Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels

Touch-based uric acid sweat biosensor towards personal health and nutrition

Monitoring uric acid (UA) levels is critical since elevated UA levels are associated with diverse conditions, such as gout, kidney disorders, kidney stones, hypertension, cardiovascular diseases, and metabolic syndrome. Maintaining balanced UA levels demands reliable and regular monitoring. Traditionally, such frequent UA measurements rely on blood-based UA self-testing strips. Developing sensitive and reliable noninvasive sweat-based UA sensors presents challenges, including the low UA sweat concentrations and interpersonal variations. We present here an attractive on-site UA self-testing approach utilizing a touch-enabled fingertip sweat UA electrochemical biosensor based on a uricase-enzyme electrode and sweat wicking hydrogel. This noninvasive method is rapid, simple, convenient, and painless, leveraging the high sweat rate on the fingertip at rest without any sweat stimulation. The touch-based protocol exhibits a wide linear range of UA concentrations from 10 to 1000 μM, covering normal and elevated UA sweat levels with high selectivity, reproducibility (RSD = 4.94%), good storage stability (1 week), and significant tolerance to temperature and humidity variations. The performance of the UA-touch sweat biosensor was evaluated and validated by parallel blood meter measurements by monitoring dynamically-changing sweat UA levels in healthy subjects after consuming purine-rich meals. The distinct sweat UA temporal profiles among individuals highlight the potential of the touch-based UA biosensor for personal health and nutrition. The speed and simplicity of this sweat UA assay thus encourage frequent self-testing and enhance user's compliance towards dietary interventions and lifestyle changes in connection to diverse healthcare and nutrition applications.

Dietary polyunsaturated fatty acid and risk of gout: a cohort study integrating genetic predisposition and metabolomics

OBJECTIVES

Gout is the most common inflammatory arthritis and affects quality of life. Dietary polyunsaturated fatty acids (PUFAs) have protective effects against various diseases, but its role in gout remains uncertain. Our study aims to assess the association between PUFAs intake and gout risk, the role of genetic factors, and the possible impact of metabolites.

METHODS

This study included 198,033 participants who were free of gout at baseline and completed at least one reliable dietary assessment in the UK Biobank. Cox proportional hazard models were used to estimate the associations between PUFAs intake and gout risk, and the modified effects of genetic predisposition. Mediation analysis also explored the mediating role of metabolic signature in associations between specific PUFAs intake and gout.

RESULTS

Over a median follow-up of 9.47 years, 1,708 incident cases of gout were recorded. Gout risk was significantly associated with the second quartile of linoleic acid (LA) (0.86 [0.75, 1.00]) intake and the highest quartiles of alpha-linolenic acid (ALA) (0.72 [0.62, 0.84]), total PUFA (HR: 0.84 [95% CI:0.71, 0.99]), n-6 PUFA (0.84 [0.71, 0.99]), n-3 PUFA (0.83 [0.71, 0.98]), and eicosapentaenoic acid (EPA) (0.79 [0.68, 0.91]), compared to the lowest quartiles. We observed joint effects of PUFAs intake and genetic susceptibility on gout risk. Mediation analysis showed that high-density lipoprotein (HDL) and triglycerides mediated the associations of ALA and LA with gout risk.

CONCLUSION

Our findings suggested the potential benefits of PUFAs in reducing gout risk, particularly vegetable sources, with HDL and triglycerides as key mediators.

Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure

Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study used data of multiple environmental chemical exposures from the 2011-2012 cycle of the National Health and Nutrition Examination Survey (NHANES) to develop an interpretable machine learning model for hyperuricemia risk prediction. The least absolute shrinkage and selection operator (LASSO) regression method was employed to select relevant variables. The dataset was split into training (80 %) and test (20 %) sets and six machine learning models were constructed, including Random Forest (RF), Gaussian Naive Bayes (GNB), Light Gradient Boosting (LGB), Extreme Gradient Boosting (XGB), Adaptive Boosting Classifier (AB), and Support Vector Machine (SVM). Our study identified a hyperuricemia prevalence of 20.58 % in the 2011-2012 NHANES cycle, which was consistent with previous studies. The XGB model exhibited optimal performance, achieving the highest AUC (0.806, 95 % CI: 0.768-0.845), balanced accuracy (0.762; 95 % CI: 0.721-0.802), F1 value (0585; 95 % CI: 0.535-0.635), as well as the lowest Brier score (0.133; 95 % CI:0.122-0.144). Estimated glomerular filtration rate (eGFR), body mass index (BMI), cobalt (Co), mono-(2-ethyl)-hexyl phthalate (MEHP), mono-(3-carboxypropyl) phthalate (MCPP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), 2-hydroxynaphthalene (OHNa2) were identified as the key factors contributing to the predictive model. The results of Shapley additive explanations and partial dependence plots indicated that hyperuricemia was positively associated with MCPP, MEHHP, and OHNa2, while negatively associated with Co and MEHP. This study is the first to predict the risk of hyperuricemia based on multiple environmental chemical exposures using a machine learning model.

Genetically proxied glucokinase activation and risk of diabetic complications: Insights from phenome-wide and multi-omics mendelian randomization

AIMS

This study aims to assess the benefits and adverse effects of long-term glucokinase (GK) activation from a genetic perspective.

METHODS

We identified genetic variants in the GCK gene associated with glycated hemoglobin (HbA1c) levels from a genome-wide association study (GWAS) involving 146,806 individuals, which served as proxies for glucokinase activation. To assess the effects and potential pathways of GK activation on a range of diabetic complications and safety outcomes, we integrated drug-target Mendelian randomization (MR), lipidome-wide and proteome-wide MR, phenome-wide MR, and colocalization analyses.

RESULTS

Genetically proxied GK activation was associated with reduced risks of several predefined diabetic complications, including cardiovascular diseases, stroke and diabetic retinopathy. No kidney-related benefits were observed. Safety analysis revealed a relationship between GK activation and elevated AST levels, while impaired interaction between GK and glucokinase regulatory protein (GKRP) was associated with dyslipidemia, increased liver fat content, AST, systolic blood pressure, and uric acid. Phenome-wide MR suggested that GK activation may have potential benefits for lung function and fluid intelligence score.

CONCLUSIONS

Our genetic evidence supports GK as a promising target for reducing the risk of specific diabetic complications. These findings require further validation through cohort studies and randomized controlled trials in patients with diabetes.

Trajectory of body shape in early and middle life and hyperuricemia: an observational study integrating mendelian randomization analysis

BACKGROUND AND AIM

Although it is recognized that obesity is linked to hyperuricemia, the research on how obesity at different stages of life affects hyperuricemia is still unclear.

METHODS AND RESULTS

Body shape trajectory of over the first 50 years of life in Henan Rural Cohort Study was accessed by using a group-based trajectory modeling approach. Multivariate logistic regression was utilized to estimate odd ratio (OR) for hyperuricemia. Causation was further assessed using mendelian randomization (MR). Five distinct trajectories were identified and a total of 22,655 participants were enrolled for final analysis. Compared to lean-stable participants, medium-moderate increase, heavy-stable, and lean-marked increase showed significantly higher OR and 95 % confidence interval (CI) for hyperuricemia, with 1.27 (1.07, 1.50), 1.81 (1.48, 2.21) and 1.84 (1.51, 2.25) for women, 1.25 (1.01, 1.54), 1.35 (1.02, 1.77) and 1.91 (1.50, 2.43) for men. This positive association was weakened in women with high healthy lifestyle score, but the weakening effect was not significant in men. Genetically predicted birth weight, childhood body mass index (BMI), and adult BMI were significantly associated with serum uric acid (SUA), with regression coefficient (β) and 95 % CI was -0.09 (-0.14, -0.04), 0.10 (0.04, 0.16), 0.20 (0.16, 0.24), respectively.

CONCLUSION

Body shape trajectory is closely associated with hyperuricemia, with MR analysis suggesting potential causal links. lifelong weight management and maintaining healthy lifestyles can reduce the adverse effects of weight gain on hyperuricemia.

Serum uric acid/creatinine ratio and osteoporosis in the elderly: a NHANES study

Background

Osteoporosis (OP) is a metabolic bone disorder that is of significant concern to the elderly. However, few studies have investigated the correlation between the serum uric acid to creatinine ratio (UA/Cr) and OP in elderly individuals. This research seeks to examine the connection between UA/Cr levels and OP in older adults.

