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Background <p>Lower respiratory tract infections (LRTI), including pneumonia, tuberculosis, and COVID-19, share overlapping clinical features and risk factors, yet their common genetic architecture remains poorly understood.</p> Methods <p>We applied genomic structural equation modeling (Genomic SEM) to dissect the shared genetic susceptibility among seven LRTI-related phenotypes using large-scale GWAS summary statistics. Multivariate GWAS (mvGWAS) was performed to identify variants associated with the latent LRTI factor. Post-GWAS analyses included Bayesian fine-mapping, transcriptome-wide association studies, MAGMA analysis, pathway enrichment, and cell-type specific heritability partitioning.</p> Results <p>A single latent factor model demonstrated excellent fit, confirming substantial genetic overlap across LRTI phenotypes. The mvGWAS identified 5,469 genome-wide significant variants, including 3,705 associations uniquely identified at the latent-factor level. Fine-mapping prioritized high-confidence causal variants at CAMK2D, NFKB1, CNTN5 and PARK2 loci, implicating calcium signaling, NF-κB-mediated inflammation, neuroimmune regulation, and mitochondrial quality control. TWAS highlighted TLK2, NUDT6, and PKN2 as key transcriptional regulators involved in chromatin homeostasis and inflammasome modulation. MAGMA identified RPL18A, HLA-DRB1, HLA-DQB1, and PTPN6, underscoring roles of ribosomal function, antigen presentation, and immune cell signaling. Pathway analysis revealed enrichment in coagulation cascades, while cell type analysis suggested involvement of hematopoietic progenitors and myeloid lineages.</p> Conclusions <p>This study provides the first comprehensive genetic framework for shared LRTI susceptibility, revealing convergent biological pathways spanning inflammation, mitochondrial homeostasis, antigen presentation, and coagulation. These findings offer candidate targets for host-directed therapeutic strategies.</p>

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Decoding the shared genetic liability of lower respiratory tract infections via genomic structural equation modeling

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月7日

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  • Ying Lei,
  • Jin Li,
  • Jia Xie,
  • Tao Wang

摘要

Background

Lower respiratory tract infections (LRTI), including pneumonia, tuberculosis, and COVID-19, share overlapping clinical features and risk factors, yet their common genetic architecture remains poorly understood.

Methods

We applied genomic structural equation modeling (Genomic SEM) to dissect the shared genetic susceptibility among seven LRTI-related phenotypes using large-scale GWAS summary statistics. Multivariate GWAS (mvGWAS) was performed to identify variants associated with the latent LRTI factor. Post-GWAS analyses included Bayesian fine-mapping, transcriptome-wide association studies, MAGMA analysis, pathway enrichment, and cell-type specific heritability partitioning.

Results

A single latent factor model demonstrated excellent fit, confirming substantial genetic overlap across LRTI phenotypes. The mvGWAS identified 5,469 genome-wide significant variants, including 3,705 associations uniquely identified at the latent-factor level. Fine-mapping prioritized high-confidence causal variants at CAMK2D, NFKB1, CNTN5 and PARK2 loci, implicating calcium signaling, NF-κB-mediated inflammation, neuroimmune regulation, and mitochondrial quality control. TWAS highlighted TLK2, NUDT6, and PKN2 as key transcriptional regulators involved in chromatin homeostasis and inflammasome modulation. MAGMA identified RPL18A, HLA-DRB1, HLA-DQB1, and PTPN6, underscoring roles of ribosomal function, antigen presentation, and immune cell signaling. Pathway analysis revealed enrichment in coagulation cascades, while cell type analysis suggested involvement of hematopoietic progenitors and myeloid lineages.

Conclusions

This study provides the first comprehensive genetic framework for shared LRTI susceptibility, revealing convergent biological pathways spanning inflammation, mitochondrial homeostasis, antigen presentation, and coagulation. These findings offer candidate targets for host-directed therapeutic strategies.