The TCF7L2 Diabetes Risk Variant is Associated with HbA1C Levels: a Genome-Wide Association Meta-Analysis

Association between Transcription Factor 7-Like 2 C/T Polymorphism and Diabetic Retinopathy Risk: A Meta-Analysis

BACKGROUND

Previous studies have suggested a close association between transcription factor 7-like 2 (TCF7L2) polymorphisms and diabetic retinopathy (DR) susceptibility. However, the published results were inconsistent. This meta-analysis was conducted to review and examine the relationship between TCF7L2 rs7903146 C/T polymorphism and DR risk.

MATERIALS AND METHODS

Online databases were searched, and the related studies were identified in this meta-analysis. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated to examine the statistical power. Moreover, heterogeneity test, sensitivity accumulative analysis, and publication bias were conducted to measure the statistical effect.

RESULT

6 studies involving 12,982 subjects were included in this meta-analysis to assess the association between rs7903146 C/T polymorphism and DR susceptibility. The synthetic results indicated that the mutation of rs7903146 C/T polymorphism maybe accompanied with an increased risk for DR (T vs. C: OR = 1.26, 95% CI = 1.00-1.60, p = 0.05, I2 = 83.5%; TT vs. CC: OR = 1.79, 95% CI = 1.12-2.86, p = 0.02, I2 = 80.2%; TT vs. CC + CT: OR = 1.62, 95% CI = 1.38-1.92, p < 0.01, I2 = 32.3%). Moreover, the subgroup analysis also demonstrated an increasing risk for DR with T mutations in Caucasian descendants.

CONCLUSION

The current evidences of meta-analysis suggested that the TCF7L2 rs7903146 C/T polymorphism might play an important role in DR susceptibility.

Genetic Variants Relate to Fasting Plasma Glucose, 2-Hour Postprandial Glucose, Glycosylated Hemoglobin, and BMI in Prediabetes

Diabetes mellitus (DM) is a chronic disease that seriously threatens human health. Prediabetes is a stage in the progression of DM. The level of clinical indicators including fasting plasma glucose (FPG), 2-h postprandial glucose (2hPG), and glycosylated hemoglobin (HbA1C) are the diagnostic markers of diabetes. In this genome-wide association study (GWAS), we aimed to investigate the association of genetic variants with these phenotypes in Hainan prediabetes. In this study, we recruited 451 prediabetes patients from the residents aged ≥18 years who participated in the National Diabetes Prevalence Survey of the Chinese Medical Association in 2017. The GWAS of FPG, 2hPG, HbA1C, and body mass index (BMI) in prediabetes was analyzed with a linear model using an additive genetic model with adjustment for age and sex. We identified that rs13052524 in MRPS6 and rs62212118 in SLC5A3 were associated with 2hPG in Hainan prediabetes (p = 4.35 × 10^-6, p = 4.05 × 10^-6, respectively). Another six variants in the four genes (LINC01648, MATN1, CRAT37, and SLCO3A1) were related to HbA1C. Moreover, rs11142842, rs1891298, rs1891299, and rs11142843 in TRPM3/TMEM2 and rs78432036 in MLYCD/OSGIN1 were correlated to BMI (all p < 5 × 10^-6). This study is the first to determine the genome-wide association of FPG, 2hPG, and HbA1C, which emphasizes the importance of in-depth understanding of the phenotypes of high-value susceptibility gene markers in the diagnosis of prediabetes.

HbA1c Performance in African Descent Populations in the United States With Normal Glucose Tolerance, Prediabetes, or Diabetes: A Scoping Review

Introduction

African descent populations in the United States have high rates of type 2 diabetes and are incorrectly represented as a single group. Current glycated hemoglobin A_1c (HbA_1c) cutoffs (5.7% to <6.5% for prediabetes; ≥6.5% for type 2 diabetes) may perform suboptimally in evaluating glycemic status among African descent groups. We conducted a scoping review of US-based evidence documenting HbA_1c performance to assess glycemic status among African American, Afro-Caribbean, and African people.

Methods

A PubMed, Scopus, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) search (January 2020) yielded 3,238 articles published from January 2000 through January 2020. After review of titles, abstracts, and full texts, 12 met our criteria. HbA_1c results were compared with other ethnic groups or validated against the oral glucose tolerance test (OGTT), fasting plasma glucose (FPG), or previous diagnosis. We classified study results by the risk of false positives and risk of false negatives in assessing glycemic status.

