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Crystalline Arthritis
Published in Jason Liebowitz, Philip Seo, David Hellmann, Michael Zeide, Clinical Innovation in Rheumatology, 2023
Hyperuricemia is primarily due to inadequate uric acid excretion in the kidneys. Several well-studied urate transporters, predominantly in the kidney (but also the gut), are responsible for uric acid handling. Genome-wide association studies (GWAS) identified SLC2A9 (encoding GLUT9), SLC22A12 (encoding URAT1), SLC17A1 (encoding NPT1), and ABCG2 as key genes. A heritability analysis of a large twin cohort reported the concordance of hyperuricemia to be 53% in monozygotic twins and 24% in dizygotic twins.5
Inosine induces acute hyperuricaemia in rhesus monkey (Macaca mulatta) as a potential disease animal model
Published in Pharmaceutical Biology, 2021
Dong-hong Tang, Chen-yun Wang, Xi Huang, Hong-kun Yi, Zhe-li Li, Kai-li Ma, You-song Ye, Jian-wen Zhang
Uric acid is excreted and reabsorbed from the kidneys and gut via uric acid transporters, whose aberrant expression is linked to HUA. Urate transporter 1 (URAT1, encoded by SLC22A12) is an important organic anion transporter that maintains uric acid homeostasis. It is located in the brush border of proximal tubular epithelial cells and mainly mediates the reabsorption of uric acid. Intracellular urate is released through glucose transporter 9 (GLUT9, encoded by SLC2A9). A multiple specific anion transporter, organic anion transporter 4 (encoded by SLC22A11), is located in the apical membrane of epithelial cells and has been demonstrated to promote urate reabsorption (Wright et al. 2010; Xu et al. 2017). ABCG2, a half-transporter protein with an ATP-binding cassette, has also been genetically linked to serum uric acid (SUA) level, HUA and gout (Wright et al. 2010; Xu et al. 2017). ABCG2 mediates renal and/or extra-renal urate excretion as a high-capacity exporter and is abundantly expressed in the proximal tubule cells, at the apical membrane, and in hepatocytes (Woodward et al. 2009; Hosomi et al. 2012).
Prescribing patterns of allopurinol and febuxostat according to directives on the reimbursement criteria and clinical guidelines: analysis of a primary care database
Published in Current Medical Research and Opinion, 2019
Ettore Marconi, Alessandra Bettiol, Niccolò Lombardi, Giada Crescioli, Luca Parretti, Alfredo Vannacci, Gerardo Medea, Claudio Cricelli, Francesco Lapi
In North America and Western Europe the gout prevalence was estimated between 1–4%5. In Italy the prevalence was estimated ∼0.9%6. The determinants for gout occurrence include age and sex (i.e. the risk increases after 65 years old and after menopause for men and women, respectively), comorbidities (e.g. metabolic syndrome, cardiovascular disease, and renal disease), dietary habits (e.g. purine-rich diet and alcoholic beverages increases the risk of gout), the use of certain pharmacological treatments (e.g. diuretics, anti-hypertensive drugs, ciclosporin, and low-dose aspirin) and, although rare, genetic variations. In this respect, function of urate transporters GLUT9, NPT1, URAT1, and OAT4 are affected by mutations of genes such as SLC22A12, SLC2A9, and ABCG21,7,8.
Cardio-metabolic disease genetic risk factors among Māori and Pacific Island people in Aotearoa New Zealand: current state of knowledge and future directions
Published in Annals of Human Biology, 2018
Tony R. Merriman, Phillip L. Wilcox
An extremely strong effect size was reported in Māori for the rs16890979 variant of SLC2A9 (Hollis-Moffatt et al., 2009) (Table 1). However, this is likely to be due to stratification, owing to admixture that was not controlled for by Hollis-Moffatt et al. (2009). A more realistic effect size estimate for the SLC2A9 locus is reported in Phipps-Green et al. (2016) (OR = 1.8) in a larger combined Māori and Pacific sample set in which an estimate of Polynesian ancestry was included as a covariate in the regression analysis. Some of the genetic studies did sub-divide the Māori and Pacific sample set into Western (Samoa, Tongan, Niue, Tokelau) and Eastern (Aotearoa NZ and Cook Island Māori) Polynesian sample sets. This was on the basis of the different genetic backgrounds of these groups, as evidenced by principal components clustering analysis (Krishnan et al., 2018), epitomised at ABCG2 rs2231142 (Phipps-Green et al., 2010) and ABCC4 rs972711951 (Tanner et al., 2017).