Skip to content
DraconiticResearch
Search Sources API
182,460 studies31 sourcesUpdated 31 min ago
Peer-reviewedCC BY-NC-NDNature Neuroscience

Spatial proteomic analysis in human Alzheimer’s disease brains enables identification of microenvironment-dependent microglial cell states

  • Paula Sanchez-Molina1,2
  • Dennis-Dominik Rosmus3,4,5
  • Dillon Brownell1,2
  • Mert Meral6
  • Cavanagh Gohlich1,2
  • Aditya Pratapa7
  • Yaser Peymanfar7
  • Alyssa Whitley7
  • Yue Hou7
  • Nadezhda Nikulina7
  • Alina P. Bogachuk1,2
  • Ellen L. Bouchard1,2
7 more authors
  • Aude Chiot1,2
  • Heidrun Kuhrt5
  • Peter Wieghofer3,5
  • Randall L. Woltjer8
  • Fabian Svara6
  • Oliver Braubach9
  • Bahareh Ajami10,11,12
12 affiliations
  1. 1Department of Behavioral and Systems Neuroscience, Oregon Health and Science University, Portland, OR, USA
  2. 2Department of Molecular Microbiology and Immunology, Oregon Health and Science University, Portland, OR, USA
  3. 3Cellular Neuroanatomy, Chair of Anatomy and Cell Biology, Institute of Theoretical Medicine, University of Augsburg, Augsburg, Germany
  4. 4Department of Neurology, Leipzig University Medical Center, Leipzig, Germany
  5. 5Institute of Anatomy, Leipzig University, Leipzig, Germany
  6. 6ariadne.ai AG, Lucerne, Switzerland
  7. 7Akoya Biosciences, Marlborough, MA, USA
  8. 8Department of Pathology, Oregon Health and Science University, Portland, OR, USA
  9. 9Akoya Biosciences, Marlborough, MA, USA. [email protected]
  10. 10Department of Behavioral and Systems Neuroscience, Oregon Health and Science University, Portland, OR, USA. [email protected]
  11. 11Department of Molecular Microbiology and Immunology, Oregon Health and Science University, Portland, OR, USA. [email protected]
  12. 12Department of Neurology and Regenerative Medicine Institute, Cedars Sinai, Los Angeles, CA, USA. [email protected]
Open at sourceDOICite

Abstract

Single-cell technologies have revealed important cell heterogeneity across the human brain. In the context of neurological diseases, the relationship between different cell subpopulations and pathological features can be crucial for their understanding. However, the combination of spatial, single-cell, and high-plex protein information together with analytical tools for the accurate segmentation of ramified cells remains a challenge to address in neuroscience. Here, we present CODEX-CNS, a modification of CO-Detection by indEXing (CODEX) technology for its use in human brain tissues. This technology consists of multiplexed fluorescent imaging that allows the detection of up to 100 proteins using DNA-barcoded antibodies. In this paper we bring technical advancements to the CODEX protocol and an improved data analysis pipeline for accurate segmentation of complex cell morphologies. As proof-of-principle, we were able to detect the different parenchymal brain cells and their cytoarchitecture, as well as blood-brain barrier and meningeal components with a 32-plex antibody panel. More specifically, we used CODEX-CNS in human brain samples of healthy and Alzheimer’s disease donors to study microglial phenotypes in relationship to their spatial context. Applying our customized cell segmentation algorithm and clustering analysis, we identified diverse microglial subpopulations differentially distributed between brain areas and according to their distance to amyloid-β plaques. These data provide a new approach for the neuroscience community that allows the characterization of microglial subpopulations at the protein level with both single-cell and spatial resolution.

