Klotho rs577912, rs564481, rs9536314; FGF23 rs7955866; IGF1 rs35767; TNFA rs1800629; IL6 rs1800795; MIF rs755622, rs1007888) chosen in relation to their possible involvement with renal disease and concomitant pathologies. Analysis of the raw data did indicate that IL6 rs180795 and MIF rs755622 SNPs might be markers of genetic susceptibility to ESRD. In particular, the C positive genotypes of MIF rs755622, (dominant model) seem to be an independent risk factor for ESDR patients . Stratifying results according to age MIF rs755622 C positive genotype frequencies are increased in both the two age classes considered (<59 and ≥59-year-old subjects). Analyses of data according to gender allowed us to observe that ESRD women shoved a significantly reduced frequency of genotypes bearing IL6 rs180795 C allele. In addition, MIF rs755622 might interact with diabetes or hypercholesterolemia in increasing susceptibility to ESRD. In conclusion, our data indicate that some polymorphisms involved in the regulation of both renal function and inflammatory response can influence the evolution of chronic kidney disease and suggest that the modulation of the activities of these and other genes should also be considered as therapeutic targets on to intervene with innovative therapies.Chronic kidney disease (CKD) is characterized by an increased risk of kidney failure and end-stage renal disease (ESRD). Aging and comorbidities as cardiovascular diseases, metabolic disorders, infectious diseases, or tumors, might increase the risk of dialysis. In addition, genetic susceptibility factors might modulate kidney damage evolution. We have analyzed, in a group of ESRD patients and matched controls, a set of SNPs of genes ( The NatIn recent years, many studies have been carried out aimed at identifying the molecules to be used as the most sensitive biomarkers of kidney function, many of which are proteins produced by different segments of the nephrons, cytokines, receptors that might be implied in the kidney acute or chronic damage ,4. In adRecently, the scenario of possible biomarkers in chronic renal failure has been enriched by new players such as Fibroblast Growth Factor-23 (FGF-23) and Klotho. The progressive deterioration of renal function is characterized by a progressive reduction of Klotho protein and an increase of the FGF-23 levels ,7,8.Klotho gene related to premature aging have also been identified [Klotho has anti-inflammatory and anti-fibrotic activity, preventing vascular calcifications. In humans, the circulating levels of Klotho decrease with age in serum, and polymorphisms of the entified ,10.Klotho expression in the kidney has a direct correlation with the reduction of GFR-23 in CKD subjects [Circulating Klotho can be considered an early diagnostic marker of CKD. Already for estimated glomerular filtration rate (eGFR) values below 90 mL/min, there is a progressive reduction. Clinical and experimental studies have shown that a significant decrease in subjects . High lesubjects  in CKD prs577912 polymorphism of the Klotho gene sequence might affect the expression of the protein and therefore its serum levels. The CC genotype is associated with a 16–21% lower Klotho expression compared to the AA/AC genotype with an association with an increased risk of mortality at 1 year from the start of dialysis [rs7955866 in exon 3 of FGF23 has been related to renal damage [FGF23-239M plasmid release higher concentrations of FGF-23 [Klotho polymorphisms involved in metabolic disorders and cardiovascular pathologies might play a role in favoring progression to ESRD. In particular, rs564481 and rs9536314 might play a role, being implied in metabolic diseases and potentially influencing the prognosis of CKD [rs56481 might influence hypertension susceptibility and creatinine serum levels in different populations [rs9536314 might influence the kidney failure susceptibility impinging on the kidney function decline due to aging. Actually, a pathophysiological modification associated with chronic kidney disease mimics that of elderly individuals, which underlies shared clinical characteristics such as an increased risk of infection and atherosclerosis [rs9536314 was the polymorphism most frequently involved in association studies on cardiovascular and non-cardiovascular mortality. This may be particularly relevant in patients with chronic kidney disease who have decreased Klotho levels in tissues and blood [In particular, dialysis . In addil damage . The minf FGF-23 . On the s of CKD ,16,17,18ulations ,16,17 whclerosis . Moreovend blood .IGF1 gene [IGF1 rs35767 increases the risk of renal disease.More recently, the interactions between the Klotho/FGF-23 system and the growth hormone (GH)/insulin-like growth factor-1 (IGF-1) axis have been analyzed. The GH/IGF-1 system appears relevant for glomerular and tubular function, as well as the synthesis of Klotho . On the GF1 gene . MoreoveGF1 gene , IGF1 rsActually, the chronic inflammation state that characterizes CKD and ESRD induces an up-regulation of proinflammatory cytokines and the associated biomarkers (interleukin (IL)-1β, IL-1 receptor antagonist, IL-6, tumor necrosis factor (TNF)-α, C-reactive protein, and fibrinogen) ,27.Proinflammatory markers are shown to be important in the development of atherosclerotic complications and inflammation. In addition, it has been associated with hypertension in both experimental animal models and human studies ,30,31,32TNF SNPs [IL6 gene SNPs [MIF gene variants [rs1800629 and rs1800795 polymorphisms of TNFA and IL6 genes can selectively affect spontaneous production of inflammatory cytokines influencing kidney function decrease and consequent development and progression of chronic kidney disease.On the other hand, an aging kidney can be considered a paradigmatic model of immunosenescence characterized by defective immune responses and increased systemic inflammation. In the kidney, resident macrophages and fibroblasts are continuously exposed to environmental stimuli, and the effects of cellular reprogramming induced by local immune responses, which accumulate with age, might have a role in the increased susceptibility to kidney disease among elderly individuals ,33 and pTNF SNPs ,39, IL-6TNF SNPs ,41, and ene SNPs ,43,44, avariants ,46,47,48Herein, data on some genetic variants of key cytokine, mediator, and receptors involved in the complex scenario of kidney chronic failure have been reported and their relevance as risk profile markers useful in the prediction of kidney disease development and progression have been evaluated.In collaboration with the Department of Nephrology and Dialysis with C.R.R. for arterial hypertension, “Paolo Giaccone” University Hospital, a population of 93 patients with end-stage renal chronic failure (ESRD) who were routinely undergoing dialysis therapy was recruited. Two control populations, for a total of 213 individuals, were recruited, one of healthy young people and one of the people over 59 years old, at the Department of Medical Biotechnology of the University of Palermo and in collaboration with the U.O.C of Transfusion Medicine of the Paolo Giaccone” University Hospital. The cut-off for age between the two control population was chosen on the basis of the median age of ESRD patients. The ≥59-year-old control population included both healthy subjects and people with hypercholesterolemia, type 2 diabetes, or hypertension without renal impairment . Persons with autoimmune or tumor pathologies or with GFR < 90 were excluded from the control group. The clinical and demographic characteristics of the populations studied are shown in Our study was performed in accordance with ethical standards of the Helsinki Declaration of the World Medical Association and Italian legislation, and was approved by the local institutional review board . All participants gave their informed consent and the data has been encoded to ensure the protection of patient privacy and controls. The EDTA peripheral blood samples used for molecular typing respectively were collected and stored at 70 °C until their use.https://www.ncbi.nlm.nih.gov/snp/, accessed on 18 January 2022).DNA were extracted using a salting-out protocol and DNA quality was verified by 260/280 nm absorbance ratio and gel electrophoresis as previously reported . SNP typhttps://sample-size.net/, accessed on 17 February 2022). Significant differences in genotype distributions between groups were calculated using chi-square or Fisher’s exact test applied to the appropriated 2 × 2 or 3 × 2 contingency tables. Multiple logistic regression models were applied using overdominant , codominant , dominant , and recessive  of heredity and adjusting the results for age, sex, and concomitance of existing pathologies. The choice of the most suitable model was based on the Bayesian Information Criterion (BIC) and the Akaike Information Verification Test (AIC). Odds ratio (OR) values and 95% confidence intervals (95% CI) were calculated and a p-value < 0.05 was considered statistically significant. Statistical analyzes were conducted using version 3.06 of GraphPadInStat software  and online statistical analysis tools  devoted to the evaluation of the association of SNPs with diseases in the presence of other biological, genetic, or clinical variances.Allele and genotype frequencies were evaluated by gene count. Pearson’s test was applied to test the Hardy–Weinberg equilibrium. Power of calculation has been evaluated for all comparisons made using an online tool  of inheritance and adjusting the results for biological variables  and concomitant comorbidities .MIF rs755622, (dominant model) is an independent risk factor for ESDR patients . In addition, a rough significant influence of both TNFA rs1800629 homozygous genotypes have been detected  and clinical variables , genotype frequencies of ESRD patients and controls were stratified and compared according to the different variables. Complete results of these analyses are reported in MIF rs755622 C positive genotype frequencies are increased both in <59 and ≥59-year-old patients than in controls  is the result of the progressive reduction of renal function and the onset of a progressively more severe chronic renal failure whose evolution is strongly influenced by the underlying disease, age, sex, and genetic background of the patients. If we consider the progressive aging trend of the population and the increase in the prevalence of the main diseases predisposing to chronic kidney failure (CKF) , identifying predicting genetic markers that allow early identification of patients with an increased risk to develop severe CKF and reach the ESRD appears to be mandatory ,53.Klotho, in spite of the above-mentioned data on the role of rs577912 polymorphism as risk factors of mortality in dialyzed patients [rs9536314 in the so-called longevity trait [FGF23 rs7955866 and IGF1 rs35767 were not found to be associated with ESRD. On the other hand, more recently, other FGF23 SNPs have been associated with CKD [rs35767 is known to contribute to the development of diabetes in various populations [Analyses of alleles and genotypes crude frequencies of nine SNPs of genes codifying for key cytokine and receptors involved in kidney damage pathogenesis do not allow to identify associations with the patients  and the ty trait . In a stty trait  but we wwith CKD . So furtulations .IL6 rs1800795 are lower in patients than in controls allowing us to hypothesize that the presence of the C allele might be protective against progression to ESRD. This was not confirmed by adjusting the odds ratio for biological variances and clinical comorbidities (Interleukin-6 (IL-6), another important proinflammatory cytokine has been shown to play a critical role in the development of atherosclerosis and atherosclerotic disease including kidney diseases ,56, and bidities , whereasrs1800795G/C variant located in the gene promoter (−174G/C) is associated with changes in transcriptional expression [It has long been known that the pression .rs1800795 and gender are not conclusive. Studies on aging frailty or longevity trait have demonstrated the possibility that genetically determined high production of IL-6 and