Environmental and genetic contributions to diabetes

The Role of circHIPK3 in Tumorigenesis and Its Potential as a Biomarker in Lung Cancer

Lung cancer treatment and detection can be improved by the identification of new biomarkers. Novel approaches in investigating circular RNAs (circRNAs) as biomarkers have yielded promising results. A circRNA molecule circHIPK3 was found to be widely expressed in non-small-cell lung cancer (NSCLC) cells, where it plays a crucial role in lung cancer tumorigenesis. CircHIPK3 promotes lung cancer progression by sponging oncosuppressive miRNAs such as miR-124, miR-381-3p, miR-149, and miR-107, which results in increased cell proliferation, migration, and resistance to therapies. Inhibiting circHIPK3 has been demonstrated to suppress tumour growth and induce apoptosis, which suggests its potential use in the development of new lung cancer treatment strategies targeting circHIPK3-related pathways. As a biomarker, circHIPK3 shows promise for early detection and monitoring of lung cancer. CircHIPK3 increased expression levels in lung cancer cells, and its potential link to metastasis risk highlights its clinical relevance. Given the promising preliminary findings, more clinical trials are needed to validate circHIPK3 efficacy as a biomarker. Moreover, future research should determine if the mechanisms discovered in NSCLC apply to small cell lung cancer (SCLC) to investigate circHIPK3-targeted therapies for SCLC.

Causal Effects of Oxidative Stress on Diabetes Mellitus and Microvascular Complications: Insights Integrating Genome-Wide Mendelian Randomization, DNA Methylation, and Proteome

BACKGROUND

Oxidative stress (OS) is involved in the development of diabetes, but the genetic mechanisms are not completely understood. We integrated multi-omics data in order to explore the genetic relations between OS-related genes, diabetes mellitus, and microvascular complications using Mendelian randomization and colocalization analysis.

METHODS

Summary-level data related to OS were acquired from respective studies of methylation, expression, and protein abundance quantitative trait loci. Genetic associations concerning diabetes, diabetic nephropathy (DN), and diabetic retinopathy (DR) were derived from the FinnGen study. Summary-data-based Mendelian randomization (SMR) analysis was conducted to evaluate the correlations between molecular features concerned with OS-related genes and diabetes mellitus, along with its microvascular complications. Additionally, we performed colocalization analysis to determine if the detected signal pairs shared a causal genetic variant.

RESULTS

At the genetic level, we identified ten potential causal associations of oxidative stress genes with diabetes, along with microvascular complications, through SMR and colocalization analysis. After integrating the DNA methylation quantitative trait loci (mQTL) and expression QTL (eQTL) data, our analyses revealed a correlation between the methylation site cg26343298 and reduced expression of TP53INP1, supporting the protective role of cg26343298 methylation on type 2 diabetes (T2D) and diabetic nephropathy. Similarly, an inverse association was observed between gene methylation and expression in CHEK1 (cg07110182), confirming the beneficial effect of modification of CHEK1 by cg07110182 in diabetic retinopathy. In addition, upregulation of SUOX expression by cg22580629 was linked to a reduced risk of diabetic retinopathy. At circulating protein levels, genetically predicted a higher level of ICAM1 (OR 1.05, 95%CI 1.03-1.08) was positively connected with the risk of diabetic retinopathy.

CONCLUSIONS

This SMR study elucidated that the TP53INP1 gene was putatively associated with T2D and DN risk, while the SUOX and CHEK1 genes were associated with DR risk through oxidative stress mechanisms. Additionally, our study showed a positive correlation between the ICAM-1 protein and DR. These findings may enhance our understanding of their pathogenesis and suggest new therapeutic targets for clinical practice.

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery

BACKGROUND

This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques.

METHODS

Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D.

RESULTS

As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures.

CONCLUSIONS

ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.

Effects of Age and Biological Age-Determining Factors on Telomere Length in Type 2 Diabetes Mellitus Patients

Background and Objectives: Telomere length (TL) undergoes attrition over time, indicating the process of aging, and is linked to a higher risk of diabetes mellitus type 2 (DM-2). This molecular epidemiological study investigated the correlation between leukocyte TL variations and determinants of molecular aging in 121 Pakistani DM-2 patients. Materials and Methods: The ratio of telomere repeats to the SCG copy number was calculated to estimate the TL in each sample through qPCR assays. Results: In this study, smaller mean TLs were observed in 48.8% of males (6.35 ± 0.82 kb), 3.3% of underweight patients (5.77 ± 1.14 kb), 61.2% of patients on regular medication (6.50 ± 0.79 kb), 9.1% with very high stress levels (5.94 ± 0.99 kb), 31.4% of smokers (5.83 ± 0.73 kb), 40.5% of patients with low physical activity (6.47 ± 0.69 kb), 47.9% of hypertensive patients (5.93 ± 0.64 kb), 10.7% of patients with DM-2 for more than 15 years, and 3.3% of patients with a delayed onset of DM-2 (6.00 ± 0.93 kb). Conclusion: This research indicated a significant negative correlation (R2 = 0.143) between TL and the age of DM-2 patients. This study demonstrated that the correlation of telomere length with age in DM-2 patients was also influenced by various age-determining factors, including hypertension and smoking habits, with significant strong (R2 = 0.526) and moderate (R2 = 0.299) correlations, respectively; sex, obesity, the stress level and age at the onset of diabetes with significant weak correlations (R2 = 0.043, 0.041, 0.037, and 0.065, respectively), and no significant correlations of medication routine, rate of physical activity, and the durations of DM-2 with age-adjusted telomere length. These results challenge TL as the sole marker of aging, thus highlighting the need for further research to understand underlying factors and mitigate the effect of aging or premature aging on diabetic patients.

Urinary neonicotinoid concentrations and obesity: A cross-sectional study among Chinese adolescents

Epidemiological and toxicological studies on neonicotinoids and obesity have been relevant to adults and young children, but data are limited in adolescents. This study aimed to examine the association between urinary neonicotinoid concentrations and obesity measures among Chinese adolescent. A total of 524 urine samples from 300 boys (11.3-16.1 years) and 224 girls (12.1-15.8 years) were collected to detect the concentrations of eleven neonicotinoids. Generalized linear regression, weighted quantile sum regression (WQS) and Bayesian kernel machine regression (BKMR) were used to estimate covariate-adjusted associations between detectable neonicotinoids and ten indicators of obesity. Nitenpyram concentration was associated with increased body mass index z-score (β = 0.170, 95% CI: 0.041, 0.299) and greater odds of being general obesity (OR = 2.46, 95% CI: 1.11, 5.46). N-desmethyl- acetamiprid concentration was associated with an increase in waist-to-height ratio (β = 0.102, 95% CI: 0.029, 0.176) and waist-to-hip ratio (β = 0.083, 95% CI: 0.011, 0.155). The concentrations of clothianidin (OR = 2.06, 95% CI: 1.10, 3.88) and flonicamid (OR = 2.39, 95% CI: 1.07, 5.32) were associated with greater odds of being abdominal obesity. In contrast, the concentrations of imidacloprid (OR = 0.35, 95% CI: 0.14, 0.88) and thiacloprid (OR = 0.28, 95% CI: 0.08, 0.99) were associated with lower odds of being general obesity. The estimates of general obesity and abdominal obesity increased significantly when concentrations of neonicotinoids mixture were at or above the 55th and 65th percentiles, respectively, compared to the 50th percentile concentration. Sex modified the association between nitenpyram and clothianidin and the risk of obesity with a positive association among boys, and a nonsignificant inverse association among girls. The findings suggest that these associations may be mixed and sex-specific.

Post-Translational Modifications and Diabetes

Diabetes and its associated complications have increasingly become major challenges for global healthcare. The current therapeutic strategies involve insulin replacement therapy for type 1 diabetes (T1D) and small-molecule drugs for type 2 diabetes (T2D). Despite these advances, the complex nature of diabetes necessitates innovative clinical interventions for effective treatment and complication prevention. Accumulative evidence suggests that protein post-translational modifications (PTMs), including glycosylation, phosphorylation, acetylation, and SUMOylation, play important roles in diabetes and its pathological consequences. Therefore, the investigation of these PTMs not only sheds important light on the mechanistic regulation of diabetes but also opens new avenues for targeted therapies. Here, we offer a comprehensive overview of the role of several PTMs in diabetes, focusing on the most recent advances in understanding their functions and regulatory mechanisms. Additionally, we summarize the pharmacological interventions targeting PTMs that have advanced into clinical trials for the treatment of diabetes. Current challenges and future perspectives are also provided.

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Background

The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidities. The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide potential targets for prevention and intervention for depression and anxiety.

Methods

This study used a cross-sectional design with data from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.

Results

According to cutoff scores indicating the presence of depression and anxiety, the prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. "Feeling blue/depressed", "Nervousness or anxiety", "Uncontrollable worry", "Trouble relaxing", and "Worry too much" had the highest EI values. "Nervousness or anxiety" and "Everything was an effort" exhibited the highest BEI values.

