Biomarkers for type 2 diabetes

Epicardial adipose tissue: a new link between type 2 diabetes and heart failure-a comprehensive review

Diabetic cardiomyopathy is a unique cardiomyopathy that is common in diabetic patients, and it is also a diabetic complication for which no effective treatment is currently available. Moreover, relevant studies have revealed that a link exists between type 2 diabetes and heart failure and that abnormal thickening of EAT is inextricably linked to the development of diabetic heart failure. Numerous clinical studies have demonstrated that EAT is implicated in the pathophysiologic process of diabetic myocardial disease. In this overview, we will introduce the physiology, pathophysiology of the disease and potential therapeutic strategies, knowledge gaps, and future directions of the role of epicardial adipose tissue in type 2 diabetes mellitus and heart failure to promote the development of novel therapeutic approaches to improve the prognosis of patients with diabetic cardiomyopathy.

A Pilates Exercise Program as a Therapeutic Strategy in Older Adults with Type 2 Diabetes: Effects on Functional Capacity and Blood Glucose

Background/Objectives: Older adults with type 2 diabetes mellitus (T2DM) often experience impaired physical function and metabolic control. This study aimed to evaluate the effectiveness of a 12-week Pilates-based intervention on blood glucose concentration and physical function in this population. Methods: A randomized controlled trial was conducted with 104 older adults (mean age: 70.6 ± 3.15 years; 70.2% women), all diagnosed with T2DM. The participants were assigned to a control group (CG, n = 52) or a Pilates training group (PG, n = 52). The intervention included 24 Pilates sessions over 12 weeks (2 sessions/week, 60 min each). Outcomes were assessed pre- and post-intervention and included capillary blood glucose, handgrip strength, functional mobility (Timed Up and Go), balance (Berg Balance Scale), and flexibility (Chair Sit-and-Reach Test and Back Scratch Test). Results: Compared to the control group, the Pilates group showed statistically significant improvements in blood glucose levels (-4.06 mg/dL (p < 0.001; d = 0.68)), handgrip strength (+1.76 kg (p < 0.001; d = 0.48)), gait speed (p < 0.001; d = 0.53), balance (Berg score) (+2.37 points (p < 0.001; d = 0.66)), and flexibility (improvements in upper limbs (BST, d = 0.78-0.98) and lower limbs (CSRT, d = 1.07 right; d = 0.63 left)). Conclusions: A 12-week Pilates program led to significant improvements in glycemic control, muscular strength, gait speed, balance, and flexibility in older adults with T2DM. These findings support Pilates as a safe, effective, and adaptable non-pharmacological intervention to promote functional and metabolic health in this population.

Association between the plasma atherogenic index and type 2 diabetes in Chinese population: prospective cohort study based on 4C study

Background

Currently, the plasma atherogenic index (AIP) is mainly used to predict atherosclerosis and cardiovascular diseases. Therefore, we aim to investigate the potential association between AIP and type 2 diabetes through a prospective cohort study.

Methods

The 4C study, a multicenter prospective cohort investigation, targets the Chinese population and initially enrolled 10,008 participants. Baseline data encompassing lifestyle, metabolic status, and various other factors were collected in 2011. A 10-year follow-up survey was subsequently conducted, ultimately including 9,092 participants. AIP, defined as the logarithmic transformation of the triglycerides to high-density lipoprotein ratio, was divided into quartiles. To explore the potential association between AIP and the risk of type 2 diabetes, Cox regression, restricted cubic spline, receiver operating characteristic curve(ROC), and subgroup analysis were employed.

Results

Over a 10-year follow-up period, 693 new cases of type 2 diabetes were identified. In a fully adjusted model, AIP demonstrated a positive association with type 2 diabetes (HR: 4.40; 95% CI: 3.21, 6.04). Compared to the Q1 group, the risk of type 2 diabetes increased progressively across the Q2, Q3, and Q4 groups, with a significant trend (p-value < 0.05). Restricted cubic spline (RCS) analysis revealed an inverse L-shaped association between AIP and the risk of type 2 diabetes, with a turning point at 0.45. The ROC analysis indicates that incorporating the AIP into the base model enhances its diagnostic performance for type 2 diabetes. Furthermore, similar patterns were observed in the subgroup analyses.

Conclusions

Among the Chinese population, elevated AIP levels are positively correlated with an increased risk of type 2 diabetes, indicating that AIP could potentially serve as a biomarker for assessing the risk of developing type 2 diabetes.

Advances in Metabolomics: A Comprehensive Review of Type 2 Diabetes and Cardiovascular Disease Interactions

Type 2 diabetes (T2D) and cardiovascular diseases (CVDs) are major public health challenges worldwide. Metabolomics, the exhaustive assessment of metabolites in biological systems, offers important insights regarding the metabolic disturbances related to these disorders. Recent advances toward the integration of metabolomics into clinical practice to facilitate the discovery of novel biomarkers that can improve the diagnosis, prognosis, and treatment of T2D and CVDs are discussed in this review. Metabolomics offers the potential to characterize the key metabolic alterations associated with disease pathophysiology and treatment. T2D is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms; therefore, the disease-causing pathways of T2D are not completely understood. Recent studies have identified several robust clusters of T2D variants representing biologically meaningful, distinct pathways, such as the beta cell and proinsulin cluster related to pancreatic insulin secretion, obesity, lipodystrophy, the liver/lipid cluster, glycemia, and blood pressure, and metabolic syndrome clusters representing different pathways causing insulin resistance. Regarding CVDs, recent studies have allowed the metabolomic profile to delineate pathways that contribute to atherosclerosis and heart failure, as well as to the development of targeted therapy. This review also covers the role of metabolomics in integrated metabolic genomics and other omics platforms to better understand disease mechanisms, along with the transition toward precision medicine. This review further investigates the use of metabolomics in multi-metabolite modeling to enhance risk prediction models for predicting the first occurrence of major adverse cardiovascular events among individuals with T2D, highlighting the value of such approaches in optimizing the preventive and therapeutic models used in clinical practice.

Effects of exogenous ghrelin treatment on oxidative stress, inflammation and histological parameters in a fat-fed streptozotocin rat model

In this study, the anti-inflammatory, antioxidative, and protective effects of ghrelin were investigated in a fat-fed streptozotocin (STZ) rat model and compared with metformin, diabetes and the healthy control groups. Histopathological evaluations were performed on H&E-stained pancreas and brain sections. Biochemical parameters were investigated by enzyme-linked immunosorbent assay. Blood glucose levels were significantly decreased with ghrelin or metformin treatments than the diabetes group. STZ administration increased brain, renal and pancreatic IL-1β, TNF-α and MDA while decreasing GPX, CAT, SOD, and NGF levels. Ghrelin increased renal GPX, CAT, NGF pancreatic GPX, SOD, CAT, NGF and brain SOD, NGF while it decreased renal, pancreatic and brain IL-1β, TNF-α and MDA levels. Ghrelin reduced neuronal loss and degeneration in the cerebral cortex and hippocampus and greatly ameliorated diabetes-related damage in pancreas. In conclusion, the data suggested that ghrelin is an effective candidate as a protectant for reducing the adverse effects of diabetes.

High-Intensity Interval Training Decreases Circulating HMGB1 in Individuals with Insulin Resistance: Plasma Lipidomics Correlate with Associated Cardiometabolic Benefits

BACKGROUND

Bodyweight high-intensity interval training (BW-HIIT) is an effective, time-efficient exercise method that reduces cardiovascular risk factors and improves muscle endurance without requiring external equipment. High mobility group box 1 (HMGB1) is a proinflammatory protein involved in insulin resistance. Previous studies revealed that HMGB1 knockout mice show improved insulin sensitivity and hyperglycemia. This study investigates whether BW-HIIT exercise can reduce proinflammatory markers, such as HMGB1, in individuals with insulin resistance.

METHODS

In total, 14 adults (2 male/12 female) aged 18 to 55 were subject to six weeks of BW-HIIT. Additionally, 10-week-old mice were subject to exercise conditioning (5 mice per group (all male)) for 4 weeks of treadmill exercise or sedentary. Human and mouse pre- and post-exercise serum/plasma samples were analyzed for lipidomics, hormonal, and cytokine multiplex assays. Cardiometabolic parameters were also performed on human subjects.

RESULTS

Post-exercise decreased systolic blood pressure (SBP), cholesterol, triglycerides, high-density lipoprotein (HDL), and cholesterol/HDL ratio in human patients with insulin resistance. Meanwhile, hormones such as amylin, glucagon, and insulin all increased post-BW-HIIT or treadmill exercise in both human and mouse models. Moreover, circulating HMBG1 levels were reduced in insulin-resistant individuals and mice after exercise. Furthermore, treadmill exercise by the animal model increased anti-inflammatory cytokines, including interleukin (IL)-10, IL-12p40, and IL-12p70, and reduced proinflammatory cytokines: eotaxin, IL-2, and macrophage inflammatory protein (MIP)-2 or CXCL2.

CONCLUSIONS

Six weeks of BW-HIIT exercise can improve cardiometabolic health, anti-inflammatory markers, hormones, and insulin sensitivity in human and mouse models undergoing exercise. Changes in circulating HMBG1 levels following BW-HIIT exercise make HMGB1 a suitable marker for cardiometabolic disease, potentiating its role beyond an alarmin. Further studies are needed to confirm these effects and to elucidate the underlying physiological mechanisms.

Oxidative stress and inflammation on metabolic abnormalities and renal involvement in prediabetic subjects across Europe

BACKGROUND

Studying the mechanisms involved in the transition from prediabetes to diabetes and its associated complications, such as kidney disease, is a growing challenge. This study focuses on identifying valuable biomarkers for the early detection of kidney damage, evaluating molecules associated with oxidative stress and inflammation in prediabetic individuals across Europe.

METHODS

In plasma samples from individuals with prediabetes included in the ePREDICE study, we determined molecules related to oxidative stress (advance oxidative protein products-AOPP) and inflammatory biomarkers (C-reactive protein - CRP; Interleukin 6 - IL-6), and correlated them with anthropometric and biochemical data, assessing their potential for the early diagnosis of renal involvement.

