The association of genetic markers for type 2 diabetes with prediabetic status - cross-sectional data of a diabetes prevention trial

Genetics of type 2 diabetes mellitus in Indian and Global Population: A Review

Background

Non-communicable diseases such as cardiovascular diseases, respiratory diseases and diabetes contribute to the majority of deaths in India. Public health programmes on non-communicable diseases (NCD) prevention primarily target the behavioural risk factors of the population. Hereditary is known as a risk factor for most NCDs, specifically, type 2 diabetes mellitus (T2DM), and hence, understanding of the genetic markers of T2DM may facilitate prevention, early case detection and management.

Main body

We reviewed the studies that explored marker-trait association with type 2 diabetes mellitus globally, with emphasis on India. Globally, single nucleotide polymorphisms (SNPs) rs7903146 of Transcription Factor 7-like 2 (TCF7L2) gene was common, though there were alleles that were unique to specific populations. Within India, the state-wise data were also taken to foresee the distribution of risk/susceptible alleles. The findings from India showcased the common and unique alleles for each region.

Conclusion

Exploring the known and unknown genetic determinants might assist in risk prediction before the onset of behavioural risk factors and deploy prevention measures. Most studies were conducted in non-representative groups with inherent limitations such as smaller sample size or looking into only specific marker-trait associations. Genome-wide association studies using data from extensive prospective studies are required in highly prevalent regions worldwide. Further research is required to understand the singular effect and the interaction of genes in predicting diabetes mellitus and other comorbidities.

SNP-Based Genetic Risk Score Modeling Suggests No Increased Genetic Susceptibility of the Roma Population to Type 2 Diabetes Mellitus

BACKGROUND

In a previous survey, an elevated fasting glucose level (FG) and/or known type 2 diabetes mellitus (T2DM) were significantly more frequent in the Roma population than in the Hungarian general population. We assessed whether the distribution of 16 single nucleotide polymorphisms (SNPs) with unequivocal effects on the development of T2DM contributes to this higher prevalence.

METHODS

Genetic risk scores, unweighted (GRS) and weighted (wGRS), were computed and compared between the study populations. Associations between GRSs and FG levels and T2DM status were investigated in separate and combined study populations.

RESULTS

The Hungarian general population carried a greater genetic risk for the development of T2DM (GRS_General = 15.38 ± 2.70 vs. GRS_Roma = 14.80 ± 2.68, p < 0.001; wGRS_General = 1.41 ± 0.32 vs. wGRS_Roma = 1.36 ± 0.31, p < 0.001). In the combined population models, GRSs and wGRSs showed significant associations with elevated FG (p < 0.001) and T2DM (p < 0.001) after adjusting for ethnicity, age, sex, body mass index (BMI), high-density Lipoprotein Cholesterol (HDL-C), and triglyceride (TG). In these models, the effect of ethnicity was relatively strong on both outcomes (FG levels: βethnicity = 0.918, p < 0.001; T2DM status: OR_ethnicity = 2.484, p < 0.001).

CONCLUSIONS

The higher prevalence of elevated FG and/or T2DM among Roma does not seem to be directly linked to their increased genetic load but rather to their environmental/cultural attributes. Interventions targeting T2DM prevention among Roma should focus on harmful environmental exposures related to their unhealthy lifestyle.

Type 2 Diabetes-Associated Genetic Polymorphisms as Potential Disease Predictors

Diabetes is a major cause of mortality worldwide. There are several types of diabetes, with type 2 diabetes mellitus (T2DM) being the most common. Many factors, including environmental and genetic factors, are involved in the etiology of the disease. Numerous studies have reported the role of genetic polymorphisms in the initiation and development of T2DM. While genome-wide association studies have identified around more than 200 susceptibility loci, it remains unclear whether these loci are correlated with the pathophysiology of the disease. The present review aimed to elucidate the potential genetic mechanisms underlying T2DM. We found that some genetic polymorphisms were related to T2DM, either in the form of single-nucleotide polymorphisms or direct amino acid changes in proteins. These polymorphisms are potential predictors for the management of T2DM.

Is bisphenol A exposure associated with the development of glucose intolerance and increased insulin resistance in Thais?

