Omics · study · 2026
Single-cell omics analysis of age-related immune signatures induced by Omicron sublineage breakthrough infection
Listed in NCBI GEO
Although COVID-19 is no longer a panic-inducing virus, immunocompromised populations, such as the elderly and those with underlying health conditions, remain at higher risk of severe illness.
Description
However, current data on population-level immunosenescence and its immune characteristics are scarce, leaving the impact of aging on antiviral immune responses largely unexplained. This study investigates the influence of age on immune responses by analyzing dynamic changes in blood indices, cytokine-related genes, T-cell receptors (TCRs), and B-cell receptors (BCRs) among COVID-19 patients of different age groups.
The findings reveal that elderly patients exhibit significantly elevated levels of routine clinical indicators, such as white blood cells (WBC) and creatinine, along with marked increases in cytokines like interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) post-infection. Gene expression analysis shows that elderly patients have a greater number of differentially expressed genes (DEGs), particularly those associated with inflammatory and antiviral response pathways, with potential therapeutic targets such as CXCR4, IL2RG, and IFITM1 identified.
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Furthermore, TCR analysis indicates a decline in TCR diversity and a reduction in virus-specific TCRs among elderly patients, suggesting weakened adaptive immune system capabilities. Similarly, BCR analysis demonstrates decreased antibody secretion and restricted B-cell responses in the elderly, indicating impaired antiviral capacity. These findings underscore that age is a critical factor influencing antiviral immune responses, with elderly patients exhibiting more vulnerable immune functions.
This study provides valuable insights for the development of personalized treatment and vaccination strategies tailored to the elderly.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE299nnn/GSE299953 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299953 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1277703 ncbi.nlm.nih.gov/bioproject/PRJNA1277703 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Cancer 65%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE299953 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |