Plasma Amino Acids May Improve Prediction Accuracy of Cerebral Vasospasm after Aneurysmal Subarachnoid Haemorrhage

Aneurysmal subarachnoid haemorrhages (aSAH) account for 5% of strokes and continues to place a great burden on patients and their families. Cerebral vasospasm (CVS) is one of the main causes of death after aSAH, and is usually diagnosed between day 3 and 14 after bleeding. Its pathogenesis remains poorly understood. To verify whether plasma concentration of amino acids have prognostic value in predicting CVS, we analysed data from 35 patients after aSAH (median age 55 years, IQR 39–62; 20 females, 57.1%), and 37 healthy volunteers (median age 50 years, IQR 38–56; 19 females, 51.4%). Fasting peripheral blood samples were collected on postoperative day one and seven. High performance liquid chromatography-mass spectrometry (HPLC-MS) analysis was performed. The results showed that plasma from patients after aSAH featured a distinctive amino acids concentration which was presented in both principal component analysis and direct comparison. No significant differences were noted between postoperative day one and seven. A total of 18 patients from the study group (51.4%) developed CVS. Hydroxyproline (AUC = 0.7042, 95%CI 0.5259–0.8826, p = 0.0248) and phenylalanine (AUC = 0.6944, 95%CI 0.5119–0.877, p = 0.0368) presented significant CVS prediction potential. Combining the Hunt-Hess Scale and plasma levels of hydroxyproline and phenylalanine provided the model with the best predictive performance and the lowest leave-one-out cross-validation of performance error. Our results suggest that plasma amino acids may improve sensitivity and specificity of Hunt-Hess scale in predicting CVS.

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Serum Metabolic Profiles of Chinese Women With Perimenopausal Obesity Explored by the Untargeted Metabolomics Approach

Frontiers in Endocrinology ◽

10.3389/fendo.2021.637317 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shanshan Ding ◽

Mingyi Chen ◽

Ying Liao ◽

Qiliang Chen ◽

Xuejuan Lin ◽

...

Keyword(s):

Amino Acids ◽

Metabolic Pathways ◽

High Performance ◽

Indoleacetic Acid ◽

Chinese Women ◽

Principal Component ◽

Untargeted Metabolomics ◽

Negative Ion ◽

Metabolic Profiles ◽

Metabolic Characteristics

By far, no study has focused on observing the metabolomic profiles in perimenopause-related obesity. This study attempted to identify the metabolic characteristics of subjects with perimenopause obesity (PO). Thirty-nine perimenopausal Chinese women, 21 with PO and 18 without obesity (PN), were recruited in this study. A conventional ultra-high-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry (UHPLC-QTOF/MS) followed by principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used as untargeted metabolomics approaches to explore the serum metabolic profiles. Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst were used to identify the related metabolic pathways. A total of 46 differential metabolites, along with seven metabolic pathways relevant to PO were identified, which belonged to lipid, amino acids, carbohydrates, and organic acids. As for amino acids, we found a significant increase in l-arginine and d-ornithine in the positive ion (POS) mode and l-leucine, l-valine, l-tyrosine, and N-acetyl-l-tyrosine in the negative ion (NEG) mode and a significant decrease in l-proline in the POS mode of the PO group. We also found phosphatidylcholine (PC) (16:0/16:0), palmitic acid, and myristic acid, which are associated with the significant upregulation of lipid metabolism. Moreover, the serum indole lactic acid and indoleacetic acid were upregulated in the NEG mode. With respect to the metabolic pathways, the d-arginine and d-ornithine metabolisms and the arginine and proline metabolism pathways in POS mode were the most dominant PO-related pathways. The changes of metabolisms of lipid, amino acids, and indoleacetic acid provided a pathophysiological scenario for Chinese women with PO. We believe that the findings of this study are helpful for clinicians to take measures to prevent the women with PO from developing severe incurable obesity-related complications, such as cardiovascular disease and stroke.

