Genome-wide association study identifies two novel Loci with sex-specific effects for type 2 diabetes mellitus and glycemic traits in a korean population

Interactions between Bitter Taste Receptor Gene Variants and Dietary Intake Are Associated with the Incidence of Type 2 Diabetes Mellitus in Middle-Aged and Older Korean Adults

The relationship between the variants of bitter taste receptor gene TAS2R4, dietary intake, and incidence of type 2 diabetes mellitus (T2DM) remains unclear. Hence, we aimed to examine the association of TAS2R4 rs2233998 variants with T2DM incidence in middle-aged and older Korean adults to understand if their association was modulated by dietary intake. Data of the Ansan-Ansung cohort from the Korean Genome and Epidemiology Study were used in this study. A total of 4552 Korean adults aged 40-69 years with no history of T2DM or cancer at baseline were followed-up for 16 years. Dietary intake was assessed using a 103-item food frequency questionnaire, and new T2DM cases were defined based on the World Health Organization and International Diabetes Federation criteria. Multivariate Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for T2DM incidence. During the mean follow-up period of 11.97 years, 1082 (23.77%) new T2DM cases were identified. Women carrying the TT genotype of TAS2R4 rs2233998 exhibited 1.48 times higher incidence of T2DM (HR: 1.48; 95 CI: 1.13-1.93) than those carrying the CC genotype. TAS2R4 rs2233998 variants were positively associated with the incidence of T2DM among Korean women with high intakes of carbohydrates or sugars and low intakes of fruits or vegetables. TT carrier women in the highest tertile of carbohydrate or sugar intake exhibited an increased incidence of T2DM (HR: 2.08, 95% CI: 1.33-3.27 for carbohydrates; HR: 2.31, 95% CI: 1.53-3.51 for sugars) than CC carrier women. Women carrying the TT genotype in the lowest tertile exhibited an increased incidence of T2DM (HR: 1.55, 95% CI: 1.02-2.37 for vegetables; HR: 1.62, 95% CI: 1.06-2.48 for fruits) than women carrying the CC genotype in the highest tertile of vegetable or fruit consumption. However, no association was observed between TAS2R4 rs2233998 variants and dietary intake with T2DM incidence in Korean men. Our findings suggest that variants of TAS2R4 rs2233998 are associated with T2DM incidence, and their associations are strengthened by excessive intake of carbohydrates or sugars and inadequate intake of fruits or vegetables. Diet encompassing optimal intake of carbohydrates or sugars and high intake of fruits or vegetables may minimize the risk of developing T2DM.

The potential effects of HECTD4 variants on fasting glucose and triglyceride levels in relation to prevalence of type 2 diabetes based on alcohol intake

Excessive alcohol intake is an important cause of major public health problem in East Asian countries. Growing evidence suggests that genetic factors are associated with alcohol consumption and the risk for alcohol-associated disease, and these factors contribute to the risk of developing chronic diseases, including diabetes. This study aims to investigate the association of type 2 diabetes with genetic polymorphisms within HECTD4 based on alcohol exposure. We performed a genome-wide association study involving the cohorts of the KoGES-HEXA study (n = 50,028) and Ansan and Ansung study (n = 7,980), both of which are prospective cohort studies in Korea. The top three single-nucleotide polymorphisms (SNPs) of the HECTD4 gene, specifically rs77768175, rs2074356 and rs11066280, were found to be significantly associated with alcohol consumption. We found that individuals carrying the variant allele in these SNPs had lower fasting blood glucose, triglyceride, and GGT levels than those with the wild-type allele. Multiple logistic regression showed that statistically significant associations of HECTD4 gene polymorphisms with an increased risk of type 2 diabetes were found in drinkers. Namely, these SNPs were associated with decreased odds of diabetes in the presence of alcohol consumption. As a result of examining the effect of alcohol on the expression of the HECTD4 gene, ethanol increased the expression of HECTD4 in cells, but the level was decreased by NAC treatment. Similar results were obtained from liver samples of mice treated with alcohol. Moreover, a loss of HECTD4 resulted in reduced levels of CYP2E1 and lipogenic gene expression in ethanol-treated cells, while the level of ALDH2 expression increased, indicating a reduction in ethanol-induced hepatotoxicity.

