The TCF7L2 Locus: A Genetic Window Into the Pathogenesis of Type 1 and Type 2 Diabetes

Pharmacoinformatics approach for type 2 diabetes mellitus therapeutics using phytocompounds from Costus genus: an in-silico investigation

Type 2 Diabetes Mellitus (T2DM), as a significant health concern globally, particularly in India, underscoring the vital need for effective therapeutics. Current drug therapies for T2DM may have limitations, leading researchers to explore natural products as alternatives. In this study. We have investigated the anti-diabetic compounds from the Costus genus, known as the insulin plant, which is abundant in southern India. The bioinformatics tools and software used for in-silico analysis to identify potential therapeutic compounds and hub genes associated with T2DM in the Indian population that could cut short the in-vitro and in-vivo experimental approaches in near future. The systematic review and combinatorial in-silico analysis revealed IGF2BP2, INS and TCF as the key targets that are associated with T2DM. The compounds stigmasterol, cycloartenol, and diosgenone were explored to be potent among all the 38 phytocompounds from genus Costus with binding energies -8.48, -10.07, and -10.31 kcal/mol against IGF2BP2, INS and TCF. The molecular dynamics (MD) simulation studies of these complexes demonstrated stable and consistent dynamic behavior, particularly in the INS-cycloartenol, IGF2BP2-stigmasterol and TCF7L2-diosgenone complexes. The identified compounds and associated targets represent potential candidates for T2DM therapeutics in the Indian population. The pharmacoinformatics approach presented in the study could streamline the drug discovery process by prioritizing compounds for further experimental validation.Communicated by Ramaswamy H. Sarma.

Novel Therapeutic Agents for Management of Diabetes Mellitus: A Hope for Drug Designing against Diabetes Mellitus

Diabetes mellitus (DM) is characterized by an absolute decline in insulin secretion and peripheral resistance and is the most prevalent metabolic and endocrine disorder. However, the pathogenesis of DM also includes adipocyte insulin resistance, increased glucagon secretion, increased renal glomerular glucose absorption, and neurotransmitter dysfunction. Although there is a wide spectrum of therapeutics available for glycemic control, owing to the identification of various pathogenic determinants of DM, management of DM remains challenging and complex. Current therapeutic interventions against DM focus mostly on glycemic control without considering the other pathological determinants that eventually lead to treatment failure and the progression of DM. Furthermore, long-term use of these conventionally available anti-diabetic drugs leads to various side effects, henceforth development of novel drugs against DM remains an unending search strategy for researchers. Various studies conducted in various parts of the world have proposed that these novel therapeutic interventions target multiple and alternate pathogenic hotspots involved in DM. The current review article discusses novel therapeutic options that hold particular promise to support their safety and discuss the side effects resulting from their use so that these novel candidate drugs can be effectively fabricated into potential drugs for the treatment of DM.

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

A PPARγ/long noncoding RNA axis regulates adipose thermoneutral remodeling in mice

Interplay between energy-storing white adipose cells and thermogenic beige adipocytes contributes to obesity and insulin resistance. Irrespective of specialized niche, adipocytes require the activity of the nuclear receptor PPARγ for proper function. Exposure to cold or adrenergic signaling enriches thermogenic cells though multiple pathways that act synergistically with PPARγ; however, the molecular mechanisms by which PPARγ licenses white adipose tissue to preferentially adopt a thermogenic or white adipose fate in response to dietary cues or thermoneutral conditions are not fully elucidated. Here, we show that a PPARγ/long noncoding RNA (lncRNA) axis integrates canonical and noncanonical thermogenesis to restrain white adipose tissue heat dissipation during thermoneutrality and diet-induced obesity. Pharmacologic inhibition or genetic deletion of the lncRNA Lexis enhances uncoupling protein 1-dependent (UCP1-dependent) and -independent thermogenesis. Adipose-specific deletion of Lexis counteracted diet-induced obesity, improved insulin sensitivity, and enhanced energy expenditure. Single-nuclei transcriptomics revealed that Lexis regulates a distinct population of thermogenic adipocytes. We systematically map Lexis motif preferences and show that it regulates the thermogenic program through the activity of the metabolic GWAS gene and WNT modulator TCF7L2. Collectively, our studies uncover a new mode of crosstalk between PPARγ and WNT that preserves white adipose tissue plasticity.

Residual insulin secretion in individuals with type 1 diabetes in Finland: longitudinal and cross-sectional analyses

BACKGROUND

Contrary to the presumption that type 1 diabetes leads to an absolute insulin deficiency, many individuals with type 1 diabetes have circulating C-peptide years after the diagnosis. We studied factors affecting random serum C-peptide concentration in individuals with type 1 diabetes and the association with diabetic complications.

METHODS

Our longitudinal analysis included individuals newly diagnosed with type 1 diabetes from Helsinki University Hospital (Helsinki, Finland) with repeated random serum C-peptide and concomitant glucose measurements from within 3 months of diagnosis and at least once later. The long-term cross-sectional analysis included data from participants from 57 centres in Finland who had type 1 diabetes diagnosed after 5 years of age, initiation of insulin treatment within 1 year from diagnosis, and a C-peptide concentration of less than 1·0 nmol/L (FinnDiane study) and patients with type 1 diabetes from the DIREVA study. We tested the association of random serum C-peptide concentrations and polygenic risk scores with one-way ANOVA, and association of random serum C-peptide concentrations, polygenic risk scores, and clinical factors with logistic regression.

FINDINGS

The longitudinal analysis included 847 participants younger than 16 years and 110 aged 16 years or older. In the longitudinal analysis, age at diagnosis strongly correlated with the decline in C-peptide secretion. The cross-sectional analysis included 3984 participants from FinnDiane and 645 from DIREVA. In the cross-sectional analysis, at a median duration of 21·6 years (IQR 12·5-31·2), 776 (19·4%) of 3984 FinnDiane participants had residual random serum C-peptide secretion (>0·02 nmol/L), which was associated with lower type 1 diabetes polygenic risk compared with participants without random serum C-peptide (p<0·0001). Random serum C-peptide was inversely associated with hypertension, HbA1c, and cholesterol, but also independently with microvascular complications (adjusted OR 0·61 [95% CI 0·38-0·96], p=0·033, for nephropathy; 0·55 [0·34-0·89], p=0·014, for retinopathy).