Results

In 5 studies of African American people, the HbA_1c test increased risk of false positives compared with White populations, regardless of glycemic status. Three studies of African Americans found that HbA_1c of 5.7% to less than 6.5% or HbA_1c of 6.5% or higher generally increased risk of overdiagnosis compared with OGTT or previous diagnosis. In one study of Afro-Caribbean people, HbA_1c of 6.5% or higher detected fewer type 2 diabetes cases because of a greater risk of false negatives. Compared with OGTT, HbA_1c tests in 4 studies of Africans found that HbA_1c of 5.7% to less than 6.5% or HbA_1c of 6.5% or higher leads to underdiagnosis.

Conclusion

HbA_1c criteria inadequately characterizes glycemic status among heterogeneous African descent populations. Research is needed to determine optimal HbA_1c cutoffs or other test strategies that account for risk profiles unique to African American, Afro-Caribbean, and African people living in the United States.

The KLF14 Variant is Associated with Type 2 Diabetes and HbA1C Level

The purpose of this study was to scan variants in coding region of Krȕppel like factor14 (KLF14) locus and assess association related to type 2 diabetes (T2D) in Iranian population. We sequenced the coding region of KLF14 to scan variants in case-sibling study (92 individuals with T2D and 92 healthy older siblings). To confirm, we analyzed rs76603546 association with T2D in a larger unrelated case-control study by PCR-RFLP (475 cases and 512 controls). We analyzed the association of rs76603546 with HbA_1C, BMI, fat mass, waist circumference, fasting glucose, cholesterol and HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) using one-way ANOVA analysis. Also, association of genotypes with T2D adjusted for confounding variables was analyzed using logistic regression. HaploReg v 4.1 was used to predict rs76603546 possible function. Sequencing results analysis revealed the association of C allele of rs76603546, synonymous variant C>T, [OR 2.10 (1.38-3.20), P value < 0.001] and CC genotype of rs76603546 [OR 4.3 (1.79-10.23), P value = 0.001] with susceptibility to T2D. PCR-Restriction Fragment Length Polymorphism (RFLP) results analysis confirmed the association of rs76603546 with T2D [C allele, OR 1.91 (1.59-2.29), P value = 0.002, CC genotype, OR 3.27 (2.26-4.73), P value = 0.002 and TC genotype, OR 1.74 (1.31-2.31), P value = 0.001]. The CC genotype of rs76603546 is associated with HbA_1C level (P value < 0.001) and BMI (P value = 0.02). After adjustment with confounding variables, we observed association of CC genotype with T2D [OR 2.542 (1.25-3.77), P value = 0.03]. Among over 220 SNPs, rs76603546 was associated with T2D, HbA_1C and BMI in our study.

A nutrigenetics approach to study the impact of genetic and lifestyle factors on cardiometabolic traits in various ethnic groups: findings from the GeNuIne Collaboration

Several studies on gene-diet interactions (nutrigenetics) have been performed in western populations; however, there are only a few studies to date in lower middle-income countries (LMIC). A large-scale collaborative project called gene-nutrient interactions (GeNuIne) Collaboration, the main objective of which is to investigate the effect of GeNuIne on cardiometabolic traits using population-based studies from various ethnic groups, has been initiated at the University of Reading, UK. While South Asians with higher genetic risk score (GRS) showed a higher risk of obesity in response to a high-carbohydrate diet, South East and Western Asian populations with higher GRS showed an increased risk of central obesity in response to a high-protein diet. The paper also provides a summary of other gene-diet interaction analyses that were performed in LMIC as part of this collaborative project and gives an overview of how these nutrigenetic findings can be translated to personalised and public health approaches for the prevention of cardiometabolic diseases such as obesity, type 2 diabetes and CVD.

Role of TCF7L2 and PPARG2 Gene Polymorphisms in Renal and Cardiovascular Complications among Patients with Type 2 Diabetes: A Cohort Study

BACKGROUND

The emerging renal and cardiovascular complications of type 2 diabetes (T2DM) genetics involves differently assembled gene variants including transcription factor 7-like 2 (TCF7L2) and peroxisome proliferator-activated receptor gamma 2 (PPARG2) polymorphisms. However, the relevance of these genes for complication prediction has not been extensively tested.

