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A Genomic Pathway Approach to a Complex Disease: Axon Guidance and Parkinson Disease

Author

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  • Timothy G Lesnick
  • Spiridon Papapetropoulos
  • Deborah C Mash
  • Jarlath Ffrench-Mullen
  • Lina Shehadeh
  • Mariza de Andrade
  • John R Henley
  • Walter A Rocca
  • J Eric Ahlskog
  • Demetrius M Maraganore

Abstract

While major inroads have been made in identifying the genetic causes of rare Mendelian disorders, little progress has been made in the discovery of common gene variations that predispose to complex diseases. The single gene variants that have been shown to associate reproducibly with complex diseases typically have small effect sizes or attributable risks. However, the joint actions of common gene variants within pathways may play a major role in predisposing to complex diseases (the paradigm of complex genetics). The goal of this study was to determine whether polymorphism in a candidate pathway (axon guidance) predisposed to a complex disease (Parkinson disease [PD]). We mined a whole-genome association dataset and identified single nucleotide polymorphisms (SNPs) that were within axon-guidance pathway genes. We then constructed models of axon-guidance pathway SNPs that predicted three outcomes: PD susceptibility (odds ratio = 90.8, p = 4.64 × 10−38), survival free of PD (hazards ratio = 19.0, p = 5.43 × 10−48), and PD age at onset (R2 = 0.68, p = 1.68 × 10−51). By contrast, models constructed from thousands of random selections of genomic SNPs predicted the three PD outcomes poorly. Mining of a second whole-genome association dataset and mining of an expression profiling dataset also supported a role for many axon-guidance pathway genes in PD. These findings could have important implications regarding the pathogenesis of PD. This genomic pathway approach may also offer insights into other complex diseases such as Alzheimer disease, diabetes mellitus, nicotine and alcohol dependence, and several cancers.: Complex diseases are common disorders that are believed to have many causes. Examples include Alzheimer disease, diabetes mellitus, nicotine and alcohol dependence, and several cancers. This study represents a paradigm shift from single gene to pathway studies of complex diseases. We present the example of Parkinson disease (PD) and a complex array of chemical signals that wires the brain during fetal development (the axon guidance pathway). We mined a dataset that studied hundreds of thousands of DNA variations (single nucleotide polymorphisms [SNPs]) in persons with and without PD and identified SNPs that were assigned to axon-guidance pathway genes. We then identified sets of SNPs that were highly predictive of PD susceptibility, survival free of PD, and age at onset of PD. The effect sizes and the statistical significance observed for the pathway were far greater than for any single gene. We validated our findings for the pathway using a second SNP dataset for PD and also a dataset for PD that studied RNA variations. There is prior evidence that the axon guidance pathway might play a role in other brain disorders (e.g., Alzheimer disease, Tourette syndrome, dyslexia, epilepsy, and schizophrenia). A genomic pathway approach may lead to important breakthroughs for many complex diseases.

Suggested Citation

  • Timothy G Lesnick & Spiridon Papapetropoulos & Deborah C Mash & Jarlath Ffrench-Mullen & Lina Shehadeh & Mariza de Andrade & John R Henley & Walter A Rocca & J Eric Ahlskog & Demetrius M Maraganore, 2007. "A Genomic Pathway Approach to a Complex Disease: Axon Guidance and Parkinson Disease," PLOS Genetics, Public Library of Science, vol. 3(6), pages 1-12, June.
  • Handle: RePEc:plo:pgen00:0030098
    DOI: 10.1371/journal.pgen.0030098
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    References listed on IDEAS

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    1. Francis S. Collins & Eric D. Green & Alan E. Guttmacher & Mark S. Guyer, 2003. "A vision for the future of genomics research," Nature, Nature, vol. 422(6934), pages 835-847, April.
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    1. 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 &, 2011. "Identifying Consensus Disease Pathways in Parkinson's Disease Using an Integrative Systems Biology Approach," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-11, February.
    2. Kelsey Chalmers & Elizabeth M Kita & Ethan K Scott & Geoffrey J Goodhill, 2016. "Quantitative Analysis of Axonal Branch Dynamics in the Developing Nervous System," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-25, March.
    3. Feng Zhang & Xiong Guo & Shixun Wu & Jing Han & Yongjun Liu & Hui Shen & Hong-Wen Deng, 2012. "Genome-Wide Pathway Association Studies of Multiple Correlated Quantitative Phenotypes Using Principle Component Analyses," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
    4. Silver Matt & Montana Giovanni & Alzheimer's Disease Neuroimaging Initiative, 2012. "Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-43, January.
    5. Mateus Rocha de Paula & Regina Berretta & Pablo Moscato, 2016. "A fast meta-heuristic approach for the $$(\alpha ,\beta )-k$$ ( α , β ) - k -feature set problem," Journal of Heuristics, Springer, vol. 22(2), pages 199-220, April.

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