women gender are risk factors for age-related disease [rs1800795 C allele might be protective against ESRD for CKD-affected women. On the other hand, the relatively small size of the patient sample does not allow to consider this observation conclusive.Even if IL-6 tracks with disability and age-related diseases, published data on the interaction among  disease ,59. In tIn diabetes, the C allele is associated with a low risk of nephropathy ,61. On tThese apparently conflicting results are not easy to interpret. On the other hand, genetically determined low production of IL-6 might be a vantage in the contrasting progression of systemic diseases characterized by a chronic low rate of the inflammatory response , as CKD,TNFA rs1800629 genotypes has been detected. Cytokines of the TNF family and their receptor has been recently proposed as biomarkers of kidney disease. Actually, TNF signaling pathways play important roles in the progression of atherosclerotic and kidney disease [As reported in  disease ,32,33 an disease ,67.TNFA SNPs have suggested that rs1800629, associated with an increased TNFA gene transcription, might be a risk factor for multifactorial diseases [rs1800629 might be a risk factor for CKD in particular in diabetic patients but data have been not conclusive [Studies on diseases , in partnclusive ,39. Genenclusive .Arterial hypertension is one of the main causes of kidney damage leading to end-stage renal disease (ESRD) ,71, and In spite of this, our data do not allow us to identify the association of hypertension and SNP genotype studied as risk or protective factors in our group of ESRD patients.MIF rs1007888, which was found associated with an increased risk of diabetes [rs755622, located at −173bp before the transcription initiation site of MIF gene and associated with a higher production of the cytokine [MIF rs755622 seem to be associated with an increased risk to develop an ESRD both in patients ≥59 and <59 years old.Typing of diabetes , does no2), the risk was relevant only when eGFR had fallen below 45 mL/min. In this view, the possibility to refine the analyses combining age and significant SNP markers could be useful for the best management of CKD prevention and therapy. However, our data indicate that the MIF rs755622 C allele is an age and gender independent risk factor for ESRD progressionAging is per se a risk factor for kidney diseases and in particular for CKD. However, it is well known that glomerular filtration rate (eGFR) declines with aging and this might impinge on the risk of CKD evolution to terminal stage and mortality. As recently reported by Delanaye et al. , for peoOur results are in good agreement with data of other groups indicating that high production of MIF is correlated with an increased susceptibility for a large number of inflammatory and metabolic diseases including chronic kidney failure ,77,78,79rs755622 on CKD predisposition and ESRD progression might be influenced by individual biological factors such as aging [On the other hand, in chronic kidney diseases (CKD), MIF limits the pro-fibrotic and proinflammatory activation of tubular cells by counteracting the arrest of the cell cycle and promoting its regeneration; In addition, in acute kidney damage (AKI), MIF also counteracts the apoptosis of tubular cells with a protective effect ,82,83. Sas aging  or the pas aging .As it is well known, diabetes is one of the major comorbidities associated with CKD. CKD can be a consequence of the alteration of the glucose status or we can have a kidney disease on which type II diabetes is superimposed. In diabetic nephropathy, the endothelial involvement and local induction of cytokines and chemokines induce immune cell recruitment accompanying and promoting tissue remodeling and nephron atrophy . MoreoveKlotho rs564481 [MIF rs755622 genetic polymorphism might play a role in ESRD progression in subjects affected by these pathologies. However, our data were obtained analyzing a relatively low number of subjects bearing diabetes or hypercholesterolemia, so a definitive conclusion cannot be drawn, even if some literature reports seem to support this view [The analysis of the association between the polymorphisms we typed and the risk of dialysis in subjects suffering from hypercholesterolemia or diabetes do not allow us to identify associations with polymorphisms known to be associated with changes in lipid and carbohydrate metabolism as rs564481 ,16, wherhis view ,89,90.IL6rs1800795 and MIF rs755622, involved in the regulation of both renal function and inflammatory response can influence the evolution of chronic kidney disease. In particular, IL6rs1800795G genotype and MIF rs755622C alleles associated with increased production of the respective cytokines inducing increased inflammatory damages of kidney parenchyma might be useful as a marker for evaluation of ESRD evolution risk.In conclusion, CKD might be considered a paradigm of the multifactorial diseases in which preexisting pathological conditions and genetic susceptibility factors might interplay with each other, resulting in different trajectories of damage evolution to the final stage as ESRD. In this view, we have analyzed the role of some genetic variants of key cytokines, mediators, and receptors involved in the complex scenario of kidney chronic failure and their interaction with comorbidities. Our data indicate that some polymorphisms, MIF rs755622, in the progression of end-stage renal disease.In addition, it is hypothesized that the modulation of the activities of these and other genes can also be considered therapeutic targets for innovative therapies. In this light, further studies will certainly be needed to investigate the role and interaction of these SNPs, in particular


The REWIND trial demonstrated cardiovascular (CV) benefits to patients with type 2 diabetes and multiple CV risk factors or established CV disease. This exploratory analysis evaluated the degree to which the effect of dulaglutide on CV risk factors could statistically account for its effects on major adverse cardiovascular events (MACE) in the REWIND trial.Potential mediators of established CV risk factors that were significantly reduced by dulaglutide were assessed in a post hoc analysis using repeated measures mixed models and included glycated hemoglobin (HbA1c), body weight, waist-to-hip ratio, systolic blood pressure, low-density lipoprotein (LDL), and urine albumin/creatinine ratio (UACR). These factors, for which the change in level during follow-up was significantly associated with incident MACE, were identified using Cox regression modeling. Each identified variable was then included as a covariate in the Cox model assessing the effect of dulaglutide on MACE to estimate the degree to which the hazard ratio of dulaglutide vs placebo was attenuated. The combined effect of the variables associated with attenuation was assessed by including all variables in an additional Cox model.Although all evaluated variables were significantly improved by treatment, only changes in HbA1c and UACR were associated with MACE and a reduction in the effect of dulaglutide on this outcome was observed. The observed hazard ratio for MACE for dulaglutide vs placebo reduced by 36.1% by the updated mean HbA1c, and by 28.5% by the updated mean UACR. A similar pattern was observed for change from baseline in HbA1c and UACR and a reduction of 16.7% and 25.4%, respectively in the hazard ratio for MACE with dulaglutide vs placebo was observed. When HbA1c and UACR were both included, the observed hazard ratio reduced by 65.4% for the updated mean and 41.7% for the change from baseline with no HbA1c-UACR interaction .Treatment-induced improvement in HbA1c and UACR, but not changes in weight, systolic blood pressure, or LDL cholesterol, appear to partly mediate the beneficial effects of dulaglutide on MACE outcomes. These observations suggest that the proven effects of dulaglutide on cardiovascular disease benefit are partially related to changes in glycemic control and albuminuria, with residual unexplained benefit.https://clinicaltrials.gov/ct2/show/NCT01394952Clinicaltrials.gov; Trial registration number: NCT01394952. URL:  Outcome trials evaluating cardiovascular (CV) effects of glucagon-like peptide-1 (GLP-1) receptor agonists have consistently demonstrated the benefit and safety of these agents in populations with type 2 diabetes (T2D) . Some ofThe Researching cardiovascular Events with Weekly INcretin in Diabetes  trial showed that, in patients with T2D and multiple CV risk factors or established CV disease, dulaglutide 1.5 mg once weekly reduced the incidence of a composite outcome comprising nonfatal myocardial infarction, nonfatal stroke, or death from CV causes or unknown causes (MACE) compared to placebo, with an observed hazard ratio (HR) of 0.88  . The tri2 were included. Participants were randomly assigned to the addition of once weekly subcutaneous dulaglutide 1.5 mg or placebo and the usual standard of care (as informed by current country guidelines). Key exclusion criteria were an estimated glomerular filtration rate less than 15 mL/min per 1.73 m2, cancer in the previous 5 years, severe hypoglycemia in the previous year, life expectancy less than 1 year, a coronary or cerebrovascular event within the previous 2 months, and plans for revascularization. A complete list of inclusion and exclusion criteria is given in the appendix (pp 151–55) of the primary results paper [The REWIND study design and eligibility criteria have been published previously –17. BrieA mediation analysis approach  was usedThe epidemiologic relationship between each of these variables and the primary MACE outcome was estimated by separate Cox models fitted using either (1) the updated mean value of the variable until a MACE occurred or the end of the period of observation, or (2) the change from baseline for the variable to the last measurement before an event or the end of observation. The only independent variable for each model was the variable being assessed. WHR analyses were performed separately for each sex because of known sex-related differences .100 x (ln HRunadjusted – ln HRadjusted))/ln HRunadjusted where ln(HRunadjusted) is the natural logarithm of the hazard ratio comparing dulaglutide to placebo from the Cox model incorporating only the treatment effect  [adjusted) is the natural logarithm of the hazard ratio from the model incorporating the potential mediator [For those variables for which either the updated mean or the change from baseline was significantly associated with the primary MACE endpoint at a nominal p-value of 0.05, the hazard ratio for dulaglutide vs placebo of the primary MACE outcome was then re-estimated using a separate Cox model. The model included treatment group, the baseline value of the measurement, and the updated mean or the change from baseline of the variable, respectively as time-dependent covariates. These produced univariate models of the treatment effect adjusted for each potential mediator. The proportion of the effect of dulaglutide mediated by the variable was estimated by nalysis) , and ln with type 2 diabetes whose mean age was 66.2 (SD 6.5) years. After random assignment to dulaglutide (N = 4949) or placebo (N = 4952), participants were followed for a median of 5.4 years during which 1257 individuals developed at least one MACE outcome . The patThe epidemiologic relationship between the change in each of these variables and incident MACE outcomes is shown in Table Re-estimating the effect of dulaglutide on the MACE outcome after accounting for change in HbA1c, the observed hazard ratio changed from 0.88 to either 0.90  or 0.92  when the change from baseline or the updated mean was used, respectively , high study retention (97%), and high dulaglutide adherence (82%) in REWIND . In addiIn conclusion, the results of these analyses suggest a substantial portion of the benefits of dulaglutide on MACE may be associated with reduction of HbA1c and UACR. These effects appear to be additive, with up to 65% of the benefit statistically explained by these variables together, although residual mediators of benefit of dulaglutide remain unexplained.


