Sarinnapha M Vasunilashorn1,2,3, Long H Ngo1,2, Noel Y Chan2,4,5, Wenxiao Zhou1, Simon T Dillon2,4,5, Hasan H Otu6, Sharon K Inouye2,3,7, Iris Wyrobnik4,5, George A Kuchel8, Janet E McElhaney9, Zhongcong Xie2,10, David C Alsop2,11, Richard N Jones3,12, Towia A Libermann2,4,5, Edward R Marcantonio1,2,3,7. 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.
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.
Authors: Tamara G Fong; Noel Y Chan; Simon T Dillon; Wenxiao Zhou; Bridget Tripp; Long H Ngo; Hasan H Otu; Sharon K Inouye; Sarinnapha M Vasunilashorn; Zara Cooper; Zhongcong Xie; Edward R Marcantonio; Towia A Libermann Journal: Ann Surg Date: 2021-04-01 Impact factor: 12.969
Authors: Sarinnapha M Vasunilashorn; Simon T Dillon; Noel Y Chan; Tamara G Fong; Marie Joseph; Bridget Tripp; Zhongcong Xie; Long H Ngo; Chun Geun Lee; Jack A Elias; Hasan H Otu; Sharon K Inouye; Edward R Marcantonio; Towia A Libermann Journal: J Gerontol A Biol Sci Med Sci Date: 2022-03-03 Impact factor: 6.053
Authors: Sarinnapha M Vasunilashorn; Simon T Dillon; Noel Y Chan; Tamara G Fong; Marie Joseph; Bridget Tripp; Zhongcong Xie; Long H Ngo; Chun Geun Lee; Jack A Elias; Hasan H Otu; Sharon K Inouye; Edward R Marcantonio; Towia A Libermann Journal: J Gerontol A Biol Sci Med Sci Date: 2022-03-03 Impact factor: 6.053
Authors: Sarinnapha M Vasunilashorn; Michael J Devinney; Leah Acker; Yoojin Jung; Long Ngo; Mary Cooter; Richard Huang; Edward R Marcantonio; Miles Berger Journal: J Am Geriatr Soc Date: 2020-06-01 Impact factor: 7.538
Authors: Yuta Katsumi; Annie M Racine; Angel Torrado-Carvajal; Marco L Loggia; Jacob M Hooker; Douglas N Greve; Baileigh G Hightower; Ciprian Catana; Michele Cavallari; Steven E Arnold; Tamara G Fong; Sarinnapha M Vasunilashorn; Edward R Marcantonio; Eva M Schmitt; Guoquan Xu; Towia A Libermann; Lisa Feldman Barrett; Sharon K Inouye; Bradford C Dickerson; Alexandra Touroutoglou; Jessica A Collins Journal: Neuroimage Clin Date: 2020-07-14 Impact factor: 4.881