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Amino Acid Profiles to Differentiate White Wines from Three Autochtonous Galician Varieties

Foods ◽

10.3390/foods9020114 ◽

2020 ◽

Vol 9 (2) ◽

pp. 114 ◽

Cited By ~ 1

Author(s):

José Manuel Mirás-Avalos ◽

Yolanda Bouzas-Cid ◽

Emiliano Trigo-Córdoba ◽

Ignacio Orriols ◽

Elena Falqué

Keyword(s):

Amino Acids ◽

Amino Acid ◽

High Performance ◽

Principal Component ◽

Wine Quality ◽

Photodiode Array Detection ◽

Relevant Role ◽

Amino Acid Profiles ◽

Primary Amino ◽

Amino Acid Contents

Amino acids play a relevant role in wine quality and can allow for classifying wines according to the variety. In this work, the amino acid contents of Albariño, Godello, and Treixadura wines, three autochthonous varieties from Galicia (NW Spain), were determined. During three consecutive vintages, these varieties were grown on the same vineyard and were harvested at optimum maturity, and the wines were elaborated following the same enological protocol. The identification and quantification of the primary amino acids were carried out by high-performance liquid chromatography with photodiode array detection, after a derivatization. Amino acid contents in these white varieties were within the range of values reported for other European wines, but Treixadura wines showed the highest concentrations, while wines from the Albariño variety showed the lowest contents. Apart from proline, whose concentrations were caused by yeast release, the most abundant amino acids were aspartic acid, glutamic acid, lysine, arginine, asparagine, alanine, and histidine. Principal component analysis separated wines by variety according to their amino acid contents.

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CryoProtect: A Web Server for Classifying Antifreeze Proteins from Nonantifreeze Proteins

Journal of Chemistry ◽

10.1155/2017/9861752 ◽

2017 ◽

Vol 2017 ◽

pp. 1-15 ◽

Cited By ~ 18

Author(s):

Reny Pratiwi ◽

Aijaz Ahmad Malik ◽

Nalini Schaduangrat ◽

Virapong Prachayasittikul ◽

Jarl E. S. Wikberg ◽

...

Keyword(s):

Amino Acids ◽

Physicochemical Properties ◽

Predictive Model ◽

High Performance ◽

Web Server ◽

Principal Component ◽

Large Set ◽

Data Set ◽

Diverse Range ◽

Ice Binding

Antifreeze protein (AFP) is an ice-binding protein that protects organisms from freezing in extremely cold environments. AFPs are found across a diverse range of species and, therefore, significantly differ in their structures. As there are no consensus sequences available for determining the ice-binding domain of AFPs, thus the prediction and characterization of AFPs from their sequence is a challenging task. This study addresses this issue by predicting AFPs directly from sequence on a large set of 478 AFPs and 9,139 non-AFPs using machine learning (e.g., random forest) as a function of interpretable features (e.g., amino acid composition, dipeptide composition, and physicochemical properties). Furthermore, AFPs were characterized using propensity scores and important physicochemical properties via statistical and principal component analysis. The predictive model afforded high performance with an accuracy of 88.28% and results revealed that AFPs are likely to be composed of hydrophobic amino acids as well as amino acids with hydroxyl and sulfhydryl side chains. The predictive model is provided as a free publicly available web server called CryoProtect for classifying query protein sequence as being either AFP or non-AFP. The data set and source code are for reproducing the results which are provided on GitHub.

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Quantitation of tryptophan and other plasma amino acids by automated pre-column o-phthaldialdehyde derivatization high-performance liquid chromatography: improved sample preparation

Journal of Chromatography B Biomedical Sciences and Applications ◽

10.1016/0378-4347(91)80071-j ◽

1991 ◽

Vol 564 (1) ◽

pp. 81-91 ◽

Cited By ~ 40

Author(s):

Anthony M. Uhe ◽

Greg R. Collier ◽

Elizabeth A. McLennan ◽

Daryl J. Tucker ◽

Kerin O'Dea

Keyword(s):

Amino Acids ◽

High Performance Liquid Chromatography ◽

Liquid Chromatography ◽

Sample Preparation ◽

High Performance ◽

Plasma Amino Acids

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Simple and rapid quantitative high-performance liquid chromatographic analysis of plasma amino acids

Journal of Chromatography B ◽

10.1016/j.jchromb.2007.01.002 ◽

2007 ◽

Vol 852 (1-2) ◽

pp. 646-649 ◽

Cited By ~ 48

Author(s):

Michael P. Frank ◽

Robert W. Powers

Keyword(s):

Amino Acids ◽

Chromatographic Analysis ◽

High Performance ◽

High Performance Liquid Chromatographic ◽

Plasma Amino Acids ◽

Liquid Chromatographic Analysis ◽

Liquid Chromatographic

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The use of high-performance liquid chromatography for quantitation of plasma amino acids in man

Analytical Biochemistry ◽

10.1016/0003-2697(82)90138-5 ◽

1982 ◽

Vol 127 (1) ◽

pp. 17-24 ◽

Cited By ~ 65

Author(s):

