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Background <p>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.</p> Methods <p>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 and the English Longitudinal Study of Ageing (ELSA) 2004–2019. 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).</p> Results <p>This study included 31,434 participants from NHANES and 17,021 participants from ELSA for observational research. In the unadjusted model, participants with depression had a significantly increased risk of asthma in comparison to participants without depression, both in NHANES (OR = 2.002, 95%CI: 1.827–2.193, P &lt; 0.001) and in ELSA (OR = 1.753, 95%CI: 1.581–1.943, P &lt; 0.001). After adjusting potential confounders, the results remain significant. The LDSC result revealed a significant positive genetic correlation between depression and asthma (<i>r</i>g = 0.352, <i>P</i> &lt; 0.001).The UVMR results further substantiated a genetically predicted causality of depression on asthma (OR = 1.291, 95%CI: 1.157–1.442, <i>P</i> &lt; 0.001), while the reverse causality does not stand. Similar findings from MVMR were obtained for the causality investigation after adjusting smoking (OR = 1.326, 95%CI: 1.156–1.520, <i>P</i> &lt; 0.001), drinking (OR = 1.375, 95%CI: 1.186–1.593, <i>P</i> &lt; 0.001), and education (OR = 1.425, 95%CI: 1.253–1.621, <i>P</i> &lt; 0.001).</p> Conclusion <p>Our findings indicate that depression may play a contributory role in the development of asthma, underscoring the potential benefit of implementing prevention strategies aimed at managing depression to mitigate asthma risk.</p>

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Association between depression and asthma: insight from observational and genetic evidence

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月12日

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  • Tanao Ji,
  • Yue Lv,
  • Jianan Yang,
  • Xianping Diao,
  • Jun Gu

摘要

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 and the English Longitudinal Study of Ageing (ELSA) 2004–2019. 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 31,434 participants from NHANES and 17,021 participants from ELSA for observational research. In the unadjusted model, participants with depression had a significantly increased risk of asthma in comparison to participants without depression, both in NHANES (OR = 2.002, 95%CI: 1.827–2.193, P < 0.001) and in ELSA (OR = 1.753, 95%CI: 1.581–1.943, P < 0.001). After adjusting potential confounders, the results remain significant. The LDSC result revealed a significant positive genetic correlation between depression and asthma (rg = 0.352, P < 0.001).The UVMR results further substantiated a genetically predicted causality of depression on asthma (OR = 1.291, 95%CI: 1.157–1.442, P < 0.001), while the reverse causality does not stand. Similar findings from MVMR were obtained for the causality investigation after adjusting smoking (OR = 1.326, 95%CI: 1.156–1.520, P < 0.001), drinking (OR = 1.375, 95%CI: 1.186–1.593, P < 0.001), and education (OR = 1.425, 95%CI: 1.253–1.621, P < 0.001).

Conclusion

Our findings indicate that depression may play a contributory role in the development of asthma, underscoring the potential benefit of implementing prevention strategies aimed at managing depression to mitigate asthma risk.