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BACKGROUND AND OBJECTIVES: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. Studies investigating the association between PCSK9 and cardiovascular disease in large cohorts of patients with CKD are limited. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The association of PCSK9 concentrations with prevalent and incident cardiovascular disease was investigated in 5138 White participants of the German Chronic Kidney Disease study with a median follow-up of 6.5 years. Inclusion criteria were eGFR of 30–60 or >60 ml/min per 1.73 m(2) in the presence of overt proteinuria (urine albumin-creatinine ratio >300 mg/g or equivalent). Prevalent cardiovascular disease was defined as a history of nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, carotid arteries interventions, and stroke. Incident major adverse cardiovascular disease events included death from cardiovascular causes, acute nonfatal myocardial infarction, and nonfatal stroke. RESULTS: Median PCSK9 concentration in the cohort was 285 ng/ml (interquartile range, 231–346 ng/ml). There was no association between PCSK9 concentrations and baseline eGFR and albuminuria. With each 100-ng/ml increment of PCSK9, the odds for prevalent cardiovascular disease (n=1284) were 1.22-fold (95% confidence interval, 1.12 to 1.34; P1.75; P=0.01). In addition, PCSK9 showed a valuable gain in classification accuracy for both prevalent cardiovascular disease (net reclassification index =0.27; 95% confidence interval, 0.20 to 0.33) and incident major adverse cardiovascular disease events during follow-up (net reclassification index =0.10; 95% confidence interval, 0.01 to 0.21) when added to an extended adjustment model. CONCLUSIONS: Our findings reveal no relation of PCSK9 with baseline eGFR and albuminuria but a significant association between higher PCSK9 concentrations and risk of cardiovascular disease independent of traditional risk factors, including LDL cholesterol levels. Clinical Trial registry name and registration number: German Chronic Kidney Disease Study (GCKD), DRKS 00003971

Background Polypharamacy is common among patients with chronic kidney disease (CKD), but little is known about urinary excretion of many drugs and their metabolites among CKD patients. Methods To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of CKD patients, the Germany Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups and coded active ingredients according to the Anatomical Therapeutic Chemical classification system. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns. Results Among 4885 participants, there were 108 medication-drug metabolite pairs based on reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range 84.0%-100%) and 71.7% (range 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin-II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was

The optimal treatment strategy for patients with small non-functioning VHL-related incidentalomas is unclear. We searched the Freiburg VHL registry for patients with radiologic evidence of pheochromocytoma/paraganglioma (PHEO/PGL). In total, 176 patients with single, multiple, and recurrent tumours were identified (1.84 tumours/patient, range 1–8). Mean age at diagnosis was 32 ± 16 years. Seventy-four percent of tumours were localised to the adrenals. Mean tumour diameter was 2.42 ± 2.27 cm, 46% were P < 0.025) and before surgery (4.89 ± 3.47 cm vs 1.36 ± 0.43 cm; P < 0.02). Disease was stable in 67% of 21 patients with evaluable tumours ≤1.5 cm according to RECIST and progressed in 7. Time till surgery in these patients was 29.5 ± 20.0 months. A total of 155 patients underwent surgery. PHEO/PGL was histologically excluded in 4 and proven in 151. Of these, one had additional metastatic disease, one harboured another tumour of a different type, and in 2 a second surgery for suspected disease recurrence did not confirm PHEO/PGL. Logistic regression analysis revealed 50% probability for a positive/negative biochemical test result at 1.8 cm tumour diameter. Values of a novel symptom score were positively correlated with tumour size (Rs = 0.46, P < 0.0001) and together with a positive biochemistry a linear size predictor (P < 0.01). Results support standardised clinical assessment and measurement of tumour size and metanephrines in VHL patients with non-functioning incidentalomas

Background Hypothyroidism and low free triiodothyronine (FT3) syndrome [low FT3 levels with normal thyroid-stimulating hormone (TSH)] have been associated with reduced kidney function cross-sectionally in chronic kidney disease (CKD) patients with severely reduced estimated glomerular filtration rate (eGFR) or end-stage kidney disease (ESKD). Results on the prospective effects of impaired thyroid function on renal events and mortality for patients with severely reduced eGFR or from population-based cohorts are conflicting. Here we evaluated the association between thyroid and kidney function with eGFR (cross-sectionally) as well as renal events and mortality (prospectively) in a large, prospective cohort of CKD patients with mild to moderately reduced kidney function. Methods Thyroid markers were measured among CKD patients from the German Chronic Kidney Disease study. Incident renal endpoints (combined ESKD, acute kidney injury and renal death) and all-cause mortality were abstracted from hospital records and death certificates. Time to first event analysis of complete data from baseline to the 4-year follow-up (median follow-up time 4.04 years) of 4600 patients was conducted. Multivariable linear regression and Cox proportional hazards models were fitted for single and combined continuous thyroid markers [TSH, free thyroxine (FT4), FT3] and thyroid status. Results Cross-sectionally, the presence of low-FT3 syndrome showed a significant inverse association with eGFR and continuous FT3 levels alone showed a significant positive association with eGFR; in combination with FT4 and TSH, FT3 levels also showed a positive association and FT4 levels showed a negative association with eGFR. Prospectively, higher FT4 and lower FT3 levels were significantly associated with a higher risk of all-cause mortality (Nevents = 297). Per picomole per litre higher FT3 levels the risk of reaching the composite renal endpoint was 0.73-fold lower (95% confidence interval 0.65–0.82; Nevents = 615). Compared with euthyroid patients, patients with low-FT3 syndrome had a 2.2-fold higher risk and patients with hypothyroidism had a 1.6-fold higher risk of experiencing the composite renal endpoint. Conclusions Patients with mild to moderate CKD suffering from thyroid function abnormalities are at an increased risk of adverse renal events and all-cause mortality over time.