INTERPRETATION

Although children with multiple autoantibodies and HLA risk genotypes progressed to absolute insulin deficiency rapidly, many adolescents and adults had residual random serum C-peptide decades after the diagnosis. Polygenic risk of type 1 and type 2 diabetes affected residual random serum C-peptide. Even low residual random serum C-peptide concentrations seemed to be associated with a beneficial complications profile.

FUNDING

Folkhälsan Research Foundation; Academy of Finland; University of Helsinki and Helsinki University Hospital; Medical Society of Finland; the Sigrid Juselius Foundation; the "Liv and Hälsa" Society; Novo Nordisk Foundation; and State Research Funding via the Helsinki University Hospital, the Vasa Hospital District, Turku University Hospital, Vasa Central Hospital, Jakobstadsnejdens Heart Foundation, and the Medical Foundation of Vaasa.

Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes

DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 × 10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.

The GSTO2 (rs156697) Polymorphism Modifies Diabetic Nephropathy Risk

Background and Objectives: In the development of type 2 diabetes mellitus (T2DM) and its complications, genetic and environmental factors play important roles. Diabetic nephropathy (DN), one of the major microangiopathic chronic diabetic complications, is associated with an increased risk of major cardiovascular events and all-cause mortality. The present study was designed to investigate the possible modifying effect of glutathione transferase polymorphisms (GSTM1, GSTT1, GSTP1 rs1138272/rs1695, GSTO1 rs4925 and GSTO2 rs156697) in the susceptibility to T2DM and diabetic nephropathy. Materials and Methods: GSTM1 and GSTT1 deletion polymorphisms were determined by multiplex PCR, whereas GSTO1, GSTO2, and GSTP1 polymorphisms were determined by the real-time PCR in 160 T2DM patients and 248 age- and gender-matched controls. Advanced glycation end products (AGEs) were measured by ELISA. Results: Among six investigated GST polymorphisms, a significant association between the GST genotypes and susceptibility for development of diabetes mellitus was found for the GSTM1, GSTT1, GSTP1 (rs1138272) and GSTO1 polymorphisms. When the GST genotypes’ distribution in diabetes patients was assessed in the subgroups with and without diabetic nephropathy, a significant association was found only for the GSTO2 rs156697 polymorphism. Diabetic patients, carriers of the GSTM1 null, GSTT1 null and variant GSTO1*AA genotypes, had significantly increased levels of AGEs in comparison with carriers of the GSTM1 active, GSTT1 active and referent GSTO1*CC genotypes (p < 0.001, p < 0.001, p = 0.004, respectively). Conclusions: The present study supports the hypothesis that GST polymorphisms modulate the risk of diabetes and diabetic nephropathy and influence the AGEs concentration, suggesting the potential regulatory role of these enzymes in redox homeostasis disturbances.

Pharmacogenomics of GLP-1 receptor agonists: Focus on pharmacological profile

Type 2 Diabetes mellitus (T2DM) is a multifactorial metabolic disorder also known as a silent killer disease. Macrovascular and microvascular complications associated with diabetes worsen the condition leading to higher comorbidity and mortality rate. Currently, available treatment strategies for diabetes include biguanides, sulfonylureas, alpha-glucosidase inhibitors, thiazolidinediones, insulin and its analogs, DPP-4 (dipeptidyl-peptidase-4) inhibitors, SGLT-2 inhibitors, and Glucagon Like Peptide-1 receptor agonists (GLP-1RAs). Synthetic agonists of GLP-1 hormone, GLP-1RAs are an emerging class of anti-diabetic drugs which target the pathophysiology of diabetes through various mechanisms and at multiple sites. They promote insulin secretion from beta cells, and the proliferation of beta cells inhibits glucagon secretion, delays gastric emptying and induces satiety. However, treatment is reported to be associated with inter-individual variations and adverse drug reactions, which are also influenced by genetic variations. There have been a few pharmacogenetic studies have been carried out on this drug class. This review discusses all the available GLP-1RAs, their pharmacokinetics, pharmacodynamics and genetic variation affecting the inter-individual variation.

Clinical signs of type 1 diabetes are associated with type 2 diabetes marker transcription factor 7-like 2 polymorphism

AIMS/INTRODUCTION

We aimed to assess the distribution of transcription factor 7-like 2 gene TCF7L2 (rs7903146) polymorphism and to find possible associations between TCF7L2 and the characteristics of type 1 diabetes.

MATERIALS AND METHODS

We studied 190 newly diagnosed type 1 diabetes patients (median age 12.7 years, range 2.0-72.5) and 246 controls (median age 23.8 years, range 1.4-81.5) for TCF7L2 single nucleotide polymorphism. We determined anti-islet autoantibodies, random C-peptide levels, diabetes associated HLA DR/DQ haplotypes and genotypes in all patients.

RESULTS

There were no differences in the distribution of TCF7L2 single nucleotide polymorphism between patients and controls. However, patients with in type 1 diabetes, after adjusting for age and sex, subjects carrying C allele were at risk for a C-peptide level lower than 0.5 nmol/L (OR 5.65 [95% CI: 1.14-27.92]) and for zinc transporter 8 autoantibody positivity (5.22 [1.34-20.24]). Participants without T allele were associated with a higher level of islet antigen-2 autoantibodies (3.51 [1.49-8.27]) and zinc transporter 8 autoantibodies (2.39 [1.14-4.99]).

