Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes

Correlation between TCF7L2 gene expression and certain biochemical parameters in type 2 diabetes mellitus

Objectives

The transcription factor 7-like 2 gene (TCF7L2) is associated with a predisposition to type 2 diabetes mellitus (T2DM) in different ethnic populations. This article investigated the relationship between TCF7L2 gene expression and several biochemical indexes among different age categories of T2DM in a sample of the Iraqi population.

Methods

One hundred and fifty blood samples were collected from three groups: young T2DM (10-35 years), old T2DM (40-80 years), and healthy control (10-65 years) groups. Both sexes were enrolled. qPCR was performed to explore the expression of the TCF7L2 gene. Biochemical tests were performed to assess hemoglobin A1C (HbA1c), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels. The body mass index (BMI) was calculated. The results were statistically analyzed.

Results

Patients with T2DM had higher BMI, TG, and LDL, and lower HDL than the control group. There was a strong positive correlation between hemoglobin A1C (HbA1c) and BMI, TG, and LDL and a negative correlation between HbA1c and HDL. Expression of the TCF7L2 gene showed a significant difference between old and young patients by 1.68 and 0.207 fold, respectively. These results showed that old patients had higher gene expression than young patients.

Conclusion

TCF7L2 gene expression was affected by age, with higher expression in old T2DM patients. This may influence beta cell functions and insulin secretion.

A, Sarma DK, Verma V, Nagpal R, Mohania D, Tiwari R, Kumar M. Deciphering the complex interplay of risk factors in type 2 diabetes mellitus: A comprehensive review

The complex and multidimensional landscape of type 2 diabetes mellitus (T2D) is a major global concern. Despite several years of extensive research, the precise underlying causes of T2D remain elusive, but evidence suggests that it is influenced by a myriad of interconnected risk factors such as epigenetics, genetics, gut microbiome, environmental factors, organelle stress, and dietary habits. The number of factors influencing the pathogenesis is increasing day by day which worsens the scenario; meanwhile, the interconnections shoot up the frame. By gaining deeper insights into the contributing factors, we may pave the way for the development of personalized medicine, which could unlock more precise and impactful treatment pathways for individuals with T2D. This review summarizes the state of knowledge about T2D pathogenesis, focusing on the interplay between various risk factors and their implications for future therapeutic strategies. Understanding these factors could lead to tailored treatments targeting specific risk factors and inform prevention efforts on a population level, ultimately improving outcomes for individuals with T2D and reducing its burden globally.

Integrated Analysis of Genomic and Genome-Wide Association Studies Identified Candidate Genes for Nutrigenetic Studies in Flavonoids and Vascular Health: Path to Precision Nutrition for (Poly)phenols

Flavonoids exert vasculoprotective effects in humans, but interindividual variability in their action has also been reported. This study aims to identify genes that are associated with vascular health effects of flavonoids and whose polymorphisms could explain interindividual variability in response to their intake. Applying the predetermined literature search criteria, we identified five human intervention studies reporting positive effects of flavonoids on vascular function together with global genomic changes analyzed using microarray methods. Genes involved in vascular dysfunction were identified from genome-wide association studies (GWAS). By extracting data from the eligible human intervention studies, we obtained 5807 differentially expressed genes (DEGs). The number of identified upstream regulators (URs) varied across the studies, from 227 to 1407. The search of the GWAS Catalog revealed 493 genes associated with vascular dysfunction. An integrative analysis of transcriptomic data with GWAS genes identified 106 candidate DEGs and 42 candidate URs, while subsequent functional analyses and a search of the literature identified 20 top priority candidate genes: ALDH2, APOE, CAPZA1, CYP11B2, GNA13, IL6, IRF5, LDLR, LPL, LSP1, MKNK1, MMP3, MTHFR, MYO6, NCR3, PPARG, SARM1, TCF20, TCF7L2, and TNF. In conclusion, this integrated analysis identifies important genes to design future nutrigenetic studies for development of precision nutrition for polyphenols.

TCF7L2 Polymorphism rs7903146 (C/T) and Gestational Diabetes Influence on Obstetric Outcome: A Romanian Case-Control Study

Gestational diabetes mellitus (GDM) is one of the most frequent predictors of obstetric outcome among Romanian pregnant women. Thus, we aimed to investigate the role of rs7903146 (C/T) TCF7L2 gene polymorphism in the presence of GDM and to evaluate the influence on maternal-fetal outcomes in a cohort of pregnant women from Northern Transylvania. Our prospective case-control study was performed in a tertiary maternity center on 61 patients diagnosed with GDM and 55 normal pregnant patients. The patients were genotyped for rs7903146 (C/T) polymorphism of the TCF7L2 gene using the PCR-RFLP method between 24 and 28 weeks of gestation. The minor T allele was associated with a high risk of developing GDM (OR 1.71 [95% CI 0.82-3.59]) if both heterozygote and homozygote types were considered. Also, a higher risk of developing GDM was observed in homozygous carriers (OR 3.26 [95% CI 1.10-9.68]). Women with the TT genotype were more likely to require insulin therapy during pregnancy than other genotypes with a 5.67-fold increased risk ([1.61-19.97], p = 0.015). TT homozygote type was significantly associated with fetal macrosomia for birth weights greater than the 95th percentile (p = 0.034). The homozygous TT genotype is associated with an increased risk of developing GDM. Also, rs7903146 (C/T) TCF7L2 variant is accompanied by a high probability of developing insulin-dependent gestational diabetes mellitus (ID-GDM). The presence of at least one minor T allele was associated with a higher risk of fetal macrosomia.

Insights on effects of Wnt pathway modulation on insulin signaling and glucose homeostasis for the treatment of type 2 diabetes mellitus: Wnt activation or Wnt inhibition?

