GRAPHICAL ABSTRACT

Highlights

• A nationwide cohort revealed a link between remnant-C and ESRD risk in T2DM.

• Elevated remnant-C was independently associated with increased ESRD risk in T2DM.

• Highest remnant-C quartile showed a 1.33-fold higher ESRD risk than lowest quartile.

• The association was stronger in high-risk groups (HTN, CKD, obesity, long T2DM).

• Remnant-C may serve as an independent predictor of ESRD in patients with T2DM.

INTRODUCTION

Over recent decades, the prevalence of type 2 diabetes mellitus (T2DM) has increased significantly worldwide, and nearly 700 million people globally are predicted to have the disease by 2045 [1]. T2DM can cause damage to the kidneys and other major organs. End-stage renal disease (ESRD) is the most devastating outcome, requiring a kidney transplant or renal replacement therapy (RRT) for the patient to survive [2], and greatly increases the risk of death from T2DM. Even with optimal glucose and blood pressure control, and the use of some renoprotective agents such as sodium-glucose cotransporters, individuals with T2DM still face a significant risk of developing ESRD [1]. Therefore, it is crucial to investigate the undiscovered residual risk factors that influence the onset and progression of ESRD in people with T2DM.

Among various lipid indicators, remnant cholesterol (remnant-C), which is the cholesterol content carried by triglyceride (TG)-rich lipoproteins [3], has recently received increasing attention because of the impact on various health outcomes. A growing body of evidence suggests that the high levels of remnant-C in the blood produce low-grade inflammation and increases the risk of various vascular disease such as cardiovascular disease, cerebrovascular disease [4-7]. In addition, high levels of remnant-C are more common in people with diabetes than in those without diabetes [8].

Dyslipidemia has been considered a risk factor for the progression of renal disease in patient with chronic kidney disease (CKD), and hypertriglyceridemia is one the most common features of dyslipidemia in patients with CKD [9-11]. However, minimal evidence is available on the association between remnant-C and ESRD in patients with T2DM. Therefore, this study aimed to investigate whether remnant-C levels are associated with the risk of developing ESRD in patients with T2DM. To address this issue, we used large-scale longitudinal data from a nationally representative sample in Korea.

METHODS

Data sources and study population

Data were obtained from the Korean National Health Insurance Service (NHIS), a government-affiliated organization in South Korea responsible for the administration of the National Health Insurance program. This program provides universal health coverage to approximately 97% of the Korean residents. The NHIS database has been described in detail in previous study [12,13].

Patients with T2DM who underwent a health examination from 2009 to 2012 (n=2,746,079) were excluded if they were aged <20 years (n=441), had ESRD before the index year (n= 10,016), or had missing data (n=172,791). To eliminate potential biases caused by pre-existing conditions and to minimize the possible effects of ‘reverse causation,’ participants who developed ESRD within 1 year after the baseline measurements (n=25,682) were not included in this study. Finally, 2,537,149 individuals were included and were divided according to remnant-C quartiles (Supplementary Fig. 1). Participants were followed up until the onset of ESRD or until December 31, 2020, whichever occurred first. This study protocol was approved by the Institutional Review Board of Hallym University College of Medicine (IRB No. HALLYM 2021-08-002), and was conducted in accordance with the tenets of the Declaration of Helsinki. The requirements for informed written consent were waived because anonymous and de-identified data were used according to the confidential guidelines of the NHIS of Korea.

Data collection and remnant cholesterol measurements

All blood samples were obtained at the health examination after the participant had fasted for at least 8 hours to measure lipid profiles and glucose levels. Lipid concentrations, including total cholesterol, low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDL-C), and TG were determined through enzymatic assays. The Korean Association of Laboratory Quality Control’s protocols were employed to ensure the quality control of the laboratory examinations.

To address the constraints of the Friedewald formula, which uses a fixed ratio of TG to cholesterol to estimate very LDL-C (VLDL-C), we used the Martin-Hopkins method for assessing LDL-C levels [14]. This method applies an individualized TG/VLDL-C ratio for each patient and obtains LDL-C levels based on direct measurements of total cholesterol, HDL-C, and TG levels [14]. Remnant-C levels were estimated using the well-validated formula: Remnant-C=total cholesterol–LDL-C–HDL-C [15].

