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The Potential of Cardiac Biomarkers, NT-ProBNP and Troponin T, in Predicting the Progression of Nephropathy in Diabetic Patients: A Meta-Analysis of Prospective Cohort Studies
Abstract
Aims:
A meta-analysis was done to investigate the association of two cardiac biomarkers of N-terminal prohormone of B-type natriuretic peptide (NT-proBNP) and circulating troponin T (TnT) with the progression of diabetic nephropathy (DN).
Methods:
A thorough search of the PubMed, Scopus, and Web of Science databases was done until June 2022. The outcome (progression of DN) was described as either of the followings: a) eGFR decline, b) albuminuria, c) end-stage renal disease, or d) mortality. A pooled analysis of eligible studies was performed using random-effect models to compensate for the differences in measurement standards between the studies. We further carried out subgroup analyses to examine our results' robustness and find the source of heterogeneity. A sensitivity analysis was performed to assess the influence of individual studies on the pooled result and the funnel plot and Egger's test were used to assess publication bias.
Results:
For NT-proBNP, 8741 participants from 14 prospective cohorts, and for TnT, 7292 participants from 9 prospective cohorts were included in the meta-analysis. Higher NT-proBNP levels in diabetic patients were associated with a higher probability of DN progression (relative risk [RR]: 1.67, 95% confidence interval [CI]: 1.44 to 1.92). Likewise, elevated levels of TnT were associated with an increased likelihood of DN (RR: 1.57, 95% CI: 1.34 to 1.83). The predictive power of both biomarkers for DN remained significant when the subgroup analyses were performed. The risk estimates were sensitive to none of the studies. The funnel plot and Egger's tests indicated publication bias for both biomarkers. Hence, trim and fill analysis was performed to compensate for this putative bias and the results remained significant both for NT-proBNP (RR: 1.50, 95% CI: 1.31 to 1.79) and TnT (RR: 1.35, 95% CI 1.15 to 1.60).
Conclusions:
The increased blood levels of TnT and NT-proBNP can be considered as predictors of DN progression in diabetic individuals. PROSPERO registration code: CRD42022350491.
... The advantages of meta-analyses are not limited to better estimates or increased statistical power; their most basic advantage is the acceptability of assessing the generalizability of discoveries made in individual studies. While meta-analyses are well-established tools for integrating clinical studies in medicine 33,34 , they are rapidly gaining traction in areas where new information is beginning to accumulate, such as metabolomic analyses. Notably, the joining analysis of information from distinct sources also works at the level of methods. ...
Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease’s underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ − 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.
Background
Chronic low-grade inflammation is considered one of the major mechanisms for the progression of diabetic kidney disease. We investigated the prognostic value of circulating soluble tumor necrosis factor receptor 2 (sTNFR2) for early nephropathy in patients with type 2 diabetes.
Materials and methods
A total of 364 patients with type 2 diabetes and an estimated glomerular filtration rate (eGFR) ≥30 mL/min/1.73m² were followed up for a median of 4 years. Renal outcomes were defined as a composite of either or both a >30% decline in the eGFR and/or albuminuria stage progression determined with consecutive tests.
Results
Seventy-three patients developed renal composite events. Serum concentrations of sTNFR2 were strongly associated with the risk of renal function decline and progressive changes in albuminuria. Through a receiver operating characteristic curve analysis, a serum sTNFR2 level of 1.608 ng/mL was adopted as the discriminator value for predicting renal outcomes (area under the curve 0.63, 95% confidence interval 0.57–0.70, p < 0.001), yielding a sensitivity of 75.3% and a specificity of 51.2%. The association of sTNFR2 levels ≥1.608 ng/mL to renal outcomes was significant after adjusting for relevant variables (hazard ratio 2.27, 95% confidence interval 1.23–4.20, p = 0.009) and remained consistent across subgroups stratified by age, sex, systolic blood pressure, eGFR, albuminuria, and the use of renin-angiotensin system blockers.
Conclusions
Higher circulating levels of sTNFR2 are independently associated with an eGFR decline and progressive albuminuria in patients with type 2 diabetes.
Background
Despite major advances in the treatment of diabetic nephropathy (DN) in recent years, it remains the most common cause of end-stage renal disease. An early diagnosis and therapy may slow down the DN progression. Numerous potential biomarkers are currently being researched. Circulating levels of the kidney-released exosomes and biological molecules, which reflect the DN pathology including glomerular and tubular dysfunction as well as mesangial expansion and fibrosis, have shown the potential for predicting the occurrence and progression of DN. Moreover, many experimental therapies are currently being investigated, including stem cell therapy and medications targeting inflammatory, oxidant, or pro-fibrotic pathways activated during the DN progression. The therapeutic potential of stem cells is partly depending on their secretory capacity, particularly exosomal microRNAs (Exo-miRs). In recent years, a growing line of research has shown the participation of Exo-miRs in the pathophysiological processes of DN, which may provide effective therapeutic and biomarker tools for DN treatment.
Methods
A systematic literature search was performed in MEDLINE, Scopus, and Google Scholar to collect published findings regarding therapeutic stem cell-derived Exo-miRs for DN treatment as well as circulating Exo-miRs as potential DN-associated biomarkers.
Findings
Glomerular mesangial cells and podocytes are the most important culprits in the pathogenesis of DN and, thus, can be considered valuable therapeutic targets. Preclinical investigations have shown that stem cell-derived exosomes can exert beneficial effects in DN by transferring renoprotective miRs to the injured mesangial cells and podocytes. Of note, renoprotective Exo-miR-125a secreted by adipose-derived mesenchymal stem cells can improve the injured mesangial cells, while renoprotective Exo-miRs secreted by adipose-derived stem cells (Exo-miR-486 and Exo-miR-215-5p), human urine‐derived stem cells (Exo-miR-16-5p), and bone marrow-derived mesenchymal stem cells (Exo-miR-let-7a) can improve the injured podocytes. On the other hand, clinical investigations have indicated that circulating Exo-miRs isolated from urine or serum hold great potential as promising biomarkers in DN.
Background
Diabetic nephropathy (DN) is the major complication of diabetes mellitus, and leading cause of end-stage renal disease. The underlying molecular mechanism of DN is not yet completely clear. The aim of this study was to analyze a DN microarray dataset using weighted gene co-expression network analysis (WGCNA) algorithm for better understanding of DN pathogenesis and exploring key genes in the disease progression.
Methods
The identified differentially expressed genes (DEGs) in DN dataset GSE47183 were introduced to WGCNA algorithm to construct co-expression modules. STRING database was used for construction of Protein-protein interaction (PPI) networks of the genes in all modules and the hub genes were identified considering both the degree centrality in the PPI networks and the ranked lists of weighted networks. Gene ontology and Reactome pathway enrichment analyses were performed on each module to understand their involvement in the biological processes and pathways. Following validation of the hub genes in another DN dataset (GSE96804), their up-stream regulators, including microRNAs and transcription factors were predicted and a regulatory network comprising of all these molecules was constructed.
Results
After normalization and analysis of the dataset, 2475 significant DEGs were identified and clustered into six different co-expression modules by WGCNA algorithm. Then, DEGs of each module were subjected to functional enrichment analyses and PPI network constructions. Metabolic processes, cell cycle control, and apoptosis were among the top enriched terms. In the next step, 23 hub genes were identified among the modules in genes and five of them, including FN1, SLC2A2, FABP1, EHHADH and PIPOX were validated in another DN dataset. In the regulatory network, FN1 was the most affected hub gene and mir-27a and REAL were recognized as two main upstream-regulators of the hub genes.
Conclusions
The identified hub genes from the hearts of co-expression modules could widen our understanding of the DN development and might be of targets of future investigations, exploring their therapeutic potentials for treatment of this complicated disease.
IntroductionPeople with advanced diabetic nephropathy (DN) are at high risk for development of end-stage renal disease (ESRD) or death. Whether renin-angiotensin system inhibitors and some concomitant drugs could still continue to delay the onset of ESRD in the later stage of DN needs to be clarified. This study aimed to evaluate the relationship of the therapeutic methods as well as clinicopathologic variables with prognosis of patients with biopsy-proven DN during stage 4 of chronic kidney disease (CKD).Methods
Forty-six DN patients who underwent renal biopsy in stage 4 CKD were enrolled from January 1, 2002, to December 31, 2019. Clinical data were abstracted retrospectively from the time of renal biopsy. Follow-up data were collected until April 1, 2020, or from the day of renal biopsy to either the occurrence of ESRD or death. The primary outcome was the composite of ESRD or death. Treatment effectiveness and the prognostic ability of clinicopathologic data were evaluated using multivariate Cox regression analyses.ResultsThe median renal survival duration was 17.3 (95% confidence interval, 7.4–27.3 months). Primary endpoint events occurred in 29 individuals (63.0%) during follow-up, including 24 who reached ESRD and 5 who died before progression to ESRD. None of the clinicopathologic data, including pathologic cass of DN, were statistically independent prognostic factors for renal survival. Conventional therapies, such as use of renin-angiotensin system (RAS) inhibitors, a level of glycated hemoglobin (HbA1c) < 7%, and blood pressure < 130/80 mmHg, were also not statistically different between the stable and progressive groups.Conclusion
Specific therapies including targeting blood pressure < 130/80 mmHg, HbA1c concentration < 7%, and use of RAS inhibitors could not effectively delay the onset of ESRD in the later stage of DN. Therefore, efforts to slow the progression of DN should focus on early diagnosis and treatment.