CONCLUSIONS

The connection of TCF7L2 polymorphism with zinc transporter 8 and islet antigen-2 autoantibodies and C-peptide levels in patients supports the viewpoint that TCF7L2 is associated with the clinical signs and autoimmune characteristics of type 1 diabetes. The mechanisms of the interaction between the TCF7L2 risk genotype and anti-islet autoantibodies need to be studied further.

WhichTF is functionally important in your open chromatin data?

We present WhichTF, a computational method to identify functionally important transcription factors (TFs) from chromatin accessibility measurements. To rank TFs, WhichTF applies an ontology-guided functional approach to compute novel enrichment by integrating accessibility measurements, high-confidence pre-computed conservation-aware TF binding sites, and putative gene-regulatory models. Comparison with prior sheer abundance-based methods reveals the unique ability of WhichTF to identify context-specific TFs with functional relevance, including NF-κB family members in lymphocytes and GATA factors in cardiac cells. To distinguish the transcriptional regulatory landscape in closely related samples, we apply differential analysis and demonstrate its utility in lymphocyte, mesoderm developmental, and disease cells. We find suggestive, under-characterized TFs, such as RUNX3 in mesoderm development and GLI1 in systemic lupus erythematosus. We also find TFs known for stress response, suggesting routine experimental caveats that warrant careful consideration. WhichTF yields biological insight into known and novel molecular mechanisms of TF-mediated transcriptional regulation in diverse contexts, including human and mouse cell types, cell fate trajectories, and disease-associated cells.

Transcription factors (TFs), a class of DNA binding proteins, regulate tissue- and cell-type-specific expression of genes. Identifying the critical TFs in a given cellular context leads to investigating molecular regulatory mechanisms in development, differentiation, and disease. Because there are more than 1,500 human TFs, experimental measurements of genome-wide occupancy across all TFs have been challenging. While computational approaches play pivotal roles, most existing methods rely on statistical enrichment, focusing either on sequence motif similarity recognized by TFs or the similarity of the genomic region of interest with the previously characterized TF occupancy profile. Here we propose WhichTF as an alternative, incorporating curated biomedical knowledge from ontology and integrating it with the high-confidence prediction of conserved TF binding sites in user-provided genomic regions of interest. We develop a new WhichTF score to rank TFs and demonstrate its applicability across human and mouse cell types, cellular differentiation trajectories, and disease-associated cells.

Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes

ABSTRACT

Gestational diabetes mellitus (GDM) is a growing public health problem worldwide that threatens both maternal and fetal health. Identifying individuals at high risk for GDM and diabetes after GDM is particularly useful for early intervention and prevention of disease progression. In the last decades, a number of studies have used metabolomics, genomics, and proteomic approaches to investigate associations between biomolecules and GDM progression. These studies clearly demonstrate that various biomarkers reflect pathological changes in GDM. The established markers have potential use as screening and diagnostic tools in GDM and in postpartum diabetes research. In the present review, we summarize recent studies of metabolites, single-nucleotide polymorphisms, microRNAs, and proteins associated with GDM and its transition to postpartum diabetes, with a focus on their predictive value in screening and diagnosis.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Personalized Nutrition in the Management of Female Infertility: New Insights on Chronic Low-Grade Inflammation

Increasing evidence on the significance of nutrition in reproduction is emerging from both animal and human studies, suggesting a mutual association between nutrition and female fertility. Different “fertile” dietary patterns have been studied; however, in humans, conflicting results or weak correlations are often reported, probably because of the individual variations in genome, proteome, metabolome, and microbiome and the extent of exposure to different environmental conditions. In this scenario, “precision nutrition”, namely personalized dietary patterns based on deep phenotyping and on metabolomics, microbiome, and nutrigenetics of each case, might be more efficient for infertile patients than applying a generic nutritional approach. In this review, we report on new insights into the nutritional management of infertile patients, discussing the main nutrigenetic, nutrigenomic, and microbiomic aspects that should be investigated to achieve effective personalized nutritional interventions. Specifically, we will focus on the management of low-grade chronic inflammation, which is associated with several infertility-related diseases.

Class I MHC Polymorphisms Associated with Type 2 Diabetes in the Mexican Population

Type 2 diabetes (T2D) has been linked to the expression of Human Leukocyte Antigens, principally to the Major Histocompatibility Complex Class II, with only scarce reports of Major Histocompatibility Complex Class I in specific populations. The objective of the present work was to explore the presence of polymorphisms in the MHC Class I related to T2D in the Mexican population using the Genome-Wide Association Studies Slim Initiative in Genomic Medicine of the Americas (GWAS SIGMA) database. This database contains information on 3848 Mexican individuals with T2D and 4366 control individuals from the same population without a clinical or hereditary history of the disease. The searching criteria considered a p-value of <0.005 and an odds ratio (OR) of >1.0. Ten novel, statistically significant nucleotide variants were identified: four polymorphisms associated with HLA-A (A*03:01:01:01) and six with HLA-C (C*01:02:01:01). These alleles have a high prevalence in Latin American populations and could potentially be associated with autoimmunity mechanisms related to the development of T2D complications.

Prediction of Drug Targets for Specific Diseases Leveraging Gene Perturbation Data: A Machine Learning Approach

Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles from gene perturbations. We present a novel computational approach for drug target discovery based on machine learning (ML) models. ML models are first trained on drug-induced expression profiles with outcomes defined as whether the drug treats the studied disease. The goal is to “learn” the expression patterns associated with treatment. Then, the fitted ML models were applied to expression profiles from gene perturbations (overexpression (OE)/knockdown (KD)). We prioritized targets based on predicted probabilities from the ML model, which reflects treatment potential. The methodology was applied to predict targets for hypertension, diabetes mellitus (DM), rheumatoid arthritis (RA), and schizophrenia (SCZ). We validated our approach by evaluating whether the identified targets may ‘re-discover’ known drug targets from an external database (OpenTargets). Indeed, we found evidence of significant enrichment across all diseases under study. A further literature search revealed that many candidates were supported by previous studies. For example, we predicted PSMB8 inhibition to be associated with the treatment of RA, which was supported by a study showing that PSMB8 inhibitors (PR-957) ameliorated experimental RA in mice. In conclusion, we propose a new ML approach to integrate the expression profiles from drugs and gene perturbations and validated the framework. Our approach is flexible and may provide an independent source of information when prioritizing drug targets.

