Stephan J. L. Bakker

Tubular kidney injury molecule-1 (KIM-1) in human renal disease.

KIM‐1, a transmembrane tubular protein with unknown function, is undetectable in normal kidneys, but is markedly induced in experimental renal injury. The KIM‐1 ectodomain is cleaved, detectable in urine, and reflects renal damage. KIM‐1 expression in human renal biopsies and its correlation with urinary KIM‐1 (uKIM‐1) is unknown. In biopsies from various renal diseases (n = 102) and controls (n = 7), the fraction of KIM‐1 positive tubules and different renal damage parameters were scored. Double labelling was performed for KIM‐1 with macrophages (MØ), α‐smooth muscle actin (α‐SMA), proximal (aquaporin‐1) and distal (E‐cadherin) tubular markers and a dedifferentiation marker (vimentin). uKIM‐1 at the time of biopsy (n = 53) was measured by ELISA. Renal KIM‐1 was significantly increased in all diseases versus controls (p < 0.05), except minimal change. KIM‐1 was primarily expressed at the luminal side of dedifferentiated proximal tubules, in areas with fibrosis (α‐SMA) and inflammation (MØ). Independent of the disease, renal KIM‐1 correlated positively with renal damage, negatively with renal function, but not with proteinuria. uKIM‐1 was increased in renal patients versus controls (p < 0.001), including minimal change, and correlated positively with tissue KIM‐1 and MØ, negatively with renal function, but not with proteinuria. In conclusion, KIM‐1 is upregulated in renal disease and is associated with renal fibrosis and inflammation. uKIM‐1 is also associated with inflammation and renal function, and reflects tissue KIM‐1, indicating that it can be used as a non‐invasive biomarker in renal disease. Copyright

Incidence and epidemiology of new onset heart failure with preserved vs. reduced ejection fraction in a community-based cohort: 11-year follow-up of PREVEND

AIMS Differences in clinical characteristics and outcome of patients with established heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) are well established. Data on epidemiology and prediction of new onset HFpEF, compared with HFrEF, have not been described. METHODS AND RESULTS In 8592 subjects of the Prevention of Renal and Vascular End-stage Disease (PREVEND), a community-based, middle-aged cohort study, we performed cause-specific hazard analyses to study the predictive value of risk factors and established cardiovascular biomarkers on new onset HFrEF vs. HFpEF (left ventricular ejection fraction ≤ 40 and ≥ 50%, respectively). A P-value for competing risk (Pcr) <0.10 between HFrEF and HFpEF was considered statistically significant. All potential new onset heart failure cases were reviewed and adjudicated to HFrEF or HFpEF by an independent committee. During a median follow-up of 11.5 years, 374 (4.4%) subjects were diagnosed with heart failure, of which 125 (34%) with HFpEF and 241 (66%) with HFrEF. The average time to diagnosis of new onset HFrEF was 6.6 ± 3.6 years; it was 8.3 ± 3.3 years for HFpEF (P < 0.001). Male gender was associated with new onset HFrEF, whereas female gender with new onset HFpEF (Pcr < 0.001). Higher age and increased N-terminal pro-B-type natriuretic peptide (NT-proBNP) increased the risk for both HFpEF and HFrEF, although for age this was stronger for HFpEF (Pcr = 0.018), whereas NT-proBNP was stronger associated with risk for HFrEF (Pcr = 0.083). Current smokers, increased highly sensitive troponin T, and previous myocardial infarction conferred a significantly increased risk for HFrEF, but not for HFpEF (Pcr = 0.093, 0.091, and 0.061, respectively). Conversely, a history of atrial fibrillation, increased urinary albumin excretion (UAE), and cystatin C were significantly more associated with the risk for HFpEF, but not for HFrEF (Pcr < 0.001, 0.061, and 0.033, respectively). The presence of obesity at baseline was associated with comparable prognostic information for both HFpEF and HFrEF. CONCLUSION Higher age, UAE, cystatin C, and history of atrial fibrillation are strong risk factors for new onset HFpEF. This underscores differential pathophysiological mechanisms for both subtypes of heart failure.

Metabolic syndrome is associated with impaired long-term renal allograft function; not all component criteria contribute equally.

