The prevalence of gout in mainland China from 2000 to 2016: a systematic review and meta-analysis

Assessment of electronic health literacy and its association with self-management among gout patients: A cross-sectional study

Objectives

This study aimed to assess electronic health (eHealth) literacy and self-management ability among gout patients in China and analyze their correlation.

Patients and methods

A cross-sectional study was conducted on 168 male gout patients (mean age: 44.5±13.8 years, range, 22 to 76 years) using a gout patient self-management assessment scale and the Chinese version of eHealth Literacy Scale between August 2020 and February 2021. The correlation between eHealth literacy and gout self-management was examined. Multivariate regression analysis was conducted to identify the predictors of gout patients' self-management ability.

Results

The scores of eHealth literacy and self-management were 28.56±1.72 and 3.59±0.78, respectively, which were both in the medium level, with the lowest score in the lifestyle management dimension. Pearson's correlation analysis showed that eHealth literacy was significantly and positively associated with the total score of gout self-management and its four dimensions. Literacy in eHealth (β=0.399, p<0.001, 95% confidence interval [CI]: 0.023-0.069), living with family members (β=0.336, p=0.001, 95% CI: 0.313-1.234), living in an urban area (β=0.312, p=0.005, 95% CI: 0.191- 1.022), and having college or a higher level of education (β=0.268, p=0.016, 95% CI: 0.032-0.302) were the significant predictors of gout patients' self-management ability, explained 30.6% of the total variance.

Conclusion

Literacy in eHealth was the most significant predictor of gout self-management ability. Gout patients had the lowest score in the perceived ability of searching and applying online health-related information, indicating that both the quantity and quality of gout-specific information needs to be enlarged in electronic resources. Healthcare providers could design and implement eHealth literacy interventions to strengthen patients' gout self-management ability.

ML335 inhibits TWIK2 channel-mediated potassium efflux and attenuates mitochondrial damage in MSU crystal-induced inflammation

BACKGROUND

Activation of the NLRP3 inflammasome is critical in the inflammatory response to gout. Potassium ion (K+) efflux mediated by the TWIK2 channel is an important upstream mechanism for NLRP3 inflammasome activation. Therefore, the TWIK2 channel may be a promising therapeutic target for MSU crystal-induced inflammation. In the present study, we investigated the effect of ML335, a known K2P channel modulator, on MSU crystal-induced inflammatory responses and its underlying molecular mechanisms.

METHODS

By molecular docking, we calculated the binding energies and inhibition constants of five K2P channel modulators (Hydroxychloroquine, Fluoxetine, DCPIB, ML365 and ML335) with TWIK2. Intracellular potassium ion concentration and mitochondrial function were assessed by flow cytometry. The interaction between MARCH5 and SIRT3 was demonstrated by immunoprecipitation and Western blotting assay. MSU suspensions were injected into mouse paw and peritoneal cavity to induce acute gout model.

RESULTS

ML335 has the highest binding energy and the lowest inhibition constant with TWIK2 in the five calculated K2P channel modulators. In comparison, among these five compounds, ML335 efficiently inhibited the release of IL-1β from MSU crystal-treated BMDMs. ML335 decreased MSU crystal-induced K+ efflux mainly dependent on TWIK2 channel. More importantly, ML335 can effectively inhibit the expression of the mitochondrial E3 ubiquitin ligase MARCH5 induced by MSU crystals, and MARCH5 can interact with the SIRT3 protein. ML335 blocked MSU crystal-induced ubiquitination of SIRT3 protein by MARCH5. In addition, ML335 improved mitochondrial dynamics homeostasis and mitochondrial function by inhibiting MARCH5 protein expression. ML335 attenuated the inflammatory response induced by MSU crystals in vivo and in vitro.

CONCLUSION

Inhibition of TWIK2-mediated K+ efflux by ML335 alleviated mitochondrial injury via suppressing March5 expression, suggesting that ML335 may be an effective candidate for the future treatment of gout.

The association between Helicobacter pylori infection and the risk for gout in hyperuricemia patients in China - A cross-sectional study

PURPOSE

Helicobacter pylori (H. pylori) infection has been reported to be associated with multiple metabolic diseases. However, the connection between H. pylori infection and gout has not been explored previously. Our study aimed to investigate the association of gout and H. pylori infection in hyperuricemia population in China.