Type 2 diabetes mellitus (T2DM) is a major worldwide chronic disease and can lead to serious diabetic complications. Despite the availability of many anti-diabetic agents in the market, they are unable to meet the long-term treatment goals. Also, they cause many side effects which justify the need for novel class of anti-diabetic drugs with newer mechanism of action. Wnt signaling is one of such novel target pathways which can be explored for metabolic disorders. Many key components of the Wnt signaling are involved in the regulation of glucose homeostasis. Polymorphism in the Transcription factor 7-like 2 (TCF7L2) gene, and mutations in the LRP5 (LDL Receptor Related Protein 5) gene lead to disturbed glucose metabolism and obesity. Despite of several years of research in this field, there is no concrete proof of concept available on whether Wnt activation or Wnt inhibition is the beneficial approach for the treatment of T2DM. Here, we have summarized the conclusions of relevant published research studies to give structured insights into possibilities to explore Wnt modulation as a novel target pathway for the treatment of T2DM. The review also highlights the present challenges and future opportunities towards the development of anti-diabetic small molecules targeting the Wnt signaling pathway.

A genomics perspective of personalized prevention and management of obesity

This review discusses the landscape of personalized prevention and management of obesity from a nutrigenetics perspective. Focusing on macronutrient tailoring, we discuss the impact of genetic variation on responses to carbohydrate, lipid, protein, and fiber consumption. Our bioinformatic analysis of genomic variants guiding macronutrient intake revealed enrichment of pathways associated with circadian rhythm, melatonin metabolism, cholesterol and lipoprotein remodeling and PPAR signaling as potential targets of macronutrients for the management of obesity in relevant genetic backgrounds. Notably, our data-based in silico predictions suggest the potential of repurposing the SYK inhibitor fostamatinib for obesity treatment in relevant genetic profiles. In addition to dietary considerations, we address genetic variations guiding lifestyle changes in weight management, including exercise and chrononutrition. Finally, we emphasize the need for a refined understanding and expanded research into the complex genetic landscape underlying obesity and its management.

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

OBJECTIVE

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

SUBJECTS AND METHODS

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

RESULTS

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

CONCLUSION

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

Insulin Resistance/Diabetes and Schizophrenia: Potential Shared Genetic Factors and Implications for Better Management of Patients with Schizophrenia

Schizophrenia is a complex psychotic disorder with co-occurring conditions, including insulin resistance and type 2 diabetes (T2D). It is well established that T2D and its precursors (i.e., insulin resistance) are more prevalent in patients with schizophrenia who are treated with antipsychotics, as well as in antipsychotic-naïve patients experiencing their first episode of psychosis, compared with the general population. However, the mechanism(s) underlying the increased susceptibility, shared genetics, and possible cause-effect relationship between schizophrenia and T2D remain largely unknown. The objective of this narrative review was to synthesize important studies, including Mendelian randomization (MR) analyses that have integrated genome-wide association studies (GWAS), as well as results from in vitro models, in vivo models, and observational studies of patients with schizophrenia. Both GWAS and MR studies have found that schizophrenia and T2D/insulin resistance share genetic risk factors, and this may mediate a connection between peripheral or brain insulin resistance and T2D with cognition impairment and an increased risk of developing prediabetes and T2D in schizophrenia. Moreover, accumulating evidence supports a causal role for insulin resistance in schizophrenia and emphasizes the importance of a genetic basis for susceptibility to T2D in patients with schizophrenia before they receive psychotic treatment. The present findings and observations may have clinical implications for the development of better strategies to treat patients with schizophrenia, with both pharmacological (i.e., samidorphan, empagliflozin) and/or nonpharmacological (i.e., lifestyle changes) approaches. Additionally, this review may benefit the design of future studies by physicians and clinical investigators.

Genetic Association of Transcription Factor 7-Like-2 rs7903146 Polymorphism With Type 2 Diabetes Mellitus

INTRODUCTION

Type 2 diabetes mellitus (T2DM) mainly results from the inability of muscle, fat, and liver cells to uptake glucose due to insulin resistance or deficiency of insulin production by the pancreas. Predisposition to T2DM may be due to environmental, hereditary, or both factors. Although there are many genes involved in causing T2DM, transcription factor 7-like-2 gene (TCF7L2) rs7903146 (C/T) single nucleotide polymorphism (SNP) found in genome-wide association studies (GWAS) is susceptible to T2DM. TCF7L2 is involved in pancreatic beta cell proliferation and differentiation via the Wnt signaling mechanism.

OBJECTIVES

To find the genetic association of TCF7L2 rs7903146 (C/T) gene polymorphism in patients with T2DM.

METHODS

A case-control study was conducted on 194 T2DM patients recruited from the endocrinology department at Indira Gandhi Institute of Medical Sciences, Patna, and 180 non-diabetic healthy controls that were age and sex-matched with the patients. All clinical examination and biochemical investigations like glycosylated hemoglobin (HbA1c), total cholesterol, triglycerides, high-density lipoprotein-cholesterol, and low-density lipoprotein-cholesterol; and determination of TCF7L2 gene polymorphism by allele-specific polymerase chain reaction (AS-PCR) were carried out for each subject.

RESULTS

 The T allele of the rs7903146 (C/T) SNP was associated with a two-fold higher risk of T2DM and the heterozygous genotype (CT) with a 1.96 times higher risk.

CONCLUSION

There is a high association of this SNP with the development of T2DM in the eastern Indian population. Serial monitoring of HbA1c should be done in an individual having this type of polymorphism for early detection of T2DM to prevent future complications.

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.

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods-SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

Partners in diabetes epidemic: A global perspective

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

Transforming Medical Paradigms: A Cutting-Edge Review of Genomic and Robotic Medical and Surgical Approaches in the Battle Against Diabetes, Hypertension, and Cardiovascular Issues

This article provides an in-depth review of the current state of management for diabetes, hypertension, and cardiovascular disease, focusing on advancements from genomics to robotics. It explores the role of genomic markers in personalized medicine, offering tailored treatment options for these chronic conditions. The article also examines the efficacy of various pharmacological and surgical interventions, including bariatric surgery for diabetes and device-based treatments for hypertension. A comparative analysis is presented to evaluate the cost-effectiveness and patient outcomes between medical and surgical approaches. The review concludes that while personalized medicine and minimally invasive surgical techniques show promise, more high-quality comparative research is needed. The ultimate goal is to integrate these emerging technologies within a framework of evidence-based medicine to improve patient outcomes and health equity.

