Aug 2026· Frontiers in Endocrinology· Vol 17· 0 citations· 35 references
Medicine
TL;DR
Residual β-cell function is independently associated with improved CGM-derived metrics (increased TIR, decreased TAR, and lower MG) in both classic T1DM and LADA, highlighting the importance of protecting residual β-cell function to achieve glycemic stability and reduce exogenous insulin dependence in T1DM.
Abstract
Background To evaluate the relationship between residual islet β-cell function assessed by fasting C-peptide (FCP) and continuous glucose monitoring (CGM) metrics in patients with type 1 diabetes mellitus (T1DM), and to clarify the impact of residual islet β-cell function on glycemic control in T1DM. Methods A retrospective study was conducted including 112 patients with T1DM [68 classic T1DM, 44 latent autoimmune diabetes in adults (LADA)] hospitalized from January 2023 to December 2025. All patients wore CGM devices for ≥7 days. Participants were stratified into four groups by FCP quartiles. Spearman correlation, restricted cubic spline (RCS) regression, and multivariable linear regression with progressive adjustment for confounders were used to evaluate associations between FCP and CGM-derived metrics, including time in range (TIR), time above range (TAR), and mean glucose (MG). Subgroup and interaction analyses were performed by diabetes subtype. Sensitivity analyses included quartile-based categorization, exclusion of LADA patients, and exclusion of those with diabetes duration ≥10 years. Results In this retrospective study, higher FCP levels were significantly associated with favorable CGM-derived metrics, including increased TIR, decreased TAR, and lower MG (all P < 0.001). These associations persisted after multivariable adjustment for sex, age, disease duration, BMI, insulin dosage, and glucose coefficient of variation (CV). RCS analysis revealed significant nonlinear dose-response relationships, with pronounced glycemic improvements at lower FCP concentrations and plateau effects at higher levels. LADA patients exhibited higher FCP levels, longer TIR, and lower TAR compared with classic T1DM (all P < 0.05). Subgroup analyses demonstrated consistent FCP-CGM associations in both subtypes without significant interaction (all P for interaction > 0.05). Sensitivity analyses confirmed robust associations after excluding LADA patients or those with disease duration ≥10 years. Shorter disease duration and lower daily insulin requirements correlated with higher FCP levels. Conclusion Residual β-cell function is independently associated with improved CGM-derived metrics (increased TIR, decreased TAR, and lower MG) in both classic T1DM and LADA. Preserved C-peptide secretion correlates with shorter disease duration and lower daily insulin requirements. These findings highlight the importance of protecting residual β-cell function to achieve glycemic stability and reduce exogenous insulin dependence in T1DM.
Objective Impaired islet β-cell function is the core mechanism underlying type 2 diabetes mellitus (T2DM). This study investigated the association between islet β-cell function and time in range (TIR) in patients with T2DM, providing a reference for individualized clinical treatment. Methods This retrospective cross-sectional observational l study included 1,160 patients with confirmed T2DM. Participants underwent continuous glucose monitoring (CGM). TIR >70% was defined as achieving the glycemic target. Subjects were divided into three groups based on TIR levels (<70%, 70%–84%, and ≥85%). The β-cell function index HOMA2–β was calculated using the Homeostasis Model Assessment 2 as the core research indicator. Results The high TIR group had significantly higher HOMA2-β (P < 0.001). Multiple linear regression analysis showed a robust positive correlation between HOMA2-β and TIR after adjusting for covariates (β = 0.402, 95% CI: 0.358–0.447, P < 0.001). Restricted cubic spline (RCS) analysis revealed a significant nonlinear relationship between HOMA2-β and TIR (P for nonlinearity < 0.001). TIR increased with rising HOMA2-β, but the rate of increase gradually slowed. Specifically, when HOMA2-β increased from approximately 10% to 100%, the predicted TIR rose rapidly from about 38% to approximately 96%, representing an increase of 58%. Sensitivity analysis using HOMA2-β calculated from fasting C-peptide instead of fasting insulin yielded consistent conclusions. Conclusion A significant, nonlinear association exists between islet β-cell function HOMA2–β and TIR. TIR levels increase progressively with higher HOMA2-β. Although the cross-sectional design precludes causal inference, these findings provide important reference values for clinical decision-making.
