Gout. Novel therapies for treatment of gout and hyperuricemia.
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ABSTRACT:
SUBMITTER: Terkeltaub R
PROVIDER: S-EPMC2745774 | biostudies-literature | 2009
REPOSITORIES: biostudies-literature
Publications
Gout. Novel therapies for treatment of gout and hyperuricemia.
Arthritis research & therapy 20090723 4
In the past few decades, gout has increased not only in prevalence, but also in clinical complexity, the latter accentuated in part by a dearth of novel advances in treatments for hyperuricemia and gouty arthritis. Fortunately, recent research reviewed here, much of it founded on elegant translational studies of the past decade, highlights how gout can be better managed with cost-effective, well-established therapies. In addition, the advent of both new urate-lowering and anti-inflammatory drugs ...[more]
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Project description:Gout is a chronic metabolic disease that seriously affects human health. It is also a major challenge facing the world, which has brought a heavy burden to patients and society. Hyperuricemia (HUA) is the most important risk factor for gout. In recent years, with the improvement of living standards and the change of dietary habits, the incidence of gout in the world has increased dramatically, and gradually tends to be younger. An increasing number of studies have shown that gene mutations may play an important role in the development of HUA and gout. Therefore, we reviewed the existing literature and summarized the susceptibility genes and research status of HUA and gout, in order to provide reference for the early diagnosis, individualized treatment and the development of new targeted drugs of HUA and gout.
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Project description:ObjectivesMicroRNAs (miRNAs) are short single-stranded RNAs that play a role in the post-transcriptional regulation of gene expression. Their deregulation can be associated with various diseases, such as cancer, neurodegenerative, and immune-related diseases. The aim of our study was to compare miRNA levels in plasma that could potentially influence the progression of hyperuricemia to gout, since the mechanism of progression is still unclear.MethodsTotal RNA, including miRNA, was isolated from the plasma of 45 patients with asymptomatic hyperuricemia, 131 patients with primary gout (including 16 patients having a gout attack), and 130 normouricemic controls. The expression of 18 selected miRNAs (cel-miR-39 and cel-miR-54 as spike-in controls, hsa-miR-16-5p and hsa-miR-25-3p as endogenous controls, hsa-miR-17-5p, hsa-miR-18a-5p, hsa-miR-30a-3p, hsa-miR-30c-5p, hsa-miR-126-3p, hsa-miR-133a-3p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146a-5p, hsa-miR-155-5p, hsa-miR-222-3p, hsa-miR-223-3p, hsa-miR-488-3p and hsa-miR-920) was measured using qPCR.ResultsWe found that hsa-miR-17-5p, hsa-miR-18a-5p, hsa-miR-30c-5p, hsa-miR-142-3p, and hsa-miR-223-3p were significantly upregulated (p < 0.001) in the plasma of hyperuricemia and gout patients compared to normouricemic individuals. As part of the follow-up of our previous study, we found a negative correlation between hsa-miR-17-5p, hsa-miR-30c-5p, hsa-miR-126-3p, hsa-miR-142-3p, and hsa-miR-223-3p with plasma levels of chemokine MCP-1. Additionally, we found a positive correlation between CRP and plasma levels of hsa-miR-17-5p, hsa-miR-18a-5p, hsa-miR-30c-5p, hsa-miR-126-3p, hsa-miR-142-3p, hsa-miR-146a-5p, hsa-miR-155-5p, hsa-miR-222-3p, and hsa-miR-223-3p. Five of those miRNAs (hsa-miR-126-3p, hsa-miR-142-3p, hsa-miR-146a-5p, hsa-miR-155-5p, and hsa-miR-222-3p) also had a positive correlation with serum creatinine and therefore a negative correlation with eGFR.ConclusionFive miRNAs were significantly upregulated in the plasma of patients with hyperuricemia and gout (and those during a gout attack) compared to normouricemic controls. We also found a correlation between the plasma levels of several miRNA and plasma levels of MCP-1, CRP, serum creatinine, and eGFR.
