Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
29 Aug 2024
29 Aug 2024
Historique:
received:
26
08
2023
accepted:
26
07
2024
medline:
1
9
2024
pubmed:
1
9
2024
entrez:
29
8
2024
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 39209814
doi: 10.1038/s41467-024-51012-6
pii: 10.1038/s41467-024-51012-6
pmc: PMC11362542
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7503Subventions
Organisme : U.S. Department of Health Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
ID : AR050401
Organisme : NIAMS NIH HHS
ID : R01 AR046713
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI175212
Pays : United States
Organisme : NIAMS NIH HHS
ID : R21 AR071670
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007356
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001866
Pays : United States
Organisme : NIAMS NIH HHS
ID : UC2 AR081025
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067690
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR050401
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR078268
Pays : United States
Organisme : NIAMS NIH HHS
ID : R01 AR056702
Pays : United States
Organisme : NIA NIH HHS
ID : F30 AG076326
Pays : United States
Investigateurs
Jennifer Albrecht
(J)
William Apruzzese
(W)
Brendan F Boyce
(BF)
David L Boyle
(DL)
Michael B Brenner
(MB)
S Louis Bridges
(SL)
Christopher D Buckley
(CD)
Jane H Buckner
(JH)
Vivian P Bykerk
(VP)
James Dolan
(J)
Thomas M Eisenhaure
(TM)
Andrew Filer
(A)
Gary S Firestein
(GS)
Chamith Y Fonseka
(CY)
Ellen M Gravallese
(EM)
Peter K Gregersen
(PK)
Joel M Guthridge
(JM)
Maria Gutierrez-Arcelus
(M)
Nir Hacohen
(N)
V Michael Holers
(VM)
Laura B Hughes
(LB)
Eddie A James
(EA)
Judith A James
(JA)
A Helena Jonsson
(AH)
Josh Keegan
(J)
Stephen Kelly
(S)
James A Lederer
(JA)
Yvonne C Lee
(YC)
David J Lieb
(DJ)
Arthur M Mandelin
(AM)
Mandy J McGeachy
(MJ)
Michael A McNamara
(MA)
Joseph R Mears
(JR)
Fumitaka Mizoguchi
(F)
Larry Moreland
(L)
Jennifer P Nguyen
(JP)
Akiko Noma
(A)
Chad Nusbaum
(C)
Harris Perlman
(H)
Christopher T Ritchlin
(CT)
William H Robinson
(WH)
Mina Rohani-Pichavant
(M)
Cristina Rozo
(C)
Karen Salomon-Escoto
(K)
Jennifer Seifert
(J)
Anupamaa Seshadri
(A)
Kamil Slowikowski
(K)
Danielle Sutherby
(D)
Darren Tabechian
(D)
Jason D Turner
(JD)
Paul J Utz
(PJ)
Gerald F M Watts
(GFM)
Kevin Wei
(K)
Costantino Pitzalis
(C)
Deepak A Rao
(DA)
Soumya Raychaudhuri
(S)
Informations de copyright
© 2024. The Author(s).
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