Genetic Pleiotropy and Causal Pathways Linking Glycemic Traits to Asthma: An Integrated Proteogenomic Investigation

<b>Background:</b> While diabetes is a recognized risk factor for asthma, the shared genetic components between diabetes/glycemic traits and asthma remain unclear. This study investigates the genetic associations, causal relationships, and underlying mechanisms linking these conditions. <b>Methods:</b> We assessed global genetic correlations using linkage disequilibrium score regression (LDSC), high-definition likelihood analysis (HDL), and genetic covariance analysis (GNOVA). Trait pairs with significant correlations subsequently underwent genetic overlap analysis (Genetic analysis integrating Pleiotropy and functional Annotation, GPA) and local genetic correlation analysis (Local Genetic Variant Association Analysis, LAVA). Cross-phenotype association (CPASSOC) and multitrait analysis of GWAS (MTAG) identified potential pleiotropic loci, followed by colocalization and functional annotation. Proteome-wide association study (PWAS) revealed proteins and pathways shared between diabetes/glycemic traits and asthma. Generalized summary-data-based Mendelian randomization (GSMR) was used to evaluate causal effects between diabetes/glycemic traits and asthma. <b>Results:</b> Significant genetic correlations were observed between body mass index (BMI) and asthma (rg = 0.280-0.397; FDR < 0.05), type 2 diabetes mellitus (T2DM) and asthma (rg = 0.240-0.289; FDR < 0.05) across all three methods. GPA revealed significant genome-wide genetic overlap, highest for BMI and asthma (pleiotropy association ratio [PAR] = 0.377) and T2DM-asthma (PAR = 0.353). LAVA identified 111 significant local correlation regions, predominantly between T2DM and asthma (70 regions). Colocalization analysis identified 24 shared pleiotropic loci, predominantly on chromosome 8. Local genetic correlation analysis revealed extensive correlations between T2DM and asthma. PWAS identified 46 shared proteins, with IL6R, MAPK3, and CSF2 being key hubs. Protein-protein interaction analysis highlighted enrichment in JAK-STAT signaling, Th1/Th2 differentiation, and IL-17 pathways. GSMR demonstrated causal effects of BMI (OR = 1.47, 95% CI: 1.42-1.53, FDR < 0.05) and T2DM (OR = 1.06, 95% CI: 1.04-1.08, FDR < 0.05) on increased asthma risk, with no evidence of reverse causality. <b>Conclusions:</b> Obesity (BMI) and T2DM exert causal effects on asthma risk via shared genetic loci and inflammatory pathways, particularly involving IL6R, MAPK3, CSF2, and JAK-STAT signaling. Targeting these colocalized proteins may offer potential therapeutic strategies.

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Journal
Children
Published
2025-10-24
DOI
https://doi.org/10.3390/children12111443
Primary Topic
Genetic Associations and Epidemiology
Type
article
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0.00
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article

Genetic Pleiotropy and Causal Pathways Linking Glycemic Traits to Asthma: An Integrated Proteogenomic Investigation

Jun‐Tao Lin, Chunlan Qiu, Ke Peng, Lin Chen et al.
Children
Genetic Associations and Epidemiology
article

Genetic Pleiotropy and Causal Pathways Linking Glycemic Traits to Asthma: An Integrated Proteogenomic Investigation

Jun‐Tao Lin, Chunlan Qiu, Ke Peng, Lin Chen, Hui Liu, Zhengxiu Luo, Yan Zhao, Zhenxuan Kong, Guangli Zhang
article en

Abstract

<b>Background:</b> While diabetes is a recognized risk factor for asthma, the shared genetic components between diabetes/glycemic traits and asthma remain unclear. This study investigates the genetic associations, causal relationships, and underlying mechanisms linking these conditions. <b>Methods:</b> We assessed global genetic correlations using linkage disequilibrium score regression (LDSC), high-definition likelihood analysis (HDL), and genetic covariance analysis (GNOVA). Trait pairs with significant correlations subsequently underwent genetic overlap analysis (Genetic analysis integrating Pleiotropy and functional Annotation, GPA) and local genetic correlation analysis (Local Genetic Variant Association Analysis, LAVA). Cross-phenotype association (CPASSOC) and multitrait analysis of GWAS (MTAG) identified potential pleiotropic loci, followed by colocalization and functional annotation. Proteome-wide association study (PWAS) revealed proteins and pathways shared between diabetes/glycemic traits and asthma. Generalized summary-data-based Mendelian randomization (GSMR) was used to evaluate causal effects between diabetes/glycemic traits and asthma. <b>Results:</b> Significant genetic correlations were observed between body mass index (BMI) and asthma (rg = 0.280-0.397; FDR < 0.05), type 2 diabetes mellitus (T2DM) and asthma (rg = 0.240-0.289; FDR < 0.05) across all three methods. GPA revealed significant genome-wide genetic overlap, highest for BMI and asthma (pleiotropy association ratio [PAR] = 0.377) and T2DM-asthma (PAR = 0.353). LAVA identified 111 significant local correlation regions, predominantly between T2DM and asthma (70 regions). Colocalization analysis identified 24 shared pleiotropic loci, predominantly on chromosome 8. Local genetic correlation analysis revealed extensive correlations between T2DM and asthma. PWAS identified 46 shared proteins, with IL6R, MAPK3, and CSF2 being key hubs. Protein-protein interaction analysis highlighted enrichment in JAK-STAT signaling, Th1/Th2 differentiation, and IL-17 pathways. GSMR demonstrated causal effects of BMI (OR = 1.47, 95% CI: 1.42-1.53, FDR < 0.05) and T2DM (OR = 1.06, 95% CI: 1.04-1.08, FDR < 0.05) on increased asthma risk, with no evidence of reverse causality. <b>Conclusions:</b> Obesity (BMI) and T2DM exert causal effects on asthma risk via shared genetic loci and inflammatory pathways, particularly involving IL6R, MAPK3, CSF2, and JAK-STAT signaling. Targeting these colocalized proteins may offer potential therapeutic strategies.

ChildrenVol. 12(11)
Children's Hospital of Chongqing Medical University (CN), Chongqing Medical University (CN)
Openalex Percentile: Top 67%
Genetic Associations and Epidemiology
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