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Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification

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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.

In: NAT COMMUN, Vol. 10, No. 1, 28.06.2019, p. 2892.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Czarnewski, P, Parigi, SM, Sorini, C, Diaz, OE, Das, S, Gagliani, N & Villablanca, EJ 2019, 'Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification', NAT COMMUN, vol. 10, no. 1, pp. 2892. https://doi.org/10.1038/s41467-019-10769-x

APA

Czarnewski, P., Parigi, S. M., Sorini, C., Diaz, O. E., Das, S., Gagliani, N., & Villablanca, E. J. (2019). Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification. NAT COMMUN, 10(1), 2892. https://doi.org/10.1038/s41467-019-10769-x

Vancouver

Czarnewski P, Parigi SM, Sorini C, Diaz OE, Das S, Gagliani N et al. Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification. NAT COMMUN. 2019 Jun 28;10(1):2892. https://doi.org/10.1038/s41467-019-10769-x

Bibtex

@article{4a816413c1c0423cb9f2fab8ea9984aa,
title = "Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification",
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.",
author = "Paulo Czarnewski and Parigi, {Sara M} and Chiara Sorini and Diaz, {Oscar E} and Srustidhar Das and Nicola Gagliani and Villablanca, {Eduardo J}",
year = "2019",
month = jun,
day = "28",
doi = "10.1038/s41467-019-10769-x",
language = "English",
volume = "10",
pages = "2892",
journal = "NAT COMMUN",
issn = "2041-1723",
publisher = "NATURE PUBLISHING GROUP",
number = "1",

}

RIS

TY - JOUR

T1 - Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification

AU - Czarnewski, Paulo

AU - Parigi, Sara M

AU - Sorini, Chiara

AU - Diaz, Oscar E

AU - Das, Srustidhar

AU - Gagliani, Nicola

AU - Villablanca, Eduardo J

PY - 2019/6/28

Y1 - 2019/6/28

N2 - 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.

AB - 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.

U2 - 10.1038/s41467-019-10769-x

DO - 10.1038/s41467-019-10769-x

M3 - SCORING: Journal article

C2 - 31253778

VL - 10

SP - 2892

JO - NAT COMMUN

JF - NAT COMMUN

SN - 2041-1723

IS - 1

ER -