Search Results (15,590)

Background/Objectives: Type 1 diabetes (T1D) is a heterogeneous disease in terms of clinical presentation, treatment requirements, and risk of complications. The identification of biological endotypes and clinical phenotypes has been proposed to support precision medicine approaches. We aimed to assess the prevalence and clinical characteristics of age-at-diagnosis-based endotypes, adult-onset phenotypes, and insulin-resistant phenotypes in a real-world cohort of adults with T1D. Methods: We conducted a single-center, observational, cross-sectional study including adults (≥18 years) with clinically confirmed T1D under active follow-up. Clinical, metabolic, and treatment-related variables were analyzed across predefined age-at-diagnosis-based endotypes and clinical phenotypes. Results: A total of 868 patients were included (median age 49 years; diabetes duration 23 years; age at diagnosis 20 years; 51.5% women). Continuous subcutaneous insulin infusion (CSII) was used by 20.4% of patients, and continuous glucose monitoring (CGM) was used by 95.3%. Mean HbA1c was 7.47%, with a median time in range (TIR) of 63%. The prevalence of age-at-diagnosis-based endotype 1 (ED1) was 11.8%, adult-onset phenotype was 31.3%, and insulin-resistant phenotype was 7.3%. No major differences in glycemic control were observed across age-at-diagnosis-based endotypes. Associations between endotypes and treatment-related variables were largely explained by current age and diabetes duration. In contrast, the adult-onset phenotype was independently associated with lower TIR, higher time above range, lower use of CSII, and greater use of adjunctive therapies. The insulin-resistant phenotype was associated with higher HbA1c, lower TIR, and greater therapeutic complexity. Conclusions: Adult T1D shows marked heterogeneity. In this real-world cohort, age-at-diagnosis-based endotypes were not independently associated with major clinical differences after adjustment for current age and diabetes duration. In contrast, adult-onset and insulin-resistant phenotypes identified subgroups with poorer glycemic control and greater therapeutic complexity. Full article

