Association between circadian physical activity trajectories and incident type 2 diabetes in the UK Biobank

Physical activity (PA) is linked to a decreased risk of type 2 diabetes mellitus (T2DM). However, the influence of circadian PA trajectories remains uncertain. This study aims to explore the optimal circadian PA trajectory pattern for reducing the risk of T2DM. Methods: A total of 502,400 participants were recruited from the UK Biobank between 2006 and 2010, and 102,323 participants provided valid accelerometer-captured acceleration data. After excluding individuals with prior T2DM, 99,532 participants were included in the final analysis. We initially investigated the association between PA intensity at 24 hourly time points and T2DM. Subsequently, PA trajectories were identified using K-means cluster analysis. Cox proportional hazard models were employed to estimate hazard ratios (HR). Four distinct PA trajectories were identified: consistently low, single peak, double peak, and intense trajectories. Compared to consistently low, single peak, double peak and intense PA trajectory reduced the risk of T2DM progressively. Sensitivity analyses, further excluding individuals with glycated hemoglobin (HbA1c) ≥ 6.5% or random glucose ≥ 11.1 mmol/L and adjusted for daily average acceleration, yielded consistent results. This confirms that the ideal circadian PA trajectory serves as a protective factor, independently of PA intensity. Subgroup analyses indicated that these effects were more pronounced in men and individuals with eGFR < 60 mL/(min*1.73 m2). In conclusion, ideal circadian PA trajectory patterns (especially intense and then double peak) reduced risk of T2DM.

Association between the trajectory of ideal cardiovascular health metrics and incident chronic kidney disease among 27,635 older adults in northern China-a prospective cohort study

BACKGROUND

There is a lack of relevant studies evaluating the long-term impact of cardiovascular health factor (CVH) metrics on chronic kidney disease (CKD).

OBJECTIVE

This study investigates the long-term change in CVH metrics in older people and explores the relationship between CVH metrics trajectory and CKD.

METHODS

In total, 27,635 older people aged over 60 from the community-based Tianjin Chronic Kidney Disease Cohort study were enrolled. The participants completed five annual physical examinations between January 01, 2014, and December 31, 2018, and a subsequent follow-up between January 01, 2019, and December 31, 2021. CVH metrics trajectories were established by the group-based trajectory model to predict CKD risk. The relationships between baseline CVH, CVH change (ΔCVH), and CKD risk were also explored by logistic regression and restricted cubic spline regression model. In addition, likelihood ratio tests were used to compare the goodness of fit of the different models.

RESULTS

Six distinct CVH metrics trajectories were identified among the participants: low-stable (11.19%), low-medium-stable (30.58%), medium-stable (30.54%), medium-high-decreased (5.46%), medium-high-stable (18.93%), and high-stable (3.25%). After adjustment for potential confounders, higher CVH metrics trajectory was associated with decreased risk of CKD (P for trend < 0.001). Comparing the high-stable with the low-stable group, the risk of CKD decreased by 46%. All sensitivity analyses, including adjusting for baseline CVH and removing each CVH component from the total CVH, produced consistent results. Furthermore, the likelihood ratio test revealed that the model established by the CVH trajectory fit better than the baseline CVH and Δ CVH.

CONCLUSION

The higher CVH metrics trajectory and improvement of CVH metrics were associated with decreased risk of CKD. This study emphasized the importance of improving CVH to achieve primary prevention of CKD in older people.

High urinary excretion rate of glucose attenuates serum uric acid level in type 2 diabetes with normal renal function

AIMS/INTRODUCTION

The relationship between urinary excretion rate of glucose (UEGL) and uric acid (UA) metabolism in adults with type 2 diabetes (T2D) remains unclear to date. This study aimed to investigate the relationships of UEGL with serum UA (SUA), urinary excretion rate of uric acid (UEUA), and renal clearance of uric acid (CLUA) in adults with T2D. We hypothesised that high UEGL increases UA excretion, which in turn leads to lower SUA.

MATERIALS AND METHODS

This was a cross-sectional study of 635 inpatients with T2D recruited between 2018 and 2019. The relationships of UEGL with UEUA, CLUA, and hyperuricaemia were assessed using analysis of covariance and multivariate regression analysis.

