Evidence map›Paper›PMID 41463538›Full record

ArticleBiology2025

Single-Cell Mapping of Genetic Risk Across Ten Respiratory Diseases.

Miao Zhou, Chao Xue

Abstract read
In one paragraph

Article in Biology, 2025. 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

2 authors.

Miao ZhouMedical College, Jiaying University, Meizhou 514031, China.
Chao XueMedical College, Jiaying University, Meizhou 514031, China.ORCID 0000-0003-3481-4224

Funding

National Natural Science Foundation of China 32300500Talent Start-up Foundation of JiaYing University 323E0461
6 · The paper itself

Abstract

Understanding how genetic risk variants contribute to respiratory diseases requires mapping genome-wide association study (GWAS) signals to disease-relevant cell types and states within the human lung. Here, we integrated GWAS summary statistics for ten major respiratory diseases, including asthma, COPD, idiopathic pulmonary fibrosis (IPF), COVID-19, and lung cancer, using a large-scale single-cell transcriptomic dataset of more than 523,000 cells from the Human Lung Cell Atlas. Applying the single-cell Disease Relevance Score (scDRS) framework, we systematically identified shared and disease-specific cellular associations across four major compartments, namely epithelial, immune, endothelial, and stromal. We found that alveolar type II (AT2) cells represent a central susceptibility hub for asthma, COPD, and COVID-19, whereas disease-specific risk enrichment was observed in subpopulations such as CCL3

Indexed as

alveolar cellsgenetic susceptibilityGWASimmune heterogeneitylungrespiratory diseasessingle-cell transcriptomics

Identifiers

PMID41463538
PMCPMC12731109

What OpenQuestion holds

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Registered trials

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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.