Interactive exploration of adverse events and multimorbidity in CKD.

BACKGROUND AND HYPOTHESIS: Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality, and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study. METHODS: The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73m2 and an overt proteinuria. Cardio-, cerebro- and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology. RESULTS: Over a median of 6.5 years, 10 271 events occurred in total and 680 participants (13.0%) died while 2947 participants (56.5%) experienced any event. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology, and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney), and 66.0 (infection). Participants with diabetic kidney disease and men were more prone to experiencing events. CONCLUSION: This comprehensive explorative tool to visualize adverse events (https://gckd.diz.uk-erlangen.de/), their combination, mortality, and multimorbidity among persons with CKD may manifest as a valuable resource for patient care, identification of high-risk groups, health services, and public health policy planning.

Apolipoprotein A-IV concentrations and cancer in a large cohort of chronic kidney disease patients: results from the GCKD study.

BACKGROUND: Chronic kidney disease (CKD) is highly connected to inflammation and oxidative stress. Both favour the development of cancer in CKD patients. Serum apolipoprotein A-IV (apoA-IV) concentrations are influenced by kidney function and are an early marker of kidney impairment. Besides others, it has antioxidant and anti-inflammatory properties. Proteomic studies and small case-control studies identified low apoA-IV as a biomarker for various forms of cancer; however, prospective studies are lacking. We therefore investigated whether serum apoA-IV is associated with cancer in the German Chronic Kidney Disease (GCKD) study. METHODS: These analyses include 5039 Caucasian patients from the prospective GCKD cohort study followed for 6.5 years. Main inclusion criteria were an eGFR of 30-60 mL/min/1.73m2 or an eGFR > 60 mL/min/1.73m2 in the presence of overt proteinuria. RESULTS: Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dL (median 27.6 mg/dL). 615 patients had a history of cancer before the enrolment into the study. ApoA-IV concentrations above the median were associated with a lower odds for a history of cancer (OR = 0.79, p = 0.02 when adjusted age, sex, smoking, diabetes, BMI, albuminuria, statin intake, and eGFRcreatinine). During follow-up 368 patients developed an incident cancer event and those with apoA-IV above the median had a lower risk (HR = 0.72, 95%CI 0.57-0.90, P = 0.004). Finally, 62 patients died from such an incident cancer event and each 10 mg/dL higher apoA-IV concentrations were associated with a lower risk for fatal cancer (HR = 0.62, 95%CI 0.44-0.88, P = 0.007). CONCLUSIONS: Our data indicate an association of high apoA-IV concentrations with reduced frequencies of a history of cancer as well as incident fatal and non-fatal cancer events in a large cohort of patients with CKD.

Cardiovascular risk due to diabetes mellitus in patients with chronic kidney disease-prospective data from the German Chronic Kidney Disease cohort.

Background: Diabetes mellitus (DM) and chronic kidney disease (CKD) are well-known cardiovascular and mortality risk factors. To what extent they act in an additive manner and whether the etiology of CKD modifies the risk is uncertain. Methods: The multicenter, prospective, observational German Chronic Kidney Disease study comprises 5217 participants (1868 with DM) with a baseline mean estimated glomerular filtration rate of 30-60 mL/min/1.73 m2 and/or proteinuria >0.5 g/day. We categorized patients whose CKD was caused by cardiovascular or metabolic diseases (CKDcvm) with and without DM, as opposed to genuine CKD (CKDgen) with and without DM. Recorded outcomes were first events of non-cardiovascular and cardiovascular death, 4-point major adverse cardiovascular events (4-point MACE) and hospitalization for heart failure (HHF). Results: During the 6.5-year follow-up 603 (12%) non-cardiovascular and 209 (4%) cardiovascular deaths, 645 (12%) 4-point MACE, and 398 (8%) HHF were observed, most frequently in patients with DM having CKDcvm. DM increased the risk of non-cardiovascular [hazard ratio (HR) 1.92; 95% confidence interval (CI) 1.59-2.32] and cardiovascular (HR 2.25; 95% CI 1.62-3.12) deaths, 4-point MACE (HR 1.93; 95% CI 1.62-2.31) and HHF (HR 1.87; 95% CI 1.48-2.36). Mortality risks were elevated by DM to a similar extent in CKDcvm and CKDgen, but for HHF in CKDcvm only (HR 2.07; 95% CI 1.55-2.77). In patients with DM, CKDcvm (versus CKDgen) only increased the risk for HHF (HR 1.93; 95% CI 1.15-3.22). Conclusions: DM contributes to cardiovascular and mortality excess risk in patients with moderate to severe CKD in both, CKDcvm and CKDgen. Patients with DM and CKDcvm are particularly susceptible to HHF.

Copeptin, Natriuretic Peptides, and Cardiovascular Outcomes in Patients With CKD: The German Chronic Kidney Disease (GCKD) Study.

Rationale & Objective: Copeptin and Midrange pro-atrial natriuretic peptide (MR-pro-ANP) are associated with outcomes independently of N-terminal pro-brain natriuretic peptide (NT-pro-BNP) in patients with heart failure (HF). The value of these markers in patients with chronic kidney disease (CKD) has not been studied. Study Design: Prospective cohort study. Setting & Participants: A total of 4,417 patients enrolled in the German Chronic Kidney Disease (GCKD) study with an estimated glomerular filtration rate of 30-60 mL/min/1.73m2 or overt proteinuria (urinary albumin-creatinine ratio >300mg/g or equivalent). Exposures: Copeptin, MR-pro-ANP, and NT-pro-BNP levels were measured in baseline samples. Outcomes: Noncardiovascular death, cardiovascular (CV) death, major adverse CV event (MACE), and hospitalization for HF. Analytical Approach: HRs for associations of Copeptin, MR-pro-ANP, and NT-pro-BNP with outcomes were estimated using Cox regression analyses adjusted for established risk factors. Results: During a maximum follow-up of 6.5 years, 413 non-CV deaths, 179 CV deaths, 519 MACE, and 388 hospitalizations for HF were observed. In Cox regression analyses adjusted for established risk factors, each one of the 3 markers were associated with all the 4 outcomes, albeit the highest HRs were found for NT-pro-BNP. When models were extended to include all the 3 markers, NT-pro-BNP remained associated with all 4 outcomes. Conversely, from the 2 novel markers, associations remained only for Copeptin with non-CV death (HR, 1.62; 95% CI, 1.04-2.54 for highest vs lowest quintile) and with hospitalizations for HF (HR, 1.73; 95% CI, 1.08-2.75). Limitations: Single-point measurements of Copeptin, MR-pro-ANP, and NT-pro-BNP. Conclusions: In patients with moderately severe CKD, we confirm NT-pro-BNP to be strongly associated with all outcomes examined. As the main finding, the novel marker Copeptin demonstrated independent associations with non-CV death and hospitalizations for HF, and should therefore be evaluated further for risk assessment in CKD. Plain-Language Summary: A blood sample-based biomarker that indicates high cardiovascular risk in a patient with kidney disease would help to guide interventions and has the potential to improve outcomes. In 4,417 patients of the German Chronic Kidney Disease study, we assessed the relationship of Copeptin, pro-atrial natriuretic peptide, and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) with important outcomes over a follow-up period of 6.5 years. NT-pro-BNP was strongly associated with all of the 4 outcomes, including death unrelated to cardiovascular disease, death because of cardiovascular disease, a major cardiovascular event, and hospitalization for heart failure. Copeptin was associated with death unrelated to cardiovascular disease and hospitalization for heart failure. NT-pro-BNP and Copeptin are, therefore, promising candidates for a blood sample-based strategy to identify patients with kidney disease at high cardiovascular risk.

Expectation of clinical decision support systems: a survey study among nephrologist end-users.

BACKGROUND: Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce. PURPOSE: Nephrologists' attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists' experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting. METHODS: The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted. RESULTS: The study population comprised 54 physicians, with a response rate of about 80-100% per question. Most participants were aged between 51-60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse. CONCLUSION: This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.

Association of mineral and bone biomarkers with adverse cardiovascular outcomes and mortality in the German Chronic Kidney Disease (GCKD) cohort.

Mineral and bone disorder (MBD) in chronic kidney disease (CKD) is tightly linked to cardiovascular disease (CVD). In this study, we aimed to compare the prognostic value of nine MBD biomarkers to determine those associated best with adverse cardiovascular (CV) outcomes and mortality. In 5 217 participants of the German CKD (GCKD) study enrolled with an estimated glomerular filtration rate (eGFR) between 30-60 mL·min-1 per 1.73 m2 or overt proteinuria, serum osteoprotegerin (OPG), C-terminal fibroblast growth factor-23 (FGF23), intact parathyroid hormone (iPTH), bone alkaline phosphatase (BAP), cross-linked C-telopeptide of type 1 collagen (CTX1), procollagen 1 intact N-terminal propeptide (P1NP), phosphate, calcium, and 25-OH vitamin D were measured at baseline. Participants with missing values among these parameters (n = 971) were excluded, leaving a total of 4 246 participants for analysis. During a median follow-up of 6.5 years, 387 non-CV deaths, 173 CV deaths, 645 nonfatal major adverse CV events (MACEs) and 368 hospitalizations for congestive heart failure (CHF) were observed. OPG and FGF23 were associated with all outcomes, with the highest hazard ratios (HRs) for OPG. In the final Cox regression model, adjusted for CV risk factors, including kidney function and all other investigated biomarkers, each standard deviation increase in OPG was associated with non-CV death (HR 1.76, 95% CI: 1.35-2.30), CV death (HR 2.18, 95% CI: 1.50-3.16), MACE (HR 1.38, 95% CI: 1.12-1.71) and hospitalization for CHF (HR 2.05, 95% CI: 1.56-2.69). Out of the nine biomarkers examined, stratification based on serum OPG best identified the CKD patients who were at the highest risk for any adverse CV outcome and mortality.

Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine.

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments.

Differential Prognostic Utility of Adiposity Measures in Chronic Kidney Disease.

OBJECTIVE: Adipose tissue contributes to adverse outcomes in chronic kidney disease (CKD), but there is uncertainty regarding the prognostic relevance of different adiposity measures. We analyzed the associations of neck circumference (NC), waist circumference (WC), and body mass index (BMI) with clinical outcomes in patients with mild to severe CKD. METHODS: The German Chronic Kidney Disease study is a prospective cohort study, which enrolled Caucasian adults with mild to severe CKD, defined as estimated glomerular filtration rate : 30-60 mL/min/1.73 m2, or >60 mL/min/1.73 m2 in the presence of overt proteinuria. Associations of NC, WC, and BMI with all-cause death, major adverse cardiovascular events (MACE: a composite of nonfatal stroke, nonfatal myocardial infarction, peripheral artery disease intervention, and cardiovascular death), and kidney failure (a composite of dialysis or transplantation) were analyzed using multivariable Cox proportional hazards regression models adjusted for confounders and the Akaike information criteria were calculated. Models included sex interactions with adiposity measures. RESULTS: A total of 4537 participants (59% male) were included in the analysis. During a 6.5-year follow-up, 339 participants died, 510 experienced MACE, and 341 developed kidney failure. In fully adjusted models, NC was associated with all-cause death in women (hazard ratio 1.080 per cm; 95% CI 1.009-1.155) but not in men. Irrespective of sex, WC was associated with all-cause death (hazard ratio 1.014 per cm; 95% CI 1.005-1.038). NC and WC showed no association with MACE or kidney failure. BMI was not associated with any of the analyzed outcomes. Models of all-cause death, including WC offered the best (lowest) Akaike information criteria. CONCLUSION: In Caucasian patients with mild to severe CKD, higher NC (in women) and WC were significantly associated with increased risk of death from any cause but BMI was not.

Development and Validation of a Prediction Model for Future Estimated Glomerular Filtration Rate in People With Type 2 Diabetes and Chronic Kidney Disease.