METHODS

We analyzed the SNP rs7903146 variants in TCF7L2 and PPARG2 gene polymorphisms for their contribution to the incidence of chronic kidney disease (CKD) and cardiovascular complications in a prospective cohort study. All T2DM patients were followed up to estimate the glomerular filtration rate and cardiovascular outcomes. Cox proportional hazards regression models were used to estimate the genotype effect on the incidence of CKD and vascular complications.

RESULTS

A total of 422 patients were included. SNP rs7903146 variants in the TCF7L2 gene were classified into 3 groups: CC, 385 patients (91.2%), CT, 32 patients (7.6%), and TT, 5 patients (1.2%), while in the PPARG2 gene they were classified into 2 groups: Pro12Pro, 404 patients (95.7%) and Pro12Ala, 18 patients (4.3%). The prevalence of CKD, cardiovascular disease, and death at the end of the 5-year follow-up was 16.8, 29, and 7.9%, respectively. The Pro12Ala variant of the PPARG2 gene was significantly associated with increased CKD risk at the end of the study (adjusted HR 3.45, 95% CI 1.01-11.77, p = 0.046); it showed a significant association with increased cerebrovascular risk, but not cardiovascular disease and mortality. No genotype effect of rs7903146 in the TCF7L2 gene was apparent on renal and cardiovascular complications, except the TT variant of rs7903146 increased cardiovascular events when compared with the non-TT variant.

CONCLUSION

The findings of our study were that the Pro12Ala variant in the PPARG2 gene was associated with risk of developing CKD and cerebrovascular disease in Asian T2DM subjects in a prospective cohort study. The TCF7L2 polymorphism was not associated with cardiovascular outcomes.

A Genome-Wide Association Study Identifies Blood Disorder-Related Variants Influencing Hemoglobin A1c With Implications for Glycemic Status in U.S. Hispanics/Latinos

OBJECTIVE

We aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries.

RESEARCH DESIGN AND METHODS

We conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies.

RESULTS

Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28).

CONCLUSIONS

This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.

Mendelian Randomization Analysis Support Causal Associations of HbA1c with Circulating Triglyceride, Total and Low-density Lipoprotein Cholesterol in a Chinese Population

Previous observational studies supported a positive association of glycated hemoglobin A1c (HbA1c) level with serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). However, the causal relationship between HbA1c and either one of them was unclear in the East Asians. We performed a Mendelian Randomization (MR) analysis in a community-based study sample in Shanghai, China (n = 11,935). To clarify the cause-and-effect relationships of HbA1c with the four interested lipids, an Expanded HbA1c genetic risk score (GRS) with 17 HbA1c-related common variants and a Conservative score by excluding 11 variants were built and adopted as the Instrumental Variables (IVs), respectively. The Expanded HbA1c-GRS was associated with 0.19 unit increment in log-TG (P = 0.009), 0.42 mmol/L TC (P = 0.01), and 0.33 mmol/L LDL-C (P = 0.01); while the Conservative HbA1c-GRS was associated with 0.22 unit in log-TG (P = 0.03), 0.60 mmol/L TC (P = 0.01), and 0.51 mmol/L LDL-C (P = 0.007). No causal relationship was detected for HDL-C. Sensitivity analysis supported the above findings. In conclusions, MR analysis supports a causal role of increased HbA1c level in increment of circulating TG, TC, and LDL-C in a Chinese population.