Conclusion

Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or currently have depressive and anxiety symptoms.

Identification of gene mutations associated with type 1 diabetes by next-generation sequencing in affected Palestinian families

Introduction: Diabetes Mellitus is a group of metabolic disorders characterized by hyperglycemia secondary to insulin resistance or deficiency. It is considered a major health problem worldwide. T1DM is a result of a combination of genetics, epigenetics, and environmental factors. Several genes have been associated with T1DM, including HLA, INS, CTLA4, and PTPN22. However, none of these findings have been based on linkage analysis because it is rare to find families with several diabetic individuals. Two Palestinian families with several afflicted members with variations in the mode of inheritance were identified and selected for this study. This study aimed to identify the putative causative gene(s) responsible for T1DM development in these families to improve our understanding of the molecular genetics of the disease. Methods: One afflicted member from each family was selected for Whole-Exome Sequencing. Data were mapped to the reference of the human genome, and the resulting VCF file data were filtered. The variants with the highest phenotype correlation score were checked by Sanger sequencing for all family members. The confirmed variants were analyzed in silico by bioinformatics tools. Results: In one family, the IGF1R p.V579F variant, which follows autosomal dominant inheritance, was confirmed and segregated in the family. In another family, the NEUROD1 p.P197H variant, which follows autosomal recessive inheritance, was positively confirmed and segregated. Conclusion: IGF1R p.V579F and NEUROD1 p.P197H variants were associated with T1DM development in the two inflicted families. Further analysis and functional assays will be performed, including the generation of mutant model cell systems, to unravel their specific molecular mechanism in the disease development.

Cardio-Metabolic Health of Offspring Exposed in Utero to Human Immuno-Deficiency Virus and Anti-Retroviral Treatment: A Systematic Review

BACKGROUND

Antiretroviral treatment (ART) use during pregnancy continues to rise as it is known to decrease the likelihood of HIV transmission from mother to child. However, it is still unknown whether foetal exposure to (ART) may affect the foetal environment, predisposing the offspring to cardiometabolic risk. Therefore, the aim of this study was to systematically review the cardio-metabolic effects of in utero exposure to HIV/ART on offspring.

METHODS

We carried out a systematic review and obtained literature from the Google scholar, PubMed, ProQuest, Web of Science, and Scopus databases. Two independent reviewers evaluated the titles, abstracts, and full-length English contents. Data from the eligible studies were included.

RESULTS

The search yielded 7596 records. After assessing all of these records, 35 of the full-length articles were included in this systematic review. Several studies showed that low birth weight, small head circumference, and altered mitochondrial content were more common among HIV-exposed uninfected (HEU) children compared to HIV-unexposed uninfected children (HUU). A few studies demonstrated elevated triglyceride levels, lower levels of insulin, and increased blood pressure, oxidative stress, vascular dysfunction, cardiac damage, and myocardial dysfunction among HEU children compared with HUU children.

CONCLUSION

Most findings showed that there were cardio-metabolic health risk factors among HEU children, indicating that maternal exposure to HIV and ART may negatively affect foetal health, which may lead to cardio-metabolic morbidity later in life.

Application of CRISPR-Cas9 technology in diabetes research

Diabetes is a chronic disorder with rapidly increasing prevalence that is a major global issue of our current era. There are two major types of diabetes. Polygenic forms of diabetes include type 1 diabetes (T1D) and type 2 diabetes (T2D) and its monogenic forms are maturity-onset diabetes of the young (MODY) and neonatal diabetes mellitus (NDM). There are no permanent therapeutic approaches for diabetes and current therapies rely on regular administration of various drugs or insulin injection. Recently, gene editing strategies have offered new promise for treating genetic disorders. Targeted genome editing is a fast-growing technology, recruiting programmable nucleases to specifically modify target genomic sequences. These targeted nucleases generate double-strand breaks at target regions in the genome, which induce cellular repair pathways including non-homologous end joining (NHEJ) and homology-directed repair (HDR). Clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) is a novel gene-editing system, permitting precise genome modification. CRISPR/Cas9 has great potential for various applications in diabetic research such as gene screening, generation of diabetic animal models and treatment. In this article, gene-editing strategies are summarized with a focus on the CRISPR/Cas9 approach in diabetes research.

Partners in diabetes epidemic: A global perspective

There is a recent increase in the worldwide prevalence of both obesity and diabetes. In this review we assessed insulin signaling, genetics, environment, lipid metabolism dysfunction and mitochondria as the major determinants in diabetes and to identify the potential mechanism of gut microbiota in diabetes diseases. We searched relevant articles, which have key information from laboratory experiments, epidemiological evidence, clinical trials, experimental models, meta-analysis and review articles, in PubMed, MEDLINE, EMBASE, Google scholars and Cochrane Controlled Trial Database. We selected 144 full-length articles that met our inclusion and exclusion criteria for complete assessment. We have briefly discussed these associations, challenges, and the need for further research to manage and treat diabetes more efficiently. Diabetes involves the complex network of physiological dysfunction that can be attributed to insulin signaling, genetics, environment, obesity, mitochondria and stress. In recent years, there are intriguing findings regarding gut microbiome as the important regulator of diabetes. Valid approaches are necessary for speeding medical advances but we should find a solution sooner given the burden of the metabolic disorder - What we need is a collaborative venture that may involve laboratories both in academia and industries for the scientific progress and its application for the diabetes control.

Exploring shared genetics between maximal oxygen uptake and disease: the HUNT study

Low cardiorespiratory fitness, measured as maximal oxygen uptake (V̇o2max), is associated with all-cause mortality and disease-specific morbidity and mortality and is estimated to have a large genetic component (∼60%). However, the underlying mechanisms explaining the associations are not known, and no association study has assessed shared genetics between directly measured V̇o2max and disease. We believe that identifying the mechanisms explaining how low V̇o2max is related to increased disease risk can contribute to prevention and therapy. We used a phenome-wide association study approach to test for shared genetics. A total of 64,479 participants from the Trøndelag Health Study (HUNT) were included. Genetic variants previously linked to V̇o2max were tested for association with diseases related to the cardiovascular system, diabetes, dementia, mental disorders, and cancer as well as clinical measurements and biomarkers from HUNT. In the total population, three single-nucleotide polymorphisms (SNPs) in and near the follicle-stimulating hormone receptor gene (FSHR) were found to be associated (false discovery rate < 0.05) with serum creatinine levels and one intronic SNP in the Rap-associating DIL domain gene (RADIL) with diabetes type 1 with neurological manifestations. In males, four intronic SNPs in the PBX/knotted homeobox 2 gene (PKNOX2) were found to be associated with endocarditis. None of the association tests in the female population reached overall statistical significance; the associations with the lowest P values included other cardiac conduction disorders, subdural hemorrhage, and myocarditis. The results might suggest shared genetics between V̇o2max and disease. However, further effort should be put into investigating the potential shared genetics between inborn V̇o2max and disease in larger cohorts to increase statistical power.NEW & NOTEWORTHY To our knowledge, this is the first genetic association study exploring how genes linked to cardiorespiratory fitness (CRF) relate to disease risk. By investigating shared genetics, we found indications that genetic variants linked to directly measured CRF also affect the level of blood creatinine, risk of diabetes, and endocarditis. Less certain findings showed that genetic variants of high CRF might cause lower body mass index, healthier HDL cholesterol, and lower resting heart rate.

Gomariz R, Muñoz-Calleja C, Fernández-Ruiz E, González-Álvaro I, Cardeñoso L. Occurrence of SARS-CoV-2 viremia is associated with genetic variants of genes related to COVID-19 pathogenesis

Introduction

SARS-CoV-2 viral load has been related to COVID-19 severity. The main aim of this study was to evaluate the relationship between SARS-CoV-2 viremia and SNPs in genes previously studied by our group as predictors of COVID-19 severity.

Materials and methods

Retrospective observational study including 340 patients hospitalized for COVID-19 in the University Hospital La Princesa between March 2020 and December 2021, with at least one viremia determination. Positive viremia was considered when viral load was above the quantifiable threshold (20 copies/ml). A total of 38 SNPs were genotyped. To study their association with viremia a multivariate logistic regression was performed.

Results

The mean age of the studied population was 64.5 years (SD 16.6), 60.9% patients were male and 79.4% white non-Hispanic. Only 126 patients (37.1%) had at least one positive viremia. After adjustment by confounders, the presence of the minor alleles of rs2071746 (HMOX1; T/T genotype OR 9.9 p < 0.0001), rs78958998 (probably associated with SERPING1 expression; A/T genotype OR 2.3, p = 0.04 and T/T genotype OR 12.9, p < 0.0001), and rs713400 (eQTL for TMPRSS2; C/T + T/T genotype OR 1.86, p = 0.10) were associated with higher risk of viremia, whereas the minor alleles of rs11052877 (CD69; A/G genotype OR 0.5, p = 0.04 and G/G genotype OR 0.3, p = 0.01), rs2660 (OAS1; A/G genotype OR 0.6, p = 0.08), rs896 (VIPR1; T/T genotype OR 0.4, p = 0.02) and rs33980500 (TRAF3IP2; C/T + T/T genotype OR 0.3, p = 0.01) were associated with lower risk of viremia.