Methods

Data on participant information for the study was obtained from four cycles of the NHANES database. Multivariable logistic regression was employed to examine the correlation between UA/Cr and OP, adjusting for potential confounders such as age, gender, and race. The diagnostic efficacy of UA/Cr for OP was evaluated utilizing ROC curves.

Results

Multivariable logistic regression analysis showed that serum UA/Cr levels were significantly lower in individuals with OP than in those without OP. (OR = 0.83 [0.76, 0.91], P < 0.001). Subgroup analyses indicated a stronger association in men (OR = 0.77 [0.64, 0.94], P = 0.009) and women (OR = 0.85 [0.76, 0.95], P < 0.003). Furthermore, multivariable logistic regression analyses by ethnicity revealed that this association was significant solely among Non-Hispanic Whites (OR = 0.78 [0.68, 0.90], P < 0.001). The area under the ROC curve (AUC) for UA/Cr in predicting OP was higher than that for SUA alone, indicating superior predictive value.

Conclusion

A higher UA/Cr level within the normal range is associated with a lower risk of OP, providing insights for its diagnosis and risk assessment.

Allantoin Serves as a Novel Risk Factor for the Progression of MASLD

Uric acid (UA), traditionally recognized as an extracellular antioxidant, exhibits paradoxical associations with metabolic disorders such as metabolic dysfunction-associated steatotic liver disease (MASLD), though its mechanistic contributions remain elusive. Here, we integrate multi-modal evidence to explore the role of UA and its oxidative metabolite, allantoin, in MASLD progression. Analysis of UK Biobank data revealed a strong association between elevated UA levels and increased risks of MASLD and type 2 diabetes (T2D). However, Mendelian randomization analysis of over 2 million samples demonstrated causal effects of urate solely on serum triglycerides and T2D risk. Targeted metabolomics in an elderly Chinese cohort identified allantoin, an oxidative by-product of UA, significantly elevated in individuals with dyslipidemia or T2D, with serum allantoin levels positively correlated with fasting glucose, triglycerides, and cholesterol. Animal studies indicated that allantoin exacerbates hepatic lipid accumulation and glucose intolerance in high-fat diet mice, driven by increased hepatic lipid biogenesis and reduced bile acid production. Notably, further research revealed a strong binding affinity of allantoin for PPARα, leading to the suppression of PPARα activity, which promotes the progression of MASLD. These findings underscore the critical role of allantoin, rather than UA, as a critical driver of MASLD development, offering valuable insights for the prediction and management of hepatic metabolic disorders.

The Estonian Biobank's journey from biobanking to personalized medicine

Large biobanks have set a new standard for research and innovation in human genomics and implementation of personalized medicine. The Estonian Biobank was founded a quarter of a century ago, and its biological specimens, clinical, health, omics, and lifestyle data have been included in over 800 publications to date. What makes the biobank unique internationally is its translational focus, with active efforts to conduct clinical studies based on genetic findings, and to explore the effects of return of results on participants. In this review, we provide an overview of the Estonian Biobank, highlight its strengths for studying the effects of genetic variation and quantitative phenotypes on health-related traits, development of methods and frameworks for bringing genomics into the clinic, and its role as a driving force for implementing personalized medicine on a national level and beyond.

Structural Basis for Inhibition of Urate Reabsorption in URAT1

The urate transporter 1 (URAT1) is the primary urate transporter in the kidney responsible for urate reabsorption and, therefore, is crucial for urate homeostasis. Hyperuricemia causes the common human disease gout and other pathological consequences. Inhibition of urate reabsorption through URAT1 has been shown as a promising strategy in alleviating hyperuricemia, and clinical and preclinical drug candidates targeting URAT1 are emerging. However, how small molecules inhibit URAT1 remains undefined, and the lack of accurate URAT1 complex structures hinders the development of better therapeutics. Here, we present cryoelectron microscopy structures of a humanized rat URAT1 bound with benzbromarone, lingdolinurad, and verinurad, elucidating the structural basis for drug recognition and inhibition. The three small molecules reside in the URAT1 central cavity with different binding modes, locking URAT1 in an inward-facing conformation. This study provides mechanistic insights into the drug modulation of URAT1 and sheds light on the rational design of potential URAT1-specific therapeutics for treating hyperuricemia.

A multi-ancestry genome-wide association study and evaluation of polygenic scores of LDL-C levels

The genetic determinants of low-density lipoprotein cholesterol (LDL-C) levels in blood have been predominantly explored in European populations and remain poorly understood in Middle Eastern populations. We investigated the genetic architecture of LDL-C variation in Qatar by conducting a genome-wide association study (GWAS) on serum LDL-C levels using whole genome sequencing data of 13,701 individuals (discovery; n = 5,939, replication; n = 7,762) from the population-based Qatar Biobank (QBB) cohort. We replicated 168 previously reported loci from the largest LDL-C GWAS by the Global Lipids Genetics Consortium (GLGC), with high correlation in allele frequencies (R2 = 0.77) and moderate correlation in effect sizes (Beta; R2 = 0.53). We also performed a multi-ancestry meta-analysis with the GLGC study using MR-MEGA (Meta-Regression of Multi-Ethnic Genetic Association) and identified one novel LDL-C-associated locus; rs10939663 (SLC2A9; genomic control-corrected P = 1.25 × 10-8). Lastly, we developed Qatari-specific polygenic score (PGS) panels and tested their performance against PGS derived from other ancestries. The multi-ancestry-derived PGS (PGS000888) performed best at predicting LDL-C levels, whilst the Qatari-derived PGS showed comparable performance. Overall, we report a novel gene associated with LDL-C levels, which may be explored further to decipher its potential role in the etiopathogenesis of cardiovascular diseases. Our findings also highlight the importance of population-based genetics in developing PGS for clinical utilization.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

Mendelian randomization study of serum uric acid levels and urate-lowering drugs on pulmonary arterial hypertension outcomes

This study aims to explore the causal relationships between serum uric acid level and pulmonary arterial hypertension (PAH) using the Mendelian randomization (MR) approach, and to assess the therapeutic impacts of urate-lowering drugs on PAH. Utilizing published genome-wide association study (GWAS) data, we applied MR and colocalization analysis to assess the link between serum uric acid levesl and PAH across four GWAS datasets from two distinct European populations. The validity and reliability of these findings were confirmed through multiple statistical methods, along with an MR analysis of urate-lowering drug targets to investigate their potential effects on PAH treatment. MR analysis revealed a significant positive correlation between serum uric acid levels and PAH (odds ratio (OR) 1.106, 95% confidence intervals (CI) 1.021-1.200, P = 0.014), corroborated by a replication MR analysis (OR 1.859, 95% CI 1.130-3.057, P = 0.015). No significant heterogeneity or horizontal pleiotropy was found in the sensitivity analyses. However, urate-lowering drugs did not demonstrate a significant direct therapeutic effect on PAH. This study establishes a genetic basis for a causal link between serum uric acid levels and PAH. However, urate-lowering drugs do not appear to have a direct causal effect on improving PAH. These findings provide a novel reference point for developing future therapeutic strategies for PAH.

Massively parallel variant-to-function mapping determines functional regulatory variants of non-small cell lung cancer

Genome-wide association studies have identified thousands of genetic variants associated with non-small cell lung cancer (NSCLC), however, it is still challenging to determine the causal variants and to improve disease risk prediction. Here, we applied massively parallel reporter assays to perform NSCLC variant-to-function mapping at scale. A total of 1249 candidate variants were evaluated, and 30 potential causal variants within 12 loci were identified. Accordingly, we proposed three genetic architectures underlying NSCLC susceptibility: multiple causal variants in a single haplotype block (e.g. 4q22.1), multiple causal variants in multiple haplotype blocks (e.g. 5p15.33), and a single causal variant (e.g. 20q11.23). We developed a modified polygenic risk score using the potential causal variants from Chinese populations, improving the performance of risk prediction in 450,821 Europeans from the UK Biobank. Our findings not only augment the understanding of the genetic architecture underlying NSCLC susceptibility but also provide strategy to advance NSCLC risk stratification.