BACKGROUND AND AIMS Over 10% of the adult population worldwide is affected by chronic kidney disease (CKD). CKD is associated with an increased risk of kidney failure (KF), cardiovascular events and mortality. CKD is defined and staged by estimated glomerular filtration rate (eGFR), the most common measure of kidney function. Genome-wide association studies enable the calculation of polygenic risk scores (PRSs), e.g. for eGFR. The aim of this study was to investigate if a polygenic predisposition to lower eGFR is associated with KF, cardiovascular events and mortality in people with CKD, and if the eGFR PRS carries predictive ability. METHOD A PRS for log(eGFR) was developed and tuned in independent, general population-based study samples consisting of European ancestry participants of the UK Biobank and the CKDGen Consortium via the LDpred algorithm [1]. Using genetic information and follow-up data of 4873 participants with moderate CKD enrolled in the German Chronic Kidney Disease study, we calculated, standardized and evaluated the association of the PRS with adverse endpoints. Main endpoints included KF, a composite endpoint of myocardial infarction, cerebral haemorrhage and stroke (3P-MACE), and overall mortality. Cox proportional hazard regression was conducted to estimate (cause-specific) hazard ratios (HRs). Predictive performance of the PRS for KF and 3P-MACE was assessed using prediction error curves and time-dependent c-index. The statistical significance level was Bonferroni-corrected for three main endpoints (P < .05/3). RESULTS After a median follow-up time of 6.5 years, 619 patients died, 466 experienced KF, and 545 3P-MACE. Higher levels of the PRS, corresponding to a genetic predisposition to lower eGFR, were associated with higher risk for all three endpoints {KF: HR 1.23, [95% confidence interval (95% CI) 1.12–1.35], 3MACE: 1.15 (1.06–1.25), mortality: 1.12 (1.04;1.22)} after adjusting for baseline age, sex and two principal components. Across deciles of the eGFR PRS, participants in the highest decile, corresponding to the genetically lowest eGFR, had a >2-fold increased risk of KF compared with those in the lowest decile [HR = 2.13 (1.39–3.27), Fig. 1]. No distinct improvement in the prediction performance for KF was observed when adding the PRS to the well-established KF risk equation by Tangri et al. [2]. This also held true for the added predictive ability of the PRS for 3P-MACE when compared with a model with established cardiovascular risk factors. CONCLUSION Our study revealed a significant association between a polygenic predisposition to lower eGFR and KF, cardiovascular events, and mortality among people with moderate CKD, emphasizing the importance of genetic background even after disease onset. The eGFR PRS carried no added predictive ability with regard to KF and 3P-MACE beyond established risk factors.

BACKGROUND AND AIMS Glomerular filtration rate (GFR) is the most common measure of kidney function. Measuring GFR is often infeasible in routine clinical practice and population studies, where it is estimated instead from blood biomarkers. Three currently recommended equations, eGFR(crea), eGFR(cystC) and eGFR(cr + cy), use either creatinine, cystatin C or both, respectively, to calculate eGFR [1]. In addition, three alternative equations were introduced recently: two of them update eGFR(crea) and eGFR(cr + cy) by excluding the race term used in them [2], and the full age spectrum (FAS) equation (creatinine-based), which was specifically developed to estimate GFR across the full age range [3]. We aimed to assess the impact of these six equations on GFR estimates and the proportion of participants with chronic kidney disease (CKD) in the German National Cohort (GNC, NAKO) Study. METHOD The NAKO study is a prospective cohort study in Germany. Data to estimate GFR (eGFR) using the six equations was available for 112 843 participants aged 19–75 years, mostly of European ancestry. Pairwise Spearman correlation coefficients between GFR estimates were calculated. CKD was defined as an eGFR RESULTS Median eGFR/equation ranged from 92.2 mL/min/1.73 m² using the new FAS-equation [3] to 105.7 mL/min/1.73 m² using the updated race-free eGFR(cr + cy)2 (Fig. 1). eGFR values of the three equations using creatinine only, as well as eGFR values from the two equations using both creatinine and cystatin C, correlated well (r > 0.95), while the correlation of GFR estimates based on equations either using creatinine or cystatin C was only moderate (r = 0.6, Fig. 1). The frequency of CKD ranged from 1.0% to 2.3%, a >2-fold difference. The agreement assessed as Cohen's κ was the smallest when comparing the CKD status based on eGFR(cy) [1] with the CKD status based on the updated race-free eGFR (crea) [2] (Cohen's κ = 0.38). While both equations led to a mutual CKD classification in 707 participants (0.6%), 613 (0.5%) were only classified as having CKD when the updated race-free eGFR (crea) [2] was used, and 1580 (1.4%) were only classified as having CKD using eGFR (cy) [1]. Interestingly, the respective serum biomarker that led to the discordant classification of CKD was abnormally high, while the other biomarker was mainly in the normal range, highlighting the potential influence of non-kidney related factors on biomarker levels that influence estimates of CKD prevalence. CONCLUSION The use of different GFR equations leads to variable estimates, affecting the proportion classified as having CKD. Non-GFR determinants with an impact on the levels of either creatinine or cystatin C may lead to incorrect estimates of GFR and affect CKD prevalence estimates, which underscores the utility of a joint view using various equations.

