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

被引:8
作者
Safra, Modi [1 ,2 ]
Tamari, Zvi [1 ,2 ]
Polak, Pazit [1 ,2 ]
Shiber, Shachaf [3 ,4 ]
Matan, Moshe [5 ]
Karameh, Hani [6 ]
Helviz, Yigal [7 ]
Levy-Barda, Adva [8 ]
Yahalom, Vered [9 ]
Peretz, Avi [5 ,10 ]
Ben-Chetrit, Eli [11 ]
Brenner, Baruch [4 ,12 ]
Tuller, Tamir [13 ]
Gal-Tanamy, Meital [10 ]
Yaari, Gur [1 ,2 ]
机构
[1] Bar Ilan Univ, Fac Engn, Bioengn, Ramat Gan, Israel
[2] Bar Ilan Univ, Bar Ilan Inst Nanotechnol & Adv Mat, Ramat Gan, Israel
[3] Rabin Med Ctr, Emergency Dept, Belinson Campus, Petah Tiqwa, Israel
[4] Tel Aviv Univ, Sackler Fac Med, Tel Aviv, Israel
[5] Baruch Padeh Med Ctr, Clin Microbiol Lab, Poriya, Israel
[6] Hebrew Univ Jerusalem, Sch Med, Jesselson Integrated Heart Ctr, Shaare Zedek Med Ctr, Jerusalem, Israel
[7] Hebrew Univ Jerusalem, Sch Med, Shaare Zedek Med Ctr, Intens Care Unit, Jerusalem, Israel
[8] Rabin Med Ctr, Dept Pathol, Biobank, Belinson Campus, Petah Tiqwa, Israel
[9] Rabin Med Ctr, Blood Serv & Apheresis Inst, Petah Tiqwa, Israel
[10] Bar Ilan Univ, Azrieli Fac Med, Safed, Israel
[11] Hebrew Univ Jerusalem, Sch Med, Shaare Zedek Med Ctr, Infect Dis Unit, Jerusalem, Israel
[12] Rabin Med Ctr, Inst Oncol, Belinson Campus, Petah Tiqwa, Israel
[13] Tel Aviv Univ, Sagol Sch Neurosci, Dept Biomed Engn, Tel Aviv, Israel
来源
FRONTIERS IN IMMUNOLOGY | 2023年 / 14卷
关键词
machine learning; BCR; AIRR-seq; COVID-19; somatic hypermutation; B cell; RECEPTOR REPERTOIRES; ANTIBODY-RESPONSES; CELL; SIGNATURES; TOOLKIT;
D O I
10.3389/fimmu.2023.1031914
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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.
引用
收藏
页数:12
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