Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity

Gene-Diet Interactions in Diabetes Mellitus: Current Insights and the Potential of Personalized Nutrition

Type 2 diabetes mellitus (T2DM) remaina significant global health challenge, with its increasing prevalence and associated complications contributing to high morbidity and economic burden. Genetic factors play a crucial role in T2DM susceptibility, yet individual responses to dietary interventions vary widely, emphasizing the importance of gene-diet (G × D) interactions. This review synthesizes the current literature on the genetic basis of T2DM and the role of G × D interactions in shaping individual responses to diet. We examine the genetics implication in T2DM risk and modulation by dietary factors, with a focus on the potential of Nutrigenetics in guiding personalized nutrition (PN) strategies. Moreover, the clinical implications of these interactions for the personalized prevention and management of T2DM are explored, highlighting the promise of tailoring dietary recommendations based on genetic profiles. Critical research gaps, including the need for diverse and longitudinal studies, the integration of multi-omic data, and the inclusion of digital health technologies in PN are discussed. Finally, future directions for the field are outlined, advocating for more inclusive, large-scale studies to optimize PN approaches for diverse populations and improve the efficacy of T2DM prevention and management. This review underscores the potential of an individualized, genetically informed dietary approach in modulating the global burden of T2DM.

Causal relationship between body mass index and insulin resistance: Linear and nonlinear Mendelian randomization study in a Japanese population

AIMS/INTRODUCTION

Obesity is a known risk factor for several chronic diseases, including type 2 diabetes mellitus, which results from increased insulin resistance and impaired insulin secretion. However, the association between obesity and insulin resistance in Asian populations has not yet been fully elucidated. Therefore, we aimed to investigate the causal relationship between body mass index (BMI) and glycemic traits using Mendelian randomization (MR).

MATERIALS AND METHODS

We performed individual-level MR analyses using genetic risk scores based on BMI-related variants in 3,745 individuals without diabetes mellitus from a Japanese cohort. We examined heterogeneity through subgroup analyses based on potential modifiers and determined the shape of the causal relationship using nonlinear MR analyses to further assess the impact of BMI on the homeostasis model assessment of insulin resistance (HOMA-IR).

RESULTS

MR analyses revealed a significant positive association between BMI and HOMA-IR (β = 0.077; 95% confidence interval, 0.014-0.141; P = 0.016; outcome variable was log-transformed and standardized). Additional analyses revealed heterogeneity among subgroups differentiated by age, sex, lifestyle habits, and cardiometabolic traits. Nonlinear MR analyses suggested a potential J-shaped causal relationship between BMI and HOMA-IR.

CONCLUSIONS

Our findings demonstrated that obesity and low BMI may contribute to increased insulin resistance. Furthermore, the impact of BMI on insulin resistance could vary owing to effect modification. Managing BMI is crucial in individuals at high risk of increased insulin resistance and may have important implications for preventing type 2 diabetes, especially given the low insulin secretory capacity observed in East Asian populations.

Polymorphisms Involved in Insulin Resistance and Metabolic Inflammation: Influence of Nutrients and Dietary Interventions

Insulin resistance (IR) is a metabolic disorder characterized by an impaired response to insulin. This condition is associated with excess adiposity and metabolic inflammation, contributing to an increased risk for related chronic diseases. Single-nucleotide polymorphisms (SNPs) can affect genes related to metabolic pathways which are related to IR and the individual response to nutrients and dietary patterns, affecting metabolic inflammation and insulin sensitivity. This narrative review explores the current evidence on interactions between genetic variants and dietary factors, specifically their effects in modulating IR and metabolic inflammation. A comprehensive search of the literature was conducted in PubMed, Google Scholar, and Web of Science, and a total of 95 articles were reviewed. The key findings reveal that SNPs in the TCF7L2, ADIPOQ, and TNF genes significantly influence metabolic responses and modulate the effects of the Mediterranean diet on biomarkers of inflammation and IR. Genotype-dependent variations in IR and inflammation biomarkers were observed in the response to different diets for SNPs in the TCF7L2, ADIPOQ, and TNF genes. Additionally, polygenic risk scores (PRSs) can also predict the response to the intake of nutrients and specific diets, and offer a promising tool for assessing genetic predisposition to IR. This review underscores the pivotal role of an individual's genetic background in the effects of their nutrient intake and in the responses to dietetic interventions, thereby laying the foundation for personalized and effective nutritional strategies tailored to each individual's necessity in mitigating IR and its associated risk factors for chronic diseases.

Association Between Triglyceride Glucose Index and Risk of Carotid Plaques in Asia: A Systematic Review and Meta-Analysis

The triglyceride glucose (TyG) index is used to assess insulin resistance, which is associated with the occurrence and development of cardiovascular diseases, but the risk of carotid plaques is controversial in Asia. We searched PubMed, Embase, Scopus, and Cochrane Library for articles published up to October 15, 2023, to assess the association and dose-response association of the TyG index with the risk of carotid plaques in Asia. The random effects model was used to calculate the effect estimates and 95% confidence intervals (CIs). A total of 534 articles were retrieved, and eleven studies were selected, involving 145 218 Asian participants. When the TyG index was analyzed as a categorical variable, compared with the low TyG index, the high TyG index increased the risk of carotid plaques (OR=1.38, 95% CI: 1.20, 1.60, p<0.001). As continuous variables were analyzed, similar results were observed (OR=1.33, 95% CI: 1.22, 1.45, p<0.001). Meanwhile, dose-response analysis showed that the risk of carotid plaque increased by 1.03 times for every unit increase in the TyG index (RR=1.03, 95% CI: 1.02, 1.03, p<0.001). Our meta-analysis indicates an association between the TyG index and the risk of carotid plaques in Asia. Further studies are required to substantiate these findings.

Transcription factor 7-like 2 rs77961654 polymorphism is related to stable angina and acute coronary syndrome in a Chinese population

Background: Transcription factor 7-like 2 (TCF7L2) is a key member of the T-cell factor/lymphoid enhancer factor family, and it plays a pivotal role in human physiological processes and has been implicated in various pathological conditions. TCF7L2 has been associated with inflammation, metabolic regulation, and the development of atherosclerosis. Notably, TCF7L2 exerts an anti-atherosclerotic effect by activating specific molecular pathways. Furthermore, TCF7L2 polymorphisms have been associated with the severity of coronary artery disease (CAD) and related mortality. This study aimed to investigate whether the TCF7L2 gene polymorphism rs77961654 A/C influences the risk of CAD. Methods: A total of 262 patients with acute coronary syndrome (ACS), 313 patients with stable angina, and 488 healthy individuals were enrolled. The rs77961654 variant of TCF7L2 was genotyped. Results: The frequency of the CC genotype of TCF7L2 was higher in the stable angina and ACS groups compared to the healthy controls. After adjusting for confounding factors including age, sex, systolic blood pressure, body mass index, fasting blood glucose, total cholesterol, triglycerides, and smoking status, the CC genotype was associated with 10.46-fold and 8.00-fold higher risks of ACS and stable angina, respectively, than the AA genotype. In addition, the CC genotype was positively correlated with both stable angina and ACS, while the AA genotype was negatively correlated with ACS. Furthermore, the patients with stable angina or ACS carrying the CC genotype had significantly elevated levels of HbA1C, total white blood cell count, and lymphocyte count, and lower levels of adiponectin and secreted frizzled-related protein 5 compared to those with the AA genotype. A significant association was also identified between TCF7L2 gene polymorphisms and type 2 diabetes mellitus (p for trend < 0.039). Conclusion: Polymorphisms in the TCF7L2 gene may be associated with a higher risk of stable angina and ACS.