Epigenome-Wide Histone Acetylation Changes in Peripheral Blood Mononuclear Cells in Patients with Type 2 Diabetes and Atherosclerotic Disease

There is emerging evidence of an association between epigenetic modifications, glycemic control and atherosclerosis risk. In this study, we mapped genome-wide epigenetic changes in patients with type 2 diabetes (T2D) and advanced atherosclerotic disease. We performed chromatin immunoprecipitation sequencing (ChIP-seq) using a histone 3 lysine 9 acetylation (H3K9ac) mark in peripheral blood mononuclear cells from patients with atherosclerosis with T2D (n = 8) or without T2D (ND, n = 10). We mapped epigenome changes and identified 23,394 and 13,133 peaks in ND and T2D individuals, respectively. Out of all the peaks, 753 domains near the transcription start site (TSS) were unique to T2D. We found that T2D in atherosclerosis leads to an H3K9ac increase in 118, and loss in 63 genomic regions. Furthermore, we discovered an association between the genomic locations of significant H3K9ac changes with genetic variants identified in previous T2D GWAS. The transcription factor 7-like 2 (TCF7L2) rs7903146, together with several human leukocyte antigen (HLA) variants, were among the domains with the most dramatic changes of H3K9ac enrichments. Pathway analysis revealed multiple activated pathways involved in immunity, including type 1 diabetes. Our results present novel evidence on the interaction between genetics and epigenetics, as well as epigenetic changes related to immunity in patients with T2D and advanced atherosclerotic disease.

Nutrigenetics and nutrigenomics-A personalized approach to nutrition

The prevalence of non-communicable diseases has been on an upward trajectory for some time and this puts an enormous burden on the healthcare expenditure. Lifestyle modifications including dietary interventions hold an immense promise to manage and prevent these diseases. Recent advances in genomic research provide evidence that focussing these efforts on individual variations in abilities to metabolize nutrients (nutrigenetics) and exploring the role of dietary compounds on gene expression (nutrigenomics and nutri-epigenomics) can lead to more meaningful personalized dietary strategies to promote optimal health. This chapter aims to provide examples on these gene-diet interactions at multiple levels to support the need of embedding targeted dietary interventions as a way forward to prevent, avoid and manage diseases.

Shortened leukocyte telomere length in young adults who use methamphetamine

Methamphetamine (METH) use, most prevalent in young adults, has been associated with high rates of morbidity and mortality. The relationship between METH use and accelerated biological aging, which can be measured using leukocyte telomere length (LTL), remains unclear. We examined whether young adult METH users have shorter LTL and explored the relationship between characteristics of METH use and LTL by using Mendelian randomization (MR) analysis. We compared the LTL for 187 METH users and 159 healthy individuals aged between 25 and 34 years and examined the relationship of LTL with METH use variables (onset age, duration, and maximum frequency of METH use) by using regression analyses. In addition, 2-stage-least-squares (2SLS) MR was also performed to possibly avoid uncontrolled confounding between characteristics of METH use and LTL. We found METH users had significantly shorter LTL compared to controls. Multivariate regression analysis showed METH use was negatively associated with LTL (β = -0.36, P < .001). Among METH users, duration of METH use was negatively associated with LTL after adjustment (β = -0.002, P = .01). We identified a single nucleotide polymorphism (SNP) rs6585206 genome-wide associated with duration of METH use. This SNP was used as an instrumental variable to avoid uncontrolled confounding for the relationship between the use duration and LTL shortening. In conclusion, we show that young adult METH users may have shorter LTL compared with controls and longer duration of METH use was significantly associated with telomere shortening. These observations suggest that METH use may accelerate biological senescence.

Nutrigenomics in Regulating the Expression of Genes Related to Type 2 Diabetes Mellitus

Nutrigenomics is the study of the gene-nutrient interaction and it indicates that some nutrients, called bioactive compounds, can mold the genetic expression or change the nucleotide chain. Polyphenols are secondary metabolites found in plants that are regularly consumed in functional foods and help prevent or delay the onset of type 2 diabetes mellitus (T2DM) and its complications. This article objected to review studies about the interaction of diet with polyphenols and Mediterranean diet in the expression of human genes related to T2DM. Resveratrol acts as an antioxidant, anti-inflammatory, and increases mitochondrial function. Regular consumption of quercetin resulted in improvement of hypertension and suppression of diabetes-induced vasoconstriction. Genistein also showed positive results in T2DM, such as increased cell mass and improved glucose tolerance and insulin levels. Catechins showed efficiency in inducing genes in triacylglycerol biosynthesis, inhibition of fatty acids and cholesterol, and resulting in their participation in mitigating complications of diabetes. Lastly, curcumin was demonstrated to be a protector of the pancreatic islets against streptozotocin-induced oxidative stress. Growing evidence suggest that bioactive compounds such as polyphenols have an important role in T2DM and the prevention and treatment of its complication, as they cause activation or inhibition of related genes.