Objective: To determine whether there is an association between microhematuria and relapse or kidney disease progression in patients with primary membranous nephropathy (PMN).Methods: A cohort of 639 patients with biopsy-proven PMN from two centers was followed for a median of 40 months. The exposures were initial hematuria, time-averaged hematuria, and cumulative duration of hematuria. The outcomes were relapse and renal progression, which were defined by a 40% reduction in renal function or end-stage renal disease. Cox proportional hazards regression and competing risk analyses were performed to yield hazard ratios (HRs) and subdistribution hazard ratios (sHRs) with 95% confidence intervals (CIs). Sensitivity and interaction analyses were also performed.Results: After adjusting for confounders, a higher level of initial hematuria was associated with a 1.43  greater hazard of relapse. Worsening hematuria remarkably increased the risk of short-term relapse . Time-averaged hematuria  and cumulative duration of hematuria  were independent predictors of renal progression. Hematuria remission was related to a reduced risk of renal progression over time in patients with positive microhematuria .Conclusions: A higher level of initial hematuria was a remarkable predictor of relapse in patients with PMN, and the magnitude and persistence of microhematuria were independently associated with kidney disease progression. Glomerulonephritis (GN) may be caused by problems with the body's immune system. Damage to the glomeruli causes blood and protein loss in the urine. Microhematuria, accompanied by variable amounts of proteinuria, is one of the most common clinical manifestations of GN, e.g., IgA nephropathy (IgAN), ANCA-associated vasculitis (AAV), and lupus nephritis –3. The s2 receptor antibody (anti-PLA2R) levels after therapy, and C3 staining in the biopsy sample (Primary membranous nephropathy (PMN) is a kidney-specific, autoimmune glomerular disease, and it is one of the most common causes of nephrotic syndrome in non-diabetic adults worldwide –14. Appry sample , 15–17.Microhematuria is not uncommon, and appears in ~50–60% of patients with PMN , 15, 18.2, calculated according to the Chronic Kidney Disease Epidemiology Collaboration equation  participated in this retrospective cohort. Other inclusion criteria were (1) a baseline  eGFR >15 ml/min/1.73 mequation , (2) at Each participant attended regular visits at intervals of 3–12 months. Urine sediment and 24-h proteinuria excretion were tested at each visit and recorded prospectively. Skilled clinical examiners performed microscopic analyses of urine sediments. Each urine sample was strictly analyzed within 2 h of collection and reported as red blood cells (RBCs)/high-power field (HPF). We only recorded the results of urine sendiments, mainly of glomerular derived RBCs (dysmorphic RBCs > 70%). Since our study was focused on the microhematuria, the results of microscopic analyses during gross hematuria episodes were excluded. Other clinical data, including age, sex, body mass index, blood pressure, serum creatine, serum albumin, and use of renin-angiotensin-aldosterone system (RAAS) blockades and immunosuppressive (IS) agents during the first year, were systematically recorded. The follow-up data were last updated on 31 December 2020.2 or chronic dialysis. Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or the use of antihypertension drugs.The follow-up time referred to the interval between kidney biopsy and the last outpatient visit, death, or ESRD, whichever occurred first. ESRD was defined as eGFR <15 ml/min/1.73 mFor PMN, nephrotic syndrome referred to proteinuria ≥3.5 g/d and serum albumin <3 g/dL. Complete remission (CR) was defined as proteinuria <0.3 g/d with serum albumin ≥3.5 g/dL and stable kidney function. A stable kidney function was defined as an eGFR that remained unchanged or declined by <40%. Partial remission (PR) was proteinuria >0.3 but <3.5 g/d plus a ≥50% reduction from baseline level, with serum albumin ≥3.5 g/dL and stable kidney function. No remission (NR) was defined as proteinuria ≥3.5 g/d, a <50% decline in proteinuria, serum albumin <3.5 g/dL, or a ≥40% decline in the eGFR prior to achieving proteinuria reduction. Relapse was defined as a reappearance of proteinuria ≥3.5 g/d after PR or CR.The variables of interest were initial hematuria and the magnitude and persistence of microhematuria over time. Due to the high variability of microscopic assessment at a single time point, we treated the average hematuria of the first 6 months during follow-up as the initial hematuria. An initial hematuria of >5 RBCs/HPF was defined as initial persistent hematuria. The magnitude of microhematuria was expressed using time-averaged hematuria (TA-H). According to previously reported methods , 9, TA-HThe primary outcome was relapse. We evaluated time to first event for relapse with start date defined as the time a patient first attained PR. As an exploratory study, the association between worsening hematuria and short-term (within 12 months) relapse was also analyzed. The worsening hematuria was defined as the appearance of positive hematuria (>3 RBCs/HPF). In this part, the exposures were the appearance of positive hematuria within 12 months before relapse (vs. no appearance) and the specific time frames  that the positive hematuria appeared in.The secondary outcome was renal progression, which was a composite endpoint that included a ≥40% decline in eGFR or ESRD. The time zero was kidney biopsy. For futher research, the relationship of hematuria remission with renal progression was also quantified. Hematuria remission was defined by the absence of microhematuria or the presence of ≤3 RBCs/HPF in all urine sediment tests performed during at least 12 months before the last outpatient visit. More details on the methods are provided in the supplementary material .t-tests for normally distributed variables, Kolmogorov-Smirnov tests for variables with skewed distributions, and chi-squared tests for categorical variables. The cumulative probability of relapse was estimated using the Kaplan-Meier method and compared using the log-rank test. Adjusted analyses were performed using Cox proportional hazards regression. The proportionality assumption of models was evaluated via the examination of Shoenfeld residuals. For renal progression, the outcome probability was evaluated using univariate analyses with cumulative incidence function (CIF) methods and Gray test and multivariate competing risk regression analyses. Death without renal progression was treated as a competing event. TA-H, CD-H, and TA-P were included as time-varying covariates. Initial hematuria, TA-H, CD-H, and TA-P were log-transformed due to their positively skewed distribution. To avoid data loss due to transformation, 0.1 was added to the values of initial hematuria, TA-H, and CD-H. The strength of association is expressed as a hazard ratio (HR) or subdistribution hazard ratio (sHR) with 95% confidence intervals (95% CIs).Continuous variables are presented as means with standard deviations (SD) for normal distributions or medians with interquartile range (IQR) for skewed distributions. Categorical variables are presented as percentages. Differences between groups were compared using Student's P value <0.05 was considered significant. Statistical analyses were performed using Stata Edition 15.0 .Sensitivity analyses were performed by (1) restricting the subcohort to a single center or (2) using a 50% decline in renal function or ESRD as the endpoint. We also tested whether nephrotic syndrome (vs. subnephrotic status) and the use of RAAS blockers or IS agents modified the effect of initial hematuria or hematuria classification by adding the interaction terms in the models. A two-sided 2, and the serum albumin was 2.88 ± 0.76 g/dL. The median proteinuria was 3.33 (1.75–5.10) g/d, and the microhematuria was 3 (1–8) RBCs/HPF at baseline.Among 1,162 participants from the two centers, 639 were eligible for analyses (474 from XH and 165 from SPHTCM) . At baseThe median follow-up was 40 (28–49) months. The median initial hematuria was 3.2 (2–6.23) RBCs/HPF. The median TA-H was 2.34 (1.28–3.78) RBCs/HPF, CD-H was 3 (1–8) months, and TA-P was 1.19 (0.65–2.07) g/d. During follow-up, 566 (88.58%) patients in the entire cohort achieved PR. Among patients who reached PR, 111 (19.61%) subsequently relapsed in a median of 30 (18–41) months. Overall, 50 (7.82%) patients reached renal progression, including 9 ESRD events.P = 0.036).The patients who attained PR (566 patients) were used for the analyses of this part . The expThe results of Cox proportional hazards regression analyses are presented in P for interaction = 0.471). Neither the use of RAAS blockers (P for interaction = 0.397) nor IS agents (P for interaction = 0.850) significantly modified the effect of initial hematuria.The effect size was recalculated in a single center in sensitivity analyses. The adjusted HR of initial hematuria in the XH center  was 1.49In this part, the patients that reached PR (566 patients) were used for the analyses . As showAll eligible participants (639 patients) were included in the analysis of the association of microhematuria with renal progression . The expP = 0.040, P = 0.019, As shown in P for interaction = 0.868; use of RAAS blockers, P for interaction = 0.824; use of IS agents, P for interaction = 0.405). Similarly, no significant heterogeneity was observed in the analyses of the association between CD-H and renal progression .The clinical characteristics of the patients grouped by centers are presented in P = 0.034, Patients with positive hematuria  were used for the analyses, and were divided into hematuria remission (71 patients) and non-remission (149 patients) groups . The expTaken together, the results from our double-center cohort suggested that (1) the initial hematuria was an independent risk factor for relapse, and the magnitude and persistence of microhematuria over time were substantially associated with kidney disease progression in patients with PMN; (2) the worsening of microhematuria markedly enhanced the hazard of short-term relapse; and (3) the remission of microhematuria exhibited a positive effect on the improvement in renal outcomes in patients with PMN and microhematuria during follow-up.Hematuria is a clinical symptom of some renal disorders with benign features, and it has been neglected by many clinicians for decades. However, multiple recent studies challenged this concept and demonstrated that the presence of hematuria, especially of glomerular origin, was a hallmark of inflammation and pathological damage in nephridial tissue –6, 23. TThe most prominent clinical feature of PMN is nephrotic syndrome and its associated manifestations. Microhematuria is not uncommon and accounts for ~50% of patients at disease onset and 60% during the course , 28, 29.Previous studies generally used TA-H >5 RBCs/HPF to represent persistent hematuria , 9. HoweOur results suggested that the initial persistent hematuria was independently associated with a greater risk of a future flare in patients with PMN. One of the greatest future challenges is the establishment of a clear association between glomerular damage and the potential utility of initial persistent hematuria to decide when it is necessary to increase IS treatment. Moreover, there was an obvious connection between worsening hematuria and the risk of a flare within the following 12 months. The appearance of positive hematuria was related to an increased risk of relapse in reference to no appearance. Notably, the worsening of hematuria over the past 4–6 months presented a more prominent warning compared to the occurrence of hematuria at the onset of a relapse. These findings support the routine use of urine sediments in clinical practice and emphasize the significance of close clinical monitoring in patients with PMN because this may be an early predictor of short-term relapse.via the oxidative stress caused by the release of hemoglobin and iron from broken erythrocytes into renal tubular cells  This was the first study to investigate the prognostic relevance of microhematuria over time in PMN. (2) The magnitude and persistence of microhematuria over time were systematically quatified. (3) The relationships between the worsening hematuria and short-term relapse, and between hematuria remission and kidney disease progression were also analyzed. (4) The two-center design made it possible to validate the robustness of our findings.2R levels after therapy, urinary excretion of β2 microglobulin, and other known or unknown confounders. Therefore, we cannot exclude the possibility of residual confounding. (3) The relatively low number of renal progression events may affect the accuracy of the results.Our study is not without its limitations. (1) This study was a retrospective cohort with a single ethnicity. (2) We did not include comprehensive data that may be associated with renal survival in patients with PMN, such as serum anti-PLAIn summary, our study showed that initial hematuria was an independent predictor for relapse, and the magnitude and persistence of microhematuria over time were independently linked with a higher risk of renal function loss in patients with PMN. Further studies are needed to verify our findings and clarify the role of surveillance and treatment of hematuria in clinical management decisions for PMN.