Bisphenol A (BPA), the monomeric component of polycarbonate plastics, reportedly possesses endocrine-disrupting effects. Exposure to low levels of BPA during more vulnerable periods leads to abnormalities related to sexual development in experimental animals. Moreover, recently a few epidemiological studies in Caucasians have demonstrated the association of BPA exposure with type 2 diabetes. Therefore, in the present study we examined the association of BPA exposure and abnormal glucose tolerance in Thais. This is a cross-sectional study of 240 participants aged at least 50 years, randomly selected by computer-generated random numbers within each glucose tolerance status from an oral glucose tolerance study of 661 participants. There were 80 participants in each group of type 2 diabetes, impaired glucose tolerance (IGT) and normal glucose tolerance (NGT). Serum BPA was measured by competitive ELISA. The detection rate of BPA was significantly higher in participants with IGT compared to those with NGT ( p < 0.05), while no difference was found between participants with type 2 diabetes and NGT. When participants with type 2 diabetes were stratified into those with fasting plasma glucose (FPG) under the diabetic threshold (<126 mg/dL) and those over (≥126 mg/dL), it was found that those with FPG under the diabetic threshold had measurable rates of BPA comparable to those with IGT, and rates significantly higher than the NGT group ( p < 0.05), while those with FPG over the diabetic threshold did not have higher rates of measurable BPA compared with the NGT group. In conclusion, BPA exposure is not uncommon in Thais. There is an association between BPA exposure and IGT, but not type 2 diabetes.

Genetic polymorphisms associated with overweight and obesity in uncontrolled Type 2 diabetes mellitus

Generally, obese and overweight individuals display higher free fatty acid levels, which stimulate insulin resistance. The combination of overweight or obesity with insulin resistance can trigger Type 2 diabetes mellitus (T2DM) and are primary contributing factors to the development of uncontrolled T2DM. Genetic polymorphisms also play an important role as they can impact a population's susceptibility to becoming overweight or obese and developing related chronic complications, such as uncontrolled T2DM. This review specifically examines the genetic polymorphisms associated with overweight and obesity in patients with uncontrolled T2DM. Particularly, gene polymorphisms in ADIPOQ (rs1501299 and rs17300539), LepR (rs1137101 and rs1045895), IRS2 (rs1805092), GRB14 (rs10195252 and rs3923113) and PPARG (rs1801282) have been associated with overweight and obesity in uncontrolled T2DM.

CDKN2A-rs10811661 polymorphism, waist-hip ratio, systolic blood pressure, and dyslipidemia are the independent risk factors for prediabetes in a Vietnamese population

BACKGROUND

People with prediabetes are at greater risk for heart attack, stroke, kidney disease, vision problems, nerve damage and high blood pressure, compared to those without the disease. Prediabetes is a complex disorder involving both genetic and environmental factors in its pathogenesis. This cross-sectional study aimed to investigate the independent risk factors for prediabetes, considering the contribution of genetic factors (TCF7L2-rs7903146, IRS1-rs1801278, INSR-rs3745551, CDKN2A-rs10811661, and FTO-rs9939609), socio-economic status, and lifestyle factors.

RESULTS

Among the candidate genes studied, the CDKN2A-rs10811661 polymorphism was found to be the most significant factor associated with prediabetes in the model unadjusted and adjusted for age, sex, obesity-related traits, systolic blood pressure, dyslipidemia, socio-economic status, and lifestyle factors. In the final model, the CDKN2A-rs10811661 polymorphism (OR per T allele = 1.22, 95 % CI = 1.04-1.44, P = 0.017), systolic blood pressure (OR per 10 mmHg = 1.14, 95 % CI = 1.08-1.20, P < 0.0001), waist-hip ratio (OR = 1.25, 95 % CI = 1.10-1.42, P < 0.0001), dyslipidemia (OR = 1.57, 95 % CI = 1.15-2.14, P = 0.004), and residence (OR = 1.93, 95 % CI = 2.82-4.14, P < 0.0001) were the most significant independent predictors of prediabetes, in which the power of the adjusted prediction model was 0.646.

