Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors

Licochalcone A alleviates abnormal glucolipid metabolism and restores energy homeostasis in diet-induced diabetic mice

Licochalcone A (LCA) is a bioactive chalcone compound identified in licorice. This study aimed to investigate the effects of LCA on glucolipid metabolism and energy homeostasis, as well as the underlying mechanisms. Blood glucose levels, oral glucose tolerance, serum parameters, and histopathology were examined in high-fat-high-glucose diet (HFD)-induced diabetic mice, with metformin as a positive control. Additionally, changes in key markers related to glucolipid metabolism and mitochondrial function were analyzed to comprehensively assess LCA's effects on metabolism. The results showed that LCA alleviated metabolic abnormalities in HFD-induced diabetic mice, which were manifested by suppression of lipogenesis, promotion of lipolysis, reduction of hepatic steatosis, increase in hepatic glycogenesis, and decrease in gluconeogenesis. In addition, LCA restored energy homeostasis by promoting mitochondrial biogenesis, enhancing mitophagy, and reducing adenosine triphosphate production. Mechanistically, the metabolic benefits of LCA were associated with the downregulation of mammalian target of rapamycin complex 1 and activation of adenosine monophosphate-activated protein kinase, the two central regulators of metabolism. This study demonstrates that LCA can alleviate abnormal glucolipid metabolism and restore energy balance in diet-induced diabetic mice, highlighting its therapeutical potential for the treatment of diabetes.

Early detection of type 2 diabetes risk: limitations of current diagnostic criteria

Type 2 diabetes (T2D) is the leading cause of diabetes worldwide and is increasing rapidly, especially in youth. It accounts for most diabetes deaths in adults ≥20 years old in the Americas, with type 2 diabetes responsible for most of the disease burden. The incidence and burden of type 2 diabetes in adolescents and young adults have risen in recent decades globally. Countries with lower socioeconomic status had the highest incidence and burden, and females generally had higher mortality and disease burden than males at ages <30 years. Early diagnosis and management are crucial to delaying progression, but current diagnostic criteria based on glucose thresholds and glycated hemoglobin have limitations. Recent analyses show that prediabetes increases cancer risk. Better diagnostic criteria are urgently needed to identify high-risk individuals earlier. This article discusses the limitations of current criteria and explores alternative approaches and future research directions.

Associations of Maternal Fructosamine before Delivery in Gestational Diabetes Mellitus Pregnancies with Neonatal Glucometabolic Disorders

Background

The offspring of pregnant women with gestational diabetes mellitus (GDM) are vulnerable to be glucometabolic disorders. However, to date, few current studies focused on the associations of maternal accumulated glucose exposure before delivery with neonatal glucometabolic disorders and large for gestational age (LGA) infants. This study is aimed at exploring the associations of maternal fructosamine (FMN) before delivery in GDM pregnant women with neonatal glucometabolic disorders in the first 3 days of life and LGA infants.

Methods

The study subjects were the GDM pregnant women, who gave birth in our hospital from September 1, 2018 to January 31, 2021, and their newborns. The maternal FMN adjusted by serum albumin (FMNALB) before delivery was selected as exposure factors. A multivariate logistical regression model was used to calculate the odds ratios (OR) for neonatal glucometabolic disorders, hypoglycemia needing intervention (<2.6 mmol/L), and glucose intolerance (>7.0 mmol/L) in the first 3 days and LGA infants.

Results

In GDM pregnant women, the newborns in the maternal FMNALB ≥ 75th percentile (≥5.89 mmol/g) group had higher risks in neonatal glucometabolic disorders (aOR 2.50, 95% CI 1.34-4.65, P = 0.004) and hypoglycemia (aOR 2.18, 95% CI 1.16-4.10, P = 0.016). However, FMNALB ≥ 75th percentile seemed to be not predictive of the glucose intolerance (aOR 1.76, 95% CI 0.82-3.79, P = 0.149) and LGA (aOR 1.56, 95% CI 0.81-3.02, P = 0.185). Further, in the sensitivity analysis, the newborns in the maternal FMNALB ≥ 90th percentile (≥6.40 mmol/g) group also had higher risks in neonatal glucometabolic disorders (aOR 5.70, 95% CI 2.18-14.89, P < 0.001) and hypoglycemia (aOR 3.72, 95% CI 1.48-9.31, P = 0.005).

Conclusions

The maternal FMNALB before delivery in GDM pregnant women was a useful biomarker to identify the offspring with high risk of neonatal glucometabolic disorders. However, the association between maternal FMNALB and the risk of LGA infants was not so strong.

Multiomics Profiling Reveals Signatures of Dysmetabolism in Urban Populations in Central India

Background: Non-communicable diseases (NCDs) have become a major cause of morbidity and mortality in India. Perturbation of host–microbiome interactions may be a key mechanism by which lifestyle-related risk factors such as tobacco use, alcohol consumption, and physical inactivity may influence metabolic health. There is an urgent need to identify relevant dysmetabolic traits for predicting risk of metabolic disorders, such as diabetes, among susceptible Asian Indians where NCDs are a growing epidemic. Methods: Here, we report the first in-depth phenotypic study in which we prospectively enrolled 218 adults from urban and rural areas of Central India and used multiomic profiling to identify relationships between microbial taxa and circulating biomarkers of cardiometabolic risk. Assays included fecal microbiota analysis by 16S ribosomal RNA gene amplicon sequencing, quantification of serum short chain fatty acids by gas chromatography-mass spectrometry, and multiplex assaying of serum diabetic proteins, cytokines, chemokines, and multi-isotype antibodies. Sera was also analysed for N-glycans and immunoglobulin G Fc N-glycopeptides. Results: Multiple hallmarks of dysmetabolism were identified in urbanites and young overweight adults, the majority of whom did not have a known diagnosis of diabetes. Association analyses revealed several host–microbe and metabolic associations. Conclusions: Host–microbe and metabolic interactions are differentially shaped by body weight and geographic status in Central Indians. Further exploration of these links may help create a molecular-level map for estimating risk of developing metabolic disorders and designing early interventions.