Associations Between TCF7L2, PPARγ, and KCNJ11 Genotypes and Insulin Response to an Oral Glucose Tolerance Test: A Systematic Review

SCOPE

Insulin responses to standardized meals differ between individuals. This variability may in part be explained by genotype. This systematic review evaluates associations between genotype and insulin response to an oral glucose tolerance test (OGTT) in terms of insulin area under the curve (AUC).

METHODS AND RESULTS

Three electronic databases (Web of Science, Embase, PubMed) were searched for studies investigating associations between insulin AUC after an OGTT and single nucleotide polymorphisms (SNPs) belonging to the transcription factor 7 like 2 (TCF7L2) gene, the peroxisome proliferator-activated receptor gamma (PPARγ) gene, or the potassium inwardly rectifying channel subfamily J member 11 (KCNJ11) gene in persons without diabetes. A total of 5199 articles were identified, of which 38 were included. Among them were family-based studies (9), twin studies (2), and studies with unrelated participants (27). Seventeen articles investigated TCF7L2 (7 SNPs), 14 investigated PPARγ (1 SNP), and 8 investigated KCNJ11 (5 SNPs). For all investigated SNPs, at least half of the reports indicated no statistically significant association with postprandial insulin AUC.

CONCLUSION

No evidence was found for associations between TCF7L2, PPARγ, and KCNJ11 genotypes and insulin AUC after an OGTT. Future studies should investigate the effect of genetic risk scores on postprandial insulin.

Evaluating the Causal Effect of Circulating Proteome on Glycemic Traits: Evidence From Mendelian Randomization

Exploring the mechanisms underlying abnormal glycemic traits is important for deciphering type 2 diabetes and characterizing novel drug targets. This study aimed to decipher the causal associations of circulating proteins with fasting glucose (FG), 2-h glucose after an oral glucose challenge (2hGlu), fasting insulin (FI), and glycated hemoglobin (HbA1c) using large-scale proteome-wide Mendelian randomization (MR) analyses. Genetic data on plasma proteomes were obtained from 10 proteomic genome-wide association studies. Both cis-protein quantitative trait loci (pQTLs) and cis + trans-pQTLs MR analyses were conducted. Bayesian colocalization, Steiger filtering analysis, assessment of protein-altering variants, and mapping expression QTLs to pQTLs were performed to investigate the reliability of the MR findings. Protein-protein interaction, pathway enrichment analysis, and evaluation of drug targets were performed. Thirty-three proteins were identified with causal effects on FG, FI, or HbA1c but not 2hGlu in the cis-pQTL analysis, and 93 proteins had causal effects on glycemic traits in the cis + trans-pQTLs analysis. Most proteins were either considered druggable or drug targets. In conclusion, many novel circulating protein biomarkers were identified to be causally associated with glycemic traits. These biomarkers enhance the understanding of molecular etiology and provide insights into the screening, monitoring, and treatment of diabetes.

ARTICLE HIGHLIGHTS

Heterogeneous endocrine cell composition defines human islet functional phenotypes

Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While α and β cell composition influenced insulin and glucagon secretory traits, the abundance of δ cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and β cell replacement therapy.

Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome

Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (nobserved = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse diseases beyond cardiometabolic diseases. Polygenic risk score analysis demonstrated better discrimination of MetS and predictive power in European and East Asian populations. Altogether, our findings will guide future studies aimed at elucidating the genetic architecture of MetS.

Genetic Underpinnings of Fasting and Oral Glucose-stimulated Based Insulin Sensitivity Indices

CONTEXT

Insulin sensitivity (IS) is an important factor in type 2 diabetes (T2D) and can be estimated by many different indices.

OBJECTIVE

We aimed to compare the genetic components underlying IS indices obtained from fasting and oral glucose-stimulated plasma glucose and serum insulin levels.

METHODS

We computed 21 IS indices, classified as fasting, OGTT0,120, and OGTT0,30,120 indices, using fasting and oral glucose tolerance test (OGTT) data in 2 cohorts. We used data from a family cohort (n = 313) to estimate the heritability and the genetic and phenotypic correlations of IS indices. The population cohort, Inter99 (n = 5343), was used to test for associations between IS indices and 426 genetic variants known to be associated with T2D.

RESULTS

Heritability estimates of IS indices ranged between 19% and 38%. Fasting and OGTT0,30,120 indices had high genetic (ρG) and phenotypic (ρP) pairwise correlations (ρG and ρP: 0.88 to 1) The OGTT0,120 indices displayed a wide range of pairwise correlations (ρG: 0.17-1.00 and ρP: 0.13-0.97). We identified statistically significant associations between IS indices and established T2D-associated variants. The PPARG rs11709077 variant was associated only with fasting indices and PIK3R rs4976033 only with OGTT0,30,120 indices. The variants in FAM63A/MINDY1, GCK, C2CD4A/B, and FTO loci were associated only with OGTT0,120 indices.

CONCLUSION

Even though the IS indices mostly share a common genetic background, notable differences emerged between OGTT0,120 indices. The fasting and OGTT-based indices have distinct associations with T2D risk variants. This work provides a basis for future large-scale genetic investigations into the differences between IS indices.

Pesticide-induced transgenerational alterations of genome-wide DNA methylation patterns in the pancreas of Xenopus tropicalis correlate with metabolic phenotypes

The unsustainable use of manmade chemicals poses significant threats to biodiversity and human health. Emerging evidence highlights the potential of certain chemicals to cause transgenerational impacts on metabolic health. Here, we investigate male transmitted epigenetic transgenerational effects of the anti-androgenic herbicide linuron in the pancreas of Xenopus tropicalis frogs, and their association with metabolic phenotypes. Reduced representation bisulfite sequencing (RRBS) was used to assess genome-wide DNA methylation patterns in the pancreas of adult male F2 generation ancestrally exposed to environmentally relevant linuron levels (44 ± 4.7 μg/L). We identified 1117 differentially methylated regions (DMRs) distributed across the X. tropicalis genome, revealing potential regulatory mechanisms underlying metabolic disturbances. DMRs were identified in genes crucial for pancreatic function, including calcium signalling (clstn2, cacna1d and cadps2), genes associated with type 2 diabetes (tcf7l2 and adcy5) and a biomarker for pancreatic ductal adenocarcinoma (plec). Correlation analysis revealed associations between DNA methylation levels in these genes and metabolic phenotypes, indicating epigenetic regulation of glucose metabolism. Moreover, differential methylation in genes related to histone modifications suggests alterations in the epigenetic machinery. These findings underscore the long-term consequences of environmental contamination on pancreatic function and raise concerns about the health risks associated with transgenerational effects of pesticides.

The effects of resistance training on cardiovascular factors and anti-inflammation in diabetic rats

Diabetes induces a range of macrovascular and microvascular changes, which lead to significant clinical complications. Although many studies have tried to solve the diabetic problem using drugs, it remains unclear. In this study, we investigated whether resistance exercise affects cardiovascular factors and inflammatory markers in diabetes. The study subjected Otsuka Long-Evans Tokushima Fatty (OLETF) rats, which have genetically induced diabetes mellitus, to a resistance exercise program for 12 weeks and assessed the levels of cardiovascular factors and inflammatory markers using western blotting analysis, ELISA, and immunohistochemistry. During the training period, OLETF + exercise (EX) group exhibited lower body weight and reduced glucose levels when compared with OLETF group. Western blotting analysis, ELISA, and immunohistochemistry revealed that the levels of PAI-1, VACM-1, ICAM-1, E-selectin, TGF-β, CRP, IL-6, and TNF-α were decreased in OLETF + EX group when compared with the OLETF group. Moreover, the anti-inflammatory markers, IL-4 and IL-10, were highly expressed after exercise. Therefore, these results indicate that exercise may influence the regulation of cardiovascular factors and inflammatory markers, as well as help patients with metabolic syndromes regulate inflammation and cardiovascular function.

