A Variation in the ABCC8 Gene Is Associated with Type 2 Diabetes Mellitus and Repaglinide Efficacy in Chinese Type 2 Diabetes Mellitus Patients

An analysis of the relationship between ABCC8 and KCNJ11 gene polymorphisms and diabetic retinopathy in Turkish population

BACKGROUND

Diabetic retinopathy (DR) occurs due to high blood glucose damage to the retina and leads to blindness if left untreated. KATP and related genes (KCNJ11 and ABCC8) play an important role in insulin secretion by glucose-stimulated pancreatic beta cells and the regulation of insulin secretion. KCNJ11 E23K (rs5219), ABCC8-3 C/T (rs1799854), Thr759Thr (rs1801261) and Arg1273Arg (rs1799859) are among the possible related single nucleotide polymorphisms (SNPs). The aim of this study is to find out how DR and these SNPs are associated with one another in the Turkish population.

MATERIALS AND METHODS

This study included 176 patients with type 2 diabetes mellitus without retinopathy (T2DM-rp), 177 DR patients, and 204 controls. Genomic DNA was extracted from whole blood, and genotypes were determined by the PCR-RFLP method.

RESULTS

In the present study, a significant difference was not found between all the groups in terms of Arg1273Arg polymorphism located in the ABCC8 gene. The T allele and the TT genotype in the -3 C/T polymorphism in this gene may have a protective effect in the development of DR (p = 0.036 for the TT genotype; p = 0.034 for T allele) and PDR (p = 0.042 and 0.025 for the TT genotype). The AA genotype showed a significant increase in the DR group compared to T2DM-rp in the KCNJ11 E23K polymorphism (p = 0.046).

CONCLUSIONS

Consequently, the T allele and TT genotype in the -3 C/T polymorphism of the ABCC8 gene may have a protective marker on the development of DR and PDR, while the AA genotype in the E23K polymorphism of the KCNJ11 gene may be effective in the development of DR in the Turkish population.

Common BMI and diabetes-related genetic variants: A pilot study among indigenous people in the Brazilian Amazon

This study was carried out to investigate the frequency of genetic variants related to body mass index (BMI) and type 2 diabetes (T2D) and evaluating the potential impact of risk alleles on susceptibility to these disorders in six indigenous peoples from Brazilian Amazon region. The majority of Fst values for pairwise population comparisons among the indigenous groups are low or moderate. The indigenous people show high values of differentiation with Africans, Europeans and Southeast Asians and moderate values with East Asian and American populations, as expected. The allelic frequencies among indigenous indicate that the majority of associations observed with T2D in continental populations can be replicated in native Amazonians. The genetic risk scores calculated for T2D in indigenous are high and similar to those calculated for Americans and East Asians, while the estimates obtained for obesity are low, probably due to the low frequencies of the risk allele of the FTO gene found in our samples. ADRB3-rs4994 and ABCC8-rs1799854 genes showed a significant association with BMI and waist circumference, and the KCNJ11-rs5219 gene with hyperglycemia. These results emphasize the importance of knowing the genetic variability underlying complex genetic diseases in indigenous peoples and the search for particular or rare variants.

Associations of ATP-Sensitive Potassium Channel’s Gene Polymorphisms With Type 2 Diabetes and Related Cardiovascular Phenotypes

