Clinical Research

Complement Activation in Peritoneal Dialysis–Induced Arteriolopathy

Maria Bartosova, Betti Schaefer, Justo Lorenzo Bermejo, Silvia Tarantino, Felix Lasitschka, Stephan Macher-Goeppinger, Peter Sinn, Bradley A. Warady, Ariane Zaloszyc, Katja Parapatics, Peter Májek, Keiryn L. Bennett, Jun Oh, Christoph Aufricht, Franz Schaefer, Klaus Kratochwill and Claus Peter Schmitt
JASN January 2018, 29 (1) 268-282; DOI: https://doi.org/10.1681/ASN.2017040436

Abstract

Cardiovascular disease (CVD) is the leading cause of increased mortality in patients with CKD and is further aggravated by peritoneal dialysis (PD). Children are devoid of preexisting CVD and provide unique insight into specific uremia- and PD-induced pathomechanisms of CVD. We obtained peritoneal specimens from children with stage 5 CKD at time of PD catheter insertion (CKD5 group), children with established PD (PD group), and age-matched nonuremic controls (n=6/group). We microdissected omental arterioles from tissue layers not directly exposed to PD fluid and used adjacent sections of four arterioles per patient for transcriptomic and proteomic analyses. Findings were validated in omental and parietal arterioles from independent pediatric control (n=5), CKD5 (n=15), and PD (n=15) cohorts. Transcriptomic analysis revealed differential gene expression in control versus CKD5 arterioles and in CKD5 versus PD arterioles. Gene ontology analyses revealed activation of metabolic processes in CKD5 arterioles and of inflammatory, immunologic, and stress-response cascades in PD arterioles. PD arterioles exhibited particular upregulation of the complement system and respective regulatory pathways, with concordant findings at the proteomic level. In the validation cohorts, PD specimens had the highest abundance of omental and parietal arteriolar C1q, C3d, terminal complement complex, and phosphorylated SMAD2/3, a downstream effector of TGF-β. Furthermore, in the PD parietal arterioles, C1q and terminal complement complex abundance correlated with the level of dialytic glucose exposure, abundance of phosphorylated SMAD2/3, and degree of vasculopathy. We conclude that PD fluids activate arteriolar complement and TGF-β signaling, which quantitatively correlate with the severity of arteriolar vasculopathy.

In children on dialysis, the risk of mortality is increased 40-fold compared with healthy populations.1,2 A third of the patients with juvenile onset of ESRD die before the fourth decade of life, the majority from cardio- and cerebrovascular disease.1,3,4 Endothelial dysfunction develops early in children with CKD5 and is followed by structural and functional vascular changes including increased arterial stiffness and wall thickening,6,7 arteriosclerotic lesions,8 and vascular calcifications,9 the progression of which is markedly accelerated after initiation of dialysis.6–8 The risk for progressive arterial disease is enhanced by both classic (hypertension, hyperlipidemia) and nonclassic, CKD-associated risk factors (hyperphosphatemia, hyperparathyroidism, subclinical inflammation).3,9,10

Peritoneal dialysis (PD) is the preferred dialysis modality in children11 and is increasingly applied in adults,12 due to its independence of a vascular access, cost effectiveness, and advantages of a home-based therapy. Patients on PD, however, face additional cardiovascular risks related to the resorption of glucose and vasculotoxic glucose degradation products (GDP) from the dialysis fluid. Observational and interventional evidence have suggested a role of peritoneal glucose and/or GDP exposure in patient survival on dialysis.13,14 The relative effect of dialytic glucose and GDP content remains controversial. GDP exposure can be substantially reduced by use of multichamber PD fluids; the effect of such solutions on long-term patient outcome, however, is still unknown.15

In this work, we sought to obtain a comprehensive understanding of the pathomechanisms of CKD-associated arteriopathy and to explore the specific contribution of PD therapy. The analysis of small arteries and precapillary arterioles is of particular interest because they control peripheral resistance and microcirculation. Vasculopathy in this part of the arterial tree predicts left ventricular hypertrophy and cardiovascular events in hypertensive patients.16–19 Peritoneal arterioles were obtained from children with CKD5, children undergoing chronic PD with double-chamber PD fluids, and healthy control children. This population is unique due to the absence of secondary pathologies typically present in adults, such as changes related to long-standing hypertension, diabetes, smoking, and ageing. We analyzed microdissected arteriolar tissue samples by means of transcriptomic and proteomic profiling and in independent cohorts by automated immunohistochemistry of intact tissue. The combination of these techniques allowed sensitive detection of molecular changes on the transcript level while controlling for biologic relevance at the level of effector proteins and subsequent quantitative validation.

Results

Transcriptomics and Gene Ontology Analysis

Clinical and biochemical findings were similar in healthy children, in children with CKD5, and in children on dialysis (Table 1). Median lumen to vessel (L/V) ratio of arterioles, a marker of vasculopathy, used for omics analysis was 0.76 (interquartile range [IQR], 0.14) in healthy controls, 0.58 (0.08) for the CKD5 group, and 0.59 (0.10) for the low-GDP PD group (P<0.001, P=0.52 CKD5 versus PD). Compared with the samples from age- and sex-matched healthy children, transcriptome analysis of arterioles from CKD5 children showed upregulation of 173 and downregulation of 117 genes (P<0.01) (Supplemental Table 1). Over-represented pathways among these differentially expressed genes mainly included protein targeting to membranes and translational initiation of various metabolic processes (Supplemental Table 2). In children on PD, 88 genes were up- and 11 genes downregulated compared with children with CKD5. Gene ontology analyses revealed an enrichment of genes involved in immune response and inflammation in arterioles, and in particular complement activation processes (Supplemental Table 3). For example, 71.7 times more genes than expected were found in the alternative pathway (i.e., four observed versus 0.06 expected), and genes belonging to the regulation of complement activation were 35.3-fold enriched (both P<0.01).

View this table:
Table 1.

Characteristics of the omic-screening cohort

Proteomic Data Integration

In parallel to transcriptomic analyses, we performed proteomics on neighboring arteriolar sections from children with CKD5 and on PD. In the single, quantitative 10-plex liquid chromatography coupled to mass spectrometry (LC-MS) experiment, 3968 unique protein IDs corresponding to 3964 unique gene symbols were identified (Supplemental Table 4). After identification of complement activation at the transcriptomic level, protein abundance ratios were extracted from the multiplex isobaric labeling experiment for all proteins related to the complement system. The IPA (Ingenuity Pathway Analysis, QIAGEN Inc.) pathway “complement system” was populated with transcript and protein ratios for comparison (Figure 1A). Both at the transcriptomic and the proteomic level, the pathway was activated through all major steps/elements.

Figure 1.

Cross-omics analysis of the complement pathway activation. Transcriptomic and proteomic analyses from adjacent sections of microdissected omental arterioles demonstrate (A) concordant activation of the IPA complement pathway and (B) correlation of complement-associated transcripts and proteins. Red shapes containing the gene symbols indicate upregulation, green symbols downregulation. In the correlation plot, black triangles represent direct members of the complement pathway; black round symbols represent gene symbols associated to the complement system in Panther, GO, and UniProt. The x axis gives mRNA expression ratios PD/CKD5, y axis respective protein ratios. The association between gene and protein ratios is highly significant when the transcriptomics outlier (CFB) is removed (P<0.01). (C) Analysis of abundance ratios for fragments of complement components as obtained from UniProt demonstrates activation on the level of biologically relevant fragments of complement components.

In addition to direct pathway members, proteins associated with the complement system on the basis of information from Panther, GO, and UniProt were used to investigate the correlation between transcript and protein ratios (Figure 1B). The overall correlation of complement-associated transcripts and proteins was high, with only inhibitory molecules downregulated.

Because of the nature of the regulated complement system that functions through specific cleavage and propagation of biologically active fragments, the proteomic analysis was repeated at the level of complement fragments (Figure 1C). The fragment with the highest abundance ratio was C3d.

