Journal of Diabetes Investigation最新文献

Introduction: Identifying patient characteristics predictive of treatment response is crucial for optimizing type 2 diabetes outcomes. Using data from three phase 2/3 imeglimin trials in Japan, this analysis applied machine learning to determine characteristics associated with HbA1c improvement.

Methods: Regression tree and random forest methods identified baseline characteristics predictive of HbA1c improvement. Partial dependence plots (PDP) visualized the relationship between HbA1c change and continuous variables deemed important by Boruta.

Results: For monotherapy, key predictors were baseline HbA1c, hypertension, smoking, type 2 diabetes duration, body mass index (BMI), low-density lipoprotein-cholesterol (LDL-C), metabolic syndrome, and estimated glomerular filtration rate. Nonsmokers with HbA1c ≥8.35% and LDL-C < 3.26 mmol/L at baseline showed the greatest improvement in HbA1c (-1.24%). Random forest analysis and Boruta identified baseline HbA1c, BMI, fatty liver index, smoking, and hypertension as significant predictors of HbA1c improvement. PDPs identified a positive correlation between higher baseline HbA1c, and a negative correlation between BMI and fatty liver index, and HbA1c improvement. For imeglimin add-on to insulin therapy, key predictors were BMI, age, LDL-C, type 2 diabetes duration, systolic blood pressure, and alanine transaminase (ALT). Patients with BMI <25.9, LDL-C < 2.68 mmol/L, and ALT <21 U/L showed the greatest HbA1c improvement (-1.48%). Random forest analysis and Boruta confirmed BMI, age, and LDL-C as significant predictors. PDPs identified a positive correlation between older age, and a negative correlation between higher BMI and LDL-C, and HbA1c improvement.

Conclusions: Machine learning effectively identified baseline characteristics predictive of HbA1c response to imeglimin, supporting the potential for personalized type 2 diabetes treatment strategies.

Aims/introduction: While treatment for diabetic polyneuropathy (DPN) is still developing, progress has stagnated. The alignment between pathological neurodegeneration in DPN and patients' subjective symptoms is often low, yet these symptoms are frequently used for diagnosis. This reliance has hindered the development of effective drugs to prevent neurodegeneration. This study aims to establish an objective electrophysiological diagnostic method that could support future treatment development and validate its accuracy.

Materials and methods: This retrospective multicenter cohort study involved hospitalized diabetic patients. A total of 314 patients underwent nerve conduction studies using standard electromyography and a simplified nerve conduction testing device (NC-stat/DPNCheck™), along with electrocardiogram-based coefficient of variation of R-R intervals (CV_R-R). Patients with a severity classification of Stage 2 or higher based on electromyography were defined as having DPN. Logistic regression analysis was used to identify significant factors explaining DPN presence, followed by ROC analysis to determine optimal cutoff values for diagnosis.

Results: Significant factors included resting CV_R-R, sural nerve conduction velocity (SNCV), and amplitude of sensory nerve action potential (SNAP). SNCV had the highest area under the curve (AUC = 0.823). The optimal cutoff values were 1.62% for CV_R-R, 46.5 m/s for SNCV, and 10.5 μV for SNAP. Diagnosing DPN based on abnormalities in two or more of these three conditions yielded an accuracy of 79.3%.

Conclusions: The established diagnostic criteria of DPN demonstrate high performance and are expected to be applicable in clinical settings.

A 48-year-old man was referred to our hospital due to hyperglycemia. His casual plasma glucose and glycated hemoglobin A1c were 25.2 mmol/L and 8.7%, respectively. He had undergone bilateral cataract surgery in his 30s. He exhibited a bird-like face contour, gray hair, alopecia, and bilateral calcifications of the Achilles' tendons, suggestive of Werner syndrome (WS). Genetic analysis revealed compound heterozygous mutations in the WRN gene (mutation c. 3139-1G>C, mutation c. 1105C>T), leading to the diagnosis of WS. Adequate glycemic control was not achieved by the treatment with pioglitazone and metformin. Additional administration of dapagliflozin, a sodium-glucose cotransporter 2 inhibitor, ameliorated insulin resistance and resulted in an improvement in glycemic control without adverse events. Dapagliflozin may potentially be a choice in treating diabetes associated with WS with an amelioration of insulin resistance.

