Biomarkers of diabetes: role in the pathogenesis of atrial fibrillation.

The prevalence of both atrial fibrillation (AF) and diabetes is increasing day by day and commonly co-exist with a longer duration of diabetes and poor control, putting the individual at higher risk of AF. This review article presented some traditional and novel biomarkers related to AF in patients with diabetes mellitus. The literature review employed several databases, including Google Scholar, PubMed, and Science Direct. The investigation was finished on October 30, 2023. Many terms are utilized, including "AF", "Biomarkers", "Diabetes Mellitus", and "Pathogenesis". There are numerous biomarkers of diabetes, but this review article reports only leptin, adiponectin, glycated hemoglobin, ceramide, ferritin, fibrinogen, hematological indices, interleukin-18, thrombospondin 1, acylcarnitine, plasminogen activator inhibitor-1 and triglycerides and high-density lipoprotein cholesterol, since those biomarkers play a significant role in the pathogenesis of AF. However, no data was found, including fructosamine, glycated albumin, 1,5 anhydroglucitol, fetuin-A, α-hydroxybutyrate, mannose-binding lectin serine peptidase, transferrin, IL-1 receptor antagonist in AF. Understanding the interplay between diabetes and AF through the measurement of relevant biomarkers can contribute to better risk assessment, early detection, and the development of targeted therapeutic strategies for individuals at risk or already affected by these conditions.

Novel anthropometric parameters in the adult population with prediabetes.

OBJECTIVE: Although it is assumed that novel-derived anthropometric indices can better reflect cardiometabolic risk than traditional ones, the results are conflicting. Previous studies have mainly focused on patients with type 2 diabetes mellitus. However, studies conducted on populations with prediabetes are scarce. The present study aimed to examine the potential relationship between prediabetes and novel anthropometric parameters [that is, cardiometabolic index (CMI), visceral adiposity index (VAI), lipid accumulation product index (LAP), body roundness index (BRI), and body adiposity index (BAI)] and traditional parameters [that is, waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR)] in adults with prediabetes. PATIENTS AND METHODS: This case-control cross-sectional study included 177 patients with prediabetes and 609 control subjects. Biochemical and simple anthropometric parameters were measured (WC, HC, body weight, and height), whereas the other parameters were calculated. RESULTS: WC, CMI, VAI, and LAP independently correlated with prediabetes. Principal component analysis (PCA) was used to extract several factors that correlated with prediabetes. Significant predictive capability was demonstrated for non-traditional anthropometric/lipid-related factors and WHipR-related factors for prediabetes (OR=1.334 and OR=1.202, respectively). However, only non-traditional anthropometric/lipid-related factors (i.e., VAI, CMI, and LAP) demonstrated an independent significant positive relationship with prediabetes in multivariate binary regression analysis. CONCLUSIONS: CMI, VAI, and LAP could be superior to BAI, BRI, and conventional anthropometric parameters for discriminating patients with prediabetes in the adult population. Prospective trials are needed to confirm our results.

Red cell distribution width is inversely associated with body mass index in late adolescents.

OBJECTIVE: There are no studies that investigated the association between red blood cell (RBC) and platelet (PLT) indices in relation to obesity in a cohort of exclusively late adolescents. Hence, we aimed to explore this potential relationship. PATIENTS AND METHODS: A cohort of adolescents (n=156) aged between 16-19 years was included. Iron homeostasis parameters [i.e. RBC, hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) and red cell distribution width (RDW)] and platelet indices [i.e., PLT, mean platelet volume (MPV), plateletcrit (PCT) and platelet distribution width (PDW)] were determined on the automatic hematology analyzer. Their indexes (i.e. MCV/RBC, MCH/RBC, RDW/MCV, MPV/PLT and PDW/PCT) were calculated. RESULTS: Univariate binary regression analysis showed negative associations between body mass index (BMI) and RDW, PDW, and PDW/PCT, respectively, and positive associations between BMI and MPV and PCT, respectively. However, only RDW kept the independent negative association with BMI in multivariate binary regression analysis [Odds Ratio (95% Confidence Interval)=0.734 (0.548-0.983); p=0.038]. CONCLUSIONS: Lower RDW values are the independent predictor of higher BMI in the adolescent population. As a low-cost and simply measured parameter, RDW could be a useful diagnostic biomarker in young populations with overweight/obesity.

Total leukocyte count, leukocyte subsets and their indexes in relation to cardiovascular risk in adolescent population.

OBJECTIVE: No studies investigated total leukocytes, their subpopulations and novel indexes based on different ratios of leukocyte subsets concerning cardiovascular risk (CV) risk in late adolescents. Therefore, the aim of the present study was to explore such potential relationships. PATIENTS AND METHODS: A total of 156 adolescents were included. CV risk score was calculated by summarizing each risk factor (i.e., female sex, low high density lipoprotein cholesterol (HDL-c), high non-HDL-c, smoking, blood pressure, and fasting glycemia). Adolescents were divided into a low CV risk score (i.e., -2≤ CV risk score ≤1) and moderate/higher CV risk score (i.e., CV risk score ≥ 2). White blood cell count (WBC) and its subsets were analyzed on an automatic device. The indexes were calculated. RESULTS: Total and differential WBC counts except basophil count were higher in moderate/higher CV risk participants. Multivariate binary regression analysis showed that total WBC count independently increased CV risk score by 1.623 times (p=0.001). Neutrophil and eosinophil counts (p=0.027 and p=0.010, respectively) were independently able to increase CV risk score by 1.486 and 1.556 times, respectively. On the contrary, indexes were not independently correlated with CV risk. CONCLUSIONS: WBC, neutrophil, and eosinophil count are the independent predictors of increased CV risk in adolescents. The associations may indicate the different pathways that lead to CV disease in adulthood.