Browse
Submit Data
Databases
API
Help

Dataset Information

27 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Type 2 Diabetes-Associated Genetic Polymorphisms as Potential Disease Predictors.

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

SUBMITTER: Witka BZ

PROVIDER: S-EPMC6927489 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Type 2 Diabetes-Associated Genetic Polymorphisms as Potential Disease Predictors.

Witka Beska Z BZ Oktaviani Dede J DJ Marcellino Marcellino M Barliana Melisa I MI Abdulah Rizky R

Diabetes, metabolic syndrome and obesity : targets and therapy 20191218

Diabetes is a major cause of mortality worldwide. There are several types of diabetes, with type 2 diabetes mellitus (T2DM) being the most common. Many factors, including environmental and genetic factors, are involved in the etiology of the disease. Numerous studies have reported the role of genetic polymorphisms in the initiation and development of T2DM. While genome-wide association studies have identified around more than 200 susceptibility loci, it remains unclear whether these loci are cor ...[more]

PMID: 31908510

Similar Datasets

Genetic risk assessment of type 2 diabetes-associated polymorphisms in African Americans.

Project description:Multiple single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D) susceptibility have been identified in predominantly European-derived populations. These SNPs have not been extensively investigated for individual and cumulative effects on T2D risk in African Americans.Seventeen index T2D risk variants were genotyped in 2,652 African American case subjects with T2D and 1,393 nondiabetic control subjects. Individual SNPs and cumulative risk allele loads were assessed for association with risk for T2D. Cumulative risk was assessed by counting risk alleles and evaluating the difference in cumulative risk scores between case subjects and control subjects. A second analysis weighted risk scores (ln [OR]) based on previously reported European-derived effect sizes.Frequencies of risk alleles ranged from 8.6 to 99.9%. Eleven SNPs had ORs >1, and 5 from ADAMTS9, WFS1, CDKAL1, JAZF1, and TCF7L2 trended or had nominally significant evidence of T2D association (P < 0.05). Individuals carried between 13 and 29 risk alleles. Association was observed between T2D and increase in risk allele load (unweighted OR 1.04 [95% CI 1.01-1.08], P = 0.010; weighted 1.06 [1.03-1.10], P = 8.10 × 10(-5)). When TCF7L2 SNP rs7903146 was included as a covariate, the risk score was no longer associated with T2D in either model (unweighted 1.02 [0.98-1.05], P = 0.33; weighted 1.02 [0.98-1.06], P = 0.40).The trend of increase in risk for T2D with increasing risk allele load is similar to observations in European-derived populations; however, these analyses indicate that T2D genetic risk is primarily mediated through the effect of TCF7L2 in African Americans.

| S-EPMC3263882 | biostudies-literature

Polymorphisms and genetic susceptibility of type 1 diabetes mellitus and celiac disease

Project description: Not available

| S-EPMC4659250 | biostudies-literature

Clinical translation of genetic predictors for type 2 diabetes.

Project description:Purpose of reviewTo highlight recent type 2 diabetes (T2D)-associated genetic discoveries and their potential for clinical application.Recent findingsThe advent of genome-wide association screening has uncovered many loci newly associated with T2D. This review describes the techniques applied to discover novel T2D genes and compares their relative strengths, biases, and findings to date. The results of large-scale genome-wide association studies carried out since 2007 are summarized, and limitations of interpreting this preliminary data are offered. Recent studies exploring the clinical potential of these discoveries are reviewed, focusing on insights into T2D pathogenesis, risk prediction of future diabetes, and utility in guiding pharmacotherapy. The new T2D-associated loci have been implicated in beta-cell development and function, highlighting insulin secretion in the disease process. Preliminary risk prediction studies show that more loci are needed to improve T2D risk indices. Studies have also revealed that genes may play a role in the pharmacologic response to antidiabetic medications.SummarySince 2007, genome-wide association studies have rapidly increased the number of T2D-associated loci. This review summarizes the history of genetic association studies, the results from the new genome-wide association studies, and the clinical application of these findings.

| S-EPMC2938779 | biostudies-literature

Genetic analysis of haptoglobin polymorphisms with cardiovascular disease and type 2 diabetes in the Diabetes Heart Study.

