Journal of Diabetes Investigation最新文献

Introduction: Nutritional management is crucial in patients with chronic kidney disease. Therefore, it is important to assess nutritional status and detect malnutrition, especially in patients with diabetes. However, there is currently a lack of evidence regarding the relationship between nutritional indices and renal function in patients with type 2 diabetes. This study investigated whether the geriatric nutritional risk index (GNRI) is related to renal prognosis in type 2 diabetes patients.

Materials and methods: The study included 946 type 2 diabetes patients enrolled in the Fukushima Cohort Study. The primary endpoint of this study was a renal event, defined as a combination of a 50% decline in eGFR from baseline and end-stage kidney disease. All-cause death and new cardiovascular events were also measured as secondary outcomes. The association between GNRI and these endpoints was assessed using Cox regression analysis.

Results: The median patient age was 66 years, 57% were men, the median eGFR was 67.9 mL/min/1.73 m², and the median GNRI was 100.0. Compared to patients in the highest GNRI tertile, patients in the lowest tertile had a significantly increased risk of the renal event (HR 5.15, 95% CI 2.51-10.6) and all-cause death (HR 2.30, 95% CI 1.20-4.42). A significant association was not observed between GNRI levels and cardiovascular events.

Conclusions: We observed an association between poor nutritional status, assessed by GNRI, and adverse outcomes in patients with type 2 diabetes. Nutritional status assessment has potential utility as a prognostic tool for individuals with type 2 diabetes.

Aims/introduction: Orthodontic treatment involves alveolar bone remodeling in response to mechanical loading, resulting in tooth movement through traction-side bone formation and compression-side bone resorption. However, there are conflicting reports regarding alveolar bone resorption during the orthodontic treatment of patients with diabetes.

Materials and methods: Diabetes was induced in 8-week-old C56BL/6J mice using streptozotocin (STZ). Four weeks after the injection of STZ, a mechanical load was applied between the first and second molars on the right side of the upper jaw using the Waldo method with orthodontic elastics in diabetic (DM) and normal (N) mice tooth movement, gene expression, osteoclast counts, alveolar bone residual volume, and bone beam structure were evaluated.

Results: The duration until spontaneous elastic loss was significantly longer in the DM group, suggesting that tooth movement may be inhibited in the diabetic state. The number of osteoclasts at 7 days after mechanical loading and the alveolar bone resorption were both significantly lower in the DM group. The gene expression levels of vascular endothelial growth factor (VEGF), a protein related to alveolar bone remodeling, and specificity protein 1 (SP1), a transcription factor of the VEGF gene, were significantly lower in the DM group than in the N group on the compression side of mechanical loading.

Conclusions: Mechanical loading-induced alveolar bone remodeling is suppressed in the diabetic state. Our results suggest that VEGF is a key molecule involved in impaired bone remodeling under mechanical loading in the diabetic state.

Aims/introduction: The aim of this study was to identify a metabolic signature of MIDD as compared to healthy controls and other types of diabetes.

Methods: We performed a comprehensive serum metabolomic analysis using gas chromatography-time of flight mass spectrometry (GC-TOFMS) in participants diagnosed with MIDD (n = 14), latent autoimmune diabetes in adults (LADA) (n = 14), type 2 diabetes mellitus (n = 14), and healthy controls (n = 14). Each group was matched for gender and age.

Results: There were significant metabolic differences among MIDD and other diabetic and control groups. Compared with control, MIDD patients had high levels of carbohydrates (glucose, galactose, mannose, sorbose, and maltose), fatty acids (2-Hydroxybutyric acid, eicosapentaenoic acid, and octadecanoic acid), and other metabolites (alanine, threonic acid, cholesterol, lactic acid, and gluconic acid), but low level of threonine. Compared with LADA, MIDD patients had high levels of threonic acid and some amino acids (alanine, tryptophan, histidine, proline, glutamine, and creatine) but low levels of serine. Compared with type 2 diabetes mellitus, MIDD patients had high levels of citrulline, creatine, 3-Amino-2-piperidone, but low levels of ornithine, fatty acids (arachidonic acid and octadecanoic acid), and intermediates of the tricarboxylic acid cycle (malic acid and succinic acid).

Conclusions: Our study identified a specific metabolic profile related to glycolysis and the tricarboxylic acid cycle in MIDD that differs from healthy controls and other types of diabetes. This unique metabolic signature provides new perspectives for understanding the pathophysiology and underlying mechanisms of MIDD.

Background and aims: To prevent end-stage renal disease caused by diabetic kidney disease, we created a predictive model for high-risk patients using machine learning.

