Sara-Joan Pinto-Sietsma

A central body fat distribution is related to renal function impairment, even in lean subjects

BACKGROUND Overweight and obesity are believed to be associated with renal damage. Whether this depends on fat distribution is not known. We hypothesize that in addition to overweight, fat distribution may be associated with renal function abnormalities. METHODS We studied the relation between body weight and fat distribution and microalbuminuria and elevated or diminished filtration in 7,676 subjects without diabetes. Microalbuminuria is defined as urinary albumin excretion (UAE) of 30 to 300 mg/24 h. Elevated and diminished filtration are defined as filtration plus or minus 2 SDs of a nondiabetic lean group with a peripheral fat distribution and UAE of 0 to 15 mg/24 h, corrected for age and sex. The total population was divided into six groups according to body weight (overweight is defined as body mass index [BMI] > 25 and < or = 30 kg/m2; obesity, as BMI > 30 kg/m2) and fat distribution. RESULTS In logistic regression analysis, obese subjects with central fat distribution had a greater risk for microalbuminuria (relative risk, 1.7; 95% confidence interval, 1.19 to 2.35). Obese subjects with either peripheral or central fat distribution had a greater risk for elevated filtration (relative risk, 3.2; 95% confidence interval, 1.19 to 8.47; relative risk, 2.6; 95% confidence interval, 1.59 to 4.28, respectively). Furthermore, subjects with central fat distribution, either lean, overweight, or obese, had a greater risk for diminished filtration (relative risk, 1.9; 95% confidence interval, 1.19 to 3.12; relative risk, 2.0; 95% confidence interval, 1.19 to 3.19; and relative risk, 2.7; 95% confidence interval, 1.46 to 4.85, respectively). Finally, by dividing waist-hip ratio (WHR) into quartiles, greater WHR was associated with a greater risk for diminished filtration, even when corrected for BMI. CONCLUSION Not only overweight and obese subjects, but also lean subjects with central fat distribution are at risk for diminished filtration. Therefore, a central pattern of fat distribution, not overweight or obesity by itself, seems to be important for renal impairment.

Smoking Is Related to Albuminuria and Abnormal Renal Function in Nondiabetic Persons