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this "simulation mis-specification" problem can be framed as a "domain adaptation" problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods-SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using the domain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

The role of sclerostin in lipid and glucose metabolism disorders

Lipid and glucose metabolism are critical for human activities, and their disorders can cause diabetes and obesity, two prevalent metabolic diseases. Studies suggest that the bone involved in lipid and glucose metabolism is emerging as an endocrine organ that regulates systemic metabolism through bone-derived molecules. Sclerostin, a protein mainly produced by osteocytes, has been therapeutically targeted by antibodies for treating osteoporosis owing to its ability to inhibit bone formation. Moreover, recent evidence indicates that sclerostin plays a role in lipid and glucose metabolism disorders. Although the effects of sclerostin on bone have been extensively examined and reviewed, its effects on systemic metabolism have not yet been well summarized. In this paper, we provide a systemic review of the effects of sclerostin on lipid and glucose metabolism based on in vitro and in vivo evidence, summarize the research progress on sclerostin, and prospect its potential manipulation for obesity and diabetes treatment.

Implication of DNA methylation during lifestyle mediated weight loss

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH

AIMS/HYPOTHESIS

Characterisation of genetic variation that influences the response to glucose-lowering medications is instrumental to precision medicine for treatment of type 2 diabetes. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH) examined the acute response to metformin and glipizide in order to identify new pharmacogenetic associations for the response to common glucose-lowering medications in individuals at risk of type 2 diabetes.

METHODS

One thousand participants at risk for type 2 diabetes from diverse ancestries underwent sequential glipizide and metformin challenges. A genome-wide association study was performed using the Illumina Multi-Ethnic Genotyping Array. Imputation was performed with the TOPMed reference panel. Multiple linear regression using an additive model tested for association between genetic variants and primary endpoints of drug response. In a more focused analysis, we evaluated the influence of 804 unique type 2 diabetes- and glycaemic trait-associated variants on SUGAR-MGH outcomes and performed colocalisation analyses to identify shared genetic signals.

RESULTS

Five genome-wide significant variants were associated with metformin or glipizide response. The strongest association was between an African ancestry-specific variant (minor allele frequency [MAFAfr]=0.0283) at rs149403252 and lower fasting glucose at Visit 2 following metformin (p=1.9×10-9); carriers were found to have a 0.94 mmol/l larger decrease in fasting glucose. rs111770298, another African ancestry-specific variant (MAFAfr=0.0536), was associated with a reduced response to metformin (p=2.4×10-8), where carriers had a 0.29 mmol/l increase in fasting glucose compared with non-carriers, who experienced a 0.15 mmol/l decrease. This finding was validated in the Diabetes Prevention Program, where rs111770298 was associated with a worse glycaemic response to metformin: heterozygous carriers had an increase in HbA1c of 0.08% and non-carriers had an HbA1c increase of 0.01% after 1 year of treatment (p=3.3×10-3). We also identified associations between type 2 diabetes-associated variants and glycaemic response, including the type 2 diabetes-protective C allele of rs703972 near ZMIZ1 and increased levels of active glucagon-like peptide 1 (GLP-1) (p=1.6×10-5), supporting the role of alterations in incretin levels in type 2 diabetes pathophysiology.

CONCLUSIONS/INTERPRETATION

We present a well-phenotyped, densely genotyped, multi-ancestry resource to study gene-drug interactions, uncover novel variation associated with response to common glucose-lowering medications and provide insight into mechanisms of action of type 2 diabetes-related variation.

DATA AVAILABILITY

The complete summary statistics from this study are available at the Common Metabolic Diseases Knowledge Portal ( https://hugeamp.org ) and the GWAS Catalog ( www.ebi.ac.uk/gwas/ , accession IDs: GCST90269867 to GCST90269899).

Body Fat Distribution, Fasting Insulin Levels, and Insulin Secretion: A Bidirectional Mendelian Randomization Study

CONTEXT

Hyperinsulinemia and adiposity are associated with one another, but the directionality of this relation is debated.

OBJECTIVE

Here, we tested the direction of the causal effects of fasting insulin (FI) levels and body fat accumulation/distribution using 2-sample bidirectional Mendelian randomization (MR).

METHODS

We included summary statistics from large-scale genome-wide association studies for body mass index (BMI, n = 806 834), waist to hip ratio adjusted for BMI (WHRadjBMI, n = 694 649), abdominal subcutaneous, visceral and gluteofemoral adipose tissue (n = 38 965), FI levels (n = 98 210), pancreatic islets gene expression (n = 420), and hypothalamus gene expression (n = 155). We used inverse variance-weighted and robust MR methods that relied on statistically and biologically driven genetic instruments.

RESULTS

Both BMI and WHRadjBMI were positively associated with FI. Results were consistent across all robust MR methods and when variants mapped to the hypothalamus (presumably associated with food behavior) were included. In multivariable MR analyses, when waist circumference and BMI were mutually adjusted, the direct effect of waist circumference on FI was 2.43 times larger than the effect of BMI on FI. FI was not associated with adiposity. By contrast, using genetic instruments mapped to gene expression in pancreatic islets (presumably more specific to insulin secretion), insulin was positively associated with BMI and abdominal subcutaneous and gluteofemoral adipose tissue, but not with visceral adipose tissue.

CONCLUSION

Although these results will need to be supported by experimental investigations, results of this MR study suggest that abdominal adiposity may be a key determinant of circulating insulin levels. Alternatively, insulin secretion may promote peripheral adipose tissue accumulation.

3D genome alterations and editing in pathology

The human genome is folded into a multi-level 3D structure that controls many nuclear functions including gene expression. Recently, alterations in 3D genome organization were associated with several genetic diseases and cancer. As a consequence, experimental approaches are now being developed to modify the global 3D genome organization and that of specific loci. Here, we discuss emerging experimental approaches of 3D genome editing that may prove useful in biomedicine.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P_FDR = 3.40 × 10^-5), CCR5 rs333 (OR = 1.99, P_FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P_FDR = 2.64 × 10^-4), TCF7L2 rs114758349 (OR = 1.77, P_FDR = 9.37 × 10^-5), and CCL2 rs1024611 (OR = 1.38, P_FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10^-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

The role of cereal soluble fiber in the beneficial modulation of glycometabolic gastrointestinal hormones