Importance: Type 2 diabetes increases the risk of progressive diabetic kidney disease, but reliable prediction tools that can be used in clinical practice and aid in patients' understanding of disease progression are currently lacking. Objective: To develop and externally validate a model to predict future trajectories in estimated glomerular filtration rate (eGFR) in adults with type 2 diabetes and chronic kidney disease using data from 3 European multinational cohorts. Design, Setting, and Participants: This prognostic study used baseline and follow-up information collected between February 2010 and December 2019 from 3 prospective multinational cohort studies: PROVALID (Prospective Cohort Study in Patients with Type 2 Diabetes Mellitus for Validation of Biomarkers), GCKD (German Chronic Kidney Disease), and DIACORE (Diabetes Cohorte). A total of 4637 adult participants (aged 18-75 years) with type 2 diabetes and mildly to moderately impaired kidney function (baseline eGFR of ≥30 mL/min/1.73 m2) were included. Data were analyzed between June 30, 2021, and January 31, 2023. Main Outcomes and Measures: Thirteen variables readily available from routine clinical care visits (age, sex, body mass index; smoking status; hemoglobin A1c [mmol/mol and percentage]; hemoglobin, and serum cholesterol levels; mean arterial pressure, urinary albumin-creatinine ratio, and intake of glucose-lowering, blood-pressure lowering, or lipid-lowering medication) were selected as predictors. Repeated eGFR measurements at baseline and follow-up visits were used as the outcome. A linear mixed-effects model for repeated eGFR measurements at study entry up to the last recorded follow-up visit (up to 5 years after baseline) was fit and externally validated. Results: Among 4637 adults with type 2 diabetes and chronic kidney disease (mean [SD] age at baseline, 63.5 [9.1] years; 2680 men [57.8%]; all of White race), 3323 participants from the PROVALID and GCKD studies (mean [SD] age at baseline, 63.2 [9.3] years; 1864 men [56.1%]) were included in the model development cohort, and 1314 participants from the DIACORE study (mean [SD] age at baseline, 64.5 [8.3] years; 816 men [62.1%]) were included in the external validation cohort, with a mean (SD) follow-up of 5.0 (0.6) years. Updating the random coefficient estimates with baseline eGFR values yielded improved predictive performance, which was particularly evident in the visual inspection of the calibration curve (calibration slope at 5 years: 1.09; 95% CI, 1.04-1.15). The prediction model had good discrimination in the validation cohort, with the lowest C statistic at 5 years after baseline (0.79; 95% CI, 0.77-0.80). The model also had predictive accuracy, with an R2 ranging from 0.70 (95% CI, 0.63-0.76) at year 1 to 0.58 (95% CI, 0.53-0.63) at year 5. Conclusions and Relevance: In this prognostic study, a reliable prediction model was developed and externally validated; the robust model was well calibrated and capable of predicting kidney function decline up to 5 years after baseline. The results and prediction model are publicly available in an accompanying web-based application, which may open the way for improved prediction of individual eGFR trajectories and disease progression.

Different roles of protein biomarkers predicting eGFR trajectories in people with chronic kidney disease and diabetes mellitus: a nationwide retrospective cohort study.

BACKGROUND: Chronic kidney disease (CKD) is a common comorbidity in people with diabetes mellitus, and a key risk factor for further life-threatening conditions such as cardiovascular disease. The early prediction of progression of CKD therefore is an important clinical goal, but remains difficult due to the multifaceted nature of the condition. We validated a set of established protein biomarkers for the prediction of trajectories of estimated glomerular filtration rate (eGFR) in people with moderately advanced chronic kidney disease and diabetes mellitus. Our aim was to discern which biomarkers associate with baseline eGFR or are important for the prediction of the future eGFR trajectory. METHODS: We used Bayesian linear mixed models with weakly informative and shrinkage priors for clinical predictors (n = 12) and protein biomarkers (n = 19) to model eGFR trajectories in a retrospective cohort study of people with diabetes mellitus (n = 838) from the nationwide German Chronic Kidney Disease study. We used baseline eGFR to update the models' predictions, thereby assessing the importance of the predictors and improving predictive accuracy computed using repeated cross-validation. RESULTS: The model combining clinical and protein predictors had higher predictive performance than a clinical only model, with an [Formula: see text] of 0.44 (95% credible interval 0.37-0.50) before, and 0.59 (95% credible interval 0.51-0.65) after updating by baseline eGFR, respectively. Only few predictors were sufficient to obtain comparable performance to the main model, with markers such as Tumor Necrosis Factor Receptor 1 and Receptor for Advanced Glycation Endproducts being associated with baseline eGFR, while Kidney Injury Molecule 1 and urine albumin-creatinine-ratio were predictive for future eGFR decline. CONCLUSIONS: Protein biomarkers only modestly improve predictive accuracy compared to clinical predictors alone. The different protein markers serve different roles for the prediction of longitudinal eGFR trajectories potentially reflecting their role in the disease pathway.

KLKB1 and CLSTN2 are associated with HDL-mediated cholesterol efflux capacity in a genome-wide association study.

