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In the past decade, kidney disease diagnosed with objective measures of kidney damage and function has been recognised as a major public health burden. The population prevalence of chronic kidney disease exceeds 10%, and is more than 50% in high-risk subpopulations. Independent of age, sex, ethnic group, and comorbidity, strong, graded, and consistent associations exist between clinical prognosis and two hallmarks of chronic kidney disease: reduced glomerular filtration rate and increased urinary albumin excretion. Furthermore, an acute reduction in glomerular filtration rate is a risk factor for adverse clinical outcomes and the development and progression of chronic kidney disease. An increasing amount of evidence suggests that the kidneys are not only target organs of many diseases but also can strikingly aggravate or start systemic pathophysiological processes through their complex functions and effects on body homoeostasis. Risk of kidney disease has a notable genetic component, and identified genes have provided new insights into relevant abnormalities in renal structure and function and essential homoeostatic processes. Collaboration across general and specialised health-care professionals is needed to fully address the challenge of prevention of acute and chronic kidney disease and improve outcomes.

The kidneys integrate information from continuous systemic processes related to the absorption, distribution, metabolism and excretion (ADME) of metabolites. To identify underlying molecular mechanisms, we performed genome-wide association studies of the urinary concentrations of 1,172 metabolites among 1,627 patients with reduced kidney function. The 240 unique metabolite–locus associations (metabolite quantitative trait loci, mQTLs) that were identified and replicated highlight novel candidate substrates for transport proteins. The identified genes are enriched in ADME-relevant tissues and cell types, and they reveal novel candidates for biotransformation and detoxification reactions. Fine mapping of mQTLs and integration with single-cell gene expression permitted the prioritization of causal genes, functional variants and target cell types. The combination of mQTLs with genetic and health information from 450,000 UK Biobank participants illuminated metabolic mediators, and hence, novel urinary biomarkers of disease risk. This comprehensive resource of genetic targets and their substrates is informative for ADME processes in humans and is relevant to basic science, clinical medicine and pharmaceutical research. Genome-wide association analysis of 1,172 urinary metabolites identifies 240 metabolite–locus associations that when combined with UK Biobank data suggest novel metabolic mediators of disease and markers of disease risk.

Genome-wide association studies (GWAS) have successfully identified common single nucleotide polymorphisms (SNPs) associated with a wide variety of complex diseases, but do not address gene function or establish causality of disease-associated SNPs. We recently used GWAS to identify SNPs in a genomic region on chromosome 4 that associate with serum urate levels and gout, a consequence of elevated urate levels. Here we show using functional assays that human ATP-binding cassette, subfamily G, 2 (ABCG2), encoded by the ABCG2 gene contained in this region, is a hitherto unknown urate efflux transporter. We further show that native ABCG2 is located in the brush border membrane of kidney proximal tubule cells, where it mediates renal urate secretion. Introduction of the mutation Q141K encoded by the common SNP rs223H42 by site-directed mutagenesis resulted in 53% reduced urate transport rates compared to wild-type ABCG2 (P < 0.001). Data from a population-based study of 14,783 individuals support rs223H42 as the causal variant in the region and show highly significant associations with urate levels [whites: P = 10⁻³⁰, minor allele frequency (MAF) 0.11; blacks P = 10⁻⁴, MAF 0.03] and gout (adjusted odds ratio 1.68 per risk allele, both races). Our data indicate that at least 10% of all gout cases in whites are attributable to this causal variant. With approximately 3 million US individuals suffering from often insufficiently treated gout, ABCG2 represents an attractive drug target. Our study completes the chain of evidence from association to causation and supports the common disease-common variant hypothesis in the etiology of gout.

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. Identifying causal variants and genes in genome-wide association studies remains a challenge, an issue that is ameliorated with larger sample sizes. Here the authors meta-analyze kidney function genome-wide association studies to identify new loci and fine-map loci to home in on variants and genes involved in kidney function.

