Abstract
While metabolomics has emerged as a powerful tool for discovering disease biomarkers, the clinical utility of plasma or tissue metabolite profiles remains limited due to metabolic heterogeneity and flexibility across cell types. Traditional bulk metabolomics fails to capture the distinct metabolic programs operating within rare cell populations that often drive disease pathogenesis. This review examines cutting-edge approaches that overcome these limitations by characterizing metabolism at single-cell and cell-type-specific resolution, with particular emphasis on rare immune cell populations as a proof of concept. We discuss how the integration of flow cytometric metabolic profiling, molecular techniques, advanced metabolomics platforms, and computational modeling enables unprecedented insight into cell-intrinsic metabolic states within physiological contexts. We critically evaluate how these technologies reveal metabolic plasticity that confounds bulk measurements while identifying cell-type-specific metabolic vulnerabilities. Finally, we address the crucial challenge of establishing causality in metabolic pathways, a prerequisite for translating metabolomic discoveries into clinically actionable interventions. By moving beyond descriptive metabolomics toward a mechanistic understanding of cell-type-specific metabolism, these approaches promise to deliver the precision required for effective metabolic targeting in disease.