A High-Throughput Screen Identifies DYRK1A Inhibitor ID-8 that Stimulates Human Kidney Tubular Epithelial Cell Proliferation.

BACKGROUND: The death of epithelial cells in the proximal tubules is thought to be the primary cause of AKI, but epithelial cells that survive kidney injury have a remarkable ability to proliferate. Because proximal tubular epithelial cells play a predominant role in kidney regeneration after damage, a potential approach to treat AKI is to discover regenerative therapeutics capable of stimulating proliferation of these cells. METHODS: We conducted a high-throughput phenotypic screen using 1902 biologically active compounds to identify new molecules that promote proliferation of primary human proximal tubular epithelial cells in vitro. RESULTS: The primary screen identified 129 compounds that stimulated tubular epithelial cell proliferation. A secondary screen against these compounds over a range of four doses confirmed that eight resulted in a significant increase in cell number and incorporation of the modified thymidine analog EdU (indicating actively proliferating cells), compared with control conditions. These eight compounds also stimulated tubular cell proliferation in vitro after damage induced by hypoxia, cadmium chloride, cyclosporin A, or polymyxin B. ID-8, an inhibitor of dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A), was the top candidate identified as having a robust proproliferative effect in two-dimensional culture models as well as a microphysiologic, three-dimensional cell culture system. Target engagement and genetic knockdown studies and RNA sequencing confirmed binding of ID-8 to DYRK1A and upregulation of cyclins and other cell cycle regulators, leading to epithelial cell proliferation. CONCLUSIONS: We have identified a potential first-in-class compound that stimulates human kidney tubular epithelial cell proliferation after acute damage in vitro.

Gain-of-function variants in NLRP1 protect against the development of diabetic kidney disease: NLRP1 inflammasome role in metabolic stress sensing?

Although inflammasome plays a well-known role in animal models of renal injury, limited studies in humans are available, and its participation in diabetic kidney disease (DKD) remains unknown. Aim of this study was to elucidate the contribution of inflammasome genetics in the development of DKD in type-1 diabetes (T1D). The association of functional variants in inflammasome genes with DKD was assessed by multivariate analysis in a retrospective and in a prospective cohort. NLRP1 rs2670660 and rs11651270 polymorphisms were significantly associated with a decrease risk to develop DKD (padj<0.01), and rs11651270 also with a lower risk of new renal events during follow-up (padj=0.01). Supporting these findings, diabetes metabolites (glycated albumin and high glucose) were able to modulate NLRP1 expression. This study is the first to suggest a protective role of NLRP1 in DKD, highlighting an emerging role of NLRP1 as a homeostatic factor against metabolic stress.

Association of genetic variants in the promoter region of genes encoding p22phox (CYBA) and glutamate cysteine ligase catalytic subunit (GCLC) and renal disease in patients with type 1 diabetes mellitus.

BACKGROUND: Oxidative stress is recognized as a major pathogenic factor of cellular damage caused by hyperglycemia. NOX/NADPH oxidases generate reactive oxygen species and NOX1, NOX2 and NOX4 isoforms are expressed in kidney and require association with subunit p22phox (encoded by the CYBA gene). Increased expression of p22phox was described in animal models of diabetic nephropathy. In the opposite direction, glutathione is one of the main endogenous antioxidants whose plasmatic concentrations were reported to be reduced in diabetes patients. The aim of the present investigation was to test whether functional single nucleotide polymorphisms (SNPs) in genes involved in the generation of NADPH-dependent O2•⁻ (-675 T → A in CYBA, unregistered) and in glutathione metabolism (-129 C → T in GCLC [rs17883901] and -65 T → C in GPX3 [rs8177412]) confer susceptibility to renal disease in type 1 diabetes patients. METHODS: 401 patients were sorted into two groups according to the presence (n = 104) or absence (n = 196) of overt diabetic nephropathy or according to glomerular filtration rate (GFR) estimated by Modification of Diet in Renal Disease (MDRD) equation: ≥ 60 mL (n = 265) or < 60 mL/min/1.73 m² (n = 136) and were genotyped. RESULTS: No differences were found in the frequency of genotypes between diabetic and non-diabetic subjects. The frequency of GFR < 60 mL/min was significantly lower in the group of patients carrying CYBA genotypes T/A+A/A (18.7%) than in the group carrying the T/T genotype (35.3%) (P = 0.0143) and the frequency of GFR < 60 mL/min was significantly higher in the group of patients carrying GCLC genotypes C/T+T/T (47.1%) than in the group carrying the C/C genotype (31.1%) (p = 0.0082). Logistic regression analysis identified the presence of at least one A allele of the CYBA SNP as an independent protection factor against decreased GFR (OR = 0.38, CI95% 0.14-0.88, p = 0.0354) and the presence of at least one T allele of the GCLC rs17883901 SNP as an independent risk factor for decreased GFR (OR = 2.40, CI95% 1.27-4.56, p = 0.0068). CONCLUSIONS: The functional SNPs CYBA -675 T → A and GCLC rs17883901, probably associated with cellular redox imbalances, modulate the risk for renal disease in the studied population of type 1 diabetes patients and require validation in additional cohorts.