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Project description:BackgroundCurrently, it is not possible to predict whether patients with hyperuricemia (HUA) will develop gout and how this progression may be affected by urate-lowering treatment (ULT). Our study aimed to evaluate differences in plasma lipidome between patients with asymptomatic HUA detected ≤ 40 years (HUA ≤ 40) and > 40 years, gout patients with disease onset ≤ 40 years (Gout ≤ 40) and > 40 years, and normouricemic healthy controls (HC).MethodsPlasma samples were collected from 94 asymptomatic HUA (77% HUA ≤ 40) subjects, 196 gout patients (59% Gout ≤ 40), and 53 HC. A comprehensive targeted lipidomic analysis was performed to semi-quantify 608 lipids in plasma. Univariate and multivariate statistics and advanced visualizations were applied.ResultsBoth HUA and gout patients showed alterations in lipid profiles with the most significant upregulation of phosphatidylethanolamines and downregulation of lysophosphatidylcholine plasmalogens/plasmanyls. More profound changes were observed in HUA ≤ 40 and Gout ≤ 40 without ULT. Multivariate statistics differentiated HUA ≤ 40 and Gout ≤ 40 groups from HC with an overall accuracy of > 95%.ConclusionAlterations in the lipidome of HUA and Gout patients show a significant impact on lipid metabolism. The most significant glycerophospholipid dysregulation was found in HUA ≤ 40 and Gout ≤ 40 patients, together with a correction of this imbalance with ULT.
| S-EPMC10693150 | biostudies-literature
Project description:Hyperuricemia and gout are complex diseases mediated by genetic, epigenetic, and environmental exposure interactions. The incidence and medical burden of gout, an inflammatory arthritis caused by hyperuricemia, increase every year, significantly increasing the disease burden. Genetic factors play an essential role in the development of hyperuricemia and gout. Currently, the search on disease-associated genetic variants through large-scale genome-wide scans has primarily improved our understanding of this disease. However, most genome-wide association studies (GWASs) still focus on the basic level, whereas the biological mechanisms underlying the association between genetic variants and the disease are still far from well understood. Therefore, we summarized the latest hyperuricemia- and gout-associated genetic loci identified in the Global Biobank Meta-analysis Initiative (GBMI) and elucidated the comprehensive potential molecular mechanisms underlying the effects of these gene variants in hyperuricemia and gout based on genetic perspectives, in terms of mechanisms affecting uric acid excretion and reabsorption, lipid metabolism, glucose metabolism, and nod-like receptor pyrin domain 3 (NLRP3) inflammasome and inflammatory pathways. Finally, we summarized the potential effect of genetic variants on disease prognosis and drug efficacy. In conclusion, we expect that this summary will increase our understanding of the pathogenesis of hyperuricemia and gout, provide a theoretical basis for the innovative development of new clinical treatment options, and enhance the capabilities of precision medicine for hyperuricemia and gout treatment.
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Project description:The goal of this study was to investigate the frequency of gout-specific ultrasonography findings in a cohort of hyperuricemic patients with various musculo-skeletal complaints. A blinded examiner regarding the patients' clinical and laboratory assessment performed standardized ultrasound examinations of 12 joints in 74 individuals with diverse musculo-skeletal complaints. Gout-specific changes were assessed and combined with the patients' medical history (diagnosis gout vs. non-gout) and laboratory values of hyperuricemia. Of 74 patients, 58 (mean age 55 yrs) had hyperuricemia (serum uric acid levels?>?7 mg/dl/420 ?mol/L). Of those, 27 (47%) had a history of gout attacks. In total, 888 joints were examined by ultrasound. With 44/324 joints (14%) the pathological finding most often found in joints of gout patients was the double contour sign compared to 29/372 joints (8%) in patients with asymptomatic hyperuricemia and 2/192 joints (1%) in normouricemic controls. In patients with gout, the ultrasound showed pathological findings in 67/324 joints (21%). In 26/39 (67%) previously affected joints, gout-specific sonographic indications were found. With regard to the first metatarsophalangeal joint, sonographic pathologies were detectable in 16/22 (73%) so far asymptomatic joints on the contralateral. Ultrasonographic gout-specific signs are not only found in joints affected by gout attacks, but often also in the corresponding contralateral, asymptomatic joint. Patients with asymptomatic hyperuricemia already showed sonographic features implicating an as yet "silent" precipitation of urate crystals. As the examined cohort represents patients at high risk, further research for gout-specific findings is indicated, especially for hyperuricemic patients.
