No correlation between the variants of exostosin 2 gene and type 2 diabetes in Burkina Faso population

Recent genome-wide association studies and replication analyses have reported the association of variants of the exostosin- 2 gene (EXT2) and risk of type 2 diabetes (T2D) in some populations, but not in others. This study aimed to characterize the variants rs1113132, rs3740878 and rs11037909 of EXT2 and to determine the existence of a possible correlation with T2D in Burkina Faso. It is a case-control study undertaken in Burkina Faso in the city of Ouagadougou at the Hospital of Saint Camille of Ouagadougou from December 2014 to June 2015. It relates to 121 type 2 diabetes cases and 134 controls. The genotyping of these polymorphisms was done by real-time PCR using the allelic exclusion method with TaqMan probes. The minor allele frequencies (MAFs) was almost identical in diabetic and control subjects for the all three Single Nucleotide Polymorphisms (SNPs) with no statistical significance, p>0.05: rs1113132 (OR=0.89; p=0.82); rs11037909 (OR=0.89; p=0.74) and rs3740878 (OR=1.52; p=0.42). None of the three polymorphisms studied was associated with the risk of DT2. However, an association between the BMI, age and type 2 diabetes was noted. The variants of EXT2 would not be associated to the risk of T2D in the African black population of Burkina Faso.

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Association Analysis of Genetic Variants with Type 2 Diabetes in a Mongolian Population in China

Journal of Diabetes Research ◽

10.1155/2015/613236 ◽

2015 ◽

Vol 2015 ◽

pp. 1-7 ◽

Cited By ~ 11

Author(s):

Haihua Bai ◽

Haiping Liu ◽

Suyalatu Suyalatu ◽

Xiaosen Guo ◽

Shandan Chu ◽

...

Keyword(s):

Type 2 Diabetes ◽

Large Scale ◽

Risk Allele ◽

Association Studies ◽

Northern China ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Genome Wide

The large scale genome wide association studies (GWAS) have identified approximately 80 single nucleotide polymorphisms (SNPs) conferring susceptibility to type 2 diabetes (T2D). However, most of these loci have not been replicated in diverse populations and much genetic heterogeneity has been observed across ethnic groups. We tested 28 SNPs previously found to be associated with T2D by GWAS in a Mongolian sample of Northern China (497 diagnosed with T2D and 469 controls) for association with T2D and diabetes related quantitative traits. We replicated T2D association of 11 SNPs, namely, rs7578326 (IRS1), rs1531343 (HMGA2), rs8042680 (PRC1), rs7578597 (THADA), rs1333051 (CDKN2), rs6723108 (TMEM163), rs163182 and rs2237897 (KCNQ1), rs1387153 (MTNR1B), rs243021 (BCL11A), and rs10229583 (PAX4) in our sample. Further, we showed that risk allele of the strongest T2D associated SNP in our sample, rs757832 (IRS1), is associated with increased level of TG. We observed substantial difference of T2D risk allele frequency between the Mongolian sample and the 1000G Caucasian sample for a few SNPs, including rs6723108 (TMEM163) whose risk allele reaches near fixation in the Mongolian sample. Further study of genetic architecture of these variants in susceptibility of T2D is needed to understand the role of these variants in heterogeneous populations.

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Type 2 Diabetes and Glycemic Traits Are Not Causal Factors of Osteoarthritis: A Two-Sample Mendelian Randomization Analysis

Frontiers in Genetics ◽

10.3389/fgene.2020.597876 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhiyong Cui ◽

Hui Feng ◽

Baichuan He ◽

Yong Xing ◽

Zhaorui Liu ◽

...

Keyword(s):

Type 2 Diabetes ◽

Mendelian Randomization ◽

Association Studies ◽

Causal Effects ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Knee Oa ◽

Increased Risk

BackgroundIt remains unclear whether an increased risk of type 2 diabetes (T2D) affects the risk of osteoarthritis (OA).MethodsHere, we used two-sample Mendelian randomization (MR) to obtain non-confounded estimates of the effect of T2D and glycemic traits on hip and knee OA. We identified single-nucleotide polymorphisms (SNPs) strongly associated with T2D, fasting glucose (FG), and 2-h postprandial glucose (2hGlu) from genome-wide association studies (GWAS). We used the MR inverse variance weighted (IVW), the MR–Egger method, the weighted median (WM), and the Robust Adjusted Profile Score (MR.RAPS) to reveal the associations of T2D, FG, and 2hGlu with hip and knee OA risks. Sensitivity analyses were also conducted to verify whether heterogeneity and pleiotropy can bias the MR results.ResultsWe did not find statistically significant causal effects of genetically increased T2D risk, FG, and 2hGlu on hip and knee OA (e.g., T2D and hip OA, MR–Egger OR = 1.1708, 95% CI 0.9469–1.4476, p = 0.1547). It was confirmed that horizontal pleiotropy was unlikely to bias the causality (e.g., T2D and hip OA, MR–Egger, intercept = −0.0105, p = 0.1367). No evidence of heterogeneity was found between the genetic variants (e.g., T2D and hip OA, MR–Egger Q = 30.1362, I2 < 0.0001, p = 0.6104).ConclusionOur MR study did not support causal effects of a genetically increased T2D risk, FG, and 2hGlu on hip and knee OA risk.