Related

  1. Brain region- and solubility-dependent proteomic signatures of neurofibrillary tangle pathology in Alzheimer's disease
    X. Zeng, E. Abrahamson, W. G. Balogun +5
    medRxivPreprintCC BYFull textNeurologymedRxiv
  2. Proteomic Characterization of Prostate Cancer Bone Metastasis Subtypes Defines Progressive Remodeling States of the Bone-Tumor Microenvironment
    D. Xie, B. Mojtahedzahdeh, K. Chan +10
    bioRxivPreprintAll rights reservedFull textOncologybioRxiv
  3. Profiling Amino Acid Substitutions in Proteomic Datasets of Alzheimer’s Disease Reveals Biological Significance
    Peize Zhao, Shengzhi Lai, Shuaijian Dai +3
    BiomedicinesPeer-reviewedCC BYFull textGeneral medicineEurope PMC
  4. Astrocyte and Microglial Transcriptional Programs in the Atypical Teratoid/Rhabdoid Tumor Microenvironment
    Yu Xue, Uvindu Thilanka, Drishty Badhon Sarker +2
    CancersPeer-reviewedCC BY 4.0Human geneticsCrossref
  5. Microglial Therapeutic Potential in Alzheimer's Disease: From Phenotypic Diversity to Targeted Interventions.
    Maria-Raluca Gogu, Ivona Mazarianu, Gabriela-Dumitrita Stanciu +3
    Pharmaceuticals (Basel, Switzerland)Peer-reviewedCC BYFull textNeurologyEurope PMC

Cite

BibTeXRIS
BibTeX
@article{sanchezmolina2026spatial,
  title = {{Spatial proteomic analysis in human Alzheimer’s disease brains enables identification of microenvironment-dependent microglial cell states}},
  author = {Paula Sanchez-Molina and Dennis-Dominik Rosmus and Dillon Brownell and Mert Meral and Cavanagh Gohlich and Aditya Pratapa and Yaser Peymanfar and Alyssa Whitley and Yue Hou and Nadezhda Nikulina and Alina P. Bogachuk and Ellen L. Bouchard and Aude Chiot and Heidrun Kuhrt and Peter Wieghofer and Randall L. Woltjer and Fabian Svara and Oliver Braubach and Bahareh Ajami},
  journal = {Nature Neuroscience},
  year = {2026},
  month = may,
  doi = {10.1038/s41593-026-02267-3},
  url = {https://doi.org/10.1038/s41593-026-02267-3},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Spatial proteomic analysis in human Alzheimer’s disease brains enables identification of microenvironment-dependent microglial cell states
AU  - Paula Sanchez-Molina
AU  - Dennis-Dominik Rosmus
AU  - Dillon Brownell
AU  - Mert Meral
AU  - Cavanagh Gohlich
AU  - Aditya Pratapa
AU  - Yaser Peymanfar
AU  - Alyssa Whitley
AU  - Yue Hou
AU  - Nadezhda Nikulina
AU  - Alina P. Bogachuk
AU  - Ellen L. Bouchard
AU  - Aude Chiot
AU  - Heidrun Kuhrt
AU  - Peter Wieghofer
AU  - Randall L. Woltjer
AU  - Fabian Svara
AU  - Oliver Braubach
AU  - Bahareh Ajami
PY  - 2026
DA  - 2026/05/18
JO  - Nature Neuroscience
DO  - 10.1038/s41593-026-02267-3
UR  - https://doi.org/10.1038/s41593-026-02267-3
AB  - Single-cell technologies have revealed important cell heterogeneity across the human brain. In the context of neurological diseases, the relationship between different cell subpopulations and pathological features can be crucial for their understanding. However, the combination of spatial, single-cell, and high-plex protein information together with analytical tools for the accurate segmentation of ramified cells remains a challenge to address in neuroscience. Here, we present CODEX-CNS, a modification of CO-Detection by indEXing (CODEX) technology for its use in human brain tissues. This technology consists of multiplexed fluorescent imaging that allows the detection of up to 100 proteins using DNA-barcoded antibodies. In this paper we bring technical advancements to the CODEX protocol and an improved data analysis pipeline for accurate segmentation of complex cell morphologies. As proof-of-principle, we were able to detect the different parenchymal brain cells and their cytoarchitecture, as well as blood-brain barrier and meningeal components with a 32-plex antibody panel. More specifically, we used CODEX-CNS in human brain samples of healthy and Alzheimer’s disease donors to study microglial phenotypes in relationship to their spatial context. Applying our customized cell segmentation algorithm and clustering analysis, we identified diverse microglial subpopulations differentially distributed between brain areas and according to their distance to amyloid-β plaques. These data provide a new approach for the neuroscience community that allows the characterization of microglial subpopulations at the protein level with both single-cell and spatial resolution.
SN  - 1097-6256
SN  - 1546-1726
ER  -