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  • Poster presentation
  • P-III-0785

Paradigm shift in biomarker translation: an innovative and automated pipeline to generate and select clinical-grade signature peptides during DIA discovery

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Data Integration: With Bioinformatics to Biological Knowledge

Poster

Paradigm shift in biomarker translation: an innovative and automated pipeline to generate and select clinical-grade signature peptides during DIA discovery

Thema

  • Data Integration: With Bioinformatics to Biological Knowledge

Mitwirkende

Qin Fu (Los Angeles, CA / US), Manasa Vegesna (Los Angeles, CA / US), Niveda Sundararaman (Los Angeles, CA / US), Nicolaie Eugen Damoc (Bremen / DE), Tabiwang Arrey (Bremen / DE), Anna Pashkova (Bremen / DE), Sandy Joung (Los Angeles, CA / US), Susan Cheng (Los Angeles, CA / US), Dalin Li (Los Angeles, CA / US), Philip Debbas (Los Angeles, CA / US), Dermot McGovern (Los Angeles, CA / US), Yue Xuan (Bremen / DE), Jennifer Van Eyk (Los Angeles, CA / US)

Abstract

The transition of biomarker candidates from discovery to the validation is an expensive, challenging, and time-consuming process. The Obitrap Astral MS platform achieves extensive plasma proteome coverage with data completeness and quantification repeatability. In combination with the innovative TEAQ (targeted extraction assessment of quantification) data analysis software solution, we have developed an automated pipeline to generate and select clinical-grade signature peptides that can directly be applied in clinical validation studies. Our test study is a 493 subjects Inflammatory bowel diseases (IBD) case-control cohort, identifying 1,116 peptides signature peptides fulfilling the clinical chemistry criteria.

Pooled plasma samples at different loading amounts 12.5ng to 500ng were analyzed at three different throughputs (180SPD, 100SPD, and 60SPD) with five technical replicates. The throughput of 60 SPD shows the best balance between identification and quantification, identifying 1662 proteins with 1% FDR. Remarkably, 649 unique proteins with 97% of the precursors quantifiable in all 5 technical replicates. Notably, 80% of these plasma proteins were quantifiable across all technical replicates with a median coefficient of variance (CV) of less than 20%, required for clinical-grade assays. Therefore, 60SPD method was applied to analyze the IBD cohort (492 samples). To automate the selection of signature peptides representing. biomarker candidates that meet clinical chemistry criteria, TEAQ, was developed and deployed as a two-step process: 1) Assignment of all quantifiable precursors or peptides based on loading curve experiments. 2) Assignment of only those correlated quantifiable precursors or peptides within the linear range. The candidate biomarkers which are altered in IBD cohort were selected based on statistical significance and fold of change. TEAQ identified a total of 9481 precursors representing 1661 proteins, 781 and 346 of which has characterizable lower limits of detection and quantitation, respectively determined from 5 injections each of 11 loading points (12.5 ng to 1000ng) at 60SPD.

To accelerate the identification of rigorous signature peptides for clinical validation phase, TEAQ selected 1,225 precursors and 1,116 peptides representing 327 proteins. This included CRP (with 1 signature peptide), a general inflammation marker which has been reported to elevate in response to inflammation in IBD patients. CRP was elevated in the IBD cohort with P=0.03. In addition, we have also observed two more acute phase proteins elevated in IBD: AGP1(Orosomucoid1) with 5 correlated signature peptides (P<0.0001) and AGP2 (Orosomucoid 2) with 3 correlated signature peptides (p=0.018). We have developed an innovative and automated pipeline to generate clinical grade signature peptides that can directly be applied in clinical validation studies.

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