Literature DB >> 25949397

Biocompatibility of peritoneal dialysis solutions determined by genomics of human leucocytes: a cross-over study.

Julia Wilflingseder, Paul Perco, Alexander Kainz, Christoph Schwarz, Reka Korbély1, Bernd Mayer2, Rainer Oberbauer.   

Abstract

Entities:  

Year:  2009        PMID: 25949397      PMCID: PMC4421315          DOI: 10.1093/ndtplus/sfp129

Source DB:  PubMed          Journal:  NDT Plus        ISSN: 1753-0784


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Sir, Peritoneal dialysis (PD) is based on passive movement of water and soluble molecules across the peritoneum. In continuous ambulatory peritoneal dialysis (CAPD), the patient's abdomen is filled with a dialysate fluid introducing an osmotic gradient driven by electrolytes and glucose, or macromolecules such as icodextrin. Biocompatibility of PD fluids is the most important criterion to enable long-term dialysis without introducing clinically significant changes in the functional characteristics of the peritoneum and systemic inflammatory effects [1]. The effects of biocompatibility on clinical outcome include changes in the physiology of cell populations constituting the peritoneal cavity (leucocyte, mesothelial and endothelial cells, and fibroblasts) and the gene expression of peripheral blood mononuclear cells (PBMCs) triggering alterations in cytokine, chemokine and growth factor networks, upregulation of proinflammatory and profibrotic pathways, and induction of carbonyl and oxidative stress [2-4]. Our study objective was to compare the genome-wide gene expression signature of PBMCs of PD patients using glucose-based (GBF) and icodextrin-based peritoneal fluids (IBF) to allow a direct comparison of biocompatibility relevant intracellular processes with respect to the PD fluid used. This pilot study should give us first insights into the alterations in gene expression of leucocytes triggered by different PD fluids and should provide an informative basis for future research. Therefore, we conducted a random cross-over study in five stable ESRD patients being treated with CAPD between 4 and 18 months (demographic data are provided on our laboratory homepage in Table 1 (http://www.meduniwien.ac.at/nephrogene/data/pd/)). Blood samples (10 ml) were collected immediately after a 4- to 6-h dwell of GBF (Physioneal® 40, Glucose 2.27% w/v, 395 mOsmol/l) and an overnight dwell of IBF (Extraneal®, icodextrin 7.5%, 284 mOsmol/l) [study approved by the local Institutional review board (Ethical Committee # EK-318/06, see http://ohrp.cit.nih.gov/search/asearch.asp)]. Oligoarrays were obtained from the Stanford University Functional Genomics core facility. All microarray experiment protocols can be found on the Stanford University webpage at http://cmgm.stanford.edu/pbrown/protocols/index.html. Stratagene Universal human reference RNA was used as a reference. Raw data files as well as the MIAME checklist are available at our laboratory webpage.
Table 1

Biological processes separating IBF- and GBF-treated patient groups as derived on the level of PBMC differential gene expression

Biological processGene symbolsP-value
DEGs up-regulated by IBF treatment
Immunity and defenceCIITA, UNQ3033, SCGB1C1, CLEC1B, CTSW, CLEC4E, TNFRSF7, CLEC10A<0.001
Natural killer cell-mediated immunityUNQ3033, CLEC1B, CTSW<0.001
T-cell-mediated immunityCIITA, CTSW, TNFRSF70.001
Cell communicationUNQ3033, SCGB1C1, CLEC1B, STAT4, CLEC10A0.008
Other neuronal activitySP110, RASGRP20.009
Macrophage-mediated immunityCLEC4E, CLEC10A0.010
Ligand-mediated signallingSTAT4, UNQ3033, SCGB1C10.010
Other immune and defenceSCGB1C1, CLEC4E0.012
Glucose haemeostasisSTAT40.021
Signal transductionLST1, STAT4, UNQ3033, SCGB1C1, RASGRP2, CLEC1B, TNFRSF7, CLEC10A0.022
MHC I-mediated immunityCTSW0.023
Cytokine- and chemokine- mediated signalling pathwaysSTAT4, TNFRSF70.029
MHC II-mediated immunityCIITA0.036
GlycolysisHK30.048
DEGs up-regulated by GBF treatment
Ectoderm developmentCELSR2, FOXA2, HLF, KRT80, TNFRSF21, COBLL1, NTN4, CRABP1, NLGN2, FGFR3, THSD3<0.001
Signal transductionFRAS1, DOC1, CELSR2, MGP, RND3,CGA, GNG4, RAB23, FOXA2, AXL, CAP2, CDH13, INPP5F, TACSTD2, TNFRST21, MFAP4, DIRAS1, CRABP1, NLGN2, SFRP2, THSD3, GPR161, FGFR3, NTN4<0.001
NeurogenesisCELSR2, FOXA2, HLF, TNFRSF21, COBLL1, NTN4, NLGN2, FGFR3, THSD3<0.001
Cell communicationFRAS1, CELSR2, MGP, CGA, FOXA2, CAP2, CDH13, MFAP4, NTN4, CRABP1, NLGN2, SFRP2, THSD3<0.001
OncogenesisDOC1, AXL, CDH13, MAGEA12, NTN4, MLF1, FGFR3, THSD3<0.001
Developmental processesDOC1, CELSR2, MGP, FOXA2, HLF, KRT80, TTK, MAGEA12, EFHD1, TNFRSF21, COBLL1, NTN4, CRABP1, NLGN2, FGFR3, THSD30.001
Other oncogenesisMAGEA12, FGFR3, THSD30.002
Cell proliferation and differentiationDOC1, FOXA2, AXL, TACSTD2, C9orf58, UHRF1, NTN4, MLF1, GINS2, FGFR30.002
Cell structureDLG5, CELSR2, COL7A1, FOXA2, KRT80, PHLDB1, TJP10.006
Cell structure and motilityDLG5, CELSR2, COL7A1, FOXA2, KRT80, PHLDB1, TJP1, RND3, CAP20.011
DNA replicationDOC1, CDC2, GINS20.014
HomeostasisCGA, HEPH, FSTL10.025
Stress responseMOCOS, C9orf58, GPX30.026
Other cell cycle processUHRF10.028
DNA metabolismDOC1, CDC2, DNTT, GINS20.028
Other receptor-mediated signalling pathwayFOXA2, TACSTD2, TNFRSF210.030
ProteolysisDOC1, DGC, C1R, MMP15, CAP2, SERPINA5, TIMP30.033
Cell surface receptor-mediated signal transductionCELSR2, RND3, GNG4, FOXA2, AXL, TACSTD2, TNFRSF21, FGFR3, THSD3, GPR1610.035
Other steroid metabolismSC5DL0.041
Cell cycleDOC1, CDC2, FOXA2, TTK, C9orf58, UHRF1, GINS20.042
Sex determinationTTK0.044
Cell cycle controlDOC1, CDC2, FOXA2, C9orf580.045
Neurotransmitter releaseSTXBP1, EHD20.046
Cell adhesionCELSR2, COL7A1, CDH13, MFAP4, NLGN20.049

