Division of General Medicine and Primary Care, Department of Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts.
Harvard Medical School, Boston, Massachusetts.
J Gerontol A Biol Sci Med Sci. 2019 Jan 16;74(2):261-268. doi: 10.1093/gerona/gly036.
Delirium is common, morbid, and costly, yet its biology is poorly understood. We aimed to develop a multi-protein signature of delirium by identifying proteins associated with delirium from unbiased proteomics and combining them with delirium biomarkers identified in our prior work (interleukin [IL]-6 and IL-2).
We used the Successful Aging after Elective Surgery (SAGES) Study of adults age ≥70 undergoing major noncardiac surgery (N = 560; 24% delirium). Plasma was collected preoperatively (PREOP) and on postoperative day 2 (POD2). In a nested matched case-control study involving 12 pairs of delirium cases and no-delirium controls, isobaric tags for relative and absolute quantitation-based (iTRAQ) mass spectrometry proteomics was applied to identify the top set of delirium-related proteins. With these proteins, we then conducted enzyme-linked immunosorbent assay (ELISA) confirmation, and if confirmed, ELISA validation in 75 matched pairs. Multi-marker conditional logistic regression was used to select the "best" PREOP and POD2 models for delirium.
We identified three proteins from iTRAQ: C-reactive protein (CRP), zinc alpha-2 glycoprotein (AZGP1), and alpha-1 antichymotrypsin (SERPINA3). The "best" multi-protein models of delirium included: PREOP: CRP and AZGP1 (Bayesian information criteria [BIC]: 93.82, c-statistic: 0.77); and POD2: IL-6, IL-2, and CRP (BIC: 87.11, c-statistic: 0.84).
The signature of postoperative delirium is dynamic, with some proteins important before surgery (risk markers) and others at the time of delirium (disease markers). Our dynamic, multi-protein signature for delirium improves our understanding of delirium pathophysiology and may identify patients at-risk of this devastating disorder that threatens independence of older adults.
谵妄很常见,且对患者危害大、花费高,但人们对其生物学机制知之甚少。本研究旨在通过非靶向蛋白质组学寻找与谵妄相关的蛋白,并与我们之前工作中确定的谵妄生物标志物(白细胞介素[IL]-6 和 IL-2)相结合,从而构建一个多蛋白谵妄标志物signature。
我们纳入了行择期非心脏大手术的年龄≥70 岁成年人(SAGES 研究)(560 例患者,24%发生谵妄)。在术前(PREOP)和术后第 2 天(POD2)收集患者的血浆。通过巢式病例对照研究(12 对谵妄病例和非谵妄对照),应用基于同位素标记相对和绝对定量(iTRAQ)的质谱蛋白质组学技术来鉴定与谵妄相关的蛋白。对这些蛋白进行酶联免疫吸附试验(ELISA)验证,如得到确认,再在另外 75 对患者中进行验证。采用多标志物条件逻辑回归来选择用于诊断谵妄的最佳 PREOP 和 POD2 模型。
我们从 iTRAQ 中鉴定出 3 种蛋白:C 反应蛋白(CRP)、锌-α2 糖蛋白(AZGP1)和α-1 抗胰蛋白酶(SERPINA3)。用于诊断谵妄的最佳多蛋白模型包括:PREOP:CRP 和 AZGP1(贝叶斯信息准则[BIC]:93.82,C 统计量:0.77);POD2:IL-6、IL-2 和 CRP(BIC:87.11,C 统计量:0.84)。
术后谵妄的标志物是动态变化的,有些蛋白在术前起风险标志物作用,有些蛋白在谵妄时起疾病标志物作用。我们的动态、多蛋白谵妄标志物signature 有助于深入了解谵妄的病理生理学,可能有助于识别有谵妄风险的患者,从而防止老年患者出现谵妄这一破坏性疾病。