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Citation: Adhikari, B.; Oltz, E.M.;
Bednash, J.S.; Horowitz, J.C.; Amimo,
J.O.; Raev, S.A.; Fernández, S.;
Anghelina, M.; Liu, S.-L.; Rubinstein,
M.P.; et al. Increased COVID-19
Mortality and Deficient SARS-CoV-2
Immune Response Are Not
Associated with Higher Levels of
Endemic Coronavirus Antibodies.
Immuno 2023,3, 330–345. https://
doi.org/10.3390/immuno3030020
Academic Editor: Stefano Aquaro
Received: 27 July 2023
Revised: 10 August 2023
Accepted: 31 August 2023
Published: 4 September 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Increased COVID-19 Mortality and Deficient SARS-CoV-2
Immune Response Are Not Associated with Higher Levels of
Endemic Coronavirus Antibodies
Bindu Adhikari 1,2, Eugene M. Oltz 3, Joseph S. Bednash 4, Jeffrey C. Horowitz 4, Joshua O. Amimo 2,
Sergei A. Raev 2, Soledad Fernández 5, Mirela Anghelina 5, Shan-Lu Liu 3,6,7,8 , Mark P. Rubinstein 9,10 ,
Daniel M. Jones 11, Linda J. Saif 1,2 and Anastasia N. Vlasova 1 ,2 ,*
1Department of Veterinary Preventive Medicine, College of Veterinary Medicine, The Ohio State University,
Wooster, OH 44691, USA; adhikari.120@osu.edu (B.A.); saif.2@osu.edu (L.J.S.)
2
Center for Food Animal Health, Department of Animal Sciences, OARDC, College of Food, Agricultural and
Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA; amimo.3@osu.edu (J.O.A.);
raev.1@osu.edu (S.A.R.)
3Department of Microbial Infection and Immunity, The Ohio State University, Columbus, OH 43210, USA;
eugene.oltz@osumc.edu (E.M.O.); liu.6244@osu.edu (S.-L.L.)
4Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, The Ohio State
University, Columbus, OH 43210, USA; joseph.bednash@osumc.edu (J.S.B.);
jeffrey.horowitz@osumc.edu (J.C.H.)
5Department of Biomedical Informatics, College of Medicine and Center for Biostatistics, The Ohio State
University, Columbus, OH 43210, USA; soledad.fernandez@osumc.edu (S.F.);
mirela.anghelina@osumc.edu (M.A.)
6Center for Retrovirus Research, The Ohio State University, Columbus, OH 43210, USA
7Department of Veterinary Biosciences, The Ohio State University, Columbus, OH 43210, USA
8Viruses and Emerging Pathogens Program, Infectious Diseases Institute, The Ohio State University,
Columbus, OH 43210, USA
9Division of Medical Oncology, Department of Internal Medicine, The Ohio State University,
Columbus, OH 43210, USA; mark.rubinstein@osumc.edu
10
The Pelotonia Institute of Immuno-Oncology, The Ohio State University James Comprehensive Cancer Center,
Columbus, OH 43210, USA
11 Department of Pathology, The Ohio State University, Columbus, OH 43210, USA; daniel.jones@osumc.edu
*Correspondence: vlasova.1@osu.edu
Abstract:
The impact of pre-existing common cold coronavirus (CCCoV) antibodies (Abs) on severe
acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune responses and pathogenesis remains
poorly defined. We evaluated these associations in a cohort of hospitalized patients with COVID-19
and respiratory failure of varying severity. Patients with respiratory failure from other causes (non-
COVID-19) were evaluated as controls. We demonstrated a positive correlation between levels of
CCCoV and SARS-CoV-2 Abs using CCCoV and SARS-CoV-2 N and S protein peptide-specific ELISA.
Consistent with the above, moderately increased levels of CCCoV-specific Abs in non-COVID-19 vs.
COVID-19 patients suggest potential protective effects. Further, higher SARS-CoV-2 N protein-specific
and CCCoV Ab levels were observed among surviving vs. non-surviving COVID-19 positive patients.
However, the highest SARS-CoV-2 N and S protein-specific IgG and IgA Ab levels were noted in the
patients with the most severe clinical disease. Finally, advanced age, cancer and immunosuppression
were associated with significantly higher mortality and reduced SARS-CoV-2 and CCCoV Ab levels.
Thus, our data highlight that sufficient SARS-CoV-2 N protein-specific Ab responses improve clinical
outcomes in severely ill COVID-19 patients. We also confirmed that pre-existing CCCoV-specific Abs
do not inhibit the SARS-CoV-2 Ab response and may further reduce the prevalence and/or severity
of COVID-19.
Keywords:
SARS-CoV-2; common cold coronavirus; serological testing; immunocompromised
patients; antibodies
Immuno 2023,3, 330–345. https://doi.org/10.3390/immuno3030020 https://www.mdpi.com/journal/immuno
Immuno 2023,3331
1. Introduction
Severe acute respiratory syndrome coronavirus (SARS-CoV) 2 (SARS-CoV-2) has
infected hundreds of millions of people and claimed the lives of nearly 7 million individuals
as of July 2023. Along with four other human coronaviruses (HCoVs) [OC43, HKU1, SARS-
CoV and Middle East respiratory syndrome CoV (MERS-CoV)], SARS-CoV-2 belongs to
the Betacoronavirus genus, family Coronaviridae [
1
], while HCoVs 229E and NL63 belong
to the Alphacoronavirus genus. SARS-CoV, MERS-CoV and SARS-CoV-2 are known to
cause severe acute respiratory symptoms, while HCoVs 229E, NL63, OC43 and HKU1 are
associated with mild respiratory symptoms and are referred to as endemic or common cold
CoVs (CCCoVs) [2,3].
Studies evaluating the characteristics of SARS-CoV-2 immune response and the in-
fluence of pre-existing Abs against CCCoVs [
4
–
8
] yielded inconsistent results, providing
conflicting evidence for a protective vs. a detrimental role for CCCoV immunity in Coro-
navirus disease 2019 (COVID-19) pathogenesis and immune responses [
7
–
11
]. These
inconsistencies may be associated with multiple confounding factors, including age, sex,
exposure dose, lifestyle/occupational risks, comorbidities and CCCoV Ab characteristics
and levels. Thus, it remains unclear whether the ‘original antigenic sin’ plays a role in the
generation of an inadequate immune response to SARS-CoV-2, in which the infection is
not controlled efficiently due to diversion of the immune response associated with prior
exposures to CCCoVs and ultimately results in the development of severe COVID-19 [
12
].
