WP4 CRS biomarker identification

WP4 - CRS biomarker identification [Months: 3-48]

DSM

Description and role of ESRs / beneficiaries / partner organizations: Biomarker panels for increased CV risk in CKD patients (and thus CRS) are not yet available. Nonetheless, identification of such biomarker panels would crucially improve diagnosis, patient stratification and therapy guidance, as demonstrated by previous accomplishments of our partners in the field of diabetic kidney disease. In this WP, ESRs will be trained in proteomics/peptidomics analyses, bio-informatics and biostatistics to identify:

 

Task 3.1: Diagnostic biomarkers for established CRS as well as biomarkers with capacity to predict the development of CRS in CKD patients, using plasma peptidomics (ESR1/UKA1), plasma proteomics (ESR2/BRFAA) and urine peptidomics (ESR3/MOS) of well-defined and already available cohorts of CRS patients through partners UKA1/2, KI and KUL.

 

Task 3.2: Biomarkers for vascular calcification in CKD patients, by combining calcification and proteomics analysis of vascular biopsies and associated plasma samples of CKD patients. Vascular calcification is a main risk factor for CVD and highly increased in CKD. ESR2/BRFAA will be trained to generate proteomics data for vascular biopsies of CKD5 patients undergoing renal transplantation, based on previous expertise. The biopsies are already available from partner KI, classified in no-minimally vs moderately-extensively calcified, and have cardiac CT-based calcification scores available. Associated plasma proteomics data are also available. ESR10/KI will use these data to identify proteins in plasma and vasculature associated with vascular calcification.

 

Task 3.3: Post-translational modifications (PTMs) as potential biomarkers of CRS in plasma from CRS patients. As PTMs can critically affect protein functions and have been increasingly identified in CKD, PTMs of calcification regulators in plasma present promising biomarkers for calcification and CRS in CKD and will be identified by ESR9/ DSM. Of note, ESR4/MUW will cooperate intensively with ESR1/UKA1, ESR2/BRFAA, ESR3/MOS, ESR9/DSM and ESR10/KI for biomarker identification by bioinformatics analyses of proteomics/peptidomics data. Identified biomarkers will be validated in independent patient cohorts.

© 2018 CaReSyAn

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 764474.

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