Methylation changes in the peripheral blood of filipinos with type 2 diabetes suggest spurious transcription initiation at TXNIP

2019 ◽  
Author(s):  
Dominic S Albao ◽  
Eva Maria Cutiongco-de la Paz ◽  
Maria Elizabeth Mercado ◽  
Alvin Lirio ◽  
Margarette Mariano ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Peripheral Blood ◽  
Transcription Initiation ◽  
Association Studies ◽  
The United States ◽  
Spurious Transcription ◽  
Functional Consequences ◽  
Different Populations ◽  
Filipino Immigrants

Abstract While much work has been done in associating differentially methylated positions (DMPs) to type 2 diabetes (T2D) across different populations, not much attention has been placed on identifying its possible functional consequences. We explored methylation changes in the peripheral blood of Filipinos with T2D and identified 177 associated DMPs. Most of these DMPs were associated with genes involved in metabolism, inflammation and the cell cycle. Three of these DMPs map to the TXNIP gene body, replicating previous findings from epigenome-wide association studies (EWAS) of T2D. The TXNIP downmethylation coincided with increased transcription at the 3’-UTR, H3K36me3 histone markings, and Sp1 binding, suggesting spurious transcription initiation at the TXNIP 3’-UTR as a functional consequence of T2D methylation changes. We also explored potential epigenetic determinants to increased incidence of T2D in Filipino immigrants in the United States and found 3 DMPs associated with the interaction of T2D and immigration. Two of these DMPs were located near MAP 2 K7 and PRMT1, which may point towards dysregulated stress response and inflammation as a contributing factor to T2D among Filipino immigrants.

scholarly journals Understanding functional consequences of type 2 diabetes risk loci using the universal data integration and visualization R package CONQUER

2020 ◽  
Author(s):  
Gerard A Bouland ◽  
Joline WJ Beulens ◽  
Joey Nap ◽  
Arno R van der Slik ◽  
Arnaud Zaldumbide ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Ribosomal Proteins ◽  
Association Studies ◽  
R Package ◽  
Diabetes Risk ◽  
Genome Wide Association Studies ◽  
Genome Database ◽  
Intergenic Regions ◽  
Functional Consequences

ABSTRACTBackgroundNumerous large genome-wide association studies (GWASs) have been performed to understand the genetic factors of numerous traits, including type 2 diabetes. Many identified risk loci are located in non-coding and intergenic regions, which complicates the understanding how genes and their downstream pathways are influenced. An integrative data approach is required to understand the mechanism and consequences of identified risk loci.ResultsHere, we developed the R-package CONQUER. Data for SNPs of interest (build GRCh38/hg38) were acquired from static- and dynamic repositories, such as, GTExPortal, Epigenomics Project, 4D genome database and genome browsers such as ENSEMBL. CONQUER modularizes SNPs based on the underlying co-expression data and associates them with biological pathways in specific tissues. CONQUER was used to analyze 403 previously identified type 2 diabetes risk loci. In all tissues, the majority of SNPs (mean = 13.50, SD = 11.70) were linked to metabolism. A tissue-shared effect was found for four type 2 diabetes-associated SNPs (rs601945, rs1061810, rs13737, rs4932265) that were associated with differential expression of HLA-DQA2, HSD17B12, MAN2C1 and AP3S2 respectively. Seven SNPs were identified that influenced the expression of seven ribosomal proteins in multiple tissues. Finally, one SNP (rs601945) was found to influence multiple HLA genes in all twelve tissues investigated.ConclusionWe present an universal R-package that aggregates and visualizes data in order to better understand functional consequences of GWAS loci. Using CONQUER, we showed that type 2 diabetes risk loci have many tissue-shared effects on multiple pathways including metabolism, the ribosome and HLA pathway.

1496-P: Clinical Inertia in Relation to Sociodemographic Factors among Patients with Type 2 Diabetes (T2D) in the United States

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1496-P
Author(s):  
GAIL FERNANDES ◽  
BAANIE SAWHNEY ◽  
HAKIMA HANNACHI ◽  
TONGTONG WANG ◽  
ANN MARIE MCNEILL ◽  
...  
Keyword(s):  
United States ◽  
Type 2 Diabetes ◽  
The United States ◽  
Sociodemographic Factors ◽  
Clinical Inertia

Analysis of the Potential Association of Drug-Metabolizing Enzymes CYP2C9*3 and CYP2C19*3 Gene Variations With Type 2 Diabetes: A Case-Control Study

2020 ◽  
Vol 21 (14) ◽  
pp. 1152-1160
Author(s):  
Imadeldin Elfaki ◽  
Rashid Mir ◽  
Faisel Mohammed Abu-Duhier ◽  
Chandan Kumar Jha ◽  
Adel Ibrahim Ahmad Al-Alawy ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Antiplatelet Drug ◽  
Drug Metabolizing Enzymes ◽  
Genotype Distribution ◽  
Nucleotide Polymorphisms ◽  
Metabolizing Enzymes ◽  
Specific Pcr ◽  
Increased Risk ◽  
Different Populations