Consequently, the amino acid (aa) identity shared between SARS-CoV-2 and CCCoV N
and S proteins reaches 18–29% resulting in variable levels of serological cross-reactivity
between these HCoVs, which may lead to a range of clinical and immunological outcomes.
To test whether pre-existing CCCoV immunity can alleviate or aggravate COVID-19
severity and alter SARS-CoV-2-specific Ab responses, we analyzed the association between
different Ab isotypes targeting SARS-CoV-2 and CCCoV nucleocapsid (N) and spike (S)
proteins and the prevalence, dynamics and severity of COVID-19 in a hospitalized cohort.
Our analysis was further stratified based on the patient’s age, sex, comorbidity status and
SARS-CoV-2 Ab response dynamics as well as the disease outcome.
2. Materials and Methods
2.1. Study Population
We obtained banked plasma samples from the Ohio State University Intensive Care
Unit Registry (BuckICU) collected from individuals admitted to the Ohio State University
(OSU) hospitals from May 2020 to December 2021. This biorepository collects longitudinal
biospecimens and associated clinical data from hospitalized patients tested positive for
COVID-19 (by RT-PCR) and non-COVID-19 respiratory failure of varying severity. Notably,
the cohort is enriched for critically ill patients admitted to the Intensive Care Unit (ICU), and
the impact of CCCoV Abs on COVID-19 pathogenesis and immunity has not been evaluated
previously in this population. The series included consecutive, randomly sampled adult
(>18 years) inpatients of both sexes (not vaccinated against COVID-19), with COVID-19
and respiratory failure, defined as any increase in supplemental oxygen and/or use of non-
invasive or invasive mechanical ventilation above baseline, and non-COVID-19 patients
with respiratory failure were used as the control population. All patients were tested for
COVID-19 and had blood drawn at the hospital admission. The three severity groups
were defined as follows: (S1) hospitalized patients not admitted to the ICU, (S2) ICU
patients without invasive respiratory support and (S3) critically ill COVID-19 patients
that required invasive ventilator support. After obtaining informed consent, peripheral
blood samples were collected at admission (week 1, W1) in sodium citrate vacutainer tubes
(BD biosciences) by trained clinical staff. Whenever possible, two more blood samples
were obtained in weeks 2 (W2) and 3 (W3). Blood tubes were centrifuged at 1800
×
gfor
15 min, at room temperature, and plasma was collected, aliquoted and stored at –80
◦
C
for later analysis. Demographic (age, sex, comorbidity type) and clinical (SARS-CoV-2
infection status and disease severity) data were collected from the electronic medical record
Immuno 2023,3332
system for each patient. Figure 1A shows the timing of hospital admission and dominant
SARS-CoV-2 variant of concern (VOC). A total of 94 patients (Figure 1) were included in
the study with 74 (79%, Figure 1B,C) being SARS-CoV-2-infected and 20 (21%, Figure 1B,C)
non-infected or non-COVID (NC).
Immuno 2023, 3, FOR PEER REVIEW 3
(SARS-CoV-2 infection status and disease severity) data were collected from the electronic
medical record system for each patient. Figure 1A shows the timing of hospital admission
and dominant SARS-CoV-2 variant of concern (VOC). A total of 94 patients (Figure 1) were
included in the study with 74 (79%, Figure 1B,C) being SARS-CoV-2-infected and 20 (21%,
Figure 1B,C) non-infected or non-COVID (NC).
Figure 1. Characteristics of the study cohort. (A) No. of patients enrolled between May 2020 and
December 2021. Vertical green lines indicate the timing when primary and booster vaccine doses
became available for high-risk populations (65+ years). (B) Patient SARS-CoV-2 infection status and
mortality rates among positive and negative subjects. (C) SARS-CoV-2 infection status, mortality
and ICU admission rates and sex distribution among SARS-CoV-2-positive patients. (D) Demo-
graphic and clinical variables among SARS-CoV-2-positive patients.
2.2. CCCoV- and SARS-CoV-2 Ab Peptides
We synthesized a series of peptides targeting highly antigenic N and S protein
epitopes of SARS-CoV-2 and each CCCoV (NL63-CoV, 229E-CoV, OC43-CoV and HKU1-
CoV) (Table 1).
Table 1. Peptides targeting highly antigenic nucleoprotein (N) and spike (S) protein epitopes of
SARS-CoV-2 and CCCoVs.
Coronavirus Species,
Peptide Location Sequence Antigenicity
Score
Peptide Posi-
tion
Hydrophobi-
city (%) Source
HKU1 N GSKLELVKRESEADSPVKDV 21.2 324–343 35 Biomatik
OC43 N AEDISLLKKMDEPYTEDTSE 26 428–447 30 Biomatik
NL63 N PRADKP-
SQLKKPRWKRVPTR 21.6 223–242 40 Biomatik
Figure 1.
Characteristics of the study cohort. (
A
) No. of patients enrolled between May 2020 and
December 2021. Vertical green lines indicate the timing when primary and booster vaccine doses
became available for high-risk populations (65+ years). (
B
) Patient SARS-CoV-2 infection status and
mortality rates among positive and negative subjects. (
C
) SARS-CoV-2 infection status, mortality and
ICU admission rates and sex distribution among SARS-CoV-2-positive patients. (
D
) Demographic
and clinical variables among SARS-CoV-2-positive patients.
2.2. CCCoV- and SARS-CoV-2 Ab Peptides
We synthesized a series of peptides targeting highly antigenic N and S protein epitopes
of SARS-CoV-2 and each CCCoV (NL63-CoV, 229E-CoV, OC43-CoV and HKU1-CoV)
(Table 1).
The S and N protein peptides were designed using Peptide Antigen Design Tool
(NovoPro) to target highly antigenic regions characterized by low amino acid identity
shared between CCCoVs and SARS-CoV-2 to ensure high specificity. Additionally, we
designed two peptides that targeted highly conserved regions of the N protein (identified
by multiple sequence alignment analysis in Mega X) representing potential targets for
cross-reactive Abs induced by CCCoVs (alpha-CCCoVs and beta-CCCoVs). The most
antigenic (Table 1) peptides were selected for each CCCoV and SARS-CoV-2 to develop
enzyme-linked immunosorbent assays (ELISA). Table 2lists the reference sera used for
peptide characterization/ELISA validation.