RESULTS

Among the 967 people with prediabetes, 94 presented some sign of renal impairment such as albuminuria, hyperfiltration or hypofiltration. Significant variations were identified between oxidative stress and inflammatory biomarkers (upper and lower quartiles of AOPP, CRP and IL6), and parameters associated with blood pressure, glucose metabolism, lipid profile, and fatty liver index. In particular, both types of biomarkers were associated with components of the metabolic syndrome. There were significant associations between AOPP and CRP, and the presence of albuminuria, but not with renal function. Overall, CRP was a better biomarker than IL-6 for most of the parameters studied.

CONCLUSION

These results highlight the important associations of oxidative stress and inflammation with metabolic abnormalities linked to the prediabetic state and its complications such as fatty liver and renal involvement. Although these results need to be confirmed, our study suggests that AOPP and CRP could be simple biomarkers of interest in predicting the risk of loss of renal function in people with prediabetes.

Comparative efficacy and safety of dipeptidyl peptidase-4 inhibitors in adults with type 2 diabetes mellitus: A network meta-analysis

AIMS

We have compiled updated evidence on the benefits and drawbacks of dipeptidyl peptidase-4 (DPP-4) inhibitors in treating type 2 diabetes mellitus.

MATERIALS AND METHODS

We systematically searched PubMed, Embase, Cochrane Library, and ClinicalTrials.gov (as of 20 May 2024). Effect estimates were calculated using network meta-analysis under the frequentist framework. The P-score established the ranking of competing treatments.

RESULTS

The authors incorporated 58 studies containing data from a substantial sample size of 21 332 patients. Based on evidence of high and moderate certainty, respectively, teneligliptin and vildagliptin were found to be superior to all other DPP-4 inhibitors in lowering haemoglobin A1c (mean difference [MD] -0.81%, 95% CI -1.03, -0.60) and fasting blood glucose (MD -1.18 mmol/L, 95% CI -1.56, -0.81) compared to placebo. The absence of conclusive differences between interventions for serious adverse events was supported by evidence, which was interpreted with low to very low certainty.

CONCLUSIONS

In adults with type 2 diabetes, teneligliptin was most effective for HbA1c control, and vildagliptin for fasting blood glucose. No significant differences in serious adverse events were noted among DPP-4 inhibitors compared to placebo. Given the therapeutic significance of these findings, more studies are needed to explore this issue more thoroughly.

Association between atherogenic index of plasma and type 2 diabetic complications: a cross-sectional study

Background

The Atherogenic Index of Plasma (AIP) was originally developed primarily as a marker for assessing atherosclerosis. Consequently, this study investigates the potential association between AIP and type 2 diabetic complications through a cross-sectional design.

Methods

The National Metabolic Management Center(MMC) serves as a comprehensive platform dedicated to the establishment of standardized protocols for the diagnosis, treatment, and long-term follow-up of metabolic diseases. Following the relevant inclusion and exclusion criteria, a total of 3,094 patients were enrolled for subsequent analysis. In this study, logistic regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between the AIP and four major complications of type 2 diabetes, namely, type 2 diabetes with carotid atherosclerosis (DA), diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic peripheral neuropathy (DPN).

Results

The logistic regression results demonstrate that in the fully adjusted model, each SD increase in AIP correlates with an elevated risk of type 2 diabetic kidney disease (DKD), with the risk of kidney damage intensifying alongside higher AIP groupings. The RCS analysis and subgroup analyses similarly revealed a dose-response relationship between AIP levels and the risk of DKD. Furthermore, the AIP was not found to be statistically significantly associated with DA, DR,and DPN.

Conclusions

The AIP may serve as a valuable predictive indicator for evaluating kidney damage in patients with type 2 diabetes, and regular screening of AIP in this population could provide significant benefits in the prevention of DKD.

Association of accelerated phenotypic aging, genetic risk, and lifestyle with progression of type 2 diabetes: a prospective study using multi-state model

BACKGROUND

Aging is a major risk factor for type 2 diabetes (T2D), but individuals of the same chronological age may vary in their biological aging rate. The associations of Phenotypic Age Acceleration (PhenoAgeAccel), a new accelerated biological aging indicator based on clinical chemistry biomarkers, with the risk of dynamic progression remain unclear. We aimed to assess these associations and examine whether these associations varied by genetic risk and lifestyle.

METHODS

We conducted a prospective cohort study that included 376,083 adults free of T2D and diabetes-related events at baseline in UK Biobank. PhenoAgeAccel > 0 and ≤ 0 were defined as biologically older and younger than chronological age. The outcomes of interest were incident T2D, diabetic complications, and mortality. Hazard ratios (HRs) with 95% confidence intervals (CIs) and population attributable fractions (PAFs) for these associations were calculated using multi-state model.

RESULTS

During a median follow-up of 13.7 years, 17,615 participants developed T2D, of whom, 4,524 subsequently developed complications, and 28,373 died. Being biologically older was associated with increased risks of transitions from baseline to T2D (HR 1.77, 95% CI 1.71-1.82; PAF 24.8 [95% CI 23.5-26.2]), from T2D to diabetic complications (1.10, 1.04-1.17; 4.4 [1.4-7.4]), from baseline to all-cause death (1.53, 1.49-1.57; 17.6 [16.6-18.6]), from T2D to all-cause death (1.14, 1.03-1.26; 7.4 [1.8-13.0]), and from diabetic complications to all-cause death (1.32, 1.15-1.51; 15.4 [7.5-23.2]) than being biologically younger. Additionally, participants with older biological age and high genetic risk had a higher risk of incident T2D (4.76,4.43-5.12;18.2 [17.5-19.0]) than those with younger biological age and low genetic risk. Compared with participants with younger biological age and healthy lifestyle, those with older biological age and unhealthy lifestyle had higher risks of transitions in the T2D trajectory, with HRs and PAFs ranging from 1.34 (1.16-1.55; 3.7 [1.8-5.6]) to 5.39 (5.01-5.79; 13.0 [12.4-13.6]).

CONCLUSIONS

PhenoAgeAccel was consistently associated with an increased risk of all transitions in T2D progression. It has the potential to be combined with genetic risk to identify early T2D incidence risk and may guide interventions throughout T2D progression while tracking their effectiveness.

Carboxymethyl chitosan and sodium alginate oxide pH-sensitive dual-release hydrogel for diabetes wound healing: The combination of astilbin liposomes and diclofenac sodium

Difficulty in diabetic wound healing presents a significant challenge in clinical practice. This study developed a hydrogel utilizing oxidized sodium alginate (OSA) and carboxymethyl chitosan (CMCS) as the matrix. Astilbin (ASB), known for its antioxidant properties, was incorporated into Astilbin liposome (AL) using a thin film dispersion method. Diclofenac sodium (DS) and AL, both possessing anti-inflammatory properties, were then encapsulated in the hydrogel to create a pH-responsive dual-release system for topical application to expedite diabetic wound healing. Results from the research demonstrate that the composite hydrogel exhibits favorable biodegradability, stable rheology, and swelling capacity, facilitating the controlled release of AL and DS. In vivo and in vitro data demonstrated that the hydrogel was biocompatible and anti-inflammatory, antibacterial and homeostatic, and significantly promoted the process of inflammation suppression, angiogenesis and fibrotic repair of wounds. In conclusion, this novel hydrogel provides a simple and effective method for the repair of chronic diabetic wounds.

Evaluating the Antidiabetic Activity of Aloe niebuhriana Latex in Alloxan-Induced Diabetic Rats and the Development of a Novel Effervescent Granule-Based Delivery System

Background: Ethnomedicine exhibits potential in developing affordable effective antidiabetic agents. Aim: This work aimed to explore the antidiabetic properties of Aloe niebuhriana latex extract both in vivo, utilizing alloxan-induced diabetic rats, and in vitro, through α-amylase enzyme testing. Additionally, it sought to formulate optimal effervescent granules derived from the extract. Methods: The α-amylase inhibition assay was performed using the α-amylase kit using biochemical analyzers. Experimental diabetes was induced in animals with alloxan. On Day 14 postdiabetes induction, body weight, fasting blood glucose, and lipid profile parameters were determined. Also, six effervescent granule preparations of the extract were formulated using wet granulation. Based on its physical and organoleptic properties, a formulation was selected and optimized. Results: The extract displayed modest α-amylase inhibition, with an IC50 value of 439.2 μg/mL. Both doses of A. niebuhriana extract (200 and 400 mg/kg) significantly reduced blood glucose level compared to their respective Day 1 levels (p < 0.001). Moreover, the extract at a dose of 400 mg/kg significantly normalized lipid profile compared to the diabetic control groups (p < 0.05 - 0.001). Six formulations containing the extract were prepared (F1-F6), and F6 containing 200 mg of the extract was selected for optimization due to its favorable odor, taste, foaming, and effervescent properties, high solubility, and absence of turbidity and adhesion. The formulated F6 granules successfully met the quality parameters assessed including flow time, pH effervescent time, angle of repose, bulk density, tapped density, Carr's index, and Hausner's ratio. Conclusion: This study highlights the antidiabetic potential of A. niebuhriana latex extract, potentially attributed to its hypolipidemic, hypoglycemic, and α-amylase inhibitory effects. The successful formulation and evaluation of the extract as effervescent granules suggest its potential as an antidiabetic drug.

Genetic association of type 2 diabetes mellitus and glycaemic factors with primary tumours of the central nervous system

Type 2 diabetes mellitus (T2DM) is a pivotal chronic disease with an increasing prevalence. Recent studies have found associations between T2DM and the development of central nervous system (CNS) tumours, a special class of solid tumours with an unclear pathogenesis. In this study, we aimed to explore the relationship between T2DM and certain glycaemic factors with common CNS tumours by using genetic data to conduct Mendelian randomization (MR) and co-localisation analysis. We found a causal relationship between T2DM and glioblastoma, fasting glucose and spinal cord tumours, glycated haemoglobin and spinal cord tumours, and insulin-like growth factor-1 and spinal cord tumours, pituitary tumours, and craniopharyngiomas. These results clarify the relationship between T2DM, glucose-related factors, and common CNS tumours, and they provide valuable insight into further clinical and basic research on CNS tumours, as well as new ideas for their diagnosis and treatment.