Study outcomes

The primary outcome was the incidence of ESRD per participant. Newly diagnosed ESRD was defined by the combination of an International Classification of Diseases, 10th Revision (ICD-10) code (N18-19, Z49, Z94.0, and Z99.2) and a special exemption codes for RRT (V001 for hemodialysis, V003 for peritoneal dialysis, and V005 for kidney transplantation) [16,17].

Covariates

Detailed information on the demographics and lifestyles of the participants were collected through standardized self-reporting questionnaires. Low income was defined as the lowest quintile of the entire population. Smoking status was divided into a nonsmoker, ex-smoker, or current smoker. Alcoholic drinking was categorized as none, mild, and heavy (0, <30, and ≥30 g/day, respectively). Regular exercise was defined as physical activity of vigorous-intensity ≥3 times per week or moderate-intensity ≥5 times per week.

T2DM was defined either via ICD-10 codes E11–14 and at least one prescription of antidiabetic medications or fasting plasma glucose (FPG) levels ≥126 mg/dL [8]. Hypertension was defined according to the presence of at least one claim per year under ICD-10 codes I10–I15 and at least one claim per year for the prescription of antihypertensive agents or systolic/diastolic blood pressure ≥140/90 mm Hg [8]. Dyslipidemia was defined by total cholesterol level ≥240 mg/dL or at least one claim per year for lipid-lowering medication under ICD-10 code E78 [18]. Statin or fibrate users were defined as people who had been prescribed those medications at baseline. Obesity was defined as body mass index (BMI) ≥25 kg/m² based on the Asia-Pacific criteria of the World Health Organization guidelines [19]. In this study, the estimated glomerular filtration rate (eGFR) was calculated using both the abbreviated Modification of Diet in Renal Disease (MDRD) formula [20] and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [20], and CKD was defined as an eGFR <60 mL/min/1.73 m² [21].

Statistical analysis

The baseline characteristics were assessed according to remnant-C quartile and the presence of ESRD. The results were described as means and standard deviations or as medians and interquartile ranges for continuous variables and as numbers (%) for categorical variables. Continuous variables were compared using t-test or one-way analysis of variance, while categorical variables were compared using the chi-square test. Incidence rates were expressed as the number of events per 1,000 person-years. The Kaplan–Meier method and log-rank tests were used to compare the cumulative incidence of ESRD among remnant-C quartile groups. Multivariate Cox proportional hazards regression was used to calculate hazard ratio (HRs) with corresponding 95% confidence interval (CIs) for the development of ESRD in each group. Model 1 was adjusted for age and sex. Model 2 was additionally adjusted for BMI, income, smoking status, alcohol consumption, regular exercise, hypertension, eGFR, and the use of antihyperlipidemic agents (statin and fibrate). Model 3 was additionally adjusted for FPG, antidiabetic medications, total cholesterol, and TG. A restricted cubic spline transformation of remnant-C was used to evaluate nonlinear associations between remnant-C and the risk of ESRD. To evaluate the robustness of the influence of clinical conditions on the association between glycaemic status, cardiovascular, and mortality, we conducted Cox regression analyses to examine the HRs within various subgroups, including P values for interactions. Subgroup analyses stratified by age (<65 and ≥65 years), sex (male and female), BMI (<25 and ≥25 kg/m²), and comorbidities (the presence or absence of hypertension) were conducted. Statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) and R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided P value <0.05 was considered statistically significant.

RESULTS

Baseline characteristics of study participants

The baseline characteristics of the study participants according to remnant-C quartiles are presented in Table 1. Participants in the higher remnant-C quartiles were younger, more likely to be men, and had higher BMI, waist circumference, systolic and diastolic blood pressure, and FPG compared to the same parameters among participants in lower remnant-C quartiles. These participants also had higher levels of total cholesterol, HDL-C, and TG, whereas their LDL-C levels were lower. Furthermore, the proportions of current smokers and heavy drinkers in higher remnant-C quartiles were higher, while the proportion of individuals engaging in regular exercise was lower. Hypertension, dyslipidemia, and CKD were more prevalent in participants with higher remnant-C quartiles. The prevalence of users of statins, fibrate, and antidiabetic medications differed between the groups.

