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Metabolomic profiling of renal cyst fluid in advanced ADPKD: insights from dialysis and transplantation cohorts
Article
Heckscher, Simon, Ihlo, Nicolas A., Schueler, Jan, Kellermeier, Fabian, Werner, Jens M.
, Nuebel, Barbara, Gross, Verena, May, Matthias, Wullich, Bernd, Kammerl, Martin, Gnewuch, Carsten, Burkhardt, Ralph
, Buchholz, Björn, Pion, Eric, Aung, Thiha, Banas, Miriam, Schlitt, Hans J.
, Oefner, Peter J.
, Dettmer, Katja
, Gronwald, Wolfram
, Behr, Merle
, Haerteis, Silke
and Schmidt, Katharina M.
(2025)
Metabolomic profiling of renal cyst fluid in advanced ADPKD: insights from dialysis and transplantation cohorts.
Metabolomics 21 (4).
DOI to cite this document: 10.5283/epub.77000
Abstract
Background Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disorder characterized by progressive renal cyst formation, often leading to end-stage kidney disease (ESKD). In contrast to the urinary metabolome in ADPKD, the composition of renal cyst fluid remains largely unexplored. Methods We conducted a comprehensive metabolomic analysis of renal cyst ...
Background
Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disorder characterized by progressive renal cyst formation, often leading to end-stage kidney disease (ESKD). In contrast to the urinary metabolome in ADPKD, the composition of renal cyst fluid remains largely unexplored.
Methods
We conducted a comprehensive metabolomic analysis of renal cyst fluid from 26 ADPKD patients (20 on dialysis, six with kidney transplants) using ¹H-NMR spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Cysts were clustered based on metabolite profiles, and differences were analyzed across groups defined by renal function status (dialysis vs. transplant), cyst volume, and cyst fluid sodium concentrations.
Results
Dialysis patients and transplant recipients differed significantly in their renal cyst fluid metabolomes. The former exhibited higher concentrations of myoinositol, creatinine, sucrose, τ-methylhistidine, trigonelline, and sarcosine, while the latter showed increased levels of leucine, isoleucine, valine and alanine. Remarkably, metabolites of the immunosuppressive prodrug mycophenolate mofetil were detected in renal cyst fluids after kidney transplantation. Despite intra- and interindividual variability, cyst fluid from the same patient displayed greater homogeneity. Interestingly, metabolomic profiles were not altered by cyst size.
Conclusion
This first systematic metabolomic analysis of renal cyst fluid in advanced ADPKD reveals distinct metabolic signatures linked to renal function status. The data provides novel insights into the pathophysiology of ADPKD and highlight the potentials of renal cyst fluid metabolomics for identifying biomarkers and therapeutic targets.
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Details
| Item type | Article | ||||
| Journal or Publication Title | Metabolomics | ||||
| Publisher | Springer | ||||
| Open Access Type | DEAL (Springer) | ||||
| Volume | 21 | ||||
| Number of Issue or Book Chapter | 4 | ||||
| Date | 26 June 2025 | ||||
| Date of publication | 02 Jul 2025 09:49 | ||||
| Institutions | Medicine > Lehrstuhl für Chirurgie Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner) Medicine > Abteilung für Nephrologie Medicine > Lehrstuhl für Klinische Chemie und Laboratoriumsmedizin Biology, Preclinical Medicine > Institut für Anatomie > Professor for Molecular and Cellular Anatomy - Prof. Dr. Silke Härteis Informatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Maschinelles Lernen (Prof. Dr. Merle Behr) | ||||
| Projects |
Funded by:
Deutsche Forschungsgemeinschaft (DFG)
(509149993)
| ||||
| Identification Number |
| ||||
| Keywords | ADPKD · Cyst fluid · Metabolomics · NMR spectroscopy · Mass spectrometry · Patient clustering | ||||
| Dewey Decimal Classification | 000 Computer science, information & general works > 004 Computer science 600 Technology > 610 Medical sciences Medicine | ||||
| Status | Published | ||||
| Refereed | Yes, this version has been refereed | ||||
| Created at the University of Regensburg | Partially | ||||
| URN of the UB Regensburg | urn:nbn:de:bvb:355-epub-770006 | ||||
| Item ID | 77000 |
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