Ningning Li, Ling Lv, Zhaoyang Zhang et al.· Frontiers in Endocrinology· 0 citations
Background The role of short‑term glycemic variability (GV) in early diabetic kidney disease (DKD) among patients with type 2 diabetes (T2D) remains controversial. This study aims to investigate the independent association between continuous glucose monitoring (CGM)-derived GV indices and early DKD in T2D patients. Methods This cross-sectional study included 315 patients with T2D. Early DKD was identified as persistent microalbuminuria (urine albumin-to-creatinine ratio 30–300 mg/g) with preserved renal function (eGFR≥60 mL/min/1.73 m2). GV metrics, including mean amplitude of glycemic excursions (MAGE) and glucose standard deviation (SDBG), were derived from CGM data. Multivariate logistic regression and generalized additive models (GAMs) were used to assess associations, with subgroup analyses and interaction tests. Results Participants with early DKD had significantly higher MAGE and SDBG (both P<0.001). After full adjustment for HbA1c, medication use, and other covariates, both MAGE (OR =1.58, 95% CI: 1.31–1.89, P<0.001) and SDBG (OR =2.14, 95% CI: 1.39–3.30, P = 0.001) were independently associated with early DKD. Compared with the lowest tertile, the highest tertiles of MAGE and SDBG were associated with a 5.78-fold (95% CI: 2.83–11.81) and 3.56-fold (95% CI: 1.77–7.18) higher risk, respectively (all P< 0.001). BMI was a significant effect modifier of the MAGE-DKD association (P for interaction = 0.014), which was present only in overweight/obese individuals. GAM analysis demonstrated a linear positive relationship for MAGE and a non-linear U-shaped association for SDBG. Conclusion CGM-derived short-term GV indices MAGE and SDBG are independently associated with early DKD in T2D patients, with distinct dose-response patterns: MAGE shows a linear positive relationship, whereas SDBG exhibits a U-shaped association. Moreover, the MAGE–DKD association is confined to overweight individuals. Prospective studies are needed to establish causality and to verify whether personalized targeting of short‑term GV might be associated with lower DKD risk.
Nan Chen, Nuojin Wang, Hao Duan et al.· Diabetes, Metabolic Syndrome...· 0 citations
C-peptide can be used as an appropriate index for identifying IR in T2DM patients with complications and illustrated the clinical utility of C-peptide in microvascular complications such as diabetic nephropathy and diabetic retinopathy.
K. Siddiqui, S. Joy, S. Nawaz et al.· Medicine· 0 citations
Objective To identify independent predictors of diabetic cardiac autonomic neuropathy (DCAN) deterioration in patients with type 2 diabetes mellitus (T2DM), develop machine learning (ML)-based risk prediction models, and explore the underlying mediation of glycemic burden. Methods This prospective cohort study included 293 T2DM patients who underwent standardized Ewing testing at baseline and follow-up. Univariable and multivariable logistic regression were utilized to identify predictors. Restricted cubic splines (RCS) were applied to evaluate non-linear relationships. Nine ML algorithms were developed and evaluated using AUC and calibration metrics, with SHAP values illustrating feature importance. Mediation analysis was performed to investigate whether longitudinal biomarker changes accounted for the association between HbA1c and DCAN deterioration. Results During follow-up, 80 patients (27.3%) experienced DCAN deterioration. Multivariable logistic regression identified elevated HbA1c at baseline as an independent risk factor, while SGLT2 inhibitor use was significantly associated with a lower risk of deterioration. RCS analysis revealed a continuous linear risk increase for HbA1c at baseline, whereas the platelet-to-lymphocyte ratio (PLR) at baseline exhibited an inverted U-shaped relationship. Among the ML algorithms, KNN achieved the highest AUC among models meeting the prespecified calibration criterion (AUC = 0.913; Brier score = 0.084; calibration slope = 0.701; calibration intercept = −0.053). SHAP analysis confirmed SGLT2 inhibitor use, HbA1c, and PLR as the top three predictors. Mediation analysis demonstrated that longitudinal increases in uric acid (ΔUA) and white blood cell count (ΔWBC) accounted for 20.6% and 12.9% of the association between HbA1c and DCAN progression, respectively. Conclusions SGLT2 inhibitor use is significantly associated with a lower risk of DCAN deterioration in T2DM patients, whereas elevated HbA1c levels correlate with disease progression, potentially involving pathways of exacerbated uric acid metabolism and systemic inflammation. Furthermore, the KNN-based ML model serves as a promising proof-of-concept tool for clinical risk stratification that warrants future external validation.
