scholarly journals Type 2 diabetes-associated genetic variants discovered in the recent genome-wide association studies are related to gestational diabetes mellitus in the Korean population

Diabetologia ◽  
2008 ◽  
Vol 52 (2) ◽  
pp. 253-261 ◽  
Author(s):  
Y. M. Cho ◽  
T. H. Kim ◽  
S. Lim ◽  
S. H. Choi ◽  
H. D. Shin ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Trans-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

2021 ◽  
Author(s):  
Natalia Pervjakova ◽  
Gunn-Helen Moen ◽  
Maria-Carolina Borges ◽  
Teresa Ferreira ◽  
James P Cook ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Increased Risk ◽  
In Pregnancy

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy (GenDIP) Consortium assembled genome-wide association studies (GWAS) of diverse ancestry in a total of 5,485 women with GDM and 347,856 without GDM. Through trans-ancestry meta-analysis, we identified five loci with genome-wide significant association (p<5×10-8) with GDM, mapping to/near MTNR1B (p=4.3×10-54), TCF7L2 (p=4.0×10-16), CDKAL1 (p=1.6×10-14), CDKN2A-CDKN2B (p=4.1×10-9) and HKDC1 (p=2.9×10-8). Multiple lines of evidence pointed to genetic contributions to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D; and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomisation analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

scholarly journals Genetics and Epigenetics: New Insight on Gestational Diabetes Mellitus

2020 ◽  
Vol 11 ◽  
Author(s):  
Maria Grazia Dalfrà ◽  
Silvia Burlina ◽  
Gloria Giovanna Del Vescovo ◽  
Annunziata Lapolla
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Maternal Metabolism

Gestational diabetes mellitus (GDM) is the most common metabolic complication of pregnancy, with a prevalence that has increased significantly in the last decade, coming to affect 12–18% of all pregnancies. GDM is believed to be the result of a combination of genetic, epigenetic and environmental factors. Following the identification of susceptibility genes for type 2 diabetes by means of genome-wide association studies, an association has also been demonstrated between some type 2 diabetes susceptibility genes and GDM, suggesting a partial similarity of the genetic architecture behind the two forms of diabetes. More recent genome-wide association studies, focusing on maternal metabolism during pregnancy, have demonstrated an overlap in the genes associated with metabolic traits in gravid and non-gravid populations, as well as in genes apparently unique to pregnancy. Epigenetic changes—such as DNA methylation, histone modifications and microRNA gene silencing—have also been identified in GDM patients. Metabolomics has been used to profile the metabolic state of women during pregnancy, based on the measurement of numerous low-molecular-weight metabolites. Measuring amino acids and conventional metabolites has revealed changes in pregnant women with a higher insulin resistance and high blood glucose levels that resemble the changes seen in non-gravid, insulin-resistant populations. This would suggest similarities in the metabolic profiles typical of insulin resistance and hyperglycemia whether individuals are pregnant or not. Future studies combining data obtained using multiple technologies will enable an integrated systems biology approach to maternal metabolism during a pregnancy complicated by GDM. This review highlights the recent knowledge on the impact of genetics and epigenetics in the pathophysiology of GDM and the maternal and fetal complications associated with this pathology condition.

P4470Identification of four genes as novel susceptibility loci for early-onset type 2 diabetes mellitus, metabolic syndrome, or hyperuricemia in Japanese

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
Y Yamase ◽  
H Horibe ◽  
K Kato ◽  
M Oguri ◽  
T Fujimaki ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Metabolic Syndrome ◽  
Genetic Variants ◽  
Early Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Susceptibility Loci ◽  
Genome Wide

Abstract Background Given that early-onset type 2 diabetes mellitus (T2DM), metabolic syndrome, and hyperuricemia have been shown to have strong genetic components, statistical power of a genetic association study may be increased by focusing on early-onset subjects with these conditions. Although genome-wide association studies have identified various genes and loci significantly associated with T2DM, metabolic syndrome, and hyperuricemia, genetic variants that contribute to predisposition to these conditions in Japanese individuals remain to be identified definitively. Purpose The purpose of the study was to identify genetic variants that confer susceptibility to early-onset T2DM, metabolic syndrome, or hyperuricemia in Japanese. We have now performed exome-wide association studies (EWASs) for early-onset subjects with T2DM, metabolic syndrome, or hyperuricemia and corresponding controls. Methods A total of 8102 individuals aged ≤65 years was enrolled in the study. The EWAS for T2DM was performed with 7407 subjects (1696 cases, 5711 controls), that for metabolic syndrome with 4215 subjects (2296 cases, 1919 controls), and that for hyperuricemia with 7919 subjects (1365 cases, 6554 controls). Single nucleotide polymorphisms (SNPs) were genotyped with Illumina Human Exome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relation of allele frequencies for 31,210, 31,521, or 31,142 SNPs that passed quality control to T2DM, metabolic syndrome, or hyperuricemia, respectively, was examined with Fisher's exact test. To compensate for multiple comparisons of genotypes with T2DM, metabolic syndrome, or hyperuricemia, we applied Bonferroni's correction for statistical significance of association. Results The EWAS of allele frequencies revealed that four, six, or nine SNPs were significantly associated with T2DM (P<1.60 × 10–6), metabolic syndrome (P<1.59 × 10–6), or hyperuricemia (P<1.61 × 10–6), respectively. Multivariable logistic regression analysis with adjustment for age and sex revealed that three, six, or nine SNPs were significantly related to T2DM (P<0.0031), metabolic syndrome (P<0.0021), or hyperuricemia (P<0.0014). After examination of the association of identified SNPs to T2DM-, metabolic syndrome-, or hyperuricemia-related traits, linkage disequilibrium of the SNPs, and results of previous genome-wide association studies, we have newly identified ZNF860 and OR4F6 as susceptibility loci for T2DM, OR52E4 and OR4F6 for metabolic syndrome, and HERPUD2 for hyperuricemia. Conclusion Given that OR4F6 was significantly associated with both T2DM and metabolic syndrome, we thus newly identified four genes (ZNF860, OR4F6, OR52E4, HERPUD2) that confer susceptibility to early-onset T2DM, metabolic syndrome, or hyperuricemia. Determination of genotypes for the SNPs in these genes may prove informative for assessment of the genetic risk for T2DM, metabolic syndrome, or hyperuricemia in Japanese.

scholarly journals Significance of the results of genome-wide association studies for primary prevention of type 2 diabetes mellitus and its complications. Personalised approach

2014 ◽  
Vol 17 (2) ◽  
pp. 10-19 ◽  
Author(s):  
Ivan Ivanovich Dedov ◽  
Olga Mikhailovna Smirnova ◽  
Irina Vladimirovna Kononenko
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cardiovascular Diseases ◽  
Primary Prevention ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

The method of Genome-Wide Association Studies (GWAS) steadily becomes the basis for searching for candidate genes of monogenic and multifactorial diseases, including type 1 and 2 diabetes mellitus, coronary heart disease, obesity, vascular diseases, and others. To date, approximately 40 loci associated with type 2 diabetes mellitus (T2DM) have been identified and genetic predisposition factors for cardiovascular diseases have been determined. In some cases, the GWAS results not only enable understanding of the pathophysiologic basis for diseases, but also may give rise to new drugs. However, the question naturally arises about the possibility of implementing the accumulated knowledge to predict the development of diseases, including T2DM and its vascular complications. This review summarises the literature data on the possibilities to use the GWAS results to calculate the risk of developing diabetes and cardiovascular diseases. Determination of the individual genetic risk will allow for the primary prevention of diseases and will apparently be the basis of personalised predictive medicine in the near future.

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