METHODS: In an international, community-based prospective study, we enrolled individuals from communities in 17 countries between Jan 1, 2005, and Dec 31, 2009 (except for in Karnataka, India, where enrolment began on Jan 1, 2003). Trained local staff obtained data from participants with interview-based questionnaires, measured weight and height, and recorded forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC). We analysed data from participants 130-190 cm tall and aged 34-80 years who had a 5 pack-year smoking history or less, who were not affected by specified disorders and were not pregnant, and for whom we had at least two FEV₁ and FVC measurements that did not vary by more than 200 mL. We divided the countries into seven socioeconomic and geographical regions: south Asia (India, Bangladesh, and Pakistan), east Asia (China), southeast Asia (Malaysia), sub-Saharan Africa (South Africa and Zimbabwe), South America (Argentina, Brazil, Colombia, and Chile), the Middle East (Iran, United Arab Emirates, and Turkey), and North America or Europe (Canada, Sweden, and Poland). Data were analysed with non-linear regression to model height, age, sex, and region.
FINDINGS: 153,996 individuals were enrolled from 628 communities. Data from 38,517 asymptomatic, healthy non-smokers (25,614 women; 12,903 men) were analysed. For all regions, lung function increased with height non-linearly, decreased with age, and was proportionately higher in men than women. The quantitative effect of height, age, and sex on lung function differed by region. Compared with North America or Europe, FEV1 adjusted for height, age, and sex was 31·3% (95% CI 30·8-31·8%) lower in south Asia, 24·2% (23·5-24·9%) lower in southeast Asia, 12·8% (12·4-13·4%) lower in east Asia, 20·9% (19·9-22·0%) lower in sub-Saharan Africa, 5·7% (5·1-6·4%) lower in South America, and 11·2% (10·6-11·8%) lower in the Middle East. We recorded similar but larger differences in FVC. The differences were not accounted for by variation in weight, urban versus rural location, and education level between regions.
INTERPRETATION: Lung function differs substantially between regions of the world. These large differences are not explained by factors investigated in this study; the contribution of socioeconomic, genetic, and environmental factors and their interactions with lung function and lung health need further clarification.
FUNDING: Full funding sources listed at end of the paper (see Acknowledgments).
MATERIAL AND METHODS: All the information for CYP1B1 missense variants was retrieved from the dbSNP database. Seven different tools, namely: SIFT, PolyPhen-2, PROVEAN, SNAP2, PANTHER, PhD-SNP, and Predict-SNP, were used for functional annotation, and two packages, which were I-Mutant 2.0 and MUpro, were used to predict the effect of the variants on protein stability. A phylogenetic conservation analysis using deleterious variants was performed by the ConSurf server. The 3D structures of the wild-type and mutants were generated using the I-TASSER tool, and a 50 ns molecular dynamic simulation (MDS) was executed using the GROMACS webserver to determine the stability of mutants compared to the native protein. Co-expression, protein-protein interaction (PPI), gene ontology (GO), and pathway analyses were additionally performed for the CYP1B1 in-depth study.
RESULTS: All the retrieved data from the dbSNP database was subjected to functional, structural, and phylogenetic analysis. From the conducted analyses, a total of 19 high-risk variants (P52L, G61E, G90R, P118L, E173K, D291G, Y349D, G365W, G365R, R368H, R368C, D374N, N423Y, D430E, P442A, R444Q, F445L, R469W, and C470Y) were screened out that were considered to be deleterious to the CYP1B1 gene. The phylogenetic analysis revealed that the majority of the variants occurred in highly conserved regions. The MD simulation analysis exhibited that all mutants' average root mean square deviation (RMSD) values were higher compared to the wild-type protein, which could potentially cause CYP1B1 protein dysfunction, leading to the severity of the disease. Moreover, it has been discovered that CYP1A1, VCAN, HSD17B1, HSD17B2, and AKR1C3 are highly co-expressed and interact with CYP1B1. Besides, the CYP1B1 protein is primarily involved in the metabolism of xenobiotics, chemical carcinogenesis, the retinal metabolic process, and steroid hormone biosynthesis pathways, demonstrating its multifaceted and important roles.
DISCUSSION: This is the first comprehensive study that adds essential information to the ongoing efforts to understand the crucial role of genetic signatures in the development of PCG and will be useful for more targeted gene-disease association studies.