The EPIC-Norfolk Study
Metabolomic differences in lung function metrics: evidence from two cohorts.
Thorax 2020
Kelly RS, Stewart ID, Bayne H, Kachroo P, Spiro Iii A, Vokonas P, Sparrow D, Weiss ST, Knihtilä HM, Litonjua AA, Wareham NJ, Langenberg C, and Lasky-Su JA
DOI : 10.1136/thoraxjnl-2020-216639
PubMed ID : 34650005
PMCID :
URL : https://thorax.bmj.com/lookup/doi/10.1136/thoraxjnl-2020-216639
Abstract
The biochemical mechanisms underlying lung function are incompletely understood.
To identify and validate the plasma metabolome of lung function using two independent adult cohorts: discovery-the European Prospective Investigation into Cancer-Norfolk (EPIC-Norfolk, n=10 460) and validation-the VA Normative Aging Study (NAS) metabolomic cohort (n=437).
We ran linear regression models for 693 metabolites to identify associations with forced expiratory volume in one second (FEV) and the ratio of FEV to forced vital capacity (FEV/FVC), in EPIC-Norfolk then validated significant findings in NAS. Significance in EPIC-Norfolk was denoted using an effective number of tests threshold of 95%; a metabolite was considered validated in NAS if the direction of effect was consistent and p<0.05.
Of 156 metabolites that associated with FEV in EPIC-Norfolk after adjustment for age, sex, body mass index, height, smoking and asthma status, 34 (21.8%) validated in NAS, including several metabolites involved in oxidative stress. When restricting the discovery sample to men only, a similar percentage, 18 of 79 significant metabolites (22.8%) were validated. A smaller number of metabolites were validated for FEV/FVC, 6 of 65 (9.2%) when including all EPIC-Norfolk as the discovery population, and 2 of 34 (5.9%) when restricting to men. These metabolites were characterised by involvement in respiratory track secretants. Interestingly, no metabolites were validated for both FEV and FEV/FVC.
The validation of metabolites associated with respiratory function can help to better understand mechanisms of lung health and may assist the development of biomarkers.