Targeted metabolomics reveals the association between central carbon metabolism and pulmonary nodules

• Published in: PloS one Vol. 18; no. 12; p. e0295276
• Main Authors: Wu, Yue-Yang, Shen, Wen-Bin, Li, Jian-Wei, Liu, Meng-Yu, Hu, Wen-Lei, Wang, Sheng, Liu, Jian-Jun, Huang, Fen, Qin, Qi-Rong
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07.12.2023; Public Library of Science (PLoS)
• Subjects: Amino acids; Analysis; Carbon; Care and treatment; Chronic obstructive pulmonary disease; Computed tomography; Diagnosis; Ethylenediaminetetraacetic acid; Family medical history; Fumaric acid; Gluconic acid; Health aspects; Hippuric acid; Humans; Lipid metabolism; Lipids; Lung cancer; Lung diseases; Lung nodules; Metabolites; Metabolomics; Multiple Pulmonary Nodules; Nodules; Population decline; Quartiles; Regression analysis; Risk Factors; Statistical analysis; Succinic acid; Tuberculosis; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0295276

With the widespread application of low-dose computed tomography (LDCT) technology, pulmonary nodules have aroused more attention. Significant alteration in plasma metabolite levels, mainly amino acid and lipid, have been observed in patients of PNs. However, evidence on the association between central carbon metabolism and PNs are largely unknown. The aim of this study was to investigate the underlying association of PNs and plasma central carbon metabolites. We measured the levels of 16 plasma central carbon metabolites in 1954 participants who gained LDCT screening in MALSC cohort. The inverse probability weighting (IPW) technique was used to control for bias due to self-selection for LDCT in the assessed high-risk population. The least absolute shrinkage and selection operator (LASSO) penalized regression was used to deal with the problem of multicollinearity among metabolites and the combined association of central carbon metabolites with PNs was estimated by using quantile g-computation (QgC) models. A quartile increase in 3-hydroxybutyric acid, gluconic acid, succinic acid and hippuric acid was positively associated with the PNs risk, whereas a quartile increase in 2-oxadipic acid and fumaric acid was negatively associated with the risk of PNs in multiple-metabolite models. A positive but insignificant joint associations of the mixture of 16 metabolites with PNs was observed by using QgC models analyses. Further studies are warranted to clarify the association between circulating metabolites and PNs and the biological mechanisms.