Risk assessment with gene expression markers in sepsis development.

IF 11.7 1区 医学 Q1 CELL BIOLOGY
Cell Reports Medicine Pub Date : 2024-09-17 Epub Date: 2024-09-03 DOI:10.1016/j.xcrm.2024.101712
Albert Garcia Lopez, Sascha Schäuble, Tongta Sae-Ong, Bastian Seelbinder, Michael Bauer, Evangelos J Giamarellos-Bourboulis, Mervyn Singer, Roman Lukaszewski, Gianni Panagiotou
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引用次数: 0

Abstract

Infection is a commonplace, usually self-limiting, condition but can lead to sepsis, a severe life-threatening dysregulated host response. We investigate the individual phenotypic predisposition to developing uncomplicated infection or sepsis in a large cohort of non-infected patients undergoing major elective surgery. Whole-blood RNA sequencing analysis was performed on preoperative samples from 267 patients. These patients developed postoperative infection with (n = 77) or without (n = 49) sepsis, developed non-infectious systemic inflammatory response (n = 31), or had an uncomplicated postoperative course (n = 110). Machine learning classification models built on preoperative transcriptomic signatures predict postoperative outcomes including sepsis with an area under the curve of up to 0.910 (mean 0.855) and sensitivity/specificity up to 0.767/0.804 (mean 0.746/0.769). Our models, confirmed by quantitative reverse-transcription PCR (RT-qPCR), potentially offer a risk prediction tool for the development of postoperative sepsis with implications for patient management. They identify an individual predisposition to developing sepsis that warrants further exploration to better understand the underlying pathophysiology.

Abstract Image

利用败血症发展过程中的基因表达标记进行风险评估。
感染是一种常见病,通常具有自限性,但也可能导致败血症,这是一种严重的宿主反应失调,危及生命。我们调查了一大批接受择期大手术的非感染患者发生无并发症感染或败血症的个体表型倾向。我们对 267 名患者的术前样本进行了全血 RNA 测序分析。这些患者术后出现感染并伴有(77 例)或不伴有(49 例)败血症,出现非感染性全身炎症反应(31 例),或术后无并发症(110 例)。建立在术前转录组特征基础上的机器学习分类模型可预测包括脓毒症在内的术后结果,其曲线下面积高达 0.910(平均值为 0.855),灵敏度/特异性高达 0.767/0.804(平均值为 0.746/0.769)。我们的模型经定量反转录 PCR(RT-qPCR)证实,有可能为术后脓毒症的发生提供一种风险预测工具,并对患者管理产生影响。它们确定了脓毒症的个体易感性,值得进一步研究,以更好地了解其潜在的病理生理学。
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来源期刊
Cell Reports Medicine
Cell Reports Medicine Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
15.00
自引率
1.40%
发文量
231
审稿时长
40 days
期刊介绍: Cell Reports Medicine is an esteemed open-access journal by Cell Press that publishes groundbreaking research in translational and clinical biomedical sciences, influencing human health and medicine. Our journal ensures wide visibility and accessibility, reaching scientists and clinicians across various medical disciplines. We publish original research that spans from intriguing human biology concepts to all aspects of clinical work. We encourage submissions that introduce innovative ideas, forging new paths in clinical research and practice. We also welcome studies that provide vital information, enhancing our understanding of current standards of care in diagnosis, treatment, and prognosis. This encompasses translational studies, clinical trials (including long-term follow-ups), genomics, biomarker discovery, and technological advancements that contribute to diagnostics, treatment, and healthcare. Additionally, studies based on vertebrate model organisms are within the scope of the journal, as long as they directly relate to human health and disease.
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