Untangling the genetic link between type 1 and type 2 diabetes using functional genomics

There is evidence pointing towards shared etiological features between type 1 diabetes (T1D) and type 2 diabetes (T2D) despite both phenotypes being considered genetically distinct. However, the existence of shared genetic features for T1D and T2D remains complex and poorly defined. To better understand the link between T1D and T2D, we employed an integrated functional genomics approach involving extensive chromatin interaction data (Hi-C) and expression quantitative trait loci (eQTL) data to characterize the tissue-specific impacts of single nucleotide polymorphisms associated with T1D and T2D. We identified 195 pleiotropic genes that are modulated by tissue-specific spatial eQTLs associated with both T1D and T2D. The pleiotropic genes are enriched in inflammatory and metabolic pathways that include mitogen-activated protein kinase activity, pertussis toxin signaling, and the Parkinson's disease pathway. We identified 8 regulatory elements within the TCF7L2 locus that modulate transcript levels of genes involved in immune regulation as well as genes important in the etiology of T2D. Despite the observed gene and pathway overlaps, there was no significant genetic correlation between variant effects on T1D and T2D risk using European ancestral summary data. Collectively, our findings support the hypothesis that T1D and T2D specific genetic variants act through genetic regulatory mechanisms to alter the regulation of common genes, and genes that co-locate in biological pathways, to mediate pleiotropic effects on disease development. Crucially, a high risk genetic profile for T1D alters biological pathways that increase the risk of developing both T1D and T2D. The same is not true for genetic profiles that increase the risk of developing T2D. The conversion of information on genetic susceptibility to the protein pathways that are altered provides an important resource for repurposing or designing novel therapies for the management of diabetes.

Pharmacogenetics of novel glucose-lowering drugs

The aim of this work was to review studies in which genetic variants were assessed with respect to metabolic response to treatment with novel glucose-lowering drugs: dipeptidyl peptidase-4 inhibitors (DPP-4i), glucagon-like peptide-1 receptor agonists (GLP-1 RA) and sodium-glucose cotransporter 2 inhibitors (SGLT2i). In total, 22 studies were retrieved from the literature (MEDLINE). Variants of the GLP-1 receptor gene (GLP1R) were associated with a smaller reduction in HbA1c in response to DPP-4i. Variants of a number of other genes (KCNQ1, KCNJ11, CTRB1/2, PRKD1, CDKAL1, IL6 promoter region, TCF7L2, DPP4, PNPLA3) have also been related to DPP-4i response, although replication studies are lacking. The GLP1R gene was also reported to play a role in the response to GLP-1 RA, with larger weight reductions being reported in carriers of GLP1R variant alleles. There were variants of a few other genes (CNR1, TCF7L2, SORCS1) described to be related to GLP-1 RA. For SGLT2i, studies have focused on genes affecting renal glucose reabsorption (e.g. SLC5A2) but no relationship between SLC5A2 variants and response to empagliflozin has been found. The relevance of the included studies is limited due to small genetic effects, low sample sizes, limited statistical power, inadequate statistics (lack of gene-drug interactions), inadequate accounting for confounders and effects modifiers, and a lack of replication studies. Most studies have been based on candidate genes. Genome-wide association studies, in that respect, may be a more promising approach to providing novel insights. However, the identification of distinct subgroups of type 2 diabetes might also be necessary before pharmacogenetic studies can be successfully used for a stratified prescription of novel glucose-lowering drugs.

TCF7L2 rs7903146 polymorphism association with diabetes and obesity in an elderly cohort from Brazil

Background

Type 2 diabetes mellitus (T2DM) and obesity are complex pandemic diseases in the 21st century. Worldwide, the T allele rs7903146 in the TCF7L2 gene is recognized as a strong GWAS signal associated with T2DM. However, the association between the C allele and obesity is still poorly explored and needs to be replicated in other populations. Thus, the primary objectives of this study were to evaluate the TCF7L2 rs7903146 association with T2DM according to BMI status and to determine if this variant is related to obesity and BMI variation in a cohort of elderly Brazilians.

Methods

A total of 1,023 participants from an elderly census-based cohort called SABE (Saúde, Bem Estar e Envelhecimento—Health, Well-Being and Aging) were stratified by BMI status and type 2 diabetes presence. The TCF7L2 genotypes were filtered from the Online Archive of Brazilian Mutations (ABraOM—Online Archive of Brazilian Mutations) database, a web-based public database with sequencing data of samples of the SABE’s participants. Logistic regression models and interaction analyses were performed. The BMI variation (∆BMI) was calculated from anthropometric data collected in up to two time-points with a ten-year-assessment interval.

Results

The association between the rs7903146 T allele and T2DM was inversely proportional to the BMI status, with an increased risk in the normal weight group (OR 3.36; 95% CI [1.46–7.74]; P = 0.004). We confirmed the T allele association with risk for T2DM after adjusting for possible confound ing variables (OR 2.35; 95% CI [1.28–4.32]; P = 0.006). Interaction analysis showed that the increased risk for T2DM conferred by the T allele is modified by BMI (P_interaction = 0.008), age (P_interaction = 0.005) and gender (P_interaction = 0.026). A T allele protective effect against obesity was observed (OR 0.71; 95% CI [0.54–0.94]; P = 0.016). The C allele increased obesity risk (OR 1.40; 95% CI [1.06–1.84]; P = 0.017) and the CC genotype showed a borderline association with abdominal obesity risk (OR 1.28; 95% CI [1.06–1.67]; P = 0.045). The CC genotype increased the obesity risk factor after adjusting for possible confounding variables (OR 1.41; 95% CI [1.06–1.86]; P = 0.017). An increase of the TT genotype in the second tertile of ∆BMI values was observed in participants without type 2 diabetes (OR 5.13; 95% CI [1.40–18.93]; P = 0.009) in the recessive genetic model.

Conclusion

We confirmed that the rs7903146 is both associated with T2DM and obesity. The TCF7L2 rs7903146 T allele increased T2DM risk in the normal weight group and interacted with sex, age and BMI, while the C allele increased obesity risk. The TT genotype was associated with a lesser extent of BMI variation over the SABE study’s 10-year period.

Identification and functional study of GATA4 gene regulatory variants in type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2D) is a common and complex disease. Dysfunction of pancreatic β cells, which cannot release sufficient insulin, plays a central role in T2D. Genetics plays a critical role in T2D etiology. Transcription factor GATA4 is required for the pancreatic development, and GATA4 gene mutations are implicated in neonatal or childhood-onset diabetes. In this study, we aimed to investigate whether regulatory variants in GATA4 gene may change GATA4 levels, conferring susceptibility to T2D development.

