Gene Logic Collaboration Reveals Genomic Predictors of Parkinson's Disease
Results Predict Likelihood and Age of Disease Onset, May Lead to Risk-Assessment Tests
The collaborators used sophisticated bioinformatic analysis methods to compare gene sequence variations called single nucleotide polymorphisms (SNPs) in the genomes of Parkinson's disease patients to those of their disease-free siblings. The collaborators targeted variants of genes related to the axon guidance pathway, a neural development pathway that plays an important role in the wiring of the brain during fetal development.
Gene Logic provided gene expression data analysis and data interpretation, comparing the whole-genome study data to the company's Parkinson's disease gene expression knowledgebase, referred to in the study as the most comprehensive such database to date. Jarlath ffrench-Mullen, Ph.D., Gene Logic Scientific Director, Central Nervous System, and a co-author of the study said, "The study methodology opens doors to more in-depth genetic understanding of complex diseases, demonstrating the value of our clinical and genomics assets and capabilities. Gene expression profiles are used in such studies to identify, understand and confirm the dysregulation of specific genes and gene variants in a target pathway. This study augments our intellectual property position around a growing set of useful markers for Parkinson's disease and other complex diseases, affording excellent opportunities to develop diagnostic, prognostic, or therapeutic products."
Most read news
Topics
Organizations
Other news from the department research and development
Get the analytics and lab tech industry in your inbox
From now on, don't miss a thing: Our newsletter for analytics and lab technology brings you up to date every Tuesday. The latest industry news, product highlights and innovations - compact and easy to understand in your inbox. Researched by us so you don't have to.