Validation of Complement Findings

Complement activation demonstrated by crossomic analysis was reconfirmed in an independent cohort of five healthy children, 15 children with CKD5, and 15 children on PD. The groups were matched for age, BMI, and BP, and biochemical findings did not differ between groups (Table 2).

View this table:
Table 2.

Characteristics of the validation cohort

C1q, C3d, and TCC staining was confined to endothelial cells (Figure 2, A and B). In controls, complement factor abundance was low in omental and parietal peritoneal endothelium (Table 3). In CKD5, arteriolar complement factor abundance tended to be higher than in controls, with TCC being significantly increased in parietal peritoneal arterioles (Figure 2, A and B, Table 3).

Figure 2.

Parietal peritoneal arteriolar complement abundance. Representative immunostainings and quantification of C1q, C3d, and TCC in (A) omental and (B) parietal peritoneal arterioles of controls (n=5), patients with CKD5 (n=15), and patients on PD (n=15). Scale bars represent 100 µm. Immunofluorescence C1q staining was quantified by Image J, C3d, and TCC immunohistochemical stainings by Aperio. Individual data, median, and IQR are given. *P<0.05; **P<0.01; ***P<0.001 versus CKD5; #P<0.05; ##P<0.01 versus controls.

View this table:
Table 3.

Omental and parietal peritoneal arteriolar immunohistochemical findings and L/V ratio in the children of the validation cohort

In omental arterioles from children on PD, median endothelial C1q and C3d abundance was higher than in controls and in CKD5; TCC abundance was higher than in children with CKD5 (Table 3).

In parietal peritoneal arterioles, endothelial C1q and TCC abundance was higher in children on PD than in controls and in CKD5; C3d staining was higher as compared with controls (Figure 2B, Table 3). Peritoneal and omental arteriolar C1q abundance correlated in children with CKD5 and in children on PD (rho=0.37, P<0.05).

L/V ratio of omental arterioles was reduced in children with CKD5 as compared with controls, but not further reduced in children on PD. Likewise, parietal peritoneal arteriolar L/V ratio was reduced in children with CKD5 compared with controls, but significantly further reduced in children on PD (Figure 3, Table 3). Intima thickness of parietal arterioles inversely correlated with L/V ratio (r=−0.77, P<0.01), whereas media thickness was independent of L/V ratio (r=−0.27, P=0.35).

Figure 3.
Figure 3.

Peritoneal arteriolar complement activation and vasculopathy. (A) Omental and (E) parietal peritoneal arteriolar L/V ratio in children with CKD5 and on PD and correlation of complement factors C1q, C3D, and of TCC with L/V ratio, in (B–D) omental and (F–H) parietal peritoneal arterioles. In parietal peritoneal arterioles, C1q and TCC abundance inversely correlate with L/V ratio (rho=−0.44/r=−0.39, both P<0.05). Triangles represent children with CKD5, circles children on PD.

In controls, omental and parietal arteriolar L/V ratio did not correlate with endothelial complement findings. In patients with CKD5 and patients on PD, parietal peritoneal but not omental endothelial C1q and TCC abundance inversely correlated with L/V ratio (rho=−0.44/r=−0.39, both P<0.05; Figure 3). In patients on PD, peritoneal but not omental endothelial C1q and TCC abundance positively correlated with glucose exposure (rho=0.5/r=0.64, P<0.05/<0.01; Figure 4).

Figure 4.
Figure 4.

Dialytic glucose exposure and parietal peritoneal arteriolar complement activation. In parietal peritoneal arterioles, (A) C1q and (B) TCC abundance correlate with the glucose exposure of the peritoneum at the time of biopsy (rho=0.5/r=0.64, P<0.05/<0.01).

Arteriolar TGF-β and VEGF-A

TGF-β downstream effector pSMAD2/3 was low in controls, increased in parietal arterioles in CKD5, and most abundant in omental and parietal peritoneal arterioles of children on PD (Figure 5, Table 3). Peritoneal but not omental arteriolar pSMAD2/3 positivity correlated with C1q and TCC abundance (rho=0.5/r=0.41, P<0.01/P<0.05) and inversely correlated with L/V ratio (r=−0.5, P<0.01) (Figure 6). Omental and parietal arteriolar cross-sectional VEGF-A positivity was similar in controls, CKD5 and children on PD. (Figure 5, Table 3) and did not correlate with complement factor abundance or L/V ratio.

Figure 5.
Figure 5.

Peritoneal arteriolar pSMAD2/3 and VEGF-A. Representative immunostainings of pSMAD2/3 and VEGF-A in omental arterioles from children with normal renal function, CKD5, and on PD, respectively, are given in the upper part and quantification of arteriolar pSMAD2/3 and VEGF-A abundance in (A and C) omental and (B and D) parietal peritoneal arterioles in the lower part. Scale bars represent 100 µm. Individual data points, median, and IQR are given. * P<0.05, ** P<0.01 versus CKD5; # P<0.05; ## P<0.01 versus controls.

Figure 6.
Figure 6.

In parietal arterioles TGF-β–induced pSMAD2/3 abundance correlates with (A) C1q and (B) TCC (rho=0.5/r=0.41, P<0.01/P<0.05) and inversely correlates with (C) L/V ratio (r=−0.5, P<0.01). Triangles represent children with CKD5, circles children on PD.

Effect of PD Fluid Type and Patient Characteristics

Endothelial complement abundance in children with CKD5 and in those on PD was independent of age and not correlated with estimated GFR, BMI, BP, or biochemical findings (Table 2). In patients on PD, complement findings did not correlate with PD duration or residual urine output and were similar in patients with and without history of peritonitis.

Two different types of double-chamber PD fluids were applied, containing different concentrations of GDP. Out of the 15 PD children of the validation cohort, ten were treated with a pure bicarbonate buffered PD fluid and low GDP content, and five with a bicarbonate-lactate buffered PD fluid with a higher total GDP and 3,4-dideoxyglucosone-3-ene (3,4DGE) content. Total glucose exposure was 92±42 and 111±54 g/m2 per day (P=0.45). Total GDP exposure was 107±49 and 874±346 µmol/m2 per day, and 3,4DGE exposure 4.6±2.1 and 67±17 µmol/m2 per day with the bicarbonate and the bicarbonate-lactate buffered PD fluids, respectively (P<0.001 for total GDP and 3,4DGE exposure). Peritoneal arteriolar cross-sectional C1q pixel intensity was 25.4 (20.5) in the group with high GDP exposure and 5.3 (9.9) with lower peritoneal GDP exposure (P<0.05), whereas C3d and TCC abundance was similar in both groups. Peritoneal arteriolar cross-sectional VEGF-A positivity was 21.1 (35.2) % in children with higher GDP exposure and 5.0 (6.7) % in children exposed to less GDP (P<0.05). Arteriolar pSMAD2/3 abundance was similar in both groups.

Discussion

This is the first study to analyze the effects of CKD and PD on arteriolar transcriptomic and proteomic profiles. Cohorts of young children with underlying diseases not affecting vessel integrity, with normal BP, and devoid of hypertension and lifestyle-related risk factors such as smoking or obesity, were selected. This allowed for a highly sensitive differential analysis of CKD-associated and PD-induced molecular arteriopathic mechanisms.