Genetic Determinants of Glycated Hemoglobin in Type 1 Diabetes

Glycated hemoglobin (HbA_1c) is an important measure of glycemia in diabetes. HbA_1c is influenced by environmental and genetic factors both in people with and in people without diabetes. We performed a genome-wide association study (GWAS) for HbA_1c in a Finnish type 1 diabetes (T1D) cohort, FinnDiane. Top results were examined for replication in T1D cohorts DCCT/EDIC, WESDR, CACTI, EDC, and RASS, and a meta-analysis was performed. Three SNPs in high linkage disequilibrium on chromosome 13 near relaxin family peptide receptor 2 (RXFP2) were associated with HbA_1c in FinnDiane at genome-wide significance (P < 5 × 10^-8). The minor alleles of rs2085277 and rs1360072 were associated with higher HbA_1c also in the meta-analysis with RASS (P < 5 × 10^-8), where these variants had minor allele frequencies ≥1%. Furthermore, these SNPs were associated with HbA_1c in an East Asian population without diabetes (P ≤ 0.013). A weighted genetic risk score created from 55 HbA_1c-associated variants from the literature was associated with HbA_1c in FinnDiane but explained only a small amount of variation. Understanding the genetic basis of glycemic control and HbA_1c may lead to better prevention of diabetes complications.

A systematic review of non-genetic predictors and genetic factors of glycated haemoglobin in type 1 diabetes one year after diagnosis

Type 1 diabetes (T1D) results from autoimmune destruction of the pancreatic βcells. Although all T1D patients require daily administration of exogenous insulin, their insulin requirement to achieve good glycaemic control may vary significantly. Glycated haemoglobin (HbA1c) level represents a stable indicator of glycaemic control and is a reliable predictor of long-term complications of T1D. The purpose of this article is to systematically review the role of non-genetic predictors and genetic factors of HbA1c level in T1D patients after the first year of T1D, to exclude the honeymoon period. A total of 1974 articles published since January 2011 were identified and 78 were finally included in the analysis of non-genetic predictors. For genetic factors, a total of 277 articles were identified and 14 were included. The most significantly associated factors with HbA1c level are demographic (age, ethnicity, and socioeconomic status), personal (family characteristics, parental care, psychological traits...) and features related to T1D (duration of T1D, adherence to treatment …). Only a few studies have searched for genetic factors influencing HbA1c level, most of which focused on candidate genes using classical genetic statistical methods, with generally limited power and incomplete adjustment for confounding factors and multiple testing. Our review shows the complexity of explaining HbA1c level variations, which involves numerous correlated predictors. Overall, our review underlines the lack of studies investigating jointly genetic and non-genetic factors and their interactions to better understand factors influencing glycaemic control for T1D patients.

Genetics of HbA1c: a case study in clinical translation

Glycated hemoglobin (HbA1c) measures the amount of glucose in the blood in the previous 2-3 months and is used to test whether an individual has diabetes (HbA1c≥6.5%), or how well they are managing their diabetes. Genome-wide association studies have successfully identified multiple genomic loci influencing HbA1c, through both glycemic (factors that affect the amount blood glucose levels) and erythrocytic (factors that affect the red blood cell) pathways. Inaccuracies in HbA1c, due to non-glycemic variants, could lead to suboptimal care or adverse health consequences. A recently published example is the erythrocytic variant (rs1050828) in G6PD, which leads to the artificial lowering of HbA1c and missed diagnosis of diabetes using current thresholds. In this review we will discuss recent insights into the genetic etiology of HbA1c, and how these can translate to the clinic.

Genome-wide meta-analysis in Japanese populations identifies novel variants at the TMC6-TMC8 and SIX3-SIX2 loci associated with HbA1c

Glycated haemoglobin (HbA1c) is widely used as a biomarker for the diagnosis of diabetes, for population-level screening, and for monitoring the glycaemic status during medical treatment. Although the heritability of HbA1c has been estimated at ~55-75%, a much smaller proportion of phenotypic variance is explained by the HbA1c-associated variants identified so far. To search for novel loci influencing the HbA1c levels, we conducted a genome-wide meta-analysis of 2 non-diabetic Japanese populations (n = 7,704 subjects in total). We identified 2 novel loci that achieved genome-wide significance: TMC6-TMC8 (P = 5.3 × 10-20) and SIX3-SIX2 (P = 8.6 × 10-9). Data from the largest-scale European GWAS conducted for HbA1c supported an association between the novel TMC6-TMC8 locus and HbA1c (P = 2.7 × 10-3). The association analysis with glycated albumin and glycation gap conducted using our Japanese population indicated that the TMC6-TMC8 and SIX3-SIX2 loci may influence the HbA1c level through non-glycaemic and glycaemic pathways, respectively. In addition, the pathway-based analysis suggested that the linoleic acid metabolic and 14-3-3-mediated signalling pathways were associated with HbA1c. These findings provide novel insights into the molecular mechanisms that modulate the HbA1c level in non-diabetic subjects.