Spatiotemporal landscape of kidney in a mouse model of hyperuricemia at single-cell level

Serum uric acid is an end-product of purine metabolism. Uric acid concentrations in excess of the physiological range may lead to diseases such as gout, cardiovascular disease, and kidney injury. The kidney includes a variety of cell types with specialized functions such as fluid and electrolyte homeostasis, detoxification, and endocrine functions. Two-thirds of uric acid is excreted through kidney, however, the exploration of markers and new therapeutic targets in renal tissue of hyperuricemia is still lacking. Single-cell and spatial omics techniques represent major milestones in life sciences. The combined measurement of the physical structure and molecular characteristics of tissues facilitates the exploration of the pathophysiological processes underlying disease development and the discovery of possible therapeutic targets. Here, the spatiotemporal atlas of hyperuricemic nephropathy was investigated using single-cell RNA sequencing, spatial transcriptomics, spatial proteomics, and spatial metabolomics in a urate oxidase knockout mouse model. Several emerging targets and pathways especially ribosome and metabolism related to uric acid excretion were discovered and will be investigated further in studies on lowering uric acid.

Associations between lipid-lowering drugs and urate and gout outcomes: a Mendelian randomization study

Objective

Gout is a common inflammatory arthritis and lipid metabolism plays a crucial role in urate and gout. Potential associations between urate and gout and lipid-lowering drugs have been revealed in observational studies. However, the effects of lipid-lowering drugs on urate and gout remain controversial. The aim of this study was to investigate the genetic association between lipid-lowering drugs and urate and gout.

Methods

In this study, two genetic proxies were employed to approximate lipid-lowering drug exposure: expression quantitative trait loci (eQTL) associated with drug-target genes and genetic variations proximal to or within genes targeted by these drugs, which are linked to low-density lipoprotein cholesterol (LDL-C) levels. The study's exposures encompassed genetic variants within drug target genes (HMGCR, PCSK9, NPC1L1), each representing distinct lipid-lowering mechanisms. Causal effects were estimated using the inverse variance weighting (IVW) method, while the Summary Data-based Mendelian Randomization (SMR) method, leveraging pooled data, was applied to compute effect estimates. These estimates were further refined through various approaches including MR-Egger, the weighted median method, simple and weighted models, and leave-one-out analyses to conduct sensitivity analyses.

Result

The analytical outcomes utilizing the IVW method indicated that inhibitors of HMGCR were correlated with an elevated risk of developing gout (IVW: OR [95%CI] = 1.25 [1.03, 1.46], p=0.0436), while PCSK9 inhibitors were linked to heightened levels of urate (IVW: OR [95%CI] = 1.06 [1.01,1.10], p=0.0167). Conversely, no significant correlation between NPC1L1 inhibitors and the levels of urate or the risk of gout was established. Furthermore, the SMR analysis failed to identify significant associations between the expression levels of the HMGCR, PCSK9, and NPC1L1 genes and the risk of gout or elevated urate levels (SMR method: all P values >0.05). Sensitivity analyses further confirmed the robustness of these results, with no significant heterogeneity or pleiotropy found.

Conclusion

This study furnishes novel causal evidence supporting the potential genetic correlation between the use of lipid-lowering drugs and the incidence of gout as well as urate levels. The findings indicate that inhibitors targeting HMGCR may elevate the risk associated with the development of gout, while inhibitors targeting PCSK9 are likely to increase urate concentrations.

Association between serum iron status and gout: results from the NHANES and Mendelian randomization study

Aims. Previous observational studies have provided inconsistent evidence for the association between serum iron status and the risk of gout. Moreover, it remains uncertain whether the observed association is causal or due to confounding or reverse causality. This research aimed to investigate the association of serum iron status indicators with the risk of gout and to further examine the causal relationship by the Mendelian randomization (MR) method. Methods. We first conducted a cross-sectional study from the National Health and Nutrition Examination Survey 2017-2018, including a total of 4635 participants. The association of serum iron status indicators with gout risk was evaluated using a multivariable logistic regression model. Furthermore, a two-sample MR study using genetic data from large-scale genome-wide association studies of serum iron status indicators (246 139 individuals) and gout (discovery: 13 179 cases and 75 0634 controls; replication: 5292 cases and 368 788 controls; 2115 cases and 67 259 controls) was conducted to infer causality. Inverse-variance-weighting (IVW) was applied as the main method of MR analysis. A series of sensitivity analyses were used to evaluate the robustness of their relationship. Results. In the cross-sectional study, there was no significant relationship between serum iron status indicators and gout risk. However, IVW results showed that genetically predicted serum iron and transferrin saturation (TSAT) were significantly associated with the increased risk of gout in the discovery analysis [odds ratio (OR): 1.21; 95% confidence interval (CI): 1.10-1.32; P = 9.80 × 10-5 for serum iron and OR: 1.16; 95% CI: 1.08-1.25; P = 7.14 × 10-5 for TSAT]. The replication analysis provided similar results compared with the discovery analysis. Conclusion. Our study provides support for potential causal associations between serum iron and the altered risk of gout. Further investigations are warranted to elucidate the biological processes through which iron influences susceptibility to gout.

Effects of Genetic Risk and Lifestyle Habits on Gout: A Korean Cohort Study

BACKGROUND

Gout is a type of inflammatory arthritis caused by monosodium urate crystal deposits, and the prevalence of this condition has been increasing. This study aimed to determine the combined effects of genetic risk factors and lifestyle habits on gout, using data from a Korean cohort study. Identifying high-risk individuals in advance can help prevent gout and its associated disorders.

METHODS

We analyzed data from the Korean Genome and Epidemiology Study-Urban Health Examinees cohort (KoGES-HEXA). Genetic information of the participants was collected at baseline, and gout cases were identified based on patient statements. The polygenic risk score (PRS) was calculated using nine independent genome-wide association study datasets, and lifestyle factors and metabolic syndrome status were measured for each participant using the KoGES. Logistic regression models were used to estimate the odds ratios (ORs) for gout in relation to genetic risk, lifestyle habits, and metabolic health status, after adjusting for age and sex.

RESULTS

Among 44,605 participants, 617 were diagnosed with gout. Gout was associated with older age, higher body mass index, and higher prevalence of hypertension, diabetes, and hypertriglyceridemia. High PRS, unfavorable lifestyle habits, and poor metabolic profiles were significantly associated with an increased risk of gout. Compared with that in the low-genetic-risk and healthy lifestyle group or ideal metabolic profile group, the risk of gout was increased in the high-genetic-risk plus unfavorable lifestyle (OR, 3.64; 95% confidence interval [CI], 2.32-6.03) or poor metabolic profile (OR, 7.78; 95% CI, 4.61-13.40) group. Conversely, adherence to favorable lifestyle habits significantly reduced gout risk, especially in high-genetic-risk groups.

CONCLUSION

Genetic predisposition and unhealthy lifestyle habits significantly increase the risk of gout. Promoting healthy lifestyle habits is crucial to prevent the development of gout, particularly in individuals with high genetic susceptibility.

The pathogenesis of gout

Gout is the most common inflammatory arthritis in adults, associated with hyperuricemia and the chronic deposition of monosodium urate (MSU) crystals. Hyperuricemia results from increased production of uric acid and decreased excretion by the kidneys and intestines. Urate excretion is regulated by a group of urate transporters, and decreased renal or intestinal excretion is the primary mechanism of hyperuricemia in most people. Genetic variability in these urate transporters is strongly related to variances in serum urate levels. Not all individuals with hyperuricemia show deposition of MSU crystals or develop gout. The initiation of the inflammatory response to MSU crystals is mainly mediated by the nucleotide-binding oligomerization domain-, leucine-rich repeat- and pyrin domain-containing protein 3 (NLRP3) inflammasome. The activated NLRP3 inflammasome complex cleaves pro-interleukin-1β (IL-1β) into its active form, IL-1β, which is a key mediator of the inflammatory response in gout. IL-1β leads to the upregulation of cytokines and chemokines, resulting in the recruitment of neutrophils and other immune cells. Neutrophils recruited to the site of inflammation also play a role in resolving inflammation. Aggregated neutrophil extracellular traps (NETs) trap and degrade cytokines and chemokines through NET-bound proteases, promoting the resolution of inflammation. Advanced gout is characterized by tophi, chronic inflammatory responses, and structural joint damage. Tophi are chronic foreign body granuloma-like structures containing collections of MSU crystals encased by inflammatory cells and connective tissue. Tophi are closely related to chronic inflammation and structural damage.

