Hypouricemia and Mortality Risk in the US General Population

Identification of hub genes and transcription factors in patients with primary gout complicated with atherosclerosis

Evidence shows that primary gout is prone to develop to atherosclerosis, but the mechanism of its occurrence is still not fully clarified. The aim of this study was to explore the molecular mechanism of the occurrence of this complication in gout. The gene expression profiles of primary gout and atherosclerosis were downloaded from the gene expression omnibus database. Overlapping differentially expressed genes (DEGs) between gout and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analyses. Hub genes were identified using protein-protein interaction networks. The immune infiltrations of 28 types of immune cells in gout and control samples from GSE160170 were evaluated by the ssGSEA method. Transcription factors (TFs) were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. A total of 168 overlapping DEGs were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in chemokine signaling pathway, regulation of actin cytoskeleton, and TNF signaling pathway. CytoScape demonstrated 11 hub genes and two gene cluster modules. The immune infiltration analysis showed that the expression of DEGs in gout was significantly upregulated in activated CD4 T cells, gamma delta T cells, T follicular helper cell, CD56dim natural killer cells, and eosinophil. TRRUST predicted one TF, RUNX family transcription factor 1. Our study explored the pathogenesis of gout with atherosclerosis and discovered the immune infiltration of gout. These results may guide future experimental research and clinical transformation.

Renal hypouricemia complicated with kidney stone: a case report

Renal hypouricemia (RHUC) is a rare autosomal recessive disorder characterized by impaired renal tubular uric acid reabsorption and abnormally high uric acid clearance, which may be manifested by reduced serum uric acid (SUA) levels and elevated fractional excretion of uric acid (FE-UA >10%). Most RHUC patients are often asymptomatic or have accidentally decreased SUA levels during health examinations, while others develop kidney stones and exercise-induced acute kidney injury (EIAKI). We now report a case of RHUC complicated with an asymptomatic kidney stone, and we identified a heterozygous mutation of c.269G > A (p.R90H) and a novel heterozygous mutation of c.674C > G (p.T225R) in the SLC22A12 gene in the patient through whole exon gene detection (NGS method). This case offers valuable insights into the mechanisms, clinical management, and prognosis of RHUC and its associated complications.

Hypouricemia as a novel predictor of mortality in anti-MDA5 positive dermatomyositis patients with ILD: A retrospective cohort study

OBJECTIVE

Anti-melanoma differentiation-associated gene 5 antibody positive dermatomyositis (MDA5+ DM) is a unique subtype of idiopathic inflammatory myopathy (IIM) that is associated with rapidly progressive interstitial lung disease (RPILD) and high mortality. This retrospective study aimed to identify predictors of mortality and discover novel easily detectable indicators.

METHODS

We retrospectively reviewed 183 MDA5+ DM-ILD patients who were from West China Hospital of Sichuan University myositis cohort, the largest single-center cohort of southwest China, from January 2016 to October 2021. Clinical characteristics were reviewed, and risk factors for mortality were determined by univariate and multivariable Cox regression analyses.

RESULTS

Of the 183 MDA5+ DM-ILD patients, 59 were presented with RP-ILD, and 53 died during the follow-up period. Compared with the survived patients, deceased patients had higher rates of dyspnea, higher concentrations of CRP, and LDH, but lower rates of heliotrope sign, lower quantity of lymphocyte and lower levels of serum uric acid (SUA). Notably, patients with hypouricemia (SUA <154 μmol/L) had higher concentrations of CRP and LDH, higher neutrophil counts, lower lymphocyte counts and higher mortality rate when compared with the non-hypouricemia group. Multivariate Cox regression analyses confirmed that hypouricemia, smoking, RPILD, high HRCT score, elevated LDH, and lymphopenia were independent risk factors for mortality in MDA5+ DM-ILD patients. Moreover, patients with hypouricemia had significantly lower survival rates than non-hypouricemia patients.

CONCLUSION

Our study identified hypouricemia as a non-redundant promising prognostic factor for the mortality of MDA5+ DM-ILD patients, which may hopefully provide insight into the prevention and pathogenesis study.

Uric acid levels and risk of cognitive impairment: Dose-response meta-analysis of prospective cohort studies

PURPOSE

Studying the effects of uric acid levels on cognitive function and quantifying the dose-response relationship.

METHODS

Based on PubMed and Embase search terms, we identified prospective cohort studies that included blood uric acid as a risk factor and cognitive impairment as a result up to September 2022. We extracted pooled relative risks (RRs) and corresponding 95% confidence intervals (CIs).

