Identification of Potential Metabolic Markers of Hypertension in Chinese Children

Background. Studies in adults have shown that several metabolites across multiple pathways are strongly associated with hypertension. However, as yet, to our knowledge, no study has investigated such association in childhood. We, therefore, compared the serum metabolite profile of children with normal and elevated blood pressure (BP) to identify potential metabolic markers and pathways that could be useful for the assessment of pediatric hypertension. Methods. The study included 26 hypertensive children (age range, 6–11 years) and 26 age- and sex-matched ones with normal BP, who were recruited from the baseline survey of the Huantai Childhood Cardiovascular Health Cohort Study. Ultrahigh-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry was performed to assess the serum metabolite profile. Logistic regression analysis was used to select significant metabolites associated with hypertension after adjustment for body mass index, waist circumference, and lipid profile. Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst were utilized to search for the potential pathways of metabolites. Results. A total of 45 and 34 metabolites were preliminarily screened in positive and negative modes, respectively (variable importance in the projection (VIP) > 1.0 and P < 0.05 ). After adjustment for the false discovery rate, 7 and 1 differential metabolites in the positive and negative modes, respectively, remained significant (VIP > 1.0 and q < 0.05). These metabolites were mainly involved in amino acid metabolism and glycerophospholipid metabolism. Among these, two significant metabolites including ethanolamine and 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate displayed an area under the curve value of 0.820 (95% confidence interval, 0.688–0.951), with a sensitivity of 0.846 and a specificity of 0.769. Conclusion. The untargeted metabolomics approach effectively identified the differential serum metabolite profile in children with and without hypertension. Notably, two metabolites including ethanolamine and 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate exhibited a good discriminative ability to identify children with hypertension, providing new insights into potential mechanisms of pediatric hypertension.

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Biomarkers identified by serum metabolomic analysis to predict biologic treatment response in rheumatoid arthritis patients

Rheumatology ◽

10.1093/rheumatology/kez199 ◽

2019 ◽

Vol 58 (12) ◽

pp. 2153-2161 ◽

Cited By ~ 3

Author(s):

Soshi Takahashi ◽

Jun Saegusa ◽

Akira Onishi ◽

Akio Morinobu

Keyword(s):

Operating Characteristic ◽

Area Under The Curve ◽

Metabolomic Analysis ◽

Eular Response ◽

Biologic Treatment ◽

Discriminative Ability ◽

Flight Mass Spectrometry ◽

Tnf Α ◽

Multiple Biomarkers ◽

Patient Groups

Abstract Objectives Biologic treatment has recently revolutionized the management of RA. Despite this success, ∼30–40% of the patients undergoing biologic treatment respond insufficiently. The aim of this study was to identify several specific reliable metabolites for predicting the response of RA patients to TNF-α inhibitors (TNFi) and abatacept (ABT), using capillary electrophoresis-time-of-flight mass spectrometry (CE-TOFMS). Methods We collected serum from RA patients with moderate or high disease activity prior to biologic treatment, and obtained the serum metabolomic profiles of these samples using CE-TOFMS. The patients' response was determined 12 weeks after starting biologic treatment, according to the EULAR response criteria. We compared the metabolites between the response and non-response patient groups and analysed their discriminative ability. Results Among 43 total patients, 14 of 26 patients in the TNFi group and 6 of 17 patients in the ABT group responded to the biologic treatment. Of the metabolites separated by CE-TOFMS, 196 were identified as known substances. Using an orthogonal partial least-squares discriminant analysis, we identified five metabolites as potential predictors of TNFi responders and three as predictors of ABT responders. Receiver operating characteristic analyses for multiple biomarkers revealed an area under the curve (AUC) of 0.941, with a sensitivity of 85.7% and specificity of 100% for TNFi, and an AUC of 0.985, with a sensitivity of 100% and specificity of 90.9% for ABT. Conclusion By metabolomic analysis, we identified serum biomarkers that have a high ability to predict the response of RA patients to TNFi or ABT treatment.

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Potential Novel Serum Metabolic Markers Associated With Progression of Prediabetes to Overt Diabetes in a Chinese Population

Frontiers in Endocrinology ◽

10.3389/fendo.2021.745214 ◽

2022 ◽

Vol 12 ◽

Author(s):

Meng Ren ◽

Diao zhu Lin ◽

Zhi Peng Liu ◽

Kan Sun ◽

Chuan Wang ◽

...

