SLC22A1  And  ATM  Genes Polymorphisms Are Associated With The Risk Of Type 2 Diabetes Mellitus In Western Saudi Arabia: A Case-Control Study

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Abstract

Introduction

Type 2 diabetes mellitus (T2DM) is a major global health problem that is progressively affected by genetic and environmental factors. The aim of this study is to determine the influence of solute carrier family 22 member 1 ( SLC22A1) rs628031 and rs461473, and ataxia telangiectasia mutated ( ATM) rs11212617 polymorphisms on the risk of T2DM in Saudi Arabia by considering many parameters associated with glycemic control of T2DM, such as body mass index (BMI), fasting blood glucose, glycated hemoglobin (HbA1c), and triglyceride.

Methods

In a case-control study, genomic DNA from controls and diabetic groups was isolated and genotyped for each single-nucleotide polymorphism.

Results

There were significant correlations between T2DM and both BMI and HbA1c. Significant associations between G/G and A/G genotypes of rs628031 and rs461473 variants of SLC22A1 and high levels of HbA1c were detected. Therefore, G was predicted to be the risk allele among the assessed SLC22A1 variants. A significant correlation was observed between A/A and A/C genotypes of the rs11212617 polymorphism of ATM and elevated HbA1c. Relative risk calculation confirmed A to be the risk allele in the T2DM population.

Conclusion

Our study showed the risk of the assessed SLC22A1 and ATM variants on glycemic control parameters in diabetic patients.

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Most cited references 23

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The Effect of Oral Antidiabetic Agents on A1C Levels

Diana Sherifali, Kara A Nerenberg, Eleanor Pullenayegum … (2010)

OBJECTIVE Previous reviews of the effect of oral antidiabetic (OAD) agents on A1C levels summarized studies with varying designs and methodological approaches. Using predetermined methodological criteria, we evaluated the effect of OAD agents on A1C levels. RESEARCH DESIGN AND METHODS The Excerpta Medica (EMBASE), the Medical Literature Analysis and Retrieval System Online (MEDLINE), and the Cochrane Central Register of Controlled Trials databases were searched from 1980 through May 2008. Reference lists from systematic reviews, meta-analyses, and clinical practice guidelines were also reviewed. Two evaluators independently selected and reviewed eligible studies. RESULTS A total of 61 trials reporting 103 comparisons met the selection criteria, which included 26,367 study participants, 15,760 randomized to an intervention drug(s), and 10,607 randomized to placebo. Most OAD agents lowered A1C levels by 0.5−1.25%, whereas thiazolidinediones and sulfonylureas lowered A1C levels by ∼1.0–1.25%. By meta-regression, a 1% higher baseline A1C level predicted a 0.5 (95% CI 0.1–0.9) greater reduction in A1C levels after 6 months of OAD agent therapy. No clear effect of diabetes duration on the change in A1C with therapy was noted. CONCLUSIONS The benefit of initiating an OAD agent is most apparent within the first 4 to 6 months, with A1C levels unlikely to fall more than 1.5% on average. Pretreated A1C levels have a modest effect on the fall of A1C levels in response to treatment.

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Candidate Gene Identification Approach: Progress and Challenges

Mengjin Zhu, Shuhong Zhao (2007)

Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach.

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Human organic cation transporter (OCT1 and OCT2) gene polymorphisms and therapeutic effects of metformin.

Keith R. Yamamoto, Ichiro Ieiri, E Shikata … (2006)

Organic cation transporters (OCTs) are responsible for the hepatic and renal transport of metformin. In this study we analyzed variants of OCT1 and OCT2 genes in 33 patients (24 responders and nine non-responders) based on the hypothesis that polymorphisms in both genes contribute to large inter-patient variability in the clinical efficacy of metformin. The sequences of the 5'-flanking and coding regions of the two genes of interest were screened by single-strand conformation polymorphism (SSCP) analysis. To compare the causative factors between responders and non-responders, we performed stepwise discriminant functional analysis. Age, body mass index (BMI) and treatment with lipid-lowering agents were demonstrated as positive predictors, and two mutations in the OCT1 gene, -43T > G in intron 1 and 408Met > Val (1222A > G) in exon 7, were negative and positive predictors, respectively, for the efficacy of metformin; the predictive accuracy was 55.5% (P < 0.05). Subsequent study indicated that OCT1 mRNA levels tended to be lower in human livers with the 408Met (1222A) variant, though the differences did not reach the level of significance. In this study it is suggested that OCT1 and OCT2 gene polymorphisms have little contribution to the clinical efficacy of metformin.

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Author and article information

Journal

Journal ID (nlm-ta): Appl Clin Genet

Journal ID (iso-abbrev): Appl Clin Genet

Journal ID (publisher-id): TACG

Journal ID (pmc): tacg

Title: The Application of Clinical Genetics

Publisher: Dove

ISSN (Electronic): 1178-704X

Publication date (Electronic): 15 November 2019

Publication date Collection: 2019

Volume: 12

Pages: 213-219

Affiliations

[1 ]Department of Biochemistry, Faculty of Science, King Abdulaziz University , Jeddah 21589, Kingdom of Saudi Arabia

[2 ]KACST Technology Innovation Center in Personalized Medicine, King Abdulaziz University , Jeddah 21589, Kingdom of Saudi Arabia

[3 ]Department of Internal Medicine, Faculty of Medicine, King Abdulaziz University , Jeddah 21589, Kingdom of Saudi Arabia

[4 ]Department of Family and Community Medicine, Faculty of Medicine, King Abdulaziz University Hospital , Jeddah 21589, Kingdom of Saudi Arabia

Author notes

Correspondence: Sherin Bakhashab King Abdulaziz University , P.O. Box 80218, Jeddah21589, Kingdom of Saudi ArabiaTel +966 12 6400000Fax +966 12 6952076 Email sbakhashab@kau.edu.sa

Author information

Rana M Altall http://orcid.org/0000-0002-0977-7911

Ashraf Dallol http://orcid.org/0000-0002-8803-228X

Sherin Bakhashab http://orcid.org/0000-0003-1580-0409

Article

Publisher ID: 229952

DOI: 10.2147/TACG.S229952

PMC ID: 6863135

SO-VID: 419c42db-73d2-4eef-a075-0a198fa0c410

License:

This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

History

Date received : 07 September 2019

Date accepted : 03 November 2019

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Tables: 5, References: 36, Pages: 7

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SLC22A1 And ATM Genes Polymorphisms Are Associated With The Risk Of Type 2 Diabetes Mellitus In Western Saudi Arabia: A Case-Control Study

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Abstract

Introduction

Methods

Results

Conclusion

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Arabidopsis genomics

Most cited references 23

The Effect of Oral Antidiabetic Agents on A1C Levels

Candidate Gene Identification Approach: Progress and Challenges

Human organic cation transporter (OCT1 and OCT2) gene polymorphisms and therapeutic effects of metformin.

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