Predictive Properties of Biomarkers GDF-15, NTproBNP, and hs-TnT for Morbidity and Mortality in Patients With Type 2 Diabetes With Nephropathy

Role of GDF-15 in diabetic nephropathy: mechanisms, diagnosis, and therapeutic potential

PURPOSE

Growth differentiation factor 15 (GDF-15) is a cytokine involved in regulating homeostasis, and its expression is up-regulated in response to injury, stress, and inflammation. This study explored the role of GDF-15 in diabetic nephropathy (DN), a severe complication of diabetes mellitus, and its potential as a biomarker for disease progression.

METHODS

As a member of the transforming growth factor-β superfamily, GDF-15 exhibits its renal protective functions primarily through its anti-inflammatory effects and the up-regulation of other renal protective factors. This study evaluated the association between circulating GDF-15 levels and DN progression, examining the underlying mechanisms.

RESULTS

Circulating GDF-15 levels are closely linked to the development and progression of DN. While existing research has yielded some consistent conclusions, a comprehensive understanding of the role of GDF-15 in DN pathogenesis is needed to identify new therapeutic targets and strategies.

CONCLUSION

GDF-15 has the potential to be a prognostic and diagnostic biomarker for DN. It is crucial to establish appropriate reference ranges and explore their clinical utility in routine practice for validating the role of GDF-15 in DN management. Further interventional studies are required to confirm its clinical value in diagnosing and predicting the progression of DN.

Testosterone and soluble ST2 as mortality predictive biomarkers in male patients with sepsis-induced cardiomyopathy

Sepsis-induced cardiomyopathy (SIC) is characterized by high mortality and poor outcomes. This study aimed to explore the relationship between testosterone and soluble ST2 (sST2) and all-cause mortality in patients with SIC. Clinical data from SIC patients at Renmin Hospital of Wuhan University from January 2021 and March 2023 were reviewed. Serum testosterone and sST2 were measured at admission. Kaplan-Meier analysis and receiver operative characteristic curve (ROC) were used to estimate the predictive values of testosterone and sST2 on 28 days and 90 days mortality of SIC. A total of 327 male subjects with SIC were enrolled in this study. During the 28 days and 90 days follow-up, 87 (26.6%) and 103 deaths (31.5%) occurred, respectively. Kaplan-Meier analysis showed significantly higher 28 days and 90 days survival in patients with higher testosterone and decreased sST2 levels (p < 0.001). Testosterone, sST2, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were significantly associated with 28 days and 90 days mortality (p < 0.05). Partial correlation analysis showed strong positive correlation between testosterone and left ventricular ejection fraction (LVEF) (p < 0.001), and negative correlation between testosterone and sST2 (p < 0.001), high-sensitivity troponin I (hs-TnI) levels (p < 0.001) and smoke history (p < 0.01). The concentrations of sST2 were positively related with E/e' ratio (p < 0.001), and negatively correlated with TAPSE (p < 0.001). The combination of testosterone and sST2 enhanced the prediction of both 28 days [area under the ROC curve (AUC), 0.805] and 90 days mortality (AUC, 0.833). Early serum testosterone and sST2 levels could predict mortality of SIC independently and jointly. Further research is needed to determine the utility of biochemical markers in identifying high-risk patients with SIC.

Comprehensive Factors for Predicting the Complications of DiabetesMellitus: A Systematic Review

BACKGROUND

This article focuses on extracting a standard feature set for predicting the complications of diabetes mellitus by systematically reviewing the literature. It is conducted and reported by following the guidelines of PRISMA, a well-known systematic review and meta-analysis method. The research articles included in this study are extracted using the search engine "Web of Science" over eight years. The most common complications of diabetes, diabetic neuropathy, retinopathy, nephropathy, and cardiovascular diseases are considered in the study.

METHOD

The features used to predict the complications are identified and categorised by scrutinising the standards of electronic health records.

RESULT

Overall, 102 research articles have been reviewed, resulting in 59 frequent features being identified. Nineteen attributes are recognised as a standard in all four considered complications, which are age, gender, ethnicity, weight, height, BMI, smoking history, HbA1c, SBP, eGFR, DBP, HDL, LDL, total cholesterol, triglyceride, use of insulin, duration of diabetes, family history of CVD, and diabetes. The existence of a well-accepted and updated feature set for health analytics models to predict the complications of diabetes mellitus is a vital and contemporary requirement. A widely accepted feature set is beneficial for benchmarking the risk factors of complications of diabetes.

CONCLUSION

This study is a thorough literature review to provide a clear state of the art for academicians, clinicians, and other stakeholders regarding the risk factors and their importance.

Prognostic value of high-sensitivity cardiac troponin for major adverse cardiovascular events in patients with diabetes: a systematic review and meta-analysis

Background

High-sensitivity cardiac troponin (hs-cTn) is associated with cardiovascular outcomes in the general population, but the prognostic value of hs-cTn in the diabetic population remains inconclusive. This study aimed to systematically review current evidence regarding the association between hs-cTn and the prognosis of diabetic patients.

Methods

MEDLINE, Embase, and the Cochrane Database were searched from inception to May, 2023. Observational studies that investigated the prognostic value of hs-cTn in diabetic patients were included in this meta-analysis. Studies were excluded if they did not report outcomes of interest, or urine hs-cTn were measured. Two independent investigators extracted and analyzed the data according to the PRISMA guidelines. The primary outcome was long-term major adverse cardiovascular events (MACE).

