Scientific Reports (Feb 2024)

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

  • Markus Hoffmann,
  • Lina-Liv Willruth,
  • Alexander Dietrich,
  • Hye Kyung Lee,
  • Ludwig Knabl,
  • Nico Trummer,
  • Jan Baumbach,
  • Priscilla A. Furth,
  • Lothar Hennighausen,
  • Markus List

DOI
https://doi.org/10.1038/s41598-024-53117-w
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 11

Abstract

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Abstract Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers insights into a patient’s immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 196 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that—combined with sequence alignments and BLASTp—they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.