PATIENTS AND METHODS

This cross-sectional study was performed among the subjects who underwent health checkup in our health promotion center from January 1, 2020 to December 31, 2021. A total of 53,629 subjects with a mean age of 44.2 years were included in this study. H. pylori infection was defined as a positive [13]C-urea breath test. The effect of H. pylori infection on gout was assessed by multiple logistic regression analysis.

RESULTS

720 subjects with gout and 15,077 subjects with asymptomatic hyperuricemia (> 420 µmol/L in male and > 360 µmol/L in female) were enrolled. The prevalence rates of H. pylori infection, hyperuricemia and gout were 26.3%, 29.5%, 1.3%, respectively. The prevalence rate of H. pylori infection was significantly higher in subjects with gout than in those with asymptomatic hyperuricemia (35.0% vs. 27.2%; P<0.001). Multiple logistic regression analysis showed that H. pylori infection was associated with an increased risk of gout independent of serum uric acid level in hyperuricemia population (odds ratio [OR]: 1.320, 95% confidence interval [CI]: 1.124-1.550, P = 0.001).

CONCLUSION

H. pylori infection is positively associated with higher risk of gout in hyperuricemia population. The causal relationship and potential mechanism between H. pylori infection and gout warrants further investigation.

Identification of potential biomarkers of gout through weighted gene correlation network analysis

Background

Although hyperuricemia is not always associated with acute gouty arthritis, uric acid is a significant risk factor for gout. Therefore, we investigated the specific mechanism of uric acid activity.

Methods

Using the gout-associated transcriptome dataset GSE160170, we conducted differential expression analysis to identify differentially expressed genes (DEGs). Moreover, we discovered highly linked gene modules using weighted gene coexpression network analysis (WGCNA) and evaluated their intersection. Subsequently, we screened for relevant biomarkers using the cytoHubba and Mcode algorithms in the STRING database, investigated their connection to immune cells and constructed a competitive endogenous RNA (ceRNA) network to identify upstream miRNAs and lncRNAs. We also collected PBMCs from acute gouty arthritis patients and healthy individuals and constructed a THP-1 cell gout inflammatory model, RT-qPCR and western blotting (WB) were used to detect the expression of C-X-C motif ligand 8 (CXCL8), C-X-C motif ligand 2 (CXCL2), and C-X-C motif ligand 1 (CXCL1). Finally, we predicted relevant drug targets through hub genes, hoping to find better treatments.

Results

According to differential expression analysis, there were 76 upregulated and 28 downregulated mRNAs in GSE160170. Additionally, WGCNA showed that the turquoise module was most strongly correlated with primary gout; 86 hub genes were eventually obtained upon intersection. IL1β, IL6, CXCL8, CXCL1, and CXCL2 are the principal hub genes of the protein-protein interaction (PPI) network. Using RT-qPCR and WB, we found that there were significant differences in the expression levels of CXCL8, CXCL1, and CXCL2 between the gouty group and the healthy group, and we also predicted 10 chemicals related to these proteins.

Conclusion

In this study, we screened and validated essential genes using a variety of bioinformatics tools to generate novel ideas for the diagnosis and treatment of gout.

Metabolomics and Machine Learning Identify Metabolic Differences and Potential Biomarkers for Frequent Versus Infrequent Gout Flares

OBJECTIVE

The objective of this study was to discover differential metabolites and pathways underlying infrequent gout flares (InGF) and frequent gout flares (FrGF) using metabolomics and to establish a predictive model by machine learning (ML) algorithms.

METHODS

Serum samples from a discovery cohort of 163 patients with InGF and 239 patients with FrGF were analyzed by mass spectrometry-based untargeted metabolomics to profile differential metabolites and explore dysregulated metabolic pathways using pathway enrichment analysis and network propagation-based algorithms. ML algorithms were performed to establish a predictive model based on selected metabolites, which was further optimized by a quantitative targeted metabolomics method and validated in an independent validation cohort with 97 participants with InGF and 139 participants with FrGF.

RESULTS

A total of 439 differential metabolites between InGF and FrGF groups were identified. Top dysregulated pathways included carbohydrates, amino acids, bile acids, and nucleotide metabolism. Subnetworks with maximum disturbances in the global metabolic networks featured cross-talk between purine metabolism and caffeine metabolism, as well as interactions among pathways involving primary bile acid biosynthesis, taurine and hypotaurine metabolism, alanine, aspartate, and glutamate metabolism, suggesting epigenetic modifications and gut microbiome in metabolic alterations underlying InGF and FrGF. Potential metabolite biomarkers were identified using ML-based multivariable selection and further validated by targeted metabolomics. Area under receiver operating characteristics curve for differentiating InGF and FrGF achieved 0.88 and 0.67 for the discovery and validation cohorts, respectively.