Results

We included 30 cohort studies of 62,419 diabetic patients. After a median follow-up of 5 (4.1-9.5) years, the pooled results suggested elevation of hs-cTn was associated with a significantly increased risk of MACE (adjusted hazard ratio (HR) per standard deviation (SD) change 1.15, 95% CI [1.06-1.25], I2 = 0%) and heart failure (adjusted HR per SD change 1.33, 95% CI [1.08-1.63], I2 = 0%) in patients with diabetes. No significant association was found regarding the association between elevation of hs-cTn and risk of all-cause mortality (adjusted HR per SD change 1.24, 95% CI [0.98-1.57], I2 = 0%). The results of sensitivity analyses were similar in prospective cohort studies, high-quality studies, or population without major cardiovascular comorbidities at baseline. hs-cTn may represent a strong and independent predictor of MACE and heart failure in diabetic patients. Future research is warranted to determine the appropriate cutoff value for hs-cTn with different comorbidities, for instance, diabetic nephropathy, peripheral artery diseases, etc.

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

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.

Identification of endoplasmic reticulum stress-related biomarkers of diabetes nephropathy based on bioinformatics and machine learning

Backgrounds

Diabetes nephropathy (DN) is a growing public health concern worldwide. Renal dysfunction impairment in DN is intimately linked to ER stress and its related signaling pathways. Nonetheless, the underlying mechanism and biomarkers for this function of ER stress in the DN remain unknown.

Methods

Microarray datasets were retrieved from the Gene Expression Omnibus (GEO) database, and ER stress-related genes (ERSRGs) were downloaded from the MSigDB and GeneCards database. We identified hub ERSRGs for DN progression by intersecting ERSRGs with differentially expressed genes and significant genes in WGCNA, followed by a functional analysis. After analyzing hub ERSRGs with three machine learning techniques and taking the intersection, we did external validation as well as developed a DN diagnostic model based on the characteristic genes. Immune infiltration was performed using CIBERSORT. Moreover, patients with DN were then categorized using a consensus clustering approach. Eventually, the candidate ERSRGs-specific small-molecule compounds were defined by CMap.

Results

Several biological pathways driving pathological injury of DN and disordered levels of immune infiltration were revealed in the DN microarray datasets and strongly related to deregulated ERSRGs by bioinformatics multi-chip integration. Moreover, CDKN1B, EGR1, FKBP5, GDF15, and MARCKS were identified as ER stress signature genes associated with DN by machine learning algorithms, demonstrating their potential as DN biomarkers.

Conclusions

Our research sheds fresh light on the function of ER stress in DN pathophysiology and the development of early diagnostic and ER stress-related treatment targets in patients with DN.

Association of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and acute kidney disease in patients undergoing coronary angiography: a cohort study

BACKGROUND

Acute kidney disease (AKD) following coronary angiography (CAG) indicates a higher risk of chronic kidney disease and follow-up cardiovascular comorbidities. However, the predictive risk factor of AKD is not clear. We sought to verify whether preoperative N-terminal pro-B-type natriuretic peptide (NT-proBNP) level was associated with AKD in patients undergoing CAG.

METHOD

We analyzed 7602 patients underwent CAG in this multi-center registry cohort study. Cardiorenal ImprovemeNt II (CIN-II) in five Chinese tertiary hospitals from 2007 to 2020. The primary outcome was AKD, defined as a ≥ 50% increase of serum creatinine within 7-90 days. Multivariable logistic regressions were used to assess the association between NT-proBNP and AKD.

RESULT

1009 patients (13.27%) eventually developed AKD, who were more likely to be female, older, and with comorbidities of chronic heart failure and anemia. After adjusting to the potential confounders, the NT-proBNP level remained an independent predictor of AKD (lnNT-proBNP OR: 1.20, 95% CI 1.13-1.28, p < 0.005). Restricted cubic spline analysis demonstrated a linear relationship between elevated NT-proBNP and AKD (p for trend < 0.001). In the subgroup analysis, elevated NT-proBNP level in patients with percutaneous coronary intervention (p for interaction < 0.001) or without previous congestive heart failure (p for interaction = 0.0346) has a more significant value of AKD prediction.

CONCLUSION

Pre-operative NT-proBNP level was independently associated with the risk of AKD in patients following CAG. Perioperative strategies are warranted to prevent AKD in patients with elevated NT-proBNP levels.

N-Terminal Prohormone Brain Natriuretic Peptide as a Prognostic Biomarker for the Risk of Complications in Type 2 Diabetes: A Systematic Review and Meta-Analysis

Objective

This systematic review and meta-analysis aimed at summarizing the existing clinical evidence to evaluate the prognostic performance of N-terminal prohormone brain natriuretic peptide (NT-proBNP) in predicting cardiovascular events, cardiovascular-related mortality, and all-cause mortality in patients with type 2 diabetes.

Methods

Searches were performed in Medline, Embase, Scopus, and Web of Science databases before August 1, 2021. The data were recorded as adjusted hazard ratio (HR).

Results

An increase in NT-proBNP increases the risk of cardiovascular events (HR = 1.63), cardiovascular mortality (HR = 1.86) and all-cause mortality (HR = 1.54). Seemingly, the best cutoffs for predicting cardiovascular events (HR = 2.30) and cardiovascular mortality (HR = 3.77) are levels greater than 100 pg/mL. The best cutoff of NT-proBNP in predicting all-cause mortality is levels greater than 225 pg/mL (HR = 4.72).

Conclusion

A moderate level of evidence demonstrated that NT-proBNP serum levels can predict future cardiovascular events, cardiovascular mortality, and all-cause mortality. Thus, it can be used as risk stratification for type 2 diabetes.