Evaluating machine learning-powered classification algorithms which utilize variants in the GCKR gene to predict metabolic syndrome: Tehran Cardio-metabolic Genetics Study

BACKGROUND

Metabolic syndrome (MetS) is a prevalent multifactorial disorder that can increase the risk of developing diabetes, cardiovascular diseases, and cancer. We aimed to compare different machine learning classification methods in predicting metabolic syndrome status as well as identifying influential genetic or environmental risk factors.

METHODS

This candidate gene study was conducted on 4756 eligible participants from the Tehran Cardio-metabolic Genetic study (TCGS). We compared predictive models using logistic regression (LR), Random Forest (RF), decision tree (DT), support vector machines (SVM), and discriminant analyses. Demographic and clinical features, as well as variables regarding common GCKR gene polymorphisms, were included in the models. We used a 10-repeated tenfold cross-validation to evaluate model performance.

RESULTS

50.6% of participants had MetS. MetS was significantly associated with age, gender, schooling years, BMI, physical activity, rs780094, and rs780093 (P < 0.05) as indicated by LR. RF showed the best performance overall (AUC-ROC = 0.804, AUC-PR = 0.776, and Accuracy = 0.743) and indicated BMI, physical activity, and age to be the most influential model features. According to the DT, a person with BMI < 24 and physical activity < 8.8 possesses a 4% chance for MetS. In contrast, a person with BMI ≥ 25, physical activity < 2.7, and age ≥ 33, has 77% probability of suffering from MetS.

CONCLUSION

Our findings indicated that, on average, machine learning models outperformed conventional statistical approaches for patient classification. These well-performing models may be used to develop future support systems that use a variety of data sources to identify persons at high risk of getting MetS.

Interactions of Habitual Coffee Consumption by Genetic Polymorphisms with the Risk of Prediabetes and Type 2 Diabetes Combined

Habitual coffee consumption and its association with health outcomes may be modified by genetic variation. Adults aged 40 to 69 years who participated in the Korea Association Resource (KARE) study were included in this study. We conducted a genome-wide association study (GWAS) on coffee consumption in 7868 Korean adults, and examined whether the association between coffee consumption and the risk of prediabetes and type 2 diabetes combined was modified by the genetic variations in 4054 adults. In the GWAS for coffee consumption, a total of five single nucleotide polymorphisms (SNPs) located in 12q24.11-13 (rs2074356, rs11066015, rs12229654, rs11065828, and rs79105258) were selected and used to calculate weighted genetic risk scores. Individuals who had a larger number of minor alleles for these five SNPs had higher genetic risk scores. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) to examine the association. During the 12 years of follow-up, a total of 2468 (60.9%) and 480 (11.8%) participants were diagnosed as prediabetes or type 2 diabetes, respectively. Compared with non-black-coffee consumers, the OR (95% CI) for ≥2 cups/day by black-coffee consumers was 0.61 (0.38–0.95; p for trend = 0.023). Similarly, sugared coffee showed an inverse association. We found a potential interaction by the genetic variations related to black-coffee consumption, suggesting a stronger association among individuals with higher genetic risk scores compared to those with lower scores; the ORs (95% CIs) were 0.36 (0.15–0.88) for individuals with 5 to 10 points and 0.87 (0.46–1.66) for those with 0 points. Our study suggests that habitual coffee consumption was related to genetic polymorphisms and modified the risk of prediabetes and type 2 diabetes combined in a sample of the Korean population. The mechanisms between coffee-related genetic variation and the risk of prediabetes and type 2 diabetes combined warrant further investigation.

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.

Impaired fasting glucose and development of chronic kidney disease in non-diabetic population: a Mendelian randomization study

INTRODUCTION

Diabetes mellitus is a risk factor of chronic kidney disease (CKD); however, the relationship between fasting glucose and CKD remains controversial in non-diabetic population. This study aimed to assess causal relationship between genetically predicted fasting glucose and incident CKD.

RESEARCH DESIGN AND METHODS

This study included 5909 participants without diabetes and CKD from the Korean Genome Epidemiology Study. The genetic risk score (GRS₉) was calculated using nine genetic variants associated with fasting glucose in previous genome-wide association studies. Incident CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m² and/or proteinuria (≥1+). The causal relationship between fasting glucose and CKD was evaluated using the Mendelian randomization (MR) approach.

