Please use this identifier to cite or link to this item:
Title: Prognosis and personalized in silico prediction of treatment efficacy in cardiovascular and chronic kidney disease : a proof-of-concept study
Author(s): Jaimes Campos, Mayra Alejandra
Beige, Joachim
[und viele weitere]
Issue Date: 2023
Type: Article
Language: English
Abstract: (1) Background: Kidney and cardiovascular diseases are responsible for a large fraction of population morbidity and mortality. Early, targeted, personalized intervention represents the ideal approach to cope with this challenge. Proteomic/peptidomic changes are largely responsible for the onset and progression of these diseases and should hold information about the optimal means of treatment and prevention. (2) Methods: We investigated the prediction of renal or cardiovascular events using previously defined urinary peptidomic classifiers CKD273, HF2, and CAD160 in a cohort of 5585 subjects, in a retrospective study. (3) Results: We have demonstrated a highly significant prediction of events, with an HR of 2.59, 1.71, and 4.12 for HF, CAD, and CKD, respectively. We applied in silico treatment, implementing on each patient’s urinary profile changes to the classifiers corresponding to exactly defined peptide abundance changes, following commonly used interventions (MRA, SGLT2i, DPP4i, ARB, GLP1RA, olive oil, and exercise), as defined in previous studies. Applying the proteomic classifiers after the in silico treatment indicated the individual benefits of specific interventions on a personalized level. (4) Conclusions: The in silico evaluation may provide information on the future impact of specific drugs and interventions on endpoints, opening the door to a precision-based medicine approach. An investigation into the extent of the benefit of this approach in a prospective clinical trial is warranted.
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Journal Title: Pharmaceuticals
Publisher: MDPI
Publisher Place: Basel
Volume: 16
Issue: 9
Original Publication: 10.3390/ph16091298
Page Start: 1
Page End: 16
Appears in Collections:Open Access Publikationen der MLU

Files in This Item:
File Description SizeFormat 
pharmaceuticals-16-01298-v2.pdf8.99 MBAdobe PDFThumbnail