Combined Analysis of Single Cell and Spatial Transcriptome Reveals Regulation of Anti-human TREM2 Agonist Monoclonal Antibody on the Functional Status of Microglia and Identification of Key Subsets and Biomarkers

Lei Sun , Jingheng Lin , Chengcheng Song , Xuan Li , Zike Dong , Yining Wang , Zhiheng Lin

BIO Integration ›› 2026, Vol. 7 ›› Issue (1) : 10

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BIO Integration ›› 2026, Vol. 7 ›› Issue (1) :10 DOI: 10.15212/bioi-2025-0179
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Combined Analysis of Single Cell and Spatial Transcriptome Reveals Regulation of Anti-human TREM2 Agonist Monoclonal Antibody on the Functional Status of Microglia and Identification of Key Subsets and Biomarkers
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Abstract

Background: Alzheimer’s disease (AD) is a neurodegenerative disorder and the leading cause of dementia worldwide. Microglia, as central nervous system (CNS) resident macrophages, are key to AD pathology. Indeed, microglia aggregation around amyloid-β (Aβ) deposits is an AD hallmark. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates microglial function. TREM2 boosts microglial responses to AD pathologic damage, drives homeostatic activation, and modulates protective pathways. Anti-human TREM2 agonist monoclonal antibody (hT2AB) serves as an alternative TREM2 ligand and has therapeutic potential in TREM2-mutant mouse models. The current study combined single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to clarify hT2AB molecular and cellular mechanisms in improving AD and analyze microglial dynamics in hT2AB-treated groups during AD progression. Key functional subpopulations and core biomarkers were identified through pseudo-time analysis, cell communication analysis, and transcription factors (TFs) with a focus on the differentiation process of microglia towards a therapeutic phenotype, providing a theoretical basis and potential targets for optimizing AD treatment.

Methods: scRNA-seq, spatial transcriptomics, and deconvolution analysis depicted microglia in AD. Differentially expressed genes underwent enrichment analyses. Pseudotemporal analysis demonstrated microglial dynamic differentiation paths during AD progression and post-hT2AB treatment. The CellChat package constructed the cell communication network. Finally, pySCENIC analysis identified key TFs in key subpopulations.

Results: Seven functionally heterogeneous microglial subpopulations were identified with the C2 subpopulation highly expressed in the hT2AB group subpopulation. The proposed temporal sequence analysis revealed two distinct microglial cell differentiation trajectories, both originating from the C6 and C7 subpopulations and extending in different directions starting from the C2 subpopulation. Lineage1-related subpopulations (C7-C6-C4-C2-C1-C5) when combined with pathway activity scoring were confirmed to align with microglial transformation toward protective phenotypes. This study also identified core biomarkers that were highly expressed in the C2 subpopulation (the critical turning subpopulation of two trajectories). In addition, this study combined the spatial transcriptome data of AD mouse brain tissue sections, providing direct evidence for the spatial distribution of key cell subpopulations and pathways.

Conclusion: This study identified the C2 microglial subpopulation as the key effector regulated by hT2AB in AD pathology. hT2AB was confirmed to guide microglia toward protective differentiation, providing cell-level direct evidence for the therapeutic effect. The results deepen our understanding of AD brain microglial heterogeneity and the hT2AB mechanism of action, offering reliable evidence for developing new AD biomarkers and optimizing TREM2-targeted therapies, and is expected to improve AD clinical outcomes.

Keywords

Alzheimer’s disease / anti-human TREM2 agonist monoclonal antibody / scRNA-seq / spatial transcriptomics

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Lei Sun, Jingheng Lin, Chengcheng Song, Xuan Li, Zike Dong, Yining Wang, Zhiheng Lin. Combined Analysis of Single Cell and Spatial Transcriptome Reveals Regulation of Anti-human TREM2 Agonist Monoclonal Antibody on the Functional Status of Microglia and Identification of Key Subsets and Biomarkers. BIO Integration, 2026, 7 (1) : 10 DOI:10.15212/bioi-2025-0179

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