Evidence map›Paper›PMID 42021271›Full record

ArticleJournal of translational medicine2026

Long COVID: Deep single-cell immunophenotyping and machine learning reveal a general signature for fatigue.

Silke Lauren Sommen, Sunniva Segtnan, Joel Selvakumar, Lise Beier Havdal, Tonje Stiansen-Sonerud, Johannes Gjerstad, Siri Mjaaland, Unni Cecilie Nygaard, Vegard Bruun Bratholm Wyller, Ratnadeep Mukherjee and 1 more

Abstract read
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Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Silke Lauren SommenDepartment of Pediatrics, Akershus University Hospital, Lørenskog, Norway.
Sunniva SegtnanUniversity of Oslo, Oslo, Norway.
Joel SelvakumarDepartment of Pediatrics, Akershus University Hospital, Lørenskog, Norway.
Lise Beier HavdalDepartment of Pediatrics, Akershus University Hospital, Lørenskog, Norway.
Tonje Stiansen-SonerudDepartment of Pediatrics, Akershus University Hospital, Lørenskog, Norway.
Johannes GjerstadDepartment of Research and Development in Mental Health, Akershus University Hospital, Lørenskog, Norway.
Siri MjaalandDivision of Infection Control, Norwegian Institute of Public Health, Lovisneberggata 8, Room 4361, Oslo, 0456, Norway.
Unni Cecilie NygaardDivision of Infection Control, Norwegian Institute of Public Health, Lovisneberggata 8, Room 4361, Oslo, 0456, Norway.
Vegard Bruun Bratholm WyllerDepartment of Pediatrics, Akershus University Hospital, Lørenskog, Norway.
Ratnadeep Mukherjee *Division of Infection Control, Norwegian Institute of Public Health, Lovisneberggata 8, Room 4361, Oslo, 0456, Norway. ratnadeep.mukherjee@fhi.no.ORCID 0000-0002-4874-4493
Lise Lund Berven *Department of Pediatrics, Akershus University Hospital, Lørenskog, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe post COVID-19 condition, commonly referred to as “Long COVID” (LC), is a constellation of long-lasting and debilitating symptoms following acute SARS-CoV-2 infection, which closely resembles other post-infective fatigue states. The underlying immunological disturbances of LC are poorly understood. Multiple explanatory mechanisms, such as persisting SARS-CoV-2 reservoirs, reactivation of latent viruses, endothelial dysfunction, auto-antibodies, tissue damage, and immune abnormalities, have been proposed but remain incompletely characterized, particularly in younger populations.

methodsThe present study included 12 to 25-year-old females with and without mild SARS-CoV-2 infection, who were prospectively followed for six months after infection and assessed according to the WHO definition of post COVID-19 condition, resulting in four groups (“Long COVID” (LC), recovered convalescents (RC), fatigued controls (FC), healthy controls (HC)). Peripheral blood mononuclear cells were either stimulated with Phorbol-12-myristate-13-acetate/ionomycin or left unstimulated, and analyzed using a 41-antibody CyTOF panel, unsupervised clustering with FlowSOM, dimensionality reduction via UMAP, polyfunctionality assessment with COMPASS, and machine learning for identifying correlates of LC and fatigue. All participants were female with a median age of 18.5 years.

resultsHigher frequencies of Terminal NK cells were associated with LC and FC, showing enhanced polyfunctional responses upon stimulation. Increased CD4 + T cell activation and exhaustion were observed in both LC and FC, with elevated effector memory and effector T cells expressing PD-1, alongside decreased marginal zone B cells and transitional B cells. Machine learning analysis revealed terminal NK cells as the most important feature for predicting fatigue. Importantly, no unique LC-specific immune changes were detected.

conclusionOur results point to a shared underlying pathophysiology in LC and other forms of fatigue. The absence of unique LC-related immune changes supports the notion that LC represents a specific example of post-infective fatigue syndrome triggered by SARS-CoV-2 in susceptible individuals. Innate and adaptive immune dysregulation, particularly higher levels of hyperresponsive terminal NK cells, is most striking and could serve as a general fatigue marker rather than an LC-specific biomarker. These findings highlight the need for further studies to correlate immune perturbations with symptom clusters and inform diagnostic and treatment strategies for fatigue states.

Indexed as

COVID-19FatigueImmunophenotypingMachine LearningSingle-Cell AnalysisAdolescentAdultCD4-Positive T-LymphocytesChildFemaleHumansKiller Cells, NaturalPost-Acute COVID-19 SyndromeSARS-CoV-2T-Cell ExhaustionYoung AdultAdolescentCyTOFFatigueImmunologyLong COVIDPost COVID-19 conditionPost-infective fatigue syndromeSARS-CoV-2

Identifiers

PMID42021271
PMCPMC13237906

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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.