The DOI matches its Crossref record; 104 of the 104 references it cites were found in a registry or an index.
Single-Cell Analysis of Crohn’s Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy
Open accessAbstract
SUMMARY Clinical benefits of cytokine blockade in ileal Crohn’s disease (iCD) are limited to a subset of patients. Here, we applied single-cell technologies to iCD lesions to address whether cellular heterogeneity contributes to treatment resistance. We found that a subset of patients expressed a unique cellular module in inflamed tissues that consisted of IgG plasma cells, inflammatory mononuclear phagocytes, activated T cells, and stromal cells, which we named the GIMATS module. Analysis of ligand-receptor interaction pairs identified a distinct network connectivity that likely drives the GIMATS module. Strikingly, the GIMATS module was also present in a subset of patients in four independent iCD cohorts (n = 441), and its presence at diagnosis correlated with failure to achieve durable corticosteroid-free remission upon anti-TNF therapy. These results emphasize the limitations of current diagnostic assays and the potential for single-cell mapping tools to identify novel biomarkers of treatment response and tailored therapeutic opportunities.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Fiji: an open-source platform for biological-image analysis
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2019 · Cited by 66,890
Dendritic cells and the control of immunity
Banchereau, J., & Steinman, R. M. (1998) · Nature · doi:10.1038/32588 · Cited by 14,336
Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., Pimentel, H., Salzberg, S. L., Rinn, J. L., & Pachter, L. (2012) · Nature Protocols · doi:10.1038/nprot.2012.016 · Cited by 12,116
QuPath: Open source software for digital pathology image analysis
Bankhead, P., Loughrey, M. B., Fernández, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D., McQuaid, S., Gray, R. T., Murray, L. J., Coleman, H. G., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-17204-5 · Cited by 8,908
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110
Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease
The International IBD Genetics Consortium (IIBDGC), Jostins, L., Ripke, S., Weersma, R. K., Duerr, R. H., McGovern, D. P., Hui, K. Y., Lee, J. C., Philip Schumm, L., Sharma, Y., et al. (2012) · Nature · doi:10.1038/nature11582 · Cited by 4,722
Self-citationDroplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356
Vedolizumab as Induction and Maintenance Therapy for Crohn's Disease
Sandborn, W. J., Feagan, B. G., Rutgeerts, P., Hanauer, S., Colombel, J.-F., Sands, B. E., Lukas, M., Fedorak, R. N., Lee, S., Bressler, B., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1215739 · Cited by 2,719
Cited by
HCA Lung Biological Network, Sungnak, W., Huang, N., Bécavin, C., Berg, M., Queen, R., Litvinukova, M., Talavera-López, C., Maatz, H., Reichart, D., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0868-6 · Cited by 2,501
Zou, X., Chen, K., Zou, J., Han, P., Hao, J., & Han, Z. (2020) · Frontiers of Medicine · doi:10.1007/s11684-020-0754-0 · Cited by 2,287
Pathophysiology of Inflammatory Bowel Diseases
Chang, J. T. (2020) · New England Journal of Medicine · doi:10.1056/nejmra2002697 · Cited by 1,295
Deciphering cell–cell interactions and communication from gene expression
Armingol, E., Officer, A., Harismendy, O., & Lewis, N. E. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00292-x · Cited by 1,267
Transfer learning enables predictions in network biology
Theodoris, C. V., Xiao, L., Chopra, A., Chaffin, M. D., Al Sayed, Z. R., Hill, M. C., Mantineo, H., Brydon, E. M., Zeng, Z., Liu, X. S., et al. (2023) · Nature · doi:10.1038/s41586-023-06139-9 · Cited by 1,193
Metadata
- Authors
- Martin, J. C., Chang, C., Boschetti, G., Ungaro, R., Giri, M., Grout, J. A., Gettler, K., Chuang, L.-S., Nayar, S., Greenstein, A. J., Dubinsky, M., Walker, L., Leader, A., Fine, J. S., Whitehurst, C. E., Mbow, M. L., Kugathasan, S., Denson, L. A., Hyams, J. S., Friedman, J. R., Desai, P. T., Ko, H. M., Laface, I., Akturk, G., Schadt, E. E., Salmon, H., Gnjatic, S., Rahman, A. H., Merad, M., Cho, J. H., & Kenigsberg, E.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 178
- Issue
- 6
- Pages
- 1493-1508.e20
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2970463661
- Cited by
- 872
- References
- 104
- FWCI
- 46.05
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Single-Cell Analysis of Crohn’s Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy. https://app.cochat.ai/papers/10.1016/j.cell.2019.08.008
- The paper
- Martin, J. C., Chang, C., Boschetti, G., Ungaro, R., Giri, M., Grout, J. A., Gettler, K., Chuang, L.-S., Nayar, S., Greenstein, A. J., Dubinsky, M., Walker, L., Leader, A., Fine, J. S., Whitehurst, C. E., Mbow, M. L., Kugathasan, S., Denson, L. A., Hyams, J. S., . . . Kenigsberg, E. (2019). Single-Cell Analysis of Crohn’s Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy. Cell. https://doi.org/10.1016/j.cell.2019.08.008
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
