Publication: An exploration of ABCG2 and SLC2A9 gene interactions with gout
3
0
Issued Date
2020
Resource Type
File Type
application/pdf
ISSN
1252208
Other identifier(s)
2-s2.0-85096169601
Rights
Srinakharinwirot University
Rights Holder(s)
Scopus
Bibliographic Citation
Journal of the Medical Association of Thailand. Vol 103, No.11 (2020), p.1163-1170
Suggested Citation
Khuancharee K., Tanunyutthawongse C., Wannaiampikul S. An exploration of ABCG2 and SLC2A9 gene interactions with gout. Journal of the Medical Association of Thailand. Vol 103, No.11 (2020), p.1163-1170. doi:10.35755/jmedassocthai.2020.11.11281 Retrieved from: https://hdl.handle.net/20.500.14740/4327
Abstract
Background: Currently, there is no systematic analysis of single nucleotide polymorphisms (SNPs) in the urate transporter genes (ABCG2 and SLC2A9), and the influence of their combination and gene-gene (G×G) interactions on gout is still unknown in the Thai population. Objective: To investigate the interaction between ABCG2 and SLC2A9 with gout. Materials and Methods: A matched case-control study with 116 Thai adults (58 gout patients and 58 control subjects) was done. Genotyping using a TaqMan SNP Genotyping Assays was performed. G×G interactions for gout risk were analyzed using an interaction analysis in multiple conditional logistic regression. Results: The results show that the rs2231142 (G/T+T/T) variants in ABCG2 was associated with gout. On the contrary, the rs2280205 (G/A+A/A) and rs6820230 (C/T-T/T) variant in SLC2A9 were not associated with gout. The result indicated that the participants carrying ABCG2 variant with SLC2A9 wild-type (i.e., original base pairs) had a significant association with gout. The present study results also revealed that epistatic interaction pairs (rs2231142:rs6820230 and rs2231142:rs2280205) were strongly associated with gout. Conclusion: The authors concluded that the ABCG2 and SLC2A9 interactions were a significant association with gout. The stronger combined effect of SNPs in the ABCG2 and SLC2A9 genes via G×G interaction may help to predict gout risk and its prognosis. However, further studies with larger sample sizes should be performed to confirm these results. © JOURNAL OF THE MEDICAL ASSOCIATION OF THAILAND | 2020.
Subject(s)
High density lipoprotein cholesterol
Low density lipoprotein cholesterol
Triacylglycerol
ABCG2 gene
Adult
Article
Body mass
Case control study
Cholesterol blood level
Controlled study
Diastolic blood pressure
Female
Gene
Gene interaction
Genetic association
Genetic variability
Genome-wide association study
Genotype
Gout
Human
Major clinical study
Male
Middle aged
Obesity
Prognosis
Sample size
Single nucleotide polymorphism
SLC2A9 gene
Systolic blood pressure
Low density lipoprotein cholesterol
Triacylglycerol
ABCG2 gene
Adult
Article
Body mass
Case control study
Cholesterol blood level
Controlled study
Diastolic blood pressure
Female
Gene
Gene interaction
Genetic association
Genetic variability
Genome-wide association study
Genotype
Gout
Human
Major clinical study
Male
Middle aged
Obesity
Prognosis
Sample size
Single nucleotide polymorphism
SLC2A9 gene
Systolic blood pressure