Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD

Radiomics-Based Image Phenotyping of Kidney Apparent Diffusion Coefficient Maps: Preliminary Feasibility & Efficacy

Given the central role of interstitial fibrosis in disease progression in chronic kidney disease (CKD), a role for diffusion-weighted MRI has been pursued. We evaluated the feasibility and preliminary efficacy of using radiomic features to phenotype apparent diffusion coefficient (ADC) maps and hence to the clinical classification(s) of the participants. The study involved 40 individuals (10 healthy and 30 with CKD (eGFR 2)). Machine learning methods, such as hierarchical clustering and logistic regression, were used. Clustering resulted in the identification of two clusters, one including all individuals with CKD (n = 17), while the second one included all the healthy volunteers (n = 10) and the remaining individuals with CKD (n = 13), resulting in 100% specificity. Logistic regression identified five radiomic features to classify participants as with CKD vs. healthy volunteers, with a sensitivity and specificity of 93% and 70%, respectively, and an AUC of 0.95. Similarly, four radiomic features were able to classify participants as rapid vs. non-rapid CKD progressors among the 30 individuals with CKD, with a sensitivity and specificity of 71% and 43%, respectively, and an AUC of 0.75. These promising preliminary data should support future studies with larger numbers of participants with varied disease severity and etiologies to improve performance

Radiomics-Based Image Phenotyping of Kidney Apparent Diffusion Coefficient Maps: Preliminary Feasibility & Efficacy

Given the central role of interstitial fibrosis in disease progression in chronic kidney disease (CKD), a role for diffusion-weighted MRI has been pursued. We evaluated the feasibility and preliminary efficacy of using radiomic features to phenotype apparent diffusion coefficient (ADC) maps and hence to the clinical classification(s) of the participants. The study involved 40 individuals (10 healthy and 30 with CKD (eGFR < 60 mL/min/1.73 m2)). Machine learning methods, such as hierarchical clustering and logistic regression, were used. Clustering resulted in the identification of two clusters, one including all individuals with CKD (n = 17), while the second one included all the healthy volunteers (n = 10) and the remaining individuals with CKD (n = 13), resulting in 100% specificity. Logistic regression identified five radiomic features to classify participants as with CKD vs. healthy volunteers, with a sensitivity and specificity of 93% and 70%, respectively, and an AUC of 0.95. Similarly, four radiomic features were able to classify participants as rapid vs. non-rapid CKD progressors among the 30 individuals with CKD, with a sensitivity and specificity of 71% and 43%, respectively, and an AUC of 0.75. These promising preliminary data should support future studies with larger numbers of participants with varied disease severity and etiologies to improve performance

Using herbs medically without knowing their composition: are we playing Russian roulette?

Herbal medicine, a form of complementary and alternative medicine (CAM), is used throughout the world, in both developing and developed countries. The ingredients in herbal medicines are not standardized by any regulatory agency. Variability exists in the ingredients as well as in their concentrations. Plant products may become contaminated with bacteria and fungi during storage. Therefore, harm can occur to the kidney, liver, and blood components after ingestion. We encourage scientific studies to identify the active ingredients in herbs and to standardize their concentrations in all herbal preparations. Rigorous studies need to be performed in order to understand the effect of herbal ingredients on different organ systems as well as these substances' interaction with other medications

Using herbs medically without knowing their composition: are we playing Russian roulette?

Herbal medicine, a form of complementary and alternative medicine (CAM), is used throughout the world, in both developing and developed countries. The ingredients in herbal medicines are not standardized by any regulatory agency. Variability exists in the ingredients as well as in their concentrations. Plant products may become contaminated with bacteria and fungi during storage. Therefore, harm can occur to the kidney, liver, and blood components after ingestion. We encourage scientific studies to identify the active ingredients in herbs and to standardize their concentrations in all herbal preparations. Rigorous studies need to be performed in order to understand the effect of herbal ingredients on different organ systems as well as these substances\u27 interaction with other medications

Genetic Association and Gene-Gene Interaction Analyses in African American Dialysis Patients With Nondiabetic Nephropathy

Background African Americans have increased susceptibility to nondiabetic nephropathy relative to European Americans. Study Design Follow-up of a pooled genome-wide association study (GWAS) in African American dialysis patients with nondiabetic nephropathy; novel gene-gene interaction analyses. Setting & Participants Wake Forest sample: 962 African American nondiabetic nephropathy cases, 931 non-nephropathy controls. Replication sample: 668 Family Investigation of Nephropathy and Diabetes (FIND) African American nondiabetic nephropathy cases, 804 non-nephropathy controls. Predictors Individual genotyping of top 1,420 pooled GWAS-associated single-nucleotide polymorphisms (SNPs) and 54 SNPs in 6 nephropathy susceptibility genes. Outcomes APOL1 genetic association and additional candidate susceptibility loci interacting with or independently from APOL1 . Results The strongest GWAS associations included 2 noncoding APOL1 SNPs, rs2239785 (OR, 0.33; dominant; P = 5.9 × 10 −24 ) and rs136148 (OR, 0.54; additive; P = 1.1 × 10 −7 ) with replication in FIND ( P = 5.0 × 10 −21 and 1.9 × 10 −05 , respectively). rs2239785 remained associated significantly after controlling for the APOL1 G1 and G2 coding variants. Additional top hits included a CFH SNP (OR from meta-analysis in the 3,367 African American cases and controls, 0.81; additive; P = 6.8 × 10 −4 ). The 1,420 SNPs were tested for interaction with APOL1 G1 and G2 variants. Several interactive SNPs were detected; the most significant was rs16854341 in the podocin gene ( NPHS2 ; P = 0.0001). Limitations Nonpooled GWASs have not been performed in African American patients with nondiabetic nephropathy. Conclusions This follow-up of a pooled GWAS provides additional and independent evidence that APOL1 variants contribute to nondiabetic nephropathy in African Americans and identified additional associated and interactive nondiabetic nephropathy susceptibility genes