BACKGROUND AND AIMS: HDL-mediated cholesterol efflux capacity (CEC) may protect from cardiovascular disease. Thus, we aimed to identify its genetic and non-genetic determinants. METHODS: We measured CEC to 2% apolipoprotein B-depleted serum using BODIPY-cholesterol and cAMP-stimulated J774A.1 macrophages using serum samples from 4,981 participants in the German Chronic Kidney Disease (GCKD) study. Variance of CEC explained by clinical and biochemical parameters in a multivariable linear regression model was calculated by proportional marginal variance decomposition. A genome-wide association study with 7,746,917 variants was performed based on an additive genetic model. The main model was adjusted for age, sex and principal components 1-10. Further models were selected for sensitivity analysis and to reduce residual variance by known CEC pathways. RESULTS: Variables that explained 1% and more of the variance of CEC were concentrations of triglycerides (12.9%), HDL-cholesterol (11.8%), LDL-cholesterol (3.0%), apolipoprotein A-IV (2.8%), PCSK9 (1.0%), and eGFR (1.0%). The KLKB1 (chr4) and APOE/C1 (chr19) loci were genome-wide significantly (p < 5x10-8) associated with CEC in our main model (p = 8.8x10-10 and p = 3.3x10-10, respectively). KLKB1 remained significantly associated after additional adjustment for either kidney parameters, HDL-cholesterol, triglycerides or apolipoprotein A-IV concentrations, while the APOE/C1 locus was not significantly associated anymore after adjustment for triglycerides. Adjustment for triglycerides also revealed an association with the CLSTN2 locus (chr3; p = 6.0x10-9). CONCLUSIONS: We identified HDL-cholesterol and triglycerides as the main determinants of CEC. Furthermore, we newly found a significant association of CEC with the KLKB1 and the CLSTN2 locus and confirmed the association with the APOE/C1 locus, likely mediated by triglycerides.

Uromodulin and its association with urinary metabolites: the German Chronic Kidney Disease Study.

BACKGROUND: The progression of chronic kidney disease (CKD), a global public health burden, is accompanied by a declining number of functional nephrons. Estimation of remaining nephron mass may improve assessment of CKD progression. Uromodulin has been suggested as a marker of tubular mass. We aimed to identify metabolites associated with uromodulin concentrations in urine and serum to characterize pathophysiologic alterations of metabolic pathways to generate new hypotheses regarding CKD pathophysiology. METHODS: We measured urinary and serum uromodulin levels (uUMOD, sUMOD) and 607 urinary metabolites and performed cross-sectional analyses within the German Chronic Kidney Disease study (N = 4628), a prospective observational study. Urinary metabolites significantly associated with uUMOD and sUMOD were used to build weighted metabolite scores for urine (uMS) and serum uromodulin (sMS) and evaluated for time to adverse kidney events over 6.5 years. RESULTS: Metabolites cross-sectionally associated with uromodulin included amino acids of the tryptophan metabolism, lipids and nucleotides. Higher levels of the sMS [hazard ratio (HR) = 0.73 (95% confidence interval 0.64; 0.82), P = 7.45e-07] and sUMOD [HR = 0.74 (95% confidence interval 0.63; 0.87), P = 2.32e-04] were associated with a lower risk of adverse kidney events over time, whereas uUMOD and uMS showed the same direction of association but were not significant. CONCLUSIONS: We identified urinary metabolites associated with urinary and serum uromodulin. The sUMOD and the sMS were associated with lower risk of adverse kidney events among CKD patients. Higher levels of sUMOD and sMS may reflect a higher number of functional nephrons and therefore a reduced risk of adverse kidney outcomes.

Prevalence of hereditary tubulointerstitial kidney diseases in the German Chronic Kidney Disease study.