NT-proBNP as a predictor of death and cardiovascular events in patients with type 2 diabetes

Existing risk prediction scores based on clinical and laboratory variables have been considered inaccurate in patients with Type 2 Diabetes Mellitus (T2DM). Circulating concentrations of natriuretic peptides have been used to aid in the diagnosis and to predict outcomes in heart failure. However, there is a growing body of evidence for the use of natriuretic peptides measurements, mainly N-terminal pro-B-type natriuretic peptide (NT-proBNP), as a tool in risk stratification for individuals with T2DM. Studies have demonstrated the ability of NT-proBNP to improve outcomes prediction when incorporated into multivariate models. More recently, evidence has emerged of the discriminatory power of NT-proBNP, demonstrating, as a single variable, a similar and even superior ability to multivariate risk models for the prediction of death and cardiovascular events in individuals with T2DM. Natriuretic peptides are synthesized and released from the myocardium as a counter-regulatory response to increased cardiac wall stress, sympathetic tone, and vasoconstriction, acting on various systems and affecting different biological processes. In this article, we present a review of the accumulated knowledge about these biomarkers, underscoring the strength of the evidence of their predictive ability for fatal and non-fatal outcomes. It is likely that, by influencing the functioning of many organs, these biomarkers integrate information from different systems. Although not yet recommended by guidelines, measurement of natriuretic peptides, and particularly NT-proBNP, should be strongly considered in the risk stratification of individuals with T2DM.

Development of clinical prediction models for renal and cardiovascular outcomes and mortality in patients with type 2 diabetes and chronic kidney disease using time-varying predictors

AIMS

To develop a set of prediction models for end-stage kidney disease (ESKD), cardiovascular outcomes, and mortality in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD) using commonly measured clinical variables.

METHODS

We studied 1432 participants with T2D and CKD enrolled in the Chronic Renal Insufficiency Cohort, followed for a median period of 7 years. We used Cox proportional-hazards models to model the six outcomes (ESKD, stroke, myocardial infarction (MI), congestive heart failure (CHF), death before ESKD, and all-cause mortality). We internally evaluated these models using concordance and calibration measures.

RESULTS

The newly developed six prediction models included 15 predictors: age at diabetes diagnosis, sex, blood pressure, body mass index, hemoglobin A1c, high density lipoprotein cholesterol, urine protein-to-creatinine ratio, estimated glomerular filtration rate, smoking status, and history of stroke, MI, CHF, ESKD, and amputation. The resulting models demonstrated good/strong discrimination (cross-validation C-index range: 0.70 to 0.90) and calibration.

CONCLUSIONS

This study provided an internally validated and useful tool for predicting individual adverse outcomes and mortality in patients with T2D and CKD. These models may inform optimal use of targeted health interventions.

Heterologous production of chondroitin

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Chondroitin sulfate (CS) is a glycosaminoglycan with a growing variety of applications.

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CS can be produced from microbial fermentation of native or engineered strains.

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Synthetic biology tools are being used to improve CS yields in different hosts.

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Integrated polymerization and sulfation can generate cost-effective CS.

Chondroitin sulfate (CS) is a glycosaminoglycan with a broad range of applications being a popular dietary supplement for osteoarthritis. Usually, CS is extracted from animal sources. However, the known risks of animal products use have been driving the search for alternative methods and sources to obtain this compound. Several pathogenic bacteria naturally produce chondroitin-like polysaccharides through well-known pathways and, therefore, have been the basis for numerous studies that aim to produce chondroitin using non-pathogenic hosts. However, the yields obtained are not enough to meet the high demand for this glycosaminoglycan. Metabolic engineering strategies have been used to construct improved heterologous hosts. The identification of metabolic bottlenecks and regulation points, and the screening for efficient enzymes are key points for constructing microbial cell factories with improved chondroitin yields to achieve industrial CS production. The recent advances on enzymatic and microbial strategies to produce non-animal chondroitin are herein reviewed. Challenges and prospects for future research are also discussed.

GDF-15, a future therapeutic target of glucolipid metabolic disorders and cardiovascular disease

Growth and differentiation factor 15 (GDF-15) was discovered as a member of the transforming growth factor β (TGF-β) superfamily and the serum level of GDF-15 was significantly correlated with glucolipid metabolic disorders (GLMD) and cardiovascular diseases. In 2017, a novel identified receptor of GDF-15-glial-derived neurotrophic factor receptor alpha-like (GFRAL) was found to regulate energy homeostasis (such as obesity, diabetes and non-alcoholic fatty liver disease (NAFLD)). The function of GDF-15/GFRAL in suppressing appetite, enhancing glucose/lipid metabolism and vascular remodeling has been gradually revealed. These effects make it a potential therapeutic target for GLMD and vascular diseases. In this narrative review, we included and reviewed 121 articles by screening 524 articles from literature database. We primarily focused on the function of GDF-15 and its role in GLMD/cardiovascular diseases and discuss its potential clinical application.

Association Between Circulating GDF-15 and Cardio-Renal Outcomes and Effect of Canagliflozin: Results From the CANVAS Trial

Background

Studies have suggested that sodium glucose co‐transporter 2 inhibitors exert anti‐inflammatory effects. We examined the association of baseline growth differentiation factor‐15 (GDF‐15), a marker of inflammation and cellular injury, with cardiovascular events, hospitalization for heart failure (HF), and kidney outcomes in patients with type 2 diabetes in the CANVAS (Canagliflozin Cardiovascular Assessment Study) and determined the effect of the sodium glucose co‐transporter 2 inhibitor canagliflozin on circulating GDF‐15.