Lp(a) and high-sensitivity C-reactive protein are predictive biomarkers for coronary heart disease in Chinese patients with type 2 diabetes mellitus

Objective

Type 2 diabetes (T2DM) is a significant risk factor for coronary heart disease (CHD). This study aimed to assess the variations in biomarkers associated with CHD in T2DM patients across different age groups in the Han Chinese population.

Methods

A strict selection process was employed, involving three groups: a control group (n = 300) with no medical history, a new-onset T2DM group (n = 300), and a new-onset T2DM + CHD group (n = 300). Participants in each group were further categorized based on age: Group 1 (<60 years), Group 2 (60-75 years), and Group 3 (>75 years). Fasting glucose, hemoglobin A1c (HbA1c), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), ApoB/ApoA1 ratio, lipoprotein(a) [Lp(a)], high-sensitivity C-reactive protein (hsCRP), and homocysteine (HCY) levels were analyzed in all groups.

Results

Both T2DM and T2DM + CHD groups exhibited elevated levels of TG, TC, LDL-C, ApoB, ApoB/ApoA1, Lp(a), hsCRP, and HCY, alongside decreased levels of HDL-C and ApoA1 in comparison to the control group. Notably, when comparing the T2DM to the T2DM + CHD groups, significant increases were noted in ApoB, Lp(a), and hsCRP levels in the T2DM + CHD group, whereas other biomarkers did not show significant differences. Across all age groups, the patterns remained consistent, with the T2DM and T2DM + CHD groups showing elevated levels of TG, TC, LDL-C, ApoB, ApoB/ApoA1, Lp(a), hsCRP, and HCY, and decreased levels of HDL-C and ApoA1 compared to their respective age-matched control groups. Furthermore, within each age category, significant increases in ApoB, Lp(a), and hsCRP were specifically observed with advancing age in the T2DM + CHD group, with Lp(a) and hsCRP levels showing particularly notable elevations, underscoring their potential as significant indicators of CHD risk in the T2DM population.

Conclusion

Lp(a) and hsCRP may serve as valuable risk biomarkers for the development of CHD in T2DM patients. Understanding the variations in these biomarkers across different age groups can assist in risk assessment and the development of personalized management strategies for CHD in T2DM patients.

Myeloid-Derived Suppressor Cells (MDSCs) and Obesity-Induced Inflammation in Type 2 Diabetes

Type 2 diabetes mellitus is a complex metabolic disorder characterized by insulin resistance and, subsequently, decreased insulin secretion. This condition is closely linked to obesity, a major risk factor that boosts the development of chronic systemic inflammation, which, in turn, is recognized for its crucial role in the onset of insulin resistance. Under conditions of obesity, adipose tissue, particularly visceral fat, becomes an active endocrine organ that releases a wide range of pro-inflammatory mediators, including cytokines, chemokines, and adipokines. These mediators, along with cluster of differentiation (CD) markers, contribute to the maintenance of systemic low-grade inflammation, promote cellular signaling and facilitate the infiltration of inflammatory cells into tissues. Emerging studies have indicated the accumulation of a new cell population in the adipose tissue in these conditions, known as myeloid-derived suppressor cells (MDSCs). These cells possess the ability to suppress the immune system, impacting obesity-related chronic inflammation. Given the limited literature addressing the role of MDSCs in the context of type 2 diabetes, this article aims to explore the complex interaction between inflammation, obesity, and MDSC activity. Identifying and understanding the role of these immature cells is essential not only for improving the management of type 2 diabetes but also for the potential development of targeted therapeutic strategies aimed at both glycemic control and the reduction in associated inflammation.

Type 2 diabetes mellitus, obesity, cesarean section delivery, and lack of exclusive breastfeeding exposure in patients from the Guadalajara Metropolitan Area, Mexico

Introduction

Introduction: the combination of cesarean section delivery and limited exposure to full breastfeeding (FBF) in the first six months of life may increase the risk of obesity and diabetes mellitus. This study aimed to establish an association between type 2 diabetes mellitus (T2DM) in adulthood, cesarean section delivery and incomplete full breastfeeding (FBF) in individuals from the metropolitan area of Guadalajara, Mexico. Methodology: this analytical cross-sectional study included patients over 18 years of age with T2DM and normal weight, overweight or obesity, regardless of sex. Informed consent was obtained. Variables encompassed T2DM, type of delivery method, first-year diet, family history, demographic, socioeconomic, and educational characteristics, and anthropometric measurements. For statistical analysis, Student's t test, chi-square tests and odds ratios were employed. Results: the study evaluated 218 patients with an average age of 57.8 years (± 12.7) and an average age at T2DM diagnosis of 46.2 years (± 12.5). FBF (65.6 %) and partial breastfeeding (PBF) (23.8 %) prevailed in the first six months. The average age at T2DM diagnosis was 46.7 years (± 12.1) for vaginally born patients and 30.7 years (± 15.5) for cesarean-born patients (p = 0.001). Cesarean delivery increased obesity risk by nine times in patients with T2DM [OR = 8.9 (CI, 1.05, 75.2), p = 0.02]. Conclusion: prioritizing the limitation of nonmedically justified cesarean section deliveries is crucial to mitigate the risk of obesity and T2DM in adulthood. .

High expression of CNOT6L contributes to the negative development of type 2 diabetes

OBJECTIVE

Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by reduced responsiveness of body cells to insulin, leading to elevated blood sugar levels. CNOT6L is involved in glucose metabolism, insulin secretion regulation, pancreatic beta-cell proliferation, and apoptosis. These functions may be closely related to the pathogenesis of T2D. However, the exact molecular mechanisms linking CNOT6L to T2D remain unclear. Therefore, this study aims to elucidate the role of CNOT6L in T2D.

METHODS

The T2D datasets GSE163980 and GSE26168 profiles were downloaded from the Gene Expression Omnibusdatabase generated by GPL20115 and GPL6883.The R package limma was used to screen differentially expressed genes (DEGs). A weighted gene co-expression network analysis was performed. Construction and analysis of the protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis, and comparative toxicogenomics database (CTD) analysis were performed. Target Scan was used to screen miRNAs that regulate central DEGs. The results were verified by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), western blotting (WB), and blood glucose measurements in mice.

RESULTS

A total of 1951 DEGs were identified. GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly enriched in the insulin signaling pathway, ECM-receptor interaction, and PPAR signaling pathway. Metascape analysis indicated enrichment primarily in the cAMP signaling pathway and enzyme-linked receptor protein signaling pathway. WGCNA analysis yielded 50 intersecting genes. PPI network construction and algorithm identification identified two core genes (CNOT6L and GRIN2B), among which CNOT6L gene was associated with multiple miRNAs. CTD analysis revealed associations of core genes with type 2 diabetes, diabetic complications, dyslipidemia, hyperglycemia, and inflammation. WB and RT-qPCR results showed that in different pathways, CNOT6L protein and mRNA levels were upregulated in type 2 diabetes.

CONCLUSION

CNOT6L is highly expressed in type 2 diabetes mellitus, and can cause diabetes complications, inflammation and other physiological processes by regulating miRNA, PPAR and other related signaling pathways, with poor prognosis. CNOT6L can be used as a potential therapeutic target for type 2 diabetes.

Delayed treatment of diabetic foot ulcer in patients with type 2 diabetes and its prediction model

BACKGROUND

Diabetic foot (DF) is a serious complication of type 2 diabetes. This study aimed to investigate the factors associated with DF occurrence and the role of delayed medical care in a cohort of patients with type 2 diabetes.

AIM

To reveal the impact of delayed medical treatment on the development of DF in patients with type 2 diabetes and to establish a predictive model for DF.

METHODS

In this retrospective cohort study, 292 patients with type 2 diabetes who underwent examination at our hospital from January 2023 to December 2023 were selected and divided into the DF group (n = 82, DF) and nondiabetic foot group (n = 210, NDF). Differential and correlation analyses of demographic indicators, laboratory parameters, and delayed medical treatment were conducted for the two groups. Logistic regression was applied to determine influencing factors. Receiver operating characteristic (ROC) analysis was performed, and indicators with good predictive value were selected to establish a combined predictive model.

RESULTS

The DF group had significantly higher body mass index (BMI) (P < 0.001), disease duration (P = 0.012), plasma glucose levels (P < 0.001), and HbA1c (P < 0.001) than the NDF group. The NDF group had significantly higher Acute Thrombosis and Myocardial Infarction Health Service System (ATMHSS) scores (P < 0.001) and a significantly lower delayed medical treatment rate (72.38% vs 13.41%, P < 0.001). BMI, duration of diabetes, plasma glucose levels, HbA1c, diabetic peripheral neuropathy, and nephropathy were all positively correlated with DF occurrence. ATMHSS scores were negatively correlated with delayed time to seek medical treatment. The logistic regression model revealed that BMI, duration of diabetes, plasma glucose levels, HbA1c, presence of diabetic peripheral neuropathy and nephropathy, ATMHSS scores, and delayed time to seek medical treatment were influencing factors for DF. ROC analysis indicated that plasma glucose levels, HbA1c, and delayed medical treatment had good predictive value with an area under the curve of 0.933 for the combined predictive model.

CONCLUSION

Delayed medical treatment significantly affects the probability of DF occurrence in patients with diabetes. Plasma glucose levels, HbA1c levels, and the combined predictive model of delayed medical treatment demonstrate good predictive value.

Type 2 diabetes mellitus in adults: pathogenesis, prevention and therapy

Type 2 diabetes (T2D) is a disease characterized by heterogeneously progressive loss of islet β cell insulin secretion usually occurring after the presence of insulin resistance (IR) and it is one component of metabolic syndrome (MS), and we named it metabolic dysfunction syndrome (MDS). The pathogenesis of T2D is not fully understood, with IR and β cell dysfunction playing central roles in its pathophysiology. Dyslipidemia, hyperglycemia, along with other metabolic disorders, results in IR and/or islet β cell dysfunction via some shared pathways, such as inflammation, endoplasmic reticulum stress (ERS), oxidative stress, and ectopic lipid deposition. There is currently no cure for T2D, but it can be prevented or in remission by lifestyle intervention and/or some medication. If prevention fails, holistic and personalized management should be taken as soon as possible through timely detection and diagnosis, considering target organ protection, comorbidities, treatment goals, and other factors in reality. T2D is often accompanied by other components of MDS, such as preobesity/obesity, metabolic dysfunction associated steatotic liver disease, dyslipidemia, which usually occurs before it, and they are considered as the upstream diseases of T2D. It is more appropriate to call "diabetic complications" as "MDS-related target organ damage (TOD)", since their development involves not only hyperglycemia but also other metabolic disorders of MDS, promoting an up-to-date management philosophy. In this review, we aim to summarize the underlying mechanism, screening, diagnosis, prevention, and treatment of T2D, especially regarding the personalized selection of hypoglycemic agents and holistic management based on the concept of "MDS-related TOD".

