Soluble CD14 and Osteoprotegerin Associate with Ankle-Brachial Index as a Measure of Arterial Stiffness in Patients with Mild-to-Moderate Chronic Kidney Disease in a Five-Year Prospective Study

In patients with chronic kidney disease (CKD), both atherosclerotic and arteriosclerotic vascular lesions appear at early stages of disease and follow an accelerated course with disease progression, contributing to an excessive cardiovascular morbidity and mortality [1‒3]. Atherosclerosis eventually leads to ischemic events through luminal obstruction, while arteriosclerosis leads to vascular calcifications, arterial stiffening, and reduced tissue perfusion. Arterial stiffness is associated with a steeper decline in kidney function and has been identified as an independent predictor of all-cause and cardiovascular mortality in CKD and end-stage kidney disease (ESKD) [3]. This suggests that vascular stiffness should be considered as a target for delaying deterioration in kidney function. However, the independent link between arterial stiffness and CKD remains unknown, and there are limited prospective data on mechanisms contributing to progression of arterial stiffness in mild-to-moderate CKD (stages 2–3) (eGFR 30–60 mL/min/1.73 m²) [4‒6].

Presence of atherosclerosis and arteriosclerosis with peripheral vascular disease in CKD can be detected noninvasively by ultrasound measurement of carotid intima-media thickness (CIMT) or by determination of ankle-brachial index (ABI), respectively [7, 8]. CIMT is an inexpensive easy-to-use reliable indicator of atherosclerosis and a rise in CIMT over time increases the risk of coronary events and related mortality [9, 10]. ABI is a predictor of adverse events and mortality in the general population, but this association is not well understood in patients with CKD. Both larger annual increases and decreases in ABI have been associated with risk of mortality in patients with CKD [11, 12].

Development of atherosclerosis in CKD is a multifactorial process involving several complex etiological mechanisms, such as retention of uremic solutes, oxidative stress, increased concentrations of pro-inflammatory biomarkers, and endothelial dysfunction [13]. Abnormal bone mineral metabolism is a key promoter of arteriosclerosis, vascular calcification, and arterial stiffness in CKD [14]. Separately and in combination these disturbances contribute to deterioration in kidney function and progress of cardiovascular disease (CVD) in patients with CKD. We and others have conducted several studies on the impact of mild-to-moderate kidney dysfunction and inflammatory mediators on cardiac remodeling, carotid structure and function, and aerobic exercise capacity during a 5-year prospective follow-up of patients with CKD stages 2–3 and healthy controls [15‒21].

In the current study, we expand on these observations through application of affinity proteomics assays [22] to identify potential biomarkers for cardiorenal complications. We initially performed a literature review to shortlist potential biomarker candidates in CKD. These were subsequently categorized into five groups based on their biological and pathophysiological role in kidney and heart disease. After screening and comparison of significant proteins at baseline and 5-year follow-up of CKD patients, three proteins (soluble CD14 [cluster of differentiation 14], angiogenin [ANG], and osteoprotegerin [OPG]), engaged in both atherosclerotic and arteriosclerotic processes [23‒25], were selected as candidate proteins for further validation analysis. Our specific objective was to study their relation to CIMT and ABI in patients with CKD stages 2–3 at baseline and after 5 years of prospective follow-up.

Study participants were enrolled in the Swedish prospective cohort study, PROGRESS, previously described in detail [15‒21]. The overall objective in the PROGRESS study was to retard progression of kidney failure in patients with mild-to-moderate CKD (stages 2–3) through a multidisciplinary approach, including strict adherence to treatment recommendations in national and international guidelines from 2002 and onwards (Swedish Society of Nephrology, Kidney Disease Outcomes Quality Initiative (K/DOQI) Clinical practice guidelines 2002, Kidney Disease: Improving Global Outcomes (KDIGO 2004). Patients with CKD 2–3 were prospectively treated and observed at least twice yearly for 5 years and in parallel age- and sex-matched healthy controls underwent examinations and tests at baseline and after 5 years, but no examinations in between. There are few prospective studies focusing on cardiorenal issues in healthy controls. Patients with CKD stages 4–5 (eGFR <30 mL/min/1.73 m²) served as disease controls, representing patients with advanced CKD or ESKD, and were only examined at baseline.