RESULTS

The GRS₉ was strongly associated with fasting glucose (β, 1.01; p<0.001). During a median follow-up of 11.6 years, 490 (8.3%) CKD events occurred. However, GRS₉ was not significantly different between participants with CKD events and those without. After adjusting for confounding factors, fasting glucose was not associated with incident CKD (OR 0.990; 95% CI 0.977 to 1.002; p=0.098). In the MR analysis, GRS₉ was not associated with CKD development (OR per 1 SD increase, 1.179; 95% CI 0.819 to 1.696; p=0.376). Further evaluation using various other MR methods and strict CKD criteria (decrease in the eGFR of ≥30% to a value of <60 mL/min/1.73 m²) found no significant relationship between GRS₉ and incident CKD.

CONCLUSIONS

Fasting glucose was not causally associated with CKD development in non-diabetic population.

Association of transcription factor 7-like 2 (TCF7L2) gene polymorphism with type 2 diabetes mellitus in Chinese Korean ethnicity population

Presently, data on the type 2 diabetes mellitus (T2DM) in Chinese Korean ethnicity are very scarce. This study aimed to explore the relationship between the transcription factor 7-like 2 (TCF7L2) and T2DM in Chinese Korean ethnicity population. This case-control study involved 43 T2DM Chinese Korean ethnicity patients (T2DM group) and 43 healthy Chinese Korean ethnicity normoglycemic subjects as controls (Control group). All included participants aged from 40 to 75 years old. Clinical and biological data were collected to determine the phenotypic traits. The restriction fragment length polymorphism-polymerase chain reaction was used to analyze the TCF7L2 by genotyping for rs7903146 (C/T). Spectrophotometer with Chronolab kits was used to conduct the biochemical analyses. TCF7L2 was associated with T2DM in the Chinese Korean ethnicity population (P < .01 for alleles, and P < .05 for genotypes). Significant differences were found 2 groups regarding the T allele (37.2% T2DM patients vs 15.1% healthy subjects, P < .01), and G allele (62.8% T2DM patients vs 84.9% healthy subjects, P < .01). The risk genotypes were GG (83.7% T2DM patients, vs 44.2% healthy control, P < .01), GT (4.7% T2DM patients, vs 20.9% healthy control, P = .04), and TT (11.6% T2DM patients, vs 34.9% healthy control, P = .01). The results of this study demonstrated that TCF7L2 is associated with T2DM in the Chinese Korean ethnicity population, which is an important risk factor for T2DM in this population.

New Common and Rare Variants Influencing Metabolic Syndrome and Its Individual Components in a Korean Population

To identify novel loci for susceptibility to MetS, we conducted genome-wide association and exome wide association studies consisting of a discovery stage cohort (KARE, 1946 cases and 6427 controls), and a replication stage cohort (HEXA, 430 cases and 3,264 controls). For finding genetic variants for MetS, with its components, we performed multivariate analysis for common and rare associations, using a standard logistic regression analysis for MetS. From the discovery and replication GWA studies, we confirmed 21 genome-wide signals significantly associated with MetS. Of these 21, four were previously unreported to associate with any MetS components: rs765547 near LPL; rs3782889 in MYL2; and rs11065756 and rs10849915 in CCDC63. Using exome chip variants, gene-based analysis of rare variants revealed three genes, CETP, SH2B1, and ZFP2, in the discovery stage, among which only CETP was confirmed in the replication stage. Finally, CETP D442G (rs2303790) associated, as a less common variant, with decreased risk of MetS. In conclusion, we discovered a total of five new MetS-associated loci, and their overlap with other disease-related components, suggest roles in the various etiologies of MetS, and its possible preventive strategies.

Opposite Genetic Effects of CMIP Polymorphisms on the Risk of Type 2 Diabetes and Obesity: A Family-Based Study in China

C-Maf Inducing Protein (CMIP) gene polymorphisms were reported to be associated with type 2 diabetes mellitus (T2DM). Whether the association between CMIP and T2DM is mediated via obesity-related phenotypes is still unclear. We analyzed the association of CMIP rs2925979 with T2DM and a comprehensive set of obesity-related phenotypes in 1576 families ascertained from a Chinese population. These families included a total of 3444 siblings (1582 with T2DM, 963 with prediabetes, and 899 with a normal glucose level). Using multi-level mixed effects regression models, we found that each copy of CMIP rs2925979_T allele was associated with a 29% higher risk of T2DM in females (p = 9.30 × 10^-4), while it was not significantly associated with T2DM in males (p = 0.705). Meanwhile, rs2925979_T allele was associated with lower levels of body mass index (BMI), waist circumference (WC), hip circumference (HC), percentage of body fat (PBF), PBF of arms, PBF of legs, and PBF of trunk in nondiabetes females (all p < 0.05). The opposite associations of rs2925979_T allele with T2DM and obesity-related phenotypes suggest that CMIP may exert independent pleiotropic effects on T2DM and obesity-related phenotypes in females.

