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J Gerontol A Biol Sci Med Sci. 2019 Jan 16;74(2):261-268. doi: 10.1093/gerona/gly036.

Development of a Dynamic Multi-Protein Signature of Postoperative Delirium.

Author information

1
Division of General Medicine and Primary Care, Department of Medicine, Beth Israel Deaconess Medical Center (BIDMC), Boston, Massachusetts.
2
Harvard Medical School, Boston, Massachusetts.
3
Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts.
4
Division of Interdisciplinary Medicine and Biotechnology, BIDMC, Boston, Massachusetts.
5
BIDMC Genomics, Proteomics, Bioinformatics and Systems Biology Center, Boston, Massachusetts.
6
Department of Electrical and Computer Engineering, University of Nebraska-Lincoln.
7
Division of Gerontology, BIDMC, Boston, Massachusetts.
8
University of Connecticut Center on Aging, University of Connecticut Health Center, Farmington.
9
Health Sciences North Research Institute, Sudbury, Ontario, Canada.
10
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston.
11
Department of Radiology, BIDMC, Boston, Massachusetts.
12
Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, Rhode Isl.

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.

PMID:
29529166
PMCID:
PMC6333936
[Available on 2019-02-24]
DOI:
10.1093/gerona/gly036

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