In recent years, it has become apparent that cigarette smoking is associated with excessive morbidity and mortality in various diseases (1), most prominently cardiovascular and lung diseases (2). Recently, however, the adverse effects of smoking on renal function have gained more attention (3), mainly through investigation in diabetic patients. In these patients, smoking is related to such variables of renal dysfunction as albuminuria (4-8) and hyperfiltration (9), which may accelerate the progression to loss of renal function (10). The adverse effects of smoking on renal function have not been investigated extensively in nondiabetic persons. Several studies show a relation between smoking and albuminuria (11, 12), but there is little information about the effects of smoking on glomerular filtration rate (GFR). The two studies that have addressed this question (13, 14) were small and do not offer information on the effect of smoking at a population level. We hypothesized that in nondiabetic persons, smoking is related to abnormal renal function manifested by albuminuria and elevated or decreased GFR. To test this hypothesis, we studied the cross-sectional relations among smoking, albuminuria, and GFR in a large cohort created to study the causes and consequences of microalbuminuria in nondiabetic persons. Methods Study Sample Our study is part of the ongoing PREVEND (Prevention of REnal and Vascular ENd stage Disease) Study, which takes place in Groningen, the Netherlands. All city inhabitants 28 to 75 years of age (n =85 421) were asked to send in a morning urine sample and to fill out a short questionnaire on demographic characteristics and cardiovascular history. Of these 85 421 persons, 40 856 (47.8%) responded. From this cohort, we selected persons with a urinary albumin concentration of at least 10 mg/L (n =7768) and a randomly selected control group with a urinary albumin concentration less than 10 mg/L (n =3395). Details of this protocol have been described elsewhere (15). Of these 11 163 persons, 8592 completed two invited visits to the outpatient clinic; participants who used insulin or were pregnant were excluded. The study was approved by the medical ethics committee of the Groningen University Hospital and was conducted in accordance with the guidelines of the Declaration of Helsinki. All participants attending the outpatient clinic gave written informed consent. Study Design The screening program in the outpatient clinic consisted of two visits. At the first visit, participants completed a self-administered questionnaire on demographic characteristics, cardiovascular and renal history, drug use, alcohol consumption, and smoking. After removal of shoes and heavy clothing, weight was measured to the nearest 0.5 kg with a seca balance scale (seca Vogel & Halke GmbH & Co., Hamburg, Germany). Height was measured to the nearest 0.5 cm. Minimum waist circumference was measured on bare skin at the natural indentation between the 10th rib and the iliac crest (16). At each visit, blood pressure was measured in the supine position every minute for 10 and 8 minutes, respectively, with an automatic DINAMAP XL Model 9300 series monitor (Critikon, Tampa, Florida). Participants received oral and written instructions on how to collect 24-hour urine samples on 2 consecutive days in the last week before the second clinic visit. They were asked to postpone collection in case of fever, urinary tract infection, or menstruation and to refrain from heavy exercise as much as possible during the 24 hours that collection was being performed. Participants were asked to store the urine cold (at 4 C) for no more than 4 days before the second visit. Measurements of urinary volume and albumin and creatinine concentrations were performed in each collection. At the second visit, blood was drawn after an overnight fast for determination of plasma glucose level, serum creatinine concentration, and cholesterol level. Calculations Systolic and diastolic blood pressure were calculated as the mean of the last two measurements at the two visits. Body mass index was calculated as the ratio between weight (kg) and height squared (m2). Body surface area was calculated according to the method of DuBois and DuBois (17). Glomerular filtration rate was defined as the mean of the two creatinine clearance values based on 24-hour urinary creatinine excretions divided by plasma creatinine concentration and corrected for body surface area (mL s 1 m 2). Albumin excretion is given as the mean of the two values for 24-hour urine excretion. Laboratory Methods Urinary albumin concentration was determined by using nephelometry with a threshold of 0.23 g/L and intra-assay and interassay coefficients of variation of 4.3% or less and 4.4% or less, respectively (Dade Behring Diagnostic, Marburg, Germany). Plasma glucose level, serum cholesterol level, and serum and urinary creatinine concentrations were determined by using Kodak Ektachem dry chemistry (Eastman Kodak, Rochester, New York). Urinary leukocytes and erythrocytes were measured by using strip testing (Nephur Test+ Leuco, Boehringer Mannheim, Mannheim, Germany). Data Handling and Definitions We excluded 433 persons because of erythrocyturia or leukocyturia (erythrocyte count>50 cells/L or leukocyte count>75 cells/L, or leukocyte count of 75 cells/L and erythrocyte count>5 cells/L). In addition, 239 persons were excluded because of diabetes, which was defined as a fasting plasma glucose level of at least 7.8 mmol/L (140.5 mg/dL), a nonfasting plasma glucose level of at least 11.1 mmol/L (200 mg/dL), or the use of oral antidiabetic drugs. Another 147 persons were excluded because of missing data on albuminuria, erythrocyturia, leukocyturia, smoking, or plasma glucose levels, and 297 persons were excluded because they had stopped smoking less than 1 year previously and therefore did not match the definition of current or former smokers. A total of 7476 persons were eligible for analysis. Most participants were white, 68 (1%) were black, and 155 (2%) were Asian. Participants were divided into three categories: nonsmokers, current smokers, and former smokers (those who had stopped smoking more than 1 year before). Current smokers were divided into two groups: those who smoked 20 or fewer cigarettes/d and those who smoked more than 20 cigarettes/d. The classic definition was used for microalbuminuria: that is, an albumin excretion of 30 to 300 mg/24 h. Because it has been suggested that the cardiovascular and renal risk associated with albuminuria may begin at an even lower cutoff point than is now considered pathologic (18, 19), we also defined a group with high normal albumin excretion (15 to 30 mg/24 h). An elevated or decreased GFR was defined as a creatinine clearance that exceeded or was less than two times the standard deviation of the mean value in a group of nondiabetic, nonsmoking persons who had an albumin excretion of 0 to 15 mg/24 h (15, 20). The mean creatinine clearance was obtained by using linear regression analysis and was adjusted for age and sex. Obesity was defined as a body mass index greater than 30 kg/m2. Hypertension was defined as systolic blood pressure of at least 160 mm Hg, diastolic blood pressure of at least 95 mm Hg, or use of antihypertensive medication. Hypercholesterolemia was defined as a total serum cholesterol level of at least 6.5 mmol/L (251.0 mg/dL), a total serum cholesterol level of at least 5.0 mmol/L (193.1 mg/dL) in persons with previous myocardial infarction, or use of lipid-lowering medications. Statistical Analysis All calculations were performed by using SPSS software, version 9.0 (SPSS, Inc., Chicago, Illinois). Continuous data are reported as the mean SD. Skewed distributions are reported as the median value with 25th and 75th percentiles. All P values are two-tailed, and a P value less than 0.05 was considered statistically significant. Differences among nonsmokers, current smokers, and former smokers were assessed by using chi-square analysis or analysis of variance. To investigate the relation between smoking and high normal albuminuria, microalbuminuria, an elevated GFR, or a decreased GFR, we used logistic regression analysis. Stepwise logistic regression analysis was used to test the independent relation among the three smoking groups and microalbuminuria, high normal albuminuria, elevated GFR, and decreased GFR. Odds ratios were estimated after adjustment for possible confounding factors, such as age, sex, body mass index, systolic and diastolic blood pressure, use of antihypertensive medication, serum cholesterol levels, use of lipid-lowering medications, plasma glucose levels, and consumption of more than three units of alcohol per day. The calculated odds ratios and 95% CIs are expressed as an approximation of relative risk. Role of the Funding Source The funding source had no role in the collection, interpretation, or analysis of the data or in the decision to submit the report for publication. Results Characteristics of the study sample are shown in Table 1. Current smokers ( 20 and>20 cigarettes/d) and former smokers had increased median albumin excretion and were more likely to have high normal albuminuria and microalbuminuria than nonsmokers. Serum creatinine concentration and creatinine clearance did not differ significantly among the two smoking groups and the nonsmoking group. However, former smokers had a significantly higher serum creatinine concentration and a significantly lower creatinine clearance than the other three groups. Of interest, significantly more current smokers than nonsmokers had elevated or decreased GFR. The percentage of former smokers who had an elevated GFR was lower than that of current smokers and greater than that of nonsmokers, whereas the percentage of former smokers who had a decreased GFR was significantly lower than that of current smokers and was similar to that of nonsmokers. Incidence of elevated or d

