Matches in SemOpenAlex for { <https://semopenalex.org/work/W3036224084> ?p ?o ?g. }
- W3036224084 endingPage "1148" @default.
- W3036224084 startingPage "1136" @default.
- W3036224084 abstract "BACKGROUND Circulating extracellular vesicles (EVs) are raising considerable interest as a non-invasive diagnostic tool, as they are easily detectable in biologic fluids and contain a specific set of nucleic acids, proteins, and lipids reflecting pathophysiologic conditions. We aimed to investigate differences in plasma-derived EV surface protein profiles as a biomarker to be used in combination with endomyocardial biopsies (EMBs) for the diagnosis of allograft rejection. METHODS Plasma was collected from 90 patients (53 training cohort, 37 validation cohort) before EMB. EV concentration was assessed by nanoparticle tracking analysis. EV surface antigens were measured using a multiplex flow cytometry assay composed of 37 fluorescently labeled capture bead populations coated with specific antibodies directed against respective EV surface epitopes. RESULTS The concentration of EVs was significantly increased and their diameter decreased in patients undergoing rejection as compared with negative ones. The trend was highly significant for both antibody-mediated rejection and acute cellular rejection (p < 0.001). Among EV surface markers, CD3, CD2, ROR1, SSEA-4, human leukocyte antigen (HLA)-I, and CD41b were identified as discriminants between controls and acute cellular rejection, whereas HLA-II, CD326, CD19, CD25, CD20, ROR1, SSEA-4, HLA-I, and CD41b discriminated controls from patients with antibody-mediated rejection. Receiver operating characteristics curves confirmed a reliable diagnostic performance for each single marker (area under the curve range, 0.727–0.939). According to differential EV-marker expression, a diagnostic model was built and validated in an external cohort of patients. Our model was able to distinguish patients undergoing rejection from those without rejection. The accuracy at validation in an independent external cohort reached 86.5%. Its application for patient management has the potential to reduce the number of EMBs. Further studies in a higher number of patients are required to validate this approach for clinical purposes. CONCLUSIONS Circulating EVs are highly promising as a new tool to characterize cardiac allograft rejection and to be complementary to EMB monitoring. Circulating extracellular vesicles (EVs) are raising considerable interest as a non-invasive diagnostic tool, as they are easily detectable in biologic fluids and contain a specific set of nucleic acids, proteins, and lipids reflecting pathophysiologic conditions. We aimed to investigate differences in plasma-derived EV surface protein profiles as a biomarker to be used in combination with endomyocardial biopsies (EMBs) for the diagnosis of allograft rejection. Plasma was collected from 90 patients (53 training cohort, 37 validation cohort) before EMB. EV concentration was assessed by nanoparticle tracking analysis. EV surface antigens were measured using a multiplex flow cytometry assay composed of 37 fluorescently labeled capture bead populations coated with specific antibodies directed against respective EV surface epitopes. The concentration of EVs was significantly increased and their diameter decreased in patients undergoing rejection as compared with negative ones. The trend was highly significant for both antibody-mediated rejection and acute cellular rejection (p < 0.001). Among EV surface markers, CD3, CD2, ROR1, SSEA-4, human leukocyte antigen (HLA)-I, and CD41b were identified as discriminants between controls and acute cellular rejection, whereas HLA-II, CD326, CD19, CD25, CD20, ROR1, SSEA-4, HLA-I, and CD41b discriminated controls from patients with antibody-mediated rejection. Receiver operating characteristics curves confirmed a reliable diagnostic performance for each single marker (area under the curve range, 0.727–0.939). According to differential EV-marker expression, a diagnostic model was built and validated in an external cohort of patients. Our model was able to distinguish patients undergoing rejection from those without rejection. The accuracy at validation in an independent external cohort reached 86.5%. Its application for patient management has the potential to reduce the number of EMBs. Further studies in a higher number of patients are required to validate this approach for clinical purposes. Circulating EVs are highly promising as a new tool to characterize cardiac allograft rejection and to be complementary to EMB monitoring." @default.
- W3036224084 created "2020-06-25" @default.
- W3036224084 creator A5001872562 @default.
- W3036224084 creator A5018227996 @default.
- W3036224084 creator A5022167195 @default.
- W3036224084 creator A5025351795 @default.
- W3036224084 creator A5032095821 @default.
- W3036224084 creator A5036834669 @default.
- W3036224084 creator A5037211974 @default.
- W3036224084 creator A5043746129 @default.
- W3036224084 creator A5047300266 @default.
- W3036224084 creator A5059253699 @default.
- W3036224084 creator A5061094903 @default.
- W3036224084 creator A5062435112 @default.
