BACKGROUND: N-glycosylation is one of the most common posttranslational modifications in humans, and these alterations are associated with kidney diseases.
METHODS: A novel technological approach, single-cell N-acetyllactosamine sequencing (scLacNAc-seq), was applied to simultaneously detect N-glycosylation expression and the transcriptome at single-cell resolution in three human kidney tissues from zero-time biopsy. Cell clusters, glycation abundance in each cell cluster, functional enrichment analysis, cell-cell crosstalk, and pseudotime analysis were applied.
RESULTS: Using scLacNAc-seq, 24,247 cells and 22 cell clusters were identified, and N-glycan abundance in each cell was obtained. Transcriptome analysis revealed a close connection between capillary endothelial cells (CapECs) and parietal epithelial cells (PECs). PECs and CapECs communicate with each other through several pairs of ligand receptors (e.g., TGFB1-EGFR, GRN-EGFR, TIMP1-FGFR2, VEGFB-FLT1, ANGPT2-TEK, and GRN-TNFRSF1A). Finally, a regulatory network of cell-cell crosstalk between PECs and CapECs was constructed, which is involved in cell development.
CONCLUSIONS: We here, for the first time, constructed the glycosylation profile of 22 cell clusters in the human kidney from zero-time biopsy. Moreover, cell-cell communication between PECs and CapECs through the ligand-receptor system may play a crucial regulatory role in cell proliferation.

OBJECTIVE: Diabetic kidney disease is a major vascular complication in patients with diabetes mellitus (DM). However, the association between the hemoglobin (Hb)A1c levels, notably the prediabetic levels, and renal pathological changes remains unclear. We investigated the association between the HbA1c levels and renal arteriolar lesions in subjects without any apparent kidney dysfunction using a living kidney donor cohort.
METHODS: Between January 2006 and May 2016, 393 living kidney donors underwent a \"zero-time\" biopsy at Kyushu University Hospital. The patients were divided into four groups (HbA1c levels ＜5.6%, 5.6%-5.7%, 5.8%-6.4%, and ≥ 6.5%, or diagnosed with DM [DM group]). Renal arteriolar hyalinization and wall thickening were assessed using semi-quantitative grading. We then investigated the association between the HbA1c levels and renal pathological changes.
RESULTS: 158 (40.2%) patients had arteriolar hyalinization and 148 (37.6%) showed wall thickening. A significant correlation was observed between the HbA1c levels and wall thickening (p for trend ＜0.001). An elevated HbA1c level was significantly associated with wall thickening according to a multivariable logistic analysis in subjects with HbA1c levels of 5.6%-5.7% and 5.8%-6.4%, and the DM group, compared with those with HbA1c levels of ＜5.6% (odds ratio [OR], 1.91; 95% confidence interval [CI]: [1.03-3.54] for 5.6%-5.7%, OR, 1.96; 95% CI: [1.09-3.53] for 5.8%-6.4%, and OR, 2.86; 95% CI: [0.91-9.01] for the DM group), whereas arteriolar hyalinization did not increase within the nondiabetic HbA1c levels.
CONCLUSIONS: Elevated high-normal HbA1c levels are considered to be independent risk factors for arteriolar wall thickening. Subclinical renal arteriolar sclerosis may develop in patients with prediabetic HbA1c levels.

Zero-time biopsies are taken to determine the quality of the donor organ at the time of transplantation. Histological analyses alone have so far not been able to identify parameters that allow the prediction of subsequent rejection episodes or graft survival. This study investigated whether gene expression analyses of zero-time biopsies might support this prediction. Using a well-characterized cohort of 26 zero-time biopsies from renal transplant patients that include 4 living donor (LD) and 22 deceased donor (DD) biopsies that later developed no rejection (Ctrl, n = 7), delayed graft function (DGF, n = 4), cellular (T-cell mediated rejection; TCMR, n = 8), or antibody-mediated rejection (ABMR, n = 7), we analyzed gene expression profiles for different types of subsequent renal transplant complication. To this end, RNA was isolated from formalin-fixed, paraffin-embedded (FFPE) sections and gene expression profiles were quantified. Results were correlated with transplant data and B-cell, and plasma cell infiltration was assessed by immunofluorescence microscopy. Both principal component analysis and clustering analysis of gene expression data revealed marked separation between LDs and DDs. Differential expression analysis identified 185 significant differentially expressed genes (adjusted p < 0.05). The expression of 68% of these genes significantly correlated with cold ischemia time (CIT). Furthermore, immunoglobulins were differentially expressed in zero-time biopsies from transplants later developing rejection (TCMR + ABMR) compared to non-rejected (Ctrl + DGF) transplants. In addition, immunoglobulin expression did not correlate with CIT but was increased in transplants with previous acute renal failure (ARF). In conclusion, gene expression profiles in zero-time biopsies derived from LDs are markedly different from those of DDs. Pre-transplant ARF increased immunoglobulin expression, which might be involved in triggering later rejection events. However, these findings must be confirmed in larger cohorts and the role of early immunoglobulin upregulation in zero-biopsies needs further clarification.

The utility of zero-time kidney biopsies (KB) in deciding to accept expanded criteria donor (ECD) kidneys remains controversial. However, zero-time histology is one of the main causes for discarding kidneys in the United States. In a single-centre study, we examined the utility and impact on outcome of the use of frozen section zero-time KB among ECD. Ninety-two zero-time KB were analysed for accept/discard decision between 2005 and 2015 among ECD. 53% of kidneys were rejected after zero-time KB analysis; there was no difference in individual clinical and biological data between accepted/rejected groups. However, histology of rejected kidneys showed more sclerotic glomeruli (20% vs. 8%; P < 0.001), increased interstitial fibrosis (1.25 ± 0.12 vs. 0.47 ± 0.09; P < 0.0001), more arteriosclerosis (2.14 ± 0.17 vs. 1.71 ± 0.11; P = 0.0032) and arteriolar hyalinosis (2.15 ± 0.12 vs. 1.55 ± 0.11; P = 0.0006). Using propensity score matching, we generated a group of 42 kidney allograft recipients who received a transplant matched for donor zero-time histology and clinical characteristics with donors whose kidneys were rejected. Interestingly, their 1- and 5-year graft survival and function were similar to the global cohort of ECD recipients. In conclusion, when performed, zero-time KB was a decisive element for kidney discard decision. However, adverse zero-time histology was not associated with poorer graft survival and kidney function among ECD.

BACKGROUND: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation.
METHODS: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women\'s Medical University Hospital (validation cohort).
RESULTS: In the derivation cohort, 89 patients (25.9%) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donor hypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer-Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donor hypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the \"zero-time\" biopsy.
CONCLUSIONS: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.