Published April 16, 2022 | Version v1
Dataset Open

Development of a machine learning model to predict non- durable response to anti-TNF therapy in Crohn's disease using transcriptome imputed from genotypes

Authors/Creators

  • 1. 1Division of Gastroenterology, Department of Internal Medicine and Inflammatory Bowel Disease Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea 2Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea
  • 2. Department of Bioinformatics, Soongsil University, Seoul, Korea
  • 3. Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea
  • 4. Department of Internal Medicine, College of Medicine, Chung-Ang University, Seoul, Korea
  • 5. Department of Internal Medicine, College of Medicine, Daejeon St. Mary's Hospital, The Catholic University of Korea, Daejeon, Korea
  • 6. Department of Internal Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
  • 7. Department of Internal Medicine, Dankook University College of Medicine, Cheonan, Korea
  • 8. Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University
  • 9. Department of Internal Medicine, Kyung Hee University Hospital at Gang Dong, Kyung Hee University College of Medicine, Seoul, Korea
  • 10. Department of Internal Medicine and Liver Research Institute, College of Medicine, Seoul National University, Seoul, Korea
  • 11. Department of Human Intelligence and Robot Engineering, Sangmyung University, Chungcheongnam-do, Korea
  • 12. Functional Genome Institute, PDXen Biosystems Inc, Seoul, Korea
  • 13. Personalized Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Korea

Description

This is the expression value predicted using PrediXcan version 7 to find a gene feature that can distinguish between patients with and without effect on infliximab.

Among the various tissue models provided by PrediXcan v7, three models were selected and used: whole blood, Colon transverse, and terminal ileum of small intestine, and the predicted gene counts of each model were 6,294, 5,612 and 3,107.

For each of the three models, predicted gene expression values and phenotype information per sample were submitted.

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md5:58b94194c555c92a63a3fc1109be4567
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Additional details

References

  • Gamazon ER†, Wheeler HE†, Shah KP†, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC, Nicolae DL, Cox NJ, Im HK. (2015) A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. doi:10.1038/ng.3367.