Association of Fasting Glucose Level with Neutrophil-Lymphocyte Ratio Compared to Leukocyte Count and Serum C-Reactive Protein

Background

The neutrophil-lymphocyte ratio (NLR) is often used as an inflammatory marker in chronic diseases such as cancer or cardiovascular diseases. However, there are few studies about the association between the NLR and diabetes mellitus (DM) or impaired fasting glucose (IFG) patients in Korea. This study investigated the association between the fasting plasma glucose (FPG) level and NLR in Koreans.

Methods

This cross-sectional retrospective study included 3,219 healthy subjects who visited Konyang University Hospital in South Korea for regular health examinations. Participants with a history of insulin administration, anti-diabetic drugs, anti-inflammatory drugs, or underlying diseases related to inflammation were excluded.

Results

All statistical evaluation was performed by dividing participants into males and females. Based on FPG levels, the subjects were classified into three groups, with normal fasting glucose (n=1,969), IFG (n=1,138), and DM (n=122). The NLR had no significant mean differences among these groups for both sexes. Multiple linear regression analysis between FPG level and NLR showed an independent and significantly negative association (β±standard error, −0.67±0.24; P=0.006) in normal subjects after adjustment. Log(serum C-reactive protein [S-CRP]) showed an independently and significantly positive association with FPG in male IFG/DM patients. Total leukocyte (white blood cell [WBC]) showed an independently and significantly positive association with FPG in female IFG/DM patients.

Conclusion

In normal subjects, NLR shows an independently and significantly negative association with FPG. In IFG/DM patients, NLR was not significantly related to FPG. WBC count in female patients and S-CRP level in male patients were significantly positively associated with FPG only in IFG/DM.

Association of genetic variants in RETN, NAMPT and ADIPOQ gene with glycemic, metabolic traits and diabetes risk in a Chinese population

Abnormal serum levels of adipokine have been established to be a strong predictor of developing several human diseases including type 2 diabetes mellitus (T2DM). Association studies have reported several genetic variants in genes coding adipokines with contributions to T2DM susceptibility as well as some glycemic and metabolic traits, of which the single nucleotide polymorphisms (SNPs) of RETN, NAMPT, and ADIPOQ gene were well documented. However, little is known about contributions of these SNPs to above phenotypes in Chinese. In the current study, with availably quantitative glycemic and metabolic data from a total of 185 T2DM patients and 191 healthy controls, we tested associations between four SNPs of RETN, NAMPT, ADIPOQ gene and 13 glycemic and metabolic traits. The results showed that the rs1862513 and rs34861192 of RETN gene were functional and negatively correlated with the levels of serum creatinine and cholesterol, respectively. The rs16861194 of ADIPOQ gene was positively correlated with the aspartate aminotransferase (AST) and AST/alanine aminotransferase level. Moreover, the rs34861192 and rs13237989 of NAMPT gene synergistically affected the levels of insulin and glycemic index. However, due to the limited sample size, only the rs16861194 exerted a significant increased risk on T2DM. These results underscore the contributions of SNPs in RETN, NAMPT, ADIPOQ gene to glycemic and metabolic traits as well as T2DM susceptibility in Chinese.

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.

Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

Type 2 Diabetes Genetic Variants and Risk of Diabetic Retinopathy

PURPOSE

Genetic association studies to date have not identified any robust risk loci for diabetic retinopathy (DR). We hypothesized that individuals with more diabetes genetic risk alleles have a higher risk of developing DR.

DESIGN

Case-control genetic association study.

PARTICIPANTS

We evaluated the aggregate effects of multiple type 2 diabetes-associated genetic variants on the risk of DR among 1528 participants with diabetes from the Singapore Epidemiology of Eye Diseases Study, of whom 547 (35.8%) had DR.