Keyword(s):

Risk Factors ◽

Chinese Population ◽

Multivariate Logistic Regression Analysis ◽

Area Under The Curve ◽

Metabolite Profile ◽

Metabolic Markers ◽

Random Forest Classification ◽

Increased Risk ◽

Study Results

BackgroundIdentifying the metabolite profile of individuals with prediabetes who turned to type 2 diabetes (T2D) may give novel insights into early T2D interception. The purpose of this study was to identify metabolic markers that predict the development of T2D from prediabetes in a Chinese population.MethodsWe used an untargeted metabolomics approach to investigate the associations between serum metabolites and risk of prediabetes who turned to overt T2D (n=153, mean follow up 5 years) in a Chinese population (REACTION study). Results were compared with matched controls who had prediabetes at baseline [age: 56 ± 7 years old, body mass index (BMI): 24.2 ± 2.8 kg/m2] and at a 5-year follow-up [age: 61 ± 7 years old, BMI: 24.5 ± 3.1 kg/m2]. Confounding factors were adjusted and the associations between metabolites and diabetes risk were evaluated with multivariate logistic regression analysis. A 10-fold cross-validation random forest classification (RFC) model was used to select the optimal metabolites panels for predicting the development of diabetes, and to internally validate the discriminatory capability of the selected metabolites beyond conventional clinical risk factors.FindingsMetabolic alterations, including those associated with amino acid and lipid metabolism, were associated with an increased risk of prediabetes progressing to diabetes. The most important metabolites were inosine [odds ratio (OR) = 19.00; 95% confidence interval (CI): 4.23-85.37] and carvacrol (OR = 17.63; 95% CI: 4.98-62.34). Thirteen metabolites were found to improve T2D risk prediction beyond eight conventional T2D risk factors [area under the curve (AUC) was 0.98 for risk factors + metabolites vs 0.72 for risk factors, P < 0.05].InterpretationsUse of the metabolites identified in this study may help determine patients with prediabetes who are at highest risk of progressing to diabetes.

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Sex disparities in cardiovascular health metrics among rural-dwelling older adults in China: a population-based study

BMC Geriatrics ◽

10.1186/s12877-021-02116-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xiaolei Han ◽

Ziying Jiang ◽

Yuanjing Li ◽

Yongxiang Wang ◽

Yajun Liang ◽

...

Keyword(s):

Older Adults ◽

Rural Communities ◽

Cardiovascular Health ◽

Rural China ◽

Descriptive Analysis ◽

Population Based ◽

Baseline Survey ◽

Chinese Older Adults ◽

Face To Face ◽

Sex Disparities

Abstract Background Cardiovascular health (CVH) metrics among Chinese older adults are poorly understood. We investigated sex disparities in CVH metrics and their management among rural-dwelling older adults in China. Methods This community-based study included 5026 participants (age ≥ 65 years; 57.2% women) in the baseline survey of a multimodal intervention study in rural China. In March–September 2018, data were collected through face-to-face interviews, clinical examinations, and laboratory tests. We defined six CVH metrics (three behavioral factors—smoking, body mass index, and physical activity; three biological factors—blood pressure, total cholesterol, and blood glucose) following the modified American Heart Association’s recommendations. We performed descriptive analysis separately for men and women. Results Of all participants, only 0.8% achieved ideal levels in all six CVH metrics. Men were more likely than women to have ideal levels in all CVH metrics but smoking. Women had higher prevalence of ideal global (9.7% vs. 7.8%) and behavioral (18.3% vs. 9.5%) CVH metrics (p < 0.001), whereas men had higher prevalence of ideal biological CVH metrics (5.4% vs. 3.5%, p < 0.001). The prevalence of ideal global and behavioral CVH metrics increased with age in both women and men (p for trend< 0.001). Women were more likely to be aware of their hypertension and diabetes, and to receive antihypertensive treatment, while men were more likely to achieve the goal of high cholesterol treatment (p < 0.05). Conclusions The CVH metrics among older adults living in the rural communities in China are characterized by an extremely low proportion of optimal global CVH metrics and distinct sex differences, alongside poor management of major biological risk factors. Trial registration ChiCTR1800017758 (Aug 13, 2018).