CONCLUSION

Systematic metabolic alterations underlie InGF and FrGF, and distinct profiles are associated with differences in gout flare frequencies. Predictive modeling based on selected metabolites from metabolomics can differentiate InGF and FrGF.

Assessment of the temporal trend and daily profiles of the dietary purine intake among Chinese residents during 2014 to 2021

The incidence of hyperuricemia is on the rise in China, primarily due to dietary habits. However, limited data exists regarding dietary purine intake in the country. This study aimed to estimate the daily dietary purine intake among Chinese residents from 2014 to 2021 and evaluate the temporal trend using joinpoint regression analysis. The analysis revealed an annual percentage change (APC) of 0.8% (95% CI: 0.1-1.5%) in dietary purine intake prior to the joinpoint (2014-2019). Following the joinpoint (2019-2021), the APC significantly increased to 6.5% (95% CI: 3.3-9.8%), indicating a noteworthy upward trend (p = 0.045). Furthermore, the average daily purine intake varied significantly among different regions of China, with the southern region showing the highest dietary intake of purines. Considering the diverse contributions of various food sources to dietary purine intake, it was observed that meat consumption had the greatest impact, accounting for 36.2% of purine intake, followed by cereals consumption (25.3%) and vegetables and edible fungi (24.2%). These findings hold significance for dietary intervention and management strategies aimed at reducing purine intake among the population.

Trends in Prevalence of Gout Among US Asian Adults, 2011-2018

Importance

Gout disparities among Black individuals in the US have recently been explained by socioclinical factors; however, no information is available among Asian individuals living in Western countries, despite their disproportionately worsening metabolic health.

Objective

To determine the prevalence of gout and serum urate concentrations according to race and ethnicity and to explore the association of social determinants of health and clinical factors.

Design, Setting, and Participants

This is a population-based, cross-sectional analysis. Data from a nationally representative sample of US adults were obtained from the National Health and Nutrition Examination Survey (NHANES) (2011-2018) in which Asian race data were collected (primary). Data from the UK Biobank (2006-2021) were used for replication of the Asian vs White differences. Data analysis was performed from December 2021 to September 2022.

Main Outcomes and Measures

Race-specific gout prevalence and serum urate levels.

Results

A total of 22 621 participants from NHANES (2011-2018) were included in the analysis (mean [SD] age, 49.8 [17.8] years; 10 948 male participants [48.4%]). In 2017 to 2018, gout affected 12.1 million US individuals, with its crude prevalence increasing from 3.6% (95% CI, 2.8%-4.5%) in 2011 to 2012 to 5.1% (95% CI, 4.2%-5.9%) in 2017 to 2018 (P for trend = .03); this trend was no longer significant after age adjustment (P for trend = .06) or excluding Asian individuals (P for trend = .11). During the same period, age- and sex-adjusted prevalence among Asian Americans doubled from 3.3% (95% CI, 2.1%-4.5%) to 6.6% (95% CI, 4.4%-8.8%) (P for trend = .007) to numerically exceed all other racial and ethnic groups in 2017 to 2018, with age- and sex-adjusted odds ratio (ORs) of 1.61 (95% CI, 1.03-2.51) and a socioclinical factor-adjusted multivariable OR of 2.62 (95% CI, 1.59-4.33) for Asian vs White individuals. The latest age- and sex-adjusted gout prevalence among US individuals aged 65 years and older was 10.0% among White individuals and 14.8% among Asian individuals (including 23.6% of Asian men). Serum urate concentrations also increased between 2011 and 2018 among US Asian individuals (P for trend = .009). The Asian vs White disparity was also present in the UK Biobank.

Conclusions and Relevance

The findings of this study suggest that the prevalence of gout among Asian individuals numerically surpassed that for all other racial and ethnic groups in 2017 to 2018. This Asian vs White disparity did not appear to be associated with socioclinical factors.

Mechanism of anti-hyperuricemia of isobavachin based on network pharmacology and molecular docking

BACKGROUND

Hyperuricemia is a more popular metabolic disease caused by a disorder of purine metabolism. Our previous study firstly screened out a natural product Isobavachin as anti-hyperuricemia targeted hURAT1 from a Chinese medicine Haitongpi (Cortex Erythrinae). In view of Isobavachin's diverse pharmacological activities, similar to the Tranilast (as another hURAT1 inhibitor), our study focused on its potential targets and molecular mechanisms of Isobavachin anti-hyperuricemia based on network pharmacology and molecular docking.