METHODS

Participants underwent a comprehensive ocular examination, including dilated fundus photography. Retinal photographs were graded using the modified Airlie House classification system to assess the presence and severity of DR following a standardized protocol. We identified 76 previously discovered type 2 diabetes-associated single nucleotide polymorphisms (SNPs) and constructed multilocus genetic risk scores (GRSs) for each individual by summing the number of risk alleles for each SNP weighted by the respective effect estimates on DR. Two GRSs were generated: an overall GRS that included all 76 discovered type 2 diabetes-associated SNPs, and an Asian-specific GRS that included a subset of 55 SNPs previously found to be associated with type 2 diabetes in East and/or South Asian ancestry populations. Associations between the GRSs with DR were determined using logistic regression analyses. Discriminating ability of the GRSs was determined by the area under the receiver operating characteristic curve (AUC).

MAIN OUTCOME MEASURES

Odds ratios on DR.

RESULTS

Participants in the top tertile of the overall GRS were 2.56-fold more likely to have DR compared with participants in the lowest tertile. Participants in the top tertile of the Asian-specific GRS were 2.00-fold more likely to have DR compared with participants in the bottom tertile. Both GRSs were associated with higher DR severity levels. However, addition of the GRSs to traditional risk factors improved the AUC only modestly by 3% to 4%.

CONCLUSIONS

Type 2 diabetes-associated genetic loci were significantly associated with higher risks of DR, independent of traditional risk factors. Our findings may provide new insights to further our understanding of the genetic pathogenesis of DR.

Statistical power considerations in genotype-based recall randomized controlled trials

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for gene-metformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design.

The role of vitamin D, obesity and physical exercise in regulation of glycemia in Type 2 Diabetes Mellitus patients

AIM

The aims of this study were to determine the role of vitamin D, obesity and physical exercise in the regulation of glycemia in Type 2 Diabetes Mellitus patients in a highly consanguineous population.

DESIGN

Case and control study.

SETTING

The survey was carried out at the Hamad General Hospital and Primary Health Care (PHC) centers in the State of Qatar.

SUBJECTS

The study was conducted from November 2012 to June 2014 among subjects above 30 years of age. Of the 2224 registered with diagnosed diabetes and free diseases attending Hamad General Hospital and PHC centers agreed and gave their consent to study.

METHODS

Questionnaire included socio-demographic variables, body mass index (BMI), consanguinity, lifestyle habits, family history of diabetes, blood pressure and development of diabetes complications such as retinopathy, nephropathy, and neuropathy were collected at regular intervals throughout the follow-up. Univariate and multivariate statistical analysis were performed.

RESULTS

There were statistically significant difference between patients with diabetic and control in terms of ethnicity (p=0.012), level of education (p=0.002), occupation (p<0.001), monthly income (p<0.001), BMI(p=0.024), sport activity (p=0.018), cigarette smoking (p<0.001), consanguinity (p=0.029) and family history of Diabetes Mellitus (p<0.001) and co-morbidity hypertension (p=0.041). Further, the biochemistry values in the studied subjects with T2DM compared to healthy controls and the study revealed that serum Vitamin D, BMI, fasting glucose level, calcium, HbA1c, total cholesterol HDL, LDL, bilirubin, triglycerides, uric acid and blood pressure systolic and diastolic were higher in T2DM compared to their counterparts. Multivariate logistic regression showed that vitamin D deficiency ng/mL, Family History of T2DM, BMI (kg/m²) hypertension, consanguinity, income, mother occupation, ethnicity, educational level and Lack of physical exercise variables were significant predictors of diabetes. In the group of Diabetes Mellitus Type 2 patients, 39.3% as opposed to 51.2% in the control group had vitamin D deficiency, 25(OH) D3 levels≤10ng/ml (p<0.001). In the group of Diabetes Mellitus Type 2 patients, 34.6% as opposed to 37.9% in the control group had vitamin D insufficiency, 25(OH)D3 levels <20ng/ml (p < 0.001). In the group of Diabetes Mellitus Type 2 patients, 22.8% as opposed to 14.2% in the control group had vitamin D sufficiency, 25(OH)D3 levels >30 10ng/ml (p < 0.001).

CONCLUSION

Vitamin D, family history of diabetes, consanguinity marriages' and hereditary gene-environment interactions and physical exercise may also contribute to the current diabetes epidemic in Qatari's Arab populations.

