A Knowledge-based Approach for Genome-wide Genotyping Analysis of Parkinson's Disease

			Personnel Mostafa Ronaghi Download PDF (592 Kb)

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.

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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