Age-Related Genetic Causal Association Between Asthma and Delirium: A Bidirectional Two-Sample Mendelian...

Despite observational studies suggesting a link between asthma and delirium, establishing a definitive causal relationship has been challenging. This study aims to investigate the genetic causality between these conditions, with a particular focus on age-related genetic associations using data from large-scale genome-wide association studies (GWASs).

Bidirectional two-sample Mendelian Randomization (MR) analyses were performed using GWAS summary statistics to evaluate the genetic association between asthma (overall, adult-onset, childhood-onset, and age at asthma diagnosis) and delirium. The inverse variance-weighted (IVW) method was the primary analytic approach, supplemented by weighted median, weighted mode, and MR-Egger methods. Multivariable Mendelian Randomization (MVMR) analyses were conducted to adjust for major confounders, including smoking, body mass index (BMI), alcohol intake, and education. Sensitivity analyses included MR-Egger regression, MR-PRESSO outlier tests, Cochran's Q for heterogeneity, and leave-one-out analyses.

The primary MR analyses found no evidence of a significant genetic causal relationship between asthma and delirium in either direction (asthma to delirium: IVW OR = 1.02, 95% CI: 0.79-1.32, p = 0.86; delirium to asthma: IVW OR = 1.05, 95% CI: 0.99-1.11, p = 0.13). Age-stratified MR analyses for adult-onset and childhood-onset asthma, as well as age at asthma diagnosis, also showed no significant associations with delirium risk. In MVMR analyses adjusting for smoking, BMI, alcohol intake, and education, the direct effects of asthma and its subtypes on delirium, and of delirium on asthma phenotypes, remained non-significant (all p > 0.05). Sensitivity analyses confirmed the robustness of these results, with no evidence of pleiotropy or heterogeneity.

These comprehensive bidirectional MR and MVMR analyses do not support a genetic causal association between asthma and delirium, even after adjusting for key confounders and across age-related asthma subtypes. These findings suggest that previously observed associations may be attributable to non-genetic factors. Future studies integrating clinical and biomarker data are warranted to further explore these relationships.