Cargando…
OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction
Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomi...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8745343/ https://www.ncbi.nlm.nih.gov/pubmed/35008760 http://dx.doi.org/10.3390/ijms23010336 |
_version_ | 1784630322671910912 |
---|---|
author | Provenzano, Michele Serra, Raffaele Garofalo, Carlo Michael, Ashour Crugliano, Giuseppina Battaglia, Yuri Ielapi, Nicola Bracale, Umberto Marcello Faga, Teresa Capitoli, Giulia Galimberti, Stefania Andreucci, Michele |
author_facet | Provenzano, Michele Serra, Raffaele Garofalo, Carlo Michael, Ashour Crugliano, Giuseppina Battaglia, Yuri Ielapi, Nicola Bracale, Umberto Marcello Faga, Teresa Capitoli, Giulia Galimberti, Stefania Andreucci, Michele |
author_sort | Provenzano, Michele |
collection | PubMed |
description | Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease. |
format | Online Article Text |
id | pubmed-8745343 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87453432022-01-11 OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction Provenzano, Michele Serra, Raffaele Garofalo, Carlo Michael, Ashour Crugliano, Giuseppina Battaglia, Yuri Ielapi, Nicola Bracale, Umberto Marcello Faga, Teresa Capitoli, Giulia Galimberti, Stefania Andreucci, Michele Int J Mol Sci Review Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease. MDPI 2021-12-29 /pmc/articles/PMC8745343/ /pubmed/35008760 http://dx.doi.org/10.3390/ijms23010336 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Provenzano, Michele Serra, Raffaele Garofalo, Carlo Michael, Ashour Crugliano, Giuseppina Battaglia, Yuri Ielapi, Nicola Bracale, Umberto Marcello Faga, Teresa Capitoli, Giulia Galimberti, Stefania Andreucci, Michele OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction |
title | OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction |
title_full | OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction |
title_fullStr | OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction |
title_full_unstemmed | OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction |
title_short | OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction |
title_sort | omics in chronic kidney disease: focus on prognosis and prediction |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8745343/ https://www.ncbi.nlm.nih.gov/pubmed/35008760 http://dx.doi.org/10.3390/ijms23010336 |
work_keys_str_mv | AT provenzanomichele omicsinchronickidneydiseasefocusonprognosisandprediction AT serraraffaele omicsinchronickidneydiseasefocusonprognosisandprediction AT garofalocarlo omicsinchronickidneydiseasefocusonprognosisandprediction AT michaelashour omicsinchronickidneydiseasefocusonprognosisandprediction AT cruglianogiuseppina omicsinchronickidneydiseasefocusonprognosisandprediction AT battagliayuri omicsinchronickidneydiseasefocusonprognosisandprediction AT ielapinicola omicsinchronickidneydiseasefocusonprognosisandprediction AT bracaleumbertomarcello omicsinchronickidneydiseasefocusonprognosisandprediction AT fagateresa omicsinchronickidneydiseasefocusonprognosisandprediction AT capitoligiulia omicsinchronickidneydiseasefocusonprognosisandprediction AT galimbertistefania omicsinchronickidneydiseasefocusonprognosisandprediction AT andreuccimichele omicsinchronickidneydiseasefocusonprognosisandprediction |