Hereditary chronic kidney disease (CKD) appears to be more frequent than the clinical perception. Exome sequencing (ES) studies in CKD cohorts could identify pathogenic variants in ~10% of individuals. Tubulointerstitial kidney diseases, showing no typical clinical/histologic finding but tubulointerstitial fibrosis, are particularly difficult to diagnose. We used a targeted panel (29 genes) and MUC1-SNaPshot to sequence 271 DNAs, selected in defined disease entities and age cutoffs from 5217 individuals in the German Chronic Kidney Disease cohort. We identified 33 pathogenic variants. Of these 27 (81.8%) were in COL4A3/4/5, the largest group being 15 COL4A5 variants with nine unrelated individuals carrying c.1871G>A, p.(Gly624Asp). We found three cysteine variants in UMOD, a novel missense and a novel splice variant in HNF1B and the homoplastic MTTF variant m.616T>C. Copy-number analysis identified a heterozygous COL4A5 deletion, and a HNF1B duplication/deletion, respectively. Overall, pathogenic variants were present in 12.5% (34/271) and variants of unknown significance in 9.6% (26/271) of selected individuals. Bioinformatic predictions paired with gold standard diagnostics for MUC1 (SNaPshot) could not identify the typical cytosine duplication ("c.428dupC") in any individual, implying that ADTKD-MUC1 is rare. Our study shows that >10% of selected individuals carry disease-causing variants in genes partly associated with tubulointerstitial kidney diseases. COL4A3/4/5 genes constitute the largest fraction, implying they are regularly overlooked using clinical Alport syndrome criteria and displaying the existence of phenocopies. We identified variants easily missed by some ES pipelines. The clinical filtering criteria applied enriched for an underlying genetic disorder.

Educational Attainment Is Associated With Kidney and Cardiovascular Outcomes in the German CKD (GCKD) Cohort.

Introduction: Prospective data on impact of educational attainment on prognosis in patients with chronic kidney disease (CKD) are scarce. We investigated the association between educational attainment and all-cause mortality, major adverse cardiovascular (CV) events (MACEs), kidney failure requiring dialysis, and CKD etiology. Methods: Participants (N = 5095, aged 18-74 years) of the ongoing multicenter German Chronic Kidney Disease (GCKD) cohort, enrolled on the basis of an estimated glomerular filtration rate (eGFR) of 30 to 60 ml/min (stages G3, A1-A3) or overt proteinuria (stages G1-G2, A3), were divided into 3 categories according to their educational attainment and were followed for 6.5 years. Results: Participants with low educational attainment (vs. high) had a higher risk for mortality (hazard ratio [HR] 1.48, 95% CI: 1.16-1.90), MACE (HR 1.37, 95% CI: 1.02-1.83), and kidney failure (HR 1.54, 95% CI: 1.15-2.05). Mediators between low educational attainment and mortality were smoking, CV disease (CVD) at baseline, low income, higher body mass index, and higher serum levels of CRP, high-density lipoprotein cholesterol, uric acid, NGAL, BAP, NT-proBNP, OPN, H-FABP, and urea. Low educational attainment was positively associated with diabetic nephropathy (odds ratio [OR] 1.65, 95% CI: 1.36-2.0) and CKD subsequent to acute kidney injury (OR 1.56, 95% CI: 1.03-2.35), but negatively associated with IgA nephropathy (OR 0.68, 95% CI: 0.52-0.90). Conclusion: Low educational attainment is associated with adverse outcomes and CKD etiology. Lifestyle habits and biomarkers mediate associations between low educational attainment and mortality. Recognition of the role of educational attainment and the associated health-relevant risk factors is important to optimize the care of patients with CKD and improve prognosis.

Heart-Type Fatty Acid Binding Protein, Cardiovascular Outcomes, and Death: Findings From the German CKD Cohort Study.

RATIONALE & OBJECTIVE: Heart-type fatty acid binding protein (H-FABP) is a biomarker that has been shown to provide long-term prognostic information in patients with coronary artery disease independently of high-sensitivity troponin T (hs-TNT). We examined the independent associations of H-FABP with cardiovascular outcomes in patients with chronic kidney disease (CKD). STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 4,951 patients enrolled in the German Chronic Kidney Disease (GCKD) study with an estimated glomerular filtration rate of 30-60 mL/min/1.73 m2 or overt proteinuria (urinary albumin-creatinine ratio > 300 mg/g or equivalent). EXPOSURE: Serum levels of H-FABP and hs-TNT were measured at study entry. OUTCOME: Noncardiovascular (non-CV) death, CV death, combined major adverse CV events (MACE), and hospitalization for congestive heart failure (CHF). ANALYTICAL APPROACH: Hazard ratios (HRs) for associations of H-FABP and hs-TNT with outcomes were estimated using Cox regression analyses adjusted for established risk factors. RESULTS: During a maximum follow-up of 6.5 years, 579 non-CV deaths, 190 CV deaths, 522 MACE, and 381 CHF hospitalizations were observed. In Cox regression analyses adjusted for established risk factors, H-FABP was associated with all 4 outcomes, albeit with lower HRs than those found for hs-TNT. After further adjustment for hs-TNT levels, H-FABP was found to be associated with non-CV death (HR, 1.57 [95% CI, 1.14-2.18]) and MACE (HR, 1.40 [95% CI, 1.02-1.92]) but with neither CV death (HR, 1.64 [95% CI, 0.90-2.99]) nor CHF hospitalizations (HR, 1.02 [95% CI, 0.70-1.49]). LIMITATIONS: Single-point measurements of H-FABP and hs-TNT. Uncertain generalizability to non-European populations. CONCLUSIONS: In this large cohort of patients with CKD, H-FABP was associated with non-CV death and MACE, even after adjustment for hs-TNT. Whether measurement of H-FABP improves cardiovascular disease risk prediction in these patients warrants further studies.