Introduction: We aimed to evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics of single and multiple doses of orforglipron in Japanese participants with type 2 diabetes.

Materials and methods: This was a double-blind, placebo-controlled, randomized, phase 1 study. In Part A, participants received single doses of orforglipron (2 or 3 mg) or placebo. In Part B, participants received multiple ascending doses of daily oral orforglipron (final target doses: 12, 24, and 45 mg) or placebo for 12 weeks.

Results: Parts A and B enrolled 23 and 60 participants, respectively. The most common treatment-emergent adverse events were gastrointestinal events of mild severity. No severe or serious adverse events were reported. At week 12, median t_max was 5.92-8.00 h, and mean terminal half-life was 51.8-76.1 h. Following multiple ascending doses, orforglipron groups had greater mean reductions from baseline to week 12 in glycemic parameters (fasting glucose: orforglipron 12 mg -64.8 mg/dL, 24 mg -61.1 mg/dL, 45 mg -65.6 mg/dL, placebo 7.4 mg/dL; glycated hemoglobin: orforglipron 12 mg -2.16%, 24 mg -2.17%, 45 mg -2.28%, placebo 0.67%) and body weight (orforglipron 12 mg -2.9 kg, 24 mg -6.3 kg, 45 mg -4.8 kg, placebo 0.3 kg) compared with placebo.

Discussion: In Japanese participants, safety, pharmacokinetic, and pharmacodynamic results were similar to those of previous orforglipron studies. The safety and tolerability of orforglipron were also consistent with those of other glucagon-like peptide-1 receptor agonists. Orforglipron is a potential new treatment option for Japanese patients with type 2 diabetes.

Aims/introduction: Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus and may be linked to renal function decline. However, the prognostic value of point-of-care nerve conduction devices such as DPN-Check® for renal outcomes remains unclear.

Materials and methods: We conducted a single-center retrospective observational study of 403 patients with diabetes (median follow-up 2.9 years) at Tokyo Metropolitan Ohkubo Hospital. DPN was assessed by DPN-Check® (amplitude [AMP] <5 μV or nerve conduction velocity [NCV] <42 m/s) and simplified diagnostic criteria (SDC). The primary outcome was annual eGFR decline, calculated by the linear least squares method; rapid decliners were defined as those with a decline ≥5 mL/min/1.73 m²/year. Multivariate linear and logistic regression analyses were performed to identify independent associations.

Results: Patients with DPN diagnosed with DPN-Check® had a greater annual eGFR decline than those without (-2.26 vs. -0.81 mL/min/1.73 m²/year, P < 0.001), whereas DPN diagnosed with SDC showed no association. In multivariate analysis, DPN diagnosed with DPN-Check® remained independently associated with faster eGFR decline (standardized β: -0.262, P < 0.001) and with rapid decliner status (odds ratio [OR]: 2.791, 95% confidence interval [CI]: 1.267-6.152, P = 0.011).

Conclusions: DPN diagnosed by DPN-Check® was independently associated with accelerated renal function decline in patients with T2DM, even after adjusting for albuminuria. DPN-Check® may help identify patients at high risk for end-stage kidney disease and guide earlier intervention for both neuropathy and kidney disease.

Aims/introduction: Leukocytes are implicated in the inflammatory cascades of diabetic retinopathy (DR), but their causal roles remain ambiguous. This study employed a two-sample Mendelian randomization (MR) analysis to dissect the causal effects of circulating leukocyte counts on DR risk.

Materials and methods: We utilized summary statistics from large-scale genome-wide association studies (GWAS) for five leukocyte subtypes and DR in European-ancestry populations. The inverse-variance weighted (IVW) method was primary, supported by comprehensive sensitivity analyses including MR-Egger, weighted median, and the MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) test to ensure result robustness.

Results: A total of 2,136 leukocyte-related SNPs were extracted as instrumental variables for causal inference. MR analysis revealed that increased lymphocyte counts are associated with reduced DR risk (IVW OR = 0.93, 95% CI = 0.86-0.99, P = 0.03), while the initial association between higher eosinophil counts and DR risk (IVW OR = 1.11, 95% CI = 1.03-1.19, P < 0.01) was attenuated following correction for outliers. No significant associations were observed for basophil, monocyte, or neutrophil counts. Sensitivity analyses found no evidence of pleiotropy or substantial influence from single SNPs.