Conclusion

Genetic variants in HMOX1 (rs2071746), SERPING1 (rs78958998), TMPRSS2 (rs713400), CD69 (rs11052877), TRAF3IP2 (rs33980500), OAS1 (rs2660) and VIPR1 (rs896) could explain heterogeneity in SARS-CoV-2 viremia in our population.

AST and ALT APRI Scores and Dysglycemia in Saudi Arabia: A Retrospective Population Study

BACKGROUND

Hyperglycemia is a common symptom of numerous conditions, most notably diabetes mellitus and Cushing's syndrome, and the liver plays a pivotal role in the regulation of glucose metabolism. The AST-platelet ratio index (AST APRI score) and ALT-platelet ratio index (ALT APRI score) are novel parameters whose association with circulating glucose levels remains poorly studied.

METHODS

Laboratory data of 14,177 subjects were retrospectively analyzed for the association between AST and ALT APRI scores and fasting blood glucose (FBG) using the Mann-Whitney U and Kruskal-Wallis tests, Spearman's rank correlation coefficient, prevalence and odds ratio (OR) and ROC curve analysis.

RESULTS

AST and ALT APRI scores showed progressive increases with FBG, and the mean FBG was significantly higher in subjects with high AST (104.9 ± 0.33 to 120.8 ± 3.27, p < 0.0001) and ALT (104.7 ± 0.34 to 111.6 ± 1.30, p < 0.0001) APRI scores. However, the AST APRI score but not the ALT APRI score was affected by age and gender. Notably, both elevated AST and ALT APRI scores were more prevalent in hyperglycemic subjects irrespective of gender and were associated with FBG, albeit through mediator variables. Increased AST (OR = 2.55, 95% CI: 1.46-2.06, p < 0.0001) and ALT (OR = 1.73, 95% CI: 1.46-2.06, p < 0.0001) APRI scores carried a significantly higher risk for hyperglycemia. Importantly, the ALT APRI score was superior to that of the AST APRI score in distinguishing hyperglycemic subjects.

CONCLUSIONS

The AST and ALT APRI scores are inexpensive, novel markers of FBG and may serve as supportive evidence in the diagnosis and management of hyperglycemic conditions.

Additive interaction of urinary total arsenic concentrations with being overweight/obesity on the risk of insulin resistance: NHANES 2007-2016

Arsenic exposure has been associated with the risk of diabetes or insulin resistance (IR), which are also related with overweight/obesity. This study aimed to explore the interaction between arsenic exposure and being overweight/obesity on diabetes or IR risk. Data from the National Health and Nutrition Examination Survey (NHANES) in cycles 2007-2016 were used to assess the interaction between arsenic exposure and being overweight/obesity on IR or diabetes risk among adults. Urinary total arsenic concentrations (UTAs) were used as a biomarker for arsenic exposure. The homeostasis model of insulin resistance (HOMA-IR) was calculated to index IR. Survey-weighted logistic regression and restricted cubic spline (RCS) analyses were performed to determine the association and dose-response relationship between UTAs and IR or diabetes risk. Additive interaction was evaluated by relative excess risk due to interaction (RERI), attributable proportion of interaction (AP), and synergy index (S). A total of 3,133 participants were included. The median (interquartile range) UTAs were 6.61 (3.83, 13.95) μg/L. The adjusted OR of IR was 1.40 (95% CI: 0.99-1.97) for UTAs, comparing the highest with the lowest quartile. And significant additive interaction was observed between high UTAs and being overweight/obesity on IR risk (RERI = 2.47, 95% CI: 0.30-4.63; AP = 0.29, 95% CI: 0.07-0.50; S = 1.48, 95% CI: 1.03-2.13). Our results suggested that there might be a potential additive interaction between high UTAs with being overweight/obesity on diabetes risk (AP = 0.27, 95%CI: 0.04-0.51). Our results indicated an additive interaction between arsenic exposure and being overweight/obesity on IR risk.

How do parasitic worms prevent diabetes? An exploration of their influence on macrophage and β-cell crosstalk

Diabetes is the fastest growing chronic disease globally, with prevalence increasing at a faster rate than heart disease and cancer. While the disease presents clinically as chronic hyperglycaemia, two distinct subtypes have been recognised. Type 1 diabetes (T1D) is characterised as an autoimmune disease in which the insulin-producing pancreatic β-cells are destroyed, and type 2 diabetes (T2D) arises due to metabolic insufficiency, in which inadequate amounts of insulin are produced, and/or the actions of insulin are diminished. It is now apparent that pro-inflammatory responses cause a loss of functional β-cell mass, and this is the common underlying mechanism of both T1D and T2D. Macrophages are the central immune cells in the pathogenesis of both diseases and play a major role in the initiation and perpetuation of the proinflammatory responses that compromise β-cell function. Furthermore, it is the crosstalk between macrophages and β-cells that orchestrates the inflammatory response and ensuing β-cell dysfunction/destruction. Conversely, this crosstalk can induce immune tolerance and preservation of β-cell mass and function. Thus, specifically targeting the intercellular communication between macrophages and β-cells offers a unique strategy to prevent/halt the islet inflammatory events underpinning T1D and T2D. Due to their potent ability to regulate mammalian immune responses, parasitic worms (helminths), and their excretory/secretory products, have been examined for their potential as therapeutic agents for both T1D and T2D. This research has yielded positive results in disease prevention, both clinically and in animal models. However, the focus of research has been on the modulation of immune cells and their effectors. This approach has ignored the direct effects of helminths and their products on β-cells, and the modulation of signal exchange between macrophages and β-cells. This review explores how the alterations to macrophages induced by helminths, and their products, influence the crosstalk with β-cells to promote their function and survival. In addition, the evidence that parasite-derived products interact directly with endocrine cells to influence their communication with macrophages to prevent β-cell death and enhance function is discussed. This new paradigm of two-way metabolic conversations between endocrine cells and macrophages opens new avenues for the treatment of immune-mediated metabolic disease.

Early detection system of risk factors for diabetes mellitus type 2 utilization of machine learning-random forest

BACKGROUND

The prevalence of morbidity and mortality for type 2 diabetes mellitus (DM) is still increasing because of changing lifestyles. There needs to be a means of controlling the rise in the incidence of the disease. Many researchers have utilized technological advances such as machine learning for disease prevention and control, especially in noncommunicable conditions. Researchers are, therefore, interested in creating an early detection system for risk factors of type 2 diabetes.

MATERIALS AND METHODS

The study was conducted in February 2022, utilizing secondary surveillance data from Puskesmas Johar Baru, Jakarta, in 2019, 2020, and 2021. Data was analyzed utilizing various bivariate and multivariate statistical methods at 5% significance level and machine learning methods (random forest algorithm) with an accuracy rate of >80%. The data for the three years was cleaned, normalized, and merged.

RESULTS

The final population was 65,533 visits out of the initial data of 196,949, and the final number of DM 2 population was 2766 out of the initial data of 9903. Age, gender, family history of DM, family history of hypertension, hypertension, high blood sugar levels, obesity, and central obesity were significantly associated with type 2 DM. Family history was the strongest risk factor of all independent variables, odds ratio of 15.101. The classification results of feature importance, with an accuracy rate of 84%, obtained in order were age, blood sugar level, and body mass index.

CONCLUSION

Blood sugar level is the most influential factor in the incidence of DM in Puskesmas Johar Baru. In other words, a person with a family history of type 2 diabetes, at unproductive age, of female gender, and of excessive weight can avoid type 2 diabetes if they can regularly maintain their blood sugar levels.

Pharmacological and Pathological Effects of Mulberry Leaf Extract on the Treatment of Type 1 Diabetes Mellitus Mice

This study investigated the pharmacological and pathological effects of aqueous mulberry leaf extract on type 1 diabetes mellitus mice induced with an intraperitoneal injection of streptozotocin (STZ). Diabetic mice were randomized into six groups: control (normal group), model, metformin-treated mice, and high-dose, medium-dose, and low-dose mulberry. The mulberry-treated mice were divided into high-, medium-, and low-dose groups based on the various doses of aqueous mulberry leaf extract during gavage. The efficacy of the six-week intervention was evaluated by measuring levels of fasting plasma glucose, alkaline phosphatase, alanine aminotransferase, aspartate transaminase, blood urea nitrogen, gamma-glutamyl transferase, glucose, high-density lipoprotein cholesterol, lactate dehydrogenase, and low-density lipoprotein cholesterol and recording body weight. Results revealed that mulberry leaf extract exhibited an ideal hypoglycemic effect, and the high-dose group was the most affected. Histology analysis, glycogen staining and apoptosis detection were used to study the extract's effects on the liver, kidney, and pancreatic cells of diabetic mice, enabling the assessment of its effectiveness and complications on a clinical and theoretical basis. It was shown that a certain concentration of aqueous mulberry leaf extract repaired the islet cells of type 1 diabetes mellitus mice, promoting normal insulin secretion. Herein, it was confirmed that mulberry leaf could be used to develop new hypoglycemic drugs or functional health food with broad applicability.