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of Xijing Hospital. Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.LH, PH, SS, CH, and HW: designed the study, analyzed the data, and drafted the manuscript. PH, JL, and YZ: collected and entered data. LH, PH, XY, SS, CH, and HW: contributed to data acquisition and interpretation. All authors have read and approved the final manuscript.This study was supported in part by grants from the National Natural Science Foundation of China (81770764 and 81770669).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Discriminating between different patterns of diastolic dysfunction in heart failure (HF) is still challenging. We tested the hypothesis that an unsupervised machine learning algorithm would detect heterogeneity in diastolic function and improve risk stratification compared with recommended consensus criteria.Methods: This study included 279 consecutive patients aged 24–97 years old with clinically stable HF referred for echocardiographic assessment, in whom diastolic variables were measured according to the current guidelines. Cluster analysis was undertaken to identify homogeneous groups of patients with similar profiles of the variables. Sequential Cox models were used to compare cluster-based classification with guidelines-based classification for predicting clinical outcomes. The primary endpoint was hospitalization for worsening HF.Results: The analysis identified three clusters with distinct properties of diastolic function that shared similarities with guidelines-based classification. The clusters were associated with brain natriuretic peptide level (p < 0.001), hemoglobin concentration (p = 0.017) and estimated glomerular filtration rate (p = 0.001). During a mean follow-up period of 2.6 ± 2.0 years, 62 patients (22%) experienced the primary endpoint. Cluster-based classification predicted events with a hazard ratio 1.68 (p = 0.019) that was independent from and incremental to the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk score for HF, and from left ventricular end-diastolic volume and global longitudinal strain, whereas guidelines-based classification did not retain its independent prognostic value .Conclusion: Machine learning can identify patterns of diastolic function that better stratify the risk for decompensation than the current consensus recommendations in HF. Integrating this data-driven phenotyping may help in refining prognostication and optimizing treatment. Left ventricular (LV) diastolic dysfunction is a key pathophysiological feature of heart failure (HF) and its assessment plays an important role in diagnosing, monitoring and prognosticating HF. It appears early in the natural course of various types of cardiovascular diseases and once severe, diastolic dysfunction is associated with elevated left atrial pressure , 2. The In clinical practice, LV diastolic function is assessed using echocardiography by measuring multiple variables, for example from transmitral flow and mitral annular velocity profiles. Each variable reflects a different physiological aspect of LV filling, and all are inter-related in a complex manner . StandarMachine learning is a method for analyzing data that, unlike traditional statistics, can deal with complex datasets with multivariable non-linear interactions. It constructs analytical models to extract insights, patterns and relationships that can be used for decision-making. In cardiovascular medicine, machine learning has identified new clinical phenotypes, predicted responses to treatment, and improved prognostication –10. AccoFrom the HF database of the Cardiovascular Institute, Japan , we retrospectively identified a consecutive series of 815 patients with clinically stable HF. Patients were eligible for this study if they were older than 20 years at the time of the index echocardiographic examination, and if they had been referred to echocardiography for hemodynamic assessment between February 2010 and August 2018, and if they had a history of previous hospitalization for acute decompensated HF with symptoms sufficient to warrant hospitalization and for which intravenous therapy was required. In total 561 patients fulfilled these criteria, but those were excluded who had any of the following: (1) being treated with intravenous therapy at the index examination, (2) atrial fibrillation at the index examination , (3) any missing data for diastolic variables, (4) rheumatic heart valve disease, (5) any other types of primary heart valve disease more than moderate, (6) pericardial disease and (7) history of cardiac surgery . This exThis study was approved by the institutional review board. All the patients gave written informed consent when registered in the hospital database.Comprehensive echocardiographic examination was performed, using commercially available ultrasound machines with a 2.5 MHz sector transducer . LV end-diastolic and end-systolic volumes and LVEF were calculated by the disk summation method. LV mass was calculated as recommended and normalized by body surface area (LVMi). LV global longitudinal and circumferential strains were measured using Image Arena . Left atrial volume was also measured by the disk summation method and normalized by body surface area (LAVi). Pulse-wave Doppler tracings at the tip of the mitral valve leaflets were recorded, and early to late diastolic transmitral velocity ratio (E/A) was calculated. Mitral annular velocities were recorded using pulsed tissue Doppler from the base of the septum in an apical 4-chamber view, to evaluate LV longitudinal function . Left atrial pressure was estimated from the ratio of transmitral E velocity to early diastolic mitral annular velocity (E/e'). A continuous-wave Doppler tracing of tricuspid regurgitation (TRV) was recorded to assess pulmonary hypertension. Right ventricular end-diastolic area and fractional area change were measured in an apical 4-chamber view to derive right ventricular size and systolic function.The current American Society of Echocardiography/European Association of Cardiovascular Imaging consensus recommendations proposed two different algorithms for assessing diastolic function . In thisModel-based cluster analysis, an unsupervised machine learning algorithm, was performed using mclust package in R . This assumes that data points within a cluster are normally distributed, and it finds the mixture of multi-dimensional Gaussian probability distributions that best models the input dataset .The analysis was applied in order to group the study population into clusters with distinct diastolic function properties. The diastolic variables used for cluster modeling were chosen based on their inclusion in current consensus recommendations  . The degThe learned clusters were characterized by comparing clinical and echocardiographic variables. These variables, including demographics, vital signs, cardiac risk factors, HF symptoms, time since the first diagnosis of HF, drug treatment, and laboratory data such as hemoglobin level and estimated glomerular filtration rate (eGFR), which had all been recorded within 3 months of the index examination, were collected from the hospital database. Brain natriuretic peptide (BNP) measurement was available in 193 (70%) patients. The Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) score, an established clinical risk score for HF, was calculated from all relevant variables .Whether or not the learned clusters reasonably captured diastolic phenotypes was tested by studying the associations of BNP level and clinical outcomes with the clusters. The outcome data were obtained from the hospital database which integrates events documented in the hospital medical records and those recorded through an annual postal survey. Patients were censored when they stopped visiting the hospital or responding to the postal survey. Those who continued to attend and remained free from events at 5 years were automatically censored then. The primary endpoint was hospitalization for worsening HF. The secondary endpoint was a composite of cardiovascular death and hospitalization for worsening HF. The cardiovascular death was ascertained from medical records of the patients and from direct contact with local physicians. Sudden death was considered as cardiovascular death in this study.We did not expect full agreement between the two classifications and would rather highlight discordance where cluster-based classification could help further risk stratification. Principal component analysis was performed on the same five diastolic variables as used for the clustering, to plot and compare the patterns of grade and cluster distribution. A contingency table was created to identify where cluster-based classification was the most discordant with guidelines-based classification. BNP level and clinical outcomes were compared among the clusters in a subgroup of patients with discordant classifications.P value < 0.05 was considered as statistically significant. All statistical analyses were performed using IBM SPSS statistics version 19 .Categorical variables were expressed as number and percentage and were compared using chi-square test. Continuous variables were expressed as mean ± standard deviation and were compared using analysis of variance if the variables were normally distributed. If they were not found to be normally distributed, they were expressed as median (25–75th percentile) and were compared using Kruskal-Wallis test. Survival curves were estimated separately for cluster-based and guidelines-based classifications, using the Kaplan-Meier method, and compared using a log-rank test. Sequential Cox models were used to compare cluster-based and guidelines-based classifications. A baseline model was constructed by entering MAGGIC score and LV end-diastolic volume (LVEDV) and LV global longitudinal strain (LVGLS). We did not add LVEF in the model because it is already included in the MAGGIC score. Nested Cox models with separate addition of cluster-based and guidelines-based classification to the baseline model were constructed. The increase in predictive power after the addition of the classification variables was assessed by the change in overall model χ (p < 0.001), E/e' (p < 0.001), LAVi (p < 0.001) and TRV (p < 0.001) progressively increased from grade 1 to 3. The e' (p = 0.001) was higher in grade 1 than in grade 2 and 3. Patients with grade 2 diastolic dysfunction were older (p < 0.001), more often women (p < 0.001) and more often had comorbidities such as hypertension (p = 0.001), diabetes (p = 0.016) than those with the other grades; heart failure with preserved ejection fraction  accounted for more than half in this subgroup. In comparison, patients with grade 3 diastolic dysfunction had lower blood pressure (p < 0.001) and were more often prescribed diuretics (p = 0.026). Heart failure with reduced ejection fraction  associated with was prevalent in