This meta-analysis examined genetic architecture in six biobanks to understand chronic rhinosinusitis (CRS) and nasal polyps (CRSwNP). Researchers employed comparative genomic analysis, genome-wide association meta-analyses, gene-prioritization strategies, pathway enrichment analyses, single-cell transcriptomic data, stratified LD score regression, and comparative genetic analyses. Additionally, proteome-wide Mendelian methods were used to identify circulating proteins. The study population comprised data from these six biobanks, though specific sample size details were not reported in the provided text.
Analysis revealed 96 genome-wide significant loci for CRSwNP and 41 loci for overall CRS. For CRSwNP, 92 candidate genes were prioritized, while 39 were prioritized for overall CRS. A genetic correlation analysis indicated shared genetic susceptibility between CRSwNP and overall CRS, with an effect size of rg = 0.59 and a P value of 6.8e-16. Heritability enrichment analysis showed that immune annotations explained more heritability than epithelial annotations for CRSwNP, with an enrichment score of 4.1 (P = 0.010). Conversely, epithelial annotations had an enrichment score of 2.5 (P = 0.072). Finally, 10 putatively causal circulating proteins were identified for CRSwNP and 8 for overall CRS.
Safety data, adverse events, and discontinuations were not reported. The study design is observational and genetic; therefore, these findings describe associations and biological mechanisms rather than therapeutic efficacy. Limitations include the lack of reported sample size and the inherent inability of genetic association studies to prove causality for clinical treatment. These results inform biological understanding but do not yet support specific clinical management changes for CRS or CRSwNP.
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Background Chronic rhinosinusitis (CRS) and nasal polyps (NP) are closely related inflammatory airway diseases, and their co-occurrence is often associated with more persistent symptoms, frequent recurrence, and substantial respiratory morbidity. However, the extent to which CRS without and with NP (CRSsNP and CRSwNP) share genetic susceptibility-and which genetic mechanisms are disease-specific-remains poorly characterized. Methods We conducted cross-population genome-wide association meta-analyses of overall CRS (including both CRSwNP and CRSsNP) and NP (a proxy for CRSwNP) using data from six biobanks. We estimated genome-wide genetic correlations between overall CRS, CRSwNP, and a spectrum of respiratory diseases. We applied five complementary gene-prioritization strategies to nominate CRS- and CRSwNP-associated genes and performed pathway enrichment analyses to infer implicated biological processes. For CRSwNP, we integrated single-cell transcriptomic data to characterize cell-type-specific expression of prioritized genes and used stratified LD score regression to quantify heritability enrichment across immune and epithelial annotations. To delineate shared versus disease-specific genetic signals, we performed three comparative analyses-local genetic correlation, CRSwNP-CRS colocalization, and genomic structural equation modeling. Finally, we performed proteome-wide Mendelian randomization to identify circulating proteins with putative causal effects on CRS and CRSwNP. Results This GWAS meta-analysis identified 96 genome-wide significant loci for CRSwNP and 41 for overall CRS, prioritizing 92 and 39 candidate genes, respectively. CRSwNP and overall CRS showed shared genetic susceptibility (rg = 0.59; P = 6.8e-16), while CRS exhibited broader genetic correlations across multiple respiratory disorders. Pathway analyses consistently implicated immune signaling albeit with disease-specific emphases and lipid-metabolism networks. Single-cell analyses demonstrated distinct expression of CRSwNP-prioritized genes across nasal epithelial and immune cell clusters, and immune annotations explained more CRSwNP heritability (enrichment score = 4.1; P = 0.010) than epithelial annotations (2.5; P = 0.072). Comparative genetic analyses highlighted multiple shared loci-including BACH2, CD247, FADS2, FOXP1, FUT2, GPX4, IL7R, NDFIP1, RAB5B, RORA, SMAD3, TSLP - as well as 3 CRSwNP-specific and 6 CRS-specific loci. Proteome-wide MR identified 10 and 8 putatively causal circulating proteins for CRSwNP and overall CRS, respectively, with protein TNFSF11, IL2RB, and STX4 associated with both conditions. Conclusions This multi-population GWAS meta-analysis expanded genetic discovery for CRS and CRSwNP and showed substantial shared liability with distinct disease-specific components. Immune components explained a larger proportion of CRSwNP heritability than epithelial annotations, reinforcing the primacy of immune-driven mechanisms in polyp disease.