METHODS

First of all, the putative target genes of compounds were screen out based on the public databases with different methods, such as SwissTargetPerdiction, PharmMapper and TargetNet,etc. Then the compound-pathways were obtained by the compounds' targets gene from David database for Gene Ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis. The cross pathways of compound-pathways and the diseases pathways of hyperuricemia from Comparative Toxicogenomics Database were be considered as the compound-disease pathways. Next, based on the compound-disease pathways and the PPI network, the core targets were identified based on the retrieved disease-genes. Finally, the compound-target-pathway-disease network was constructed by Cytoscape and the mechanism of isobavachin anti-hyperuricemia was discussed based on the network analysis.

RESULTS

Our study demonstrated that there were five pathways involved in Isobavachin against hyperuricemia, including Drug metabolism-other enzymes, Metabolic pathways, Bile secretion, Renin-angiotensin system and Renin secretion. Among the proteins involved in these pathways, HPRT1, REN and ABCG2 were identified as the core targets associated with hyperuricemia, which regulated the five pathways mentioned above. It is quite different from that of Tranilast, which involved in the same pathways except Bile secretion instead of purine metabolism.

CONCLUSION

This study revealed Isobavachin could regulate the pathways including Drug metabolism-other enzymes, Metabolic pathways, Bile secretion, Renin-angiotensin system, Renin secretion by core targets HPRT1, REN and ABCG2, in the treatment of hyperuricemia effect. Among them, the Bile secretion regulated by ABCG2 probably would be a novel pathway. Our work provided a theoretical basis for the pharmacological study of Isobavachin in lowering uric acid and further basic research.

The interplay between herbal medicines and gut microbiota in metabolic diseases

Globally, metabolic diseases are becoming a major public health problem. Herbal medicines are medicinal materials or preparations derived from plants and are widely used in the treatment of metabolic diseases due to their good curative effects and minimal side effects. Recent studies have shown that gut microbiota plays an important role in the herbal treatment of metabolic diseases. However, the mechanisms involved are still not fully understood. This review provides a timely and comprehensive summary of the interactions between herbal medicines and gut microbiota in metabolic diseases. Mechanisms by which herbal medicines treat metabolic diseases include their effects on the gut microbial composition, the intestinal barrier, inflammation, and microbial metabolites (e.g., short-chain fatty acids and bile acids). Herbal medicines can increase the abundance of beneficial bacteria (e.g., Akkermansia and Blautia), reduce the abundance of harmful bacteria (e.g., Escherichia-Shigella), protect the intestinal barrier, and alleviate inflammation. In turn, gut microbes can metabolize herbal compounds and thereby increase their bioavailability and bioactivity, in addition to reducing their toxicity. These findings suggest that the therapeutic effects of herbal medicines on metabolic diseases are closely related to their interactions with the gut microbiota. In addition, some methods, and techniques for studying the bidirectional interaction between herbal medicines and gut microbiota are proposed and discussed. The information presented in this review will help with a better understanding of the therapeutic mechanisms of herbal medicines and the key role of gut microbiota.

Optimization of the extraction process and metabonomics analysis of uric acid-reducing active substances from Gymnadenia R.Br. and its protective effect on hyperuricemia zebrafish

Background

As Gymnadenia R.Br. (Gym) has an obvious uric acid-lowering effect, but its specific bioactive substances and mechanism are still unclear. The key metabolites and pathways used by Gym to reduce uric acid (UA) were identify.

Methods

An optimized extraction process for urate-lowering active substances from Gym was firstly been carried out based on the xanthine oxidase (XOD) inhibition model in vitro; then, the Ultra-high-performance liquid chromatography and Q-Exactive mass spectrometry (UHPLC-QE-MS) based on non-targeted metabolomics analysis of Traditional Chinese Medicine were performed for comparison of Gym with ethanol concentration of 95% (low extraction rate but high XOD inhibition rate) and 75% (high extraction rate but low XOD inhibition rate), respectively; finally, the protective effect of ethanolic extract of Gym on zebrafish with Hyperuricemia (referred to as HUA zebrafish) was explored.