BACKGROUND AND AIMS Chronic kidney disease (CKD) affects around 10% of adults worldwide and an estimated 13–17% in Germany1. Imaging is a novel, promising approach to identify additional markers of kidney function and CKD2. Within a large, population-based cohort study, the German National Cohort study (NAKO/GNC), 30 000 participants underwent a whole-body MRI protocol3. The goal of our project was to develop an automated kidney segmentation workflow and to examine distributions of the segmented kidneys and kidney sub-compartments. METHOD Data from the first 11 207 participants were used to develop a robust image processing pipeline for kidney segmentation and apply it to participants’ abdominal MRI images. After importing 3D gradient echo and 2D haste images into the imaging platform NORA (www.nora-imaging.org), an in-house ‘patchwork’-framework (https://bitbucket.org/reisert/patchwork) based on deep-learning convolutional neural networks was trained on data from 300 persons to automatically segment different kidney compartments (cortex, hilus, medulla and cysts). After an initial training round, the model was improved over four iterations by a loop of prediction, manual correction and retraining. The final model was then applied to the full dataset of 11 207 abdominal MR images, followed by manual quality control prior to statistical analysis. Volumetric parameters for total kidney volume [TKV, defined as cortex + medulla] and compartments were calculated from the segmentations. Values were calculated in absolute units of mL and normalized to body-surface-area (BSA) defined as sqrt(weight in kg*height in cm)/3600. RESULTS TKV and the kidney compartments cortex, medulla and hilus could be segmented robustly with the trained network (Fig. 1A). After exclusion of approximately 10% of images because of insufficient segmentation quality due to initial imaging artifacts or poor image quality, the mean (SD) TKV was 364 (±60) mL for men and 290 (±51) mL for women. This difference was markedly attenuated after normalisation to BSA (Fig. 1B). The right kidney was systematically smaller than the left kidney by approximately 5% (Fig. 1C). There was a strong association between participants’ BSA with TKV (Fig. 1D). The normalized kidney sub-compartment volumes showed different patterns across age, with medullary volume decreasing and hilus increasing (Fig. 2). CONCLUSION The developed framework enables robust segmentation of kidneys in abdominal MRI data from a nonspecific clinical routine protocol of a large cohort study. Basic parameters such as TKV and sub-compartment volumes of the kidney show correlations with participants’ height, weight, sex and age that are consistent with prior knowledge and may enable an estimation of ‘kidney age’. This is an optimal starting point to identify more advanced imaging biomarkers of kidney function and CKD.

BACKGROUND AND AIMS UMOD is a major risk gene for monogenic and complex forms of kidney disease. The encoded kidney-specific protein uromodulin is the most abundant protein in urine and related to chronic kidney disease, hypertension and pathogen defense. Through basolateral release from kidney epithelial cells, uromodulin also reaches the blood, where its function is largely unknown. To gain insights into potential systemic roles, we performed genome-wide screens of circulating uromodulin in seven cohorts using two complementary assays. METHOD Separate genome-wide association study meta-analyses for circulating uromodulin were conducted for the antibody-based assay (five cohorts, N = 13 985) and the aptamer-based SOMAscan assay (two cohorts, N = 18 070). Genome-wide significant loci were placed into their functional genomic context using RNA-seq, ATAC-seq and Hi-C data generated from primary human kidney tissue. An array of downstream genetic analyses was then performed for significant loci, including fine-mapping, colocalization analyses and gene-by-gene interaction analyses. The B4GALNT2 p.Cys466Arg allele was expressed in MDCK cells and studied by immunofluorescence and Western blotting analyses. RESULTS We detected and replicated 13 genome-wide significant loci (P CONCLUSION This study provides human genetic evidence of new pathway members of uromodulin and delivers novel insights into its determinants and systemic role in the circulation.

BACKGROUND AND OBJECTIVES: Metabolomics facilitates the discovery of biomarkers and potential therapeutic targets for CKD progression. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We evaluated an untargeted metabolomics quantification of stored plasma samples from 645 Chronic Kidney Disease in Children (CKiD) participants. Metabolites were standardized and logarithmically transformed. Cox proportional hazards regression examined the association between 825 nondrug metabolites and progression to the composite outcome of KRT or 50% reduction of eGFR, adjusting for age, sex, race, body mass index, hypertension, glomerular versus nonglomerular diagnosis, proteinuria, and baseline eGFR. Stratified analyses were performed within subgroups of glomerular/nonglomerular diagnosis and baseline eGFR. RESULTS: Baseline characteristics were 391 (61%) male; median age 12 years; median eGFR 54 ml/min per 1.73 m(2); 448 (69%) nonglomerular diagnosis. Over a median follow-up of 4.8 years, 209 (32%) participants developed the composite outcome. Unique association signals were identified in subgroups of baseline eGFR. Among participants with baseline eGFR ≥60 ml/min per 1.73 m(2), two-fold higher levels of seven metabolites were significantly associated with higher hazards of KRT/halving of eGFR events: three involved in purine and pyrimidine metabolism (N6-carbamoylthreonyladenosine, hazard ratio, 16; 95% confidence interval, 4 to 60; 5,6-dihydrouridine, hazard ratio, 17; 95% confidence interval, 5 to 55; pseudouridine, hazard ratio, 39; 95% confidence interval, 8 to 200); two amino acids, C-glycosyltryptophan, hazard ratio, 24; 95% confidence interval 6 to 95 and lanthionine, hazard ratio, 3; 95% confidence interval, 2 to 5; the tricarboxylic acid cycle intermediate 2-methylcitrate/homocitrate, hazard ratio, 4; 95% confidence interval, 2 to 7; and gulonate, hazard ratio, 10; 95% confidence interval, 3 to 29. Among those with baseline eGFR

