This work quantified 126 proteins (509 peptides) directly in crude plasma from 490 individuals spanning 16 diseases spanning 16 diseases plus age- and sex-matched controls plus age- and sex-matched controls, each protein referenced to a stable-isotope-labelled internal standard.
Abstract
Population health screening is fragmented across dozens of single-condition assays. We asked whether one targeted mass-spectrometry measurement of the plasma proteome could screen simultaneously for many common diseases. Using multiple-reaction-monitoring LC-MS/MS, we quantified 126 proteins (509 peptides) directly in crude plasma from 490 individuals spanning 16 diseases (eight cancers, three inflammatory or renal conditions, and five metabolic and lifestyle disorders) plus age- and sex-matched controls, each protein referenced to a stable-isotope-labelled internal standard. Proteome variation was organised primarily by disease rather than demographics. Cross-validated classifiers detected each disease against matched controls with a mean AUROC of 0.979, a 17-way model identified the specific disease at roughly ten times chance, and a 20-protein subset reproduced full-panel performance. We show that these within-cohort estimates are optimistic upper bounds because each disease was acquired as a separate case-control batch without independent validation. We quantify this, establishing analytical feasibility and defining the validation required for translation.
Improvements enabling quantification of site-specific modifications, including post-translational modifications and covalent compound-protein interactions spanning diverse pathways are described.
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A large-scale metabolome relative quantitative method workflow using ultrahigh-performance liquid chromatography coupled with Q-TRAP mass spectrometry to identify novel biomarkers in the serum of CC patients demonstrates applicability in identifying potential metabolite biomarkers for CC and provides a promising tool f...
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This large-scale proteome-wide study not only reveals significant proteomic changes preceding SLD diagnosis but also establishes GDF15 as both a promising preclinical biomarker and opening new avenues for early intervention in at-risk individuals.
This study defined the serum metabolomic signature of MSA and highlighted novel biomarkers, pathological mechanisms, and therapeutic targets deserving further validation.
Lin-Lin Wan, Zhao Chen, Na Wan et al.· Movement Disorders· 0 citations
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