In brief, 103 patients between 18 and 65 years of age were consecutively recruited from the outpatient clinic at the Department of Nephrology at the Karolinska University Hospital, Stockholm, Sweden, if they had a kidney function (based on glomerular filtration rate (GFR) measured as CKD-EPI) corresponding to CKD stages 2–3 (n = 54) (mild-to-moderate renal dysfunction) or CKD 4–5 (n = 49), as defined by the National Kidney Foundation [26] (Fig. 1). The disease controls with CKD 4–5 were included to represent clinical features and concentrations of biomarkers in patients with advanced CKD or ESKD. The CKD stages 2–3 cohort was monitored closely at the Department of Nephrology, with regular visits to nephrologists and registered nurses with early actions taken to adjust and optimize treatment of anemia, hypertension, proteinuria, hyperlipidemia, hyperphosphatemia, and vitamin D deficiency during 5 years of follow-up. Of the controls (n = 54), 31 were recruited from the Swedish Total Population Register and 23 were recruited by advertisement on the Karolinska University Hospital website. The controls underwent a written interview concerning their health history and medication to exclude any history of kidney disease, CVD, diabetes, or any ongoing medication. Exclusion criteria for all participants were known current malignancy, kidney transplantation, kidney donation, immunosuppressive therapy, or a blood-transmitted disease. The healthy controls were merely observed at Department of Nephrology at baseline and after 5 years of follow-up with clinical examination, blood pressure (BP) control, and laboratory blood and urine measurements. The ultrasound examinations of patients and healthy controls were performed at the Department of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden. The etiology of CKD in patients with CKD 2–3 was primary inactive glomerulonephritis (32%), congenital kidney diseases (26%), secondary systemic disease (17%), and unknown cause of CKD (25%).

When planning and designing the current project, we initially performed a literature review to shortlist potential biomarker candidates in CKD. This effort revealed a set of 213 proteins (online suppl. Table 1; for all online suppl. material, see https://doi.org/10.1159/000530985). These 213 proteins were then categorized into five groups (bone metabolism, cardiovascular markers, inflammatory markers, fibrosis, kidney disease marker) based on their biological and pathophysiological role through searches on The Human Protein Atlas [27] and PubMed. These proteins were used to select antibodies for the initial screening phase.

Antibodies were selected to perform protein analysis of biotinylated proteins in plasma samples, as described in detail elsewhere [28]. In short, an antibody bead array was prepared by coupling antibodies to magnetic and color-coded beads at the Science for Life Laboratory, Stockholm, Sweden. Neat plasma samples were diluted in a buffer, the proteins were labelled with biotin, and diluted in an assay buffer, and heat treated at 56°C for 30 min and cooled to room temperature prior the incubation with the beads. Labelled samples and beads were incubated overnight at room temperature under permanent shaking. The beads were then washed, and fluorescent streptavidin was added to detect biotinylated proteins that were captured by the antibodies. The beads were analyzed in a Luminex FlexMap3D cytometer to record the median levels of fluorescent per bead population. Data analysis was conducted on the bead arrays and the sandwich assay for the selected target.

After screening and comparison of significant candidate biomarkers at baseline and after a 5-year follow-up of patients with CKD 2–3 and healthy controls, three proteins (sCD14, ANG, and OPG), engaged in both atherosclerotic and arteriosclerotic processes in CKD [23‒25] were selected for further analysis and confirmation and protein quantification. The proteins were quantified using Luminex Discovery Assays (LXSAHM, R&D Systems) in accordance with the manufactures instructions and using the provided reagents. The proteins sCD14 and ANG were analyzed in one duplex assay at a 1:200 sample dilution. The protein OPG was analyzed in a separate assay at a 1:2 dilution.

ABI was assessed by duplicate resting measurements of BP in upper arms and ankles as previously described (15). Briefly, the participants were asked to lie flat on an examination table and standard arm BP was measured on the right and left upper arm after rest. Thereafter, a standard BP cuff was applied to the ankle and a Doppler stethoscope (Minidop ES-100VX, Hadeco/Hayashi Denki Co., Ltd.) was used to measure the systolic BP (SBP) in the posterior tibial or dorsalis pedis artery. The ABI was calculated as the ratio between SBP in each leg divided by the SBP in left and right arms, respectively; the lowest value of the four ratios obtained was selected. Normal ABI was defined as between >0.90 and <1.40 because of the increased risk of CVD at levels below or above this interval [29].

The ultrasound examinations were performed by two experienced sonographers, using an ultrasound machine (Sequoia 512; Siemens Medical Solutions, Mountain View, CA, USA) with an appropriate transducer as previously described [15, 19, 21]. The diameter and CIMT of the left and right common carotid artery were measured from 2D images and the average calculated M-mode recording of the right common carotid artery was obtained for measurements of the systolic and diastolic diameters, averaged from three cardiac cycles, and used for calculation of the pressure-strain elastic modulus (Ep). Resting brachial BP was measured in the right arm with a sphygmomanometer immediately before and after the M-mode recording with participants in the supine position, and the average SBP and diastolic BP were used in the equation for Ep.