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Replication of Genome-Wide Association Studies of Type 2 Diabetes Susceptibility in Japan

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2008-0452 ◽

2008 ◽

Vol 93 (8) ◽

pp. 3136-3141 ◽

Cited By ~ 95

Author(s):

Yukio Horikawa ◽

Kazuaki Miyake ◽

Kazuki Yasuda ◽

Mayumi Enya ◽

Yushi Hirota ◽

...

Keyword(s):

Type 2 Diabetes ◽

Association Studies ◽

Susceptibility Genes ◽

Large Sample Size ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Diabetes Susceptibility ◽

Genome Wide ◽

Candidate Loci

Abstract Background: In Europeans and populations of European origin, several groups have recently identified novel type 2 diabetes susceptibility genes, including FTO, SLC30A8, HHEX, CDKAL1, CDKN2B, and IGF2BP2, none of which were in the list of functional candidates. Objective and Design: The aim of this study was to replicate in a Japanese population previously identified associations of single nucleotide polymorphisms (SNPs) within 10 candidate loci with type 2 diabetes using a relatively large sample size: 1921 subjects with type 2 diabetes and 1622 normal controls. Results: A total of 15 SNPs were genotyped. Eight SNPs in five loci were found to be associated with type 2 diabetes: rs3802177 [odds ratio (OR) = 1.16 (95% confidence interval (CI) 1.05–1.27); P = 4.5 × 10−3] in SLC30A8; rs1111875 [OR = 1.27 (95% CI 1.14–1.40); P = 1.4 × 10−5] and rs7923837 [OR = 1.27 (95% CI 1.13–1.43); P = 1.0 × 10−4] in HHEX; rs10811661 [OR = 1.27 (95% CI 1.15–1.40); P = 1.9 × 10−6] in CDKN2B; rs4402960 [OR = 1.23 (95% CI 1.11–1.36); P = 8.1 × 10−5] and rs1470579 [OR = 1.18 (95% CI 1.07–1.31); P = 8.3 × 10−4] in IGF2BP2; and rs7754840 [OR = 1.28 (95% CI 1.17–1.41); P = 4.5 × 10−7] and rs7756992 [OR = 1.27 (95% CI 1.15–1.40); P = 9.8 × 10−7] in CDKAL1. The first and second strongest associations were found at variants in CDKAL1 and CDKN2B, both of which are involved in the regenerative capacity of pancreatic β-cells. Conclusion: Some of these variants represent common type 2 diabetes-susceptibility genes in both Japanese and Europeans.

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Replication of Type 2 diabetes-associated variants in a Saudi Arabian population

Physiological Genomics ◽

10.1152/physiolgenomics.00100.2017 ◽

2018 ◽

Vol 50 (4) ◽

pp. 296-297 ◽

Cited By ~ 1

Author(s):

Ruifang Li-Gao ◽

Salma M. Wakil ◽

Brian F. Meyer ◽

Nduna Dzimiri ◽

Dennis O. Mook-Kanamori

Keyword(s):

Type 2 Diabetes ◽

Large Scale ◽

Association Studies ◽

Saudi Arabian ◽

P Value ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Significance Level ◽

Arabian Population

Over 120 Type 2 diabetes (T2D) loci have been identified from genome-wide association studies (GWAS), mainly from Caucasian populations. Very limited knowledge is available on the Saudi Arabian population. In this study, 122 previously reported T2D-related variants from 84 loci were examined in a Saudi Arabian cohort of 1,578 individuals (659 T2D cases and 919 controls). Eleven single nucleotide polymorphisms (SNPs) corresponding to nine independent loci had a P value <0.05. If a more stringent Bonferroni threshold of P = 4.1 × 10−4 ( = 0.05/122) were applied, none of the SNPs would have reached the significance level. Nine of the SNPs with a P value <0.05 showed similar odds ratios as previously described, but rs11605924 ( CRY2) and rs9470794 ( ZFAND3) were in the opposite direction. This study demonstrates the importance of large-scale GWAS in the Saudi Arabian population to identify ethnicity-specific disease-associated variants.

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Type 2 diabetes and glycemic traits are not causal factors of osteoarthritis: A two-sample Mendelian randomization analysis

10.21203/rs.3.rs-37242/v1 ◽

2020 ◽

Author(s):

Zhiyong Cui ◽

Hui Feng ◽

Baichuan He ◽

Yong Xing ◽

Zhaorui Liu ◽

...

