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Record W3133646555 · doi:10.1101/2021.03.05.21252707

Centenarians and extremely old people living with frailty can elicit durable SARS-CoV-2 spike specific IgG antibodies with virus neutralization functions following virus infection

2021· preprint· en· W3133646555 on OpenAlexafffundabout
Mary K. Foley, Samuel D. Searle, Ali Toloue Ostadgavahi, Ryan Booth, Alec Falkenham, Darryl Falzarano, Salvatore Rubino, Magen E. Francis, Mara McNeil, Christopher T. Richardson, Jason J. LeBlanc, Sharon A. Oldford, Volker Gerdts, Melissa K. Andrew, Shelly McNeil, Barry Clarke, Kenneth Rockwood, David J. Kelvin, Alyson A. Kelvin

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of SaskatchewanIzaak Walton Killam Health CentreDalhousie University
FundersNational Institutes of HealthCanadian Frailty NetworkGenome AtlanticDalhousie UniversityResearch Nova ScotiaConsortium canadien en neurodégénérescence associée au vieillissementCanadian Institutes of Health ResearchInnovation SaskatchewanGenome CanadaNational Institute of Allergy and Infectious DiseasesDalhousie Medical Research Foundation
KeywordsAntibodyImmunityMedicineVirusImmunologyOutbreakImmune systemHumoral immunitySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyBiologyCoronavirus disease 2019 (COVID-19)Internal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Abstract Background The SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2) has led to more than 114 million COVID-19 cases and >2.5 million deaths worldwide. Epidemiological analysis has revealed that the risk of developing severe COVID-19 increases with age. Despite a disproportionate number of older individuals and long-term care facilities being affected by SARS-CoV-2 and COVID-19, very little is understood about the immune responses and development of humoral immunity in the extremely old person after SARS-CoV-2 infection. Here we investigated the development of humoral immunity in centenarians following a SARS-CoV-2 outbreak in a long-term care facility. Methods Extreme aged individuals and centenarians who were residents in a long-term care facility and infected with or exposed to SARS-CoV-2 were investigated for the development of antibodies to SARS-CoV-2. Blood samples were collected from positive and bystander individuals 30 and 60 days after original diagnosis of SARS-CoV-2 infection. Plasma was used to quantify IgG, IgA, and IgM isotypes and subsequent subclasses of antibodies specific for SARS-CoV-2 spike protein. The function of anti-spike was then assessed by virus neutralization assays against the native SARS-CoV-2 virus. Findings Fifteen long-term care residents were investigated for SARS-CoV-2 infection. All individuals had a Clinical Frailty scale score ≥5 and were of extreme older age or were centenarians. Six women with a median age of 98.8 years tested positive for SARS-CoV-2. Anti-spike IgG antibody titers were the highest titers observed in our cohort with all IgG positive individuals having virus neutralization ability. Additionally, 5 out of the 6 positive participants had a robust IgA anti-SARS-CoV-2 response. In all 5, antibodies were detected after 60 days from initial diagnosis. Interpretation Extreme older frail individuals and centenarians were able to elicit robust IgG and IgA antibodies directed toward SARS-CoV-2 spike protein. The antibodies were able to neutralize the virus. Humoral responses were still detectable after 60 days from initial diagnosis. Together, these data suggest that recovered participants who are of extreme old age would be protected if re-exposed to the same SARS-CoV-2 viral variant. Considering the threat of SARS-CoV-2 and COVID-19 to older age groups and long-term care facilities, the humoral responses to SARS-CoV-2 in older age groups is of public health importance and has implications to vaccine responses. Funding Canadian Institutes of Health Research (CIHR), NIH/NIAID, Genome Atlantic. VIDO receives operational funding from the Canada Foundation for Innovation through the Major Science Initiatives Fund and by Government of Saskatchewan through Innovation Saskatchewan.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.308
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes3
Has abstractyes

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