To the Editor:
The functional characteristic of HDL particles to remove cholesterol from peripheral cells—cholesterol efflux capacity (CEC)—associates inversely with cardiovascular disease (CVD), independent of HDL cholesterol (HDL-C) (1). In addition to increased cardiometabolic risk, low HDL-CEC appears to be distinctive for kidney disease, including prediction of graft failure in renal transplant recipients (2). Thus, there appears to be a link between CEC and kidney function, but no previous study has looked at whether HDL-CEC was associated with incident kidney disease. The paucity of large-scale epidemiology in this area is likely owing to the complexity and cost of cellular HDL-CEC assays (1).
We analyzed HDL-CEC, 4 HDL subclass particle concentrations, standard lipoprotein lipids, apolipoprotein A-I, and creatinine by a serum nuclear magnetic resonance platform (1, 3). Two large Finnish population-based prospective cohorts were studied: DILGOM2007 (n = 4739, 47% men; median [interquartile range] for age: 54 years [42–64 years]; HDL-CEC: 20.4% [19.4%–21.8%]; and HDL-C: 1.4 mmol/L [1.2–1.7 mmol/L]) and FINRISK1997 (n = 7471, 50% men; median [interquartile range] for age: 48 years [37–59 years]; HDL-CEC: 21.8% [20.7%–23.4%]; HDL-C: 1.5 mmol/L [1.3–1.8 mmol/L]), with follow-up times of 8 and 15 years, respectively. The studies were approved by the Coordinating Ethical Committee of Helsinki and Uusimaa Hospital District, and written informed consent was obtained from all participants. The HDL-CEC values correspond to the most commonly used assay to quantify HDL-CEC, namely, the use of cAMP-treated J774 murine macrophages with radiolabeled cholesterol (1).
The HDL subclasses were defined by particle size: very large (mean diameter: 14.3 nm), large (12.1 nm), medium (10.9 nm), and small HDL (8.7 nm) (3). The association of HDL-CEC was investigated with incident kidney disease, including chronic and unspecific kidney disease (International Classification of Diseases, 10th Revision: N18–N19; Ninth Revision: 585; Eighth Revision: 58200) in comparison to other HDL-related biomarkers. Outliers for each measure were defined as values that were >4 times the interquartile range below the 25th and above the 75th percentile. For HDL-CEC, 212 outliers were detected (1.3%). To study the associations of HDL-CEC and other HDL-related measures with the incident events, participants with prevalent kidney disease (n = 16), outliers, and missing data (n = 261) were excluded before analyses, leaving complete data for 12 210 participants and 61 incident kidney disease events. Thereafter, data were analyzed by Cox proportional hazards regression models in each cohort, and the results were combined by inverse variance-weighted fixed-effects meta-analysis. Glomerular filtration rates were estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula in the R software package nephron. All statistical analyses were undertaken in R v4.0.2.
The Cox regression results for the associations of HDL-CEC and the various HDL-related concentration measures with incident kidney disease are illustrated in Fig. 1. Age- and sex-adjusted HDL-CEC was associated inversely with incident kidney disease (hazard ratio: 0.72 [95% CI, 0.57–0.92]; P = 0.009), and adjusting for traditional risk factors and HDL-C did not affect the association (hazard ratio: 0.74 [95% CI, 0.56–0.97]; P = 0.031). In contrast, none of the HDL-related concentration measures were clearly associated with incident kidney disease after corresponding adjustments (instead of HDL-C, the HDL-related concentration measures were adjusted for HDL-CEC). Adjusting for inflammation markers, C-reactive protein and glycoprotein acetyls—either alone or together—did not notably affect any association.
Association of HDL-CEC, HDL-C, apolipoprotein A-I (ApoA-1), total HDL, very large HDL (XL-HDL), large HDL (L-HDL), medium HDL (M-HDL), and small HDL (S-HDL) concentration measures with incident kidney disease. Hazard ratios are per 1-SD HDL-measure. Traditional risk factors (TRFs) included age, sex, log body mass index, smoking, geographical region, diabetes, mean arterial pressure, estimated glomerular filtration rate, lipid treatment, blood pressure treatment, and serum concentrations of LDL cholesterol and log triglycerides. In the right panel, HDL-CEC was adjusted for TRF + HDL-C and the other HDL-related measures for TRF + HDL-CEC. Total HDL refers to the sum of all 4 HDL subclass particle concentrations. Open and closed black diamonds indicate P ≥ 0.05 and P < 0.05, respectively.
The current findings add to the accumulating evidence that HDL-CEC would be systemically beneficial, not only for CVD but also for the development of kidney disease. These findings also support the independent role of HDL functionality in disease risk assessment.
Large-scale epidemiological research regarding kidney disease is currently limited to HDL-C, and information on HDL-CEC and HDL subclasses are scarce. Recent Mendelian randomization analyses support a causal relationship between genetically higher HDL-C and better kidney function (4). However, genetic associations between estimated glomerular filtration rate and HDL-C are highly pleiotropic, advocating for the existence of multiple causal pathways, some of which might better relate to other HDL characteristics than cholesterol. The metabolic pathways that link HDL to glomerular microcirculation may, at least in part, be different from those for CVD. Clear-cut interpretations of the individual roles of various, both genetically and observationally correlating HDL measures, are thus challenging. It has also been demonstrated recently that the relative role of different HDL characteristics appears to depend on kidney function; the associations of HDL-CEC with CVD end points are not identical for individuals with and without kidney disease, in contrast to HDL particle concentrations (5).
Our current finding that better HDL functionality, in terms of cholesterol efflux, predicts lower incidence of kidney disease concurs well with the above-mentioned findings. Our findings advocate for continued attention to the functional attributes of HDL in the risk assessment of not only CVD but also kidney disease. Large-scale longitudinal studies would be needed to better understand the role of kidney status on these associations.
Author Contributions
All authors confirmed they have contributed to the intellectual content of this paper and have met the following 4 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved.
M. Perola, provision of study material or patients; V. Salomaa, administrative support; J. Kettunen, financial support; M. Ala-Korpela, financial support, provision of study material or patients.
Authors’ Disclosures or Potential Conflicts of Interest
Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:
Employment or Leadership
A.J. Kangas, Nightingale Health Ltd.
Consultant or Advisory Role
None declared.
Stock Ownership
A.J. Kangas, Nightingale Health Ltd.
Honoraria
None declared.
Research Funding
None declared.
Expert Testimony
None declared.
Patents
None declared.
