Chronic kidney disease (CKD) is highly prevalent worldwide and is an important cause of morbidity, especially due to cardiovascular disease (CVD). In classical CVD, without renal dysfunction, most atherosclerosis is caused by traditional risk factors that can be controlled, treated or modified (such as hypertension, tobacco use, diabetes, lipid levels) or factors that cannot be changed (such as age, gender, and family history) [1
]. In these cases, atherosclerosis is the consequence of many years of exposure to atherogenic influences that lead to early lesions. Then, under the influence of age and different factors, such as lipid metabolism, blood pressure, and diet, these early lesions advance, and atherogenesis is accelerated. Chronic kidney disease-related atherosclerosis (CKD-A) is more complex and is related to traditional and non-traditional risk factors, including inflammation, endothelial dysfunction, oxidative stress, vascular calcification, and volume overload. All of these problems lead to hypertension, anemia, mineral and bone disorders, and vascular remodeling and damage [2
]. However, these risk factors and complications, especially inflammation and endothelial dysfunction, are also related to the pathogenesis of non-renal atherosclerotic CVDs [3
]. Therefore, we sought to determine which of these risk factors have a substantial role in and are specific for CKD-A.
The diagnosis of CKD is mainly based on the measured or estimated glomerular filtration rate (eGFR) and/or evidence of kidney damage (usually indicated by albuminuria or proteinuria) for a period of at least three months. The first and second stages of CKD (CKD1, CKD2) are the mildest ones, and although eGFRs are normal (above 90 mL/min/1.73 m2
) or slightly decreased (at most 60 mL/min/1.73 m2
), they have other evidence of renal disease like proteinuria or structural or functional abnormalities of the kidney. In the third and fourth stages of CKD, moderate and severe reduction in the eGFR are observed (CKD3: eGFR 30–59 mL/min/1.73 m2
; CKD4: 15–29 mL/min/1.73 m2
). The fifth stage of CKD (CKD5) is the most advanced stage and is related to kidney failure (GFR < 15 mL/min/1.73 m2
). The latter end-stage renal disease (ESRD) patients receive renal replacement therapy. The typical eGFR in adults aged 60 years is between 60 and 90 mL/min per 1.73 m2
. The eGFR declines during the progression of CKD and the aging process. However, among CKD patients, even a mild or moderate eGFR decrease increases the risk of serious cardiovascular events and CVD-related mortality [4
Herein, we applied a label-free proteomic approach to screen changes in protein expression in three stages of CKD and one stage of CVD as well as in healthy volunteers (HVs) to better understand the role of individual processes, pathways, and risk factors in CKD-A. All of the patients varied in both the progression of atherosclerosis and the advancement of renal disease. Furthermore, we reported the relative quantification information for 162 differentially expressed proteins. In this study, we focused on the relationship between the altered accumulation of differential proteins and the progression of CKD-A. The obtained data were evaluated by functional annotation and validated with an enzyme-linked immunosorbent assay (ELISA).
Several methods for relative proteomic quantitation have been described in recent years [5
]. Labeling methods, including iTRAQ analysis, can be expensive but generally require fewer LC-MS/MS runs to generate robust results [7
]. In label-free quantitation strategies, each sample must be analyzed separately with replicates for a high level of reproducibility; however, this technique is extremely convenient due to the simplicity of sample preparation. Moreover, the capabilities of the Q-Exactive Orbitrap spectrometer make a label-free approach very attractive and precise in quantitative protein analysis. In combination with the MaxQuant software, Q-Exactive enabled the identification of 611 plasma proteins with two or more unique peptides with 99% confidence. Additionally, the obtained results revealed a high level of run-to-run and sample-to-sample reproducibility, confirming that two experimental and two injection replicates were sufficient for the precise determination of protein ratios in label-free studies of plasma. The high level of run-to-run and sample-to-sample reproducibility was probably obtained because the plasma protein procedure did not require complex and multistep methods for isolation and purification. We have previously shown that one of the main drawbacks of removing abundant proteins from plasma using an affinity column is the simultaneous removal of non-targeted proteins [8
]. We have also shown that strong cation exchange (SCX) chromatography without affinity depletion is a suitable plasma sample pretreatment method for proteomic analysis. However, the preparation of 150 samples in this manner would be extremely time consuming. Instead, we decided to use a simple method of plasma protein sample preparation and extend the LC separation to 230 min. In this way we obtained very reliable data. The results of the PCA analysis by Perseus are shown in Figure 1
. PCA allowed us to separate all of the analyzed CKD experimental groups according to protein abundance variation, which was helpful in interpreting the relationships between the experimental groups. The pathway analysis showed that most of the differentially expressed proteins related to CKD progression were linked with hemostasis, inflammation and the inflammatory response, calcium ion metabolism, and the cellular response to oxidative stress.