this subgroup; global circumferential strain was lower (p = 0.016) than in the other grades, although LVGLS was not different (p = 0.112); right ventricular function was also reduced (p < 0.001).The comparisons of diastolic variables across the grades are illustrated in After confirming that diastolic variables  were not strongly correlated each other , we perfp < 0.001), LAVi (p < 0.001) and TRV (p < 0.001) progressively increased from cluster 1 to 3, as assigned (p < 0.001) and thinner (p = 0.028). HFpEF was dominant in clusters 1 (59%) and 2 (50%), whereas HFrEF was more prevalent in cluster 3 (44%). LV myocardial function measured by LVGLS and LV circumferential strains was abnormal in all the clusters and decreased gradually from cluster 1 to 3 . Right ventricular function was reduced in cluster 3 (p = 0.010). These trends resulted in increasing MAGGIC scores from cluster 1 to 3 (p < 0.001).E/e' (assigned . Clusterp < 0.001). There were no significant differences in major baseline characteristics between patients with and without BNP measurement (p = 0.017) and worsening renal function  across the clusters but not across the grades.surement . Figures2 . In the sequential Cox proportional hazard analysis, the baseline model including MAGGIC score, LVEDV and LVGLS gave an overall χ2 value of 48.1 for the primary endpoint and 44.5 for the secondary endpoint , whereas the addition of clusters significantly improved the predictive power for both study endpoints .During a follow-up period of 2.6 ± 2.0 years, 62 patients (22%) experienced the primary endpoint of worsening HF, and 69 patients (25%) experienced the secondary composite endpoint of worsening HF (62 patients) and/or cardiovascular death (seven patients). endpoint . The addp < 0.001 for both statistics). Patients diagnosed as grade 1 diastolic dysfunction by the guidelines (n = 188) were allocated mostly to cluster 1 (22%) and cluster 2 (76%) but 5 patients (3%) were allocated even to cluster 3.The patterns of grade and cluster distributions were mapped in p < 0.001) even after adjusting for MAGGIC score, LVEDV and LVGLS.To assess whether clustering helped stratify risk in grade 1 diastolic dysfunction, BNP levels and clinical outcomes were assessed within this subgroup . BNP levWe demonstrated that cluster analysis outperforms diastolic function classification by echocardiographic consensus recommendations, for the prediction of hospitalizations or cardiovascular deaths in patients with HF, irrespective of LVEF. The improved performance was the greatest for subjects with grade 1 diastolic dysfunction. These results suggest a more data-driven approach for developing diagnostic recommendations.Precise assessment of diastolic function is essential for diagnosing and managing HF. To grade diastolic function in clinical practice, the consensus recommendations have proposed complex decision-tree algorithms that evolved through multiple iterations . The updThere are some reasons why the current diagnostic algorithms remain suboptimal. The algorithms have been developed by theoretical considerations that diastolic variables uniformly follow typical changes during the progression from normal to severe diastolic dysfunction in all patients , 2. HoweThe current diagnostic algorithms use discrete categorizations defined by cut-off points. These categorizations are easier for us to analyze and interpret than measured continuous variables themselves, but they cause a loss of information on between-subject variability. For example, two subjects between whom a diastolic variable differs greatly but with both values above the cut-off point will be graded similarly, while two subjects with a similar difference in a diastolic variable but with one value lying above and the other below the cut-off point will be categorized in different grades. Echocardiographic measurements of diastolic variables are subject to errors of 5–10% . This smCluster analysis captures the natural structure of multivariate data without a priori knowledge and it has been applied extensively in medical science, for example to identify clinical phenotypes , 21. ThiA previous study has already investigated the natural clustering of diastolic variables and successfully isolated a high-risk phenotype in a convenience sample of subjects predominantly with preserved LVEF . Our curThe learned clusters can be used for assessing new patients. Model-based cluster analysis, which we used in this study, will give the probability of membership for each cluster or distance from each cluster if we enter diastolic variables obtained from new patients into the learned model ; those cThere are several limitations. Firstly, because of the retrospective nature of this study, there were some patients in the HF database in whom all the diastolic variables were not measured. We excluded them from the study population to avoid imputation for cluster modeling. This exclusion may bias the results. Secondly, we did not include stress echocardiographic data in the cluster modeling. Previous studies have demonstrated that diastolic variables obtained using resting echocardiography were not sensitive enough to diagnose elevated left atrial pressure and diastolic stress test would improve the diagnosis , so currMachine learning allows echocardiographic diastolic function phenotyping that associates with HF biomarker and stratifies HF risk better than the current recommendations. The results of this study provide the basis for applying this data-driven approach for precise diagnosis and prognostication in HF, in order to formulate diagnostic recommendations that are based on evidence rather than consensus.The original contributions presented in the study are included in the article/HK and TU contributed to conception and design of the study, performed statistical analyses, interpreted results, and drafted the manuscript. HK, TU, LT, JC, SS, and YK constructed the database. AF helped revise the manuscript. All authors approved the final version of the manuscript.TU received a research funding from Hitachi. SS received a lecture fee from Daiichi-Sankyo and a research funding from Daiichi-Sankyo and Mitsubishi-Tanabe. TY has received a research funding from Daiichi-Sankyo, Bayer Healthcare, and Bristol Meyers Squibb and a remuneration from Daiichi-Sankyo, Pfizer, Bayer Healthcare, Bristol-Myers Squibb, Toa Eiyo, and Ono Pharmaceutical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Microalbuminuria is a well-characterized marker of kidney malfunction, both in diabetic and non-diabetic populations, and is used as a prognostic marker for cardiovascular morbidity and mortality. A few studies implied that it has the same value in kidney transplanted patients, but the information relies on spot or dipstick urine protein evaluations, rather than the gold standard of timed urine collection.Methods: We revisited a cohort of 286 kidney transplanted patients, several years after completing a meticulously timed urine collection and assessed the prevalence of major cardiovascular adverse events (MACE) in relation to albuminuria.Results: During a median follow up of 8.3 years (IQR 6.4–9.1) 144 outcome events occurred in 101 patients. By Kaplan-Meier analysis microalbuminuria was associated with increased rate of CV outcome or death (p = 0.03), and this was still significant after stratification according to propensity score quartiles (p = 0.048). Time dependent Cox proportional hazard analysis showed independent association between microalbuminuria and CV outcomes 2 years following microalbuminuria detection .Conclusions: Two years after documenting microalbuminuria in kidney transplanted patients, their CVD risk was increased. There is need for primary prevention strategies in this population and future studies should address the topic. Increased urine protein excretion is a validated risk factor for end stage kidney disease (ESKD), and cardiovascular morbidity and mortality –3. microFollowing kidney transplantation recipients become a unique chimera, in which the renal vasculature is different from that of the other organs. This is an interesting setting to explore the link between microalbuminuria and CVD, as the kidney endothelium, that facilitate most of the leakage of protein into the urine, represents the donor rather than the recipient. A paper published in 2007, was the first to describe in kidney transplanted patients the correlation between albuminuria, mortality and eventually graft loss, stating that its prognostic strength surpasses that of renal function . The larThe study cohort included adult kidney allograft recipients that participated in a study comparing the agreement between urine collection and albumin creatinine ratio for evaluation of urinary albumin excretion, termed UAE . Sixty-sUrine collection was evaluated once for each patient. Patients were asked to provide a 24 h urine collection and were instructed to accurately monitor the collection time. When the duration of the collection differed from 24 h, the urine albumin was divided by the collection exact duration and multiplied by 24 so urine albumin excretion ration (UAER) was expressed per 24 h. Exclusion criteria were an infectious disease, use of non-steroidal anti-inflammatory drugs or acute rejection during the 30 days before the collection. Blood pressure (BP) was measured on the morning following the urine collection; BP is the mean of 3 measurements, taken by a trained personal following 5 min of complete rest, using an electronic oscillometric device. Gender, age, body weight and height were also recorded. Blood was drawn from a peripheral vein for serum creatinine measurement. The urinary albumin concentration was determined by a solid-phase, competitive chemiluminesence enzyme immunoassay . We revisited this cohort, 5 years after it was created, to evaluate time dependent CVD risk in relation to microalbuminuria.The primary outcome was the composite of MACE and all-cause mortality. The secondary outcomes included death censored MACE and the separate CV outcomes; coronary artery disease (CAD), cerebrovascular disease, peripheral vascular disease (PVD) and CV mortality. All-cause mortality was specified as primary outcome since the exact cause of death is sometimes complex, and the contribution of CV disease might be significant even when the cause of death is attributed to other factors. In addition, including all-cause mortality in the composite outcome reduced the risk of bias by competing risks.CAD was defined as myocardial infarction, acute coronary syndrome and coronary artery revascularization percutaneously or by surgery. Cerebrovascular disease included cerebrovascular accident (CVA), transient ischemic attack (TIA), or carotid or cerebral revascularization, documented by emergency department referral or imaging. Peripheral vascular disease was defined as hospitalization due to peripheral ischemia, need for revascularization or need for amputation due to limb ischemia. Congestive heart failure (CHF) was defined according to echocardiogram evaluating new onset systolic heart function . Cardiovascular mortality was defined as mortality attributed to CVA, PVD, CAD, arrhythmia, or CHF.All outcomes were collected from the patients' electronic health records (EHR) that included complete reports of all hospitalizations during the study period. Study researcher (DB) evaluated all reports for outcome events, in case of any doubt another researcher (BRZ) evaluated the report and in case of disagreement third researcher (RR) decided between the different opinions.t-test. To describe non-normally distributed variables we used median and interquartile range, and Mann-Whitney to show differences between groups. Comparison of frequency distribution was estimated by the χ2 test.Data were analyzed using SPSS (version 25). For normally distributed variables results are expressed as mean and standard deviation (SD), and differences between the means of different groups were analyzed using standard We used propensity stratified (PS) analysis to overcome confounding caused by differences in baseline characteristics. Propensity score was used by performing a forward stepwise logistic