between urinary glycosylation profile measured by 45 lectins at baseline and renal prognosis in 142 patients with IgAN. The primary outcome was estimated glomerular filtration rate (eGFR) decline (> 4 mL/min/1.73 m²/year), or eGFR ≥ 30% decline from baseline, or initiation of renal replacement therapies within 3 years. During follow-up (3.4 years, median), 26 patients reached the renal outcome (Group P), while 116 patients were with good renal outcome (Group G). Multivariate logistic regression analyses revealed that lectin binding signals of Erythrina cristagalli lectin (ECA) (odds ratio [OR] 2.84, 95% confidence interval [CI] 1.11–7.28) and Narcissus pseudonarcissus lectin (NPA) (OR 2.32, 95% CI 1.11–4.85) adjusted by age, sex, eGFR, and urinary protein were significantly associated with the outcome, and they recognize Gal(β1-4)GlcNAc and high-mannose including Man(α1-6)Man, respectively. The addition of two lectin-binding glycan signals to the interstitial fibrosis/tubular atrophy score further improved the model fitness (Akaike’s information criterion) and incremental predictive abilities (c-index, net reclassification improvement, and integrated discrimination improvement). Urinary N-glycan profiling by lectin array is useful in the prediction of IgAN prognosis, since ECA and NPA recognize the intermediate glycans during N-glycosylation of various glycoproteins.

Intra-individual variability of eGFR trajectories in early diabetic kidney disease and lack of performance of prognostic biomarkers

Studies reporting on biomarkers aiming to predict adverse renal outcomes in patients with type 2 diabetes and kidney disease (DKD) conventionally define a surrogate endpoint either as a percentage of decrease of eGFR (e.g. ≥ 30%) or an absolute decline (e.g. ≥ 5 ml/min/year). The application of those study results in clinical practise however relies on the assumption of a linear and intra-individually stable progression of DKD. We studied 860 patients of the PROVALID study and 178 of an independent population with a relatively preserved eGFR at baseline and at least 5 years of follow up. Individuals with a detrimental prognosis were identified using various thresholds of a percentage or absolute decline of eGFR after each year of follow up. Next, we determined how many of the patients met the same criteria at other points in time. Interindividual eGFR decline was highly variable but in addition intra-individual eGFR trajectories also were frequently non-linear. For example, of all subjects reaching an endpoint defined as a decrease of eGFR by ≥ 30% between baseline and 3 years of follow up, only 60.3 and 45.2% lost at least the same amount between baseline and year 4 or 5. The results were similar when only patients on stable medication or subpopulations based on baseline eGFR or albuminuria status were analyzed or an eGFR decline of ≥ 5 ml/min/1.73m²/year was used. Identification of reliable biomarkers predicting adverse prognosis is a strong clinical need given the large interindividual variability of DKD progression. However, it is conceptually challenging in early DKD because of non-linear intra-individual eGFR trajectories. As a result, the performance of a prognostic biomarker may be accurate after a specific time of follow-up in a single population only.

Integrated glycomics strategy for the evaluation of glycosylation alterations in salivary proteins associated with type 2 diabetes mellitus

