Chronic Kidney Disease (CKD) is a clinical condition associated with an increased risk for cardiovascular (CV) events, all-cause mortality and End Stage Kidney Disease (ESKD). Moreover, its incidence and prevalence are increasing dramatically, having nearly doubled in the past two decades. One important issue in CKD patients is their residual risk, namely the presence of modifiable risk factors over time despite treatment with agents aimed at "normalizing" such risk factors. One example is represented by albuminuria. It has been shown that >60% patients have mild-to-severe albuminuria despite optimal treatment with RAASi. This can be explained with the individual variability in response to treatment. Other than treatment response, a large variability in developing ESKD or CV endpoints that is not completely captured by baseline levels of kidney function (eGFR) or albuminuria. Further effort is needed to identify patients who will likely develop a cardio-renal event (prognosis) as well as those who are more likely to respond to a specific treatment (prediction). Hence, more focus is needed on biomarker discovery and genotyping, but also to take into account personal, social, and environmental factors to fully provide precision medicine in CKD.
The objective of the Research Topic is to point out the state of art of personalized medicine in CKD, in terms of both prognosis and prediction. All original articles that evaluate novel biomarkers (data about urine or blood biomarkers, omics as well as integrated omics would be highly appreciated) used to predict events in CKD and/or treatment response could be considered for this topic. With respect to prognosis, individual risk prediction models showing how to improve risk stratification (on top of the already established risk factors) could be considered as well. Similarly, original articles related to an individual’s personality, coping mechanisms, preferences, values, social support, financial resources and life circumstances – personomics – will be appreciated. For this Research Topic, also narrative or systematic reviews which summarize the state of art around the aforementioned and novel research ideas/concepts should be accepted.
The Personalized Medicine in CKD patients Research Topic covers, but is not limited to:
- Proteomics and risk stratification in CKD: a focus on CKD273 or other classifiers.
-Prognostic role of SNP in patients with CKD.
- How genetic variants (SNP) influence treatment response in CKD.
- Integrated omics (metabolomic, proteomic, genomic) in CKD.
- Risk stratification: are there sufficient individual risk prediction models (i.e. risk scores) to accurately predict prognosis in CKD patients?
- Personomics: personalized treatment of CKD as influenced by personal, social, and environmental factors of the patient
- Novel concepts moving from cohort to precision medicine
Chronic Kidney Disease (CKD) is a clinical condition associated with an increased risk for cardiovascular (CV) events, all-cause mortality and End Stage Kidney Disease (ESKD). Moreover, its incidence and prevalence are increasing dramatically, having nearly doubled in the past two decades. One important issue in CKD patients is their residual risk, namely the presence of modifiable risk factors over time despite treatment with agents aimed at "normalizing" such risk factors. One example is represented by albuminuria. It has been shown that >60% patients have mild-to-severe albuminuria despite optimal treatment with RAASi. This can be explained with the individual variability in response to treatment. Other than treatment response, a large variability in developing ESKD or CV endpoints that is not completely captured by baseline levels of kidney function (eGFR) or albuminuria. Further effort is needed to identify patients who will likely develop a cardio-renal event (prognosis) as well as those who are more likely to respond to a specific treatment (prediction). Hence, more focus is needed on biomarker discovery and genotyping, but also to take into account personal, social, and environmental factors to fully provide precision medicine in CKD.
The objective of the Research Topic is to point out the state of art of personalized medicine in CKD, in terms of both prognosis and prediction. All original articles that evaluate novel biomarkers (data about urine or blood biomarkers, omics as well as integrated omics would be highly appreciated) used to predict events in CKD and/or treatment response could be considered for this topic. With respect to prognosis, individual risk prediction models showing how to improve risk stratification (on top of the already established risk factors) could be considered as well. Similarly, original articles related to an individual’s personality, coping mechanisms, preferences, values, social support, financial resources and life circumstances – personomics – will be appreciated. For this Research Topic, also narrative or systematic reviews which summarize the state of art around the aforementioned and novel research ideas/concepts should be accepted.
The Personalized Medicine in CKD patients Research Topic covers, but is not limited to:
- Proteomics and risk stratification in CKD: a focus on CKD273 or other classifiers.
-Prognostic role of SNP in patients with CKD.
- How genetic variants (SNP) influence treatment response in CKD.
- Integrated omics (metabolomic, proteomic, genomic) in CKD.
- Risk stratification: are there sufficient individual risk prediction models (i.e. risk scores) to accurately predict prognosis in CKD patients?
- Personomics: personalized treatment of CKD as influenced by personal, social, and environmental factors of the patient
- Novel concepts moving from cohort to precision medicine