Methods and Results

The CANVAS trial randomized 4330 people with type 2 diabetes at high cardiovascular risk to canagliflozin or placebo. The association between baseline GDF‐15 and cardiovascular (non‐fatal myocardial infarction, non‐fatal stroke, cardiovascular death), HF, and kidney (40% estimated glomerular filtration rate decline, end‐stage kidney disease, renal death) outcomes was assessed using multivariable adjusted Cox regression models. During median follow‐up of 6.1 years (N=3549 participants with available samples), 555 cardiovascular, 129 HF, and 137 kidney outcomes occurred. Each doubling in baseline GDF‐15 was significantly associated with a higher risk of cardiovascular (hazard ratio [HR], 1.2; 95% CI, 1.0‒1.3), HF (HR, 1.5; 95% CI, 1.2‒2.0) and kidney (HR, 1.5; 95% CI, 1.2‒2.0) outcomes. Baseline GDF‐15 did not modify canagliflozin’s effect on cardiovascular, HF, and kidney outcomes. Canaglifozin treatment modestly lowered GDF‐15 compared with placebo; however, GDF‐15 did not mediate the protective effect of canagliflozin on cardiovascular, HF, or kidney outcomes.

Conclusions

In patients with type 2 diabetes at high cardiovascular risk, higher GDF‐15 levels were associated with a higher risk of cardiovascular, HF, and kidney outcomes. Canagliflozin modestly lowered GDF‐15, but GDF‐15 reduction did not mediate the protective effect of canagliflozin.

Changes in the prognostic values of modern cardiovascular biomarkers in relation to duration of diabetes mellitus

BACKGROUND

Based on the complex pathophysiology of type 2 diabetes and atherosclerosis we hypothesized a dynamic change in prognostic value of cardiovascular biomarkers over time.

METHODS

In this prospective study 746 patients with type 2 diabetes mellitus, being followed up for 60 months were analysed. The primary endpoint was defined as unplanned hospitalization for cardiovascular disease or death. Beside others, especially the prognostic performance of the biomarkers of interest (GDF-15, NT-proBNP, hs-TnT) was evaluated in relation to quartiles of diabetes duration.

RESULTS

In patients having a diabetes duration below 7 years lnGDF-15 (HR 2.84; p < 0.01) and lnhs-TnT (HR 2.96; p < 0.01) were significant predictors of the primary endpoint. LnAge (HR 40.01; p < 0.01) and lnNT-proBNP (HR 1.56; p = 0.03) were significant predictors in patients with a diabetes duration between 7 and 12 years. In the third quartile (diabetes duration 12-22 years) lnurinary albumin to creatinine ratio (HR 1.25; p = 0.005) and lnNT-proBNP (HR 2.13, p < 0.001) predicted the endpoint. In patients with a diabetes duration above 22 years, lnAge (HR 75.35; p = 0.001) and lnNT-proBNP (HR 2.0; p < 0.01) were the only significant predictors of the endpoint.

CONCLUSION

Prognostic power of cardiovascular biomarkers changes dynamically in relation to duration of type 2 diabetes mellitus. In patients with shorter duration of the disease markers of subclinical cardiovascular dysfunction and inflammation perform better than markers of systemic advanced organ dysfunction and cardiovascular disease.

Importance of Identifying Novel Biomarkers of Microvascular Damage in Type 1 Diabetes

Microvascular complications of type 1 diabetes, which primarily include diabetic kidney disease, retinopathy, and neuropathy, are characterized by damage to the microvasculature of the kidney, retina, and neurons. The pathogenesis of these complications is multifactorial, and several pathways are implicated. These complications are often silent during their early stages, and once symptoms develop, there might be little to be done to cure them. Thus, there is a strong need for novel biomarkers to identify individuals at risk of microvascular complications at an early stage and guide the implementation of new therapeutic options for preventing their development and progression. Recent advancements in proteomics, metabolomics, and other 'omics' have led to the identification of several potential biomarkers of microvascular complications. However, biomarker discovery has met several challenges and, up to now, there are no new biomarkers that have been implemented into clinical practice. This highlights the need for further work in this area to move towards better diagnostic and prognostic approaches.

Associations of GDF-15 and GDF-15/adiponectin ratio with odds of type 2 diabetes in the Chinese population

PURPOSE

We elucidate the effect of Growth differentiation factor-15(GDF-15)/adiponectin ratio in improving the assessment value for odds of type 2 diabetes.

METHODS

Cross-sectional design. A total of 405 participants (135 patients with newly diagnosed type 2 diabetes, 135 age- and sex-matched participants with prediabetes, and 135 healthy controls) were collected from Guangzhou and Dongguan, China. The serum GDF-15 and adiponectin levels were measured by ELISA and latex-enhanced immunoturbidimetry. Logistic regression analysis and restricted cubic splines were used to evaluate the associations between diabetes and the indicators.

RESULTS

The low level of adiponectin and high GDF-15/adiponectin ratio were significantly associated with increased odds of type 2 diabetes, but not for GDF-15. Three clusters were identified based on the K-means clustering analysis. Compared to the lowest quartiles of adiponectin, the OR and 95% CI of the highest adiponectin with type 2 diabetes was 0.24 (0.07-0.74, p trend = 0.004) after adjusting for sex, age, BMI, and DBP only in cluster 1. After adjusting for confounding factors, subjects with the highest GDF-15/adiponectin ratio quartiles had 3.9 times (OR = 3.85, 95% CI = 0.76-24.25) and 3.8 times (OR = 3.80, 95% CI = 1.02-14.68) higher odds of type 2 diabetes in cluster 2 and cluster 3, respectively. The association between the GDF-15/adiponectin ratio and type 2 diabetes was attenuated, but still remarkable (OR = 3.18, 95% CI = 1.11-10.18), in cluster 1.