Comparison of Variants of Uncertain Significance in Three Regions of the Human Glucokinase Protein Using In Vitro and In Silico Analyses

There is a growing field of research focusing on the bioinformatic analysis of human genetic variation and the associated diseases. To study how well in vitro testing of purified proteins compares to bioinformatic variant prediction, we chose to analyze glucokinase (GCK) missense variations between residues 119-132, 257-262, and 412-427. These regions contained a large number of variants of uncertain significance (VUS) as well as a few pathogenic variants to use for comparison. We compared experimentally produced Vmax values from purified GCK variant proteins to predictive methods such as molecular dynamics simulation, ConSurf, iStable, the evolutionary model of variant effect (EVE), PredictSNP, and calculated binding energy. After determining which variants are pathogenic or benign based on experimental results or previous genetic studies, we found that ConSurf was the best at predicting pathogenicity. Interestingly, one VUS, D262N, showed an increase in activity and thus was difficult to interpret as pathogenic or benign. This study is an attempt to provide a framework for the utility of missense variant predictive programs.

Current approaches in CRISPR-Cas systems for diabetes

In the face of advancements in health care and a shift towards healthy lifestyle, diabetes mellitus (DM) still presents as a global health challenge. This chapter explores recent advancements in the areas of genetic and molecular underpinnings of DM, addressing the revolutionary potential of CRISPR-based genome editing technologies. We delve into the multifaceted relationship between genes and molecular pathways contributing to both type1 and type 2 diabetes. We highlight the importance of how improved genetic screening and the identification of susceptibility genes are aiding in early diagnosis and risk stratification. The spotlight then shifts to CRISPR-Cas9, a robust genome editing tool capable of various applications including correcting mutations in type 1 diabetes, enhancing insulin production in T2D, modulating genes associated with metabolism of glucose and insulin sensitivity. Delivery methods for CRISPR to targeted tissues and cells are explored, including viral and non-viral vectors, alongside the exciting possibilities offered by nanocarriers. We conclude by discussing the challenges and ethical considerations surrounding CRISPR-based therapies for DM. These include potential off-target effects, ensuring long-term efficacy and safety, and navigating the ethical implications of human genome modification. This chapter offers a comprehensive perspective on how genetic and molecular insights, coupled with the transformative power of CRISPR, are paving the way for potential cures and novel therapeutic approaches for DM.

Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk

Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs for cis regulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.

RFX6 haploinsufficiency predisposes to diabetes through impaired beta cell function

AIMS/HYPOTHESIS

Regulatory factor X 6 (RFX6) is crucial for pancreatic endocrine development and differentiation. The RFX6 variant p.His293LeufsTer7 is significantly enriched in the Finnish population, with almost 1:250 individuals as a carrier. Importantly, the FinnGen study indicates a high predisposition for heterozygous carriers to develop type 2 and gestational diabetes. However, the precise mechanism of this predisposition remains unknown.

METHODS

To understand the role of this variant in beta cell development and function, we used CRISPR technology to generate allelic series of pluripotent stem cells. We created two isogenic stem cell models: a human embryonic stem cell model; and a patient-derived stem cell model. Both were differentiated into pancreatic islet lineages (stem-cell-derived islets, SC-islets), followed by implantation in immunocompromised NOD-SCID-Gamma mice.

RESULTS

Stem cell models of the homozygous variant RFX6-/- predictably failed to generate insulin-secreting pancreatic beta cells, mirroring the phenotype observed in Mitchell-Riley syndrome. Notably, at the pancreatic endocrine stage, there was an upregulation of precursor markers NEUROG3 and SOX9, accompanied by increased apoptosis. Intriguingly, heterozygous RFX6+/- SC-islets exhibited RFX6 haploinsufficiency (54.2% reduction in protein expression), associated with reduced beta cell maturation markers, altered calcium signalling and impaired insulin secretion (62% and 54% reduction in basal and high glucose conditions, respectively). However, RFX6 haploinsufficiency did not have an impact on beta cell number or insulin content. The reduced insulin secretion persisted after in vivo implantation in mice, aligning with the increased risk of variant carriers to develop diabetes.

CONCLUSIONS/INTERPRETATION

Our allelic series isogenic SC-islet models represent a powerful tool to elucidate specific aetiologies of diabetes in humans, enabling the sensitive detection of aberrations in both beta cell development and function. We highlight the critical role of RFX6 in augmenting and maintaining the pancreatic progenitor pool, with an endocrine roadblock and increased cell death upon its loss. We demonstrate that RFX6 haploinsufficiency does not affect beta cell number or insulin content but does impair function, predisposing heterozygous carriers of loss-of-function variants to diabetes.

DATA AVAILABILITY

Ultra-deep bulk RNA-seq data for pancreatic differentiation stages 3, 5 and 7 of H1 RFX6 genotypes are deposited in the Gene Expression Omnibus database with accession code GSE234289. Original western blot images are deposited at Mendeley ( https://data.mendeley.com/datasets/g75drr3mgw/2 ).

Development of a live cell assay for the zinc transporter ZnT8

Zinc is an essential trace element that is involved in many biological processes and in cellular homeostasis. In pancreatic β-cells, zinc is crucial for the synthesis, processing, and secretion of insulin, which plays a key role in glucose homeostasis and which deficiency is the cause of diabetes. The accumulation of zinc in pancreatic cells is regulated by the solute carrier transporter SLC30A8 (or Zinc Transporter 8, ZnT8), which transports zinc from cytoplasm in intracellular vesicles. Allelic variants of SLC30A8 gene have been linked to diabetes. Given the physiological intracellular localization of SLC30A8 in pancreatic β-cells and the ubiquitous endogenous expression of other Zinc transporters in different cell lines that could be used as cellular model for SLC30A8 recombinant over-expression, it is challenging to develop a functional assay to measure SLC30A8 activity. To achieve this goal, we have firstly generated a HEK293 cell line stably overexpressing SLC30A8, where the over-expression favors the partial localization of SLC30A8 on the plasma membrane. Then, we used the combination of this cell model, commercial FluoZin-3 cell permeant zinc dye and live cell imaging approach to follow zinc flux across SLC30A8 over-expressed on plasma membrane, thus developing a novel functional imaging- based assay specific for SLC30A8. Our novel approach can be further explored and optimized, paving the way for future small molecule medium-throughput screening.

Haplotype-based association study of TCF7L2 gene variants with the development of diabetic retinopathy in an Iranian population

BACKGROUND

Diabetic retinopathy (DR) is recognized as one of the most prevalent complications of diabetes and a major cause of morbidity. Transcription factor 7-like 2 (TCF7L2), a pivotal component in the Wnt-signaling pathway, plays a significant role in β-cell development, blood-glucose homeostasis, cell survival, cell migration, and cell proliferation. Thus, this study aimed to assess the association between TCF7L2 variants (rs7903146, rs11196205, and rs12255372) with DR in a population-based association study.