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Oxidative Stress-Induced Alteration of Plant Central Metabolism

Life ◽

10.3390/life11040304 ◽

2021 ◽

Vol 11 (4) ◽

pp. 304

Author(s):

Tatyana Savchenko ◽

Konstantin Tikhonov

Keyword(s):

Oxidative Stress ◽

Stress Responses ◽

Tricarboxylic Acid Cycle ◽

Strong Dependence ◽

Plant Stress ◽

Metabolite Profile ◽

Agricultural Practice ◽

Central Metabolism ◽

Metabolic Markers ◽

Sugar Derivatives

Oxidative stress is an integral component of various stress conditions in plants, and this fact largely determines the substantial overlap in physiological and molecular responses to biotic and abiotic environmental challenges. In this review, we discuss the alterations in central metabolism occurring in plants experiencing oxidative stress. To focus on the changes in metabolite profile associated with oxidative stress per se, we primarily analyzed the information generated in the studies based on the exogenous application of agents, inducing oxidative stress, and the analysis of mutants displaying altered oxidative stress response. Despite of the significant variation in oxidative stress responses among different plant species and tissues, the dynamic and transient character of stress-induced changes in metabolites, and the strong dependence of metabolic responses on the intensity of stress, specific characteristic changes in sugars, sugar derivatives, tricarboxylic acid cycle metabolites, and amino acids, associated with adaptation to oxidative stress have been detected. The presented analysis of the available data demonstrates the oxidative stress-induced redistribution of metabolic fluxes targeted at the enhancement of plant stress tolerance through the prevention of ROS accumulation, maintenance of the biosynthesis of indispensable metabolites, and production of protective compounds. This analysis provides a theoretical basis for the selection/generation of plants with improved tolerance to oxidative stress and the development of metabolic markers applicable in research and routine agricultural practice.

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ONE-LEGGED STANCE BALANCE OF OLDER ADULTS WITH AND WITHOUT FALLS

Innovation in Aging ◽

10.1093/geroni/igz038.1754 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S470-S470

Author(s):

Edgar R Vieira ◽

Márcio Oliveira ◽

Andre Gil ◽

Karen Fernandes ◽

Denilson Teixeira ◽

...

Keyword(s):

Older Adults ◽

Fear Of Falling ◽

Center Of Pressure ◽

Area Under The Curve ◽

Test Duration ◽

Mobility Impairments ◽

Eyes Open ◽

Falls In Older Adults ◽

Elliptical Area ◽

Age Range

Abstract Balance impairment is a common problem among older adults. Poor balance in older adults is often associated with mobility impairments, activity limitations and fear of falling in older adults. Thus, balance assessment is useful for early detection of postural control deficits to prevent mobility impairments and falls in older adults. The aim of this study was to assess if balance measures based in center of pressure (COP) parameters during one-legged stance could differentiate between older adults with and without falls in the past 12 months. One-hundred and seventy older adults (50 fallers and 120 non-fallers, age range: 63-72 years) performed three 30s one-legged stance trials with eyes open on a force platform with 30s of rest between each trial. The following variables were evaluated: COP 95% elliptical area, COP velocity in the anterior-posterior and medio-lateral directions, and test duration (how long the participant was able to stay in one-legged stance, up to 30s). Fallers had poorer balance than non-fallers (P ≤0.004). The COP parameters presented an area under the curve between 0.65-0.72, with sensitivity varying from 66 to 78% and specificity from 54 to 68%. There were no significant differences between fallers and non-fallers on test duration (17 vs. 18s, respectively). The findings showed that the fallers had similar duration time, but poorer balance than the non-fallers during one-legged stance. The COP parameters were able to differentiate the balance between fallers and non-fallers with acceptable area under curve, sensitivity and specificity.

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Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study

Biomarker Insights ◽

10.1177/11772719211027022 ◽

2021 ◽

Vol 16 ◽

pp. 117727192110270

Author(s):

Gönül Açıksarı ◽

Mehmet Koçak ◽

Yasemin Çağ ◽

Lütfiye Nilsun Altunal ◽

Adem Atıcı ◽

...

