KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies.

BACKGROUND: Genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with kidney function. By combining these findings with post-GWAS information (e.g., statistical fine-mapping to identify independent association signals and to narrow down signals to causal variants; or different sources of annotation data), new hypotheses regarding physiology and disease aetiology can be obtained. These hypotheses need to be tested in laboratory experiments, for example, to identify new therapeutic targets. For this purpose, the evidence obtained from GWAS and post-GWAS analyses must be processed and presented in a way that they are easily accessible to kidney researchers without specific GWAS expertise. MAIN: Here we present KidneyGPS, a user-friendly web-application that combines genetic variant association for estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics consortium with annotation of (i) genetic variants with functional or regulatory effects ("SNP-to-gene" mapping), (ii) genes with kidney phenotypes in mice or human ("gene-to-phenotype"), and (iii) drugability of genes (to support re-purposing). KidneyGPS adopts a comprehensive approach summarizing evidence for all 5906 genes in the 424 GWAS loci for eGFR identified previously and the 35,885 variants in the 99% credible sets of 594 independent signals. KidneyGPS enables user-friendly access to the abundance of information by search functions for genes, variants, and regions. KidneyGPS also provides a function ("GPS tab") to generate lists of genes with specific characteristics thus enabling customizable Gene Prioritisation (GPS). These specific characteristics can be as broad as any gene in the 424 loci with a known kidney phenotype in mice or human; or they can be highly focussed on genes mapping to genetic variants or signals with particularly with high statistical support. KidneyGPS is implemented with RShiny in a modularized fashion to facilitate update of input data ( https://kidneygps.ur.de/gps/ ). CONCLUSION: With the focus on kidney function related evidence, KidneyGPS fills a gap between large general platforms for accessing GWAS and post-GWAS results and the specific needs of the kidney research community. This makes KidneyGPS an important platform for kidney researchers to help translate in silico research results into in vitro or in vivo research.

Polygenic scores for estimated glomerular filtration rate in a population of general adults and elderly - comparative results from the KORA and AugUR study.

BACKGROUND: Polygenic scores (PGSs) combining genetic variants found to be associated with creatinine-based estimated glomerular filtration rate (eGFRcrea) have been applied in various study populations with different age ranges. This has shown that PGS explain less eGFRcrea variance in the elderly. Our aim was to understand how differences in eGFR variance and the percentage explained by PGS varies between population of general adults and elderly. RESULTS: We derived a PGS for cystatin-based eGFR (eGFRcys) from published genome-wide association studies. We used the 634 variants known for eGFRcrea and the 204 variants identified for eGFRcys to calculate the PGS in two comparable studies capturing a general adult and an elderly population, KORA S4 (n = 2,900; age 24-69 years) and AugUR (n = 2,272, age ≥ 70 years). To identify potential factors determining age-dependent differences on the PGS-explained variance, we evaluated the PGS variance, the eGFR variance, and the beta estimates of PGS association on eGFR. Specifically, we compared frequencies of eGFR-lowering alleles between general adult and elderly individuals and analyzed the influence of comorbidities and medication intake. The PGS for eGFRcrea explained almost twice as much (R2 = 9.6%) of age-/sex adjusted eGFR variance in the general adults compared to the elderly (4.6%). This difference was less pronounced for the PGS for eGFRcys (4.7% or 3.6%, respectively). The beta-estimate of the PGS on eGFRcrea was higher in the general adults compared to the elderly, but similar for the PGS on eGFRcys. The eGFR variance in the elderly was reduced by accounting for comorbidities and medication intake, but this did not explain the difference in R2-values. Allele frequencies between general adult and elderly individuals showed no significant differences except for one variant near APOE (rs429358). We found no enrichment of eGFR-protective alleles in the elderly compared to general adults. CONCLUSIONS: We concluded that the difference in explained variance by PGS was due to the higher age- and sex-adjusted eGFR variance in the elderly and, for eGFRcrea, also by a lower PGS association beta-estimate. Our results provide little evidence for survival or selection bias.

DNA extraction from clotted blood in genotyping quality.

DNA extraction from frozen blood clots is challenging. Here, the authors applied QIAGEN Clotspin Baskets and the Gentra Puregene Blood Kit for DNA extraction to cellular fraction of 5.5 ml whole blood without anticoagulating additives. The amount and quality of extracted DNA were assessed via spectrophotometer and gel electrophoresis. Results from array-based genotyping were analyzed. All steps were compared with DNA isolated from anticoagulated blood samples from a separate study. The quality and concentration of DNA extracted from clotted blood were comparable to those of DNA extracted from anticoagulated blood. DNA yield was on average 27 µg per ml clotted blood, with an average purity of 1.87 (A260/A280). Genotyping quality was similar for both DNA sources (call rate: 99.56% from clotted vs 99.49% from anticoagulated blood).

Diverse molecular causes of unsolved autosomal dominant tubulointerstitial kidney diseases.

Autosomal Dominant Tubulointerstitial Kidney Disease (ADTKD) is caused by mutations in one of at least five genes and leads to kidney failure usually in mid adulthood. Throughout the literature, variable numbers of families have been reported, where no mutation can be found and therefore termed ADTKD-not otherwise specified. Here, we aim to clarify the genetic cause of their diseases in our ADTKD registry. Sequencing for all known ADTKD genes was performed, followed by SNaPshot minisequencing for the dupC (an additional cytosine within a stretch of seven cytosines) mutation of MUC1. A virtual panel containing 560 genes reported in the context of kidney disease (nephrome) and exome sequencing were then analyzed sequentially. Variants were validated and tested for segregation. In 29 of the 45 registry families, mutations in known ADTKD genes were found, mostly in MUC1. Sixteen families could then be termed ADTKD-not otherwise specified, of which nine showed diagnostic variants in the nephrome (four in COL4A5, two in INF2 and one each in COL4A4, PAX2, SALL1 and PKD2). In the other seven families, exome sequencing analysis yielded potential disease associated variants in novel candidate genes for ADTKD; evaluated by database analyses and genome-wide association studies. For the great majority of our ADTKD registry we were able to reach a molecular genetic diagnosis. However, a small number of families are indeed affected by diseases classically described as a glomerular entity. Thus, incomplete clinical phenotyping and atypical clinical presentation may have led to the classification of ADTKD. The identified novel candidate genes by exome sequencing will require further functional validation.

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.

Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals.

Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.