Gender, body mass index, and PPARγ polymorphism are good indicators in hyperuricemia prediction for han Chinese

Ming Fen Lee, Tsan Hon Liou, Weu Wang, Wen Harn Pan, Wei Jei Lee, Chung Tan Hsu, Suh Fen Wu, Hsin Hung Chen

研究成果: 雜誌貢獻文章

3 引文 (Scopus)

摘要

Hyperuricemia is closely associated with obesity and metabolic abnormalities, which is also an independent risk factor for cardiovascular diseases. The PPARγ gene, which is linked to obesity and metabolic abnormalities in Han Chinese, might be considered a top candidate gene that is involved in hyperuricemia. This study recruited 457 participants, aged 20-40 years old, to investigate the associations of the PPARγ gene and metabolic parameters with hyperuricemia. Three tag-single nucleotide polymorphisms, rs2292101, rs4684846, and rs1822825, of the PPARγ gene were selected to explore their association with hyperuricemia. Risk genotypes on rs1822825 of the PPARγ gene exhibited statistical significance with hyperuricemia (odds ratio: 1.9; 95% confidence interval: 1.05-3.57). Although gender, body mass index (BMI), serum total cholesterol concentration, or protein intake per day were statistically associated with hyperuricemia, the combination of BMI, gender, and rs1822825, rather than that of age, serum lipid profile, blood pressure, and protein intake per day, satisfied the predictability for hyperuricemia (sensitivity: 69.3%; specificity: 83.7%) in Taiwan-born obese Han Chinese. BMI, gender, and the rs1822825 polymorphism in the PPARγ gene appeared good biomarkers in hyperuricemia; therefore, these powerful indicators may be included in the prediction of hyperuricemia to increase the accuracy of the analysis.

原文英語
頁(從 - 到)40-46
頁數7
期刊Genetic Testing and Molecular Biomarkers
17
發行號1
DOIs
出版狀態已發佈 - 一月 1 2013

指紋

Hyperuricemia
Peroxisome Proliferator-Activated Receptors
Body Mass Index
Genes
Obesity
Serum
Taiwan
Single Nucleotide Polymorphism
Blood Proteins
Cardiovascular Diseases
Biomarkers
Odds Ratio
Cholesterol
Genotype
Confidence Intervals
Blood Pressure
Lipids

ASJC Scopus subject areas

  • Genetics(clinical)

引用此文

Gender, body mass index, and PPARγ polymorphism are good indicators in hyperuricemia prediction for han Chinese. / Lee, Ming Fen; Liou, Tsan Hon; Wang, Weu; Pan, Wen Harn; Lee, Wei Jei; Hsu, Chung Tan; Wu, Suh Fen; Chen, Hsin Hung.

於: Genetic Testing and Molecular Biomarkers, 卷 17, 編號 1, 01.01.2013, p. 40-46.

研究成果: 雜誌貢獻文章

Lee, Ming Fen ; Liou, Tsan Hon ; Wang, Weu ; Pan, Wen Harn ; Lee, Wei Jei ; Hsu, Chung Tan ; Wu, Suh Fen ; Chen, Hsin Hung. / Gender, body mass index, and PPARγ polymorphism are good indicators in hyperuricemia prediction for han Chinese. 於: Genetic Testing and Molecular Biomarkers. 2013 ; 卷 17, 編號 1. 頁 40-46.
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abstract = "Hyperuricemia is closely associated with obesity and metabolic abnormalities, which is also an independent risk factor for cardiovascular diseases. The PPARγ gene, which is linked to obesity and metabolic abnormalities in Han Chinese, might be considered a top candidate gene that is involved in hyperuricemia. This study recruited 457 participants, aged 20-40 years old, to investigate the associations of the PPARγ gene and metabolic parameters with hyperuricemia. Three tag-single nucleotide polymorphisms, rs2292101, rs4684846, and rs1822825, of the PPARγ gene were selected to explore their association with hyperuricemia. Risk genotypes on rs1822825 of the PPARγ gene exhibited statistical significance with hyperuricemia (odds ratio: 1.9; 95{\%} confidence interval: 1.05-3.57). Although gender, body mass index (BMI), serum total cholesterol concentration, or protein intake per day were statistically associated with hyperuricemia, the combination of BMI, gender, and rs1822825, rather than that of age, serum lipid profile, blood pressure, and protein intake per day, satisfied the predictability for hyperuricemia (sensitivity: 69.3{\%}; specificity: 83.7{\%}) in Taiwan-born obese Han Chinese. BMI, gender, and the rs1822825 polymorphism in the PPARγ gene appeared good biomarkers in hyperuricemia; therefore, these powerful indicators may be included in the prediction of hyperuricemia to increase the accuracy of the analysis.",
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