No abstract

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.

Cell-lineage–specific transcripts are essential for differentiated tissue function, implicated in hereditary organ failure, and mediate acquired chronic diseases. However, experimental identification of cell-lineage–specific genes in a genome-scale manner is infeasible for most solid human tissues. We developed the first genome-scale method to identify genes with cell-lineage–specific expression, even in lineages not separable by experimental microdissection. Our machine-learning–based approach leverages high-throughput data from tissue homogenates in a novel iterative statistical framework. We applied this method to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary and most acquired glomerular kidney disease. In a systematic evaluation of our predictions by immunohistochemistry, our in silico approach was significantly more accurate (65% accuracy in human) than predictions based on direct measurement of in vivo fluorescence-tagged murine podocytes (23%). Our method identified genes implicated as causal in hereditary glomerular disease and involved in molecular pathways of acquired and chronic renal diseases. Furthermore, based on expression analysis of human kidney disease biopsies, we demonstrated that expression of the podocyte genes identified by our approach is significantly related to the degree of renal impairment in patients. Our approach is broadly applicable to define lineage specificity in both cell physiology and human disease contexts. We provide a user-friendly website that enables researchers to apply this method to any cell-lineage or tissue of interest. Identified cell-lineage–specific transcripts are expected to play essential tissue-specific roles in organogenesis and disease and can provide starting points for the development of organ-specific diagnostics and therapies.

Diabetic nephropathy (DN) is a frequent complication in patients with diabetes. Although the majority of DN models and human studies have focused on glomeruli, tubulointerstitial damage is a major feature of DN and an important predictor of renal dysfunction. This study sought to investigate molecular markers of pathogenic pathways in the renal interstitium of patients with DN. Microdissected tubulointerstitial compartments from biopsies with established DN and control kidneys were subjected to expression profiling. Analysis of candidate genes, potentially involved in DN on the basis of common hypotheses, identified 49 genes with significantly altered expression levels in established DN in comparison with controls. In contrast to some rodent models, the growth factors vascular endothelial growth factor A (VEGF-A) and epidermal growth factor (EGF) showed a decrease in mRNA expression in DN. This was validated on an independent cohort of patients with DN by real-time reverse transcriptase-PCR. Immunohistochemical staining for VEGF-A and EGF also showed a reduced expression in DN. The decrease of renal VEGF-A expression was associated with a reduction in peritubular capillary densities shown by platelet-endothelial cell adhesion molecule-1/CD31 staining. Furthermore, a significant inverse correlation between VEGF-A and proteinuria, as well as EGF and proteinuria, and a positive correlation between VEGF-A and hypoxia-inducible factor-1␣ mRNA was found. Thus, in human DN, a decrease of VEGF-A, rather than the reported increase as described in some rodent models, may contribute to the progressive disease. These findings and the questions about rodent models in DN raise a note of caution regarding the proposal to inhibit VEGF-A to prevent progression of DN.

No abstract

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 GFRassociated 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.

APOL1 variants have been associated with renal phenotypes in blacks. To refine clinical outcomes and discover mechanisms of APOL1-associated kidney injury, we analyzed clinical and genomic datasets derived from 90 black subjects in the Nephrotic Syndrome Study Network (NEPTUNE), stratified by APOL1 risk genotype. Ninety subjects with proteinuria $0.5 g/d were enrolled at first biopsy for primary nephrotic syndrome and followed. Clinical outcomes were determined, and renal histomorphometry and sequencing of Mendelian nephrotic syndrome genes were performed. APOL1 variants were genotyped, and glomerular and tubulointerstitial transcriptomes from protocol renal biopsy cores were analyzed for differential and correlative gene expression. Analyses were performed under the recessive model (high-risk genotype defined by two risk alleles). APOL1 high-risk genotype was significantly associated with a 17 ml/min per 1.73 m 2 lower eGFR and a 69% reduction in the probability of complete remission at any time, independent of histologic diagnosis. Neither APOL1 risk group was enriched for Mendelian mutations. On renal biopsy, high-risk genotype was associated with increased fractional interstitial area, interstitial fibrosis, and tubular atrophy. Risk genotype was not associated with intrarenal APOL1 mRNA expression levels. Differential expression analysis demonstrated an increased steady-state level of five genes associated with the high-risk genotype (CXCL9, CXCL11, and UBD in glomerulus; SNOR14B and MUC13 in tubulointerstitium). APOL1 tubulointerstitial coexpression analysis showed coexpression of APOL1 mRNA levels with a group of intrarenal transcripts that together were associated with increased interstitial fibrosis and tubular atrophy. These data indicate the high-risk APOL1 genotype confers renal risk across histopathologic diagnoses.

Focal segmental glomerulosclerosis (FSGS) is a common form of idiopathic nephrotic syndrome defined by the characteristic lesions of focal glomerular sclerosis and foot process effacement; however, its etiology and pathogenesis are unknown. We used mRNA isolated from laser-captured glomeruli from archived formalin-fixed, paraffin-embedded renal biopsies, until recently considered an unsuitable source of mRNA for microarray analysis, to investigate the glomerular gene expression profiles of patients with primary classic FSGS, collapsing FSGS (COLL), minimal change disease (MCD), and normal controls (Normal). Amplified mRNA was hybridized to an Affymetrix Human X3P array. Unsupervised (unbiased) hierarchical clustering revealed two distinct clusters delineating FSGS and COLL from Normal and MCD. Class comparison analysis of FSGS + COLL combined versus Normal + MCD revealed 316 significantly differentially regulated genes (134 up-regulated, 182 down-regulated). Among the differentially regulated genes were those known to be part of the slit diaphragm junctional complex and those previously described in the dysregulated podocyte phenotype. Analysis based on Gene Ontology categories revealed overrepresented biological processes of development, differentiation and morphogenesis, cell motility and migration, cytoskeleton organization, and signal transduction. Transcription factors associated with developmental processes were heavily overrepresented, indicating the importance of reactivation of developmental programs in the pathogenesis of FSGS. Our findings reveal novel insights into the molecular pathogenesis of glomerular injury and structural degeneration in FSGS.