Abstract:
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.
