Observational and Mendelian randomization analysis reveals an increased risk of asthma in survey participants, suggesting a causal relationship between depression and asthma.
Background Depression and asthma share several pathophysiologic risk factors, and their precise connection remains unclear. Our research seeks to assess the relationship between depression and asthma. Methods The association between depression and asthma was assessed through a multivariable logistic regression analysis, with data sourced from The National Health and Nutrition Examination Survey (NHANES) 2007–2018. Subsequently, a linkage disequilibrium score regression (LDSC) analysis was conducted to evaluate the genetic correlation between depression and asthma. Moreover, a two-sample Mendelian randomization (MR) analysis was conducted by employing genome-wide association study (GWAS) summary statistics by means of both univariable MR (UVMR) and multivariable MR (MVMR). Results This study included 22467 participants from NHANES for our observational research. In the unadjusted model, participants with depression symptoms had a significantly increased risk of asthma in comparison to participants without depression symptoms (OR = 1.924, 95%CI: 1.717–2.152, P < 0.0001). After adjusting potential confounders, the results remain significant. The LDSC result revealed a significant positive genetic correlation between depression and asthma ( r g = 0.254, P < 0.0001).The UVMR results further substantiated a causal effect between depression and asthma (OR = 1.243, 95%CI: 1.141–1.354, P < 0.0001). Similar findings from MVMR were obtained for the causality investigation after adjusting smoking (OR = 1.29, 95%CI: 1.17–1.42, P < 0.0001), drinking (OR = 1.27, 95%CI: 1.16–1.38, P < 0.0001), and education attainment (OR = 1.21, 95%CI: 1.11–1.31, P < 0.001). Conclusion Our study showed that depression is an independent risk factor for asthma and may increase the risk of asthma.
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Ji et al. (2024) studied this question.
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