Development of a Machine Learning Model to Predict Non-Durable Response to Anti-TNF Therapy in Crohn’s Disease Using Transcriptome Imputed from Genotypes

Development of a Machine Learning Model to Predict Non-Durable Response to Anti-TNF Therapy in Crohn’s Disease Using Transcriptome Imputed from Genotypes

Almost half of patients show no primary or secondary response to monoclonal anti-tumor necrosis factor α (anti-TNF) antibody treatment for inflammatory bowel disease (IBD). Thus, the exact mechanisms of a non-durable response (NDR) remain inadequately defined. We used our genome-wide genotype data t...

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Bibliographic Details
Main Authors: Soo Kyung Park, Yea Bean Kim, Sangsoo Kim, Chil Woo Lee, Chang Hwan Choi, Sang-Bum Kang, Tae Oh Kim, Ki Bae Bang, Jaeyoung Chun, Jae Myung Cha, Jong Pil Im, Min Suk Kim, Kwang Sung Ahn, Seon-Young Kim, Dong Il Park
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Journal of Personalized Medicine
Subjects:
genotype
genetic features
anti-TNF
Crohn’s disease
Online Access:https://www.mdpi.com/2075-4426/12/6/947

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https://www.mdpi.com/2075-4426/12/6/947

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