According to cohort studies, cereal fiber, and whole-grain products might decrease risk for type 2 diabetes (T2DM), inflammatory processes, cancer, and cardiovascular diseases. These associations, mainly affect insoluble, but not soluble cereal fiber. In intervention studies, soluble fiber elicit anti-hyperglycemic and anti-inflammatory short-term effects, partially explained by fermentation to short-chain fatty acids, which acutely counteract insulin resistance and inflammation. ß-glucans lower cholesterol levels and possibly reduce liver fat. Long-term benefits are not yet shown, maybe caused by T2DM heterogeneity, as insulin resistance and fatty liver disease - the glycometabolic points of action of soluble cereal fiber - are not present in every patient. Thus, only some patients might be susceptive to fiber. Also, incretin action in response to fiber could be a relevant factor for variable effects. Thus, this review aims to summarize the current knowledge from human studies on the impact of soluble cereal fiber on glycometabolic gastrointestinal hormones. Effects on GLP-1 appear to be highly contradictory, while these fibers might lower GIP and ghrelin, and increase PYY and CCK. Even though previous results of specific trials support a glycometabolic benefit of soluble fiber, larger acute, and long-term mechanistic studies are needed in order to corroborate the results.

Deciphering the role of aberrant DNA methylation in NAFLD and NASH

The global incidence of nonalcoholic fatty liver disease (NAFLD) is mounting incessantly, and it is emerging as the most frequent cause of chronic and end stage liver disorders. It is the starting point for a range of conditions from simple steatosis to more progressive nonalcoholic steatohepatitis (NASH) and associated hepatocellular carcinoma (HCC). Dysregulation of insulin secretion and dyslipidemia due to obesity and other lifestyle variables are the primary contributors to establishment of NAFLD. Onset and progression of NAFLD is orchestrated by an interplay of metabolic environment with genetic and epigenetic factors. An incompletely understood mechanism of NAFLD progression has greatly hampered the progress in identification of novel prognostic and therapeutic strategies. Emerging evidence suggests altered DNA methylation pattern as a key determinant of NAFLD pathogenesis. Environmental and lifestyle factors can manipulate DNA methylation patterns in a reversible manner, which manifests as changes in gene expression. In this review we attempt to highlight the importance of DNA methylation in establishment and progression of NAFLD. Development of novel diagnostic, prognostic and therapeutic strategies centered around DNA methylation signatures and modifiers has also been explored.

On the Verge of Precision Medicine in Diabetes

The epidemic of type 2 diabetes (T2D) is a significant global public health challenge and a major cause of morbidity and mortality. Despite the recent proliferation of pharmacological agents for the treatment of T2D, current therapies simply treat the symptom, i.e. hyperglycemia, and do not directly address the underlying disease process or modify the disease course. This article summarizes how genomic discovery has contributed to unraveling the heterogeneity in T2D, reviews relevant discoveries in the pharmacogenetics of five commonly prescribed glucose-lowering agents, presents evidence supporting how pharmacogenetics can be leveraged to advance precision medicine, and calls attention to important research gaps to its implementation to guide treatment choices.

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.

β-cell dynamics in type 2 diabetes and in dietary and exercise interventions

Pancreatic β-cell dysfunction and insulin resistance are two of the major causes of type 2 diabetes (T2D). Recent clinical and experimental studies have suggested that the functional capacity of β-cells, particularly in the first phase of insulin secretion, is a primary contributor to the progression of T2D and its associated complications. Pancreatic β-cells undergo dynamic compensation and decompensation processes during the development of T2D, in which metabolic stresses such as endoplasmic reticulum stress, oxidative stress, and inflammatory signals are key regulators of β-cell dynamics. Dietary and exercise interventions have been shown to be effective approaches for the treatment of obesity and T2D, especially in the early stages. Whilst the targeted tissues and underlying mechanisms of dietary and exercise interventions remain somewhat vague, accumulating evidence has implicated the improvement of β-cell functional capacity. In this review, we summarize recent advances in the understanding of the dynamic adaptations of β-cell function in T2D progression and clarify the effects and mechanisms of dietary and exercise interventions on β-cell dysfunction in T2D. This review provides molecular insights into the therapeutic effects of dietary and exercise interventions on T2D, and more importantly, it paves the way for future research on the related underlying mechanisms for developing precision prevention and treatment of T2D.

TCF7L2 plays a complex role in human adipose progenitor biology, which might contribute to genetic susceptibility to type 2 diabetes

INTRODUCTION

Non-coding genetic variation at TCF7L2 is the strongest genetic determinant of type 2 diabetes (T2D) risk in humans. TCF7L2 encodes a transcription factor mediating the nuclear effects of WNT signaling in adipose tissue (AT). In vivo studies in transgenic mice have highlighted important roles for TCF7L2 in adipose tissue biology and systemic metabolism.

OBJECTIVE

To map the expression of TCF7L2 in human AT, examine its role in human adipose cell biology in vitro, and investigate the effects of the fine-mapped T2D-risk allele at rs7903146 on AT morphology and TCF7L2 expression.

METHODS

Ex vivo gene expression studies of TCF7L2 in whole and fractionated human AT. In vitro TCF7L2 gain- and/or loss-of-function studies in primary and immortalized human adipose progenitor cells (APCs) and mature adipocytes (mADs). AT phenotyping of rs7903146 T2D-risk variant carriers and matched controls.

RESULTS

Adipose progenitors (APs) exhibited the highest TCF7L2 mRNA abundance compared to mature adipocytes and adipose-derived endothelial cells. Obesity was associated with reduced TCF7L2 transcript levels in whole subcutaneous abdominal AT but paradoxically increased expression in APs. In functional studies, TCF7L2 knockdown (KD) in abdominal APs led to dose-dependent activation of WNT/β-catenin signaling, impaired proliferation and dose-dependent effects on adipogenesis. Whilst partial KD enhanced adipocyte differentiation, near-total KD impaired lipid accumulation and adipogenic gene expression. Over-expression of TCF7L2 accelerated adipogenesis. In contrast, TCF7L2-KD in gluteal APs dose-dependently enhanced lipid accumulation. Transcriptome-wide profiling revealed that TCF7L2 might modulate multiple aspects of AP biology including extracellular matrix secretion, immune signaling and apoptosis. The T2D-risk allele at rs7903146 was associated with reduced AP TCF7L2 expression and enhanced AT insulin sensitivity.