Background and Aims Chronic kidney disease (CKD) affects >10% of the adult population worldwide and is associated with increased risk of kidney failure (KF) and mortality. Mechanisms underlying the variable course of disease progression are incompletely understood. This study aimed at identifying novel metabolite biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiological mechanisms. Method Using measurements of 1,487 metabolites in urine of 5,087 CKD patients enrolled in the German Chronic Kidney Disease study, we evaluated the association of urine metabolite levels with adverse events. Main endpoints include KF, a combined endpoint of KF and acute kidney injury (KF+AKI), and overall mortality. Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable adjusted Cox regression models. We performed cause-specific hazard regression as well as subdistribution hazard analyses with death of other causes as a competing event for the endpoints KF and KF+AKI. Statistical significance was defined using a Bonferroni correction for the number of tested metabolites per stage. An association was considered replicated if effect estimates from both stages were significant and direction-consistent. Results Median follow-up time was 4 years. At time of analysis, 362 patients died, 241 experienced KF, and 382 KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly and reproducibly associated with adverse kidney outcomes and/or mortality. Cause-specific and subdistribution hazard analyses showed almost identical results. Higher levels of the amino acid C-glycosyltryptophan in urine were associated with higher risk for all three endpoints (KF: hazard ratio 1.43, 95% confidence interval [1.27;1.61], KF+AKI: 1.40 [1.27;1.55], mortality: 1.47 [1.33;1.63]). The cumulative incidence function of KF was higher for each quartile of urine C-glycosyltryptophan levels and the effect were most pronounced in the highest quartile (see Figure). The replicated metabolites belong to different biochemical classes, and those belonging to the phosphatidylcholines pathway showed enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established kidney failure risk equation by Tangri. Conclusion This comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identified and replicated 55 urine metabolites associated with adverse kidney events, potentially providing new insights into the mechanisms of kidney disease progression. The study represents a valuable resource for future experimental studies of biomarkers of CKD progression.

Background and Aims Osteopontin (OPN) is synthesized in the thick ascending limb of Henle’s loop and in the distal tubule. Numerous studies have shown that OPN mRNA and protein expression is increased in animal models of many different renal diseases, especially glomerular diseases as well as diabetic nephropathy. Here, high OPN expression correlated with proteinuria, reduction of creatinine clearance, fibrosis as well as macrophage and T-cell infiltration. OPN has therefore been suggested to be a promising biomarker for various kidney diseases. Further studies are needed to fully understand its role in kidney (patho-)physiology and its potential as a marker of kidney disease progression and adverse renal events. We therefore evaluated the association of OPN with kidney events and all-cause mortality in a cohort of CKD patients, the German Chronic Kidney Disease (GCKD) study. Method OPN was measured from baseline serum samples using the Quantikine Human OPN Immunoassay. Coefficients of variation were Results Over 6.5 years of follow-up, 473 kidney events and 582 deaths occurred among 4,950 GCKD patients. Hundred-and-forty-eight deaths and 62 kidney events occurred in 1,143 hypertensive nephropathy patients, 49 deaths and 118 kidney events occurred in 935 primary glomerular nephropathy patients, and 170 deaths and 99 kidney events in diabetic nephropathy patients (Table 1). Overall mean age was 60.1 years (±12.0), with 60.3% men. Median OPN levels were 29.2 ng/mL (IQR 21.2). Cross-sectionally a 10% change in OPN was associated with 0.5% lower eGFR on average (p Conclusion Higher OPN levels were associated with lower eGFR and higher UACR cross-sectionally and significantly associated with a higher risk of renal events and all-cause mortality especially for diabetic nephropathy patients even after adjustment for baseline eGFR, UACR and other confounding factors. These results are supportive of OPN being a potential marker of CKD progression and mortality.

Background and Aims Chronic kidney disease (CKD) patients are prone to prescription of multiple medications. Medication adherence is a well-recognized problem in the management of patients with chronic diseases requiring polypharmacy. This study aimed to evaluate the connection between self-reported medication use and urine drug metabolite levels in a large cohort of CKD patients, the GCKD study, as a basis for future pharmacometabolomics studies. Method Self-reported medication use of 160 substances and 41 medication groups was ascertained at study baseline and coded according to the Anatomical Therapeutic Chemical classification system. A non-targeted mass spectrometry-based approach (Metabolon HD4™) was used for concomitant metabolite quantification in urine. Specificity, sensitivity and accuracy of medication use and the corresponding urine metabolite measurements were calculated. Multivariable regression models (adjusted to age, sex, eGFR, log(UACR), systolic blood pressure, LDL, log(triglycerides), log(HBA1c) were used to establish associations in prescription patterns. Results Among 4,885 participants, 78 drug metabolites were detected in urine (frequency range: 0.4-58%) and assigned into 110 medication – drug metabolite pairs (MMPs) based on reported individual substances and medication groups. For all 68 MMPs of individual substances, accuracy of medication use and the corresponding drug metabolite measurement was excellent (median 97.0%, range 43%-100%), as was measurement-based specificity (median 99.3%, range 73.3%-100%; Fig. 1). Median measurement-based sensitivity was 72.1% (range 1.1%-100%, Fig. 1). Sensitivity and specificity were especially high for angiotensin-II receptor blockers (92%-96%; 99-100%), calcium channel blockers (85-100%; 91-100%), and metoprolol (90%; 98% respectively) commonly prescribed and important medications for blood pressure control and cardiovascular risk reduction in CKD patients. MMPs showing sensitivity Conclusion This study provides a comprehensive screen of the associations between urine drug metabolite levels and self-reported medication use. It supports the usefulness of pharmacometabolomics to assess medication use, frequency of OTC analgesics use, and prescription patterns in persons with CKD.

Rationale & Objective Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms. Study Design Metabolome-wide association study. Setting & Participants 5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study. Exposures Measurements of 1,487 metabolites in urine. Outcomes End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality. Analytical Approach Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models. Results After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation. Limitations Findings among patients of European ancestry with CKD may not be generalizable to the general population. Conclusions Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.

