Clonal expansion of cytotoxic CD8⁺ T cells in lecanemab-associated ARIA

Abstract

Amyloid-related imaging abnormalities (ARIA) are the principal safety concern limiting anti-amyloid therapies for Alzheimer's disease, yet their biology remains unclear. Here we show, through multi-omic profiling of peripheral blood from three ARIA+ patients and matched controls, that ARIA is associated with coordinated reprogramming of CD8 + T cells. CD8+ effector memory (TEM) and terminally differentiated (TEMRA) subsets were expanded, clonally enriched, and transcriptionally primed for cytotoxicity and vascular trafficking. Transcription factor inference and metabolomics converged on glycolytic reprogramming favoring short-lived effector function. Ligand-receptor modeling revealed enhanced monocyte-to-T cell signaling through antigen presentation, adhesion, and chemokine axes, while integration with a cerebrovascular atlas confirmed that ARIA-associated TEMRAs are transcriptionally "addressed" for vascular engagement. Together, these findings identify a peripheral immune signature linking metabolic reprogramming, clonal CD8+ expansion, and altered intercellular communication to ARIA, with implications for biomarker development and risk mitigation pending validation in larger cohorts.

Fig. 1. ARIA is associated with expansion of peripheral CD8⁺ TEMRA cells.

a Representative MRIs show edema/effusions on T2-FLAIR/TIRM (blue triangles) and microhemorrhages/siderosis on SWI (orange triangles) from three selected ARIA cases (ARIA-E, ARIA-H, and ARIA-E/H). Cases were matched to three controls by age, sex, APOE genotype, and infusion number. “Baseline” indicates pre-treatment MRI; “At diagnosis” indicates surveillance MRI when ARIA was first detected. Clinical characteristics provided in Supplemental Table 1. b Study design and multi-omic profiling workflow (Created in BioRender. Morganti, J. (2026) https://BioRender.com/9hv27wi). PBMCs collected pre-infusion underwent 5′ scRNA-seq with CITE-seq and V(D)J, plus targeted metabolomics. c, d Multimodal (RNA + Antibody-Derived Tags (ADT)) UMAP of ~117,000 cells resolves major PBMC lineages (T, B, NK, monocytes, DCs). e Proportions of major lymphocyte classes show increased CD8⁺ and decreased CD4⁺ frequencies in ARIA+ subjects. f Routine clinical counts reveal similar CBC differentials across groups, with a trend toward higher absolute lymphocyte counts in ARIA+ cases. g, h Re-clustering of 65,481 T cells identifies canonical CD4⁺ (naïve, central/effector memory, Tregs) and CD8⁺ (naïve, central/effector memory, TEMRA, intermediate cytotoxic) states using concordant RNA and surface markers. i ARIA+ patients exhibit contraction of naïve CD8⁺ cells and enrichment of effector memory/TEMRA subsets. j Quantification of CD8 + TEM and TEMRA absolute cell counts from scRNAseq data. Individual samples show elevations in TEM (top) and TEMRA (bottom) numbers in ARIA+ patients (*p = 0.0234, Student’s two-tailed t-Test, squares = male, circles = female). Density plots k highlight TEMRA accumulation in ARIA+ only. l Differential expression (Fisher meta-analysis) in TEMRA cells from ARIA+ versus ARIA- reveals increased cytotoxic/Fc-receptor signaling, chemokine/migratory genes, MHC-II, inhibitory/stress markers, and metabolic regulators consistent with a glycolytic, glutamine-fueled effector state. Source data are provided as a Source Data file.

Fig. 2. ARIA is associated with immunometabolic reprogramming, increased cytotoxicity, and clonal remodeling of CD8⁺ T cells.

a Transcription factor activity inferred with decoupleR shows reduced VHL activity (red boxes) in ARIA + TEM/TEMRA cells. Activity scores compared between ARIA+ and ARIA− within each cell type; n = 3 biologically independent patients per group; differential activity assessed by two-tailed t-test with Benjamini-Hochberg correction; significance defined as adjusted p < 0.05 and |log₂FC | > 0.5. b Targeted PBMC metabolomics workflow (Created in BioRender. Johnson, L. (2026) https://BioRender.com/09ib3if). c, d Principal component analysis of metabolomic profiles from n = 3 ARIA+ and n = 3 ARIA− biologically independent patient samples (one measurement per patient), Volcano plot showing differential metabolite abundance; two-tailed t-test with Benjamini-Hochberg correction; metabolites with p < 0.05 and |log₂FC | > 0.5 labeled. Heatmap highlights individual metabolites across samples showing increased lactate, pyruvate, and itaconate with decreased citrate in ARIA + . e Pathway impact analysis using MetaboAnalyst; enrichment assessed by hypergeometric test with Benjamini-Hochberg correction; pathway impact calculated by topological analysis, hypergeometric test (one-tailed, testing for over-representation) with Benjamini-Hochberg correction for multiple comparisons. f Cytotoxicity module scores across CD8+ subsets. Box plots show median (center line), interquartile range (box bounds), and whiskers extending to 1.5x IQR. Cell numbers per subset: Naive CD8 (n = 3,085 cells), TRM CD8 (n = 892 cells), TEM CD8 (n = 4,967 cells), TEMRA CD8 (n = 9,262 cells) across 6 biologically independent patients; Wilcoxon rank-sum test comparing adjacent differentiation states. g Pseudotime trajectory from naïve CD8⁺ to TEMRA inferred using Slingshot; 200 variable genes shown. h Clonal expansion categories by V(D)J sequencing. Left: proportion of clones by expansion category for each patient (n = 3 ARIA + , n = 3 ARIA − ; biologically independent). Right: subset-specific clonality compared between groups. i Differential expression by clone size; Wilcoxon rank-sum test comparing clonal categories; genes with adjusted p < 0.05 and log₂FC > 1 shown; Gene Ontology enrichment by two-tailed hypergeometric test with Benjamini-Hochberg correction. Source data are provided as a Source Data file.

Fig. 3. ARIA reshapes monocyte–T-cell communication and primes effector CD8⁺ subsets for cerebrovascular engagement.

a Gene set enrichment analysis comparing ARIA+ versus ARIA− across CD8 subsets; n = 3 biologically independent patients per group; enrichment assessed by two-tailed permutation test (1000 permutations) with Benjamini-Hochberg correction; gene sets with adjusted p < 0.05 shown. b Monocyte transcriptional programs comparing CD14⁺ and CD16⁺ subsets between ARIA+ and ARIA− samples. c Cell-cell communication strength (CellChat) showing incoming signals to CD8 subsets from monocytes; communication probabilities calculated per condition (ARIA+ or ARIA − ) with n = 3 biologically independent patients per group (Created in BioRender. Morganti, J. (2026) https://BioRender.com/oqzqxjb). d Ligand-receptor interaction dot plot; dot size indicates communication probability; color indicates pathway. e Cross-modal integration with brain endothelial cells from van Olst et al.; peripheral CD8 subsets from this study (n = 3 ARIA+ patients) projected onto endothelial interaction framework (Created in BioRender. Morganti, J. (2026) https://BioRender.com/oqzqxjb). f Chord diagrams showing inferred endothelial interactions; line thickness proportional to interaction strength. g Proportion of predicted cerebrovascular interactions by CD8 subset.