A Knowledge-based Approach for Genome-wide Genotyping Analysis of Parkinson's Disease
A NextBio Whitepaper
In this paper, we utilize a novel knowledge platform from NextBio to gain new insights into Parkinson's disease (PD). We were able to explore candidate non-synonymous SNPs using NextBio’s reference library of neurological expression studies, regulatory motifs, gene ontology functional groups and pathways to identify candidate genes for further study.
Personnel
Mostafa Ronaghi
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Background
To study PD, different approaches have been used to identify important genes including PARK1-11. The protein products of these genes are involved in different pathways of neurodegeneration, making elucidation of the underlying disease mechanism difficult. The emergence of high-throughput gene expression and genotyping technologies enabled a systematic approach to the study of PD in human, as well as in model organisms. With the accumulation of high-throughput data, a single-gene approach in the study of complex diseases is giving way to global, genome-wide approach that captures the complexity of associated phenotypes.
Study Results
In this report we explore results of a high-throughput genotyping study of PD patients using NextBio (Fig. 1). In the approach presented here, we explore non-synonymous SNPs with statistically significant association with PD within the context of gene expression signatures of phenotypes related to PD.
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