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Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data

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Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data

Arthritis & Rheumatology

Fecha de publicación: 22 February 2018

DOI: https://doi.org/10.1002/art.40428

Autores: Dana E. Orange MD,MSc, Phaedra Agius PhD, Edward F. DiCarlo MD, Nicolas Robine PhD, Heather Geiger BA, Jackie Szymonifka PhD, Michael McNamara BS, Ryan Cummings AB…

Background: Objective in this study, we sought to refine histologic scoring of rheumatoid arthritis (RA) synovial tissue by training with gene expression data and machine learning.

Methods: Twenty histologic features were assessed in 129 synovial tissue samples (n = 123 RA patients and n = 6 osteoarthritis [OA] patients). Consensus clustering was performed on gene expression data from a subset of 45 synovial samples. Support vector machine learning was used to predict gene expression subtypes, using histologic data as the input. Corresponding clinical data were compared across subtypes.

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