The salient finding of the study is the consistent activation of the complement system in the arteriolar endothelium of patients on PD. Transcriptomics demonstrated differential regulation of genes involved in immune response and inflammation in arterioles from children on PD versus CKD5, with the highest enrichment found for complement-associated biologic processes. Transcriptomic and proteomic ratios of complement-associated genes showed a concordant pattern, proving both transcriptional and translational activation of the complement system. Because of the high abundance of complement proteins, we not only obtained almost complete coverage of the complement pathway but we were also able to demonstrate global activation effects on the level of biologically relevant fragments of complement components. The findings were confirmed immunohistochemically in independent cohorts of children with CKD5 and on PD. Key components of both the classic and alternative complement pathway and the terminal complement complex correlated with PD-associated glucose exposure, degree of arteriolopathy, and vascular pSMAD2/3 abundance. The upper 2–3 mm of the peritoneum participate in the exchange of fluid and solutes, with 90% of the concentration changes occurring within the first 400 μm.20,21 Findings were more pronounced in parietal arterioles exposed to PD fluids than in omental arterioles surrounded by at least 1 mm of fat tissue. In children with CKD5, endothelial arteriolar complement abundance was only slightly increased as compared with children with normal renal function.

The outcome of patients on PD is substantially compromised by infection and by the local and systemic toxicity of PD fluids, which contain supra-physiologic concentrations of lactate, glucose, and GDP at an acidic pH. Multichambered PD fluids separate glucose from the buffer compound during production and storage and therefore contain less GDP at neutral pH. GDPs are absorbed into the circulation and increase systemic advanced glycation end products (AGE) load.22,23 The clinical effect of lower GDP and AGE exposure in patients on PD is uncertain, and their role in dialysis-associated accelerated CVD is only partly understood.24 Recent randomized trials suggest better preservation of residual renal function, a slightly better preservation of the peritoneal membrane transporter function, and a reduction in peritonitis incidence and severity in association with the use of low-GDP fluids.25–27 Experimental studies provide evidence for less depression of the innate and adaptive immune response with these fluids.28 Other trials, however, did not reconfirm these findings,29,30 and a recent Cochrane analysis yielded sufficient evidence in favor of low-GDP fluids only with respect to preservation of residual renal function.15 The effect on patient outcome remains unclear.31 The effect of GDP and PD fluids on the complement system has not been studied in detail. Effluent and in vitro mesothelial cell studies suggest upregulation of the complement system by glucose and PD fluids.32,33 The findings in our pediatric patients on PD neither support the notion of a reconstituted host defense system nor do they suggest any cardiovascular benefits. Multichamber, low-GDP fluids significantly activate the endothelial complement and complement regulatory pathways. All individuals studied were devoid of clinical or biochemical signs of acute, local, or systemic inflammatory disease. In a large, adult PD cohort, effluent complement factor concentrations have been associated with worse survival.34

In patients with diabetes, clinical and experimental studies have provided evidence for a significant role of the complement system in the pathogenesis of vascular disease. TCC inhibitor CD59 is suppressed by glycation and AGEs bind C1q and activate TCC downstream cascades, which induce the release of proinflammatory and prothrombotic cytokines and growth factors, promoting diabetic vasculopathy.35–37 These findings are in line with our observations of peritoneal and omental endothelial complement activation correlating with intraperitoneal glucose exposure and with the degree of vasculopathy. PD fluids contain 10–40-fold supra-physiologic glucose concentrations, create a local diabetic milieu, and promote local and systemic AGE formation.38

Furthermore, complement activation and the degree of vasculopathy were found to be correlated with parietal arteriolar pSMAD2/3 abundance. Arteriolar TGF-β signaling was significantly increased in children with CKD5 and even further increased in children on PD. The TGF-β signaling pathway is a well established mediator of PD fluid toxicity39 and involved in arteriolopathy.40 Recent genome wide association studies and systems biology have identified the TGF-β–SMAD pathway to be strongly associated with coronary artery disease.40 Experimental studies demonstrate a multifunctional and context-dependent role, comprising induction of vascular smooth muscle cell proliferation, hypertrophy and migration, extracellular matrix accumulation, inhibition of smooth muscle cell relaxation, and anti-inflammatory effects.40 The precise role of the TGF-β–SMAD signaling pathway in the initiation and progression of artery disease is still vague. Here, we provide the first evidence that this pathway may also play a role in PD-induced vasculopathy.

VEGF-A is induced by PD fluids in mesothelial cells and is secreted by submesothelial cells that have undergone epithelial mesenchymal transition, promoting peritoneal angiogenesis.41 VEGF-A protects from complement-mediated retinal and glomerular microvasculopathy42 and promotes intraplaque vascularization and thus progression of atherosclerosis.43,44 We therefore measured VEGF-A in omental and parietal arterioles, but neither found a CKD5- or PD-associated upregulation in the transcriptomics or proteomics study, nor a consistent upregulation in the validation cohort, nor an association with complement activation or the degree of vasculopathy.

A major strength of this study is the careful selection of a unique cohort of young pediatric patients largely devoid of confounding factors in combination with the open omics approach. The reported associations of elements of the complement system with peritoneal glucose exposure and arteriolar vasculopathy may indicate a causative pathomechanism. Complement activation was more pronounced in parietal arterioles than in fat-surrounded omental arterioles and in the children treated with PD fluid with higher GDP content. Notably, the latter comparison comprises small patient numbers only; the statistical power is low. Because most of the 31 centers participating in the International Pediatric Peritoneal Biopsy Study use multichamber, low-GDP fluids, we were unable to obtain sufficient tissue to study the effect of single-chamber PD fluids, which have the highest GDP content, on vascular complement. In rats,45 the physiologic response to inflammatory stimuli is suppressed to a greater extend with single-chamber, high-GDP PD fluids as compared with double-chamber, low-GDP fluids. Thus, we cannot rule out that the activation of the endothelial complement system in our patients on low-GDP dialysis fluid reflects a more physiologic immune response pattern as compared with treatment with high-GDP fluids. However, on the basis of our findings it is tempting to speculate that complement activation and vasculopathy is even more pronounced with high-GDP fluids. A recent biopsy study in 23 adult patients on PD46 suggested a lower degree of peritoneal vasculopathy with low- as compared with single-chamber, high-GDP fluids.

In summary, our study in a highly selected cohort of children with ESRD before dialysis and on chronic PD demonstrates marked activation of the arteriolar complement system and the TGF-β signaling cascade, which is quantitatively correlated with dialytic glucose exposure and the severity of arteriolar vasculopathy.

Concise Methods

Patient Characteristics

Fifty-three children (22 girls) were included in the study. Omental and parietal peritoneal specimens were obtained from 11 children with normal renal function undergoing elective surgery for local diseases not affecting the peritoneal vasculature, 21 children with CKD5 at time of PD catheter insertion, and 21 children on PD with low-GDP, pH neutral dialysis fluid. Thirteen out of the 21 children on PD underwent tissue sampling at time of transplantation, three during catheter revision, two with bladder reconstruction, and one during hernia repair, catheter removal, and catheter exchange, respectively. Children with increased BP, clinical signs of infection, or increased C reactive protein were excluded from the study. None of the children were obese (BMI>90th age-related percentile), were smoking, or had a history of smoking. Six omental samples per group were used for transcriptomics and proteomics; five, 15, and 15 omental and parietal samples were obtained from children with normal renal function, CKD5, and on PD, respectively, for validation of complement findings. Seven patients of the validation cohort and one patient of the omics cohort had a history of peritonitis, with median 42 (range, 9–150) weeks before biopsy. GFR was estimated according to Schwartz formula. Seven of the 21 patients on PD were oligo-anuric; all seven were part of the validation cohort. Two omental samples from the PD validation cohort had to be excluded due to inadequate tissue quality and insufficient quantity, respectively. Underlying diseases of the children with renal diseases were congenital abnormalities of the kidney and urinary tract (23), nephronophthisis (8), congenital nephrotic syndrome (5), hereditary FSGS (2), autosomal recessive polycystic kidney disease (1), perinatal asphyxia (1), hereditary tubular disorder (1), and meningomyelocele (1).

