To determine the associations between sleep phenotypes and the risks of specific obesity types and weight gain in patients with type 2 diabetes (T2D), especially in different genetic risk groups.
We conducted a prospective study involving 58 890 participants. Sleep and napping were assessed according to the standardized questionnaire. General and abdominal obesity were defined by BMI or visceral fat area (VFA), respectively. Multivariable Cox regression, stratified, and joint analysis were performed to explore potential correlations. Furthermore, mediation models were constructed to figure out the mediating role of metabolic factors (blood pressure, UACR, and HbA1c).
During a median 3.05-year follow-up period, short sleep increased the risk of obesity (HR 1.42, 95% CI 1.17–1.71; 1.33, 1.08–1.65) and weight gain (1.21, 1.09–1.34; 1.17, 1.06–1.29), while long sleep and napping were unrelated to abdominal obesity and weight gain. Mediation analysis showed that systolic blood pressure, UACR, and HbA1c mediated the statistical association between night sleep duration and general obesity with proportions (%) of 7.9, 1.8, and 8.8, respectively. Joint analysis showed both sleep and napping groups had no significance among the low genetic risk group, while long napping, short sleep, and long sleep increased the risk of general obesity in medium to high risk patients.
Short sleep, long sleep, and long napping increased the risk of general obesity and BMI-defined weight gain, and were more pronounced in the medium to high genetic risk group. Napping was unrelated to abdominal obesity. Metabolic factors partially explain the mechanism between sleep and obesity.
The relationship between diabetes and Alzheimer's Disease (AD) has increasingly been recognized. Diabetes is associated with the doubling of vascular dementia and with a one-third increase in the risk of AD [1]. AD prevalence and mortality have particularly increased over the past three decades in China, and among women in relation to increases in longevity, with higher levels of glycemia the major attributable risk factor, with further risk associated with cigarette use and obesity [2], at least in part reflecting the association of all three of these factors with insulin resistance. During this time period, obesity has shown greater attributable risk while smoking has become a weaker risk factor, while other factors including environmental pollutants, nutritional deficiencies, alcohol use, and hypertension appear to be associated with considerably lower population attributable risk [2].
Insulin plays a variety of roles in neuronal function and survival, with diabetes increasing AD risk indirectly as a function of underlying brain insulin resistance, leading to impaired cognitive processes and increasing AD susceptibility [3]. In insulin-resistant states, brain insulin levels rise, leading to reduced insulin-degrading enzyme (IDE) activity. IDE is responsible for clearing Amyloid-beta (Aβ). Aβ monomers play roles in neuronal synaptic activity, but Aβ has a tendency to autoaggregate, with reduction in IDE activity resulting in greater levels of Aβ, promoting plaque formation and contributing to AD pathology from Aβ accumulation, aggregation, and fibril formation [4]. Tau protein functions by stabilizing neuronal microtubules and plays a role in neuronal cell signaling. Insulin resistance downregulates an insulin signaling pathway, leading to decreased phosphoinositide 3-kinase (PI3K) activity, in turn altering the activity of the serine/threonine kinase Akt pathway, leading to activation of glycogen synthase kinase-3β (GSK-3β). In addition to its function in regulating glycogen synthesis, GSK-3β is an enzyme involved in phosphorylation of tau protein, with hyperphosphorylated tau aggregating to form neurofibrillary tangles [4]. The typical pathologic findings of AD, then, are exacerbated by insulin resistance, underlying the association of diabetes with AD.
Both among individuals having and not having diabetes, higher average glucose levels are associated with an increased hazard ratio for dementia [5]. Similarly, higher HbA1c levels are also associated with greater risk of dementia in patients with diabetes [6]. There may be relationships between diabetes treatment approaches and dementia development. Of concern, sulfonylureas were associated with a higher risk of dementia development than dipeptidyl peptidase 4 inhibitors (DPP4i) [7]. The glucagon-like protein-1 receptor agonists (GLP-1 RAs) may reduce brain Aβ lev
To explore the influence of the serum total bilirubin to total cholesterol (TBIL/TC) ratio on the progression of chronic kidney disease (CKD) in people with type 2 diabetes.
