Gene expression profile based classification models of psoriasis.
Psoriasis is an autoimmune disease, which symptoms can significantly impair the patient's life quality. It is mainly diagnosed through the visual inspection of the lesion skin by experienced dermatologists. Currently no cure for psoriasis is available due to limited knowledge about its pathogenesis and development mechanisms. Previous studies have profiled hundreds of differentially expressed genes related to psoriasis, however with no robust psoriasis prediction model available. This study integrated the knowledge of three feature selection algorithms that revealed 21 features belonging to 18 genes as candidate markers. The final psoriasis classification model was established using the novel Incremental Feature Selection algorithm that utilizes only 3 features from 2 unique genes, IGFL1 and C10orf99. This model has demonstrated highly stable prediction accuracy (averaged at 99.81%) over three independent validation strategies. The two marker genes, IGFL1 and C10orf99, were revealed as the upstream components of growth signal transduction pathway of psoriatic pathogenesis.
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Department of Public Health, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong 515041, PR China.
Pi
P
Guo
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China.
Youxi
Y
Luo
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China.
Guoqin
G
Mai
Department of Epidemiology and Biostatistics, Faculty of Infectious Diseases, University of Georgia, Athens, GA 30605, USA; Institute of Bioinformatics, University of Georgia, Athens, GA 30605, USA.
Ming
M
Zhang
Department of Pathogeny Biology, Norman Bethune Medical College, Jilin University, Changchun, Jilin 130021, PR China; Department of Pathogeny Biology, Norman Bethune Medical College, Jilin University, Changchun, Jilin 130021, PR China.
Guoqing
G
Wang
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China.
Miaomiao
M
Zhao
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China.
Liming
L
Gao
Department of Pathogeny Biology, Norman Bethune Medical College, Jilin University, Changchun, Jilin 130021, PR China; Key Laboratory of Zoonosis Research, Ministry of Education, Jilin University, Changchun, Jilin 130021, PR China.
Fan
F
Li
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China; Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, PR China. Electronic address: ff.zhou@siat.ac.cn.
Fengfeng
F
Zhou
D000465:Algorithms; D001185:Artificial Intelligence; D016022:Case-Control Studies; D049109:Cell Proliferation; D016208:Databases, Factual; D020869:Gene Expression Profiling; D005819:Genetic Markers; D006801:Humans; D046228:Microarray Analysis; D008957:Models, Genetic; D011565:Psoriasis / Q000145:classification / Q000175:diagnosis* / Q000235:genetics*; D012372:ROC Curve; D015398:Signal Transduction / Q000235:genetics; D012867:Skin / Q000166:cytology / Q000473:pathology; D059467:Transcriptome
D005819:Genetic Markers
Classification; Gene expression profiles; Psoriasis