Literature DB >> 26829381

Functional genomics of candidate genes derived from genome-wide association studies for five common neurological diseases.

Gina P Guio-Vega1, Diego A Forero1.   

Abstract

AIM: Recent genome-wide association studies (GWAS) are identifying novel candidate genes for several neurological diseases (NDs). However, a global functional analysis of those genes derived from GWAS for NDs is missing. We explored the genomic and functional features of novel candidate genes for five common NDs: Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, stroke and migraine.
MATERIALS AND METHODS: A functional enrichment analysis was performed for GWAS-derived genes, for categories such as Kyoto Encyclopedia of Genes and Genomes pathways, gene expression, InterPro domains, transcription factor binding sites, gene ontology (GO) terms and microRNA (miRNA) targets. An analysis of protein-protein interactions was carried out.
RESULTS: Six hundred and forty-two unique single nucleotide polymorphisms (SNPs) were identified for the five NDs and 2.3% of them were non-synonymous SNPs. There were no common SNPs for all five NDs and eight genes were associated with more than one ND. The enrichment analysis showed significant values for several GO categories, such as cell-cell adhesion and location in neurites and for expression in prefrontal cortex. An analysis of protein-protein interactions showed the evidence of a large component. Fifty-one of these GWAS-derived genes are known to be potentially druggable and twelve are known to harbor mutations for neuropsychiatric disorders.
CONCLUSIONS: Our results suggest that there is little overlap between the genes identified in GWAS for the five common NDs. Identification of functional categories in the GWAS-derived candidate genes for common NDs could lead to a better understanding of their functional consequences and could be useful for the future discovery of additional genetic risk factors for those diseases.

Entities:  

Keywords:  computational biology; genomics; neurological disorders; systems biology

Mesh:

Year:  2016        PMID: 26829381     DOI: 10.3109/00207454.2016.1149172

Source DB:  PubMed          Journal:  Int J Neurosci        ISSN: 0020-7454            Impact factor:   2.292


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