Prevalence of Type 2 Diabetes, Impaired Fasting Glucose, and Diabetes Risk in an Adult and Older North-Eastern Portuguese Population

The aims of this study were (1) to evaluate the prevalence of type 2 diabetes (T2D) in a middle-aged north-eastern Portuguese population, (2) to analyze the prevalence of impaired fasting glucose (IFG), and (3) to assess the risk of T2D in this community-based sample. An exploratory, retrospective, and cross-sectional study was conducted from a total of 6570 individuals aged 18-102 years, among which 3865 were women (57.4 ± 18.1 years) and 2705 were men (60.0 ± 16.8 years). T2D diagnosis, IFG, and the diabetes risk score (low to very high risk) were assessed. The prevalence of T2D in this adult and an older north-eastern Portuguese population was 17.4%. A higher prevalence of T2D was reported in men (22.2%) than in women (14.0%); however, this was without significant differences (p = 0.086). Otherwise, the prevalence of T2D was significantly different among the age groups and increased with age (p < 0.001). Regarding IFG, a higher percentage of cases was observed in men (14.1%) than in women (8.4%) (p < 0.001). The risk of developing T2D in the next 10 years showed an association with sex and age group (p < 0.001) with a small-to-moderate effect (V = 0.1-0.3). Men and the elderly had the highest percentage of cases in the moderate-to-very high-risk bands. The current research confirmed a higher prevalence of T2D, IFG, and diabetes risk than previous Portuguese epidemiological reports. The results also suggest potential prediabetes cases, which should be carefully monitored. The current research adds evidence to the worldwide trend of the increasing prevalence of T2D and intermediate hyperglycemia (i.e., prediabetes).

Triazine herbicides exposure, natural immunoglobulin M antibodies, and fasting plasma glucose changes: Association and mediation analyses in general Chinese urban adults

The effects of triazine herbicides on glucose metabolism remain unclear. In this study, we aimed to assess the associations between serum triazine herbicides and glycemia-related risk indicators in general adults, and to evaluate the mediating role of natural immunoglobulin M antibodies (IgM) in the above associations among uninfected participants. We measured the concentrations of atrazine, cyanazine, and IgM in serum, as well as fasting plasma glucose (FPG), and fasting plasma insulin in 4423 adult participants from the Wuhan-Zhuhai cohort baseline population, enrolled in 2011-2012. Generalized linear models were used to evaluate the associations of serum triazine herbicides with glycemia-related risk indicators, and mediation analyses were performed to evaluate the mediating role of serum IgM in the above associations. The median levels of serum atrazine and cyanazine were 0.0237 μg/L and 0.0786 μg/L, respectively. Our study found significant positive associations of serum atrazine, cyanazine, and Σtriazine with FPG levels, risk of impaired fasting glucose (IFG), abnormal glucose regulation (AGR), and type 2 diabetes (T2D). Additionally, serum cyanazine and Σtriazine were found to be significant positive associated with the homeostatic model assessment of insulin resistance (HOMA-IR) levels. Significant negative linear relationships were observed in associations of serum IgM with serum triazine herbicides, FPG, HOMA-IR levels, the prevalence of T2D, and AGR (P < 0.05). Furthermore, we observed a significant mediating role by IgM in the associations of serum triazine herbicides with FPG, HOMA-IR, and AGR, with the proportions ranging from 2.96% to 7.71%. To ensure the stability of our findings, we conducted sensitivity analyses in normoglycemic participants and found that the association of serum IgM with FPG and the mediating role by IgM remained stable. Our results suggest that triazine herbicides exposure is positively associated with abnormal glucose metabolism, and decreasing serum IgM may partly mediate these associations.

Molecular Genetics of Abnormal Redox Homeostasis in Type 2 Diabetes Mellitus

Numerous studies have shown that oxidative stress resulting from an imbalance between the production of free radicals and their neutralization by antioxidant enzymes is one of the major pathological disorders underlying the development and progression of type 2 diabetes (T2D). The present review summarizes the current state of the art advances in understanding the role of abnormal redox homeostasis in the molecular mechanisms of T2D and provides comprehensive information on the characteristics and biological functions of antioxidant and oxidative enzymes, as well as discusses genetic studies conducted so far in order to investigate the contribution of polymorphisms in genes encoding redox state-regulating enzymes to the disease pathogenesis.

Novel loci for hyperglycemia identified by QTL mapping of longitudinal phenotypes and congenic analysis

We previously reported that four hyperglycemia loci are located on three chromosomes in the Nagoya-Shibata-Yasuda (NSY) mouse model, commonly used to study type 2 diabetes. However, we did not search for hyperglycemia loci across all chromosomes. In this study, we performed quantitative trait loci (QTLs) mapping of longitudinal phenotypes from crosses between NSY (hyperglycemic) and C3H (normoglycemic) mice. We identified four new QTLs for hyperglycemia, namely Nidd5nsy, Nidd6nsy, Nidd1c3h, and Nidd2c3h, on Chromosome 1, 4, 10, and 13, respectively. These QTLs were associated with hyperglycemia in young mice and had attenuated effects in older mice. Nidd5nsy and Nidd6nsy were hyperglycemic with NSY alleles, and Nidd1c3h and Nidd2c3h were hyperglycemic with C3H alleles. We further bred Nidd5nsy congenic mice and demonstrated that Nidd5nsy has a strong effect on hyperglycemia when young, accompanied by insulin resistance and visceral fat accumulation. These results showed that the effects of individual QTLs strengthened or weakened with age, and that the sum of the effects of QTLs captured the age-related deterioration of glucose tolerance in individuals. Our results support the importance of longitudinal phenotypes in the genetic analysis of polygenic traits and have implications for the genetic basis and pathogenesis of type 2 diabetes in humans.

Association between TCF7L2 polymorphism and type 2 diabetes mellitus susceptibility: a case-control study among the Bangladeshi population

BACKGROUND

Diabetes is a severe health burden for Bangladesh. Genetic polymorphism has been reported to be one of the major risk factors for diabetes in various studies. TCF7L2 (transcription factor 7 like 2) transcripts in the human β-cell have effects on β-cell survival, function, and Wnt signaling activation. This study aimed to evaluate the frequency and association of various polymorphisms namely TCF7L2 rs12255372 and rs7903146 among Bangladeshi patients with T2DM (Type 2 Diabetes Mellitus).

METHODS

This case-control study included 300 patients with T2DM and 234 healthy individuals from two health facilities in the Chattogram Division of Bangladesh. Anthropometric measurements were assessed using a self-reported, structured, eight-item questionnaire. The polymorphisms were identified by PCR-RFLP and sequencing method.

RESULTS

A strong association of T2DM with polymorphisms was observed, including rs12255372 (p = 0.0004) and rs7903146 (p = 0.005). It was observed that the risk genotype at rs12255372 was associated with age (p = 0.009), a family history of diabetes (p < 0.0001), and HbA1C (p < 0.0001). Furthermore, it was found that rs12255372 was substantially associated with hypertension (p = 0.03), eye problems (p = 0.01), and neurological abnormalities (p = 0.02).

CONCLUSION

This study postulates that TCF7L2 genetic polymorphism is associated with the risk of T2DM among the studied Bangladeshi population. The findings should be replicated through more studies with a large number of samples and in different populations.

Immunoglobulin G N-glycan, inflammation and type 2 diabetes in East Asian and European populations: a Mendelian randomization study

Background

Immunoglobulin G (IgG) N-glycans have been shown to be associated with the risk of type 2 diabetes (T2D) and its risk factors. However, whether these associations reflect causal effects remain unclear. Furthermore, the associations of IgG N-glycans and inflammation are not fully understood.

Methods

We examined the causal associations of IgG N-glycans with inflammation (C-reactive protein (CRP) and fibrinogen) and T2D using two-sample Mendelian randomization (MR) analysis in East Asian and European populations. Genetic variants from IgG N-glycan quantitative trait loci (QTL) data were used as instrumental variables. Two-sample MR was conducted for IgG N-glycans with inflammation (75,391 and 18,348 participants of CRP and fibrinogen in the East Asian population, 204,402 participants of CRP in the European population) and T2D risk (77,418 cases and 356,122 controls of East Asian ancestry, 81,412 cases and 370,832 controls of European ancestry).