Methods and results: The reference point was the time at which each patient's estimated glomerular filtration rate (eGFR) first fell below 60 mL/min/1.73 m². The input period spanned the reference point to 1 year prior. The primary endpoint was a 50% decrease in eGFR from the mean of the input period over the 3 year evaluation period. We created predictive models for patients' primary endpoints using time series data of various variables over the input period. Among 2,533 total patients, 1,409 had reference points, 31 had records for their input and evaluation periods and had reached their primary endpoints, and 317 patients had not. The area under the curve (AUC) of the predictive model peaked (0.81) when the minimum eGFR, the difference between maximum and minimum eGFR, and both maximum and minimum urinary protein values were included in the features.

Conclusion: The accuracy of prognosis prediction can be improved by considering the variable components of urinary protein and eGFR levels. This model will allow us to identify patients whose renal functions are relatively preserved with eGFR of more than 60 mL/min/1.73 m² and are likely to benefit clinically from immediate treatment intensification.

Objective: To investigate the risk of biliary diseases in patients with type 2 diabetes mellitus (T2DM) or obesity treated with tirzepatide.

Methods: Literature searches were performed using the PubMed, Web of Science, Cochrane Library, and CNKI databases until 20 May 2024. Randomized controlled studies (RCTs) investigating the safety of tirzepatide vs placebo/other hypoglycemic drugs in patients with T2DM or obesity were included. The safety outcomes mainly included the incidence of cholelithiasis, pancreatitis, cholecystitis, and gallbladder/biliary diseases. Cochrane Collaboration's tool for assessing the risk of bias was used to assess the quality of literature. Heterogeneity was evaluated using I² statistics.

Results: A total of 12 high-quality RCTs (involving 12,351 patients) were included. The results of meta-analysis showed that tirzepatide was associated with gallbladder/biliary diseases (RR = 1.52; 95%CI: 1.17-1.98; I² = 0%, P = 0.76) and cholelithiasis (RR = 1.67; 95%CI: 1.14-2.44; I² = 0%, P = 0.95). Subgroup analysis based on the dose of tirzepatide found no dose-response relationship between different doses of tirzepatide and the risk of gallbladder/biliary diseases and cholelithiasis.

Conclusions: Based on the data currently available, tirzepatide is associated with the development of cholelithiasis in patients. However, the findings from RCTs still need to be further investigated in many post-marketing safety surveillance programs.

Aim: Hyperglycemia was found to be associated with an increased risk of cancer in a general population cohort. However, it remains to be established whether the severity of diabetic complications is associated with cancer risk in patients with diabetes.

Materials and methods: We used the National Health Insurance Research Database from 2000 through 2013, including those with newly diagnosed diabetic patients (n = 616,742). We collected all vascular and metabolic complications to develop an adapted diabetic complication severity index (aDCSI), ranging from 0 to 13 annually, as proxies of the severity of diabetic complications and performed follow-up from the onset of diabetes until incident cancer, death, or the study end.

Results: Within the mean follow-up period of 9 years, the rates of cancer incidence per 100,000 person-years were 815.2 vs 482.0 and 611.1 vs 358.9 for the top vs bottom quartiles, respectively, of aDCSI in men and women (adjusted HRs 1.17 (95% CI 1.10-1.25) and 1.20 (95% CI 1.10-1.30), respectively). The risk of cancer was 1.7- to 1.9-fold for the top vs bottom quartiles of aDCSI in diabetic onset age of 40-44 (HRs 1.74 (95% CI, 1.39-2.18) in men and HRs 1.93 (95% CI, 1.39-2.66) in women). However, among patients with diabetic onset age of 60-64, the associations between the severity of diabetic complications and cancer risk were attenuated.

Conclusions: Patients with higher severity of diabetic complications have an increased risk of cancer compared to those with the lowest severity, particularly for those with earlier onset and greater severity of diabetic complications.

Aims/introduction: The relationship between economic disadvantages and the risk of developing gestational diabetes mellitus (GDM), as well as its impact on birth outcomes, remains uncertain.

Materials and methods: From the Taiwan Maternal and Child Health Database, we identified 984,712 pregnant women between 1 January 2007 and 31 December 2018. Using propensity score matching, we selected 5,068 pairs of women across four income levels: very low, low, middle and high. We used a multivariable Cox regression model to assess the risk of GDM in these pregnant women and analyzed the birth outcomes.

