The Genetic Epidemiology of Type 2 Diabetes: Opportunities for Health Translation

Single-cell transcriptome sequencing revealed the metabolic changes and microenvironment changes of cardiomyocytes induced by diabetes

PURPOSE

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels. This study aimed to analyze the changes underlying heterogeneities and communication properties of CMs in diabetes mellitus (DM).

METHODS

GSE213337 dataset was retrieved from NCBI Gene Expression Omnibus, containing the single-cell RNA sequencing data of hearts from the control and streptozotocin-induced diabetic mice. GSEA and GSVA were used to explore the function enrichment of DEGs in CM. Cell communication analysis was carried out to study the altered signals and significant ligand-receptor interactions.

RESULTS

Seventeen cell types were identified between DM and the controls. The increasing ratio of CM suggested the occurrence of diabetes induces potential pathological changes of CM proliferation. A total of 1144 DEGs were identified in CM. GSEA and GSVA analysis indicated the enhancing lipid metabolism involving in DM. The results of cell communication analysis suggested that high glucose activated the ability of CM receiving fibroblast and LEC, while inhibited the capacity of receiving ECC and pericyte. Furthermore, GAS and ANGPTL were significantly decreased under DM, which was consistent with the results of GSEA and GSVA. Finally, the ligand-receptor interactions such as vegfc-vegfr2, angptl1 were changes in CM.

CONCLUSIONS

The CM showed the significant heterogeneities in DM, which played an important role in myocardial fibrosis induce by hyperglycemia.

Perspectives on genetic studies of type 2 diabetes from the genome-wide association studies era to precision medicine

Genome-wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS until 2023. From 2018 to 2022, hundreds of type 2 diabetes susceptibility loci with smaller effect sizes were identified through large-scale GWAS with sample sizes of 200,000 to >1 million. The clinical translation of genetic information for type 2 diabetes includes the development of novel therapeutics and risk predictions. Although drug discovery based on loci identified in GWAS remains challenging owing to the difficulty of functional annotation, global efforts have been made to identify novel biological mechanisms and therapeutic targets by applying multi-omics approaches or searching for disease-associated coding variants in isolated founder populations. Polygenic risk scores (PRSs), comprising up to millions of associated variants, can identify individuals with higher disease risk than those in the general population. In populations of European descent, PRSs constructed from base GWAS data with a sample size of approximately 450,000 have predicted the onset of diseases well. However, European GWAS-derived PRSs have limited predictive performance in non-European populations. The predictive accuracy of a PRS largely depends on the sample size of the base GWAS data. The results of GWAS meta-analyses for multi-ethnic groups as base GWAS data and cross-population polygenic prediction methodology have been applied to establish a universal PRS applicable to small isolated ethnic populations.

High-throughput sequencing reveals differences in microbial community structure and diversity in the conjunctival tissue of healthy and type 2 diabetic mice

BACKGROUND

To investigate the differences in bacterial and fungal community structure and diversity in conjunctival tissue of healthy and diabetic mice.

METHODS

RNA-seq assays and high-throughput sequencing of bacterial 16 S rDNA and fungal internal transcribed spacer (ITS) gene sequences were used to identify differentially expressed host genes and fungal composition profiles in conjunctival tissues of diabetic BKS-db/db mice and BKS (control) mice. Functional enrichment analysis of differentially expressed genes and the correlation between the relative abundance of bacterial and fungal taxa in the intestinal mucosa were also performed.

RESULTS

Totally, 449 differential up-regulated genes and 1,006 down-regulated genes were identified in the conjunctival tissues of diabetic mice. The differentially expressed genes were mainly enriched in metabolism-related functions and pathways. A decrease in conjunctival bacterial species diversity and abundance in diabetic mice compared to control mice. In contrast, fungal species richness and diversity were not affected by diabetes. The microbial colonies were mainly associated with cellular process pathways regulating carbohydrate and lipid metabolism, as well as cell growth and death. Additionally, some interactions between bacteria and fungi at different taxonomic levels were also observed.

CONCLUSION

The present study revealed significant differences in the abundance and composition of bacterial and fungal communities in the conjunctival tissue of diabetic mice compared to control mice. The study also highlighted interactions between bacteria and fungi at different taxonomic levels. These findings may have implications for the diagnosis and treatment of diabetes.

RNA therapeutics for treatment of diabetes

Diabetes is an ongoing global problem as it affects health of more than 537 million people around the world. Diabetes leaves many serious complications that affect patients and can cause death if not detected and treated promptly. Some of the complications of diabetes include impaired vascular system, increased risk of stroke, neurological diseases that cause pain and numbness, diseases related to the retina leading to blindness, and other complications affecting kidneys, heart failure, muscle weakness, muscle atrophy. All complications of diabetes seriously affect the health of patients. Recently, gene therapy has emerged as a viable treatment strategy for various diseases. DNA and RNA are among the target molecules that can change the structure and function of proteins and are effective methods of treating diseases, especially genetically inherited diseases. RNA therapeutics has attracted deep interest as it has been approved for application in the treatment of functional system disorders such as spinal muscular atrophy, and muscular dystrophy. In this review, we cover the types of RNA therapies considered for treatment of diabetes. In particular, we delve into the mechanism of action of RNA therapies for diabetes, and studies involving testing of these RNA therapies. Finally, we have highlighted the limitations of the current understanding in the mechanism of action of RNA therapies.

