Abstract
Microarray searches have revealed potential genetic biomarkers in a wide variety of human diseases. Identification of biomarkers for disease status is particularly important in chronic neurodegenerative diseases where brain tissue cannot be sampled. A previous study identified 12 genes from microarray analysis as associated with Huntington's disease, although the relationships had not been validated. We used new machine learning approaches to reanalyse those microarray data and to rank the identified potential genetic biomarkers. We then performed quantitative reverse transcription–polymerase chain reaction analysis on a subset of the candidate genes in blood samples from an independent cohort of 23 Huntington's disease patients and 23 healthy controls. Our highest ranked genes did not overlap with the 12 previously identified, but two were significantly up-regulated in the Huntington's disease group: ARFGEF2 and GOLGA8G. Little is known about the latter, but the former warrants further analysis as it is known to be associated with intracellular vesicular trafficking, disturbances of which characterize Huntington's disease.