Obesity and target organ damage : the kidney

Obesity is a risk marker for progressive renal function loss in patients with known renal disease. There is, however, increasing evidence that obesity may also damage the kidney in otherwise healthy subjects. There appears to be an intriguing parallel between the renal effects of obesity and those of diabetes. First, an increased renal blood flow and glomerular filtration rate has been described in obesity and, second, microalbuminuria is found to be related to obesity. These two events are known to predict future loss of renal function in diabetes. The mechanism responsible for the renal damage in obesity has not been established but there is evidence suggesting that this might be related to both hormonal changes as well as low-grade inflammation.

Reduction in left ventricular messenger RNA for transforming growth factor beta(1) attenuates left ventricular fibrosis and improves survival without lowering blood pressure in the hypertensive TGR(mRen2)27 rat

Angiotensin II recruits transforming growth factor &bgr;1 (TGF&bgr;1) and is related to left ventricular fibrosis. However, it is unclear whether chronic in vivo reduction in left ventricular TGF&bgr;1 expression blunts fibrosis and improves outcome in angiotensin II–dependent hypertension. Four-week-old male hypertensive TGR(mRen2)27 (Ren2) rats received either normal food, low-dose losartan (0.5 mg · kg−1 · d−1), or tranilast (a nonspecific TGF&bgr; inhibitor; 400 mg · kg−1 · d−1) (n=10 for each group) for 12 weeks and were compared with Sprague-Dawley control rats. The effect of tranilast on survival was evaluated in 34 additional untreated homozygous Ren2 rats. Tranilast or low-dose losartan did not lower blood pressure. However, the increase in left ventricular weight (Ren2 versus SD 3.1±0.16 versus 2.1± 0.06 mg/g body wt;P <0.05) was significantly (P <0.05) blunted by both tranilast (2.7±0.05) and losartan (2.7±0.07). Both drugs prevented the increase in left ventricular TGF&bgr;1 mRNA and fibronectin mRNA and blunted the increase in hydroxyproline content and the increase in perivascular fibrosis. The perivascular fibrosis score correlated significantly with the level of expression of TGF&bgr;1 (r =0.62;P =0.019). In situ hybridization demonstrated increases in TGF&bgr;1 mRNA, predominantly in perivascular and nonmyocyte areas. Both drugs did not prevent the decrease in systolic or diastolic dP/dt, but tranilast significantly improved the survival of untreated Ren2 rats (P =0.029). In conclusion, TGF&bgr;1 mRNA expression is increased predominantly in nonmyocyte regions in the hypertrophied left ventricle in this angiotensin II–dependent model of hypertension. This increase is probably due to high angiotensin II levels rather than to hypertension. This is the first study to suggest that chronic inhibition of TGF&bgr;1 expression attenuates left ventricular hypertrophy and fibrosis, even without lowering blood pressure.

