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A proteomics approach towards identification and validation of blood-based protein biomarkers for the differentiation of ischemic stroke from intracerebral hemorrhage

ABSTRACT: Background & aims: Stroke diagnosis is challenging in the acute phase. We aimed to determine biomarkers for the differentiation of ischemic stroke (IS) from intracerebral hemorrhage (ICH) using SWATH-MS and validate the discovered biomarkers within 24 hours using MRM proteomics. Methods: The study was conducted at Department of Neurology, All India Institute of Medical Sciences, New Delhi, India. Serum samples were collected within 24 hours from acute stroke (IS & ICH) patients & healthy controls. SWATH-MS proteomics identified significantly differentially expressed (SDE) proteins (fold change: 1.5, p<0.05 and confirmed/tentative selection using Boruta random forest) between IS and ICH which were then validated using protein MRM. Cut-off points were determined using Youden Index. Prediction models were developed using forward stepwise multivariate logistic regression analysis. Integrated discrimination improvement index determined the added value of biomarkers to clinical models. Results: Discovery phase included 20 IS, 20 ICH and 40 controls while validation phase included 150 IS and 150 ICH subjects. Total 365 proteins were quantified using SWATH-MS. Between IS and ICH, 20 SDE proteins were identified. Prediction model including clinical variables (sex, hypertension, atrial fibrillation, current smoking, baseline NIHSS) and biomarkers (GFAP, MMP9, APOC1) independently differentiated IS from ICH (accuracy: 92%, sensitivity: 96%, specificity: 69%). Addition of biomarkers improved the discrimination capacity by 26% (p<0.001) compared to clinical variables alone. Conclusion: Our study identified a range of potential protein biomarkers for the differentiation of IS. Protein biomarkers along with clinical predictors might be useful candidates in differentiating IS from ICH in acute settings.

INSTRUMENT(S): TSQ Altis, TripleTOF 6600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Stroke

SUBMITTER: Shubham Misra

LAB HEAD: Dr. Deepti Vibha

PROVIDER: PXD032917 | Pride | 2022-09-21

REPOSITORIES: Pride

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			Action	DRS
	01122021_anlysis.sky	Other
	01122021_anlysis.sky.view	Other
	01122021_anlysis.skyd	Other
	01122021_anlysis.skyl	Other
	21072021_nanoflow_library.swath	Other

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Project description:The current state of proteomics requires a choice between targeted and discovery methods. The former provides exceptional quantitation and data completeness, but only with few analytes. Discovery proteomics can identify hundreds and thousands of proteins in a sample, but with poor quantitation and data completeness. We have established and optimized a method that combines targeted and data-independent acquisition for absolute quantitation of all plasma proteins in a single sequential window acquisition of all theoretical fragment ions (SWATH) acquisition run using a panel of spike-in standards (SIS). We compared the absolute quantitation (AQ) of SWATH and high-resolution multiple-reaction monitoring (MRM-HR) acquisition methods using the 100 protein PlasmaDive SIS panel spiked into human plasma. SWATH provided equivalent quantitation and differentially abundant protein profiles as MRM-HR. Absolute quantities of the SIS peptides from the SWATH data were used to estimate the absolute quantities (eAQ) for all the proteins in the run. The eAQ values provided similar quantitation and differentially abundant protein profiles as AQ and protein group (PG) values, and the eAQ method was the only scheme where all selected proteins were verified by MRM-HR. We applied the eAQ method to a cohort of 16 non-small cell lung cancer (NSCLC) patients receiving immunotherapeutics and found that fibronectin (FN1) and proteoglycan 4 (PRG4) were useful markers for predicting patients who would stay on these agents for at least 6 months (area under the curve of 0.8438 and 0.6735, respectively). Thirteen additional plasma samples confirmed that FN1 and PRG4 are putative biomarkers (positive predictive value is 100% and 85.7%, respectively) for a prolonged (>6 months) response to immunotherapeutic agents. In conclusion, we describe an optimized method for absolute quantification of all proteins in a SWATH run, and this approach is amenable for the identification of plasma biomarkers.

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A proteomics approach towards identification and validation of blood-based protein biomarkers for the differentiation of ischemic stroke from intracerebral hemorrhage

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