Background
Chronic kidney disease (CKD) is an emerging major global public health problem, due to its increasing prevalence, poor outcomes, and substantial cost of renal replacement therapy [
1]. CKD has multiple risk factors. Some risk factors for CKD, especially hypertension and diabetes, are well established; others are emerging, and yet others are unknown [
2]. Thus, identification and treatment of modifiable risk factors remain the best strategy to prevent and delay CKD development.
Dyslipidaemia, including increased total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and decreased high-density lipoprotein cholesterol (HDL-C) are risk factors for cardiovascular disease (CVD) [
3‐
9]. Data from several clinical trials have confirmed that treatment with a statin, which lowers LDL-C, substantially reduces the incidence of CVD [
10,
11]. However, the association of these different lipids with the development of renal dysfunction remains controversial. Some observational studies have demonstrated a significant association between TC [
12], TG [
13], LDL-C [
12], and HDL-C [
14] and the development of CKD, whereas an opposite result was observed in other studies [
15,
16]. These inconsistent findings may be attributed to reverse causality, different study populations, different adjustments, different definitions of CKD, and concurrent lipid-lowering therapy.
Given the clinical uncertainty, we sought to determine whether TC, TG, LDL-C, and HDL-C are independently associated with the onset of CKD stages 4–5 using large-scale, prospectively collected data from a general population. Also, we aimed to assess how much of the observed lipid-CKD associations are explained by the established risk factors for CKD.
Discussion
In this large cohort, nearing a million individuals, with more than 7 years median follow-up we found an independent and graded association between quarters of baseline TG and HDL-C and onset of CKD stages 4–5. The hazard ratio for the highest versus lowest quarters was 1.28 (95% CI, 1.15–1.43) for TG and the lowest versus the highest quarters was 1.27 (95% CI, 1.14–1.41) for HDL-C, after adjustment for sex, age, smoking status, IMD tenth, BMI, SBP, eGFR, prior diabetes mellitus, prior CVD, antihypertensive medication, insulin, and statin use, at baseline. Also, the pattern of the associations between the quarters of TG and HDL-C with CKD stages 4–5 appears to be consistent by pre-defined baseline subgroups, except that there was evidence of a greater effect in women than men. In addition, there was a stronger association between TG and advanced CKD in individuals with eGFR ≥60 mL/min/1.73 m2 than eGFR < 60 mL/min/1.73 m2. These findings suggest that therapeutic approaches such as fibrates that reduce TG levels and raise HDL-C levels, which were correlated in this study population, may thus reduce the risk of advanced CKD. Conversely, there was no evidence of an association between quarters of TC and LDL-C with risk of CKD stages 4–5, suggesting that lowering TC and LDL-C levels might not have an effect on the prevention of advanced CKD.
Several small studies have found that TG and/or HDL-C levels are associated with the development and/or progression of CKD [
13,
22‐
25]. A systematic review and meta-analysis of longitudinal studies including 30,146 individuals with metabolic syndrome reported that elevated TG and low HDL-C are associated with the development of CKD (eGFR < 60 mL/min per 1.73 m
2) [
22]. Another study found that a higher TG:HDL-C ratio is an independent risk factor for the incidence and progression of CKD [
26]. Similarly, a study in 12,549 hypertensive individuals of the China Stroke Primary Prevention Trial (CSPPT) showed that higher TG and TG:HDL-C ratio are independent predictors for rapid renal function decline (eGFR ≥5 mL/min/1.73m
2 per year) [
27]. A study in 12,728 individuals of the Atherosclerosis Risk in Communities (ARIC) cohort showed that high TG and low HDL-C levels are associated with a higher risk of renal dysfunction (serum creatinine ≥0.4 mg/dL) [
23]. A study on 15,362 individuals with a baseline eGFR ≥60 mL/min/1.73m
2 attending Italian diabetes centers, showed that high TG and low HDL-C levels are independent risk factors for the development of diabetic kidney disease [
28]. In a community-based, longitudinal cohort study of 2585 individuals, the HDL-C level predicted the development of new-onset kidney disease [
24]. In 17,375 individuals of the general Viennese population, lower HDL-C was a predictor of the development of renal dysfunction [
25]. In a 2-sample Mendelian randomization study, higher HDL-C was causally related with higher eGFR and lower odds of eGFR < 60 ml/min/1.73 m
2 per year [
14]. A large study in 1,943,682 US veterans with an average eGFR of 74.85 mL/min/1.73 m
2 showed a U-shaped association between HDL-C levels and renal outcomes [
29]. A
post-hoc analysis of 4326 individuals found that TG levels significantly (
P value < 0.05) predict the development of proteinuria in both men and women [
13]. Further, an analysis of the Action in Diabetes and Vascular Disease: preterAx and diamicroN-MR Controlled Evaluation (ADVANCE) study, a cohort of 11,140 individuals with type 2 diabetes, found that HDL-C is associated with the development of microalbuminuria and macroalbuminuria [
30].
Our study, using a large primary care database, confirmed that higher TG and lower HDL-C levels are independently associated with the development of CKD stages 4–5. It is possible that the cholesterol content of triglyceride-rich lipoproteins and low HDL-C levels may lead to inflammation, foam cell formation, atherosclerotic plaques, and ultimately CVD and renal damage [
4,
7,
31,
32]. It is also possible that there is a link between low HDL-C, reduced glucose metabolism, and risk of diabetes mellitus [
33]. Furthermore, estrogen may have a negative impact on triglycerides contributing to damage to renal structure and function in females [
34]. In our study we found a significant interaction by sex, indicating a differential effect of TG and HDL-C in females versus males.
The strengths of our study are the large sample size, long follow-up, well-defined outcome, and subgroup analysis. Additionally, this study compared the magnitude of the risk of CKD stages 4–5 by each component of lipids separately, which might help adopt the best approach for identifying individuals at risk of developing advanced CKD. Furthermore, we omitted the initial 2 years of follow-up from the analysis because underlying diseases might impact negatively on lipid levels, and the observed association between lipid levels and CKD stages 4–5 may be driven by the causal link between the underlying disease stage and a subsequent outcome event. We also acknowledge that this study has limitations. First, a single measurement of each lipid may have resulted in the misclassification of the covariates and the outcome. While non-differential misclassification often results in a bias toward the null, this is not always the case. Second, the completeness of data was another limitation. In our study, 27.5% of individuals had missing TG measurements, 44.5% individuals had missing LDL-C measurements, and 28.6% individuals had missing HDL-C measurements. The decisions to perform cholesterol tests may have been related to confounding by indication if laboratory tests were ordered when individuals presented with illness. Accordingly, individuals with non-measured cholesterol values might differ from those with values recorded. Third, although major risk factors and the issue of reverse causality have been considered, as with any epidemiological study, there are possibilities that residual confounding and selection bias might still exist. Finally, the inclusion of proteinuria would have been helpful as extra confirmation of renal dysfunction, however, it was only available in a small proportion of individuals, so, unfortunately, it was not included in our CKD definition.
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