Identification of biomarkers for unstable angina by plasma metabolomic profiling

Sun, Meng; Gao, Xueqin; Zhang, Dongwei; Ke, Chaofu; Hou, Yan; Fan, Lijun; Zhang, Ruoxi; Liu, Haixia; Li, Kang; Yu, Bo

doi:10.1039/c3mb70216b

Cited by 28 publications

(26 citation statements)

References 43 publications

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“…Structure identification was carried out as described in our previous study. 27 The quasi-molecular ions were first identified based on peak lists and annotation results. The accurate mass data of the monoisotopic ions were then used to search online databases (HMDB, METLINE, and MassBank).…”

Section: Identification Of Metabolic Biomarkersmentioning

confidence: 99%

Prediction of advanced ovarian cancer recurrence by plasma metabolic profiling

Zhang

Cui

et al. 2015

Mol. BioSyst.

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Epithelial ovarian cancer (EOC) is the most lethal of gynecologic malignancies due to the high rate of recurrence and poor prognosis. Predicting the prognosis in patients with EOC is clinically challenging, partly because appropriate biomarkers of recurrence have yet to be explored. In this prospective study, pre-treatment plasma samples were collected from 38 patients with stage III or IV EOC who were subsequently followed up. Ultra-performance liquid chromatography mass spectrometry was used to perform metabolic profiling, which yielded five metabolites that were potential biomarkers for EOC recurrence: l-tryptophan, kynurenine, bilirubin, LysoPC (14 : 0) and LysoPE (18 : 2). A combination of these five potential biomarkers strongly predicted recurrence, the area under the curve being 0.91. In summary, the candidate biomarkers identified in this study may both facilitate clinical prediction of EOC recurrence and prognosis and serve as potential therapeutic targets in patients with EOC.

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Section: Identification Of Metabolic Biomarkersmentioning

confidence: 99%

Prediction of advanced ovarian cancer recurrence by plasma metabolic profiling

Zhang

Cui

et al. 2015

Mol. BioSyst.

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“…Phytosphingosine and phosphatidylcholine were elevated and phosphatidylglycerol was reduced relative to the atherosclerosis control (36).…”

Section: Human Studiesmentioning

confidence: 78%

Metabolomics in atherosclerosis

Djekic

Nicoll

Novo

et al. 2015

IJC Metabolic & Endocrine

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It is well established that atherosclerotic cardiovascular disease (ACD) is a leading cause of death in the West. There are several predisposing factors for ACD, which can be divided into two groups: firstly modifiable risk factors, including hypertension, dyslipidaemia, type 2 diabetes mellitus, obesity, smoking and a sedentary lifestyle and secondly the unmodifiable risk factors such as age, gender and heredity. Since single biomarkers are unable to provide sufficient information about the biochemical pathways responsible for the disease, there is a need for a holistic approach technology, e.g. metabolomics, that provide sufficiently detailed information about the metabolic status and assay results will be able to guide food, drug and lifestyle optimisation. Rather than investigating a single pathway, metabolomics deal with the integrated identification of biological and pathological molecular pathways. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the two most commonly used techniques for metabolite profiling. This detailed review concluded that metabolomics investigations seem to have great potential in identifying small groups of disturbed metabolites which if put together should draw various metabolic routs that lead to the common track pathophysiology. The current evidence in using metabolomics in atherosclerotic cardiovascular disease is also limited and morewell designed studies remain to be established, which might significantly improve the comprehension of atherosclerosis pathophysiology and consequently management.

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“…Sun et al find 16 differential metabolites between unstable angina (UA) and atherosclerosis patients, which are closely associated with phospholipid metabolism, tryptophan metabolism, and MG metabolism. These potential biomarkers can provide information on understanding the biological mechanisms of UA and the diagnosis of UA [22]. In our previous studies with GC-MS technology, we obtained 32 potential biomarkers of CHD patients, including amino acids, fatty acids, organic acids, glucose, and alcohol esters [23].…”

Section: Discussionmentioning

confidence: 99%

A Metabonomics Profiling Study on Phlegm Syndrome and Blood‐Stasis Syndrome in Coronary Heart Disease Patients Using Liquid Chromatography/Quadrupole Time‐of‐Flight Mass Spectrometry

Zhao¹,

Wan²,

Qiu³

et al. 2014

Evidence-Based Complementary and Alternative Medicine

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A metabonomics approach based on liquid chromatography/quadrupole time-of-flight mass spectrometry (LC-Q-TOF/MS) was utilized to obtain potential biomarkers of coronary heart disease (CHD) patients and investigate the ZHENG types differentiation in CHD patients. The plasma samples of 20 CHD patients with phlegm syndrome, 20 CHD patients with blood-stasis syndrome, and 16 healthy volunteers were collected in the study. 26 potential biomarkers were identified in the plasma of CHD patients and 19 differential metabolites contributed to the discrimination of phlegm syndrome and blood-stasis syndrome in CHD patients (VIP > 1.5; P < 0.05) which mainly involved purine metabolism, pyrimidine metabolism, amino acid metabolism, steroid biosynthesis, and arachidonic acid metabolism. This study demonstrated that metabonomics approach based on LC-MS was useful for studying pathologic changes of CHD patients and interpreting the differentiation of ZHENG types (phlegm and blood-stasis syndrome) in traditional Chinese medicine (TCM).

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Identification of biomarkers for unstable angina by plasma metabolomic profiling

Cited by 28 publications

References 43 publications

Prediction of advanced ovarian cancer recurrence by plasma metabolic profiling

Prediction of advanced ovarian cancer recurrence by plasma metabolic profiling

Metabolomics in atherosclerosis

A Metabonomics Profiling Study on Phlegm Syndrome and Blood‐Stasis Syndrome in Coronary Heart Disease Patients Using Liquid Chromatography/Quadrupole Time‐of‐Flight Mass Spectrometry

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