Gender-specific assessment of lipid profiles correlation with serum uric acid in non-dialysis chronic kidney disease patients: prospective observational cross-sectional study

Background Serum uric acid (SUA) serves as an important marker for assessing kidney function in chronic kidney disease (CKD) patients. Emerging reports suggest a potential relationship between SUA and dyslipidemia. The study aims to examine the correlation between SUA and lipid profiles in CKD population. Method We conducted a multicenter, prospective observational cross-sectional study, enrolled n=374 stages 1/4 CKD participants were stratified by gender into (n=210 males and n=164 females). Using a multistage stratified sampling method based on age and SUA to examine the differences among groups, Spearman’s correlation and linear regression analysis were utilized to study the association between SUA and lipid profiles, and multivariate analysis to determine the effect of SUA quartiles on multiple dependent variables collectively. Results LDL-c was positively correlated with SUA levels, with Spearman’s correlation coefficients of R=0.3553 in males and 0.5137 in females (both with P<0.0001). TG also showed a positive correlation, with coefficients R=0.1797 in males and 0.5115 in females ( P<0.0091 and P<0.0001 , respectively). Similarly, TC showed a positive correlation R=0.2979 in males and 0.2741 in females ( P<0.0001 and P<0.0004 , respectively), while HDL-c showed an inverse correlation with SUA correlation coefficients R=-0.3445 in males and -0.4055 in females (both with P<0.0001 ). The age-stratified analysis indicated that LDL-c was higher in individuals aged ≥70 compared to younger groups ( P<0.002 ), while HDL-c was higher in the 20–29 age group; with ( P<0.031 ). Post-hoc univariate tests revealed significant between quartile differences for all lipid variables (all P ≤ 0.05 ). Conclusion In CKD population, SUA levels were positively associated with LDL-c, TC, and TG, while inversely associated with HDL-c. Additionally, lipid profiles were identified as significant predictors of SUA levels. Furthermore, the graded associations of SUA quartiles with lipid profiles suggest that SUA may be employed as a biomarker of dyslipidemia risk among this population.