Project description:Haptoglobin (HP) is an acute phase protein that binds to freely circulating hemoglobin. HP exists as two distinct forms, HP1 and HP2. The longer HP2 form has been associated with cardiovascular (CVD) events and mortality in individuals with type 2 diabetes (T2DM).This study examined the association of HP genotypes with subclinical CVD, T2DM risk, and associated risk factors in a T2DM-enriched sample. Haptoglobin genotypes were determined in 1208 European Americans (EA) from 473 Diabetes Heart Study (DHS) families via PCR. Three promoter SNPs (rs5467, rs5470, and rs5471) were also genotyped.Analyses revealed association between HP2-2 duplication and increased carotid intima-media thickness (IMT; p = 0.001). No association between HP and measures of calcified arterial plaque were observed, but the HP polymorphism was associated with triglyceride concentrations (p = 0.005) and CVD mortality (p = 0.04). We found that the HP2-2 genotype was associated with increased T2DM risk with an odds ratio (OR) of 1.49 (95% CI 1.18-1.86, p = 6.59x10(-4)). Promoter SNPs were not associated with any traits.This study suggests association between the HP duplication and IMT, triglycerides, CVD mortality, and T2DM in an EA population enriched for T2DM. Lack of association with atherosclerotic calcified plaque likely reflect differences in the pathogenesis of these CVD phenotypes. HP variation may contribute to the heritable risk for CVD complications in T2DM.

| S-EPMC3576297 | biostudies-literature

Glucose metabolism-related gene polymorphisms as the risk predictors of type 2 diabetes.

Project description:Type 2 diabetes mellitus (T2DM) is a complex polygenic metabolic disease characterized by elevated blood glucose. Multiple environmental and genetic factors can increase the risk of T2DM and its complications, and genetic polymorphisms are no exception. This review is mainly focused on the related genes involved in glucose metabolic, including G6PC2, GCK, GCKR and OCT3. In this review, we have summarized the results reported globally and found that the genetic variants of GCK and OCT3 genes is a risk factor for T2DM while G6PC2 and GCKR genes are controversial in different ethnic groups. Hopefully, this summary could possibly help researchers and physicians understand the mechanism of T2DM so as to diagnose and even prevent T2DM at early time.

| S-EPMC7643457 | biostudies-literature

Genetic polymorphisms in genes encoding antioxidant enzymes are associated with diabetic retinopathy in type 1 diabetes.

Project description:OBJECTIVE:Oxidative stress plays an important role in the development of microangiopathic complications in type 1 diabetes. We investigated polymorphic markers in genes encoding enzymes regulating production of reactive oxygen species in association with diabetic retinopathy or diabetic nephropathy. RESEARCH DESIGN AND METHODS:A total of 124 patients with type 1 diabetes were investigated in this case-control study. All subjects were matched for sex, age, and duration of diabetes. Genotyping was conducted using real-time PCR for p.Val16Ala polymorphism in the MnSOD gene and c.C-262T in the promoter region of the CAT gene. Multiplex PCR method was used for determination of GSTM1 and GSTT1 polymorphic deletions. Fluorescence-labeled PCR amplicons and fragment analysis was used for assessing the number of pentanucleotide (CCTTT)n repeats in inducible nitric oxide synthase. RESULTS:A positive association of MnSOD genotype Val/Val (odds ratio [OR] 2.49, 95% CI 1.00-6.16, P = 0.045) and GSTM1-1 genotype (2.63, 1.07-6.47, P = 0.031) with diabetic retinopathy but not with diabetic nephropathy was demonstrated. Additionally, the combination of the two genotypes conveyed an even higher risk (4.24, 1.37-13.40, P = 0.009). No other investigated genetic polymorphisms were associated with either diabetic retinopathy or diabetic nephropathy. CONCLUSIONS:Selected polymorphisms in genes encoding MnSOD and GSTM1 could be added to a panel of genetic markers for identification of individuals with type 1 diabetes at an increased risk for developing diabetic retinopathy.

| S-EPMC2782987 | biostudies-literature

Genetic polymorphisms of cytokine genes in type 2 diabetes mellitus.

Project description:Diabetes mellitus is a combined metabolic disorder which includes hyperglycemia, dyslipidemia, stroke and several other complications. Various groups all over the world are relentlessly working out the possible role of a vast number of genes associated with type 2 diabetes (T2DM). Inflammation is an important outcome of any kind of imbalance in the body and is therefore an indicator of several diseases, including T2DM. Various ethnic populations around the world show different levels of variations in single nucleotide polymorphisms (SNPs). The present review was undertaken to explore the association of cytokine gene polymorphisms with T2DM in populations of different ethnicities. This will lead to the understanding of the role of cytokine genes in T2DM risk and development. Association studies of genotypes of SNPs present in cytokine genes will help to identify risk haplotype(s) for disease susceptibility by developing prognostic markers and alter treatment strategies for T2DM and related complications. This will enable individuals at risk to take prior precautionary measures and avoid or delay the onset of the disease. Future challenges will be to understand the genotypic interactions between SNPs in one cytokine gene or several genes at different loci and study their association with T2DM.

| S-EPMC4127584 | biostudies-literature

The role of MTNR1B genetic polymorphisms in type 2 diabetes mellitus

Project description: Not available

| S-EPMC4075489 | biostudies-literature

PDX1 and MC4R genetic polymorphisms are associated with type 2 diabetes mellitus risk in the Chinese Han population.

Project description:BackgroundDiabetes mellitus (DM) is a complex metabolic disease that is caused by a complex interplay between genetic and environmental factors. This research aimed to investigate the association of genetic polymorphisms in PDX1 and MC4R with T2DM risk.MethodsThe genotypes of 10 selected SNPs in PDX1 and MC4R were identified using the Agena MassARRAY platform. We utilized odds ratio (OR) and 95% confidence intervals (CIs) to assess the correlation between genetic polymorphisms and T2DM risk.ResultsWe found that PDX1-rs9581943 decreased susceptibility to T2DM among in a Chinese Han population (OR = 0.76, p = 0.045). We also found that selected genetic polymorphisms in PDX1 and MC4R could modify the risk of T2DM, which might also be influenced by age, sex, BMI, smoking status, and drinking status (p < 0.05).ConclusionsWe concluded that PDX1 and MC4R genetic variants were significantly associated with T2DM risk in a Chinese Han population. These single polymorphic markers may be considered to be new targets in the assessment and prevention of T2DM among Chinese Han people.

| S-EPMC8543917 | biostudies-literature

Genetic risk reclassification for type 2 diabetes by age below or above 50 years using 40 type 2 diabetes risk single nucleotide polymorphisms.

Project description:To test if knowledge of type 2 diabetes genetic variants improves disease prediction.We tested 40 single nucleotide polymorphisms (SNPs) associated with diabetes in 3,471 Framingham Offspring Study subjects followed over 34 years using pooled logistic regression models stratified by age (<50 years, diabetes cases = 144; or ?50 years, diabetes cases = 302). Models included clinical risk factors and a 40-SNP weighted genetic risk score.In people <50 years of age, the clinical risk factors model C-statistic was 0.908; the 40-SNP score increased it to 0.911 (P = 0.3; net reclassification improvement (NRI): 10.2%, P = 0.001). In people ?50 years of age, the C-statistics without and with the score were 0.883 and 0.884 (P = 0.2; NRI: 0.4%). The risk per risk allele was higher in people <50 than ?50 years of age (24 vs. 11%; P value for age interaction = 0.02).Knowledge of common genetic variation appropriately reclassifies younger people for type 2 diabetes risk beyond clinical risk factors but not older people.

| S-EPMC3005447 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data