An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.

Candidaemia is a bloodstream infection caused by Candida species that primarily affects specific groups of at-risk patients. Because only small candidaemia patient cohorts are available, classical genome wide association cannot be used to identify Candida susceptibility genes. Therefore, we have app...

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Main Authors: Vasiliki Matzaraki, Mark S Gresnigt, Martin Jaeger, Isis Ricaño-Ponce, Melissa D Johnson, Marije Oosting, Lude Franke, Sebo Withoff, John R Perfect, Leo A B Joosten, Bart Jan Kullberg, Frank L van de Veerdonk, Iris Jonkers, Yang Li, Cisca Wijmenga, Mihai G Netea, Vinod Kumar
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5519064?pdf=render
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author Vasiliki Matzaraki
Mark S Gresnigt
Martin Jaeger
Isis Ricaño-Ponce
Melissa D Johnson
Marije Oosting
Lude Franke
Sebo Withoff
John R Perfect
Leo A B Joosten
Bart Jan Kullberg
Frank L van de Veerdonk
Iris Jonkers
Yang Li
Cisca Wijmenga
Mihai G Netea
Vinod Kumar
author_facet Vasiliki Matzaraki
Mark S Gresnigt
Martin Jaeger
Isis Ricaño-Ponce
Melissa D Johnson
Marije Oosting
Lude Franke
Sebo Withoff
John R Perfect
Leo A B Joosten
Bart Jan Kullberg
Frank L van de Veerdonk
Iris Jonkers
Yang Li
Cisca Wijmenga
Mihai G Netea
Vinod Kumar
author_sort Vasiliki Matzaraki
collection DOAJ
description Candidaemia is a bloodstream infection caused by Candida species that primarily affects specific groups of at-risk patients. Because only small candidaemia patient cohorts are available, classical genome wide association cannot be used to identify Candida susceptibility genes. Therefore, we have applied an integrative genomics approach to identify novel susceptibility genes and pathways for candidaemia. Candida-induced transcriptome changes in human primary leukocytes were assessed by RNA sequencing. Genetic susceptibility to candidaemia was assessed using the Illumina immunochip platform for genotyping of a cohort of 217 patients. We then integrated genetics data with gene-expression profiles, Candida-induced cytokine production capacity, and circulating concentrations of cytokines. Based on the intersection of transcriptome pathways and genomic data, we prioritized 31 candidate genes for candidaemia susceptibility. This group of genes was enriched with genes involved in inflammation, innate immunity, complement, and hemostasis. We then validated the role of MAP3K8 in cytokine regulation in response to Candida stimulation. Here, we present a new framework for the identification of susceptibility genes for infectious diseases that uses an unbiased, hypothesis-free, systems genetics approach. By applying this approach to candidaemia, we identified novel susceptibility genes and pathways for candidaemia, and future studies should assess their potential as therapeutic targets.
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spelling doaj.art-f6256566380a42a59a899b29b2e9aa2d2022-12-22T01:53:47ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01127e018082410.1371/journal.pone.0180824An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.Vasiliki MatzarakiMark S GresnigtMartin JaegerIsis Ricaño-PonceMelissa D JohnsonMarije OostingLude FrankeSebo WithoffJohn R PerfectLeo A B JoostenBart Jan KullbergFrank L van de VeerdonkIris JonkersYang LiCisca WijmengaMihai G NeteaVinod KumarCandidaemia is a bloodstream infection caused by Candida species that primarily affects specific groups of at-risk patients. Because only small candidaemia patient cohorts are available, classical genome wide association cannot be used to identify Candida susceptibility genes. Therefore, we have applied an integrative genomics approach to identify novel susceptibility genes and pathways for candidaemia. Candida-induced transcriptome changes in human primary leukocytes were assessed by RNA sequencing. Genetic susceptibility to candidaemia was assessed using the Illumina immunochip platform for genotyping of a cohort of 217 patients. We then integrated genetics data with gene-expression profiles, Candida-induced cytokine production capacity, and circulating concentrations of cytokines. Based on the intersection of transcriptome pathways and genomic data, we prioritized 31 candidate genes for candidaemia susceptibility. This group of genes was enriched with genes involved in inflammation, innate immunity, complement, and hemostasis. We then validated the role of MAP3K8 in cytokine regulation in response to Candida stimulation. Here, we present a new framework for the identification of susceptibility genes for infectious diseases that uses an unbiased, hypothesis-free, systems genetics approach. By applying this approach to candidaemia, we identified novel susceptibility genes and pathways for candidaemia, and future studies should assess their potential as therapeutic targets.http://europepmc.org/articles/PMC5519064?pdf=render
spellingShingle Vasiliki Matzaraki
Mark S Gresnigt
Martin Jaeger
Isis Ricaño-Ponce
Melissa D Johnson
Marije Oosting
Lude Franke
Sebo Withoff
John R Perfect
Leo A B Joosten
Bart Jan Kullberg
Frank L van de Veerdonk
Iris Jonkers
Yang Li
Cisca Wijmenga
Mihai G Netea
Vinod Kumar
An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.
PLoS ONE
title An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.
title_full An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.
title_fullStr An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.
title_full_unstemmed An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.
title_short An integrative genomics approach identifies novel pathways that influence candidaemia susceptibility.
title_sort integrative genomics approach identifies novel pathways that influence candidaemia susceptibility
url http://europepmc.org/articles/PMC5519064?pdf=render
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