The University of Southampton
University of Southampton Institutional Repository

Proteomic profiling to identify prognostic biomarkers in heart failure

Proteomic profiling to identify prognostic biomarkers in heart failure
Proteomic profiling to identify prognostic biomarkers in heart failure
Background: the ability to predict mode, as well as risk, of death in left ventricular systolic dysfunction (LVSD) is important, as the clinical and cost-effectiveness of implantable cardioverter defibrillators (ICD) therapy depends on its use in appropriately selected patient populations. The value of a proteomic approach in identifying prognostic biomarkers in LVSD is unknown. The aims of this pilot study were to use proteomic techniques to identify serum biomarkers associated with LVSD and to prospectively explore their association with prognosis.

Patients and methods: serum was analysed by surface-enhanced laser desorption ionisation time-of-flight mass spectrometry (SELDI-TOF MS) in patients with (n=78) and without (n=45) systolic heart failure (SHF). Spectra were compared to identify differentially expressed signal peaks as potential biomarker indicators. The ability of these peaks to predict all-cause mortality and survival with appropriate ICD therapy was then tested prospectively in patients with ICDs, on the background of LVSD (n=141).

Results: for the identification stage spectra (2-200 kDa) from SHF and control patients were randomly separated into two equally sized discovery and validation sets. Six protein peaks were identified that were differentially expressed in SHF in both sets. In the prospective phase, during a mean follow-up of 15±3 months, 11 patients died and 39 survived with appropriate ICD therapy. Five out of the six proteomic biomarkers predicted all-cause mortality but none predicted appropriate ICD therapy.

Conclusion: these results provide proof-of-principle and are supportive of the SELDI proteomic approach as a high-throughput screening tool in identifying potentially prognostic protein peaks in patients with LVSD.
implantable cardioverter defibrillators, heart failure, biomarkers, mortalityarrhythmias, proteomics, SELDI-TOF MS
0258-851X
875-882
Scott, Paul A.
5a16b1f4-74d3-473f-9eeb-c2a823d690dc
Zeidan, Bashar
acd18415-22ee-43b8-a102-a36ea22dd0af
Ng, Leong L.
7c95e856-3d42-42b5-9f3d-467efa7145c2
Zeb, Mehmood
469fda8e-8318-4fe5-97f3-a46eec60f333
Rosengarten, James A.
3ccf8397-ca9e-4b04-864f-5c2515db8965
Garbis, Spiros D.
7067fd19-50c9-4d42-9611-f370289470bd
Curzen, Nick P.
70f3ea49-51b1-418f-8e56-8210aef1abf4
Morgan, John M.
ac98099e-241d-4551-bc98-709f6dfc8680
Townsend, Paul A
143dc9b4-fc30-477e-bb38-28a6fde5cea3
Scott, Paul A.
5a16b1f4-74d3-473f-9eeb-c2a823d690dc
Zeidan, Bashar
acd18415-22ee-43b8-a102-a36ea22dd0af
Ng, Leong L.
7c95e856-3d42-42b5-9f3d-467efa7145c2
Zeb, Mehmood
469fda8e-8318-4fe5-97f3-a46eec60f333
Rosengarten, James A.
3ccf8397-ca9e-4b04-864f-5c2515db8965
Garbis, Spiros D.
7067fd19-50c9-4d42-9611-f370289470bd
Curzen, Nick P.
70f3ea49-51b1-418f-8e56-8210aef1abf4
Morgan, John M.
ac98099e-241d-4551-bc98-709f6dfc8680
Townsend, Paul A
143dc9b4-fc30-477e-bb38-28a6fde5cea3

Scott, Paul A., Zeidan, Bashar, Ng, Leong L., Zeb, Mehmood, Rosengarten, James A., Garbis, Spiros D., Curzen, Nick P., Morgan, John M. and Townsend, Paul A (2012) Proteomic profiling to identify prognostic biomarkers in heart failure. In Vivo, 26 (6), 875-882. (PMID:23160667)

Record type: Article

Abstract

Background: the ability to predict mode, as well as risk, of death in left ventricular systolic dysfunction (LVSD) is important, as the clinical and cost-effectiveness of implantable cardioverter defibrillators (ICD) therapy depends on its use in appropriately selected patient populations. The value of a proteomic approach in identifying prognostic biomarkers in LVSD is unknown. The aims of this pilot study were to use proteomic techniques to identify serum biomarkers associated with LVSD and to prospectively explore their association with prognosis.

Patients and methods: serum was analysed by surface-enhanced laser desorption ionisation time-of-flight mass spectrometry (SELDI-TOF MS) in patients with (n=78) and without (n=45) systolic heart failure (SHF). Spectra were compared to identify differentially expressed signal peaks as potential biomarker indicators. The ability of these peaks to predict all-cause mortality and survival with appropriate ICD therapy was then tested prospectively in patients with ICDs, on the background of LVSD (n=141).

Results: for the identification stage spectra (2-200 kDa) from SHF and control patients were randomly separated into two equally sized discovery and validation sets. Six protein peaks were identified that were differentially expressed in SHF in both sets. In the prospective phase, during a mean follow-up of 15±3 months, 11 patients died and 39 survived with appropriate ICD therapy. Five out of the six proteomic biomarkers predicted all-cause mortality but none predicted appropriate ICD therapy.

Conclusion: these results provide proof-of-principle and are supportive of the SELDI proteomic approach as a high-throughput screening tool in identifying potentially prognostic protein peaks in patients with LVSD.

Full text not available from this repository.

More information

Published date: November 2012
Keywords: implantable cardioverter defibrillators, heart failure, biomarkers, mortalityarrhythmias, proteomics, SELDI-TOF MS
Organisations: Cancer Sciences, Human Development & Health

Identifiers

Local EPrints ID: 345485
URI: https://eprints.soton.ac.uk/id/eprint/345485
ISSN: 0258-851X
PURE UUID: 68b8b4c8-b80c-4036-85a8-0acbd017124c
ORCID for Spiros D. Garbis: ORCID iD orcid.org/0000-0002-1050-0805

Catalogue record

Date deposited: 23 Nov 2012 09:49
Last modified: 07 Jun 2019 00:32

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×