Background/Objectives: Advanced technologies in type 1 diabetes mellitus (T1DM) management have reshaped the strategies used to achieve optimal glucose control. Continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems are effective alternatives to multiple daily injections (MDI). This study aims to evaluate glycemic regulation in children and adolescents transitioning from MDI to insulin pumps and to raise awareness among patients and their families regarding the benefits of these systems. Methods: 50 pediatric patients with T1DM (24 males, 26 females; mean age 10.76 ± 3.2 years) were evaluated. Cycle 1 established MDI metrics 3 months pre-transition. In cycle 2, patients transitioned either to an AID system (Medtronic MiniMed 780G, (Northridge, CA, USA), 78%), or a non-automated system (Omnipod DASH, 22%). Data were assessed at 3 and 6 months post-initiation. Parameters assessed were glycosylated hemoglobin (HbA1c), time in range (TIR), time above range (TAR), time below range (TBR), glucose management indicator (GMI) and coefficient of variation (CV). Results: The cohort exhibited a statistically significant increase in TIR (p = 0.0038) with mean values of 70.9% at 3 months and 73.2% at 6 months. TAR significantly reduced (p = 0.033) to 26.5% and 24.3% at 3 and 6 months, respectively. Sub-analysis in the AID group revealed a marked increase in TIR (p = 0.0001) alongside significant reductions in TAR (p = 0.0009) and GMI (p = 0.03). Conclusions: Transitioning from MDI to insulin pump therapy, particularly AID systems, leads to modest but significant improvements in specific sensor metrics (TIR, TAR) in real-world clinical practice. The consistency of these results across age groups indicates that AID systems can successfully overcome pediatric and adolescent diabetes management challenges. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder associated with substantial long-term morbidity and mortality. Routinely collected anthropometric, biochemical, and hematological variables may contain useful discriminatory information for data-driven classification. This study aimed to compare the apparent classification performance of multiple machine learning algorithms for distinguishing individuals with and without T2DM using routinely obtained clinical parameters in a single-center dataset. Methods: This single-center observational study included 160 adults (95 females, 65 males) evaluated at the Endocrinology Outpatient Clinic of Gaziantep Islam Science and Technology University, Faculty of Medicine, Ersin Arslan Training and Research Hospital. The dataset comprised anthropometric measurements, biochemical markers, and complete blood count parameters. SMOTE was applied only within the training folds to address class imbalance and to avoid information leakage. Following fold-internal data preprocessing, which included imputing missing values and feature standardization where appropriate, the dataset was evaluated using stratified 5-fold cross-validation. SHAP analysis was performed to interpret the model predictions. A calibration curve was used to assess the model’s reliability. Eight supervised machine learning models were evaluated with and without HbA1c: Logistic Regression, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Decision Tree, Random Forest, Extra Trees, Gaussian Naive Bayes, and k-Nearest Neighbors. Model performance was evaluated using accuracy, sensitivity, specificity, and F1 score, and ROC curves were used as a diagnostic tool. Results: The models were evaluated in two different ways: with and without HbA1c. Random Forest demonstrated the best classification performance in the cross-validated evaluation; without HbA1c, it achieved 92.2% accuracy, 93.9% sensitivity, 97.9% specificity, and a 95.9% F1 score. When HbA1c was included, it achieved 98.0% accuracy, 97.9% sensitivity, 98.8% specificity, and a 99.0% F1 score. Decision Tree and Extra Trees demonstrated strong performance with accuracy rates of 87.6% and 92.8%, respectively, without HbA1c, and 90% and 93.5% when HbA1c was included; in contrast, KNN yielded the lowest accuracy rate (70.6%). Overall, tree-based models performed better than linear classifiers on this dataset. Conclusions: Machine learning models based on routine clinical and anthropometric variables demonstrated promising performance for T2DM classification in this single-center dataset; tree-based approaches yielded the most promising results. Including HbA1c improved the models’ ability to classify individuals with and without T2DM. However, since HbA1c was included both as a predictor and as part of the operational definition of the diabetes group, the findings should be interpreted with caution due to the risk of target leakage. Therefore, these results should be considered exploratory rather than evidence of clinically applicable predictive performance, and an independent external validation study should be conducted prior to clinical application. Full article

Hypertrophic cardiomyopathy (HCM) is the most common inherited myocardial disorder and a major cause of heart failure (HF) and sudden cardiac death. Although sarcomeric gene mutations initiate the disease, increasing evidence identifies oxidative stress, mitochondrial dysfunction, and maladaptive nutrient signaling as key drivers of disease progression. Enhanced reactive oxygen species (ROS) production in HCM promotes energetic impairment, calcium mishandling, fibrosis, and the activation of pro-hypertrophic pathways, while disrupting protein quality control and endothelial function. Despite recent therapeutic advances, effective disease-modifying strategies targeting these molecular mechanisms remain limited. Sodium–glucose cotransporter 2 inhibitors (SGLT2i), originally developed for type 2 diabetes, have demonstrated robust cardioprotective effects in HF independent of glycemic control. Beyond their renal actions, SGLT2i modulate myocardial metabolism, reduce oxidative stress, improve mitochondrial function, restore sodium and calcium homeostasis, and attenuate inflammation and maladaptive mTOR activation. Emerging preclinical and translational data suggest that these pleiotropic mechanisms may counteract key pathophysiological processes underlying HCM. This review summarizes the molecular interplay between oxidative stress and hypertrophic remodeling in HCM and explores the rationale for SGLT2 inhibition as a potential disease-modifying therapeutic strategy. Full article