Fifteen children were dialyzed with a double-chamber PD fluid containing 34 mmol/L of bicarbonate (BicaVera; Fresenius Medical Care, Bad Homburg, Germany), and six children with a double-chamber PD fluid containing 25 mmol/L bicarbonate and 15 mmol/L lactate (Physioneal; Baxter Healthcare Corporation, Deerfield, IL). The PD fluids were similar in pH, electrolyte composition, and osmolarity, but differed in buffer, and in total GDP and 3,4 DGE content (BicaVera 1.5% glucose: 17.2 and 0.7 µmol/L; 2.3% glucose: 28.5 and 1.3 µmol/L. Physioneal 1.36% glucose: 114 and 9.9 µmol/L; 2.27% glucose: 163 and 14.3 µmol/L; 3.86% glucose: 214 and 12.4 µmol/L total GDP and 3,4 DGE, respectively).47,48 Dialytic glucose, total GDP, and 3,4 DGE exposure was calculated as the glucose/GDP/3,4DGE content of the PD solution × volume of instilled solution × number of cycles and corrected for body surface area.

Comprehensive individual clinical data were collected and assessed before analysis to exclude disparity regarding disease susceptibility or comorbidity. Blood was drawn within 24 hours before tissue sampling in all patients. The United States center only provided samples from children with CKD5. Approval was obtained from local ethical committees, and written informed consent from patient and parents. The study was performed according to the Declaration of Helsinki and registered at www.clinicaltrials.gov (NCT01893710).

Histomorphometry

Specimens obtained during surgery were instantaneously frozen with liquid nitrogen and stored at −80°C. Arterioles macroscopically located within fat tissue and microscopically at least 1 mm distant from the surface were microdissected, Elastica van Gieson (EvG)–stained, and analyzed by histomorphometry. EvG stainings of the arteriolar elastic lamina were used as templates for microdissection of arterioles from cresol violet–stained neighboring sections. Slides 100-µm thick were cut on a Leica cryotome CM1950 and 40 deep-frozen arteriolar rings per patient microdissected using a Leica S8 APO stereo microscope and a microneedle. Homogenization with beads on a Tissue Lyser (Qiagen, Hildesheim, Germany) was performed in RLT Buffer with 1% β-mercaptoethanol and glycogen for RNA isolation. RNA from ten arteriolar rings per patient was isolated using RNAeasy Micro Kit (Qiagen, Hildesheim, Germany) with on-column DNA digestion according to manufacturer instructions, and quantified with Pico RNA 6000 Pico Chip (Agilent, Santa Clara). Samples with RNA integrity number >7 and a target concentration of at least 2.5 ng in a maximal volume of 5 µl were used for transcriptomics. For proteomic analyses, 30 arteriolar rings per patient were microdissected and lysed in DIGE buffer (30 mM Tris, pH 8.5, 7M urea, 2M thiourea, 4% 3-[(3-Cholamidopropyl) dimethylammonio]-1-propanesulfonate, 1 mM EDTA, one tablet of Complete Protease Inhibitor (Roche, Basel, Switzerland) and one tablet of phosphatase inhibitor (PhosSTOP; Roche)) per 100 ml. The resulting lysates were stored at −80°C until further processing. SDS-page gel was run for quality control and quantification of protein content.

Transcriptomics

Microarray analysis was performed using Illumina Human Sentrix Beads (Illumina, San Diego) according to the manufacturer’s protocol. Microarray scanning was done using an iScan array scanner. Data extraction was done for all beads individually, and outliers were removed when the absolute difference to the median was >2.5 times MAD (2.5 Hampel’s method). Remaining bead level data points were quantile normalized.49 For microarray data preprocessing, t test was used to assess positive expression against background. The average expression value was calculated as the mean of measured expressions of all beads together. Raw RNA-seq data were submitted to ArrayExpress under the accession E-MTAB-5695. Out of 48,107 ProbeIDs on the chip, 8703 transcripts remained after deletion of average expression values with a detection P value >0.05, exclusion of transcripts with less than two observations per group, and removal of transcripts with a median absolute deviation of the average expression values <20.

Proteomics

Proteomic analysis was performed using high-performance LC-MS. In brief, filter-aided sample preparation was performed according to the procedure described by Wiśniewski et al.50 TMT labeling was performed according to the instructions provided by the manufacturer. Pooled samples were concentrated and desalted with C18 microspin columns (5−60 μg; The Nest Group, Southborough, MA). Eluates were dried in a vacuum concentrator and reconstituted in 2 mM ammonia formate buffer, pH 10, before fractionation at basic pH. Two-dimensional liquid chromatography was performed by reverse-phase chromatography at high pH on an offline Agilent 1200 series HPLC collecting 20 time-based fractions, as previously described.51,52 Fractions were analyzed at low pH on an Agilent 1200 series nanoHPLC coupled directly to a Q Exactive mass spectrometer (Thermo Fisher Scientific, Waltham, MA). The acquired raw MS data files were processed and searched against the human SwissProt database (downloaded on 29 Jan 2017) with the Andromeda search engine using MaxQuant.53 One missed tryptic cleavage site was allowed. Carbamidomethyl cysteine, N-terminal, and lysine-modified TMT 10-plex were set as fixed modifications, and oxidized methionine was set as a variable modification. Protein ratios were calculated on the basis of unique and razor peptides. Raw LC-MS data were submitted to PRIDE54 under the accession PXD006298.

Immunofluorescence

For validation of complement system activation in arterioles, another set of age-matched samples from patients who were uremic and patients on PD was used. Immunofluorescence staining was performed on formalin-fixed paraffin-embedded samples, using FITC polyclonal goat anti-C1q Primary Antibody (Ventana Medical Systems Inc., Roche, Tucson). All samples were stained in the same run and the pictures taken on the same day. Signal intensity was quantified with Image J.55 After splitting the color channels, endothelium was marked as region of interest (ROI). Positivity was quantified as intensity of the pixels in ROI minus background normalized for ROI area. The microscope settings and exposure time were the same for all samples (exposure: 202 milliseconds for L5 channel and 65.8 for DAPI; γ: 2.88; gain: 1.5; capture format: 2560×1920; magnification: 20×).

Immunohistochemistry

Immunohistochemistry was performed on formalin-fixed tissue sections according to standard methods. Dewaxed and rehydrated tissue sections were incubated in 3% hydrogen peroxide to block endogenous peroxidases. The heat-induced antigen retrieval was performed in a pressure cooker, using the 0.01 or 0.005 M citrate buffer, pH 6. The primary antibodies were applied for 1 hour at room temperature or overnight at 4°C. Incubation with biotinylated secondary reagents for 30 minutes was followed by the ABC reagent (both from Vector Laboratories, Burlingame). DAB and Sirius Red (Sigma, Taufkirchen, Germany) were used for detection. Universal blocking reagent in PBS (1:100) without primary antibody was used for negative control. Cell nuclei were counterstained with hematoxylin. C1q antibody was obtained from Ventana (Roche Diagnostics, Basel, Switzerland); C3d, C4d, TCC (Clone aE11), and CD31 (clone JC70A) were obtained from Dako (Dako Cytomation, Glostrup, Denmark); VEGF-A antibody from Abcam (ab46154, Cambridge, United Kingdom); and pSMAD2/3 from Santa Cruz Biotechnology (sc-11769, Santa Cruz).

Digital Image Analysis

Immunohistochemical stainings were evaluated using the Aperio Positive Pixel Count Algorithm (version 9) for quantification of the amounts of positive pixels per scanned virtual slide. Arterioles were marked as ROI, excluding surrounding fat tissue and lumen. Intensity ranges for weak, medium, and strong signals and negative pixels were validated for each specific staining. Positivity was calculated as total number of positive pixels divided by total number of pixels in ROI area.

Vasculopathy Evaluation

Vasculopathy was defined as endothelial wall thickening and lumen narrowing as described before.56 The extent of vasculopathy was determined on CD31 stained slides by evaluation of the ratio of luminal diameter to vessel external diameter (L/V), of 5–10 arterioles per patient sample. The measurements were done in short axis to avoid artificial effects of elongated distance due to tangential cutting of the vessel during the histologic preparation. EvG staining was performed to see if vasculopathy developed due to thickening of intima or media.

