Evidence map›Paper›PMID 42111219›Full record

ArticleiScience2026

Causal and shared genetic insights into severe COVID-19 and idiopathic pulmonary fibrosis.

Shan Lin, Xin Dang, Xiaofeng Kou, Xianyue Zhang, Xuefeng Ding, Xiao Li

Abstract read
In one paragraph

Article in iScience, 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

6 authors.

Shan LinDepartment of Respiratory and Critical Care Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Xin DangDepartment of Respiratory and Critical Care Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Xiaofeng KouDepartment of Respiratory and Critical Care Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Xianyue ZhangDepartment of Respiratory and Critical Care Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Xuefeng DingDepartment of Critical Care Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
Xiao LiDepartment of Respiratory and Critical Care Medicine, People's Hospital of Yuxi City, Yuxi, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the immediate threat of COVID-19 has lessened, survivors of severe disease still face long-term risks. Utilizing publicly available GWAS summary statistics, we conducted PheWAS enrichment across 2,142 phenotypes to ascertain the traits linked to severe COVID-19. Subsequently, we conducted genome-wide cross-trait analyses to explore genetic correlations, pleiotropic loci, and functional annotations. Mendelian randomization (MR) was employed to deduce causality. Idiopathic pulmonary fibrosis (IPF) emerged as a phenotype significantly linked to severe COVID-19 after false discovery rate correction. We identified substantial genetic correlations and 14 shared pleiotropic loci between severe COVID-19 and IPF, encompassing five additional loci that validated nine variants, notably rs34517439. MR and CAUSE analyses substantiated the causal impact of genetic predisposition on IPF in individuals with severe COVID-19. These findings demonstrate a genetic overlap and a causal relationship between IPF and severe COVID-19, enhancing comprehension of the mechanisms and guiding risk stratification and prevention strategies.

Indexed as

Health sciencesMedical microbiologyMedicineRespiratory medicineVirology

Identifiers

PMID42111219
PMCPMC13156648

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.