Associations of combined phenotypic ageing and genetic risk with incidence of chronic respiratory diseases in the UK Biobank: a prospective cohort study

Abstract

Background: Accelerated biological ageing has been associated with an increased risk of several chronic respiratory diseases. However, the associations between phenotypic age, a new biological age indicator based on clinical chemistry biomarkers, and common chronic respiratory diseases have not been evaluated.

Methods: We analysed data from 308 592 participants at baseline in the UK Biobank. The phenotypic age was calculated from chronological age and nine clinical chemistry biomarkers, including albumin, alkaline phosphatase, creatinine, glucose, C-reactive protein, lymphocyte percent, mean cell volume, red cell distribution width and white blood cell count. Furthermore, phenotypic age acceleration (PhenoAgeAccel) was calculated by regressing phenotypic age on chronological age. The associations of PhenoAgeAccel with incident common chronic respiratory diseases and cross-sectional lung function were investigated. Moreover, we constructed polygenic risk scores and evaluated whether PhenoAgeAccel modified the effect of genetic susceptibility on chronic respiratory diseases and lung function.

Results: The results showed significant associations of PhenoAgeAccel with increased risk of idiopathic pulmonary fibrosis (IPF) (hazard ratio (HR) 1.52, 95% CI 1.45-1.59), COPD (HR 1.54, 95% CI 1.51-1.57) and asthma (HR 1.18, 95% CI 1.15-1.20) per 5-year increase and decreased lung function. There was an additive interaction between PhenoAgeAccel and the genetic risk for IPF and COPD. Participants with high genetic risk and who were biologically older had the highest risk of incident IPF (HR 5.24, 95% CI 3.91-7.02), COPD (HR 2.99, 95% CI 2.66-3.36) and asthma (HR 2.07, 95% CI 1.86-2.31). Mediation analysis indicated that PhenoAgeAccel could mediate 10∼20% of the associations between smoking and chronic respiratory diseases, while ∼10% of the associations between particulate matter with aerodynamic diameter <2.5 µm and the disorders were mediated by PhenoAgeAccel.

Conclusion: PhenoAgeAccel was significantly associated with incident risk of common chronic respiratory diseases and decreased lung function and could serve as a novel clinical biomarker.

FIGURE 1

Study design and workflow. PRS: polygenic risk score; CS: continuous shrinkage; C+T: clumping and thresholding; PhenoAgeAccel: phenotypic age acceleration.

FIGURE 2

Linear and nonlinear association of phenotypic age acceleration (PhenoAgeAccel) with the risk of chronic respiratory diseases (Cox model) and lung function (linear model). a) Idiopathic pulmonary fibrosis (IPF); b) COPD; c) asthma; d) forced vital capacity (FVC); e) forced expiratory volume in 1 s (FEV₁); f) FEV₁/FVC; g) peak expiratory flow (PEF). Restricted cubic spline analyses were performed by adjusting for chronological age, sex, ethnicity, education, body mass index, Townsend deprivation index, smoking status, pack-years of smoking, particulate matter with aerodynamic diameter <2.5 µm and <10 µm, coarse particulate matter, nitrogen dioxide and nitric oxides levels. HR: hazard ratio.

FIGURE 3

Joint effects of phenotypic age acceleration (PhenoAgeAccel) and polygenic risk score (PRS) on the risk of chronic respiratory diseases. a) idiopathic pulmonary fibrosis (IPF); b) COPD; c) asthma. PRS was calculated with PRS-CS (continuous shrinkage) for IPF, COPD and asthma. Genetic risk was categorised into low (the bottom quintile), intermediate (quintiles 2–4) and high (the top quintile) groups according to the distributions of PRS. Hazard ratios (HR) and 95% confidence intervals were estimated using Cox proportional hazard models with adjustment for chronological age, sex, ethnicity, education, body mass index, Townsend deprivation index, smoking status, pack-years of smoking, particulate matter with aerodynamic diameter <2.5 µm and <10 µm, coarse particulate matter, nitrogen dioxide and nitric oxides levels.