Immuno 2023,3333
Table 1.
Peptides targeting highly antigenic nucleoprotein (N) and spike (S) protein epitopes of
SARS-CoV-2 and CCCoVs.
Coronavirus
Species, Peptide
Location
Sequence Antigenicity Score Peptide Position Hydrophobicity (%) Source
HKU1 N
GSKLELVKRESEADSPVKDV
21.2 324–343 35 Biomatik
OC43 N
AEDISLLKKMDEPYTEDTSE
26 428–447 30 Biomatik
NL63 N
PRADKPSQLKKPRWKRVPTR
21.6 223–242 40 Biomatik
229E N
SSETKEQKHEMQKPRWKRQP
22.2 234–253 20 Biomatik
SARS-CoV-2 N
HIDAYKTFPPTEPKKDKKKK
21.8 356–375 30 Biomatik
ALPHA N
VANGVKAKGYPQFAELVPST
NA 286–322 50 Biomatik
BETA N
MLKLGTSDPQFPILAELAPT
NA 303–322 60 Biomatik
HKU1 S
SSRNESWHFDKSEPLCLFKK
12.4 168–187 30 Biomatik
OC43 S
LNCPLDPRLKGSFNDRDTGP
15.8 19–38 35 Biomatik
NL63 S
IYNRVKSGSPGDSSWHIYLK
9.4 527–546 30 Biomatik
229E S
SWSDGDVITGVPKPVEGVSS
10 415–434 40 Biomatik
SARS-CoV-2 S
YDPLQPELDSFKEELDKYFK
19.6 1120–1139 35 Biomatik
Table 2. Reference sera used for peptide characterization and ELISA validation.
SARS-CoV-2 seronegative serum samples
Negative serum samples (n= 7) from healthy individuals prior
to 2019 (provided by Shan-Lu Liu)—SARS-CoV-2 N and S
protein ELISA development and validation.
Commercial pre-pandemic normal human serum (SARS-CoV-2
Neutralizing Antibody-Negative Pre-pandemic Human Serum,
Cayman chemicals, Item No. 31569)—ELISA validation and as a
negative control sample to determine cutoff values for each
SARS-CoV-2 Ab test.
Seventy-eight SARS-CoV-2 seronegative samples—SeroNet
Blinded Panel.
SARS-CoV-2 seropositive serum samples
Thirty samples from 10 COVID-19 patients from BUCK-ICU
biorepository (3 longitudinal samples per patient) with variable
disease severity—SARS-CoV-2 N and S protein ELISA
development and validation.
Thirty-one SARS-CoV-2 seropositive samples—SeroNet
Blinded Panel.
Virus/antigen-specific and negative rabbit serum samples
Commercial CCCoV-specific and negative rabbit antisera
(Table S1) were used for CCCoV N and S protein ELISA
development and validation.
2.3. Reference Sera Used for Peptide Characterization Sensitivity and Specificity and
ELISA Validation
2.4. ELISA
ELISA was conducted as described elsewhere [
13
]. Briefly, 96-well plates (Nunc
MaxiSorp) were coated with 800 ng/well (determined to be the optimal coating amount) of
each peptide in 1
×
phosphate-buffered saline (PBS) overnight at 4
◦
C. After rinsing and
blocking the plates, plasma dilutions (for CCCoVs, 1:100, and SARS-CoV-2, serial 4-fold
dilutions starting at 1:100) were prepared using a 5% NFDM in PBS-T, loaded (
50 µL/well
)
in duplicates and incubated at 37
◦
C for 45 min. After, the plates were washed 5 times
using 0.05% PBS-T. Next, 50
µ
L of a horse radish peroxidase (HRP)-conjugated goat anti-
human Fc cross-absorbed Ab (Table S2) were added at the dilutions recommended by the
manufacturer (IgG 1:2000; IgM 1:1000; IgA 1:1000) in 5% NFDM in PBS-T, incubated at
37 ◦C
for 45 min and washed 5 times with 0.05% PBS-T. Then, the plates were developed as
described previously [
12
], and the optical density (OD) values were read at 650 nm using
Immuno 2023,3334
SoftMax Pro 7.1 (Molecular Devices, LLC., San Jose, CA, USA). For SARS-CoV-2-specific
ELISAs, the cut-off values were determined as 3 standard deviations above the mean of 4
replicates of the negative control samples.
2.5. Statistical Analysis
Most of the statistical analyses were performed using PRISM 9 (GraphPad). Kaplan
Meier survival analysis was conducted using R studio to compare the probability of
survival among patients during the study period. Mann–Whitney test was used to compare
unpaired values. One-way analysis of variance (ANOVA followed by Kruskal–Wallis post
hoc test) was used for multiple-group comparisons. For correlation studies, Pearson’s rank
correlation was used. The significance level of 0.05 was used to determine significance;
*p< 0.05, ** p< 0.01, *** p< 0.001 and **** p< 0.0001.
3. Results
3.1. Design and Characterization of SARS-CoV-2 and CCCoV N and S Protein Peptides and
ELISA Development Subsection
Thirty-seven SARS-CoV-2/CCCoV N and S protein-specific peptides with a predicted
high antigenic score and a hydrophobicity index
≤
60% were designed using the NovoPro
peptide design tool (Figure 2A). Four additional peptides targeting conserved regions of
nucleoprotein, Alpha N and Beta N were designed (Figure 2A). Peptide-coating conditions
(optimal coating buffer and peptide concentration) were optimized, and peptide antigenic-
ity was tested. Moreover, 1
×
PBS was found to be optimal for coating for all peptides, and
800 ng/well was determined to be the optimal coating amount. Twenty-seven peptides
were shown to possess satisfactory antigenic characteristics in ELISA with positive-to-
negative (P/N) serum (OD) 650 nm (OD
650
) values > 2 for IgG Abs. Based on the best
antigenicity (P/N values = 3–8) (Figure 2B), we selected one S and one N protein-specific
peptide for each CCCoV and SARS-CoV-2 that mapped to the S or N protein regions where
SARS-CoV-2 and CCCoV share low (for S protein) or low-to-moderate (for N protein)
amino-acid sequence identity to develop ELISA and screen clinical samples (Figure 2C,D,
Table 1). Of note, the selected SARS-CoV-2 N/S peptides shared 100% aa identity with the
different SARS-CoV-2 variants (including alpha, delta, and omicron VOCs) analyzed.