Analysis of multiple related phenotypes in genome-wide association studies

Most genome-wide association studies (GWAS) have been conducted by focusing on one phenotype of interest for identifying genetic variants associated with common complex phenotypes. However, despite many successful results from GWAS, only a small number of genetic variants tend to be identified and replicated given a very stringent genome-wide significance criterion, and explain only a small fraction of phenotype heritability. In order to improve power by using more information from data, we propose an alternative multivariate approach, which considers multiple related phenotypes simultaneously. We demonstrate through computer simulation that the multivariate approach can improve power for detecting disease-predisposing genetic variants and pleiotropic variants that have simultaneous effects on multiple related phenotypes. We apply the multivariate approach to a GWA dataset of 8,842 Korean individuals genotyped for 327,872 SNPs, and detect novel genetic variants associated with metabolic syndrome related phenotypes. Considering several related phenotype simultaneously, the multivariate approach provides not only more powerful results than the conventional univariate approach but also clue to identify pleiotropic genes that are important to the pathogenesis of many related complex phenotypes.

Sex and Gender Differences in Risk, Pathophysiology and Complications of Type 2 Diabetes Mellitus

The steep rise of type 2 diabetes mellitus (T2DM) and associated complications go along with mounting evidence of clinically important sex and gender differences. T2DM is more frequently diagnosed at lower age and body mass index in men; however, the most prominent risk factor, which is obesity, is more common in women. Generally, large sex-ratio differences across countries are observed. Diversities in biology, culture, lifestyle, environment, and socioeconomic status impact differences between males and females in predisposition, development, and clinical presentation. Genetic effects and epigenetic mechanisms, nutritional factors and sedentary lifestyle affect risk and complications differently in both sexes. Furthermore, sex hormones have a great impact on energy metabolism, body composition, vascular function, and inflammatory responses. Thus, endocrine imbalances relate to unfavorable cardiometabolic traits, observable in women with androgen excess or men with hypogonadism. Both biological and psychosocial factors are responsible for sex and gender differences in diabetes risk and outcome. Overall, psychosocial stress appears to have greater impact on women rather than on men. In addition, women have greater increases of cardiovascular risk, myocardial infarction, and stroke mortality than men, compared with nondiabetic subjects. However, when dialysis therapy is initiated, mortality is comparable in both males and females. Diabetes appears to attenuate the protective effect of the female sex in the development of cardiac diseases and nephropathy. Endocrine and behavioral factors are involved in gender inequalities and affect the outcome. More research regarding sex-dimorphic pathophysiological mechanisms of T2DM and its complications could contribute to more personalized diabetes care in the future and would thus promote more awareness in terms of sex- and gender-specific risk factors.

Recent progress in genetic and epigenetic research on type 2 diabetes

Type 2 diabetes (T2DM) is a common complex metabolic disorder that has a strong genetic predisposition. During the past decade, progress in genetic association studies has enabled the identification of at least 75 independent genetic loci for T2DM, thus allowing a better understanding of the genetic architecture of T2DM. International collaborations and large-scale meta-analyses of genome-wide association studies have made these achievements possible. However, whether the identified common variants are causal is largely unknown. In addition, the detailed mechanism of how these genetic variants exert their effect on the pathogenesis of T2DM requires further investigation. Currently, there are ongoing large-scale sequencing studies to identify rare, functional variants for T2DM. Environmental factors also have a crucial role in the development of T2DM. These could modulate gene expression via epigenetic mechanisms, including DNA methylation, histone modification and microRNA regulation. There is evidence that epigenetic changes are important in the development of T2DM. Recent studies have identified several DNA methylation markers of T2DM from peripheral blood and pancreatic islets. In this review, we will briefly summarize the recent progress in the genetic and epigenetic research on T2DM and discuss how environmental factors, genetics and epigenetics can interact in the pathogenesis of T2DM.

