Integrative biology identifies shared transcriptional networks in CKD.

A previous meta-analysis of genome-wide association data by the Cohorts for Heart and Aging Research in Genomic Epidemiology and CKDGen consortia identified 16 loci associated with eGFR. To define how each of these single-nucleotide polymorphisms (SNPs) could affect renal function, we integrated GFR-associated loci with regulatory pathways, producing a molecular map of CKD. In kidney biopsy specimens from 157 European subjects representing nine different CKDs, renal transcript levels for 18 genes in proximity to the SNPs significantly correlated with GFR. These 18 genes were mapped into their biologic context by testing coregulated transcripts for enriched pathways. A network of 97 pathways linked by shared genes was constructed and characterized. Of these pathways, 56 pathways were reported previously to be associated with CKD; 41 pathways without prior association with CKD were ranked on the basis of the number of candidate genes connected to the respective pathways. All pathways aggregated into a network of two main clusters comprising inflammation- and metabolism-related pathways, with the NRF2-mediated oxidative stress response pathway serving as the hub between the two clusters. In all, 78 pathways and 95% of the connections among those pathways were verified in an independent North American biopsy cohort. Disease-specific analyses showed that most pathways are shared between sets of three diseases, with closest interconnection between lupus nephritis, IgA nephritis, and diabetic nephropathy. Taken together, the network integrates candidate genes from genome-wide association studies into their functional context, revealing interactions and defining established and novel biologic mechanisms of renal impairment in renal diseases.

Multi-Scalar Data Integration Links Glomerular Angiopoietin-Tie Signaling Pathway Activation With Progression of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N = 58) in the Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this panel improved prediction of the composite outcome of ESKD or a 40% decline in glomerular filtration rate. The panel was validated in an independent group (N = 68), who also had kidney transcriptomic profiles. One marker, plasma angiopoietin 2 (ANGPT2), was significantly associated with outcomes in cohorts from the Cardiovascular Health Study (N = 3,183) and the Chinese Cohort Study of Chronic Kidney Disease (N = 210). Glomerular transcriptional angiopoietin/Tie (ANG-TIE) pathway scores, derived from the expression of 154 ANG-TIE signaling mediators, correlated positively with plasma ANGPT2 levels and kidney outcomes. Higher receptor expression in glomeruli and higher ANG-TIE pathway scores in endothelial cells corroborated potential functional effects in the kidney from elevated plasma ANGPT2 levels. Our work suggests that ANGPT2 is a promising prognostic endothelial biomarker with likely functional impact on glomerular pathogenesis in DKD.

Soluble ST2 and Galectin-3 and Progression of CKD.

INTRODUCTION: Cardiac biomarkers soluble ST2 (sST2) and galectin-3 may reflect cardiac inflammation and fibrosis. It is plausible that these mechanisms may also contribute to the progression of kidney disease. We examined associations of sST2 and galectin-3 with kidney function decline in participants with chronic kidney disease (CKD). METHODS: This was a pooled analysis of 2 longitudinal cohorts of participants with CKD: the Clinical Phenotyping and Resource Biobank (C-PROBE) study and the Seattle Kidney Study (SKS). We measured circulating concentrations of sST2 and galectin-3 at baseline. Our primary outcome was progression to estimated glomerular filtration rate (eGFR) <15 ml/min per 1.73 m2 or end-stage renal disease (ESRD). We used competing risk Cox regression models to study the association of sST2 and galectin-3 with CKD progression, adjusting for demographics, kidney function, and comorbidity. RESULTS: Among the 841 participants in the pooled cohort, baseline eGFR was 51 ± 27 ml/min per 1.73 m2 and median urine albumin-to-creatinine ratio (UACR) was 141 (interquartile range = 15-736) mg/g. Participants with higher sST2 and galectin-3 were more likely to be older, to have heart failure and diabetes, and to have lower eGFR. Adjusting for demographics, kidney function, and comorbidity, every doubling of sST2 was not associated with progression to eGFR <15 ml/min per 1.73 m2 or ESRD (adjusted hazard ratio 1.02, 95% confidence interval = 0.76-1.38). Every doubling of galectin-3 was significantly associated with a 38% (adjusted hazard ratio = 1.35, 95% confidence interval = 1.01-1.80) increased risk of progression to eGFR <15 ml/min per 1.73 m2 or ESRD. CONCLUSION: Higher concentrations of the cardiac biomarker galectin-3 may be associated with progression of CKD, highlighting potential novel mechanisms that may contribute to the progression of kidney disease.

Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the baseline estimated glomerular filtration rate (eGFR) in 261 patients. Proteins encoded by eGFR-associated transcripts were tested in urine for association with renal tissue injury and baseline eGFR. The ability to predict CKD progression, defined as the composite of ESKD or 40% reduction of baseline eGFR, was then determined in three independent CKD cohorts. A panel of intrarenal transcripts, including epidermal growth factor (EGF), a tubule-specific protein critical for cell differentiation and regeneration, predicted eGFR. The amount of EGF protein in urine (uEGF) showed significant correlation (P < 0.001) with intrarenal EGF mRNA, interstitial fibrosis/tubular atrophy, eGFR, and rate of eGFR loss. Prediction of the composite renal end point by age, gender, eGFR, and albuminuria was significantly (P < 0.001) improved by addition of uEGF, with an increase of the C-statistic from 0.75 to 0.87. Outcome predictions were replicated in two independent CKD cohorts. Our approach identified uEGF as an independent risk predictor of CKD progression. Addition of uEGF to standard clinical parameters improved the prediction of disease events in diverse CKD populations with a wide spectrum of causes and stages.