Metabolomics in Kidney Disease

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Endocrinology and Clinical Metabolic Research".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 12503

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Guest Editor

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Guest Editor
Department of Medical and Surgical Sciences - Clinical Pathology Unit. University of Foggia, Foggia, Italy
Interests: kidney transplantation; renal disease
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Special Issue Information

Dear Colleagues,

The high-throughput analysis of low-molecular-weight metabolites allows the global assessment of a cellular state in normal and pathological conditions. Metabolomics is the comprehensive analysis of the complete set of metabolic products in a cell, tissue, organ, or organism. This approach can be used to define the “metabolic fingerprint” of a disease and identify novel biomarkers that may be potentially useful for both early diagnosis and monitoring the therapeutic response. Metabolomics has great potential in clinical medicine, especially in urology and nephrology, and is a tool for the identification of molecular pathways that can provide novel insight into pathophysiological mechanisms and biomarker discovery in renal diseases. This Special Issue of Metabolites, “Metabolomics in kidney diseases”, will be dedicated to the application of this methodology for understanding the perturbations of biochemical systems occurring in kidney diseases, including renal cancer and different types of renal injury.

Prof. Dr. Giuseppe Lucarelli
Dr. Giuseppe Stefano Netti
Guest Editors

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Published Papers (3 papers)

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Research

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15 pages, 4989 KiB  
Article
Tissue-Specific 1H-NMR Metabolomic Profiling in Mice with Adenine-Induced Chronic Kidney Disease
by Ram B. Khattri, Trace Thome and Terence E. Ryan
Metabolites 2021, 11(1), 45; https://doi.org/10.3390/metabo11010045 - 10 Jan 2021
Cited by 22 | Viewed by 4487
Abstract
Chronic kidney disease (CKD) results in the impaired filtration of metabolites, which may be toxic or harmful to organs/tissues. The objective of this study was to perform unbiased 1H nuclear magnetic resonance (NMR)-based metabolomics profiling of tissues from mice with CKD. Five-month-old [...] Read more.
Chronic kidney disease (CKD) results in the impaired filtration of metabolites, which may be toxic or harmful to organs/tissues. The objective of this study was to perform unbiased 1H nuclear magnetic resonance (NMR)-based metabolomics profiling of tissues from mice with CKD. Five-month-old male C57BL6J mice were placed on either a casein control diet or adenine-supplemented diet to induce CKD for 24 weeks. CKD was confirmed by significant increases in blood urea nitrogen (24.1 ± 7.7 vs. 105.3 ± 18.3 mg/dL, p < 0.0001) in adenine-fed mice. Following this chronic adenine diet, the kidney, heart, liver, and quadriceps muscles were rapidly dissected; snap-frozen in liquid nitrogen; and the metabolites were extracted. Metabolomic profiling coupled with multivariate analyses confirm clear separation in both aqueous and organic phases between control and CKD mice. Severe energetic stress and apparent impaired mitochondrial metabolism were observed in CKD kidneys evidenced by the depletion of ATP and NAD+, along with significant alterations in tricarboxylic acid (TCA) cycle intermediates. Altered amino acid metabolism was observed in all tissues, although significant differences in specific amino acids varied across tissue types. Taken together, this study provides a metabolomics fingerprint of multiple tissues from mice with and without severe CKD induced by chronic adenine feeding. Full article
(This article belongs to the Special Issue Metabolomics in Kidney Disease)
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18 pages, 7120 KiB  
Article
Integration of Lipidomics and Transcriptomics Reveals Reprogramming of the Lipid Metabolism and Composition in Clear Cell Renal Cell Carcinoma
by Giuseppe Lucarelli, Matteo Ferro, Davide Loizzo, Cristina Bianchi, Daniela Terracciano, Francesco Cantiello, Lauren N. Bell, Stefano Battaglia, Camillo Porta, Angela Gernone, Roberto A. Perego, Eugenio Maiorano, Ottavio de Cobelli, Giuseppe Castellano, Leonardo Vincenti, Pasquale Ditonno and Michele Battaglia
Metabolites 2020, 10(12), 509; https://doi.org/10.3390/metabo10120509 - 13 Dec 2020
Cited by 51 | Viewed by 4541
Abstract
Clear cell renal cell carcinoma (ccRCC) is fundamentally a metabolic disease. Given the importance of lipids in many cellular processes, in this study we delineated a lipidomic profile of human ccRCC and integrated it with transcriptomic data to connect the variations in cancer [...] Read more.
Clear cell renal cell carcinoma (ccRCC) is fundamentally a metabolic disease. Given the importance of lipids in many cellular processes, in this study we delineated a lipidomic profile of human ccRCC and integrated it with transcriptomic data to connect the variations in cancer lipid metabolism with gene expression changes. Untargeted lipidomic analysis was performed on 20 ccRCC and 20 paired normal tissues, using LC-MS and GC-MS. Different lipid classes were altered in cancer compared to normal tissue. Among the long chain fatty acids (LCFAs), significant accumulations of polyunsaturated fatty acids (PUFAs) were found. Integrated lipidomic and transcriptomic analysis showed that fatty acid desaturation and elongation pathways were enriched in neoplastic tissue. Consistent with these findings, we observed increased expression of stearoyl-CoA desaturase (SCD1) and FA elongase 2 and 5 in ccRCC. Primary renal cancer cells treated with a small molecule SCD1 inhibitor (A939572) proliferated at a slower rate than untreated cancer cells. In addition, after cisplatin treatment, the death rate of tumor cells treated with A939572 was significantly greater than that of untreated cancer cells. In conclusion, our findings delineate a ccRCC lipidomic signature and showed that SCD1 inhibition significantly reduced cancer cell proliferation and increased cisplatin sensitivity, suggesting that this pathway can be involved in ccRCC chemotherapy resistance. Full article
(This article belongs to the Special Issue Metabolomics in Kidney Disease)
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Review

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18 pages, 1520 KiB  
Review
Metabolic Fingerprinting of Fabry Disease: Diagnostic and Prognostic Aspects
by Maria Teresa Rocchetti, Federica Spadaccino, Valeria Catalano, Gianluigi Zaza, Giovanni Stallone, Daniela Fiocco, Giuseppe Stefano Netti and Elena Ranieri
Metabolites 2022, 12(8), 703; https://doi.org/10.3390/metabo12080703 - 28 Jul 2022
Cited by 4 | Viewed by 2664
Abstract
Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. In the early stages, FD [...] Read more.
Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. In the early stages, FD could involve the peripheral nervous system (acroparesthesias and dysautonomia) and the ski (angiokeratoma), but later kidney, heart or central nervous system impairment may significantly decrease life expectancy. The advent of omics technologies offers the possibility of a global, integrated and systemic approach well-suited for the exploration of this complex disease. In this narrative review, we will focus on the main metabolomic studies, which have underscored the importance of detecting biomarkers for a diagnostic and prognostic purpose in FD. These investigations are potentially useful to explain the wide clinical, biochemical and molecular heterogeneity found in FD patients. Moreover, the quantitative mass spectrometry methods developed to evaluate concentrations of these biomarkers in urine and plasma will be described. Finally, the complex metabolic biomarker profile depicted in FD patients will be reported, which varies according to gender, types of mutations, and therapeutic treatment. Full article
(This article belongs to the Special Issue Metabolomics in Kidney Disease)
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