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

Disease-associated microglial states are thought to contribute to Alzheimer’s disease (AD) progression, but characterizing them and their relationships to pathology remains challenging. Here we introduce CODEX-CNS—a multiplexed protein imaging technology with a custom data analysis pipeline for use in human brain samples. We profiled 704,706 cells in samples from the frontal cortex of 8 people with AD and 8 healthy controls and mapped features including blood–brain barrier, meningeal components and cell–cell interactions within the same tissue sections. Amongst the myeloid cell populations we identified, we found a border-associated macrophage-like microglial subset associated with aging. Further classifying myeloid cell subsets based on their spatial neighborhood, we identified a border-associated macrophage-like microglial subpopulation that was associated significantly with dense amyloid-β plaques, which we termed human plaque-associated microglia. This work offers insights into myeloid cell heterogeneity in AD and provides a new spatial approach to characterizing brain cells at the single-cell protein level. Myeloid cells show marked heterogeneity in Alzheimer’s disease. This study introduces CODEX-CNS, a single-cell spatial proteomics pipeline, and identifies a human microglial subpopulation enriched in Alzheimer’s disease brains that associates with dense amyloid-β plaques.

Authors

Institutions

Publication Details

Journal
Nature Neuroscience
Published
2026-05-18
DOI
https://doi.org/10.1038/s41593-026-02267-3
Primary Topic
Neuroinflammation and Neurodegeneration Mechanisms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Peter Wieghofer, Aditya Pratapa, Heidrun Kuhrt, Cavanagh Gohlich et al.
Nature Neuroscience
Neuroinflammation and Neurodegeneration Mechanisms
article

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

Peter Wieghofer, Aditya Pratapa, Heidrun Kuhrt, Cavanagh Gohlich, Yaser Peymanfar, Aude Chiot, Bahareh Ajami, Nadezhda Nikulina, Dennis-Dominik Rosmus, Dillon Brownell, Mert Meral, Alyssa Whitley, Randall Woltjer, Ellen Lara Bouchard, Alina Bogachuk, Yue Hou, Paula Sanchez-Molina, Fabian Svara, Oliver Braubach
article en

Abstract

Disease-associated microglial states are thought to contribute to Alzheimer’s disease (AD) progression, but characterizing them and their relationships to pathology remains challenging. Here we introduce CODEX-CNS—a multiplexed protein imaging technology with a custom data analysis pipeline for use in human brain samples. We profiled 704,706 cells in samples from the frontal cortex of 8 people with AD and 8 healthy controls and mapped features including blood–brain barrier, meningeal components and cell–cell interactions within the same tissue sections. Amongst the myeloid cell populations we identified, we found a border-associated macrophage-like microglial subset associated with aging. Further classifying myeloid cell subsets based on their spatial neighborhood, we identified a border-associated macrophage-like microglial subpopulation that was associated significantly with dense amyloid-β plaques, which we termed human plaque-associated microglia. This work offers insights into myeloid cell heterogeneity in AD and provides a new spatial approach to characterizing brain cells at the single-cell protein level. Myeloid cells show marked heterogeneity in Alzheimer’s disease. This study introduces CODEX-CNS, a single-cell spatial proteomics pipeline, and identifies a human microglial subpopulation enriched in Alzheimer’s disease brains that associates with dense amyloid-β plaques.

Nature Neuroscience
Cedars-Sinai Medical Center (US), Oregon Health & Science University (US), University of Augsburg (DE), University Hospital Augsburg (DE), MSD (Switzerland) (CH), Regenerative Medicine Institute (MX), Akoya Biosciences (United States) (US), Leipzig University (DE)
Openalex Percentile: Top 6%
Neuroinflammation and Neurodegeneration Mechanisms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.