Aging‐related cell type‐specific pathophysiologic immune responses that exacerbate disease severity in aged COVID‐19 patients

  1. Yuan Hou
  2. Yadi Zhou
  3. Lara Jehi
  4. Yuan Luo
  5. Michaela U. Gack
  6. Timothy A. Chan
  7. Haiyuan Yu
  8. Charis Eng
  9. Andrew A. Pieper
  10. Feixiong Cheng

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Abstract

Coronavirus disease 2019 (COVID‐19) is especially severe in aged patients, defined as 65 years or older, for reasons that are currently unknown. To investigate the underlying basis for this vulnerability, we performed multimodal data analyses on immunity, inflammation, and COVID‐19 incidence and severity as a function of age. Our analysis leveraged age‐specific COVID‐19 mortality and laboratory testing from a large COVID‐19 registry, along with epidemiological data of ~3.4 million individuals, large‐scale deep immune cell profiling data, and single‐cell RNA‐sequencing data from aged COVID‐19 patients across diverse populations. We found that decreased lymphocyte count and elevated inflammatory markers (C‐reactive protein, D‐dimer, and neutrophil–lymphocyte ratio) are significantly associated with age‐specific COVID‐19 severities. We identified the reduced abundance of naïve CD8 T cells with decreased expression of antiviral defense genes (i.e., IFITM3 and TRIM22 ) in aged severe COVID‐19 patients. Older individuals with severe COVID‐19 displayed type I and II interferon deficiencies, which is correlated with SARS‐CoV‐2 viral load. Elevated expression of SARS‐CoV‐2 entry factors and reduced expression of antiviral defense genes ( LY6E and IFNAR1 ) in the secretory cells are associated with critical COVID‐19 in aged individuals. Mechanistically, we identified strong TGF‐beta‐mediated immune–epithelial cell interactions (i.e., secretory‐non‐resident macrophages) in aged individuals with critical COVID‐19. Taken together, our findings point to immuno‐inflammatory factors that could be targeted therapeutically to reduce morbidity and mortality in aged COVID‐19 patients.

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  1. Version published to 10.1111/acel.13544
  2. ScreenIT

    SciScore for 10.1101/2021.09.13.21263504: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: COVID-19 registry: We used institutional review board–approved COVID-19 registry data, including 45,077 individuals (12,651 were aged patients and 32,426 were younger patients, Supplementary Table 3) tested during March to December, 2020 from the Cleveland Clinic Health System in Ohio and Florida.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were extracted from electronic health records (EPIC Systems), and patient data was managed using REDCap electronic data capture tools.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Cumulative hazard analysis was performed using the Survival and Survminer packages in R 3.6.0 (https://www.r-project.org).
    https://www.r-project.org
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Bulk RNA-sequencing dataset in nasal tissue31: The dataset was publically available from NCBI GEO database (GSE152075).
    NCBI GEO
    suggested: None
    Single-cell sequencing data analyses: All single-cell data analyses and visualizations were performed with the R package Seurat v3.1.4 40.
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    The analysis was performed by CellPhoneDB40 v2.1.4 (https://github.com/Teichlab/cellphonedb) based on the python 3.7 platform.
    CellPhoneDB40
    suggested: None
    We selected 22 immune-related pathways and 1241 genes from KEGG belonging to the immune system subtype.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    All analyses were performed with the prerank function in GSEApy package (https://gseapy.readthedocs.io/en/master/index.html) on Python 3.7 platform.
    GSEApy
    suggested: None
    Python
    suggested: (IPython, RRID:SCR_001658)
    All statistical analysis was performed by SciPy Statistics (https://docs.scipy.org/doc/scipy/reference/stats.html#module-scipy.stats).
    SciPy
    suggested: (SciPy, RRID:SCR_008058)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Lastly, we acknowledge the potential limitations of our study. Although we inspected omics data from multiple tissues, including PBMCs, plasma, and nasal tissues, additional analysis of other COVID-19 and aging relevant tissues, such as lung and brain, should be investigated in the future. In addition, our COVID-19 database and omics data were generated from acute COVID-19 patients, and identification of the underlying genetic and molecular basis of aging differences for long-haul COVID-19 patients will be an important area of future investigation60. Finally, investigation of COVID-19 vaccine responses between aged and young patients are also warranted in the future.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04320615CompletedA Study to Evaluate the Safety and Efficacy of Tocilizumab i…
    NCT04469621CompletedA Phase 1b Trial to Evaluate Safety and Effect of SAR443122 …

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2021.09.13.21263504v1 on medRxiv