Identifying consensus disease pathways in Parkinson's disease using an integrative systems biology approach

Yvonne J.K. Edwards, Gary W. Beecham, William K. Scott, Sawsan Khuri, Guney Bademci, Demet Tekin, Eden R. Martin, Zhijie Jiang, Deborah C. Mash, Jarlath ffrench-Mullen, Margaret A. Pericak-Vance, Nicholas Tsinoremas, Jeffery M. Vance

Research output: Contribution to journalArticle

52 Scopus citations

Abstract

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p<0.01) from a joint analysis of three existing PD GWAS were identified and each assigned to a gene. For gene expression, rather than the traditional comparison of one anatomical region between sets of patients and controls, we identified differentially expressed genes between adjacent Braak regions in each individual and adjusted using average control expression profiles. Over-represented pathways were calculated using a hyper-geometric statistical comparison. An integrated, systems meta-analysis of the over-represented pathways combined the expression and GWAS results using a Fisher's combined probability test. Four of the top seven pathways from each approach were identical. The top three pathways in the meta-analysis, with their corrected p-values, were axonal guidance (p = 2.8E-07), focal adhesion (p = 7.7E-06) and calcium signaling (p = 2.9E-05). These results support that a systems biology (pathway) approach will provide additional insight into the genetic etiology of PD and that these pathways have both biological and statistical support to be important in PD.

Original languageEnglish (US)
Article numbere16917
JournalPloS one
Volume6
Issue number2
DOIs
StatePublished - 2011

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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