Results

We found that the inhibition rate of Gym extract with 95% ethanol concentration on XOD was 84.02%, and the extraction rate was 4.32%. Interestingly, when the other conditions were the same, the XOD inhibition rate of the Gym extract with 75% ethanol concentration was 76.84%, and the extraction rate was 14.68%. A total of 539 metabolites were identified, among them, 162 different metabolites were screened, of which 123 were up-regulated and 39 were down-regulated. Besides significantly reducing the contents of UA, BUN, CRE, ROS, MDA, and XOD activity in HUA zebrafish by Gym and acutely reduce the activity of SOD.

Conclusion

Along with the flavonoids, polyphenols, alkaloids, terpenoids, and phenylpropanoids, the ethanolic extract of Gym may be related to reduce the UA level of Gym.

Comparison of 3 hyperuricemia mouse models and evaluation of food-derived anti-hyperuricemia compound with spontaneous hyperuricemia mouse model

Hyperuricemia animal models have long been used for evaluating food-derived anti-hyperuricemia compounds. Fructose and potassium oxonate are commonly used for developing hyperuricemia mouse model. Recent research also developed spontaneous hyperuricemia model by uricase knockout (Uox^-/-). In this work, we evaluated 3 kinds of models with the same gene background to illustrate the differences between the treatments. Unlike the uric acid levels in potassium oxonate (224.79 ± 33.62 μmol/L) and Uox^-/- groups (458.39 ± 38.29 μmol/L), fructose treatment did not lead to higher serum uric acid level (174.93 ± 30.46 μmol/L) comparing to the control group (153.53 ± 40.96 μmol/L). However, abnormal glycometabolism only developed in the fructose and the Uox^-/- group. In addition, anemia, inflammasome and severe renal injury occurred in the Uox^-/- group. The Uox^-/- mice were then treated with puerarin and allopurinol, and found that puerarin could reduce serum uric acid and alleviated the serious renal damage associated with high uric acid. Thus, the Uox^-/- mice could be a suitable model for screening and evaluating anti-hyperuricemia compounds.

Mapping Knowledge Structure and Global Research Trends in Gout: A Bibliometric Analysis From 2001 to 2021

Background

The incidence and prevalence of gout have been steadily increasing globally, which has resulted in gout research attracting consistently increased attention. This study aimed to visualize the knowledge structure and research trends in gout research through bibliometrics to help understand the future development of basic and clinical research.

Methods

Articles and reviews on gout from 2001 to 2021 were extracted from the Web of Science Core Collection database. CiteSpace and VOSviewer software were used to visualize the knowledge network of countries, institutions, authors, references, and keywords in this field. SPSS and Microsoft Excel software were used for curve fitting and correlation analysis.

Results

A total of 3,259 articles and reviews were included. The number of publications about gout significantly increased yearly. Publications were mainly concentrated in North America, Europe, Oceania, and East Asia. The USA contributed most with 1,025 publications, followed by China and New Zealand. After adjusting for publications by population size and Gross Domestic Product (GDP), New Zealand ranked in the first place. GDP and international collaboration were significantly correlated with scientific productivity for gout research. University of Auckland and Professor Dalbeth Nicola were the most prolific institutions and influential authors, respectively. Rheumatology was the most productive journal for gout research. Gout research hotspots have shifted over time in the following order: clinical features, pathological mechanisms, complications, gouty arthritis, epidemiology, and dual-energy computed tomography to drug clinical trials, which can be observed from the keyword analysis and co-cited reference cluster analysis.

Conclusions

This study found that research on gout is flourishing. The development and experimentation of drugs for the prevention and treatment of gouty arthritis would be the focus of current research and developmental trends in future research.

Prevalence and Risk Factors for Peripheral Neuropathy in Chinese Patients With Gout

Objective

Peripheral neuropathies (PNs) are a group of disorders that affect the peripheral nervous system. PN in gout has been scarcely described. This study is conducted to determine the prevalence and related risk factors of PN, as assessed by vibration perception threshold (VPT) in patients with gout.

Methods

A total of 442 patients were included in the cross-sectional study. The VPT values were measured by using the Biothesiometer sensory quantitative tester on each patient. The VPT value of either limb higher than 15 V was considered abnormal and is considered to have PN. The univariate and multivariate logistic regression models were used to identify risk factors for PN in patients with gout.