Both conditions, CKD and CVD, are chronic inflammatory diseases [9
]. Chronic inflammation and endothelial dysfunction, resulting in the disintegration of vascular structure and its function, are key elements in the progression of both atherosclerosis and kidney failure. CKD patients, especially ESRD patients treated with hemodialysis, are exposed to vessel damage during each dialysis session because of the contact of blood with the dialysis membrane [11
]. Our study confirmed that inflammation is more pronounced in CKD patients than in CVD patients. This finding is supported by the differential accumulation of proteins that are involved in immune reactions and act as acute phase proteins. Among proteins associated with CKD progression β2m, α1m, two complement components, α-1-acid glycoprotein 1 and 2, cysC, monocyte differentiation antigen CD14, fibrinogen and uteroglobin contribute to signaling in the immune system, inflammation, cytokine secretion, and the acute phase response. These proteins differentiated both CKD and CVD patients from HVs. However, the differences in the relative abundance of both comparisons were completely different. For example, the accumulation of α1m was only 1.4 times higher in CVD patients and up to 5.6 times higher in CKD5 patients compared to HVs (Figure 3
a). In a similar situation, we observed an abundance of β2m. The level of this protein was tens of times higher in CKD patients than CVD patients. The abundance of cysC, a well-known marker of renal failure [13
], was increased in the plasma of CVD patients compared to HVs (fold change of 1.53 in the ELISA). However, the accumulation of cysC in the plasma of the CKD3-4 and CKD5 patients was several times greater. The level of this protein was similar between the CVD and CKD1-2 patients (Figure 5
b). The diagnostic values of β2m and cysC as markers of inflammation and kidney failure have been confirmed in multiple clinical studies [14
]. Furthermore, other studies have postulated a significant correlation between high serum cysC levels and cardiovascular risk factors in individuals with atherosclerosis and normal renal function [18
]. Classical CVD is also characterized by vascular inflammation. The question is whether inflammation is more specific to CKD or CVD. The direct comparison of the blood plasma proteomes isolated from CKD and CVD patients performed in this study, also confirmed by our previous findings [21
], shows that classical CVD is related to inflammation but to a lesser extent than CKD. This finding is also confirmed by the calculated level of serum CRP, the most important biomarker of systemic inflammation.
The high concentration of circulating uremia-specific toxins also contributed to inflammation and endothelial dysfunction long before renal replacement therapy [22
]. Furthermore, oxidative stress, acidosis, and the accumulation of mediators in renal failure (advanced glycation end (AGE) products, pro-inflammatory cytokines) may contribute to inflammation [9
]. Our results showed that the plasma marker of endothelial activation vascular adhesion molecule-1 (VCAM-1) was increased in the later stages of CKD (CKD3-4 and CKD5), whereas this marker was undetectable in the plasma of the CVD, CKD1-2, and HV groups (Figure 6
b). Endothelial activation as a result of oxidative stress appears to be involved in vascular damage and pathophysiology of the cardiovascular complications of CKD. The present study showed that with the development of CKD, the plasma glutathione peroxidase was significantly decreased and that this change was positively associated with eGFR (Figure 4
c). In contrast, the level of PRDX2 increased in CKD patients but not in CVD patients (Figure 5
a). The accumulation of superoxide dismutase was observed only in the most advanced CKD stage (Figure 6
c). Glutathione peroxidase catalyzes the reduction of hydrogen peroxide and other organic hydroperoxides into water by using glutathione as the reducing agent [24
]. Therefore, this enzyme protects cell membrane lipids, proteins, and DNA against oxidative stress. The level of glutathione peroxidase in CVD patients was also decreased compared to that in HVs but was similar to that in CKD1-2 patients. These results suggest that oxidative stress, especially in ESRD patients, plays a more important role in CKD-A than in classical CVD.