Healthy dietary pattern is associated with lower glycemia independently of the genetic risk of type 2 diabetes: a cross-sectional study in Finnish men

PURPOSE

Hyperglycemia is affected by lifestyle and genetic factors. We investigated if dietary patterns associate with glycemia in individuals with high or low genetic risk for type 2 diabetes (T2D).

METHODS

Men (n = 1577, 51-81 years) without T2D from the Metabolic Syndrome in Men (METSIM) cohort filled a food-frequency questionnaire and participated in a 2-hour oral glucose tolerance test. Polygenetic risk score (PRS) including 76 genetic variants was used to stratify participants into low or high T2D risk groups. We established two data-driven dietary patterns, termed healthy and unhealthy, and investigated their association with plasma glucose concentrations and hyperglycemia risk.

RESULTS

Healthy dietary pattern was associated with lower fasting and 2-hour plasma glucose, glucose area under the curve, and better insulin sensitivity (Matsuda insulin sensitivity index) and insulin secretion (disposition index) in unadjusted and adjusted models, whereas the unhealthy pattern was not. No interaction was observed between the patterns and PRS on glycemic measures. Healthy dietary pattern was negatively associated with the risk for hyperglycemia in an adjusted model (OR 0.69, 95% CI 0.51-0.95, in the highest tertile), whereas unhealthy pattern was not (OR 1.08, 95% CI 0.79-1.47, in the highest tertile). No interaction was found between diet and PRS on the risk for hyperglycemia (p = 0.69 for healthy diet, p = 0.54 for unhealthy diet).

CONCLUSION

Our findings suggest that healthy diet is associated with lower glucose concentrations and lower risk for hyperglycemia in men with no interaction with the genetic risk.

The causal association between type 2 diabetes and spinal stenosis: A Mendelian randomization analysis

Spinal stenosis is a prevalent degenerative spinal disease and one of the main causes of pain and dysfunction in older adults. Substantial evidence indicates a potentially relevant association between type 2 diabetes mellitus (T2DM) and spinal stenosis. However, the causality between these 2 disorders remains unclear. Therefore, we intended to elucidate this relationship using Mendelian Randomization (MR) analysis in this study. Based on genome-wide association study (GWAS) data on T2DM and spinal stenosis, we performed a bidirectional 2-sample MR analysis to evaluate the causality of T2DM and spinal stenosis. We assessed heterogeneity using Cochran's Q statistic and horizontal pleiotropy using the MR-Egger-intercept. "Leave-one-out" analysis was performed to determine the reliability of causal relationships. In addition, we conducted multivariate MR to clarify the direct influence of T2DM on spinal stenosis after accounting for the effect of body mass index (BMI) on spinal stenosis. Our results indicated that Individuals with T2DM had a heightened risk of spinal stenosis (odds ratio [OR]: 1.050; 95% CI: 1.004-1.098, P = .031). Moreover, no reverse causality existed between T2DM and spinal stenosis. The results of the sensitivity analysis suggest that causality is steady and robust. Multivariate MR results demonstrated that the causality of T2DM on spinal stenosis was not related to BMI (OR, 1.047; 95% CI: 1.003-1.093; P = .032). MR analyses demonstrated a possible positive causal relationship between T2DM and spinal stenosis and that this causality was unrelated to BMI.

A systematic review and meta-analysis of ischemia-modified albumin in diabetes mellitus

Aim

There is an ongoing search for novel biomarkers of diabetes. We conducted a systematic review and meta-analysis of the serum concentrations of ischemia-modified albumin (IMA), a candidate biomarker of oxidative stress, acidosis, and ischemia, in patients with pre-diabetes, different types of diabetes mellitus (type 1, T1DM, type 2, T2DM, and gestational, GDM), and healthy controls.

Methods

We searched for case-control studies published in PubMed, Web of Science, and Scopus from inception to December 31, 2023. The risk of bias and the certainty of evidence were assessed using the Joanna Briggs Institute Critical Appraisal Checklist and GRADE, respectively.

Results

In 29 studies, T2DM patients had significantly higher IMA concentrations when compared to controls (standard mean difference, SMD = 1.83, 95 % CI 1.46 to 2.21, p˂0.001; I2 = 95.7 %, p < 0.001; low certainty of evidence). Significant associations were observed between the SMD and glycated hemoglobin (p = 0.007), creatinine (p = 0.003), triglycerides (p = 0.029), and the presence of diabetes complications (p = 0.003). Similar trends, albeit in a smaller number of studies, were observed in T1DM (two studies; SMD = 1.59, 95 % CI -0.09 to 3.26, p˂0.063; I2 = 95.8 %, p < 0.001), GDM (three studies; SMD = 3.41, 95 % CI 1.14 to 5.67, p = 0.003; I2 = 97.0 %, p < 0.001) and pre-diabetes (three studies; SMD = 15.25, 95 % CI 9.86 to 20.65, p˂0.001; I2 = 99.3 %, p < 0.001).

Conclusion

Our study suggests that IMA is a promising biomarker for determining the presence of oxidative stress, acidosis, and ischemia in pre-diabetes and T1DM, T2DM, and GDM. However, the utility of measuring circulating IMA warrants confirmation in prospective studies investigating clinical endpoints in pre-diabetes and in different types of diabetes (PROSPERO registration number: CRD42024504690).

MTHFR gene polymorphisms in diabetes mellitus

The methylenetetrahydrofolate reductase (MTHFR), methionine synthase (MTR), and methionine synthase reductase (MTRR) are three regulatory enzymes in the folic acid (FA) cycle play a critical role in the balance of methionine and homocysteine. MTHFR and MTRR gene polymorphisms affect the biochemical activities of enzymes, impairing the remethylation of homocysteine to methionine. In 1972, severe MTHFR deficiency resulting in homocystinuria was first reported, suggesting MTHFR involvement in the disease. MTHFR C677T polymorphism can independently increase the risk of high homocysteine (HHcy) in plasma. Elevation of homocysteine levels could increase the risk of microvascular damage, thrombosis, heart disease, etc. Vascular complications were regarded as a leading major cause of diabetes mortality, and disability increases individual health and economic burden. Diabetes mellitus (DM) is a chronic inflammatory disease, and conventional medications do not provide a complete cure for diabetes. It was essential to identify other risk factors for the intervention and prevention of diabetes. MTHFR gene polymorphism is an emerging risk factor in diabetes. Recent studies have shown that polymorphisms of the MTHFR gene play a significant role in the pathophysiology of diabetes, including inflammation and insulin resistance. This review summarizes the association between MTHER gene polymorphism and diabetes.

Changes in Isoleucine, Sarcosine, and Dimethylglycine During OGTT as Risk Factors for Diabetes

CONTEXT

Current metabolomics studies in diabetes have focused on the fasting state, while only a few have addressed the satiated state.

OBJECTIVE

We combined the oral glucose tolerance test (OGTT) and metabolomics to examine metabolite-level changes in populations with different glucose tolerance statuses and to evaluate the potential risk of these changes for diabetes.

METHODS

We grouped participants into those with normal glucose tolerance (NGT), impaired glucose regulation (IGR), and newly diagnosed type 2 diabetes (NDM). During the OGTT, serum was collected at 0, 30, 60, 120, and 180 minutes. We evaluated the changes in metabolite levels during the OGTT and compared metabolic profiles among the 3 groups. The relationship between metabolite levels during the OGTT and risk of diabetes and prediabetes was analyzed using a generalized estimating equation (GEE). The regression results were adjusted for sex, body mass index, fasting insulin levels, heart rate, smoking status, and blood pressure.

RESULTS

Glucose intake altered metabolic profile and induced an increase in glycolytic intermediates and a decrease in amino acids, glycerol, ketone bodies, and triglycerides. Isoleucine levels differed between the NGT and NDM groups and between the NGT and IGR groups. Changes in sarcosine levels during the OGTT in the diabetes groups were opposite to those in glycine levels. GEE analysis revealed that during OGTT, isoleucine, sarcosine, and acetic acid levels were associated with NDM risks, and isoleucine and acetate levels with IGR risks.

CONCLUSION

Metabolic profiles differ after glucose induction in individuals with different glucose tolerance statuses. Changes in metabolite levels during OGTT are potential risk factors for diabetes development.

Based on systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for diabetes

Purpose

Diabetes and its complications cause a heavy burden of disease worldwide. In recent years, Mendelian randomization (MR) has been widely used to discover the pathogenesis and epidemiology of diseases, as well as to discover new therapeutic targets. Therefore, based on systematic "druggable" genomics, we aim to identify new therapeutic targets for diabetes and analyze its pathophysiological mechanisms to promote its new therapeutic strategies.

Material and method

We used double sample MR to integrate the identified druggable genomics to evaluate the causal effect of quantitative trait loci (eQTLs) expressed by druggable genes in blood on type 1 and 2 diabetes (T1DM and T2DM). Repeat the study using different data sources on diabetes and its complications to verify the identified genes. Not only that, we also use Bayesian co-localization analysis to evaluate the posterior probabilities of different causal variations, shared causal variations, and co-localization probabilities to examine the possibility of genetic confounding. Finally, using diabetes markers with available genome-wide association studies data, we evaluated the causal relationship between established diabetes markers to explore possible mechanisms.