regression model with microalbuminuria as outcome. Variables considered in the model were gender, systolic blood pressure, donor type (living or deceased), immunosuppressive drug, LDL cholesterol, blood creatinine, anti-hypertensive medications  and creatinine clearance.For survival analysis we used Kaplan-Meier survival curve with log rank test for significance level. For adjusted analysis we stratified the analysis according to PS quartile.We also used univariable and multivariable Cox proportional hazard model. The proportionality of hazard assumption was evaluated by examining the interaction between each variable and time. Multivariable analysis included traditional risk factors for CVD and albuminuria: age, gender, systolic blood pressure, LDL cholesterol, HbA1C, BMI, ACE I, or ARB use, blood creatinine and donor type.The proportional hazard assumption for albuminuria was rejected. As a result, we used time varying Cox analysis investigating the first 2 years and the rest of the follow up time separately. This time point was chosen because the Kaplan Meier curve showed different hazard ratios before and after 2 years following the urine collection. The proportional hazard assumption for albuminuria was valid when evaluated for each time period separately.For evaluation of subgroup interaction with the association between the exposure and the outcome, we used Cox analysis with microalbuminuria as time varying variable, and the interaction term between the subgroup and microalbuminuria and evaluated for significance of the interaction term.Between December 2007 and February 2012, 330 urine collections were performed of them 286 patients were included in the analysis, their characteristics are presented in The mean 24 h urinary albumin excretion was 48.9 ± 63.3 mg [median 23 mg interquartile range (IQR) 9–56 mg]. Microalbuminuria was present in 121 patients (42.5%) and was associated with higher systolic blood pressure, use of antihypertensive medications, hyperlipidemia, higher blood creatinine, higher BMI, a living donor, and the use of mTOR inhibitors. By multivariable analysis all these factors, in addition to gender, were associated with microalbuminuria and used to calculate the propensity score.Prevalence of primary renal disease was evaluated in both groups. However, since our institution serves as a tertiary referral center we rely on primary care physician investigation and diagnosis. We assume that glomerular disease, that tend to recur in the transplant, are usually diagnosed by biopsy. Other diseases such as PKD or diabetic nephropathy do not mandate invasive procedures unless diagnosis is unclear. There was no difference in the distribution of the different etiologies for renal failure between the groups . As a reSix patients (2.1%), of the 286 patients included in the cohort, were lost to follow up and hence excluded from the survival analysis.We calculated the propensity score for microalbuminuria using the variables described above. The area under the receiver operating characteristic (ROC) curve for this model was 0.79 (0.73–0.84). The ROC curve analysis and Box plot of the four quartiles according to microalbuminuria status are presented in p = 0.03, p = 0.048). By univariable time varying Cox proportional hazard analysis there was no association between microalbuminuria and CV outcomes during the first 2 years  but significant association appeared thereafter . The association between microalbuminuria and CV outcomes after 2 years was significant even after stratification according to PS quartiles . These results were not influenced by multivariable analysis for age, gender, systolic blood pressure, LDL cholesterol, HbA1C, BMI, blood creatinine, ACE I or ARB use and donor type , which are traditional risk factors for CVD and albuminuria.During median follow up time of 8.3 years (IQR 6.4–9.1) 144 outcome events occurred in 101 patients. The outcome events are described in the next section. By Kaplan-Meier analysis microalbuminuria was associated with increased rate of CV outcome or death , history of heart disease, hypertension, time from transplantation, living donor, and median age (56 years), respectively.Subgroup analysis for the main outcome of CV events and mortality is presented in p = 0.008, p = 0.045). This association became significant according to time varying analysis after 2 years from documentation of albuminuria, by simple and PS stratified analyses [ and ], respectively. It was still significant using multivariable analysis adjusted for widely accepted CV risk factors including gender, systolic blood pressure, LDL cholesterol, HbA1C, blood creatinine and donor type .Microalbuminuria was associated with increased risk for CV outcomes, without mortality, according to Kaplan-Meier curve  in the microalbuminuria group and 15 (9.1%) in the non-microalbuminuria group. By Cox model there was no difference in the hazard for CVA between the groups .In contrast, PVD occurred in 12 (9.9%) patients in the microalbuminuria group and 4 (2.4%) in the non-microalbuminuria group. Simple cox model revealed a significantly increased risk for PVD associated with microalbuminuria . However, after stratification according to PS quartiles the association was no longer significant .During follow up there were 42 events of all-cause mortality, 22 of them (18.6%) in the microalbuminuria group and 20 (12.4%) in the control group. There was no statistically significant association between microalbuminuria and mortality .We evaluated the association between microalbuminuria, as measured by accurate urine collection, and the composite outcome of CVD and all-cause mortality, following kidney transplantation. We found time varying association between microalbuminuria and CVD morbidity and mortality, with increased risk emerging around 2 years post documentation of albuminuria. The results were similar for the secondary outcome of CVD excluding non-cardiovascular death. The increased risk of CV events in the presence of albuminuria was driven mainly by CAD and PVD cases, while CVA incidence was similar between groups.Our results are in accordance with previous studies in various populations that showed an association between microalbuminuria and CVD. The first hint to this phenomena in kidney transplanted patients was observed was in a paper describing microalbuminuria as a cause of graft loss and death . A few yThe attenuated effect described by Weiner et al. might result from the use of ACR, which could be confounded by creatinine excretion, a measure affected by gender, BMI and age. This study also assessed incidence of CVD close to specimen collection, hence did not have the perspective of long-term follow-up.Attention should be given to other contributing factors and possible confounders that arise during analysis. In a recent paper by Rahamimov et al. BMI was associated with microalbuminuria by univariate logistic regression analysis, yet after multivariate analysis this relation lost significance. BMI was also associated with increased odds ratio [OR] for microalbuminuria , as wellMultivariate logistic regression analysis, in our cohort, showed that treatment with mTOR inhibitor, systolic blood pressure, serum creatinine, and BMI were associated with increased OR for microalbuminuria. BMI was still significantly associated with increased rate of urinary albumin excretion after introducing DM status into the model. The influence of adiposity on albuminuria, if it occurs, is expected to be time-related and to develop after prolonged exposure to an obese environment provided by the recipient. Risk of albuminuria was shown to correlate with high BMI 3 years following transplantation , howeverSeveral mechanistic explanations were suggested to elucidate in the late period, BMI is an independent predictor of albuminuria and microalbuminuria after adjustment, amongst others, for arterial pressure and the presence of DM. The association between microalbuminuria and cardiovascular risk. One of them poses albuminuria as a marker of diffuse atherosclerosis, a major cause for CVD in transplanted patients –15. As aOne possible contributory factor could be glomerular hyperfiltration. The solitary functioning kidney carries the metabolic burden alone, and more so in the presence of increased weight and BMI as seen in the MIA group. Among 9,515 healthy participants from the CARTaGENE trial , 473 hadOne reasonable pathway linking albuminuria with CVD could be endothelial dysfunction, that might link both phenomena. Endothelial dysfunction was characterized in diabetic patients, as well as the general population , by variThe reason for the time varying nature of this association is not clear and further studies are needed to answer this question. A possible explanation is that there is a different threshold of damage accumulation, needed for each manifestation. Common biological pathways can cause both microalbuminuria and CVD but at different time course, i.e., rapid development of microalbuminuria and slower for CVD. Since urine collection was performed chronologically soon after transplantation (median time of 2.8 years) this could be a reasonable interpretation. Longitudinal studies evaluating change in urine albumin excretion over time, and its association with cardiovascular risk, might shed some light on this important observation.Our study has several important strengths. First, for albuminuria evaluation, we used very accurate timed urine collection, in a research setting and under strict observation. This prevented the confounding effects of both adjustment to creatinine as mentioned above and imprecise collection that is very common in the clinical setting. Another advantage we employed was the use of EHR as a reliable information source to report cardiovascular events, and their evaluation by experienced physicians. The use of EHR also enabled detailed analysis of the different CV outcomes. Last, our cohort was followed for an extensive time period, enabling the discussion of causality between a known risk factor and disease progression. These characteristics are unique and provide both insight and strength to our findings, and reduce bias resulting from incomplete reporting.This study has also some limitations. First, our findings suggest different association for the various components of the secondary outcome. Unlike CAD and PVD that were associated with microalbuminuria this was not the case for CVA. Composite CV outcome are a common and powerful tool, but there is some difference in the pathophysiology of the different components and detailed analysis might be of value. These differences should be evaluated in larger studies and in other populations, in search for mechanistic distinction.Second, our small size population attenuates the study power. As accurate urine collection is cumbersome and time consuming, it is hard to use in large sample groups. Due to that, subgroup analysis was limited and valuable data regarding interactions between microalbuminuria and CVD could not be interpreted. Another limitation is that this is a single center study which might limit its external validity especially regarding non-Caucasians populations that were not represented in the analysis.Changes in GFR over time with progressive CKD, could account for the increase rate of MACEs rather than microalbuminuria. Unfortunately, serial GFR evaluations were no available for our cohort. However, a recently published evaluation of the effect of time dependent proteinuria on CVD found no independent association between serial GFR measurements and MACE .Of note, prevalence of primary renal disease was similar between groups, yet as a tertiary referral center, we rely on primary care physician evaluation and diagnosis and primary renal disease prevalence should be interpreted cautiously.Last, the interaction of CVD with time was not pre specified and was discovered when the proportionality assumption was evaluated before performing Cox analysis. Thus, this observation should be interpreted cautiously until verified by other studies. Nevertheless, the time varying nature might give important insights regarding the association of microalbuminuria and