Rationale & Objective
Identification of novel risk factors for chronic kidney disease (CKD) progression may inform mechanistic investigations and improve identification of high-risk subgroups. The current study aimed to characterize CKD progression across levels of numerous risk factors and to identify independent risk factors for CKD progression among those with and without diabetes.
Study Design
The Chronic Renal Insufficiency Cohort (CRIC) Study is a prospective cohort study of adults with CKD conducted at seven US clinical centers.
Setting & Participants
Participants (N=3379) had up to 12.3 years of follow-up; 47% had diabetes.
Predictors
Thirty risk factors for CKD progression across sociodemographic, behavioral, clinical and biochemical domains at baseline.
Outcomes
Study outcomes were estimated glomerular filtration rate (eGFR) slope and the composite of halving of eGFR or initiation of kidney replacement therapy (KRT).
Analytical Approach
Stepwise selection of independent risk factors was performed stratified by diabetes status using linear mixed effects and Cox proportional hazards models.
Results
Among those without and with diabetes, respectively, the mean (SD) eGFR slope was -1.4 (3.3) and -2.7 (4.7) mL/min/1.73m²/year. Among participants with diabetes, multivariable-adjusted hazard of the composite outcome was approximately twofold or greater with higher levels of the inflammatory chemokine CXCL12, the cardiac marker N-terminal pro-B-type natriuretic peptide (NTproBNP) and the kidney injury marker urine neutrophil gelatinase-associated lipocalin (NGAL). Among those without diabetes, low serum bicarbonate as well as higher high-sensitivity troponin T, NTproBNP and urine NGAL were all significantly associated with a 1.5-fold or greater rate of the composite outcome.
Limitations
The observational study design precludes causal inference.
Conclusions
Strong associations for cardiac markers, plasma CXCL12 and urine NGAL exceeded that of systolic blood pressure ≥140 mmHg, a well-established risk factor for CKD progression. This warrants further investigation into the potential mechanisms these markers indicate and opportunities to use them to improve risk stratification.
Diabetic nephropathy (DN) is a major healthcare challenge. It occurs in up to 50% of those living with diabetes, is a major cause of end-stage kidney disease (ESKD) that requires treatment with dialysis or renal transplantation, and is associated with significantly increased cardiovascular morbidity and mortality. DN is a clinical syndrome characterized by persistent albuminuria and a progressive decline in renal function, but it is increasingly recognized that the presentation and clinical course of kidney disease in diabetes is heterogeneous. The term diabetic kidney disease (DKD) is now commonly used to encompass the spectrum of people with diabetes who have either albuminuria or reductions in renal function. In this article, the clinical presentation and approach to diagnosis of DKD will be discussed, as will its prognosis. The general principles of management of DKD will also be reviewed with reference to current international guidelines.
Background:
Diabetic kidney disease (DKD) is the most common cause of the end-stage renal disease (ESRD). Regardless of intensive treatments with hyperglycemic control, blood pressure control, and the use of renin-angiotensin system blockades, the prevalence of DKD remains high. Recent studies suggest that the spectrum of DKD has been changed and many progresses have been made to develop new treatments for DKD. Therefore, it is time to perform a systemic review on the new developments in the field of DKD.
Summary:
Although the classic clinical presentation of DKD is characterized by a slow progression from microalbuminuria to macroalbuminuria and by a hyperfiltration at the early stage and progressive decline of renal function at the late stage, recent epidemiological studies suggest that DKD patients have a variety of clinical presentations and progression rates to ESRD. Some DKD patients have a decline in renal function without albuminuria but display prominent vascular and interstitial fibrosis on renal histology. DKD patients are more susceptible to acute kidney injury, which might contribute to the interstitial fibrosis. A large portion of type 2 diabetic patients with albuminuria could have overlapping nondiabetic glomerular disease, and therefore, kidney biopsy is required for differential diagnosis for these patients. Only a small portion of DKD patients eventually progress to end-stage renal failure. However, we do not have sensitive and specific biomarkers to identify these high-risk patients. Genetic factors that have a strong association with DKD progression have not been identified yet. A combination of circulating tumor necrosis factor receptor (TNFR)1, TNFR2, and kidney injury molecular 1 provides predictive value for DKD progression. Artificial intelligence could enhance the predictive values for DKD progression by combining the clinical parameters and biological markers. Sodium-glucose co-transporter-2 inhibitors should be added to the new standard care of DKD patients. Several promising new drugs are in clinical trials.
Key messages:
Over last years, our understanding of DKD has been much improved and new treatments to halt the progression of DKD are coming. However, better diagnostic tools, predictive markers, and treatment options are still urgently needed to help us to better manage these patients with this detrimental disease.
Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD) worldwide. Renin-angiotensin-aldosterone system (RAAS) inhibitors and sodium-glucose co-transporter 2 (SGLT2) inhibitors have shown efficacy in reducing the risk of ESRD. However, patients vary in their response to RAAS blockades, and the pharmacodynamic responses to SGLT2 inhibitors decline with increasing severity of renal impairment. Thus, effective therapy for DKD is yet unmet. Transforming growth factor-β1 (TGF-β1), expressed by nearly all kidney cell types and infiltrating leukocytes and macrophages, is a pleiotropic cytokine involved in angiogenesis, immunomodulation, and extracellular matrix (ECM) formation. An overactive TGF-β1 signaling pathway has been implicated as a critical profibrotic factor in the progression of chronic kidney disease in human DKD. In animal studies, TGF-β1 neutralizing antibodies and TGF-β1 signaling inhibitors were effective in ameliorating renal fibrosis in DKD. Conversely, a clinical study of TGF-β1 neutralizing antibodies failed to demonstrate renal efficacy in DKD. However, overexpression of latent TGF-β1 led to anti-inflammatory and anti-fibrosis effects in non-DKD. This evidence implied that complete blocking of TGF-β1 signaling abolished its multiple physiological functions, which are highly associated with undesirable adverse events. Ideal strategies for DKD therapy would be either specific and selective inhibition of the profibrotic-related TGF-β1 pathway or blocking conversion of latent TGF-β1 to active TGF-β1.
Background:
Identifying patients at high risk of diabetic kidney disease (DKD) helps improve clinical outcome.
Purpose:
To establish a model for predicting DKD.
Data sources:
The derivation cohort was from a meta-analysis. The validation cohort was from a Chinese cohort.
Study selection:
Cohort studies that reported risk factors of DKD with their corresponding risk ratios (RRs) in patients with type 2 diabetes were selected. All patients had estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 and urinary albumin-to-creatinine ratio (UACR) <30 mg/g at baseline.
Data extraction:
Risk factors and their corresponding RRs were extracted. Only risk factors with statistical significance were included in our DKD risk prediction model.
Data synthesis:
Twenty cohorts including 41,271 patients with type 2 diabetes were included in our meta-analysis. Age, BMI, smoking, diabetic retinopathy, hemoglobin A1c, systolic blood pressure, HDL cholesterol, triglycerides, UACR, and eGFR were statistically significant. All these risk factors were included in the model except eGFR because of the significant heterogeneity among studies. All risk factors were scored according to their weightings, and the highest score was 37.0. The model was validated in an external cohort with a median follow-up of 2.9 years. A cutoff value of 16 was selected with a sensitivity of 0.847 and a specificity of 0.677.
Limitations:
There was huge heterogeneity among studies involving eGFR. More evidence is needed to power it as a risk factor of DKD.
Conclusions:
The DKD risk prediction model consisting of nine risk factors established in this study is a simple tool for detecting patients at high risk of DKD.
Aims/hypothesis
As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts.
Methods
We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min⁻¹ [1.73 m]⁻². A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function.
Results
Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets.
Conclusions/interpretation
Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min⁻¹ [1.73 m]⁻² in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.
Aims/hypothesis:
We investigated whether biochemical cardiovascular risk factors and/or markers of subclinical cardiovascular disease were associated with the development of reduced renal function in people with type 2 diabetes.
Methods:
A cohort of 1066 Scottish men and women aged 60-74 years with type 2 diabetes from the Edinburgh Type 2 Diabetes Study were followed up for a median of 6.7 years. New-onset reduced renal function was defined as two eGFRs <60 ml(-1) min(-1) (1.73 m)(-2) at least 3 months apart with a > 25% decline from baseline eGFR. Ankle brachial pressure index (ABI), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT) were measured at baseline. Pulse wave velocity (PWV) and carotid intima media thickness were measured 1 year into follow-up. Data were analysed using Cox proportional hazards models.