Genetic aetiology of glycaemic traits: approaches and insights

Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.

Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis

BACKGROUND

Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

METHODS & FINDINGS

Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

CONCLUSIONS

As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

Transcription factor 7-like 2 polymorphism and context-specific risk of metabolic syndrome, type 2 diabetes, and dyslipidemia

BACKGROUND

The transcription factor 7-like 2 gene (TCF7L2) is an element of the Wnt signaling pathway. There is lack of evidence if TCF7L2 has a functional role in lipid metabolism and regulation of the components constitutes the metabolic syndrome (MetSyn). The aims of this study were to evaluate whether the risk allele of TCF7L2 gene polymorphism is associated with dyslipidemia and MetSyn.

MATERIALS AND METHODS

The MetSyn subjects were participated only based on the National Cholesterol Education Program - Third Adult Treatment Panel criteria. In this case-control study, the DNA from MetSyn patients without (n = 90) and with type 2 diabetes (T2D) (n = 94) were genotyped.

RESULTS

The results show that the genotype-phenotype for CC, CT/TT of TCF7L2 gene polymorphism correlated with body mass index and waist circumference in MetSyn and MetSyn + T2D subjects (r = -0.949 and r = -0.963, respectively). The subjects that only possess MetSyn but are not diabetics show the 2 h postprandial glucose and fasting blood glucose, glycated hemoglobin significantly lower (P < 0.05) than those subjects have both abnormality. The level of triglyceride in CT/TT carriers in MetSyn was higher than CC carriers (P = 0.025). A comparison with the controls subjects, the frequencies of the T allele in the groups of MetSyn (46.66%) and MetSyn + T2D (47.34%) show significantly different (P < 0.05). The odds ratios for T allele in (MetSyn)/(normal), (MetSyn + T2D)/(normal), and in (MetSyn + T2D)/(MetSyn) were 3.59 (95% confidence interval [CI], 1.33-9.67, P = 0.0093), 3.76 (95% CI, 1.40-10.07, P = 0.0068), and 1.08 (95% CI: 0.55- 2.11, P = 0.834), respectively.

CONCLUSION

The results revealed the important insights essential for the role of TCF7L2 that the T allele of TCF7L2 plays a significant role in the susceptibility to dyslipidemia, MetSyn, and T2D.

Type 2 Diabetes Prevention: Implications of Hemoglobin A1c Genetics

Hemoglobin A1c (HbA1c) is a biomarker used for population-level screening of type 2 diabetes (T2D) and risk stratification. Large-scale, genome-wide association studies have identified multiple genomic loci influencing HbA1c. We discuss the challenges of classifying these genomic loci as influencing HbA1c through glycemic or nonglycemic pathways, based on their probable biology and pleiotropic associations with erythrocyte traits. We show that putative nonglycemic genetic variants have a measurable, albeit small, impact on the classification of T2D status by HbA1c in white and Asian populations. Accounting for their effect on HbA1c may be relevant when screening populations with higher frequencies of nonglycemic HbA1c-altering alleles. As carriers of such HbA1c-altering alleles have HbA1c levels that may not accurately reflect overall glycemia, we describe how accounting for genotype may improve the performance of HbA1c in T2D prediction models and risk stratification, allowing for lifestyle intervention strategies to be directed towards those who are truly at elevated risk for developing T2D. In a Mendelian randomization framework, genetic variants can be used as instrumental variables to estimate causal relationships between HbA1c and T2D-related complications. This approach may help to support or refute HbA1c as an appropriate biomarker for long-term health outcomes in the general population.

