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

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

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

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of OttawaQueen's University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)HaematopoiesisLineage (genetic)BiologyPneumonia2019-20 coronavirus outbreakImmunologyPandemicMedicineVirologyGeneticsOutbreakStem cellInternal medicineDiseaseGeneInfectious disease (medical specialty)

Abstract

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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.

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)0.002
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 score0.261
Threshold uncertainty score0.520

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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".

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Citations1
Published2024
Admission routes2
Has abstractyes

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