Result

Overall, a total of 4,477 unique druggable genes have been gathered. After filtering using methods such as Bonferroni significance (P<1.90e-05), the MR Steiger directionality test, Bayesian co-localization analysis, and validation with different datasets, Finally, 7 potential druggable genes that may affect the results of T1DM and 7 potential druggable genes that may affect the results of T2DM were identified. Reverse MR suggests that C4B may play a bidirectional role in the pathogenesis of T1DM, and none of the other 13 target genes have a reverse causal relationship. And the 7 target genes in T2DM may each affect the biomarkers of T2DM to mediate the pathogenesis of T2DM.

Conclusion

This study provides genetic evidence supporting the potential therapeutic benefits of targeting seven druggable genes, namely MAP3K13, KCNJ11, REG4, KIF11, CCNE2, PEAK1, and NRBP1, for T2DM treatment. Similarly, targeting seven druggable genes, namely ERBB3, C4B, CD69, PTPN22, IL27, ATP2A1, and LT-β, has The potential therapeutic benefits of T1DM treatment. This will provide new ideas for the treatment of diabetes and also help to determine the priority of drug development for diabetes.

Network Pharmacology Analysis, Molecular Docking Integrated Experimental Verification Reveal the Mechanism of Gynostemma pentaphyllum in the Treatment of Type II Diabetes by Regulating the IRS1/PI3K/Akt Signaling Pathway

Gynostemma pentaphyllum (Thunb.) Makino (GP), a plant with homology of medicine and food, as a traditional Chinese medicine, possesses promising biological activities in the prevention and treatment of type 2 diabetes mellitus (T2DM). However, the material basis and the mechanism of action of GP in the treatment of T2DM have not been fully elucidated. This study aimed to clarify the active components, potential targets and signaling pathways of GP in treating T2DM. The chemical ingredients of GP were collected by combining UPLC-HRMS analysis and literature research. Network pharmacology revealed that GP had 32 components and 326 potential targets in treating T2DM. The results showed that GP affected T2DM by mediating the insulin resistance signaling pathway, PI3K/Akt signaling pathway and FoxO1 signaling pathway, which had a close relationship with T2DM. Molecular docking results showed that STAT3, PIK3CA, AKT1, EGFR, VEGFA and INSR had high affinity with the active compounds of GP. In vitro, GP extracts obviously increased the glucose uptake and glucose consumption in IR-HepG2 cells. GP extracts increased the levels of PI3K, p-AKT, p-GSK3β and p-FoxO1 and decreased the expression of p-IRS1, p-GS, PEPCK and G6Pase, which indicated that GP could promote glycogen synthesis and inhibit gluconeogenesis by regulating the IRS1/PI3K/Akt signaling pathway. The results demonstrated that GP could improve insulin resistance by promoting glucose uptake and glycogen synthesis and inhibiting gluconeogenesis through regulating the IRS1/PI3K/Akt signaling pathway, which might be a potential alternative therapy for T2DM.

Correlation of ChREBP Gene Methylation with Pathological Characteristics of Type 2 Diabetes Mellitus

The objective of this study is to investigate the expression of the carbohydrate response element binding protein (ChREBP) gene in type 2 diabetes mellitus (T2DM) and its correlation with pathological features. For obtaining and exploring the pathological features in patients, sixty T2DM patients (the research group) and thirty healthy controls (the control group) presented to our hospital between January 2019 and June 2019 were selected as the research participants. After DNA extraction from peripheral blood mononuclear cells (PBMCs) and modification of target gene methylation with bisulfite, differences in methylation were verified, and the correlation of ChREBP methylation level with T2DM pathological features and single nucleotide polymorphism (SNP) typing was discussed. According to the prediction results of UCSC Genome Browser Home, there were two CpG islands in the promoter region of the ChREBP gene, and the first exon was selected for research. The ChREBP methylation rate was statistically higher in the research group versus the control group (P < 0.05). Age, FPG, TC, and TG were confirmed by the multiple linear regression analysis to be correlated with the ChREBP methylation rate (P < 0.05). Finally, there was no difference in ChREBP methylation level between CT- and CC-type patients at rs17145750 and rs1051921 loci (P > 0.05). Peripheral blood ChREBP methylation is elevated in T2DM patients and is closely related to age, blood glucose, and blood-lipid level, which is expected to be a new direction for future T2DM diagnosis and treatment.

Are miR-26a and miR-26b microRNAs potent prognostic markers of gestational diabetes?

Background

Gestational diabetes mellitus is a common public health problem, accompanied by complications for the mother and fetus. So, introducing new biomarkers to identify early diabetes is essential. As serum miRNAs are potentially appropriate markers, we investigated miR-26a and miR-26b expression levels in pregnant women with and without gestational diabetes.

Method

Demographic and clinical characteristics of 40 gestational diabetic patients and 40 healthy controls were assessed. The expression level of miR-26a and miR-26b microRNAs was measured by real-time PCR. Statistical analysis was done with GraphPad Prism software (version 8.4.3).

Result

The findings of this study showed that the expression level of miR-26a and miR-26b increased in women with gestational diabetes compared with healthy pregnant women, but the increase in expression was only significant for miR-26a (p < 0.05).

Conclusion

According to the statistical and ROC curves, we suggest miR-26a as a potential biomarker for the early diagnosis of gestational diabetes mellitus.

Design of Machine Learning Algorithms and Internal Validation of a Kidney Risk Prediction Model for Type 2 Diabetes Mellitus

Objective

This study aimed to explore specific biochemical indicators and construct a risk prediction model for diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D).

Methods

This study included 234 T2D patients, of whom 166 had DKD, at the First Hospital of Jilin University from January 2021 to July 2022. Clinical characteristics, such as age, gender, and typical hematological parameters, were collected and used for modeling. Five machine learning algorithms [Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF)] were used to identify critical clinical and pathological features and to build a risk prediction model for DKD. Additionally, clinical data from 70 patients (nT2D = 20, nDKD = 50) were collected for external validation from the Third Hospital of Jilin University.

Results

The RF algorithm demonstrated the best performance in predicting progression to DKD, identifying five major indicators: estimated glomerular filtration rate (eGFR), glycated albumin (GA), Uric acid, HbA1c, and Zinc (Zn). The prediction model showed sufficient predictive accuracy with area under the curve (AUC) values of 0.960 (95% CI: 0.936-0.984) and 0.9326 (95% CI: 0.8747-0.9885) in the internal validation set and external validation set, respectively. The diagnostic efficacy of the RF model (AUC = 0.960) was significantly higher than each of the five features screened with the highest feature importance in the RF model.

Conclusion

The online DKD risk prediction model constructed using the RF algorithm was selected based on its strong performance in the internal validation.

AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes

Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating prevalence, underscoring the critical need for precision health strategies and early detection initiatives. Leveraging artificial intelligence, particularly eXtreme Gradient Boosting (XGBoost), we devise robust risk assessment models for T2D. Drawing upon comprehensive genetic and medical imaging datasets from 68,911 individuals in the Taiwan Biobank, our models integrate Polygenic Risk Scores (PRS), Multi-image Risk Scores (MRS), and demographic variables, such as age, sex, and T2D family history. Here, we show that our model achieves an Area Under the Receiver Operating Curve (AUC) of 0.94, effectively identifying high-risk T2D subgroups. A streamlined model featuring eight key variables also maintains a high AUC of 0.939. This high accuracy for T2D risk assessment promises to catalyze early detection and preventive strategies. Moreover, we introduce an accessible online risk assessment tool for T2D, facilitating broader applicability and dissemination of our findings.

Elevated ITGA1 levels in type 2 diabetes: implications for cardiac function impairment

AIMS/HYPOTHESIS

Type 2 diabetes mellitus is known to contribute to the development of heart failure with preserved ejection fraction (HFpEF). However, identifying HFpEF in individuals with type 2 diabetes early on is often challenging due to a limited array of biomarkers. This study aims to investigate specific biomarkers associated with the progression of HFpEF in individuals with type 2 diabetes, for the purpose of enabling early detection and more effective management strategies.

METHODS

Blood samples were collected from individuals with type 2 diabetes, both with and without HFpEF, for proteomic analysis. Plasma integrin α1 (ITGA1) levels were measured and compared between the two groups. Participants were further categorised based on ITGA1 levels and underwent detailed transthoracic echocardiography at baseline and during a median follow-up period of 30 months. Multivariable linear and Cox regression analyses were conducted separately to assess the associations between plasma ITGA1 levels and changes in echocardiography indicators and re-hospitalisation risk. Additionally, proteomic data for the individuals' left ventricles, from ProteomeXchange database, were analysed to uncover mechanisms underlying the change in ITGA1 levels in HFpEF.

RESULTS

Individuals with type 2 diabetes and HFpEF showed significantly higher plasma ITGA1 levels than the individuals with type 2 diabetes without HFpEF. These elevated ITGA1 levels were associated with left ventricular remodelling and impaired diastolic function. Furthermore, during a median follow-up of 30 months, multivariable analysis revealed that elevated ITGA1 levels independently correlated with deterioration of both diastolic and systolic cardiac functions. Additionally, higher baseline plasma ITGA1 levels independently predicted re-hospitalisation risk (HR 2.331 [95% CI 1.387, 3.917], p=0.001). Proteomic analysis of left ventricular myocardial tissue provided insights into the impact of increased ITGA1 levels on cardiac fibrosis-related pathways and the contribution made by these changes to the development and progression of HFpEF.

CONCLUSIONS/INTERPRETATION

ITGA1 serves as a biomarker for monitoring cardiac structural and functional damage, can be used to accurately diagnose the presence of HFpEF, and can be used to predict potential deterioration in cardiac structure and function as well as re-hospitalisation for individuals with type 2 diabetes. Its measurement holds promise for facilitating risk stratification and early intervention to mitigate the adverse cardiovascular effects associated with diabetes.

DATA AVAILABILITY

The proteomic data of left ventricular myocardial tissue from individuals with type 2 diabetes, encompassing both those with and without HFpEF, is available from the ProteomeXchange database at http://proteomecentral.proteomexchange.org .

NAMPT, IL-6, and vaspin gene expressions and serum protein levels in type 2 diabetes mellitus and related complication

Background/aim

Type 2 diabetes mellitus (T2DM) is the most common type of diabetes and occurs due to insufficient insulin secretion or inability to use existing insulin and the effects of environmental factors. Although there are many studies on the pathophysiology of T2DM, the mechanisms contributing to the pathogenesis of insulin resistance and pancreatic beta-cell dysfunction have not been completely elucidated. Some adipokines secreted from adipose tissue, which are the primary regulators of insulin resistance, affect immune and inflammatory functions. Altered adipokine profiles have been observed in obesity and T2DM, leading to severe metabolic risks and changes in insulin sensitivity.

