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The risk of COVID-19 death is much greater and age-dependent with type I IFN autoantibodies
Jérémy Manry, Paul Bastard, Adrian Gervais, Tom Le Voyer, Jérémie Rosain, Quentin Philippot, Eleftherios Michailidis, Hans-Heinrich Hoffmann, Shohei Eto, Marina García-Prat, Lucy Bizien, Alba Parra-Martínez, Rui Yang, Liis Haljasmägi, Mélanie Migaud, Karita Särekannu, Julia Maslovskaja, Nicolas de Prost, Yacine Tandjaoui-Lambiotte, Charles‐Édouard Luyt, Blanca Amador-Borrero, Alexandre Gaudet, Julien Poissy, Pascal Morel, Pascale Richard, Fabrice Cognasse, Jesús Troya, Sophie Trouillet‐Assant, Alexandre Bélot, Kahina Saker, Pierre Garçon, Jacques G. Rivière, Jean‐Christophe Lagier, Stéphanie Gentile, Lindsey B. Rosen, Elana Shaw, Tomohiro Morio, Junko Tanaka, David Dalmau, Pierre‐Louis Tharaux, D. Sène, Alain Stépanian, Bruno Mégarbane, Vasiliki Triantafyllia, Arnaud Fekkar, James R. Heath, José Luis Franco, Juan‐Manuel Anaya, Jordi Solé‐Violán, Luisa Imberti, Andrea Biondi, Paolo Bonfanti, Riccardo Castagnoli, Ottavia M. Delmonte, Yu Zhang, Andrew L. Snow, Steven M. Holland, Catherine M. Biggs, Marcela Moncada‐Vélez, Andrés A. Arias, Lazaro Lorenzo, Soraya Boucherit, Dany Anglicheau, Anna M. Planas, Filomeen Haerynck, Sotiriјa Duvlis, Robert L. Nussbaum, Tayfun Özçelık, Sevgi Keleş, Aziz Bousfiha, Jalila El Bakkouri, Carolina Ramı́rez-Santana, Stéphane Paul, Qiang Pan‐Hammarström, Lennart Hammarström, Annabelle Dupont, Alina Kurolap, Christine N. Metz, Alessandro Aiuti, Giorgio Casari, Vito Lampasona, Fabio Ciceri, Lucila Akune Barreiros, Elena Domínguez‐Garrido, Mateus Vidigal, Mayana Zatz, Diederik van de Beek, Sabina Sahanic, Ivan Tancevski, Yuriy Stepanovskyy, Oksana Boyarchuk, Yoko Nukui, Miyuki Tsumura, Loreto Vidaur, Stuart G. Tangye, Sonia Burrel, Darragh Duffy, Lluís Quintana‐Murci, Adam Klocperk, Nelli Y. Kann, Anna Shcherbina, YL Lau, Daniel Leung, Matthieu Coulongeat, Julien Marlet, Rutger Koning, Luis Felipe Reyes, Angélique Chauvineau‐Grenier, Fabienne Venet, Guillaume Monneret, Michel C. Nussenzweig, Romain Arrestier, Idris Boudhabhay, Hagit Baris Feldman, David Hagin, Joost Wauters, Isabelle Meyts, Adam H. Dyer, Seán Kennelly, Nollaig M. Bourke, Rabih Halwani, Fatemeh Saheb Sharif‐Askari, Karim Dorgham, Jérôme Sallette, Souad Mehlal-Sedkaoui, Suzan A. AlKhater, Raül Rigo‐Bonnin, Francisco Morandeira, Lucie Roussel, Donald C. Vinh, Christian Erikstrup, Antônio Condino‐Neto, Carolina Prando, Анастасія Бондаренко, András N. Spaan, Laurent Gilardin, Jacques Fellay, Stanislas Lyonnet, Kaya Bilgüvar, Richard P. Lifton, Shrikant Mane, Mark S. Anderson, Bertrand Boisson, Vivien Béziat, Shen‐Ying Zhang, Evangelos Andreakos, Olivier Hermine, Aurora Pujol, Pärt Peterson, Trine H. Mogensen, Lee Rowen, James Mond, Stéphanie Debette, Xavier de-Lamballerie, Charles Burdet, Lila Bouadma, Marie Zins, Pere Soler‐Palacín, Roger Colobrán, Guy Gorochov, Xavier Solanich, Sophie Susen, Javier Martínez‐Picado, Didier Raoult, Marc Vasse, Peter K. Gregersen, Carlos Rodríguez‐Gallego, Lorenzo Piemonti, Luigi D. Notarangelo, Helen C. Su, Kai Kisand, Satoshi Okada, Anne Puel, Emmanuelle Jouanguy, Charles M. Rice, Pierre Tiberghien, Qian Zhang, Jean‐Laurent Casanova, Laurent Abel, Aurélie Cobat
Bibliographic record
VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsMcGill University Health CentreBC Children's HospitalUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesInstitut des maladies génétiques ImagineTartu ÜlikoolNational Institutes of HealthAgence Nationale de la RechercheSt. Giles Foundation
KeywordsAutoantibodyCoronavirus disease 2019 (COVID-19)ImmunologyMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakVirologyAntibodyInternal medicineDiseaseInfectious disease (medical specialty)
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.002
metaresearch head score (Gemma)0.006
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 score0.014
Threshold uncertainty score0.048
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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 head0.166
GPT teacher head0.516
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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
Citations24
Published2022
Admission routes1
Has abstractno