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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
- 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.
- Subjects :
- 0301 basic medicine
MESH: Gene Ontology
Candidate gene
Microarray
Microarrays
Physiology
MESH: Gene Expression Profiling
[SDV]Life Sciences [q-bio]
Gene regulatory network
lcsh:Medicine
Gene Expression
Genome-wide association study
Biochemistry
MESH: Genotype
Mathematical and Statistical Techniques
Databases, Genetic
Medicine and Health Sciences
MESH: Computational Biology/methods
Data Mining
Gene Regulatory Networks
Post-Translational Modification
lcsh:Science
MESH: Databases, Genetic
MESH: Gene Regulatory Networks
Regulation of gene expression
MESH: Transcriptome
Multidisciplinary
MESH: Anemia, Sickle Cell/genetics
MESH: Polymorphism, Single Nucleotide
Genomics
MESH: Genome-Wide Association Study
3. Good health
Body Fluids
Bioassays and Physiological Analysis
Blood
Physical Sciences
DNA microarray
Anatomy
Statistics (Mathematics)
Research Article
Genotype
Computational biology
Heme
Anemia, Sickle Cell
Biology
Research and Analysis Methods
Polymorphism, Single Nucleotide
03 medical and health sciences
DNA-binding proteins
Genetics
Genome-Wide Association Studies
SNP
Humans
Gene Regulation
Statistical Methods
Alleles
MESH: Humans
MESH: Alleles
MESH: Data Mining
Gene Expression Profiling
lcsh:R
Biology and Life Sciences
Computational Biology
Proteins
Human Genetics
Genome Analysis
Regulatory Proteins
Gene expression profiling
030104 developmental biology
Gene Ontology
lcsh:Q
Transcriptome
Mathematics
Meta-Analysis
Transcription Factors
Genome-Wide Association Study
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 13
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....8f9c4bed394da9f0ff5a67ac94d7f98a