Evidence map›Paper›PMID 33950324›Full record

ArticleJournal of clinical immunology2021

Profiling of T Cell Repertoire in SARS-CoV-2-Infected COVID-19 Patients Between Mild Disease and Pneumonia.

Che-Mai Chang, Po-Hao Feng, Tsung-Hsun Wu, Houda Alachkar, Kang-Yun Lee, Wei-Chiao Chang

Open access · bronzeAbstract read
In one paragraph

Article in Journal of clinical immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
3.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. AnalyzAIRR: A user-friendly guided workflow for AIRR data analysis.Immunoinformatics (Amsterdam, Netherlands) · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Low-frequency CD8NPJ vaccines · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Che-Mai ChangPh.D. Program in Medical Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
Po-Hao FengDivision of Pulmonary Medicine, Department of Internal Medicine, Taipei Medical University-Shuang Ho Hospital, No. 291, Zhongzheng Rd., Zhonghe Dist., New Taipei City, 235, Taiwan.
Tsung-Hsun WuMaster Program in Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Houda AlachkarDepartment of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA.
Kang-Yun LeeDivision of Pulmonary Medicine, Department of Internal Medicine, Taipei Medical University-Shuang Ho Hospital, No. 291, Zhongzheng Rd., Zhonghe Dist., New Taipei City, 235, Taiwan. leekangyun@tmu.edu.tw.
Wei-Chiao ChangMaster Program in Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan. wcc@tmu.edu.tw.
Taipei Medical University · TWUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a public health emergency. The most common symptoms of COVID-19 are fever, cough, and fatigue. While most patients with COVID-19 present with mild illness, some patients develop pneumonia, an important risk factor for mortality, at early stage of viral infection, putting these patients at increased risk of death. So far, little has been known about differences in the T cell repertoires between COVID-19 patients with and without pneumonia during SARS-CoV-2 infection. Herein, we aimed to investigate T cell receptor (TCR) repertoire profiles and patient-specific SARS-CoV-2-associated TCR clusters between COVID-19 patients with mild disease (no sign of pneumonia) and pneumonia. The TCR sequencing was conducted to characterize the peripheral TCR repertoire profile and diversity. The TCR clustering and CDR3 annotation were exploited to further discover groups of patient-specific TCR clonotypes with potential SARS-CoV-2 antigen specificities. Our study indicated a slight decrease in the TCR repertoire diversity and a skewed CDR3 length usage in patients with pneumonia compared to those with mild disease. The SARS-CoV-2-associated TCR clusters enriched in patients with mild disease exhibited significantly higher TCR generation probabilities and most of which were highly shared among patients, compared with those from pneumonia patients. Importantly, using similarity network-based clustering followed by the sequence conservation analysis, we found different patterns of CDR3 sequence motifs between mild disease- and pneumonia-specific SARS-CoV-2-associated public TCR clusters. Our results showed that characteristics of overall TCR repertoire and SARS-CoV-2-associated TCR clusters/clonotypes were divergent between COVID-19 patients with mild disease and patients with pneumonia. These findings provide important insights into the correlation between the TCR repertoire and disease severity in COVID-19 patients.

Indexed as

AdultAgedCOVID-19Disease ProgressionFemaleHumansMaleMiddle AgedPandemicsPneumoniaReceptors, Antigen, T-CellSARS-CoV-2Sequence Analysis, DNASeverity of Illness IndexT-LymphocytesReceptors, Antigen, T-CellCOVID-19SARS-CoV-2T cell receptorTCR repertoireTCR sequencing

Identifiers

PMID33950324
PMCPMC8096628
OpenAlexW3158986585

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.