Literature DB >> 21146886

Association between polymorphisms in RAPGEF1, TP53, NRF1 and type 2 diabetes in Chinese Han population.

Lili Qu1, Bangshun He, Yuqin Pan, Yongfei Xu, Chan Zhu, Zhipeng Tang, Qian Bao, Fuliang Tian, Shukui Wang.   

Abstract

Type 2 diabetes is a common complex disorder with environmental and genetic components. The aim of the present study was to investigate the association between the polymorphisms of RAPGEF1, TP53 and NRF1 and the risk of type 2 diabetes in the Chinese Han population. We genotyped rs11243444 (RAPGEF1), rs1042522 (TP53) and rs1882095 (NRF1) in a case-control study, including 273 type 2 diabetes and 247 healthy controls. A significant association was found in a variant of TP53 (rs1042522, odd ratio (OR)=1.28, 95% confidence interval (CI)=1.00-1.64; P=0.046), whereas polymorphisms in RAPGEF1, NRF1 were not associated with the risk of type 2 diabetes. Furthermore, a potential gene-gene interaction showed the odds of being affected with type 2 diabetes was 2.54 times greater in subjects with the TP53 (rs1042522) and RAPGEF1 (rs11243444) risk alleles than those without either (95% CI=1.34-4.81; P=0.004) and the NRF1 gene polymorphism reached significance when paired with TP53:(OR=3.87, 95% CI=1.87-8.40; P=0.0006). We demonstrated that the polymorphism in TP53 (rs1042522) was associated with type 2 diabetes, and that potential interaction of TP53 (rs1042522) and RAPGEF1 (rs11243444), or NRF1 (rs1882095) increased the risk of type 2 diabetes.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 21146886     DOI: 10.1016/j.diabres.2010.11.019

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  10 in total

1.  Accelerated fat cell aging links oxidative stress and insulin resistance in adipocytes.

Authors:  Finny Monickaraj; Sankaramoorthy Aravind; Pichamoorthy Nandhini; Paramasivam Prabu; Chandrakumar Sathishkumar; Viswanathan Mohan; Muthuswamy Balasubramanyam
Journal:  J Biosci       Date:  2013-03       Impact factor: 1.826

Review 2.  The role of the p53 tumor suppressor in metabolism and diabetes.

Authors:  Che-Pei Kung; Maureen E Murphy
Journal:  J Endocrinol       Date:  2016-09-09       Impact factor: 4.286

3.  Association between Gene Polymorphisms of Seven Newly Identified Loci and Type 2 Diabetes and the Correlate Quantitative Traits in Chinese Dong Populations.

Authors:  Liya Liu; Lizhang Chen; Zhanzhan Li; Liang Li; Jian Qu; Jing Xue
Journal:  Iran J Public Health       Date:  2014-10       Impact factor: 1.429

4.  Maternal BMI as a predictor of methylation of obesity-related genes in saliva samples from preschool-age Hispanic children at-risk for obesity.

Authors:  Kathryn Tully Oelsner; Yan Guo; Sophie Bao-Chieu To; Amy L Non; Shari L Barkin
Journal:  BMC Genomics       Date:  2017-01-09       Impact factor: 3.969

Review 5.  Is p53 Involved in Tissue-Specific Insulin Resistance Formation?

Authors:  Justyna Strycharz; Jozef Drzewoski; Janusz Szemraj; Agnieszka Sliwinska
Journal:  Oxid Med Cell Longev       Date:  2017-01-17       Impact factor: 6.543

6.  Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus.

Authors:  Zijing Lin; Xinyu Li; Xiaorong Zhan; Lijie Sun; Jie Gao; Yan Cao; Hui Qiu
Journal:  J Cell Mol Med       Date:  2017-06-23       Impact factor: 5.310

7.  Relationship between TP53 and interleukin-6 gene variants and the risk of types 1 and 2 diabetes mellitus development in the Kermanshah province.

Authors:  Lida Haghnazari; Ramin Sabzi
Journal:  J Med Life       Date:  2021 Jan-Mar

8.  Modulation of autoimmune diabetes by N-ethyl-N-nitrosourea- induced mutations in non-obese diabetic mice.

Authors:  Lucienne Chatenoud; Cindy Marquet; Fabrice Valette; Lindsay Scott; Jiexia Quan; Chun Hui Bu; Sara Hildebrand; Eva Marie Y Moresco; Jean-François Bach; Bruce Beutler
Journal:  Dis Model Mech       Date:  2022-06-01       Impact factor: 5.732

9.  Therapeutic Role of Curcumin in Diabetes: An Analysis Based on Bioinformatic Findings.

Authors:  Ali Mahmoudi; Stephen L Atkin; Nikita G Nikiforov; Amirhossein Sahebkar
Journal:  Nutrients       Date:  2022-08-08       Impact factor: 6.706

10.  ProSim: A Method for Prioritizing Disease Genes Based on Protein Proximity and Disease Similarity.

Authors:  Gamage Upeksha Ganegoda; Yu Sheng; Jianxin Wang
Journal:  Biomed Res Int       Date:  2015-08-03       Impact factor: 3.411

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.