Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation

Martin Cadeiras, Manuel von Bayern, Anshu Sinha, Khurram Shahzad, Farhana Latif, Wei Keat Lim, Hernan Grenett, Esteban Tabak, Tod Klingler, Andrea Califano, Mario C. Deng

Research output: Contribution to journalArticle

Abstract

Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37%) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6%). Overall, 75% (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets and biomarkers.

Original languageEnglish (US)
Pages (from-to)949-956
Number of pages8
JournalJournal of Cellular and Molecular Medicine
Volume15
Issue number4
DOIs
StatePublished - Apr 2011

Fingerprint

Genetic Association Studies
Heart Transplantation
Genes
Blood Cells
Transcription Factors
GA-Binding Protein Transcription Factor
Information Services
Gene Regulatory Networks
Chromatin Immunoprecipitation
Response Elements
Adenosine Monophosphate
Cellular Immunity
Cell Communication
Observational Studies
Allografts
Carrier Proteins
B-Lymphocytes
Biomarkers
Apoptosis
Transplants

Keywords

  • Candidate gene
  • Cardiac transplant
  • Cellular networks
  • Gene expression
  • Rejection
  • Systems biology

ASJC Scopus subject areas

  • Cell Biology
  • Molecular Medicine

Cite this

Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation. / Cadeiras, Martin; von Bayern, Manuel; Sinha, Anshu; Shahzad, Khurram; Latif, Farhana; Lim, Wei Keat; Grenett, Hernan; Tabak, Esteban; Klingler, Tod; Califano, Andrea; Deng, Mario C.

In: Journal of Cellular and Molecular Medicine, Vol. 15, No. 4, 04.2011, p. 949-956.

Research output: Contribution to journalArticle

Cadeiras, M, von Bayern, M, Sinha, A, Shahzad, K, Latif, F, Lim, WK, Grenett, H, Tabak, E, Klingler, T, Califano, A & Deng, MC 2011, 'Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation', Journal of Cellular and Molecular Medicine, vol. 15, no. 4, pp. 949-956. https://doi.org/10.1111/j.1582-4934.2010.01092.x
Cadeiras, Martin ; von Bayern, Manuel ; Sinha, Anshu ; Shahzad, Khurram ; Latif, Farhana ; Lim, Wei Keat ; Grenett, Hernan ; Tabak, Esteban ; Klingler, Tod ; Califano, Andrea ; Deng, Mario C. / Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation. In: Journal of Cellular and Molecular Medicine. 2011 ; Vol. 15, No. 4. pp. 949-956.
@article{15d333f6139c4b4cb34b6e702511634c,
title = "Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation",
abstract = "Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37{\%}) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6{\%}). Overall, 75{\%} (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets and biomarkers.",
keywords = "Candidate gene, Cardiac transplant, Cellular networks, Gene expression, Rejection, Systems biology",
author = "Martin Cadeiras and {von Bayern}, Manuel and Anshu Sinha and Khurram Shahzad and Farhana Latif and Lim, {Wei Keat} and Hernan Grenett and Esteban Tabak and Tod Klingler and Andrea Califano and Deng, {Mario C.}",
year = "2011",
month = "4",
doi = "10.1111/j.1582-4934.2010.01092.x",
language = "English (US)",
volume = "15",
pages = "949--956",
journal = "Journal of Cellular and Molecular Medicine",
issn = "1582-1838",
publisher = "Wiley-Blackwell",
number = "4",

}

TY - JOUR

T1 - Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation

AU - Cadeiras, Martin

AU - von Bayern, Manuel

AU - Sinha, Anshu

AU - Shahzad, Khurram

AU - Latif, Farhana

AU - Lim, Wei Keat

AU - Grenett, Hernan

AU - Tabak, Esteban

AU - Klingler, Tod

AU - Califano, Andrea

AU - Deng, Mario C.

PY - 2011/4

Y1 - 2011/4

N2 - Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37%) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6%). Overall, 75% (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets and biomarkers.

AB - Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37%) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6%). Overall, 75% (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets and biomarkers.

KW - Candidate gene

KW - Cardiac transplant

KW - Cellular networks

KW - Gene expression

KW - Rejection

KW - Systems biology

UR - http://www.scopus.com/inward/record.url?scp=79955656379&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79955656379&partnerID=8YFLogxK

U2 - 10.1111/j.1582-4934.2010.01092.x

DO - 10.1111/j.1582-4934.2010.01092.x

M3 - Article

VL - 15

SP - 949

EP - 956

JO - Journal of Cellular and Molecular Medicine

JF - Journal of Cellular and Molecular Medicine

SN - 1582-1838

IS - 4

ER -