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.

Prospective Cohort Study of Soluble Urokinase Plasminogen Activation Receptor and Cardiovascular Events in Patients With CKD.

Introduction: Soluble urokinase plasminogen activation receptor (suPAR) is an immune-derived pathogenic factor for kidney and atherosclerotic disease. Whether the association between suPAR and cardiovascular (CV) outcomes is dependent on the severity of underlying kidney disease is unclear. Methods: We measured serum suPAR levels in 4994 participants (mean age 60 years; 60% men; 36% with diabetes mellitus; mean estimated glomerular filtration rate (eGFR) 49 ml/min per 1.73 m2, SD 18) of the German Chronic Kidney Disease (GCKD) cohort and examined its association with all-cause death, CV death, and major CV events (MACE) across the range of eGFR and urine albumin-to-creatinine ratio (UACR). Results: The median suPAR level was 1771 pg/ml (interquartile range [IQR] 1447-2254 pg/ml). SuPAR levels were positively and independently correlated with age, eGFR, UACR, and parathyroid hormone levels. There were 573 deaths, including 190 CV deaths and 683 MACE events at a follow-up time of 6.5 years. In multivariable analyses, suPAR levels (log2) were associated with all-cause death (hazard ratio [HR] 1.36, 95% confidence interval [CI] 1.21-1.53), CV death (HR 1.27, 95% CI 1.03-1.57), and MACE (HR 1.13, 95% CI 1.00-1.28), and were not found to differ according to diabetes mellitus status, baseline eGFR, UACR, or parathyroid hormone levels. In mediation analysis, suPAR's direct effect on all-cause death, CV death, and MACE accounted for 77%, 67%, and 60% of the total effect, respectively; whereas the effect mediated through eGFR accounted for 23%, 34%, and 40%, respectively. Conclusion: In a large cohort of individuals with chronic kidney disease (CKD), suPAR levels were associated with mortality and CV outcomes independently of indices of kidney function, consistent with its independent role in the pathogenesis of atherosclerosis.

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.

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.

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.

Clinical and biochemical footprints of inherited metabolic diseases. XIV. Metabolic kidney diseases.

Kidney disease is a global health burden with high morbidity and mortality. Causes of kidney disease are numerous, extending from common disease groups like diabetes and arterial hypertension to rare conditions including inherited metabolic diseases (IMDs). Given its unique anatomy and function, the kidney is a target organ in about 10% of known IMDs, emphasizing the relevant contribution of IMDs to kidney disease. The pattern of injury affects all segments of the nephron including glomerular disease, proximal and distal tubular damage, kidney cyst formation, built-up of nephrocalcinosis and stones as well as severe malformations. We revised and updated the list of known metabolic etiologies associated with kidney involvement and found 190 relevant IMDs. This represents the 14th of a series of educational articles providing a comprehensive and revised list of metabolic differential diagnoses according to system involvement.

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.

Association of osteopontin with kidney function and kidney failure in chronic kidney disease patients: the GCKD study.

BACKGROUND: Osteopontin (OPN), synthesized in the thick ascending limb of Henle's loop and in the distal tubule, is involved in the pathogenesis of kidney fibrosis, a hallmark of kidney failure (KF). In a cohort of chronic kidney disease (CKD) patients, we evaluated OPN's association with kidney markers and KF. METHODS: OPN was measured from baseline serum samples of German Chronic Kidney Disease study participants. Cross-sectional regression models for estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR) as well as Cox regression models for all-cause mortality and KF were evaluated to estimate the OPN effect. Additionally, the predictive ability of OPN and time-dependent population-attributable fraction were evaluated. RESULTS: Over a median follow-up of 6.5 years, 471 KF events and 629 deaths occurred among 4950 CKD patients. One-unit higher log(OPN) was associated with 5.5 mL/min/1.73 m2 lower eGFR [95% confidence interval (95% CI) -6.4 to -4.6] and 1% change in OPN with 0.7% higher UACR (estimated effect 0.7, 95% CI 0.6-0.8). Moreover, higher OPN levels were associated with a higher risk of KF [hazard ratio (HR) 1.4, 95% CI 1.2-1.7] and all-cause mortality (HR 1.5, 95% CI 1.3-1.8). After 6 years, 31% of the KF events could be attributed to higher OPN levels (95% CI 3%-56%). CONCLUSIONS: In this study, higher OPN levels were associated with kidney function markers worsening and a higher risk for adverse outcomes. A larger proportion of KF could be attributed to higher OPN levels, warranting further research on OPN with regards to its role in CKD progression and possible treatment options.

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.

Genetics of osteopontin in patients with chronic kidney disease: The German Chronic Kidney Disease study.

Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]≥1%) and aggregated variant testing (AVT, MAF<1%) of ELISA-quantified serum OPN, adjusted for age, sex, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) was conducted. In the project, GCKD participants had a mean age of 60 years (SD 12), median eGFR of 46 mL/min/1.73m2 (p25: 37, p75: 57) and median UACR of 50 mg/g (p25: 9, p75: 383). GWAS revealed 3 loci (p<5.0E-08), two of which replicated in the population-based Young Finns Study (YFS) cohort (p<1.67E-03): rs10011284, upstream of SPP1 encoding the OPN protein and related to OPN production, and rs4253311, mapping into KLKB1 encoding prekallikrein (PK), which is processed to kallikrein (KAL) implicated through the kinin-kallikrein system (KKS) in blood pressure control, inflammation, blood coagulation, cancer, and cardiovascular disease. The SPP1 gene was also identified by AVT (p = 2.5E-8), comprising 7 splice-site and missense variants. Among others, downstream analyses revealed colocalization of the OPN association signal at SPP1 with expression in pancreas tissue, and at KLKB1 with various plasma proteins in trans, and with phenotypes (bone disorder, deep venous thrombosis) in human tissue. In summary, this GWAS of OPN levels revealed two replicated associations. The KLKB1 locus connects the function of OPN with PK, suggestive of possible further post-translation processing of OPN. Further studies are needed to elucidate the complex role of OPN within human (patho)physiology.

Genome-wide studies reveal factors associated with circulating uromodulin and its relationships to complex diseases.

Uromodulin (UMOD) is a major risk gene for monogenic and complex forms of kidney disease. The encoded kidney-specific protein uromodulin is highly abundant in urine and related to chronic kidney disease, hypertension, and pathogen defense. To gain insights into potential systemic roles, we performed genome-wide screens of circulating uromodulin using complementary antibody-based and aptamer-based assays. We detected 3 and 10 distinct significant loci, respectively. Integration of antibody-based results at the UMOD locus with functional genomics data (RNA-Seq, ATAC-Seq, Hi-C) of primary human kidney tissue highlighted an upstream variant with differential accessibility and transcription in uromodulin-synthesizing kidney cells as underlying the observed cis effect. Shared association patterns with complex traits, including chronic kidney disease and blood pressure, placed the PRKAG2 locus in the same pathway as UMOD. Experimental validation of the third antibody-based locus, B4GALNT2, showed that the p.Cys466Arg variant of the encoded N-acetylgalactosaminyltransferase had a loss-of-function effect leading to higher serum uromodulin levels. Aptamer-based results pointed to enzymes writing glycan marks present on uromodulin and to their receptors in the circulation, suggesting that this assay permits investigating uromodulin's complex glycosylation rather than its quantitative levels. Overall, our study provides insights into circulating uromodulin and its emerging functions.

PCSK9 and Cardiovascular Disease in Individuals with Moderately Decreased Kidney Function.

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 m2 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; P<0.001) higher in a model with extended adjustment for major confounders. This association was stronger in nonstatin than statin users (P value for interaction =0.009). During follow-up, 474 individuals experienced a major adverse cardiovascular disease event, and participants in PCSK9 quartiles 2-4 had a 32%-47% higher risk compared with those in quartile 1 (P<0.05). Subgroup analysis revealed that this association was restricted to those participants who already had cardiovascular disease at baseline (all hazard ratios >1.75; 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.

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.

A Predictive Model for Progression of CKD to Kidney Failure Based on Routine Laboratory Tests.

RATIONALE & OBJECTIVE: Stratification of chronic kidney disease (CKD) patients at risk for progressing to kidney failure requiring kidney replacement therapy (KFRT) is important for clinical decision-making and trial enrollment. STUDY DESIGN: Four independent prospective observational cohort studies. SETTING & PARTICIPANTS: The development cohort comprised 4,915 CKD patients, and 3 independent validation cohorts comprised a total of 3,063. Patients were observed for approximately 5 years. EXPOSURE: 22 demographic, anthropometric, and laboratory variables commonly assessed in CKD patients. OUTCOME: Progression to KFRT. 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 KFRT. Model discrimination and calibration were assessed and compared against the 4-variable Tangri (T4) risk equation both in 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 risk score (Z6) included serum creatinine, albumin, cystatin C, and urea, as well as hemoglobin and the urinary albumin-creatinine ratio. In the the resampling approach, Z6 achieved a median C statistic of 0.909 (95% CI, 0.868-0.937) at 2 years after the baseline visit, whereas the T4 achieved a median C statistic of 0.855 (95% CI, 0.799-0.915). In the 3 independent validation cohorts, the Z6C statistics were 0.894, 0.921, and 0.891, whereas the T4C statistics 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 6 routinely available laboratory tests facilitates identification of patients with CKD who are at high risk of progressing to KFRT.