The specificity of these peptides (Table 1) was evaluated using indirect ELISA in
which each of the selected peptides was tested with the reference positive and negative
sera (Table 2). Our results demonstrated that all virus-specific peptides were recognized
by the virus-/antigen-specific sera only, while no cross-reactivity/non-specific reactivity
with heterologous or negative sera was observed (Figure 2E). Unexpectedly, Alpha N
peptide was only recognized with 229E-specific rabbit antiserum, while Beta N peptide
was recognized with NL63-, OC43- and HKU1-specific rabbit antisera (Figure 2E).
We next tested the selected peptides with a panel of SARS-CoV-2 seropositive (31) and
seronegative (78) blinded serum samples (n= 109), 7 negative pre-COVID-19 (pre-2019) and
30 SARS-CoV-2 seropositive plasma samples (3 longitudinal samples from 10 COVID-19-
positive cases of variable severity) collected in 2020 (Table 2). For the SARS-CoV-2-specific
peptides, there was no reactivity with plasma from healthy volunteers collected prior to
2019, while variable levels of SARS-CoV-2-specific IgM/IgA/IgG Abs were detected in
the samples from COVID-19-positive individuals (1:100–256,000). Additionally, low but
variable levels of CCCoV-specific IgM/IgA/IgG Abs were detected in the pre-COVID-19
and SARS-CoV-2 seropositive samples (OD
650
0.03–0.9). The sensitivity and specificity of
the SARS-CoV-2 N- and S-specific ELISA are shown in Table 3.
Immuno 2023,3335
Immuno 2023, 3, FOR PEER REVIEW 6
Figure 2. SARS-CoV-2 and CCCoV S and N protein peptide antigenicity, localization and specificity.
(A) SARS-CoV-2 and CCCoV S and N protein peptide antigenicity was evaluated using indirect
ELISA. All peptides were screened with a panel of human pre-pandemic (Negative) and SARS-CoV-
2 serum samples from SARS-CoV-2-positive cases (Positive) for SARS-CoV-2 peptide validation or
with commercial (Sino Biologicals/Native antigen) OC43-, HKU1-, 229E- and NL63-specific rabbit
antisera (Positive) and normal rabbit serum (Negative) for CCCoV peptides. A heatmap shows raw
OD
650
values generated with the positive and negative sera. The peptides for which optimal posi-
tive/negative ratio values were selected for ELISA development are highlighted in green color (B).
Percent (%) identity between SARS-CoV-2 and CCCoV spike (C) and nucleoprotein (D). Domain
abbreviations: NTD, N-terminal domain; RBD, receptor-binding domain; S1/S2, furin cleavage site;
FP, fusion peptide; HR1/HR2, heptad repeat regions. N, nucleocapsid; S, spike. Peptide abbrevia-
tions: HKU1 RBD, OC43 RBD, NL63 RBD, 229E RBD, SARS-CoV-2 spike, HKU1 nucleocapsid, OC43
nucleocapsid, NL63 nucleocapsid, 229E nucleocapsid and SARS-CoV-2 nucleocapsid (E). Cross-re-
activity testing for the selected SARS-CoV-2/CCCoV S and N peptides with a panel of virus-/pro-
tein-specific positive and negative sera using indirect ELISA. Each plot represents data (OD
650
val-
ues) for individual peptide reactivity with virus-/protein-specific positive and negative sera.
The specificity of these peptides (Table 1) was evaluated using indirect ELISA in
which each of the selected peptides was tested with the reference positive and negative
sera (Table 2). Our results demonstrated that all virus-specific peptides were recognized
by the virus-/antigen-specific sera only, while no cross-reactivity/non-specific reactivity
with heterologous or negative sera was observed (Figure 2E). Unexpectedly, Alpha N pep-
tide was only recognized with 229E-specific rabbit antiserum, while Beta N peptide was
recognized with NL63-, OC43- and HKU1-specific rabbit antisera (Figure 2E).
We next tested the selected peptides with a panel of SARS-CoV-2 seropositive (31)
and seronegative (78) blinded serum samples (n = 109), 7 negative pre-COVID-19 (pre-
2019) and 30 SARS-CoV-2 seropositive plasma samples (3 longitudinal samples from 10
COVID-19-positive cases of variable severity) collected in 2020 (Table 2). For the SARS-
Figure 2.
SARS-CoV-2 and CCCoV S and N protein peptide antigenicity, localization and specificity.
(
A
) SARS-CoV-2 and CCCoV S and N protein peptide antigenicity was evaluated using indirect
ELISA. All peptides were screened with a panel of human pre-pandemic (Negative) and SARS-CoV-2
serum samples from SARS-CoV-2-positive cases (Positive) for SARS-CoV-2 peptide validation or
with commercial (Sino Biologicals/Native antigen) OC43-, HKU1-, 229E- and NL63-specific rabbit
antisera (Positive) and normal rabbit serum (Negative) for CCCoV peptides. A heatmap shows
raw OD
650
values generated with the positive and negative sera. The peptides for which optimal
positive/negative ratio values were selected for ELISA development are highlighted in green color
(
B
). Percent (%) identity between SARS-CoV-2 and CCCoV spike (
C
) and nucleoprotein (
D
). Domain
abbreviations: NTD, N-terminal domain; RBD, receptor-binding domain; S1/S2, furin cleavage site;
FP, fusion peptide; HR1/HR2, heptad repeat regions. N, nucleocapsid; S, spike. Peptide abbreviations:
HKU1 RBD, OC43 RBD, NL63 RBD, 229E RBD, SARS-CoV-2 spike, HKU1 nucleocapsid, OC43
nucleocapsid, NL63 nucleocapsid, 229E nucleocapsid and SARS-CoV-2 nucleocapsid (
E
). Cross-
reactivity testing for the selected SARS-CoV-2/CCCoV S and N peptides with a panel of virus-
/protein-specific positive and negative sera using indirect ELISA. Each plot represents data (OD
650
values) for individual peptide reactivity with virus-/protein-specific positive and negative sera.
