LC–MS-based serum fingerprinting reveals significant dysregulation of phospholipids in chronic heart failure

Marcinkiewicz-Siemion, Marta; Ciborowski, Michał; Ptaszyńska‐Kopczyńska, Katarzyna; Szpakowicz, Anna; Lisowska, Anna; Jasiewicz, Małgorzata; Waszkiewicz, Ewa; Krętowski, Adam; Musiał, W; Kamiński, Karol

doi:10.1016/j.jpba.2018.03.027

Cited by 27 publications

(26 citation statements)

References 31 publications

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“…Basic statistical analyses were performed as described previously 8 . In short, continuous variables are expressed as the mean ± standard deviation (SD) or median and interquartile range (IQR), depending on the type of distribution.…”

Section: Discussionmentioning

confidence: 99%

“…Study population. Study population, methodology for obtaining peripheral blood samples, clinical and metabolomics evaluation were as described previously 8 . In brief, 67 patients with chronic heart failure with reduced ejection fraction (HFrEF) and 39 age-, ischemic heart disease (IHD) occurrence-and body mass index (BMI)-matched controls were enrolled in the study.…”

Section: Methodsmentioning

confidence: 99%

“…They were prepared independently following the same procedure as for the rest of the samples and injected at the beginning of the run and after every 6-7 real samples. Samples were analyzed by the HPLC system that consisted of a degasser, two binary pumps and thermostated auto sampler connected to a mass spectrometry detector using previously described method 8 . Samples from each set (derivation and validation) were analyzed in a randomized order in separate runs (first for positive and then for negative ion mode).…”

Section: Metabolic Fingerprinting By Lc-qtof-msmentioning

confidence: 99%

“…Processing of LC-MS data was performed as described previously 8 . Briefly, the raw data collected by the analytical instrumentation was cleaned of background noise and unrelated ions by the Molecular Feature Extraction (MFE) tool in the Mass Hunter Qualitative Analysis Software (B.06.00, Agilent).…”

Section: Metabolic Fingerprinting By Lc-qtof-msmentioning

confidence: 99%

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Machine-learning facilitates selection of a novel diagnostic panel of metabolites for the detection of heart failure

Marcinkiewicz-Siemion

Kamiński

Ciborowski

et al. 2020

Sci Rep

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the metabolic derangement is common in heart failure with reduced ejection fraction (Hfref). the aim of the study was to check feasibility of the combined approach of untargeted metabolomics and machine learning to create a simple and potentially clinically useful diagnostic panel for Hfref. the study included 67 chronic HFrEF patients (left ventricular ejection fraction-LVEF 24.3 ± 5.9%) and 39 controls without the disease. Fasting serum samples were fingerprinted by liquid chromatographymass spectrometry. Feature selection based on random-forest models fitted to resampled data and followed by linear modelling, resulted in selection of eight metabolites (uric acid, two isomers of Lpc 18:2, LPC 20:1, deoxycholic acid, docosahexaenoic acid and one unknown metabolite), demonstrating their predictive value in Hfref. the accuracy of a model based on metabolites panel was comparable to BNP (0.85 vs 0.82), as verified on the test set. Selected metabolites correlated with clinical, echocardiographic and functional parameters. the combination of two innovative tools (metabolomics and machine-learning methods), both unrestrained by the gaps in the current knowledge, enables identification of a novel diagnostic panel. Its diagnostic value seems to be comparable to BNP. Large scale, multi-center studies using validated targeted methods are crucial to confirm clinical utility of proposed markers.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Metabolic Fingerprinting By Lc-qtof-msmentioning

confidence: 99%

Section: Metabolic Fingerprinting By Lc-qtof-msmentioning

confidence: 99%

See 2 more Smart Citations

Machine-learning facilitates selection of a novel diagnostic panel of metabolites for the detection of heart failure

Marcinkiewicz-Siemion

Kamiński

Ciborowski

et al. 2020

Sci Rep

Self Cite

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“…PC also takes part in the process of oxidative stress in the body through the oxidase pathway and activation of intravascular protein kinase C that plays a crucial role in the body. PA may protect the cardiomyocytes by activating the LPA3 receptor and inhibiting the mitochondria‐dependent apoptosis pathway . This abnormal state can be changed after GXSC treatment.…”

Section: Discussionmentioning

confidence: 99%

Characterization of chemical constituents and absorbed components, screening the active components of gelanxinning capsule and an evaluation of therapeutic effects by ultra‐high performance liquid chromatography with quadrupole time of flight mass spectrometry

Gao

Zhang

et al. 2019

J of Separation Science

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We revealed the potential biomarker and pathway of gelanxinning capsule on rat model with coronary heart disease, which aims to clarify holistic therapeutic effect and predict quality‐markers of gelanxinning capsule. Ultra‐high performance liquid chromatography coupled with mass spectrometry based on metabolomics technique was used to find the biomarkers and related metabolic pathways of coronary heart disease model, which evaluates the intervention effect of gelanxinning capsule. Using serum pharmacochemistry of traditional Chinese medicine and Pearson correlation analysis, effective ingredients in serum is analyzed to characterize the activity of gelanxinning capsule on coronary heart disease under valid state. A total of 20 biomarkers from coronary heart disease were identified and 12 of them were regulated by gelanxinning capsule treatment, which is mainly involved in sphingolipid metabolism and glycerophospholipid metabolism. With the high sensitivity liquid chromatography coupled with mass spectrometry technology, a total of 46 compounds from gelanxinning capsule were identified in vitro and 25 of them were absorbed in blood. The correlation analysis of serum biomarkers and absorbed components was used to find 11 compounds as quality‐markers to be responsible for the efficacy of gelanxinning capsule. This strategy was successfully applied to screening of potential mechanism and quality‐markers from herbal medicine.

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Exploring lipid biomarkers of coronary heart disease for elucidating the biological effects of gelanxinning capsule by lipidomics method based on LC–MS

Gao

Hu²,

Zhang³

et al. 2021

Biomedical Chromatography

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High-throughput lipidomics technology was used to explore the potential therapeutic targets and mechanism of action of gelanxinning capsule on rat model with coronary heart disease (CHD). This study attempts to provide a novel method to interpret the molecular mechanism of traditional medicine. The lipid markers of CHD were determined by full-scan analysis based on ultra-performance liquid chromatography-highdefinition mass spectrometry. Then, the metabolic changes associated with gelanxinning capsule treatment via the modulation of lipid biomarkers and pathway in rats were characterized. After gelanxinning treatment, the metabolic profile tended to recover compared with the model group. A total of 26 potential biomarkers were

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LC–MS-based serum fingerprinting reveals significant dysregulation of phospholipids in chronic heart failure

Cited by 27 publications

References 31 publications

Machine-learning facilitates selection of a novel diagnostic panel of metabolites for the detection of heart failure

Machine-learning facilitates selection of a novel diagnostic panel of metabolites for the detection of heart failure

Characterization of chemical constituents and absorbed components, screening the active components of gelanxinning capsule and an evaluation of therapeutic effects by ultra‐high performance liquid chromatography with quadrupole time of flight mass spectrometry

Exploring lipid biomarkers of coronary heart disease for elucidating the biological effects of gelanxinning capsule by lipidomics method based on LC–MS

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