Background: Pathological aggregation of islet amyloid polypeptide (IAPP) contributes to β-cell dysfunction in type 2 diabetes. Our previous studies demonstrated that caveolin-1 (Cav-1) deficiency protects β-cells from palmitate-induced apoptosis. Microarray profiling further indicated that Cav-1 silencing alters IAPP expression. This study aimed to investigate the effects of Cav-1 depletion on IAPP secretion and expression and to explore the potential involvement of thioredoxin-interacting protein (TXNIP). Methods: We performed lentiviral-mediated Cav-1 knockdown in NIT-1 cells and isolated murine islets, and simultaneously generated an inducible β-cell-specific Cav-1 knockout (iβ-Cav1 KO) mouse model. IAPP secretion and expression were assessed by ELISA, Western blot, qPCR and immunofluorescence. The expression of IAPP-processing enzymes (PAM, PC1, and PC2) and degradation factors (IDE and BACE2) was examined. Co-immunoprecipitation (Co-IP) and immunofluorescence were performed to investigate the interaction between Cav-1 and TXNIP. Results: Cav-1 depletion significantly reduced both IAPP secretion and expression in vitro and in vivo. High-fat-diet-fed iβ-Cav1 KO mice exhibited the lowest serum IAPP levels. Mechanistically, Cav-1 depletion was associated with downregulation of PAM, PC1, and PC2 and upregulation of IDE and BACE2. Additionally, Cav-1 depletion decreased TXNIP expression. Immunofluorescence revealed co-localization of Cav-1 and TXNIP, and co-immunoprecipitation further demonstrated their direct physical interaction. Conclusions: Cav-1 is essential for IAPP secretion and expression in β-cells. The direct physical interaction between Cav-1 and TXNIP suggests that TXNIP may mediate the regulatory effects of Cav-1 on IAPP processing or secretion. These findings identify the Cav-1–TXNIP axis as a potential target for mitigating IAPP-related β-cell dysfunction. Full article

Background/Objectives: Exercise is pivotal for glycemic control in type 2 diabetes mellitus (T2DM), yet the relative efficacy of various exercise modalities remains inconclusive. This network meta-analysis aimed to evaluate and provide a preliminary ranking of exercise interventions on HbA1c levels in adults with type 2 diabetes mellitus, to facilitate clinically relevant network comparisons and to generate evidence for future large-scale comparative trials. Methods: A systematic review and network meta-analysis were conducted in accordance with PRISMA guidelines. Electronic databases (PubMed, MEDLINE, Cochrane Library, CINAHL, and ProQuest) were searched from inception to Dec 2024. Randomized controlled trials evaluating exercise interventions in adults with T2DM were included. Risk of bias was assessed independently by two reviewers using the JBI critical appraisal tool. The primary outcome was the change in HbA1c level. Results: Six randomized controlled trials involving a total of 511 participants (256 in the treatment group and 255 in the control group) were included in the final analysis. Both high-intensity interval training (MD = −0.322; 95% CI: −0.559 to −0.084; p = 0.008) and yoga (MD = −0.366; 95% CI: −0.534 to −0.198; p < 0.001) significantly reduced HbA1c compared with the active control. Although the preliminary ranking analysis suggested a higher probability of effectiveness for yoga (SUCRA 1) than for HIIT (SUCRA 0.5), the indirect comparison revealed no statistically significant difference in HbA1c reduction between the two interventions (MD = −0.044; 95% CI: −0.335 to 0.247; p = 0.766). Conclusions: These findings provide preliminary, evidence-generating; however, given the sparse network and absence of head-to-head trials, the treatment hierarchy should be interpreted with extreme caution and selected based on patients’ preferences and tolerance. Registration: PROSPERO [CRD42025650162]. Full article