Results:
A total of 119 participants developed reduced renal function during follow-up. ABI, PWV, NT-proBNP and hsTnT were all associated with onset of decline in renal function following adjustment for age and sex. These associations were attenuated after adjustment for additional diabetes renal disease risk factors (systolic BP, baseline eGFR, albumin:creatinine ratio and smoking pack-years), with the exception of hsTnT which remained independently associated (HR 1.51 [95% CI 1.22, 1.87]). Inclusion of hsTnT in a predictive model improved the continuous net reclassification index by 0.165 (0.008, 0.286).
Conclusions/interpretation:
Our findings demonstrate an association between hsTnT, a marker of subclinical cardiac ischaemia, and subsequent renal function decline. Further research is required to establish the predictive value of hsTnT and response to intervention.
Biomarkers of diverse pathophysiologic mechanisms may improve risk stratification for incident or progressive diabetic kidney disease (DKD) in persons with type 2 diabetes. To evaluate such biomarkers, we performed a nested case-control study (n=190 cases of incident DKD and 190 matched controls) and a prospective cohort study (n=1156) using banked baseline plasma samples from participants of randomized, controlled trials of early (ACCORD) and advanced (VA NEPHRON-D) DKD. We assessed the association and discrimination obtained with baseline levels of plasma TNF receptor-1 (TNFR-1), TNFR-2, and kidney injury molecule-1 (KIM-1) for the outcomes of incident DKD (ACCORD) and progressive DKD (VA-NEPHRON-D). At baseline, median concentrations of TNFR-1, TNFR-2, and KIM-1 were roughly two-fold higher in the advanced DKD population (NEPHRON-D) than in the early DKD population (ACCORD). In both cohorts, patients who reached the renal outcome had higher baseline levels than those who did not reach the outcome. Associations between doubling in TNFR-1, TNFR-2, and KIM-1 levels and risk of the renal outcomes were significant for both cohorts. Inclusion of these biomarkers in clinical models increased the area under the curve (SEM) for predicting the renal outcome from 0.68 (0.02) to 0.75 (0.02) in NEPHRON-D. Systematic review of the literature illustrated high consistency in the association between these biomarkers of inflammation and renal outcomes in DKD. In conclusion, TNFR-1, TNFR-2, and KIM-1 independently associated with higher risk of eGFR decline in persons with early or advanced DKD. Moreover, addition of these biomarkers to clinical prognostic models significantly improved discrimination for the renal outcome.
Diabetic nephropathy (DN) is a common and serious complication of diabetes associated with adverse outcomes of renal failure, cardiovascular disease, and premature mortality. Early and accurate identification of DN is therefore of critical importance to improve patient outcomes. Albuminuria, a marker of glomerular involvement in early renal damage, cannot always detect early DN. Thus, more sensitive and specific markers in addition to albuminuria are needed to predict the early onset and progression of DN. Tubular injury, as shown by the detection of tubular injury markers in the urine, is a critical component of the early course of DN. These urinary tubular markers may increase in diabetic patients, even before diagnosis of microalbuminuria representing early markers of normoalbuminuric DN. In this review we summarized some new and important urinary markers of tubular injury, such as neutrophil gelatinase associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid binding protein (L-FABP), N-acetyl-beta-glucosaminidase (NAG), alpha-1 microglobulin (A1M), beta 2-microglobulin (B2-M), and retinol binding protein (RBP) associated with early DN.
Background:
Abnormal expression of serum TGF-β1 was found in patients with diabetic nephropathy. However, the association of TGF-β1 with the risk of diabetic nephropathy remains unknown. The present study was undertaken to investigate whether such an association exists.
Methods:
We searched the Chinese VIP, Wangfang, China National Knowledge Infrastructure, PubMed, Embase, and Google Scholar databases for relevant studies and extracted all eligible data. Stata12 software was used for statistical analysis.
Results:
Nine reports met our criteria and were used for data extraction. There were 264 patients and 227 healthy controls from qualified reports in this meta-analysis. The results suggested that serum TGF-β1 levels were significantly up-regulated in patients with diabetic nephropathy; the instrumental variable was 3.94 (95% confidence interval 3.20-4.68, p<0.01).
Conclusions:
Meta-analysis suggested that elevated serum TGF-β level in patients with diabetes is associated with a high risk of nephropathy. Further studies are required to validate these observations.
The Kidney Disease: Improving Global Outcomes (KDIGO) 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease (CKD) serves to update the 2002 KDOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification following a decade of focused research and clinical practice in CKD. The document aims to provide state-of-the-art guidance on the evaluation, management and treatment for all patients with CKD. Specifically, the guideline retains the definition of CKD but presents an enhanced classification framework for CKD; elaborates on the identification and prognosis of CKD; discusses the management of progression and complications of CKD; and expands on the continuum of CKD care: timing of specialist referral, ongoing management of people with progressive CKD, timing of the initiation of dialysis, and finally the implementation of a treatment program which includes comprehensive conservative management. The development of the guideline followed an explicit process of evidence review and appraisal. Treatment approaches are addressed in each chapter and guideline recommendations are based on systematic reviews of relevant trials. Practical comments or statements which serve as educational purposes are ungraded, but included as important information for the readership. Appraisal of the quality of the evidence and the strength of recommendations followed the GRADE approach. Ongoing areas of controversies, limitations of the evidence, and international relevance are discussed and additional suggestions are provided for future research.
Background:
The aim of this study was to estimate the economic burden of diabetes mellitus (DM) in Iran from 2009 to 2030.
Methods:
A Markov micro-simulation (MM) model was developed to predict the DM population size and associated economic burden. Age- and sex-specific prevalence and incidence of diagnosed and undiagnosed DM were derived from national health surveys. A systematic review was performed to identify the cost of diabetes in Iran and the mean annual direct and indirect costs of patients with DM were estimated using a random-effect Bayesian meta-analysis. Face, internal, cross and predictive validity of the MM model were assessed by consulting an expert group, performing sensitivity analysis (SA) and comparing model results with published literature and national survey reports. Sensitivity analysis was also performed to explore the effect of uncertainty in the model.
Results:
We estimated 3.78 million cases of DM (2.74 million diagnosed and 1.04 million undiagnosed) in Iran in 2009. This number is expected to rise to 9.24 million cases (6.73 million diagnosed and 2.50 million undiagnosed) by 2030. The mean annual direct and indirect costs of patients with DM in 2009 were US 689 (619), respectively. Total estimated annual cost of DM was ) billion (including US1.93 billion indirect costs) in 2009 and is predicted to increase to ) billion (including US4.8 billion indirect costs) by 2030.
Conclusions:
The economic burden of DM in Iran is predicted to increase markedly in the coming decades. Identification and implementation of effective strategies to prevent and manage DM should be considered as a public health priority.
Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, β2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.Kidney International advance online publication, 22 July 2015; doi:10.1038/ki.2015.199.
Kidney injury molecule-1 (KIM-1), a recently discovered transmembrane protein, is expressed in dedifferentiated proximal renal tubular epithelial cells in damaged regions. Kidney injury early detection in diabetic patients has great importance for therapy and prognosis. Therefore, the aim of the present study is to predict, validate and evaluate the presence of KIM-1 in kidney inflammation, dialectic and diabetic nephropathy diseases.
Sixty males and females subjects (30-52 years) were selected for this study. They were subdivided into three main groups; kidney injury, diabetic and diabetic nephropathy patients. The work was extended to evaluate KIM-1 after treatment of each disease.
The results revealed significant elevation of KIM-1 in the diseased groups and a noticeable reduction after treatment. Diabetic nephropathy recorded the highest KIM-1 level than the AKI state or the diabetic patients. We noticed an association between KIM-1 and sex and a positive correlation (p < 0.0001) with the disease severity.
In conclusion, urinary KIM-1 has been reported to be a noninvasive, rapid, sensitive, and reproducible biomarker to detect early kidney injury. We speculate that KIM-1 is expected to be a therapeutic target for kidney injury.
Objective:
We investigated microvascular event risk in people with type 2 diabetes and assessed whether N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT) improved prediction.
Research design and methods:
We performed a case-cohort study, including 439 incident cases of microvascular events (new or worsening nephropathy or retinopathy) and 2,946 noncase subjects identified from participants in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial. NT-proBNP and hsTnT were measured in stored plasma samples using automated commercial assays.
Results:
After adjustment for age, sex, and randomized treatment, the hazard ratios for microvascular events per 1-SD increase in the log-transformed hsTnT and NT-proBNP were 1.67 (95% CI 1.51-1.85) and 1.63 (1.44-1.84), respectively. After further adjustment for classical and diabetes-related cardiovascular disease risk factors, the hazard ratios attenuated to 1.40 (1.24-1.58) and 1.41 (1.24-1.60), respectively. While the C statistic did not improve on addition of hsTnT or NT-proBNP for the total microvascular end point, a combination of both markers improved the prediction of nephropathy (P = 0.033) but not retinopathy (P = 0.72). The corresponding net reclassification indices in a three-risk category model (<10%, 10-15%, and >15% 5-year risk) for all microvascular events were 7.31% (95% CI 2.24-12.79) for hsTNT addition, 6.23% (1.74-11.5) for NT-proBNP addition, and 7.1% (1.5-12.9) for both markers together.
