@article{ZHANG2026, 
author = {Qinghan ZHANG and Lijun FAN and Mingxiao SONG and Ziyi GUO and Jing WANG and Xuewei CHEN and Junyu LU},
title = {Serum lipids and immune factor omics of operational fatigue in young males},
year = {2026},
journal = {Military Medical Sciences},
volume = {50},
number = {6},
pages = {425-433},
keywords = {operational fatigue, lipidomics, immune factor omics, biomarkers},
url = {https://www.sciopen.com/article/10.7644/j.issn.1674-9960.2026-00010},
doi = {10.7644/j.issn.1674-9960.2026-00010},
abstract = {ObjectiveTo study the molecular mechanisms underlying operational fatigue in young males using serum lipidomics and immune factor omics.MethodsSixty young males were involved in this study, who were asked to fill in the questionnaire about their fatigue and sleep during training period (TP) and recovery period (RP). The levels of blood lactic acid (BLA) and creatine kinase (CK) were measured to determine their levels of fatigue. Serum lipidomics and immune factor profiles were also analyzed to identify potential biomarkers that were detected using ELISA.ResultsFatigue scores were significantly higher during TP than during RP (P<0.05) while sleep quality was poorer. CK[TP:(498.90±215.50) U/L vs. RP:(181.74±65.14) U/L] and BLA levels [TP:(5.83±1.23) mmol/L vs. RP:(3.07±0.64) mmol/L] were higher during TP. Lipidomics analysis suggested that the phosphatidylcholine (PC) subclass lipid molecule PC (18∶1-20∶3) +Na (AUC=0.85) was moderately correlated with fatigue scores (r=-0.64, P<0.001) and with BLA levels (r=0.57, P<0.001). Immune factor profiling indicated that platelet-derived growth factor BB (PDGF-BB) (AUC=0.78) was negatively correlated with BLA levels (r=-0.40, P<0.01) and CK (r=-0.46, P<0.001). The trends observed in the omics analyses were corroborated by ELISA validation results.ConclusionThese findings suggest a “lipid-immune”two-dimensional evaluation system for operational fatigue. The lipid subclass PC and PDGF-BB may serve as candidate biomarkers for monitoring operational fatigue by reflecting changes in energy metabolism and responses related to minor tissue injury and repair. Furthermore, the PDGF-BB-PC metabolic axis may provide new insights into the mechanisms underlying the occurrence of operational fatigue.}
}