From medical to biological informatics: Searching for diagnostic markers in Parkinson's disease patients' lymphocytes using transcriptomics

Objective: To determine whether the transcriptomic profile of PD patients’s lymphocytescould be used in separating them from the healthy (with respect to PD) subjects.Background: To-date, the diagnosis of Parkinson’s disease (PD) is based primarily onclinical symptoms. These symptoms, however, are not specific for the disease, since theycharacterize the clinical syndrome of parkinsonism in general, the latter being originated fromother disorders as well. It becomes apparent then that there is a need for accurate, diseasespecific,non- or least-invasive diagnostic tools for PD. Peripheral blood lymphocytes (PBLs)are a readily accessible peripheral tissue. They have been studied in the context of brainresearch, because it is believed that they could provide leads into the biochemistry,physiology and pathophysiology of the central nervous system (CNS), as they exhibitbiochemical similarities with their CNS counterparts.Methods: We analyzed the blood samples of a group of 7 idiopathic first-time diagnosedPD patients prior to the initiation of any treatment, at the transcriptional level using fullgenomeDNA microarrays of Affymetrix platform. The acquired data were subsequentlyinvestigated using multivariate statistical analysis techniques.Results: Combination of the microarray analysis results with any available informationfrom the medical history of the patients and their diagnosis based on the clinical symptomsrevealed the importance of the integration of medical with the biological informatics to (a)correctly select the control subjects of the study, and, especially in the case of diagnostic toolsbased on blood samples, (b) isolate the disease-specific markers/molecular differences fromany other medical history that could contribute to the particular transcriptomic profile.Conclusions: Analyzing high-throughput –omic data in the context of the patients’medical history is indeed very significant towards the goal of the modern biomedicine forpersonalized diagnosis and therapy.