Risk for incident ESRD according to quartiles of remnant-C levels

Among 2,537,149 participants with complete follow-up data, 26,246 individuals (1.03% of the total population) developed ESRD during the median follow-up period of 10.3 years (interquartile range, 10.1 to 10.6). The cumulative incidence of ESRD according to quartiles of remnant-C was estimated using the Kaplan–Meier curve (Fig. 1). Participants in the upper quartiles of the remnant-C had a significantly higher cumulative incidence of ESRD than those of participants in the lowest quartiles of the remnant-C (log-rank test, P<0.0001).

The risk of incident ESRD according to remnant-C levels is shown in Table 2. The risk of ESRD increased 20% (HR, 1.20; 95% CI, 1.15 to 1.26) per every 10 mg/dL increase in remnant-C. When categorized by age groups, a 10 mg/dL increase in remnant-C was associated with an increase in the risk of ESRD of 14%, 22%, and 22% in participants aged 20–39 years (HR, 1.14; 95% CI, 1.08 to 1.21), 40–64 years (HR, 1.22; 95% CI, 1.16 to 1.28), and 65 years and older (HR, 1.22; 95% CI, 1.16 to 1.28), respectively.

Analyzing remnant-C as a continuous variable, a cubic spline graph depicted a dose-response relationship with remnant-C and the incidence of ESRD, characterized by a positive but nonlinear association. As remnant-C levels increased, the HR concomitantly increased for ESRD; however, this upward trend plateaued at the highest levels of remnant-C (Fig. 2).

In multivariate analyses, the risk of ESRD increased gradually with higher quartiles of remnant-C levels (Table 3). The risk of ESRD significantly increased in the highest quartile group of remnant-C (Q4), with a HR of 1.33 (95% CI, 1.26 to 1.41), followed by the third quartile (Q3) with a HR of 1.20 (95% CI, 1.15 to 1.24), and the second quartile (Q2) with a HR of 1.12 (95% CI, 1.08 to 1.17), compared with that in lowest quartile group (Q1), after adjusting for age, sex, BMI, current smoking, heavy drinking, regular exercise, low income, hypertension, eGFR, statin use, fibrate use, FPG, antidiabetic medications, total cholesterol, and TG. The risk of ESRD associated with higher quartiles of remnant-C was found to be increased in participants aged 65 years and older (Q4 vs. Q1: HR, 1.30; 95% CI, 1.21 to 1.39) and in those aged 40‒64 years (Q4 vs. Q1: HR, 1.39; 95% CI, 1.30 to 1.48), whereas this increase was not statistically significant in the 20‒39 years age group.

Risk for incident ESRD according to quartiles of remnant-C levels in subgroups

Subgroup analyses were performed, categorizing participants based on sex, existing comorbidities including hypertension, CKD, and obesity, and their usage of statin and fibrate (Supplementary Table 1). The positive association between elevated levels of remnant-C and incident ESRD remained consistent in all subgroups; however, an interaction existed between subgroups. Notably, the increment in ESRD risk in the highest quartiles of remnant-C was slightly more pronounced in women and those with comorbidities (hypertension, CKD, and obesity) in an all-adjusted model. Moreover, the risk of ESRD based on the remnant-C quartiles showed a significant interaction with the use of statin, with a higher risk of ESRD in participants with higher remnant-C quartiles who were taking statins, compared to that observed in those not taking statins (P for interaction <0.0001). Conversely, no modification of effects was observed in relation to use of fibrate (P for interaction=0.6118) and ezetimibe (P for interaction=0.558).

Next, we performed a subgroup analysis stratified by eGFR levels and the severity of proteinuria (Supplementary Table 2). Among eGFR subgroups, the association between elevated remnant-C and ESRD risk was most evident in patients with an eGFR of 45–59 mL/min/1.73 m², followed by those with an eGFR of 30–44 mL/min/1.73 m², where the association remained significant. In contrast, for patients with an eGFR below 30 mL/min/1.73 m², the relationship between remnant-C and ESRD risk was not statistically significant. When stratified by proteinuria status, the ESRD risk associated with remnant-C was notably higher in patients with positive proteinuria compared to those with negative or trace proteinuria levels.