Statistical Analyses

The study comprised a screening phase aiming at the identification of the most promising expression differences, followed by validation of the strongest expression differences in independent samples. Calculations of the required sample size for validation of initial expression differences identified in the omics-screening cohort relied on t tests, and they pointed to seven samples per group for top candidate genes (statistical power, 80%, and type I error rates without multiplicity adjustment, 5%). Gene enrichment analyses were conducted on the basis of three main categories: biologic process, molecular function, and cellular component, using the PANTHER online database.57 In validation experiments, data were summarized using means (SD) or medians (IQR), as appropriate. Normal distribution was graphically assessed. Pearson’s or Spearman’s correlations were used as appropriate on the basis of the data distribution. To compare data between three groups of children, ANOVA or Kruskal–Wallis test were used, on the basis of the data distribution. To compare two groups of children, t test or Mann–Whitney test were used, as appropriate. ANOVA and subsequent post hoc tests (Tukey’s) were used to examine possible differences in baseline characteristics of the investigated omic-screening and validation cohorts. In all statistics, two-sided tests were used; P<0.05 was considered significant.

Disclosures

None.

Acknowledgments

We are grateful to Dr. E. Herpel and Mr. J. Moyers from the Tissue Bank of the National Center for Tumor Diseases (Heidelberg, Germany) and the Institute of Pathology (Heidelberg University Hospital), as well as Mr. M. Unterwurzacher and Ms. A. Wagner (Christian Doppler Laboratory for Molecular Stress Research in Peritoneal Dialysis Vienna, Austria) for technical assistance.

M.B. and S.T. were supported by the European Training and Research in Peritoneal Dialysis (EuTRiPD) program, a project funded by the European Union within the Marie Curie Scheme (287813). Parts of the study were funded by a grant of the German Research Foundation (Sonderforschungsbereich 1118). The financial support of K.K. by the Austrian Federal Ministry of Science, Research and Economy and the National Foundation for Research, Technology and Development (CD10278101) is gratefully acknowledged. Research at Research Center for Molecular Medicine of the Austrian Academy of Sciences is supported by the Austrian Academy of Sciences.

M.B. contributed to the conception of the study, collected and microdissected specimens, performed immunostainings and digital imaging analyses, and wrote the manuscript. B.S. contributed to the conception of the study, collected specimens, performed digital imaging analyses, and contributed to the manuscript. J.L.B. analyzed transcriptomic data and contributed to the manuscript. S.T. contributed to the proteomic analysis and the manuscript. F.L. contributed to microdissections, immunostainings, and analyses, and to the manuscript. S.M.-G. contributed to immunostainings, analyses, and the manuscript. P.S. contributed to digital imaging analyses. B.A.W. contributed to the conception of the study, contributed specimens from children with CKD5, and contributed to analyses and the manuscript. A.Z. collected specimens and contributed to analyses and the manuscript. K.P. performed the liquid chromatography coupled to mass spectrometry analysis and contributed to the manuscript. P.M. contributed to the bioinformatic analysis and the manuscript. K.L.B. contributed to the proteomic analysis and the manuscript. J.O. collected specimens, and contributed to complement analyses and the manuscript. C.A. contributed to the conception of the study, analyses, and the manuscript. F.S. contributed to the conception of the study, analyses, and the manuscript. K.K. conceptualized the crossomic and proteomic study, performed proteomic and bioinformatic analysis, and contributed to the manuscript. C.P.S. conceptualized the study; contributed to microdissection, immunostainings, and digital imaging analyses; and wrote the manuscript. All authors reviewed the manuscript.