MATERIALS AND METHODS

DNA was extracted from whole blood of all subjects by salting-out procedure. Total 524 T2DM patients including 234 T2DM individuals without DR and 290 T2DM individuals with DR were genotyped by TaqMan assay technology. Clinical characteristics of subjects were conducted to evaluate the plausible association between TCF7L2 variants and DR with univariate linear regression analysis.

RESULTS

Demographic analysis between case and control groups revealed significant differences in FBS, HbA1c, lipidemia, heart disease, and family history of T2DM (p < 0.05). No significant difference was observed in either genotypes distribution or allele frequency (p > 0.05) between T2DM individuals with and without DR in any models of inheritance. Genotype-phenotype association showed no significant association. Result of analysis indicated that HbAlc with adjusted OR of 1.8 (p < 0.0001) and first-degree relatives of family history with adjusted OR of 3.04 (p < 0.0001) were significantly associated with DR. Finally, haplotype analysis showed no noticeable association.

CONCLUSION

In conclusion, there was no significant genetic association between rs7903146, rs11196205, and rs12255372 with DR among T2DM Iranians; however, these variants may play unknown roles in other populations.

Multiple nanotechnological approaches using natural compounds for diabetes management

Objectives

Diabetes mellitus (DM) is a long-standing and non-transmissible endocrine disease that generates significant clinical issues and currently affects approximately 400 million people worldwide. The aim of the present review was to analyze the most relevant and recent studies that focused on the potential application of plant extracts and phytocompounds in nanotechnology for the treatment of T2DM.

Methods

Various databases were examined, including Springer Link, Google Scholar, PubMed, Wiley Online Library, and Science Direct. The search focused on discovering the potential application of nanoparticulate technologies in enhancing drug delivery of phytocompounds for the mentioned condition.

Results

Several drug delivery systems have been considered, that aimed to reduce adverse effects, while enhancing the efficiency of oral antidiabetic medications. Plant-based nanoformulations have been highlighted as an innovative approach for DM treatment due to their eco-friendly and cost-effective synthesis methods. Their benefits include targeted action, enhanced availability, stability, and reduced dosage frequency.

Conclusions

Nanomedicine has opened new opportunities for the diagnosis, treatment, and prevention of DM. The use of nanomaterials has demonstrated improved outcomes for both T1DM and T2DM. Notably, flavonoids, including substances such as quercetin, naringenin and myricitrin, have been recognized for their enhanced efficacy when delivered through novel nanotechnologies in preventing T2DM onset and associated complications. The perspectives on the addressed subject point to the development of more nanostructured phytocompounds with improved bioavailability and therapeutic efficacy.

MTNR1B genotype and effects of carbohydrate quantity and dietary glycaemic index on glycaemic response to an oral glucose load: the OmniCarb trial

AIMS/HYPOTHESIS

A type 2 diabetes-risk-increasing variant, MTNR1B (melatonin receptor 1B) rs10830963, regulates the circadian function and may influence the variability in metabolic responses to dietary carbohydrates. We investigated whether the effects of carbohydrate quantity and dietary glycaemic index (GI) on glycaemic response during OGTTs varied by the risk G allele of MTNR1B-rs10830963.

METHODS

This study included participants (n=150) of a randomised crossover-controlled feeding trial of four diets with high/low GI levels and high/low carbohydrate content for 5 weeks. The MTNR1B-rs10830963 (C/G) variant was genotyped. Glucose response during 2 h OGTT was measured at baseline and the end of each diet intervention.

RESULTS

Among the four study diets, carrying the risk G allele (CG/GG vs CC genotype) of MTNR1B-rs10830963 was associated with the largest AUC of glucose during 2 h OGTT after consuming a high-carbohydrate/high-GI diet (β 134.32 [SE 45.69] mmol/l × min; p=0.004). The risk G-allele carriers showed greater increment of glucose during 0-60 min (β 1.26 [0.47] mmol/l; p=0.008) or 0-90 min (β 1.10 [0.50] mmol/l; p=0.028) after the high-carbohydrate/high-GI diet intervention, but not after consuming the other three diets. At high carbohydrate content, reducing GI levels decreased 60 min post-OGTT glucose (mean -0.67 [95% CI: -1.18, -0.17] mmol/l) and the increment of glucose during 0-60 min (mean -1.00 [95% CI: -1.67, -0.33] mmol/l) and 0-90 min, particularly in the risk G-allele carriers (pinteraction <0.05 for all).

CONCLUSIONS/INTERPRETATION

Our study shows that carrying the risk G allele of MTNR1B-rs10830963 is associated with greater glycaemic responses after consuming a diet with high carbohydrates and high GI levels. Reducing GI in a high-carbohydrate diet may decrease post-OGTT glucose concentrations among the risk G-allele carriers.

BMI and Cardiometabolic Traits in Japanese: A Mendelian Randomization Study

BACKGROUND

Although many observational studies have demonstrated significant relationships between obesity and cardiometabolic traits, the causality of these relationships in East Asians remains to be elucidated.

METHODS

We conducted individual-level Mendelian randomization (MR) analyses targeting 14,083 participants in the Japan Multi-Institutional Collaborative Cohort Study and two-sample MR analyses using summary statistics based on genome-wide association study data from 173,430 Japanese. Using 83 body mass index (BMI)-related loci, genetic risk scores (GRS) for BMI were calculated, and the effects of BMI on cardiometabolic traits were examined for individual-level MR analyses using the two-stage least squares estimator method. The β-coefficients and standard errors for the per-allele association of each single-nucleotide polymorphism as well as all outcomes, or odds ratios with 95% confidence intervals were calculated in the two-sample MR analyses.

RESULTS

In individual-level MR analyses, the GRS of BMI was not significantly associated with any cardiometabolic traits. In two-sample MR analyses, higher BMI was associated with increased risks of higher blood pressure, triglycerides, and uric acid, as well as lower high-density-lipoprotein cholesterol and eGFR. The associations of BMI with type 2 diabetes in two-sample MR analyses were inconsistent using different methods, including the directions.

CONCLUSION

The results of this study suggest that, even among the Japanese, an East Asian population with low levels of obesity, higher BMI could be causally associated with the development of a variety of cardiometabolic traits. Causality in those associations should be clarified in future studies with larger populations, especially those of BMI with type 2 diabetes.

Associations of diabetes, circulating protein biomarkers, and risk of pancreatic cancer

BACKGROUND

Type 2 diabetes (T2D) is associated with higher risk of pancreatic cancer (PC), but the underlying mechanisms are not fully understood.

METHODS

We conducted a case-subcohort study involving 610 PC cases and 623 subcohort participants with 92 protein biomarkers measured in baseline plasma samples. Genetically-instrumented T2D was derived using 86 single-nucleotide polymorphisms (SNPs), including insulin resistance (IR) SNPs.

RESULTS

In observational analyses of 623 subcohort participants (mean age, 52 years; 61% women), T2D was positively associated with 13 proteins (SD difference: IL6: 0.52 [0.23-0.81]; IL10: 0.41 [0.12-0.70]), of which 8 were nominally associated with incident PC. The 8 proteins potentially mediated 36.9% (18.7-75.0%) of the association between T2D and PC. In MR, no associations were observed for genetically-determined T2D with proteins, but there were positive associations of genetically-determined IR with IL6 and IL10 (SD difference: 1.23 [0.05-2.41] and 1.28 [0.31-2.24]). In two-sample MR, fasting insulin was associated with both IL6 and PC, but no association was observed between IL6 and PC.