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort

OBJECTIVE

Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout.

METHODS

We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1.

RESULTS

In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation.

CONCLUSION

This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Pediatrics hyperuricemia in clinical practice: A retrospective analysis in 1753 children and adolescents with hyperuricemia

OBJECTIVES

Serum levels of uric acid (S-UA) are influenced by the interaction of genetic and environmental factors; detailed studies of hyperuricemia in children are rare. This retrospective study aimed to analyze the causes, risk factors, and therapeutic approaches associated with the development of hyperuricemia in childhood.

METHODS

In a single-center study, serum uric acid levels were analyzed in 33,900 samples from 13,890 children and adolescents<19 years (6760 girls and 7130 boys) obtained between 2013 and 2023. Hyperuricemia was defined as S-UA>370μmol/L (6.22mg/dL) in girls and>420μmol/L (7.06mg/dL) in boys; mild hyperuricemia was defined as 370-420μmol/L in boys<13 years.

RESULTS

In the analyzed group, hyperuricemia was found in 1753 patients (12.6%), including 586 girls and 864 boys; mild hyperuricemia was found in 303 boys<13 years. The most common associated conditions were obesity with body mass index>95th percentile (27.8% of girls, 26.3% of boys) and chronic kidney disease (18.6% of boys, 11.4% of girls). Hyperuricemia was also relatively common in children with connective tissue disorders (10.6%) or different inherited metabolic disorders (10.7%). Transitory hyperuricemia was found in 19.1% of girls and 10.1% of boys with acute gastroenteritis. Urate-lowering therapy was used in 73 children and adolescents with severe hyperuricemia (S-UA 556±107μmol/L, fraction excretion of UA 3.27±1.98%). Eight treated children had chronic kidney disease, nine were extremely obese, one had combined antiepileptic therapy, and 55 had inherited metabolic diseases, including 26 children with disorders of purine metabolism. The initial daily dose of allopurinol (50-100mg) normalized the S-UA (350±80μmol/L) in a majority of children, except for extremely obese adolescents (weight 98-149kg) where the dose had to be increased to 200-300mg.

CONCLUSIONS

Asymptomatic hyperuricemia is a relatively common biochemical finding in pediatric clinical practice. The etiology of hyperuricemia should be carefully analyzed, and the value of individualized hyperuricemia management and the eventual benefits of urate-lowering therapy in children must be carefully considered.

Population-specific reference panel improves imputation quality for genome-wide association studies conducted on the Japanese population

To improve imputation quality for genome-wide association studies (GWAS) conducted on the Japanese population, we developed and evaluated four Japanese population-specific reference panels. These panels were constructed through the augmentation of the 1000 Genomes Project (1KG) panel using Japanese whole genome sequencing (WGS) data, with sample sizes ranging from 1 K to 7 K individuals enrolled through the Biobank Japan (BBJ) project, and sequencing depths ranging from 3× to 30×. Among these panels, an augmented reference panel comprising 7472 WGS samples of mixed depth (1KG+7K) exhibit the greatest improvement in imputation quality relative to the Trans-Omics for Precision Medicine (TOPMed) reference panel. Notably, we observe these improvements primarily for rare variants with a minor allele frequency (MAF) <5%. To demonstrate the benefits of improved imputation quality in association analyses of complex traits, we conducted GWAS for serum uric acid and total cholesterol levels following imputation up to the 1KG+7K panel. The analysis reveals several loci reaching genome-wide significance (P < 5 × 10-8) in the 1KG+7K imputation output yet remaining undetected when the same sample set is imputed up to the TOPMed reference panel. In summary, the 1KG+7K panel demonstrates significant advantages in the discovery of trait-associated loci, particularly those influenced by low-frequency association signals.

The genetic architecture of age at menarche and its causal effects on other traits

Age at menarche (AAM) is a sign of puberty of females. It is a heritable trait associated with various adult diseases. However, the genetic mechanism that determines AAM and links it to disease risk is poorly understood. Aiming to uncover the genetic basis for AAM, we conducted a joint association study in up to 438,089 women from 3 genome-wide association studies of European and East Asian ancestries. A series of bioinformatical analyses and causal inference were then followed to explore in-depth annotations at the associated loci and infer the causal relationship between AAM and other complex traits/diseases. This largest meta-analysis identified a total of 21 novel AAM associated loci at the genome wide significance level (P < 5.0  × 10-8), 4 of which were European ancestry-specific loci. Functional annotations prioritized 33 candidate genes at newly identified loci. Significant genetic correlations were observed between AAM and 67 complex traits. Further causal inference demonstrated the effects of AAM on 13 traits, including forced vital capacity (FVC), high blood pressure, age at first live birth, etc, indicating that earlier AAM causes lower FVC, worse lung function, hypertension and earlier age at first (last) live birth. Enrichment analysis identified 5 enriched tissues, including the hypothalamus middle, hypothalamo hypophyseal system, neurosecretory systems, hypothalamus and retina. Our findings may provide useful insights that elucidate the mechanisms determining AAM and the genetic interplay between AAM and some traits of women.

Prediagnostic Amino Acid Metabolites and Risk of Gout, Accounting for Serum Urate: Prospective Cohort Study and Mendelian Randomization

OBJECTIVE

Our objective was to prospectively investigate prediagnostic population-based metabolome for risk of hospitalized gout (ie, most accurate, severe, and costly cases), accounting for serum urate.

METHODS

We conducted prediagnostic metabolome-wide analyses among 249,677 UK Biobank participants with nuclear magnetic resonance metabolomic profiling (N = 168 metabolites, including eight amino acids) from baseline blood samples (2006-2010) without a history of gout. We calculated multivariable hazard ratios (HRs) for hospitalized incident gout, before and after adjusting for serum urate levels; we included patients with nonhospitalized incident gout in a sensitivity analysis. Potential causal effects were evaluated with two-sample Mendelian randomization.

RESULTS

Correcting for multiple testing, 107 metabolites were associated with incidence of hospitalized gout (n = 2,735) before urate adjustment, including glycine and glutamine (glutamine HR 0.64, 95% confidence interval [CI] 0.54-0.75, P = 8.3 × 10-8; glycine HR 0.69, 95% CI 0.61-0.78, P = 3.3 × 10-9 between extreme quintiles), and glycoprotein acetyls (HR 2.48, 95% CI 2.15-2.87, P = 1.96 × 10-34). Associations remained significant and directionally consistent following urate adjustment (HR 0.83, 95% CI 0.70-0.98; HR 0.86, 95% CI 0.76-0.98; HR 1.41, 95% CI 1.21-1.63 between extreme quintiles), respectively; corresponding HRs per SD were 0.91 (95% CI 0.86-0.97), 0.94 (95% CI 0.91-0.98), and 1.10 (95% CI 1.06-1.14). Findings persisted when including patients with nonhospitalized incident gout. Mendelian randomization corroborated their potential causal role on hyperuricemia or gout risk; with change in urate levels of -0.05 mg/dL (95% CI -0.08 to -0.01) and -0.12 mg/dL (95% CI -0.22 to -0.03) per SD of glycine and glutamine, respectively, and odds ratios of 0.94 (95% CI 0.88-1.00) and 0.81 (95% CI 0.67-0.97) for gout.

CONCLUSION

These prospective findings with causal implications could lead to biomarker-based risk prediction and potential supplementation-based interventions with glycine or glutamine.

