BACKGROUND: A blood-based test for the early detection of Parkinson's disease (PD) would be an important diagnostic tool and useful for patient selection when developing novel drugs or treatments for the disease. OBJECTIVE: Here, we aimed to identify potential biomarkers associated with PD. METHODS: We applied gene expression profiling to the study of peripheral blood from 75 healthy control subjects and 79 PD patients at different stages of the disease. Healthy control subjects were matched for age and gender with PD subjects, and the diagnosis of patients was based on clinical evaluation by specialists in movement disorders. RNA was extracted from the blood samples and the gene expressions were measured using the Illumina HumanHT-12 v4.0 Expression BeadChip. RESULTS: Our results support previous studies that gene expression in blood may be instrumental in the search for molecular biomarkers for PD. Single cross-validation results show that PD can be correctly classified from healthy controls with an agreement of 88% to clinical diagnosis. De novo PD patients are classified with a sensitivity of 87%, which is close to what was achieved for the patients having a confirmed PD diagnosis with disease duration <5 and >5 years (93% and 88%). A double cross-validation procedure showed that using a selected set of around 650 informative genes, similar results are achieved. Functional analysis of the selected genes showed genes significantly associated to mitochondrial dysfunction, protein ubiquitination, gene expression and cell death. CONCLUSIONS: PD affects gene expression in blood, suggesting the potential for the development of a blood-based gene expression test.
BACKGROUND: A blood-based test for the early detection of Parkinson's disease (PD) would be an important diagnostic tool and useful for patient selection when developing novel drugs or treatments for the disease. OBJECTIVE: Here, we aimed to identify potential biomarkers associated with PD. METHODS: We applied gene expression profiling to the study of peripheral blood from 75 healthy control subjects and 79 PDpatients at different stages of the disease. Healthy control subjects were matched for age and gender with PD subjects, and the diagnosis of patients was based on clinical evaluation by specialists in movement disorders. RNA was extracted from the blood samples and the gene expressions were measured using the Illumina HumanHT-12 v4.0 Expression BeadChip. RESULTS: Our results support previous studies that gene expression in blood may be instrumental in the search for molecular biomarkers for PD. Single cross-validation results show that PD can be correctly classified from healthy controls with an agreement of 88% to clinical diagnosis. De novo PDpatients are classified with a sensitivity of 87%, which is close to what was achieved for the patients having a confirmed PD diagnosis with disease duration <5 and >5 years (93% and 88%). A double cross-validation procedure showed that using a selected set of around 650 informative genes, similar results are achieved. Functional analysis of the selected genes showed genes significantly associated to mitochondrial dysfunction, protein ubiquitination, gene expression and cell death. CONCLUSIONS:PD affects gene expression in blood, suggesting the potential for the development of a blood-based gene expression test.
Authors: Katrina Gwinn; Karen K David; Christine Swanson-Fischer; Roger Albin; Coryse St Hillaire-Clarke; Beth-Anne Sieber; Codrin Lungu; F DuBois Bowman; Roy N Alcalay; Debra Babcock; Ted M Dawson; Richard B Dewey; Tatiana Foroud; Dwight German; Xuemei Huang; Vlad Petyuk; Judith A Potashkin; Rachel Saunders-Pullman; Margaret Sutherland; David R Walt; Andrew B West; Jing Zhang; Alice Chen-Plotkin; Clemens R Scherzer; David E Vaillancourt; Liana S Rosenthal Journal: Biomark Med Date: 2017-06-23 Impact factor: 2.851
Authors: Anelya Kh Alieva; Elena V Filatova; Aleksey V Karabanov; Sergey N Illarioshkin; Petr A Slominsky; Maria I Shadrina Journal: Parkinsons Dis Date: 2015-09-21
Authors: Sarah J Annesley; Sui T Lay; Shawn W De Piazza; Oana Sanislav; Eleanor Hammersley; Claire Y Allan; Lisa M Francione; Minh Q Bui; Zhi-Ping Chen; Kevin R W Ngoei; Flora Tassone; Bruce E Kemp; Elsdon Storey; Andrew Evans; Danuta Z Loesch; Paul R Fisher Journal: Dis Model Mech Date: 2016-09-16 Impact factor: 5.758
Authors: Oxana P Trifonova; Dmitri L Maslov; Elena E Balashova; Guzel R Urazgildeeva; Denis A Abaimov; Ekaterina Yu Fedotova; Vsevolod V Poleschuk; Sergey N Illarioshkin; Petr G Lokhov Journal: Diagnostics (Basel) Date: 2020-05-25