Gabriele Lileikyte , Anahita Bakochi , Marc Isaksson , Filip Årman , Marion Moseby-Knappe , Johan Malmström , Niklas Nielsen
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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.</div></div><div><h3>Methods</h3><div>All patients with available serum samples at 24, 48, and/or 72 h after return of spontaneous circulation (<em>N</em> = 682 patients and <em>N</em> = 1882 samples) will be included in the liquid chromatography and tandem mass spectrometry analysis using <em>diaPASEF</em>, 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.</div></div><div><h3>Conclusion</h3><div>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.</div></div>","PeriodicalId":94192,"journal":{"name":"Resuscitation plus","volume":"25 ","pages":"Article 101014"},"PeriodicalIF":2.4000,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Proteomic analysis of serum samples after cardiac arrest: Rationale and design of a TTM-trial substudy\",\"authors\":\"Gabriele Lileikyte , Anahita Bakochi , Marc Isaksson , Filip Årman , Marion Moseby-Knappe , Johan Malmström , Niklas Nielsen\",\"doi\":\"10.1016/j.resplu.2025.101014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>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. 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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. 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引用次数: 0
摘要
一项初步研究调查了院外心脏骤停(TTM)后目标温度管理试验中78名患者的蛋白质组学特征,揭示了35种与功能结局相关的蛋白质,6种与33°C目标温度管理相关的蛋白质。我们提出了一项研究方案,在ttm试验生物库的全队列中调查蛋白质组学概况。目的是根据生存、功能结果、靶向温度管理和MIRACLE2评分对蛋白质谱进行分层,以寻找潜在的新型生物标志物。方法采用diaPASEF,将自动循环恢复后24、48和/或72 h可获得血清样本的患者(N = 682例,N = 1882份样本)纳入液相色谱和串联质谱分析,将数据独立获取光谱与平行累积-序列碎片化相结合。统计分析将包括数据归一化、探索性主成分分析和差异表达分析。将根据随机化、随机化至目标温度为33°C或36°C以及MIRACLE2评分后6个月的生存率和二元功能结局(改良Rankin量表0-3 vs. 4-6)分析血清蛋白丰富度的变化。二级分层包括性别、年龄、自然循环恢复时间、休克与非休克初始节律、入院时循环性休克和推定死因。结论:该前瞻性研究将提供心脏骤停后蛋白质组学信息,并可能为鉴定用于预测预后的新型生物标志物提供见解。
Proteomic analysis of serum samples after cardiac arrest: Rationale and design of a TTM-trial substudy
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.