Vascular calcification is another risk factor that is related to progression and mortality in CKD patients [25
]. Osteopontin and fetuin A are expressed in atherosclerotic plaques and participate in atherosclerotic calcification. Circulating osteopontin is associated with vascular calcification and arterial stiffness in coronary artery disease [29
]. High levels of osteopontin are associated with cardiovascular risk in CKD patients [31
]. In our study, osteopontin was undetectable in HVs and non-dialyzed CKD patients (Figure 6
a). The accumulation of this protein only in the plasma of ESRD patients was measured by LC-MS/MS analysis. Osteopontin was also absent in CVD patients, which confirms that the vascular calcification mechanism is associated with CKD. Furthermore, these observations are confirmed by the accumulation of another protein that participates in the process of vascular calcification, fetuin A. The concentration of fetuin A was highest in HVs and gradually decreased from CKD1-2 patients, reaching its lowest value in patients with ESRD (Figure 4
b). Moreover, the concentration of this protein was the highest in CVD patients. Fetuins are carrier proteins, similar to albumins, and form soluble complexes with calcium and phosphate; thus, they are carriers of insoluble calcium and are potent inhibitors of pathological calcification [32
]. In addition to fetuin A, fetuin B is another member of the fetuin family with a similar function (Figure 4
a). Fetuin B, similarly to fetuin A, is an inhibitor of basic calcium phosphate precipitation [34
]. Some reports have demonstrated that fetuin A levels are inversely correlated with coronary artery calcification in hemodialysis patients [35
] and diabetic patients [36
]. Information on the relationship among fetuin A levels, the degree of calcification, and mortality is less clear for patients with normal renal function as well as predialysed CKD patients. To our knowledge, this is the first study showing an association between fetuin A and atherosclerosis comparing renal and non-renal conditions. To our knowledge, this is also the first report presenting an alteration in the level of fetuin B in CKD patients. The altered levels of the inhibitors of atherosclerosis-related vascular calcification, fetuin A and B as well as osteopontin, support the notion that vascular calcification is more pronounced in CKD than in CVD. Vascular calcifications may be a more specific marker for CKD-related atherosclerosis, and this phenomenon is correlated with CKD progression.
All of the aforementioned factors, including inflammation, oxidative stress, vascular calcification, and endothelial activation, lead to endothelial injury. As a result, the underlying extracellular matrix is exposed, and platelets adhere to the vessel wall, leading to leukocyte and thrombocyte activation. This vascular “microinflammation” activates the coagulation cascade, which further accelerates vessel wall damage [9
]. Therefore, the connection between the coagulation process and atherosclerosis development is beyond dispute. In our previous studies, we have revealed an elevated level of fibrinogen in the plasma of CVD patients compared to HVs [21
]. The current results confirm our previous data and demonstrate that the levels of many proteins that are involved in hemostasis are also elevated in the plasma of CVD patients. However, changes in the accumulation of these proteins are more pronounced in CKD patients. Among the 33 differential proteins related to the hemostasis process, only five proteins differentiated the HV and CVD groups. The remaining 28 proteins differentiated the HV and CKD groups according to CKD progression. Large numbers of clinical studies on atherosclerotic disease have shown a generally increased involvement of coagulation processes in CVD [40
]. The elevated levels of fibrinogen and other proteins related to the blood coagulation process have also been found in the sera of subjects with renal insufficiency [42
]. However, no studies have demonstrated alterations of the blood coagulation proteins in both diseases to highlight the differences between them. Our results suggest that despite the relationships of different non-traditional risk factors with classical CVD, similar relationships with CKD-A are not evident. We demonstrated that patients with CKD have increased oxidative stress, vascular damage, inflammation, vascular calcification, and disturbances in the blood coagulation process at higher levels than do patients with advanced classical CVD without CKD. The relative abundances of differential proteins presented in this study revealed that CVD is similar to early stages of CKD (as in the CKD1-2 group) in its relationship with non-traditional risk factors. This knowledge was obtained through the direct comparison of the blood plasma proteomes isolated from HVs and from CKD and CVD patients. In this manner, we were able to identify the differences between the relative levels of many proteins in both diseases simultaneously.
