Open AccessA common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study
Author(s) -
Cherif Ben Hamda,
Raphael Zozimus Sangeda,
Liberata Mwita,
Ayton Meintjes,
Siakya,
Sumir Panji,
Nicola Mulder,
Lamia Guizani-Tabbane,
Alia Benkahla,
Julie Makani,
Kaïs Ghedira
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0199461
Subject(s) - genome wide association study , biology , single nucleotide polymorphism , transcriptome , microarray analysis techniques , computational biology , genetics , gene expression profiling , gene , genetic association , microarray , snp , bioinformatics , gene expression , genotype
A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysiology. 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.