Association of the ratio of non-HDL-cholesterol to HDL-cholesterol with clinical and pathological characteristics in diabetic kidney disease

INTRODUCTION: Diabetic kidney disease (DKD) is a severe complication of diabetes (DM), and dyslipidemia has a vital role in its progression. It is necessary to identify lipid-related biomarkers related to disease severity and prognosis in DKD to facilitate early risk stratification and prevent progression to advanced renal disease. The non-high-density lipoprotein cholesterol (non-HDL-C) to HDL-C ratio (NHHR), an emerging composite lipid metric, has demonstrated potential in assessing metabolic and cardiovascular risks. This investigation was designed to examine the link between NHHR and clinicopathological characteristics, as well as renal outcomes in individuals with DKD and T2DM. METHODS: A total of 521 individuals with DKD and T2DM were retrospectively enrolled. Demographic, laboratory, and renal outcomes data were collected. Renal histopathology was assessed in 208 individuals with biopsy-proven DKD. Linear, ordinal logistic and Cox regression analyses were utilized to assess the link between NHHR and clinicopathological parameters and the risk of end-stage kidney disease (ESKD), respectively. Nested models were utilized to compare the prognostic value of NHHR against conventional lipid parameters. RESULTS: Higher NHHR levels were significantly associated with poorer glycemic control, advanced glomerular lesions, and a higher risk of progressing to ESKD. Multivariable Cox regression analysis considered NHHR as an independent indicator of progressing to ESKD after the adjustment for conventional risk factors. Furthermore, the nested model analysis demonstrated better prognostic value of NHHR compared with conventional lipid parameters. Subgroup analysis illustrated that high NHHR was significantly related to high ESKD risk across subgroups, such as varied ages, sexes, BMI classifications, and in patients with established renal dysfunction or albuminuria. CONCLUSION: NHHR could act as a potential biomarker for risk stratification in DKD and predicting renal outcomes, meriting prospective validation for clinical implementation.