Materials and methods

This study used quantitative PCR and ELISA techniques to analyze samples from individuals without diabetes (control group) and with T2DM (macrovascular and microvascular complications and without complications) for at least 10 years.

Results

The mRNA expression and protein levels of NAMPT, IL-6, and vaspin genes were determined. While there was no significant difference in NAMPT, IL-6, and vaspin mRNA expression levels between diabetic groups, there was a significant decrease between the patient and control groups (p < 0.001). For serum protein levels, NAMPT protein levels decreased significantly in the uncomplicated group, while IL-6 and vaspin protein levels increased significantly in both microvascular and macrovascular complication groups (p < 0.001).

Conclusion

The correlations between gene expressions, clinical parameters, and protein levels are crucial to understanding the implications of the findings.

The clinical relevance of a polygenic risk score for type 2 diabetes mellitus in the Korean population

The clinical utility of a type 2 diabetes mellitus (T2DM) polygenic risk score (PRS) in the East Asian population remains underexplored. We aimed to examine the potential prognostic value of a T2DM PRS and assess its viability as a clinical instrument. We first established a T2DM PRS for 5490 Korean individuals using East Asian Biobank data (269,487 samples). Subsequently, we assessed the predictive capability of this T2DM PRS in a prospective longitudinal study with baseline data and data from seven additional follow-ups. Our analysis showed that the T2DM PRS could predict the transition of glucose tolerance stages from normal glucose tolerance to prediabetes and from prediabetes to T2DM. Moreover, T2DM patients in the top-decile PRS group were more likely to be treated with insulin (hazard ratio = 1.69, p value = 2.31E-02) than were those in the remaining PRS groups. T2DM PRS values were significantly high in the severe diabetes subgroup, characterized by insulin resistance and β -cell dysfunction (p value = 0.0012). The prediction models with the T2DM PRS had significantly greater Harrel's C-indices than did corresponding models without it. By utilizing prospective longitudinal study data and extensive clinical risk factor information, our analysis provides valuable insights into the multifaceted clinical utility of the T2DM PRS.

Alanine to glycine ratio is a novel predictive biomarker for type 2 diabetes mellitus

AIM

We aimed to evaluate the metabolite ratios that could predict the clinical incidence or remission of type 2 diabetes mellitus (T2D).

METHODS

The Cox proportional hazards regression model was used to assess 1813 individuals without T2D to test the predictive value of metabolite ratios for T2D incidence and 451 newly diagnosed T2D for remission. The receiver operating characteristic curve analysis was performed to determine the best cut-off values for the metabolite ratios. Survival analyses were performed to compare the four subgroups defined by baseline metabolite ratios and clinical status of obesity.

RESULTS

The alanine/glycine was the most significant marker for T2D incidence (hazard ratio per SD: 1.24; p < .001). On the other hand, metabolite hydroxy sphingomyelin C22:2 was most specific for T2D remission (hazard ratio per SD: 1.32; p = .029). Survival analysis of T2D incidence among the subgroups defined by the combination of alanine/glycine and obesity showed the group with a high alanine/glycine and obesity had the highest risk of T2D incidence (p < .001). The alanine/glycine as a T2D risk marker was also validated in the independent external data.

CONCLUSIONS

The combination of obesity and the alanine/glycine ratio can be used to evaluate the diabetes risk.

From hyperglycemia to intervertebral disc damage: exploring diabetic-induced disc degeneration

The incidence of lumbar disc herniation has gradually increased in recent years, and most patients have symptoms of low back pain and nerve compression, which brings a heavy burden to patients and society alike. Although the causes of disc herniation are complex, intervertebral disc degeneration (IDD) is considered to be the most common factor. The intervertebral disc (IVD) is composed of the upper and lower cartilage endplates, nucleus pulposus, and annulus fibrosus. Aging, abnormal mechanical stress load, and metabolic disorders can exacerbate the progression of IDD. Among them, high glucose and high-fat diets (HFD) can lead to fat accumulation, abnormal glucose metabolism, and inflammation, which are considered important factors affecting the homeostasis of IDD. Diabetes and advanced glycation end products (AGEs) accumulation- can lead to various adverse effects on the IVD, including cell senescence, apoptosis, pyroptosis, proliferation, and Extracellular matrix (ECM) degradation. While current research provides a fundamental basis for the treatment of high glucose-induced IDD patients. further exploration into the mechanisms of abnormal glucose metabolism affecting IDD and in the development of targeted drugs will provide the foundation for the effective treatment of these patients. We aimed to systematically review studies regarding the effects of hyperglycemia on the progress of IDD.

Serum tumor markers expression (CA199, CA242, and CEA) and its clinical implications in type 2 diabetes mellitus

BACKGROUND

Glucose and lipid metabolic disorder in patients with type 2 diabetes mellitus (T2DM) is associated with the levels of serum tumor markers of the digestive tract, such as cancer antigen (CA)199. Therefore, tumor markers in T2DM are important.

AIM

To evaluate the expression of serum tumor markers [CA199, CA242, and car-cinoembryonic antigen (CEA)] and the clinical implications of the expression in T2DM.

METHODS

For this observational study conducted at Hefei BOE Hospital, China, we enrolled 82 patients with first-onset T2DM and 51 controls between April 2019 and December 2020. Levels of fasting blood glucose (FBG), tumor markers (CA199, CEA, and CA242), glycosylated hemoglobin (HbA1c), etc. were measured and group index levels were compared. Moreover, FBG and HbA1c levels were correlated with tumor marker levels. Tumor markers were tested for diagnostic accuracy in patients with > 9% HbA1c using the receiver operating curve (ROC) curve.

RESULTS

The T2DM group had high serum FBG, HbA1c, CA199, and CEA levels (P < 0.05). A comparative analysis of the two groups based on HbA1c levels (Group A: HbA1c ≤ 9%; Group B: HbA1c > 9%) revealed significant differences in CEA and CA199 levels (P < 0.05). The areas under the ROC curve for CEA and CA199 were 0.853 and 0.809, respectively. CA199, CEA, and CA242 levels positively correlated with HbA1c (r = 0.308, 0.426, and 0.551, respectively) and FBG levels (r = 0.236, 0.231, and 0.298, respectively).

CONCLUSION

As compared to controls, serum CEA and CA199 levels were higher in patients with T2DM. HbA1c and FBG levels correlated with CA199, CEA, and CA242 levels. Patients with poorly controlled blood sugar must be screened for tumor markers.

Vaspin: A Novel Biomarker Linking Gluteofemoral Body Fat and Type 2 Diabetes Risk

OBJECTIVE

To determine whether adiposity depots modulate vaspin levels and whether vaspin predicts type 2 diabetes (T2D) risk, through epidemiological and genetic analyses.

RESEARCH DESIGN AND METHODS

We assessed the relationship of plasma vaspin concentration with incident and prevalent T2D and adiposity-related variables in 1) the Prospective Urban and Rural Epidemiology (PURE) biomarker substudy (N = 10,052) and 2) the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial (N = 7,840), using regression models. We then assessed whether vaspin is causally associated with T2D and whether genetic variants associated with MRI-measured adiposity depots modulate vaspin levels, using two-sample Mendelian randomization (MR).

RESULTS

A 1-SD increase in circulating vaspin levels was associated with a 16% increase in incident T2D in the PURE cohort (hazard ratio 1.16; 95% CI 1.09-1.23; P = 4.26 × 10-7) and prevalent T2D in the ORIGIN cohort (odds ratio [OR] 1.16; 95% CI 1.07-1.25; P = 2.17 × 10-4). A 1-unit increase in BMI and triglyceride levels was associated with a 0.08-SD (95% CI 0.06-0.10; P = 2.04 × 10-15) and 0.06-SD (95% CI 0.04-0.08; P = 4.08 × 10-13) increase, respectively, in vaspin in the PURE group. Consistent associations were observed in the ORIGIN cohort. MR results reinforced the association between vaspin and BMI-adjusted T2D risk (OR 1.01 per 1-SD increase in vaspin level; 95% CI 1.00-1.02; P = 2.86 × 10-2) and showed that vaspin was increased by 0.10 SD per 1-SD decrease in genetically determined gluteofemoral adiposity (95% CI 0.02-0.18; P = 2.01 × 10-2). No relationships were found between subcutaneous or visceral adiposity and vaspin.

CONCLUSIONS

These findings support that higher vaspin levels are related to increased T2D risk and reduced gluteofemoral adiposity, positioning vaspin as a promising clinical predictor for T2D.

DiaNet v2 deep learning based method for diabetes diagnosis using retinal images

Diabetes mellitus (DM) is a prevalent chronic metabolic disorder linked to increased morbidity and mortality. With a significant portion of cases remaining undiagnosed, particularly in the Middle East North Africa (MENA) region, more accurate and accessible diagnostic methods are essential. Current diagnostic tests like fasting plasma glucose (FPG), oral glucose tolerance tests (OGTT), random plasma glucose (RPG), and hemoglobin A1c (HbA1c) have limitations, leading to misclassifications and discomfort for patients. The aim of this study is to enhance diabetes diagnosis accuracy by developing an improved predictive model using retinal images from the Qatari population, addressing the limitations of current diagnostic methods. This study explores an alternative approach involving retinal images, building upon the DiaNet model, the first deep learning model for diabetes detection based solely on retinal images. The newly proposed DiaNet v2 model is developed using a large dataset from Qatar Biobank (QBB) and Hamad Medical Corporation (HMC) covering wide range of pathologies in the the retinal images. Utilizing the most extensive collection of retinal images from the 5545 participants (2540 diabetic patients and 3005 control), DiaNet v2 is developed for diabetes diagnosis. DiaNet v2 achieves an impressive accuracy of over 92%, 93% sensitivity, and 91% specificity in distinguishing diabetic patients from the control group. Given the high prevalence of diabetes and the limitations of existing diagnostic methods in clinical setup, this study proposes an innovative solution. By leveraging a comprehensive retinal image dataset and applying advanced deep learning techniques, DiaNet v2 demonstrates a remarkable accuracy in diabetes diagnosis. This approach has the potential to revolutionize diabetes detection, providing a more accessible, non-invasive and accurate method for early intervention and treatment planning, particularly in regions with high diabetes rates like MENA.