CVD, as a continuum of the same pathological process.According to our results, and studies evaluating other populations, microalbuminuria is an independent risk factor for CVD, and a marker of it –24. ChroFurther research is needed in order to extend our understanding of the association between albuminuria and CVD. These should rely on the association between urine albumin excretion using urine collection to verify our results. large scale studies are not expected due to the relative complexity of accurate timed urine collection, but even small series can be pooled together to generate statistical power. Another important aspect that should be explored is the dynamic of urine albumin excretion and its association with CVD. These kinds of studies are especially important due to the time varying nature of the association observed in our study. Furthermore, a mechanistic explanation should be sought to reveal the relation between albuminuria and different time points after kidney transplantation, by using urine exosome extraction technique. Since the origin of the endothall differ, from recipient vs. donor, this could be a non-invasive manor to assess pathology emergence.We show that microalbuminuria is associated with increased risk of CVD in kidney transplanted patients, 2 years after a timed urine collection documenting its appearance. Therefore, newly documented albuminuria after kidney transplantation should be considered risk equivalent for CVD.benayarz@gmail.com.The data analyzed in this study is subject to the following licenses/restrictions: deidentified database will be provided from the corresponding author upon a specified request. Requests to access these datasets should be directed to The studies involving human participants were reviewed and approved by Rabin Medical Center ethics committee approved the study. Informed consent was obtained from all participants and the study was conducted according to the declarations of Helsinki and Istanbul. The patients/participants provided their written informed consent to participate in this study.DB performed data collection, decision making regarding clinical outcome per patient, designed the figures, and wrote the manuscript with BR. RR, BZ, and LA-G performed research conduction and contributed to the final version of the manuscript. AC was involved in data collection and analysis of the baseline data. BR conceived the presented idea, performed the statistical analysis, designed the figures, and wrote the manuscript with DB. All authors discussed the results and contributed to the final manuscript.BR received consultation fee from Fresenius medical care and AstraZenca. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Compared to NBP, a graded and significant increase in the TAC metrics was observed starting from EBP and S1 and S2 HTN, using the new 2017 ACC/AHA guidelines . These differences remained consistent after being fully adjusted. Older age (>50 years), S1 and S2 HTN, prevalent diabetes, and chronic kidney disease (<60 mL/min/1.73 m2) are all independently contributing factors to higher TAC risk using multivariate stepwise logistic regressions . The optimal cutoff values of systolic blood pressure, diastolic blood pressure, and pulse pressure were 121, 74, and 45 mmHg, respectively, for the presence of TAC after excluding subjects with known CVD and ongoing HTN medication treatment. Our data showed that the presence of TAC starts at a stage of elevated blood pressure not categorized as HTN from the updated 2017 ACC/AHA hypertension guidelines.The recently revised 2017 American College of Cardiology/American Heart Association (ACC/AHA) hypertension (HTN) guidelines employ a lower blood pressure threshold to define HTN, aiming for earlier prevention of HTN-related cardiovascular diseases (CVD). Thoracic aortic calcification (TAC), a new surrogate marker of aging and aortic medial layer degeneration, and different stages of HTN, according to the 2017 ACC/AHA HTN guidelines, remain unknown. We classified 3022 consecutive asymptomatic individuals enrolled into four HTN categories using the revised 2017 ACC/AHA guidelines: normal blood pressure (NBP), elevated blood pressure (EBP), and stage 1 (S1) and stage 2 (S2) HTN. The coronary artery calcification score and TAC metrics (total Agaston TAC score, total plaque volume (mm Hypertension (HTN) is one of the most important cardiovascular risk factors, and accounts for approximately half of all cardiovascular disease (CVD) events worldwide . In 2017Recent studies have shown that thoracic aorta calcification (TAC) is a potent marker of age-related pathological degeneration in the great arteries, and a predictor of major cardiovascular disorders and non-cardiovascular mortality ,5,6,7,8.The findings of previous studies have suggested that Asian populations are more susceptible to hypertension-related CVD at early stages of the disease relative to other ethnic groups ,13. In tAs the correlation between TAC and the different levels of hypertension classified in the revised HTN guidelines has not been fully established, the objective of this study was to investigate the correlations between the TAC burden assessed by multi-detector computed tomography (MDCT) , blood pressure metrics ), and other cardiovascular risk factors in a large cohort of Asian patients with hypertension, according to the 2017 ACC/AHA guidelines [From January 2005 to December 2012, a total of 3120 consecutive subjects underwent health surveys and non-contrast-enhanced MDCT scan for assessment of the coronary artery calcium score in the health promotion and evaluation center, Mackay Memorial Hospital, Taipei, Taiwan. Of these patients, 3022  who had complete clinical and MDCT data were enrolled in this study. The clinical and CT data were analyzed retrospectively and de-identified prior to author access and analysis. The study was approved by the Institutional Research Ethics Board (IRB) of MacKay Memorial Hospital in Taipei, Taiwan (17MMHIS082e), and the requirement for written patient consent was waived by the IRB.The enrolled subjects were divided into four study groups according to their blood pressure measurements and the 2017 ACC/AHA HTN guidelines: (1) normal blood pressure (NBP), defined as SBP less than 120 mmHg and DBP less than 80 mmHg; (2) pre-clinical stage of HTN as elevated blood pressure (EBP), defined as SBP between 120 and 129 mmHg and DBP less than 80 mmHg; (3) stage 1 hypertension (S1 HTN), defined as SBP between 130 and 139 mmHg or DBP between 80 and 89 mmHg; and (4) stage 2 hypertension (S2 HTN), defined as an SBP greater than or equal to 140 mmHg or DBP greater than or equal to 90 mmHg, or with a known history of hypertension. Hypertension medication use referred to the use of renin–angiotensin system (RAS) inhibitors, calcium channel blockers, alpha- or beta-blockers, and diuretics prescribed by physicians aiming for treatment of hypertension.In comparison, the four categories of hypertension defined in the 2018 ESH/ESC guidelines for the management of arterial hypertension  were as The baseline characteristics and biochemical data, including age, sex, body mass index (BMI), body fat composition, waist–hip ratio (WHR), and lipid profiles, including total cholesterol, triglycerides, LDL cholesterol, HDL cholesterol, estimated glomerular filtration rate (eGFR), high-sensitivity C-reactive protein (hs-CRP), and homocysteine level were collected. A thorough review of the subject’s health history, including the use of dyslipidemia medication, known CVD (such as stroke or coronary artery disease), diabetes, and smoking habits, was also conducted via detailed questionnaires. Resting blood pressure was measured using a standardized sphygmomanometer by the medical staff, who were blinded to the other test results. 70% of the R–R interval. Transaxial images were reconstructed from the scan data with a standard image reconstruction kernel at 3 mm slice thickness without overlapping and with a 25 cm display field of view. All image analyses were performed on a dedicated workstation . The Agatston score, volume score (mm3), and density score (HU) were measured to quantify arterial calcification and for coronary artery calcification (CAC) (using the Agatston score). TAC in the ascending or descending aorta was defined as a region covering at least four contiguous pixels with an average intensity greater than 130 Hounsfield units (HU) [3) and TAC mean density  were also demonstrated  with 16 × 0.75 mm collimation, a 420 ms gantry rotation period, and 120 kV tube voltage. Transaxial images were acquired from the point above the level of the tracheal bifurcation to the point below the base of the heart in a single breath-hold using prospective electrocardiogram triggering, with the center of the acquisition window set at nstrated .n = 237) and known CVD (n = 133) from analysis.Continuous variables were expressed as mean ± standard deviation (SD), and categorical data were presented as numbers and percentages. All statistical analyses were performed using the IBM SPSS Statistics software version 22 . The between-group differences were assessed using analysis of variance and the chi-squared test. The correlations between the TAC burden and BP components (as continuous variables) were assessed by calculating the Pearson product–moment correlation coefficient. The chi-squared test and logistic regression were used to establish the risk of TAC (odds ratio (OR) and 95% confidence interval (CI)) associated with the BP components. A multivariate, forward, stepwise logistic regression analysis was used to explore the association between BP and TAC severity. A general linear model was used to analyze the effects of multiple variables and to obtain the adjusted estimation of various TAC measures (presented as mean ± standard error) without assuming that the response is normally distributed, according to the 2017 ACC/AHA HTN guidelines. A sensitivity analysis was conducted by excluding the subjects with an ongoing use of HTN medications  in the presence of TAC as an outcome measure were examined. Analysis was conducted by using the area under the receiver operating characteristic (ROC) curves to define the optimal cutoffs from various BP components  to identify the presence of TAC by the maximal Youden index (largest summation of sensitivity and specificity). A sensitivity analysis was also conducted by excluding those with an ongoing HTN treatment and those with known CVD.The detailed clinical characteristics and baseline biochemical data are summarized in r = 0.28, 0.30, and 0.33, respectively; all p < 0.001). The individuals with TAC were also more likely to have CAC (OR = 7.03 (95% CI: 5.69–8.68), p < 0.001), which remained significant after full adjustment (adjusted OR = 3.47 (95% CI: 2.70–4.44), p < 0.001). The TAC score, volume, and mean density showed a graded and significant increase across different HTN stages/grades defined by the 2017 ACC/AHA HTN and the 2018 ESC/ESH HTN guidelines, even after full adjustment (n = 2784) in our sensitivity analysis , and PP  were independently associated with a higher TAC burden by three different TAC measures in multivariate regression analysis, although only the TAC mean density was significantly associated with DBP in the adjusted model . Older age (>50 years), higher blood pressure (including ACC/AHA-defined stage 1 and stage 2 HTN), prevalent diabetes, and chronic kidney disease (CKD) were likely the main determinants of TAC development. Male sex, age more than 50 years, BMI > 25 kg/m2, higher blood pressure (including ACC/AHA-defined S1 and S2 HTN), and diabetes were statistically independent predictors of CAC  of 0.65 and a cutoff value of 129 mmHg (54.52% sensitivity and 69.01% specificity). The ROC analysis of DBP revealed an AUC of 0.56 and a cutoff value of 71 mmHg (69.84% sensitivity and 40.51% specificity). The ROC analysis of PP revealed an AUC of 0.64 and a cutoff value of 44 mmHg (69.14% sensitivity and 51.60% specificity). The SBP, DBP, and PP were set at 128, 74, and 49 mmHg, respectively. The sensitivity analysis showed that the SBP, DBP, and PP at the optimal cutoff thresholds  had the largest area