β-Cell function or insulin resistance was associated with the risk of type 2 diabetes among women with or without obesity and a history of gestational diabetes

Associations between Diabetes Mellitus and Selected Cancers

Cancer is one of the major causes of mortality and is the second leading cause of death. Diabetes mellitus is a serious and growing problem worldwide, and its prevalence continues to grow; it is the 12th leading cause of death. An association between diabetes mellitus and cancer has been suggested for more than 100 years. Diabetes is a common disease diagnosed among patients with cancer, and evidence indicates that approximately 8-18% of patients with cancer have diabetes, with investigations suggesting an association between diabetes and some particular cancers, increasing the risk for developing cancers such as pancreatic, liver, colon, breast, stomach, and a few others. Breast and colorectal cancers have increased from 20% to 30% and there is a 97% increased risk of intrahepatic cholangiocarcinoma or endometrial cancer. On the other hand, a number of cancers and cancer therapies increase the risk of diabetes mellitus. Complications due to diabetes in patients with cancer may influence the choice of cancer therapy. Unfortunately, the mechanisms of the associations between diabetes mellitus and cancer are still unknown. The aim of this review is to summarize the association of diabetes mellitus with selected cancers and update the evidence on the underlying mechanisms of this association.

Genetic risk of type 2 diabetes modifies the association between lifestyle and glycemic health at 5 years postpartum among high-risk women

INTRODUCTION

Lifestyle interventions are effective in preventing type 2 diabetes, but genetic background may influence the individual response. In the Finnish gestational diabetes prevention study, RADIEL, lifestyle intervention during pregnancy and first postpartum year was effective in preventing gestational diabetes (GDM) and postpartum glycemic abnormalities only among women at highest genetic risk of type 2 diabetes. This study aimed to assess whether still 5 years postpartum the genetic risk modifies the association between lifestyle and glycemic health.

RESEARCH DESIGN AND METHODS

The RADIEL study (randomized controlled trial) aimed to prevent GDM with a lifestyle intervention among high-risk women (body mass index ≥30 kg/m2 and/or prior GDM). The follow-up study 5 years postpartum included anthropometric measurements, laboratory assessments, device-measured physical activity (PA), and questionnaires. A Healthy Lifestyle Score (HLS) indicated adherence to lifestyle goals (PA, diet, smoking) and a polygenic risk score (PRS) based on 50 type 2 diabetes risk alleles depicted the genetic risk.

RESULTS

Altogether 314 women provided genetic and glycemic data 5 years postpartum. The PRS for type 2 diabetes was not associated with glycemic abnormalities, nor was HLS in the total study sample. There was, however, an interaction between HLS and type 2 diabetes PRS on glycemic abnormalities (p=0.03). When assessing the association between HLS and glycemic abnormalities in PRS tertiles, HLS was associated with reduced risk of glycemic abnormalities only among women at the highest genetic risk (p=0.008).

CONCLUSIONS

These results extend our previous findings from pregnancy and first postpartum year demonstrating that still at 5 years postpartum, healthy lifestyle is associated with a lower risk of prediabetes/diabetes only among women at the highest genetic risk of type 2 diabetes.

Changes in insulin resistance, body mass index and degree of obesity among junior high school students: A comparison before and after the outbreak of the COVID-19 pandemic

This study aimed to investigate how the COVID-19 pandemic since 2020 has affected the homeostasis model assessment of insulin resistance (HOMA-IR), body mass index (BMI) and degree of obesity among Japanese children. HOMA-IR, BMI and degree of obesity were calculated for 378 children 14-15 years old (boys/girls, 208/170) who underwent checkups during 2015-2021. Changes in these parameters over time and correlations between parameters were assessed, and the proportions of participants with IR (HOMA-IR ≥2.5) were compared. HOMA-IR values increased significantly over the study period (p < 0.001), with a significantly large proportion of participants with IR in 2020-2021 (p < 0.001). Conversely, BMI and degree of obesity did not change significantly. HOMA-IR did not correlate with BMI or degree of obesity during 2020-2021. In conclusion, the COVID-19 pandemic may have had an impact on the increase in the proportion of children with IR, regardless of BMI or degree of obesity.

