About this Research Topic
In developed countries, economic and public health efforts in the form of kidney transplant programs, dialysis, and nephrology clinics are being made to address the burden of kidney disease, which is mainly related to non-communicable chronic diseases such as hypertension and diabetes.
In young adulthood, between the ages of 18 and 35, proteinuria and hypertension may be harbingers of current or future kidney disease unrelated to common risk factors, while people come to dialysis or transplantation in 25% of cases without a diagnosis of causative disease. Genetic and familial aspects of kidney disease are often neglected, and improvement of the phenotypic description with the aim of better genetic classification and understanding of disease mechanisms seems advisable.
To detect kidney disease in a timely manner, we propose to conduct research, including in small groups of individuals, using a balanced multilevel or a multistage approach between the traditional screening methods - urinalysis, serum creatinine, blood pressure measurement- and genetics, as the cost of the latter continues to decline over time. It is also important to explore the use of artificial intelligence (AI) in the detection of kidney disease through phenotypic screening.
The screening for kidney disease in this call for papers could also be retrospectively analyzed together with kidney biopsy and subsequent follow-up, as they are the previous classical ways to diagnose kidney disease. The subsequent investigative steps: genetic analysis by microarrays or next-generation sequencing on predefined panels of genes already recognized as associated with kidney disease, whole exome, and whole genome sequencing, could be reported as prospective or retrospective analyses. Genetic investigation and/ or AI analysis are an add-on to the accuracy of diagnosis and classification of kidney disease, oriented to causal inference.
Research in this area could look for new markers, metabolomics, GFR measurements, and/or computations that are adapted to each population to achieve better follow-ups and pave the way for timely treatment through preventive personalized therapies promoting a patient-centered approach.
Kidney disease screening with solid clues of efficacy may revamp this approach in the early stages of the disease.
This Research Topic welcomes all article types.
In young adulthood, between the ages of 18 and 35, proteinuria and hypertension may be harbingers of current or future kidney disease unrelated to common risk factors, while people come to dialysis or transplantation in 25% of cases without a diagnosis of causative disease. Genetic and familial aspects of kidney disease are often neglected, and improvement of the phenotypic description with the aim of better genetic classification and understanding of disease mechanisms seems advisable.
To detect kidney disease in a timely manner, we propose to conduct research, including in small groups of individuals, using a balanced multilevel or a multistage approach between the traditional screening methods - urinalysis, serum creatinine, blood pressure measurement- and genetics, as the cost of the latter continues to decline over time. It is also important to explore the use of artificial intelligence (AI) in the detection of kidney disease through phenotypic screening.
The screening for kidney disease in this call for papers could also be retrospectively analyzed together with kidney biopsy and subsequent follow-up, as they are the previous classical ways to diagnose kidney disease. The subsequent investigative steps: genetic analysis by microarrays or next-generation sequencing on predefined panels of genes already recognized as associated with kidney disease, whole exome, and whole genome sequencing, could be reported as prospective or retrospective analyses. Genetic investigation and/ or AI analysis are an add-on to the accuracy of diagnosis and classification of kidney disease, oriented to causal inference.
Research in this area could look for new markers, metabolomics, GFR measurements, and/or computations that are adapted to each population to achieve better follow-ups and pave the way for timely treatment through preventive personalized therapies promoting a patient-centered approach.
Kidney disease screening with solid clues of efficacy may revamp this approach in the early stages of the disease.
This Research Topic welcomes all article types.
Keywords: nephrology, clinical research, kidney disease, young adulthood, early diagnosis
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