Footnotes

References

  1. ↵
    1. McDonald SP,
    2. Craig JC; Australian and New Zealand Paediatric Nephrology Association
    : Long-term survival of children with end-stage renal disease. N Engl J Med 350: 2654–2662, 2004pmid:15215481
    OpenUrlCrossRefPubMed
  2. ↵
    1. Chesnaye N,
    2. Bonthuis M,
    3. Schaefer F,
    4. Groothoff JW,
    5. Verrina E,
    6. Heaf JG,
    7. Jankauskiene A,
    8. Lukosiene V,
    9. Molchanova EA,
    10. Mota C,
    11. Peco-Antić A,
    12. Ratsch IM,
    13. Bjerre A,
    14. Roussinov DL,
    15. Sukalo A,
    16. Topaloglu R,
    17. Van Hoeck K,
    18. Zagozdzon I,
    19. Jager KJ,
    20. Van Stralen KJ; ESPN/ERA–EDTA registry
    : Demographics of paediatric renal replacement therapy in Europe: A report of the ESPN/ERA-EDTA registry. Pediatr Nephrol 29: 2403–2410, 2014pmid:25039018
    OpenUrlCrossRefPubMed
  3. ↵
    1. Oh J,
    2. Wunsch R,
    3. Turzer M,
    4. Bahner M,
    5. Raggi P,
    6. Querfeld U,
    7. Mehls O,
    8. Schaefer F
    : Advanced coronary and carotid arteriopathy in young adults with childhood-onset chronic renal failure. Circulation 106: 100–105, 2002pmid:12093777
    OpenUrlAbstract/FREE Full Text
  4. ↵
    1. de Jager DJ,
    2. Grootendorst DC,
    3. Jager KJ,
    4. van Dijk PC,
    5. Tomas LM,
    6. Ansell D,
    7. Collart F,
    8. Finne P,
    9. Heaf JG,
    10. De Meester J,
    11. Wetzels JF,
    12. Rosendaal FR,
    13. Dekker FW
    : Cardiovascular and noncardiovascular mortality among patients starting dialysis. JAMA 302: 1782–1789, 2009pmid:19861670
    OpenUrlCrossRefPubMed
  5. ↵
    1. Kari JA,
    2. Donald AE,
    3. Vallance DT,
    4. Bruckdorfer KR,
    5. Leone A,
    6. Mullen MJ,
    7. Bunce T,
    8. Dorado B,
    9. Deanfield JE,
    10. Rees L
    : Physiology and biochemistry of endothelial function in children with chronic renal failure. Kidney Int 52: 468–472, 1997pmid:9264003
    OpenUrlCrossRefPubMed
  6. ↵
    1. Litwin M,
    2. Wühl E,
    3. Jourdan C,
    4. Niemirska A,
    5. Schenk JP,
    6. Jobs K,
    7. Grenda R,
    8. Wawer ZT,
    9. Rajszys P,
    10. Mehls O,
    11. Schaefer F
    : Evolution of large-vessel arteriopathy in paediatric patients with chronic kidney disease. Nephrol Dial Transplant 23: 2552–2557, 2008pmid:18344239
    OpenUrlCrossRefPubMed
  7. ↵
    1. Goodman WG,
    2. Goldin J,
    3. Kuizon BD,
    4. Yoon C,
    5. Gales B,
    6. Sider D,
    7. Wang Y,
    8. Chung J,
    9. Emerick A,
    10. Greaser L,
    11. Elashoff RM,
    12. Salusky IB
    : Coronary-artery calcification in young adults with end-stage renal disease who are undergoing dialysis. N Engl J Med 342: 1478–1483, 2000pmid:10816185
    OpenUrlCrossRefPubMed
  8. ↵
    1. Litwin M,
    2. Wühl E,
    3. Jourdan C,
    4. Trelewicz J,
    5. Niemirska A,
    6. Fahr K,
    7. Jobs K,
    8. Grenda R,
    9. Wawer ZT,
    10. Rajszys P,
    11. Tröger J,
    12. Mehls O,
    13. Schaefer F
    : Altered morphologic properties of large arteries in children with chronic renal failure and after renal transplantation. J Am Soc Nephrol 16: 1494–1500, 2005pmid:15772249
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Shroff RC,
    2. McNair R,
    3. Skepper JN,
    4. Figg N,
    5. Schurgers LJ,
    6. Deanfield J,
    7. Rees L,
    8. Shanahan CM
    : Chronic mineral dysregulation promotes vascular smooth muscle cell adaptation and extracellular matrix calcification. J Am Soc Nephrol 21: 103–112, 2010pmid:19959717
    OpenUrlAbstract/FREE Full Text
  10. ↵
    1. Brady TM,
    2. Schneider MF,
    3. Flynn JT,
    4. Cox C,
    5. Samuels J,
    6. Saland J,
    7. White CT,
    8. Furth S,
    9. Warady BA,
    10. Mitsnefes M
    : Carotid intima-media thickness in children with CKD: Results from the CKiD study. Clin J Am Soc Nephrol 7: 1930–1937, 2012pmid:22977209
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. van de Luijtgaarden MW,
    2. Jager KJ,
    3. Segelmark M,
    4. Pascual J,
    5. Collart F,
    6. Hemke AC,
    7. Remón C,
    8. Metcalfe W,
    9. Miguel A,
    10. Kramar R,
    11. Aasarød K,
    12. Abu Hanna A,
    13. Krediet RT,
    14. Schön S,
    15. Ravani P,
    16. Caskey FJ,
    17. Couchoud C,
    18. Palsson R,
    19. Wanner C,
    20. Finne P,
    21. Noordzij M
    : Trends in dialysis modality choice and related patient survival in the ERA-EDTA registry over a 20-year period. Nephrol Dial Transplant 31: 120–128, 2016pmid:26311215
    OpenUrlCrossRefPubMed
  12. ↵
    1. Mehrotra R,
    2. Devuyst O,
    3. Davies SJ,
    4. Johnson DW
    : The current state of peritoneal dialysis. J Am Soc Nephrol 27: 3238–3252, 2016pmid:27339663
    OpenUrlAbstract/FREE Full Text
  13. ↵
    1. Wu HY,
    2. Hung KY,
    3. Huang TM,
    4. Hu FC,
    5. Peng YS,
    6. Huang JW,
    7. Lin SL,
    8. Chen YM,
    9. Chu TS,
    10. Tsai TJ,
    11. Wu KD
    : Safety issues of long-term glucose load in patients on peritoneal dialysis--a 7-year cohort study. PLoS One 7: e30337, 2012pmid:22303440
    OpenUrlCrossRefPubMed
  14. ↵
    1. Mehrotra R,
    2. de Boer IH,
    3. Himmelfarb J
    : Adverse effects of systemic glucose absorption with peritoneal dialysis: How good is the evidence? Curr Opin Nephrol Hypertens 22: 663–668, 2013pmid:24076559
    OpenUrlCrossRefPubMed
  15. ↵
    1. Cho Y,
    2. Johnson DW,
    3. Craig JC,
    4. Strippoli GF,
    5. Badve SV,
    6. Wiggins KJ
    : Biocompatible dialysis fluids for peritoneal dialysis. Cochrane Database Syst Rev 27(3): CD007554, 2014pmid:24671928
    OpenUrlPubMed
  16. ↵
    1. De Ciuceis C,
    2. Porteri E,
    3. Rizzoni D,
    4. Rizzardi N,
    5. Paiardi S,
    6. Boari GE,
    7. Miclini M,
    8. Zani F,
    9. Muiesan ML,
    10. Donato F,
    11. Salvetti M,
    12. Castellano M,
    13. Tiberio GA,
    14. Giulini SM,
    15. Agabiti Rosei E
    : Structural alterations of subcutaneous small-resistance arteries may predict major cardiovascular events in patients with hypertension. Am J Hypertens 20: 846–852, 2007pmid:17679031
    OpenUrlCrossRefPubMed
    1. Christensen KL,
    2. Mulvany MJ
    : Location of resistance arteries. J Vasc Res 38: 1–12, 2001pmid:11173989
    OpenUrlPubMed
    1. Rizzoni D,
    2. Porteri E,
    3. Boari GE,
    4. De Ciuceis C,
    5. Sleiman I,
    6. Muiesan ML,
    7. Castellano M,
    8. Miclini M,
    9. Agabiti-Rosei E
    : Prognostic significance of small-artery structure in hypertension. Circulation 108: 2230–2235, 2003pmid:14557363
    OpenUrlAbstract/FREE Full Text
  19. ↵
    1. Vakili BA,
    2. Okin PM,
    3. Devereux RB
    : Prognostic implications of left ventricular hypertrophy. Am Heart J 141: 334–341, 2001pmid:11231428
    OpenUrlCrossRefPubMed
  20. ↵
    1. Stachowska-Pietka J,
    2. Waniewski J,
    3. Flessner MF,
    4. Lindholm B
    : Computer simulations of osmotic ultrafiltration and small-solute transport in peritoneal dialysis: A spatially distributed approach. Am J Physiol Renal Physiol 302: F1331–F1341, 2012pmid:22301624
    OpenUrlCrossRefPubMed
  21. ↵
    1. Flessner MF,
    2. Fenstermacher JD,
    3. Dedrick RL,
