Pathogenesis of gout.

Arthritis Research Centre of Canada, University of British Columbia, Vancouver, British Columbia, Canada.
Annals of internal medicine (Impact Factor: 16.1). 11/2005; 143(7):499-516.
Source: PubMed
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    ABSTRACT: AimOriginal studies have employed various genetic models in association analysis between ABCG2 Q141K (rs2231142) with gout risk and different or conflicting results, especially regarding the role of gender in this association. In addition, it is not clear whether the association varies by ethnicity.Method Articles published before September 1, 2013 were extracted and registered into databases for the systematic review of this polymorphism. The quality of each study was scored based on predefined criteria. The genetic model was identified through stratification analysis, then a meta-analysis including all publically available data was preformed to test the association between rs2231142 and gout risk. Potential sources of heterogeneity were sought out via stratification analysis and meta-regression analysis.ResultsNine case–control studies involving 17 942 individuals were eligible for the meta-analysis of rs2231142. Codominant model was the most appropriate genetic model to interpret the susceptibility cause. It showed that the rs2231142 T allele obviously increased gout risk, and TT was much stronger than GT (TT vs. GG: OR, 4.10; 95% CI, 2.90–5.80; GT vs. GG: OR, 1.71, 95% CI, 1.39–2.10). In addition, gender and ethnicity were found to affect the association between the susceptibility of gout and rs2231142.ConclusionABCG2 rs2231142 is an important genetic factor in increasing gout risk, and the difference in genetic association has been found between male and female populations. In addition, the degree of association has been found to vary with ethnicity.
    International Journal of Rheumatic Diseases 10/2014; DOI:10.1111/1756-185X.12519 · 1.77 Impact Factor
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    ABSTRACT: The associations of serum uric acid (UA), atherogenic index of plasma (AIP) and albuminuria with cardiovascular disease have been shown. Several studies focused on association of serum UA and dyslipidemia, serum UA and renal impairment, dyslipidemia and renal impairment. However, to date, in literature, there have been no studies demonstrating the relationship between these parameters in diabetic patients together. We aimed to investigate the association between serum UA, albuminuria and AIP in diabetic patients. This was a retrospective study involving data of 645 diabetic patients. The patients were separated into groups according to their serum uric acid and AIP levels. The quantitative urine albumin/creatinine ratio in morning spot urine samples were used for standard albuminuria determination. Serum uric acid levels under 6 mg/dL were considered as normal. AIP was calculated as the logarithmically transformed ratio of triglyceride to high density lipoprotein cholesterol. AIP and albuminuria levels were high in high serum UA group compared to normal UA group. Uric acid and albuminuria tended to increase with increasing AIP. Correlation analysis showed that albuminuria, AIP and UA were significantly correlated with each other. Additionally, in binary logistic regression analysis, AIP was found to be independently associated with high UA levels. Present study reveals that serum UA, AIP and albuminuria are closely related. Physicians should be aware that patients with concomitant hyperuricemia, albuminuria and high AIP are at increased risk of developing cardiovascular disease. Our study confirms that there is a need for larger prospective studies to determine the mechanisms underlying the association of serum UA, AIP and albuminuria.
    International Journal of Clinical and Experimental Medicine 01/2014; 7(12):5737-43. · 1.42 Impact Factor
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    ABSTRACT: Creatinine (Cr), uric (UA) and ascorbic acid (AA) are common constituents in human fluids. Their abnormal concentrations in human fluids are associated with various diseases. Thus, apart from the endogenous formation in human body, it is also important to examine their sources from food products. In this study, a rapid and accurate HILIC method was developed for simultaneous determination of Cr, UA and AA in bovine milk and orange juice. Milk samples were pretreated by protein precipitation, centrifugation and filtration, followed by HPLC separation and quantification using a Waters Spherisorb S5NH2 column. The developed method has been successfully applied to determine the concentration of UA, AA and Cr in milk and fruit juice samples. The milk samples tested were found to contain UA and creatinine in the concentration range of 24.1-86.0 and 5.07-11.2μgmL(-1), respectively. The orange juices contain AA over 212μgmL(-1). Copyright © 2015 Elsevier Ltd. All rights reserved.
    Food Chemistry 09/2015; 182. DOI:10.1016/j.foodchem.2015.02.142 · 3.26 Impact Factor

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