The Genetic Variants Influencing Hypertension Prevalence Based on the Risk of Insulin Resistance as Assessed Using the Metabolic Score for Insulin Resistance (METS-IR)

Insulin resistance is a major indicator of cardiovascular diseases, including hypertension. The Metabolic Score for Insulin Resistance (METS-IR) offers a simplified and cost-effective way to evaluate insulin resistance. This study aimed to identify genetic variants associated with the prevalence of hypertension stratified by METS-IR score levels. Data from the Korean Genome and Epidemiology Study (KoGES) were analyzed. The METS-IR was calculated using the following formula: ln [(2 × fasting blood glucose (FBG) + triglycerides (TG)) × body mass index (BMI)]/ ln [high-density lipoprotein cholesterol (HDL-C)]. The participants were divided into tertiles 1 (T1) and 3 (T3) based on their METS-IR scores. Genome-wide association studies (GWAS) were performed for hypertensive cases and non-hypertensive controls within these tertile groups using logistic regression adjusted for age, sex, and lifestyle factors. Among the METS-IR tertile groups, 3517 of the 19,774 participants (17.8%) at T1 had hypertension, whereas 8653 of the 20,374 participants (42.5%) at T3 had hypertension. A total of 113 single-nucleotide polymorphisms (SNPs) reached the GWAS significance threshold (p < 5 × 10-8) in at least one tertile group, mapping to six distinct genetic loci. Notably, four loci, rs11899121 (chr2p24), rs7556898 (chr2q24.3), rs17249754 (ATP2B1), and rs1980854 (chr20p12.2), were significantly associated with hypertension in the high-METS-score group (T3). rs10857147 (FGF5) was significant in both the T1 and T3 groups, whereas rs671 (ALDH2) was significant only in the T1 group. The GWASs identified six genetic loci significantly associated with hypertension, with distinct patterns across METS-IR tertiles, highlighting the role of metabolic context in genetic susceptibility. These findings underscore critical genetic factors influencing hypertension prevalence and provide insights into the metabolic-genetic interplay underlying this condition.

Serum uric acid and pulmonary arterial hypertension: A two-sample Mendelian randomization study

BACKGROUND

Observational studies have suggested a correlation between hyperuricemia and pulmonary arterial hypertension (PAH), yet the causal relationship remains uncertain. We aimed to establish this link using Mendelian Randomization (MR) methods.

OBJECTIVES

Based on publicly accessible data, our study employs MR to determine the causal relationship between uric acid (UA) and PAH.

METHOD

MR analysis was conducted among individuals of European descent. Genetic instruments linked to UA (p-value < 5 × 10-8) were extracted from the Chronic Kidney Disease Genetic Consortium and genome-wide association study databases. PAH risk genetic associations were sourced separately. We employed four MR methods (MR-Egger, weighted median, inverse variance weighted, and weighted mode) with selected instrumental variables to assess the causal association between UA and PAH. MR-PRESSO was used to evaluate pleiotropy and outlier Single Nucleotide Polymorphisms (SNPs), while Cochran's Q test and funnel plot assessed SNP heterogeneity. Leave-one-out analysis examined SNP impacts on causal assessment.

RESULT

Two-sample MR analysis revealed a positive, causal relationship between UA levels and PAH.

CONCLUSION

Our MR analysis provides robust evidence of a causal link between serum UA and PAH, suggesting UA's potential as a biomarker and therapeutic target for PAH.

A genome-wide association analysis reveals new pathogenic pathways in gout

Gout is a chronic disease that is caused by an innate immune response to deposited monosodium urate crystals in the setting of hyperuricemia. Here, we provide insights into the molecular mechanism of the poorly understood inflammatory component of gout from a genome-wide association study (GWAS) of 2.6 million people, including 120,295 people with prevalent gout. We detected 377 loci and 410 genetically independent signals (149 previously unreported loci in urate and gout). An additional 65 loci with signals in urate (from a GWAS of 630,117 individuals) but not gout were identified. A prioritization scheme identified candidate genes in the inflammatory process of gout, including genes involved in epigenetic remodeling, cell osmolarity and regulation of NOD-like receptor protein 3 (NLRP3) inflammasome activity. Mendelian randomization analysis provided evidence for a causal role of clonal hematopoiesis of indeterminate potential in gout. Our study identifies candidate genes and molecular processes in the inflammatory pathogenesis of gout suitable for follow-up studies.

Discovery and prioritization of genetic determinants of kidney function in 297,355 individuals from Taiwan and Japan

Current genome-wide association studies (GWAS) for kidney function lack ancestral diversity, limiting the applicability to broader populations. The East-Asian population is especially under-represented, despite having the highest global burden of end-stage kidney disease. We conducted a meta-analysis of multiple GWASs (n = 244,952) on estimated glomerular filtration rate and a replication dataset (n = 27,058) from Taiwan and Japan. This study identified 111 lead SNPs in 97 genomic risk loci. Functional enrichment analyses revealed that variants associated with F12 gene and a missense mutation in ABCG2 may contribute to chronic kidney disease (CKD) through influencing inflammation, coagulation, and urate metabolism pathways. In independent cohorts from Taiwan (n = 25,345) and the United Kingdom (n = 260,245), polygenic risk scores (PRSs) for CKD significantly stratified the risk of CKD (p < 0.0001). Further research is required to evaluate the clinical effectiveness of PRSCKD in the early prevention of kidney disease.

NUMB dysfunction defines a novel mechanism underlying hyperuricemia and gout

Defective renal excretion and increased production of uric acid engender hyperuricemia that predisposes to gout. However, molecular mechanisms underlying defective uric acid excretion remain largely unknown. Here, we report a rare genetic variant of gout-unprecedented NUMB gene within a hereditary human gout family, which was identified by an unbiased genome-wide sequencing approach. This dysfunctional missense variant within the conserved region of the NUMB gene (NUMBR630H) underwent intracellular redistribution and degradation through an autophagy-dependent mechanism. Mechanistically, we identified the uric acid transporter, ATP Binding Cassette Subfamily G Member 2 (ABCG2), as a novel NUMB-binding protein through its intracellular YxNxxF motif. In polarized renal tubular epithelial cells (RTECs), NUMB promoted ABCG2 trafficking towards the apical plasma membrane. Genetic loss-of-function of NUMB resulted in redistribution of ABCG2 in the basolateral domain and ultimately defective excretion of uric acid. To recapitulate the clinical situation in human gout patients, we generated a NUMBR630H knock-in mouse strain, which showed marked increases of serum urate and decreased uric acid excretion. The NUMBR630H knock-in mice exhibited clinically relevant hyperuricemia. In summary, we have uncovered a novel NUMB-mediated mechanism of uric acid excretion and a functional missense variant of NUMB in humans, which causes hyperuricemia and gout.

Modal-nexus auto-encoder for multi-modality cellular data integration and imputation

Heterogeneous feature spaces and technical noise hinder the cellular data integration and imputation. The high cost of obtaining matched data across modalities further restricts analysis. Thus, there's a critical need for deep learning approaches to effectively integrate and impute unpaired multi-modality single-cell data, enabling deeper insights into cellular behaviors. To address these issues, we introduce the Modal-Nexus Auto-Encoder (Monae). Leveraging regulatory relationships between modalities and employing contrastive learning within modality-specific auto-encoders, Monae enhances cell representations in the unified space. The integration capability of Monae furnishes it with modality-complementary cellular representations, enabling the generation of precise intra-modal and cross-modal imputation counts for extensive and complex downstream tasks. In addition, we develop Monae-E (Monae-Extension), a variant of Monae that can converge rapidly and support biological discoveries. Evaluations on various datasets have validated Monae and Monae-E's accuracy and robustness in multi-modality cellular data integration and imputation.

A Mendelian randomization study of the association between serum uric acid and osteoporosis risk

BACKGROUND

The relationship between serum uric acid (SUA) and osteoporosis (OP) has yielded conflicting results in observational studies. This Mendelian randomization (MR) study aims to elucidate the causal association between SUA and OP.

METHODS

A two-sample MR analysis was conducted using summary-level data from genome-wide association studies (GWAS). Two sets of polygenic instruments strongly associated (p < 5 × 10-8) with SUA were extracted from the CKDGen consortium and UK biobank. Polygenic instruments associated with OP (p < 5 × 10-8) were derived from FinnGen biobank and UK biobank. Inverse variance weighting (IVW) was employed as the primary analysis method. Additionally, we utilized MR-Egger, weighted median, the simple mode method, and the weighted mode as complementary analyses. Cochran's Q statistics were used to assess heterogeneity, with MR-Egger intercept testing and MR pleiotropy residual sum and outlier (MR-PRESSO) to examine horizontal pleiotropy. Sensitivity analysis was performed using the leave-one-out method.

RESULTS

The IVW analysis conducted across four groups confirms no significant causal relationship between SUA concentration and OP: UKB-UKB (OR: 1.001, 95% CI: 0.999-1.003, p=0.464), CKD-UKB (OR: 1.001, 95% CI: 0.999-1.003, p=0.349), UKB-Fin (OR: 0.934, 95% CI: 0.747-1.168, p=0.549), CKD-Fin (OR: 1.041, 95%CI: 0.934-1.161, p=0.470). Furthermore, additional four MR analyses corroborated these findings. Upon excluding all outliers identified by the MR-PRESSO test, no significant directional pleiotropy was observed, except for some data heterogeneity noted in the UKB-UKB group (Q=50.65, P=0.002). Additionally, a leave-one-out analysis indicated that no single SNP exerted undue influence on the results.