The global prevalence of autoimmune diseases ranges from 3% to 8%, with women at a significantly higher risk than men. The core mechanisms underlying these diseases include impaired T-cell and B-cell immune tolerance, abnormal cytokine production, and aberrant activation of related signaling pathways. Conventional treatments primarily focus on suppressing immune responses, but their efficacy remains limited and they are often associated with substantial side effects. Nanomedicine leverages nanoscale materials to enable precise diagnosis and targeted therapy. Nanocarriers can penetrate biological barriers, enhance cellular uptake, and prolong circulation time in vivo, demonstrating considerable potential for drug delivery. Common nanoscale drug delivery platforms include nanoparticles, polymeric micelles, liposomes, dendrimers, mesoporous materials, hydrogels, and exosomes. Each carrier type possesses distinct characteristics in terms of drug-loading capacity, stability, responsiveness, and biocompatibility, thereby enabling targeted delivery and controlled release. This review summarizes recent advances in nano-delivery technologies for three representative chronic autoimmune diseases: diabetes mellitus (DM), inflammatory bowel disease (IBD), and rheumatoid arthritis (RA). Nano-delivery systems can improve therapeutic outcomes by optimizing drug delivery, targeting complications, and modulating the pathological microenvironment. They enhance drug bioavailability, reduce off-target and systemic adverse effects, and provide novel strategies for the precise and efficient treatment of chronic autoimmune diseases. Full article

Down syndrome (DS), caused by trisomy 21, is associated with a wide spectrum of endocrine and gastrointestinal disorders that often arise early in life and significantly impact long-term health. This narrative review examines the pathophysiological mechanisms underlying these conditions, with a particular focus on their bidirectional interactions. Endocrine abnormalities in DS, including thyroid dysfunction, type 1 diabetes mellitus, growth impairment, and altered bone metabolism, occur at higher rates than in the general population and are largely driven by immune dysregulation, chronic inflammation, and gene dosage effects. Similarly, gastrointestinal disorders—ranging from congenital malformations to autoimmune conditions such as celiac disease—are highly prevalent and often present with atypical clinical features. Emerging evidence highlights the central role of gut dysbiosis, characterized by reduced microbial diversity and increased pro-inflammatory taxa, in modulating immune and metabolic pathways. This altered gut environment contributes to a chronic inflammatory state and may promote autoimmunity and endocrine dysfunction through the gut–endocrine–immune axis. Nutritional deficiencies and epigenetic factors, including microRNA dysregulation, further influence disease expression. Understanding this complex cross-talk is essential for improving clinical management. Integrated, multidisciplinary approaches and early screening strategies are crucial to optimize outcomes and guide future research in DS. Full article

Background: Type 1 diabetes mellitus (T1D) is associated with chronic inflammation, platelet-related alterations, and increased cardiovascular risk (CVR). The relationships between adipokines and platelet indices in long-standing T1D remain incompletely defined. Objective: To explore the relationships between adipokines (adiponectin and leptin), platelet indices, and inflammatory status in adults with long-standing T1D. Methods: This cross-sectional study included 124 adults with long-standing T1D and 59 non-diabetic controls. Platelet indices were obtained from automated blood count, and serum leptin (LEP), adiponectin (ADNC), and C-reactive protein (CRP) were measured using standardized assays. Associations were evaluated using correlation and multivariable regression analyses with adjustment for body mass index (BMI). Results: Platelet count (PLT) and plateletcrit (PCT) were higher in T1D compared with non-diabetic individuals (p = 0.003 for both), while mean platelet volume (MPV) and platelet distribution width (PDW) showed non-significant upward trends. ADNC levels were higher in T1D (p < 0.001), whereas LEP and the leptin–adiponectin ratio (LAR) did not differ between groups. In T1D, LEP correlated with PLT (rho = 0.235), PCT (rho = 0.263), and CRP (rho = 0.474), all p < 0.05. Similar associations were observed for LAR. No significant associations were found in non-diabetic controls. In multivariable analyses, PCT remained associated with LEP in T1D after adjustment for BMI, whereas in the control group, LEP was associated with BMI only. Conclusions: LEP and platelet-related indices were associated in individuals with long-standing T1D, whereas ADNC showed no such relationships. These findings suggest a distinct pattern of adipokine–platelet associations in long-standing T1D. Full article