CONCLUSIONS

Higher GDF-15/adiponectin ratio is independently associated with increased odds of type 2 diabetes for all study populations, suggesting that the GDF-15/adiponectin ratio may be a better indicator of type 2 diabetes.

Relationship between plasma growth differentiation factor-15 level and estimated glomerular filtration rate in type 2 diabetes patients with and without albuminuria

AIM

To assess the relationship between growth differentiation factor-15 (GDF-15) levels and estimated glomerular filtration rate (eGFR) in type 2 diabetes mellitus (DM) patients with and without albuminuria.

METHODS

We examined 324 patients with type 2 DM in a cross-sectional study. eGFR was determined using equations from creatinine (eGFR_cr) and the combination of creatinine and cystatin C (eGFR_cr-cys). The patients were classified into two groups based on urinary albumin: creatinine ratio (ACR): the normoalbuminuria group (urinary ACR < 30 mg/g) and the albuminuria group (urinary ACR ≥ 30 mg/g).

RESULTS

In individuals both with and without albuminuria, higher GDF-15 levels were associated with lower eGFR_cr and eGFR_cr-cys. Plasma GDF-15 levels were inversely correlated with eGFR_cr in individuals both with and without albuminuria (γ = -0.624, p < 0.001 and γ = -0.509, p < 0.001, respectively). A multiple regression analysis showed that GDF-15 levels were significantly associated with eGFR_cr after adjusting for age, sex and other confounders, including urinary ACR as a continuous or categorical variable (β = -0.309, p < 0.001 and β = -0.318, p < 0.001, respectively). Similarly, these results were replicated when eGFR_cr-cys was considered instead of eGFR_cr in correlation and regression analyses.

CONCLUSION

GDF-15 levels were inversely associated with eGFR in patients with type 2 DM. This relationship was independent of albuminuria status.

Towards the best kidney failure prediction tool: a systematic review and selection aid

Background

Prediction tools that identify chronic kidney disease (CKD) patients at a high risk of developing kidney failure have the potential for great clinical value, but limited uptake. The aim of the current study is to systematically review all available models predicting kidney failure in CKD patients, organize empirical evidence on their validity and ultimately provide guidance in the interpretation and uptake of these tools.

Methods

PubMed and EMBASE were searched for relevant articles. Titles, abstracts and full-text articles were sequentially screened for inclusion by two independent researchers. Data on study design, model development and performance were extracted. The risk of bias and clinical usefulness were assessed and combined in order to provide recommendations on which models to use.

Results

Of 2183 screened studies, a total of 42 studies were included in the current review. Most studies showed high discriminatory capacity and the included predictors had large overlap. Overall, the risk of bias was high. Slightly less than half the studies (48%) presented enough detail for the use of their prediction tool in practice and few models were externally validated.

Conclusions

The current systematic review may be used as a tool to select the most appropriate and robust prognostic model for various settings. Although some models showed great potential, many lacked clinical relevance due to being developed in a prevalent patient population with a wide range of disease severity. Future research efforts should focus on external validation and impact assessment in clinically relevant patient populations.

Opposing Associations of NT-proBNP With Risks of Diabetes and Diabetes-Related Complications

OBJECTIVE

Circulating N-terminal pro B-type natriuretic peptide (NT-proBNP) is a classic diagnostic and prognostic marker for heart failure. However, it is inversely associated with diabetes risk. We aimed to investigate relationships of NT-proBNP with risk of diabetes-related complications in initially healthy individuals.

RESEARCH DESIGN AND METHODS

We performed a case-cohort study within the European Prospective Investigation Into Cancer and Nutrition (EPIC)-Potsdam cohort including a random subcohort (n = 1,294) and incident cases of type 2 diabetes (n = 649) and cardiovascular diseases (n = 478). Incident cases of type 2 diabetes (n = 545) were followed up for microvascular (n = 133) and macrovascular (n = 50) complications. Plasma NT-proBNP was measured at baseline in initially healthy participants.

RESULTS

In multivariable models, NT-proBNP was linearly inversely associated with incident type 2 diabetes with a hazard ratio (HR) (95% CI) per doubling in NT-proBNP of 0.91 (0.86, 0.98). The association was only observable in women (0.80 [0.72, 0.90]) compared with men (0.98 [0.91, 1.07]). Among people with incident diabetes, NT-proBNP was positively associated with diabetes complications: overall, 1.31 (1.13, 1.53); microvascular complications, 1.20 (1.01, 1.43); and macrovascular complications, 1.37 (1.03, 1.83).

CONCLUSIONS

Although higher NT-proBNP levels are associated with lower diabetes risk, NT-proBNP is a biomarker for vascular complications in people who develop diabetes independent of potential confounders. Thus, NT-proBNP might be informative to monitor risk for diabetes-related microvascular and macrovascular complications, which should be further explored in future prospective studies.

Plasma proteomic biomarker signature of age predicts health and life span

Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.

