Journal of Diabetes Investigation最新文献

Objective: We here investigated whether lactation during puerperium could help to reverse the diabetogenic effect of gestation and further explored the lipid profiling changes upon breastfeeding.

Methods: Thirty-five women diagnosed with GDM were recruited, and fasting plasma samples were collected at ~6 weeks postpartum. Maternal metabolic parameters were determined, and an untargeted lipidomic analysis was performed. The relationship between underlying lipidomic responses and lactation was explored.

Results: Improved glucose homeostasis and insulin sensitivity were observed in GDM women who adopted breastfeeding during the puerperium. Further lipidomics analysis revealed prominent correlations between lipid constitution changes and breastfeeding in women with GDM. A total of 766 lipid species were identified, 33 of which were found to be significantly altered in response to lactation. Significant associations between dysregulated lipids and maternal metabolic parameters were also shown. Subsequently, we identified a panel of three lipids that were strongly associated with breastfeeding, from which we constructed a predictive model with higher discriminating power.

Conclusions: We generally revealed that lactation during puerperium appears to have favorable effects on diabetogenic risk factors for GDM women. We also discovered that lipidomic changes related to lactation could elucidate the mother's recovery from GDM pregnancy.

We report case details of a morbidly obese patient with type 2 diabetes mellitus (T2DM) who became a failure of diabetes remission after laparoscopic sleeve gastrectomy (LSG). He had a marked improvement of hyperglycemia after the revision surgery using Roux-en-Y gastric bypass (RYGB), where passage failure of a solid food intake at the gastric angle portion disappeared after the revision surgery. Interestingly, he showed improvements of insulin and a marked glicentin secretions with minor changes in glucagon related peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) secretions in the oral glucose tolerance test OGTT after the RYGB surgery compared with post-LSG. Although a marked increase in glucose-induced glicentin secretion after RYGB surgery with increased insulin secretion, further studies are needed to confirm if the increased glicentin secretion after RYGB surgery is linked to stimulation of insulin secretion.

Background: This study investigates the gender-specific genetic influence of the single nucleotide polymorphism (SNP) rs1111875 on diabetes risk within the Taiwanese population using data from the Taiwan Biobank. Diabetes mellitus, particularly type 2 diabetes (T2D), is influenced by genetic factors, and the rs1111875 SNP near the hematopoietically expressed homeobox (HHEX) gene has been linked to T2D susceptibility.

Methods: The study included 69,272 participants after excluding those from arsenic-polluted areas and those with incomplete data. Logistic regression models were used for analyses.

Results: The analyses revealed that the CT genotype of rs1111875 was associated with an increased risk of diabetes (OR = 1.092, 95% CI = 1.030-1.157, P = 0.003), as was the TT genotype (OR = 1.280, 95% CI = 1.165-1.407, P < 0.001). The effect was more pronounced in women (CT: OR = 1.118, 95% CI = 1.036-1.207, P = 0.004; TT: OR = 1.404, 95% CI = 1.243-1.585, P < 0.001). Men exhibited a higher overall risk of diabetes (OR = 1.565, 95% CI = 1.445-1.694, P < 0.001) and had a higher prevalence (12.71% vs 7.80%, P < 0.001) compared to women.

Conclusions: The findings underscore the importance of considering gender differences in genetic studies of diabetes and suggest that personalized diabetes management strategies should account for both genetic and gender-specific risk factors. This research contributes to the broader understanding of genetic determinants of diabetes and their interaction with gender, aiming to enhance personalized healthcare strategies for diabetes prevention and treatment.

Aims/introduction: To determine the association of irregular dietary habits with HbA1c and body mass index (BMI) in people with diabetes.

Materials and methods: We included 4,421 people with diabetes aged 20-74 years (type 1 diabetes (T1D), 19.1%) who answered a questionnaire at mealtime. Adjusted least square means in HbA1c and BMI in patients with irregular dietary habits: "irregular mealtimes (irregular)," "skipping breakfast (SB)," and "late dinner (LD)" were compared to those with "regular dietary habits (regular)." Multivariable logistic regression analyses were performed to examine the association of irregular dietary habits with HbA1c ≥ 7% and BMI ≥25 kg/m².

Results: HbA1c was significantly higher for "irregular" in both sexes and for "LD" in women than those of "regular" in people with T1D. HbA1c was significantly higher for "LD," and BMI was higher for almost all irregular dietary habits than those of "regular" in people with type 2 diabetes (T2D). Odds ratios (ORs) for HbA1c ≥7% were 3.20 (95% confidence interval (CI), 1.30-7.89) for T1D women with "irregular" and 1.73 (1.20-2.49) and 2.20 (1.14-3.65) for T2D men and women with "LD," respectively. ORs for BMI ≥25 kg/m² were 1.60 (95% CI, 1.15-2.22) for T2D men with "irregular" and 1.43 (1.02-2.01) and 2.11 (1.21-3.65) for T2D women and men with "LD," respectively.

Conclusions: Irregular mealtimes are associated with poor glycemic control in T1D women and are associated with obesity in T2D men. Furthermore, a late dinner was associated with high HbA1c levels and BMI in people with T2D.

