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Nonlinear association of TSH with pulmonary ventilation: insights from bidirectional Mendelian randomization and
Yuxin Wang1, Jinmei Luo1, Rong Huang1
1Department of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background:
Thyroid hormones play a crucial role in numerous physiological processes, including pulmonary function. However, the relationship between thyroid function and different patterns of pulmonary ventilation remains unclear.
Methods:
This study employed a bidirectional two-sample Mendelian randomization (MR) approach combined with a cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) to explore the relationship between thyroid function and pulmonary ventilation indicators. We used genomic data from the ThyroidOmics Consortium and the UK Biobank to derive instrumental variables for thyroid and pulmonary functions. Adults from the NHANES 2007-2012 were included to validate the MR findings through weighted generalized linear model (GLM) regression and restricted cubic spline (RCS) analysis.
Results:
Genetically predicted thyroid-stimulating hormone (TSH) was associated with pulmonary ventilatory function (forced expiratory volume in 1 s (FEV1): β = 0.0223, 95% confidence interval (CI) 0.0040-0.0406, p-value = 0.0170), particularly with a restrictive ventilatory pattern (forced vital capacity (FVC): β = 0.0237, 95% CI 0.0047-0.0427, p-value = 0.0143). This association was more robust in the low TSH subgroup. Additionally, the NHANES data revealed a nonlinear relationship between both FEV1% predicted and FVC% predicted and TSH, characterized by a positive relationship at lower TSH ranges and a negative relationship at higher TSH ranges.
Conclusions:
Our findings highlight a significant association between TSH levels and a restrictive ventilatory pattern, underscoring the importance of thyroid health in the clinical evaluation of certain pulmonary diseases. These insights may guide more personalized interventions in respiratory medicine.
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