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dc.contributor.authorRomaine, Simon
dc.contributor.authorSamani, Nilesh
dc.date.accessioned2022-07-19T13:44:52Z
dc.date.available2022-07-19T13:44:52Z
dc.date.issued2022-06
dc.identifier.citationNath, M., Romaine, S., Koekemoer, A., Hamby, S., Webb, T. R., Nelson, C. P., Castellanos-Uribe, M., Papakonstantinou, M., Anker, S. D., Lang, C. C., Metra, M., Zannad, F., Filippatos, G., van Veldhuisen, D. J., Cleland, J. G., Ng, L. L., May, S. T., Marelli-Berg, F., Voors, A. A., Timmons, J. A., … Samani, N. J. (2022). Whole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failure. European journal of heart failure, 24(6), 1009–1019. https://doi.org/10.1002/ejhf.2540en_US
dc.identifier.other10.1002/ejhf.2540
dc.identifier.urihttp://hdl.handle.net/20.500.12904/15653
dc.description.abstractAims: Chronic heart failure (CHF) is a systemic syndrome with a poor prognosis and a need for novel therapies. We investigated whether whole blood transcriptomic profiling can provide new mechanistic insights into cardiovascular (CV) mortality in CHF. Methods and results: Transcriptome profiles were generated at baseline from 944 CHF patients from the BIOSTAT-CHF study, of whom 626 survived and 318 died from a CV cause during a follow-up of 21 months. Multivariable analysis, including adjustment for cell count, identified 1153 genes (6.5%) that were differentially expressed between those that survived or died and strongly related to a validated clinical risk score for adverse prognosis. The differentially expressed genes mainly belonged to five non-redundant pathways: adaptive immune response, proteasome-mediated ubiquitin-dependent protein catabolic process, T-cell co-stimulation, positive regulation of T-cell proliferation, and erythrocyte development. These five pathways were selectively related (RV coefficients >0.20) with seven circulating protein biomarkers of CV mortality (fibroblast growth factor 23, soluble ST2, adrenomedullin, hepcidin, pentraxin-3, WAP 4-disulfide core domain 2, and interleukin-6) revealing an intricate relationship between immune and iron homeostasis. The pattern of survival-associated gene expression matched with 29 perturbagen-induced transcriptome signatures in the iLINCS drug-repurposing database, identifying drugs, approved for other clinical indications, that were able to reverse in vitro the molecular changes associated with adverse prognosis in CHF. Conclusion: Systematic modelling of the whole blood protein-coding transcriptome defined molecular pathways that provide a link between clinical risk factors and adverse CV prognosis in CHF, identifying both established and new potential therapeutic targets.
dc.description.urihttps://onlinelibrary.wiley.com/doi/10.1002/ejhf.2540en_US
dc.language.isoenen_US
dc.subjectchronic heart failureen_US
dc.subjectdrug-repurposingen_US
dc.subjectfibroblast growth factor 23en_US
dc.subjectinterleukinsen_US
dc.subjectironen_US
dc.subjectRNAen_US
dc.subjectT-cellsen_US
dc.titleWhole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failureen_US
dc.typeArticleen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
rioxxterms.versionNAen_US
rioxxterms.versionofrecordhttps://doi.org/10.1002/ejhf.2540en_US
rioxxterms.typeJournal Article/Reviewen_US
refterms.panelUnspecifieden_US
html.description.abstractAims: Chronic heart failure (CHF) is a systemic syndrome with a poor prognosis and a need for novel therapies. We investigated whether whole blood transcriptomic profiling can provide new mechanistic insights into cardiovascular (CV) mortality in CHF. Methods and results: Transcriptome profiles were generated at baseline from 944 CHF patients from the BIOSTAT-CHF study, of whom 626 survived and 318 died from a CV cause during a follow-up of 21 months. Multivariable analysis, including adjustment for cell count, identified 1153 genes (6.5%) that were differentially expressed between those that survived or died and strongly related to a validated clinical risk score for adverse prognosis. The differentially expressed genes mainly belonged to five non-redundant pathways: adaptive immune response, proteasome-mediated ubiquitin-dependent protein catabolic process, T-cell co-stimulation, positive regulation of T-cell proliferation, and erythrocyte development. These five pathways were selectively related (RV coefficients >0.20) with seven circulating protein biomarkers of CV mortality (fibroblast growth factor 23, soluble ST2, adrenomedullin, hepcidin, pentraxin-3, WAP 4-disulfide core domain 2, and interleukin-6) revealing an intricate relationship between immune and iron homeostasis. The pattern of survival-associated gene expression matched with 29 perturbagen-induced transcriptome signatures in the iLINCS drug-repurposing database, identifying drugs, approved for other clinical indications, that were able to reverse in vitro the molecular changes associated with adverse prognosis in CHF. Conclusion: Systematic modelling of the whole blood protein-coding transcriptome defined molecular pathways that provide a link between clinical risk factors and adverse CV prognosis in CHF, identifying both established and new potential therapeutic targets.en_US
rioxxterms.funder.project94a427429a5bcfef7dd04c33360d80cden_US


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