    4. Blasberg RG
    : A distributed model of peritoneal-plasma transport: Tissue concentration gradients. Am J Physiol 248: F425–F435, 1985pmid:3919596
    OpenUrlPubMed
  22. ↵
    1. Schmitt CP,
    2. von Heyl D,
    3. Rieger S,
    4. Arbeiter K,
    5. Bonzel KE,
    6. Fischbach M,
    7. Misselwitz J,
    8. Pieper AK,
    9. Schaefer F; Mid European Pediatric Peritoneal Dialysis Study Group (MEPPS)
    : Reduced systemic advanced glycation end products in children receiving peritoneal dialysis with low glucose degradation product content. Nephrol Dial Transplant 22: 2038–2044, 2007pmid:17420168
    OpenUrlCrossRefPubMed
  23. ↵
    1. Zeier M,
    2. Schwenger V,
    3. Deppisch R,
    4. Haug U,
    5. Weigel K,
    6. Bahner U,
    7. Wanner C,
    8. Schneider H,
    9. Henle T,
    10. Ritz E
    : Glucose degradation products in PD fluids: Do they disappear from the peritoneal cavity and enter the systemic circulation? Kidney Int 63: 298–305, 2003pmid:12472796
    OpenUrlCrossRefPubMed
  24. ↵
    1. Stinghen AE,
    2. Massy ZA,
    3. Vlassara H,
    4. Striker GE,
    5. Boullier A
    : Uremic toxicity of advanced glycation end products in CKD. J Am Soc Nephrol 27: 354–370, 2016pmid:26311460
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Johnson DW,
    2. Brown FG,
    3. Clarke M,
    4. Boudville N,
    5. Elias TJ,
    6. Foo MW,
    7. Jones B,
    8. Kulkarni H,
    9. Langham R,
    10. Ranganathan D,
    11. Schollum J,
    12. Suranyi MG,
    13. Tan SH,
    14. Voss D; balANZ Trial Investigators
    : The effects of biocompatible compared with standard peritoneal dialysis solutions on peritonitis microbiology, treatment, and outcomes: The balANZ trial. Perit Dial Int 32: 497–506, 2012pmid:22991015
    OpenUrlAbstract/FREE Full Text
    1. Kim SG,
    2. Kim S,
    3. Hwang YH,
    4. Kim K,
    5. Oh JE,
    6. Chung W,
    7. Oh KH,
    8. Kim HJ,
    9. Ahn C; Korean Balnet Study Group
    : Could solutions low in glucose degradation products preserve residual renal function in incident peritoneal dialysis patients? A 1-year multicenter prospective randomized controlled trial (Balnet Study). Perit Dial Int 28[Suppl 3]: S117–S122, 2008pmid:18552239
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Johnson DW,
    2. Brown FG,
    3. Clarke M,
    4. Boudville N,
    5. Elias TJ,
    6. Foo MW,
    7. Jones B,
    8. Kulkarni H,
    9. Langham R,
    10. Ranganathan D,
    11. Schollum J,
    12. Suranyi M,
    13. Tan SH,
    14. Voss D; balANZ Trial Investigators
    : Effects of biocompatible versus standard fluid on peritoneal dialysis outcomes. J Am Soc Nephrol 23: 1097–1107, 2012pmid:22440906
    OpenUrlAbstract/FREE Full Text
  28. ↵
    1. Mortier S,
    2. Lameire NH,
    3. De Vriese AS
    : The effects of peritoneal dialysis solutions on peritoneal host defense. Perit Dial Int 24: 123–138, 2004pmid:15119633
    OpenUrlAbstract
  29. ↵
    1. Park SH,
    2. Do JY,
    3. Kim YH,
    4. Lee HY,
    5. Kim BS,
    6. Shin SK,
    7. Kim HC,
    8. Chang YK,
    9. Yang JO,
    10. Chung HC,
    11. Kim CD,
    12. Lee WK,
    13. Kim JY,
    14. Kim YL
    : Effects of neutral pH and low-glucose degradation product-containing peritoneal dialysis fluid on systemic markers of inflammation and endothelial dysfunction: A randomized controlled 1-year follow-up study. Nephrol Dial Transplant 27: 1191–1199, 2012pmid:21862454
    OpenUrlCrossRefPubMed
  30. ↵
    1. Bajo MA,
    2. Pérez-Lozano ML,
    3. Albar-Vizcaino P,
    4. del Peso G,
    5. Castro MJ,
    6. Gonzalez-Mateo G,
    7. Fernández-Perpén A,
    8. Aguilera A,
    9. Sánchez-Villanueva R,
    10. Sánchez-Tomero JA,
    11. López-Cabrera M,
    12. Peter ME,
    13. Passlick-Deetjen J,
    14. Selgas R
    : Low-GDP peritoneal dialysis fluid (‘balance’) has less impact in vitro and ex vivo on epithelial-to-mesenchymal transition (EMT) of mesothelial cells than a standard fluid. Nephrol Dial Transplant 26: 282–291, 2011pmid:20571097
    OpenUrlCrossRefPubMed
  31. ↵
    1. Yohanna S,
    2. Alkatheeri AM,
    3. Brimble SK,
    4. McCormick B,
    5. Iansavitchous A,
    6. Blake PG,
    7. Jain AK
    : Effect of neutral-pH, low-glucose degradation product peritoneal dialysis solutions on residual renal function, urine volume, and ultrafiltration: A systematic review and meta-analysis. Clin J Am Soc Nephrol 10: 1380–1388, 2015pmid:26048890
    OpenUrlAbstract/FREE Full Text
  32. ↵
    1. Sei Y,
    2. Mizuno M,
    3. Suzuki Y,
    4. Imai M,
    5. Higashide K,
    6. Harris CL,
    7. Sakata F,
    8. Iguchi D,
    9. Fujiwara M,
    10. Kodera Y,
    11. Maruyama S,
    12. Matsuo S,
    13. Ito Y
    : Expression of membrane complement regulators, CD46, CD55 and CD59, in mesothelial cells of patients on peritoneal dialysis therapy. Mol Immunol 65: 302–309, 2015pmid:25725314
    OpenUrlCrossRefPubMed
  33. ↵
    1. Tang S,
    2. Leung JC,
    3. Chan LY,
    4. Tsang AW,
    5. Chen CX,
    6. Zhou W,
    7. Lai KN,
    8. Sacks SH
    : Regulation of complement C3 and C4 synthesis in human peritoneal mesothelial cells by peritoneal dialysis fluid. Clin Exp Immunol 136: 85–94, 2004pmid:15030518
    OpenUrlCrossRefPubMed
  34. ↵
    1. Zelek W,
    2. Harris CL,
    3. Topley N,
    4. Weeks I,
    5. Lambie M,
    6. Davies SJ,
    7. Morgan BP
    : Complement biomarkers in the management of peritoneal dialysis. Immunobiology 221: 1172, 2016
    OpenUrl
  35. ↵
    1. Ghosh P,
    2. Vaidya A,
    3. Sahoo R,
    4. Goldfine A,
    5. Herring N,
    6. Bry L,
    7. Chorev M,
    8. Halperin JA
    : Glycation of the complement regulatory protein CD59 is a novel biomarker for glucose handling in humans. J Clin Endocrinol Metab 99: E999–E1006, 2014pmid:24628556
    OpenUrlPubMed
    1. Chikazawa M,
    2. Shibata T,
    3. Hatasa Y,
    4. Hirose S,
    5. Otaki N,
    6. Nakashima F,
    7. Ito M,
    8. Machida S,
    9. Maruyama S,
    10. Uchida K
    : Identification of C1q as a binding protein for advanced glycation end products. Biochemistry 55: 435–446, 2016pmid:26731343
    OpenUrlPubMed
  37. ↵
    1. Ghosh P,
    2. Sahoo R,
    3. Vaidya A,
    4. Chorev M,
    5. Halperin JA
    : Role of complement and complement regulatory proteins in the complications of diabetes. Endocr Rev 36: 272–288, 2015pmid:25859860
    OpenUrlCrossRefPubMed
  38. ↵
    1. Jiang J,
    2. Chen P,
    3. Chen J,
    4. Yu X,
    5. Xie D,
    6. Mei C,
    7. Xiong F,
    8. Shi W,
    9. Zhou W,
    10. Liu X,
    11. Sun S,
    12. Zhang P,
    13. Yang X,
    14. Zhang Y,
    15. Zhang Y,
    16. Liang X,
    17. Zhang Z,
    18. Lin Q,
    19. Yu Y,
    20. Miyata T,
    21. Tian J,
    22. Liang M,
    23. Luo W,
    24. Xu X,
    25. Hou F
    : Accumulation of tissue advanced glycation end products correlated with glucose exposure dose and associated with cardiovascular morbidity in patients on peritoneal dialysis. Atherosclerosis 224: 187–194, 2012pmid:22857897
    OpenUrlPubMed
  39. ↵
    1. Loureiro J,
    2. Aguilera A,
    3. Selgas R,
    4. Sandoval P,
    5. Albar-Vizcaíno P,
    6. Pérez-Lozano ML,