The present retrospective discovery cohort investigated 4282 patients. The exposure was baseline TBIL/TC ratio. The outcome was the first time to progressing CKD, defined by a drop in the estimated glomerular filtration rate (eGFR) category, along with a reduction in eGFR of at least 25% compared to the baseline value. Hazard ratios (HRs) for CKD progression were evaluated based on the Cox proportional hazards approach. Dose–response relationships were conducted using Restricted Cubic Splines (RCS). Additionally, 758 patients were enrolled as an independent validation cohort.
During a median observation period of 2.4 years (interquartile range 1.3–3.8 years) within the discovery cohort, 522 individuals showed progression in CKD. The analysis revealed a negative association between the TBIL/TC ratio and the risk of CKD progression, with an adjusted HR of 0.17 and a 95% CI ranging from 0.07 to 0.41. After adjusting for confounding variables, the HRs for the second, third, and fourth quartiles of the TBIL/TC ratio were recorded at 0.61 (95% CI 0.48, 0.78), 0.55 (95% CI 0.42, 0.72), and 0.55 (95% CI 0.41, 0.74), respectively. Analysis with RCS indicated an optimal TBIL/TC ratio threshold of 0.25%. Similar results were also observed in the validation cohort.
A higher TBIL/TC ratio was significantly associated with a reduced risk of CKD progression in patients with type 2 diabetes.
To examine whether patients exposed to primary care telemedicine (telephone or video) early in the COVID-19 pandemic had higher rates of downstream HbA1c measurement and improved HbA1c levels in the second year of the pandemic.
In a cohort of 242,848 Kaiser Permanente Northern California patients with diabetes, we examined associations between early-pandemic patient-initiated telemedicine visits and downstream HbA1c monitoring and results during the second year of the pandemic.
Adjusted HbA1c measurement rates were significantly higher among patients with telemedicine exposure in the early-pandemic prior year than those with no visits in the prior year (91.0% testing for patients with video visits, 90.5% for telephone visits, visits, 86.7% for no visits, p < 0.05). Among those with HbA1c measured, the rates of having an HbA1c < 8% in the second year of the COVID-19 pandemic were also statistically significantly higher among patients with telemedicine exposure in the early-pandemic prior year than those with no visits in the prior year (68.5% with HbA1c < 8% for video visits, 67.3% for telephone visits, 66.6% for no visits, p < 0.05).
Access to telephone and video telemedicine throughout the early COVID-19 pandemic was associated with patients' continued engagement in recommended diabetes care. Although our study analyzed telemedicine use during a pandemic, telemedicine visits may continue to support ongoing health care access and positive clinical outcomes.
Diabetic peripheral neuropathy (DPN) may affect the biomechanical properties and morphology of the plantar tissue. This study aimed to compare plantar stiffness and thickness in individuals with diabetes with and without DPN and develop a novel explanatory model for DPN risk assessment by integrating these measures with clinical parameters.
Thirty-two healthy controls and 84 people with diabetes (41 with DPN and 43 without DPN) were included. Shear wave elastography evaluated plantar thickness and stiffness at the heel, hallux, and first and fifth metatarsal heads (1st MTH, 5th MTH). An integrated thickness or stiffness index was generated at multiple locations by principal component analysis (PCA).
People with DPN showed a significant increase in plantar thickness (heel, 1st MTH) (p < 0.001) and stiffness (all tested locations) compared to healthy controls (p < 0.05). Moreover, plantar thickness at 1st MTH, plantar stiffness at 5th MTH, and integrated stiffness index generated by PCA were significantly higher in DPN than in the non-DPN group (p < 0.05). A DPN explanatory model was developed using multivariate logistic regression, incorporating the integrated plantar stiffness index, diabetes duration, and gender. The model showed high discriminative ability (AUROC: 97.7%), with an optimal cutoff of 0.56 yielding 92.7% sensitivity and 95.3% specificity.
The integrated plantar stiffness index, combined with gender and diabetes duration, offers a novel approach for DPN, providing a noninvasive tool for DPN risk assessment.
Diabetes is a prevalent public health issue worldwide, and the cognitive dysfunction and subsequent dementia caused by it seriously affect the quality of life of patients.
Recent studies were reviewed to provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for diabetes-related cognitive dysfunction (DACD).
