Adropin Predicts Chronic Kidney Disease in Type 2 Diabetes Mellitus Patients with Chronic Heart Failure

Adropin: A crucial regulator of cardiovascular health and metabolic balance

Adropin, a peptide discovered in 2008, has gained recognition as a key regulator of cardiovascular health and metabolic balance. Initially identified for its roles in energy balance, lipid metabolism, and glucose regulation, adropin has also been found to improve cardiovascular health by enhancing endothelial function, modulating lipid profiles, and reducing oxidative stress. These protective mechanisms suggest that adropin may be able to help prevent conditions such as atherosclerosis, hypertension, and other cardiovascular diseases. Research has established connections between adropin and cardiovascular risk factors, such as obesity, insulin resistance, and dyslipidemia, positioning it as a valuable biomarker for evaluating cardiovascular disease risk. New studies highlight adropin's diagnostic and prognostic significance, showing that higher levels are linked to better cardiovascular outcomes, while lower levels are associated with a higher risk of cardiovascular diseases. This review aims to summarize current knowledge on adropin, emphasizing its significance as a promising focus in the intersection of cardiovascular health and metabolic health. By summarizing the latest research findings, this review aims to offer insights into the potential applications of adropin in both clinical practice and research, leading to a deeper understanding of its role in maintaining cardiovascular and metabolic health.

Methods to predict heart failure in diabetes patients

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is one of the leading causes of cardiovascular disease and powerful predictor for new-onset heart failure (HF).

AREAS COVERED

We focus on the relevant literature covering evidence of risk stratification based on imaging predictors and circulating biomarkers to optimize approaches to preventing HF in DM patients.

EXPERT OPINION

Multiple diagnostic algorithms based on echocardiographic parameters of cardiac remodeling including global longitudinal strain/strain rate are likely to be promising approach to justify individuals at higher risk of incident HF. Signature of cardiometabolic status may justify HF risk among T2DM individuals with low levels of natriuretic peptides, which preserve their significance in HF with clinical presentation. However, diagnostic and predictive values of conventional guideline-directed biomarker HF strategy may be non-optimal in patients with obesity and T2DM. Alternative biomarkers affecting cardiac fibrosis, inflammation, myopathy, and adipose tissue dysfunction are plausible tools for improving accuracy natriuretic peptides among T2DM patients at higher HF risk. In summary, risk identification and management of the patients with T2DM with established HF require conventional biomarkers monitoring, while the role of alternative biomarker approach among patients with multiple CV and metabolic risk factors appears to be plausible tool for improving clinical outcomes.

Plausible prediction of renoprotective effects of sodium-glucose cotransporter-2 inhibitors in patients with chronic kidney diseases

This narrative review was conducted due to uncertainty in predicting the beneficial impact of sodium-glucose cotransporter-2 (SGLT2) inhibitors on a dip of estimated glomerular filtration rate (eGFR), regardless of albuminuria presence, with the aim of elucidating plausible predictors of kidney function outcome among patients treated with SGLT2 inhibitors. The PubMed and Web of Science databases were searched in May 2023 for relevant articles published in English between 2013 and 2023. A total of 25 full-length scientific publications (comprising 11 large randomized trials and two cohort studies) were included for analysis. The majority of studies demonstrated a limited value of conventional biomarkers, such as initial decline in eGFR, a trajectory of eGFR during SGLT2 inhibitor administration, and urine albumin-to-creatinine ratio (UACR), in prediction of renoprotection. Included studies showed that the tendency to decreased eGFR, UACR, hemoglobin, glycosylated hemoglobin, lipid profile, serum uric acid, inflammatory biomarkers and natriuretic peptides did not predict clinical outcomes in groups without heart failure (HF) treated with SGLT2 inhibitors. In HF groups, biomarkers of inflammation, kidney injury, oxidative stress, mitochondrial dysfunction, ketogenesis, energy metabolism, and adipose tissue dysfunction (adropin and irisin), were detected with the aim of finding potential biomarkers. Biomarkers of adipose tissue dysfunction and inflammation may be promising for predicting SGLT2 inhibitor benefit compared with N-terminal pro-B-type natriuretic peptide and energy metabolism indicators.

Predictors of Kidney Function Outcomes and Their Relation to SGLT2 Inhibitor Dapagliflozin in Patients with Type 2 Diabetes Mellitus Who Had Chronic Heart Failure

INTRODUCTION

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have a favorable impact on the kidney function in patients with heart failure (HF), while there is no clear evidence of what factors predict this effect. The aim of the study was to identify plausible predictors for kidney function outcome among patients with HF and investigate their association with SGLT2i.

