Medeea Badii (1,2), Zhaoli Liu (3), Orsolya Gaal (1,2), Georgiana Cabău (1), Valentin Nica (1), Ancuta R. Straton (1), Ioana Hotea (4), Hint Consortium, Cristina Pamfil (4), Simona Rednic (4), Radu A Popp (1), Cheng-Jian Xu (6, Tania O Crişan (1,2), Leo A B Joosten (1,2)
Affiliation(s):
1 Department Of Medical Genetics, Iuliu Hațieganu University Of Medicine And Pharmacy, 400349 Cluj-napoca, Romania.
2 Department Of Internal Medicine And Radboud Institute For Molecular Life Sciences (rimls), Radboud University Medical Centre, 6525ga Nijmegen, The Netherlands.
3 Centre For Individualized Infection Medicine (ciim), A Joint Venture Between Hannover Medical School And Helmholtz Centre For Infection Research, 30625 Hannover, Germany.
4 Department Of Rheumatology, Iuliu Hațieganu University Of Medicine And Pharmacy, 400006 Cluj-napoca, Romania.
4 Centre For Individualized Infection Medicine (ciim), A Joint Venture Between Hannover Medical School And Helmholtz Centre For Infection Research, 30625 Hannover, Germany.
5 Department Of Rheumatology, Iuliu Hațieganu University Of Medicine And Pharmacy, 400006 Cluj-napoca, Romania.
6 Centre For Individualized Infection Medicine (ciim), A Joint Venture Between Hannover Medical School And Helmholtz Centre For Infection Research, 30625 Hannover, Germany.
Objective: Hyperuricemia is a metabolic disorder that plays a key role in the onset of gout. This study aims to expand on the exploration of DNA methylation patterns in whole blood samples from individuals with hyperuricemia and normouricemia, building on existing knowledge that elevated uric acid concentrations can have pro-inflammatory effects and influence the epigenetic landscape in myeloid cells.
Methodology: DNA methylation patterns were analyzed using the EPICv2 array in two groups: 149 normouricemic controls and 119 individuals with asymptomatic hyperuricemia. The control group comprised 106 women and 43 men, with ages ranging from 36 to 82 years (median age 62). The hyperuricemic group comprised 75 women and 44 men, with ages ranging from 27 to 87 years (median age 64). The age difference between the groups was not statistically significant. Uric acid levels averaged 4.96 mg/dL in the control group (range 2.6–6.99 mg/dL) and 8.35 mg/dL in the hyperuricemic group (range 7–13.9 mg/dL). The association analysis was performed with limma, including age and sex as covariates. Differential methylated regions (DMRs), which cover at least 2 CpGs, were examined using DRMcate.
Results: Principal component analysis (PCA), focusing on the top 10% most variable probes, showed the most variation on PC1 (24,7 %) with a clear distinction of the two groups. The analysis of differentially methylated probes (DMPs) revealed numerous hypo- and hypermethylated CpG in samples from hyperuricemic individuals compared to controls. Gene Ontology (GO) enrichment analysis for differentially methylated regions (DMRs) identified various biological processes impacted by changes in DNA methylation. Significant enriched processes identified include terms involved in cell signaling and transport, neuronal development, and lymphocyte differentiation.
Conclusion: DNA methylation and pathway analysis identified significant DMRs with roles in cellular and regulatory pathways, with implications for understanding the biological impact of methylation changes in hyperuricemia. These findings coincide with terms from previous report examining the epigenetic signatures related to circulating urate levels and their increase following BCG vaccination. Further analysis employing adjusted models and cell composition correction is necessary to extend and validate these findings.