Conclusions:
These data suggest that cardiac biomarkers moderately improve microvascular event risk prediction, in particular the risk of nephropathy. Further studies examining the value of this approach for trial design and clinical use are warranted.
Precise effects of albuminuria and low estimated glomerular filtration rate (eGFR) on cardiovascular mortality, all-cause mortality, and renal events in diabetic patients are uncertain.
A systematic review was conducted of the literature through MEDLINE, EMBASE, and CINHAL from 1950 to December 2010. Cohort studies of diabetic patients providing adjusted relative risk (RR) of albuminuria and eGFR for risks of cardiovascular mortality, all-cause mortality, and renal events were selected. Two reviewers screened abstracts and full papers of each study using standardized protocol.
We identified 31 studies fulfilling the criteria from 6546 abstracts. With regard to the risk of cardiovascular mortality, microalbuminuria (RR 1.76, 95%CI 1.38-2.25) and macroalbuminuria (RR 2.96 95%CI 2.44-3.60) were significant risk factors compared to normoalbuminuria. The same trends were seen in microalbuminuria (RR 1.60, 95%CI 1.42-1.81), and macroalbuminuria (RR 2.64, 95%CI 2.13-3.27) for the risk of all-cause mortality, and also in microalbuminuria (RR 3.21, 95%CI 2.05-5.02) and macroalbuminuria (RR 11.63, 95%CI 5.68-23.83) for the risk of renal events. The magnitudes of relative risks associated with low eGFR along with albuminuria were almost equal to multiplying each risk rate of low eGFR and albuminuria. No significant factors were found by investigating potential sources of heterogeneity using subgroup analysis.
High albuminuria and low eGFR are relevant risk factors in diabetic patients. Albuminuria and low eGFR may be independent of each other. To evaluate the effects of low eGFR, intervention, or race, appropriately designed studies are needed.
Diabetes mellitus (DM) is the most prevalent metabolic disease worldwide and is associated with coronary artery disease (CAD). Therefore it is very important to find a clue to diagnose the presence of CAD as early as possible in DM patients. The aim of this study was to find any correlation between microalbuminuria (MAU) and the severity of CAD in patients with DM type 2. This was a cross sectional study that included 77 DM type 2 patients with suspected CAD that all of whom were performed coronary angiography in our hospital (from 2010 to 2011). Patients were divided into two groups, the case group (group 1) that includes patients with MAU and the control group (group 2) that include patients without MAU. Severity of CAD was estimated by using Gensini score and MAU was defined as the ratio of urine albumin to urine creatinine. Of 77 patients forty three (55.8%) were female, mean ± SD of their ages was 55.8 ± 10.3 and sixteen (21%) of them had MAU. Gensini score of case group was significantly higher than control group (94.94 ± 12 versus 33.25 ± 25.4, P<0.001). The linear regression analysis revealed urinary albumin to creatinine ratio (UA/CR) as an independent predictor for the severity of CAD (P<0.001). Based on the ROC curve, 10.25 was the best albumin level cut off point for differentiating Gensini score over and below 70. Area under curve was 0.9; sensitivity and specificity were 72% and 80%, respectively (P<0.001). According to this study, in patients with DM type2, MAU is an independent predictor of severity of coronary artery stenosis and reveals a positive correlation between MAU and the Gensini score.
Circulating levels of NH(2)-terminal probrain natriuretic peptide (NT-proBNP), a marker of acute heart failure, are associated with increased risk of cardiovascular disease (CVD) in the general population. However, there is little information on the potential role of NT-proBNP as a biomarker of vascular complications in type 1 diabetic patients. We investigated whether serum NT-proBNP levels were associated with micro- and macrovascular disease in type 1 diabetic subjects.
A cross-sectional nested case-control study from the EURODIAB Prospective Complications Study of 507 type 1 diabetic patients was performed. Case subjects (n = 345) were defined as those with one or more complications of diabetes; control subjects (n = 162) were those with no evidence of any complication. We measured NT-proBNP levels by a two-site sandwich electrochemiluminescence immunoassay and investigated their associations with complications.
Mean NT-proBNP levels were significantly higher in case than in control subjects. In logistic regression analyses, NT-proBNP values >26.46 pg/mL were independently associated with a 2.56-fold increased risk of all complications. Odds ratios of CVD (3.95 [95% CI 1.26-12.35]), nephropathy (4.38 [1.30-14.76]), and distal symmetrical polyneuropathy (4.32 [1.41-13.23]) were significantly increased in patients with NT-proBNP values in the highest quartile (>84.71 pg/mL), independently of renal function and known risk factors. These associations were no longer significant after inclusion of TNF-α into the model.
In this large cohort of type 1 diabetic subjects, we found an association between NT-proBNP and diabetic micro- and macrovascular complications. Our results suggest that the inflammatory cytokine TNF-α may be involved in this association.
To evaluate N-terminal pro brain natriuretic peptide (NT-proBNP) as a marker of long-term micro- and macrovascular complications in type 1 diabetes.
This was a cross-sectional study of 208 long-term surviving type 1 diabetic patients from a population-based cohort from Fyn County, Denmark. In a clinical examination in 2007-2008, NT-proBNP was measured and related to proliferative diabetic retinopathy (PDR), nephropathy, neuropathy and macrovascular disease.
Median age and duration of diabetes was 58.7 and 43 years, respectively. Median NT-proBNP concentration was 78 pg/ml (10th-90th percentile 25-653 pg/ml). The NT-proBNP level (89 vs. 71 pg/ml, p = 0.02) was higher in women. In univariate analyses, NT-proBNP was associated with age, duration of diabetes, diastolic blood pressure (inversely), nephropathy, neuropathy and macrovascular disease. For instance, median NT-proBNP concentrations were 70, 91 and 486 pg/ml for patients with normo-, micro- and macroalbuminuria, respectively (p < 0.01). When adjusted for age, sex, duration of diabetes, high sensitivity CRP, HbA(1c), diastolic blood pressure and smoking, higher NT-proBNP concentrations (4th vs. 1st quartile) were related to nephropathy (odds ratio [OR] 5.03; 95% confidence interval [CI] 1.77-14.25), neuropathy (OR 4.08; 95% CI 1.52-10.97) and macrovascular disease (OR 5.84; 95% CI 1.65-20.74). There was no association with PDR.
NT-proBNP has traditionally been described as a marker of heart failure and left ventricular dysfunction. In this study of long-term surviving type 1 diabetic patients, we found NT-proBNP associated with nephropathy, neuropathy and macrovascular disease. If confirmed by prospective studies, NT-proBNP might be a useful prognostic marker of diabetes-related complications.
Background:
Diabetic nephropathy (DN) which refers to the cases with biopsy proven kidney lesions, is one of the main complications of diabetes all around the world; however, the underlying biological changes causing DN remain to be understood. Studying the alterations in gene expression profiles could give a holistic view of the molecular pathogenicity of DN and aid to discover key molecules as potential therapeutic targets. Here, we performed a meta-analysis study that included microarray gene expression profiles coming from glomerular samples of DN patients in order to acquire a list of consensus Differentially Expressed Genes (meta-DEGs) correlated with DN.
Methods:
After quality control and normalization steps, five gene expression datasets (GES1009, GSE30528, GSE47183, GSE104948, and GSE93804) were entered into the meta-analysis. The meta-analysis was performed by random effect size method and the meta-DEGs were put through network analysis and different pathway enrichment analyses steps. MiRTarBase and TRRUST databases were utilized to predict the meta-DEGs related miRNAs and transcription factors. A co-regulatory network including DEGs, transcription factors and miRNAs was constructed by Cytoscape, and top molecules were identified based on centrality scores in the network.
Results:
The identified meta-DEGs were 1364 DEGs including 665 downregulated and 669 upregulated DEGs. The results of pathway enrichment analysis showed, "immune system", "extracellular matrix organization", "hemostasis", "signal transduction", and "platelet activation" to be the top enriched terms with involvement of the meta-DEGs. After construction of the multilayer regulatory network, several top DEGs (TP53, MYC, BTG2, VEGFA, PTEN, etc.), as well as top miRNAs (miR-335, miR-16, miR-17, miR-20a, and miR-93), and transcription factors (SP1, STAT3, NF-KB1, RELA, E2F1), were introduced as potential therapeutic targets in DN. Among the regulatory molecules, miR-335-5p and SP1 were the most interactive miRNA and transcription factor molecules with the highest degree scores in the constructed network.
Conclusion:
By performing a meta-analysis of available DN-related transcriptomics datasets, we reached a consensus list of DEGs for this complicated disorder. Further enrichment and network analyses steps revealed the involved pathways in the DN pathogenesis and marked the most potential therapeutic targets in this disease.
Aims:
To study the association of circulating β2 (B2M) and α1 microglobulins (A1M) with diabetic nephropathy (DN) progression, a meta-analysis was performed on the prospective cohort studies.