RESULTS

Nine reports (including 488,915 participants and 5516 cognitive impairment cases) with median follow-up of 8.8-22 years were eligible for analyses. Compared with lowest category of blood uric acid concentration, the combined RR of cognitive impairment events in the highest classification was 0.81 (95% CI: 0.70-0.92, P < 0.001). Dose-response analysis of eight reports (including 484,297 participants and 5059 cognitive impairment cases) showed that there was no evidence of a curvilinear relationship between blood uric acid levels and cognitive impairment (P = 0.51 for nonlinear relationship). The summary RR of cognitive impairment for an increase of 1 mg/dL blood uric acid level was 0.98 (95% CI: 0.95-1.00; linear trend P = 0.07, I2 = 67.1%, heterogeneity P < 0.05). There was also a linear negative association between blood uric acid levels and cognitive impairment risk in the male subgroup analysis (RR = 0.97, 95% CI: 0.95-0.99, P < 0.05).

CONCLUSION

Levels of blood uric acid are not related to risk of cognitive impairment. A subgroup analysis shows that the rise in blood uric acid levels in the male population is related to a decreased risk of cognitive impairment. These results need to be confirmed by further studies.

U-shaped association of serum uric acid with all-cause mortality in patients with hyperlipidemia in the United States: a cohort study

Background

Serum uric acid (SUA) interferes with lipid metabolism and is considered an independent risk factor for atherosclerosis, a major complication in patients with hyperlipidemia. However, the effects of uric acid levels on mortality in hyperlipidemic patients has yet to be sufficiently determined. In this study, we aimed to assess the association between all-cause mortality and SUA in a hyperlipidemic population.

Methods

To determine mortality rates, we obtained data for 20,038 hyperlipidemia patients from the U.S. National Health and Nutrition Examination Surveys (NHANES) 2001-2018 and National Death Index. To examine the all-cause mortality effect of SUA, multivariable Cox regression models, restricted cubic spline models, and two pairwise Cox regression models were used.

Results

Over a median follow-up of 9.4 years, a total of 2079 deaths occurred. Mortality was examined according to SUA level quintiles: <4.2, 4.3-4.9, 5.0-5.7, 5.8-6.5, and >6.6 mg/dl. In multivariable analysis using 5.8-6.5 mg/dl SUA as a reference, the hazard ratios (95% confidence interval) of all-cause mortality across the five groups were 1.24 (1.06-1.45), 1.19 (1.03-1.38), 1.07 (0.94-1.23), 1.00 (reference), and 1.29 (1.13-1.48), respectively. According to a restricted cubic spline, we noted a U-shaped relationship between SUA and all-cause mortality. The inflection point was approximately 6.30 mg/dl, with hazard ratios of 0.91 (0.85-0.97) and 1.22 (1.10-1.35) to the left and right of the inflection point, respectively. In both sexes, SUA was characterized by a U-shaped association, with inflection points at 6.5 and 6.0 mg/dl for males and females, respectively.

Conclusion

Using nationally representative NHANES data, we identified a U-shaped association between SUA and all-cause mortality in participants with hyperlipidemia.

Researchers in rheumatology should avoid categorization of continuous predictor variables

BACKGROUND

Rheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology.

METHODS

We conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes.

RESULTS

For eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association).

CONCLUSIONS

Categorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.

The Association Between Hypouricemia and Cardiometabolic Diseases: Analyzing Nationwide Data From Medical Checkup and Health Insurance Records

OBJECTIVES

The aims of this study were to evaluate the association between hypouricemia and cardiometabolic diseases, such as hypertension, dyslipidemia, and reduced kidney function, and to explore the sex-specific optimal range for serum uric acid (sUA) associated with the lowest risk for these diseases.

METHODS

In this cross-sectional study, we identified individuals with sUA data between April 2018 and March 2019 and recorded the frequency of cardiometabolic comorbidities according to sUA. Univariable and multivariable logistic regression analyses were performed for the overall population and after classifying by sex to assess the association between sUA and cardiometabolic comorbidities.

RESULTS

Among 796,508 individuals, a J-shaped association was observed between the sUA level and cardiometabolic diseases in the overall population. The adjusted odds ratios (95% confidence interval) for hypertension, dyslipidemia, and reduced renal function in individuals with sUA ≤1.0 mg/dL compared with those with sUA ranging between 2.1 and 3.0 mg/dL were 1.38 (1.13-1.69), 1.52 (1.30-1.78), and 2.17 (1.47-3.20), respectively. A J-shaped association between sUA and hypertension was observed only in women. The optimal range of sUA associated with the lowest risk for hypertension was assumed to be <6 mg/dL in men and 1-4 mg/dL in women. A J-shaped association between the sUA and dyslipidemia and reduced renal function was observed in both men and women. The optimal range of sUA for dyslipidemia and reduced renal function was approximately 2-5 mg/dL in men and 1-4 mg/dL in women.