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Project description:Genome-wide association studies that scan the genome for common genetic variants associated with phenotype have greatly advanced medical knowledge. Hyperuricemia is no exception, with 28 loci identified. However, genetic control of pathways determining gout in the presence of hyperuricemia is still poorly understood. Two important pathways determining hyperuricemia have been confirmed (renal and gut excretion of uric acid with glycolysis now firmly implicated). Major urate loci are SLC2A9 and ABCG2. Recent studies show that SLC2A9 is involved in renal and gut excretion of uric acid and is implicated in antioxidant defense. Although etiological variants at SLC2A9 are yet to be identified, it is clear that considerable genetic complexity exists at the SLC2A9 locus, with multiple statistically independent genetic variants and local epistatic interactions. The positions of implicated genetic variants within or near chromatin regions involved in transcriptional control suggest that this mechanism (rather than structural changes in SLC2A9) is important in regulating the activity of SLC2A9. ABCG2 is involved primarily in extra-renal uric acid under-excretion with the etiological variant influencing expression. At the other 26 loci, probable causal genes can be identified at three (PDZK1, SLC22A11, and INHBB) with strong candidates at a further 10 loci. Confirmation of the causal gene will require a combination of re-sequencing, trans-ancestral mapping, and correlation of genetic association data with expression data. As expected, the urate loci associate with gout, although inconsistent effect sizes for gout require investigation. Finally, there has been no genome-wide association study using clinically ascertained cases to investigate the causes of gout in the presence of hyperuricemia. In such a study, use of asymptomatic hyperurcemic controls would be expected to increase the ability to detect genetic associations with gout.
| S-EPMC4392805 | biostudies-literature
Project description:BackgroundEpidemiological evidence of the associations between metal exposure and gout-related outcomes (including serum uric acid [SUA], hyperuricemia and gout) is scarce. The aim of the study is to investigate the associations of metal exposure with SUA, hyperuricemia and gout in general adults.MethodsIn this study, the exposure to five blood metals (mercury, manganese, lead, cadmium and selenium) of general adults was analyzed based on the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018 (n = 14,871). Linear, logistic and weighted quantile sum (WQS) regression models were applied to examine the associations of blood metals with gout-related outcomes. Possible dose-response relationships were analyzed through restricted cubic spline regression.ResultsCompared with the lowest quartile of blood metals, mercury (quartile 2 and 4), lead (quartile 2, 3, and 4) and selenium (quartile 2 and 4) were found to be positively correlated with SUA and hyperuricemia. Higher levels of mercury and lead were associated with gout, but only those in the fourth quartile had statistical significance (OR [95%CI]: 1.39 [1.10-1.75] and 1.905 [1.41-2.57]) respectively). The WQS index of the blood metals was independently correlated with SUA (β [95%CI]: 0.17 [0.13-0.20]), hyperuricemia (OR [95%CI]: 1.29 [1.16-1.42]) and gout (OR [95%CI]: 1.35 [1.15-1.58]). Among them, lead was the most heavily weighted component (weight = 0.589 for SUA, 0.482 for hyperuricemia, and 0.527 for gout). In addition, restricted cubic spline regression models showed a linear association of lead with the prevalence of hyperuricemia and gout.ConclusionOur results suggested that blood metal mixtures were positively associated with gout-related outcomes, with the greatest effect coming from lead.
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