Comprehensive assessment of the combined impact of dyslipidemia and inflammation on chronic kidney disease development: A prospective cohort study.

BACKGROUND

There remains a limited comprehensive understanding of how dyslipidemia and chronic inflammation collectively contribute to the development of chronic kidney disease (CKD).

OBJECTIVE

We aimed to identify clusters of individuals with five variables, including lipid profiles and C-reactive protein (CRP) levels, and to assess whether the clusters were associated with incident CKD risk.

METHODS

We used the Korean Genome and Epidemiology Study-Ansan and Ansung data. K-means clustering analysis was performed to identify distinct clusters based on total cholesterol, triglyceride, non-high-density lipoprotein (HDL)-C, HDL-C, and CRP levels. Cox proportional hazards models were used to examine the association between incident CKD risk and the different clusters.

RESULTS

During the mean 10-year follow-up period, CKD developed in 1,645 participants (690 men and 955 women) among a total of 8,053 participants with a mean age of 51.8 years. Four distinct clusters were identified: C1, low cholesterol group (LC); C2, high-density lipoprotein cholesterol group (HC); C3, insulin resistance and inflammation group (IIC); and C4, dyslipidemia and inflammation group (DIC). Cluster 4 had a significantly higher risk of incident CKD compared to clusters 2 (hazard ratio (HR) 1.455 [95% confidence interval (CI) 1.234-1.715]; p < 0.001) and cluster 1 (HR 1.264 [95% CI 1.067-1.498]; p = 0.007) after adjusting for confounders. Cluster 3 had a significantly higher risk of incident CKD compared to clusters 2 and 1.

CONCLUSION

Clusters 4 and 3 had higher risk of incident CKD compared to clusters 2 and 1. The combination of dyslipidemia with inflammation or insulin resistance with inflammation appears to be pivotal in the development of incident CKD.