CONCLUSIONS

Proteomics were likely to explain the association between T2D and PC, but were not causal mediators. Elevated fasting insulin driven by insulin resistance might explain the associations of T2D, proteomics, and PC.

Genome-wide analysis study of gestational diabetes mellitus and related pathogenic factors in a Chinese Han population

BACKGROUND

Gestational diabetes mellitus (GDM) affects the metabolism of both the mother and fetus during and after pregnancy. Genetic factors are important in the pathogenesis of GDM, and associations vary by ethnicity. However, related studies about the relationship between the susceptibility genes and glucose traits remain limited in China. This study aimed to identify genes associated with GDM susceptibility in Chinese Han women and validate those findings using clinical data during pregnancy and postpartum period.

METHODS

A genome-wide association study (GWAS) of 398 Chinese Han women (199 each with and without GDM) was conducted and associations between single nucleotide polymorphisms (SNPs) and glucose metabolism were identified by searching public databases. Relationships between filtered differential SNPs and glucose metabolism were verified using clinical data during pregnancy. The GDM group were followed up postpartum to evaluate the progression of glucose metabolism.

RESULTS

We identified five novel SNPs with genome-wide significant associations with GDM: rs62069863 in TRPV3 gene and rs2232016 in PRMT6 gene were positive correlated with 1 h plasma glucose (1hPG) and 2 h plasma glucose (2hPG), rs1112718 in HHEX/EXOC6 gene and rs10460009 in LPIN2 gene were positive associated with fasting plasma glucose, 1hPG and 2hPG, rs927316 in GLIS3 gene was negative correlated with 2hPG. Of the 166 GDM women followed up postpartum, rs62069863 in TRPV3 gene was positively associated with fasting insulin, homoeostasis model assessment of insulin resistance.

CONCLUSIONS

The variants of rs62069863 in TRPV3 gene, rs2232016 in PRMT6 gene, rs1112718 in HHEX/EXOC6 gene, rs927316 in GLIS3 gene, and rs10460009 in LPIN2 gene were newly-identified susceptibility loci for GDM in the Chinese Han population. TRPV3 was associated with worse insulin resistance postpartum.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry.

TRIAL REGISTRATION NUMBER

ChiCTR2100043762. Date of first registration: 28/02/2021.

Kruppel-like factor 14 ameliorated obesity and related metabolic disorders by promoting adipose tissue browning

Obesity has been identified as a serious and debilitating disease that threatens human health, but the current treatment strategies still have some shortcomings. Exercise and dieting are difficult for many people to adhere to, and a series of surgical risks and pain brought about by volume reduction have made it difficult for the current weight loss effect to meet human expectations. In this study, we first found that mice with overexpression of the transcription factor Kruppel-like factor 14 (KLF14) in subcutaneous adipose tissue gained weight more slowly while consuming a high-fat diet than did control mice, and these mice also showed reduced insulin resistance and liver lipid deposition abnormalities. Mechanistically, the browning of white adipose tissue was promoted in adipose tissue with KLF14 overexpression; therefore, we preliminarily concluded that KLF14 can improve obesity by promoting the browning of white adipose tissue and energy consumption, thus ameliorating obesity and related metabolic disturbances. In summary, our results revealed that KLF14 may promote white adipose tissue browning, thus ameliorating high-fat diet-induced obesity and hepatic steatosis, as well as serum lipid levels and insulin resistance, thereby achieving a positive effect on metabolism.NEW & NOTEWORTHY Our study first explored the role of KLF14 in the development and progression of HFD-induced obesity in male mice. Its beneficial effect on adipose browning and metabolic disorders suggests that KLF14 may provide us a new therapeutic strategy for obesity and related metabolic complications. This health problem is of global concern and needs to be addressed.

eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk

The impact of genetic regulatory variation active in early pancreatic development on adult pancreatic disease and traits is not well understood. Here, we generate a panel of 107 fetal-like iPSC-derived pancreatic progenitor cells (iPSC-PPCs) from whole genome-sequenced individuals and identify 4065 genes and 4016 isoforms whose expression and/or alternative splicing are affected by regulatory variation. We integrate eQTLs identified in adult islets and whole pancreas samples, which reveal 1805 eQTL associations that are unique to the fetal-like iPSC-PPCs and 1043 eQTLs that exhibit regulatory plasticity across the fetal-like and adult pancreas tissues. Colocalization with GWAS risk loci for pancreatic diseases and traits show that some putative causal regulatory variants are active only in the fetal-like iPSC-PPCs and likely influence disease by modulating expression of disease-associated genes in early development, while others with regulatory plasticity likely exert their effects in both the fetal and adult pancreas by modulating expression of different disease genes in the two developmental stages.

Novel regulators of islet function identified from genetic variation in mouse islet Ca2+ oscillations

Insufficient insulin secretion to meet metabolic demand results in diabetes. The intracellular flux of Ca2+ into β-cells triggers insulin release. Since genetics strongly influences variation in islet secretory responses, we surveyed islet Ca2+ dynamics in eight genetically diverse mouse strains. We found high strain variation in response to four conditions: (1) 8 mM glucose; (2) 8 mM glucose plus amino acids; (3) 8 mM glucose, amino acids, plus 10 nM glucose-dependent insulinotropic polypeptide (GIP); and (4) 2 mM glucose. These stimuli interrogate β-cell function, α- to β-cell signaling, and incretin responses. We then correlated components of the Ca2+ waveforms to islet protein abundances in the same strains used for the Ca2+ measurements. To focus on proteins relevant to human islet function, we identified human orthologues of correlated mouse proteins that are proximal to glycemic-associated single-nucleotide polymorphisms in human genome-wide association studies. Several orthologues have previously been shown to regulate insulin secretion (e.g. ABCC8, PCSK1, and GCK), supporting our mouse-to-human integration as a discovery platform. By integrating these data, we nominate novel regulators of islet Ca2+ oscillations and insulin secretion with potential relevance for human islet function. We also provide a resource for identifying appropriate mouse strains in which to study these regulators.

Diabetes among Muslims during Ramadan: A narrative review

Fasting during the month of Ramadan is one of the five fundamental principles of Islam, and it is obligatory for healthy Muslim adults and adolescents. During the fasting month, Muslims usually have two meals a day, suhur (before dawn) and iftar (after dusk). However, diabetic patients may face difficulties when fasting, so it is important for medical staff to educate them on safe fasting practices. Prolonged strict fasting can increase the risk of hypoglycemia and diabetic ketoacidosis, but with proper knowledge, careful planning, and medication adjustment, diabetic Muslim patients can fast during Ramadan. For this review, a literature search was conducted using PubMed and Google Scholar until May 2023. Articles other than the English language were excluded. Current strategies for managing blood sugar levels during Ramadan include a combination of patient education on nutrition, regular monitoring of blood glucose, medications, and insulin therapy. Insulin therapy can be continued during fasting if properly titrated to the patients' needs, and finger prick blood sugar levels should be assessed regularly. If certain symptoms such as hypoglycemia, hyperglycemia, dehydration, or acute illness occur, or blood glucose levels become too high (> 300 mg/dL) or too low (< 70 mg/dL), the fast should be broken. New insulin formulations such as pegylated insulin and medications like tirzepatide, a dual agonist of gastric-inhibitory peptideand glucagonlike-peptide 1 receptors, have shown promise in managing blood sugar levels during Ramadan. Non-insulin-dependent medications like sodium-glucose-cotransporter-2 inhibitors, including the Food and Drug Administration-approved ertugliflozin, are also being used to provide additional cardiovascular benefits in patients with type 2 diabetes.

