Laboratory tests for Parkinson's disease (PD) were recently extended to microarray analyses of nucleated blood cells. Here, we report the use of statistical and gene ontology tools to re-examine these microarray data. Distribution plots and PCA mapping enabled removal of several outliers out of the 105 analyzed PD and control samples, which improved the discriminative power for PD blood cells compared to healthy and neurological disease controls. Combined with gene ontology tests, our findings point at neuro-immune signaling-related transcripts as distinctly expressed early in PD progress and call for exploiting microarray tests also for follow-up of PD treatment efficacy.