Blood metabolites of the tryptophan pathway were found to be associated with kidney function and disease in observational studies. In order to evaluate causal relationship and direction, we designed a study using a bidirectional Mendelian randomization approach. The analyses were based on published summary statistics with study sizes ranging from 1,960 to 133,413. After correction for multiple testing, results provided no evidence of an effect of metabolites of the tryptophan pathway on estimated glomerular filtration rate (eGFR). Conversely, lower eGFR was related to higher levels of four metabolites: C-glycosyltryptophan (effect estimate = − 0.16, 95% confidence interval [CI] (− 0.22; − 0.1); p = 9.2e−08), kynurenine (effect estimate = − 0.18, 95% CI (− 0.25; − 0.11); p = 1.1e−06), 3-indoxyl sulfate (effect estimate = − 0.25, 95% CI (− 0.4; − 0.11); p = 6.3e−04) and indole-3-lactate (effect estimate = − 0.26, 95% CI (− 0.38; − 0.13); p = 5.4e−05). Our study supports that lower eGFR causes higher blood metabolite levels of the tryptophan pathway including kynurenine, C-glycosyltryptophan, 3-indoxyl sulfate, and indole-3-lactate. These findings aid the notion that metabolites of the tryptophan pathway are a consequence rather than a cause of reduced eGFR. Further research is needed to specifically examine relationships with respect to chronic kidney disease (CKD) progression among patients with existing CKD.

Identification of chronic kidney disease patients at risk of progressing to end-stage renal disease (ESRD) is essential for treatment decision-making and clinical trial design. Here, we explored whether proton nuclear magnetic resonance (NMR) spectroscopy of blood plasma improves the currently best performing kidney failure risk equation, the so-called Tangri score. Our study cohort comprised 4640 participants from the German Chronic Kidney Disease (GCKD) study, of whom 185 (3.99%) progressed over a mean observation time of 3.70 ± 0.88 years to ESRD requiring either dialysis or transplantation. The original four-variable Tangri risk equation yielded a C statistic of 0.863 (95% CI, 0.831-0.900). Upon inclusion of NMR features by state-of-the-art machine learning methods, the C statistic improved to 0.875 (95% CI, 0.850-0.911), thereby outperforming the Tangri score in 94 out of 100 subsampling rounds. Of the 24 NMR features included in the model, creatinine, high-density lipoprotein, valine, acetyl groups of glycoproteins, and Ca2+-EDTA carried the highest weights. In conclusion, proton NMR-based plasma fingerprinting improved markedly the detection of patients at risk of developing ESRD, thus enabling enhanced patient treatment.

RATIONALE & OBJECTIVE: Stratification of chronic kidney disease (CKD) patients at risk for progressing to end-stage kidney disease (ESKD) requiring kidney replacement therapy (KRT) is important for clinical decision-making and trial enrollment. STUDY DESIGN: Four independent prospective observational cohort studies. SETTING & PARTICIPANTS: The development cohort was comprised of 4,915 CKD patients and three independent validation cohorts were comprised of a total of 3,063. Patients were followed-up for approximately five years. NEW PREDICTORS & ESTABLISHED PREDICTORS: 22 demographic, anthropometric and laboratory variables commonly assessed in CKD patients. OUTCOMES: Progression to ESKD requiring KRT. ANALYTICAL APPROACH: A Least Absolute Shrinkage and Selection Operator (LASSO) Cox proportional hazards model was fit to select laboratory variables that best identified patients at high risk for ESKD. Model discrimination and calibration were assessed and compared against the 4-variable Tangri (T4) risk equation. Both used a resampling approach within the development cohort and in the validation cohorts using cause-specific concordance (C) statistics, net reclassification improvement, and calibration graphs. RESULTS: The newly derived 6-variable (Z6) risk score included serum creatinine, albumin, cystatin C and urea, as well as hemoglobin and the urine albumin-to-creatinine ratio. Based on the resampling approach, Z6 achieved a median C value of 0.909 (95% CI, 0.868-0.937) at two years after the baseline visit, whereas the T4 achieved a median C value of 0.855 (95% CI, 0.799-0.915). In the three independent validation cohorts, Z6 C values were 0.894, 0.921, and 0.891, whereas the T4 C values were 0.882, 0.913, and 0.862. LIMITATIONS: The Z6 was both derived and tested only in White European cohorts. CONCLUSIONS: A new risk equation, based on six routinely available laboratory tests facilitates identification of patients with CKD who are at high risk of progressing to ESKD.

Background The kidneys have a central role in the generation, turnover, transport, and excretion of metabolites, and these functions can be altered in CKD. Genetic studies of metabolite concentrations can identify proteins performing these functions. Methods We conducted genome-wide association studies and aggregate rare variant tests of the concentrations of 139 serum metabolites and 41 urine metabolites, as well as their pairwise ratios and fractional excretions in up to 1168 patients with CKD. Results After correction for multiple testing, genome-wide significant associations were detected for 25 serum metabolites, two urine metabolites, and 259 serum and 14 urinary metabolite ratios. These included associations already known from population-based studies. Additional findings included an association for the uremic toxin putrescine and variants upstream of an enzyme catalyzing the oxidative deamination of polyamines (AOC1, P-min=2.4×10(−12)), a relatively high carrier frequency (2%) for rare deleterious missense variants in ACADM that are collectively associated with serum ratios of medium-chain acylcarnitines (P-burden=6.6×10(−16)), and associations of a common variant in SLC7A9 with several ratios of lysine to neutral amino acids in urine, including the lysine/glutamine ratio (P=2.2×10(−23)). The associations of this SLC7A9 variant with ratios of lysine to specific neutral amino acids were much stronger than the association with lysine concentration alone. This finding is consistent with SLC7A9 functioning as an exchanger of urinary cationic amino acids against specific intracellular neutral amino acids at the apical membrane of proximal tubular cells. Conclusions Metabolomic indices of specific kidney functions in genetic studies may provide insight into human renal physiology.