Regular consumption of excess sugar is linked to nutrition-based diseases, including gut problems, Non-Alcoholic Fatty Liver Disease, and Type 2 Diabetes Mellitus. Increasing sweetness perception is a novel technique to decrease sugar consumption. This experiment compared the sweetness perception of sweetened and unsweetened almond milk in response to different virtual environments with music and visuals. Two music types, the classical song Goldberg Variations, BMV. 998-Variation 13 and a jazz song generated by AI were used. Additionally, fall and spring forest backgrounds were generated by the Blockade Labs 3D image generator. Each participant tasted sweetened and unsweetened almond milk in music-only, background-only, and combination music and background environments. Results revealed significant differences in sweetness ratings for music type (p = 0.015) and between milk types (p < 0.001). Viscosity rating differed significantly between backgrounds (p = 0.04) and by milk type (p < 0.001). Liking ratings varied significantly between backgrounds (p < 0.001) and between music genres (p = 0.011). The results suggest that altering music and background may be a strategy to change sweetness and viscosity perception in unsweetened beverages. Full article

Background: Post-COVID syndrome represents a significant medical and public health challenge, particularly among older adults and individuals with type 2 diabetes mellitus (T2DM), in whom disturbances in immune and metabolic homeostasis may contribute to the development and persistence of symptoms following SARS-CoV-2 infection. Objective: To investigate the clinical, immunological, and metabolic characteristics of post-COVID syndrome in older adults with T2DM. Methods: A cross-sectional comparative study was conducted involving 141 patients aged ≥ 60 years who were evaluated more than one year after SARS-CoV-2 infection. Clinical data, anthropometric measurements, complete blood count parameters, biochemical markers, glycated hemoglobin (HbA1c), and SARS-CoV-2-specific IgG antibodies were assessed. Statistical analyses were performed using nonparametric methods, while Pearson’s χ² test was applied for categorical variables. A p-value < 0.05 was considered statistically significant. Results: Symptoms consistent with post-COVID syndrome one year after SARS-CoV-2 infection were identified in 53.2% of participants. No significant differences in anthropometric characteristics, hematological parameters, or most biochemical markers were observed between patients with and without post-COVID syndrome. Patients with T2DM exhibited higher fasting glucose, HbA1c, and SARS-CoV-2–specific IgG antibody levels, reflecting underlying metabolic characteristics and differences in humoral immune responses during the late post-COVID period. Conclusions: Post-COVID syndrome symptoms were frequently observed among older adults at the time of assessment, more than one year after SARS-CoV-2 infection, despite normalization of most laboratory parameters. In patients with T2DM, higher glucose, HbA1c, and antibody levels likely reflect underlying metabolic characteristics rather than a direct effect of post-COVID syndrome. Further longitudinal studies are warranted to clarify the long-term clinical significance of the observed metabolic and immunological findings. Full article

This paper analyzes the role of cereal products in the diet of individuals with disorders of carbohydrate metabolism, with particular emphasis on their impact on postprandial glycemia and the risk of developing type 2 diabetes (T2D). Cereal products, as the main source of dietary carbohydrates, also provide dietary fiber, minerals, B vitamins, and key bioactive compounds such as β-glucans, arabinoxylans, resistant starch (RS), and polyphenols. These components may reduce the rate of starch digestion and glucose absorption in the small intestine by increasing the viscosity of intestinal contents or by directly inhibiting digestive enzymes such as α-glucosidase. It has been shown that fermentation of these compounds by the gut microbiota leads to the production of short-chain fatty acids (SCFAs), which improve insulin sensitivity and stimulate the secretion of incretin hormones such as GLP-1. A literature review confirms that regular consumption of whole-grain products is associated with a reduced risk of T2D, whereas refining processes and excessive grain fragmentation lead to an increased glycemic index of products. Based on clinical guidelines and a narrative synthesis of the available literature, minimally processed whole-grain products were identified as a fundamental component of dietary therapy for diabetes, which is illustrated by the cereal product pyramid presented in the paper. This review involved a comprehensive literature search in PubMed, Scopus, and Web of Science using relevant keywords. Peer-reviewed articles, reviews, and meta-analyses (mainly 2000–2025) were included based on their relevance. Full article