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

Gene-environment interaction in long-term effects of polychlorinated biphenyls exposure on glucose homeostasis and type 2 diabetes: The modifying effects of genetic risk and lifestyle

The longitudinal relationships of polychlorinated biphenyls (PCBs) exposure with glucose homeostasis and type 2 diabetes (T2D) risk among Chinese population have not been assessed, and interactions of PCB exposure with genetic susceptibility and lifestyle are unclear. In this prospective cohort study, fasting plasma glucose (FPG) and insulin (FPI) and seven serum indicator-PCBs were measured for each participant. We constructed polygenic risk score (PRS) of T2D and healthy lifestyle score. Each 1-unit increment of ln-transformed PCB-118 was related with a 0.141 mmol/L, 11.410 pmol/L, 0.661, and 74.5% increase in FPG, FPI, homeostasis model assessment of insulin resistance, and incident T2D risk over 6 years, respectively. Each 1-unit increment in T2D-PRS was related with a 0.169 mmol/L elevation of FPG and 65.5% elevation of incident T2D risk during 6 years. Compared with participants who had low T2D-PRS and low PCB-118, participants with high T2D-PRS and high PCB-118 showed a significant increase in FPG (0.162 mmol/L; P for interaction <0.001) and incident T2D risk [hazard ratio (HR)= 2.222]. Participants with low PCB-118, low PRS, and healthy lifestyle had the lowest incident T2D risk (HR=0.232). Our findings highlighted the significance of reducing PCB exposure and improvement in lifestyle for T2D prevention and management, especially for individuals with higher genetic risk of T2D.

Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P < 5 × 10-8) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits.

The Role of Krüppel-like Factors in Pancreatic Physiology and Pathophysiology

Krüppel-like factors (KLFs) belong to the family of transcription factors with three highly conserved zinc finger domains in the C-terminus. They regulate homeostasis, development, and disease progression in many tissues. It has been shown that KLFs play an essential role in the endocrine and exocrine compartments of the pancreas. They are necessary to maintain glucose homeostasis and have been implicated in the development of diabetes. Furthermore, they can be a vital tool in enabling pancreas regeneration and disease modeling. Finally, the KLF family contains proteins that act as tumor suppressors and oncogenes. A subset of members has a biphasic function, being upregulated in the early stages of oncogenesis and stimulating its progression and downregulated in the late stages to allow for tumor dissemination. Here, we describe KLFs' function in pancreatic physiology and pathophysiology.

Effects of a genetic variant rs13266634 in the zinc transporter 8 gene (SLC30A8) on insulin and lipid levels before and after a high-fat mixed macronutrient tolerance test in U.S. adults

BACKGROUND

The common C-allele of rs13266634 (c.973C>T or p.Arg325Trp) in SLC30A8 (ZNT8) is associated with increased risk of type 2 diabetes. While previous studies have examined the correlation of the variant with insulin and glucose metabolism, the effects of this variant on insulin and lipid responses after a lipid challenge in humans remain elusive. The goal of this study was to determine whether the C-allele had an impact on an individual's risk to metabolic syndromes in U.S. adults.

METHOD

We studied the genotypes of rs13266634 in 349 individuals aged between 18 and 65 y with BMI ranging from 18.5 to 45 kg/m². The subjects were evaluated for insulin, glucose, HbA1c, ghrelin, and lipid profiles before and after a high-fat mixed macronutrient tolerance test (MMTT).

RESULTS

We found that the effects of variants rs13266634 on glucose and lipid metabolism were sex-dimorphic, greater impact on males than on females. Insulin incremental area under the curve (AUC) after MMTT was significantly decreased in men with the CC genotype (p < 0.05). Men with the CC genotype also had the lowest fasting non-esterified fatty acid (NEFA) concentrations. On the other hand, the TT genotype was associated with a slower triglyceride removal from the circulation in men after MMTT. The reduced triglyceride removal was also observed in subjects with BMI ≥ 30 carrying either the heterozygous or homozygous T-allele. Nevertheless, the SNP had little effect on fasting or postprandial blood glucose and cholesterol concentrations.

CONCLUSION

We conclude that the CC genotype negatively affects insulin response after MMTT while the T-allele may negatively influence lipolysis during fasting and postprandial blood triglyceride removal in men and obese subjects, a novel finding in this study.

A large-scale functional analysis of genes expressed differentially in insulin secreting MIN6 sublines with high versus mildly reduced glucose-responsiveness

Molecular mechanisms of glucose-stimulated insulin secretion (GSIS) from pancreatic β-cells are not fully understood. GSIS deteriorations are believed to underlie the pathogenesis of type 2 diabetes mellitus. By comparing transcript levels of 3 insulin secreting MIN6 cell sublines with strong glucose-responsiveness and 3 with mildly reduced responsiveness, we identified 630 differentially expressed genes. Using our recently developed system based on recombinase-mediated cassette exchange, we conducted large-scale generation of stable clones overexpressing such genes in the doxycycline-regulated manner. We found that overexpressions of 18, out of 83, genes altered GSIS. Sox11 ((sex determining region Y)-box 11) was selected to confirm its roles in regulating insulin secretion, and the gene was subjected to shRNA-mediated suppression. While Sox11 overexpression decreased GSIS, its suppression increased GSIS, confirming the role of Sox11 as a negative regulator of insulin secretion. Furthermore, metabolic experiments using radiolabelled glucose showed Sox11 to participate in regulating glucose metabolism. Our data suggested that overexpression screening is a feasible option for systemic functional testing to identify important genes in GSIS.

Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression

AIMS/HYPOTHESIS

Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk.

METHODS

A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-βH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles.

RESULTS

CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-βH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-βH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function.

CONCLUSIONS/INTERPRETATION

Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.

High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease

AIMS/HYPOTHESIS

Type 2 diabetes is highly polygenic and influenced by multiple biological pathways. Rapid expansion in the number of type 2 diabetes loci can be leveraged to identify such pathways.

METHODS

We developed a high-throughput pipeline to enable clustering of type 2 diabetes loci based on variant-trait associations. Our pipeline extracted summary statistics from genome-wide association studies (GWAS) for type 2 diabetes and related traits to generate a matrix of 323 variants × 64 trait associations and applied Bayesian non-negative matrix factorisation (bNMF) to identify genetic components of type 2 diabetes. Epigenomic enrichment analysis was performed in 28 cell types and single pancreatic cells. We generated cluster-specific polygenic scores and performed regression analysis in an independent cohort (N=25,419) to assess for clinical relevance.

RESULTS

We identified ten clusters of genetic loci, recapturing the five from our prior analysis as well as novel clusters related to beta cell dysfunction, pronounced insulin secretion, and levels of alkaline phosphatase, lipoprotein A and sex hormone-binding globulin. Four clusters related to mechanisms of insulin deficiency, five to insulin resistance and one had an unclear mechanism. The clusters displayed tissue-specific epigenomic enrichment, notably with the two beta cell clusters differentially enriched in functional and stressed pancreatic beta cell states. Additionally, cluster-specific polygenic scores were differentially associated with patient clinical characteristics and outcomes. The pipeline was applied to coronary artery disease and chronic kidney disease, identifying multiple overlapping clusters with type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Our approach stratifies type 2 diabetes loci into physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes. The pipeline allows for efficient updating as additional GWAS become available and can be readily applied to other conditions, facilitating clinical translation of GWAS findings. Software to perform this clustering pipeline is freely available.