Metabolites are small molecules that are intermediates or products of metabolism, many of which are freely filtered by the kidneys. In addition, the kidneys have a central role in metabolite anabolism and catabolism, as well as in active metabolite reabsorption and/or secretion during tubular passage. This review article illustrates how the coupling of genomics and metabolomics in genome-wide association analyses of metabolites can be used to illuminate mechanisms underlying human metabolism, with a special focus on insights relevant to nephrology. First, genetic susceptibility loci for reduced kidney function and chronic kidney disease (CKD) were reviewed systematically for their associations with metabolite concentrations in metabolomics studies of blood and urine. Second, kidney function and CKD-associated metabolites reported from observational studies were interrogated for metabolite-associated genetic variants to generate and discuss complementary insights. Finally, insights originating from the simultaneous study of both blood and urine or by modeling intermetabolite relationships are summarized. We also discuss methodologic questions related to the study of metabolite concentrations in urine as well as among CKD patients. In summary, genome-wide association analyses of metabolites using metabolite concentrations quantified from blood and/or urine are a promising avenue of research to illuminate physiological and pathophysiological functions of the kidney.

Early diagnosis and prognosis monitoring for Stevens-Johnson syndrome/toxic epidermal necrolysis (TEN) still remain a challenge. This study aims to explore any cytokine/chemokine with prognostic potential in StevensJohnson syndrome/TEN. Through screening a panel of 28 serological factors, IL-6, IL-8, IL-15, tumor necrosis factor-a, and granulysin were upregulated in patients with Stevens-Johnson syndrome/TEN and selected for the further validation in total 155 patients with Stevens-Johnson syndrome/TEN, including 77 from Taiwan and 78 from the Registry of Severe Cutaneous Adverse Reactions. Among these factors evaluated, the levels of IL-15 (r = 0.401; P

Higher serum 6-bromotryptophan has been associated with lower risk of chronic kidney disease (CKD) progression, implicating mechanisms beyond renal clearance. We studied genetic determinants of urine 6-bromotryptophan and its association with CKD risk factors and incident end-stage kidney disease (ESKD) in 4,843 participants of the German Chronic Kidney Disease (GCKD) study. 6-bromotryptophan was measured from urine samples using mass spectrometry. Patients with higher levels of urine 6-bromotryptophan had higher baseline estimated glomerular filtration rate (eGFR, p

The purpose of this paper is to help readers choose an appropriate observational study design for measuring an association between an exposure and disease incidence. We discuss cohort studies, sub-samples from cohorts (case-cohort and nested case-control designs), and population-based or hospital-based case-control studies. Appropriate study design is the foundation of a scientifically valid observational study. Mistakes in design are often irremediable. Key steps are understanding the scientific aims of the study and what is required to achieve them. Some designs will not yield the information required to realise the aims. The choice of design also depends on the availability of source populations and resources. Choosing an appropriate design requires balancing the pros and cons of various designs in view of study aims and practical constraints. We compare various cohort and case-control designs to estimate the effect of an exposure on disease incidence and mention how certain design features can reduce threats to study validity.

Mendelian randomization refers to an analytic approach to assess the causality of an observed association between a modifiable exposure or risk factor and a clinically relevant outcome. It presents a valuable tool, especially when randomized controlled trials to examine causality are not feasible and observational studies provide biased associations because of confounding or reverse causality. These issues are addressed by using genetic variants as instrumental variables for the tested exposure: the alleles of this exposure-associated genetic variant are randomly allocated and not subject to reverse causation. This, together with the wide availability of published genetic associations to screen for suitable genetic instrumental variables make Mendelian randomization a time- and cost-efficient approach and contribute to its increasing popularity for assessing and screening for potentially causal associations. An observed association between the genetic instrumental variable and the outcome supports the hypothesis that the exposure in question is causally related to the outcome. This review provides an overview of the Mendelian randomization method, addresses assumptions and implications, and includes illustrative examples. We also discuss special issues in nephrology, such as inverse risk factor associations in advanced disease, and outline opportunities to design Mendelian randomization studies around kidney function and disease.

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.

Background When many (up to millions) of statistical tests are conducted in discovery set analyses such as genome-wide association studies (GWAS), approaches controlling family-wise error rate (FWER) or false discovery rate (FDR) are required to reduce the number of false positive decisions. Some methods were specifically developed in the context of high-dimensional settings and partially rely on the estimation of the proportion of true null hypotheses. However, these approaches are also applied in low-dimensional settings such as replication set analyses that might be restricted to a small number of specific hypotheses. The aim of this study was to compare different approaches in low-dimensional settings using (a) real data from the CKDGen Consortium and (b) a simulation study. Results In both application and simulation FWER approaches were less powerful compared to FDR control methods, whether a larger number of hypotheses were tested or not. Most powerful was the q-value method. However, the specificity of this method to maintain true null hypotheses was especially decreased when the number of tested hypotheses was small. In this low-dimensional situation, estimation of the proportion of true null hypotheses was biased. Conclusions The results highlight the importance of a sizeable data set for a reliable estimation of the proportion of true null hypotheses. Consequently, methods relying on this estimation should only be applied in high-dimensional settings. Furthermore, if the focus lies on testing of a small number of hypotheses such as in replication settings, FWER methods rather than FDR methods should be preferred to maintain high specificity. Electronic supplementary material The online version of this article (10.1186/s12859-018-2081-x) contains supplementary material, which is available to authorized users.

