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A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study

Authors :
Sumir Panji
Julie Makani
Liberata Mwita
Cherif Ben Hamda
Kais Ghedira
Raphael Z. Sangeda
Alia Benkahla
Ayton Meintjes
Lamia Guizani-Tabbane
Siana Nkya
Nicola Mulder
Faculté des Sciences de Bizerte [Université de Carthage]
Université de Carthage - University of Carthage
Laboratoire de Bioinformatique, biomathématiques, biostatistiques (BIMS) (LR11IPT09)
Institut Pasteur de Tunis
Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Tunis El Manar (UTM)
Université de Tunis El Manar (UTM)
Muhimbili University of Health and Allied Sciences
University of Cape Town
Laboratoire de Parasitologie Médicale, Biotechnologies et Biomolécules (LR11IPT06)
Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)
Research reported in this publication was supported by the National Institutes of Health Common Fund under grant number U41HG006941 (NM).
The authors would like to thank Pr. Faisal Fadlelmola and Dr. Amel Ghouila the chair and co-chair of the H3ABioNet Research and Tool Development Working Group for the follow up of the present project.
Source :
PLoS ONE, PLoS ONE, Public Library of Science, 2018, 13 (7), pp.e0199461. ⟨10.1371/journal.pone.0199461⟩, PLoS ONE, Vol 13, Iss 7, p e0199461 (2018)
Publication Year :
2018
Publisher :
Public Library of Science, 2018.

Abstract

International audience; A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysi-ology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.

Details

Language :
English
ISSN :
19326203
Volume :
13
Issue :
7
Database :
OpenAIRE
Journal :
PLoS ONE
Accession number :
edsair.doi.dedup.....8f9c4bed394da9f0ff5a67ac94d7f98a