Multiple nonglycemic genomic loci are newly associated with blood level of glycated hemoglobin in East Asians

Glycated hemoglobin A1c (HbA1c) is used as a measure of glycemic control and also as a diagnostic criterion for diabetes. To discover novel loci harboring common variants associated with HbA1c in East Asians, we conducted a meta-analysis of 13 genome-wide association studies (GWAS; N = 21,026). We replicated our findings in three additional studies comprising 11,576 individuals of East Asian ancestry. Ten variants showed associations that reached genome-wide significance in the discovery data set, of which nine (four novel variants at TMEM79 [P value = 1.3 × 10(-23)], HBS1L/MYB [8.5 × 10(-15)], MYO9B [9.0 × 10(-12)], and CYBA [1.1 × 10(-8)] as well as five variants at loci that had been previously identified [CDKAL1, G6PC2/ABCB11, GCK, ANK1, and FN3KI]) showed consistent evidence of association in replication data sets. These variants explained 1.76% of the variance in HbA1c. Several of these variants (TMEM79, HBS1L/MYB, CYBA, MYO9B, ANK1, and FN3K) showed no association with either blood glucose or type 2 diabetes. Among individuals with nondiabetic levels of fasting glucose (<7.0 mmol/L) but elevated HbA1c (≥6.5%), 36.1% had HbA1c <6.5% after adjustment for these six variants. Our East Asian GWAS meta-analysis has identified novel variants associated with HbA1c as well as demonstrated that the effects of known variants are largely transferable across ethnic groups. Variants affecting erythrocyte parameters rather than glucose metabolism may be relevant to the use of HbA1c for diagnosing diabetes in these populations.

Insights into the genetic basis of type 2 diabetes

Type 2 diabetes is one of the most common complex diseases, of which considerable efforts have been made to unravel the pathophysiological mechanisms. Recently, large‐scale genome‐wide association (GWA) studies have successfully identified genetic loci robustly associated with type 2 diabetes by searching susceptibility variants across the entire genome in an unbiased, hypothesis‐free manner. The number of loci has climbed from just three in 2006 to approximately 70 today. For the common type 2 diabetes‐associated variants, three features have been noted. First, genetic impacts of individual variants are generally modest; mostly, allelic odds ratios range between 1.06 and 1.20. Second, most of the loci identified to date are not in or near obvious candidate genes, but some are often located in the intergenic regions. Third, although the number of loci is limited, there might be some population specificity in type 2 diabetes association. Although we can estimate a single or a few target genes for individual loci detected in GWA studies by referring to the data for experiments in vitro, biological function remains largely unknown for a substantial part of such target genes. Nevertheless, new biology is arising from GWA study discoveries; for example, genes implicated in β‐cell dysfunction are over‐represented within type 2 diabetes‐associated regions. Toward translational advances, we have just begun to face new challenges – elucidation of multifaceted (i.e., molecular, cellular and physiological) mechanistic insights into disease biology by considering interaction with the environment. The present review summarizes recent advances in the genetics of type 2 diabetes, together with its realistic potential.

A study assessing the association of glycated hemoglobin A1C (HbA1C) associated variants with HbA1C, chronic kidney disease and diabetic retinopathy in populations of Asian ancestry

Glycated hemoglobin A1C (HbA1C) level is used as a diagnostic marker for diabetes mellitus and a predictor of diabetes associated complications. Genome-wide association studies have identified genetic variants associated with HbA1C level. Most of these studies have been conducted in populations of European ancestry. Here we report the findings from a meta-analysis of genome-wide association studies of HbA1C levels in 6,682 non-diabetic subjects of Chinese, Malay and South Asian ancestries. We also sought to examine the associations between HbA1C associated SNPs and microvascular complications associated with diabetes mellitus, namely chronic kidney disease and retinopathy. A cluster of 6 SNPs on chromosome 17 showed an association with HbA1C which achieved genome-wide significance in the Malays but not in Chinese and Asian Indians. No other variants achieved genome-wide significance in the individual studies or in the meta-analysis. When we investigated the reproducibility of the findings that emerged from the European studies, six loci out of fifteen were found to be associated with HbA1C with effect sizes similar to those reported in the populations of European ancestry and P-value ≤ 0.05. No convincing associations with chronic kidney disease and retinopathy were identified in this study.

Association of resistin gene polymorphisms with insulin resistance in Egyptian obese patients

BACKGROUND

Obesity associated insulin resistance is a major risk factor for type 2 diabetes mellitus. Resistin is recently reported to provide a link between obesity, insulin resistance and type 2 diabetes mellitus. We aimed to investigate the possible associations of resistin gene (RETN) polymorphisms with obesity, and to detect whether these polymorphisms are associated with glucose intolerance and type 2 diabetes mellitus in obese patients.

