Glycomics meets artificial intelligence - Potential of glycan analysis for identification of seropositive and seronegative rheumatoid arthritis patients revealed

被引:20
作者
Chocholova, Erika [1 ]
Bertok, Tomas [1 ]
Jane, Eduard [1 ]
Lorencova, Lenka [1 ]
Holazova, Alena [1 ]
Belicka, Ludmila [1 ]
Belicky, Stefan [1 ]
Mislovicova, Danica [1 ]
Vikartovska, Alica [1 ]
Imrich, Richard [2 ,3 ]
Kasak, Peter [4 ]
Tkac, Jan [1 ]
机构
[1] Slovak Acad Sci, Inst Chem, Dubravska Cesta 9, Bratislava 84538, Slovakia
[2] Slovak Acad Sci, Biomed Res Ctr, Dubravska Cesta 9, Bratislava 84505, Slovakia
[3] Natl Inst Rheumat Dis, Nabrezie 1 Krasku 4, Piestany 92112, Slovakia
[4] Qatar Univ, Ctr Adv Mat, Doha 2713, Qatar
基金
欧洲研究理事会;
关键词
Glycoprotein; Glycan; Immunoassay; Rheumatoid arthritis; Lectin; Biomarker; Machine learning algorithm; Feedforward artificial neural network; MACHINE LEARNING TECHNIQUES; DIAGNOSIS; GLYCOSYLATION; BIOMARKERS; CLASSIFICATION; INTERFACE;
D O I
10.1016/j.cca.2018.02.031
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
In this study, one hundred serum samples from healthy people and patients with rheumatoid arthritis (RA) were analyzed. Standard immunoassays for detection of 10 different RA markers and analysis of glycan markers on antibodies in 10 different assay formats with several lectins were applied for each serum sample. A dataset containing 2000 data points was data mined using artificial neural networks (ANN). We identified key RA markers, which can discriminate between healthy people and seropositive RA patients (serum containing autoantibodies) with accuracy of 83.3%. Combination of RA markers with glycan analysis provided much better discrimination accuracy of 92.5%. Immunoassays completely failed to identify seronegative RA patients (serum not containing autoantibodies), while glycan analysis correctly identified 43.8% of these patients. Further, we revealed other critical parameters for successful glycan analysis such as type of a sample, format of analysis and orientation of captured antibodies for glycan analysis.
引用
收藏
页码:49 / 55
页数:7
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