Normalization panels for the reliable quantification of circulating microRNAs by RT-qPCR

Circulating microRNAs (miRNAs) have been reported as biomarkers for disease diagnosis. RT‐qPCR is most commonly used to detect miRNAs; however, no consensus on the most appropriate method for data normalization exists. Via a standardized selection method, we aimed to determine separate miRNA normalization panels for RT‐qPCR measurements on whole blood, platelets, and serum. Candidate miRNAs were selected from studies describing circulating miRNA microarray data in the Gene Expression Omnibus or ArrayExpress. miRNA expression data of healthy controls were retrieved from each study. For each sample type, we selected those miRNAs that were least variable and sufficiently highly expressed in multiple microarray experiments, performed on at least 2 different platforms. Stability of the candidate miRNAs was assessed using NormFinder and geNorm algorithms in a RT‐qPCR cohort of 10 patients with coronary artery disease and 10 healthy controls. We selected miRNA normalization panels for RT‐qPCR measurements on whole blood, platelets, and serum. As a validation, we assessed the precision of all 3 panels in 3 independent RT‐qPCR cohorts and compared this with normalization for miR‐16 or RNU6B. The proposed normalization panels for whole blood, platelets, and serum show better precision than normalization for miR‐16 or RNU6B.—Kok, M. G. M., Halliani, A., Moerland, P. D., Meijers, J. C. M., Creemers, E. E., Pinto‐Sietsma, S.‐J. Normalization panels for the reliable quantification of circulating microRNAs by RT‐qPCR. FASEB J. 29, 3853‐3862 (2015). www.fasebj.org

Role of the Endothelin-1 Gene Locus for Renal Impairment in the General Nondiabetic Population

A decreased GFR in the range of mild renal insufficiency and an increased urinary albumin excretion (UAE) rate in the range of microalbuminuria are important cardiovascular risk factors. Endothelin-1 (ET-1) has been suggested to be a major disease promoting factor in renal disease. The role of the ET-1 gene locus (EDN1) for renal function in the general nondiabetic population was evaluated. To explore the overall relevance of EDN1, two suitable single-nucleotide polymorphisms, EDN1 K198N and EDN1 T-1370G, were selected, and haplotype analysis was performed. Determined were genotypes in 7291 nondiabetic subjects from the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. Genetic analysis was related to UAE and GFR as continuous variables and to microalbuminuria and diminished filtration as dichotomous traits. In a logistic regression analysis, no significant higher risk for increased UAE, microalbuminuria, decreased GFR, or diminished filtration could be observed for either single-nucleotide polymorphism separately. Haplotype analysis revealed that individuals with the homozygous G-N haplotype (compound EDN1 -1370GG/198NN genotype) have a lower GFR than the remaining subjects (P < 0.05) and exhibit a significant higher risk for the presence of a diminished filtration (relative risk, 2.4; 95% confidence interval, 1.07 to 5.33; P < 0.05). Further analysis demonstrated no association between this haplotype and UAE or plasma ET-1 levels. Although a functional relevance of the EDN1 G-N haplotype itself remains unclear, the data demonstrate that genetic variation at the EDN1 locus has a significant effect on glomerular filtration but not on UAE in the general nondiabetic population.

Birth Weight and Creatinine Clearance in Young Adult Twins: Influence of Genetic, Prenatal, and Maternal Factors

Previous studies have shown that low birth weight (LBW) is a risk factor for renal impairment in adult life. The effects of LBW and renal function were studied by using twins, which allows distinguishing among fetoplacental, maternal, and genetic influences. Perinatal data were obtained at birth, and absolute creatinine clearance (not corrected for body surface area) was measured at a mean age of 25.6 yr in 653 individuals. Twins were considered both as individuals and as members of twin pairs. Statistical analyses were performed with and without adjusting for gestational age, zygosity, gender, age, body mass index, glucose level, BP, and smoking status. Creatinine clearance was 4 ml/min lower in twins with LBW (<2500 g) than in twins with a high birth weight (P < 0.04, adjusted). Intrapair birth weight difference correlated positively with the intrapair difference in creatinine clearance equally in monozygotic and dizygotic twins (r = 0.35, P < 0.0001; r = 0.43, P < 0.0001, respectively). This suggests that fetoplacental factors are related to renal function and that genetic factors are less important. There was no significant difference in creatinine clearance between twins who both had LBW as compared with twins who both had a high birth weight. This may suggest that maternal factors, which influence the relation between LBW and renal function, are less important. LBW is related to a lower creatinine clearance at adult age. This relationship is probably due to fetoplacental factors. Surprising, genetic and maternal factors seem less important.