We analyzed the correlation between the three selected biomarkers sCD14, ANG, and OPG and CIMT and ABI at baseline and after 5 years. In addition, changes in CIMT and ABI from baseline to 5 years were correlated to absolute levels and changes in concentrations of the biomarkers at baseline and at 5 years.

The analyses were performed comparing three groups of individuals at baseline, patients with CKD stages 2–3, patients with CKD stages 4–5, and healthy controls. After 5-year follow-up, the analyses were performed comparing two groups of individuals, patients with CKD stages 2–3 and healthy controls. All values are given as median and interquartile range. Since the values were not normally distributed in all groups, comparisons between three groups at baseline were performed using the nonparametric Kruskal-Wallis test, and comparison between two groups at 5-year follow-up with Mann-Whitney U test. Dunn’s post hoc test was applied for multiple comparisons following the Kruskal-Wallis test. Comparisons within one group at baseline and at 5 years were done using Wilcoxon matched-paired signed rank test. Spearman’s rank correlation test was applied to determine the relationship between the selected biomarkers sCD14, ANG, and OPG and CIMT and ABI. Statistical analyses were done in GraphPad Prism 8.3 (GraphPad Software, Inc., USA), STATISTICA version 10 (StatSoft, Inc., USA) and IBM SPSS Statistics 27 (IBM Corp., USA). A p value <0.05 for a two-tailed test was considered significant.

This study focuses on concentrations of the selected candidate biomarkers sCD14, ANG, and OPG in relation to CIMT and ABI in patients with CKD 2–3 and healthy controls at baseline and after 5 years of follow-up. Results from clinical examinations (CIMT and ABI) and laboratory tests in patients with CKD 2–3 and healthy controls have previously been published [21]. The number of patients included in the current proteomic study was, however, not the same as previously presented.

The baseline characteristics of all participants (CKD 2–3, CKD 4–5, and healthy controls) are shown in Table 1. The CKD groups presented with lower serum albumin, higher phosphate, and CRP compared to controls. Both SBP and diastolic BP were higher in the CKD groups compared to healthy controls. 78% of patients with CKD 2–3 were treated with an ACE inhibitor or with an angiotensin II receptor blocker (ARB).

Laboratory values in patients with CKD 2–3 (n = 48) and healthy controls (n = 44) at 5th year of follow-up are shown in Table 2 eGFR was lower than in controls, but the slope of eGFR over 5 years was similar in patients and controls as previously described [21]. Calcium and CRP were significantly elevated in patients with CKD 2–3 compared to controls, while albumin was lower.

We performed a screening of 103 patient samples and 54 healthy controls and used 322 antibodies to measure 213 selected proteins (online suppl. Table 1). Figure 2 displays a volcano plot showing differences in biomarkers between patients with CKD 4–5 and healthy controls. Of these biomarkers, 19 were statistically different in CKD 4–5 compared with healthy controls (Table 3).

Table 4 shows the changes in concentrations of candidate biomarkers in patients with CKD 2–3 and healthy controls. Changes in protein concentrations occurred both in patients with CKD 2–3 and in healthy controls during 5 years of follow-up, but they were significantly more pronounced in patients with CKD 2–3 compared to controls.

At baseline patients with CKD 2–3 had significantly lower ABI compared to healthy controls (p = 0.0002). During the 5-year follow-up, ABI increased significantly in patients with CKD (p = 0.001), but not in healthy controls, resulting in similar ABI between groups at 5 years (Table 4). CIMT was similar in patients with CKD 2–3 and healthy controls at baseline, but as CIMT increased significantly in healthy controls during follow-up (p = 0.0005) values were higher in heathy subjects than in patients with CKD 2–3 at follow-up (p = 0.03) (Table 5).

The concentrations of sCD14, ANG, and OPG at baseline are shown in Figure 3. Results are confirmative showing significantly higher concentrations in all 3 biomarkers in patients with CKD 2–3 and CKD 4–5, compared to healthy controls. Figure 4 shows differences in concentrations after 5 years of follow-up. The concentrations of sCD14 and ANG were significantly higher in patients with CKD 2–3 compared to controls, but the concentration of OPG was similar.

