Association Analysis of Depression and Asthma

This study integrates retrospective studies, observational studies and Mendelian randomization (MR) to systematically analyze the association strength between depression and asthma. Retrospective studies provide a basis via Meta-analysis of published data. Prospective observational studies verify conclusions and clarify net association by adjusting confounders. MR infers causal links using GWAS-derived SNPs as instruments, with IVW and tests ensuring reliability. This framework clarifies real association strength and causality, supporting comorbidity research.

This study aims to explore the potential causal relationship between depression and asthma, while identifying key confounding factors. Retrospective and prospective observational studies help screen confounders like smoking, BMI, and comorbidities. Mendelian randomization uses GWAS-derived SNPs as instruments to mitigate confounding and reverse causality, with IVW method and reliability tests. It clarifies causal direction and verifies confounding impacts, laying a foundation for comorbidity intervention.

This study focuses on screening key confounding variables that affect the association between depression and asthma. Based on retrospective and prospective observational data, it identifies factors like smoking, BMI, age, gender, and comorbid chronic diseases. Mental stress, socioeconomic status, and medication use are also evaluated. Mendelian randomization further excludes residual confounding, verifying which variables truly mediate their association, to ensure accurate inference of the intrinsic link between the two conditions.

This study analyzes the correlation between depression and asthma severity. Asthma severity is assessed via clinical indicators like lung function (FEV1), symptom frequency, and acute exacerbation rate. Retrospective and observational data are used to quantify their correlation, adjusting for confounding variables. Mendelian randomization excludes reverse causality and residual confounders, clarifying whether depression correlates with aggravated asthma severity, providing insights for targeted comorbidity management.

This study focuses on verifying the stability of instrumental variables (IVs) in the Mendelian Randomization (MR) analysis. SNPs selected from GWAS as IVs are tested for reliability via multiple approaches: linkage disequilibrium filtering, heterogeneity assessment, and horizontal pleiotropy detection using MR-Egger intercept test. Sensitivity analyses, including leave-one-out and IVW robust models, are conducted to confirm IV stability, ensuring no single SNP biases results and reinforcing the credibility of causal inference.