Results

After correcting for multiple testing, in the East Asian population, genetically determined IgG N-glycans were associated with a higher risk of T2D, the odds ratios (ORs) were 1.009 for T2D per 1- standard deviation (SD) higher GP5, 95% CI = 1.003–1.015; P = 0.0019; and 1.013 for T2D per 1-SD higher GP13, 95% CI = 1.006–1.021; P = 0.0005. In the European population, genetically determined decreased GP9 was associated with T2D (OR = 0.899 per 1-SD lower GP9, 95% CI: 0.845–0.957). In addition, there was suggestive evidence that genetically determined IgG N-glycans were associated with CRP in both East Asian and European populations after correcting for multiple testing, but no associations were found between IgG N-glycans and fibrinogen. There was limited evidence of heterogeneity and pleiotropy bias.

Conclusions

Our results provided novel genetic evidence that IgG N-glycans are causally associated with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00543-z.

A Polymorphism in the Gene Encoding Heat Shock Factor 1 (HSF1) Increases the Risk of Type 2 Diabetes: A Pilot Study Supports a Role for Impaired Protein Folding in Disease Pathogenesis

The aim of this pilot study was to investigate whether polymorphisms in the gene encoding heat shock factor 1 (HSF1), a transcriptional activator of molecular chaperones, play a role in the development of type 2 diabetes (T2D). A total of 3229 unrelated individuals of Slavic origin, including 1569 T2D patients and 1660 age- and sex-matched healthy controls, were enrolled for the study. Five common single nucleotide polymorphisms (SNPs) of the HSF1 gene were genotyped using the MassArray-4 system. SNPs rs7838717 (p = 0.002) and rs3757971 (p = 0.005) showed an association with an increased risk of T2D in females with a body mass index ≥ 25 kg/m². The rs7838717T-rs4279640T-rs3757971C and rs7838717T-rs4279640T-rs3757971T haplotypes were associated with increased and decreased disease risk in overweight or obese females, respectively. The associations were replicated as disease susceptibility genes in large cohorts from the UK Biobank (p = 0.008), DIAMANTE (p = 2.7 × 10^-13), and DIAGRAM (p = 0.0004) consortiums. The functional annotation of the SNPs revealed that the rs7838717-T and rs3757971C alleles correlated with increased expression of the genes involved in unfolded protein response. The present study showed, for the first time, that genetic variation of HSF1 is associated with the risk of type 2 diabetes, supporting a role for impaired protein folding in disease pathogenesis.

Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness

The early prediction of diabetes can facilitate interventions to prevent or delay it. This study proposes a diabetes prediction model based on machine learning (ML) to encourage individuals at risk of diabetes to employ healthy interventions. A total of 38,379 subjects were included. We trained the model on 80% of the subjects and verified its predictive performance on the remaining 20%. Furthermore, the performances of several algorithms were compared, including logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), Cox regression, and XGBoost Survival Embedding (XGBSE). The area under the receiver operating characteristic curve (AUROC) of the XGBoost model was the largest, followed by those of the decision tree, logistic regression, and random forest models. For the survival analysis, XGBSE yielded an AUROC exceeding 0.9 for the 2- to 9-year predictions and a C-index of 0.934, while the Cox regression achieved a C-index of 0.921. After lowering the threshold from 0.5 to 0.25, the sensitivity increased from 0.011 to 0.236 for the 2-year prediction model and from 0.607 to 0.994 for the 9-year prediction model, while the specificity showed negligible changes. We developed a high-performance diabetes prediction model that applied the XGBSE algorithm with threshold adjustment. We plan to use this prediction model in real clinical practice for diabetes prevention after simplifying and validating it externally.

The Diagnostic and Therapeutic Role of Circular RNA HIPK3 in Human Diseases

Circular RNAs (circRNAs) are a class of noncoding RNAs with closed-loop of single-stranded RNA structure. Although most of the circRNAs do not directly encode proteins, emerging evidence suggests that circRNAs play a pivotal and complex role in multiple biological processes by regulating gene expression. As one of the most popular circRNAs, circular homeodomain-interacting protein kinase 3 (circHIPK3) has frequently gained the interest of researchers in recent years. Accumulating studies have demonstrated the significant impacts on the occurrence and development of multiple human diseases including cancers, cardiovascular diseases, diabetes mellitus, inflammatory diseases, and others. The present review aims to provide a detailed description of the functions of circHIPK3 and comprehensively overview the diagnostic and therapeutic value of circHIPK3 in these certain diseases.

Importance of Heparan Sulfate Proteoglycans in Pancreatic Islets and β-Cells

β-cells in the islets of Langerhans of the pancreas secrete insulin in response to the glucose concentration in the blood. When these pancreatic β-cells are damaged, diabetes develops through glucose intolerance caused by insufficient insulin secretion. High molecular weight polysaccharides, such as heparin and heparan sulfate (HS) proteoglycans, and HS-degrading enzymes, such as heparinase, participate in the protection, maintenance, and enhancement of the functions of pancreatic islets and β-cells, and the demand for studies on glycobiology within the field of diabetes research has increased. This review introduces the roles of complex glycoconjugates containing high molecular weight polysaccharides and their degrading enzymes in pancreatic islets and β-cells, including those obtained in studies conducted by us earlier. In addition, from the perspective of glycobiology, this study proposes the possibility of application to diabetes medicine.

Impact of land use and food environment on risk of type 2 diabetes: A national study of veterans, 2008-2018

BACKGROUND

Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent.

OBJECTIVE

To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment.

METHODS

The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum.

RESULTS

In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001).

CONCLUSION

Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

Reduced Retinoic Acid Receptor Beta (Rarβ) Affects Pancreatic β-Cell Physiology

Various studies have suggested a link between vitamin A (VA), all-trans-retinol, and type 2 diabetes (T2D). However, the functional role/expression of vitamin A receptors (Rarα, β, and γ) in pancreatic β-cells is not clear yet. Accordingly, we performed a series of bioinformatics, molecular and functional experiments in human islet and INS-1 cells to evaluate the role of Rarβ on insulin secretion and pancreatic β-cell function. Microarray and RNA-sequencing (RAN-seq) expression analysis showed that RARα, β, and γ are expressed in human pancreatic islets. RNA-seq expression of RARβ in diabetic/hyperglycemic human islets (HbA1c ≥ 6.3%) revealed a significant reduction (p = 0.004) compared to nondiabetic/normoglycemic cells (HbA1c < 6%). The expression of RARβ with INS and PDX1 showed inverse association, while positive correlations were observed with INSR and HbA1c levels. Exploration of the T2D knowledge portal (T2DKP) revealed that several genetic variants in RARβ are associated with BMI. The most associated variant is rs6804842 (p = 1.2 × 10−25). Silencing of Rarβ in INS-1 cells impaired insulin secretion without affecting cell viability or apoptosis. Interestingly, reactive oxygen species (ROS) production levels were elevated and glucose uptake was reduced in Rarβ-silenced cells. mRNA expression of Ins1, Pdx1, NeuroD1, Mafa, Snap25, Vamp2, and Gck were significantly (p < 0.05) downregulated in Rarβ-silenced cells. For protein levels, Pro/Insulin, PDX1, GLUT2, GCK, pAKT/AKT, and INSR expression were downregulated considerably (p < 0.05). The expression of NEUROD and VAMP2 were not affected. In conclusion, our results indicate that Rarβ is an important molecule for β-cell function. Hence, our data further support the potential role of VA receptors in the development of T2D.

IPMK modulates hepatic glucose production and insulin signaling

Hepatic glucose production (HGP) is crucial for the maintenance of normal glucose homeostasis. Although hepatic insulin resistance contributes to excessive glucose production, its mechanism is not well understood. Here, we show that inositol polyphosphate multikinase (IPMK), a key enzyme in inositol polyphosphate biosynthesis, plays a role in regulating hepatic insulin signaling and gluconeogenesis both in vitro and in vivo. IPMK-deficient hepatocytes exhibit decreased insulin-induced activation of Akt-FoxO1 signaling. The expression of messenger RNA levels of phosphoenolpyruvate carboxykinase 1 (Pck1) and glucose 6-phosphatase (G6pc), key enzymes mediating gluconeogenesis, are increased in IPMK-deficient hepatocytes compared to wild type hepatocytes. Importantly, re-expressing IPMK restores insulin sensitivity and alleviates glucose production in IPMK-deficient hepatocytes. Moreover, hepatocyte-specific IPMK deletion exacerbates hyperglycemia and insulin sensitivity in mice fed a high-fat diet, accompanied by an increase in HGP during pyruvate tolerance test and reduction in Akt phosphorylation in IPMK deficient liver. Our results demonstrate that IPMK mediates insulin signaling and gluconeogenesis and may be potentially targeted for treatment of diabetes.

