Defining tissue- and disease-associated macrophages using a transcriptome-based classification model
H.-J. Chen, A. Y. F. Li Yim, G. R. Griffith, W. J. de Jonge, M. M. A. M. Mannens, E. Ferrero, P. Henneman, M. P. J. de Winther
Abstract
Macrophages are heterogeneous multifunctional leukocytes which are regulated in a tissue-and disease-specific context. Many different studies have been published using in vitro macrophage models to study disease. Here, we aggregated public expression data to define consensus expression profiles for eight commonly-used in vitro macrophage models. Altogether, we observed well-known but also novel markers for different macrophage subtypes. Using these data we subsequently built the classifier macIDR, capable of distinguishing macrophage subsets with high accuracy (>0.95). This classifier was subsequently applied to transcriptional profiles of tissue-isolated and disease-associated macrophages to specifically define macrophage characteristics in vivo. Classification of these in vivo macrophages showed that alveolar macrophages displayed high resemblance to interleukin-10 activated macrophages, whereas macrophages from patients with chronic obstructive pulmonary disease patients displayed a drop in interferon-{gamma} signature. Adipose tissue-derived macrophages were classified as unstimulated macrophages, but resembled LPS-activated macrophages more in diabetic-obese patients. Finally, rheumatoid arthritic synovial macrophages showed characteristics of both interleukin-10 or interferon-{gamma} signatures. Altogether, our results suggest that macIDR is capable of identifying macrophage-specific changes as a result of tissue-and disease-specific stimuli and thereby can be used to better define and model populations of macrophages that contribute to disease.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- In vitro and in vivo derived macrophages occupy distinct phenotypic states
Stéphane Chevrier, Vito RT Zanotelli, … Bernd Bodenmiller·bioRxiv·Sep 20, 2025
- Predictive framework of macrophage activation
D. E. Sanin, Y. Ge, … E. J. Pearce·bioRxiv·Aug 2, 2021
- A data-driven model of macrophage polarization states reveals an IFN macrophage signature in active Crohn's disease
Sarina C. Lowe, Madelaine Leitman, … Alexander Hoffmann·Frontiers in ImmunologyPeer-reviewed·Dec 4, 2025
- Machine Learning Identifies Signatures of Macrophage Reactivity and Tolerance that Predict Disease Outcomes
Pradipta Ghosh, Saptarshi Sinha, … Debashis Sahoo·EBioMedicinePeer-reviewed·Jul 27, 2023
- An integrated analysis of myeloid cells identifies gaps in in vitro models of in vivo biology
Nadia Rajab, Paul W. Angel, … Christine Anne Wells·bioRxiv·Jul 8, 2020
- Tissue signatures of human macrophages during homeostasis and activation
Daniel P. Caron, William L. Specht, … Donna L. Färber·The Journal of ImmunologyPeer-reviewed·Dec 12, 2025