Results

We included 442 patients with gout, 97.5% men, 26.9% tophaceous gout, mean age 45.5 ± 15.2 years, and 7.4 ± 4.6 years of disease duration. The prevalence of PN in patients with gout was 11.1%. Patients in the abnormal VPT group were older, had a longer gout duration, and had significantly higher levels of waist circumference, waist-to-hip ratio, systolic blood pressure (SBP), and erythrocyte sedimentation rate (ESR), as compared to patients in the normal vibration group (P < 0.05). The univariate logistic regression analysis demonstrated that there was a significant association between abnormal VPT and age, duration of gout, SBP, C-reactive protein, ESR, presence of tophi, and estimated glomerular filtration rate (eGFR) in all the subjects (P < 0.05). The multivariate logistic regression analysis indicated that age (odds ratio, 1.094) and presence of tophi (odds ratio, 1.048) were independent risk factors for PN in patients with gout.

Conclusion

The abnormal VPT was significantly correlated with age and presence of tophi in patients with gout and the VPT level may be useful as a screening tool for assessment of PN in gout.

Recombinant Human Proteoglycan 4 Regulates Phagocytic Activation of Monocytes and Reduces IL-1β Secretion by Urate Crystal Stimulated Gout PBMCs

Objectives

To compare phagocytic activities of monocytes in peripheral blood mononuclear cells (PBMCs) from acute gout patients and normal subjects, examine monosodium urate monohydrate (MSU) crystal-induced IL-1β secretion ± recombinant human proteoglycan 4 (rhPRG4) or interleukin-1 receptor antagonist (IL-1RA), and study the anti-inflammatory mechanism of rhPRG4 in MSU stimulated monocytes.

Methods

Acute gout PBMCs were collected from patients in the Emergency Department and normal PBMCs were obtained from a commercial source. Monocytes in PBMCs were identified by flow cytometry. PBMCs were primed with Pam3CSK4 (1μg/mL) for 24h and phagocytic activation of monocytes was determined using fluorescently labeled latex beads. MSU (200μg/mL) stimulated IL-1β secretion was determined by ELISA. Reactive oxygen species (ROS) generation in monocytes was determined fluorometrically. PBMCs were incubated with IL-1RA (250ng/mL) or rhPRG4 (200μg/mL) and bead phagocytosis by monocytes was determined. THP-1 monocytes were treated with MSU crystals ± rhPRG4 and cellular levels of NLRP3 protein, pro-IL-1β, secreted IL-1β, and activities of caspase-1 and protein phosphatase-2A (PP2A) were quantified. The peritoneal influx of inflammatory and anti-inflammatory monocytes and neutrophils in Prg4 deficient mice was studied and the impact of rhPRG4 on immune cell trafficking was assessed.

Results

Enhanced phagocytic activation of gout monocytes under basal conditions (p<0.001) was associated with ROS generation and MSU stimulated IL-1β secretion (p<0.05). rhPRG4 reduced bead phagocytosis by normal and gout monocytes compared to IL-1RA and both treatments were efficacious in reducing IL-1β secretion (p<0.05). rhPRG4 reduced pro-IL-1β content, caspase-1 activity, conversion of pro-IL-1β to mature IL-1β and restored PP2A activity in monocytes (p<0.05). PP2A inhibition reversed rhPRG4’s effects on pro-IL-1β and mature IL-1β in MSU stimulated monocytes. Neutrophils accumulated in peritoneal cavities of Prg4 deficient mice (p<0.01) and rhPRG4 treatment reduced neutrophil accumulation and enhanced anti-inflammatory monocyte influx (p<0.05).

Conclusions

MSU phagocytosis was higher in gout monocytes resulting in higher ROS and IL-1β secretion. rhPRG4 reduced monocyte phagocytic activation to a greater extent than IL-1RA and reduced IL-1β secretion. The anti-inflammatory activity of rhPRG4 in monocytes is partially mediated by PP2A, and in vivo, PRG4 plays a role in regulating the trafficking of immune cells into the site of a gout flare.

Illness perception and treatment experience in patients with gout: a descriptive qualitative study

OBJECTIVE

To explore the illness perception and treatment experience of gout patients in China.

METHODS

A descriptive qualitative approach was used. In-depth semi-structured individual interviews were conducted among 18 adults with gout between August 2020 and December 2020. The Common-Sense Model of Self-Regulation was used as the conceptual framework for developing interview guide and data analysis. Interviews were audio recorded, transcribed, independently coded, and analyzed for themes.

RESULTS

The 18 gout patients aged 23-77 years old, with 16 being male. Four themes were generated to reflect the experience of patients with gout: limited knowledge of gout, various but inadequate sources of gout knowledge, multifaceted influences of gout, and seeking for diversified disease treatment methods.

CONCLUSION

There is a gap between patients' anticipation and practical service that is closely linked with subsequent poor gout management among the participants. The findings indicate a need of strengthening health education about gout by considering building nurse-led support groups and developing mobile health applications, as well as addressing the long-term influence of the Chinese alcoholic drinking culture to promote patients' effective disease management.

