Performance evaluation of polarity switching for plasma untargeted metabolomics using Orbitrap mass spectrometer

Untargeted metabolomics often requires separate positive and negative ionization mode injections to maximize metabolome coverage, increasing analytical time, analysis cost, and complexity. Polarity switching (PSW) represents a promising alternative, yet its adoption in untargeted metabolomics remains limited, likely due to the lack of systematic performance evaluations as well as lack of polarity-switching capability on some mass spectrometers. In this study, we compared the performance of the PSW method to that of separate polarity injections by assessing the total number of detected features, the total number of metabolite annotations, Level 1 and 2 annotations, statistical analysis outcomes, and functional enrichment analysis results. Overall, separate polarity acquisition yielded the highest number of total detected features and annotations. Despite these differences, a strong overlap was observed at higher annotation confidence levels, with 70–76% overlap in Level 1 and Level 2 identified metabolites between the two methods. Notably, metabolites exhibiting significant fold changes showed consistent directional changes across both acquisition approaches, indicating that both methods captured similar biological trends. Statistical analyses using approaches such as t -tests and linear mixed models (LMM) showed that 50–60% of significant metabolites overlapped between methods, with similarity increasing when adjusted p -values were applied. Functional analysis further demonstrated strong agreement between the two approaches, with the most significant pathways consistently identified by both approaches. Overall, while separate polarity acquisition detects a larger number of features and annotations, PSW acquisition captures largely comparable biological information. These findings support PSW for untargeted metabolomics, particularly in exploratory, high-throughput studies prioritizing global metabolic trends with limited resources, providing practical guidance for strategy selection based on study goals and analytical priorities.