Evidence map›Paper›PMID 41757169›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Early Fc-effector antibody signatures impact COVID-19 disease trajectory.

Alba Escalera, Ana S Gonzalez-Reiche, Sadaf Aslam, Enrique Bernal, Galit Alter, Amaya Rojo-Fernandez, Alexander Rombauts, Gabriela Abelenda-Alonso, Mary Anne Amper, Venugopalan D Nair and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Alba EscaleraDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0003-0061-0768
Ana S Gonzalez-ReicheDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0003-3583-4497
Sadaf AslamDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Enrique BernalInstituto Murciano de Investigación Biosanitaria, Universidad de Murcia, Hospital General Universitario Reina Sofía, 30003 Murcia, Spain.
Galit AlterThe Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA.
Amaya Rojo-FernandezDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Alexander RombautsDepartment of Infectious Diseases, Bellvitge University Hospital, 08907 L'Hospitalet de Llobregat, Spain.
Gabriela Abelenda-AlonsoDepartment of Infectious Diseases, Bellvitge University Hospital, 08907 L'Hospitalet de Llobregat, Spain.
Mary Anne AmperDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Venugopalan D NairDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Harm van BakelDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0002-1376-6916
Jordi CarratalàDepartment of Infectious Diseases, Bellvitge University Hospital, 08907 L'Hospitalet de Llobregat, Spain.
Adolfo García-SastreDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Teresa AydilloDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0003-3086-1058

Funding

NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00014 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GARCIA-SASTRE, ADOLFO · 2021 to 2025
$62.6M
SARS-CoV adaptations through a Systems Biology Lens (SYBIL)U19AI135972 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Adolfo Garcia-Sastre · 2018 to 2026
$27.2M
Viral Immunity and VAccination (VIVA) Human Immunology Project Consortium (HIPC)U19AI168631 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Ana Fernandez-Sesma · 2022 to 2026
$14.4M
NIAID NIH HHS U19 AI135972NIAID NIH HHS U19 AI168631NIH HHS 75N93021C00014
6 · The paper itself

Abstract

Why do some individuals develop mild COVID-19 while others progress to severe disease remains a central challenge in SARS-CoV-2 immunology. In this study, we leveraged the BACO Cohort - a unique historical cohort of immunologically naïve, hospitalized COVID-19 patients from the first pandemic wave - to investigate early immune determinants of clinical disease trajectories. Integrating bulk RNA-seq, Olink proteomics, and systems serology, we identified two fundamentally distinct immune trajectories according to disease phenotypes. Severe patients exhibited upregulation of proinflammatory genes and monocyte-associated transcripts, alongside downregulation of genes related to T cell responses and immune signaling. Notably, an upregulation of inhibitory Fc-receptor-associated gene was also found in severe cases. In contrast, mild cases showed coordinated lymphoid activation and limited inflammation. Building on these findings, we performed a functional profiling of Fc-effector activity in the polyclonal serum of the patients and found that monocyte-mediated phagocytosis was a common feature of mild disease. Interestingly, this response was mainly driven by rapid induction of S1-specific antibodies. Conversely, severe patients tended to generate higher levels of S2-biased antibodies early after infection with poor Fc-effector functionality. Together, these findings demonstrate that early S1-directed, Fc-competent humoral immunity is a key determinant of favorable COVID-19 outcomes, while delayed functional maturation and early S2 bias characterized severe disease in the BACO cohort.

Identifiers

PMID41757169
PMCPMC12934865

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.