Evidence map›Paper›PMID 23663527›Full record

ArticleBMC medical genomics2013

A specific immune transcriptomic profile discriminates chronic kidney disease patients in predialysis from hemodialyzed patients.

Gianluigi Zaza, Simona Granata, Federica Rascio, Paola Pontrelli, Maria Pia Dell'Oglio, Sharon Natasha Cox, Giovanni Pertosa, Giuseppe Grandaliano, Antonio Lupo

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
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  6. Association of lactate dehydrogenase with mortality in incident hemodialysis patients.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2021
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  15. Comparison of epitheliotrophic factors in autologous serum eyedrops from sera of chronic renal failure patients vs. normal controls.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2015
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Gianluigi ZazaRenal Unit, Department of Medicine, University-Hospital of Verona, Piazzale A, Stefani 1, Verona 37126, Italy. gianluigi.zaza@univr.it.
Simona Granata
Federica Rascio
Paola Pontrelli
Maria Pia Dell'Oglio
Sharon Natasha Cox
Giovanni Pertosa
Giuseppe Grandaliano
Antonio Lupo
University of Bari Aldo Moro · ITUniversity of Verona · ITUniversity of Foggia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) patients present a complex interaction between the innate and adaptive immune systems, in which immune activation (hypercytokinemia and acute-phase response) and immune suppression (impairment of response to infections and poor development of adaptive immunity) coexist. In this setting, circulating uremic toxins and microinflammation play a critical role. This condition, already present in the last stages of renal damage, seems to be enhanced by the contact of blood with bioincompatible extracorporeal hemodialysis (HD) devices. However, although largely described, the cellular machinery associated to the CKD- and HD-related immune-dysfunction is still poorly defined. Understanding the mechanisms behind this important complication may generate a perspective for improving patients outcome.

methodsTo better recognize the biological bases of the CKD-related immune dysfunction and to identify differences between CKD patients in conservative (CKD) from those in HD treatment, we used an high-throughput strategy (microarray) combined with classical bio-molecular approaches.

resultsImmune transcriptomic screening of peripheral blood mononuclear cells (1030 gene probe sets selected by Gene-Ontology) showed that 275 gene probe sets (corresponding to 213 genes) discriminated 9 CKD patients stage III-IV (mean±SD of eGFR: 32.27+/-14.7 ml/min) from 17 HD patients (p<0.0001, FDR=5%). Seventy-one genes were up- and 142 down-regulated in HD patients. Functional analysis revealed, then, close biological links among the selected genes with a pivotal role of PTX3, IL-15 (up-regulated in HD) and HLA-G (down-regulated in HD). ELISA, performed on an independent testing-group [11 CKD stage III-IV (mean±SD of eGFR: 30.26±14.89 ml/min) and 13 HD] confirmed that HLA-G, a protein with inhibition effects on several immunological cell lines including natural killers (NK), was down-expressed in HD (p=0.04). Additionally, in the testing-group, protein levels of CX3CR1, an highly selective chemokine receptor and surface marker for cytotoxic effector lymphocytes, resulted higher expressed in HD compared to CKD (p<0.01).

conclusionTaken together our results show, for the first time, that HD patients present a different immune-pattern compared to the un-dialyzed CKD patients. Among the selected genes, some of them encode for important biological elements involved in proliferation/activation of cytotoxic effector lymphocytes and in the immune-inflammatory cellular machinery. Additionally, this study reveals new potential diagnostic bio-markers and therapeutic targets.

Indexed as

Gene Expression ProfilingAdultC-Reactive ProteinCX3C Chemokine Receptor 1Discriminant AnalysisDown-RegulationFemaleGene Regulatory NetworksHLA-G AntigensHumansInterleukin-15Kidney Failure, ChronicLeukocytes, MononuclearMaleMiddle AgedPentraxinsC-Reactive ProteinCX3C Chemokine Receptor 1CX3CR1 protein, humanHLA-G AntigensInterleukin-15PentraxinsReceptors, ChemokineSerum Amyloid P-Component

Identifiers

PMID23663527
PMCPMC3655909
OpenAlexW1987524865

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.