CONCLUSIONS

Excess and extremely low uric acid levels may be related to an increased cardiometabolic risk.

Associations Between Low Serum Urate, Body Composition, and Mortality

OBJECTIVE

Controversy remains as to whether low serum urate or uric acid (UA) levels contribute to adverse outcomes. We evaluated the relation between low serum UA levels and sarcopenia and assessed whether sarcopenia confounds associations between these low levels and mortality.

METHODS

We utilized data from the National Health and Nutrition Examination Survey (1999-2006). Participants with available whole-body dual x-ray absorptiometry body composition measurements and serum UA concentrations were included. Body composition assessments included body mass index (BMI), waist circumference, maximum lifetime BMI, and age-, sex-, and race-specific appendicular lean mass index (ALMI) and fat mass index (FMI) Z scores. We also calculated Z scores for ALMI relative to FMI (ALMIFMI ). We evaluated associations between serum UA levels and body composition using logistic regression and assessed associations between serum UA levels and mortality before and after adjusting for differences in body composition using Cox proportional hazards regression.

RESULTS

Among the 13,979 participants, low serum UA concentrations (<2.5 mg/dl in women, <3.5 mg/dl in men) were associated with low lean mass (ALMI and ALMIFMI Z scores), underweight BMI (<18.5 kg/m2 ), and higher rates of weight loss. The proportion of patients with low ALMI Z scores was 29% in the low serum UA group and 16% in the normal serum UA group (P = 0.001). Low serum UA levels were associated with increased mortality before we adjusted for body composition (hazard ratio 1.61 [95% confidence interval 1.14-2.28]; P = 0.008) but was attenuated and not significant after adjustment for body composition and weight loss (hazard ratio 1.30 [95% confidence interval 0.92-1.85], P = 0.13).

CONCLUSION

Sarcopenia and weight loss are more common among patients with low serum UA concentrations. Differences in body composition may help to explain associations between low levels of serum UA and higher mortality.

Hypouricemia and Urate Transporters

Hypouricemia is recognized as a rare disorder, defined as a serum uric acid level of 2.0 mg/dL or less. Hypouricemia is divided into an overexcretion type and an underproduction type. The former typical disease is xanthinuria, and the latter is renal hypouricemia (RHUC). The frequency of nephrogenic hypouricemia due to a deficiency of URAT1 is high in Japan, accounting for most asymptomatic and persistent cases of hypouricemia. RHUC results in a high risk of exercise-induced acute kidney injury and urolithiasis. It is vital to promote research on RHUC, as this will lead not only to the elucidation of its pathophysiology but also to the development of new treatments for gout and hyperuricemia.

Diagnostic model for predicting hyperuricemia based on alterations of the gut microbiome in individuals with different serum uric acid levels

BACKGROUND

We aimed to assess the differences in the gut microbiome among participants with different uric acid levels (hyperuricemia [HUA] patients, low serum uric acid [LSU] patients, and controls with normal levels) and to develop a model to predict HUA based on microbial biomarkers.

METHODS

We sequenced the V3-V4 variable region of the 16S rDNA gene in 168 fecal samples from HUA patients (n=50), LSU patients (n=61), and controls (n=57). We then analyzed the differences in the gut microbiome between these groups. To identify gut microbial biomarkers, the 107 HUA patients and controls were randomly divided (2:1) into development and validation groups and 10-fold cross-validation of a random forest model was performed. We then established three diagnostic models: a clinical model, microbial biomarker model, and combined model.

RESULTS

The gut microbial α diversity, in terms of the Shannon and Simpson indices, was decreased in LSU and HUA patients compared to controls, but only the decreases in the HUA group were significant (P=0.0029 and P=0.013, respectively). The phylum Proteobacteria (P<0.001) and genus Bacteroides (P=0.02) were significantly increased in HUA patients compared to controls, while the genus Ruminococcaceae_Ruminococcus was decreased (P=0.02). Twelve microbial biomarkers were identified. The area under the curve (AUC) for these biomarkers in the development group was 84.9% (P<0.001). Notably, an AUC of 89.1% (P<0.001) was achieved by combining the microbial biomarkers and clinical factors.

CONCLUSIONS

The combined model is a reliable tool for predicting HUA and could be used to assist in the clinical evaluation of patients and prevention of HUA.