NRBP1 modulates uric acid transporter ABCG2 expression by activating the Wnt/β-catenin pathway in HK-2 cells

Association of Klotho and Gout in Middle-Aged and Older Adults: National Health and Nutrition Survey (2007-2016)

BACKGROUND

Klotho, which is known to negatively regulate metabolic disorders and kidney disease, has a role in gout that remains unclear. This research explored how klotho levels correlate with the prevalence of gout.

METHODS

Participants aged 40 to 79 from the National Health and Nutrition Examination Survey (2007-2016) were examined in both lines. The connection between klotho levels and gout was analyzed through weighted multivariate logistic regression. Restricted cubic splines were used to assess linearity and investigate the dose-response relationship. To ensure the stability of the results, subgroup and sensitivity analyses were conducted.

RESULTS

In total, 9660 individuals participated, with the weighted sample size calculated at 88,892,738.77. The group included 47.79% males (4793), with the median age being 57.00 years. Upon adjusting for all covariates, the multivariate analysis indicated an odds ratio of 0.51 (95% confidence interval [CI]: 0.33~0.78, p = 0.003) for the likelihood of occurrence of gout. When compared with the lowest klotho quartile Q1 (≥151.3, <655.3 pg/mL), the adjusted odds ratios for the subsequent quartiles Q2 (≥655.5, <800.9 pg/mL), Q3 (≥801.0, <991.6 pg/mL), and Q4 (≥991.7, ≤3998.5 pg/mL) were 0.97 (95% CI: 0.68~1.38), 0.78 (95% CI: 0.50~1.21), and 0.48 (95% CI: 0.32~0.73), respectively. Analyses focusing on subgroups and sensitivity confirmed these results.

CONCLUSIONS

This research found a negative correlation between serum α-klotho concentrations and the occurrence of gout. Those with the highest levels of klotho exhibited the lowest likelihood of gout, indicating potential importance for future studies and clinical uses.

The role of ABCG2 in health and disease: Linking cancer therapy resistance and other disorders

All biological systems have adenosine triphosphate (ATP) binding cassette (ABC) transporters, one of the significant protein superfamilies involved in transport across membranes. ABC transporters have been implicated in the etiology of diseases like metabolic disorders, cancer, and Alzheimer's disease. ATP-binding cassette superfamily G member 2 (ABCG2), one of the ABC transporters, is necessary for the ATP-dependent efflux of several endogenous and exogenous substances. Consequently, it maintained cellular homeostasis and shielded tissue from xenobiotic substances. ABCG2 was initially identified in an Adriamycin-selected breast cancer cell line (MCF-7/AdrVp) and was linked to the emergence of multidrug resistance (MDR) in cancerous cells. Under many pathophysiological conditions, including inflammation, disease pathology, tissue injury, infection, and in response to xenobiotics and endogenous substances, the expression of ABCG2 undergoes alterations that result in modifications in its function and activity. Genetic variants in the ABCG2 transporter can potentially impact its expression and function, contributing to the development of many disorders. This review aimed to illustrate the impact of ABCG2 expression and its variants on oral drug bioavailability, MDR in specific cancer cells, explore the relationship between ABCG2 expression and other disorders such as gout, Alzheimer's disease, epilepsy, and erythropoietic protoporphyria, and demonstrate the influence of various synthetic and natural compounds in regulating ABCG2 expression.

Genetic insights into therapeutic targets for gout: evidence from a multi-omics mendelian randomization study

BACKGROUND

Considering that the treatment of gout is poor, we performed a Mendelian randomization (MR) study to identify candidate biomarkers and therapeutic targets for gout.

METHODS

A drug-targeted MR study was performed for gout by integrating the gout genome-wide association studies (GWAS) summary data and cis expression quantitative trait loci of 2,633 druggable genes from multiple cohorts. Summary data-based Mendelian randomization (SMR) analyses based on transcript and protein levels were further implemented to validate the reliability of the identified potential therapeutic targets for gout. Phenome-wide MR (Phe-MR) analysis was conducted in 1403 diseases to investigate incidental side effects of potential therapeutic targets for gout.