Genome editing tools such as CRISPR/Cas9 enable the rapid and precise manipulation of genomes. CRISPR-based genome editing has greatly simplified the study of gene function in cell lines, but its widespread use has also highlighted challenges of reproducibility. Phenotypic variability among different knockout clones of the same gene is a common problem confounding the establishment of robust genotype–phenotype correlations. Optimized genome editing protocols to enhance reproducibility include measures to reduce off-target effects. However, even if current state-of-the-art protocols are applied phenotypic variability is frequently observed. Here we identify heterogeneity of wild-type cells as an important and often neglected confounding factor in genome-editing experiments. We demonstrate that isolation of individual wild-type clones from an apparently homogenous stable cell line uncovers significant phenotypic differences between clones. Strikingly, we observe hundreds of differentially regulated transcripts (477 up- and 306 downregulated) when comparing two populations of wild-type cells. Furthermore, we show a variety of cellular and biochemical alterations in different wild-type clones in a range that is commonly interpreted as biologically relevant in genome-edited cells. Heterogeneity of wild-type cells thus contributes to variability in genome-edited cells when these are generated through isolation of clones. We show that the generation of monoclonal isogenic wild-type cells prior to genomic manipulation reduces phenotypic variability. We therefore propose to generate matched isogenic control cells prior to genome editing to increase reproducibility.

Chronic kidney disease (CKD) is defined by reduced estimated glomerular filtration rate (eGFR). Previous genetic studies have implicated regulatory mechanisms contributing to CKD. Here we present epigenome-wide association studies of eGFR and CKD using whole-blood DNA methylation of 2264 ARIC Study and 2595 Framingham Heart Study participants to identify epigenetic signatures of kidney function. Of 19 CpG sites significantly associated ( P  < 1e-07) with eGFR/CKD and replicated, five also associate with renal fibrosis in biopsies from CKD patients and show concordant DNA methylation changes in kidney cortex. Lead CpGs at PTPN6 / PHB2 , ANKRD11 , and TNRC18 map to active enhancers in kidney cortex. At PTPN6 / PHB2 cg19942083, methylation in kidney cortex associates with lower renal PTPN6 expression, higher eGFR, and less renal fibrosis. The regions containing the 243 eGFR-associated ( P  < 1e-05) CpGs are significantly enriched for transcription factor binding sites of EBF1, EP300, and CEBPB ( P  < 5e-6). Our findings highlight kidney function associated epigenetic variation. Genome-wide association studies of kidney function show enrichment of associated genetic variants in regulatory regions. Here, the authors perform epigenome-wide association studies of kidney function and disease, identifying 19 CpG sites significantly associated with these.

Biomarkers common to chronic kidney disease (CKD) and cardiovascular disease (CVD) may reflect early impairments underlying both diseases. We evaluated associations of 71 CVD-related plasma proteins measured in 2,873 Framingham Heart Study (FHS) Offspring cohort participants with cross-sectional continuous eGFR and with longitudinal change in eGFR from baseline to follow-up (ΔeGFR). We also evaluated the associations of the 71 CVD proteins with the following dichotomous secondary outcomes: prevalent CKD stage ≥3 (cross-sectional), new-onset CKD stage ≥3 (longitudinal), and rapid decline in eGFR (longitudinal). Proteins significantly associated with eGFR and ΔeGFR were subsequently validated in 3,951 FHS Third Generation cohort participants and were tested using Mendelian randomization (MR) analysis to infer putatively causal relations between plasma protein biomarkers and kidney function. In cross-sectional analysis, 37 protein biomarkers were significantly associated with eGFR at FDR<0.05 in the FHS Offspring cohort and 20 of these validated in the FHS Third Generation cohort at p<0.05/37. In longitudinal analysis, 27 protein biomarkers were significantly associated with ΔeGFR at FDR<0.05 and 12 of these were validated in the FHS Third Generation cohort at p<0.05/27. Additionally, 35 protein biomarkers were significantly associated with prevalent CKD, five were significantly associated with new-onset CKD, and 17 were significantly associated with rapid decline in eGFR. MR suggested putatively causal relations of melanoma cell adhesion molecule (MCAM; -0.011±0.003 mL/min/1.73m2, p = 5.11E-5) and epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1; -0.006±0.002 mL/min/1.73m2, p = 0.0001) concentration with eGFR. Eight protein biomarkers were consistently associated with eGFR in cross-sectional and longitudinal analysis in both cohorts and may capture early kidney impairment; others were implicated in association and causal inference analyses. A subset of CVD protein biomarkers may contribute causally to the pathogenesis of kidney impairment and should be studied as targets for CKD treatment and early prevention.