Pathogenesis of Type 1 Diabetes: Established Facts and New Insights

Type 1 diabetes (T1D) is an autoimmune disease characterized by the T-cell-mediated destruction of insulin-producing β-cells in pancreatic islets. It generally occurs in genetically susceptible individuals, and genetics plays a major role in the development of islet autoimmunity. Furthermore, these processes are heterogeneous among individuals; hence, different endotypes have been proposed. In this review, we highlight the interplay between genetic predisposition and other non-genetic factors, such as viral infections, diet, and gut biome, which all potentially contribute to the aetiology of T1D. We also discuss a possible active role for β-cells in initiating the pathological processes. Another component in T1D predisposition is epigenetic influences, which represent a link between genetic susceptibility and environmental factors and may account for some of the disease heterogeneity. Accordingly, a shift towards personalized therapies may improve the treatment results and, therefore, result in better outcomes for individuals in the long-run. There is also a clear need for a better understanding of the preclinical phases of T1D and finding new predictive biomarkers for earlier diagnosis and therapy, with the final goal of reverting or even preventing the development of the disease.

Exploring the relationship between vitamin D and leptin hormones in type 2 diabetes mellitus patients from Kuwait

BACKGROUND

Type 2 diabetes mellitus (T2DM) and obesity are prevalent in Kuwait. Vitamin D (VD) deficiency and leptin resistance are risk factors for both disorders. A correlation between the two risk factors has been suggested albeit inconsistently reported. Our objective was to determine the effect and association of VD and leptin levels and their related common variants with T2DM.

METHODS

This case-control study included 203 Kuwaiti T2DM patients and 162 healthy Kuwaiti controls. Leptin and VD levels were measured using enzyme linked immunosorbent assays. Genotyping of LEP rs7799039, LEPR rs1137101, VDR rs2228570 and rs731236 was performed using Taqman genotyping assays.

RESULTS

Leptin levels were higher in T2DM patients than controls, but vitamin D levels did not differ. No correlation was found between the levels of the two hormones. VDR rs731236G associated with T2DM risk (Odds ratio 1.66, p=0.0008). VDR haplotype analysis revealed GG/AA, GA/AA or GG/AG to associate with T2DM risk (p=0.01) and increased risk of diabetic neuropathy (p=0.002). VDR rs2228570GG associated with leptin levels in T2DM (p=0.01). Effect of LEP rs7799039 on leptin (p=0.01) and VD levels (p=0.02) was only evident in healthy controls.

CONCLUSIONS

VDR rs731236G is associated with T2DM risk in Kuwait, and a VDR haplotype of a less active, low expressing VDR is associated with T2DM and diabetic neuropathy risk. Common variants in leptin and VD related genes appear to mediate the suggested positive correlation of both hormones however their influence is disrupted in T2DM.

Gene–Environment Interaction on Type 2 Diabetes Risk among Chinese Adults Born in Early 1960s

Background: Gene–environment interactions on type 2 diabetes (T2D) risk are studied little among Chinese adults. Aim: This study aimed to explore the interactions among Chinese adults born in early 1960s. Methods: The interaction of single nucleotide polymorphisms (SNPs) and environmental factors on T2D risk were analyzed by multiple linear or logistic regression models, and in total 2216 subjects were included with the age of 49.7 ± 1.5 years. Results: High dietary intake increased the effects of rs340874 on impaired fasting glucose (IFG), rs5015480, rs7612463 on T2D (OR = 2.27, 2.37, 11.37, respectively), and reduced the effects of rs7172432 on IFG, rs459193 on impaired glucose tolerance (IGT) (OR = 0.08, 0.28, respectively). The associations between rs4607517 and T2D, rs10906115 and IGT, rs4607103, rs5015480 and IFG could be modified by drinking/smoking (OR = 2.28, 0.20, 3.27, 2.58, respectively). Physical activity (PA) interacted with rs12970134, rs2191349, rs4607517 on T2D (OR = 0.39, 3.50, 2.35, respectively), rs2796441 and rs4607517 on IGT (OR = 0.42, 0.33, respectively), and rs4430796, rs5215, and rs972283 on IFG (OR = 0.39, 3.05, 7.96, respectively). Significant interactions were identified between socioeconomic status and rs10830963, rs13266634 on T2D (OR = 0.41, 0.44, respectively), rs1470579 and rs2796441 on IGT (OR = 2.13, 2.37, respectively), and rs7202877 and rs7612463 on IFG (OR = 5.64, 9.18, respectively). Conclusion: There indeed existed interactions between environmental factors and genetic variants on T2D risk among Chinese adults.

Twelve Variants Polygenic Score for Low-Density Lipoprotein Cholesterol Distribution in a Large Cohort of Patients With Clinically Diagnosed Familial Hypercholesterolemia With or Without Causative Mutations

Background

A significant proportion of individuals clinically diagnosed with familial hypercholesterolemia (FH), but without any disease‐causing mutation, are likely to have polygenic hypercholesterolemia. We evaluated the distribution of a polygenic risk score, consisting of 12 low‐density lipoprotein cholesterol (LDL‐C)‐raising variants (polygenic LDL‐C risk score), in subjects with a clinical diagnosis of FH.

Methods and Results

Within the Lipid Transport Disorders Italian Genetic Network (LIPIGEN) study, 875 patients who were FH‐mutation positive (women, 54.75%; mean age, 42.47±15.00 years) and 644 patients who were FH‐mutation negative (women, 54.21%; mean age, 49.73±13.54 years) were evaluated. Patients who were FH‐mutation negative had lower mean levels of pretreatment LDL‐C than patients who were FH‐mutation positive (217.14±55.49 versus 270.52±68.59 mg/dL, P<0.0001). The mean value (±SD) of the polygenic LDL‐C risk score was 1.00 (±0.18) in patients who were FH‐mutation negative and 0.94 (±0.20) in patients who were FH‐mutation positive (P<0.0001). In the receiver operating characteristic analysis, the area under the curve for recognizing subjects characterized by polygenic hypercholesterolemia was 0.59 (95% CI, 0.56–0.62), with sensitivity and specificity being 78% and 36%, respectively, at 0.905 as a cutoff value. Higher mean polygenic LDL‐C risk score levels were observed among patients who were FH‐mutation negative having pretreatment LDL‐C levels in the range of 150 to 350 mg/dL (150–249 mg/dL: 1.01 versus 0.91, P<0.0001; 250–349 mg/dL: 1.02 versus 0.95, P=0.0001). A positive correlation between polygenic LDL‐C risk score and pretreatment LDL‐C levels was observed among patients with FH independently of the presence of causative mutations.

Conclusions

This analysis confirms the role of polymorphisms in modulating LDL‐C levels, even in patients with genetically confirmed FH. More data are needed to support the use of the polygenic score in routine clinical practice.

Deep Resequencing of 9 Candidate Genes Identifies a Role for ARAP1 and IGF2BP2 in Modulating Insulin Secretion Adjusted for Insulin Resistance in Obese Southern Europeans

Type 2 diabetes is characterized by impairment in insulin secretion, with an established genetic contribution. We aimed to evaluate common and low-frequency (1–5%) variants in nine genes strongly associated with insulin secretion by targeted sequencing in subjects selected from the extremes of insulin release measured by the disposition index. Collapsing data by gene and/or function, the association between disposition index and nonsense variants were significant, also after adjustment for confounding factors (OR = 0.25, 95% CI = 0.11–0.59, p = 0.001). Evaluating variants individually, three novel variants in ARAP1, IGF2BP2 and GCK, out of eight reaching significance singularly, remained associated after adjustment. Constructing a genetic risk model combining the effects of the three variants, only carriers of the ARAP1 and IGF2BP2 variants were significantly associated with a reduced probability to be in the lower, worst, extreme of insulin secretion (OR = 0.223, 95% CI = 0.105–0.473, p < 0.001). Observing a high number of normal glucose tolerance between carriers, a regression posthoc analysis was performed. Carriers of genetic risk model variants had higher probability to be normoglycemic, also after adjustment (OR = 2.411, 95% CI = 1.136–5.116, p = 0.022). Thus, in our southern European cohort, nonsense variants in all nine candidate genes showed association with better insulin secretion adjusted for insulin resistance, and we established the role of ARAP1 and IGF2BP2 in modulating insulin secretion.

Precision Medicine in Patients with Differential Diabetic Phenotypes: Novel Opportunities from Network Medicine

INTRODUCTION

Diabetes mellitus (DM) comprises differential clinical phenotypes ranging from rare monogenic to common polygenic forms, such as type 1 (T1DM), type 2 (T2DM), and gestational diabetes, which are associated with cardiovascular complications. Also, the high- -risk prediabetic state is rising worldwide, suggesting the urgent need for early personalized strategies to prevent and treat a hyperglycemic state.

OBJECTIVE

We aim to discuss the advantages and challenges of Network Medicine approaches in clarifying disease-specific molecular pathways, which may open novel ways for repurposing approved drugs to reach diabetes precision medicine and personalized therapy.