under the ROC curve for identifying the presence of TAC after eliminating the subjects with known CVD and ongoing use of HTN medications . The relationship between each higher blood pressure component and the likelihood of TAC, after excluding known CVD and consumption of HTN medications, signified the importance of hypertension on the development of TAC at relatively lower blood pressure levels .Our findings suggest that advanced age, hypertension, and prevalent diabetes are strongly correlated with calcification in the aorta and coronary arteries. Individuals who were traditionally classified in the elevated blood pressure category (SBP range: 130–139 mmHg), but not classified as hypertensive, according to the updated ACC/AHA guidelines were associated with a higher TAC score than coronary calcification burden after detailed adjustment. Our findings on the presence of TAC as highly specific for early-stage HTN support the 2017 ACC/AHA HTN guidelines for lowering the target threshold of HTN management.The results of the multi-ethnic study of atherosclerosis and the Heinz Nixdorf Recall study ,11 colleA previous study showed that a higher arterial afterload was independently correlated with TAC . Other eFollowing the SPRINT trial ,36, the This study had several limitations. First, our study was cross-sectional; therefore, we were unable to infer causality or determine the causal effects of blood pressure on aortic calcification. Additional longitudinal studies are needed to discern the temporal nature of these events. Second, information regarding the exact time point of hypertension onset and some clinical hypertension subgroups, such as those with masked hypertension or morning surge in blood pressure, were missing in our study samples. Hence, a prospective study may be needed to further elucidate the relationship between hypertension and TAC. Third, as greater TAC burden likely reflects increasing cardiovacular co-morbid conditions and positively correlates with higher blood pressure  , the sen2) were all associated with the development of TAC. Furthermore, TAC may begin to develop in the pre-clinical stage of HTN, which highlights the importance of early diagnosis of and intervention for arterial hypertension in patients at high risk.In summary, we demonstrated a significant association between the TAC and HTN stages defined in the 2017 ACC/AHA guidelines in a large, asymptomatic Asian population. We also identified that advanced age (>50 years), HTN, diabetes, and CKD (eGFR <60 mL/min/1.73 m


Excessive intake of fructose increases serum uric acid concentration. Hyperuricemia induces a negative effect on atherosclerosis and inflammation. Hyperuricemia is common in patients with arterial hypertension. Several antihypertensive drugs including diuretics increase serum uric acid concentration. In contrast, the angiotensin II receptor antagonist (ARB) losartan was found to lower serum uric acid though it may increase renal excretion while other ARBs showed mostly a neutral effect. In this study, effects of two AT1 receptor antagonists losartan and eprosartan on serum uric acid changes induced by oral fructose load were directly compared.  The randomized, crossover, head-to-head comparative study comprised 16 ambulatory patients (mean age 64.5 ± 9.8 years). The patients fulfilled AHA/NHLBI 2005 criteria of metabolic syndrome. A daily single morning dose of each study drug (50 mg of losartan or 600 mg of eprosartan) was given during two 3-month periods in a random order separated by 2-week washout time. The oral fructose tolerance test (OFTT) was performed at baseline and after each two 3-onth treatment periods. Before and during OFTT, urine excretion of uric acid and creatinine was assessed in the first morning portion of urine. Blood samples for the measurement of serum uric acid and lipids were taken at baseline and 30, 60, and 120 minutes after oral intake of 75 g of fructose.  After 3-month treatment with eprosartan and losartan, both systolic and diastolic blood pressure decreased significantly and to a similar extent. After the treatment, serum uric acid and its baseline and postfructose urine excretion were unchanged. No significant changes of plasma lipids before and after OFTT were observed throughout the study. NCT04954560. The study showed that in patients with hypertension and metabolic syndrome, both losartan and eprosartan have a neutral effect on fasting and postfructose load serum uric acid concentration and its urinary excretion. This trial is registered with  Hyperuricemia is seen in about 20% of adults in the general population  and is mOn the one hand, high uric acid concentration may be an important link in the pathogenesis of hypertension, but on the other hand, in mild and moderate hypertension, uric acid excretion is frequently impaired . A studySeveral studies showed that the prevalence of hyperuricemia in patients with hypertension is much higher than that in the general population and may worsen after the onset of antihypertensive treatment . That maThe uricosuric effect of losartan is most likely due to overlapping two different mechanisms regulating the excretion of uric acid. Losartan may increase uric acid tubular secretion in the same way as other inhibitors of the renin-angiotensin-aldosterone system, but in addition, it may specifically inhibit postsecretory resorption of uric acid in the proximal tubule. The effect may be due to a specific structure of the losartan molecule . The uraAn increased accessibility of the high-calorie food contributes to the worldwide epidemic of the metabolic syndrome. The rapidly increasing rate of obesity and metabolic syndrome may be partly related to an excessive consumption of fructose added to sweetened beverages and food –16. FrucThe aim of our study was to directly compare the effect of two AT1 receptor antagonists, losartan and eprosartan, on serum uric acid changes stimulated by an oral fructose load.2; chronic liver disease; acute infection; psychiatric disorders; mean serum potassium concentration at the last three measurements < 4.0 mmol/l, or aspartate aminotransferase or alanine aminotransferase or creatinine kinase > ×1.5 upper range limit. Seven patients had diabetes mellitus of which 4 were treated with insulin. Twelve patients were receiving metformin. Waist circumference was measured on the initial visit. Plasma lipids and blood glucose were measured in a fasting state during the study.The study group included 16 patients . The patients selected for the study fulfilled the AHA/NHLBI 2005 criteria of the metabolic syndrome  and ESC/The study was designed as a randomized, crossover, head-to-head comparative study. Randomization was carried out using an MS Excel random number generator. After qualification, each patient was randomly assigned to receive either losartan  or eprosartan . The patients were taking all other previously prescribed drugs in unmodified doses during the whole course of the study. Each study drug was given in a random order as a single morning dose (50 mg of losartan or 600 mg of eprosartan) for two periods each lasting 3 months separated by 2-week washout time.22H23CIN6O) is approximately 33% orally bioavailable and has a Tmax of 1 hour, and its active metabolite has a Tmax of 3-4 hours. The terminal elimination half-life of losartan is 1.5-2.5 hours while the active metabolite has a half-life of 6-9 hours [Losartan (C-9 hours .23H24N2O4S) has an absolute bioavailability after a single 300 mg oral dose of 13%. Food delays absorption of the drug. Eprosartan is not metabolized by the cytochrome P450 system and is eliminated as unchanged drug. Less than 2% of an oral dose is excreted in the urine. The terminal elimination half-life of eprosartan following oral administration is 5 to 9 hours [Eprosartan . Subsequent blood samples were taken three times during each OFTT, i.e., after 30, 60, and 120 minutes from its start to determine serum uric acid concentration. In addition, peripheral blood pressure was measured before the collection of each blood sample. After 120 minutes, blood was also taken to assess plasma lipids. The second timed 2-hour urine collection was obtained during OFTT. The same procedures were repeated after each treatment period. The patients took all their prescribed medication including the study drug in the morning 120 minutes before the beginning of OFTT.Routine automated laboratory tests were used to assess blood and urine parameters. Blood pressure was taken in a sitting position with the aneroid sphygmomanometer. Blood pressure was measured both at baseline and after 3-month therapy with each study drug. The mean from four measurements obtained between 0 and 120 minutes of OFTT was taken for the analysis. Blood pressure was measured by a designated single member of the staff. Mean blood pressure (MAP) was calculated for all measurements as diastolic BP + 1/3 of pulse pressure (systolic BP–diastolic BP).p < 0.05. The within-group comparisons were analyzed using one-way ANOVA and t-test for normally distributed variables or alternatively with the nonparametric Wilcoxon test. The normality of the variable distribution was checked with the Shapiro-Wilk test. The Pearson or Spearman correlation coefficient was used to assess the relations between variables depending on their distribution. The area under the curve (AUC) of serum uric acid during oral fructose tolerance test was calculated using the trapezoidal rule.The results are expressed as mean ± SD or median with interquartile range depending on each variable distribution. 95% confidence intervals were calculated for the changes of the parameters caused by the treatment. Statistical significance was defined at Twenty-two patients were recruited to the study; after screening, 6 patients did not complete the study procedure and therefore were not included in the final per-protocol data analysis; in total, 16 patients were included. All dropouts were due to gastrointestinal intolerance of oral fructose. No side effects of the study drugs were observed. Baseline clinical characteristics of the study population are presented in Systolic, diastolic, and mean blood pressure decreased significantly and to a similar extent from baseline after 3 months of eprosartan and losartan administration. No significant changes of blood glucose and serum creatinine were observed throughout the study. p < 0.001 in both study periods). Serum uric acid increased significantly during OFTT after the therapy with either losartan or eprosartan  on serum uric acid –25. WhilAlthough some research demonstrated an increased urinary uric acid excretion and a decrease in serum uric acid during losartan therapy, there is only a scarce evidence from head-to-head studies in which the effect of the drug was compared to that of other ARBs in the patients with arterial hypertension , 27, 28.Unlike our study, all previous studies investigated only the effect of losartan on a fasting serum level of uric acid but did not assess the effect of this drug on the changes of serum uric acid induced by dietary stimuli. That was also the case in the study  which coβ-blocker, or diuretic which may have a weak uricosuric activity [Our study was designed to address the uncertainty around the effects of different ARBs on uricemia. The crossover design of the study allowed a direct comparison of the effect of both drugs in the same subject and in the same condition . It is oactivity , 31, 32.Schmidt et al.  showed tThree months of treatment with eprosartan or losartan led to an expected significant decrease in arterial pressure. It should be noted that our patients had a well-controlled blood pressure already at the beginning of the study, so the addition of further antihypertensive drug only had a small effect on blood pressure.Our study demonstrated that losartan did not specifically affect serum concentration and urinary excretion of uric acid, as well as the magnitude of the changes of serum uric acid concentration after the oral fructose load. Therefore, we were not able to confirm the usefulness of losartan compared to other ARBs in the treatment of arterial hypertension in the patients with metabolic syndrome.