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Metabolomic profiling of overnight peritoneal dialysis effluents predicts the peritoneal equilibration test type

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Abstract
This study primarily aimed to evaluate whether peritoneal equilibration test (PET) results can be predicted through the metabolomic analysis of overnight peritoneal dialysis (PD) efuents. From a total of 125 patients, overnight PD efuents on the day of the frst PET after PD initiation were analyzed. A modifed 4.25% dextrose PET was performed, and the PET type was categorized according to the dialysate-to-plasma creatinine ratio at the 4-h dwell time during the PET as follows: high, high average, low average, or low transporter. Nuclear magnetic resonance (NMR)based metabolomics was used to analyze the efuents and identify the metabolites. The predictive performances derived from the orthogonal projection to latent structure discriminant analysis (OPLS-DA) modeling of the NMR spectrum were estimated by calculating the area under the curve (AUC) using receiver operating characteristic curve analysis. The OPLS-DA score plot indicated signifcant metabolite diferences between high and low PET types. The relative concentrations of alanine and creatinine were greater in the high transporter type than in the low transporter type. The relative concentrations of glucose and lactate were greater in the low transporter type than in the high transporter type. The AUC of a composite of four metabolites was 0.975 in distinguish between high and low PET types. Measured PET results correlated well with the total NMR metabolic profle of overnight PD efuents.
Issued Date
2023
Hyo Jin Kim
Munki Choo
Hyuk Nam Kwon
Kyung DonYoo
Yunmi Kim
BodokhsurenTsogbadrakh
Eunjeong Kang
Sunghyouk Park
Kook‑Hwan Oh
Type
Article
Keyword
CreatinineDextroseDialysisDialysis SolutionsDiscriminant analysisHuman beingsLactic acidMembrane Transport ProteinsMetabolitesMetabolomicsNuclear magnetic resonancePeritoneal dialysisPeritoneumScience
DOI
10.1038/s41598-023-29741-3
URI
https://oak.ulsan.ac.kr/handle/2021.oak/15828
Publisher
SCIENTIFIC REPORTS
Language
한국어
ISSN
2045-2322
Citation Volume
13
Citation Number
1
Citation Start Page
1
Citation End Page
9
Appears in Collections:
Medicine > Nursing
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