J. Wang, Jie Hu, Wu Dai et al.· Frontiers in Endocrinology· 0 citations
Background The rising prevalence of early-onset type 2 diabetes (T2DM) has become a major public health concern, with these patients facing a particularly high risk of early diabetic kidney disease (DKD). Although continuous glucose monitoring (CGM)-derived metrics have shown promise in predicting complications in later-onset T2DM, their utility in early-onset T2DM, a more aggressive phenotype characterized by rapid β-cell decline and heightened complication risk, remains unclear. Moreover, the relationship between glycemic variability and renal injury, as well as the mechanisms underlying the associations between CGM metrics and DKD, have not been fully elucidated. This study aimed to evaluate the associations of time in range (TIR), coefficient of variation (CV), and glycemic risk index (GRI) with early DKD in Chinese patients with early-onset T2DM, and to explore the potential mediating role of triglycerides. Methods This cross-sectional study included 810 individuals with early-onset T2DM, defined as diagnosis before age 40. All participants underwent ≥7 days of CGM. Early DKD was defined as a urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g with an estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73m². Multivariable logistic regression, restricted cubic splines, and mediation analysis were used to evaluate independent associations, nonlinear relationships, and the mediating role of triglycerides (TG), respectively. Results Among the participants, 183 (22.59%) had early DKD. After full adjustment including HbA1c, higher TIR was associated with lower odds of early DKD (per 1% increase: OR 0.99, 95% CI 0.98–0.99, P < 0.001), whereas higher GRI was associated with increased odds (per 1-unit increase: OR 1.01, 95% CI 1.01–1.02, P < 0.001). A U-shaped relationship was observed between CV and early DKD risk, with the nadir observed at approximately 20–30% CV. In mediation analysis, TG statistically accounted for 13.01% of the association between TIR and early DKD, and 11.92% of the association between GRI and early DKD. Conclusions In Chinese patients with early-onset T2DM, CGM-derived metrics are independently associated with early DKD, with TIR and GRI showing opposite associations and CV exhibiting a U-shaped relationship. The observed association involving triglycerides suggests that lipid metabolism may be a correlate of glycemic control in relation to renal injury. These findings support a multidimensional strategy integrating glucose control, glycemic stability, and lipid management for renal protection in this high-risk population.
Yuanshuang Jiang, Jing Kang, Yan Chen· Frontiers in Endocrinology· 0 citations
Objective: To determine whether continuous glucose monitoring (CGM) identifies clinically relevant glycemic heterogeneity and subclinical end-organ alterations in adults without diabetes. Research Design and Methods: We analyzed 1,017 AI-READI Year 3 participants without diabetes (558 with normoglycemia and 459 with prediabetes by A1C). Fifty-two metrics from 10-day blinded CGM were reduced to nonredundant glycemic axes. Partial Spearman correlations between representative CGM metrics and clinical measures across 13 domains were adjusted for age, sex, and BMI and controlled for false discovery rate. CGM-derived subphenotypes were identified using unsupervised UMAP-HDBSCAN-based clustering. Results: Among 462 glycemic-clinical associations tested, 99 (21.4%) remained significant after false discovery rate correction. Hyperglycemia-related metrics, including mean glucose, time above range, and time in tight range, showed more associations than variability metrics. The strongest signals involved cardiometabolic, cardiovascular, and cognitive measures. Greater hyperglycemia and glucose excursions were associated with lower language performance, slower processing speed, and lower cognitive efficiency ({rho} {approx} -0.10 to -0.14; all P < 0.01). Clustering identified four reproducible glycemic subphenotypes: Healthy, Mild Hyperglycemia, High Variability, and Hyperglycemia. CGM phenotypes reclassified A1C-defined groups: 58.1% of participants with normoglycemia fell into dysglycemic phenotypes, whereas 18.8% of participants with prediabetes fell into more favorable phenotypes. The Hyperglycemia phenotype had the most adverse cardiometabolic profile and lower cognitive performance. Conclusions: In adults without diabetes, CGM revealed glycemic patterns associated with distinct subclinical alterations. CGM-based phenotyping may complement A1C for characterizing early dysglycemia and selecting individuals for longitudinal risk-stratification studies.
B. Chen, Andreas S. Alexopoulos, W. T. Lau et al.· medRxiv· 0 citations