Categories are ranked by the P-value (comparison of expected number of genes and observed number of genes in each biological process) indicating the relevance of a particular process.

Biological processes separating IBF- and GBF-treated patient groups as derived on the level of PBMC differential gene expression Categories are ranked by the P-value (comparison of expected number of genes and observed number of genes in each biological process) indicating the relevance of a particular process. A paired t-test (P < 0.05) of log-transformed expression values was used to evaluate differences between IBF and GBF treatment. Differentially expressed genes (DEGs) were hierarchically clustered and graphically represented using the MultiExperiment Viewer (MeV) (Pearson correlation, complete linkage) [5]. DEGs were furthermore analysed with respect to their molecular functions, biological processes and interaction partner using gene ontology terms (GO-Terms), PANTHER (Protein ANalysis THrough Evolutionary Relationships) ontologies and Online Predicted Human Interaction Database (OPHID). A total of 124 genes (fold change over two, 34 up-regulated and 90 down-regulated in the IBF group) were identified as being significantly differentially expressed in PBMCs comparing patients under IBF and GBF usage (Figure 1 online on our homepage). A total of 27 up-regulated genes assigned to IBF treatment and 81 up-regulated genes associated with GBF treatment could be classified according to PANTHER ontologies (Table 1). A number of the genes up-regulated in the course of IBF usage were found to be involved in immune response and inflammatory processes. Genes up-regulated by GBF usage in contrast are found to be assigned to development and signal transduction processes. Our study provides full genome differential gene expression profiles of PBMCs after peritoneal dialysis on a genome-wide scale comparing GBF and IBF peritoneal dialysis fluids confirming the differential involvement of inflammation. A limitation of our study is the small sample size of five CAPD patients. Therefore, we used a random cross-over design and computed a paired t-test. These pilot data suggest reduced inflammation and consequently an improved biocompatibility of GBF peritoneal fluids compared with IBF fluids. Certainly, further evaluation in larger studies is needed.
  5 in total

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Authors:  A I Saeed; V Sharov; J White; J Li; W Liang; N Bhagabati; J Braisted; M Klapa; T Currier; M Thiagarajan; A Sturn; M Snuffin; A Rezantsev; D Popov; A Ryltsov; E Kostukovich; I Borisovsky; Z Liu; A Vinsavich; V Trush; J Quackenbush
Journal:  Biotechniques       Date:  2003-02       Impact factor: 1.993

Review 2.  In vitro biocompatibility performance of Physioneal.

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Journal:  Kidney Int Suppl       Date:  2003-12       Impact factor: 10.545

Review 3.  T lymphocytes: the "cellular" arm of acquired immunity in the peritoneum.

Authors:  Amir Glik; Amos Douvdevani
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4.  Short-term effects of bicarbonate/lactate-buffered and conventional lactate-buffered dialysis solutions on peritoneal ultrafiltration: a comparative crossover study.

Authors:  Jernej Pajek; Radoslav Kveder; Andrej Bren; Andrej Gucek; Maja Bucar; Andrej Skoberne; Jacek Waniewski; Bengt Lindholm
Journal:  Nephrol Dial Transplant       Date:  2008-12-09       Impact factor: 5.992

5.  Benefits of biocompatible PD fluid for preservation of residual renal function in incident CAPD patients: a 1-year study.

Authors:  Sejoong Kim; Jieun Oh; Suhnggwon Kim; Wookyung Chung; Curie Ahn; Sung Gyun Kim; Kook-Hwan Oh
Journal:  Nephrol Dial Transplant       Date:  2009-03-03       Impact factor: 5.992

  5 in total

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