Proteomic Analysis of Ischemic Stroke Blood Biomarkers

Bibliographic Details
Main Author: Daubenspeck, April Arnold
Language:English
Published: Wright State University / OhioLINK 2017
Subjects:
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=wright1515748115902114
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-wright15157481159021142021-08-03T07:05:20Z Proteomic Analysis of Ischemic Stroke Blood Biomarkers Daubenspeck, April Arnold Biomedical Research biomedical research Stroke is a global burden that claims 6 million lives and permanently disables another 5 million each year. The risk of morbidity and mortality following stroke decreases when early diagnosis and treatment are achieved. However there is no blood test to diagnose ischemic stroke because biomarkers to date have not shown adequate sensitivity and specificity to be adopted into hospital protocols. The overall objective of this dissertation was to identify novel blood protein biomarkers of ischemic stroke. We achieved this by using a number of proteomic and statistical techniques to investigate the differential abundance of proteins in the blood of stroke and non-stroke groups. We identified four high-abundance serum proteins differentially expressed between the ischemic brain of stroke patients undergoing mechanical thrombectomy and the same patient’s circulating arterial blood. Three proteins were significantly higher in the circulating blood, and a fourth protein had a large fold change in abundance in the ischemic blood of a few patients. We then identified an additional fourteen serum proteins with significant differences between the venous blood of stroke patients and that of healthy individuals. To expand these findings in a more clinically relevant patient group, protein concentrations for these eighteen individual proteins were evaluated in stroke patients and patients with stroke-mimicking symptoms. Separate analysis of each protein revealed a low diagnostic accuracy. A new analysis was therefore initiated to compare the concentrations of 1310 serum proteins in stroke patients and stroke-mimicking patients. We identified 27 additional proteins that were significantly different between stroke and stroke-mimicking patient groups, and used machine learning to determine combinations of these proteins that could constitute a stroke biomarker panel. Random Forest Analysis identified three protein panels which differentiated stroke from non-stroke groups. Thus, consistent with previous research, we did not find an individual blood protein that was likely to be clinically useful as a diagnostic biomarker. However, three protein biomarker panels successfully differentiated stroke patients from stroke-mimicking patients which may lead to the development of a validated point-of-care diagnostic test. 2017 English text Wright State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=wright1515748115902114 http://rave.ohiolink.edu/etdc/view?acc_num=wright1515748115902114 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Biomedical Research
biomedical research
spellingShingle Biomedical Research
biomedical research
Daubenspeck, April Arnold
Proteomic Analysis of Ischemic Stroke Blood Biomarkers
author Daubenspeck, April Arnold
author_facet Daubenspeck, April Arnold
author_sort Daubenspeck, April Arnold
title Proteomic Analysis of Ischemic Stroke Blood Biomarkers
title_short Proteomic Analysis of Ischemic Stroke Blood Biomarkers
title_full Proteomic Analysis of Ischemic Stroke Blood Biomarkers
title_fullStr Proteomic Analysis of Ischemic Stroke Blood Biomarkers
title_full_unstemmed Proteomic Analysis of Ischemic Stroke Blood Biomarkers
title_sort proteomic analysis of ischemic stroke blood biomarkers
publisher Wright State University / OhioLINK
publishDate 2017
url http://rave.ohiolink.edu/etdc/view?acc_num=wright1515748115902114
work_keys_str_mv AT daubenspeckaprilarnold proteomicanalysisofischemicstrokebloodbiomarkers
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