RESULTS

Eight potential therapeutic targets (ALDH3B1, FCGR2B, IL2RB, NRBP1, RCE1, SLC7A7, SUMF1, THBS3) for gout were identified in the discovery cohort using MR analysis. Replication analysis and meta-analysis implemented in the replication cohort validated the robustness of the MR findings (P < 0.05). Evidence from the SMR analysis (P < 0.05) further strengthened the reliability of the 8 potential therapeutic targets for gout also revealed that high levels of ALDH3B1 reduced the gout risk possibly modified by the methylation site cg25402137. SMR analysis (P < 0.05) at the protein level added emphasis on the impact of the risk genes NRBP1 and SUMF1 on gout. Phe-MR analysis indicated significant causality between 7 gout causal genes and 45 diseases.

CONCLUSION

This study identified several biomarkers associated with gout risk, providing new insights into the etiology of gout and promising targets for the development of therapeutic agents.

Transcriptome- and proteome-wide association studies nominate determinants of kidney function and damage

BACKGROUND

The pathophysiological causes of kidney disease are not fully understood. Here we show that the integration of genome-wide genetic, transcriptomic, and proteomic association studies can nominate causal determinants of kidney function and damage.

RESULTS

Through transcriptome-wide association studies (TWAS) in kidney cortex, kidney tubule, liver, and whole blood and proteome-wide association studies (PWAS) in plasma, we assess for effects of 12,893 genes and 1342 proteins on kidney filtration (glomerular filtration rate (GFR) estimated by creatinine; GFR estimated by cystatin C; and blood urea nitrogen) and kidney damage (albuminuria). We find 1561 associations distributed among 260 genomic regions that are supported as putatively causal. We then prioritize 153 of these genomic regions using additional colocalization analyses. Our genome-wide findings are supported by existing knowledge (animal models for MANBA, DACH1, SH3YL1, INHBB), exceed the underlying GWAS signals (28 region-trait combinations without significant GWAS hit), identify independent gene/protein-trait associations within the same genomic region (INHBC, SPRYD4), nominate tissues underlying the associations (tubule expression of NRBP1), and distinguish markers of kidney filtration from those with a role in creatinine and cystatin C metabolism. Furthermore, we follow up on members of the TGF-beta superfamily of proteins and find a prognostic value of INHBC for kidney disease progression even after adjustment for measured glomerular filtration rate (GFR).

CONCLUSION

In summary, this study combines multimodal, genome-wide association studies to generate a catalog of putatively causal target genes and proteins relevant to kidney function and damage which can guide follow-up studies in physiology, basic science, and clinical medicine.

Genome-wide search identified DNA methylation sites that regulate the metabolome

Background: Identifying DNA methylation sites that regulate the metabolome is important for several purposes. In this study, publicly available GWAS data were integrated to find methylation sites that impact metabolome through a discovery and replication scheme and by using Mendelian randomization. Results: The outcome of analyses revealed 107 methylation sites associated with 84 metabolites at the genome-wide significance level (p<5e^-8) at both the discovery and replication stages. A large percentage of the observed associations (85%) were with lipids, significantly higher than expected (p = 0.0003). A number of CpG (methylation) sites showed specificity e.g., cg20133200 within PFKP was associated with glucose only and cg10760299 within GATM impacted the level of creatinine; in contrast, there were sites associated with numerous metabolites e.g., cg20102877 on the 2p23.3 region was associated with 39 metabolites. Integrating transcriptome data enabled identifying genes (N = 82) mediating the impact of methylation sites on the metabolome and cardiometabolic traits. For example, PABPC4 mediated the impact of cg15123755-HDL on type-2 diabetes. KCNK7 mediated the impact of cg21033440-lipids on hypertension. POC5, ILRUN, FDFT1, and NEIL2 mediated the impact of CpG sites on obesity through metabolic pathways. Conclusion: This study provides a catalog of DNA methylation sites that regulate the metabolome for downstream applications.