CONCLUSION

This MR analysis provides convincing genetic evidence that there is no causal association between SUA and OP, SUA is unlikely to increase or reduce the risk of OP.

Association of visceral adipose tissue with gout: Observational and Mendelian randomization analyses

BACKGROUND

The causal relationship between visceral adipose tissue (VAT) and gout is still unclear. We aimed to examine the potential association between them using observational and Mendelian randomization (MR) analyses.

METHODS

In the observational analyses, a total of 11,967 participants (aged 39.5 ± 11.5 years) were included from the National Health and Nutrition Examination Survey. Logistic regression models were used to investigate the association between VAT mass and the risk of gout. In two-sample MR analyses, 211 VAT mass-related independent genetic variants (derived from genome-wide association studies in 325,153 UK biobank participants) were used as instrumental variables. The random-effects inverse-variance weighted (IVW) method was used as the primary analysis. Additional sensitivity analyses were also performed to validate our results.

RESULTS

Observational analyses found that an increase in VAT mass (per standard deviation) was associated with a higher risk of gout after controlling for confounding factors (odds ratio [OR] = 1.27, 95% confidence intervals [CI] = 1.11-1.45). The two-sample MR analyses demonstrated a causal relationship between increased VAT mass and the risk of gout in primary analyses (OR = 1.78, 95% CI = 1.57-2.03). Sensitivity analyses also showed similar findings, including MR-Egger, weighted median, simple mode, weighted mode, and leave-one-out analyses.

CONCLUSIONS

Observational analyses showed a robust association of VAT mass with the risk of gout. Meanwhile, MR analyses also provided evidence of a causal relationship between them. In summary, our findings suggested that targeted interventions for VAT mass may be beneficial to prevent gout.

A combination of red and processed meat intake and polygenic risk score influences the incidence of hyperuricemia in middle-aged Korean adults

BACKGROUND/OBJECTIVES

The high consumption of purine-rich meat is associated with hyperuricemia. However, there is limited evidence linking the consumption of red and processed meat to the genetic risk of hyperuricemia. We investigated the relationship between various combinations of red and processed meat consumption and the polygenic risk scores (PRSs) and the incidence of hyperuricemia in middle-aged Koreans.

SUBJECTS/METHODS

We analyzed the data from 44,053 participants aged ≥40 years sourced from the Health Examinees (HEXA) cohort of the Korean Genome and Epidemiology Study (KoGES). Information regarding red and processed meat intake was obtained using a semiquantitative food frequency questionnaire (SQ-FFQ). We identified 69 independent single-nucleotide polymorphisms (SNPs) at uric acid-related loci using genome-wide association studies (GWASs) and clumping analyses. The individual PRS, which is the weighted sum of the effect size of each allele at the SNP, was calculated. We used multivariable Cox proportional hazards models adjusted for covariates to determine the relationship between red and processed meat intake and the PRS in the incidence of hyperuricemia.

RESULTS

During an average follow-up period of 5 years, 2,556 patients with hyperuricemia were identified. For both men and women, the group with the highest red and processed meat intake and the highest PRS was positively associated with the development of hyperuricemia when compared with the group with the lowest red and processed meat intake and the lowest PRS (hazard ratio [HR], 2.72; 95% confidence interval [CI], 2.10-3.53; P < 0.0001; HR, 3.28; 95% CI, 2.45-4.40; P < 0.0001).

CONCLUSION

Individuals at a high genetic risk for uric acid levels should moderate their consumption of red and processed meat to prevent hyperuricemia.

Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare

Introduction

There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches.

Methods

The single-cell RNA sequencing (scRNA-seq), large-scale genome-wide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data.

Results

The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that NLRP3 was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, IER3 was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized.

Discussion

Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases.

The Causal Effect of Urate Level on Female Infertility: A Mendelian Randomization Study

BACKGROUND/OBJECTIVE

This study aimed to investigate the causal relationship between urate level and female infertility using Mendelian randomization (MR) analysis.

METHODS

To identify instrumental variables, we selected independent genetic loci associated with serum urate levels in individuals of European ancestry, utilizing data from large-scale genome-wide association studies (GWAS). The GWAS dataset included information on serum urate levels from 288,649 CKDGen participants. Female infertility data, including different etiologic classifications, consisted of 13,142 female infertility patients and 107,564 controls. We employed four MR methods, namely inverse variance weighted (IVW), MR-Egger, weighted median, and weighted model, to investigate the causal relationship between urate levels and female infertility. The Cochran Q-test was used to assess heterogeneity among single nucleotide polymorphisms (SNPs), and the MR-Egger intercept test was employed to evaluate the presence of horizontal pleiotropy. Additionally, a "leave-one-out" sensitivity analysis was conducted to examine the influence of individual SNPs on the MR study.

RESULTS

The IVW analysis demonstrated that elevated serum urate levels increased the risk of female infertility (odds ratio [OR] = 1.18, 95% confidence interval [CI]: 1.07-1.33). Furthermore, serum urate levels were found to be associated with infertility due to cervical, vaginal, or other unknown causes (OR = 1.16, 95% CI: 1.06-1.26), also confirmed by other methods. Heterogeneity among instrumental variables was assessed using Cochran's Q-test (p < 0.05), so a random-effects IVW approach was employed in the effects model. The MR-Egger intercept test indicated no presence of horizontal pleiotropy. A "leave-one-out" sensitivity analysis was conducted, demonstrating that no individual SNP had a substantial impact on the overall findings.

CONCLUSIONS

In the European population, the urate level is significantly and causally associated with an increased risk of female infertility.

No causal relationship between serum urate and neurodegenerative diseases: A Mendelian randomization study

OBJECTIVE

Observational studies have shown that increased serum urate is associated with a lower risk of neurodegenerative diseases (NDs), but the causality remains unclear. We employed a two-sample Mendelian randomization (MR) approach to assess the causal relationship between serum urate and four common subtypes of NDs, including Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS).

METHODS

Serum urate data came from the CKDGen Consortium. GWAS data for PD, AD, ALS, and MS were obtained from four databases in the primary analysis and then acquired statistics from the FinnGen consortium for replication and meta-analysis. Inverse variance weighted (IVW), weighted median (WM), and MR-Egger regression methods were applied in the MR analyses. Pleiotropic effects, heterogeneity, and leave-one-out analyses were evaluated to validate the results.

RESULTS

There was no evidence for the effect of serum urate on PD (OR: 1.00, 95 % CI: 0.90-1.11, P = 0.97), AD (OR: 1.02, 95 % CI: 1.00-1.04, P = 0.06), ALS (OR: 1.05, 95 % CI: 0.97-1.13, P = 0.22), and MS (OR: 1.01, 95 % CI: 0.89-1.14, P = 0.90) risk when combined with the FinnGen consortium, neither was any evidence of pleiotropy detected between the instrumental variables (IVs).

CONCLUSION

The MR analysis suggested that serum urate may not be causally associated with a risk of PD, AD, ALS, and MS.

Multimodal Machine Learning-Based Marker Enables Early Detection and Prognosis Prediction for Hyperuricemia

Hyperuricemia (HUA) has emerged as the second most prevalent metabolic disorder characterized by prolonged and asymptomatic period, triggering gout and metabolism-related outcomes. Early detection and prognosis prediction for HUA and gout are crucial for pre-emptive interventions. Integrating genetic and clinical data from 421287 UK Biobank and 8900 Nanfang Hospital participants, a stacked multimodal machine learning model is developed and validated to synthesize its probabilities as an in-silico quantitative marker for hyperuricemia (ISHUA). The model demonstrates satisfactory performance in detecting HUA, exhibiting area under the curves (AUCs) of 0.859, 0.836, and 0.779 within the train, internal, and external test sets, respectively. ISHUA is significantly associated with gout and metabolism-related outcomes, effectively classifying individuals into low- and high-risk groups for gout in the train (AUC, 0.815) and internal test (AUC, 0.814) sets. The high-risk group shows increased susceptibility to metabolism-related outcomes, and participants with intermediate or favorable lifestyle profiles have hazard ratios of 0.75 and 0.53 for gout compared with those with unfavorable lifestyles. Similar trends are observed for other metabolism-related outcomes. The multimodal machine learning-based ISHUA marker enables personalized risk stratification for gout and metabolism-related outcomes, and it is unveiled that lifestyle changes can ameliorate these outcomes within high-risk group, providing guidance for preventive interventions.

