Defining tissue- and disease-associated macrophages using a transcriptome-based classification model
Andrew Y.F. Li Yim,
Guillermo R. Griffith,
Wouter J. de Jonge,
Marcel M.A.M. Mannens,
Menno P.J. de Winther
Posted 29 Jan 2019
bioRxiv DOI: 10.1101/532986 (published DOI: 10.3389/fimmu.2019.02887)
Posted 29 Jan 2019
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-γ 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-γ 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.
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