TCF7L2 and FTO Polymorphisms Are Associated with Type 2 Diabetes Mellitus Risk in Kuwait

OBJECTIVE

Despite the high prevalence of type 2 diabetes mellitus (T2DM) and obesity in the region, reports are limited on genetic risk factors associated with T2DM risk in Kuwait. Our aim was to investigate the association of reported FTO and TCF7L2 T2DM genetic risk variants in Kuwaiti T2DM patients.

SUBJECTS AND METHODS

FTO rs9939609 and TCF7L2 rs7903146 variants were genotyped in 203 T2DM patients and 162 healthy controls. Data analysis included Fisher's exact test, χ2 test, and linear and logistic regression analyses.

RESULTS

FTO rs9939609 (AA) and TCF7L2 rs7903146 (TT) genotypes associated with T2DM risk among Kuwaitis (p = 0.0016 and p < 0.0001; respectively). Both variants had the strongest association with T2DM risk in an autosomal recessive inheritance model (FTO rs9939609A: odds ratio (OR) 2.136, 95% confidence interval (CI): 1.21-3.67, p = 0.0075; TCF7L2 rs7903146T: OR 3.283, 95% CI: 1.92-5.76, p < 0.0001). Moreover, rs7903146T associated with risk of peripheral neuropathy (β = 0.735, 95% CI: 0.514-0.96, p < 0.001) and risk of myocardial infarction (β = 0.36, 95% CI: 0.024-0.7, p = 0.036) in T2DM patients.

CONCLUSION

The increased susceptibility of Kuwaitis to T2DM is influenced by the same common genetic factors found in other T2DM populations. Further investigations of other T2DM genetic risk factors in Kuwait should refine and further support the clinical utility of a genetic risk score in predicting T2DM risk in a high-risk population such as Kuwait.

Exploring the Effects of Cyanidin-3-O-Glucoside on Type 2 Diabetes Mellitus: Insights into Gut Microbiome Modulation and Potential Antidiabetic Benefits

Berries and their functional components have been put forward as an alternative to pharmacological treatments of type 2 diabetes mellitus (T2DM), and more attention has been paid to the gut microbiome in the pathophysiology of T2DM. Thus, we tried to examine the metabolic impact of red bayberry-derived cyanidin-3-O-glucoside (C3G) and investigate whether the antidiabetic effects of C3G were associated with the gut microbiome. As a result, C3G administration was found to reduce blood glucose levels of diabetic db/db mice, accompanied by increased levels of glucagon-like peptide (GLP-1) and insulin. Moreover, 16S rRNA analysis showed that the dominant microbiota modulated by C3G were pivotal in the glucose metabolism. Furthermore, the modulation of C3G on metabolic activities of gut bacteria leads to an increase in intestinal levels of key metabolites, particularly short-chain fatty acids. This contribution helps in promoting the secretion of GLP-1, which in turn increases insulin release with the purpose of reducing blood glucose levels. Overall, these findings may offer new thoughts concerning C3G against metabolic disorders in T2DM.

A multi-scale digital twin for adiposity-driven insulin resistance in humans: diet and drug effects

BACKGROUND

The increased prevalence of insulin resistance is one of the major health risks in society today. Insulin resistance involves both short-term dynamics, such as altered meal responses, and long-term dynamics, such as the development of type 2 diabetes. Insulin resistance also occurs on different physiological levels, ranging from disease phenotypes to organ-organ communication and intracellular signaling. To better understand the progression of insulin resistance, an analysis method is needed that can combine different timescales and physiological levels. One such method is digital twins, consisting of combined mechanistic mathematical models. We have previously developed a model for short-term glucose homeostasis and intracellular insulin signaling, and there exist long-term weight regulation models. Herein, we combine these models into a first interconnected digital twin for the progression of insulin resistance in humans.

METHODS

The model is based on ordinary differential equations representing biochemical and physiological processes, in which unknown parameters were fitted to data using a MATLAB toolbox.

RESULTS

The interconnected twin correctly predicts independent data from a weight increase study, both for weight-changes, fasting plasma insulin and glucose levels, and intracellular insulin signaling. Similarly, the model can predict independent weight-change data in a weight loss study with the weight loss drug topiramate. The model can also predict non-measured variables.

CONCLUSIONS

The model presented herein constitutes the basis for a new digital twin technology, which in the future could be used to aid medical pedagogy and increase motivation and compliance and thus aid in the prevention and treatment of insulin resistance.

The association between bedtime at night and diabetes in US adults: Data from National Health and Nutrition Examination Survey (NHANES) 2015-March -2020 pre-pandemic

OBJECTIVE

The purpose of this study was to investigate the relationship between bedtime at night and the risk of diabetes in adults.

METHODS

We extracted data from 14,821 target subjects from the NHANES database for a cross-sectional study. The data on bedtime came from the question in the sleep questionnaire: "What time do you usually fall asleep on weekdays or workdays?". Diabetes was defined as fasting blood sugar ≥ 126mg/dL, or glycohemoglobin ≥ 6.5%, or 2-hour Oral Glucose Tolerance Test blood sugar ≥ 200mg/dL, or taking hypoglycemic agent and insulin, or self-reported diabetes mellitus. A weighted multivariate logistic regression analysis was conducted to explore the relationship between bedtime at night and diabetes in adults.