Background/Objectives: Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia, dyslipidemia, and oxidative stress, leading to severe systemic complications. Medicinal plants rich in polyphenolic compounds have gained increasing attention as complementary therapeutic agents. This study aimed to comparatively evaluate the chemical composition, as well as the antidiabetic, hypolipidemic, and antioxidant effects of Polygonum persicaria and Vaccinium myrtillus in a streptozotocin-induced diabetic model. Although Vaccinium myrtillus has been more extensively investigated for its antidiabetic potential, the pharmacological relevance of Polygonum persicaria in diabetes remains insufficiently characterized, particularly in direct comparison with a recognized phytotherapeutic comparator. Methods: Hydroalcoholic tinctures prepared from Polygonum persicaria L. herb and Vaccinium myrtillus L. leaves were subjected to phytochemical analysis using High-Performance Thin-Layer Chromatography (HPTLC) for the identification of flavonoids and phenolcarboxylic acids, alongside spectrophotometric determination of total polyphenol and flavonoid content. Experimental diabetes was induced in CD1 mice by streptozotocin administration. Animals were treated orally for 35 days, and glycemic parameters, lipid profile, body weight, food and water intake, and oxidative stress markers (MDA, SOD, TAC, and GPx) were evaluated. Results: HPTLC/CSS screening indicated the presence of rutin, chlorogenic acid, and caffeic acid in Polygonum persicaria, while Vaccinium myrtillus showed stronger densitometric signals for phenolcarboxylic acid-type compounds, particularly chlorogenic and caffeic acids. Total polyphenol and flavonoid content were also higher in Vaccinium myrtillus (433.89 ± 8.67 mg/L GAE; 154.38 ± 3.08 mg/L QE) compared to Polygonum persicaria (269.28 ± 5.25 mg/L GAE; 132.75 ± 2.65 mg/L QE). Functionally, Vaccinium myrtillus demonstrated a significant antihyperglycemic effect from day 14 (p = 0.009) and improved lipid parameters, while Polygonum persicaria showed a delayed glycemic effect, significant only at day 35 (p = 0.014), without significant hypolipidemic activity. In contrast, Polygonum persicaria exerted a marked antioxidant effect, significantly increasing GPx activity (p = 0.025) and reducing MDA levels (p = 0.053). Conclusions: Vaccinium myrtillus showed stronger antihyperglycemic and hypolipidemic effects, while Polygonum persicaria was mainly associated with antioxidant-related biochemical changes. These differences may be influenced by phytochemical composition, but they cannot be attributed solely to total polyphenol or flavonoid content. Full article