Table 3. Sensitivity and specificity of SARS-CoV-2 S- and N-protein ELISA.
Test SARS-CoV-2
(N)
SARS-CoV-2
(S)
Sensitivity 95.08% 96.77%
Specificity 97.65% 100%
Accuracy 96.58% 98.63%
Immuno 2023,3336
Because reference human serum samples seronegative for CCCoV are not available,
we report raw OD
650
values for CCCoV Ab levels thereafter, while for SARS-CoV-2 Abs
we present both OD
650
values (included in all heatmaps together with CCCoV data) and
SARS-CoV-2 Ab titers (shown in Supplementary Materials figures).
3.2. Advanced Age and Higher Prevalence of Comorbidities Were Associated with Increased
Patient Mortality
Of the COVID-19-positive patients, 57% were males, 85% were admitted to the ICU
and 38% died (Figure 1C). The cause of death for most deceased COVID-19 positive
patients was consistent with COVID-19 (Table S3), and mortality increased progressively
with disease severity. So, in the group (S1) with the least severe disease at admission, 1 out
of 11 patients (9%) died. In the ICU-admitted but non-intubated inpatients (S2), 2 out of
10 patients (20%) died, while among hospitalized, ICU-admitted and intubated inpatients
(S3), 25 out of 53 (47%) died. Patients in our study had high levels of comorbidities,
including heart disease (the most prevalent comorbidity found in 83% of the patients),
diabetes (43%) and pulmonary disease (38%) (Figure 1D), all previously identified as risk
factors for severe COVID-19. Moreover, our analysis demonstrated that advanced age
was significantly associated with a higher prevalence of comorbidities (Table 4), and the
probability of survival was the lowest among the oldest (80+ years) (Figure 3). Overall,
clinical outcomes varied drastically depending on the comorbidity status/type, suggestive
of differing mechanisms of the disease pathogenesis or the ability to effectively clear
infection associated with various comorbidities (Table 5).
Table 4.
Median age of SARS-CoV-2 positive patients associated with different clinical and demo-
graphic variables.
Clinical and Demographic Variables Patient Median Age pValue
Survivors (n= 46) 61 0.32
Non-survivors (n= 28) 62
Male (n= 42) 61 0.44
Female (n= 32) 63
No comorbidity (n= 8) 36 0.001
Comorbidity (n= 66) 63
Table 5. Mortality rates among patients with and without comorbidities.
Comorbidity Patients
Non-survivors, % Survivors, %
Heart disease (n= 76) 39 61
Pulmonary disease (n= 37) 41 59
Liver disease (n= 5) 80 20
Diabetes (n= 39) 41 59
Hematological disorder (n= 3)
0 100
Immunosuppression (n= 12) 42 58
Cancer (n= 11) 55 45
No comorbidities (n= 8) 25 75
Immuno 2023,3337
Immuno 2023, 3, FOR PEER REVIEW 8
Figure 3. Survival analysis among SARS-CoV-2-infected patients from three different age groups
(19–49 years, 50–79 years and 80+ years). The doed lines represent the median survival time.
Shaded area represents a 95% confidence interval.
Table 5. Mortality rates among patients with and without comorbidities.
Comorbidity
Patients
Non-survivors, % Survivors, %
Heart disease (n = 76) 39 61
Pulmonary disease (n = 37) 41 59
Liver disease (n = 5) 80 20
Diabetes (n = 39) 41 59
Hematological disorder (n = 3) 0 100
Immunosuppression (n = 12) 42 58
Cancer (n = 11) 55 45
No comorbidities (n = 8) 25 75
Figure 3.
Survival analysis among SARS-CoV-2-infected patients from three different age groups
(19–49 years, 50–79 years and 80+ years). The dotted lines represent the median survival time. Shaded
area represents a 95% confidence interval.
3.3. Correlation between CCCoV- and SARS-CoV-2-Specific Ab Levels and COVID-19 Severity
To identify the role of pre-existing CCCoV Abs in severe COVID-19 pathogenesis
and immunity, we analyzed the levels of SARS-CoV-2/CCCoV IgG/IgA/IgM Abs in the
plasma samples of the 94 individuals. A comparison of CCCoV- and SARS-CoV-2-specific
anti-N/S Ab levels among NC and COVID-19 patients with variable severity (S1, S2 and S3)
of clinical disease revealed largely distinct profiles of SARS-CoV-2- vs. CCCoV-specific Abs
(Figure 4and Figure S1 in Supplementary Materials). Consistent with the absence of SARS-
CoV-2 infection, NC patients generally had similar and low levels of SARS-CoV-2- and
CCCoV-specific Abs (except for high IgG/IgM S Abs to OC43), while COVID-19-positive
patients had higher SARS-CoV-2 Ab levels sometimes coinciding with noticeably decreased
CCCoV Ab levels (e.g., N protein-specific IgG). This is suggestive of a protective role of pre-
existing CCCoV Abs. Further, we demonstrated that SARS-CoV-2 N/S Ab levels correlated
significantly (p< 0.05) with the respective levels of CCCoV N and S Abs (
Figure S2
). SARS-
CoV-2 infection induced variable levels of S-/N-specific IgG/IgA/IgM Abs in S1, S2 and
S3 patients. Surprisingly, ICU-admitted, non-intubated COVID-19 positive patients (S2)
had the lowest SARS-CoV-2 N/S protein-specific IgA and IgM Ab levels, while the highest
disease severity (S3) was invariably associated with the highest SARS-CoV-2 IgG/IgA N/S
protein-specific Ab levels. Because the remainder of our study is focused on COVID-19
patients, the NC group is not included in the data analyses presented below.
