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Enregistrement W4405041543 · doi:10.1182/blood-2024-203228

Associations of Lineage-Specific Clonal Hematopoiesis with COVID-19 Hospitalization and Mortality

2024· article· en· W4405041543 sur OpenAlexaffabout
Yasmeen Choudhri, Olivia Lopes, Caitlyn Vlasschaert, David M. Maslove, Michael J. Rauh

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueHemoglobinopathies and Related Disorders
Établissements canadiensUniversity of OttawaQueen's University
Organismes subventionnairesnon disponible
Mots-clésCoronavirus disease 2019 (COVID-19)HaematopoiesisLineage (genetic)BiologyPneumonia2019-20 coronavirus outbreakImmunologyPandemicMedicineVirologyGeneticsOutbreakStem cellInternal medicineDiseaseGeneInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

Introduction: Somatic variants indicative of clonal hematopoiesis (CH) are known to increase risks of prevalent inflammatory diseases, hematologic malignancies, and mortality. In recent years, the relevance of CH to COVID-19 has been controversial, with conflicting reports of the association between myeloid clonal hematopoiesis (M-CH) variants and COVID-19 severity. Furthermore, the prevalence of CH variants in lymphoid driver genes (L-CH) has not been investigated in COVID-19 thus far. This study reports prevalences of both M-CH and L-CH in a large Canadian COVID-19 cohort and explores associations with disease severity. Methods: CH variants were detected from whole-genome sequences of 6651 patients with COVID-19 enrolled in the CGEn HostSeq initiative (CGEn- Canada's national platform for genome sequencing and analysis) between 01/2020 and 10/2022. The median age of the cohort was 50 years (range 20-103 years) and 57.9% (n=3851) were female. Patients with a prior diagnosis of leukemia were excluded from these analyses. Variant calling was performed using Mutect2, following a pre-defined list of putative variants in 144 genes associated with myeloid and/or lymphoid malignancies. Additional filters were applied to exclude germline variants and probable sequencing artifacts. Associations of CH with clinical severity status and hematologic laboratory parameters were determined using regression analyses adjusted for age and sex. Results: The total prevalence of CH was 6.6% (n=441/6651). Most patients had M-CH exclusively (81.4%, n=359), though others had L-CH (12.2%, n=54), or both M-CH and L-CH (6.3%, n=28). 456 M-CH variants were found, and were most frequent in DNMT3A (n=125) and TET2 (n=96). Among 88 identified L-CH variants, those in KMT2C were most common (n=20), followed by KMT2D (n=18) and SPEN (n=10). Disease severity status was defined for a subset of 5890 patients as: ambulatory (n=3927), hospitalized with mild disease (with or without oxygen by mask or nasal prongs; n=1180), hospitalized with severe disease (requiring intubation, mechanical ventilation, high-flow oxygen, or other organ support; n=499), or death (n=284). CH was significantly more prevalent among patients hospitalized with mild disease compared to the ambulatory group (odds ratio [OR]=1.70, 95% confidence interval [CI]=1.29-2.25, p=0.0002). This association remained significant when restricting the analyses to patients with M-CH (OR=1.50, 95% CI=1.11-2.01, p=0.007) and L-CH (OR=3.38, 95% CI=1.78-6.40, p=0.0002). Laboratory results of 942 patients hospitalized with mild COVID-19 showed that CH and M-CH were associated with lower hemoglobin (β=-4.97, 95% CI=-8.50- -1.45, p=0.006 and β=-6.02, 95% CI=-9.74- -2.29, p=0.002); and L-CH was associated with increased white blood cell count (β=1.8, 95% CI=0.08-3.43, p=0.04). Differences in CH status between patients with severe versus mild disease were not statistically significant (OR=0.78, 95% CI=0.54-1.13, p=0.18). Notably, L-CH alone was significantly overrepresented among patients with COVID-19-related mortality when compared to the ambulatory group (OR=4.22, 95% CI=1.39-12.78, p=0.01). Conclusions: This study demonstrates an association of CH with COVID-19 hospitalization, and introduces L-CH as a potentially important prognostic factor of the disease. These results support earlier suggestions that antiviral responses may be altered in the presence of CH, including possible influence on the inflammatory cascade that is thought to drive worse outcomes. No associations were found between CH and the need for advanced respiratory support, suggesting that the progression from mild to severe disease may be affected by other biological or clinical factors. This work highlights lineage-specific variants and disease severity status as important considerations in the relationship between CH and COVID-19. These findings may carry relevance for ongoing work looking at CH in the context of other infectious diseases.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,261
Score d'incertitude au seuil0,520

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,282
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2024
Routes d'admission2
Résumé présentoui

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