A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk

Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

A long non-coding RNA that harbors a SNP associated with type 2 diabetes regulates the expression of TGM2 gene in pancreatic beta cells

INTRODUCTION

Most of the disease-associated single nucleotide polymorphisms (SNPs) lie in non- coding regions of the human genome. Many of these variants have been predicted to impact the expression and function of long non-coding RNAs (lncRNA), but the contribution of these molecules to the development of complex diseases remains to be clarified.

METHODS

Here, we performed a genetic association study between a SNP located in a lncRNA known as LncTGM2 and the risk of developing type 2 diabetes (T2D), and analyzed its implication in disease pathogenesis at pancreatic beta cell level. Genetic association study was performed on human samples linking the rs2076380 polymorphism with T2D and glycemic traits. The pancreatic beta cell line EndoC-bH1 was employed for functional studies based on LncTGM2 silencing and overexpression experiments. Human pancreatic islets were used for eQTL analysis.

RESULTS

We have identified a genetic association between LncTGM2 and T2D risk. Functional characterization of the LncTGM2 revealed its implication in the transcriptional regulation of TGM2, coding for a transglutaminase. The T2Dassociated risk allele in LncTGM2 disrupts the secondary structure of this lncRNA, affecting its stability and the expression of TGM2 in pancreatic beta cells. Diminished LncTGM2 in human beta cells impairs glucose-stimulated insulin release.

CONCLUSIONS

These findings provide novel information on the molecular mechanisms by which T2D-associated SNPs in lncRNAs may contribute to disease, paving the way for the development of new therapies based on the modulation of lncRNAs.

Impacts of the COVID-19 pandemic on a human research islet program

Designated a pandemic in March 2020, the spread of severe acute respiratory syndrome virus 2 (SARS-CoV2), the virus responsible for coronavirus disease 2019 (COVID-19), led to new guidelines and restrictions being implemented for individuals, businesses, and societies in efforts to limit the impacts of COVID-19 on personal health and healthcare systems. Here we report the impacts of the COVID-19 pandemic on pancreas processing and islet isolation/distribution outcomes at the Alberta Diabetes Institute IsletCore, a facility specializing in the processing and distribution of human pancreatic islets for research. While the number of organs processed was significantly reduced, organ quality and the function of cellular outputs were minimally impacted during the pandemic when compared to an equivalent period immediately prior. Despite the maintained quality of isolated islets, feedback from recipient groups was more negative. Our findings suggest this is likely due to disrupted distribution which led to increased transit times to recipient labs, particularly those overseas. Thus, to improve overall outcomes in a climate of limited research islet supply, prioritization of tissue recipients based on likely tissue transit times may be needed.

Non-alcoholic fatty liver disease (NAFLD) and mental illness: Mechanisms linking mood, metabolism and medicines

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in the world and one of the leading indications for liver transplantation. It is one of the many manifestations of insulin resistance and metabolic syndrome as well as an independent risk factor for cardiovascular disease. There is growing evidence linking the incidence of NAFLD with psychiatric illnesses such as schizophrenia, bipolar disorder and depression mechanistically via genetic, metabolic, inflammatory and environmental factors including smoking and psychiatric medications. Indeed, patients prescribed antipsychotic medications, regardless of diagnosis, have higher incidence of NAFLD than population norms. The mechanistic pharmacology of antipsychotic-associated NAFLD is beginning to emerge. In this review, we aim to discuss the pathophysiology of NAFLD including its risk factors, insulin resistance and systemic inflammation as well as its intersection with psychiatric illnesses.

Phenotypic and genetic classification of diabetes

The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implementation that would need to be overcome before incorporation into clinical practice.

Periodontitis and implant complications in diabetes

Epidemiologic evidence indicates that periodontitis is more frequent in patients with uncontrolled diabetes mellitus than in healthy controls, suggesting that it could be considered the "sixth complication" of diabetes. Actually, diabetes mellitus and periodontitis are two extraordinarily prevalent chronic diseases that share a number of comorbidities all converging toward an increased risk of cardiovascular disease. Periodontal treatment has recently been shown to have the potential to improve the metabolic control of diabetes, although long-term studies are lacking. Uncontrolled diabetes also seems to affect the response to periodontal treatment, as well as the risk to develop peri-implant diseases. Mechanisms of associations between diabetes mellitus and periodontal disease include the release of advanced glycation end products as a result of hyperglycemia and a range of shared predisposing factors of genetic, microbial, and lifestyle nature. This review discusses the evidence for the risk of periodontal and peri-implant disease in diabetic patients and the potential role of the dental professional in the diabetes-periodontal interface.

High-throughput analysis of ANRIL circRNA isoforms in human pancreatic islets

The antisense non-coding RNA in the INK locus (ANRIL) is a hotspot for genetic variants associated with cardiometabolic disease. We recently found increased ANRIL abundance in human pancreatic islets from donors with certain Type II Diabetes (T2D) risk-SNPs, including a T2D risk-SNP located within ANRIL exon 2 associated with beta cell proliferation. Recent studies have found that expression of circular species of ANRIL is linked to the regulation of cardiovascular phenotypes. Less is known about how the abundance of circular ANRIL may influence T2D phenotypes. Herein, we sequence circular RNA in pancreatic islets to characterize circular isoforms of ANRIL. We identify several consistently expressed circular ANRIL isoforms whose expression is correlated across dozens of individuals and characterize ANRIL splice sites that are commonly involved in back-splicing. We find that samples with the T2D risk allele in ANRIL exon 2 had higher ratios of circular to linear ANRIL compared to protective-allele carriers, and that higher circular:linear ANRIL was associated with decreased beta cell proliferation. Our study points to a combined involvement of both linear and circular ANRIL species in T2D phenotypes and opens the door for future studies of the molecular mechanisms by which ANRIL impacts cellular function in pancreatic islets.

Generation of Isogenic hiPSCs with Targeted Edits at Multiple Intronic SNPs to Study the Effects of the Type 2 Diabetes Associated KCNQ1 Locus in American Indians

The top genetic association signal for type 2 diabetes (T2D) in Southwestern American Indians maps to intron 15 of KCNQ1, an imprinted gene. We aim to understand the biology whereby variation at this locus affects T2D specifically in this genomic background. To do so, we obtained human induced pluripotent stem cells (hiPSC) derived from American Indians. Using these iPSCs, we show that imprinting of KCNQ1 and CDKN1C during pancreatic islet-like cell generation from iPSCs is consistent with known imprinting patterns in fetal pancreas and adult islets and therefore is an ideal model system to study this locus. In this report, we detail the use of allele-specific guide RNAs and CRISPR to generate isogenic hiPSCs that differ only at multiple T2D associated intronic SNPs at this locus which can be used to elucidate their functional effects. Characterization of these isogenic hiPSCs identified a few aberrant cell lines; namely cell lines with large hemizygous deletions in the putative functional region of KCNQ1 and cell lines hypomethylated at the KCNQ1OT1 promoter. Comparison of an isogenic cell line with a hemizygous deletion to the parental cell line identified CDKN1C and H19 as differentially expressed during the endocrine progenitor stage of pancreatic-islet development.