METHODS

The promoter region of GATA4 gene was analyzed by targeted sequencing in T2D patients (n = 255) and ethnic-matched controls (n = 371). Dual luciferase activity assay was used for functional study, and EMSA (electrophoretic mobility shift assay) was performed for detecting transcription factor binding.

RESULTS

Thirteen regulatory variants including 5 SNPs were identified. A novel heterozygous variant (32124C > T) and one SNP [31487C > G (rs1053351749)] were only identified in T2D. Both regulatory variants significantly affected GATA4 gene promoter activity in cultured HEK-293 and INS-1 cells. Furthermore, the variant (32124C > T) evidently enhanced the binding of unknown transcriptional activator.

CONCLUSIONS

Our data suggested that GATA4 gene regulatory variants may contribute to T2D development as a rare risk factor.

Genetics of Cardiovascular Disease: How Far Are We from Personalized CVD Risk Prediction and Management?

Despite the rapid progress in diagnosis and treatment of cardiovascular disease (CVD), this disease remains a major cause of mortality and morbidity. Recent progress over the last two decades in the field of molecular genetics, especially with new tools such as genome-wide association studies, has helped to identify new genes and their variants, which can be used for calculations of risk, prediction of treatment efficacy, or detection of subjects prone to drug side effects. Although the use of genetic risk scores further improves CVD prediction, the significance is not unambiguous, and some subjects at risk remain undetected. Further research directions should focus on the “second level” of genetic information, namely, regulatory molecules (miRNAs) and epigenetic changes, predominantly DNA methylation and gene-environment interactions.

Narrative review of the influence of diabetes mellitus and hyperglycemia on colorectal cancer risk and oncological outcomes

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Diabetes mellitus and hyperglycemia significantly affect the incidence and prognosis of colorectal cancer.

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Evidence of the effects of metformin remain controversial in cancer prognosis.

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Potential molecular mechanisms by which DM and hyperglycemia affects cancer risk.

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Potential roles of glucose modulation in CRC therapy.

Diabetes mellitus (DM) and hyperglycemia have been shown to have significant effects on the incidence, chemoresistance, and prognosis of colorectal cancer (CRC), as well as the outcomes of localized and metastatic CRC. Inflammation and endocrine effects may act as central mechanisms of DM and cancer and stimulate the insulin‐like growth factor 1–phosphoinositide 3-kinase–Akt–mammalian target of rapamycin (IGF-1–PI3K–AKT–mTOR) pathway. Dysregulation of the AMP-activated protein kinase (AMPK) pathway leads to metabolic imbalance and indicates cancer risk. The use of metformin for chemoprevention has been shown to reduce CRC and adenoma incidence through the upregulation of AMPK, which causes cell cycle arrest in the Gap 1–S (G1–S) phase and inhibits the mTOR pathway, even potentially reversing the epithelial–mesenchymal transition. However, evidence of the effects of metformin remain controversial in cancer prognosis. Several genes, such as transcription factor 7-like 2(TCF7L2), tumor protein P53 inducible nuclear protein 1(TP53INP1), gremlin 1 (GREM1), and potassium voltage-gated channel subfamily Q member 1(KCNQ1), are pleiotropically related to DM as well as cancer risk and prognosis. Epigenetic modification of members of the Let-7 family such as miR-497, miR-486, and miR-223 is strongly associated with impaired glucose tolerance and CRC risk. Herein we review the pathophysiological and epidemiological evidence as well as potential underlying molecular mechanisms by which DM and hyperglycemia affect CRC risk. We also suggest potential roles of glucose modulation in CRC therapy and propose an agenda for future research and clinical practice.

Lack of association between single nucleotide polymorphisms in TCF7L2 and T2DM in the Chinese Yao population: A case-control study

Single-nucleotide polymorphisms (SNPs) in the transcription factor 7-like 2 (TCF7L2) gene have been identified to be associated with the susceptibility to type 2 diabetes mellitus (T2DM) in various populations worldwide, but the results in Chinese are conflicting, and no data are available about the Liannan Yao population. Therefore, this study aimed to investigate the association of the TCF7L2 gene polymorphisms (rs12255372, rs7903146, rs7901695, rs11196205, and rs7895340) with T2DM in the Yao population living in the rural areas in the Liannan Yao Autonomous County.This was a case-control study of 28 subjects with T2DM or prediabetes and 52 non-T2DM controls, all from the Chinese Yao population and recruited between January 2019 and June 2020. Patients with T2DM and prediabetes were grouped as the case group. The five SNPs (rs12255372, rs7903146, rs7901695, rs11196205, and rs7895340) were examined by polymerase chain reaction and direct genomic DNA sequencing in case and control groups.The subjects in case group were older than the controls (55±14 vs 48 ± 15 years, P = .047), had higher FBG levels (9.31 ± 5.43 vs 4.09 ± 0.81, P < .001), higher TC (5.79 ± 1.29 vs 5.13 ± 1.18 mmol/L, P = .025), and higher triglycerides (2.94 ± 2.04 vs 1.86 ± 1.39 mmol/L, P = .003). The genotypic distribution for each of the SNPs was in agreement with the Hardy-Weinberg equilibrium. There were no statistically significant differences in the distributions of genotypes or alleles at all five SNPs of the TCF7L2 gene between the case and control groups (all P > .05).TCF7L2 SNPs were not associated with T2DM in the Liannan Yao population.

TCF7L2 polymorphisms, nut consumption, and the risk of metabolic syndrome: a prospective population based study

Background

The aim of this study was to investigate whether two variants of the TCF7L2 (rs7903146 and rs12255372) modify the association between nut consumption and the risk of metabolic syndrome (MetS). Additionally, the modifying effect of weight change during follow-up on these associations was investigated.

Material and methods

We prospectively studied 1423 participants of the Tehran Lipid and Glucose study aged 19–74 years who were followed-up for dietary assessment using a validated, semi-quantitative food frequency questionnaire. Multivariable-adjusted Cox regression was used to estimate hazard ratios (HRs) for MetS events. Genotyping was performed by Human Omni Express-24-v1-0 chip.