CONCLUSION

The interactome or protein-protein interactions (PPIs) is a useful tool to identify subtle molecular differences between precise diabetic phenotypes and predict putative novel drugs. Despite being previously unappreciated as T2DM determinants, the growth factor receptor-bound protein 14 (GRB14), calmodulin 2 (CALM2), and protein kinase C-alpha (PRKCA) might have a relevant role in disease pathogenesis. Besides, in silico platforms have suggested that diflunisal, nabumetone, niflumic acid, and valdecoxib may be suitable for the treatment of T1DM; phenoxybenzamine and idazoxan for the treatment of T2DM by improving insulin secretion; and hydroxychloroquine reduce the risk of coronary heart disease (CHD) by counteracting inflammation. Network medicine has the potential to improve precision medicine in diabetes care and enhance personalized therapy. However, only randomized clinical trials will confirm the clinical utility of network- oriented biomarkers and drugs in the management of DM.

Multi-Omics Comparison of the Spontaneous Diabetes Mellitus and Diet-Induced Prediabetic Macaque Models

The prevalence of diabetes mellitus has been increasing for decades worldwide. To develop safe and potent therapeutics, animal models contribute a lot to the studies of the mechanisms underlying its pathogenesis. Dietary induction using is a well-accepted protocol in generating insulin resistance and diabetes models. In the present study, we reported the multi-omics profiling of the liver and sera from both peripheral blood and hepatic portal vein blood from Macaca fascicularis that spontaneously developed Type-2 diabetes mellitus with a chow diet (sDM). The other two groups of the monkeys fed with chow diet and high-fat high-sugar (HFHS) diet, respectively, were included for comparison. Analyses of various omics datasets revealed the alterations of high consistency. Between the sDM and HFHS monkeys, both the similar and unique alterations in the lipid metabolism have been demonstrated from metabolomic, transcriptomic, and proteomic data repeatedly. The comparison of the proteome and transcriptome confirmed the involvement of fatty acid binding protein 4 (FABP4) in the diet-induced pathogenesis of diabetes in macaques. Furthermore, the commonly changed genes between spontaneous diabetes and HFHS diet-induced prediabetes suggested that the alterations in the intra- and extracellular structural proteins and cell migration in the liver might mediate the HFHS diet induction of diabetes mellitus.

Circulating expression levels of CircHIPK3 and CDR1as circular-RNAs in type 2 diabetes patients

BACKGROUND

Recent investigations suggested that deregulated levels of Circular RNAs (circRNAs) could be associated with type 2 diabetes mellitus (T2DM) pathogenesis. Accordingly, this study aimed to determine the expression levels of circulating CircHIPK3, CDR1as and their correlation with biochemical parameters in patients with T2DM, pre-diabetes and control subjects.

METHODS AND RESULTS

The expression of circRNAs in peripheral blood was determined using QRT-PCR in 70 patients with T2DM, 60 pre-diabetes and in 69 age and sex matched healthy controls. Moreover, bioinformatics tools were applied to explore and predict the potential interactions between circRNAs and other non-coding RNAs (ncRNAs). Our analysis revealed that the expression level of CircHIPK3 was significantly elevated in T2DM patients compared to healthy participants (P < 0.001) and pre-diabetes subjects (P = 0.018). In addition, ROC analysis suggested that at the cutoff value of 0.24 and the sensitivity and specificity of 50% and 88.4%, respectively, CircHIPK3 could distinguish between T2DM patients and control subjects. Furthermore, it was observed that the expression level of CDR1as is higher in pre-diabetic individuals than healthy individuals (P = 0.004). Finally, Spearman correlation analysis showed that there was a significant correlation between CircHIPK3 and CDR1as expression levels and clinical and anthropometrical parameters such as BMI, systolic and diastolic blood pressure, HbA1c and fasting blood glucose (P < 0.005).

CONCLUSIONS

The data of this study provided evidence that the expression levels of CircHIPK3, CDR1as increased in T2DM and pre-diabetes subjects, respectively.

Ethnicity Differences in the Association of UCP1-3826A/G, UCP2-866G/A and Ala55Val, and UCP3-55C/T Polymorphisms with Type 2 Diabetes Mellitus Susceptibility: An Updated Meta-Analysis

Background

The relationship between uncoupling protein (UCP) 1-3 polymorphisms and susceptibility to type 2 diabetes mellitus (T2DM) has been extensively studied, while conclusions remain contradictory. Thus, we performed this meta-analysis to elucidate whether the UCP1-3826A/G, UCP2-866G/A, Ala55Val, and UCP3-55C/T polymorphisms are associated with T2DM.

Methods

Eligible studies were searched from PubMed, Cochrane Library, and Web of Science database before 12 July 2020. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated to evaluate the strength of the association. Heterogeneity analysis, subgroup analysis, sensitivity analysis, and publication bias were also performed.

Results

A total of 38 case-control studies were included in this meta-analysis. The overall results revealed significant association between T2DM and the UCP2 Ala55Val polymorphism (recessive model: OR = 1.25, 95% CI 1.12-1.40, P < 0.01; homozygous model: OR = 1.33, 95% CI 1.03-1.72, P = 0.029, respectively). In subgroup analysis stratified by ethnicity, T2DM risk was increased with the UCP2 Ala55Val polymorphism (allele model: OR = 1.17, 95% CI 1.02-1.34, P = 0.023; recessive model: OR = 1.28, 95% CI 1.13-1.45, P < 0.01; homozygous model: OR = 1.39, 95% CI 1.05-1.86, P = 0.023, respectively), while decreased with the UCP2-866G/A polymorphism in Asians (dominant model: OR = 0.86, 95% CI 0.74-1.00, P = 0.045).

Conclusions

Our results demonstrate that the UCP2-866G/A polymorphism is protective against T2DM, while the UCP2 Ala55Val polymorphism is susceptible to T2DM in Asians.

CTNNA3 genetic polymorphism may be a new genetic signal of type 2 diabetes in the Chinese Han population: a case control study

BACKGROUND

Type 2 Diabetes (T2D) is the result of a combination of genes and environment. The identified genetic loci can only explain part of T2D risk. Our study is aimed to explore the association between CTNNA3 single nucleotide polymorphisms (SNPs) and T2D risk.

METHODS

We conducted a 'case-control' study among 1002 Chinese Han participants. Four candidate SNPs of CTNNA3 were selected (rs10822745 C/T, rs7920624 A/T, rs2441727 A/G, rs7914287 A/G), and logistic regression analysis was used to evaluate the association between candidate SNPs and T2D risk. We used single factor analysis of variance to analyze the differences of clinical characteristics among different genotypes. In this study, haplotype analysis was conducted by plink1.07 and Haploview software and linkage disequilibrium (LD) was calculated. The interaction of candidate SNPs in T2D risk was evaluated by multi-factor dimensionality reduction (MDR). Finally, we conducted a false-positive report probability (FPRP) analysis to detect whether the significant findings were just chance or noteworthy observations.

RESULTS

The results showed that CTNNA3-rs7914287 was a risk factor for T2D ('T': OR = 1.33, p = 0.003; 'TT': OR = 2.21, p = 0.001; 'TT' (recessive): OR = 2.09, p = 0.001; Log-additive: OR = 1.34, p = 0.003). The results of subgroup analysis showed that rs7914287 was significantly associated with the increased risk of T2D among participants who were older than 60 years, males, smoking, drinking, or BMI > 24. We also found that rs2441727 was associated with reducing the T2D risk among participants who were older than 60 years, smoking, or drinking. In addition, rs7914287 was associated with T2D patients with no retinal degeneration; rs10822745 and rs7920624 were associated with the course of T2D patients. High density lipoprotein levels had significant differences under different genotypes of rs10822745. Under the different genotypes of rs7914287, the levels of aspartate aminotransferase, alanine aminotransferase and gamma-glutamyltransferase were also significantly different.

CONCLUSION

We found that CTNNA3 genetic polymorphisms can be used as a new genetic signal of T2D risk in Chinese Han population. Especially, CTNNA3-rs7914287 showed an outstanding and significant association with T2D risk in both overall analysis and subgroup analysis.

Molecular mechanisms underlying hepatitis C virus infection-related diabetes

Diabetes is a noncommunicable widespread disease that poses the risk of severe complications in patients, with certain complications being life-threatening. Hepatitis C is an infectious disease that mainly causes liver damage, which is also a profound threat to human health. Hepatitis C virus (HCV) infection has many extrahepatic manifestations, including diabetes. Multiple mechanisms facilitate the strong association between HCV and diabetes. HCV infection can affect the insulin signaling pathway in liver and pancreatic tissue and change the profiles of circulating microRNAs, which may further influence the occurrence and development of diabetes. This review describes how HCV infection causes diabetes and discusses the current research progress with respect to HCV infection-related diabetes.

Is there a relationship between the prevalence of autoimmune thyroid disease and diabetic kidney disease?

