Development of a Dynamic Multi-Protein Signature of Postoperative Delirium. (24th February 2018) - Vasunilashorn, Sarinnapha M; Ngo, Long H; Chan, Noel Y; Zhou, Wenxiao; Dillon, Simon T; Otu, Hasan H; Inouye, Sharon K; Wyrobnik, Iris; Kuchel, George A; McElhaney, Janet E; Xie, Zhongcong; Alsop, David C; et al.
Abstract: Background: 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). Methods: 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. Results: 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). Conclusion: 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.