ArticleAmerican journal of physiology. Renal physiology2023
Metabolomic profiling to identify early urinary biomarkers and metabolic pathway alterations in autosomal dominant polycystic kidney disease.
Article in American journal of physiology. Renal physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Urine as a source of biomarkers and biological knowledge in chronic kidney disease.Nature reviews. Nephrology · 2026Review
- Developing serum proteomics based prediction models of disease progression in ADPKD.Nature communications · 2025Article
- Physiologic mechanisms underlying polycystic kidney disease.Physiological reviews · 2025Review
- Metabolomic profiling of renal cyst fluid in advanced ADPKD: insights from dialysis and transplantation cohorts.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- AAV1-CFTR preferentially transduces cysts and reduces cyst size in a mouse model of ADPKD.American journal of physiology. Cell physiology · 2025Article
- Electrolyte and metabolite composition of cystic fluid from a rat model of ARPKD.Communications biology · 2025Article
- Urinary Biomarkers in Monitoring the Progression and Treatment of Autosomal Dominant Polycystic Kidney Disease-The Promised Land?Medicina (Kaunas, Lithuania) · 2023Review
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of numerous fluid-filled cysts that lead to progressive loss of functional nephrons. Currently, there is an unmet need for diagnostic and prognostic indicators of early stages of the disease. Metabolites were extracted from the urine of patients with early-stage ADPKD (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.