AgingImmunologyPeer-reviewed journal article
Utilizing blood single-cell transcriptomics to integrate intrinsic and systemic immune aging
Alan TomusiakiD, Sierra LoreiD, Morten Scheibye‐KnudseniD, Eric VerdiniD
Abstract
Biomarkers of aging provide insight into the biological effects of interventions and diseases. However, most biomarkers today are based on measurements derived from bulk cell measurements, making it challenging to interpret whether an effect is due to changes in cell type composition (systemic factors) or a cell intrinsic effect. Single-cell RNA sequencing provides a unique platform to simultaneously compare aging-associated changes on both a cellular and bulk level. We first generated a single-cell combined automated human blood cell type and age predictor (clock) for six distinct human T cell subsets. We applied these tools to find acute COVID is associated with a shift in CD8+ cytotoxic cell proportions, while cell type proportions are stable in patients with HIV on long-term ART treatment (HIV+ART). Both COVID and HIV+ART were associated with an increase in naive CD8 T cell transcriptomic age. We further found our single-cell aging biomarker is linked to ribosomal gene expression and has a link to mean cellular transcript length. This study highlights the potential of single cell transcriptomic biomarkers for understanding how the human immune system is impacted by age-associated systemic changes in cell type composition and intrinsic cellular aging.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 4
- FWCI
- 5.15
- Field percentile
- top 5%
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