4. Materials and Methods
4.1. Subjects and Samples
Our study protocol conformed to the Ethical Guidelines of the World Medical Association Declaration of Helsinki. Before the project commenced, appropriate approval was obtained from the Bioethical Commission of the Karol Marcinkowski University of Poznan Medical Sciences, Poznan, Poland (no. 14/07; 1 April 2007). All participating individuals provided signed informed consent for inclusion before they participated in the study. The characteristics of the studied population were presented previously [21
]. The study involved 150 persons divided into five equal groups. They were matched for age and gender. All of studied patients suffered from hypertension, were non-diabetic, and non-albuminuric. The majority were patients with CKD (90 persons) who were treated by the Department of Nephrology, Transplantology and Internal Medicine at Poznan University of Medical Sciences. Based on the Kidney Disease: Improving Global Outcomes [43
] and the National Institute for Health and Care Excellence [44
] guidelines, the examined CKD patients were divided into three groups according to their estimated GFR (eGFR). Their eGFR was calculated by the formula developed by Levey et al.
]. The first group, CKD1-2, contained patients in the initial stages of CKD with eGFR = 77.04 ± 22.9 mL/min/1.73 m2
(mean ± SD). The second group, CKD3-4, included pre-dialyzed patients with eGFR = 19.1 ± 8.0 mL/min/1.73 m2
. The third group, CKD5, contained end-stage renal disease (ESRD) patients with eGFR = 5.75 ± 7.1 mL/min/1.73 m2
who had undergone hemodialysis for 39.6 ± 9.5 months, three times per week. The CKD patients varied in the progression of atherosclerosis (significant differences in carotid intima media thickness (CIMT) were observed) and in the percentage of cardiovascular events. The CKD1-2 group primarily showed the initial clinical consequences of hypertension and/or ischemic heart disease. In the more advanced stages of CKD, the number of people with serious symptoms and consequences of CVD was greater. Fifty-nine percent of the CKD5 patients had a history of myocardial infarction or stroke. The underlying renal diseases of the patients were hypertensive nephropathy (n
= 33), chronic glomerulonephritis (n
= 21), chronic interstitial nephritis (n
= 21), polycystic kidney disease (n
= 3), and other/unknown (n
A fourth group (called CVD) included 30 non-diabetic patients with a history and symptoms of atherosclerotic occlusive disease who were admitted for angiography to the Department of Internal Medicine, Division of Cardiac Intensive Care in Poznan University of Medical Sciences. All of the CVD patients had at least one artery stenosis, causing at least 50% of the lumen reduction. Sixty-eight percent of CVD patients had a history of myocardial infarction or stroke. No subjects from the CVD group had any clinical symptoms of renal dysfunction (mean eGFR = 92.7 ± 21.1). A fifth group, which served as a control group, contained 30 HVs with a mean eGFR of 123.6 ± 17.6. Persons with diabetes mellitus, acute inflammatory processes, and malignant tumors either at the time of study or within the previous 10 years were excluded from the study. All of the studied subjects were tested for atherosclerosis on the basis of their medical history (history of myocardial infarction or/and ischemic stroke), systolic and diastolic blood pressure levels, their lipid metabolism parameters, and CIMT. Although patients enrolled to this study were treated by recommended groups of drugs, related to the control of blood pressure, history of cardiovascular disease and lipid profile, such as angiotensin-converting enzyme inhibitors (ACEI), non-steroidal anti-inflammatory drugs (NSAID), β-blockers, and statins, not all of them received all of these medications. Despite of the differences in the treatment between studied groups which cannot be avoided, there were no significant impacts of drugs on the obtained results. Therefore, detailed information on this issue has been omitted in this study. The peripheral blood of the persons was collected into a closed monovette system containing EDTA and was centrifuged immediately at 1000× g for 15 min. The obtained supernatants were then centrifuged at 16,000× g for 15 min at 4 °C and frozen at −80 °C. It should be emphasized that all of the analyses conducted in the CKD5 group were carried out on blood samples collected immediately before the mid-week hemodialysis session, as is usually recommended in scientific research.
