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Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification.
Czarnewski, Paulo; Parigi, Sara M; Sorini, Chiara; Diaz, Oscar E; Das, Srustidhar; Gagliani, Nicola; Villablanca, Eduardo J.
Afiliación
  • Czarnewski P; Immunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
  • Parigi SM; Immunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
  • Sorini C; Immunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
  • Diaz OE; Immunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
  • Das S; Immunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
  • Gagliani N; Immunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
  • Villablanca EJ; Department of Medicine and Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany.
Nat Commun ; 10(1): 2892, 2019 06 28.
Article en En | MEDLINE | ID: mdl-31253778
ABSTRACT
Clinical manifestations and response to therapies in ulcerative colitis (UC) are heterogeneous, yet patient classification criteria for tailored therapies are currently lacking. Here, we present an unsupervised molecular classification of UC patients, concordant with response to therapy in independent retrospective cohorts. We show that classical clustering of UC patient tissue transcriptomic data sets does not identify clinically relevant profiles, likely due to associated covariates. To overcome this, we compare cross-sectional human data sets with a newly generated longitudinal transcriptome profile of murine DSS-induced colitis. We show that the majority of colitis risk-associated gene expression peaks during the inflammatory rather than the recovery phase. Moreover, we achieve UC patient clustering into two distinct transcriptomic profiles, differing in neutrophil-related gene activation. Notably, 87% of patients in UC1 cluster are unresponsive to two most widely used biological therapies. These results demonstrate that cross-species comparison enables stratification of patients undistinguishable by other molecular approaches.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Inflamatorias del Intestino / Mapeo Cromosómico / Colitis / Transcriptoma Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2019 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Inflamatorias del Intestino / Mapeo Cromosómico / Colitis / Transcriptoma Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2019 Tipo del documento: Article País de afiliación: Suecia