RESULTS

From 19:00 to 23:00, a significantly negative association can be found between bedtime and diabetes(OR, 0.91 [95%CI, 0.83, 0.99]). From 23:00 to 02:00, The relationship between the two was positive(OR, 1.07 [95%CI, 0.94, 1.22]), nevertheless, the P values was not statistically significant(p = 0.3524). In subgroup analysis, from 19:00-23:00, the relationship was negative across genders, and in males, the P-values were still statistically significant(p = 0.0414). From 23:00-02:00, the relationship was positive across genders.

CONCLUSION

Earlier bedtime (before 23:00) increased the risk of developing diabetes. And this effect was not significantly different between male and female. For bedtime between 23:00-2:00, there was a trend of increasing the risk of diabetes as the bedtime was delayed.

Association of SLC11A1 polymorphisms with anthropometric and biochemical parameters describing Type 2 Diabetes Mellitus

Diabetes, a leading cause of death globally, has different types, with Type 2 Diabetes Mellitus (T2DM) being the most prevalent one. It has been established that variations in the SLC11A1 gene impact risk of developing infectious, inflammatory, and endocrine disorders. This study is aimed to investigate the association between the SLC11A1 gene polymorphisms (rs3731864 G/A, rs3731865 C/G, and rs17235416 + TGTG/- TGTG) and anthropometric and biochemical parameters describing T2DM. Eight hundred participants (400 in each case and control group) were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and amplification-refractory mutation system-PCR (ARMS-PCR) methods. Lipid profile, fasting blood sugar (FBS), hemoglobin A1c level, and anthropometric indices were also recorded for each subject. Findings revealed that SLC11A1-rs3731864 G/A, -rs17235416 (+ TGTG/- TGTG) were associated with T2DM susceptibility, providing protection against the disease. In contrast, SLC11A1-rs3731865 G/C conferred an increased risk of T2DM. We also noticed a significant association between SLC11A1-rs3731864 G/A and triglyceride levels in patients with T2DM. In silico evaluations demonstrated that the SLC11A2 and ATP7A proteins also interact directly with the SLC11A1 protein in Homo sapiens. In addition, allelic substitutions for both intronic variants disrupt or create binding sites for splicing factors and serve a functional effect. Overall, our findings highlighted the role of SLC11A1 gene variations might have positive (rs3731865 G/C) or negative (rs3731864 G/A and rs17235416 + TGTG/- TGTG) associations with a predisposition to T2DM.

Association between serum S100A11 levels and glucose metabolism in diabetic process

BACKGROUND

Diabetes mellitus (DM) is a prevalent non-communicable metabolic disease, and S100A11 is a newly identified gene closely related to metabolism. The association of S100A11 with diabetes is unclear. This study aimed to assess the relationship between S100A11 and markers of glucose metabolism in patients with different glucose tolerance and gender.

METHODS

This study included 97 participants. Baseline data were obtained, and the serum levels of S100A11 and metabolic markers (glycated hemoglobin [HbA1c], insulin release test, and oral glucose tolerance test) were measured. Linear and nonlinear correlations between serum S100A11 levels and HOMA-IR, HOMA of β, HbA1c, insulin sensitivity index (ISI), corrected insulin response (CIR), and oral disposition index (DIo) were analyzed. The expression of S100A11 was also detected in mice.

RESULTS

Serum S100A11 levels increased in patients with impaired glucose tolerance (IGT) of both genders. S100A11 mRNA and protein expression increased in obese mice. There were nonlinear correlations between S10011 levels and CIR, FPI, HOMA-IR, whole-body ISI in the IGT group. S100A11 was nonlinearly correlated with HOMA-IR, hepatic ISI, FPG, FPI, and HbA1c in the DM group. In the male group, S100A11 was linearly correlated with HOMA-IR and nonlinearly correlated with DIo (derived from hepatic ISI) and HbA1c. In the female population, S100A11 was nonlinearly correlated with CIR.

CONCLUSIONS

Serum S100A11 levels were highly expressed in patients with IGT and in the liver of obese mice. In addition, there were linear and nonlinear correlations between S100A11 and markers of glucose metabolism, demonstrating that S100A11 has a role in diabetes. Trial registration ChiCTR1900026990.

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.

Variants in the Control Region of Mitochondrial Genome Associated with type 2 Diabetes in a Cohort of Mexican Mestizos

BACKGROUND

According to the International Diabetes Federation, Mexico is seventh place in the prevalence of type 2 diabetes (T2D) worldwide. Mitochondrial DNA variant association studies in multifactorial diseases like T2D are scarce in Mexican populations.

AIM OF THE STUDY

The objective of this study was to analyze the association between 18 variants in the mtDNA control region and T2D and related metabolic traits in a Mexican mestizo population from Mexico City.

METHODS

This study included 1001 participants divided into 477 cases with T2D and 524 healthy controls aged between 42 and 62 years and 18 mtDNA variants with frequencies >15%.

RESULTS

Association analyses matched by age and sex showed differences in the distribution between cases and controls for variants m.315_316insC (p = 1.18 × 10^-6), m.489T>C (p = 0.009), m.16362T>C (p = 0.001), and m.16519T>C (p = 0.004). The associations between T2D and variants m.315_316ins (OR = 6.13, CI = 3.42-10.97, p = 1.97 × 10^-6), m.489T>C (OR = 1.45, CI = 1.00-2.11, p = 0.006), m.16362T>C (OR = 2.17, CI = 1.57-3.00, p = 0.001), and m.16519T>C (OR = 1.69, CI = 1.23-2.33, p = 0.006) were significant after performing logistic regression models adjusted for age, sex, and diastolic blood pressure. Metabolic traits in the control group through linear regressions, adjusted for age, sex and BMI, and corrected for multiple comparisons showed nominal association between glucose and variants m.263A>G (p <0.050), m.16183A>C (p <0.010), m.16189T>C (p <0.020), and m.16223C>T (p <0.024); triglycerides, and cholesterol and variant m.309_310insC (p <0.010 and p <0.050 respectively); urea, and creatinine, and variant m.315_316insC (p <0.007, and p <0.004 respectively); diastolic blood pressure and variants m.235A>G (p <0.016), m.263A>G (p <0.013), m.315_316insC (p <0.043), and m.16111C>T (p <0.022).