KEY POINTS

• This qualitative study fills a knowledge gap on illness perception and treatment experience among Chinese gout patients, exploring how these patients perceived gout and manage gout. • The gout patients in this study reported disparity between personal anticipation and healthcare service that largely contributes to their poor gout management. • The Chinese alcoholic drinking culture embedded in personal, professional, and social activities posed extra difficulties and challenges on modifying lifestyle for gout patients that needs to be addressed for promoting gout management among this group.

Potential Development of a Mobile Application for Gout Self-Management: What Support Do Patients Need?

PURPOSE

With the increasing prevalence and chronic course of gout, the use of mobile health (mHealth) applications (APPs) for gout self-management is attracting considerable research attention as an effective approach to improving health outcomes. However, there is limited knowledge regarding the self-management support that a mHealth APP for gout should provide to patients according to their needs. The aim of this study was to interview patients with gout and identify their needs with respect to gout self-management support.

PATIENTS AND METHODS

We conducted qualitative research using a purposive sampling method from January 2019 to August 2019. Individual face-to-face semi-structured interviews were conducted with patients recruited from West China Hospital in Sichuan, China. The qualitative data were transcribed verbatim and analyzed by thematic analysis.

RESULTS

Ten male patients with gout were included in the final analysis. Instrumental, psychological, and relational support emerged as themes describing the needs of patients for gout self-management support. The instrumental support included health education, hospital registration, setting reminders, and shopping. Psychological support referred to helping patients mitigate various negative emotions. Relational support included interactions with healthcare providers and fellow patients.

CONCLUSION

The present findings indicate that healthcare providers or companies should develop mHealth APPs for gout self-management based on the needs of patients.

Metagenomic analysis revealed the potential role of gut microbiome in gout

Emerging evidence indicates an association between gut microbiome and arthritis diseases including gout. However, how and which gut bacteria affect host urate degradation and inflammation in gout remains unclear. Here we performed a metagenome analysis on 307 fecal samples from 102 gout patients and 86 healthy controls. Gout metagenomes significantly differed from those of healthy controls. The relative abundances of Prevotella, Fusobacterium, and Bacteroides were increased in gout, whereas those of Enterobacteriaceae and butyrate-producing species were decreased. Functionally, gout patients had greater abundances for genes in fructose, mannose metabolism and lipid A biosynthesis, and lower for genes in urate degradation and short chain fatty acid production. A three-pronged association between metagenomic species, functions and clinical parameters revealed that decreased abundances of species in Enterobacteriaceae were associated with reduced amino acid metabolism and environmental sensing, which together contribute to increased serum uric acid and C-reactive protein levels in gout. A random forest classifier based on three gut microbial genes showed high predictivity for gout in both discovery and validation cohorts (0.91 and 0.80 accuracy), with high specificity in the context of other chronic disorders. Longitudinal analysis showed that uric-acid-lowering and anti-inflammatory drugs partially restored gut microbiota after 24-week treatment. Comparative analysis with obesity, type 2 diabetes, ankylosing spondylitis and rheumatoid arthritis indicated that gout metagenomes were more similar to those of autoimmune than metabolic diseases. Our results suggest that gut dysbiosis was associated with dysregulated host urate degradation and systemic inflammation and may be used as non-invasive diagnostic markers for gout.

Establishment of a clinical diagnostic model for gouty arthritis based on the serum biochemical profile: A case-control study

The disease progression of gouty arthritis (GA) is relatively clear, with the 4 stages of hyperuricemia (HUA), acute gouty arthritis (AGA), gouty arthritis during the intermittent period (GIP), and chronic gouty arthritis (CGA). This paper attempts to construct a clinical diagnostic model based on blood routine test data, in order to avoid the need for bursa fluid examination and other tedious steps, and at the same time to predict the development direction of GA.Serum samples from 579 subjects were collected within 3 years in this study and were divided into a training set (n = 379) and validation set (n = 200). After a series of multivariate statistical analyses, the serum biochemical profile was obtained, which could effectively distinguish different stages of GA. A clinical diagnosis model based on the biochemical index of the training set was established to maximize the probability of the stage as a diagnosis, and the serum biochemical data from 200 patients were used for validation.The total area under the curve (AUC) of the clinical diagnostic model was 0.9534, and the AUCs of the 5 models were 0.9814 (Control), 0.9288 (HUA), 0.9752 (AGA), 0.9056 (GIP), and 0.9759 (CGA). The kappa coefficient of the clinical diagnostic model was 0.80.This clinical diagnostic model could be applied clinically and in research to improve the accuracy of the identification of the different stages of GA. Meanwhile, the serum biochemical profile revealed by this study could be used to assist the clinical diagnosis and prediction of GA.