Lamin A/C mutation is independently associated with an increased risk of arterial and venous thromboembolic complications

BACKGROUND Lamin A/C (LMNA) mutation carriers suffer from a variety of clinical phenotypes, including dilated cardiomyopathy (DCM). Although it has been suggested that carriers are at risk for thromboembolic complications, it is unknown whether this risk is higher than can be expected from the underlying cardiac abnormalities. The purpose of this study was to determine whether a LMNA mutation is associated with an increased risk of thromboembolic complications. METHODS We compared a cohort of 76 LMNA mutation carriers with a cohort of 224 idiopathic DCM patients without a LMNA mutation, with respect to the prevalence of arterial and venous thromboembolic complications. Furthermore, we carried out a case-control study to explore whether a prothrombotic phenotype was present in LMNA mutation carriers without DCM or atrial tachyarrhythmias (n=14) and compared this with mutation negative relatives (n=13). RESULTS The prevalence of thromboembolic complications was higher in the cohort of LMNA mutation carriers than in DCM patients (22 vs 11%; p<0.05), after respectively mean follow-up of 42 ± 12 and 49 ± 12 years. After adjustment for possible confounders, including atrial tachyarrhythmias and left ventricular ejection fraction, LMNA mutation carriership was independently associated with an increased risk of thromboembolic complications (HR 4.8, 95% CI: 2.2-10.6). The results of the case-control study suggested a prothrombotic phenotype in LMNA mutation carriers, as reflected by an altered platelet function and increased thrombin generation. CONCLUSIONS LMNA mutation is independently associated with an increased risk of arterial and venous thromboembolic complications. Laboratory research in LMNA mutation carriers without severe cardiac abnormalities suggests a prothrombotic phenotype.

Individual with subclinical atherosclerosis have impaired proliferation of blood outgrowth endothelial cells, which can be restored by statin therapy.

Background To study the regenerative capacity of the endothelium in patients with coronary artery disease (CAD), we cultured blood outgrowth endothelial cells (BOECs) of patients with premature CAD and their first degree relatives (FDR). Additionally we evaluated the influence of statin treatment on circulating BOEC precursors in subjects with subclinical atherosclerosis. Methods and Results Patients with premature CAD (men <51 yr, women <56 yr) and their FDRs were included. Based on coronary calcification (CAC) scores FDRs were divided in a group of healthy subjects (CAC = 0) and subjects with subclinical atherosclerosis (CAC>0). We did not observe differences in the number of BOEC colonies and proliferation between premature CAD patients and FDRs. FDRs with subclinical atherosclerosis had lower colony numbers compared with healthy FDRs, however this was not statistically significant, and BOEC proliferation was significantly impaired (OR = 0.45, 95% CI 0.21–0.96). Unexpectedly, the number of BOEC colonies and BOEC proliferation were similar for premature CAD patients and healthy FDRs. Since a considerable number of premature CAD patients used statins, we studied the number of BOEC precursors as well as their proliferative capacity in ten individuals with subclinical atherosclerosis, before and after statin therapy. Interestingly, FDRs with subclinical atherosclerosis showed a significant increase in the number of BOEC colonies after statin therapy. Conclusion BOEC proliferation of subjects with subclinical atherosclerosis is impaired compared with healthy controls. In these subjects, statin therapy significantly increased the number of circulating BOEC precursors as well as their proliferative capacity, revealing a beneficial effect of statins on endothelial regeneration.

Circulating microRNA biomarkers for cardiovascular risk prediction: are we approaching clinical application?

Patients at high risk of cardiovascular morbidity and mortality are still difficult to identify. Unfortunately, the most widely used standard risk prediction models predict cardiovascular disease (CVD) rather poorly, since these risk calculators are mostly driven by age. Therefore, most young subjects are regarded as low risk merely based on their age, despite sometimes quite obvious adverse risk factors. Circulating biomarkers that can help to improve the identification of individuals at risk are therefore highly needed.