Keyword(s):

Retrospective Study ◽

Hospital Mortality ◽

Prognostic Value ◽

Current Knowledge ◽

Area Under The Curve ◽

Prognostic Nutritional Index ◽

Inflammatory Biomarkers ◽

Single Center ◽

Discriminative Ability ◽

Lymphocyte Ratio

Background: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including C-reactive protein/albumin ratio (CAR), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in patients with severe COVID-19. Methods: This single-center, retrospective study included a total of 223 patients diagnosed with severe COVID-19. Primary outcome measure was mortality during hospitalization. Multivariate logistic regression analyses were performed to identify independent predictors associated with mortality in patients with severe COVID-19. Receiver operating characteristic (ROC) curve was used to determine cut-offs, and area under the curve (AUC) values were used to demonstrate discriminative ability of biomarkers. Results: Compared to survivors of severe COVID-19, non-survivors had higher CAR, NLR, and PLR, and lower LMR and lower PNI ( P < .05 for all). The optimal CAR, PNI, NLR, PLR, and LMR cut-off values for detecting prognosis were 3.4, 40.2, 6. 27, 312, and 1.54 respectively. The AUC values of CAR, PNI, NLR, PLR, and LMR for predicting hospital mortality in patients with severe COVID-19 were 0.81, 0.91, 0.85, 0.63, and 0.65, respectively. In ROC analysis, comparative discriminative ability of CAR, PNI, and NLR for hospital mortality were superior to PLR and LMR. Multivariate analysis revealed that CAR (⩾0.34, P = .004), NLR (⩾6.27, P = .012), and PNI (⩽40.2, P = .009) were independent predictors associated with mortality in severe COVID-19 patients. Conclusions: The CAR, PNI, and NLR are independent predictors of mortality in hospitalized severe COVID-19 patients and are more closely associated with prognosis than PLR or LMR.

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Different chest CT scoring systems in patients with COVID-19: could baseline CT be a helpful tool in predicting survival in patients with matched ages and co-morbid conditions?

Acta Radiologica ◽

10.1177/02841851211006316 ◽

2021 ◽

pp. 028418512110063

Author(s):

Okan Dilek ◽

Emin Demirel ◽

Hüseyin Akkaya ◽

Mehmet Cenk Belibagli ◽

Gokhan Soker ◽

...

Keyword(s):

Computed Tomography ◽

Severity Score ◽

Area Under The Curve ◽

Scoring Systems ◽

Survival Prediction ◽

Success Rates ◽

Survival Times ◽

The Mean ◽

Early Decision ◽

Age Range

Background Computed tomography (CT) gives an idea about the prognosis in patients with COVID-19 lung infiltration. Purpose To evaluate the success rates of various scoring methods utilized in order to predict survival periods, on the basis of the imaging findings of COVID-19. Another purpose, on the other hand, was to evaluate the agreements among the evaluating radiologists. Material and Methods A total of 100 cases of known COVID-19 pneumonia, of which 50 were deceased and 50 were living, were included in the study. Pre-existing scoring systems, which were the Total Severity Score (TSS), Chest Computed Tomography Severity Score (CT-SS), and Total CT Score, were utilized, together with the Early Decision Severity Score (ED-SS), which was developed by our team, to evaluate the initial lung CT scans of the patients obtained at their initial admission to the hospital. The scans were evaluated retrospectively by two radiologists. Area under the curve (AUC) values were acquired for each scoring system, according to their performances in predicting survival times. Results The mean age of the patients was 61 ± 14.85 years (age range = 18–87 years). There was no difference in co-morbidities between the living and deceased patients. The survival predicted AUC values of ED-SS, CT-SS, TSS, and Total CT Score systems were 0.876, 0.823, 0.753, and 0.744, respectively. Conclusion Algorithms based on lung infiltration patterns of COVID-19 may be utilized for both survival prediction and therapy planning.

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Development of prognostic nomograms using institutional data for patients with triple-negative breast cancer

Future Oncology ◽

10.2217/fon-2021-0677 ◽

2021 ◽

Author(s):

Jie-Yu Zhou ◽

Kang-Kang Lu ◽

Wei-Da Fu ◽

Hao Shi ◽

Jun-Wei Gu ◽

...