Pathophysiological Role of Genetic Factors Associated With Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) is a highly prevalent maternal pathology characterized by maternal glucose intolerance during pregnancy that is, associated with severe complications for both mother and offspring. Several risk factors have been related to GDM; one of the most important among them is genetic predisposition. Numerous single nucleotide polymorphisms (SNPs) in genes that act at different levels on various tissues, could cause changes in the expression levels and activity of proteins, which result in glucose and insulin metabolism dysfunction. In this review, we describe various SNPs; which according to literature, increase the risk of developing GDM. These SNPs include: (1) those associated with transcription factors that regulate insulin production and excretion, such as rs7903146 (TCF7L2) and rs5015480 (HHEX); (2) others that cause a decrease in protective hormones against insulin resistance such as rs2241766 (ADIPOQ) and rs6257 (SHBG); (3) SNPs that cause modifications in membrane proteins, generating dysfunction in insulin signaling or cell transport in the case of rs5443 (GNB3) and rs2237892 (KCNQ1); (4) those associated with enzymes such as rs225014 (DIO2) and rs9939609 (FTO) which cause an impaired metabolism, resulting in an insulin resistance state; and (5) other polymorphisms, those are associated with growth factors such as rs2146323 (VEGFA) and rs755622 (MIF) which could cause changes in the expression levels of these proteins, producing endothelial dysfunction and an increase of pro-inflammatory cytokines, characteristic on GDM. While the pathophysiological mechanism is unclear, this review describes various potential effects of these polymorphisms on the predisposition to develop GDM.

Circulating metabolite profile in young adulthood identifies long-term diabetes susceptibility: the Coronary Artery Risk Development in Young Adults (CARDIA) study

AIMS/HYPOTHESIS

The aim of this work was to define metabolic correlates and pathways of diabetes pathogenesis in young adults during a subclinical latent phase of diabetes development.

METHODS

We studied 2083 young adults of Black and White ethnicity in the prospective observational cohort Coronary Artery Risk Development in Young Adults (CARDIA) study (mean ± SD age 32.1 ± 3.6 years; 43.9% women; 42.7% Black; mean ± SD BMI 25.6 ± 4.9 kg/m2) and 1797 Framingham Heart Study (FHS) participants (mean ± SD age 54.7 ± 9.7 years; 52.1% women; mean ± SD BMI 27.4 ± 4.8 kg/m2), examining the association of comprehensive metabolite profiles with endophenotypes of diabetes susceptibility (adipose and muscle tissue phenotypes and systemic inflammation). Statistical learning techniques and Cox regression were used to identify metabolite signatures of incident diabetes over a median of nearly two decades of follow-up across both cohorts.

RESULTS

We identified known and novel metabolites associated with endophenotypes that delineate the complex pathophysiological architecture of diabetes, spanning mechanisms of muscle insulin resistance, inflammatory lipid signalling and beta cell metabolism (e.g. bioactive lipids, amino acids and microbe- and diet-derived metabolites). Integrating endophenotypes of diabetes susceptibility with the metabolome generated two multi-parametric metabolite scores, one of which (a proinflammatory adiposity score) was associated with incident diabetes across the life course in participants from both the CARDIA study (young adults; HR in a fully adjusted model 2.10 [95% CI 1.72, 2.55], p<0.0001) and FHS (middle-aged and older adults; HR 1.33 [95% CI 1.14, 1.56], p=0.0004). A metabolite score based on the outcome of diabetes was strongly related to diabetes in CARDIA study participants (fully adjusted HR 3.41 [95% CI 2.85, 4.07], p<0.0001) but not in the older FHS population (HR 1.15 [95% CI 0.99, 1.33], p=0.07).

CONCLUSIONS/INTERPRETATION

Selected metabolic abnormalities in young adulthood identify individuals with heightened diabetes risk independent of race, sex and traditional diabetes risk factors. These signatures replicate across the life course.

Noise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity

Clustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease.

Cardiovascular Risk Factors and Physical Activity for the Prevention of Cardiovascular Diseases in the Elderly

Cardiovascular diseases create an important burden on the public health systems, especially in the elderly, mostly because this group of patients frequently suffer from multiple comorbidities. Accumulating cardiovascular risk factors during their lifetime has a detrimental effect on an older adult's health status. The modifiable and non-modifiable cardiovascular risk factors are very diverse, and are frequently in a close relationship with the metabolic comorbidities of the elderly, mainly obesity and Diabetes Mellitus. In this review, we aim to present the most important cardiovascular risk factors which link aging and cardiovascular diseases, starting from the pathophysiological links between these factors and the aging process. Next, we will further review the main interconnections between obesity and Diabetes Mellitus and cardiovascular diseases of the elderly. Lastly, we consider the most important aspects related to prevention through lifestyle changes and physical activity on the occurrence of cardiovascular diseases in the elderly.

Astragalus hamosus Acts as an Insulin Sensitizer Through the Treatment of Polycystic Ovary Syndrome Rat Models by Affecting IRS1 Expression

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common endocrine abnormality among women of reproductive age. Insulin resistance is known as the hallmark of PCOS that leads to hyperinsulinemia and type 2 diabetes in PCOS patients.

OBJECTIVE

This study aimed to evaluate the expression pattern of IRS1 as a candidate gene in insulin resistance development in the PCOS Rat models.

METHODS

In this study, estradiol valerate was used for PCOS induction. Then, all of the rats were divided into five experimental groups and treated with Astragalus hamosus extract. Ethanol was used for extraction by Soxhlet, and extracts were analyzed by GC-MS. Ovarian morphology was analyzed using histological experiments. Finally, the expression of IRS1 and hormonal titration of testosterone and insulin were evaluated using qRT-PCR and ELISA assays, respectively.

RESULTS

Induction of PCOS led to an increase in body weight, which decreased after treatment with the extract. Histological assessment declared an increased number of corpus luteums in treated groups and reduced cystic follicles compared with the PCOS group. Astragalus hamosus extract-treated groups exhibited decreased levels of insulin and testosterone compared to the PCOS group. qRT-PCR results showed an increase in the expression levels of IRS1 in the treated groups compared to the PCOS group.

CONCLUSIONS

This study indicated the impact of Astragalus hamosus extract on PCOS by clarifying the increased levels of IRS1 expression in the treated groups compared to the PCOS group.

Association of diabetes-related variants in ADCY5 and CDKAL1 with neonatal insulin, C-peptide, and birth weight

BACKGROUND AND PURPOSE

Neonates at the highest and lowest percentiles of birth weight present an increased risk of developing metabolic diseases in adult life. While environmental events in utero may play an important role in this association, some genetic variants are associated both with birth weight and type 2 diabetes mellitus (T2DM), suggesting a genetic link between intrauterine growth and metabolism in adult life. Variants rs11708067 in ADCY5 and rs7754840 in CDKAL1 are associated with low birth weight, risk of T2DM, and lower insulin secretion in adults. We aimed to investigate whether, besides birth weight, these polymorphisms were related to insulin secretion at birth.

METHODS

A cohort of 218 healthy term newborns from uncomplicated pregnancies were evaluated for anthropometric and biochemical variables. Cord blood insulin and C-peptide were analyzed by ELISA. Genotyping of rs11708067 in ADCY5 and rs7754840 in CDKAL1 was performed.

RESULTS

Newborns carrying the A allele of ADCY5 rs11708067 had lower cord blood insulin and C-peptide, even after adjusting by maternal glycemia, HbA1c, and pregestational BMI. Lower birth weight was found for AA-AG genotypes compared to GG, but no differences were seen in adjusted birth weight or z-score. Variant rs7754840 in CDKAL1 was not associated with birth weight, neonatal insulin, or C-peptide for any genotype or genetic model.

CONCLUSIONS

The variant rs11708067 in ADCY5 is associated with lower neonatal insulin and C-peptide concentrations. Our results suggest that the genetic influence on insulin secretion may be evident from birth, even in healthy newborns, independently of maternal glycemia and BMI.