Frontiers in Immunology (Apr 2023)

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity

  • Modi Safra,
  • Modi Safra,
  • Zvi Tamari,
  • Zvi Tamari,
  • Pazit Polak,
  • Pazit Polak,
  • Shachaf Shiber,
  • Shachaf Shiber,
  • Moshe Matan,
  • Hani Karameh,
  • Yigal Helviz,
  • Adva Levy-Barda,
  • Vered Yahalom,
  • Avi Peretz,
  • Avi Peretz,
  • Eli Ben-Chetrit,
  • Baruch Brenner,
  • Baruch Brenner,
  • Tamir Tuller,
  • Meital Gal-Tanamy,
  • Gur Yaari,
  • Gur Yaari

DOI
https://doi.org/10.3389/fimmu.2023.1031914
Journal volume & issue
Vol. 14

Abstract

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IntroductionThe success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance.MethodsWe report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls.ResultsIn contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients.DiscussionThese features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.

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