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Predictive Accuracy ◽

Area Under The Curve ◽

Disease Free Survival ◽

Discriminative Ability ◽

Free Survival ◽

Disease Free

Background: Triple-negative breast cancer (TNBC) is an aggressive disease. Nomograms can predict prognosis of patients with TNBC. Methods: A total of 745 eligible TNBC patients were recruited and randomly divided into training and validation groups. Endpoints were disease-free survival and overall survival. Concordance index, area under the curve and calibration curves were used to analyze the predictive accuracy and discriminative ability of nomograms. Results: Based on the training cohort, neutrophil-to-lymphocyte ratio, positive lymph nodes, tumor size and tumor-infiltrating lymphocytes were used to construct a nomogram for disease-free survival. In addition, age was added to the overall survival nomogram. Conclusion: The current study developed and validated well-calibrated nomograms for predicting disease-free survival and overall survival in patients with TNBC.

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Investigation of the Effect of Rice Wine on the Metabolites of the Main Components of Herbal Medicine in Rat Urine by Ultrahigh-Performance Liquid Chromatography-Quadrupole/Time-of-Flight Mass Spectrometry: A Case Study onCornus officinalis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2013/306712 ◽

2013 ◽

Vol 2013 ◽

pp. 1-10

Author(s):

Gang Cao ◽

Hao Cai ◽

Xianke Yue ◽

Sicong Tu ◽

Baochang Cai ◽

...

Keyword(s):

Mass Spectrometry ◽

Liquid Chromatography ◽

Herbal Medicine ◽

Rice Wine ◽

Rat Urine ◽

Flight Mass Spectrometry ◽

Cornus Officinalis ◽

Ultrahigh Performance Liquid Chromatography ◽

Main Components

Ultrahigh-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC-QTOF/MS) was developed for rapid and sensitive analysis of the effect of rice wine on the metabolites of the main components of herbal medicine in rat urine. UsingCornus officinalisas a model of herbal medicine, the metabolite profiles of crude and processed (steaming the crude drug presteeped in rice wine)Cornus officinalisextracts in rat urine were investigated. The metabolites ofCornus officinaliswere identified by using dynamic adjustment of the fragmentor voltage to produce structure-relevant fragment ions. In this work, we identified the parent compounds and metabolites of crude and processedCornus officinalisin rats. In total, three parent compounds and seventeen new metabolites ofCornus officinaliswere found in rats. The contents of the parent compounds and metabolitesin vivovaried significantly after intragastric (i.g.) administration of aqueous extracts of crude and processedCornus officinalis. Data from this study suggests that UPLC-QTOF/MS could be used as a potential tool for uncovering the effects of excipients found in the metabolites of the main components of herbal medicine,in vivo, to predict and discover the processing mechanisms of herbal medicine.

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Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder

International Journal of Endocrinology ◽

10.1155/2020/9015713 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Zexin Li ◽

Kaiji Yang ◽

Lili Zhang ◽

Chiju Wei ◽

Peixuan Yang ◽

...

Keyword(s):

Likelihood Ratio ◽

Predictive Value ◽

Thyroid Nodules ◽

Area Under The Curve ◽

Positive Likelihood Ratio ◽

Negative Likelihood Ratio ◽

Discriminative Ability ◽

Sparse Autoencoder ◽

Immune Related Genes

Purpose. Several commercial tests have been used for the classification of indeterminate thyroid nodules in cytology. However, the geographic inconvenience and high cost confine their widespread use. This study aims to develop a classifier for conveniently clinical utility. Methods. Gene expression data of thyroid nodule tissues were collected from three public databases. Immune-related genes were used to construct the classifier with stacked denoising sparse autoencoder. Results. The classifier performed well in discriminating malignant and benign thyroid nodules, with an area under the curve of 0.785 [0.638–0.931], accuracy of 92.9% [92.7–93.0%], sensitivity of 98.6% [95.9–101.3%], specificity of 58.3% [30.4–86.2%], positive likelihood ratio of 2.367 [1.211–4.625], and negative likelihood ratio of 0.024 [0.003–0.177]. In the cancer prevalence range of 20–40% for indeterminate thyroid nodules in cytology, the range of negative predictive value of this classifier was 37–61%, and the range of positive predictive value was 98–99%. Conclusion. The classifier developed in this study has the superb discriminative ability for thyroid nodules. However, it needs validation in cytologically indeterminate thyroid nodules before clinical use.

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