Keyword(s):

Type 2 Diabetes ◽

Mendelian Randomization ◽

Association Studies ◽

Causal Effects ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Knee Oa ◽

Increased Risk

Abstract Background: It remains unclear whether an increased risk of type 2 diabetes (T2D) affects the risk of osteoarthritis (OA). Methods: Here, we used two-sample Mendelian randomization (MR) to obtain non-confounded estimates of the effect of T2D and glycemic traits on hip and knee OA. We identified single nucleotide polymorphisms (SNPs) strongly associated with T2D, fasting glucose (FG) and 2-hour postprandial glucose (2hGlu) from genome-wide association studies (GWAS) . We used MR inverse variance weighted (IVW), the MR-Egger method, the weighted median (WM) and Robust Adjusted Profile Score (MR.RAPS) to reveal the associations of T2D, FG and 2hGlu with hip and knee OA risk. Sensitivity analyses were also conducted to verify whether heterogeneity and pleiotropy can bias the MR results.Results: We did not find statistically significant causal effects of genetically increased T2D risk, FG and 2hGlu on hip and knee OA (e.g., T2D and hip OA, MR-Egger OR=0.9536, 95% CI 0.5585 to 1.6283, p=0.8629). It was confirmed that horizontal pleiotropy was unlikely to bias the causality (e.g., T2D and hip OA, MR-Egger, intercept=-0.0032, p=0.8518). No evidence of heterogeneity was found between the genetic variants (e.g., T2D and hip OA, MR-Egger Q=40.5481, I2=0.1368, p=0.2389). Conclusions: Our MR study did not support causal effects of a genetically increased T2D risk, FG and 2hGlu on hip and knee OA risk.

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Emerging Roles for the INK4a/ARF (CDKN2A) Locus in Adipose Tissue: Implications for Obesity and Type 2 Diabetes

Biomolecules ◽

10.3390/biom10091350 ◽

2020 ◽

Vol 10 (9) ◽

pp. 1350

Author(s):

Yasmina Kahoul ◽

Frédérik Oger ◽

Jessica Montaigne ◽

Philippe Froguel ◽

Christophe Breton ◽

...

Keyword(s):

Type 2 Diabetes ◽

Adipose Tissue ◽

Energy Homeostasis ◽

Metabolic Diseases ◽

Association Studies ◽

Cardiovascular Complications ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Cdkn2a Locus

Besides its role as a cell cycle and proliferation regulator, the INK4a/ARF (CDKN2A) locus and its associated pathways are thought to play additional functions in the control of energy homeostasis. Genome-wide association studies in humans and rodents have revealed that single nucleotide polymorphisms in this locus are risk factors for obesity and related metabolic diseases including cardiovascular complications and type-2 diabetes (T2D). Recent studies showed that both p16INK4a-CDK4-E2F1/pRB and p19ARF-P53 (p14ARF in humans) related pathways regulate adipose tissue (AT) physiology and adipocyte functions such as lipid storage, inflammation, oxidative activity, and cellular plasticity (browning). Targeting these metabolic pathways in AT emerged as a new putative therapy to alleviate the effects of obesity and prevent T2D. This review aims to provide an overview of the literature linking the INK4a/ARF locus with AT functions, focusing on its mechanisms of action in the regulation of energy homeostasis.

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

Human Molecular Genetics ◽

10.1093/hmg/ddab044 ◽

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.

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

International Journal of Epidemiology ◽

10.1093/ije/dyaa262 ◽

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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Evaluation of glycemic traits in susceptibility to COVID-19 risk: a Mendelian randomization study

BMC Medicine ◽

10.1186/s12916-021-01944-3 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Shiu Lun Au Yeung ◽

Jie V Zhao ◽

C Mary Schooling

Keyword(s):

Type 2 Diabetes ◽

Genetic Predisposition ◽

Mendelian Randomization ◽

Fasting Glucose ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Inverse Association ◽

Wide Confidence Interval

Abstract Background Observational studies suggest poorer glycemic traits and type 2 diabetes associated with coronavirus disease 2019 (COVID-19) risk although these findings could be confounded by socioeconomic position. We conducted a two-sample Mendelian randomization to clarify their role in COVID-19 risk and specific COVID-19 phenotypes (hospitalized and severe cases). Method We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). We used inverse variance weighting to obtain the causal estimates of glycemic traits and genetic predisposition to type 2 diabetes in COVID-19 risk. Sensitivity analyses included MR-Egger and weighted median method. Results We found genetic predisposition to type 2 diabetes was not associated with any COVID-19 phenotype (OR: 1.00 per unit increase in log odds of having diabetes, 95%CI 0.97 to 1.04 for overall COVID-19; OR: 1.02, 95%CI 0.95 to 1.09 for hospitalized COVID-19; and OR: 1.00, 95%CI 0.93 to 1.08 for severe COVID-19). There were no strong evidence for an association of glycemic traits in COVID-19 phenotypes, apart from a potential inverse association for fasting glucose albeit with wide confidence interval. Conclusion We provide some genetic evidence that poorer glycemic traits and predisposition to type 2 diabetes unlikely increase the risk of COVID-19. Although our study did not indicate glycemic traits increase severity of COVID-19, additional studies are needed to verify our findings.

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