Daniel L. Hogan ◽

Kevin L. Kraemer ◽

Jon I. Isenberg

Keyword(s):

Amino Acids ◽

High Performance Liquid Chromatography ◽

Liquid Chromatography ◽

High Performance ◽

Plasma Amino Acids

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CSF and Serum Biomarkers Focusing on Cerebral Vasospasm and Ischemia after Subarachnoid Hemorrhage

Stroke Research and Treatment ◽

10.1155/2013/560305 ◽

2013 ◽

Vol 2013 ◽

pp. 1-7 ◽

Cited By ~ 22

Author(s):

Carla S. Jung ◽

Bettina Lange ◽

Michael Zimmermann ◽

Volker Seifert

Keyword(s):

Amino Acids ◽

Subarachnoid Hemorrhage ◽

Cerebral Vasospasm ◽

High Performance ◽

Cerebral Metabolism ◽

Delayed Cerebral Ischemia ◽

Neuron Specific Enolase ◽

Serum S100b ◽

Delayed Cerebral Vasospasm ◽

Suitable Marker

Delayed cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI) remain severe complications after subarachnoid hemorrhage (SAH). Although focal changes in cerebral metabolism indicating ischemia are detectable by microdialysis, routinely used biomarkers are missing. We therefore sought to evaluate a panel of possible global markers in serum and cerebrospinal fluid (CSF) of patients after SAH. CSF and serum of SAH patients were analyzed retrospectively. In CSF, levels of inhibitory, excitatory, and structural amino acids were detected by high-performance liquid chromatography (HPLC). In serum, neuron-specific enolase (NSE) and S100B level were measured and examined in conjunction with CVS and DCI. CVS was detected by arteriography, and ischemic lesions were assessed by computed tomography (CT) scans. All CSF amino acids were altered after SAH. CSF glutamate, glutamine, glycine, and histidine were significantly correlated with arteriographic CVS. CSF glutamate and serum S100B were significantly correlated with ischemic events after SAH; however, NSE did not correlate neither with ischemia nor with vasospasm. Glutamate, glutamine, glycine, and histidine might be used in CSF as markers for CVS. Glutamate also indicates ischemia. Serum S100B, but not NSE, is a suitable marker for ischemia. These results need to be validated in larger prospective cohorts.

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Metabolomic signatures associated with disease severity in multiple sclerosis

Neurology Neuroimmunology & Neuroinflammation ◽

10.1212/nxi.0000000000000321 ◽

2017 ◽

Vol 4 (2) ◽

pp. e321 ◽

Cited By ~ 35

Author(s):

Pablo Villoslada ◽

Cristina Alonso ◽

Ion Agirrezabal ◽

Ekaterina Kotelnikova ◽

Irati Zubizarreta ◽

...

Keyword(s):

Multiple Sclerosis ◽

Amino Acids ◽

Disease Severity ◽

High Performance ◽

Severe Disease ◽

Principal Component ◽

Partial Least Square ◽

Least Square ◽

Serum Samples ◽

Prospective Assessment

Objective:To identify differences in the metabolomic profile in the serum of patients with multiple sclerosis (MS) compared to controls and to identify biomarkers of disease severity.Methods:We studied 2 cohorts of patients with MS: a retrospective longitudinal cohort of 238 patients and 74 controls and a prospective cohort of 61 patients and 41 controls with serial serum samples. Patients were stratified into active or stable disease based on 2 years of prospective assessment accounting for presence of clinical relapses or changes in disability measured with the Expanded Disability Status Scale (EDSS). Metabolomic profiling (lipids and amino acids) was performed by ultra-high-performance liquid chromatography coupled to mass spectrometry in serum samples. Data analysis was performed using parametric methods, principal component analysis, and partial least square discriminant analysis for assessing the differences between cases and controls and for subgroups based on disease severity.Results:We identified metabolomics signatures with high accuracy for classifying patients vs controls as well as for classifying patients with medium to high disability (EDSS >3.0). Among them, sphingomyelin and lysophosphatidylethanolamine were the metabolites that showed a more robust pattern in the time series analysis for discriminating between patients and controls. Moreover, levels of hydrocortisone, glutamic acid, tryptophan, eicosapentaenoic acid, 13S-hydroxyoctadecadienoic acid, lysophosphatidylcholines, and lysophosphatidylethanolamines were associated with more severe disease (non-relapse-free or increase in EDSS).Conclusions:We identified metabolomic signatures composed of hormones, lipids, and amino acids associated with MS and with a more severe course.

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