Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders DOI Creative Commons

J Ibáñez Ruán,

Xinglin Yi

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: April 15, 2025

The intricate shared genetic architecture underlying allergic disorders-including asthma, atopic dermatitis, contact rhinitis, conjunctivitis, urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized. Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing of disorders. Coupled with diverse post-GWAS analytical methods, we aimed discover susceptible loci investigate associations external traits. Furthermore, explored enriched pathways, cellular layers, elements, investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted assess chromosomal-level for A well-fitted SEM revealing We identified a total 2038 genome-wide significant SNP (p < 5e-8), including 31 previously unreported loci. Fine-mapping variants gene sets pinpointed 2 causal candidate genes. Genetic correlation analyses further illuminated multiple traits, notably psychiatric Preliminary findings four Notably, this presents first comprehensive characterization disorders through analysis an unmeasured composite phenotype, providing novel insights into etiological pathways across these conditions.

Language: Английский

Genomic Structural Equation Modeling Elucidates the Shared Genetic Architecture of Allergic Disorders DOI Creative Commons

J Ibáñez Ruán,

Xinglin Yi

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Abstract Background The intricate shared genetic architecture underlying allergic disorders—including asthma, atopic dermatitis, contact rhinitis, conjunctivitis, urticaria, anaphylaxis, and eosinophilic esophagitis—remains incompletely characterized. Methods Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing of disorders. Coupled with diverse post-GWAS analytical methods, we aimed discover susceptible loci investigate associations external traits. Furthermore, explored enriched pathways, cellular layers, elements, investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted assess chromosomal-level for Results A well-fitted SEM revealing We identified a total 2038 genome-wide significant SNP (p < 5e-8), including 31 previously unreported loci. Fine-mapping variants gene sets pinpointed 2 causal candidate genes. Genetic correlation analyses further illuminated multiple traits, notably psychiatric Preliminary findings four Conclusion Notably, this presents first comprehensive characterization disorders through analysis an unmeasured composite phenotype, providing novel insights into etiological pathways across these conditions.

Language: Английский

Citations

0
Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders DOI Creative Commons

J Ibáñez Ruán,

Xinglin Yi

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: April 15, 2025

The intricate shared genetic architecture underlying allergic disorders-including asthma, atopic dermatitis, contact rhinitis, conjunctivitis, urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized. Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing of disorders. Coupled with diverse post-GWAS analytical methods, we aimed discover susceptible loci investigate associations external traits. Furthermore, explored enriched pathways, cellular layers, elements, investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted assess chromosomal-level for A well-fitted SEM revealing We identified a total 2038 genome-wide significant SNP (p < 5e-8), including 31 previously unreported loci. Fine-mapping variants gene sets pinpointed 2 causal candidate genes. Genetic correlation analyses further illuminated multiple traits, notably psychiatric Preliminary findings four Notably, this presents first comprehensive characterization disorders through analysis an unmeasured composite phenotype, providing novel insights into etiological pathways across these conditions.

Language: Английский

Citations

0