Immuno 2023,3338
Immuno 2023, 3, FOR PEER REVIEW 9
3.3. Correlation between CCCoV- and SARS-CoV-2-Specific Ab Levels and COVID-19 Severity
To identify the role of pre-existing CCCoV Abs in severe COVID-19 pathogenesis and
immunity, we analyzed the levels of SARS-CoV-2/CCCoV IgG/IgA/IgM Abs in the plasma
samples of the 94 individuals. A comparison of CCCoV- and SARS-CoV-2-specific anti-
N/S Ab levels among NC and COVID-19 patients with variable severity (S1, S2 and S3) of
clinical disease revealed largely distinct profiles of SARS-CoV-2- vs. CCCoV-specific Abs
(Figure 4 and Figure S1 in Supplementary Materials). Consistent with the absence of
SARS-CoV-2 infection, NC patients generally had similar and low levels of SARS-CoV-2-
and CCCoV-specific Abs (except for high IgG/IgM S Abs to OC43), while COVID-19-pos-
itive patients had higher SARS-CoV-2 Ab levels sometimes coinciding with noticeably de-
creased CCCoV Ab levels (e.g., N protein-specific IgG). This is suggestive of a protective
role of pre-existing CCCoV Abs. Further, we demonstrated that SARS-CoV-2 N/S Ab lev-
els correlated significantly (p < 0.05) with the respective levels of CCCoV N and S Abs
(Figure S2). SARS-CoV-2 infection induced variable levels of S-/N-specific IgG/IgA/IgM
Abs in S1, S2 and S3 patients. Surprisingly, ICU-admied, non-intubated COVID-19 pos-
itive patients (S2) had the lowest SARS-CoV-2 N/S protein-specific IgA and IgM Ab levels,
while the highest disease severity (S3) was invariably associated with the highest SARS-
CoV-2 IgG/IgA N/S protein-specific Ab levels. Because the remainder of our study is fo-
cused on COVID-19 patients, the NC group is not included in the data analyses presented
below.
Figure 4.
CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented as
mean OD
650
values) in NC (non-COVID) and SARS-CoV-2-infected patients with variable COVID-19
severity (S1, S2 and S3).
3.4. Relationship between Virus-Specific Ab Levels, Survival and Various Comorbidities
A comparison of SARS-CoV-2- and CCCoV-specific Ab levels for patients with and
without comorbidities yielded inconsistent results, with inversely correlated N and S Ab
titers noted in some cases (Figures 5B and S4). Further analysis of the data based on
individual comorbidities demonstrated that samples from patients with hematological
diseases, cancer and/or immunosuppression generally resulted in the lowest levels of
SARS-CoV-2 and CCCoV N/S protein-specific IgG/IgA/IgM Abs (Figures 5A and S3).
However, other comorbidities (liver disease and diabetes) were generally associated with
increased Ab responses.
Immuno 2023,3339
Immuno 2023, 3, FOR PEER REVIEW 10
Figure 4. CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as mean OD
650
values) in NC (non-COVID) and SARS-CoV-2-infected patients with variable
COVID-19 severity (S1, S2 and S3).
3.4. Relationship between Virus-Specific Ab Levels, Survival and Various Comorbidities
A comparison of SARS-CoV-2- and CCCoV-specific Ab levels for patients with and
without comorbidities yielded inconsistent results, with inversely correlated N and S Ab
titers noted in some cases (Figures 5B and S4). Further analysis of the data based on indi-
vidual comorbidities demonstrated that samples from patients with hematological dis-
eases, cancer and/or immunosuppression generally resulted in the lowest levels of SARS-
CoV-2 and CCCoV N/S protein-specific IgG/IgA/IgM Abs (Figures 5A and S3). However,
other comorbidities (liver disease and diabetes) were generally associated with increased
Ab responses.
Figure 5. CCCoV and SARS-CoV-2 S and N protein-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected patients with different comorbidities (A), with and without
comorbidities (B), in surviving and dying SARS-CoV-2 infected patients (C).
Further, generally, survivors had higher SARS-CoV-2 N (but not S) protein-specific
Ab levels than those who died (Figures 5C and S5). Similarly, CCCoV Ab levels were
slightly higher in survivors vs. non-survivors (Figures 5C). These findings suggest that
efficient Ab responses to SARS-CoV-2 N protein may have significant prognostic value of
patient survival in this cohort or could be reflective of differences in the underlying pop-
ulation.
3.5. SARS-CoV-2 Ab Levels, Dynamics and the Risk of ICU Admission
Figure 5.
CCCoV and SARS-CoV-2 S and N protein-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected patients with different comorbidities (
A
), with and without
comorbidities (B), in surviving and dying SARS-CoV-2 infected patients (C).
Further, generally, survivors had higher SARS-CoV-2 N (but not S) protein-specific Ab
levels than those who died (Figures 5C and S5). Similarly, CCCoV Ab levels were slightly
higher in survivors vs. non-survivors (Figure 5C). These findings suggest that efficient
Ab responses to SARS-CoV-2 N protein may have significant prognostic value of patient
survival in this cohort or could be reflective of differences in the underlying population.
3.5. SARS-CoV-2 Ab Levels, Dynamics and the Risk of ICU Admission
We observed that increased levels of SARS-CoV-2 N/S protein-specific IgG/IgA/IgM
Abs among COVID-19 positive patients were associated with an increased risk of ICU
admission (Figures 6and S6). This suggests that increased Ab levels in the patients may be
due to higher levels of SARS-CoV-2 replication and COVID-19 severity. Variable levels of
CCCoV-specific Ab levels were observed among ICU-admitted and non-ICU patients.
Immuno 2023,3340
Immuno 2023, 3, FOR PEER REVIEW 11
We observed that increased levels of SARS-CoV-2 N/S protein-specific IgG/IgA/IgM
Abs among COVID-19 positive patients were associated with an increased risk of ICU
admission (Figures 6 and S6). This suggests that increased Ab levels in the patients may
be due to higher levels of SARS-CoV-2 replication and COVID-19 severity. Variable levels
of CCCoV-specific Ab levels were observed among ICU-admied and non-ICU patients.
Figure 6. CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected male and female patients.
We also compared the dynamics of SARS-CoV-2 N/S protein-specific IgG/IgA/IgM
Ab responses and observed that the Ab levels increased gradually from week 1 (W1) to
week 3 (W3) (Figures 7 and S7). This was least pronounced for IgM Abs, which is con-
sistent with the fact that this Ab isotype peaks earlier than IgG and IgA. Although the
levels of CCCoV N/S protein-specific Abs remained low throughout the observation pe-
riod, there was a slight increase in W3, mainly for IgG Abs (Figure 7). Of interest, we ob-
served slightly increased levels of HKU1 and OC43 betaCoVs S protein-specific IgM Abs
(Figures 4–7) which is likely indicative of previous or concurrent (Beta CCCoVs, HKU1
and OC43) infections and widespread circulation of these CoVs.