N-lactoyl-phenylalanine (Lac-Phe) is a lactate-derived metabolite that suppresses food intake and body weight. Little is known about the mechanisms that mediate Lac-Phe transport across cell membranes. Here we identify SLC17A1 and SLC17A3, two kidney-restricted plasma membrane-localized solute carriers, as physiologic urine Lac-Phe transporters. In cell culture, SLC17A1/3 exhibit high Lac-Phe efflux activity. In humans, levels of Lac-Phe in urine exhibit a strong genetic association with the SLC17A1-4 locus. Urine Lac-Phe levels are increased following a Wingate sprint test. In mice, genetic ablation of either SLC17A1 or SLC17A3 reduces urine Lac-Phe levels. Despite these differences, both knockout strains have normal blood Lac-Phe and body weights, demonstrating SLC17A1/3-dependent de-coupling of urine and plasma Lac-Phe pools. Together, these data establish SLC17A1/3 family members as the physiologic urine Lac-Phe transporters and uncover a biochemical pathway for the renal excretion of this signaling metabolite. The lactate metabolite N-lactoyl-phenylalanine (Lac-Phe) plays a role in suppressing food intake and body weight. Here, the authors identify kidney transporters responsible for the renal excretion of Lac-Phe. This discovery highlights a pathway for Lac-Phe regulation in mice and humans.

Background Reduced kidney function is a risk factor of cardiovascular and all-cause mortality. This association was demonstrated for several kidney function markers, but it is unclear whether integrating multiple measured markers may improve mortality risk prediction. Methods We conducted an exploratory factor analysis (EFA) of serum creatinine– and cystatin C–based estimated glomerular filtration rate [eGFRcre and eGFRcys; derived by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) equations], blood urea nitrogen (BUN), uric acid and serum albumin among 366 758 participants in the UK Biobank without a history of kidney failure. Fitting Cox proportional hazards models, we compared the ability of the identified latent factors to predict overall mortality and mortality by cardiovascular disease (CVD), also considering CVD-specific causes like coronary heart disease (CHD) and cerebrovascular disease. Results During 12.5 years of follow-up, 26 327 participants died from any cause, 5376 died from CVD, 2908 died from CHD and 1116 died from cerebrovascular disease. We identified two latent factors, EFA1 and EFA2, both representing kidney function variations. When using the CKD-EPI equation, EFA1 performed like eGFRcys, with EFA1 showing slightly larger hazard ratios for overall and CVD-related mortality. At 10 years of follow-up, EFA1 and eGFRcys showed moderate discrimination performance for CVD-related mortality, outperforming all other kidney indices. eGFRcre was the least predictive marker across all outcomes. When using the EKFC equation, eGFRcys performed better than EFA1 while all other results remaining similar. Conclusions While EFA is an attractive approach to capture the complex effects of kidney function, eGFRcys remains the most practical and effective measurement for all-cause and CVD mortality risk prediction. Graphical Abstract Graphical Abstract

The filtration of blood in the kidney which is crucial for mammalian life is determined by the slit-diaphragm, a cell-cell junction between the foot processes of renal podocytes. The slit-diaphragm is thought to operate as final barrier or as molecular sensor of renal filtration. Using high-resolution proteomic analysis of slit-diaphragms affinity-isolated from rodent kidney, we show that the native slit-diaphragm is built from the junction-forming components Nephrin, Neph1 and Podocin and a co-assembled high-molecular weight network of proteins. The network constituents cover distinct classes of proteins including signaling-receptors, kinases/phosphatases, transporters and scaffolds. Knockout or knock-down of either the core components or the selected network constituents tyrosine kinase MER (MERTK), atrial natriuretic peptide-receptor C (ANPRC), integral membrane protein 2B (ITM2B), membrane-associated guanylate-kinase, WW and PDZ-domain-containing protein1 (MAGI1) and amyloid protein A4 resulted in target-specific impairment or disruption of the filtration process. Our results identify the slit-diaphragm as a multi-component system that is endowed with context-dependent dynamics via a co-assembled protein network. The slit-diaphragm is a cellular junction that is crucial for blood filtration in the kidney. Kocylowski et al . show that the junction-spanning components are embedded in a protein network for dynamic control of filtration; network disturbance leads to severe filtration defects with proteinuria.