Conclusions: Our findings provide genetic evidence supporting a potential causal association between lymphocyte counts and diabetic retinopathy risk, while the association for eosinophil counts was attenuated after correction for outliers. These results highlight the importance of further investigating the physiological role of lymphocytes in diabetic retinopathy to inform effective prevention and treatment strategies.

Aims/introduction: COVID-19 containment measures in Japan, characterized by intermittent states of emergency (SE) without strict lockdowns from April 2020 to September 2021, may have significantly impacted lifestyle, weight, and body composition in individuals with diabetes. This study examines changes in glycemic management, body weight, and body composition before, during, and after SE in adults with diabetes.

Materials and methods: This retrospective study included individuals with diabetes aged 20 years or older whose HbA1c and body composition were measured in three periods of pre-SE (April 2019-March 2020), SE (April 2020-September 2021), and post-SE (October 2021-September 2022). Hospitalized individuals were excluded. Participants were divided into subgroups by age (young: <65 years, older: ≥65 years) and gender for analysis.

Results: A total of 673 subjects were analyzed. No significant changes in HbA1c were observed in any period. Body weight remained constant during SE but decreased post-SE. Continuous decreases in skeletal muscle mass were noted in all groups. In the total analysis, body fat mass initially increased during SE but decreased post-SE. However, due to weight loss in the post-SE, the overall body fat percentage rose. Notably, in older males, body fat mass increased during SE and remained unchanged post-SE, resulting in a continuous increase in body fat percentage throughout observational periods.

Conclusion: The study highlights a continuous decline in muscle mass and body weight changes, with body fat percentage fluctuations differing by age and gender. The impact was most significant in older males, underscoring the need for targeted health interventions.

Introduction: MiniMed 780G was the first automated insulin delivery (AID) system approved in Poland. Although it has been studied extensively, there are relatively less data regarding its use in children with type 1 diabetes from the onset of the disease. We aimed to evaluate and compare glycemic parameters in children treated from type 1 diabetes onset with either an AID system or a pump with predictive-low glucose suspend (SAP-PLGS).

Material and methods: We retrospectively gathered anthropometric data and systems records of 50 children with a newly diagnosed type 1 diabetes, 22 using an AID system (aged 9.66 ± 3.76 years), and 28 using a SAP-PLGS device (aged 8.13 ± 4.2 years). Glycemic parameters and other collected data were compared at four different time points: the first 2 weeks using the insulin pump and 2 weeks after 3, 6, and 12 months of insulin therapy.

Results: After the first year of treatment, we found in the AID group higher time in range (TIR) 70-180 mg/dL (P = 0.001) as well as time in tight range (TITR) 70-140 mg/dL (P = 0.0003). There were no significant differences in the C-peptide level after 1 year of treatment between the two studied groups (P = 0.41).

Conclusions: Using the AID system from the onset of type 1 diabetes resulted in improved glycemic control parameters in the studied children compared with using SAP-PLGS. The C-peptide preservation was comparable in both analyzed groups.

Objective: To analyze the disease burden of chronic kidney disease due to diabetes mellitus type 2 (CKD due to diabetes mellitus type 2) in China and the global population from 1990 to 2021, and to predict the future trend of the population.

Methods: Joinpoint regression quantifies trends by the average annual percentage change (AAPC). Decomposition analysis assessed the contribution of aging, population growth, and epidemiological transitions to changes in the disease burden. The Bayesian model predicts the number of cases and deaths in 2022-2031.

Results: From 1990 to 2021, the global and Chinese age-standardized incidence rates (ASIRs) showed an upward trend, of which the global AAPC was 1.928% (95% CI = 1.908-1.948%); global and Chinese age-standardized mortality rates (ASMRs) are on the rise. In the decomposition analysis, population growth was the main driving force for the increase of global and Chinese cases and deaths, accounting for 60.14, 53.99, 56.64, and 72.82% of the change, respectively. 87.17% of the global age-standardized DALY rate was attributed to hyperglycemia. High BMI has become a major risk factor in China. It is expected that by 2031, the number of ASIR and deaths of CKD worldwide will continue to rise.

Conclusions: The CKD due to diabetes mellitus type 2 burden remains severe worldwide and in China. Strengthened public health policies and clinical prevention strategies are urgently needed to mitigate this burden.