Autoimmune thyroid disease (AITD) is more common among diabetes mellitus (DM) patients and may impact its microvascular complications. The present study aimed to assess the relationship between AITD and the prevalence of diabetic kidney disease (DKD) in patients with diabetes mellitus type 1 (DM1). Anthropometric parameters, parameters of metabolic control of DM, thyreometabolic status, and the UACR were assessed. DKD was diagnosed if patients' UACR level was ≥30 mg/g or eGFR level was <60 mL/min. This study involved 144 patients with DM1 aged 36.2 ± 11.7 years: 49 men and 95 women. Significant differences in creatinine, eGFR, and UACR levels were found in patients with DKD. fT3 concentration was significantly lower among DKD patients. A significantly higher probability of DKD was found in DM1 patients with lower fT3 levels. Patients with DM1 and AITD had significantly lower creatinine levels than the control group. However, the study did not show any significant relationship between AITD and the occurrence of DKD in patients with DM1. Significantly lower fT3 concentrations in DKD patients may be caused by metabolic disorders in the course of DKD and require further cohort studies in a larger population of patients with DM1 and AITD.

Emerging roles of rare and low-frequency genetic variants in type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) is defined as an autoimmune disorder and has enormous complexity and heterogeneity. Although its precise pathogenic mechanisms are obscure, this disease is widely acknowledged to be precipitated by environmental factors in individuals with genetic susceptibility. To date, the known susceptibility loci, which have mostly been identified by genome-wide association studies, can explain 80%–85% of the heritability of T1DM. Researchers believe that at least a part of its missing genetic component is caused by undetected rare and low-frequency variants. Most common variants have only small to modest effect sizes, which increases the difficulty of dissecting their functions and restricts their potential clinical application. Intriguingly, many studies have indicated that rare and low-frequency variants have larger effect sizes and play more significant roles in susceptibility to common diseases, including T1DM, than common variants do. Therefore, better recognition of rare and low-frequency variants is beneficial for revealing the genetic architecture of T1DM and for providing new and potent therapeutic targets for this disease. Here, we will discuss existing challenges as well as the great significance of this field and review current knowledge of the contributions of rare and low-frequency variants to T1DM.

Alzheimer's Disease and Diabetes: Role of Diet, Microbiota and Inflammation in Preclinical Models

Alzheimer's disease (AD) is the most common cause of dementia. Epidemiological studies show the association between AD and type 2 diabetes (T2DM), although the mechanisms are not fully understood. Dietary habits and lifestyle, that are risk factors in both diseases, strongly modulate gut microbiota composition. Also, the brain-gut axis plays a relevant role in AD, diabetes and inflammation, through products of bacterial metabolism, like short-chain fatty acids. We provide a comprehensive review of current literature on the relation between dysbiosis, altered inflammatory cytokines profile and microglia in preclinical models of AD, T2DM and models that reproduce both diseases as commonly observed in the clinic. Increased proinflammatory cytokines, such as IL-1β and TNF-α, are widely detected. Microbiome analysis shows alterations in Actinobacteria, Bacteroidetes or Firmicutes phyla, among others. Altered α- and β-diversity is observed in mice depending on genotype, gender and age; therefore, alterations in bacteria taxa highly depend on the models and approaches. We also review the use of pre- and probiotic supplements, that by favoring a healthy microbiome ameliorate AD and T2DM pathologies. Whereas extensive studies have been carried out, further research would be necessary to fully understand the relation between diet, microbiome and inflammation in AD and T2DM.

Level of and Related Factors to Diabetes Awareness among Diabetic Adults by Gender: Based on Data from the Korean National Health and Nutrition Examination Survey

PURPOSE

This study aimed to determine the level of awareness about diabetes mellitus (DM) and identify the associated factors among diabetic adults in Korea by sex, using data from most recent nationwide representative survey.

METHODS

Secondary data analysis was conducted using data obtained from the Korean National Health and Nutrition Examination Survey VII (2016-2018). In total, 2,026 participants (1,049 men, 977 women) aged ≥30 years with DM were included. Data were analyzed using a complex sample analysis considering the combined sampling weight for 3 years. Odds ratios and 95% confidence intervals were calculated using stepwise multiple logistic regression analysis to identify the association between DM awareness (DA) and sociodemographic and health-related factors.

RESULTS

Researchers observed that 60.2% of men and 68.4% of women had DA. DA levels in both men and women were higher in those who were older, less educated, had normal weight, had hypertension and/or dyslipidemia, and had a family history of DM than in their counterparts. Having undergone a health screening in the past 2 years was associated with DA levels in men, whereas glycated hemoglobin levels of 5.7-6.4% were associated with higher DA levels in women.

CONCLUSION

The level of DA is unsatisfactory. Although the DA level is slightly higher in women than in men, it needs to be improved regardless of gender. Most of the factors associated with DA levels are similar in both men and women. Nurses in the community setting should provide health education, conduct campaigns, and promote referral to medical services by targeting the high-risk groups with lower DA identified in this study.

Epigenetic changes caused by diabetes and their potential role in the development of periodontitis

Aims/Introduction

Periodontal disease, a chronic inflammation induced by bacteria, is closely linked with diabetes mellitus. Many complications associated with diabetes are related to epigenetic changes. However, the exact epigenetic changes whereby diabetes affects periodontal disease remain largely unknown. Thus, we sought to investigate the role of diabetes‐dependent epigenetic changes of gingival tissue in the susceptibility to periodontal disease.

Materials and Methods

We studied the effect of streptozotocin‐induced diabetes in minipigs on gingival morphological and epigenetic tissue changes. Accordingly, we randomly divided six minipigs into two groups: streptozotocin‐induced diabetes group, n = 3; and non‐diabetes healthy control group, n = 3. After 85 days, all animals were killed, and gingival tissue was collected for histology, deoxyribonucleic acid methylation analysis and immunohistochemistry.

Results

A diabetes mellitus model was successfully created, as evidenced by significantly increased blood glucose levels, reduction of pancreatic insulin‐producing β‐cells and histopathological changes in the kidneys. The gingival tissues in the diabetes group presented acanthosis of both gingival squamous epithelium and sulcular/junctional epithelium, and a significant reduction in the number and length of rete pegs. Deoxyribonucleic acid methylation analysis showed a total of 1,163 affected genes, of which 599 and 564 were significantly hypermethylated and hypomethylated, respectively. Immunohistochemistry staining showed that the hypomethylated genes – tumor necrosis factor‐α and interleukin‐6 – were positively expressed under the junctional epithelium area in the diabetes group.

Conclusions

Diabetes mellitus induces morphological and epigenetic changes in periodontal tissue, which might contribute to the increased susceptibility of periodontal diseases in patients with diabetes.

A benchmark dose analysis for urinary cadmium and type 2 diabetes mellitus

Cadmium (Cd) is a heavy metal referred to as one of the environmental endocrine disruptors. The dose-dependent association between Cd and type 2 diabetes mellitus (T2DM) has been elucidated, but the corresponding threshold has not been established. To evaluate the urinary Cd levels associated with T2DM, we perform a benchmark dose (BMD) analysis based on data from the 1999-2006 National Health and Nutrition Examination Survey (NHANES). Weighted datasets were generated by the inverse probability of treatment weighting analysis to develop the robustness of our analysis. We inferred a strong positive association between urinary Cd and T2DM in unweighted and weighted populations. BMD and its low limit (BMDL) estimates for 5% benchmark responses (BMR) was 0.297 (0.198) and 0.190 (0.178) μg/g creatinine for each population, respectively. The sensitivity analysis by race, followed by weight of sum method showed similar estimates of urinary Cd level for the risk of developing T2DM, which are rather low and far less than those for the renal or bone disease development risk. This indicates that T2DM can be a sensitive outcome of Cd exposure and therefore should be taken into account in the development of standard regulatory limits for safe exposure to Cd.

Vitamin A levels are decreased but not influenced by glucose- or lipid-lowering medications in subjects with type 2 diabetes

Background and aim

Type 2 diabetes (T2D) is a complex polygenic disease with unclear mechanisms. Clinical studies on the association of vitamin A with T2D in humans are still controversial. Herein, we aimed to investigate the plasma levels of vitamin A, predictor factors, and its correlations with clinical phenotypes in Emirati population. The effect of glucose-and lipid-lowering medications on vitamin A levels was also studied.

Methods

A cross-sectional cohort comprised 158 T2D-subjects and 90 healthy controls were recruited from the United Arab Emirates National Diabetes Study (UAEDIAB). All anthropometric, clinical, and biomedical measurements were collected. Plasma levels of vitamin A were determined using ELISA assay.

Results

Levels of vitamin A were significantly lower in T2D-subjects compared to healthy control (p < 0.01). Vitamin A levels were unaffected by gender base and inversely correlated with age, fasting blood glucose (FBG), glycated hemoglobin (HbA1c), waist circumference, triglycerides, and body mass index (BMI). Regression analysis revealed that HbA1c and age are predictors for vitamin A. Intake of glucose- or lipid-lowering medications showed no effect on vitamin A levels.

Conclusion

HbA1c and age are predictors for low levels of vitamin A among Emirati-T2D subjects. No influence of glucose and lipid-lowering medications on the plasma levels of vitamin A.