CONCLUSION

These results demonstrate a strong association between variant m.315_316insC and T2D and a nominal association with T2D traits.

Bulk and single-cell transcriptome analyses of islet tissue unravel gene signatures associated with pyroptosis and immune infiltration in type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is a common chronic heterogeneous metabolic disorder. However, the roles of pyroptosis and infiltrating immune cells in islet dysfunction of patients with T2D have yet to be explored. In this study, we aimed to explore potential crucial genes and pathways associated with pyroptosis and immune infiltration in T2D.

METHODS

To achieve this, we performed a conjoint analysis of three bulk RNA-seq datasets of islets to identify T2D-related differentially expressed genes (DEGs). After grouping the islet samples according to their ESTIMATE immune scores, we identified immune- and T2D-related DEGs. A clinical prediction model based on pyroptosis-related genes for T2D was constructed. Weighted gene co-expression network analysis was performed to identify genes positively correlated with pyroptosis-related pathways. A protein-protein interaction network was established to identify pyroptosis-related hub genes. We constructed miRNA and transcriptional networks based on the pyroptosis-related hub genes and performed functional analyses. Single-cell RNA-seq (scRNA-seq) was conducted using the GSE153885 dataset. Dimensionality was reduced using principal component analysis and t-distributed statistical neighbor embedding, and cells were clustered using Seurat. Different cell types were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA). Cell-cell communication and pseudotime trajectory analyses were conducted using the samples from patients with T2D.

RESULTS

We identified 17 pyroptosis-related hub genes. We determined the abundance of 13 immune cell types in the merged matrix and found that these cell types were correlated with the 17 pyroptosis-related hub genes. Analysis of the scRNA-seq dataset of 1892 islet samples from patients with T2D and controls revealed 11 clusters. INS and IAPP were determined to be pyroptosis-related and candidate hub genes among the 11 clusters. GSEA of the 11 clusters demonstrated that the myc, G2M checkpoint, and E2F pathways were significantly upregulated in clusters with several differentially enriched pathways.

DISCUSSION

This study elucidates the gene signatures associated with pyroptosis and immune infiltration in T2D and provides a critical resource for understanding of islet dysfunction and T2D pathogenesis.

Identification of New Genes and Genetic Variant Loci Associated with Breast Muscle Development in the Mini-Cobb F2 Chicken Population Using a Genome-Wide Association Study

Native chicken has become a favorite choice for consumers in many Asian countries recently, not only for its potential nutritional value but also for its deep ties to local food culture. However, low growth performance and limited meat production restrict their economic potential. Conducting a genome-wide association study (GWAS) for chicken-breast muscle development will help identify loci or candidate genes for different traits and potentially provide new insight into this phenotype in chickens and other species. To improve native chicken growth performance, especially breast muscle development, we performed a GWAS to explore the potential genetic mechanisms of breast muscle development in an F2 population constructed by reciprocal crosses between a fast-growing broiler chicken (Cobb500) and a slow-growing native chicken (Daweishan mini chicken). The results showed that 11 SNPs, which exceeded the 10% genome significance level (p = 1.79 × 10-8) were considered associated with breast muscle development traits, where six SNPS, NC_006126.5: g.3138376T>G, NC_006126.5: g.3138452A>G, NC_006088.5: g.73837197A>G, NC_006088.5: g.159574275A>G, NC_006089.5: g.80832197A>G, and NC_006127.5: g.48759869G>T was first identified in this study. In total, 13 genes near the SNPs were chosen as candidate genes, and none of them had previously been studied for their role in breast muscle development. After grouping the F2 population according to partial SNPs, significant differences in breast muscle weight were found among different genotypes (p < 0.05), and the expression levels of ALOX5AP, USPL1, CHRNA9, and EFNA5 among candidate genes were also significantly different (p < 0.05). The results of this study will contribute to the future exploration of the potential genetic mechanisms of breast muscle development in domestic chickens and also support the expansion of the market for native chicken in the world.

Evidence that the pituitary gland connects type 2 diabetes mellitus and schizophrenia based on large-scale trans-ethnic genetic analyses

BACKGROUND

Previous studies on European (EUR) samples have obtained inconsistent results regarding the genetic correlation between type 2 diabetes mellitus (T2DM) and Schizophrenia (SCZ). A large-scale trans-ethnic genetic analysis may provide additional evidence with enhanced power.

OBJECTIVE

We aimed to explore the genetic basis for both T2DM and SCZ based on large-scale genetic analyses of genome-wide association study (GWAS) data from both East Asian (EAS) and EUR subjects.

METHODS

A range of complementary approaches were employed to cross-validate the genetic correlation between T2DM and SCZ at the whole genome, autosomes (linkage disequilibrium score regression, LDSC), loci (Heritability Estimation from Summary Statistics, HESS), and causal variants (MiXeR and Mendelian randomization, MR) levels. Then, genome-wide and transcriptome-wide cross-trait/ethnic meta-analyses were performed separately to explore the effective shared organs, cells and molecular pathways.

