Diagnostic Performance of Urinary Resveratrol Metabolites as a Biomarker of Moderate Wine Consumption

Abstract Background: Nutritional biomarkers may be better measures of dietary exposure than self-reported dietary data. We evaluated resveratrol metabolites, potential biomarkers of wine consumption, in humans after moderate consumption of sparkling, white, or red wines. Methods: We performed 2 randomized, crossover trials and a cohort study. In the first study, 10 healthy men consumed 30 g of ethanol/day as sparkling wine or gin for 28 days. In the second trial, 10 healthy women consumed 20 g of ethanol/day as white or red wine for 28 days. We also evaluated 52 participants in a study on the effects of a Mediterranean diet on primary prevention of cardiovascular disease (the PREDIMED Study). We used liquid chromatography–tandem mass spectrometry to analyze urinary total resveratrol metabolites (TRMs) and predictive values and ROC curve analyses to assess the diagnostic accuracy. Results: We observed significant increases in TRMs [72.4 (95% confidence interval, 48.5–96.2; P = 0.005), 211.5 (166.6–256.3; P = 0.005), and 560.5 nmol/g creatinine (244.9–876.1; P = 0.005)] after consumption of sparkling, white, or red wine, respectively, but no changes after the washout or gin periods. In the cohort study, the reported daily dose of wine consumption correlated directly with TRMs (r = 0.654; P <0.001). Using a cutoff of 90 nmol/g, we were able to use TRMs to differentiate wine consumers from abstainers with a sensitivity of 72% (60%–84%); and a specificity of 94% (87%–100%). Conclusions: Resveratrol metabolites in urine may be useful biomarkers of wine intake in epidemiologic and intervention studies.

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The glass that cheers: Phenolic and polyphenolic constituents and the beneficial effects of moderate red wine consumption

The Biochemist ◽

10.1042/bio03206004 ◽

2010 ◽

Vol 32 (6) ◽

pp. 4-9 ◽

Cited By ~ 6

Author(s):

Alan Crozier ◽

Gina Borges ◽

Danielle Ryan

Keyword(s):

Cardiovascular Disease ◽

Phenolic Compounds ◽

Red Wine ◽

Protective Effects ◽

Red Wines ◽

Wine Consumption ◽

Beneficial Effects ◽

Rich Diversity ◽

Polyphenolic Profile

Red wines, moderate consumption of which is associated with beneficial effects on health, including a reduced incidence of cardiovascular disease, contain a rich diversity of simple and complex (poly)phenolic compounds. Subtle changes in the polyphenolic profile occur during maturation of the wine which affects its colour and taste. Although the protective effects of red wine consumption have been linked with resveratrol and procyanidins, the identity of the compounds involved remains unclear.

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A prospective cohort study of red wine consumption and risk of prostate cancer

International Journal of Cancer ◽

10.1002/ijc.22498 ◽

2007 ◽

Vol 120 (7) ◽

pp. 1529-1535 ◽

Cited By ~ 31

Author(s):

Siobhan Sutcliffe ◽

Edward Giovannucci ◽

Michael F. Leitzmann ◽

Eric B. Rimm ◽

Meir J. Stampfer ◽

...

Keyword(s):

Prostate Cancer ◽

Cohort Study ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Red Wine ◽

Wine Consumption

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Plasma Metabolites Associated with Frequent Red Wine Consumption: A Metabolomics Approach within the PREDIMED Study

Molecular Nutrition & Food Research ◽

10.1002/mnfr.201900140 ◽

2019 ◽

Vol 63 (17) ◽

pp. 1900140 ◽

Cited By ~ 8

Author(s):

Pablo Hernández‐Alonso ◽

Christopher Papandreou ◽

Mònica Bulló ◽

Miguel Ruiz‐Canela ◽

Courtney Dennis ◽

...

Keyword(s):

Red Wine ◽

Plasma Metabolites ◽

Wine Consumption ◽

Predimed Study

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Element and redox homeostasis in rats after red wine consumption

Zeitschrift für Gastroenterologie ◽

10.1055/s-0031-1278515 ◽

2011 ◽

Vol 49 (05) ◽

Author(s):

K Szentmihályi ◽

Z May ◽

H Fébel ◽

G Bekő ◽

A Blázovics

Keyword(s):

Red Wine ◽

Redox Homeostasis ◽

Wine Consumption

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Predictive value of the neutrophil to lymphocyte ratio for disease deterioration and serious adverse outcomes in patients with COVID-19: a prospective cohort study

BMC Infectious Diseases ◽

10.1186/s12879-021-05796-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Zhi-Yong Zeng ◽

Shao-Dan Feng ◽

Gong-Ping Chen ◽

Jiang-Nan Wu

Keyword(s):

Cohort Study ◽

Hospital Admission ◽

Clinical Outcomes ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Characteristic Curve ◽