The Cardiovascular Literature-Based Risk Algorithm (CALIBRA): Predicting Cardiovascular Events in Patients With Non-Dialysis Dependent Chronic Kidney Disease.

Background and Objectives: Cardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA). Methods: CALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD®) and the German Chronic Kidney Disease (GCKD) study prospective cohort. CALIBRA performance was evaluated by c-statistics and calibration charts. In addition, CALIBRA discrimination was compared with that of three validated tools currently used for CV prediction in CKD, namely the Framingham Heart Study (FHS) risk score, the atherosclerotic cardiovascular disease risk score (ASCVD), and the Individual Data Analysis of Antihypertensive Intervention Trials (INDANA) calculator. Superiority was defined as a ΔAUC>0.05. Results: CALIBRA showed good discrimination in both the EuCliD® medical registry (AUC 0.79, 95%CI 0.76-0.81) and the GCKD cohort (AUC 0.73, 95%CI 0.70-0.76). CALIBRA demonstrated improved accuracy compared to the benchmark models in EuCliD® (FHS: ΔAUC=-0.22, p<0.001; ASCVD: ΔAUC=-0.17, p<0.001; INDANA: ΔAUC=-0.14, p<0.001) and GCKD (FHS: ΔAUC=-0.16, p<0.001; ASCVD: ΔAUC=-0.12, p<0.001; INDANA: ΔAUC=-0.04, p<0.001) populations. Accuracy of the CALIBRA score was stable also for patients showing missing variables. Conclusion: CALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings.

Validation of a Novel Predictive Algorithm for Kidney Failure in Patients Suffering from Chronic Kidney Disease: The Prognostic Reasoning System for Chronic Kidney Disease (PROGRES-CKD).

Current equation-based risk stratification algorithms for kidney failure (KF) may have limited applicability in real world settings, where missing information may impede their computation for a large share of patients, hampering one from taking full advantage of the wealth of information collected in electronic health records. To overcome such limitations, we trained and validated the Prognostic Reasoning System for Chronic Kidney Disease (PROGRES-CKD), a novel algorithm predicting end-stage kidney disease (ESKD). PROGRES-CKD is a naïve Bayes classifier predicting ESKD onset within 6 and 24 months in adult, stage 3-to-5 CKD patients. PROGRES-CKD trained on 17,775 CKD patients treated in the Fresenius Medical Care (FMC) NephroCare network. The algorithm was validated in a second independent FMC cohort (n = 6760) and in the German Chronic Kidney Disease (GCKD) study cohort (n = 4058). We contrasted PROGRES-CKD accuracy against the performance of the Kidney Failure Risk Equation (KFRE). Discrimination accuracy in the validation cohorts was excellent for both short-term (stage 4-5 CKD, FMC: AUC = 0.90, 95%CI 0.88-0.91; GCKD: AUC = 0.91, 95% CI 0.86-0.97) and long-term (stage 3-5 CKD, FMC: AUC = 0.85, 95%CI 0.83-0.88; GCKD: AUC = 0.85, 95%CI 0.83-0.88) forecasting horizons. The performance of PROGRES-CKD was non-inferior to KFRE for the 24-month horizon and proved more accurate for the 6-month horizon forecast in both validation cohorts. In the real world setting captured in the FMC validation cohort, PROGRES-CKD was computable for all patients, whereas KFRE could be computed for complete cases only (i.e., 30% and 16% of the cohort in 6- and 24-month horizons). PROGRES-CKD accurately predicts KF onset among CKD patients. Contrary to equation-based scores, PROGRES-CKD extends to patients with incomplete data and allows explicit assessment of prediction robustness in case of missing values. PROGRES-CKD may efficiently assist physicians' prognostic reasoning in real-life applications.