An Early Mediterranean-Based Nutritional Intervention during Pregnancy Reduces Metabolic Syndrome and Glucose Dysregulation Rates at 3 Years Postpartum

A Mediterranean diet (MedDiet)-based intervention reduces the rate of immediate postpartum maternal metabolic disorders. Whether these effects persist long-term remains to be determined. A total of 2526 normoglycemic women were randomized before the 12th gestational week (GW). IG women followed a MedDiet with extra virgin olive oil (EVOO) (>40 mL/day) and a handful of nuts daily, whereas CG women had to restrict all kinds of dietary fat. At 3 months postpartum, a motivational lifestyle interview was held. The endpoint of the study evaluated the rate of abnormal glucose regulation (AGR) and metabolic syndrome (MetS) at 3 years postpartum in women of the San Carlos cohort. A total of 369/625 (59%) CG women and 1031/1603 (64.3%) IG women were finally analyzed. At 3 months and 3 years postdelivery, the IG women showed higher adherence to the MedDiet, which was associated with lower values of body mass index (BMI) and lipid and glycemic profiles. Body weight change and waist circumference were lower in the IG women. After applying multiple regression analysis, the ORs (95%CI) resulted in AGR (3.18 (2.48-4.08); p < 0.001)/MetS (3.79 (1.81-7.95); p = 0.001) for women with GDM and higher OR for development of MetS in CG women (3.73 (1.77-7.87); p = 0.001). A MedDiet-based intervention early in pregnancy demonstrated persistent beneficial effects on AGR and MetS rates at 3 years postpartum.

An early prediction model for gestational diabetes mellitus based on metabolomic biomarkers

BACKGROUND

Gestational diabetes mellitus (GDM) represents the main metabolic alteration during pregnancy. The available methods for diagnosing GDM identify women when the disease is established, and pancreatic beta-cell insufficiency has occurred.The present study aimed to generate an early prediction model (under 18 weeks of gestation) to identify those women who will later be diagnosed with GDM.

METHODS

A cohort of 75 pregnant women was followed during gestation, of which 62 underwent normal term pregnancy and 13 were diagnosed with GDM. Targeted metabolomics was used to select serum biomarkers with predictive power to identify women who will later be diagnosed with GDM.

RESULTS

Candidate metabolites were selected to generate an early identification model employing a criterion used when performing Random Forest decision tree analysis. A model composed of two short-chain acylcarnitines was generated: isovalerylcarnitine (C5) and tiglylcarnitine (C5:1). An analysis by ROC curves was performed to determine the classification performance of the acylcarnitines identified in the study, obtaining an area under the curve (AUC) of 0.934 (0.873-0.995, 95% CI). The model correctly classified all cases with GDM, while it misclassified ten controls as in the GDM group. An analysis was also carried out to establish the concentrations of the acylcarnitines for the identification of the GDM group, obtaining concentrations of C5 in a range of 0.015-0.25 μmol/L and of C5:1 with a range of 0.015-0.19 μmol/L.

CONCLUSION

Early pregnancy maternal metabolites can be used to screen and identify pregnant women who will later develop GDM. Regardless of their gestational body mass index, lipid metabolism is impaired even in the early stages of pregnancy in women who develop GDM.

Inverse Correlation of Superoxide Dismutase and Catalase with Type 2 Diabetes among Rural Thais

Oxidative stress contributes to defective antioxidant defenses, which may lead to type 2 diabetes (T2D). This study aimed to elucidate the T2D risks and antioxidant defenses by investigating the superoxide dismutase (SOD), catalase (CAT), vitamin A, and vitamin E status. We observed 102 participants aged 35-66 years from Sung Neon, Nakhon Ratchasima, Thailand. The blood samples were collected to measure the SOD, CAT, vitamin A, and vitamin E concentrations. The SOD and CAT activities were inversely associated with T2D risk. When compared with participants in the highest quartile of SOD and CAT, those in the lowest quartile for T2D risk obtained multivariable-adjusted odds ratios of 4.77 (SOD: 95% confident interval CI, 1.01-22.40; p = 0.047) and 4.22 (CAT: 95% CI, 1.07-16.60; p = 0.039). The possible influencing factors (e.g., physical activity, total cholesterol, and triglyceride) might mediate the association of SOD and CAT with T2D risk. Meanwhile, the relationship between vitamin A and vitamin E concentrations and T2D risk was insignificant. In conclusion, lower concentrations of antioxidant enzyme activity (SOD and CAT) may be an additional risk factor for T2D.