METHODS

We prospectively enrolled 480 patients with type 2 diabetes mellitus (T2DM) treated with diet and metformin and concomitant chronic HF and followed them for 52 weeks. In the study, we determined kidney outcome as a composite of ≥ 40% reduced estimated glomerular filtration rate from baseline, newly diagnosed end-stage kidney disease or kidney replacement therapy. The relevant medical information and measurement of the biomarkers (N-terminal natriuretic pro-peptide, irisin, apelin, adropin, C-reactive protein, tumor necrosis factor-alpha) were collected at baseline and at the end of the study.

RESULTS

The composite kidney outcome was detected in 88 (18.3%) patients of the entire population. All patients received guideline-recommended optimal therapy, which was adjusted to phenotype/severity of HF, cardiovascular risk and comorbidity profiles, and fasting glycemia. Levels of irisin, adropin and apelin significantly increased in patients without clinical endpoint, whereas in those with composite endpoint the biomarker levels exhibited a decrease with borderline statistical significance (p = 0.05). We noticed that irisin ≤ 4.50 ng/ml at baseline and a ≤ 15% increase in irisin serum levels added more valuable predictive information than the reference variable. However, the combination of irisin ≤ 4.50 ng/ml at baseline and ≤ 15% increase in irisin serum levels (area under curve = 0.91; 95% confidence interval = 0.87-0.95) improved the discriminative value of each biomarker alone.

CONCLUSION

We suggest that low levels of irisin and its inadequate increase during administration of SGLT2i are promising predictors for unfavorable kidney outcome among patients with T2DM and concomitant HF.

Clinical Significance of Adropin and Afamin in Evaluating Renal Function and Cardiovascular Health in the Presence of CKD-MBD Biomarkers in Chronic Kidney Disease

AIM

The study aims to test the hypothesis that concentrations of adropin and afamin differ between patients in various stages of chronic kidney disease when compared with healthy controls. The study also investigates the association of the biomarkers (adropin and afamin) with CKD-MBD and traditional cardiovascular risk parameters in CKD patients.

METHODOLOGY

The cross-sectional study includes the subjects divided into four groups comprising the control group (healthy volunteers = 50), CKD stages 1-2 patients (n = 50), CKD stages 3-4 patients (n = 50), CKD stage 5 patients (n = 50). Serum concentrations of adropin and afamin were determined using ELISA. Clinical variables (renal, lipid, and CKD-MBD parameters) were correlated to adropin and afamin concentrations.

RESULTS

Afamin concentration was found to be higher in group IV, followed by groups III and II when compared to the control group, i.e., (83.243 ± 1.46, 64.233 ± 0.99, and 28.948 ± 0.72 vs. 14.476 ± 0.5) mg/L (p < 0.001), and adropin concentration was found to be lower in group IV as compared to groups III, II, and I (200.342 ± 8.37 vs. 284.682 ± 9.89 vs. 413.208 ± 12.32 vs. 706.542 ± 11.32) pg/mL (p < 0.001), respectively. Pearson correlation analysis showed that afamin was positively correlated with traditional cardiovascular risk biomarkers, while adropin showed a negative correlation.

CONCLUSIONS

Adropin and afamin may potentially serve as futuristic predictors for the deterioration of renal function and may be involved in the pathological mechanisms of CKD and its associated complications such as CKD-MBD and high lipid levels.

Serum Adropin Levels and Body Mass Composition in Kidney Transplant Recipients-Are There Sex Differences?

Adropin is a secretory peptide that regulates glucose, lipid, and protein metabolism, which is closely related to obesity, insulin resistance, dyslipidemia, and atherogenesis. The serum adropin level is related to sex and depends upon nutritional preferences. This study aims to determine the association between serum adropin levels and body composition parameters in kidney transplant recipients (KTRs), especially emphasizing sex differences. Our case-control study involved 59 KTRs (28 postmenopausal women and 31 men) who were divided into two groups according to sex, and each group of those KTRs was further divided into higher or lower adropin values than the mean value in each sex group. Univariate regression showed a negative association of adropin levels with most anthropometric and body composition parameters in men's KTRs. Contrary to this, the serum adropin level was negatively associated only with phase angle in postmenopausal female KTRs. Multivariate regression showed that skeletal muscle mass and phase angle were the only negative predictors in women's KTRs, whereas in men, negative predictors were BMI and body water. These findings imply that adropin could have a different impact on metabolic homeostasis in KTRs regarding sex and could be considered a negative predictor of body composition in KTRs.