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Updated: Sep 14, 2025

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
Published on: June 8, 2020
Proteomic analysis of serum samples after cardiac arrest: Rationale and design of a TTM-trial substudy
Gabriele Lileikyte1, Anahita Bakochi2, Marc Isaksson2
1Department of Clinical Sciences Helsingborg, Anaesthesia and Intensive Care, Lund University, Skåne University Hospital, Malmö, Sweden.
Background:
A pilot study investigating proteomic profiles from 78 patients from the Target Temperature Management after Out-of-hospital Cardiac arrest (TTM) trial revealed 35 proteins associated to functional outcome, and six proteins associated to targeted temperature management at 33 °C. We present the protocol for a study investigating proteomic profiles in the full cohort of the TTM-trial biobank. The aim is to stratify protein profiles based on survival, functional outcome, targeted temperature management, and MIRACLE2 score in order to search for potential novel biomarkers.
Methods:
All patients with available serum samples at 24, 48, and/or 72 h after return of spontaneous circulation (N = 682 patients and N = 1882 samples) will be included in the liquid chromatography and tandem mass spectrometry analysis using diaPASEF, combining data-independent-acquisition of spectra with parallel accumulation-serial fragmentation. Statistical analysis will include data normalisation, exploratory principal component analysis, and differential expression analysis. Changes in serum protein abundance will be analysed according to survival and binary functional outcome (modified Rankin Scale 0-3 vs. 4-6) at six-months after randomisation, randomisation to target temperature of 33 °C or 36 °C, and the MIRACLE2 score. Secondary stratifications will include sex, age, time to return of spontaneous circulation, shockable vs. non-shockable initial rhythm, circulatory shock on admission, and presumed cause of death.
Conclusion:
This prospective study will provide information about proteomic profiles after cardiac arrest and may give insight for identification of novel biomarkers for prediction of outcome.
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