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Record W4406628138 · doi:10.1136/bmjresp-2024-002725

Role of IPF genetic risk loci in post-COVID-19 lung abnormalities: a cohort study

2025· article· en· W4406628138 on OpenAlexafffund
Daniel-Costin Marinescu, Alyson W. Wong, Aditi Shah, Cameron Hague, Darra Murphy, Julia Yang, James C. Johnston, Janice Ching Nam Leung, Christopher Carlsten, Christopher J. Ryerson

Bibliographic record

VenueBMJ Open Respiratory Research · 2025
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaMichael Smith Health Research BC
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Cohort2019-20 coronavirus outbreakLungSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Cohort studyVirologyGeneticsInternal medicineBiologyOutbreakDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Introduction Persistent lung abnormalities following COVID-19 infection are common. Similar parenchymal changes are observed in idiopathic pulmonary fibrosis (IPF). We investigated whether common genetic risk factors in IPF are associated with developing lung parenchymal abnormalities following severe COVID-19 disease. Methods Consecutive adults hospitalised for laboratory-confirmed COVID-19 infection were prospectively recruited from March to May 2020. Three single-nucleotide polymorphisms (SNPs) conferring risk for IPF were genotyped ( MUC5B rs35705950 , ATP11A rs1278769 and DPP9 rs12610495). High-resolution CT and pulmonary function tests were performed at 3 months postdischarge from hospital. Ground glass opacities and reticulation on imaging were visually quantified by two expert thoracic radiologists. Linear regression was used to evaluate the association between risk alleles at each of the three SNPs and (a) lung parenchymal abnormalities as well as (b) pulmonary function, adjusted for age, sex, smoking history and days spent on supplemental oxygen during acute illness. Results 71 patients were included. Mean age was 63±16 years, 62% were male, 31% were ever-smokers and median hospital length of stay was 9±11 days, with 23% requiring mechanical ventilation. The MUC5B risk allele was associated with a significant decrease in ground glass (β=−0.8, 95% CI −1.5 to –0.1, p=0.02) at 3 months, and this finding was paralleled by a concurrent but non-significant trend towards increased diffusion capacity for carbon monoxide (DLCO) (β=8.8, 95% CI −1.2 to 18.8, p=0.08) compared with patients without this risk allele. None of the risk alleles were significantly associated with reticulation at 3 months. Conclusion In an adjusted analysis controlling for severity of infection, MUC5B was associated with reduced ground glass and a trend towards concordant higher DLCO at 3 months after severe COVID-19 illness. This hypothesis-generating result suggests a possible protective effect of MUC5B in postinfectious lung abnormalities as compared with fibrosis in IPF, highlighting a plausible trade-off between its role in immune defence and epithelial cell function.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.034
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.463
Teacher spread0.398 · 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 teacher head, 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

Citations1
Published2025
Admission routes2
Has abstractyes

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