Methods:
Up to October 2021, a comprehensive search of the PubMed, EMBASE, Scopus, Web of Science, and Cochrane Library databases was performed. The primary outcome (progression of DN) was defined as a decrease in eGFR or the occurrence of end stage renal disease or DN-related mortality. Eligible studies were included in a pooled analysis that used either fixed-effect or random-effect models to compensate for variation in measurement standards between studies. The funnel plot and Egger's test were used to assess publication bias.
Results:
The meta-analysis included 4398 people from 9 prospective trials (8 cohorts) for B2M and 3110 people from 4 prospective trials (3 cohorts) for A1M. Diabetic individuals with higher B2M levels had an increased risk for DN (relative risk [RR]: 1.81, 95% confidence interval [CI]: 1.56-2.09). Likewise, higher A1M was associated with augmented probability of DN (RR: 1.96, 95% CI: 1.46-2.62). The funnel plot and Egger's tests indicated no publication bias for A1M. Additionally, to compensate for putative publication bias for B2M, using trim and fill analysis, four studies were filled for this marker and the results remained significant (RR: 1.62, 95% CI: 1.37-1.92).
Conclusions:
The elevated serum levels of B2M and A1M could be considered as potential predictors of DN progression in diabetic patients.
Protocol registration:
PROSPERO CRD42021278300.
Background: Diabetic nephropathy (DN) which refers to the cases with biopsy proven kidney lesions, is one of the main complications of diabetes all around the world; However, the underlying biological changes causing DN remain to be understood. Studying the alterations in gene expression profiles could give a holistic view of the molecular pathogenicity of DN and aid to discover key molecules as potential therapeutic targets. Here, we performed a meta-analysis study that included microarray gene expression profiles coming from glomerular samples of DN patients in order to acquire a list of consensus Differentially Expressed Genes (meta-DEGs) correlated with DN.
Methods: After quality control and normalization steps, five gene expression datasets (GES1009, GSE30528, GSE47183, GSE104948, and GSE93804) were entered into the meta-analysis. The mata-analysis was performed by random effect size method and the meta-DEGs were put through network analysis and different pathway enrichment analyses steps. MiRTarBase and TRRUST databases were utilized to predict the meta-DEGs related miRNAs and transcription factors. A co-regulatory network including DEGs, transcription factors and miRNAs was constructed by Cytoscape, and top molecules were identified based on centrality scores in the network.
Results: The identified meta-DEGs were 1364 DEGs including 665 downregulated and 669 upregulated DEGs. The results of pathway enrichment analysis showed, “immune system”, “extracellular matrix organization”, “hemostasis”, “signal transduction”, and “platelet activation” to be the top enriched terms with involvement of the meta-DEGs. After construction of the multilayer regulatory network, several top DEGs (TP53, MYC, BTG2, VEGFA, PTEN, etc.), as well as top miRNAs (miR-335, miR-16, miR-17, miR-20a, and miR-93), and transcription factors (SP1, STAT3, NF-KB1, RELA, E2F1), were introduced as potential therapeutic targets in DN. Among the regulatory molecules, miR-335-5p and SP1 were the most interactive miRNA and transcription factor molecules with the highest degree scores in the constructed network.
Conclusion: By performing a meta-analysis of available DN-related transcriptomics datasets, we reached a consensus list of DEGs for this complicated disorder. Further enrichment and network analyses steps revealed the involved pathways in the DN pathogenesis and marked the most potential therapeutic targets in this disease.
Background: Inflammation is a main mechanism for the pathogenesis and progression of diabetic kidney disease (DKD). Interleukin-6 (IL-6) is an important inflammatory mediator that is suggested to be involved in the pathogenesis of DKD. The aim of our study was to evaluate the association between IL-6 levels and progression of DKD in patients with type 2 diabetes mellitus.
Materials and methods: IL-6 levels were measured at baseline and after 4 and 12 months in 70 patients included in a multi-center, randomized controlled clinical trial designed to compare the effect of RAS blockers in monotherapy to dual blockade for slowing the progression of DKD. The primary composite endpoint was > 50% increase in baseline serum creatinine, end-stage kidney disease (ESKD), or death.
Results: The median follow-up was 36 months, during which 27 patients (38.6%) reached the primary endpoint. Baseline IL-6 levels correlated with TNF-α, C-reactive protein, and PTH levels. Survival analysis showed that patients with the highest IL-6 levels (> 4.84 pg/mL) reached the primary endpoint faster than the other two groups. Multivariate Cox regression analysis showed that baseline IL-6 levels > 4.84 pg/mL (HR 4.10, 95% CI 1.36 - 12.31) were a risk factor for reaching the primary endpoint adjusted for eGFR and proteinuria. Generalized linear mixed model analysis showed no effect on subsequent IL-6 levels either with RAS blockade monotherapy or dual blockade.
Conclusion: These results suggest that treatment with RAS blockade does not influence IL-6 levels. IL-6 is independently associated with an increased risk for progression of DKD.
Background and Aims
Diabetic nephropathy (DN) is one of the worst complications of diabetes. Despite a growing number of DN metabolite profiling studies, most studies are suffering from inconsistency in their findings. The main goal of this meta-analysis was to reach to a consensus panel of significantly dysregulated metabolites as potential biomarkers in DN.
Methods and Results
To identify the significant dysregulated metabolites, meta-analysis was performed by “vote-counting rank” and “robust rank aggregation” strategies. Bioinformatics analyses were performed to identify the most affected genes and pathways. Among 44 selected studies consisting of 98 metabolite profiles, 17 metabolites (9 up-regulated and 8 down-regulated metabolites), were identified as significant ones by both the meta-analysis strategies (p-value<0.05 and OR>2 or <0.5) and selected as DN metabolite meta-signature. Furthermore, enrichment analyses confirmed the involvement of various effective biological pathways in DN pathogenesis, such as urea cycle, TCA cycle, glycolysis, and amino acid metabolisms. Finally, by performing a meta-analysis over existing time-course studies in DN, the results indicated that lactic acid, hippuric acid, allantoin (in urine), and glutamine (in blood), are the topmost non-invasive early diagnostic biomarkers.
Conclusion
The identified metabolites are potentially involved in diabetic nephropathy pathogenesis and could be considered as biomarkers or drug targets in the disease.
PROSPERO registration number
CRD42020197697.
Background
Patients with chronic kidney disease often have increased plasma cardiac troponin concentration in the absence of myocardial infarction. Incidence of myocardial infarction is high in this population, and diagnosis, particularly of non ST-segment elevation myocardial infarction (NSTEMI), is challenging. Knowledge of biological variation aids understanding of serial cardiac troponin measurements and could improve interpretation in clinical practice. The National Academy of Clinical Biochemistry (NACB) recommended the use of a 20% reference change value in patients with kidney failure. The aim of this study was to calculate the biological variation of cardiac troponin I and cardiac troponin T in patients with moderate chronic kidney disease (glomerular filtration rate [GFR] 30–59 mL/min/1.73 m ² ).
Methods and results
Plasma samples were obtained from 20 patients (median GFR 43.0 mL/min/1.73 m ² ) once a week for four consecutive weeks. Cardiac troponin I (Abbott ARCHITECT® i2000 SR, median 4.3 ng/L, upper 99th percentile of reference population 26.2 ng/L) and cardiac troponin T (Roche Cobas® e601, median 11.8 ng/L, upper 99th percentile of reference population 14 ng/L) were measured in duplicate using high-sensitivity assays. After outlier removal and log transformation, 18 patients’ data were subject to ANOVA, and within-subject (CV I ), between-subject (CV G ) and analytical (CV A ) variation calculated. Variation for cardiac troponin I was 15.0%, 105.6%, 8.3%, respectively, and for cardiac troponin T 7.4%, 78.4%, 3.1%, respectively. Reference change values for increasing and decreasing troponin concentrations were +60%/–38% for cardiac troponin I and +25%/–20% for cardiac troponin T.
Conclusions
The observed reference change value for cardiac troponin T is broadly compatible with the NACB recommendation, but for cardiac troponin I, larger changes are required to define significant change. The incorporation of separate RCVs for cardiac troponin I and cardiac troponin T, and separate RCVs for rising and falling concentrations of cardiac troponin, should be considered when developing guidance for interpretation of sequential cardiac troponin measurements.
Diabetic nephropathy (DN) is one of the most feared diabetic chronic microvascular complications and the major cause of end-stage renal disease (ESRD). The classical presentation of DN is characterized by hyperfiltration and albuminuria in the early phases which is then followed by a progressive renal function decline. The presentation of diabetic kidney disease (DKD) can vary especially in patients with T2DM where concomitant presence of other glomerular/tubular pathologies and severe peripheral vascular disease can become important confounders. All-cause mortality in individuals with DKD is approximately 30 times higher than that in diabetic patients without nephropathy and a great majority of patients with DKD will die from cardiovascular disease before they reach ESRD. The management of metabolic and hemodynamic perturbations for the prevention and for the delay of progression of DKD is very important. DKD is a global challenge and a significant social and economic burden; research should aim at developing new ideas to tackle this devastating condition.
Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m2, urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.
Background and aims:
Fibroblast growth factor 21 (FGF21) has been suggested as a novel biomarker for cardiovascular disease (CVD), especially in people with high CVD risk. However, it is not known whether FGF21 is a CVD biomarker in an initially healthy cohort. We therefore investigated the relationship of plasma FGF21 levels with measures of subclinical atherosclerosis and cardiovascular events in Multi-Ethnic Study of Atherosclerosis participants without known CVD at baseline.
Methods:
A total of 5788 participants had plasma FGF21 levels measured at the baseline exam (2000-2002). Carotid intima-media thickness (IMT), ankle-brachial index (ABI) and coronary artery calcification (CAC) were measured at baseline. Participants were followed up for incident CVD events over a median period of 14 years.
Results:
In cross-sectional analyses adjusting for socio-demographic variables, participants with higher FGF21 levels had higher carotid IMT, lower ABI, and higher prevalence of CAC (p < 0.001). However, these associations were not significant after simultaneously adjusting for demographic, socioeconomic and lifestyle factors, traditional CVD risk factors, and biomarkers of inflammation and hemostasis. Among 5768 patients with follow-up data, 820 developed incident CVD endpoints. Higher baseline FGF21 levels were not associated with the risk for incident CVD endpoints after adjusting for multiple confounding factors (odds ratio 1.03; 95% confidence interval, 0.94-1.12, per SD increase in ln-transformed FGF21 levels).
Conclusions:
Although FGF21 has been suggested as a CVD biomarker for people with high CVD risk, our findings do not support a role of FGF21 as a CVD biomarker in those without a history of CVD.
Background:
We conducted a meta-analysis to investigate the associations of circulating tumor necrosis factor-1 (TNFR-1) and TNFR-2 with diabetic kidney disease (DKD) progression, which is the first-ever quantitative synthesis of these associations thus far. Whether TNFRs were better than albumin-creatinine ratio (ACR) in predicting DKD progression were also explored.
Methods:
A systematic search of the PubMed, EMBASE and Cochrane Library databases up to February 1, 2018, was conducted. The main outcome was DKD progression, which was defined as eGFR decline, macroalbuminuria, or incidence of DKD-related events. Eligible studies were included for pooled analysis using either fixed-effects or random-effects models to incorporate between-study variation by different measurement standards. Publication bias was evaluated using Egger's test.
Results:
The meta-analysis included 6526 participants from 11 cohorts with circulating TNFR-1 measurements and 5385 participants from 10 prospective studies with circulating TNFR-2 measurements. Compared to the lowest level category, diabetic patients with the highest TNFR-1 or TNFR-2 level category exhibited a higher risk of DKD progression (RR 2.51, 95% CI [1.92-3.27] for TNFR-1; 3.23 [1.99-5.26] for TNFR-2). The risk of DKD progression was also increased with the per unit increment of TNFR-1 or TNFR-2 (1.68 [1.43-1.97] for TNFR-1; 1.69 [1.31-2.17] for TNFR-2). Although existing studies did not support a direct comparison between ACR and TNFRs, it was undeniable that TNFRs could improve the predictive value in DKD progression.
Conclusions:
Circulating TNFR-1 and TNFR-2 are reliable predictors of DKD progression. Whether TNFRs were better than ACR at predicting DKD progression needs to be further investigated.
Background:
Currently, there is a lack of prediction markers for diabetic nephropathy (DN) in patients with type 1 and type 2 diabetes mellitus (T1DM/T2DM). The aim of this systematic review and meta-analysis was to evaluate the value of a promising biomarker, neutrophil gelatinase-associated lipocalin (NGAL), in both serum and urine for the diagnosis of early DN in T1DM and T2DM patients with different stages of albuminuria.
Methods:
A comprehensive search was performed on PubMed by 2 reviewers until September 2018. Studies in which (a) the degree of DN was determined according to the urinary albumin/creatinine ratio and (b) NGAL was measured in healthy individuals and in diabetes patients with DN were included in the meta-analysis. For each study, a 2 × 2 contingency table was formulated. Sensitivity, specificity, and other estimates of accuracy were calculated using a bivariate random effects model. The hierarchical summary ROC method was used to pool data and to evaluate the area under the curve (AUC). The sources of heterogeneity were explored by subgroup analysis. Publication bias was assessed using the Deeks test.
Results:
The meta-analysis enrolled 22 studies involving 683 healthy individuals and 3249 patients with diabetes, of which 488 were T1DM and 2761 were T2DM patients. Overall, pooled sensitivity and specificity among the different settings analyzed ranged from 0.42 (95% CI, 0.22-0.66) to 1.00 (95% CI, 0.99-1.00) and 0.72 (95% CI, 0.62-0.80) to 0.98 (95% CI, 0.50-1.00) in T2DM patients, respectively. For T1DM patients, the corresponding estimates were 0.71 (95% CI, 0.59-0.81) to 0.89 (95% CI, 0.64-0.97) and 0.72 (95% CI, 0.62-0.80) to 0.79 (95% CI, 0.67-0.87). The AUC of NGAL for T2DM patients ranged from 0.69 (95% CI, 0.65-0.73) to 1.00 (95% CI, 0.99-1.00) in the different settings.
Conclusion:
The results of this meta-analysis suggest that NGAL in both serum and urine can be considered a valuable biomarker for early detection of DN in diabetes patients.
AimsThe aim was to perform a meta-analysis on the miRNA expression profiling studies in diabetic nephropathy (DN) to identify candidate diagnostic biomarkers. MethodsA comprehensive literature search was done in several databases and 53 DN miRNA expression studies were selected. To identify significant DN-miR meta-signatures, two meta-analysis methods were employed: vote-counting strategy and the robust rank aggregation method. The targets of DN-miRs were obtained and a gene set enrichment analysis was carried out to identify the pathways most strongly affected by dysregulation of these miRNAs. ResultsWe identified a significant miRNA meta-signature common to both meta-analysis approaches of three up-regulated (miR-21-5p, miR-146a-5p, miR-10a-5p) and two down-regulated (miR-25-3p and miR-26a-5p) miRNAs. Besides that, subgroup analyses divided and compared the differentially expressed miRNAs according to species (human and animal), types of diabetes (T1DN and T2DN) and tissue types (kidney, blood and urine). Enrichment analysis confirmed that DN-miRs supportively target functionally related genes in signaling and community pathways in DN. Conclusion
Five highly significant and consistently dysregulated miRNAs were identified, and future studies should focus on discovering their potential effect on DN and their clinical value as DN biomarkers and therapeutic mediators.
Objective:
The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable, and early interventions would likely be cost-effective. We elucidated the contribution of 17 plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors.
Research design and methods:
We studied participants in PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers), a prospective multinational cohort study of patients with type 2 diabetes and a follow-up of more than 24 months (n = 2,560; baseline median eGFR, 84 mL/min/1.73 m2; urine albumin-to-creatinine ratio, 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling.
Results:
In univariable analyses, 9 of the 17 markers showed significant differences in median concentration between stable and fast-progressing patients. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted R2 of 62%. A panel of 12 biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% were due to 5 markers. The individual contribution of each biomarker to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (R2 of 79%), and the contribution of each biomarker dropped below 1%.
Conclusions:
In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low.
Aims:
A portion of patients with diabetes mellitus follow the progression of a non-albuminuria-based pathway; i.e., normoalbuminuric diabetic kidney disease (NA-DKD). However, the risk factors which determine NA-DKD are not yet fully understood. This cross-sectional study was therefore aimed to investigate the association between various biomarker levels and estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes mellitus and normoalbuminuria (T2D-NA).
Methods:
We measured cardiovascular disease (CVD) [serum osteoprotegerin (OPG), plasma brain natriuretic peptide (BNP), cardio-ankle vascular index (CAVI)], tubular damage [urinary L-type fatty acid binding protein (L-FABP)], and inflammatory [serum tumornecrosis factor (TNF) α and its receptors (TNFRs)] biomarkers in 314 patients with T2D-NA.
Results:
The biomarkers of CVD and inflammation showed a significant negative correlation with eGFR. In a logistic multivariate model, none of the biomarkers, except TNFα and TNFRs, were associated with reduced renal function (eGFR < 60 mL/min/1.73 m2) after adjustment for possible biological and clinical covariates. However, the association observed in TNFα was lost after adjusting for TNFR and other covariates.
Conclusions:
In patients with T2D-NA, elevated levels of circulating TNFRs, but not of TNFα, were strongly associated with reduced renal function, independently of all relevant covariates.
Background and objective:
Previous studies revealed the association between serum N-terminal pro-brain natriuretic peptide (NT-proBNP) level and chronic kidney diseases (CKD) in general population. However, little is known about the association between serum NT-proBNP level and incident CKD in patients with type 2 diabetes. Thus, we investigated the impact of serum NT-proBNP level on incident CKD in patients with type 2 diabetes.