CONCLUSIONS

TCF7L2 plays a complex role in AP biology and has both dose- and depot-dependent effects on adipogenesis. In addition to regulating pancreatic insulin secretion, genetic variation at TCF7L2 might also influence T2D risk by modulating AP function.

Combined effect of pancreatic lipid content and gene variants (TCF7L2, WFS1 and 11BHSD1) on B-cell function in Middle Aged Women in a Post Hoc Analysis

BACKGROUND

TCF7L2 rs7903146 and PNPLA3 rs738409 gene variants confer the strongest risk for type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD), respectively. Pancreatic triacylglycerol content (PTGC) was reported to have a role in T2DM development. We aimed to assess the correlation between PTGC and hepatic triacylglycerol content (HTGC) stratified by PNPLA3 rs738409 genotype and subsequently interactions between PTGC and gene variants associated with β-cell dysfunction (TCF7L2, WFS1) and visceral adiposity (11ΒHSD1) on β-cell function were also tested.

METHODS

PTGC and HTGC were assessed using MR in a post-hoc analysis of a genotype-based (PNPLA3 rs738409) recall study of 39 (lipid- and glucose lowering) drug-naïve women. Oral glucose tolerance test, HbA1c, insulin indices, anthropometric data were evaluated. The effect of minor allele carrying of TCF7L2 (rs7903146); WFS1 (rs1801214) and 11ΒHSD1 (rs4844880) variants in combination with PTGC was studied on surrogate markers of β-cell function. We used Spearman's rank-order, Mann-Whitney-U tests, and linear regression models.

RESULTS

PTGC and HTGC values were correlated after stratification by the rs738409 variant (only in CC genotype group R = 0.67, p = 10- 4). PTGC and HbA1c values correlated in the entire study population (R = 0.58, p = 10- 4). Insulin resistance, sensitivity and disposition indices were correlated with PTGC (HOMA2-IR: R = 0.42, p = 0.008; TyG: R = 0.38, p = 0.018; Matsuda: R= - 0.48, p = 0.002; DIbasal: R=-0.33, p = 0.039; ISSI-2: R=-0.35, p = 0.028). Surrogate markers of β-cell function (HOMA2-B, AUCinsulin/AUCglucose) correlated significantly with PTGC in subjects with the following genotypes rs7903146: CC R = 0.51, p = 0.022; rs18001214: CT + CC R = 0.55, p = 0.013; rs4844880: TA + AA R = 0.56, p = 0.016. The strongest interactions were found between PTGC and TCF7L2 rs7903146 effect on HOMA2-B (p = 0.001) and AUCinsulin/AUCglucose (p = 0.013).

CONCLUSIONS

The PNPLA3 rs738409 genotype has a major effect on the correlation between PTGC and HTGC. Furthermore we first report the combined effect of PTGC and individual risk gene variants of TCF7L2, WFS1 and 11ΒHSD1 on β-cell dysfunction. The correlation between pancreatic lipid accumulation and HbA1c also indicates an important role for the latter pathology.

Olanzapine Promotes the Occurrence of Metabolic Disorders in Conditional TCF7L2-Knockout Mice

Objectives: Schizophrenia (SCZ) patients display higher incidence of metabolic syndrome (MetS) and comorbidity of type II diabetes. Both atypical antipsychotics and genetic variants are believed to predispose the patients with the risk, but their interplay remains largely unknown. TCF7L2 is one of the most common genes strongly associated with glucose homeostasis which also participates in the pathogenesis of schizophrenia. In this study, we aimed to explore the regulatory roles of TCF7L2 in atypical antipsychotics-induced MetS.

Methods: Mice with pancreatic β-cell–specific Tcf7l2 deletion (CKO) were generated. The CKO mice and control littermates were subjected to olanzapine (4 mg/kg/day) or saline gavage for 6 weeks. Metabolic indices, β cell mass, and the expressing levels of TCF7L2 and GLP-1R in the pancreatic tissue were closely monitored.

Results: Tcf7l2 CKO mice displayed a spectrum of core features of MetS, which included remarkably increased rate of weight gain, higher fasting insulin, higher values of blood lipids (cholesterol, triglyceride, and low-density lipoprotein), impaired glucose tolerance, and hypertrophy of adipocytes. Notably, these effects could be further exacerbated by olanzapine. In addition, Tcf7l2 CKO mice with the olanzapine group showed significantly decreased expressions of GLP-1R protein and a trend of reduced pancreatic β-cell mass. RT-qPCR revealed that the CKO mice presented a significantly less transcription of Sp5, an important element of the Wnt signaling pathway.

Conclusion: Our study illustrates that mice with pancreatic β-cell–targeted Tcf7l2 deletion were more vulnerable to suffer metabolic abnormalities after olanzapine administration. This impairment may be mediated by the reduced expression of GLP-1R.

Update on Non-Alcoholic Fatty Liver Disease-Associated Single Nucleotide Polymorphisms and Their Involvement in Liver Steatosis, Inflammation, and Fibrosis: A Narrative Review

Genetic factors are involved in the development, progression, and severity of NAFLD. Polymorphisms in genes regulating liver functions may increase liver susceptibility to NAFLD. Therefore, we conducted this literature study to present recent findings on NAFLD-associated polymorphisms from published articles in PubMed from 2016 to 2021. From 69 selected research articles, 20 genes and 34 SNPs were reported to be associated with NAFLD. These mutated genes affect NAFLD by promoting liver steatosis (PNPLA3, MBOAT7, TM2SF6, PTPRD, FNDC5, IL-1B, PPARGC1A, UCP2, TCF7L2, SAMM50, IL-6, AGTR1, and NNMT), inflammation (PNPLA3, TNF-α, AGTR1, IL-17A, IL-1B, PTPRD, and GATAD2A), and fibrosis (IL-1B, PNPLA3, MBOAT7, TCF7L2, GATAD2A, IL-6, NNMT, UCP, AGTR1, and TM2SF6). The identification of these genetic factors helps to better understand the pathogenesis pathways of NAFLD

Family history of menstrual irregularity or diabetes mellitus enhances the susceptibility to polycystic ovary syndrome among subjects harboring rs7903146 genetic variant of TCF7L2

Purpose

TCF7L2 mediated Wnt signaling cascade regulates glucose homeostasis by orchestrating expression, processing, and hepatic clearance of insulin. Type 2 diabetes mellitus (T2DM) and polycystic ovary syndrome (PCOS) significantly overlap in pathophysiological features with insulin resistance as a central driver. While TCF7L2 is the most potent T2DM locus, studies on the association of TCF7L2 with PCOS are limited and inconclusive. Therefore, in addition to expression profiling, the association of TCF7L2 polymorphic variant rs7903146 with PCOS was evaluated.

