APOL1-Associated glomerular disease among African-American children: A collaboration of the chronic kidney disease in children (CKiD) and nephrotic syndrome study network (NEPTUNE) cohorts

Background: Individuals of African ancestry harboring two variant alleles within apolipoprotein L1 (APOL1) are classified with a high-risk (HR) genotype. Adults with an HR genotype have increased risk of focal segmental glomerulosclerosis and chronic kidney disease compared with those with a low-risk (LR) genotype (0 or 1 variants). The role of APOL1 risk genotypes in children with glomerular disease is less well known. Methods: This study characterized 104 African-American children with a glomerular disease by APOL1 genotype in two cohorts: The Chronic Kidney Disease in Children (CKiD) and Nephrotic Syndrome Study Network (NEPTUNE). Results: Among these subjects, 46% had an HR genotype with a similar age at cohort enrollment. For APOL1 HR children, the median age of disease onset was older (CKiD: 4.5 versus 11.5 years for LR versus HR; NEPTUNE: 11 versus 14 years for LR versus HR, respectively) and preterm birth was more common [CKiD: 27 versus 4%; NEPTUNE: 26 versus 12%; combined odds ratio 4.6 (95% confidence interval: 1.4, 15.5)].Within studies, HR children had lower initial estimated glomerular filtration rate (EGFR) (CKiD: 53 versus 69 mL/min/1.73 m2; NEPTUNE: 74 versus 94 mL/min/1.73 m2). Longitudinal EGFR decline was faster among HR children versus LR (CKiD: -18 versus -8% per year; NEPTUNE: -13 versus-3% per year). Conclusions: Children with an HR genotype in CKiD and NEPTUNE seem to have a more aggressive form of glomerular disease, in part due to a higher prevalence of focal segmental glomerulosclerosis. These consistent findings across independent cohorts suggest a common natural history for children with APOL1-Associated glomerular disease. Further study is needed to determine the generalizability of these findings

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

Complete remission in the nephrotic syndrome study network

Background and objectives This analysis from the Nephrotic Syndrome Study Network (NEPTUNE) assessed the phenotypic and pathology characteristics of proteinuric patients undergoing kidney biopsy and defined the frequency and factors associated with complete proteinuria remission (CRever). Design, setting, participants, &amp; measurements We enrolled adults and children with proteinuria ≥0.5 g/d at the time of first clinically indicated renal biopsy at 21 sites in North America from April 2010 to June 2014 into a prospective cohort study. NEPTUNE central pathologists assigned participants to minimal-change disease (MCD), FSGS, membranous nephropathy, or other glomerulopathy cohorts. Outcome measures for this analysis were (1) CRever with urine protein-to-creatinine ratio (UPC)&lt;0.3 g/g with preserved native kidney function and (2) ESRD. Continuous variables are reported as median and interquartile range (IQR; 25th, 75th percentile). Cox proportional hazards modeling was used to assess factors associated with CRever. Results We enrolled 441 patients: 116 (27%) had MCD, 142 (32%) had FSGS, 66 (15%) had membranous nephropathy, and 117 (27%) had other glomerulopathy. The baseline UPC was 4.1 g/g (IQR, 1.9, 7.7) and the eGFR was 81 ml/min per 1.73 m2 (IQR, 50, 105). Median duration of observation was 19 months (IQR, 11, 30). CRever occurred in 46% of patients, and 4.6% progressed to ESRD. Multivariate analysis demonstrated that higher prebiopsy proteinuria (hazard ratio, 0.3; 95% confidence interval, 0.2 to 0.5) and pathology diagnosis (FSGS versus MCD; hazard ratio, 0.2; 95% confidence interval, 0.1 to 0.5) were inversely associated with CRever. The effect of immunosuppressive therapy on remission varied by pathology diagnosis. Conclusions In NEPTUNE, the high frequency of other pathology in proteinuric patients affirms the value of the diagnostic kidney biopsy. Clinical factors, including level of proteinuria before biopsy, pathology diagnosis, and immunosuppression, are associated with complete remission

Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.

The application of deep learning for automated segmentation (delineation of boundaries) of histologic primitives (structures) from whole slide images can facilitate the establishment of novel protocols for kidney biopsy assessment. Here, we developed and validated deep learning networks for the segmentation of histologic structures on kidney biopsies and nephrectomies. For development, we examined 125 biopsies for Minimal Change Disease collected across 29 NEPTUNE enrolling centers along with 459 whole slide images stained with Hematoxylin &amp; Eosin (125), Periodic Acid Schiff (125), Silver (102), and Trichrome (107) divided into training, validation and testing sets (ratio 6:1:3). Histologic structures were manually segmented (30048 total annotations) by five nephropathologists. Twenty deep learning models were trained with optimal digital magnification across the structures and stains. Periodic Acid Schiff-stained whole slide images yielded the best concordance between pathologists and deep learning segmentation across all structures (F-scores: 0.93 for glomerular tufts, 0.94 for glomerular tuft plus Bowman's capsule, 0.91 for proximal tubules, 0.93 for distal tubular segments, 0.81 for peritubular capillaries, and 0.85 for arteries and afferent arterioles). Optimal digital magnifications were 5X for glomerular tuft/tuft plus Bowman's capsule, 10X for proximal/distal tubule, arteries and afferent arterioles, and 40X for peritubular capillaries. Silver stained whole slide images yielded the worst deep learning performance. Thus, this largest study to date adapted deep learning for the segmentation of kidney histologic structures across multiple stains and pathology laboratories. All data used for training and testing and a detailed online tutorial will be publicly available