Dietary Carbohydrates, Genetic Susceptibility, and Gout Risk: A Prospective Cohort Study in the UK

This study aimed to investigate the associations between carbohydrate intake and gout risk, along with interactions between genetic susceptibility and carbohydrates, and the mediating roles of biomarkers. We included 187,387 participants who were free of gout at baseline and completed at least one dietary assessment in the UK Biobank. Cox proportional hazard models were used to estimate the associations between carbohydrate intake and gout risk. Over a median follow-up of 11.69 years, 2548 incident cases of gout were recorded. Total carbohydrate intake was associated with a reduced gout risk (Q4 vs. Q1: HR 0.67, 95% CI 0.60-0.74), as were total sugars (0.89, 0.80-0.99), non-free sugars (0.70, 0.63-0.78), total starch (0.70, 0.63-0.78), refined grain starch (0.85, 0.76-0.95), wholegrain starch (0.73, 0.65-0.82), and fiber (0.72, 0.64-0.80), whereas free sugars (1.15, 1.04-1.28) were associated with an increased risk. Significant additive interactions were found between total carbohydrates and genetic risk, as well as between total starch and genetic risk. Serum urate was identified as a significant mediator in all associations between carbohydrate intake (total, different types, and sources) and gout risk. In conclusion, total carbohydrate and different types and sources of carbohydrate (excluding free sugars) intake were associated with a reduced risk of gout.

Hyperuricemia and its related diseases: mechanisms and advances in therapy

Hyperuricemia, characterized by elevated levels of serum uric acid (SUA), is linked to a spectrum of commodities such as gout, cardiovascular diseases, renal disorders, metabolic syndrome, and diabetes, etc. Significantly impairing the quality of life for those affected, the prevalence of hyperuricemia is an upward trend globally, especially in most developed countries. UA possesses a multifaceted role, such as antioxidant, pro-oxidative, pro-inflammatory, nitric oxide modulating, anti-aging, and immune effects, which are significant in both physiological and pathological contexts. The equilibrium of circulating urate levels hinges on the interplay between production and excretion, a delicate balance orchestrated by urate transporter functions across various epithelial tissues and cell types. While existing research has identified hyperuricemia involvement in numerous biological processes and signaling pathways, the precise mechanisms connecting elevated UA levels to disease etiology remain to be fully elucidated. In addition, the influence of genetic susceptibilities and environmental determinants on hyperuricemia calls for a detailed and nuanced examination. This review compiles data from global epidemiological studies and clinical practices, exploring the physiological processes and the genetic foundations of urate transporters in depth. Furthermore, we uncover the complex mechanisms by which the UA induced inflammation influences metabolic processes in individuals with hyperuricemia and the association with its relative disease, offering a foundation for innovative therapeutic approaches and advanced pharmacological strategies.

The SGLT2 inhibitor dapagliflozin ameliorates renal fibrosis in hyperuricemic nephropathy

Hyperuricemic nephropathy (HN) is a global metabolic disorder characterized by uric acid (UA) metabolism dysfunction, resulting in hyperuricemia (HUA) and tubulointerstitial fibrosis (TIF). Sodium-dependent glucose transporter 2 inhibitor, dapagliflozin, has shown potential in reducing serum UA levels in patients with chronic kidney disease (CKD), though its protective effects against HN remain uncertain. This study investigates the functional, pathological, and molecular changes in HN through histological, biochemical, and transcriptomic analyses in patients, HN mice, and UA-stimulated HK-2 cells. Findings indicate UA-induced tubular dysfunction and fibrotic activation, which dapagliflozin significantly mitigates. Transcriptomic analysis identifies estrogen-related receptor α (ERRα), a downregulated transcription factor in HN. ERRα knockin mice and ERRα-overexpressed HK-2 cells demonstrate UA resistance, while ERRα inhibition exacerbates UA effects. Dapagliflozin targets ERRα, activating the ERRα-organic anion transporter 1 (OAT1) axis to enhance UA excretion and reduce TIF. Furthermore, dapagliflozin ameliorates renal fibrosis in non-HN CKD models, underscoring the therapeutic significance of the ERRα-OAT1 axis in HN and CKD.

The pathogenesis of gout: molecular insights from genetic, epigenomic and transcriptomic studies

The pathogenesis of gout involves a series of steps beginning with hyperuricaemia, followed by the deposition of monosodium urate crystal in articular structures and culminating in an innate immune response, mediated by the NLRP3 inflammasome, to the deposited crystals. Large genome-wide association studies (GWAS) of serum urate levels initially identified the genetic variants with the strongest effects, mapping mainly to genes that encode urate transporters in the kidney and gut. Other GWAS highlighted the importance of uncommon genetic variants. More recently, genetic and epigenetic genome-wide studies have revealed new pathways in the inflammatory process of gout, including genetic associations with epigenomic modifiers. Epigenome-wide association studies are also implicating epigenomic remodelling in gout, which perhaps regulates the responsiveness of the innate immune system to monosodium urate crystals. Notably, genes implicated in gout GWAS do not include those encoding components of the NLRP3 inflammasome itself, but instead include genes encoding molecules involved in its regulation. Knowledge of the molecular mechanisms underlying gout has advanced through the translation of genetic associations into specific molecular mechanisms. Notable examples include ABCG2, HNF4A, PDZK1, MAF and IL37. Current genetic studies are dominated by participants of European ancestry; however, studies focusing on other population groups are discovering informative population-specific variants associated with gout.

A phenome-wide association and factorial Mendelian randomization study on the repurposing of uric acid-lowering drugs for cardiovascular outcomes

Uric acid has been linked to various disease outcomes. However, it remains unclear whether uric acid-lowering therapy could be repurposed as a treatment for conditions other than gout. We first performed both observational phenome-wide association study (Obs-PheWAS) and polygenic risk score PheWAS (PRS-PheWAS) to identify associations of uric acid levels with a wide range of disease outcomes. Then, trajectory analysis was conducted to explore temporal progression patterns of the observed disease outcomes. Finally, we investigated whether uric acid-lowering drugs could be repurposed using a factorial Mendelian randomization (MR) study design. A total of 41 overlapping phenotypes associated with uric acid levels were identified by both Obs- and PRS- PheWASs, primarily cardiometabolic diseases. The trajectory analysis illustrated how elevated uric acid levels contribute to cardiometabolic diseases, and finally death. Meanwhile, we found that uric acid-lowering drugs exerted a protective role in reducing the risk of coronary atherosclerosis (OR = 0.96, 95%CI: 0.93, 1.00, P = 0.049), congestive heart failure (OR = 0.64, 95%CI: 0.42, 0.99, P = 0.043), occlusion of cerebral arteries (OR = 0.93, 95%CI: 0.87, 1.00, P = 0.044) and peripheral vascular disease (OR = 0.60, 95%CI: 0.38, 0.94, P = 0.025). Furthermore, the combination of uric acid-lowering therapy (e.g. xanthine oxidase inhibitors) with antihypertensive treatment (e.g. calcium channel blockers) exerted additive effects and was associated with a 6%, 8%, 8%, 10% reduction in risk of coronary atherosclerosis, heart failure, occlusion of cerebral arteries and peripheral vascular disease, respectively. Our findings support a role of elevated uric acid levels in advancing cardiovascular dysfunction and identify potential repurposing opportunities for uric acid-lowering drugs in cardiovascular treatment.

Sex-specific epigenetic signatures of circulating urate and its increase after BCG vaccination

Background

Urate concentration and the physiological regulation of urate homeostasis exhibit clear sex differences. DNA methylation has been shown to explain a substantial proportion of serum urate variance, mediate the genetic effect on urate concentration, and co-regulate with cardiometabolic traits. However, whether urate concentration is associated with DNA methylation in a sex-dependent manner is unknown. Additionally, it is worth investigating if urate changes after perturbations, such as vaccination, are associated with DNA methylation in a sex-specific manner.