Table 6 shows changes in the concentrations of sCD14, ANG, and OPG from baseline to 5 years of follow-up. The concentrations were not significantly different in patients with CKD 2–3 over time, but in healthy controls the concentration of ANG decreased (p = 0.002), while OPG increased (p = 0.009). No significant correlation between changes in eGFR or CRP levels from baseline to 5 years and changes in sCD14, ANG, and OPG were observed (data not shown).

At baseline, there is a significant correlation between CIMT and OPG in patients with CKD 2–3 (r = 0.35, p = 0.01) as well as in healthy controls (r = 0.37, p = 0.01) (Fig. 5). There were no significant correlations between CIMT and concentrations of sCD14 and ANG in patients with CKD 2–3 or healthy at baseline (data not shown).

At 5-year follow-up, there were no significant correlations between CIMT and concentrations of sCD14, ANG, or OPG in patients with CKD 2–3. However, in healthy controls there was a significant correlation between OPG and CIMT at 5 years (r = 0.392, p < 0.05).

There were significant positive correlations between ABI and sCD14 (r = 0.35, p = 0.01) and between ABI and OPG (r = 0.31, p = 0.03) at 5-year follow-up in patients with CKD 2–3 (Fig. 6). No significant correlations were observed in healthy controls. Furthermore, there were no correlations between ABI and ANG in patients and controls. In addition, changes in sCD14 during follow-up correlated significantly to changes in ABI from baseline to 5 years (r = 0.41, p = 0.004) (Fig. 7).

The principal findings, in this prospective study of patients with mild-to-moderate kidney disease and healthy controls, are that the concentrations of sCD14, ANG, and OPG were higher in patients with CKD 2–3 at baseline and that concentrations of sCD14 and ANG still were higher in patients after 5 years of prospective follow-up. Furthermore, higher levels of sCD14 and OPG in patients with CKD 2–3 were significantly associated with higher ABI, a measure of arterial stiffness, at follow-up. In addition, an increase in sCD14 over time in patients with CKD 2–3 was associated with a corresponding increase in ABI from baseline to 5 years.

The design of this study includes two important features. First, patients with CKD 2–3 were closely monitored by dedicated nephrologists and nurses to align treatment with recommendations in international guidelines for treatment of patients with CKD. The goal was to study if disease progression could be retarded by a multifactorial approach. Second, an age- and sex-matched group of healthy controls was examined at baseline and after 5 years. In most previous studies, CKD patients are compared with healthy controls in a cross-sectional way, and not through prospective long-term comparisons, as in the current study.

Substantial proportions of patients with CKD carry multiple cardiovascular risk factors and accumulating evidence suggests a strong association between cardiovascular pathology, i.e., atherosclerosis and arteriosclerosis with arterial stiffness, and CKD [3‒7]. However, the precise mechanisms connecting cardiovascular diseases with kidney impairment remain to be elucidated.

ABI is a noninvasive measure of peripheral vascular disease and arterial stiffness that has been proposed as a predictor of adverse CVD events in patients with CKD [8]. In the general population, changes in ABI over time have been associated with risk of mortality, but this association is not well understood in patients with CKD. A larger annual increase in ABI was related to a higher risk of mortality in CKD patients [11]. However, also a decrease in ABI over time has been associated to worse outcomes in CKD [30]. In contrast to an ABI measured once, associations with repeated measurements of ABI over time with subsequent mortality risk have been much less explored. We have recently reported that ABI increased over time in the CKD 2–3 patients, but not in the healthy controls, which may indicate increasing arterial stiffness in the CKD 2–3 group [21]. The ABI values in our CKD patients were mostly below the upper limit of normal, which suggests that in mild-to-moderate CKD, an ABI value within the upper normal range may indicate early lesions in the arterial wall [21].

sCD14 is a circulating pattern recognition receptor that has been proposed as a cardiovascular disease risk factor [31]. Prospective studies evaluating sCD14 with occurrence of cardiovascular disease events in CKD are limited. Increased concentrations of sCD14 have been linked with progression of subclinical atherosclerosis in patients with HIV infection [32]. In patients with CKD, increased sCD14 was associated with occurrence of CVD events independent of other risk factors [23]. Furthermore, higher sCD14 has been associated with increased risk of coronary heart disease, stroke, and heart failure after adjustment for CVD risk factors in American adults, but not in European men [31, 33]. Thus, the increased concentration of sCD14 in patients with CKD 2–3, compared to healthy controls, both at baseline and after 5 years, in the present study, and the correlation with ABI as a measure of arterial stiffness, both in absolute and relative values after 5 years, supports a potential role for sCD14 in cardiovascular disease progression in patients with mild-to-moderate CKD.