Figure 6.
CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD650 values) in ICU-admitted and non-ICU SARS-CoV-2-infected patients.
3.6. Age and Sex Effects on SARS-CoV-2 Ab Responses
Younger (19–49 years) patients had increased SARS-CoV-2 N/S protein-specific IgG
Ab levels while older patients had higher IgA Ab levels (Figures 8and S8). Of interest,
the oldest (80+ years) age group was associated with the lowest SARS-CoV-2 IgM and the
highest IgA Ab levels suggesting that isotype specificity of Ab response may change with
age. In contrast to the above, variable levels of CCCoV-specific Ab levels were observed
among patients regardless of age. However, higher IgG/IgA Abs to 229E N and IgA
Abs to HKU1 S were observed in the oldest patients. Finally, overall, females had higher
SARS-CoV-2 S/N protein-specific IgG/IgA Ab levels compared to males (
Figures 9and S9
).
There were no appreciable sex-related differences in CCCoV N/S protein-specific Abs
levels. However, the levels of CCCoV S vs. N protein-specific Abs were generally higher
likely due to the faster decay rates of N protein-specific Ab responses.
We also compared the dynamics of SARS-CoV-2 N/S protein-specific IgG/IgA/IgM
Ab responses and observed that the Ab levels increased gradually from week 1 (W1) to
week 3 (W3) (Figures 7and S7). This was least pronounced for IgM Abs, which is consistent
with the fact that this Ab isotype peaks earlier than IgG and IgA. Although the levels of
CCCoV N/S protein-specific Abs remained low throughout the observation period, there
was a slight increase in W3, mainly for IgG Abs (Figure 7). Of interest, we observed slightly
increased levels of HKU1 and OC43 betaCoVs S protein-specific IgM Abs (Figures 4–7)
which is likely indicative of previous or concurrent (Beta CCCoVs, HKU1 and OC43)
infections and widespread circulation of these CoVs.
Immuno 2023,3341
Immuno 2023, 3, FOR PEER REVIEW 12
Figure 7. Dynamics of CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab
levels (presented as OD
650
values) in SARS-CoV-2-infected patients. W1, week 1; W2, week 2; W3,
week 3.
3.6. Age and Sex Effects on SARS-CoV-2 Ab Responses
Younger (19–49 years) patients had increased SARS-CoV-2 N/S protein-specific IgG
Ab levels while older patients had higher IgA Ab levels (Figures 8 and S8). Of interest, the
oldest (80+ years) age group was associated with the lowest SARS-CoV-2 IgM and the
highest IgA Ab levels suggesting that isotype specificity of Ab response may change with
age. In contrast to the above, variable levels of CCCoV-specific Ab levels were observed
among patients regardless of age. However, higher IgG/IgA Abs to 229E N and IgA Abs
to HKU1 S were observed in the oldest patients. Finally, overall, females had higher SARS-
CoV-2 S/N protein-specific IgG/IgA Ab levels compared to males (Figures 9 and S9). There
were no appreciable sex-related differences in CCCoV N/S protein-specific Abs levels.
However, the levels of CCCoV S vs. N protein-specific Abs were generally higher likely
due to the faster decay rates of N protein-specific Ab responses.
Figure 7.
Dynamics of CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels
(presented as OD
650
values) in SARS-CoV-2-infected patients. W1, week 1; W2, week 2; W3, week 3.
Immuno 2023, 3, FOR PEER REVIEW 13
Figure 8. CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected patients of different age groups.
Figure 9. CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected male and female patients.
4. Discussion
This study generated the first comprehensive evidence regarding the interactions be-
tween pre-existing CCCoV Abs and SARS-CoV-2 clinical outcomes and Ab responses in
hospitalized COVID-19 patients with respiratory failure. Another novel aspect of our
study is the use of species-specific peptide-based ELISA to minimize/eliminate cross-re-
activity observed for SARS-CoV-2 ELISA based on whole virus or full-length/truncated
proteins.
Figure 8.
CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD650 values) in SARS-CoV-2-infected patients of different age groups.
Immuno 2023,3342
Immuno 2023, 3, FOR PEER REVIEW 13
Figure 8. CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected patients of different age groups.
Figure 9. CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD
650
values) in SARS-CoV-2-infected male and female patients.
4. Discussion
This study generated the first comprehensive evidence regarding the interactions be-
tween pre-existing CCCoV Abs and SARS-CoV-2 clinical outcomes and Ab responses in
hospitalized COVID-19 patients with respiratory failure. Another novel aspect of our
study is the use of species-specific peptide-based ELISA to minimize/eliminate cross-re-
activity observed for SARS-CoV-2 ELISA based on whole virus or full-length/truncated
proteins.
Figure 9.
CCCoV and SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab levels (presented
as OD650 values) in SARS-CoV-2-infected male and female patients.
4. Discussion
This study generated the first comprehensive evidence regarding the interactions
between pre-existing CCCoV Abs and SARS-CoV-2 clinical outcomes and Ab responses in
hospitalized COVID-19 patients with respiratory failure. Another novel aspect of our study
is the use of species-specific peptide-based ELISA to minimize/eliminate cross-reactivity
observed for SARS-CoV-2 ELISA based on whole virus or full-length/truncated proteins.
Our findings demonstrated that, in this cohort, CCCoV Abs were present at variable
but generally low levels that correlated positively with SARS-CoV-2 Ab responses, ruling
out the inhibitory effects of CCCoV Abs on SARS-CoV-2 Ab development. Additionally,
we did not find any evidence suggesting that increased COVID-19 severity was associated
with higher CCCoV Ab levels as would be expected if CCCoV-driven Ab-dependent
enhancement effects (as observed for some other CoVs) were present [
14
]. In contrast, the
higher CCCoV Ab levels we observed in the NC patients compared to COVID-19 patients
may be indicative of a protective role of CCCoV Abs. Thus, our data suggest that it is
unlikely that the ‘original antigenic sin’ phenomenon plays a role in the development of
severe COVID-19 in this cohort [12].
