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Metabolomic profiling of renal cyst fluid in advanced ADPKD: insights from dialysis and transplantation cohorts
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
und Schmidt, Katharina M.
(2025)
Metabolomic profiling of renal cyst fluid in advanced ADPKD: insights from dialysis and transplantation cohorts.
Metabolomics 21 (4).
Veröffentlichungsdatum dieses Volltextes: 02 Jul 2025 09:49
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.77000
Zusammenfassung
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
| Dokumentenart | Artikel | ||||
| Titel eines Journals oder einer Zeitschrift | Metabolomics | ||||
| Verlag: | Springer | ||||
|---|---|---|---|---|---|
| Band: | 21 | ||||
| Nummer des Zeitschriftenheftes oder des Kapitels: | 4 | ||||
| Datum | 26 Juni 2025 | ||||
| Institutionen | Medizin > Lehrstuhl für Chirurgie Medizin > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner) Medizin > Abteilung für Nephrologie Medizin > Lehrstuhl für Klinische Chemie und Laboratoriumsmedizin Biologie und Vorklinische Medizin > Institut für Anatomie > Professur für Molekulare und Zelluläre Anatomie - Prof. Dr. Silke Härteis Informatik und Data Science > Fachbereich Maschinelles Lernen und Data Science > Chair of Machine Learning (Prof. Dr. Merle Behr) | ||||
| Projekte |
Gefördert von:
Deutsche Forschungsgemeinschaft (DFG)
(509149993)
| ||||
| Identifikationsnummer |
| ||||
| Stichwörter / Keywords | ADPKD · Cyst fluid · Metabolomics · NMR spectroscopy · Mass spectrometry · Patient clustering | ||||
| Dewey-Dezimal-Klassifikation | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Zum Teil | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-770006 | ||||
| Dokumenten-ID | 77000 |
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