RESULTS

A weak genome-wide negative genetic correlation between SCZ and T2DM was found for the EUR (r_g = - 0.098, P = 0.009) and EAS (r_g =- 0.053 and P = 0.032) populations, which showed no significant difference between the EUR and EAS populations (P = 0.22). After Bonferroni correction, the r_g remained significant only in the EUR population. Similar results were obtained from analyses at the levels of autosomes, loci and causal variants. 25 independent variants were firstly identified as being responsible for both SCZ and T2DM. The variants associated with the two disorders were significantly correlated to the gene expression profiles in the brain (P = 1.1E-9) and pituitary gland (P = 1.9E-6). Then, 61 protein-coding and non-coding genes were identified as effective genes in the pituitary gland (P < 9.23E-6) and were enriched in metabolic pathways related to glutathione mediated arsenate detoxification and to D-myo-inositol-trisphosphate.

CONCLUSION

Here, we show that a negative genetic correlation exists between SCZ and T2DM at the whole genome, autosome, locus and causal variant levels. We identify pituitary gland as a common effective organ for both diseases, in which non-protein-coding effective genes, such as lncRNAs, may be responsible for the negative genetic correlation. This highlights the importance of molecular metabolism and neuroendocrine modulation in the pituitary gland, which may be responsible for the initiation of T2DM in SCZ patients.

Association of GLP1R Polymorphisms With the Incretin Response

CONTEXT

Polymorphisms in the gene encoding the glucagon-like peptide-1 receptor (GLP1R) are associated with type 2 diabetes but their effects on incretin levels remain unclear.

OBJECTIVE

We evaluated the physiologic and hormonal effects of GLP1R genotypes before and after interventions that influence glucose physiology.

DESIGN

Pharmacogenetic study conducted at 3 academic centers in Boston, Massachusetts.

PARTICIPANTS

A total of 868 antidiabetic drug-naïve participants with type 2 diabetes or at risk for developing diabetes.

INTERVENTIONS

We analyzed 5 variants within GLP1R (rs761387, rs10305423, rs10305441, rs742762, and rs10305492) and recorded biochemical data during a 5-mg glipizide challenge and a 75-g oral glucose tolerance test (OGTT) following 4 doses of metformin 500 mg over 2 days.

MAIN OUTCOMES

We used an additive mixed-effects model to evaluate the association of these variants with glucose, insulin, and incretin levels over multiple timepoints during the OGTT.

RESULTS

During the OGTT, the G-risk allele at rs761387 was associated with higher total GLP-1 (2.61 pmol/L; 95% CI, 1.0.72-4.50), active GLP-1 (2.61 pmol/L; 95% CI, 0.04-5.18), and a trend toward higher glucose (3.63; 95% CI, -0.16 to 7.42 mg/dL) per allele but was not associated with insulin. During the glipizide challenge, the G allele was associated with higher insulin levels per allele (2.01 IU/mL; 95% CI, 0.26-3.76). The other variants were not associated with any of the outcomes tested.

CONCLUSIONS

GLP1R variation is associated with differences in GLP-1 levels following an OGTT load despite no differences in insulin levels, highlighting altered incretin signaling as a potential mechanism by which GLP1R variation affects T2D risk.

Associations between polygenic risk of coronary artery disease and type 2 diabetes, lifestyle, and cardiovascular mortality: A prospective UK Biobank study

Background

Previous studies primarily targeted the ability of polygenic risk scores (PRSs) to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular (CV) mortality. We assessed PRSs for coronary artery disease (CAD) and type 2 diabetes (T2DM) as the predictive factors for CV mortality, independent of traditional risk factors, and further investigated the additive effect between lifestyle behavior and PRS on CV mortality.

Methods

We used genetic and phenotypic data from UK Biobank participants aged 40-69 years at baseline, collected with standardized procedures. Genome-wide PRSs were constructed using >6 million genetic variants. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior.

Results

Of 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS [low vs. very high genetic risk groups, CAD PRS hazard ratio (HR) 2.61 (2.02-3.36)] and T2DM PRS [HR 2.08 (1.58-2.73)], respectively. These relationships remained significant even after an adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality [favorable vs. unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 (5.12-13.49); T2DM PRS, HR 5.84 (3.39-10.04)]. Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior [population attributable fraction (PAF) 32.1% (95% CI 28.8-35.3%)] and 14.1% was attributable to smoking [PAF 14.1% (95% CI 12.4-15.7%)]. There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality.

Conclusion

PRSs for CAD or T2DM and lifestyle behaviors are the independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify the individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.

Regulation of the intestinal flora: A potential mechanism of natural medicines in the treatment of type 2 diabetes mellitus

Diabetes mellitus comprises a group of heterogeneous disorders, which are usually subdivided into type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Both genetic and environmental factors have been implicated in the onset of diabetes. Type 1 diabetes primarily involves autoimmune insulin deficiency. In comparison, type 2 diabetes is contributed by the pathological state of insulin deficiency and insulin resistance. In recent years, significant differences were found in the abundance of microflora, intestinal barrier, and intestinal metabolites in diabetic subjects when compared to normal subjects. To further understand the relationship between diabetes mellitus and intestinal flora, this paper summarizes the interaction mechanism between diabetes mellitus and intestinal flora. Furthermore, the natural compounds found to treat diabetes through intestinal flora were classified and summarized. This review is expected to provide a valuable resource for the development of new diabetic drugs and the applications of natural compounds.

Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations and Experiences

With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) became a new scientific field and the first commercial offerings of genotype-based nutrition advice emerged at the same time. Here, we summarize the state of evidence for the effect of genetic and epigenetic factors in the development of obesity, the metabolic syndrome and resulting illnesses such as non-insulin-dependent diabetes mellitus and cardiovascular diseases. We also critically value the concepts of PN that were built around the new genetic avenue from both the academic and a commercial perspective and their effectiveness in causing sustained changes in diet, lifestyle and for improving health. Despite almost 20 years of research and commercial direct-to-consumer offerings, evidence for the success of gene-based dietary recommendations is still generally lacking. This calls for new concepts of future PN solutions that incorporate more phenotypic measures and provide a panel of instruments (e.g., self- and bio-monitoring tools, feedback systems, algorithms based on artificial intelligence) that increases compliance based on the individual´s physical and social environment and value system. This article is protected by copyright. All rights reserved.

Transcultural Lifestyle Medicine in Type 2 Diabetes Care: Narrative Review of the Literature

Disparities in type 2 diabetes (T2D) care is a global problem across diverse cultures. The Dysglycemia-Based Chronic Disease (DBCD) model promotes early and sustainable interventions along the insulin resistance (stage 1), prediabetes (stage 2), T2D (stage 3), and complications (stage 4) spectrum. In this model, lifestyle medicine is the cornerstone of preventive care to reduce DBCD progression and the socioeconomic/biological burden of disease. A comprehensive literature review, spanning 2000 to 2021, was performed and 55 studies were included examining the effects of lifestyle medicine and their cultural adaptions with different prevention modalities. In stage 1, primordial prevention targets modifiable primary drivers (behavior and environment), unhealthy lifestyles, abnormal adiposity, and insulin resistance with educational and motivational health promotion activities at individual, group, community, and population-based scales. Primary, secondary, and tertiary prevention targets individuals with mild hyperglycemia, severe hyperglycemia, and complications, respectively, using programs that incorporate structured lifestyle interventions. Culturally adapted lifestyle change in primary and secondary prevention improved quality of life and biomarkers, but with a limited impact of tertiary prevention on cardiovascular events. In conclusion, lifestyle medicine with cultural adaptations is an integral part of preventive care in patients with T2D. However, considerable research gaps exist, especially for tertiary prevention.

Dietary Intake of Polyphenols or Polyunsaturated Fatty Acids and Its Relationship with Metabolic and Inflammatory State in Patients with Type 2 Diabetes Mellitus

Background: The aim of the study was to evaluate the relationship between polyphenol or polyunsaturated fatty acids (PUFAs) consumption and the selected metabolic and inflammatory markers in type 2 diabetes (T2DM) patients. Methods: The study enrolled 129 diabetics (49 men, mean age 64.1 ± 9.8 years) with different amounts of polyphenol and PUFAs consumption. Results: A significant effect of polyphenol or PUFAs omega-3 consumption on fasting glucose concentration (FG) or glycated haemoglobin fraction (HbA1c) was reported. A negative association was observed between FG and total polyphenol, flavonoid, flavan-3-ol and stilbene intake. In the group with high flavonoid intake, the FG was significantly lower compared to the group characterised by low flavonoid intake. Polyphenols, except stilbenes, did not modulate HbA1c. Additionally, higher consumption of PUFAs omega-3 significantly decreased HbA1c, and the intake of eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids negatively and significantly correlated with FG and HbA1c. Further analysis confirmed a significant association between EPA + DHA intake and HbA1c, with significant interactions with age and gender or with body mass index and waist-to-hip ratio. The dietary intake of polyphenols or PUFAs was independent of familial diabetes or diabetic diet application. Conclusions: Our study indicates a positive effect of high consumption of flavonoids, omega-3 PUFAs and stilbenes on the markers of carbohydrate metabolism balance and the absence of such an effect on other cardiometabolic markers and inflammatory conditions.

Effective, disease-modifying, clinical approaches to patients with mild-to-moderate hypertriglyceridaemia

Plasma triglyceride concentration is easily, inexpensively, and accurately measured, and when elevated is a highly informative disease marker that identifies individuals who frequently have a host of underlying metabolic, inflammatory, and atherogenic risk factors. Although this concept aligns with much that has been discussed regarding the metabolic syndrome, individuals identified with mild-to-moderate hypertriglyceridaemia on a screening lipid profile are not necessarily recognised as having features of the metabolic syndrome and frequently do not receive definitive, meaningful, disease-modifying therapy. This treatment would include (1) lifestyle modification; (2) LDL-lowering therapies to aggressively treat elevated apolipoprotein B-containing particles; (3) antihypertensive therapies that have optimal therapeutic profiles for those individuals with metabolic syndrome; (4) icosapent ethyl for those individuals at high risk, particularly patients with established atherosclerotic cardiovascular disease who have residual hypertriglyceridaemia despite treatment with appropriate LDL-lowering therapies; (5) preferential use of cardiovascular protective diabetes therapies, in individuals with diabetes; and (6) antithrombotic therapies for secondary prevention of atherosclerotic cardiovascular disease in the context of high vascular disease risk and diabetes. Several emerging therapies, such as novel weight reducing, anti-inflammatory, lipid-modifying therapies, and therapies targeting the progression of non-alcoholic fatty liver disease, could also soon enter the clinical arena for patients with mild-to-moderate hypertriglyceridaemia and associated metabolic syndrome.