Type 2 diabetes (T2D) is characterized by increased levels of blood glucose but is increasingly recognized as a heterogeneous disease, especially its multiple discrete cardiovascular phenotypes. Genetic variations play key roles in the heterogeneity of diabetic cardiovascular phenotypes. This study investigates possible associations of ATP-sensitive potassium channel (KATP) variants with cardiovascular phenotypes among the Chinese patients with T2D. Six hundred thirty-six patients with T2D and 634 non-diabetic individuals were analyzed in the study. Nine KATP variants were determined by MassARRAY. The KATP rs2285676 (AA + GA, OR = 1.43, 95% CI: 1.13–1.81, P = 0.003), rs1799858 (CC, OR = 1.42, 95% CI: 1.12–1.78, P = 0.004), and rs141294036 (CC, OR = 1.45, 95% CI: 1.15–1.83, P = 0.002) are associated with increased T2D risk. A follow-up of at least 45.8-months (median) indicates further association between the 3 variants and risks of diabetic-related cardiovascular conditions. The associations are categorized as follows: new-onset/recurrent acute coronary syndrome (ACS) (rs2285676/AA + GA, HR = 1.37, 95% CI: 1.10–1.70, P = 0.005; rs141294036/TT + CT, HR = 1.59, 95% CI: 1.28–1.99, P < 0.001), new-onset stroke (rs1799858/CC, HR = 2.58, 95% CI: 1.22–5.43, P = 0.013; rs141294036/CC, HR = 2.30, 95% CI: 1.16–4.55, P = 0.017), new-onset of heart failure (HF) (rs1799858/TT + CT, HR = 2.78, 95% CI: 2.07–3.74, P < 0.001; rs141294036/TT + CT, HR = 1.45, 95% CI: 1.07–1.96, P = 0.015), and new-onset atrial fibrillation (AF) (rs1799858/TT + CT, HR = 2.05, 95% CI: 1.25–3.37, P = 0.004; rs141294036/CC, HR = 2.31, 95% CI: 1.40–3.82, P = 0.001). In particular, the CC genotype of rs1799858 (OR = 2.38, 95% CI: 1.11–5.10, P = 0.025) and rs141294036 (OR = 1.95, 95% CI: 1.04–3.66, P = 0.037) are only associated with the risk of ischemic stroke while its counterpart genotype (TT + CT) is associated with the risks of HF with preserved ejection fraction (HFpEF) (rs1799858, OR = 3.46, 95% CI: 2.31–5.18, P < 0.001) and HF with mildly reduced ejection fraction (HFmrEF) (rs141294036, OR = 2.74, 95% CI: 1.05–7.15, P = 0.039). Furthermore, the 3 variants are associated with increased risks of abnormal serum levels of triglyceride (TIRG) (≥ 1.70 mmol/L), low-density lipoprotein cholesterol (LDL-C) (≥ 1.40 mmol/L), apolipoprotein B (ApoB) (≥ 80 mg/dL), apolipoprotein A-I (ApoA-I) level (< 120 mg/dL), lipoprotein(a) Lp(a) (≥ 300 mg/dL) and high-sensitivity C-reactive protein (HsCRP) (≥ 3.0 mg/L) but exhibited heterogeneity (all P < 0.05). The KATP rs2285676, rs1799858, and rs141294036 are associated with increased risks of T2D and its related cardiovascular phenotypes (ACS, stroke, HF, and AF), but show heterogeneity. The 3 KATP variants may be promising markers for diabetic cardiovascular events favoring “genotype-phenotype” oriented prevention and treatment strategies.

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic β-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature’s applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient's genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and "multiomics" studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.

The Mutation Spectrum of Maturity Onset Diabetes of the Young (MODY)-Associated Genes among Western Siberia Patients

Maturity onset diabetes of the young (MODY) is a congenital form of diabetes characterized by onset at a young age and a primary defect in pancreatic-β-cell function. Currently, 14 subtypes of MODY are known, and each is associated with mutations in a specific gene: HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, KCNJ11, ABCC8, and APPL1. The most common subtypes of MODY are associated with mutations in the genes GCK, HNF1A, HNF4A, and HNF1B. Among them, up to 70% of cases are caused by mutations in GCK and HNF1A. Here, an analysis of 14 MODY genes was performed in 178 patients with a MODY phenotype in Western Siberia. Multiplex ligation-dependent probe amplification analysis of DNA samples from 50 randomly selected patients without detectable mutations did not reveal large rearrangements in the MODY genes. In 38 patients (37% males) among the 178 subjects, mutations were identified in HNF4A, GCK, HNF1A, and ABCC8. We identified novel potentially causative mutations p.Lys142*, Leu146Val, Ala173Glnfs*30, Val181Asp, Gly261Ala, IVS7 c.864 -1G>T, Cys371*, and Glu443Lys in GCK and Ser6Arg, IVS 2 c.526 +1 G>T, IVS3 c.713 +2 T>A, and Arg238Lys in HNF1A.

Pharmacogenomic Studies of Current Antidiabetic Agents and Potential New Drug Targets for Precision Medicine of Diabetes

Diabetes is a major threat to people's health and has become a burden worldwide. Current drugs for diabetes have limitations, such as different drug responses among individuals, failure to achieve glycemic control, and adverse effects. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Currently pharmacogenomics has provided potential for individualized drug therapy based on genetic and genomic information of patients, and has made precision medicine possible. Responses and adverse effects to antidiabetic drugs are significantly associated with gene polymorphisms in patients. Many new targets for diabetes also have been discovered and developed, and even entered clinical trial phases. This review summarizes pharmacogenomic evidence of some current antidiabetic agents applied in clinical settings, and highlights potential drugs with new targets for diabetes, which represent a more effective treatment in the future.