Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders
Abstract Background The intricate shared genetic architecture underlying allergic disorders—including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis—remains incompletely characterized....
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BMC
2025-04-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06465-8 |
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| author | Jingsheng Ruan Xinglin Yi |
| author_facet | Jingsheng Ruan Xinglin Yi |
| author_sort | Jingsheng Ruan |
| collection | DOAJ |
| description | Abstract Background The intricate shared genetic architecture underlying allergic disorders—including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis—remains incompletely characterized. Methods Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders. Results A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p < 5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers. Conclusion Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions. |
| format | Article |
| id | doaj-art-2f74de9a4996401fab4c24d57b7ba2bb |
| institution | OA Journals |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-2f74de9a4996401fab4c24d57b7ba2bb2025-08-20T02:28:11ZengBMCJournal of Translational Medicine1479-58762025-04-0123111610.1186/s12967-025-06465-8Genomic structural equation modeling elucidates the shared genetic architecture of allergic disordersJingsheng Ruan0Xinglin Yi1Department of Thoracic, Jinshan Hospital of Fudan University, Fudan UniversityDepartment of Respiratory and Critical Care Medicine, Third Military Medical UniversityAbstract Background The intricate shared genetic architecture underlying allergic disorders—including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis—remains incompletely characterized. Methods Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders. Results A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p < 5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers. Conclusion Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions.https://doi.org/10.1186/s12967-025-06465-8Genomic SEMAllergic disordersFAM114 A1Rs145982144Rs78017269 |
| spellingShingle | Jingsheng Ruan Xinglin Yi Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders Journal of Translational Medicine Genomic SEM Allergic disorders FAM114 A1 Rs145982144 Rs78017269 |
| title | Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders |
| title_full | Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders |
| title_fullStr | Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders |
| title_full_unstemmed | Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders |
| title_short | Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders |
| title_sort | genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders |
| topic | Genomic SEM Allergic disorders FAM114 A1 Rs145982144 Rs78017269 |
| url | https://doi.org/10.1186/s12967-025-06465-8 |
| work_keys_str_mv | AT jingshengruan genomicstructuralequationmodelingelucidatesthesharedgeneticarchitectureofallergicdisorders AT xinglinyi genomicstructuralequationmodelingelucidatesthesharedgeneticarchitectureofallergicdisorders |