Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score

Sen, Sanjana; Sanders, Emily; Gabriel, Kristin; Miller, Bill R.; Isoda, Hariny M.; Salcedo, Gabriela S.; Garrido, Jason E; Dyer, Rebekah P.; Nakajima, Rie; Jain, Aarti; Caldaruse, Ana Maria; Santos, Alicia M; Bhuvan, Keertna; Tifrea, Delia F.; Ricks-Oddie, Joni; Felgner, Philip L.; Edwards, Robert A.; Majumdar, Sudipta; Weiss, Gregory A.

doi:10.1128/msphere.00203-21

Cited by 24 publications

(27 citation statements)

References 56 publications

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“…Several studies have reported that biased humoral N-reactive response could lead to poor prognosis [44,45]. In this study, we described a contrasting pattern between the serum and the MBC compartment reactive to SARS-CoV-2 N. IgM response to N exhibited lower magnitude, consistent with what have been previously reported [38], raising questions on the characteristics of N-reactive B cells that respond to infection.…”

Section: Discussionsupporting

confidence: 86%

Formation and Expansion of Memory B Cells against Coronavirus in Acutely Infected COVID-19 Individuals

Embong

Nguyen-Contant²,

Wang

et al. 2022

Pathogens

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Infection with the β-coronavirus SARS-CoV-2 typically generates strong virus-specific antibody production. Antibody responses against novel features of SARS-CoV-2 proteins require naïve B cell activation, but there is a growing appreciation that conserved regions are recognized by pre-existing memory B cells (MBCs) generated by endemic coronaviruses. The current study investigated the role of pre-existing cross-reactive coronavirus memory in the antibody response to the viral spike (S) and nucleocapsid (N) proteins following SARS-CoV-2 infection. The breadth of reactivity of circulating antibodies, plasmablasts, and MBCs was analyzed. Acutely infected subjects generated strong IgG responses to the S protein, including the novel receptor binding domain, the conserved S2 region, and to the N protein. The response included reactivity to the S of endemic β-coronaviruses and, interestingly, to the N of an endemic α-coronavirus. Both mild and severe infection expanded IgG MBC populations reactive to the S of SARS-CoV-2 and endemic β-coronaviruses. Avidity of S-reactive IgG antibodies and MBCs increased after infection. Overall, findings indicate that the response to the S and N of SARS-CoV-2 involves pre-existing MBC activation and adaptation to novel features of the proteins, along with the potential of imprinting to shape the response to SARS-CoV-2 infection.

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Section: Discussionsupporting

confidence: 86%

Formation and Expansion of Memory B Cells against Coronavirus in Acutely Infected COVID-19 Individuals

Embong

Nguyen-Contant²,

Wang

et al. 2022

Pathogens

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“…We wondered whether low anti-RBD reactivity levels observed in this cohort is because the cases were mild. Indeed, we have reported that that elevated levels of antibody against a SARS-CoV-2 NP epitope predicts disease severity in COVID-19 patients 19 . Consequently, we compared the antibody levels among 93 hospitalized individuals who were either in intensive care or not and the results are shown in Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Distinct SARS-CoV-2 antibody reactivity patterns elicited by natural infection and mRNA vaccination

et al. 2021

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We analyzed data from two ongoing COVID-19 longitudinal serological surveys in Orange County, CA., between April 2020 and March 2021. A total of 8476 finger stick blood specimens were collected before and after a vaccination campaign. IgG levels were determined using a multiplex antigen microarray containing antigens from SARS-CoV-2, SARS, MERS, Common CoV, and Influenza. Twenty-six percent of specimens from unvaccinated Orange County residents in December 2020 were SARS-CoV-2 seropositive; out of 852 seropositive individuals 77 had symptoms and 9 sought medical care. The antibody response was predominantly against nucleocapsid (NP), full length, and S2 domain of spike. Anti-receptor binding domain (RBD) reactivity was low and not cross-reactive against SARS S1 or SARS RBD. A vaccination campaign at the University of California Irvine Medical Center (UCIMC) started on December, 2020 and 6724 healthcare workers were vaccinated within 3 weeks. Seroprevalence increased from 13% pre-vaccination to 79% post-vaccination in January, 93% in February, and 99% in March. mRNA vaccination induced higher antibody levels than natural exposure, especially against the RBD domain and cross-reactivity against SARS RBD and S1 was observed. Nucleocapsid protein antibodies can be used to distinguish vaccinees to classify pre-exposure to SARS-CoV-2 Previously infected individuals developed higher antibody titers to the vaccine than non pre-exposed individuals. Hospitalized patients in intensive care with severe disease reach significantly higher antibody levels than mild cases, but lower antibody levels compared to the vaccine. These results indicate that mRNA vaccination rapidly induces a much stronger and broader antibody response than SARS-CoV-2 infection.

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“…These findings may also imply convalescent plasma collections (e.g., CCP units with greater NL63 antibody responses and lower HKU1 antibodies) had higher neutralizing antibodies to the SARS-CoV-2 receptor-binding domain (RBD) [38]. Another study found better outcomes in recipients of CCP units with higher anti-NL63 or anti-OC43 antibodies [39]; Influenza virus A(H 3 N 2 ): Antibody binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, is associated with greater COVID-19 disease severity [40]. Bioinformatics analysis identified the neuraminidase protein (not present in the influenza vaccine) of influenza virus A(H3N2) as responsible, a strain that circulated widely in 2014 [41]; Acute malaria infection: Plasmodium infection induces cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 spike protein [42]; Natural ABO isoagglutinins: The ABO blood group affects COVID-19 incidence and severity, as well as the type and duration of the cellular immune response [43].…”

Section: • Pathogensmentioning

confidence: 99%

COVID-19 Convalescent Plasma Is More than Neutralizing Antibodies: A Narrative Review of Potential Beneficial and Detrimental Co-Factors

Focosi¹,

Franchini

Pirofski

et al. 2021

Viruses

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COVID-19 convalescent plasma (CCP) is currently under investigation for both treatment and post-exposure prophylaxis. The active component of CCP mediating improved outcome is commonly reported as specific antibodies, particularly neutralizing antibodies, with clinical efficacy characterized according to the level or antibody affinity. In this review, we highlight the potential role of additional factors in CCP that can be either beneficial (e.g., AT-III, alpha-1 AT, ACE2+ extracellular vesicles) or detrimental (e.g., anti-ADAMTS13, anti-MDA5 or anti-interferon autoantibodies, pro-coagulant extracellular vesicles). Variations in these factors in CCP may contribute to varied outcomes in patients with COVID-19 and undergoing CCP therapy. We advise careful, retrospective investigation of such co-factors in randomized clinical trials that use fresh frozen plasma in control arms. Nevertheless, it might be difficult to establish a causal link between these components and outcome, given that CCP is generally safe and neutralizing antibody effects may predominate.

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Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score

Abstract: The COVID-19 pandemic has resulted in over two million deaths worldwide. Despite efforts to fight the virus, the disease continues to overwhelm hospitals with severely ill patients.

Cited by 24 publications

References 56 publications

Formation and Expansion of Memory B Cells against Coronavirus in Acutely Infected COVID-19 Individuals

Formation and Expansion of Memory B Cells against Coronavirus in Acutely Infected COVID-19 Individuals

Distinct SARS-CoV-2 antibody reactivity patterns elicited by natural infection and mRNA vaccination

COVID-19 Convalescent Plasma Is More than Neutralizing Antibodies: A Narrative Review of Potential Beneficial and Detrimental Co-Factors

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