Methods

We investigated the association between DNA methylation and serum urate concentrations in a Dutch cohort of 325 healthy individuals. Urate concentration and DNA methylation were measured before and after Bacillus Calmette-Guérin (BCG) vaccination, used as a perturbation associated with increased gout flares. The association analysis included united, interaction, and sex-stratified analysis. Validation of the identified CpG sites was conducted using three independent cohorts.

Results

215 CpG sites were associated with serum urate in males, while 5 CpG sites were associated with serum urate in females, indicating sex-specific associations. Circulating urate concentrations significantly increased after BCG vaccination, and baseline DNA methylation was associated with differences in urate concentration before and after vaccination in a sex-specific manner. The CpG sites associated with urate concentration in males were enriched in neuro-protection pathways, whereas in females, the urate change-associated CpG sites were related to lipid and glucose metabolism.

Conclusion

Our study enhances the understanding of how epigenetic factors contribute to regulating serum urate levels in a sex-specific manner. These insights have significant implications for the diagnosis, prevention, and treatment of various urate-related diseases and highlight the importance of personalized and sex-specific approaches in medicine.

Changes in alcohol intake and serum urate changes: longitudinal analyses of annual medical examination database

INTRODUCTION

Despite the established cross-sectional association between alcohol intake and serum urate (SU), its longitudinal association remains unknown. This study aimed to determine whether changes in alcohol intake have a clinically relevant association with SU change.

METHOD

We conducted retrospective analyses using systematically collected annual medical examination data from October 2012 to October 2022 in a Japanese preventive medicine centre. The exposure was changes in alcohol intake between two consecutive visits. The association of SU changes with alcohol intake changes was estimated by mixed-effect linear regression with adjustment for relevant covariates.

RESULTS

We analysed 63 486 participants (median age, 47.0 years; 55% women; 58.6% regular alcohol drinkers with a median of 1.4 drinks/day) with 370 572 visits. The median SU level was 5.3 mg/dL, and 506 (0.8%) participants had diagnoses of gout or hyperuricemia without medication use during the study period. Decreasing one daily alcohol intake had a clinically small association with SU changes (-0.019 (95% CI: -0.021 to -0.017) mg/dL). Beer had the largest association with SU (-0.036 (95% CI: -0.039 to -0.032) mg/dL for one beer decrease). Complete discontinuation of any alcohol from a mean of 0.8 drinks/day was associated with -0.056 mg/dL (95% CI: -0.068 to -0.043) decrease in SU; the association became larger in hyperuricemic participants (-0.110 mg/dL (95% CI: -0.154 to -0.066) for alcohol discontinuation from a mean of 1.0 drinks/day).

CONCLUSIONS

This study revealed changes in alcohol intake had small associations with SU change at the general Japanese population level. Complete discontinuation of alcohol in hyperuricemic participants had only modest improvement in SU.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (β coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Causal impact of human blood metabolites and metabolic pathways on serum uric acid and gout: a mendelian randomization study

Objective

Hyperuricaemia and gout are common metabolic disorders. However, the causal relationships between blood metabolites and serum urate levels, as well as gout, remain unclear. A systematic evaluation of the causal connections between blood metabolites, hyperuricemia, and gout could enhance early screening and prevention of hyperuricemia and gout in clinical settings, providing novel insights and approaches for clinical treatment.

Methods

In this study, we employed a bidirectional two-sample Mendelian randomization analysis utilizing data from a genome-wide association study involving 7,286 participants, encompassing 486 blood metabolites. Serum urate and gout data were sourced from the Chronic Kidney Disease Genetics consortium, including 288,649 participants for serum urate and 9,819 African American and 753,994 European individuals for gout. Initially, LDSC methodology was applied to identify blood metabolites with a genetic relationship to serum urate and gout. Subsequently, inverse-variance weighting was employed as the primary analysis method, with a series of sensitivity and pleiotropy analyses conducted to assess the robustness of the results.

Results

Following LDSC, 133 blood metabolites exhibited a potential genetic relationship with serum urate and gout. In the primary Mendelian randomization analysis using inverse-variance weighting, 19 blood metabolites were recognized as potentially influencing serum urate levels and gout. Subsequently, the IVW p-values of potential metabolites were corrected using the false discovery rate method. We find leucine (IVW P FDR = 0.00004), N-acetylornithine (IVW P FDR = 0.0295), N1-methyl-3-pyridone-4-carboxamide (IVW P FDR = 0.0295), and succinyl carnitine (IVW P FDR = 0.00004) were identified as significant risk factors for elevated serum urate levels. Additionally, 1-oleoylglycerol (IVW P FDR = 0.0007) may lead to a substantial increase in the risk of gout. Succinyl carnitine exhibited acceptable weak heterogeneity, and the results for other blood metabolites remained robust after sensitivity, heterogeneity, and pleiotropy testing. We conducted an enrichment analysis on potential blood metabolites, followed by a metabolic pathway analysis revealing four pathways associated with serum urate levels.

Conclusion

The identified causal relationships between these metabolites and serum urate and gout offer a novel perspective, providing new mechanistic insights into serum urate levels and gout.

Association between combined exposure to ambient air pollutants, genetic risk, and incident gout risk: A prospective cohort study in the UK Biobank

BACKGROUND

Limited research has been conducted on the association between long-term exposure to air pollutants and the incidence of gout.

OBJECTIVES

This study aims to assess the individual and combined effects of prolonged exposure to five air pollutants (NO2, NOx, PM10, PMcoarse and PM2.52) on the incidence of gout among 458,884 initially gout-free participants enrolled in the UK Biobank.

METHODS

Employing a land use regression model, we utilized an estimation method to ascertain the annual concentrations of the five air pollutants. Subsequently, we devised a weighted air pollution score to facilitate a comprehensive evaluation of exposure. The Cox proportional hazards model was utilized to investigate the association between ambient air pollution and gout risk. Interaction and stratification analyses were conducted to evaluate age, sex, BMI, and genetic predisposition as potential effect modifiers in the air pollution-gout relationship. Furthermore, mediation analyses were conducted to explore the potential involvement of biomarkers in mediating the association between air pollution and gout.

RESULTS

Over a median follow-up time of 12.0 years, 7,927 cases of gout were diagnosed. Significant associations were observed between the risk of gout and a per IQR increase in NO2 (HR3: 1.05, 95 % CI4: 1.02-1.08, p = 0.003), NOx (HR: 1.04, 95 % CI: 1.01-1.06, p = 0.003), and PM2.5 (HR: 1.03, 95 % CI: 1.00-1.06, p = 0.030). Per IQR increase in the air pollution score was associated with an elevated risk of gout (p = 0.005). Stratified analysis revealed a significant correlation between the air pollution score and gout risk in participants ≥60 years (HR: 1.05, 95 % CI: 1.02-1.09, p = 0.005), but not in those <60 years (p = 0.793), indicating a significant interaction effect with age (p-interaction=0.009). Mediation analyses identified five serum biomarkers (SUA:15.87 %, VITD: 5.04 %, LDLD: 3.34 %, GGT: 1.90 %, AST: 1.56 %5) with potential mediation effects on this association.

CONCLUSIONS

Long-term exposure to air pollutants, particularly among the elderly population, is associated with an increased risk of gout. The underlying mechanisms of these associations may involve the participation of five serum biomarkers.

Understanding the impact of ABCG2 polymorphisms on drug pharmacokinetics: focus on rosuvastatin and allopurinol

INTRODUCTION

In addition to the well-established understanding of the pharmacogenetics of drug-metabolizing enzymes, there is growing data on the effects of genetic variation in drug transporters, particularly ATP-binding cassette (ABC) transporters. However, the evidence that these genetic variants can be used to predict drug effects and to adjust individual dosing to avoid adverse events is still limited.

AREAS COVERED

This review presents a summary of the current literature from the PubMed database as of February 2024 regarding the impact of genetic variants on ABCG2 function and their relevance to the clinical use of the HMG-CoA reductase inhibitor rosuvastatin and the xanthine oxidase inhibitor allopurinol.

EXPERT OPINION

Although there are pharmacogenetic guidelines for the ABCG2 missense variant Q141K, there is still some conflicting data regarding the clinical benefits of these recommendations. Some caution appears to be warranted in homozygous ABCG2 Q141K carriers when rosuvastatin is administered at higher doses and such information is already included in the drug label. The benefit of dose adaption to lower possible side effects needs to be evaluated in prospective clinical studies.