- W3036224084 creator A5064876009 @default.
- W3036224084 creator A5077167101 @default.
- W3036224084 creator A5077749268 @default.
- W3036224084 creator A5080808518 @default.
- W3036224084 creator A5082533033 @default.
- W3036224084 date "2020-10-01" @default.
- W3036224084 modified "2023-10-14" @default.
- W3036224084 title "Circulating extracellular vesicles as non-invasive biomarker of rejection in heart transplant" @default.
- W3036224084 cites W1734741969 @default.
- W3036224084 cites W1859632889 @default.
- W3036224084 cites W1965214548 @default.
- W3036224084 cites W1979727969 @default.
- W3036224084 cites W1981117979 @default.
- W3036224084 cites W1992927731 @default.
- W3036224084 cites W1994585497 @default.
- W3036224084 cites W2010324176 @default.
- W3036224084 cites W2026898720 @default.
- W3036224084 cites W2027342684 @default.
- W3036224084 cites W2070070981 @default.
- W3036224084 cites W2071520532 @default.
- W3036224084 cites W2080418767 @default.
- W3036224084 cites W2082237882 @default.
- W3036224084 cites W2084788875 @default.
- W3036224084 cites W2108013658 @default.
- W3036224084 cites W2114456475 @default.
- W3036224084 cites W2130485791 @default.
- W3036224084 cites W2133842584 @default.
- W3036224084 cites W2153806783 @default.
- W3036224084 cites W2163369593 @default.
- W3036224084 cites W2166628353 @default.
- W3036224084 cites W2231585839 @default.
- W3036224084 cites W2274860869 @default.
- W3036224084 cites W2510104459 @default.
- W3036224084 cites W2565271826 @default.
- W3036224084 cites W2584870882 @default.
- W3036224084 cites W2586038252 @default.
- W3036224084 cites W2587850954 @default.
- W3036224084 cites W2595618566 @default.
- W3036224084 cites W2599029890 @default.
- W3036224084 cites W2618954006 @default.
- W3036224084 cites W2736355888 @default.
- W3036224084 cites W2768837776 @default.
- W3036224084 cites W2786043034 @default.
- W3036224084 cites W2808148330 @default.
- W3036224084 cites W2810438245 @default.
- W3036224084 cites W2882974125 @default.
- W3036224084 cites W2888181094 @default.
- W3036224084 cites W2902383254 @default.
- W3036224084 cites W2913761274 @default.
- W3036224084 cites W2947340802 @default.
- W3036224084 cites W2956865263 @default.
- W3036224084 cites W2959812202 @default.
- W3036224084 cites W2965574093 @default.
- W3036224084 cites W4250483374 @default.
- W3036224084 cites W4250934836 @default.
- W3036224084 cites W4254350734 @default.
- W3036224084 doi "https://doi.org/10.1016/j.healun.2020.06.011" @default.
- W3036224084 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32665078" @default.
- W3036224084 hasPublicationYear "2020" @default.
- W3036224084 type Work @default.
- W3036224084 sameAs 3036224084 @default.
- W3036224084 citedByCount "46" @default.
- W3036224084 countsByYear W30362240842020 @default.
- W3036224084 countsByYear W30362240842021 @default.
- W3036224084 countsByYear W30362240842022 @default.
- W3036224084 countsByYear W30362240842023 @default.
- W3036224084 crossrefType "journal-article" @default.
- W3036224084 hasAuthorship W3036224084A5001872562 @default.
- W3036224084 hasAuthorship W3036224084A5018227996 @default.
- W3036224084 hasAuthorship W3036224084A5022167195 @default.
- W3036224084 hasAuthorship W3036224084A5025351795 @default.
- W3036224084 hasAuthorship W3036224084A5032095821 @default.
- W3036224084 hasAuthorship W3036224084A5036834669 @default.
- W3036224084 hasAuthorship W3036224084A5037211974 @default.
- W3036224084 hasAuthorship W3036224084A5043746129 @default.
- W3036224084 hasAuthorship W3036224084A5047300266 @default.
- W3036224084 hasAuthorship W3036224084A5059253699 @default.
- W3036224084 hasAuthorship W3036224084A5061094903 @default.
- W3036224084 hasAuthorship W3036224084A5062435112 @default.
- W3036224084 hasAuthorship W3036224084A5064876009 @default.
- W3036224084 hasAuthorship W3036224084A5077167101 @default.
- W3036224084 hasAuthorship W3036224084A5077749268 @default.
- W3036224084 hasAuthorship W3036224084A5080808518 @default.
- W3036224084 hasAuthorship W3036224084A5082533033 @default.