Efficacy and safety of pricking-blood therapy for acute gouty arthritis: A protocol for systematic review and meta-analysis

BACKGROUND

Acute gouty arthritis is a joint inflammatory reaction that affects the daily quality of patients. Previous reviews of pricking-blood therapy for acute gouty arthritis have been growing, but a systematic review is not available. This study aimed to systematically investigate the efficacy and safety of pricking-blood therapy in treating acute gout arthritis.

METHODS

We will search for relevant literature through Chinese and English databases, with the retrieval deadline being December 2020. Databases include PubMed, Embase, Web of Science, the Cochrane Library, China National Knowledge Infrastructure, the Chongqing VIP Chinese Science and Technology Periodical Database, Wanfang Database, and China Biomedical Literature Database. We will also manually search Chinese Acupuncture & Moxibustion, Acupuncture Research, Chinese Clinical Trial Register, and unpublished studies or references. According to the inclusion and exclusion criteria, the literature will be screened, and the data are extracted independently by the 2 researchers. The primary outcomes were the total effective rate and Visual Analogue Scale (VAS) score. RevMan 5.3.5. software will be used for statistical analysis. According to the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE), each evidence of outcome quality will be appraised.

RESULTS

This study will provide a comprehensive review of current evidence for a pricking-blood therapy treatment for acute gouty arthritis.

CONCLUSION

The efficacy and safety of picking-blood therapy in treating acute gout arthritis will be evaluated.

UNIQUE INPLASY NUMBER

INPLASY2020100094.

Global epidemiology of gout: prevalence, incidence, treatment patterns and risk factors

Gout is the most common inflammatory arthritis and occurs when hyperuricaemia, sustained elevation of serum urate levels resulting in supersaturation of body tissues with urate, leads to the formation and deposition of monosodium urate crystals in and around the joints. Recent reports of the prevalence and incidence of gout vary widely according to the population studied and methods employed but range from a prevalence of <1% to 6.8% and an incidence of 0.58-2.89 per 1,000 person-years. Gout is more prevalent in men than in women, with increasing age, and in some ethnic groups. Despite rising prevalence and incidence, suboptimal management of gout continues in many countries. Typically, only a third to half of patients with gout receive urate-lowering therapy, which is a definitive, curative treatment, and fewer than a half of patients adhere to treatment. Many gout risk factors exist, including obesity, dietary factors and comorbid conditions. As well as a firmly established increased risk of cardiovascular disease and chronic kidney disease in those with gout, novel associations of gout with other comorbidities have been reported, including erectile dysfunction, atrial fibrillation, obstructive sleep apnoea, osteoporosis and venous thromboembolism. Discrete patterns of comorbidity clustering in individuals with gout have been described. Increasing prevalence and incidence of obesity and comorbidities are likely to contribute substantially to the rising burden of gout.

Plasma profiling of amino acids distinguishes acute gout from asymptomatic hyperuricemia

Gout and hyperuricemia are highly prevalent metabolic diseases caused by high level of uric acid. Amino acids (AAs) involve in various biochemical processes including the biosynthesis of uric acid. However, the role of AAs in discriminating gout from hyperuricemia remains unknown. Here, we report that the plasma AAs profile can distinguish acute gout (AG) from asymptomatic hyperuricemia (AHU). We established an LC-MS/MS-based method to measure the plasma AAs without derivatization for the AG and AHU patients, and healthy controls. We found that the plasma profiling of AAs separated the AG patients from AHU patients and controls visually in both principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA) models. In addition, L-isoleucine, L-lysine, and L-alanine were suggested as the key mediators to distinguish the AG patients from AHU and control groups based on the S-plot analysis and variable importance in the projection values in the OPLS-DA models, volcano plot, and the receiver operating characteristic curves. In addition, the saturation of monosodium urate in the AA solutions at physiologically mimic status supported the changes in plasma AAs facilitating the precipitation of monosodium urate. This study suggests that L-isoleucine, L-lysine, and L-alanine could be the potential markers to distinguish the AG from AHU when the patients have similar blood levels of uric acid, providing new strategies for the prevention, treatment, and management of acute gout.