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.

Appraisal of Gene-Environment Interactions in GWAS for Evidence-Based Precision Nutrition Implementation

PURPOSE OF REVIEW

This review aims to analyse the currently reported gene-environment (G × E) interactions in genome-wide association studies (GWAS), involving environmental factors such as lifestyle and dietary habits related to metabolic syndrome phenotypes. For this purpose, the present manuscript reviews the available GWAS registered on the GWAS Catalog reporting the interaction between environmental factors and metabolic syndrome traits.

RECENT FINDINGS

Advances in omics-related analytical and computational approaches in recent years have led to a better understanding of the biological processes underlying these G × E interactions. A total of 42 GWAS were analysed, reporting over 300 loci interacting with environmental factors. Alcohol consumption, sleep time, smoking habit and physical activity were the most studied environmental factors with significant G × E interactions. The implementation of more comprehensive GWAS will provide a better understanding of the metabolic processes that determine individual responses to environmental exposures and their association with the development of chronic diseases such as obesity and the metabolic syndrome. This will facilitate the development of precision approaches for better prevention, management and treatment of these diseases.

Personalized Type 2 Diabetes Management: An Update on Recent Advances and Recommendations

Previous guidelines for the treatment of people with type 2 diabetes mellitus (T2D) have relied heavily upon rigid algorithms for the sequential addition of pharmacotherapies to achieve target glycemic control. More recent guidelines advocate a personalized approach for diabetes treatment, to improve patient satisfaction, quality of life, medication adherence and overall health outcomes. Clinicians should work with patients to develop personalized goals for their treatment, including targeted glycemic control, weight management, prevention and treatment of associated comorbidities and avoidance of complications such as hypoglycemia. Factors that affect the intensity of treatment and choice of pharmacotherapy should include medical and patient influences. Medical considerations include the diabetes phenotype, biomarkers including genetic tests, and the presence of comorbidities such as cardiovascular, renal, or hepatic disease. Patient factors include their treatment preference, age and life expectancy, diabetes duration, hypoglycemia fear and unawareness, psychological and social circumstances. The use of a personalized approach in the management of people with T2D can reduce the cost and failure associated with the algorithmic "one-size-fits-all" approach, to anticipate disease progression, improve the response to diabetes pharmacotherapy and reduce the incidence of diabetes-associated complications. Ultimately, the use of personalized medicine in people with T2D should improve medication adherence, patient satisfaction and quality of life to reduce diabetes distress and improve physical health outcomes.

Association of low fasting C-peptide levels with cardiovascular risk, visit-to-visit glucose variation and severe hypoglycemia in the Veterans Affairs Diabetes Trial (VADT)

Aims

Low C-peptide levels, indicating beta-cell dysfunction, are associated with increased within-day glucose variation and hypoglycemia. In advanced type 2 diabetes, severe hypoglycemia and increased glucose variation predict cardiovascular (CVD) risk. The present study examined the association between C-peptide levels and CVD risk and whether it can be explained by visit-to-visit glucose variation and severe hypoglycemia.

Materials and methods

Fasting C-peptide levels at baseline, composite CVD outcome, severe hypoglycemia, and visit-to-visit fasting glucose coefficient of variation (CV) and average real variability (ARV) were assessed in 1565 Veterans Affairs Diabetes Trial participants.

Results

There was a U-shaped relationship between C-peptide and CVD risk with increased risk with declining levels in the low range (< 0.50 nmol/l, HR 1.30 [95%CI 1.05–1.60], p = 0.02) and with rising levels in the high range (> 1.23 nmol/l, 1.27 [1.00–1.63], p = 0.05). C-peptide levels were inversely associated with the risk of severe hypoglycemia (OR 0.68 [0.60–0.77]) and visit-to-visit glucose variation (CV, standardized beta-estimate − 0.12 [SE 0.01]; ARV, − 0.10 [0.01]) (p < 0.0001 all). The association of low C-peptide levels with CVD risk was independent of cardiometabolic risk factors (1.48 [1.17–1.87, p = 0.001) and remained associated with CVD when tested in the same model with severe hypoglycemia and glucose CV.

Conclusions

Low C-peptide levels were associated with increased CVD risk in advanced type 2 diabetes. The association was independent of increases in glucose variation or severe hypoglycemia. C-peptide levels may predict future glucose control patterns and CVD risk, and identify phenotypes influencing clinical decision making in advanced type 2 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01418-z.

Type 2 Diabetes and Dietary Carbohydrate Intake of Adolescents and Young Adults: What Is the Impact of Different Choices?

Type 2 diabetes mellitus has a high prevalence worldwide, with a rapidly increasing incidence even in youth. Nutrition, dietary macronutrient composition, and in particular dietary carbohydrates play a major role in the development of type 2 diabetes. The aim of this narrative review is to discuss the current evidence on the role of dietary carbohydrates in the prevention and management of type 2 diabetes. The digestibility or availability of carbohydrates and their glycemic index (and glycemic load) markedly influence the glycemic response. High consumption of dietary fiber is beneficial for management of type 2 diabetes, whereas high consumption of both glycemic starch and sugars may have a harmful effect on glucose metabolism, thereby increasing the risk of developing type 2 diabetes in the presence of genetic predisposition or making its glycemic control more difficult to achieve in people with established T2D. Therefore, the same dietary macronutrient may have harmful or beneficial effects on type 2 diabetes mainly depending on the subtypes consumed. Some other factors are involved in glucose metabolism, such as meal composition, gut microbiota and genetics. For this reason, the glycemic response after carbohydrate consumption is not easy to predict in the single individual. Nutrition suggested to subjects with known type 2 diabetes should be always person-centered, considering the individual features of each subject.