Aims: This study aimed to identify metabolic markers for diabetic peripheral neuropathic pain (DPNP) in patients with type 2 diabetes mellitus (T2DM).

Materials and methods: Blood metabolite levels in the amino acid, biogenic amine, sphingomyelin, phosphatidylcholine (PC), carnitines, and hexose classes were analyzed in nondiabetic control (n = 27), T2DM without DPNP (n = 58), and T2DM with DPNP (n = 29) using liquid chromatography tandem mass spectrometry. Variable importance projection (VIP) evaluation by partial least squares discriminant analysis was performed on clinical parameters and metabolites.

Results: Sixteen variables with VIP > 1.0 (P < 0.05) were identified across all patient groups, and 5 variables were identified to discriminate between the two T2DM groups. DPNP patients showed elevated fasting blood glucose, glutamate, PC aa C36:1, lysoPC a C18:1, and lysoPC a C18:2, while low-density lipoprotein cholesterol, phenylalanine, and tryptophan were reduced. Glutamate, lysoPC a C18:1, and lysoPC a C18:2 discriminated T2DM with DPNP from those without DPNP with an AUC of 0.671. The AUC was improved to 0.765 when ratios of metabolite pairs were considered.

Interpretation: Blood metabolites include glutamate, and phospholipid-related metabolites implicated in neuropathic pain may have the potential as biomarkers for DPNP. Further investigation is required to understand the mechanism of action of these altered metabolites in DPNP.

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.

Objective: To explore the relationship between adipose tissue deposition and triglyceride-glucose (TyG) index, an indicator clinically used to assess insulin resistance (IR), in middle-aged and elderly women using quantitative computed tomography (QCT) and MRI mDIXON-Quant sequence.

Methods: All participants underwent quantitative computed tomography (QCT) and MRI mDIXON-Quant examination and calculated the TyG index based on the fasting blood glucose and triacylglycerol. Bounded by the median TyG index, all participants were divided into low TyG group and high TyG group. Visceral fat mass (VFM) and subcutaneous fat mass (SFM) were measured on QCT images. Hepatic proton density fat fraction (H-PDFF), pancreatic proton density fat fraction (P-PDFF), and lumbar bone marrow fat fraction (L-BMFF) were measured on MRI mDIXON-Quant images.

Results: Adjusting for age and body mass index (BMI), TyG was moderately positively correlated with H-PDFF, and r/P was 0.416/<0.001, TyG index was weakly positively correlated with VFM and P-PDFF, and r/P were 0.385/<0.001 and 0.221/0.030. There was a difference of VFM, H-PDFF, and P-PDFF between low TyG group and high TyG group (P < 0.05). Adjusting for age and BMI, VFM, and H-PDFF were the risk factors of high TyG, and H-PDFF was the independent risk factor of high TyG.

Conclusions: VFM and H-PDFF were the risk factors of IR, and H-PDFF was the independent risk factor. Early identification and active treatment of adipose tissue deposition, especially hepatic fat deposition, may reserve and delay the progression of IR and even metabolic syndrome.

GIP is a multifaceted hormone whose role in metabolism is highly context-dependent. Pharmacological GIP receptor activation promotes weight loss and improves insulin sensitivity, contrasting sharply with the lipogenic and insulin-resistant effects of endogenous GIP. However, it remains unclear whether these effects simply amplify endogenous GIP's actions or represent distinct mechanisms.

Introduction: The early detection of high-risk individuals is crucial to delay and reduce the incidence of type 2 diabetes. In this study, we aimed to explore the performance of a novel subgroup-specific biomarker strategy in the prediction of incident diabetes.

Materials and methods: In the Taiwan Lifestyle Cohort Study, adult subjects without diabetes were included and followed for the incidence of diabetes in 2006-2019. The biomarkers measured included blood secretogranin III (SCG3), vascular adhesion protein-1 (VAP-1), fibrinogen-like protein 1 (FGL1), angiopoietin-like protein 6 (ANGPTL6), and angiopoietin-like protein 4 (ANGPTL4).

Results: Among the 1,287 subjects, 12.2% developed diabetes during a 6 year follow-up. Blood VAP-1 was significantly associated with incident diabetes in the overall population (HR = 0.724, P < 0.05), participants under 65 years old (HR = 0.685, P < 0.05), those with a BMI of ≥24 kg/m² (HR = 0.673, P < 0.05), and females (HR = 0.635, P < 0.05). Blood ANGPTL6 was significantly correlated with incident diabetes in participants aged 65 and older (HR = 0.314, P < 0.05), and blood SCG3 was associated with incident diabetes in those with a BMI of <24 kg/m² (HR = 1.296, P < 0.05). Two subgroup-specific biomarker strategies were developed. The gender and BMI-specific biomarker strategy, using traditional risk factors and blood SCG3 or VAP-1 in different subgroups, could improve prediction performance, especially the specificity and positive prediction value, compared with the whole-population strategy using only traditional risk factors or traditional risk factors plus blood VAP-1.

Conclusion: Gender- and BMI-specific biomarker strategy can improve the prediction of incident diabetes. A subgroup-specific biomarker strategy is a novel approach in the prediction of incident diabetes.

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.