A Systems Toxicology Approach for the Prediction of Kidney Toxicity and Its Mechanisms In Vitro.

The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. Here, we used primary human kidney cells and applied a systems biology approach that combines multidimensional datasets and machine learning to identify biomarkers that not only predict nephrotoxic compounds but also provide hints toward their mechanism of toxicity. Gene expression and high-content imaging-derived phenotypical data from 46 diverse kidney toxicants were analyzed using Random Forest machine learning. Imaging features capturing changes in cell morphology and nucleus texture along with mRNA levels of HMOX1 and SQSTM1 were identified as the most powerful predictors of toxicity. These biomarkers were validated by their ability to accurately predict kidney toxicity of four out of six candidate therapeutics that exhibited toxicity only in late stage preclinical/clinical studies. Network analysis of similarities in toxic phenotypes was performed based on live-cell high-content image analysis at seven time points. Using compounds with known mechanism as reference, we could infer potential mechanisms of toxicity of candidate therapeutics. In summary, we report an approach to generate a multidimensional biomarker panel for mechanistic de-risking and prediction of kidney toxicity in in vitro for new therapeutic candidates and chemical entities.

Linkage disequilibrium with HLA-DRB1-DQB1 haplotypes explains the association of TNF-308G>A variant with type 1 diabetes in a Brazilian cohort.

BACKGROUND: A functional variant in the promoter region of the gene encoding tumor necrosis factor (TNF; rs1800629, -308G>A) showed to confer susceptibility to T1D. However, TNF rs1800629 was found, in several populations, to be in linkage disequilibrium with HLA susceptibility haplotypes to T1D. We evaluated the association of TNF rs1800629 with T1D in a cohort of Brazilian subjects, and assessed the impact of HLA susceptibility haplotypes in this association. METHODS: 659 subjects with T1D and 539 control subjects were genotyped for TNF-308G>A variant. HLA-DRB1 and HLA-DQB1 genes were genotyped in a subset of 313 subjects with T1D and 139 control subjects. RESULTS: Associations with T1D were observed for the A-allele of rs1800629 (OR 1.69, 95% CI 1.33-2.15, p<0.0001, in a codominant model) and for 3 HLA haplotypes: DRB1*03:01-DQB1*02:01 (OR 5.37, 95% CI 3.23-8.59, p<0.0001), DRB1*04:01-DQB1*03:02 (OR 2.95, 95% CI 1.21-7.21, p=0.01) and DRB1*04:02-DQB1*03:02 (OR 2.14, 95% CI 1.02-4.50, p=0.04). Linkage disequilibrium was observed between TNF rs1800629 and HLA-DRB1 and HLA-DQB1 alleles. In a stepwise regression analysis HLA haplotypes, but not TNF rs1800629, remained independently associated with T1D. CONCLUSION: Our results do not support an independent effect of allelic variations of TNF in the genetic susceptibility to T1D.