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Identifying Consensus Disease Pathways in Parkinson's Disease Using an Integrative Systems Biology Approach

Overview of attention for article published in PLOS ONE, February 2011
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Title
Identifying Consensus Disease Pathways in Parkinson's Disease Using an Integrative Systems Biology Approach
Published in
PLOS ONE, February 2011
DOI 10.1371/journal.pone.0016917
Pubmed ID
Authors

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

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.

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The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 3%
Germany 2 2%
Luxembourg 2 2%
United States 2 2%
China 1 <1%
France 1 <1%
Italy 1 <1%
Spain 1 <1%
Unknown 92 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 27%
Student > Ph. D. Student 24 23%
Student > Master 12 11%
Other 8 8%
Professor 6 6%
Other 14 13%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 34%
Biochemistry, Genetics and Molecular Biology 16 15%
Medicine and Dentistry 12 11%
Computer Science 8 8%
Neuroscience 7 7%
Other 11 10%
Unknown 15 14%