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Metabolic implications of amino acid metabolites in chronic kidney disease progression: a metabolomics analysis using OPLS-DA and MBRole2.0 database

  • Nephrology - Original Paper
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Abstract

Background

As chronic kidney disease (CKD) progresses, metabolites undergo diverse transformations. Nevertheless, the impact of these metabolic changes on the etiology, progression, and prognosis of CKD remains uncertain. Our objective is to conduct a metabolomics analysis to scrutinize metabolites and identify significant metabolic pathways implicated in CKD progression, thereby pinpointing potential therapeutic targets for CKD management.

Methods

We recruited 145 patients with CKD and determined their mGFR by measuring the plasma iohexol clearance, whereupon we partitioned them into four groups based on their mGFR values. Non-targeted metabolomics analysis was conducted using UPLC-MS/MS assays. Differential metabolites were identified via one-way ANOVA, PCA, PLS-DA, and OPLS-DA analyses employing the MetaboAnalyst 5.0 platform. Ultimately, we performed differential metabolite pathway enrichment analysis, using both the MetaboAnalyst 5.0 platform and the MBRole2.0 database.

Results

According to the findings of the MBRole2.0 and MetaboAnalyst 5.0 enrichment analysis, six amino acid metabolism pathways were discovered to have significant roles in the progression of CKD, with the glycine, serine, and threonine metabolism pathway being the most prominent. The latter enriched 14 differential metabolites, of which six decreased while two increased concomitantly with renal function deterioration.

Conclusions

The metabolic analysis unveiled that glycine, serine, and threonine metabolism plays a pivotal role in the progression of CKD. Specifically, glycine was found to increase while serine decreased with the deterioration of CKD.

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Data availability

The original contributions presented in the study are included in the article material, further inquiries can be directed to the corresponding authors.

Code availability

Not applicable.

Abbreviations

ANOVA:

Analysis of variance

BMI:

Body mass index

CKD:

Chronic kidney disease

eGFR:

Estimated glomerular filtration rate

ESI:

Electrospray ionization

FA:

Formic acid

GFR:

Glomerular filtration rate

HILIC:

Hydrophilic interaction chromatography

IAA:

Indole-3-acetic acid

IS:

Indoxyl sulphate

mGFR:

Measured glomerular filtration rate

5-MTP:

5-Methoxy tryptophan

m/z :

Mass to charge ratio

NF-κB:

Nuclear factor-κB

OPLS-DA:

Orthogonal partial least squares-discriminant analysis

OSC:

Orthogonal signal correction

PCA:

Principal component analysis

PCS:

p-Cresyl sulphate

PFPA:

Perfluoropentanoic acid

PLS-DA:

Partial least squares-discriminant analysis

RP:

Reversed-phase

TPH-1:

Tryptophan hydroxylase-1

UPLC-MS/MS:

Ultra performance liquid chromatograph tandem mass spectrometry

VIP:

Variable importance in the projection

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Funding

This study was supported by grants from the National Natural Science Foundation of China (Grant No. 81873631, 81370866, 81070612) and Science and Technology Plan Project of Guangzhou (Grant No. 202002020047, 202007040003), The Science and Technology Development Fund, Macau SAR (File no. 0032/2018/A1).

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Author notes

  1. Jianhao Kang and Xinghua Guo contributed equally to this work.

Authors and Affiliations

  1. Division of Nephrology, Department of Internal Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

    Jianhao Kang, Ying Deng, Jiahui Lai & Xun Liu

  2. Department of Rheumatology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China

    Xinghua Guo

  3. Department of Nephrology, Kiang Wu Hospital, Macau, Macao SAR, China

    Hongquan Peng, Chiwa Aoieong, Tou Tou & Tsungyang Tsai

  4. Department of Cardiovasology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China

    Leile Tang

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  1. Jianhao Kang
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Contributions

All authors have read and approved the manuscript. JK and XG: Conceptualization, methodology, and writing—original draft preparation. XL and HP: Funding acquisition. YD and CA: Visualization and Supervision. JL and TsT: Investigation. LT and TT: Data curation and Validation. XL and HP: Writing-review, funding, and editing.

Corresponding authors

Correspondence to Hongquan Peng or Xun Liu.

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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethical approval

The studies involving human participants were reviewed and approved by the Institutional Review Board of Ethics Commission of Kiang Wu Hospital (KWH 2018-001). The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

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Kang, J., Guo, X., Peng, H. et al. Metabolic implications of amino acid metabolites in chronic kidney disease progression: a metabolomics analysis using OPLS-DA and MBRole2.0 database. Int Urol Nephrol 56, 1173–1184 (2024). https://doi.org/10.1007/s11255-023-03779-8

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