RESULTS

Patients in the higher quartile of UEGL tended to have lower SUA levels than those in the lower quartile. In contrast, patients in the higher quartile of UEGL tended to have higher CLUA (p for trend < 0.0001), and a similar trend was observed for UEUA. In adjusted multivariable linear regression model, UEGL was negatively correlated with SUA (β = - 0.023, 95% CI - 0.034 to - 0.013, p < 0.0001). However, positive correlations of UEGL with UEUA (β = 0.046, 95% CI 0.018-0.074, p = 0.001) and CLUA (β = 0.063, 95% CI 0.042-0.085, p < 0.0001) were found. Furthermore, consistent significant inverse associations were observed between quartiles of UEGL and hyperuricaemia in the adjusted multivariate logistic regression model.

CONCLUSIONS

A high UEGL level was positively correlated with UEUA and CLUA. Moreover, it was inversely associated with SUA level, and a consistently increased UEGL level reduced the risk of hyperuricaemia in patients with T2D.

Development and validation of a prediction model estimating the 10-year risk for type 2 diabetes in China

PURPOSE

To derive and validate a concise prediction model estimating the 10-year risk for type 2 diabetes (T2DM) in China.

METHODS

A total of 11494 subjects from the China Health and Nutrition Survey recorded from 2004 to 2015 were analyzed and only 6023 participants were enrolled in this study. Four logistic models were analyzed using the derivation cohort. Methods of calibration and discrimination were used for the validation cohort.

RESULTS

In the derivation cohort, 257 patients were identified from a total of 4498 cases. In the validation cohort, 92 patients were identified from a total of 1525 cases. Four models performed nicely for both calibration and discrimination. The AUC in the derivation cohort for models A, B, C and D were 0.788 (0.761-0.816), 0.807 (0.780-0.834), 0.905 (0.879-0.932) and 0.882 (0.853-0.912), respectively. The Youden index for models A, B, C and D were 1.46, 1.48, 1.67 and 1.65, respectively. Model C showed the highest sensitivity and model D showed the highest specificity.

CONCLUSION

Models A and B were non-invasive and can be used to identify high-risk patients for broad screening. Models C and D may be used to provide more accurate assessments of diabetes risk. Furthermore, model C showed the best performance for predicting T2DM risk and identifying individuals who are in need of interventions, current approach improvement and additional follow-up.

The Association Between Phosphorylated Neurofilament Heavy Chain (pNF-H) and Small Fiber Neuropathy (SFN) in Patients with Impaired Glucose Tolerance

INTRODUCTION

Small fiber neuropathy (SFN)-the early stage of diabetic peripheral neuropathy (DPN)-progresses gradually and is difficult to diagnose using neurophysiological tests. To facilitate the early diagnosis of SFN, biomarkers for SFN must be identified. The purpose of this study was to investigate the characteristics of SFN in prediabetic patients and the relationship between pNF-H and SFN.

METHODS

44 IGT patients (inpatients and outpatients) were selected at random. 33 healthy subjects served as controls. Data on clinical characteristics and laboratory parameters were collected. Quantitative sensory testing (QST), electromyography (EMG), and Sudoscan were performed, and pNF-H was measured by ELISA.

RESULTS

24 of the 44 patients with impaired glucose tolerance (IGT) were diagnosed with SFN according to the modified Toronto Diabetic Neuropathy Expert Group consensus criteria. The thermal sensory thresholds of the IGT-SFN group were significantly different from those of the CTRL group (p < 0.05), except for the heat pain threshold. The sensory nerve action potential (SNAP) of the sural nerve was 12.39 in the IGT-SFN group, which was significantly lower than those in the other groups. No significant difference in nerve conduction velocity (NCV) was observed among the three groups. The electrochemical skin conductance (ESC) in the IGT-SFN group was 69.78 ± 14.03uS, which was significantly lower than that in the CTRL group. The pNF-H in the IGT-SFN group was 170.6 (140.0, 223.6) pg/ml, which was significantly higher than those in the CTRL and IGT-non-SFN groups (76.55 and 64.7 pg/ml, respectively). Multivariate regression analysis demonstrated that pNF-H and 2h plasma glucose were independently correlated with SFN; the ORs (95% CI) were 1.429 (1.315, 1.924) and 2.375 (1.157, 4.837), respectively.

CONCLUSIONS

Serum pNF-H may be associated with SFN in IGT patients, and serum pNF-H could therefore serve as a sensitive biomarker for the detection of SFN.