NT-proBNP by Itself Predicts Death and Cardiovascular Events in High-Risk Patients With Type 2 Diabetes Mellitus

Background NT-proBNP (N-terminal pro-B-type natriuretic peptide) improves the discriminatory ability of risk-prediction models in type 2 diabetes mellitus (T2DM) but is not yet used in clinical practice. We assessed the discriminatory strength of NT-proBNP by itself for death and cardiovascular events in high-risk patients with T2DM. Methods and Results Cox proportional hazards were used to create a base model formed by 20 variables. The discriminatory ability of the base model was compared with that of NT-proBNP alone and with NT-proBNP added, using C-statistics. We studied 5509 patients (with complete data) of 8561 patients with T2DM and cardiovascular and/or chronic kidney disease who were enrolled in the ALTITUDE (Aliskiren in Type 2 Diabetes Using Cardiorenal Endpoints) trial. During a median 2.6-year follow-up period, 469 patients died and 768 had a cardiovascular composite outcome (cardiovascular death, resuscitated cardiac arrest, nonfatal myocardial infarction, stroke, or heart failure hospitalization). NT-proBNP alone was as discriminatory as the base model for predicting death (C-statistic, 0.745 versus 0.744, P=0.95) and the cardiovascular composite outcome (C-statistic, 0.723 versus 0.731, P=0.37). When NT-proBNP was added, it increased the predictive ability of the base model for death (C-statistic, 0.779 versus 0.744, P<0.001) and for cardiovascular composite outcome (C-statistic, 0.763 versus 0.731, P<0.001). Conclusions In high-risk patients with T2DM, NT-proBNP by itself demonstrated discriminatory ability similar to a multivariable model in predicting both death and cardiovascular events and should be considered for risk stratification. Registration URL: https://www.clini​caltr​ials.gov; Unique identifier: NCT00549757.

The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications

INTRODUCTION

Cellular senescence is a rapidly growing field with potential relevance for the treatment of multiple human diseases. In the last decade, cellular senescence and the senescence-associated secretory phenotype (SASP) have emerged as central drivers of aging and many chronic diseases, including cancer, neurodegeneration, heart disease and osteoarthritis. Major efforts are underway to develop drugs that selectively eliminate senescent cells (senolytics) or alter the SASP (senomorphics) to treat age-related diseases in humans. The translation of senescence-targeting therapies into humans is still in early stages. Nonetheless, it is clear that proteomic approaches will facilitate the discovery of important SASP proteins, development of senescence- and SASP-derived biomarkers, and identification of therapeutic targets for senolytic and senomorphic drugs.

AREAS COVERED

We review recent proteomic studies of cellular senescence and their translational relevance and, particularly, characterization of the secretory phenotype and preclinical development of biomarkers (from 2008-2020, PubMed). We focus on emerging areas, such as the heterogeneity of senescent cells and the SASP, extracellular vesicles released by senescent cells, and validating biomarkers of aging in vivo.

EXPERT OPINION

Proteomic and multi-omic approaches will be important for the development of senescence-based biomarkers to facilitate and monitor future therapeutic interventions that target senescent cells.

Growth differentiation factor 15 (GDF-15) is a potential biomarker of both diabetic kidney disease and future cardiovascular events in cohorts of individuals with type 2 diabetes: a proteomics approach

Background: Diabetic kidney disease (DKD) is a leading risk factor for end-stage renal disease and is one of the most important risk factors for cardiovascular disease in patients with diabetes. It is possible that novel markers portraying the pathophysiological underpinning processes may be useful.Aim: To investigate the associations between 80 circulating proteins, measured by a proximity extension assay, and prevalent DKD and major adverse cardiovascular events (MACE) in type 2 diabetes.Methods: We randomly divided individuals with type 2 diabetes from three cohorts into a two-thirds discovery and one-third replication set (total n = 813, of whom 231 had DKD defined by estimated glomerular filtration rate <60 mg/mL/1.73 m² and/or urinary albumin-creatinine ratio ≥3 g/mol). Proteins associated with DKD were also assessed as predictors for incident major adverse cardiovascular events (MACE) in persons with DKD at baseline.Results: Four proteins were positively associated with DKD in models adjusted for age, sex, cardiovascular risk factors, glucose control, and diabetes medication: kidney injury molecule-1 (KIM-1, odds ratio [OR] per standard deviation increment, 1.65, 95% confidence interval [CI] 1.27-2.14); growth differentiation factor 15 (GDF-15, OR 1.40, 95% CI 1.16-1.69); myoglobin (OR 1.57, 95% CI 1.30-1.91), and matrix metalloproteinase 10 (MMP-10, OR 1.43, 95% CI 1.17-1.74). In patients with DKD, GDF-15 was significantly associated with increased risk of MACE after adjustments for baseline age, sex, microalbuminuria, and kidney function and (59 MACE events during 7 years follow-up, hazard ratio per standard deviation increase 1.43 [95% CI 1.03-1.98]) but not after further adjustments for cardiovascular risk factors.Conclusion: Our proteomics approach confirms and extends previous associations of higher circulating levels of GDF-15 with both micro- and macrovascular disease in patients with type 2 diabetes. Our data encourage additional studies evaluating the clinical utility of our findings.

A proteomic atlas of senescence-associated secretomes for aging biomarker development

The senescence-associated secretory phenotype (SASP) has recently emerged as a driver of and promising therapeutic target for multiple age-related conditions, ranging from neurodegeneration to cancer. The complexity of the SASP, typically assessed by a few dozen secreted proteins, has been greatly underestimated, and a small set of factors cannot explain the diverse phenotypes it produces in vivo. Here, we present the “SASP Atlas,” a comprehensive proteomic database of soluble proteins and exosomal cargo SASP factors originating from multiple senescence inducers and cell types. Each profile consists of hundreds of largely distinct proteins but also includes a subset of proteins elevated in all SASPs. Our analyses identify several candidate biomarkers of cellular senescence that overlap with aging markers in human plasma, including Growth/differentiation factor 15 (GDF15), stanniocalcin 1 (STC1), and serine protease inhibitors (SERPINs), which significantly correlated with age in plasma from a human cohort, the Baltimore Longitudinal Study of Aging (BLSA). Our findings will facilitate the identification of proteins characteristic of senescence-associated phenotypes and catalog potential senescence biomarkers to assess the burden, originating stimulus, and tissue of origin of senescent cells in vivo.