No Interaction with Alcohol Consumption, but Independent Effect of C12orf51 (HECTD4) on Type 2 Diabetes Mellitus in Korean Adults Aged 40-69 Years: The KoGES_Ansan and Ansung Study

Previously, genetic polymorphisms of C12orf51 (HECTD4) (rs2074356 and/or rs11066280) have been shown to be related to alcohol consumption and type 2 diabetes (T2D). This study aimed to prospectively examine whether C12orf51 had an interaction with or independent effect on alcohol consumption and the risk of T2D. The present study included 3,244 men and 3,629 women aged 40 to 69 years who participated in the Korean Genome and Epidemiology Study (KoGES)_Ansan and Ansung Study. Cox proportional hazards models were used to estimate HRs and 95% CIs for T2D. rs2074356 and rs11066280 were associated with the risk of T2D after adjusting for alcohol consumption (rs2074356 for AA: HR = 0.39 and 95% CI = 0.17–0.87 in men, and HR = 0.36 and 95% CI = 0.13–0.96 in women; rs11066280 for AA: HR = 0.44 and 95% CI = 0.23–0.86 in men, and HR = 0.39 and 95% CI = 0.16–0.94 in women). We identified that the association of each variant (rs2074356 and rs11065756) in C12orf51 was nearly unchanged after adjusted for alcohol consumption. Therefore, the association of 2 SNPs in C12orf51 with diabetes may not be mediated by alcohol use. There was no interaction effect between alcohol consumption and the SNPs with T2D. However, even in never-drinkers, minor allele homozygote strongly influenced T2D risk reduction (rs2074356 for AA: HR = 0.35, 95% CI = 0.14–0.90, and p-trend = 0.0035 in men and HR = 0.34, 95% CI = 0.13–0.93, and p-trend = 0.2348 in women; rs11066280 for AA: HR = 0.36, 95% CI = 0.16–0.82, and p-trend = 0.0014 in men and HR = 0.39, 95% CI = 0.16–0.95, and p-trend = 0.3790 in women), while alcohol consumption did not influence the risk of T2D within each genotype. rs2074356 and rs11066280 in or near C12orf51, which is related to alcohol drinking behavior, may longitudinally decrease the risk of T2D, but not through regulation of alcohol consumption.

10-year trajectory of β-cell function and insulin sensitivity in the development of type 2 diabetes: a community-based prospective cohort study

BACKGROUND

The relative contributions of β-cell function and insulin sensitivity in the pathogenesis of type 2 diabetes are not fully understood. We investigated the longitudinal change in β-cell function and insulin sensitivity in the development of diabetes and the role of genetic variants in deterioration of glucose tolerance.

METHODS

We followed up 4106 participants with normal glucose tolerance (NGT) from the Korean Genome and Epidemiology Study with oral glucose tolerance tests every 2 years for 10 years. We estimated pancreatic β-cell function with the 60 min insulinogenic index (IGI60) and insulin sensitivity with the composite (Matsuda) insulin sensitivity index (ISI). We investigated the association of 66 known type 2 diabetes genetic variants with risk of prediabetes or diabetes and impaired β-cell function and insulin sensitivity.

FINDINGS

During 10 years of follow-up, 1093 (27%) of 4106 participants developed prediabetes and 498 (12%) participants developed diabetes. Compared with participants who remained NGT, those who progressed to diabetes had a lower IGI60 (unadjusted data 5·1 μU/mmol [95% CI 0·5-56·1] vs 7·9 μU/mmol [0·5-113·8]; p<0·0001) and lower ISI (unadjusted data 8·2 [2·6-26·0] vs 10·0 [3·2-31·6]; p<0·0001) at baseline. Participants who had NGT at 10 years showed a decrease in ISI (adjusted data 10·1 [9·9-10·3] vs 7·4 [7·3-7·6]; p<0·0001) but a compensatory increase in IGI60 (adjusted data 6·9 μU/mmol [6·5-7·2] vs 11·7 μU/mmol [11·2-12·1]; p<0·0001) compared with baseline. By contrast, participants who developed diabetes showed a decrease in ISI (adjusted data 8·4 [8·0-8·7] vs 3·0 [2·8-3·2]; p<0·0001) but no significant compensatory increase (p=0·95) in IGI60. A genetic variant near the glucokinase gene (rs4607517) was significantly associated with progression to prediabetes or diabetes (hazard ratio 1·27, 1·16-1·38; p=1·70 × 10(-7)).

INTERPRETATION

Decreased β-cell function, which might be determined partly by genetic factors, and impaired β-cell compensation for progressive decline in insulin sensitivity are crucial factors in the deterioration of glucose tolerance.

FUNDING

South Korean Ministry of Health & Welfare.

Recent advances in understanding the genetic architecture of type 2 diabetes

Genome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c). At the end of 2011, established loci (P < 5 × 10(-8)) totaled 55 for T2D and 32 for glycemic traits. Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05] variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations. Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF ≤ 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci. Established published loci now total ∼88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered. Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes.