Disentangling Shared and Differential Genetic Architectures Between COVID-19 and Other Respiratory Disorders—A Genome-Wide Multi-Omics Framework

A bidirectional relationship has been observed between COVID-19 and respiratory disorders, where respiratory comorbidities increase severity, and COVID-19 induces respiratory sequelae. The underlying biological and genetic mechanisms remain unclear. While previous studies have identified overlapping genetic loci, few have systematically disentangled the genetic factors shared between these conditions versus those specific to COVID-19, particularly at a multi-omics level. We developed and applied a unified analytical framework to compare three COVID-19 phenotypes with eight respiratory disorders (including asthma, COPD, IPF, and pneumonia). Utilizing the cofdr method for shared genetic signal analysis and DDx/mtCOJO for differentiation, we integrated genome-wide association statistics with multi-omics data (transcriptome, splicing, and proteome). This approach allowed for the simultaneous identification of shared genetic signals (concordant or discordant) and disease-specific variants across expression (TWAS), alternative splicing (spTWAS), and protein abundance (PWAS). We delineated a comprehensive atlas of 214 differential and numerous shared loci across 24 pairwise comparisons. The shared genetic architecture was characterized by pleiotropic effects in genes such as ATP11A (exhibiting opposing effects in COVID-19 vs. IPF) and GSDMB (shared with COPD). Crucially, differentiation analysis revealed that severe COVID-19 is genetically distinct from other respiratory infections (e.g., pneumonia and influenza) through dysregulated Type I/III interferon signaling and specific defects in alveolar epithelial and macrophage function, as well as GM-CSF/surfactant metabolism pathways. These findings provide human genetic evidence consistent with the therapeutic rationale underlying GM-CSF modulators and interferon-lambda for COVID-19, both of which have entered clinical trials. Furthermore, multi-trait conditional analysis prioritized FYCO1 and HCN3 as potential COVID-19-specific risk genes. Splicing analysis underscored the critical role of alternative splicing in both shared and differential architectures, highlighting IFNAR2 isoform regulation as a key discriminator between COVID-19 and other respiratory traits. This study provides the first genome-wide, multi-omics map revealing the shared and differential genetic landscapes of COVID-19 and other respiratory phenotypes. By uncovering specific molecular mechanisms that distinguish COVID-19 pathology, specifically involving surfactant homeostasis and interferon pathways, our findings offer novel insights for targeted drug repurposing and precision risk stratification.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2026-07-22
DOI
https://doi.org/10.3390/ijms27146536
Primary Topic
COVID-19 Clinical Research Studies
Type
article
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article

Disentangling Shared and Differential Genetic Architectures Between COVID-19 and Other Respiratory Disorders—A Genome-Wide Multi-Omics Framework

Hon‐Cheong So, Yuping Lin, Xue Xiao, Yaning Feng
International Journal of Molecular Sciences
COVID-19 Clinical Research Studies
article

Disentangling Shared and Differential Genetic Architectures Between COVID-19 and Other Respiratory Disorders—A Genome-Wide Multi-Omics Framework

Hon‐Cheong So, Yuping Lin, Xue Xiao, Yaning Feng
article en

Abstract

A bidirectional relationship has been observed between COVID-19 and respiratory disorders, where respiratory comorbidities increase severity, and COVID-19 induces respiratory sequelae. The underlying biological and genetic mechanisms remain unclear. While previous studies have identified overlapping genetic loci, few have systematically disentangled the genetic factors shared between these conditions versus those specific to COVID-19, particularly at a multi-omics level. We developed and applied a unified analytical framework to compare three COVID-19 phenotypes with eight respiratory disorders (including asthma, COPD, IPF, and pneumonia). Utilizing the cofdr method for shared genetic signal analysis and DDx/mtCOJO for differentiation, we integrated genome-wide association statistics with multi-omics data (transcriptome, splicing, and proteome). This approach allowed for the simultaneous identification of shared genetic signals (concordant or discordant) and disease-specific variants across expression (TWAS), alternative splicing (spTWAS), and protein abundance (PWAS). We delineated a comprehensive atlas of 214 differential and numerous shared loci across 24 pairwise comparisons. The shared genetic architecture was characterized by pleiotropic effects in genes such as ATP11A (exhibiting opposing effects in COVID-19 vs. IPF) and GSDMB (shared with COPD). Crucially, differentiation analysis revealed that severe COVID-19 is genetically distinct from other respiratory infections (e.g., pneumonia and influenza) through dysregulated Type I/III interferon signaling and specific defects in alveolar epithelial and macrophage function, as well as GM-CSF/surfactant metabolism pathways. These findings provide human genetic evidence consistent with the therapeutic rationale underlying GM-CSF modulators and interferon-lambda for COVID-19, both of which have entered clinical trials. Furthermore, multi-trait conditional analysis prioritized FYCO1 and HCN3 as potential COVID-19-specific risk genes. Splicing analysis underscored the critical role of alternative splicing in both shared and differential architectures, highlighting IFNAR2 isoform regulation as a key discriminator between COVID-19 and other respiratory traits. This study provides the first genome-wide, multi-omics map revealing the shared and differential genetic landscapes of COVID-19 and other respiratory phenotypes. By uncovering specific molecular mechanisms that distinguish COVID-19 pathology, specifically involving surfactant homeostasis and interferon pathways, our findings offer novel insights for targeted drug repurposing and precision risk stratification.

International Journal of Molecular SciencesVol. 27(14)
Zhejiang Chinese Medical University (CN), Chinese University of Hong Kong (HK), Kunming Institute of Zoology (CN), Chinese Academy of Sciences (CN), City University of Hong Kong, Shenzhen Research Institute (CN), University of Hong Kong (HK)
Good health and well-being
Openalex Percentile: Top 8%
COVID-19 Clinical Research Studies
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