The first comprehensive proteomic characterization of senescence-associated secretory phenotypes (SASPs) to our knowledge reveals substantial heterogeneity based on senescence inducer and cell type. The SASP Atlas represents a valuable resource for the identification of further candidate biomarkers of ageing.

Defining reference intervals for a serum growth differentiation factor-15 (GDF-15) assay in a Caucasian population and its potential utility in diabetic kidney disease (DKD)

BACKGROUND

Growth differentiation factor-15 (GDF-15), a stress responsive cytokine, is a promising biomarker of renal functional decline in diabetic kidney disease (DKD). This study aimed primarily to establish normative data and secondarily to evaluate the potential utility of GDF-15 in DKD using Roche Diagnostics electrochemiluminescence immunoassay (ECLIA) in an Irish Caucasian population.

METHODS

Following informed consent, 188 healthy volunteers and 128 participants with diabetes (72 with and 56 without DKD) were recruited to a cross-sectional study. Baseline demographics, anthropometric measurements and laboratory measurements were recorded. Blood for GDF-15 measurement was collected into plain specimen tubes kept at room temperature and processed (centrifugation, separation of serum, freezing at -80 °C) within 1 h of phlebotomy pending batch analyses. Reference intervals were determined using the 2.5th and 97.5th percentiles for serum GDF-15 concentration.

RESULTS

Of 188 healthy participants, 63 failed to meet study inclusion criteria. The reference interval for serum GDF-15 was 399 ng/L (90% confidence interval [CI]: 399-399) - 1335 ng/L (90% CI: 1152-1445). Receiver operator characteristics (ROC) curve analysis for DKD determined the area under the ROC curve to be 0.931 (95% CI: 0.893-0.959; p<0.001). The optimum GDF-15 cutoff for predicting DKD was >1136 ng/L providing a diagnostic sensitivity and specificity of 94.4% and 79%, respectively, and positive likelihood ratio of 4.5:1 (95% CI: 3.4-6.0).

CONCLUSIONS

The reference interval for serum GDF-15 in a healthy Irish Caucasian population using Roche Diagnostics ECLIA was established and a preliminary determination of the potential of GDF-15 as a screening test for DKD was made. Further prospective validation with a larger DKD cohort will be required before the cutoff presented here is recommended for clinical use.

The clinical impact of growth differentiation factor-15 in heart disease: A 2019 update

Growth differentiation factor-15 (GDF-15), also known as macrophage inhibitory cytokine-1 (MIC-1) or non-steroidal anti-inflammatory drug-activated gene (NAG-1) has been identified as a biomarker of response to treatment and prognosis in cardiovascular diseases. GDF-15 is a member of the transforming growth factor-β superfamily and is involved in several pathological conditions such as inflammation, cancer, cardiovascular, pulmonary and renal diseases. Cardiac myocytes produce and secrete GDF-15 in response to oxidative stress, stimulation with angiotensin II or proinflammatory cytokines, ischemia, and mechanical stretch. Other cellular sources of GDF-15 production are macrophages, vascular smooth muscle cells, endothelial cells, and adipocytes, which secrete GDF-15 in response to oxidative or metabolic stress or stimulation of proinflammatory cytokines. GDF-15 is induced in hypertrophic and dilated cardiomyopathy after volume overload, ischemia, and heart failure. GDF-15 can be used as a marker of prognosis in patients with cardiovascular disorders, in combination with conventional prognostic factors, such as N-terminal pro B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hs-TnT).

Prognostication of clinical outcomes in diabetes mellitus: Emerging role of cardiac biomarkers

Type 2 diabetes mellitus (T2DM) remains substantial health problem and one of the most prevalent metabolic diseases worldwide. The impact of T2DM on CV mortality and morbidity is embedded through a nature evolution of the disease and is modulated by numerous risk factors, such as hypertension, obesity, dyslipidemia. There is large body of evidence regarding use of the cardiac biomarkers to risk stratification at higher CV risk individuals who belongs to general population and cohort with established CV disease. Although T2DM patients have higher incidence of cardiac and vascular complications than the general population, whether cardiac biomarkers would be effective to risk stratification of the T2DM is not fully understood. The aim of the review is to summarize our knowledge regarding clinical implementation of cardiac biomarkers in risk assessment for T2DM patients. The role of natriuretic peptides, soluble ST2, galectin-3, growth differentiation factor-15, and cardiac troponins are widely discussed.

Towards frailty biomarkers: Candidates from genes and pathways regulated in aging and age-related diseases

OBJECTIVE

Use of the frailty index to measure an accumulation of deficits has been proven a valuable method for identifying elderly people at risk for increased vulnerability, disease, injury, and mortality. However, complementary molecular frailty biomarkers or ideally biomarker panels have not yet been identified. We conducted a systematic search to identify biomarker candidates for a frailty biomarker panel.

METHODS

Gene expression databases were searched (http://genomics.senescence.info/genes including GenAge, AnAge, LongevityMap, CellAge, DrugAge, Digital Aging Atlas) to identify genes regulated in aging, longevity, and age-related diseases with a focus on secreted factors or molecules detectable in body fluids as potential frailty biomarkers. Factors broadly expressed, related to several "hallmark of aging" pathways as well as used or predicted as biomarkers in other disease settings, particularly age-related pathologies, were identified. This set of biomarkers was further expanded according to the expertise and experience of the authors. In the next step, biomarkers were assigned to six "hallmark of aging" pathways, namely (1) inflammation, (2) mitochondria and apoptosis, (3) calcium homeostasis, (4) fibrosis, (5) NMJ (neuromuscular junction) and neurons, (6) cytoskeleton and hormones, or (7) other principles and an extensive literature search was performed for each candidate to explore their potential and priority as frailty biomarkers.