4.2. In-Solution Trypsin Digestion
One microliter of each plasma sample without depletion was diluted with MiliQ water to a final volume of 60 μL. The protein concentration was determined using a bicinchoninic acid (BCA) (Pierce) assay. Then, 10 μg of plasma protein was reduced in the presence of 50 mM NH4HCO3 with 5.6 mM DTT for 5 min at 95 °C. Then, the sample was alkylated with 5 mM iodoacetamide for 20 min in the dark at room temperature (RT). The proteins were digested with 0.2 μg of sequencing-grade trypsin (Promega, Mannheim, Germany) overnight at 37 °C. Each plasma sample was prepared for digestion in duplicate.
4.3. NanoLC-MS/MS Analysis
For each run, 1.5 μg of the digested protein samples was injected onto an RP C18 precolumn (Thermo Fisher Scientific, Waltham, MA, USA) connected to a 75 μm i.d. × 25 cm RP C18 Acclaim PepMap column with a particle size of 2 μm and a pore size of 100 Å (Thermo Fisher Scientific) using a Dionex UltiMate 3000 RSLCnano System (Thermo Fisher Scientific). Every sample was injected in duplicate at random. Every 19 sample injections, the system was calibrated using Pierce LTQ ESI Positive Ion Calibration Solution (Thermo Fisher Scientific). Then, 19 freshly digested samples were injected without any break. The following LC buffers were used: buffer A (0.1% (v/v) formic acid in Milli-Q water) and buffer B (0.1% formic acid in 90% acetonitrile). The peptides were eluted from the column with a constant flow rate of 300 nL·min−1 with a linear gradient of buffer B from 5% to 65% over 208 min. At 208 min, the gradient increased to 90% B and was held there for 10 min. Between 218 and 230 min, the gradient returned to 5% to re-equilibrate the column for the next injection. The peptides eluted from the column were analyzed in the data-dependent MS/MS mode on a Q-Exactive Orbitrap mass spectrometer (Thermo Fisher Scientific). The instrument settings were as follows: the resolution was set to 70,000 for MS scans, and 17,500 for the MS/MS scans to increase the acquisition rate. The MS scan range was from 300 to 2000 m/z. The MS AGC target was set to 1 × 106 counts, whereas the MS/MS AGC target was set to 5 × 104. Dynamic exclusion was set with a duration of 20 s. The isolation window was set to 2 m/z.
4.4. Qualitative Analysis of Proteomic Data
After each LC-MS/MS run, the raw files were qualitatively analyzed by Proteome Discoverer (PD), version 1.4.14 (Thermo Fisher Scientific). To evaluate the quality of the performed runs, the number of peptide spectrum matches (PSMs) and the number of identified proteins were calculated. The LC-MS/MS runs with the number of PSMs below 125,000 and the number of identified proteins below 450 (with 1% FDR) were excluded from further analysis. The identification of proteins by PD was performed using the SEQUEST engine against the UniProt Complete Proteome Set of Humans (123,619 sequences) using the following parameters: a tolerance level of 10 ppm for MS and 0.05 Da for MS/MS. Trypsin was used as the digesting enzyme, and two missed cleavages were allowed. The carbamidomethylation of cysteines was set as a fixed modification, and the oxidation of methionines was allowed as a variable modification.
