Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue

Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium

doi:10.1038/s41467-024-51012-6

Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue

Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium

Medicine, Rheumatology Division

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.

Original language	English (US)
Article number	7503
Journal	Nature communications
Volume	15
Issue number	1
DOIs	https://doi.org/10.1038/s41467-024-51012-6
State	Published - Dec 2024

Funding

The authors would like to sincerely thank the QuPath user community and development team at https://forum.image.sc/tag/qupath. Some figures were made with BioRender.com (Supplemental Fig.\u00A01A, B, Fig.\u00A02B). This work was supported by\u00A0Research into Inflammatory Arthritis Centre Versus Arthritis funding (to\u00A0A.F.); National Institutes of Health (NIH) grants R21-AR071670, R01-AI175212, UH2-AR067690, and UC2-AR081025\u00A0(to J.H.A.);\u00A0NIH grants\u00A0F30-AG076326 and T32-GM007356 (to H.M.K.); NIH grants RO1-AR046713 and R01-AR050401 (to L.B.I.); NIH grants R01-AR078268, UC2-AR081025, and UL1-TR001866 (to D.E.O.); NIH grant\u00A0R01-AR056702 (to E.M.S.); and National Science Foundation (NSF) grants 1750326 and 2212175 (to F.W.). The authors would like to sincerely thank the QuPath user community and development team at https://forum.image.sc/tag/qupath . Some figures were made with BioRender.com (Supplemental Fig. , Fig. ). This work was supported by Research into Inflammatory Arthritis Centre Versus Arthritis funding (to A.F.); National Institutes of Health (NIH) grants R21-AR071670, R01-AI175212, UH2-AR067690, and UC2-AR081025 (to J.H.A.); NIH grants F30-AG076326 and T32-GM007356 (to H.M.K.); NIH grants RO1-AR046713 and R01-AR050401 (to L.B.I.); NIH grants R01-AR078268, UC2-AR081025, and UL1-TR001866 (to D.E.O.); NIH grant R01-AR056702 (to E.M.S.); and National Science Foundation (NSF) grants 1750326 and 2212175 (to F.W.).

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-024-51012-6

Cite this

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title = "Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue",

abstract = "Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.",

author = "{Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium} and Bell, {Richard D.} and Matthew Brendel and Konnaris, {Maxwell A.} and Justin Xiang and Miguel Otero and Fontana, {Mark A.} and Zilong Bai and Soumya Raychaudhuri and Rao, {Deepak A.} and Costantino Pitzalis and Kevin Wei and Watts, {Gerald F.M.} and Utz, {Paul J.} and Turner, {Jason D.} and Darren Tabechian and Danielle Sutherby and Kamil Slowikowski and Anupamaa Seshadri and Jennifer Seifert and Karen Salomon-Escoto and Cristina Rozo and Mina Rohani-Pichavant and Robinson, {William H.} and Ritchlin, {Christopher T.} and Harris Perlman and Chad Nusbaum and Akiko Noma and Nguyen, {Jennifer P.} and Larry Moreland and Fumitaka Mizoguchi and Mears, {Joseph R.} and McNamara, {Michael A.} and McGeachy, {Mandy J.} and Mandelin, {Arthur M.} and Lieb, {David J.} and Lee, {Yvonne C.} and Lederer, {James A.} and Stephen Kelly and Josh Keegan and Jonsson, {A. Helena} and James, {Judith A.} and James, {Eddie A.} and Hughes, {Laura B.} and Holers, {V. Michael} and Nir Hacohen and Maria Gutierrez-Arcelus and Guthridge, {Joel M.} and Gregersen, {Peter K.} and Gravallese, {Ellen M.} and Fonseka, {Chamith Y.}",

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doi = "10.1038/s41467-024-51012-6",

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AU - Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Consortium

AU - Bell, Richard D.

AU - Brendel, Matthew

AU - Konnaris, Maxwell A.

AU - Xiang, Justin

AU - Otero, Miguel

AU - Fontana, Mark A.

AU - Bai, Zilong

AU - Raychaudhuri, Soumya

AU - Rao, Deepak A.

AU - Pitzalis, Costantino

AU - Wei, Kevin

AU - Watts, Gerald F.M.

AU - Utz, Paul J.

AU - Turner, Jason D.

AU - Tabechian, Darren

AU - Sutherby, Danielle

AU - Slowikowski, Kamil

AU - Seshadri, Anupamaa

AU - Seifert, Jennifer

AU - Salomon-Escoto, Karen

AU - Rozo, Cristina

AU - Rohani-Pichavant, Mina

AU - Robinson, William H.

AU - Ritchlin, Christopher T.

AU - Perlman, Harris

AU - Nusbaum, Chad

AU - Noma, Akiko

AU - Nguyen, Jennifer P.

AU - Moreland, Larry

AU - Mizoguchi, Fumitaka

AU - Mears, Joseph R.

AU - McNamara, Michael A.

AU - McGeachy, Mandy J.

AU - Mandelin, Arthur M.

AU - Lieb, David J.

AU - Lee, Yvonne C.

AU - Lederer, James A.

AU - Kelly, Stephen

AU - Keegan, Josh

AU - Jonsson, A. Helena

AU - James, Judith A.

AU - James, Eddie A.

AU - Hughes, Laura B.

AU - Holers, V. Michael

AU - Hacohen, Nir

AU - Gutierrez-Arcelus, Maria

AU - Guthridge, Joel M.

AU - Gregersen, Peter K.

AU - Gravallese, Ellen M.

AU - Fonseka, Chamith Y.

PY - 2024/12

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N2 - Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.

AB - Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.

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Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue

Abstract

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UN SDGs

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