OBJECTIVE: Parkinson disease (PD) is a degenerative disorder of the central nervous system, and in the majority of cases, the causes of PD are unknown. Coupled with impressive advances in statistical tools for analyzing large, complex data sets, well-designed microarray experiments are poised to make a big impact in the field of diseases. So we set the study to identify distinct PD-associated candidates. METHODS: Candidate genes, with statistical significant changes of expression in PD patients' samples, were extracted from a transcriptome-wide microarray data in 105 individuals, which were downloaded from GEO, NCBI, by using statistical methods; Selected findings were confirmed by principal component analysis (PCA) and functional and pathway enrichment analysis were used to further study about the distinct candidates. RESULTS: A total of 10 distinctly differentially expressed genes were identified in PD patitents' samples. After PCA confirmation, we specifically pointed out 4 genes (PRKAG2, DLG1, DDX3Y, RPS4Y) as the high confidence distinct candidates in PD. Network and functional categories showed that they were most related to translational elongation(GO:0006414) and participated in mTOR signaling pathway(hsa04150). CONCLUSION: Among 10 distinct genes which are identified in PD patients' samples, DLG1, XIST, DDX3Y and RPS4Y1 genes can classify samples into different group clearly, and they are regarded as high confidence distinct gene biomarkers of PD. Our results provide a systematic view of the functional alterations of PD that may help to elucidate the mechanisms of PD and lead to improved treatments for PD patients.
OBJECTIVE:Parkinson disease (PD) is a degenerative disorder of the central nervous system, and in the majority of cases, the causes of PD are unknown. Coupled with impressive advances in statistical tools for analyzing large, complex data sets, well-designed microarray experiments are poised to make a big impact in the field of diseases. So we set the study to identify distinct PD-associated candidates. METHODS: Candidate genes, with statistical significant changes of expression in PDpatients' samples, were extracted from a transcriptome-wide microarray data in 105 individuals, which were downloaded from GEO, NCBI, by using statistical methods; Selected findings were confirmed by principal component analysis (PCA) and functional and pathway enrichment analysis were used to further study about the distinct candidates. RESULTS: A total of 10 distinctly differentially expressed genes were identified in PD patitents' samples. After PCA confirmation, we specifically pointed out 4 genes (PRKAG2, DLG1, DDX3Y, RPS4Y) as the high confidence distinct candidates in PD. Network and functional categories showed that they were most related to translational elongation(GO:0006414) and participated in mTOR signaling pathway(hsa04150). CONCLUSION: Among 10 distinct genes which are identified in PDpatients' samples, DLG1, XIST, DDX3Y and RPS4Y1 genes can classify samples into different group clearly, and they are regarded as high confidence distinct gene biomarkers of PD. Our results provide a systematic view of the functional alterations of PD that may help to elucidate the mechanisms of PD and lead to improved treatments for PDpatients.
Authors: Jari Tiihonen; Marja Koskuvi; Markus Storvik; Ida Hyötyläinen; Yanyan Gao; Katja A Puttonen; Raisa Giniatullina; Ekaterina Poguzhelskaya; Ilkka Ojansuu; Olli Vaurio; Tyrone D Cannon; Jouko Lönnqvist; Sebastian Therman; Jaana Suvisaari; Jaakko Kaprio; Lesley Cheng; Andrew F Hill; Markku Lähteenvuo; Jussi Tohka; Rashid Giniatullin; Šárka Lehtonen; Jari Koistinaho Journal: Nat Commun Date: 2019-09-02 Impact factor: 14.919
Authors: Clara Isaza; Juan F Rosas; Enery Lorenzo; Arlette Marrero; Cristina Ortiz; Michael R Ortiz; Lynn Perez; Mauricio Cabrera-Ríos Journal: Cancer Med Date: 2018-04-10 Impact factor: 4.452