Subsequently, we conducted subgroup analyses considering various factors relevant to diabetes management, such as the duration of diabetes, the types of antidiabetic medications used, and the numbers of oral antidiabetic drugs used (Supplementary Table 3). The elevated risk of ESRD associated with higher remnant-C quartiles was significantly higher in participants with a diabetes duration of more than 5 years compared to that associated with those of less than 5 years, in individuals using antidiabetic medications compared with the risks observed in nonusers, and in individuals taking more than three oral antidiabetic drugs compared with those taking fewer than three (P for interaction <0.0001).

Sensitivity analysis

We excluded individuals who developed outcomes within the first 4 years of baseline to minimize the potential effects of reverse causality (Supplementary Table 4). Consistent with the main analyses, individuals with highest remnant-C quartile exhibited a significantly increased risk of ESRD compared to those in the lowest quartile (Q4 vs. Q1: HR, 1.32; 95% CI, 1.23 to 1.41). The risk of ESRD associated with higher quartiles of remnant-C was notably increased in participants aged 65 years and older (Q4 vs. Q1: HR, 1.35; 95% CI, 1.25 to 1.47) as well as in those aged 40‒64 years (Q4 vs. Q1: HR, 1.33; 95% CI, 1.23 to 1.44), whereas this association was not statistically significant in individuals aged 20‒39 years.

DISCUSSION

This study of 2,537,149 individuals with up to 10.3 years of follow-up consistently showed a positive association of remnant-C levels with the risk of developing ESRD in patients with T2DM. The highest versus lowest quartile of remnant-C was associated with a 33% higher risk of developing ESRD even after adjusting for various traditional risk factors for renal dysfunction. Furthermore, stratified analysis shows that higher remnant-C levels were associated with a higher risk of developing ESRD, regardless of age, sex, presence of pre-existing comorbidities, and use of anti-dyslipidemic agents. This result confirms that remnant-C has emerged as a possible contributor to the development of various vascular diseases, including microvascular disease, particularly in patients with diabetes.

Dyslipidemia has been considered a risk factor for the progression of renal disease in patient CKD, and hypertriglyceridemia is one the most common features of dyslipidemia in patients with CKD [9-11]. Previous epidemiological and genetic studies have identified a clear causal relationship between conventional lipid profiles and the development and progression of CKD [22]. Remnant-C has been recently identified as a potential cause of various vascular diseases [3-7,23]. Thus, research is beginning to elucidate the role of remnant-C in diabetic kidney disease, which is the most common microvascular diseases in people with diabetes. A study involving 3,388 people with T2DM has shown the association between remnant-C levels and CKD [24], but this study was relatively small and cross-sectional in design; therefore, the effect of remnant-C on developing CKD could not be determined. Recently, Jansson Sigfrids et al. [25] reported that remnant-C concentrations predicted diabetic nephropathy progression; however, this study was only conducted in people with type 1 diabetes mellitus. Therefore, the role of remnant-C in the pathogenesis and development of diabetic kidney disease in patients with T2DM remains unclear until now. Furthermore, the role of remnant-C in the development of ESRD, the most serious and severe form of diabetic kidney disease, has never been investigated in T2DM. Therefore, our study is the first study to show the association between remnant-C levels and risk of developing ESRD in people with T2DM.

In the present study, we clearly showed that an incrementally higher risk of developing ESRD was observed with higher remnant-C quartiles compared with that in the lowest quartile group in all-adjusted models. Moreover, the strong association between elevated levels of remnant-C and the risk of developing ESRD remained consistent across all subgroups. A subgroup analysis based on the characteristics of the study participants revealed interesting findings, with interactions between groups evident in several subgroups. In people with individual comorbidities, who were at a high risk for renal dysfunction at baseline (e.g., had hypertension, CKD, obesity, longer duration of diabetes, or were taking antidiabetic medication), the association between high levels of remnant-C and incident ESRD was more pronounced compared with that in those without comorbidities. Thus, higher remnant-C concentrations may be harmful to the kidneys, particularly in people who are at high risk of kidney disease to begin with. Therefore, more aggressive management of remnant-C levels should be considered to prevent ESRD in this population. Similarly, the association between high levels of remnant-C and incident ESRD was much stronger in people already using statin than in those not using statin. These findings suggest the need to specifically investigate the optimal remnant-C level to prevent renal deterioration based on patient characteristics.

