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

TLDR

Common variants with small effect sizes have limited impact on complex diseases, but joint actions within biological pathways may play a major role; progress in identifying genetic causes of rare Mendelian disorders has not yet translated into similar advances for complex diseases. The study aimed to determine whether polymorphisms in the axon‑guidance pathway predispose individuals to Parkinson disease. Researchers mined a whole‑genome association dataset to identify SNPs within axon‑guidance genes, built predictive models of Parkinson disease outcomes, and validated the approach with a second GWAS and expression profiling data. The axon‑guidance SNP models predicted Parkinson disease susceptibility (OR 90.8), survival free of Parkinson disease (HR 19.0), and age at onset (R² 0.68) with highly significant p‑values, outperforming random SNP models, and indicating a key role for axon‑guidance genes in Parkinson disease pathogenesis and potential relevance to other complex diseases.

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.