CONCLUSIONS

The study suggested that the CDKN2A-rs10811661 polymorphism, waist-hip ratio, systolic blood pressure, and dyslipidemia were significantly associated with the increased risk of prediabetes in a Vietnamese population. The studied genetic variant had a small effect on prediabetes.

Screening for pre-diabetes using support vector machine model

The global prevalence of diabetes is rapidly increasing. Studies support screening and interventions for pre-diabetes, which results in serious complications and diabetes. This study aimed at developing an intelligence-based screening model for pre-diabetes that could assist with decreasing the prevalence of diabetes through early identification and subsequent interventions. Data from the Korean National Health and Nutrition Examination Survey (KNHANES) were used, excluding subjects with diabetes. The KNHANES 2010 data (n = 4,685) were used for training and internal validation, while data from KNHANES 2011 (n = 4,566) were used for external validation. We developed a model to screen for pre-diabetes using support vector machine (SVM), and performed a systematic evaluation of the SVM model using internal and external validation. We compared the performance of the SVM model with that of a screening score model based on logistic regression analysis for pre-diabetes that had been developed previously. Backward elimination logistic regression resulted in associations between pre-diabetes and age, sex, waist circumference, body mass index, alcohol intake, family history of diabetes, and hypertension. The areas under the curves (AUCs) for the SVM model in the internal and external datasets were 0.761 and 0.731, respectively, while the AUCs for the screening score model were 0.734 and 0.712, respectively. The SVM model developed in this study performed better than the screening score model that had been developed previously and may be more effective for pre-diabetes screening.

Screening for prediabetes using machine learning models

The global prevalence of diabetes is rapidly increasing. Studies support the necessity of screening and interventions for prediabetes, which could result in serious complications and diabetes. This study aimed at developing an intelligence-based screening model for prediabetes. Data from the Korean National Health and Nutrition Examination Survey (KNHANES) were used, excluding subjects with diabetes. The KNHANES 2010 data (n = 4685) were used for training and internal validation, while data from KNHANES 2011 (n = 4566) were used for external validation. We developed two models to screen for prediabetes using an artificial neural network (ANN) and support vector machine (SVM) and performed a systematic evaluation of the models using internal and external validation. We compared the performance of our models with that of a screening score model based on logistic regression analysis for prediabetes that had been developed previously. The SVM model showed the areas under the curve of 0.731 in the external datasets, which is higher than those of the ANN model (0.729) and the screening score model (0.712), respectively. The prescreening methods developed in this study performed better than the screening score model that had been developed previously and may be more effective method for prediabetes screening.

Not only type 2 diabetes but also prediabetes is associated with portal inflammation and fibrosis in patients with non-alcoholic fatty liver disease

AIMS

Growing evidence suggests that not only type 2 diabetes (T2D) but also prediabetes (PD) is common in patients with non-alcoholic fatty liver disease (NAFLD). However, few data exist on how PD impacts the histological characteristics of NAFLD patients. In this exploratory study, we sought to investigate the associations of PD and T2D with the severity of the histological features in patients with NAFLD.

METHODS

The population consisted of 280 patients with biopsy-proven NAFLD. The associations of PD and T2D with the severity of histological features of NAFLD were analyzed using multiple logistic (or ordinal logistic) regression models after adjustment for confounding factors.

RESULTS

PD and T2D was noted in 102 (36.4%) and 92 (32.8%) of patients, respectively. Of the 92 patients with T2D, ten (10.9%) were diagnosed de novo after the OGTT. PD and T2D were significantly associated with more severe portal inflammation (P<0.01); the adjusted odds ratios (ORs) of PD and T2D for having a higher grade of portal inflammation were 1.8 [95% CI, 1.1, 3.2] and 2.6 [95% CI, 1.3, 5.8]), respectively. A similar relationship was observed for liver fibrosis (P<0.001); specifically, the adjusted ORs of PD and T2D for having a higher grade of hepatic fibrosis were 2.4 [95% CI, 1.3, 3.7] and 3.8 [95% CI, 1.9, 6.1]), respectively.

CONCLUSION

Not only T2D but also PD is independently associated with portal inflammation and fibrosis in NAFLD patients. PD may be useful as a clinical indicator of patients who are likely to have already more severe histological findings.