GEO series

Immunological Differences in Atopic Dermatitis Across Age Groups: Insights from Single-Cell Multi-Omics

GSE332623 Homo sapiens Expression profiling by high throughput sequencing; Other 54 samples Submitted 2026/08/07 Platform GPL24676

Summary

Background: Atopic dermatitis (AD) occurs across all ages but presents distinct clinical and immunologic features between children, adults, and older adults. The molecular programs underlying these age-specific immune differences remain poorly understood. Methods: We performed single-cell multi-omics profiling of peripheral blood mononuclear cells (PBMCs) from 29 AD patients and 29 matched healthy controls (HC), spanning pediatric (0–17 years), adult (18–59 years), and geriatric (≥60 years) groups. Using Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), we simultaneously quantified transcriptomic (RNA) and surface proteomic (ADT) profiles across ~280,000 immune cells. Integrated analyses identified 30 immune subsets for cell-type proportion and differential expression analyses. Machine-learning classifiers were trained on significant gene and protein features to distinguish AD subgroups by age. Results: Compared with HC, AD blood showed enrichment of CD14+ monocytes, plasmacytoid dendritic cells, and CD4+ proliferating T cells, and differential gene expression analysis of AD vs HC revealed downstream Th2-associated signatures shared across all age groups. Within AD, pediatric patients had increased γδ T cells, naïve CD4+, and naïve CD8+ T cells, while geriatric patients exhibited more CD4+ cytotoxic and CD8+ central memory T cells, indicating a shift from naive to effector predominance with aging. Transcriptomic and proteomic analyses revealed distinct programs: pediatric AD was enriched for IL-10 and cytokine–cytokine receptor signaling; adult AD demonstrated activation of metabolic and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)/Th1/Th17 pathways; and geriatric AD exhibited reduced adaptive immune activity but increased innate signaling. Machine-learning models based on differentially expressed genes and proteins accurately classified AD age groups (transcript-based F1 = 0.70, AUC = 0.79), identifying stable markers such as *IRF2*, *PDK4*, *ZFP90*, CD21, CD94, and CD122. Conclusions: Single-cell multi-omics profiling revealed immune differences across the AD lifespan, transitioning from developmental tolerance in children to inflammatory and metabolic activation in adults to enhanced innate signaling in geriatric individuals. These findings highlight molecular signatures that could support age-group subtyping and therapeutic strategies for AD across the lifespan.

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Direct links to NCBI, no account and no request form: the whole study as GSE332623_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 54 samples. Raw sequencing reads are also available from ENA.

Whole study · RAW.tar ↓ Series matrix ↓ All supplementary files ↗ Raw reads on ENA ↗

Also filed as BioProject PRJNA1453002 and SRA study SRP698538. Searching any of these in the dataset finder brings you back here.

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Study design

11 conditions, mostly with about 4 replicates each

TotalseqB_NEA1_cDNA ×4 TotalseqB_NEA1_ADT ×4 TotalseqB_NEA3_cDNA ×4 TotalseqB_NEA3_ADT ×4 TotalseqB_NEA4_cDNA ×4 TotalseqB_NEA4_ADT ×4 TotalseqB_NEA5_cDNA ×4 TotalseqB_NEA5_ADT ×4 +3 more

Supports a between-group comparison across 40 samples.

11 replicated groups read from the first 40 of 54 sample titles; they account for 40 of them. Check it against the sample list below before relying on it.

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