Gut Microbiota Associated with Gestational Health Conditions in a Sample of Mexican Women

Gestational diabetes (GD), pre-gestational diabetes (PD), and pre-eclampsia (PE) are morbidities affecting gestational health which have been associated with dysbiosis of the mother's gut microbiota. This study aimed to assess the extent of change in the gut microbiota diversity, short-chain fatty acids (SCFA) production, and fecal metabolites profile in a sample of Mexican women affected by these disorders. Fecal samples were collected from women with GD, PD, or PE in the third trimester of pregnancy, along with clinical and biochemical data. Gut microbiota was characterized by high-throughput DNA sequencing of V3-16S rRNA gene libraries; SCFA and metabolites were measured by High-Pressure Liquid Chromatography (HPLC) and (Fourier Transform Ion Cyclotron Mass Spectrometry (FT-ICR MS), respectively, in extracts prepared from feces. Although the results for fecal microbiota did not show statistically significant differences in alfa diversity for GD, PD, and PE concerning controls, there was a difference in beta diversity for GD versus CO, and a high abundance of Proteobacteria, followed by Firmicutes and Bacteroidota among gestational health conditions. DESeq2 analysis revealed bacterial genera associated with each health condition; the Spearman's correlation analyses showed selected anthropometric, biochemical, dietary, and SCFA metadata associated with specific bacterial abundances, and although the HPLC did not show relevant differences in SCFA content among the studied groups, FT-ICR MS disclosed the presence of interesting metabolites of complex phenolic, valeric, arachidic, and caprylic acid nature. The major conclusion of our work is that GD, PD, and PE are associated with fecal bacterial microbiota profiles, with distinct predictive metagenomes.

Metabolic Profiling of Pregnant Women with Obesity: An Exploratory Study in Women at Greater Risk of Gestational Diabetes

Gestational diabetes mellitus (GDM) is one of the most prevalent obstetric conditions, particularly among women with obesity. Pathways to hyperglycaemia remain obscure and a better understanding of the pathophysiology would facilitate early detection and targeted intervention. Among obese women from the UK Pregnancies Better Eating and Activity Trial (UPBEAT), we aimed to compare metabolic profiles early and mid-pregnancy in women identified as high-risk of developing GDM, stratified by GDM diagnosis. Using a GDM prediction model combining maternal age, mid-arm circumference, systolic blood pressure, glucose, triglycerides and HbA1c, 231 women were identified as being at higher-risk, of whom 119 women developed GDM. Analyte data (nuclear magnetic resonance and conventional) were compared between higher-risk women who developed GDM and those who did not at timepoint 1 (15+0−18+6 weeks) and at timepoint 2 (23+2−30+0 weeks). The adjusted regression analyses revealed some differences in the early second trimester between those who developed GDM and those who did not, including lower adiponectin and glutamine concentrations, and higher C-peptide concentrations (FDR-adjusted p < 0.005, < 0.05, < 0.05 respectively). More differences were evident at the time of GDM diagnosis (timepoint 2) including greater impairment in β-cell function (as assessed by HOMA2-%B), an increase in the glycolysis-intermediate pyruvate (FDR-adjusted p < 0.001, < 0.05 respectively) and differing lipid profiles. The liver function marker γ-glutamyl transferase was higher at both timepoints (FDR-adjusted p < 0.05). This exploratory study underlines the difficulty in early prediction of GDM development in high-risk women but adds to the evidence that among pregnant women with obesity, insulin secretory dysfunction may be an important discriminator for those who develop GDM.

Pregnancy-induced changes in β-cell function: what are the key players?

Maternal metabolic adaptations during pregnancy ensure appropriate nutrient supply to the developing fetus. This is facilitated by reductions in maternal peripheral insulin sensitivity, which enables glucose to be available in the maternal circulation for transfer to the fetus for growth. To balance this process and avoid excessive hyperglycaemia and glucose intolerance in the mother during pregnancy, maternal pancreatic β-cells undergo remarkable changes in their function including increasing their proliferation and glucose-stimulated insulin secretion. In this review we examine how placental and maternal hormones work cooperatively to activate several signalling pathways, transcription factors and epigenetic regulators to drive adaptations in β-cell function during pregnancy. We also explore how adverse maternal environmental conditions, including malnutrition, obesity, circadian rhythm disruption and environmental pollutants, may impact the endocrine and molecular mechanisms controlling β-cell adaptations during pregnancy. The available data from human and experimental animal studies highlight the need to better understand how maternal β-cells integrate the various environmental, metabolic and endocrine cues and thereby determine appropriate β-cell adaptation during gestation. In doing so, these studies may identify targetable pathways that could be used to prevent not only the development of pregnancy complications like gestational diabetes that impact maternal and fetal wellbeing, but also more generally the pathogenesis of other metabolic conditions like type 2 diabetes.