OPG, which is produced by osteoblasts and vascular endothelial and smooth muscle cells, has been proposed to play an important role in the regulation of vascular calcification [34, 35] and associates with mortality in ESKD [36]. Patients with CKD stages 2–5 and hemodialysis patients have higher serum OPG levels compared with control subjects [37, 38]. Furthermore, plasma OPG concentrations have been associated with arterial calcification in CKD and ESKD patients and in patients with diabetes [35, 39]. In the present study, a higher OPG concentration was associated with higher ABI and arterial stiffness in patients with CKD 2–3 at 5 years of follow-up, but not in healthy controls, which accords with previous observations [35].

By contrast, animal studies have suggested a protective role of OPG on the vasculature and OPG administration in rats inhibits artery calcification [40]. Thus, the association of OPG with vascular calcification in humans may not essentially be causative and may merely represent a compensatory mechanism to attenuate further vascular lesions.

CIMT is used to evaluate the presence of atherosclerosis and autopsy studies have demonstrated a histological relationship between presence of atherosclerosis in the carotid artery and coronary arteries [37]. An increase in CIMT has been observed in patients with CKD and increases the risk of CVD events and mortality in ESKD [37, 41]. Information on CIMT in our patient cohort with CKD stages 2–5 has previously been published elsewhere [19]. In the present study, CIMT increased significantly during follow-up in healthy controls, but not in patients with CKD 2–3, and was significantly higher at 5 years in controls. In addition, higher OPG correlated to higher CIMT in healthy controls, which is in accordance with previous observations [42]. The strict adherence to treatment guidelines during 5 years in patients with CKD 2–3 with early use of statins, vitamin D, and antihypertensives may have retarded the progression of vascular lesions in this group, but further studies are needed to elucidate and confirm this.

Previous studies have shown that plasma ANG concentrations increase with progression of CKD, but there was no significant association between plasma ANG concentration and arterial stiffness [24]. This is in accordance with the observations in the present study. Patients with CKD 4–5 had the highest concentrations of ANG, and patients with CKD 2–3 had higher ANG levels than healthy controls, both at baseline and after 5 years of follow-up. In addition, no significant association with ABI or CIMT was found.

In conclusion, patients with mild-to-moderate kidney disease exhibited increased plasma concentrations of sCD14, ANG, and OPG at baseline and the concentrations of sCD14 and ANG were also higher in patients with CKD 2–3 after 5 years of prospective follow-up. Higher levels of sCD14 and OPG in patients with CKD 2–3 were significantly associated with higher ABI, a measure of arterial stiffness, and an increase in sCD14 over time in CKD 2–3 patients was associated with a corresponding increase in ABI. Vascular stiffness should be considered as a target for delaying deterioration in kidney function. Further studies are needed to examine to what extent the intensive multifactorial approach and early start of medication to align with international treatment targets may have influenced the results.

We sincerely thank all the participants and staff of PROGRESS study, especially research nurse/PhL Agneta Aspegren-Pagels, and sonographers Eva Wallén-Nielsen, the late Eva Linder-Klingsell, Anna Asp and Carin Wallquist. All plasma analyses were performed at SciLifeLab’s Affinity Proteomics Unit in Stockholm (formerly Biobank Profiling), and we are grateful to all members of the unit for their work on our project and a special and sincere thanks to Maja Neiman.

The study complied with the Declaration of Helsinki, and informed consent was obtained from all healthy individuals and patients. The study protocol was reviewed and approved by Swedish Ethical Review Authority (Approval number DNR 02–052).

None of the authors have any disclosures to report.

This study was supported by grants provided by Stockholm County Council and the Swedish Kidney Foundation.

Senka Sendic contributed to formal analysis, validation and writing original draft, reviewing, and editing. Ladan Mansouri contributed to investigation, data curation, methodology, formal analysis, validation and writing original draft, reviewing, and editing. Mun-Gwan Hong contributed to formal analysis, validation, and reviewing. Jochen M Schwenk contributed to conceptualization, formal analysis, reviewing, and editing. Maria J Erikson contributed to project administration, investigation, data curation, and reviewing. Britta Hylander contributed to conceptualization, funding acquisition, project administration, investigation, data curation, reviewing, and editing. Joachim Lundahl contributed to project administration, methodology, formal analysis, validation, writing original draft, reviewing, and editing. Stefan H Jacobson contributed to conceptualization, funding acquisition, project administration, formal analysis, validation, writing original draft, reviewing, and editing.

Senka Sendic and Ladan Mansouri contributed equally to this work.

The data that support the findings of this study are openly available from corresponding author.