The association between remnant-C and the pathological development of ESRD is not yet fully understood. However, several potential mechanisms could partially explain the results of the present study. One possible reason for this association may be that elevated remnant-C causes low-grade inflammation and endothelial dysfunction, which is an important pathogenesis of diabetic kidney disease [26]. Simialr to LDL-C, remnant-C can pass through the arterial wall and be internalized by macrophages, leading to foam cell formation and the development of atherosclerosis. Remnant-C can induce low-grade inflammation even more strongly than LDL-C can, as remnant lipoproteins can be easily assimilated by macrophages in the intima without the necessity of modifications such as oxidation or glycation. Varbo et al. [27] identified a direct correlation between remnant-C and low-grade systemic inflammation manifested as high levels of C-reactive protein. Another explanation could be the oxidative stress induced by remnant-C [28]. Oxidative stress, which plays a role in the development and progression of diabetic nephropathy, can cause cellular damage in the kidneys, ultimately contributing to ESRD. Additionally, insulin resistance and dysglycemia may influence remnant-C concentrations and functions by affecting the overall metabolism of TG-rich lipoproteins [29]. Consequently, patients with T2DM have higher remnant-C levels than those without diabetes, and both remnant-C itself and the accompanying insulin resistance may lead to renal deterioration.

The strength of our study is that it analyzed data from a large prospective cohort comprising people with T2DM, which more firmly establishes the involvement of remnant-C in the development of ESRD. However, several limitations were also present. First, the study population comprised a single ethnicity, so out results should be extrapolated to other ethnicities and should be performed with caution. Second, remnant-C levels were calculated rather than measured directly. However, calculation of remnant-C levels is more affordable and useful in clinical practice than direct measurement. Additionally, the European Atherosclerosis Society recently suggested using the measured remnant-C levels, which is commonly used in population studies and has a strong correlation with the directly measured concentrations [30]. Third, we used self-reporting or medical records to collect data on ESRD events and confounders, such as lifestyle factors. Consequently, differences between the conclusions drawn by physicians and those documented in claims data might have influenced our results.

In conclusion, this nationwide population-based longitudinal cohort study demonstrated that an elevated remnant-C level was associated with higher risks of ESRD, independent of traditional risk factors for renal dysfuction in people with T2DM. The positive association between remnant-C and ESRD was more pronounced in high-risk groups such as hypertension, CKD, obesity, and long-duration of diabetes. Our results may have implications for risk prediction and prevention of ESRD in people with T2DM. Further research is warranted to validate our study findings based on observational data.

SUPPLEMENTARY MATERIALS

NOTES

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Conception or design: E.R., J.H.H., K.D.H., J.G.K.

Acquisition, analysis, or interpretation of data: E.R., J.H.H., K.D.H., J.G.K.

Drafting the work or revising: all authors.

Final approval of the manuscript: all authors.

FUNDING

This research was supported by the Hallym University Research Fund, 2022 (HURF-2022-52).

ACKNOWLEDGMENTS

This work was performed in cooperation with the National Health Insurance Service (NHIS). The National Health Information Database constructed by the NHIS was used, and the results do not necessarily represent the opinion of the National Health Insurance Corporation.

Fig. 1.

Kaplan–Meier estimates of cumulative incidence of newly developed end-stage renal disease based on quartiles of remnant cholesterol (remnant-C) levels. Q, quartiles.

Fig. 2.

Restricted cubic spline modes for incident end-stage renal disease according to remnant cholesterol (remnant-C) levels. Adjusted for age, sex, body mass index, current smoking, heavy drinking status, regular exercise, low income, hypertension, estimated glomerular filtration rate, statin use, fibrate use, fasting blood glucose, antidiabetic medications, total cholesterol, and triglyceride. HR, hazard ratio; CI, confidence interval.

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Roh E, Heo JH, Jung HN, Han KD, Kang JG, Lee SJ, Ihm SH. Impact of Remnant Cholesterol on the Risk for End-Stage Renal Disease in Type 2 Diabetes Mellitus: A Nationwide Population-Based Cohort Study. Diabetes Metab J. 2025 May 21. doi: 10.4093/dmj.2024.0406. Epub ahead of print.

Received: Jul 21, 2024; Accepted: Jan 23, 2025

DOI: https://doi.org/10.4093/dmj.2024.0406.

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