Ji Tanao, Lv Yue, Yang Jianan, Diao Xianping, Gu Jun
Department of General Practice, , Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, China.
Department of Hematology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, China.
BMC Psychiatry. 2025 Aug 12;25(1):786. doi: 10.1186/s12888-025-07245-w.
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.
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).
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).
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.
抑郁症和哮喘有多种共同的病理生理风险因素,它们的确切联系尚不清楚。我们的研究旨在评估抑郁症与哮喘之间的关系。
通过多变量逻辑回归分析评估抑郁症与哮喘之间的关联,数据来源于2007 - 2018年美国国家健康与营养检查调查(NHANES)以及2004 - 2019年英国老龄化纵向研究(ELSA)。随后,进行连锁不平衡评分回归(LDSC)分析以评估抑郁症与哮喘之间的遗传相关性。此外,通过单变量孟德尔随机化(UVMR)和多变量孟德尔随机化(MVMR)方法,利用全基因组关联研究(GWAS)汇总统计数据进行两样本孟德尔随机化(MR)分析。
本研究纳入了来自NHANES的31434名参与者和来自ELSA的17021名参与者进行观察性研究。在未调整模型中,与无抑郁症的参与者相比,抑郁症患者患哮喘的风险显著增加,在NHANES中(OR = 2.002,95%CI:1.827 - 2.193,P < 0.001)以及在ELSA中(OR = 1.753,95%CI:1.581 - 1.943,P < 0.001)。调整潜在混杂因素后,结果仍然显著。LDSC结果显示抑郁症与哮喘之间存在显著的正遗传相关性(rg = 0.352,P < 0.001)。UVMR结果进一步证实了抑郁症对哮喘的遗传预测因果关系(OR = 1.291,95%CI:1.157 - 1.442,P < 0.001),而反向因果关系不成立。在调整吸烟(OR = 1.326,95%CI:1.156 - 1.520,P < 0.001)、饮酒(OR = 1.375,95%CI:1.186 - 1.593,P < 0.001)和教育程度(OR = 1.425,95%CI:1.253 - 1.621,P < 0.001)后,MVMR的因果关系调查得到了类似的结果。
我们的研究结果表明,抑郁症可能在哮喘的发生发展中起作用,这突出了实施旨在管理抑郁症以降低哮喘风险的预防策略的潜在益处。