The Role of GLP-1, GIP, MCP-1 and IGFBP-7 Biomarkers in the Development of Metabolic Disorders: A Review and Predictive Analysis in the Context of Diabetes and Obesity

Metabolic illnesses, including obesity and type 2 diabetes, have become worldwide epidemics that have an effect on public health. Clinical investigations and further exploration of these mechanisms could lead to innovative, effective, and personalized treatment strategies for individuals. It is important to screen biomarkers in previous studies to discover what is missing. Glucagon-like peptide-1's role in insulin secretion and glucose control highlights its diagnostic and therapeutic potential. Glucose-dependent insulinotropic peptide's influence on postprandial satiety and weight management signifies its importance in understanding metabolic processes. Monocyte chemoattractant protein-1's involvement in inflammation and insulin resistance underlines its value as a diagnostic marker. Insulin-like growth factor-binding protein-7's association with insulin sensitivity and kidney function presents it as a potential target for these diseases' management. In validating these biomarkers, it will be easier to reflect pathophysiological processes, and clinicians will be able to better assess disease severity, monitor disease progression, and tailor treatment strategies. The purpose of the study was to elucidate the significance of identifying novel biomarkers for type 2 diabetes mellitus and obesity, which can revolutionize early detection, risk assessment, and personalized treatment strategies. Standard literature searches of PubMed (MEDLINE), EMBASE, and Cochrane Library were conducted in the year 2023 to identify both original RCTs and recent systematic reviews that have explored the importance of identifying novel biomarkers for T2D and obesity. This search produced 1964 results, and then was reduced to randomized controlled trial and systematic reviews, producing 145 results and 44 results, respectively. Researchers have discovered potential associations between type 2 diabetes mellitus and obesity and the biomarkers glucagon-like peptide-1, glucose-dependent insulinotropic peptide, monocyte chemoattractant protein-1, and insulin-like growth factor-binding protein-7. Understanding the role of those biomarkers in disease pathogenesis offers hope for improving diagnostics, personalized treatment, and prevention strategies.

Potential Association of The Pathogenic Kruppel-like Factor 14 (KLF14) and Adiponectin (ADIPOQ) SNVs with Susceptibility to T2DM

AIM

To evaluate the associations of the pathogenic variants in Kruppel-like Factor 14 (KLF 14) and Adiponectin (ADIPOQ) with susceptibility to type 2 diabetes mellitus (T2DM).

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a pandemic metabolic disease characterized by increased blood sugar and caused by resistance to insulin in peripheral tissues and damage to pancreatic beta cells. Kruppel-like Factor 14 (KLF-14) is proposed to be a regulator of metabolic diseases, such as diabetes mellitus (DM) and obesity. Adiponectin (ADIPOQ) is an adipocytokine produced by the adipocytes and other tissues and was reported to be involved in T2DM.

OBJECTIVES

To study the possible association of the KLF-14 rs972283 and ADIPOQ-rs266729 with the risk of T2DM in the Saudi population.

METHODS

We have evaluated the association of KLF-14 rs972283 C>T and ADIPOQ-rs266729 C>G SNV with the risk to T2D in the Saudi population using the Amplification Refractory Mutation System PCR (ARMS-PCR), and blood biochemistry analysis. For the KLF-14 rs972283 C>T SNV we included 115 cases and 116 healthy controls, and ADIPOQ-rs266729 C>G SNV, 103 cases and 104 healthy controls were included.

RESULTS

Results indicated that the KLF-14 rs972283 GA genotype and A allele were associated with T2D risk with OR=2.14, p-value= 0.014 and OR=1.99, p-value=0.0003, respectively. Results also ADIPOQ-rs266729 CG genotype and C allele were associated with an elevated T2D risk with an OR=2.53, p=0.003 and OR=1.66, p-value =0.012, respectively.

CONCLUSION

We conclude that SNVs in KLF-14 and ADIPOQ are potential loci for T2D risk. Future large-scale studies to verify these findings are recommended. These results need further verifications in protein functional and large-scale case control studies before being introduced for genetic testing.

Therapeutic Potential of Syzygium aromaticum in Gut Dysbiosis via TMAO Associated Diabetic Cardiomyopathy

BACKGROUND

Dysbiosis of the gastrointestinal microbiota is not only related to the pathogenesis of intestinal disorders but also associated with extra-intestinal diseases. Various studies have revealed the role of an imbalance of intestinal microbiota and their metabolites including bile acids, indole derivatives, polyamines, and trimethylamine in the progression of various diseases. The elevated plasma level of the oxidized form of trimethylamine is associated with the increased risk of cardiovascular diseases. Literature supports that herbal medicines can modulate human health by altering the diversity of gut microbiota and their metabolites and proposes the use of prebiotics to improve dysbiotic conditions as a new way of therapeutic strategy.

METHODS

In silico studies including drug likeliness, toxicity prediction, and molecular interaction of phytochemicals against trimethylamine lyase enzyme have been done. Antimicrobial activity of extracts of selected plant i.e. Syzygium aromaticum was done by disc diffusion and the protective effects of plant compounds were examined on trimethylamine-n-oxide a bacterial metabolic product and high glucose induced toxicity.

RESULTS

The current study has found that the phytochemicals of S. aromaticum identified as nontoxic and followed the standard rules of drug likeliness and showed a significant binding affinity against trimethylamine-n-oxide producing enzymes. Furthermore, S. aromaticum extract was found to have antimicrobial potential and cardioprotective effects by reducing the production of intracellular reactive oxygen species and correcting the distorted nuclear morphology in the presence of high trimethylamine-n-oxide.

CONCLUSION

Conclusively, our study explored the herbal intervention in intestinal dysbiosis and suggested a natural therapy against dysbiosis associated with cardiac disease, and S, aromaticum was found to have exceptional cardioprotective potential against TMAO induced gut dysbiosis, which provides a novel future therapeutic intervention for treating cardiovascular complications.

Exploration of human pancreatic alpha-amylase inhibitors from Physalis peruviana for the treatment of type 2 diabetes

Type 2 Diabetes (T2D), a chronic metabolic disorder characterized by persistent hyperglycemia, accounts for ∼90% of all types of diabetes. Pancreatic α-amylase is a potential drug target for preventing postprandial hyperglycemia and inhibiting T2D in humans. Although many synthetic drugs have been identified against pancreatic α-amylase, however, reported several side effects, and plant-derived natural products are less explored against T2D. This study tested 34 flavonoids derived from the plant Physalis peruviana against the human pancreatic α-amylase (HPA) using in silico computational approaches such as molecular docking and molecular dynamics simulation approaches. Schrödinger, a drug discovery package with modules applicable for molecular docking, protein-ligand interaction analysis, molecular dynamics, post-dynamics simulation, and binding free energy calculation, was employed for all computational studies. Four flavonoids, namely, Chlorogenic acid, Withaperuvin F, Withaperuvin H, and Rutin, were picked based on their docking score ranging between -7.03 kcal/mol and -11.35 kcal/mol compared to the docking score -7.3 kcal/mol of reference ligand, i.e. Myricetin. The molecular dynamics analysis suggested that all flavonoids showed considerable stability within the protein's catalytic pocket, except chlorogenic acid, which showed high deviation during the last 15 ns. However, the interactions observed in initial docking and extracted from the simulation trajectory involved > 90% identical residues, indicating the affinity and stability of the docked flavonoids with the protein. Therefore, all four compounds identified in this study are proposed as promising antidiabetic candidates and should be further considered for their in vitro and in vivo validation.Communicated by Ramaswamy H. Sarma.

Associations of Clinical Risk Factors and Novel Biomarkers With Age at Onset of Type 2 Diabetes

CONTEXT

Younger onset of type 2 diabetes (T2D) was associated with higher risks of vascular complications and mortality.

OBJECTIVE

To prospectively assess risk profiles for incident T2D stratified by age at onset.

METHODS

A total of 471 269 participants free of T2D at baseline were included from the UK Biobank. Approximately 70 clinical, lipid, lipoprotein, inflammatory, and metabolic markers, and genetic risk scores (GRSs) were analyzed. Stratified Cox proportional-hazards regression models were used to estimate hazard ratios (HRs) for T2D with age of diagnosis divided into 4 groups (≤50.0, 50.1-60.0, 60.1-70.0, and >70.0 years).

RESULTS

During 11 years of follow-up, 15 805 incident T2D were identified. Among clinical risk factors, obesity had the highest HR at any age, ranging from 13.16 (95% CI, 9.67-17.91) for 50.0 years and younger to 4.13 (3.78-4.51) for older than 70.0 years. Other risks associated with T2D onset at age 50.0 years and younger included dyslipidemia (3.50, 2.91-4.20), hypertension (3.21, 2.71-3.80), cardiovascular disease (2.87, 2.13-3.87), parental history of diabetes (2.42, 2.04-2.86), education lower than college (1.89, 1.57-2.27), physical inactivity (1.73, 1.43-2.10), smoking (1.38, 1.13-1.68), several lipoprotein particles, inflammatory markers, liver enzymes, fatty acids, amino acids, as well as GRS. Associations of most risk factors and biomarkers were markedly attenuated with increasing age at onset (P interaction <.05), and some were not significant for onset at age older than 70.0 years, such as smoking, systolic blood pressure, and apolipoprotein B.

CONCLUSION

Most risk factors or biomarkers had stronger relative risks for T2D at younger ages, which emphasizes the necessity of promoting primary prevention among younger individuals. Moreover, obesity should be prioritized.