In 2012, a novel case series method dubbed the "case-chaos" design was proposed as an alternative to case-control studies, whereby controls are artificially created by permutating the exposure information of the cases. Our aim in the current work was to further evaluate the case-chaos method. Using a theoretical example of 2 risk factors, we demonstrated that the case-chaos design yields risk estimations for which the odds ratios obtained for every risk factor are in the same ascending order as the risk factors' exposure prevalences in the case group. Applying the method to data from the European Study of Severe Cutaneous Adverse Reactions (EuroSCAR; 1997-2001), we were not able to obtain sensible results but instead produced results as predicted by our theoretical assessment. We therefore claim that the method is equivalent to declaring risk solely on the basis of prevalences obtained in cases. While the proposers of the case-chaos method view it as a useful adjunct, we show that it cannot produce sensible estimates. Language: en

HLA-A*31:01 was reported to be associated with carbamazepine (CBZ)-induced severe cutaneous adverse reactions (SCAR), including drug reaction with eosinophilia and systemic symptoms (DRESS), Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). We conducted an international study using consensus diagnosis criteria to enroll a total of 93 patients with CBZ-SCAR from Europe or Asia. We found that HLA-A*31:01 showed a significant association with CBZ-DRESS in Europeans (P0.001; odds ratio (OR) (95% confidence interval (CI))=57.6 (11.0-340)), and the strong association was also found in Chinese (P0.001; OR (95% CI)=23.0 (4.2-125)). However, HLA-A*31:01 had no association with CBZ-SJS/TEN in neither Chinese nor Europeans. By comparison, HLA-B*15:02 showed a strong association with CBZ-SJS/TEN in Chinese (P0.001, OR (95% CI)=58.1 (17.6-192)). A meta-analysis of this and other published studies confirmed that in all populations, HLA-A*31:01 had an extremely strong association with CBZ-DRESS (P0.001, a pooled OR (95% CI)=13.2 (8.4-20.8)), but a much weaker association with CBZ-SJS/TEN (P=0.01, OR (95% CI)=3.94 (1.4-11.5)). Our data revealed that HLA-A*31:01 is a specific predictor for CBZ-DRESS but not for CBZ-SJS/TEN. More studies are needed to investigate the genetic determinant of CBZ-SJS/TEN in Europeans. Considering the potential clinical utility, the cost-effectiveness of the combined HLA-A*31:01 and HLA-B*15:02 genetic test to prevent CBZ-SCAR in Chinese needs further investigation.

BACKGROUND: Serum metabolites are associated cross-sectionally with kidney function in population-based studies. METHODS: Using flow injection and liquid chromatography tandem mass spectrometry methods, we examined longitudinal associations of baseline concentrations of 140 metabolites and their 19 460 ratios with kidney function decline and chronic kidney disease (CKD) incidence over 7 years in 1104 participants of the Cooperative Health Research in the Region of Augsburg S4/F4 study. RESULTS: Corrected for multiple testing, a significant association with annual change in the estimated glomerular filtration rate was observed for spermidine (P = 5.8 × 10-7) and two metabolite ratios, the phosphatidylcholine diacyl C42:5-to-phosphatidylcholine acyl-alkyl C36:0 ratio (P = 1.5 × 10-6) and the kynurenine-to-tryptophan ratio (P = 1.9 × 10-6). The kynurenine-to-tryptophan ratio was also associated with significantly higher incidence of CKD at the follow-up visit with an odds ratio of 1.36 per standard deviation increase; 95% confidence interval 1.11-1.66, P = 2.7 × 10-3). In separate analyses, the predictive ability of the metabolites was assessed: both the three significantly associated metabolite (ratios) as well as a panel of 35 metabolites selected from all metabolites in an unbiased fashion provided as much but not significantly more prognostic information than selected clinical predictors as judged by the area under the curve. CONCLUSIONS: Baseline serum concentrations of spermidine and two metabolite ratios were associated with kidney function change over subsequent years in the general population. In separate analyses, baseline serum metabolites were able to predict incident CKD to a similar but not better extent than selected clinical parameters. Our longitudinal findings provide a basis for targeted studies of certain metabolic pathways, e.g. tryptophan metabolism, and their relation to kidney function decline. KEYWORDS: GFR, incident chronic kidney disease, kidney function loss, metabolites, prediction &nbsp

Disorders of water balance, an excess or deficit of total body water relative to body electrolyte content, are common and ascertained by plasma hypo- or hypernatremia, respectively. We performed a two-stage genome-wide association study meta-analysis on plasma sodium concentration in 45,889 individuals of European descent (stage 1 discovery) and 17,637 additional individuals of European descent (stage 2 replication), and a transethnic meta-analysis of replicated single-nucleotide polymorphisms in 79,506 individuals (63,526 individuals of European descent, 8765 individuals of Asian Indian descent, and 7215 individuals of African descent). In stage 1, we identified eight loci associated with plasma sodium concentration at P-6. Of these, rs9980 at NFAT5 replicated in stage 2 meta-analysis (P=3.1 3 x 10-5), with combined stages 1 and 2 genomewide significance of P=5.6 x 10-10. Transethnic meta-analysis further supported the association at rs9980 (P=5.9 x 10-12). Additionally, rs16846053 at SLC4A10 showed nominally, but not genome-wide, significant association in combined stages 1 and 2 meta-analysis (P=6.7 x 10-8). NFAT5 encodes a ubiquitously expressed transcription factor that coordinates the intracellular response to hypertonic stress but was not previously implicated in the regulation of systemic water balance. SLC4A10 encodes a sodium bicarbonate transporter with a brain-restricted expression pattern, and variant rs16846053 affects a putative intronic NFAT5 DNA binding motif. The lead variants for NFAT5 and SLC4A10 are cis expression quantitative trait loci in tissues of the central nervous systemand relevant to transcriptional regulation. Thus, genetic variation in NFAT5 and SLC4A10 expression and function in the central nervous system may affect the regulation of systemic water balance.

