This paper aims to examine the current landscape of novel biomarkers in diabetes mellitus (DM), with particular emphasis on emerging candidates, and their roles in early diagnosis, monitoring disease progression, risk stratification, and managing complications. Given the global prevalence of DM and its complex pathophysiology, identifying reliable biomarkers is critical for optimizing prevention strategies and personalized treatment approaches. This review highlights the shift from traditional glycemic markers, which remain clinically useful but limited, to a broader array of novel biomarkers that more accurately reflect the complex pathophysiology of DM. In addition to conventional measures, inflammatory and oxidative stress mediators, along with genetic and epigenetic regulators, provide added predictive value for disease susceptibility, progression, and complications. Recent research has identified emerging biomarkers, such as adiponectin, adropin, netrin-1, α-hydroxybutyrate, fetuin-A, lipo-protein(a), and lysophosphatidylcholine, which detect early metabolic imbalances and reveal mechanistic links to insulin resistance, β-cell dysfunction, and vascular injury. Their integration into multimarker panels holds particular promise for precision medicine, supporting tailored prevention, targeted therapy, and improved outcomes for individuals with prediabetes and DM.

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder characterized not only by impaired carbohydrate metabolism but also by alterations in lipid and protein metabolism. Hyperglycaemia in T2DM can promote the excessive production of reactive oxygen species (ROS), leading to oxidative stress. 8-Hydroxy-2′-deoxyguanosine (8-OHdG) is a biomarker of oxidative DNA damage commonly used to investigate oxidative stress. Methods: In this cross-sectional analytical observational study, patients diagnosed with T2DM and healthy controls were enrolled. Plasma 8-OHdG concentrations were measured using an enzyme-linked immunosorbent assay (ELISA). Associations between 8-OHdG concentrations and age, fasting blood glucose, and lipid profile parameters were evaluated. These associations were further explored in patient subgroups defined according to glycated haemoglobin (HbA1c) levels. Results: Patients with T2DM had higher plasma 8-OHdG concentrations than healthy controls (Cohen’s d = 1.092; 95% CI, 0.646–1.532; p < 0.001). After adjustment for age, the between-group difference was attenuated, with an adjusted mean difference of 28.84 ng/mL (95% CI, 0.278–57.41; p = 0.048). In the overall cohort, statistically significant correlations were identified between 8-OHdG levels and age (ρ = 0.379; 95% CI, 0.164–0.556; p < 0.001), fasting blood glucose (ρ = 0.266; 95% CI, 0.059–0.474; p = 0.011), and triglycerides (ρ = 0.376, 95% CI, 0.178–0.554; p < 0.001). Stratification of patients according to HbA1c levels revealed no statistically significant differences in 8-OHdG concentrations among the subgroups. Furthermore, none of the correlations examined within these subgroups remained statistically significant after adjustment for multiple testing. Conclusions: Plasma 8-OHdG concentrations were higher in patients with T2DM than in healthy controls, although the magnitude of the between-group difference was attenuated after adjustment for age. In the overall study population, 8-OHdG concentrations were associated with age, fasting blood glucose, and triglyceride concentrations. These findings suggest that 8-OHdG levels may be associated with demographic and metabolic factors. Given the cross-sectional design, these associations should not be interpreted as causal. Further prospective studies with larger cohorts are needed to evaluate the potential clinical relevance of plasma 8-OHdG measurement in T2DM.

Background/Objectives: Our study aimed to evaluate the oral health status associated with levels of certain inflammatory biomarkers in the gingival crevicular fluid (GCF) and plasma of children and adolescents with leukemia, in comparison to healthy subjects, in order to assess the correlation between pediatric leukemia and gingivo-periodontal alterations. Methods: The study was conducted on 97 subjects, divided into two groups: the study group, n = 47 leukemia subjects, and the control group, n = 50 healthy subjects. The collected GCF and plasma samples were analyzed for interleukins IL-1β, IL-6 and IL-17α and transforming growth factor TGF-β1 values using ELISA (enzyme-linked immunosorbent assay) techniques. Results: IL-6, IL-17α, and TGF-β1 recorded higher values for leukemia subjects, both in the GCF and plasma, compared to healthy subjects. Our results also pointed out higher gingival fluid IL-1β values in children with leukemia compared to the control group. Conclusions: Elevated expressions of IL-1β in the GCF and IL-6, IL-17α, and TGF-β1, both systemic and local, in the GCF of children with leukemia were associated with oral hygiene status and gingival inflammation, respectively. All inflammatory biomarkers generally tended to rise in close correlation with oral hygiene worsening and gingival inflammation extension; however, IL-1β in the GCF and plasma, plasma IL-6, and gingival fluid IL-17α pointed out a stronger correlation with gingival inflammation status.