An Update on the Epidemiology of Type 2 Diabetes: A Global Perspective

Type 2 diabetes (T2D) is a public health burden associated with immense health care and societal costs, early death, and morbidity. Largely because of epidemiologic changes, including nutrition transitions, urbanization, and sedentary lifestyles, T2D is increasing in every region of the world, particularly in low-income and middle-income countries. This article highlights global trends in T2D and discusses the role of genes, early-life exposures, and lifestyle risk factors in the cause of T2D, with an emphasis on populations in current hotspots of the epidemic. It also considers potential impacts of the coronavirus disease 2019 pandemic and T2D prevention policies and action.

Evaluation of the Associations of GC and CYP2R1 Genes and Gene-Obesity Interactions with Type 2 Diabetes Risk in a Chinese Rural Population

INTRODUCTION

Group-specific component (GC) and cytochrome P450 family 2 subfamily R member 1 (CYP2R1) gene polymorphisms and obesity have been associated with an increased risk for development of type 2 diabetes mellitus (T2DM) in Asian populations.

OBJECTIVE

This study assessed the associations of interactions between GC gene variants and CYP2R1 gene variants and between genes and obesity with T2DM risk.

METHODS

A study that included 2,271 subjects was performed. Eight single nucleotide polymorphisms in the GC and CYP2R1 genes were genotyped. Interaction analysis was performed using rs7041 in the GC gene and rs1993116 in the CYP2R1 gene. The effects of multiplicative and additive gene-gene and gene-environment interactions on T2DM risk were assessed.

RESULTS

The T2DM risk was significantly associated with being overweight/obese, abdominal obesity, rs7041, and rs1993116. A significant additive interaction between rs1993116 and rs7041 was associated with T2DM. In addition, there was a significant multiplicative interaction between rs7041 and body mass index (BMI) associated with elevated blood glucose levels, and at a higher BMI (>28.47), the G allele carrier showed a stronger effect than the TT genotype.

CONCLUSIONS

The interactions between GC rs7041-CYP2R1 rs1993116 and GC rs7041-BMI may explain the mechanisms by which these factors increase the risk of T2DM development.

Sweet Selenium: Synthesis and Properties of Selenium-Containing Sugars and Derivatives

In the last decades, organoselenium compounds gained interest due to their important biological features. However, the lack of solubility, which characterizes most of them, makes their actual clinical exploitability a hard to reach goal. Selenosugars, with their intrinsic polarity, do not suffer from this issue and as a result, they can be conceived as a useful alternative. The aim of this review is to provide basic knowledge of the synthetic aspects of selenosugars, selenonium salts, selenoglycosides, and selenonucleotides. Their biological properties will be briefly detailed. Of course, it will not be a comprehensive dissertation but an analysis of what the authors think is the cream of the crop of this interesting research topic.

[there any association of metabolic disturbances with joint destruction and pain?]

Osteoarthritis and type 2 diabetes mellitus represent two the most common chronic diseases. They possess many shared epidemiologic traits, have common risk factors, and embody heterogeneous multifactorial pathologies, which develop due to interaction of genetic an environmental factors. In addition, these diseases are often occurring in the same patient. In spite of the differences in clinical manifestation both diseases have similar disturbances of cellular metabolism, primarily associated with ATP production and utilization. The review discusses molecular mechanisms determining pathophysiological processes associated with glucose and lipid metabolism as well as the means aiming to alleviate the disturbances of energy metabolism as a new a therapeutic approach.

Type 2 diabetes-associated polymorphisms correlate with SIRT1 and TGF-β1 gene expression

The polymorphisms rs3758391 and rs1800470 located in SIRT1 and TGF-β1 have been associated with type 2 diabetes in different populations but its functional effect is not clear. In this study, we evaluated their effect on the expression of SIRT1 and TGF-β1 in peripheral blood as well as their participation in the formation of DNA-protein complexes in a pancreas-derived cell line. It has been described that SIRT1 and TGF-β1 participate in cell growth and regulation of production and secretion of insulin in the pancreas. Anthropometric and biochemical profiles of 127 adults were measured. Genotypes for rs3758391 and rs1800470 were determined using TaqMan assays. Expression analysis of SIRT1 and TGF-β1 were performed using real-time PCR. Gene expression of these genes increased 1.8 ± 0.6- and 1.3 ± 0.6-fold in patients carrying the TT genotype of rs3758391 and rs1800470 when compared to carriers of the CC genotype. Then, we tested whether these single-nucleotide polymorphisms (SNPs) (and rs932658, which is in linkage disequilibrium with rs3758391) are located in regulatory DNA-protein binding sites by electrophoretic mobility shift assays using nuclear extract from the pancreas-derived cell line BxPC-3. The electrophoretic mobility shift assay showed no binding of nuclear proteins to DNA. In conclusion, the genotypes of rs3758391 and rs1800470 are associated with modifications in the expression of the genes SIRT1 and TGF-β1, respectively, but none of the tested SNPs are located in regulatory DNA-protein binding sites.