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. 2024 Dec 20;63(52):e202409446.
doi: 10.1002/anie.202409446. Epub 2024 Nov 11.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery

Qin Fu  1 , Manasa Vegesna  1 , Niveda Sundararaman  1 , Eugen Damoc  2 , Tabiwang N Arrey  2 , Anna Pashkova  2 , Emebet Mengesha  1 , Philip Debbas  1 , Sandy Joung  1 , Dalin Li  1 , Susan Cheng  1 , Jonathan Braun  1 , Dermot P B McGovern  1 , Christopher I Murray  1 , Yue Xuan  2 , Jennifer E Van Eyk  1
Affiliations

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery

Qin Fu et al. Angew Chem Int Ed Engl. .

Abstract

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data-independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA-MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation based on 8- or 11-point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.

Keywords: Clinical biomarker translation; discovery proteomics; inflammatory bowel disease; peptide selection algorithm; targeted peptides.

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