Background/Objectives: The increasing burden of non-communicable diseases, together with accelerating environmental degradation, highlights the urgent need for sustainable dietary patterns that promote both human and planetary health. The Mediterranean diet (MedDiet), traditionally followed in countries bordering the Mediterranean basin, has gained recognition as a model of sustainable nutrition due to its well-documented health benefits and relatively low environmental impact. However, its broader role within sustainable food systems requires comprehensive and interdisciplinary evaluation. The aim of this review is to provide a state-of-the-art synthesis of the evidence on the MedDiet as a sustainable dietary pattern, integrating its health, environmental, economic, and socio-cultural dimensions. Methods: This state-of-the-art narrative review synthesizes evidence from peer-reviewed literature on the MedDiet and sustainability. Relevant studies were identified through major scientific databases, focusing on publications addressing nutritional, environmental, economic, and socio-cultural dimensions. Both observational and interventional studies, as well as modeling and life cycle assessment analyses, were included. Additional sources from international organizations and policy reports were incorporated to contextualize global trends and challenges. Results: High adherence to the MedDiet is consistently associated with a reduced risk of cardiovascular disease, type 2 diabetes, cancer, and all-cause mortality. From an environmental perspective, the MedDiet is associated with lower greenhouse gas emissions, reduced land and water use, and enhanced biodiversity conservation compared with Western dietary patterns. Economically, it may represent a cost-effective dietary model and support local food systems when grounded in traditional practices, although affordability varies across contexts. Socio-culturally, the MedDiet promotes food heritage, culinary skills, and social cohesion. Nevertheless, globalization, urbanization, and the increasing consumption of ultra-processed foods have contributed to declining adherence, posing significant challenges to its sustainability and scalability. Moreover, the sustainability benefits of the MedDiet seem to be context-dependent rather than intrinsic, raising several challenges and limitations for its adoption. Conclusions: The MedDiet should be viewed not as a definitive solution to global food-system challenges but as a valuable reference model that illustrates how dietary practices can contribute simultaneously to human health, environmental sustainability, and cultural continuity. Modern sustainable dietary strategies should build upon the strengths of the MedDiet while recognizing its limitations, embracing contextual adaptation, and addressing the structural determinants that shape food choices. Full article

Background and Objectives: Type 2 diabetes mellitus (T2DM) causes retinal microvascular changes that precede clinically apparent diabetic retinopathy (DR). We aimed to identify which optical coherence tomography angiography (OCTA) biomarkers best distinguish eyes with T2DM without clinical DR from healthy controls and to evaluate machine learning classifiers trained on a comprehensive 68-parameter OCTA panel. Materials and Methods: In this prospective case–control study, 80 patients with T2DM without clinical DR and 33 controls underwent 3 × 3 mm macular OCTA using an Optovue RTVue Avanti System. After outlier screening, 221 eyes (155 T2DM, 66 controls) were analyzed. Sixty-eight OCTA parameters were extracted, covering FAZ morphometry (including foveal density FD-300), SCP and DCP vessel density and layer thickness, outer-retina and choriocapillaris flow, and a full retinal-thickness map. Between-group comparisons used the Mann–Whitney U test with Benjamini–Hochberg FDR correction. Logistic regression, random forest, and XGBoost classifiers were evaluated with patient-grouped 10-fold cross-validation; feature importance was quantified via SHAP. Results: Forty-two of 68 parameters reached FDR significance (q < 0.05). Deep capillary plexus vessel density was the most discriminative family (whole image rb = −0.66, q = 2.5 × 10⁻¹³; parafovea rb = −0.64). FD-300 was reduced in T2DM (median 47.55% vs. 51.86%; rb = −0.57; q = 1.0 × 10⁻¹⁰) and emerged as the top SHAP feature (mean |SHAP| = 0.81). FAZ circularity decreased without FAZ-area enlargement, and outer-retina flow was paradoxically elevated (rb = +0.39), consistent with a projection artifact. XGBoost using all 68 features achieved a patient-grouped cross-validated AUC of approximately 0.91, compared with 0.85 for conventional SCP + DCP whole-image density. No parameter correlated with current HbA1c in T2DM (all q > 0.98), and the well-controlled (<7%) and poorly controlled (≥7%) subgroups were indistinguishable across five of six principal biomarkers, consistent with metabolic memory. FD-300 remained independent after adjustment for hypertension, hyperlipidemia, and age (OR = 0.76; 95% CI 0.69–0.84; p < 0.001). Conclusions: A multi-compartment OCTA panel outperforms conventional two-layer vessel-density metrics in detecting preclinical diabetic microvasculopathy, although external validation is required before clinical use. FD-300 is the single most informative biomarker, while choriocapillaris and retinal thickness measures provide complementary, compartment-specific signals. Because the OCTA signature is decoupled from the current HbA1c, screening should not be deferred in well-controlled T2DM. Full article