Ontology highlight
ABSTRACT:
PROVIDER: PRJEB83688 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| MS4042_PAN1.NORM_GQ20DP10_vep_NO_GENO.vcf.csi | Other | |||
| MS4042_PAN1.NORM_GQ20DP10_vep_NO_GENO.vcf.gz | Vcf |
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Project description:Medical research focuses on disease-specific genes. By contrast, here we systematically examined the roles of shared genes for disease susceptibility and as therapeutic and diagnostic targets. Meta-analysis of all published disease-related genome-wide association studies (GWAS) showed that T helper (Th) cell differentiation was the most shared pathway. Expression profiling data from highly diverse CD4+ T cell-associated diseases revealed shared disease-associated genes, which were enriched for Th cell differentiation, but also metabolic and proliferative pathways. This pleiotropy suggested that altered functions of shared genes could generally increase disease susceptibility. Indeed, compared to specific genes, the shared genes were enriched for disease-associated SNPs identified by all published disease-related GWAS. To examine if the shared genes induced disease-relevant pathways, we focused on transcription factors (TFs) that induced Th differentiation. Those TFs were enriched among the shared genes, as well as for disease-associated SNPs identified by GWAS, and disease-phenotypes in mice knock-out studies. Original GWAS and profiling data from patients with multiple sclerosis and allergy confirmed enrichment of disease-associated SNPs in the TFs, and that the TFs were differentially expressed at early disease stages, and their targets increased in parallel with disease development. From a clinical perspective, the shared genes were significantly enriched for known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed that shared or specific genes could be used to stratify patients for individualized medicine. Our findings show that shared disease genes generally increase disease susceptibility and are important therapeutic and diagnostic targets. Patients with multiple sclerosis (MS) display variations in response to natalizumab treatment. PBMCs were collected from 8 high responders (HR) and 8 low responders (LR) to natalizumab treatment. CD4+ T cells were cultured for 48h. Cells were activated with anti-CD3 and anti-CD28 mAbs (0.5 µg/mL), either with natalizumab (25 µg/mL BiogenIdec) or without additional stimulus. Gene expression analysis was performed using SurePrint G3 Human Gene Expression 8X60K microarrays.
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