    7. Ruiz-Carpio V,
    8. Majano PL,
    9. Lamas S,
    10. Rodríguez-Pascual F,
    11. Borras-Cuesta F,
    12. Dotor J,
    13. López-Cabrera M
    : Blocking TGF-β1 protects the peritoneal membrane from dialysate-induced damage. J Am Soc Nephrol 22: 1682–1695, 2011pmid:21742730
    OpenUrlAbstract/FREE Full Text
  40. ↵
    1. Zeng L,
    2. Dang TA,
    3. Schunkert H
    : Genetics links between transforming growth factor β pathway and coronary disease. Atherosclerosis 253: 237–246, 2016pmid:27596813
    OpenUrlPubMed
  41. ↵
    1. Selgas R,
    2. Bajo A,
    3. Jiménez-Heffernan JA,
    4. Sánchez-Tomero JA,
    5. Del Peso G,
    6. Aguilera A,
    7. López-Cabrera M
    : Epithelial-to-mesenchymal transition of the mesothelial cell--its role in the response of the peritoneum to dialysis. Nephrol Dial Transplant 21[Suppl 2]: ii2–ii7, 2006pmid:16825254
    OpenUrlCrossRefPubMed
  42. ↵
    1. Keir LS,
    2. Firth R,
    3. Aponik L,
    4. Feitelberg D,
    5. Sakimoto S,
    6. Aguilar E,
    7. Welsh GI,
    8. Richards A,
    9. Usui Y,
    10. Satchell SC,
    11. Kuzmuk V,
    12. Coward RJ,
    13. Goult J,
    14. Bull KR,
    15. Sharma R,
    16. Bharti K,
    17. Westenskow PD,
    18. Michael IP,
    19. Saleem MA,
    20. Friedlander M
    : VEGF regulates local inhibitory complement proteins in the eye and kidney. J Clin Invest 127: 199–214, 2017pmid:27918307
    OpenUrlCrossRefPubMed
  43. ↵
    1. Van der Veken B,
    2. De Meyer GR,
    3. Martinet W
    : Intraplaque neovascularization as a novel therapeutic target in advanced atherosclerosis. Expert Opin Ther Targets 20: 1247–1257, 2016pmid:27148888
    OpenUrlPubMed
  44. ↵
    1. Inoue M,
    2. Itoh H,
    3. Ueda M,
    4. Naruko T,
    5. Kojima A,
    6. Komatsu R,
    7. Doi K,
    8. Ogawa Y,
    9. Tamura N,
    10. Takaya K,
    11. Igaki T,
    12. Yamashita J,
    13. Chun TH,
    14. Masatsugu K,
    15. Becker AE,
    16. Nakao K
    : Vascular endothelial growth factor (VEGF) expression in human coronary atherosclerotic lesions: Possible pathophysiological significance of VEGF in progression of atherosclerosis. Circulation 98: 2108–2116, 1998pmid:9815864
    OpenUrlAbstract/FREE Full Text
  45. ↵
    1. Mortier S,
    2. De Vriese AS,
    3. McLoughlin RM,
    4. Topley N,
    5. Schaub TP,
    6. Passlick-Deetjen J,
    7. Lameire NH
    : Effects of conventional and new peritoneal dialysis fluids on leukocyte recruitment in the rat peritoneal membrane. J Am Soc Nephrol 14: 1296–1306, 2003pmid:12707398
    OpenUrlAbstract/FREE Full Text
  46. ↵
    1. del Peso G,
    2. Jiménez-Heffernan JA,
    3. Selgas R,
    4. Remón C,
    5. Ossorio M,
    6. Fernández-Perpén A,
    7. Sánchez-Tomero JA,
    8. Cirugeda A,
    9. de Sousa E,
    10. Sandoval P,
    11. Díaz R,
    12. López-Cabrera M,
    13. Bajo MA
    : Biocompatible dialysis solutions preserve peritoneal mesothelial cell and vessel wall integrity. A case-control study on human biopsies. Perit Dial Int 36: 129–134, 2016pmid:26475848
    OpenUrlAbstract/FREE Full Text
  47. ↵
    1. Frischmann M,
    2. Spitzer J,
    3. Fünfrocken M,
    4. Mittelmaier S,
    5. Deckert M,
    6. Fichert T,
    7. Pischetsrieder M
    : Development and validation of an HPLC method to quantify 3,4-dideoxyglucosone-3-ene in peritoneal dialysis fluids. Biomed Chromatogr 23: 843–851, 2009pmid:19353694
    OpenUrlCrossRefPubMed
  48. ↵
    1. Mittelmaier S,
    2. Fünfrocken M,
    3. Fenn D,
    4. Berlich R,
    5. Pischetsrieder M
    : Quantification of the six major α-dicarbonyl contaminants in peritoneal dialysis fluids by UHPLC/DAD/MSMS. Anal Bioanal Chem 401: 1183–1193, 2011pmid:21725830
    OpenUrlCrossRefPubMed
  49. ↵
    1. Bolstad B
    : Probe level quantile normalization of high density oligonucleotide array data, Berkeley, Division of Biostatistics, University of California, 2001
  50. ↵
    1. Wiśniewski JR,
    2. Zougman A,
    3. Nagaraj N,
    4. Mann M
    : Universal sample preparation method for proteome analysis. Nat Methods 6: 359–362, 2009pmid:19377485
    OpenUrlCrossRefPubMed
  51. ↵
    1. Maurer M,
    2. Müller AC,
    3. Parapatics K,
    4. Pickl WF,
    5. Wagner C,
    6. Rudashevskaya EL,
    7. Breitwieser FP,
    8. Colinge J,
    9. Garg K,
    10. Griss J,
    11. Bennett KL,
    12. Wagner SN
    : Comprehensive comparative and semiquantitative proteome of a very low number of native and matched epstein-barr-virus-transformed B lymphocytes infiltrating human melanoma. J Proteome Res 13: 2830–2845, 2014pmid:24803318
    OpenUrlPubMed
  52. ↵
    1. Bennett KL,
    2. Funk M,
    3. Tschernutter M,
    4. Breitwieser FP,
    5. Planyavsky M,
    6. Ubaida Mohien C,
    7. Müller A,
    8. Trajanoski Z,
    9. Colinge J,
    10. Superti-Furga G,
    11. Schmidt-Erfurth U
    : Proteomic analysis of human cataract aqueous humour: Comparison of one-dimensional gel LCMS with two-dimensional LCMS of unlabelled and iTRAQ®-labelled specimens. J Proteomics 74: 151–166, 2011pmid:20940065
    OpenUrlCrossRefPubMed
  53. ↵
    1. Tyanova S,
    2. Temu T,
    3. Cox J
    : The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11: 2301–2319, 2016pmid:27809316
    OpenUrlCrossRefPubMed
  54. ↵
    1. Vizcaíno JA,
    2. Csordas A,
    3. del-Toro N,
    4. Dianes JA,
    5. Griss J,
    6. Lavidas I,
    7. Mayer G,
    8. Perez-Riverol Y,
    9. Reisinger F,
    10. Ternent T,
    11. Xu QW,
    12. Wang R,
    13. Hermjakob H
    : 2016 update of the PRIDE database and its related tools. Nucleic Acids Res 44[D1]: D447–D456, 2016pmid:26527722
    OpenUrlCrossRefPubMed
  55. ↵
    1. Abramoff MD,
    2. Magalhaes PJ,
    3. Ram SJ
    : Image processing with ImageJ. Biophoton Int 11: 36–42, 2004
    OpenUrlCrossRef
  56. ↵
    1. Honda K,
    2. Hamada C,
    3. Nakayama M,
    4. Miyazaki M,
    5. Sherif AM,
    6. Harada T,
    7. Hirano H; Peritoneal Biopsy Study Group of the Japanese Society for Peritoneal Dialysis
    : Impact of uremia, diabetes, and peritoneal dialysis itself on the pathogenesis of peritoneal sclerosis: A quantitative study of peritoneal membrane morphology. Clin J Am Soc Nephrol 3: 720–728, 2008pmid:18272828
    OpenUrlAbstract/FREE Full Text
  57. ↵
    1. Mi H,
    2. Poudel S,
    3. Muruganujan A,
    4. Casagrande JT,
    5. Thomas PD
    : PANTHER version 10: Expanded protein families and functions, and analysis tools. Nucleic Acids Res 44(D1): D336–D342, 2016pmid:26578592
    OpenUrlCrossRefPubMed
View Abstract
Back to top

In this issue

View Selected Citations (0)
Print
Download PDF
Email Article
Citation Tools
Request Permissions
Complement Activation in Peritoneal Dialysis–Induced Arteriolopathy
Maria Bartosova, Betti Schaefer, Justo Lorenzo Bermejo, Silvia Tarantino, Felix Lasitschka, Stephan Macher-Goeppinger, Peter Sinn, Bradley A. Warady, Ariane Zaloszyc, Katja Parapatics, Peter Májek, Keiryn L. Bennett, Jun Oh, Christoph Aufricht, Franz Schaefer, Klaus Kratochwill, Claus Peter Schmitt
JASN Jan 2018, 29 (1) 268-282; DOI: 10.1681/ASN.2017040436
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo

Jump to section

Keywords