Results

Over a median 8.9 years of follow-up, 415 new cases of MetS were documented. The median nut consumption was 20.0 g/week (Interquartile Range (IQR): 8.6–38.9 g/week). Regarding the rs7903146 genotype, in carriers of T allele (CT + TT), highest tertile of nut consumption was associated with a reduced risk of MetS after adjusting for confounders (HR: 0.67 (0.50–0.91)). Regarding the rs12255372 genotype, highest versus lowest tertile of nut consumption in participants with T allele (GT + TT) resulted in 34% reduction of MetS risk after adjustment for confounders (HR: 0.66 (0.49–0.69)). After stratification by weigh change (< 7% or ≥ 7% weight gain), in individuals with ≥ 7% weight gain, highest tertile of nut consumption was associated with reduced risk of MetS among the risk allele of rs7903146. In the risk allele of rs12255372, among individuals with < 7% weight gain, third tertile of nuts intake reduced the risk of MetS, after adjustment for confounders.

Conclusion

Higher consumption of nuts may reduces the risk of MetS in T-risk allele of the TCF7L2 rs7903146 and rs12255372 variants and weight change may modify this association.

Association of type 2 diabetes mellitus and periodontal disease susceptibility with genome-wide association-identified risk variants in a Southeastern Brazilian population

OBJECTIVE

Genome-wide association studies (GWAS) and literature have identified polymorphisms in the KCNJ11, HNF1A, IRS1, TCF7L2, CDKAL1, CDKN2B, RPSAP52, GPR45 HHEX, IL18, and RUNX2 genes associated with type 2 diabetes mellitus (T2DM) and/or periodontitis (P) in diverse populations, and we sought to evaluate them as genetic risk variants for these diseases in the Brazilian population.

MATERIAL AND METHODS

Periodontal, glycemic, and lipid data were obtained from 931 individuals divided into: control (n = 334), periodontitis (P; n = 358), and periodontitis associated with T2DM (P + T2DM; n = 239). After genotyping, associations between polymorphisms and pathologies were tested by multiple logistic and linear regressions, adjusting for age, sex, and smoking habits.

RESULTS

Considering the studied subjects, the increased risk to develop periodontitis in the periodontitis P + T2DM group was found for HNF1A-rs7957197-TA, CDKAL1-rs7754840-CG, RPSAP52-rs1531343-GC, TCF7L2-rs7903146-TT, and CDKN2B-rs7018475-GG. The association of these genetic variants for TCF7L2 and CDKN2B was confirmed for female, never smokers, and poorly controlled P + T2DM. CDKN2B-rs7018475 was associated with worse glycemic condition and periodontal parameters.

CONCLUSION

These five reported genetic variants were associated in the studied Southeastern Brazilian population as genetic risk variants of periodontitis and T2DM associated to periodontitis as comorbidity. Gene-phenotype associations with sex and smoking habits and the CDKN2B-rs7018475 with the poor glycemic control and more severe periodontal conditions should be further investigated.

CLINICAL RELEVANCE

Polymorphisms in the CDKAL1-rs7754840, HNF1A-rs7957197, RPSAP52-rs1531343, TCF7L2-rs7903146, and CDKN2B-rs7018475 might predispose to periodontitis and T2DM associated with periodontitis. These findings may be useful in public health genomics and future advanced clinical practice, since genetic carriage can be measured before disease onset, being of potential great benefit for treatment planning and prognosis in early disease stages.

Obesity in Patients with Type 1 Diabetes: Links, Risks and Management Challenges

Obesity affects large numbers of patients with type 1 diabetes (T1D) across their lifetime, with rates ranging between 2.8% and 37.1%. Patients with T1D and obesity are characterized by the presence of insulin resistance, of high insulin requirements, have a greater cardiometabolic risk and an enhanced risk of developing chronic complications when compared to normal-weight persons with T1D. Dual treatment of obesity and T1D is challenging and no specific guidelines for improving outcomes of both glycemic control and weight management have been established for this population. Nevertheless, although evidence is scarce, a comprehensive approach based on a balanced hypocaloric diet, physical activity and cognitive behavioral therapy by a multidisciplinary team, expert in both obesity and diabetes, remains as the best clinical practice. However, weight loss responses with lifestyle changes alone are limited, so in the "roadmap" of the treatment of obesity in T1D, it will be helpful to include anti-obesity pharmacotherapy despite at present there is a lack of evidence since T1D patients have been excluded from anti-obesity drug clinical trials. In case of severe obesity, bariatric surgery has proven to be of benefit in obtaining a substantial and long-term weight loss and reduction in cardiovascular risk. The near future looks promising with the development of new and more effective anti-obesity treatments and strategies to improve insulin resistance and oxidative stress. Advances in precision medicine may help individualize and optimize the medical management and care of these patients. This review, by gathering current evidence, highlights the need of solid knowledge in all facets of the treatment of patients with obesity and T1D that can only be obtained through high quality well-designed studies.

Adipocyte-specific deletion of Tcf7l2 induces dysregulated lipid metabolism and impairs glucose tolerance in mice

AIMS/HYPOTHESIS

Transcription factor 7-like 2 (TCF7L2) is a downstream effector of the Wnt/β-catenin signalling pathway implicated in type 2 diabetes risk through genome-wide association studies. Although its expression is critical for adipocyte development, the potential roles of changes in adipose tissue TCF7L2 levels in diabetes risk are poorly defined. Here, we investigated whether forced changes in Tcf7l2 expression in adipocytes affect whole body glucose or lipid metabolism and crosstalk between disease-relevant tissues.

METHODS

Tcf7l2 was selectively ablated in mature adipocytes in C57BL/6J mice using Cre recombinase under Adipoq promoter control to recombine Tcf7l2 alleles floxed at exon 1 (referred to as aTCF7L2 mice). aTCF7L2 mice were fed normal chow or a high-fat diet for 12 weeks. Glucose and insulin sensitivity, as well as beta cell function, were assessed in vivo and in vitro. Levels of circulating NEFA, selected hormones and adipokines were measured using standard assays.

RESULTS

Reduced TCF7L2 expression in adipocytes altered glucose tolerance and insulin secretion in male but not in female mice. Thus, on a normal chow diet, male heterozygote knockout mice (aTCF7L2het) exhibited impaired glucose tolerance at 16 weeks (p = 0.03) and increased fat mass (1.4 ± 0.1-fold, p = 0.007) but no changes in insulin secretion. In contrast, male homozygote knockout (aTCF7L2hom) mice displayed normal body weight but impaired oral glucose tolerance at 16 weeks (p = 0.0001). These changes were mechanistically associated with impaired in vitro glucose-stimulated insulin secretion (decreased 0.5 ± 0.1-fold vs control mice, p = 0.02) and decreased levels of the incretins glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide (0.6 ± 0.1-fold and 0.4 ± 0.1-fold vs control mice, p = 0.04 and p < 0.0001, respectively). Circulating levels of plasma NEFA and fatty acid binding protein 4 were increased by 1.3 ± 0.1-fold and 1.8 ± 0.3-fold vs control mice (p = 0.03 and p = 0.05, respectively). Following exposure to a high-fat diet for 12 weeks, male aTCF7L2hom mice exhibited reduced in vivo glucose-stimulated insulin secretion (0.5 ± 0.1-fold vs control mice, p = 0.02).

CONCLUSIONS/INTERPRETATION

Loss of Tcf7l2 gene expression selectively in adipocytes leads to a sexually dimorphic phenotype, with impairments not only in adipocytes, but also in pancreatic islet and enteroendocrine cells in male mice only. Our findings suggest novel roles for adipokines and incretins in the effects of diabetes-associated variants in TCF7L2, and further illuminate the roles of TCF7L2 in glucose homeostasis and diabetes risk. Graphical abstract.

Decline Pattern of Beta-cell Function in Adult-onset Latent Autoimmune Diabetes: an 8-year Prospective Study

OBJECTIVE

To explore the decline pattern and possible determinants of beta-cell function progression in patients with latent-onset autoimmune diabetes in adults (LADA).

RESEARCH DESIGN AND METHODS

In this 8-year prospective study, 106 LADA individuals underwent annual follow-up and their pattern of beta-cell function progression was assessed. Beta-cell function failure was defined by fasting C-peptide (FCP) < 75 pmol/L. Other clinical characteristics, including age of onset, body mass index (BMI), and glutamic acid decarboxylase autoantibody (GADA) titer, were analyzed to find out possible determinants of beta-cell function progression.

RESULTS

The dropout rate was 4.7%. During the 8-year follow-up period, 29 (28.7%) of the 101 subjects developed beta-cell function failure. The decline pattern of C-peptide in LADA was biphasic, showing an initial rapid linear progression and then followed by a stable mode. The declination speed of FCP was 55.19 pmol/L/year (95% CI, -62.54 to -47.84, P < 0.001) during the first 5 years and 4.62 pmol/L/year (95% CI, -69.83 to 60.60, P = 0.790) thereafter. Further analysis showed that GADA titer was the most valuable discriminatory parameter related to a higher risk of development of beta-cell function failure (GADA titer of 173.5 WHO units/mL; area under the curve [AUC], 0.824). Beta-cell function failure occurred in 71.3% of high-GADA titer patients while only 6.2% of low-titer patients.

CONCLUSIONS

The decline pattern of C-peptide was a fast-followed-by-slow biphasic mode, with about a quarter of LADA patients developing beta-cell function failure during the first 8 years. GADA titer less than 173.5 WHO units /mL was propitious for the preservation of beta-cell function.

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

Excess BMI Accelerates Islet Autoimmunity in Older Children and Adolescents

OBJECTIVE

Sustained excess BMI increases the risk of type 1 diabetes (T1D) in autoantibody-positive relatives without diabetes of patients. We tested whether elevated BMI also accelerates the progression of islet autoimmunity before T1D diagnosis.

RESEARCH DESIGN AND METHODS

We studied 706 single autoantibody-positive pediatric TrialNet participants (ages 1.6-18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies.

RESULTS

At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was -9.2 to 15.6 kg/m² (median -1.91), with ceBMI ≥0 kg/m² corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m², age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m² increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type.

CONCLUSIONS

These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity.

Porcine models for studying complications and organ crosstalk in diabetes mellitus

The worldwide prevalence of diabetes mellitus and obesity is rapidly increasing not only in adults but also in children and adolescents. Diabetes is associated with macrovascular complications increasing the risk for cardiovascular disease and stroke, as well as microvascular complications leading to diabetic nephropathy, retinopathy and neuropathy. Animal models are essential for studying disease mechanisms and for developing and testing diagnostic procedures and therapeutic strategies. Rodent models are most widely used but have limitations in translational research. Porcine models have the potential to bridge the gap between basic studies and clinical trials in human patients. This article provides an overview of concepts for the development of porcine models for diabetes and obesity research, with a focus on genetically engineered models. Diabetes-associated ocular, cardiovascular and renal alterations observed in diabetic pig models are summarized and their similarities with complications in diabetic patients are discussed. Systematic multi-organ biobanking of porcine models of diabetes and obesity and molecular profiling of representative tissue samples on different levels, e.g., on the transcriptome, proteome, or metabolome level, is proposed as a strategy for discovering tissue-specific pathomechanisms and their molecular key drivers using systems biology tools. This is exemplified by a recent study providing multi-omics insights into functional changes of the liver in a transgenic pig model for insulin-deficient diabetes mellitus. Collectively, these approaches will provide a better understanding of organ crosstalk in diabetes mellitus and eventually reveal new molecular targets for the prevention, early diagnosis and treatment of diabetes mellitus and its associated complications.