A prediction model for the decline in renal function in people with type 2 diabetes mellitus: study protocol.

BACKGROUND: Chronic kidney disease (CKD) is a well-established complication in people with diabetes mellitus. Roughly one quarter of prevalent patients with diabetes exhibit a CKD stage of 3 or higher and the individual course of progression is highly variable. Therefore, there is a clear need to identify patients at high risk for fast progression and the implementation of preventative strategies. Existing prediction models of renal function decline, however, aim to assess the risk by artificially grouped patients prior to model building into risk strata defined by the categorization of the least-squares slope through the longitudinally fluctuating eGFR values, resulting in a loss of predictive precision and accuracy. METHODS: This study protocol describes the development and validation of a prediction model for the longitudinal progression of renal function decline in Caucasian patients with type 2 diabetes mellitus (DM2). For development and internal-external validation, two prospective multicenter observational studies will be used (PROVALID and GCKD). The estimated glomerular filtration rate (eGFR) obtained at baseline and at all planned follow-up visits will be the longitudinal outcome. Demographics, clinical information and laboratory measurements available at a baseline visit will be used as predictors in addition to random country-specific intercepts to account for the clustered data. A multivariable mixed-effects model including the main effects of the clinical variables and their interactions with time will be fitted. In application, this model can be used to obtain personalized predictions of an eGFR trajectory conditional on baseline eGFR values. The final model will then undergo external validation using a third prospective cohort (DIACORE). The final prediction model will be made publicly available through the implementation of an R shiny web application. DISCUSSION: Our proposed state-of-the-art methodology will be developed using multiple multicentre study cohorts of people with DM2 in various CKD stages at baseline, who have received modern therapeutic treatment strategies of diabetic kidney disease in contrast to previous models. Hence, we anticipate that the multivariable prediction model will aid as an additional informative tool to determine the patient-specific progression of renal function and provide a useful guide to early on identify individuals with DM2 at high risk for rapid progression.

Association of the metabolic syndrome with mortality and major adverse cardiac events: A large chronic kidney disease cohort.

BACKGROUND: Metabolic syndrome with its key components insulin resistance, central obesity, dyslipidaemia, and hypertension is associated with a high risk for cardiovascular events and all-cause mortality in the general population. However, evidence that these findings apply to patients with chronic kidney disease (CKD) with moderately reduced estimated glomerular filtration rate and/or albuminuria is limited. OBJECTIVES: We aimed to investigate the association between metabolic syndrome and its components with all-cause mortality and cardiovascular outcomes in CKD patients. METHODS: Prospective observation of a cohort of 5110 CKD patients from the German Chronic Kidney Disease study with 3284 (64.3%) of them having a metabolic syndrome at baseline. RESULTS: During the follow-up of 6.5 years, 605 patients died and 650 patients experienced major cardiovascular events. After extended data adjustment, patients with a metabolic syndrome had a higher risk for all-cause mortality (hazard ratio [HR] = 1.26, 95% confidence interval [CI]: 1.04-1.54) and cardiovascular events (HR = 1.48, 95% CI: 1.22-1.79). The risk increased steadily with a growing number of metabolic syndrome components (increased waist circumference, glucose, triglycerides, hypertension and decreased HDL cholesterol): HR per component = 1.09 (95% CI: 1.02-1.17) for all-cause mortality and 1.23 (95% CI: 1.15-1.32) for cardiovascular events. This resulted in hazard ratios between 1.50 and 2.50 in the case when four or five components are present. An analysis of individual components of metabolic syndrome showed that the glucose component led to the highest increase in risk for all-cause mortality (HR = 1.68, 95% CI: 1.38-2.03) and cardiovascular events (HR = 1.81, 95% CI: 1.51-2.18), followed by the HDL cholesterol and triglyceride components. CONCLUSIONS: We observed a high prevalence of metabolic syndrome among patients with moderate CKD. Metabolic syndrome increases the risk for all-cause mortality and cardiovascular events. The glucose and lipid components seem to be the main drivers for the association with outcomes.