European journal of heart failure · 2022
Whole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failure.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Nath Mintu, Romaine Simon P R, Koekemoer Andrea, Hamby Stephen, Webb Thomas R, Nelson Christopher P, Castellanos-Uribe Marcos, Papakonstantinou Manolo, Anker Stefan D, Lang Chim C, Metra Marco, Zannad Faiez, Filippatos Gerasimos, van Veldhuisen Dirk J, Cleland John G, Ng Leong L, May Sean T, Marelli-Berg Federica, Voors Adriaan A, Timmons James A, Samani Nilesh J
Аннотация
AIMS: 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.
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.