Chronic renal transplant dysfunction (CRTD) remains a leading cause of renal allograft loss. Evidence suggests that immunological and ischemic insults are mainly associated with CRTD occurring within the first year after transplantation, whereas nonimmunological insults are predominantly associated with CRTD beyond the first year. Several cardiovascular risk factors, such as obesity, dyslipidemia, hypertension, and diabetes mellitus have been identified as important nonimmunological risk factors for CRTD. These risk factors constitute the metabolic syndrome (MS). As renal allograft function is a surrogate marker of renal allograft loss, we investigated the association of MS with impairment of renal allograft function beyond the first year after transplantation in a cross‐sectional study of 606 renal transplant outpatients. Metabolic syndrome was defined using the definition of the National Cholesterol Education Program. Renal allograft function was assessed as the 24‐h urinary creatinine clearance. A total of 383 out of 606 patients (63%) suffered from MS at a median time of 6 years (2.6–11.4) post‐transplant. Presence of MS was associated with impaired renal allograft function beyond 1 year post‐transplant [−4.1 mL/min, 95%CI (−7.1, −1.1)]. The impact of MS did not change appreciably after adjustment for established risk factors for CRTD [−3.1 mL/min, 95%CI (−6.0, −0.2)]. However, not all component criteria of MS contributed equally. Only systolic blood pressure and hypertriglyceridemia were independently associated with impaired renal allograft function beyond 1 year post‐transplant in multivariate analyses.

Advanced glycation end-products (AGEs) and heart failure: pathophysiology and clinical implications.

Advanced glycation end‐products (AGEs) are molecules formed during a non‐enzymatic reaction between proteins and sugar residues, called the Maillard reaction. AGEs accumulate in the human body with age, and accumulation is accelerated in the presence of diabetes mellitus. In patients with diabetes, AGE accumulation is associated with the development of cardiac dysfunction. Enhanced AGE accumulation is not restricted to patients with diabetes, but can also occur in renal failure, enhanced states of oxidative stress, and by an increased intake of AGEs. Several lines of evidence suggest that AGEs are related to the development and progression of heart failure in non‐diabetic patients as well. Preliminary small intervention studies with AGE cross‐link breakers in heart failure patients have shown promising results. In this review, the role of AGEs in the development of heart failure and the role of AGE intervention as a possible treatment for heart failure are discussed.

Macroalbuminuria Is a Better Risk Marker than Low Estimated GFR to Identify Individuals at Risk for Accelerated GFR Loss in Population Screening

Macroalbuminuria, erythrocyturia, and impaired renal function are strong predictors of poor renal outcome in patients with known renal disease. However, the yield of mass screening for these variables to identify individuals who are at risk for GFR loss is yet unknown in a Western population. With the use of data from the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study, a prospective, population-based cohort study, the cardiovascular and renal prognosis was investigated in patients with classical renal risk markers: Macroalbuminuria (> or =300 mg albumin/24 h urine), erythrocyturia (> or =250 erythrocytes/L, without leukocyturia), and impaired renal function (both 24-h creatinine clearance and Modification of Diet in Renal Disease clearance below the fifth percentile of age- and gender-matched control subjects). The 8592 patients who were included in this study were followed for a 4-yr period. We identified 134 patients with macroalbuminuria, 128 with erythrocyturia, and 103 with impaired renal function. There was only a little overlap among the three groups. The prevalence of macroalbuminuria, erythrocyturia, and impaired renal function was calculated to be in the general population 0.6, 1.3, and 0.9%, respectively. In all three groups, fewer than 30% of patients were known to have this laboratory abnormality before screening. The incidence of cardiovascular disease was high in the macroalbuminuria group (e.g., the age- and gender-adjusted hazard ratio for mortality as a result of cardiovascular disease is 2.6 [1.1 to 6.0]) and for the impaired renal function group (3.4 [1.5 to 8.0]). After a mean follow-up of 4.2 yr, the macroalbuminuria group showed a -7.2 ml/min per 1.73 m2 estimated GFR (eGFR) loss, compared with -2.3 ml/min per 1.73 m2 in the control group (difference P < 0.001), whereas the rate of eGFR loss in the impaired renal function group (-0.2 ml/min per 1.73 m2; P = 0.18) and the erythrocyturia group (-2.6 ml/min per 1.73 m2) was not different from the control group. Macroalbuminuria and impaired renal function both predict a worse prognosis with respect to cardiovascular morbidity and mortality. However, macroalbuminuria is a better risk marker than low eGFR or erythrocyturia to identify in population screening of individuals who are at risk for accelerated GFR loss.