Method:
We enrolled 211 type 2 diabetic patients without CKD in this cohort study. CKD was diagnosed as estimated glomerular filtration rate <60 ml/min/1.73 m2. We divided the patients into three groups according to the tertiles of serum NT-proBNP level. Univariates and multivariate hazard ratios (HRs) for the incident CKD were calculated by Cox regression analyses.
Results:
Over the median follow-up period of 7 years, 56 patients developed incident CKD. Log NT-proBNP was positively associated with incident CKD (HR 3.70, 95%CI 1.72-8.18, p <0.001). Compared with the lowest level of serum NT-proBNP tertile (<36 pg/mL), the highest level of serum NT-proBNP tertile (>84 pg/mL) showed increased risk of incident CKD after adjusting age, sex, body mass index, hemoglobin A1c, creatinine, smoking, usage of hypertension drug and urinary albumin excretion at baseline examination (adjusted HR2.37, 95% CI 1.09-5.48, p = 0.028).
Conclusion:
Serum NT-proBNP level is an independent biomarker for incident CKD in patients with type 2 diabetes.
High-sensitivity troponin T (hsTnT) is a marker of cardiovascular disease (CVD) and in type 2 diabetes also a marker of renal events, but has not been evaluated in type 1 diabetics. We therefore reviewed a type 1 diabetes cohort of 442 without and 458 with diabetic nephropathy. Baseline samples were analyzed for hsTnT levels. Cox regression analyses assessed predictive value in relation to the development of end-stage renal disease (ESRD) in 99 patients, all-cause mortality in 178, and CVD events in 134 after up to 12 years of follow-up. To assess if hsTnT improved risk prediction beyond traditional clinical risk markers, we calculated c statistics and relative integrated discrimination improvement. HsTnT was significantly higher in patients with diabetic nephropathy compared to normoalbuminuria (median 8.9 vs 3.1 ng/L). For a doubling in hsTnT levels, and after adjustment for well-known risk factors, including NT-proBNP and hsCRP, the hazard ratio for ESRD at 1.26 was not significant in the diabetic nephropathy group, but there was a significant association with GFR decline after adjustment during follow-up (2.9 ml/min/1.73 m² annual decline per doubling in hsTnT). The unadjusted and adjusted hazard ratios for mortality (1.64 and 1.32, respectively) were significant in patients with, but not for patients without, nephropathy. Adjusted hazard ratios for fatal and non-fatal CVD events were significant for the whole cohort (1.13), and those with nephropathy (1.14), but not significant for normoalbuminuria (1.06). Addition of hsTNT to traditional risk factors significantly increased the area under the curve by 0.01 in a receiver-operating characteristic curve for mortality. The relative integrated discrimination improvement was increased 15.7% for mortality, 6.3% for CVD, and 1.9% for ESRD (all significant). Thus, higher hsTnT is an independent predictor of renal decline and cardiovascular events in patients with type 1 diabetes and diabetic nephropathy.
Objective:
Although type 2 diabetes (T2D) patients with nephropathy are at high risk for renal and cardiovascular complications, relevant biomarkers have been poorly identified. Because renal impairment may increase biomarker levels, this potentially confounds associations between biomarker levels and risk. To investigate the predictive value of a biomarker in such a setting, we examined baseline levels of growth differentiation factor-15 (GDF-15), N-terminal prohormone of B-type natriuretic peptide (NTproBNP), and high-sensitivity troponin-T (hs-TnT) in relation to renal and cardiovascular risk in T2D patients with nephropathy.
Research design and methods:
Eight hundred sixty-one T2D patients from the sulodexide macroalbuminuria (Sun-MACRO) trial were included in our post hoc analysis. Prospective associations of baseline serum GDF-15, NTproBNP, and hs-TnT with renal and cardiovascular events were determined by Cox multiple regression and C-statistic analysis. Renal base models included albumin-to-creatinine ratio (ACR), serum creatinine, hemoglobin, age, and sex. Cardiovascular base models included diastolic blood pressure, ACR, cholesterol, age, and sex.
Results:
The mean (?SD) estimated glomerular filtration rate was 33 ? 9 mL/min/1.73 m(2), and the median serum concentration for GDF-15 was 3,228 pg/mL (interquartile range 2,345-4,310 pg/mL), for NTproBNP was 380 ng/L (155-989 ng/L), and for hs-TnT was 30 ng/L (20-47 ng/L). In multiple regression analysis, GDF-15 (hazard ratio [HR] 1.83, P = 0.04), NTproBNP (HR 2.34, P = 0.004), and hs-TnT (HR 2.09, P = 0.014) were associated with renal events, whereas NTproBNP (HR 3.45, P < 0.001) was associated with cardiovascular events. The C-statistic was improved by adding NTproBNP and hs-TNT to the renal model (0.793 vs. 0.741, P = 0.04). For cardiovascular events, the C-statistic was improved by adding NTproBNP alone (0.722 vs. 0.658, P = 0.018).
Conclusion:
Biomarkers GDF-15, NTproBNP, and hs-TnT associate independently with renal risk, whereas NTproBNP independently predicts cardiovascular risk.
Background:
Prognosis in chronic kidney disease (CKD) for adverse outcomes differs substantially based on the etiology of CKD. We examined whether the biomarker profile differed based on CKD etiology and whether they were associated with mortality.
Methods:
Prospective observational study of 1,157 patients, 663 with diabetic kidney disease (DKD), 273 with glomerulonephritis (GN), and 221 with cystic/interstitial disease (polycystic kidney disease, pyelonephritis or chronic tubulointerstitial nephritis [PCK/TIN]) were identified in the Canadian Study of Prediction of Dialysis, Death and Interim Cardiovascular events over Time cohort. The outcome of interest was mortality before commencing dialysis. The biomarker profile consisted of N-terminal pro-brain natriuretic peptide (NT-proBNP), troponin I (TnI), asymmetric dimethylarginine (ADMA), interleukin (IL)-6, high sensitivity C-reactive protein, fibroblast growth factor-23 (FGF23), transforming growth factor-beta, 25-hydroxylvitamin D, and cystatin C (CysC).
Results:
The mean estimated glomerular filtration rate was 27 mL/min/1.73 m2 and median follow-up time was 44 months. Mortality before dialysis commencement was the greatest in DKD (20%), followed by PCK/TIN (13%), and was least in those GN (8%). The majority of deaths were cardiovascular in nature, 17, 9, and 5.5% for DKD, PCK/TIN, GN, respectively. Those with DKD had higher hazard for mortality, unadjusted (hazard ratio [HR] 2.7, 95% CI 1.7-4.3) and adjusted (HR 1.7, 95% CI 1.1-2.8). The biomarker profiles associated with mortality differed significantly by CKD etiology as follows: DKD was associated with CysC (HR 1.3, 95% CI 1.0-1.6), ADMA (HR 1.3, 95% CI 1.1-1.6), and NT-proBNP (HR 1.7, 95% CI 1.4-2.1), GN was associated with FGF23 (HR 1.8, 95% CI 1.1-2.8), TnI (HR 3.6, 95% CI 1.3-9.5), and transforming growth factor-beta (HR 0.6, 95% CI 0.4-0.9) and PCK/TIN was associated with ADMA (HR 1.5, 95% CI 1.3-1.8) and IL-6 (HR 2.1, 95% CI 1.5-3.1).
Conclusions:
Biomarkers profiles differ according to the etiology of CKD and are associated with mortality.
Chronic kidney disease (CKD) typically evolves over many years, with a long latent period when the disease is clinically silent and therefore diagnosis, evaluation and treatment is based mainly on biomarkers that assess kidney function. Glomerular filtration rate (GFR) remains the ideal marker of kidney function. Unfortunately measuring GFR is time consuming and therefore GFR is usually estimated from equations that take into account endogenous filtration markers like serum creatinine (SCr) and cystatin C (CysC). Other biomarkers such as albuminuria may precede kidney function decline and have demonstrated to have strong associations with disease progression and outcomes. New potential biomarkers have arisen with the promise of detecting kidney damage prior to the currently used markers. The aim of this review is to discuss the utility of the GFR estimating equations and biomarkers in CKD and the different clinical settings where these should be applied. The CKD-Epidemiology Collaboration equation performs better than the modification of diet in renal disease equation, especially at GFR above 60 mL/min per 1.73 m(2). Equations combining CysC and SCr perform better than the equations using either CysC or SCr alone and are recommended in situations where CKD needs to be confirmed. Combining creatinine, CysC and urine albumin to creatinine ratio improves risk stratification for kidney disease progression and mortality. Kidney injury molecule and neutrophil gelatinase-associated lipocalin are considered reasonable biomarkers in urine and plasma to determine severity and prognosis of CKD.