Several risk factors contribute to DACD, including hyperglycemia, hypoglycemia, blood sugar fluctuations, hyperinsulinemia, aging, and others. Among them, modifiable risk factors for DACD include blood glucose control, physical activity, diet, smoking, and hypertension management, while non-modifiable risk factors include age, genetic predisposition, sex, and duration of diabetes. At the present, the pathogenesis of DACD mainly includes insulin resistance, neuroinflammation, vascular disorders, oxidative stress, and neurotransmitter disorders.
In this review, we provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for DACD, providing information from multiple perspectives for its prevention and management.
We appreciate the author's attention to our study [1] and their detailed comments. To address their questions and help the readers better understand this research, we would like to provide the following explanation of our study's process.
A study titled “Altitudes and Hemoglobin A1c Value” conducted by my colleagues was published in 2024 [2]. Their analysis, which included 95 052 individuals across 162 sites in China, revealed a positive correlation between altitude above 2500 m and HbA1c levels, while no such correlation was observed at altitudes below 2500 m. Due to the lack of data on hemoglobin concentrations and red blood cell counts, their study could not provide more in-depth results. Fortunately, our team had some data suitable for further investigation. We selected two cities with altitudes below 2500 m: Kunming (1891 m) and Chengdu (503 m). The hemoglobin concentration in Kunming (mean: 158.73 g/L, SD: 16.36) was higher than in Chengdu (mean: 145.44 g/L, SD: 16.82). There was no difference in HbA1c levels between two groups, with Kunming showing a mean of 5.40 (SD: 0.48) and Chengdu 5.41 (SD: 0.41).
Although hemoglobin levels in the two cities differ, they remain within the normal reference range. Moreover, residents of both cities shared similar lifestyles and socio-economic conditions; we combined the data to analyze the effects of gender and age. We employed the Generalized Additive Model (GAM) for our analysis, as it effectively captures nonlinear relationships and allows us to focus on trends and patterns. Notably, Figure D reveals a significant gender-based difference in the relationship between HbA1c and age. The HbA1c curve for women shows a distinctive turning point around age 45, which prompted our further investigation in Figures C and D. In Figure D, the disparity in HbA1c levels between women above and below the age of 45 is likely influenced by menopause and changes in estrogen levels. Unfortunately, our dataset does not include estrogen-related data, preventing further analyses in this direction. However, a previous study indicated that estrogen therapy in postmenopausal women with type 1 or type 2 diabetes can reduce HbA1c and fasting glucose levels, which supports our findings [3].
We acknowledge that our analysis has limitations regarding the types and scope of the real-world clinical data. Therefore, the findings presented in this article underscore the need for more epidemiological studies with rigorous system design to achieve more reliable conclusions.
T.Z. and B.C. drafted and revised the manuscript.
The authors declare no conflicts of interest.
The management of metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus (T2DM) presents a significant clinical challenge, with a focus on preventing progression to liver and renal complications.
To evaluate the liver and renal outcomes among new users of sodium-glucose cotransporter 2 inhibitors (SGLT2i) versus glucagon-like peptide-1 receptor agonists (GLP-1RA), dipeptidyl peptidase-4 inhibitors (DPP4i) and other anti-diabetic medications in patients with MASLD and T2DM.
Retrospective cohort study.
Electronic health records.
A total number of 88 306 patients with MASLD and T2DM were included in a propensity score-matched analysis comparing the effects of anti-diabetic drugs.
Patients were categorized into groups based on their initiation of anti-diabetic medications.
The primary outcomes were the incidence of cirrhosis, hepatic decompensations, and hepatocellular carcinoma. Secondary outcomes were a progression of chronic kidney disease (CKD), severity of CKD stages, and the need for hemodialysis.
In the SGLT2i versus DPP4i, a reduced risk of cirrhosis was observed in the SGLT2i (HR: 0.97), along with fewer hepatic decompensations (HR: 0.84) and a lower incidence of HCC (HR: 0.50). CKD progression, particularly to stages 4–5, was significantly lower in the SGLT2i (HR: 0.53), as was hemodialysis (HR: 0.38). However, SGLT2i exhibited a slightly lower risk of CKD progression (HR: 0.77) and a reduced need for hemodialysis (HR: 0.71) compared to the GLP-1RA, while there was no difference in hepatic outcomes between the GLP-1RA and SGLT2i.
SGLT2 inhibitors in patients with MASLD and T2DM
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