METHODS

One hundred and forty-five Egyptian obese patients with or without glucose intolerance and 155 unrelated healthy controls were enrolled in this study. Polymorphisms of RETN +299G>A and RETN -420 C>G gene were detected by polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP). Serum resistin was measured by ELISA.

RESULTS

RETN +299 AA and RETN -420 GG genotypes were significantly associated with obesity in Egyptian population. Moreover, the mutant alleles or genotypes of both examined polymorphisms were associated with impaired glucose tolerance and diabetes mellitus compared to normal glucose tolerant obese patients. Furthermore, our results revealed elevated waist/hip ratio, BMI, blood pressure, fasting blood glucose level, HOMA-IR, triglycerides, total cholesterol, resistin level, and decreased HDL cholesterol level in homozygote mutant genotypes carriers of both RETN polymorphisms among obese patients.

CONCLUSION

Resistin gene polymorphisms may play an important role in pathogenesis and susceptibility to obesity, impaired glucose tolerance, and type 2 diabetes mellitus in Egyptian population.

Role of TCF7L2 risk variant and dietary fibre intake on incident type 2 diabetes

AIMS/HYPOTHESIS

The T allele of transcription factor 7-like 2 gene variant, TCF7L2 rs7903146, increases the risk of type 2 diabetes by 40-50%. As TCF7L2 rs7903146 has been associated with diminished incretin effect we investigated whether interaction between dietary intake of carbohydrate, fat, protein or fibre and this variant affects the risk of type 2 diabetes.

METHODS

A cohort of 24,799 non-diabetic individuals from the Malmö Diet and Cancer Study (MDCS), with dietary data obtained by a modified diet history method, were followed up for 12 years, with 1,649 recordings of incident type 2 diabetes made. Risk of type 2 diabetes in strata of diet quintiles was analysed prospectively adjusting for potential confounders. Cross-sectional analyses were performed on baseline fasting glucose and HbA(1c) levels in a subset of 5,216 randomly selected individuals from the MDCS.

RESULTS

The elevated risk of type 2 diabetes with rs7903146 (OR 1.44, 95% CI 1.33, 1.56, p = 4.6 × 10(-19)) increased with higher intake of dietary fibre (OR 1.24, 95% CI 1.04, 1.47 to OR 1.56, 95% CI 1.31, 1.86 from the lowest to highest quintile; p (interaction) = 0.049). High intake of dietary fibre was inversely associated with diabetes incidence only among CC genotype carriers (OR 0.74, 95% CI 0.58, 0.94 per quintile, p = 0.025). The T allele was associated with 0.027% elevated HbA(1c) (p = 0.02) and this effect increased with higher intake of fibre (from -0.021% to 0.079% for the lowest to the highest quintile, p (interaction) = 0.02). Each quintile of higher fibre intake was associated with lower HbA(1c) levels among CC and CT but not among TT genotype carriers (-0.036%, p = 6.5 × 10(-7); -0.023%, p = 0.009; and 0.012%, p = 0.52, respectively).

CONCLUSIONS/INTERPRETATION

Our study suggests that dietary fibre intake may modify the association between TCF7L2 rs7903146 and incidence of type 2 diabetes, and that higher fibre intake may associate with protection from type 2 diabetes only among non-risk allele carriers.

Genetic determinants of variability in glycated hemoglobin (HbA(1c)) in humans: review of recent progress and prospects for use in diabetes care

Glycated hemoglobin A(1c) (HbA(1c)) indicates the percentage of total hemoglobin that is bound by glucose, produced from the nonenzymatic chemical modification by glucose of hemoglobin molecules carried in erythrocytes. HbA(1c) represents a surrogate marker of average blood glucose concentration over the previous 8 to 12 weeks, or the average lifespan of the erythrocyte, and thus represents a more stable indicator of glycemic status compared with fasting glucose. HbA(1c) levels are genetically determined, with heritability of 47% to 59%. Over the past few years, inroads into understanding genetic predisposition by glycemic and nonglycemic factors have been achieved through genomewide analyses. Here I review current research aimed at discovering genetic determinants of HbA(1c) levels, discussing insights into biologic factors influencing variability in the general and diabetic population, and across different ethnicities. Furthermore, I discuss briefly the relevance of findings for diabetes monitoring and diagnosis.

