High-dimensional Spatial Immune Profiling Highlights Microglia-Like Cells in Human Dorsal Root Ganglia.
Overview
- Institute of Neuropathology, Faculty of Medicine University of Freiburg Freiburg Germany
- Department of Neurosurgery University Medical Center Freiburg Freiburg Germany
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Disease, Faculty of Medicine University Medical Center Freiburg Freiburg Germany
- Signalling Research Centres BIOSS and CIBSS University of Freiburg Freiburg Germany
- Center Brain Research and Advancements In Neuroimmunology (BRAIN), Faculty of Medicine University of Freiburg Freiburg Germany
Abstract
The human dorsal root ganglia (DRG) are increasingly recognized as immunologically active sites within the peripheral nervous system. While single‐cell transcriptomics has recently identified myeloid populations with microglia‐like profiles in DRG across species, an in‐depth, spatially resolved protein‐level characterization in human tissue is lacking. Here, we used highly multiplexed Imaging Mass Cytometry (IMC) to map and phenotype myeloid cells in human DRG at subcellular resolution. A 41‐marker panel enabled in‐depth profiling of immune and neural cell types in situ. We identified a subset of Iba1+ myeloid cells co‐expressing canonical microglial markers such as P2RY12, TMEM119, and SLC2A5, located in close spatial proximity to neuronal somata. Unsupervised clustering (FlowSOM) of >6000 Iba1+ cells identified eight distinct clusters. Among them, distinct myeloid cell subsets exhibited a clear microglial‐like signature and were localized near neurofilament+ neurons. In contrast, Iba1+ clusters expressing CD68, HLA‐DR, and other activation markers were spatially segregated. These findings provide a spatially resolved, protein‑level atlas of Iba1+ myeloid subsets in human DRG and offer a resource for dissecting neuroimmune niches relevant to chronic pain and peripheral neuropathies.
Reproduced under the paper's license (CC BY), from the paper cited above.
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Data
Datasets cited
- zenodo:19299768 — at Zenodo; found in “Data Availability Statement”
Data Availability Statement
All data supporting the findings of this study have been deposited in a publicly available repository and can be accessed at https://
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.
Version 2, 28 September 2026
- Publisher: — → Wiley
Version 1, 27 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 5 keywords, 14 MeSH terms, 1 funder, 23 references.
Cite
This paper
Schwabenland, M., Oeztuerk, B., Blank, T., Beck, J., Bengsch, B., & Prinz, M. (2026). High-dimensional Spatial Immune Profiling Highlights Microglia-Like Cells in Human Dorsal Root Ganglia. European journal of immunology, 56(5), e70211. https://
BibTeX
@article{schwabenland202
author = {Schwabenland, Marius and Oeztuerk, Busranur and Blank, Thomas and Beck, Juergen and Bengsch, Bertram and Prinz, Marco},
title = {{High-dimensional Spatial Immune Profiling Highlights Microglia-Like Cells in Human Dorsal Root Ganglia}},
journal = {European journal of immunology},
year = {2026},
month = may,
volume = {56},
number = {5},
pages = {e70211},
publisher = {Wiley},
issn = {0014-2980},
doi = {10.1002/
url = {https://
pmid = {42153599},
pmcid = {PMC13185684}
}
RIS
TY - JOUR
AU - Schwabenland, Marius
AU - Oeztuerk, Busranur
AU - Blank, Thomas
AU - Beck, Juergen
AU - Bengsch, Bertram
AU - Prinz, Marco
TI - High-dimensional Spatial Immune Profiling Highlights Microglia-Like Cells in Human Dorsal Root Ganglia
T2 - European journal of immunology
J2 - Eur J Immunol
PY - 2026
DA - 2026/
VL - 56
IS - 5
SP - e70211
SN - 0014-2980
PB - Wiley
DO - 10.1002/
UR - https://
LA - en
ER -
CSL-JSON
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"language": "en",
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