The youngest patients (19–49 years) had the highest SARS-CoV-2 S IgG and SARS-
CoV-2 N IgM Ab levels, while the oldest patients had the lowest SARS-CoV-2 IgM/IgG
but highest IgA Ab responses which is suggestive of age-specific Ab isotype prevalence.
Consistent with previously published reports [
15
–
18
], advanced age and higher prevalence
of various comorbidities (especially cancer and immunosuppression) were associated
with decreased CCCoV/SARS-CoV-2-specific Ab levels and increased mortality among
hospitalized patients. Thus, advanced age combined with deficient Ab response can serve
as a reliable prognostic factor of increased mortality among severe COVID-19 patients.
However, our analysis did not identify strong predictors of increased risk for ICU admission.
This is likely because higher SARS-CoV-2 replication may result in an increased antigenic
stimulation of Ig production masking suboptimal Ab responses in the ICU-admitted vs.
non-ICU patients.
The influence of sex on SARS-CoV-2 immune responses was confirmed by our findings
of higher SARS-CoV-2 Ab responses in females vs. males. This is consistent with previous
findings demonstrating that females mount a more robust Ab response against SARS-CoV-2
Immuno 2023,3343
and other pathogens [
19
–
22
] and aligns with prior evidence for an immunosuppressive
role of testosterone [23].
Because CCCoVs are endemic and most humans encounter them early in childhood, it
was not possible to include a randomized control group without pre-existing CCCoV Abs
which is a limitation of our study. Nevertheless, our findings improve our understanding
of SARS-CoV-2 Ab responses and clinical outcomes in severe COVID-19 patients as well as
the role of CCCoV-induced Ab responses in these interactions.
To our knowledge, this is the first study to comprehensively evaluate the levels of
SARS-CoV-2 and CCCoV N/S protein-specific IgG/IgA/IgM Abs in patients with severe
COVID-19. We generated conclusive evidence that insufficient (rather than excessive) Ab
response against SARS-CoV-2 is associated with increased mortality among severe COVID-
19 patients. Furthermore, our findings confirm that while CCCoV-specific Ab responses are
generally present at low levels in this group of patients, their increased levels may mediate
partial cross-protection. Experimental studies are needed to mechanistically evaluate the
observed interactions in appropriate preclinical models of immunological senescence and
defined comorbidities.
Supplementary Materials:
The following supporting information can be downloaded at https:
//www.mdpi.com/article/10.3390/immuno3030020/s1: Figure S1: SARS-CoV-2 S and N protein-
specific IgG, IgA and IgM Ab titers in NC (non-COVID)- and SARS-CoV-2-infected patients with
variable COVID-19 severity (S1, S2, S3). Differences were considered significant at a p-value < 0.05
(*), <0.01 (**), <0.001 (***), <0.0001 (****); Figure S2: A correlation analysis of IgG, IgA and IgM Ab
responses to the spike and N proteins of SARS-CoV-2 and CCCoVs; Figure S3: SARS-CoV-2 S and
N protein-specific IgG, IgA and IgM Ab titers in SARS-CoV-2-infected patients with and without
comorbidities; Figure S4: SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab titers in SARS-
CoV-2-infected patients with different comorbidities; Figure S5: SARS-CoV-2 S and N protein-specific
IgG, IgA and IgM Ab titers in surviving and deceased SARS-CoV-2-infected patients. Differences
were considered significant at a p-value < 0.05 (*), <0.01 (**), <0.001 (***); Figure S6: SARS-CoV-2 S and
N protein-specific IgG, IgA and IgM Ab titers in ICU-admitted and non-ICU SARS-CoV-2-infected
patients. Differences were considered significant at a p-value < 0.05 (*), <0.01 (**); Figure S7: Dynamics
of SARS-CoV-2 S and N peptide-specific IgG, IgA and IgM Ab titers in SARS-CoV-2-infected patients.
Differences were considered significant at a p-value < 0.05 (*), <0.01 (**), <0.001 (***), <0.0001 (****)
(W1, week 1; W2, week 2; W3, week 3); Figure S8: SARS-CoV-2 S and N peptide-specific IgG, IgA and
IgM Ab titers in SARS-CoV-2-infected patients of different age groups. Differences were considered
significant at a p-value < 0.05 (*), <0.01 (**), <0.001 (***), <0.001 (***); Figure S9: SARS-CoV-2 S and
N peptide-specific IgG, IgA and IgM Ab titers in SARS-CoV-2-infected male and female patients.
Differences were considered significant at a p-value < 0.05 (*), <0.01 (**), <0.001 (***). Table S1: Virus-
specific polyclonal rabbit antisera and normal rabbit serum; Table S2: HRP-conjugated Anti-Human
IgG, IgA or IgM; Table S3: Death cause.
Author Contributions:
Funding acquisition and conceptualization: E.M.O., L.J.S. and A.N.V. Project
supervision: A.N.V. Methodology: A.N.V., B.A. and S.A.R. Investigation: B.A. Data analysis: B.A.,
A.N.V., M.A. and S.F. Patient recruitment and biorepository establishment: J.S.B. and J.C.H. First
draft—writing and editing: B.A. and A.N.V. Manuscript critical review: E.M.O., L.J.S., J.S.B., J.O.A.,
S.A.R., S.F., M.A., M.P.R., D.M.J. and S.-L.L. All authors have read and agreed to the published version
of the manuscript.
Funding:
This research was supported by the National Cancer Institute of the NIH (award No
U54CA260582).
Institutional Review Board Statement:
All methods were carried out in accordance with relevant
guidelines and regulations. This study was approved by the Institutional Review Board (IRB #
2020H0198) of the Ohio State University. Samples were obtained from the Ohio State University
Intensive Care Unit Registry (BuckICU, IRB approval #2020H0175) biorepository. This biorepository
collects longitudinal biospecimens and associated clinical data from hospitalized patients with
respiratory failure.
Immuno 2023,3344
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the
study. Written informed consent has been obtained from the patient(s) to publish this paper.
Data Availability Statement:
The data that support the findings of this study are available from the
corresponding author upon reasonable request.
Acknowledgments:
We are grateful to the BUCK-ICU cohort study participants and to the clinical
and technical staff who provided support with sample collection, processing and distribution. We
also thank Maryssa Kick and Maria Chellis for technical support.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design
of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; or
in the decision to publish the results.
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