First Morning Voids Are More Reliable Than Spot Urine Samples to Assess Microalbuminuria

Measurement of urinary albumin excretion (UAE) in a 24-h collection is the gold standard method to determine the presence of microalbuminuria. We sought to compare more practical alternatives--measurement of urinary albumin concentration (UAC) or albumin:creatinine ratio (ACR)--in a first morning void or in a spot urine sample with this gold standard. We asked 241 participants of a prospective cohort study to make three 24-h urine collections, a first morning void, and a spot urine sample. Regression analysis showed that the ACR in a first morning void best agreed with 24-h UAE. The prevalence of microalbuminuria determined by data from a first morning void (7.5%, whether by UAC or ACR) nearly equaled the prevalence of microalbuminuria determined by 24-h UAE (10.0%), whereas the prevalence was higher when determined by spot urine samples (25.4% for UAC and 22.4% for ACR; both P < 0.001 versus 24-h UAE). The intraindividual coefficients of variation of the ACR in a first morning void and 24-h UAE were similar (19%). Intraindividual coefficients of variations of all other measurements of albuminuria were significantly greater. In conclusion, measurement of albuminuria in a first morning void, preferably as the ACR, is more reliable than a spot urine sample to diagnose and monitor microalbuminuria.

Cardiovascular and renal outcome in subjects with K/DOQI stage 1–3 chronic kidney disease: the importance of urinary albumin excretion

BACKGROUND The Kidney Disease Outcomes Quality Initiative guidelines aim to define chronic kidney disease (CKD) and classify its stages. Stage 3 CKD generally receives more attention than stage 1 or 2, because the more impaired glomerular filtration rate (GFR) in stage 3 suggests a higher cardiovascular and renal risk. In this study we evaluated cardiovascular and renal outcome in subjects with stage 1 and 2 CKD. For comparison, we also studied these outcomes in stage 3 CKD. METHODS We used data of 8495 subjects of the PREVEND study, a prospective community-based cohort study, with data on urinary albumin excretion (UAE) and serum creatinine available. As measure of cardiovascular outcome, combined cardiovascular morbidity and mortality was used. As renal outcome, mean annual change of estimated GFR (eGFR) was used. RESULTS 6905 subjects had no CKD; 243, 856 and 491 subjects had stage 1, 2 and 3 CKD, respectively. During a median follow-up of 7.5 years 565 cardiovascular events occurred. Incidence rates of cardiovascular events were higher (P < 0.001 for all groups) in subjects with stage 1-3 CKD (17.2, 22.2 and 20.9 events/1000 person-years, respectively) than in subjects without CKD (7.0 events/1000 person-years). Using subjects without CKD as reference, age- and sex-adjusted hazard ratios [HR (95% CI)] were 2.2 (1.5-3.3), 1.6 (1.3-2.0) and 1.3 (1.0-1.7), respectively. Compared to subjects without CKD but similar baseline eGFR, subjects with stage 1 or 2 CKD showed a larger decline in eGFR (-1.1 versus -1.5 and -0.2 versus -0.6 ml/min/1.73 m(2)/year, respectively, both P < 0.01). When subjects with stage 3 CKD were stratified according to the absence or presence of a UAE >30 mg/24 h, age- and sex-adjusted HRs for CVD were 1.0 (0.7-1.4) and 1.6 (1.1-2.3) and the change in eGFR was 0.2 versus -0.3 ml/min/1.73 m(2)/year, respectively. CONCLUSION Subjects with stage 1 or 2 CKD have an increased risk for adverse cardiovascular and renal outcome and should receive equal attention as subjects with stage 3 CKD. Subdividing stage 3 CKD according to the presence or absence of a UAE >30 mg/24 h improves risk stratification within this stage.

Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study

Objective To identify existing prediction models for the risk of development of type 2 diabetes and to externally validate them in a large independent cohort. Data sources Systematic search of English, German, and Dutch literature in PubMed until February 2011 to identify prediction models for diabetes. Design Performance of the models was assessed in terms of discrimination (C statistic) and calibration (calibration plots and Hosmer-Lemeshow test).The validation study was a prospective cohort study, with a case cohort study in a random subcohort. Setting Models were applied to the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition cohort study (EPIC-NL). Participants 38 379 people aged 20-70 with no diabetes at baseline, 2506 of whom made up the random subcohort. Outcome measure Incident type 2 diabetes. Results The review identified 16 studies containing 25 prediction models. We considered 12 models as basic because they were based on variables that can be assessed non-invasively and 13 models as extended because they additionally included conventional biomarkers such as glucose concentration. During a median follow-up of 10.2 years there were 924 cases in the full EPIC-NL cohort and 79 in the random subcohort. The C statistic for the basic models ranged from 0.74 (95% confidence interval 0.73 to 0.75) to 0.84 (0.82 to 0.85) for risk at 7.5 years. For prediction models including biomarkers the C statistic ranged from 0.81 (0.80 to 0.83) to 0.93 (0.92 to 0.94). Most prediction models overestimated the observed risk of diabetes, particularly at higher observed risks. After adjustment for differences in incidence of diabetes, calibration improved considerably. Conclusions Most basic prediction models can identify people at high risk of developing diabetes in a time frame of five to 10 years. Models including biomarkers classified cases slightly better than basic ones. Most models overestimated the actual risk of diabetes. Existing prediction models therefore perform well to identify those at high risk, but cannot sufficiently quantify actual risk of future diabetes.

High urinary excretion of kidney injury molecule-1 is an independent predictor of graft loss in renal transplant recipients

Background. Chronic transplant dysfunction is characterized by renal function decline and proteinuria. Kidney injury molecule (KIM)-1, a transmembrane tubular protein with unknown function, is undetectable in normal kidneys, but markedly induced after injury. Urinary KIM-1 excretion has been quantified as biomarker of renal damage. We prospectively studied whether urinary KIM-1 predicts graft loss, independent of renal function and proteinuria. Methods. Renal transplant recipients (n=145) visiting our outpatient clinic between August 2001 and July 2003 collected 24-hour urine samples for assessment of baseline urinary KIM-1 excretion (microsphere-based Luminex technology), and were followed for graft loss. Results. Recipients participated at a median (interquartile range) of 6.0 (2.5–12.0) years posttransplant in baseline measurements. Follow-up beyond baseline was 4.0 (3.2–4.5) years. Urinary KIM-1 excretion was 0.72 (0.42–1.37) ng per 24 hours. Occurrence of graft loss increased over tertiles of KIM-1 excretion: 3 (6.3%), 11 (22.4%), and 17 cases (35.4%; P=0.001), respectively. High KIM-1 excretion was associated with proteinuria, low creatinine clearance, and high donor age (all P<0.01). In multivariate Cox regression analyses, prediction of graft loss by KIM-1 appeared independent of creatinine clearance, proteinuria, and donor age. Hazard ratios (95% CI) for the second and third tertile of KIM-1 excretion were 3.6 (0.9–13.5) and 5.1 (1.5–17.8) in the final model. Conclusions. Urinary excretion of KIM-1 is an independent predictor of long-term graft loss and therefore a promising new biomarker in early prediction of graft loss.

Cohort Profile: LifeLines, a three-generation cohort study and biobank

The LifeLines Cohort Study is a large population-based cohort study and biobank that was established as a resource for research on complex interactions between environmental, phenotypic and genomic factors in the development of chronic diseases and healthy ageing. Between 2006 and 2013, inhabitants of the northern part of The Netherlands and their families were invited to participate, thereby contributing to a three-generation design. Participants visited one of the LifeLines research sites for a physical examination, including lung function, ECG and cognition tests, and completed extensive questionnaires. Baseline data were collected for 167 729 participants, aged from 6 months to 93 years. Follow-up visits are scheduled every 5 years, and in between participants receive follow-up questionnaires. Linkage is being established with medical registries and environmental data. LifeLines contains information on biochemistry, medical history, psychosocial characteristics, lifestyle and more. Genomic data are available including genome-wide genetic data of 15 638 participants. Fasting blood and 24-h urine samples are processed on the day of collection and stored at -80 °C in a fully automated storage facility. The aim of LifeLines is to be a resource for the national and international scientific community. Requests for data and biomaterials can be submitted to the LifeLines Research Office [LLscience@umcg.nl].