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1.
Lipids Health Dis ; 18(1): 81, 2019 Apr 01.
Artículo en Inglés | MEDLINE | ID: mdl-30935401

RESUMEN

BACKGROUND: The aim of this study was to determine the association between hypertriglyceridemia and hyperuricemia (HUA). METHODS: The study was conducted in 3884 subjects who had not received medication enrolled as a baseline. Each participant received at least three annual health check-ups between 2011 and 2017. The risk of hyperuricemia was assessed in four Quartiles (Q1 to Q4) according to TG levels using multivariate-adjusted logistic regression models. RESULTS: The total incidence rate of HUA was 62.3/1000 person-years. In the univariate analysis, the risk of hyperuricemia in people with hypertriglyceridemia was 2.353 times that of normal triglycerides, with a 95% confidence interval of (2.011, 2.754), and the risk of hyperuricemia in men was 1.86 times of female, and the 95% confidence interval is (1.634, 2.177). After adjusting the potential confounders, the relative risk RR of TG at Q2 Q3 Q4 was 1.445 (95%CI:1.114, 1.901), 2.075 (1.611, 2.674), 2.972 (2.322, 3.804). CONCLUSIONS: TG is an independent risk factor for hyperuricemia. As the level of TG increases, the risk of HUA increases.


Asunto(s)
Hipertrigliceridemia/epidemiología , Hiperuricemia/epidemiología , Metabolismo de los Lípidos , Triglicéridos/sangre , Adulto , Anciano , Femenino , Humanos , Hipertrigliceridemia/sangre , Hipertrigliceridemia/patología , Hiperuricemia/sangre , Hiperuricemia/patología , Masculino , Persona de Mediana Edad , Factores de Riesgo , Caracteres Sexuales , Población Urbana , Ácido Úrico/sangre
2.
Diagnosis (Berl) ; 6(3): 277-286, 2019 08 27.
Artículo en Inglés | MEDLINE | ID: mdl-30511928

RESUMEN

Background Clinical evidence indicates that genetic variations may interfere with the mechanism of drug action. Recently, it has been reported that the single nucleotide polymorphisms (SNPs) of STAT4, PTPN2, PSORS1C1 and TRAF3IP2RA genes are associated with the clinical efficacy of tumor necrosis factor (TNF) inhibitors in the treatment of rheumatoid arthritis (RA) patients. Therefore, the detection of the SNPs linked with TNF inhibitor efficacy may provide an important basis for the treatment of RA. This study intended to establish molecular diagnostic methods for genotyping the linked SNPs based on high resolution melting (HRM) curve analysis. Methods The polymerase chain reaction-HRM (PCR-HRM) curve analysis detecting systems were established by designing the primers of the four SNPs, rs7574865G>T, rs7234029A>G, rs2233945C>A and rs33980500C>T, and the performance and clinical applicability of which were evaluated by using the Sanger sequencing method and genotyping test for 208 clinical samples. Results The self-developed molecular diagnostic methods of PCR-HRM were confirmed to be able to correctly genotype the four SNPs, the sensitivity and specificity of which were 100% in this study. The repeatability and reproducibility tests showed that there is little variable in intra-assay and inter-assay (the coefficient of variation ranged from 0.01% to 0.07%). The slight changes of DNA template and primer concentrations, PCR cycle number and reaction system volume had no significant effect on the genotyping performance of the method. The PCR-HRM assays were also applied to other PCR thermocyclers with HRM function and use different saturation fluorescent dyes. Conclusions The PCR-HRM genotyping method established in this study can be applied to the routine molecular diagnosis of rs7574865, rs7234029, rs2233945 and rs33980500.


Asunto(s)
Técnicas de Genotipaje , Técnicas de Diagnóstico Molecular , Reacción en Cadena de la Polimerasa , Polimorfismo de Nucleótido Simple , Inhibidores del Factor de Necrosis Tumoral , Artritis Reumatoide/tratamiento farmacológico , Artritis Reumatoide/genética , Femenino , Genotipo , Humanos , Masculino , Persona de Mediana Edad , Patología Molecular , Proteína Tirosina Fosfatasa no Receptora Tipo 2/genética , Proteínas/genética , Reproducibilidad de los Resultados , Factor de Transcripción STAT4/genética , Sensibilidad y Especificidad
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