Glycosylation is involved in several biological processes, and its alterations can reflect the process of certain diseases. Type 2 diabetes mellitus (T2DM) has attained the status of a global pandemic; however, the difference in salivary protein glycosylation between healthy subjects and patients with T2DM has not been fully understood. In the present study, salivary specimens from patients with T2DM (n = 72) and healthy volunteers (HVs, n = 80) were enrolled and divided into discovery and validation cohorts. A method combining the lectin microarray and lectin blotting was employed to investigate and confirm the altered glycopatterns in salivary glycoproteins. Then, lectin-mediated affinity capture of glycoproteins and MALDI-TOF/TOF-MS were performed to obtain the precise structural information of the altered glycans. As a result, the glycopatterns recognized by 5 lectins (LEL, VVA, Jacalin, RCA120 and DSA) showed significant alteration in the saliva of T2DM patients. Notably, the glycopattern of Galβ-1,4GlcNAc (LacNAc) recognized by LEL exhibited a significant increase in T2DM patients compared to HVs in both discovery and validation cohorts. The MALDI-TOF/TOF-MS results indicated that there were 10 and 7 LacNAc-containing N/O-glycans (e.g. m/z 1647.586, 11 688.613 and 1562.470) that were identified only in T2DM patients. Besides, the relative abundance of 3 LacNAc-containing N-glycans and 10 LacNAc-containing O-glycans showed an increase in the glycopattern in T2DM patients. These results indicated that the glycopattern of LacNAc is increased in salivary glycoproteins from T2DM patients, and an increase in LacNAc-containing N/O-glycans may contribute to this alteration. Our findings provide useful information to understand the complex physiological changes in the T2DM patients.

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.

Gut microbiome-derived phenyl sulfate contributes to albuminuria in diabetic kidney disease

Diabetic kidney disease is a major cause of renal failure that urgently necessitates a breakthrough in disease management. Here we show using untargeted metabolomics that levels of phenyl sulfate, a gut microbiota-derived metabolite, increase with the progression of diabetes in rats overexpressing human uremic toxin transporter SLCO4C1 in the kidney, and are decreased in rats with limited proteinuria. In experimental models of diabetes, phenyl sulfate administration induces albuminuria and podocyte damage. In a diabetic patient cohort, phenyl sulfate levels significantly correlate with basal and predicted 2-year progression of albuminuria in patients with microalbuminuria. Inhibition of tyrosine phenol-lyase, a bacterial enzyme responsible for the synthesis of phenol from dietary tyrosine before it is metabolized into phenyl sulfate in the liver, reduces albuminuria in diabetic mice. Together, our results suggest that phenyl sulfate contributes to albuminuria and could be used as a disease marker and future therapeutic target in diabetic kidney disease.

Diabetes is a major cause of kidney disease. Here Kikuchi et al. show that phenol sulfate, a gut microbiota-derived metabolite, is increased in diabetic kidney disease and contributes to the pathology by promoting kidney injury, suggesting phenyl sulfate could be used a marker and therapeutic target for the treatment of diabetic kidney disease.

Alteration of glycosylation in serum proteins: a new potential indicator to distinguish non-diabetic renal diseases from diabetic nephropathy

Diabetic nephropathy (DN) and nondiabetic renal disease (NDRD) are two major categories of renal diseases in diabetes mellitus patients. The clinical differentiation among them is usually not so clear and effective. In this study, sera from DN and NDRD patients were collected, and glycan profiles of serum proteins from DN and NDRD patients were investigated and compared by using lectin microarray and lectin blot. Then, altered glycoproteins were enriched by lectin coupled magnetic particle conjugate and characterized by LC-MS/MS. We found significant change in glycan patterns between DN and NDRD patients. In particular, the relative abundance of the glycopattern of Galβ1-3GalNAc which was identified by BPL (Bauhinia purpurea lectin) was significantly decreased in DN patients compared to four types of NDRD patients (p < 0.05). Moreover, BPL blotting indicated that the proteins with a molecular weight of about 53 kDa exhibited low staining signal in DN compared to all NDRD groups, which was consistent with results of lectin microarrays. After enriching by BPL and identification by LC-MS/MS, a total of 235 and 258 proteins were characterized from NDRD and DN respectively. Among these, the relative abundance of 12 isolated serum proteins exhibited significantly alteration between DN and NDRD (p < 0.05). Our findings indicated not only the relative abundance of Galβ1-3GalNAc on serum proteins but also certain glycoproteins modified with this glycopattern showed a difference between DN and NDRD patients. This suggested that the analysis of this alteration by using urine specimens may constitute an additional valuable diagnostic tool for differentiating DN and NDRD with a non-invasive method.