Using a non-targeted metabolomics platform, we recently identified C-mannosyltryptophan and pseudouridine as non-traditional kidney function markers. The aims of this study were to obtain absolute concentrations of both metabolites in blood and urine from individuals with and without CKD to provide reference ranges and to assess their fractional excretions (FE), and to assess the agreement with their non-targeted counterparts. In individuals without/with CKD, mean plasma and urine concentrations for C-mannosyltryptophan were 0.26/0.72 μmol/L and 3.39/4.30 μmol/mmol creatinine, respectively. The respective concentrations for pseudouridine were 2.89/5.67 μmol/L and 39.7/33.9 μmol/mmol creatinine. Median (25 th , 75 th percentiles) FEs were 70.8% (65.6%, 77.8%) for C-mannosyltryptophan and 76.0% (68.6%, 82.4%) for pseudouridine, indicating partial net reabsorption. Association analyses validated reported associations between single metabolites and eGFR. Targeted measurements of both metabolites agreed well with the non-targeted measurements, especially in urine. Agreement for composite nephrological measures FE and urinary metabolite-to-creatinine ratio was lower, but could be improved by replacing non-targeted creatinine measurements with a standard clinical creatinine test. In summary, targeted quantification and additional characterization in relevant populations are necessary steps in the translation of non-traditional biomarkers in nephrology from non-targeted discovery to clinical application.

Summary Background Generalized bullous fixed drug eruption (GBFDE) is a rare cutaneous adverse reaction to drugs, and may resemble Stevens–Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN), but is usually considered less severe. Objectives To compare the severity and mortality rate in cases of GBFDE and control cases of SJS or TEN of similar extent of skin detachment. Methods This was a case–control analysis of 58 patients with GBFDE matched by age and extent of skin detachment to 170 control patients with a validated diagnosis of SJS or SJS/TEN overlap. Data for cases and controls were extracted from the EuroSCAR and RegiSCAR databases resulting from two population-based studies of severe cutaneous adverse reactions conducted in Europe. Preselected outcome criteria were death (primary), and fever, duration of hospitalization and transfer to an intensive care or burn unit (secondary). Results GBFDE affected mainly older patients (median age 78 years, interquartile range 68–84 years); 13 of 58 cases died (22%). The mortality rate was slightly but not significantly lower for patients with GBFDE than controls [28%, multivariate odds ratio 0·6 (95% confidence interval 0·30–1·4)]. Patients with GBFDE and controls did not differ in other preselected criteria for severity. Conclusions Although our study featured limited statistical power, we were not able to confirm that GBFDE had better prognosis than SJS or SJS/TEN of similar disease extent in older patients. Severe cases of GBFDE deserve the attention and active management given to patients with SJS or TEN.

Objectives When study groups fail to publish their results, a subsequent systematic review may come to incorrect conclusions when combining information only from published studies. p53 expression measured by immunohistochemistry is a potential prognostic factor in bladder cancer. Although numerous studies have been conducted, its role is still under debate. The assumption that unpublished studies too harbour evidence on this research topic leads to the question about the attributable effect when adding this information and comparing it with published data. Thus, the aim was to identify published and unpublished studies and to explore their differences potentially affecting the conclusion on its function as a prognostic biomarker. Design Systematic review of published and unpublished studies assessing p53 in bladder cancer in Germany between 1993 and 2007. Results The systematic search revealed 16 studies of which 11 (69%) have been published and 5 (31%) have not. Key reason for not publishing the results was a loss of interest of the investigators. There were no obviously larger differences between published and unpublished studies. However, a meaningful meta-analysis was not possible mainly due to the poor (ie, incomplete) reporting of study results. Conclusions Within this well-defined population of studies, we could provide empirical evidence for the failure of study groups to publish their results that was mainly caused by loss of interest. This fact may be coresponsible for the role of p53 as a prognostic factor still being unclear. We consider p53 and the restriction to studies in Germany as a specific example, but the critical issues are probably similar for other prognostic factors and other countries.

Summary Background Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are immunologically mediated, severe cutaneous adverse reactions involving cytotoxic T cells, natural killer cells and various mediators. In large studies, up to 15% of SJS/TEN occurred in patients with chronic corticosteroid use. It is unclear if this prior exposure to corticosteroids modified the disease course. Objectives To evaluate whether systemic corticosteroid usage prior to the onset of SJS/TEN modified the clinical course and outcome. If a disease-modifying effect is present, information from such an analysis may have implications on the therapeutic use of corticosteroids in SJS/TEN. Methods This is a case–control study based on data collected in the EuroSCAR and RegiSCAR studies. Ninety-two cases of SJS/TEN with exposure to corticosteroids prior to the onset of disease, and 321 randomly selected SJS/TEN patients without prior exposure were included. Primary outcomes included progression of disease, disease severity and mortality. A secondary analysis of latency between the beginning of drug use and the onset of disease, based on exposure to a single high-risk drug, was also performed. Results On multivariate analysis, cases with prior exposure to corticosteroids had a longer progression of disease by 2·2 days [95% confidence interval (CI) 1·1–3·2]. The disease severity and mortality outcome were unaffected. In addition, there is evidence that corticosteroids delayed the onset of SJS/TEN in patients with exposure to high-risk drugs by 7·1 days (CI −0·2 to 14·5). Conclusions The prior use of corticosteroids prolonged the period of disease progression without influencing the disease severity or mortality. In addition, when SJS/TEN is preceded by use of a single high-risk drug, the latency between the drug intake and the onset of SJS/TEN may also be increased. These findings suggest that corticosteroids have a mild impact on the course of SJS/TEN, and further studies are required to clarify any potential therapeutic effects.