Evidence map›Paper›PMID 31253778›Full record

ArticleNature communications2019

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

Paulo Czarnewski, Sara M Parigi, Chiara Sorini, Oscar E Diaz, Srustidhar Das, Nicola Gagliani, Eduardo J Villablanca

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed
9.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

79 citing papers in PubMed, 128 citations in OpenAlex.

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19 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 2 countries.

Paulo CzarnewskiImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
Sara M ParigiImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
Chiara SoriniImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.ORCID http://orcid.org/0000-0002-6803-8377
Oscar E DiazImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-7622-7832
Srustidhar DasImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
Nicola GaglianiImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden.
Eduardo J VillablancaImmunology and Allergy Unit, Department of Medicine, Solna, Karolinska Institute and University Hospital, 17176, Stockholm, Sweden. eduardo.villablanca@ki.se.ORCID http://orcid.org/0000-0001-9522-9729
Karolinska University Hospital · SE

Funding

Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation) WAF2014Svenska Forskningsrådet Formas (Swedish Research Council Formas) FR-2016/2005Vetenskapsrådet (Swedish Research Council) K2015-68X-22765-01-6
6 · The paper itself

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.

Indexed as

Chromosome MappingTranscriptomeAnimalsColitisFlow CytometryGene Expression RegulationHumansInflammatory Bowel DiseasesMiceMucous MembraneRNA, MessengerRNA, Messenger

Identifiers

PMID31253778
PMCPMC6598981
OpenAlexW2954675852

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.