RESULTS

A total of 44 markers were evaluated in the seven categories listed above, and 19 were awarded a high priority score, 22 identified as medium priority and three were low priority. In each category high and medium priority markers were identified.

CONCLUSION

Biomarker panels for frailty would be of high value and better than single markers. Based on our search we would propose a core panel of frailty biomarkers consisting of (1) CXCL10 (C-X-C motif chemokine ligand 10), IL-6 (interleukin 6), CX3CL1 (C-X3-C motif chemokine ligand 1), (2) GDF15 (growth differentiation factor 15), FNDC5 (fibronectin type III domain containing 5), vimentin (VIM), (3) regucalcin (RGN/SMP30), calreticulin, (4) PLAU (plasminogen activator, urokinase), AGT (angiotensinogen), (5) BDNF (brain derived neurotrophic factor), progranulin (PGRN), (6) α-klotho (KL), FGF23 (fibroblast growth factor 23), FGF21, leptin (LEP), (7) miRNA (micro Ribonucleic acid) panel (to be further defined), AHCY (adenosylhomocysteinase) and KRT18 (keratin 18). An expanded panel would also include (1) pentraxin (PTX3), sVCAM/ICAM (soluble vascular cell adhesion molecule 1/Intercellular adhesion molecule 1), defensin α, (2) APP (amyloid beta precursor protein), LDH (lactate dehydrogenase), (3) S100B (S100 calcium binding protein B), (4) TGFβ (transforming growth factor beta), PAI-1 (plasminogen activator inhibitor 1), TGM2 (transglutaminase 2), (5) sRAGE (soluble receptor for advanced glycosylation end products), HMGB1 (high mobility group box 1), C3/C1Q (complement factor 3/1Q), ST2 (Interleukin 1 receptor like 1), agrin (AGRN), (6) IGF-1 (insulin-like growth factor 1), resistin (RETN), adiponectin (ADIPOQ), ghrelin (GHRL), growth hormone (GH), (7) microparticle panel (to be further defined), GpnmB (glycoprotein nonmetastatic melanoma protein B) and lactoferrin (LTF). We believe that these predicted panels need to be experimentally explored in animal models and frail cohorts in order to ascertain their diagnostic, prognostic and therapeutic potential.

Biomarkers of diabetic kidney disease

Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.

Growth differentiation factor-15 and fibroblast growth factor-23 are associated with mortality in type 2 diabetes - An observational follow-up study

Objectives

Two biomarkers, growth differentiation factor 15 (GDF-15) and fibroblast growth factor 23 (FGF-23)), reflecting different aspects of renal pathophysiology, were evaluated as determinants of decline in estimated glomerular filtration rate (eGFR), incident cardiovascular disease (CVD) and all-cause mortality in patients with type 2 diabetes (T2D) and microalbuminuria, but without clinical cardiac disease.

Materials and methods

Prospective study including 200 T2D patients. The predefined endpoint of chronic kidney disease (CKD) progression: A decline in eGFR of >30% at any time point during follow-up. Hazard ratios (HR) are provided per 1 SD increment of log2-transformed values.

Results

Mean (± SD) age was 59 ± 9 years, eGFR 91.1 ± 18.3 ml/min/1.73m² and median (IQR) UAER 103 (39–230) mg/24-h. During a median 6.1 years follow-up, 40 incident CVD events, 26 deaths and 42 patients reached the CKD endpoint after median 4.9 years. Higher GDF-15 was a determinant of decline in eGFR >30% and all-cause mortality in adjusted models (HR 1.7 (1.1–2.5); p = 0.018 and HR 1.9 (1.2–2.9); p = 0.003, respectively). Adding GDF-15 to traditional risk factors improved risk prediction of decline in renal function (relative integrated discrimination improvement (rIDI) = 30%; p = 0.037). Higher FGF-23 was associated with all-cause mortality in adjusted models (HR 1.6 (1.1–2.2); p = 0.011) with a rIDI of 30% (p = 0.024).

Conclusions

In patients with T2D and microalbuminuria, higher GDF-15 and FGF-23 were independently associated with all-cause mortality and higher GDF-15 improved risk prediction of decline in kidney function and higher FGF-23 of all-cause mortality, beyond traditional risk factors, but not independently of GDF-15.

Novel Biomarkers for Predicting Cardiovascular Disease in Patients With Diabetes

It is generally acknowledged that patients with diabetes comprise a high-risk population for the development of cardiovascular disease. However, it is perhaps less well recognized that there actually exists considerable heterogeneity in vascular risk within this patient population, with a sizable subset of individuals seemingly at low risk for major cardiovascular events despite the presence of diabetes. Because traditional clinical risk calculators have shown wide variability in their performance in the setting of diabetes, there exists a need for additional risk predictors in this patient population. In this context, there has been considerable interest in the potential utility of circulating biomarkers as clinical tools that might facilitate risk stratification and thereby guide therapeutic and preventative decision-making. Coupled with the current era of dedicated cardiovascular outcome trials in type 2 diabetes, this interest has spawned a growing literature of recent studies that evaluated potential biomarkers. To date, these studies have identified N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponins, and growth differentiation factor-15 as cardiovascular biomarkers of particular potential in patients with diabetes. Furthermore, recognizing the potential benefit of collective consideration of different biomarkers reflecting distinct pathophysiologic processes that might contribute to the development of cardiovascular disease, there is emerging emphasis on the evaluation of combinations of biomarkers for optimal risk prediction. Although not currently ready for clinical practice, this rapidly-growing topic of biomarker research might ultimately facilitate the goal of individualized risk stratification and thereby enable truly personalized management of diabetes.