Results: The mean age of the pregnant women was 30.89 years. We found no significant difference in GDM risk among pregnant women with different family income. However, newborns of women with GDM and very low-income were at higher risk for several adverse conditions, such as small for gestational age (adjusted odds ratio (aOR) 1.17, 95% confidence interval (CI) 1.04-1.31), large for gestational age (aOR 1.27, 95% CI 1.08-1.51), hypoxic-ischemic encephalopathy (aOR 3.19, 95% CI 1.15-8.86), respiratory distress (aOR 1.58, 95% CI 1.14-2. 19), congenital anomalies (aOR 1.32, 95% CI 1.08-1.62), jaundice requiring phototherapy or exchange transfusion (aOR 1.14, 95% CI 1.05-1.24) and so on.

Conclusions: This study found that low family income alone was not associated with GDM development. However, for a GDM pregnancy, pregnant women with lower income had worse birth outcomes. Improving maternal health and nutrition among low-income pregnant women with GDM might be critical to improving birth outcomes.

Insulin treatment should be introduced in patients with slowly progressive type 1 diabetes (SPIDDM; definite), according to the revised diagnostic criteria of SPIDDM (2023). In contrast, SPIDDM (probable) patients are in a non-insulin-dependent state; therefore, a more flexible treatment can be considered, although sulfonylurea agents should be avoided. Insulin treatment has been shown to maintain endogenous insulin secretion capacity in SPIDDM (probable); however, this does not mean that all SPIDDM (probable) patients should use insulin from the early phase. Dipeptidyl peptidase-4 inhibitors and biguanides might be the treatment of choice for SPIDDM (probable), but no evidence exists for other hypoglycemic agents. In any case, careful monitoring of the endogenous insulin secretion capacity should be carried out, and if a decrease in insulin secretion capacity is suspected, a change in treatment should be considered to prevent progression to an insulin-dependent state.

Aims/introduction: We investigated the association between impaired fasting glucose (IFG) and cardiometabolic multimorbidity (CMM) in the Chinese population.

Materials and methods: We included 119,368 participants, free of diabetes mellitus and cardiovascular disease, who participated in the health examination (2006, 2008, 2010) of the Kailuan Study. According to World Health Organization diagnostic criteria, participants were divided into normal fasting blood glucose (FBG) (<6.1 mmol/L) and IFG (FBG 6.1-6.9 mmol/L) groups. CMM was defined as having two or more cardiometabolic diseases, including myocardial infarction, stroke and diabetes mellitus. We used Cox proportional hazards models to evaluate associations between IFG and CMM.

Results: During a median follow-up period of 13.94 years, 2,432 CMM incident events occurred. After adjusting potential confounders, the hazard ratio (HR) and 95% confidence interval (CI) for CMM in the IFG group was 2.83 (95% CI 2.58-3.10) versus the normal FBG group. The HR of IFG for diabetes mellitus was 3.43 (95% CI 3.30-3.55), which was >1.25 (95% CI 1.13-1.37) for myocardial infarction, 1.16 (95% CI 1.07-1.25) for ischemic stroke and 1.06 (95% CI 0.88-1.27) for hemorrhagic stroke. Compared with normal FBG, HRs for risk of IFG for CMM were 2.73 (95% CI 2.48-3.02) in men and 3.86 (95% CI 2.92-5.09) in women.

Conclusion: IFG was a risk factor for CMM. The effect of IFG on diabetes mellitus was stronger than that on other cardiometabolic diseases. The effects of IFG for CMM differed by sex.

Aims/introduction: This study aimed to investigate the risk factors for diabetic retinopathy (DR) and diabetic kidney disease (DKD) in Japanese patients with diabetes mellitus (DM). Identifying these factors could provide insights into the shared and distinct mechanisms contributing to these complications in the diabetic population.

Materials and methods: We conducted a retrospective analysis using the J-DREAMS (Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System) database, which is directly linked to electronic medical records. The study included Japanese people aged 18 years and older with diabetes, who were registered at a referral center between December 1, 2015, and March 31, 2021, and had simultaneous measurements of serum creatinine and hemoglobin A1c (HbA1c). The presence or absence of DR and DKD was determined for 8,794 and 8,770 patients, respectively. Multivariable logistic regression analyses were used to identify risk factors, considering patient characteristics, comorbid conditions, and laboratory data as explanatory variables.

Results: Common risk factors for both DR and DKD included hypertension, anemia, diabetic neuropathy, cerebrovascular disease, chronic heart failure, low serum albumin levels, and elevated HbA1c. The contributions of age, duration of DM, and body mass index (BMI) differed between the DR and DKD groups.

Conclusions: In addition to poor glycemic control and hypertension, anemia, low serum albumin, cerebrovascular disease, and heart failure were identified as independent common risk factors for DR and DKD, suggesting the existence of cardio-renal anemia syndrome in patients with DM.