Methods

Using Rotterdam-2003 criteria for the diagnosis, 120 PCOS cases, and 120 age-matched controls were recruited. Subjects underwent clinical, biochemical, and hormonal assessment, followed by genotyping for rs7903146, carried out by PCR-RFLP and TCFL2 expression profiling by qRT-PCR. Genotype-phenotype correlation analysis was performed to evaluate any such associations. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were computed by conditional logistic regression.

Results

Higher odds of developing PCOS were observed in the women having a family history (FH) of either T2DM (OR = 3.86, 95% CI:1.90 - 7.83), hirsutism (OR = 4.74. 95%CI: 1.91 - 17.21) or menstrual irregularities (MI) (OR = 3.07, 95%CI: 1.61 - 8.54). The genotypes of rs7903146 did not confer any risk for developing PCOS (OR = 0.46;95%CI: 0.15 - 2.03). However, the elevated risk was seen in the subjects who harbored the variant allele and had FH of either T2DM (OR = 6.71; 95%CI: 1.89 - 23.78) or MI (OR = 9.71; 95% CI:1.89 - 23.78).

Conclusion

TCF7L2 polymorphic variant rs7903146 is not independently linked to PCOS risk, but modulates the risk in the subjects having a family history of either T2DM or MI.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-022-01050-y.

Role of EPO and TCF7L2 Gene Polymorphism Contribution to the Occurrence of Diabetic Retinopathy

Objective: For studying the association of EPO (rs551238), EPO (rs1617640), and TCF7L2 (rs7903146) gene with diabetic retinopathy in Northern Chinese population. Methods: We conducted a case-control study, which enrolled 680 subjects and performed SNP genotyping and calculated allele frequencies. Results: When comparison was performed between DR patients and normal persons, the EPO (rs551238) AA genotype has a significant risk association with DR, and AC genotype has a significant protective association with DR. The EPO (rs551238) A allele has a significant risk association with DR, and C allele has a significant protective association with DR. When comparison was performed between DR patients and DM patients, the EPO (rs551238) CC genotype has a significant protective association with DR; the EPO (rs551238) A allele has a significant risk association with DR; and C allele has a significant protective association with DR. When comparison was performed between DR patients and normal persons, the EPO (rs1617640) GT genotype has a significant protective association with DR, and TT genotype has a significant risk association with DR. The EPO (rs1617640) G allele has a significant protective association with DR, and T allele has a significant risk association with DR. In addition, we found that TT genotype does not exist in rs7903146 of TCF7L2 in Chinese population so that the data could not be used. Conclusions: EPO (rs551238, rs1617640) genotype is a susceptible gene for DR in Chinese type 2 diabetic patients, especially the high-risk PDR.

Is type 2 diabetes mellitus another intercellular junction-related disorder?

Type 2 diabetes mellitus (T2D) is nowadays a worldwide epidemic and has become a major challenge for health systems around the world. It is a multifactorial disorder, characterized by a chronic state of hyperglycemia caused by defects in the production as well as in the peripheral action of insulin. This minireview highlights the experimental and clinical evidence that supports the novel idea that intercellular junctions (IJs)-mediated cell-cell contacts play a role in the pathogenesis of T2D. It focuses on IJs repercussion for endocrine pancreas, intestinal barrier, and kidney dysfunctions that contribute to the onset and evolution of this metabolic disorder.

Dysregulation of Wnt signaling in bone of type 2 diabetes mellitus and diabetic Charcot arthropathy

Background

Type 2 diabetes mellitus (T2DM) patients show a markedly higher fracture risk and impaired fracture healing when compared to non-diabetic patients. However in contrast to type 1 diabetes mellitus, bone mineral density in T2DM is known to be normal or even regionally elevated, also known as diabetic bone disease. Charcot arthropathy is a severe and challenging complication leading to bone destruction and mutilating bone deformities. Wnt signaling is involved in increasing bone mineral density, bone homeostasis and apoptotic processes. It has been shown that type 2 diabetes mellitus is strongly associated with gene variants of the Wnt signaling pathway, specifically polymorphisms of TCF7L2 (transcription factor 7 like 2), which is an effector transcription factor of this pathway.

Methods

Bone samples of 19 T2DM patients and 7 T2DM patients with additional Charcot arthropathy were compared to 19 non-diabetic controls. qPCR analysis for selected members of the Wnt-signaling pathway (WNT3A, WNT5A, catenin beta, TCF7L2) and bone gamma-carboxyglutamate (BGLAP, Osteocalcin) was performed and analyzed using the 2-ΔΔCt- Method. Statistical analysis comprised one-way analysis of variance (ANOVA).

Results

In T2DM patients who had developed Charcot arthropathy WNT3A and WNT5A gene expression was down-regulated by 89 and 58% compared to healthy controls (p < 0.0001). TCF7L2 gene expression showed a significant reduction by 63% (p < 0.0001) and 18% (p = 0.0136) in diabetic Charcot arthropathy. In all diabetic patients BGLAP (Osteocalcin) was significantly decreased by at least 59% (p = 0.0019).

Conclusions

For the first time with this study downregulation of members of the Wnt-signaling pathway has been shown in the bone of diabetic patients with and without Charcot arthropathy. This may serve as future therapeutic target for this severe disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05314-9.

