Multiplatform metabolomics provides insight into the molecular basis of chronic kidney disease

Kordalewska, Marta; Macioszek, Szymon; Wawrzyniak, Renata; Sikorska-Wiśniewska, Małgorzata; Śledziński, Tomasz; Chmielewski, Michael S.; Mika, Adriana; Markuszewski, Michał J.

doi:10.1016/j.jchromb.2019.04.003

Cited by 13 publications

(13 citation statements)

References 44 publications

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“…Some previous studies have reported dysregulation of lipids in several diseases 17 , 48 – 50 . Unfortunately, molar concentrations are often not provided for measured lipids, therefore, the correlation of their conclusions with other studies is difficult.…”

Section: Discussionmentioning

confidence: 96%

“…Recently, the successful detection of eight cancer types based on the analysis of proteins and mutations in ctDNA in blood was reported 15 . Metabolomics also attracts research attention in cancer screening 16 and other metabolic disorders 17 . Lipidomics can be considered as a part of metabolomics that deals with the comprehensive analysis of lipids, which are important biomolecules involved in many biological processes, such as signaling molecules or constituents of cell membranes, energy storage, and various other metabolic pathways 18 .…”

Section: Introductionmentioning

confidence: 99%

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Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls

Wolrab

Jirásko

Peterka

et al. 2021

Sci Rep

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Early detection of cancer is one of the unmet needs in clinical medicine. Peripheral blood analysis is a preferred method for efficient population screening, because blood collection is well embedded in clinical practice and minimally invasive for patients. Lipids are important biomolecules, and variations in lipid concentrations can reflect pathological disorders. Lipidomic profiling of human plasma by the coupling of ultrahigh-performance supercritical fluid chromatography and mass spectrometry is investigated with the aim to distinguish patients with breast, kidney, and prostate cancers from healthy controls. The mean sensitivity, specificity, and accuracy of the lipid profiling approach were 85%, 95%, and 92% for kidney cancer; 91%, 97%, and 94% for breast cancer; and 87%, 95%, and 92% for prostate cancer. No association of statistical models with tumor stage is observed. The statistically most significant lipid species for the differentiation of cancer types studied are CE 16:0, Cer 42:1, LPC 18:2, PC 36:2, PC 36:3, SM 32:1, and SM 41:1 These seven lipids represent a potential biomarker panel for kidney, breast, and prostate cancer screening, but a further verification step in a prospective study has to be performed to verify clinical utility.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls

Wolrab

Jirásko

Peterka

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The comparison of the samples was not the aim of this study, therefore the urine samples were not normalized. However, for the application of the method in metabolomics studies in the future, the normalization will be necessary [35]. The analysis of urine with more analytical techniques can increase the number of metabolites of different physicochemical properties, and consequently may provide more information about the metabolic state of the body [36].…”

Section: Methods Application-gc-msmentioning

confidence: 99%

An Optimization of Liquid–Liquid Extraction of Urinary Volatile and Semi-Volatile Compounds and Its Application for Gas Chromatography-Mass Spectrometry and Proton Nuclear Magnetic Resonance Spectroscopy

et al. 2020

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Urinary volatile compounds (VCs) have been recently assessed for disease diagnoses. They belong to very diverse chemical classes, and they are characterized by different volatilities, polarities and concentrations, complicating their analysis via a single analytical procedure. There remains a need for better, lower-cost methods for VC biomarker discovery. Thus, there is a strong need for alternative methods, enabling the detection of a broader range of VCs. Therefore, the main aim of this study was to optimize a simple and reliable liquid–liquid extraction (LLE) procedure for the analysis of VCs in urine using gas chromatography-mass spectrometry (GC-MS), in order to obtain the maximum number of responses. Extraction parameters such as pH, type of solvent and ionic strength were optimized. Moreover, the same extracts were analyzed using Proton Nuclear Magnetic Resonance Spectroscopy (1H-NMR), to evaluate the applicability of a single urine extraction for multiplatform purposes. After the evaluation of experimental conditions, an LLE protocol using 2 mL of urine in the presence of 2 mL of 1 M sulfuric acid and sodium sulphate extracted with dichloromethane was found to be optimal. The optimized method was validated with the external standards and was found to be precise and linear, and allowed for detection of >400 peaks in a single run present in at least 50% of six samples—considerably more than the number of peaks detected by solid-phase microextracton fiber pre-concentration-GC-MS (328 ± 6 vs. 234 ± 4). 1H-NMR spectroscopy of the polar and non-polar extracts extended the range to >40 more (mainly low volatility compounds) metabolites (non-destructively), the majority of which were different from GC-MS. The more peaks detectable, the greater the opportunity of assessing a fingerprint of several compounds to aid biomarker discovery. In summary, we have successfully demonstrated the potential of LLE as a cheap and simple alternative for the analysis of VCs in urine, and for the first time the applicability of a single urine solvent extraction procedure for detecting a wide range of analytes using both GC-MS and 1H-NMR analysis to enhance putative biomarker detection. The proposed method will simplify the transport between laboratories and storage of samples, as compared to intact urine samples.

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“…To improve its sensitivity, MS is often used in combination with one of the separation techniques: liquid chromatography (LC), gas chromatography (GC) or capillary electrophoresis (CE). The methods complement one another as each provides information about different compound classes [4]. However, as a single analytical platform, LC-MS provides the highest metabolome coverage [5] and therefore it was used in our study.…”

Section: Introductionmentioning

confidence: 99%

Amniotic fluid metabolic fingerprinting indicated metabolites which may play a role in the pathogenesis of foetal Down syndrome — a preliminary report

et al. 2021

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Objectives: Down syndrome is the most common human chromosomal aberration. It is commonly known that it is a genetic-based disease, but still, pathomechanisms which lead to observed disorders have not been explained. The objective of this study was to determine the metabolic fingerprinting of the amniotic fluid women carrying foetuses with Down syndrome (DS). Material and methods: The study and control groups consisted of women who underwent routine amniocentesis between the 15 th and 18 th week of gestation. After analysis of the karyotyping results, 13 women with foetal DS were chosen. For the control group, 13 healthy patients with uncomplicated pregnancies who delivered healthy newborns at term was selected. Amniotic fluid was analyzed using liquid chromatography combined with high resolution mass spectrometry. Results: In the amniotic fluid of women with foetal DS compared to patients with healthy foetuses, we reported significant differences in the level of four metabolites: methylhistidine, hexanoylcarnitine, diacetylspermine and p-cresol sulfate which may be connected with improper development of nervous system and muscles. We detected bacterial metabolite, which support the latest thesis about non-sterile intrauterine environment. Conclusions: Based on our findings, we hypothesise that differences in the level of four metabolites in the amniotic fluid may play role in the pathogenesis of DS. Defining their potential as biochemical pathogenic factors of DS requires further investigation of the biological pathways involving in the foetal development.

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Multiplatform metabolomics provides insight into the molecular basis of chronic kidney disease

Cited by 13 publications

References 44 publications

Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls

Plasma lipidomic profiles of kidney, breast and prostate cancer patients differ from healthy controls

An Optimization of Liquid–Liquid Extraction of Urinary Volatile and Semi-Volatile Compounds and Its Application for Gas Chromatography-Mass Spectrometry and Proton Nuclear Magnetic Resonance Spectroscopy

Amniotic fluid metabolic fingerprinting indicated metabolites which may play a role in the pathogenesis of foetal Down syndrome — a preliminary report

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