Background:: Cytochrome P450s (CYPs) are drug-metabolizing enzymes catalyzing the metabolism of about 75% of drug in clinical use. CYP2C9 represents 20% CYP proteins in liver cells and is a crucial member of CYPs superfamily. CYP2C19 metabolizes very important drugs such as antiulcer drug omeprazole, the antiplatelet drug clopidogrel and anticonvulsant mephenytoin. Single nucleotide polymorphisms (SNPs) of CYP genes have been associated with unexpected drug reactions and diseases in different populations. Objective:: We examined the associations of CYP2C9*3 (rs1057910) and CYP2C19*3 (rs4986893) with T2D in Saudi population. Methods:: We used the allele-specific PCR (AS-PCR) and DNA sequencing in 111 cases and 104 controls for rs1057910, and in 119 cases and 110 controls for rs4986893. Results:: It is indicated that the genotype distribution of rs1057910 in cases and controls were not significantly different (P=0.0001). The genotypes of rs1057910 were not associated with type 2 diabetes (T2D) (P>0.05). Whereas the genotype distribution of rs4986893 in cases and controls was significantly different (P=0.049). The AA genotype of rs4986893 may be associated in increased risk to T2D with OR=17.25 (2.06-143.8), RR=6.14(0.96-39.20), P=0.008. Conclusion:: The CYP2C9*3 (rs1057910) may not be associated with T2D, while CYP2C19*3 (rs4986893) is probably associated with T2D. These findings need to be validated in follow-up studies with larger sample sizes and different populations.

scholarly journals How Family Physicians Practice the Principle of Remission Along the Glycemic Continuum

2020 ◽  
Vol 11 ◽  
pp. 215013272097774
Author(s):  
Stephanie T. Fulleborn ◽  
Paul F. Crawford ◽  
Jeremy T. Jackson ◽  
Christy J.W. Ledford
Keyword(s):  
Type 2 Diabetes ◽  
Medical Record ◽  
The United States ◽  
Case Scenario ◽  
Cross Sectional ◽  
Normal Glucose ◽  
Normal Glucose Regulation

Introduction Recent evidence reveals that diabetes and prediabetes (preDM) can be reversed to normal glucose regulation (NGR) through significant weight loss, but how physicians clinically identify the principles of partial and complete remission of diabetes is largely unknown. Methods As part of the cross-sectional omnibus survey conducted in March 2019 at a professional annual meeting in the United States, physician participants answered case scenario questions about the diagnosis and documentation of patients with preDM and type 2 diabetes (T2DM). Results Of the registered conference attendees, 387 (72.7%) responded. When presented with the initial case of preDM, 201 physicians (70.8%) selected R73.03 Prediabetes. In a follow-up encounter with improved lab results, 118 physicians (58.7%) indicated that they would not chart any diabetes-related code and 62 (30.8%) would chart preDM again. When presented with the case of T2DM, 256 physicians (90.1%) indicated E11.0–E11.9 Type 2 Diabetes. In the follow-up encounter, only 38 (14.8%) coded a diagnosis reflecting remission from T2DM to prediabetes and 211 (82.4%) charted T2DM. Conclusion Physicians may be reluctant to document diabetes regression as there is little evidence for long-term outcomes and “downgrading” the diagnosis in the medical record may cause screenings to be missed. Documenting this regression in the medical record should communicate the accurate point on the continuum of glucose intolerance with both the patient and the care team.

Genome-Wide Association Studies Identify Two Novel Loci Conferring Susceptibility to Diabetic Retinopathy in Japanese Patients with Type 2 Diabetes

2021 ◽  
Author(s):  
Minako Imamura ◽  
Atsushi Takahashi ◽  
Masatoshi Matsunami ◽  
Momoko Horikoshi ◽  
Minoru Iwata ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Association Studies ◽  
Meta Analysis ◽  
Japanese Patients ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Stage 1

Abstract Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases, and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (p < 1.0 × 10−4) in an independent case–control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stage-1 and -2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, p = 1.62 × 10−9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11–1.23, and rs140508424 within PALM2 on chromosome 9, p = 4.19 × 10−8, OR = 1.61, 95% CI 1.36–1.91. However, the association of these two loci were not replicated in Korean, European, or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (p = 2.17 × 10−6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.

scholarly journals A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes

2021 ◽  
Author(s):  
Guanghao Qi ◽  
Nilanjan Chatterjee
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Real Data ◽  
Causal Effects ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Sample Sizes

Abstract Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

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