The Effect of Diabetes-Associated Variation in TCF7L2 on Postprandial Glucose Metabolism When Glucagon and Insulin Concentrations Are Matched

Background: The rs7903146 variant in the TCF7L2 gene is associated with defects in postprandial insulin and glucagon secretion and increased risk of type 2 diabetes. However, it is unclear if this variant has effects on glucose metabolism that are independent of islet function. Methods: We studied 54 nondiabetic subjects on two occasions where endogenous hormone secretion was inhibited by somatostatin. Twenty-nine subjects were homozygous for the diabetes-associated allele (TT) and 25 for the diabetes-protective allele (CC) at rs7903146, but otherwise matched for anthropometric characteristics. On 1 day, glucagon infused at a rate of 0.65 ng/kg/min, and at 0 min prevented a fall in glucagon (nonsuppressed day). On the contrary, infusion commenced at 120 min to create a transient fall in glucagon (suppressed day). Subjects received glucose (labeled with [3-³H]-glucose) infused to mimic the systemic appearance of oral glucose. Insulin was infused to mimic a prandial insulin response. Endogenous glucose production (EGP) was measured using the tracer dilution technique. Results: Lack of glucagon suppression increased postchallenge glucose concentrations and impaired EGP suppression. However, in the presence of matched insulin and glucagon concentrations, genetic variation in TCF7L2 did not alter glucose metabolism. Conclusion: These data suggest that genetic variation in TCF7L2 alters glucose metabolism through changes in islet hormone secretion.

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.

Association of gene polymorphisms with body weight changes in prediabetic patients

BACKGROUND

Recent research has demonstrated that Type 2 Diabetes (T2D) risk is influenced by a number of common polymorphisms, including MC4R rs17782313, PPARG rs1801282, and TCF7L2 rs7903146. Knowledge of the association between these single nucleotide polymorphisms (SNPs) and body weight changes in different forms of prediabetes treatment is still limited. The aim of this study was to investigate the association of polymorphisms within the MC4R, PPARG, and TCF7L2 genes on the risk of carbohydrate metabolism disorders and body composition changes in overweight or obese patients with early carbohydrate metabolism disorders.

METHODS AND RESULTS

From 327 patients, a subgroup of 81 prediabetic female patients (48.7 ± 14.8 years) of Eastern European descent participated in a 3-month study comprised of diet therapy or diet therapy accompanied with metformin treatment. Bioelectrical impedance analysis and genotyping of MC4R rs17782313, PPARG rs1801282, and TCF7L2 rs7903146 polymorphisms were performed. The MC4R CC and TCF7L2 TT genotypes were associated with increased risk of T2D (OR = 1.46, p = 0.05 and OR = 2.47, p = 0.006, respectively). PPARG CC homozygotes experienced increased weight loss; however, no additional improvements were experienced with the addition of metformin. MC4R TT homozygotes who took metformin alongside dietary intervention experienced increased weight loss and reductions in fat mass (p < 0.05).

CONCLUSIONS

We have shown that the obesity-protective alleles (MC4R T and PPARG C) were positively associated with weight loss efficiency. Furthermore, we confirmed the previous association of the MC4R C and TCF7L2 T alleles with T2D risk.

Estimating the Direct Effect between Dietary Macronutrients and Cardiometabolic Disease, Accounting for Mediation by Adiposity and Physical Activity

Assessing the causal effects of individual dietary macronutrients and cardiometabolic disease is challenging because distinguish direct effects from those mediated or confounded by other factors is difficult. To estimate these effects, intake of protein, carbohydrate, sugar, fat, and its subtypes were obtained using food frequency data derived from a Swedish population-based cohort (n~60,000). Data on clinical outcomes (i.e., type 2 diabetes (T2D) and cardiovascular disease (CVD) incidence) were obtained by linking health registry data. We assessed the magnitude of direct and mediated effects of diet, adiposity and physical activity on T2D and CVD using structural equation modelling (SEM). To strengthen causal inference, we used Mendelian randomization (MR) to model macronutrient intake exposures against clinical outcomes. We identified likely causal effects of genetically predicted carbohydrate intake (including sugar intake) and T2D, independent of adiposity and physical activity. Pairwise, serial- and parallel-mediational configurations yielded similar results. In the integrative genomic analyses, the candidate causal variant localized to the established T2D gene TCF7L2. These findings may be informative when considering which dietary modifications included in nutritional guidelines are most likely to elicit health-promoting effects.

A Deep-Learning Approach for Inference of Selective Sweeps from the Ancestral Recombination Graph

Detecting signals of selection from genomic data is a central problem in population genetics. Coupling the rich information in the ancestral recombination graph (ARG) with a powerful and scalable deep-learning framework, we developed a novel method to detect and quantify positive selection: Selection Inference using the Ancestral recombination graph (SIA). Built on a Long Short-Term Memory (LSTM) architecture, a particular type of a Recurrent Neural Network (RNN), SIA can be trained to explicitly infer a full range of selection coefficients, as well as the allele frequency trajectory and time of selection onset. We benchmarked SIA extensively on simulations under a European human demographic model, and found that it performs as well or better as some of the best available methods, including state-of-the-art machine-learning and ARG-based methods. In addition, we used SIA to estimate selection coefficients at several loci associated with human phenotypes of interest. SIA detected novel signals of selection particular to the European (CEU) population at the MC1R and ABCC11 loci. In addition, it recapitulated signals of selection at the LCT locus and several pigmentation-related genes. Finally, we reanalyzed polymorphism data of a collection of recently radiated southern capuchino seedeater taxa in the genus Sporophila to quantify the strength of selection and improved the power of our previous methods to detect partial soft sweeps. Overall, SIA uses deep learning to leverage the ARG and thereby provides new insight into how selective sweeps shape genomic diversity.

Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction

Pancreatic β cell dysfunction is a central component of diabetes progression. During the last decades, the genetic basis of several monogenic forms of diabetes has been recognized. Genome-wide association studies (GWAS) have also facilitated the identification of common genetic variants associated with an increased risk of diabetes. These studies highlight the importance of impaired β cell function in all forms of diabetes. However, how most of these risk variants confer disease risk, remains unanswered. Understanding the specific contribution of genetic variants and the precise role of their molecular effectors is the next step toward developing treatments that target β cell dysfunction in the era of personalized medicine. Protocols that allow derivation of β cells from pluripotent stem cells, represent a powerful research tool that allows modeling of human development and versatile experimental designs that can be used to shed some light on diabetes pathophysiology. This article reviews different models to study the genetic basis of β cell dysfunction, focusing on the recent advances made possible by stem cell applications in the field of diabetes research.