The aim of the study was to examine the relationship between the brain natriuretic peptide (BNP) level and progression or remission of diabetic nephropathy with microalbuminuria for 3 years. The subjects were 100 Japanese type 2 diabetes mellitus outpatients with microalbuminuria. Associations between metabolic parameters at baseline [HbA1c, systolic blood pressure (SBP), urine albumin-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), and BNP] and the progression or remission of diabetic nephropathy were examined for 3 years. A total of 83 patients were examined at the end of the 3-year period, including 17 with remission to normoalbuminuria, 47 with continuing microalbuminuria, and 19 with progression to macroalbuminuria. HbA1c, ACR, and BNP differed significantly among the 3 groups (p=0.024, p<0.001, p=0.002, respectively). Among baseline factors, HbA1c and BNP were significant predictors of the percentage increase in ACR for 3 years in multiple linear regression analysis (β=0.259, p=0.02; β=0.299, p=0.007, respectively). In multivariate logistic regression analysis, HbA1c and ACR were independently associated with progression of diabetic nephropathy (p=0.008, p=0.023, respectively), and ACR and BNP were independently associated with remission of diabetic nephropathy (p=0.029, p=0.012, respectively). ROC curve analysis gave a cutoff value for BNP of 14.9 pg/ml for prediction of remission of diabetic nephropathy (p=0.016). The BNP level has a relationship with diabetic nephropathy and a low BNP level predicts remission of diabetic nephropathy. Therefore, monitoring of BNP can play an important role in management of diabetic nephropathy.
© Georg Thieme Verlag KG Stuttgart · New York.
Currently, no blood biomarker that specifically indicates injury to the proximal tubule of the kidney has been identified. Kidney injury molecule-1 (KIM-1) is highly upregulated in proximal tubular cells following kidney injury. The ectodomain of KIM-1 is shed into the lumen, and serves as a urinary biomarker of kidney injury. We report that shed KIM-1 also serves as a blood biomarker of kidney injury. Sensitive assays to measure plasma and serum KIM-1 in mice, rats, and humans were developed and validated in the current study. Plasma KIM-1 levels increased with increasing periods of ischemia (10, 20, or 30 minutes) in mice, as early as 3 hours after reperfusion; after unilateral ureteral obstruction (day 7) in mice; and after gentamicin treatment (50 or 200 mg/kg for 10 days) in rats. In humans, plasma KIM-1 levels were higher in patients with AKI than in healthy controls or post-cardiac surgery patients without AKI (area under the curve, 0.96). In patients undergoing cardiopulmonary bypass, plasma KIM-1 levels increased within 2 days after surgery only in patients who developed AKI (P<0.01). Blood KIM-1 levels were also elevated in patients with CKD of varous etiologies. In a cohort of patients with type 1 diabetes and proteinuria, serum KIM-1 level at baseline strongly predicted rate of eGFR loss and risk of ESRD during 5-15 years of follow-up, after adjustment for baseline urinary albumin-to-creatinine ratio, eGFR, and Hb1Ac. These results identify KIM-1 as a blood biomarker that specifically reflects acute and chronic kidney injury.
Diabetic nephropathy is the most common cause of CKD and represents a large and ominous public health problem. Patients with diabetic kidney disease have exceptionally high rates of cardiovascular morbidity and mortality. In fact, the excess mortality among patients with diabetes appears to be largely limited to the subgroup with kidney disease and explained by their high burden of cardiovascular disease. The mechanisms underlying the strong association between diabetic kidney disease and various forms of cardiovascular disease are poorly understood. Traditional risk factors for cardiovascular disease, although prevalent among those with diabetes, do not fully account for the heightened risk observed. Despite their susceptibility to cardiovascular disease, patients with CKD are less likely to receive appropriate risk factor modification than the general population. Moreover, because patients with CKD have commonly been excluded from major cardiovascular trials, the evidence for potential treatments remains limited. The mainstays of treatment for diabetic kidney disease currently include blockade of the renin-angiotensin-aldosterone system and control of hypertension, hyperglycemia, and dyslipidemia. Increased awareness of the vulnerability of this patient population and more timely interventions are likely to improve outcomes while large evidence gaps are filled with newer studies.
This review basically provided a conceptual framework for sample size calculation in epidemiologic studies with various designs and outcomes. The formula requirement of sample size was drawn based on statistical principles for both descriptive and comparative studies. The required sample size was estimated and presented graphically with different effect sizes and power of statistical test at 95% confidence level. This would help the clinicians to decide and ascertain a suitable sample size in research protocol in order to detect an effect of interest.
Background:
Hypertension is the most prevalent comorbidity in individuals with chronic kidney disease. However, whether the association of the kidney disease measures, estimated glomerular filtration rate (eGFR) and albuminuria, with mortality or end-stage renal disease (ESRD) differs by hypertensive status is unknown.
Methods:
We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and ESRD associated with eGFR and albuminuria in individuals with and without hypertension.
Findings:
We analysed data for 45 cohorts (25 general population, seven high-risk, and 13 chronic kidney disease) with 1,127,656 participants, 364,344 of whom had hypertension. Low eGFR and high albuminuria were associated with mortality irrespective of hypertensive status in the general population and high-risk cohorts. All-cause mortality risk was 1·1-1·2 times higher in individuals with hypertension than in those without hypertension at preserved eGFR. A steeper relative risk gradient in individuals without hypertension than in those with hypertension at eGFR range 45-75 mL/min per 1·73 m(2) led to much the same mortality risk at lower eGFR. With a reference eGFR of 95 mL/min per 1·73 m(2) in each group to explicitly assess interaction, adjusted HR for all-cause mortality at eGFR 45 mL/min per 1·73 m(2) was 1·77 (95% CI 1·57-1·99) in individuals without hypertension versus 1·24 (1·11-1·39) in those with hypertension (p for overall interaction=0·0003). Similarly, for albumin-creatinine ratio of 300 mg/g (vs 5 mg/g), HR was 2·30 (1·98-2·68) in individuals without hypertension versus 2·08 (1·84-2·35) in those with hypertension (p for overall interaction=0·019). We recorded much the same results for cardiovascular mortality. The associations of eGFR and albuminuria with ESRD, however, did not differ by hypertensive status. Results for chronic kidney disease cohorts were similar to those for general and high-risk population cohorts.
Interpretation:
Chronic kidney disease should be regarded as at least an equally relevant risk factor for mortality and ESRD in individuals without hypertension as it is in those with hypertension.
Funding:
US National Kidney Foundation.
Objective: To review the use of cardiac troponins as biomarkers for myocardial injury in human and veterinary medicine.
Data sources: Data sources included scientific reviews and original research publications.
Human data synthesis: Cardiac troponins have been extensively studied in human medicine. Finding an elevated cardiac troponin level carries important diagnostic and prognostic information for humans with cardiovascular disease. Troponin assays are used primarily to diagnose acute myocardial infarction in patients with ischemic symptoms such as chest pain. However, elevated blood levels may be found with any cause of myocardial injury.
Veterinary data synthesis: Several studies have shown that cardiac troponins are sensitive and specific for myocardial damage in veterinary patients and may have utility in diagnosis and prognosis for certain disease states. Human assays may be used in most animals due to significant homology in the troponin proteins between species.
Conclusions: Cardiac troponins are sensitive and specific markers of myocardial injury although they do not give any information regarding the mechanism of injury. They have redefined how acute myocardial infarction is diagnosed in humans. Their use in the clinical management of veterinary patients is limited at this time. Further prospective studies are warranted.
In patients with chronic kidney disease (CKD), as in other populations, elevations in cardiac biomarker levels predict increased risk of cardiovascular events. We examined the value of troponin T (TnT) and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) in assessing the risk of developing end-stage renal disease (ESRD) in diabetic patients with CKD.
Prospective cohort study nested within a randomized clinical trial.
Patients with type 2 diabetes, CKD (estimated glomerular filtration rate [eGFR], 20-60 mL/min/1.73 m(2)), and anemia enrolled in TREAT (Trial to Reduce Cardiovascular Events With Aranesp Therapy).
Serum levels of the cardiac biomarkers TnT and NT-pro-BNP.
Incidence of ESRD and the composite of death or ESRD.
We measured TnT and NT-pro-BNP in baseline serum samples from the first 1,000 patients enrolled in TREAT. The relationship of these cardiac biomarker levels to the development of ESRD and death or ESRD was analyzed in multivariable regression models.
Detectable TnT (≥0.01 ng/mL) was present in 45% of participants, and median NT-pro-BNP level was elevated at 605 pg/mL. Higher levels of both cardiac biomarkers were associated independently with higher rates of ESRD, as well as death or ESRD, and remained prognostically important after adjustment for eGFR, proteinuria, and other known predictors of CKD progression. The addition of cardiac biomarkers to a multivariable model for prediction of ESRD improved discrimination of those with and without an event by 16.9% (95% CI, 6.3%-27.4%).
Observational study in a clinical trial cohort; results require validation.
In ambulatory patients with type 2 diabetes, anemia, and CKD, TnT and NT-pro-BNP levels frequently are elevated. These cardiac-derived biomarkers enhance prediction of ESRD beyond established risk factors. Measurement of TnT and NT-pro-BNP may improve the identification of patients with CKD who are likely to require renal replacement therapy, supporting a link between cardiac injury and the development of ESRD.