Untargeted Metabolomics Reveals N, N, N-trimethyl-L-alanyl-L-proline Betaine (TMAP) As a Novel Biomarker of Kidney Function
Authors
Affiliations
The diagnosis and prognosis of chronic kidney disease (CKD) currently relies on very few circulating small molecules, which can vary by factors unrelated to kidney function. In end-stage renal disease (ESRD), these same small molecules are used to determine dialysis dose and dialytic clearance. Therefore, we aimed to identify novel plasma biomarkers to estimate kidney function in CKD and dialytic clearance in ESRD. Untargeted metabolomics was performed on plasma samples from patients with a single kidney, non-dialysis CKD, ESRD and healthy controls. For ESRD patients, pre- and post-dialysis plasma samples were obtained from several dialysis modalities. Metabolomics analysis revealed over 400 significantly different features in non-dialysis CKD and ESRD plasma compared to controls while less than 35 features were significantly altered in patients with a single kidney. N,N,N-trimethyl-L-alanyl-L-proline betaine (TMAP, AUROC = 0.815) and pyrocatechol sulfate (AUROC = 0.888) outperformed creatinine (AUROC = 0.745) in accurately identifying patients with a single kidney. Several metabolites accurately predicted ESRD; however, when comparing pre-and post-hemodialysis, TMAP was the most robust biomarker of dialytic clearance for all modalities (AUROC = 0.993). This study describes TMAP as a novel potential biomarker of kidney function and dialytic clearance across several hemodialysis modalities.
Li H, Huang J, Zhao D, Zhu L, Zhang Z, Yi M Neural Regen Res. 2024; 20(10):2982-2997.
PMID: 39610107 PMC: 11826447. DOI: 10.4103/NRR.NRR-D-23-01979.
Maguire C, Chen J, Rouphael N, Pickering H, Phan H, Glascock A bioRxiv. 2024; .
PMID: 39605478 PMC: 11601417. DOI: 10.1101/2024.11.14.622799.
Peris-Fernandez M, Roca-Marugan M, Amengual J, Balaguer-Timor A, Viejo-Boyano I, Soldevila-Orient A Int J Mol Sci. 2024; 25(17).
PMID: 39273311 PMC: 11394964. DOI: 10.3390/ijms25179364.
A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes.
Halama A, Zaghlool S, Thareja G, Kader S, Al Muftah W, Mook-Kanamori M Nat Commun. 2024; 15(1):7111.
PMID: 39160153 PMC: 11333501. DOI: 10.1038/s41467-024-51134-x.
Geographic variation of mutagenic exposures in kidney cancer genomes.
Senkin S, Moody S, Diaz-Gay M, Abedi-Ardekani B, Cattiaux T, Ferreiro-Iglesias A Nature. 2024; 629(8013):910-918.
PMID: 38693263 PMC: 11111402. DOI: 10.1038/s41586-024-07368-2.