Endothelial progenitor cells as biomarkers of diabetes-related cardiovascular complications

Diabetes mellitus (DM) constitutes a chronic metabolic disease characterized by elevated levels of blood glucose which can also lead to the so-called diabetic vascular complications (DVCs), responsible for most of the morbidity, hospitalizations and death registered in these patients. Currently, different approaches to prevent or reduce DM and its DVCs have focused on reducing blood sugar levels, cholesterol management or even changes in lifestyle habits. However, even the strictest glycaemic control strategies are not always sufficient to prevent the development of DVCs, which reflects the need to identify reliable biomarkers capable of predicting further vascular complications in diabetic patients. Endothelial progenitor cells (EPCs), widely known for their potential applications in cell therapy due to their regenerative properties, may be used as differential markers in DVCs, considering that the number and functionality of these cells are affected under the pathological environments related to DM. Besides, drugs commonly used with DM patients may influence the level or behaviour of EPCs as a pleiotropic effect that could finally be decisive in the prognosis of the disease. In the current review, we have analysed the relationship between diabetes and DVCs, focusing on the potential use of EPCs as biomarkers of diabetes progression towards the development of major vascular complications. Moreover, the effects of different drugs on the number and function of EPCs have been also addressed.

miR-135a-5p overexpression in peripheral blood-derived exosomes mediates vascular injury in type 2 diabetes patients

Objective

Diabetes pathology relies on exosomes (Exos). This study investigated how peripheral blood Exo-containing microRNAs (miRNAs) cause vascular injury in type 2 diabetes (T2D).

Methods

We removed DEmiRNA from T2D chip data from the GEO database. We isolated Exo from 15 peripheral blood samples from T2D patients and 15 healthy controls and measured Exo DEmiRNA levels. We employed the intersection of Geneards and mirWALK database queries to find T2D peripheral blood mRNA-related chip target genes. Next, we created a STRING database candidate target gene interaction network map. Next, we performed GO and KEGG enrichment analysis on T2D-related potential target genes using the ClusterProfiler R package. Finally, we selected T2D vascular damage core genes and signaling pathways using GSEA and PPI analysis. Finally, we used HEK293 cells for luciferase assays, co-cultured T2D peripheral blood-derived Exo with HVSMC, and detected HVSMC movement alterations.

Results

We found 12 T2D-related DEmiRNAs in GEO. T2D patient-derived peripheral blood Exo exhibited significantly up-regulated miR-135a-3p by qRT-PCR. Next, we projected miR-135a-3p's downstream target mRNA and screened 715 DEmRNAs to create a regulatory network diagram. DEmRNAs regulated biological enzyme activity and vascular endothelial cells according to GO function and KEGG pathway analysis. ErbB signaling pathway differences stood out. PPI network study demonstrated that DEmRNA ATM genes regulate the ErbB signaling pathway. The luciferase experiment validated miR-135a-3p and ATM target-binding. Co-culture of T2D patient-derived peripheral blood Exo with HVSMC cells increases HVSMC migration, ErbB2, Bcl-2, and VEGF production, and decreases BAX and ATM. However, miR-135a-3p can reverse the production of the aforesaid functional proteins and impair HVSMC cell movement.

Conclusion

T2D patient-derived peripheral blood Exo carrying miR-135a-3p enter HVSMC, possibly targeting and inhibiting ATM, activating the ErbB signaling pathway, promoting abnormal HVSMC proliferation and migration, and aggravating vascular damage.

Designing and computational analyzing of chimeric long-lasting GLP-1 receptor agonists for type 2 diabetes

Glucagon-like peptide-1 (GLP-1) is an intestinally derived incretin that plays a vital role in engineering the biological circuit involved in treating type 2 diabetes. Exceedingly short half-life (1-2 min) of GLP-1 limits its therapeutic applicability, and the implication of its new variants is under question. Since albumin-binding DARPin as a mimetic molecule has been reported to increase the serum half-life of therapeutic compounds, the interaction of new variants of GLP-1 in fusion with DARPin needs to be examined against the GLP-1 receptor. This study was aimed to design stable and functional fusion proteins consisting of new protease-resistant GLP-1 mutants (mGLP1) genetically fused to DARPin as a critical step toward developing long-acting GLP-1 receptor agonists. The stability and solubility of the engineered fusion proteins were analyzed, and their secondary and tertiary structures were predicted and satisfactorily validated. Molecular dynamics simulation studies revealed that the predicted structures of engineered fusion proteins remained stable throughout the simulation. The relative binding affinity of the engineered fusion proteins' complex with human serum albumin and the GLP-1 receptor individually was assessed using molecular docking analyses. It revealed a higher affinity compared to the interaction of the individual GLP-1 and HSA-binding DARPin with the GLP-1 receptor and human serum albumin, respectively. The present study suggests that engineered fusion proteins can be used as a potential molecule in the treatment of type 2 diabetes, and this study provides insight into further experimental use of mimetic complexes as alternative molecules to be evaluated as new bio-breaks in the engineering of biological circuits in the treatment of type 2 diabetes.

Factors associated with adherence or nonadherence to insulin therapy among adults with type 2 diabetes mellitus: A scoping review

BACKGROUND AND AIM

One of the greatest barriers to the treatment of T2DM is nonadherence which particularly applies to insulin therapy. There is a need for a comprehensive overview of all factors associated with nonadherence to insulin therapy. The aim of this study was to identify factors associated with adherence or nonadherence to insulin therapy among adults with T2DM.

METHODS

A scoping review was conducted in accordance with the PRISMA 2020 statement. A systematic search was performed in PubMed, Cinahl, and Web of Science (January 2013 to March 2023).

RESULTS

A final sample of 48 studies was included in the scoping review. The synthesis revealed 30 factors associated with adherence or nonadherence. The factors were grouped into 6 themes: demographics, attitude and perceptions, management of diabetes, impact on daily living, disease and medication, and healthcare system.

CONCLUSION

The most prominent factors identified were age, cost of healthcare, personal beliefs towards insulin therapy, social stigma, patient education, complexity of diabetes treatment, impact of insulin therapy on daily life, and fear of side effects. The results indicate a need for further research to determine threshold values for the factors associated with adherence or nonadherence.

An environment-wide association study for the identification of non-invasive factors for type 2 diabetes mellitus: Analysis based on the Henan Rural Cohort study

AIM

To explore the influencing factors of Type 2 diabetes mellitus (T2DM) in the rural population of Henan Province and evaluate the predictive ability of non-invasive factors to T2DM.

METHODS

A total of 30,020 participants from the Henan Rural Cohort Study in China were included in this study. The dataset was randomly divided into a training set and a testing set with a 50:50 split for validation purposes. We used logistic regression analysis to investigate the association between 56 factors and T2DM in the training set (false discovery rate < 5 %) and significant factors were further validated in the testing set (P < 0.05). Gradient Boosting Machine (GBM) model was used to determine the ability of the non-invasive variables to classify T2DM individuals accurately and the importance ranking of these variables.

RESULTS

The overall population prevalence of T2DM was 9.10 %. After adjusting for age, sex, educational level, marital status, and body measure index (BMI), we identified 13 non-invasive variables and 6 blood biochemical indexes associated with T2DM in the training and testing dataset. The top three factors according to the GBM importance ranking were pulse pressure (PP), urine glucose (UGLU), and waist-to-hip ratio (WHR). The GBM model achieved a receiver operating characteristic (AUC) curve of 0.837 with non-invasive variables and 0.847 for the full model.

CONCLUSIONS

Our findings demonstrate that non-invasive variables that can be easily measured and quickly obtained may be used to predict T2DM risk in rural populations in Henan Province.

Impact of Fixed Combination of Metformin and Pioglitazone on Insulin Resistance of Patients with Type 2 Diabetes: Results of a Randomized Open-Label Study

AIM

To compare the effect of metformin, a fixed combination of metformin and pioglitazone, or dapagliflozin on insulin resistance in patients with newly diagnosed type 2 diabetes.

METHODS

In this 6-week randomized open-label trial, 58 patients were randomly assigned to insulin with metformin, a fixed combination of metformin and pioglitazone, or dapagliflozin for 4 weeks. Hyperinsulinemic euglycemic clamp tests and FreeStyle Libre Pro Sensor were used to evaluate the insulin sensitivity represented by glucose-infusion rate (M value) and glycemic control, respectively. The main outcome was changes in insulin resistance compared with baseline.

RESULTS

The baseline characteristics were well matched among the three groups. When compared to baseline, insulin sensitivity after treatment was significantly improved. Further study revealed that the fixed combination of metformin and pioglitazone provided superior M-value improvement compared with metformin, but not different from dapagliflozin. Moreover, a greater reduction in insulin dose was observed in the fixed combination of metformin and pioglitazone group than the metformin or dapagliflozin group. However, there were no significant differences in the parameters of glycemic control within the groups.

CONCLUSION

In patients with newly diagnosed type 2 diabetes, a fixed combination of metformin and pioglitazone provided greater improvement in insulin resistance than metformin alone and similar changes in insulin resistance to dapagliflozin.

Strikes and Gutters: Biomarkers and anthropometric measures for predicting diagnosed diabetes mellitus in adults in low- and middle-income countries

The management of diabetes necessitates the requirement of reliable health indices, specifically biomarkers and anthropometric measures, to detect the presence or absence of the disease. Nevertheless, limited robust empirical evidence exists regarding the optimal metrics for predicting diabetes in adults, particularly within low- and middle-income countries. This study investigates objective and subjective indices for screening diabetes in these countries.

METHODS

Data for this study was sourced from surveys conducted among adults (aged 18 years and above) in seventeen (17) countries. Self-reported diabetes status, fifty-four biomarkers, and twenty-six core and twenty-eight estimated anthropometric indices, including weight, waist circumference, body mass index, glycaemic triglycerides, and fasting blood glucose, were utilised to construct lasso regression models.

RESULTS

The study revealed variances in diabetes prediction outcomes across different countries. Central adiposity measures, fasting plasma glucose and glycaemic triglycerides demonstrated superior predictive capabilities for diabetes when compared to body mass index. Furthermore, fasting plasma or blood glucose, serving as a biomarker, emerged as the most accurate predictor of diabetes.

CONCLUSIONS

These findings offer critical insights into both general and context-specific tools for diabetes screening. The study proposes that fasting plasma glucose and central adiposity indices should be considered as routine screening tools for diabetes, both in policy interventions and clinical practice. By identifying adults with or at higher risk of developing diabetes and implementing appropriate interventions, these screening tools possess the potential to mitigate diabetes-related complications in low- and middle-income countries.