4.5. Quantitative Analysis of Proteomic Data
The raw files positively evaluated by PD were quantitatively analyzed by MaxQuant [46
], version 220.127.116.11 (Available online: http://www.coxdocs.org website
). The database search engine Andromeda was used to search the MS/MS spectra against the UniProt database, with the same parameters as for PD at ≤1% FDR. The analysis of the plasma samples was based on the label-free quantification (LFQ) intensities. The data were evaluated, and the statistics were calculated using Perseus software (version 18.104.22.168, Max Planck Institute of Biochemistry, Martinsried, Germany). The MQ data were filtered for reverse identifications (false positives), contaminants, and proteins “only identified by site”. The mean LFQ intensities as well as the standard deviation of this value were calculated for all experimental groups. The fold changes in the level of the proteins were assessed by comparing the mean LFQ intensities among all experimental groups. A protein was considered to be differentially expressed if the difference was statistically significant (p
< 0.05), the fold change of minimum was ±1.5, it was identified with a minimum of two peptides with >99% confidence.
4.6. Assessment of Variability/Reproducibility
The technical and biological variabilities of each plasma sample from each experimental group were estimated by scatter plot and calculated using the Pearson correlation coefficients of the LFQ intensities in Perseus. To assess the reproducibility, the percentage overlap between the protein identification in both the technical/injection and biological replicates was calculated using PD software (Thermo Fisher Scientific, Waltham, MA, USA).
4.7. ELISA Validation
An ELISA was used to validate the differentially expressed proteins. The plasma protein levels were measured using a commercially available sandwich colorimetric ELISA kit (Abcam, Cambridge, UK or Elabscience, Wuhan, China) against the following proteins: α-1-microglobulin, cystatin C, β-2-microglobulin, apolipoprotein AIV, and fibrinogen α, β, and γ. All assays were prepared according to the manufacturers’ instructions. The O.D. absorbance was read at 450 nm with an Infinite 200 PRO multimode reader (Tecan, Männedorf, Switzerland).
4.8. Pathway and Network Analyses of Dysregulated Proteins in Plasma Samples
Only the proteins that were quantified as unique and non-redundant were used in the subsequent analyses. Proteins were considered to be differentially expressed if the difference was statistically significant (p
< 0.05) and the fold-change minimum was ±1.5. The dysregulated proteins were chosen based on the criterion that the protein must be quantified by a minimum of two peptides with >99% confidence. Uncharacterized proteins and fragments of immunoglobulins were excluded from the analysis. The differential proteins were subjected to analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (Available online: http://david.abcc.ncifcrf.gov/
] and Protein ANalysis THrough Evolutionary Relationships (PANTHER) (Available online: http://pantherdb.org/
] analysis tools for identifying enriched functions, signaling pathways or networks and diseases categories. p
values and Benjamini-corrected p
-values below 0.05 were considered significant. The pathway analysis using the DAVID tool was based on the REACTOME, KEGG pathway, and PANTHER pathway databases.
4.9. Statistical Analysis
The LFQ intensities derived from all of the evaluated PD samples were considered for statistical analysis. For multiple comparisons, one-way analysis of variance (ANOVA) with a Bonferroni correction for multiple testing was performed. For the comparison between two groups, t-tests were performed. p values less than 0.05 were considered to be statistically significant. Regression and correlation analyses were also performed for the obtained results. The correlations between variables were defined by the Pearson (Perseus) and Spearman (Statistica) coefficients, and p values less than 0.05 were considered significant. Multivariate analyses were carried out by untargeted principal component analysis (PCA). All statistical analyses were performed using the Statistica v. 10.0 software (StatSoft, Inc., Kraków, Poland) and Perseus 22.214.171.124 which is freely available from the MaxQuant website.