Pharmacogenomics of oral antidiabetic medications: current data and pharmacoepigenomic perspective

Type 2 diabetes mellitus (T2DM) is an increasingly prevalent disease. Several classes of drugs are currently available to treat T2DM patients; however, clinical response to these drugs often exhibits significant variation among individuals. For the oral antidiabetic drug classes of sulfonylureas, nonsulfonylurea insulin secretagogs, biguanides and thiazolidinediones, pharmacogenomic evidence has accumulated demonstrating an association between specific gene polymorphisms and interindividual variability in their therapeutic and adverse reaction effects. These polymorphisms are in genes of molecules involved in metabolism, transport and therapeutic mechanisms of the aforementioned drugs. Overall, it appears that pharmacogenomics has the potential to improve the management of T2DM and help clinicians in the effective prescribing of oral antidiabetic medications. Although pharmacogenomics can explain some of the heterogeneity in dose requirements, response and incidence of adverse effects of drugs between individuals, it is now clearly understood that much of the diversity in drug effects cannot be solely explained by studying the genomic diversity. Epigenomics, the field that focuses on nongenomic modifications that influence gene expression, may expand the scope of pharmacogenomics towards optimization of drug therapy. Therefore, pharmacoepigenomics, the combined analysis of genetic variations and epigenetic modifications, holds promise for the realization of personalized medicine. Although pharmacoepigenomics has so far been evaluated mainly in cancer pharmacotherapy, studies on epigenomic modifications during T2DM development provide useful data on the potential of pharmacoepigenomics to elucidate the mechanisms underlying interindividual response to oral antidiabetic treatment. In summary, the present article focuses on available data from pharmacogenomic studies of oral antidiabetic drugs and also provides an overview of T2DM epigenomic research, which has the potential to boost the development of pharmacoepigenomics in antidiabetic treatment.

Novel adiponectin-resistin (AR) and insulin resistance (IRAR) indexes are useful integrated diagnostic biomarkers for insulin resistance, type 2 diabetes and metabolic syndrome: a case control study

Background

Adiponectin and resistin are adipokines which modulate insulin action, energy, glucose and lipid homeostasis. Meta-analyses showed that hypoadiponectinemia and hyperresistinemia are strongly associated with increased risk of insulin resistance, type 2 diabetes (T2DM), metabolic syndrome (MS) and cardiovascular disease. The aim of this study was to propose a novel adiponectin-resistin (AR) index by taking into account both adiponectin and resistin levels to povide a better indicator of the metabolic homeostasis and metabolic disorders. In addition, a novel insulin resistance (IR_AR) index was proposed by integration of the AR index into an existing insulin resistance index to provide an improved diagnostic biomarker of insulin sensitivity.

Methods

In this case control study, anthropometric clinical and metabolic parameters including fasting serum total adiponectin and resistin levels were determined in 809 Malaysian men (208 controls, 174 MS without T2DM, 171 T2DM without MS, 256 T2DM with MS) whose ages ranged between 40-70 years old. Significant differences in continuous variables among subject groups were confirmed by ANCOVA or MANCOVA test using 1,000 stratified bootstrap samples with bias corrected and accelerated (BCa) 95% CI. Spearman's rho rank correlation test was used to test the correlation between two variables.

Results

The AR index was formulated as 1+log₁₀(R₀)-log₁₀(A₀). The AR index was more strongly associated with increased risk of T2DM and MS than hypoadiponectinemia and hyperresistinemia alone. The AR index was more strongly correlated with the insulin resistance indexes and key metabolic endpoints of T2DM and MS than adiponectin and resistin levels alone. The AR index was also correlated with a higher number of MS components than adiponectin and resistin levels alone. The IR_AR index was formulated as log₁₀(I₀G₀)+log₁₀(I₀G₀)log₁₀(R₀/A₀). The normal reference range of the IR_AR index for insulin sensitive individuals was between 3.265 and 3.538. The minimum cut-off values of the IR_AR index for insulin resistance assessment were between 3.538 and 3.955.

Conclusions

The novel AR and IR_AR indexes are cost-effective, precise, reproducible and reliable integrated diagnostic biomarkers of insulin sensitivity for screening subjects with increased risk of future development of T2DM and MS.