TCF7L2 gene associated postprandial triglyceride dysmetabolism- a novel mechanism for diabetes risk among Asian Indians

AIM

TCF7L2 gene is believed to increase the risk of T2DM by its effects on insulin secretion. However, the exact mechanism of this enhanced risk is not clearly known. While TCF7L2 gene has been shown to affect lipid metabolism, these effects have remained largely unexplored in the context of diabetes risk.

METHODS

Postprandial lipid responses to a standardized fat challenge test were performed in 620 Asian Indian subjects (310 with NGT and 310 with T2DM/prediabetes) and compared between the risk and wild genotypes of the rs7903146 TCF7L2 gene. In 30 subjects scheduled to undergo abdominal surgery (10 each with NGT, Prediabetes and T2DM), adipocyte TCF7L2 gene expression was also performed by real time qPCR and confirmed by protein expression in western blot.

RESULTS

T allele of rs7903146 TCF7L2 gene was confirmed as the risk allele for T2DM (OR=1.8(1.2-2.74), p=0.005). TT+CT genotypes of rs7903146 TCF7L2 gene showed significantly higher 4hrTg (p<0.01), TgAUC (p<0.01), peakTg (p<0.01) as well as higher postprandial plasma glucose (p=.006) levels and HOMA-IR (p=0.03) and significantly lower adiponectin levels (p=0.02) as compared to CC genotype. The expression of TCF7L2 gene in VAT was 11-fold higher in prediabetes group as compared to NGT (P<0.01) and 5.7-fold higher in T2DM group as compared to NGT group(P=0.003) and was significantly associated with PPTg and glucose levels.

CONCLUSION

There is significant PPTg dysmetabolism associated with the risk allele of rs7903146 polymorphism as well as adipocyte expression of TCF7L2 gene. Significant upregulation of TCF7L2 gene expression in VAT that correlates with PPTg and glycaemia is also seen in Asian Indians with glucose intolerance. Modulation of PPTg metabolism by TCF7L2 gene and the resultant PPHTg may be a novel mechanism that contributes to its diabetes risk in them.

Possible Role of rs7903146 Polymorphism of the Transcription Factor 7-Like 2 Gene in Genetic Predisposition to Type 2 Diabetes

&lt;b&gt;Background and Objective:&lt;/b&gt; The association of rs7903146 polymorphism of TCF7L2 gene with Type 2 diabetes mellitus found almost in all ethnic groups. Therefore, the current study focused on estimating this association in the Azerbaijan population for the 1st time. &lt;b&gt;Materials and Methods:&lt;/b&gt; A study was conducted on 110 patients with Type 2 diabetes mellitus and 115 healthy controls. The biochemical parameters were analyzed and calculated with an independent t-test and Fisher exact test. DNA extracted from the blood samples run in PCR. PCR was used to detect the presence of TCF7L2 rs7903146 C/T polymorphism and the products of the PCR were visualized in a 1.5% gel electrophoresis. &lt;b&gt;Results:&lt;/b&gt; According to the obtained data, T allele and TT genotype of rs7903146 polymorphism strongly correlated with the risk for Type 2 diabetes (odds ratio of 1.68 for T allele and p = 0.007, odds ratio of 3.9 for TT genotype, p = 0.0028). These results were adjusted by applying the recessive model (p = 0.003). Moreover, the biochemical parameters also show a significant difference in the fasting glucose level (p = 0.0001), fasting insulin (p = 0.0001), BMI (p = 0.0002) and age (p = 0.015) inpatient and control groups. &lt;b&gt;Conclusion:&lt;/b&gt; Based on the results, the TCF7L2 rs7903146 (C>T) polymorphism is the genetic risk factor related to Type 2 diabetes in the Azerbaijan population.

The role of Wnt pathway in obesity induced inflammation and diabetes: a review

Diabetes has become a major killer worldwide and at present, millions are affected by it. Being a chronic disease it increases the risk of other diseases ranging from pulmonary disorders to soft tissue infections. The loss of insulin-producing capacity of the pancreatic β-cells is the main reason for the development of the disease. Obesity is a major complication that can give rise to several other diseases such as cancer, diabetes, etc. Visceral adiposity is one of the major factors that play a role in the development of insulin resistance. Obesity causes a chronic low-grade inflammation in the tissues that further increases the chances of developing diabetes. Several pathways have been associated with the development of diabetes due to inflammation caused by obesity. The Wnt pathway is one such candidate pathway that is found to have a controlling effect on the development of insulin resistance. Moreover, the pathway has also been linked to obesity and inflammation. This review aims to find a connection between obesity, inflammation, and diabetes by taking the wnt pathway as the connecting link.

TCF7L2 rs7903146 Is Associated With Increased Risk of New-Onset Diabetes After Transplant: A Meta-analysis of Literature

BACKGROUND

Single nucleotide polymorphisms may influence the risk of development of new-onset diabetes after transplant (NODAT), a post-transplant clinical complication that is often implicated in allograft rejection and mortality. We performed a meta-analysis of association between transcription factor 7-like-2 (TCF7L2) rs7903146 and risk of NODAT.

METHODS

A systematic search was conducted using PubMed and ScienceDirect electronic databases for studies published between January 2001 and January 2021. Case-control or cohort studies reporting association between NODAT (diagnosis based on American Diabetes Association criteria) and TCF7L2 rs7903146 were included. MetaGenyo was used for meta-analysis (random-effects model). Pooled odds ratios with 95% confidence intervals were reported to evaluate the strength of association.

RESULTS

Two reviewers independently screened for articles. A total of 6 case-control studies were included for full-text review and quantitative analysis after screening for eligibility. Genotypic distributions were in Hardy-Weinberg equilibrium for included studies. All articles reported statistically significant association of TCF7L2 rs7903146 for risk of NODAT except for 1 study. There was moderate heterogeneity among studies (I² = 60.6%). Pooled analysis revealed 51% odds of developing NODAT with TCF7L2 rs7903146 T allele (allele contrast model: odds ratio, 1.51; 95% confidence interval, 1.13-2.02; P = .005).

CONCLUSIONS

The present meta-analysis demonstrated association between TCF7L2 variant rs7903146 and risk of developing NODAT. This finding suggest clinical implications for individuals undergoing kidney transplant.

Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes

Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the TCF7L2 locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near LRMDA was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.