Adverse Outcomes ◽

Neutrophil To Lymphocyte Ratio ◽

Predictive Values ◽

Lymphocyte Ratio

Abstract Background Early identification of patients who are at high risk of poor clinical outcomes is of great importance in saving the lives of patients with novel coronavirus disease 2019 (COVID-19) in the context of limited medical resources. Objective To evaluate the value of the neutrophil to lymphocyte ratio (NLR), calculated at hospital admission and in isolation, for the prediction of the subsequent presence of disease progression and serious clinical outcomes (e.g., shock, death). Methods We designed a prospective cohort study of 352 hospitalized patients with COVID-19 between January 9 and February 26, 2020, in Yichang City, Hubei Province. Patients with an NLR equal to or higher than the cutoff value derived from the receiver operating characteristic curve method were classified as the exposed group. The primary outcome was disease deterioration, defined as an increase of the clinical disease severity classification during hospitalization (e.g., moderate to severe/critical; severe to critical). The secondary outcomes were shock and death during the treatment. Results During the follow-up period, 51 (14.5%) patients’ conditions deteriorated, 15 patients (4.3%) had complicated septic shock, and 15 patients (4.3%) died. The NLR was higher in patients with deterioration than in those without deterioration (median: 5.33 vs. 2.14, P < 0.001), and higher in patients with serious clinical outcomes than in those without serious clinical outcomes (shock vs. no shock: 6.19 vs. 2.25, P < 0.001; death vs. survival: 7.19 vs. 2.25, P < 0.001). The NLR measured at hospital admission had high value in predicting subsequent disease deterioration, shock and death (all the areas under the curve > 0.80). The sensitivity of an NLR ≥ 2.6937 for predicting subsequent disease deterioration, shock and death was 82.0% (95% confidence interval, 69.0 to 91.0), 93.3% (68.0 to 100), and 92.9% (66.0 to 100), and the corresponding negative predictive values were 95.7% (93.0 to 99.2), 99.5% (98.6 to 100) and 99.5% (98.6 to 100), respectively. Conclusions The NLR measured at admission and in isolation can be used to effectively predict the subsequent presence of disease deterioration and serious clinical outcomes in patients with COVID-19.

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Comparison of Three Accelerated Oxidation Tests Applied to Red Wines with Different Chemical Composition

Molecules ◽

10.3390/molecules26040815 ◽

2021 ◽

Vol 26 (4) ◽

pp. 815

Author(s):

Francesca Coppola ◽

Luigi Picariello ◽

Martino Forino ◽

Luigi Moio ◽

Angelita Gambuti

Keyword(s):

Red Wine ◽

Phenolic Composition ◽

Red Wines ◽

Initial Composition ◽

Accelerated Oxidation ◽

Before And After ◽

Saturation Method ◽

Lower Variability ◽

Wine Oxidation ◽

Wine Color

Background: Three accelerated oxidation tests were proposed to simulate red wine oxidation thus providing information useful to correctly manage moderate oxygen exposure of wine during aging in regard to phenolic composition and wine color. Since the results of the tests have never been compared on wines with different initial composition, the aim of this study was to find a suitable method to simulate oxidation of any still red wine. Methods: Aglianico, Barbera, Gaglioppo, Magliocco, and Nerello wines were treated with (1) three cycles of air saturation, (2) the addition of hydrogen peroxide, and (3) the addition of acetaldehyde. Changes in chromatic characteristics and phenolic composition were determined by spectrophotometric and HPLC methods. Results: Important differences in the behavior of the different wines were detected: the highest formation of polymeric pigments was observed in Barbera and Aglianico wines. In contrast, Gaglioppo and Magliocco wines showed a lower variability before and after the oxidation probably due to the lower anthocyanin/tannin ratio. Among the accelerated oxidation tests applied, no significant differences in color parameters and phenolic composition were detected in samples treated with the addition of H2O2 and the air saturation method. Conclusion: The study demonstrated that H2O2 addition is a successful tool to predict the evolution of different phenolic compounds during the air saturation treatment of wines.

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Developing a clinical prediction rule for repeated consultations with functional somatic symptoms in primary care: a cohort study

BMJ Open ◽

10.1136/bmjopen-2020-040730 ◽

2021 ◽

Vol 11 (1) ◽

pp. e040730

Author(s):

Gea A Holtman ◽

Huibert Burger ◽

Robert A Verheij ◽

Hans Wouters ◽

Marjolein Y Berger ◽

...

Keyword(s):

Primary Care ◽

Cohort Study ◽

Somatic Symptoms ◽

Prediction Rule ◽

Clinical Prediction Rule ◽

Model Discrimination ◽

Clinical Prediction ◽

Internal Validation ◽

Predictive Values ◽

Healthy Activity

ObjectivesPatients who present in primary care with chronic functional somatic symptoms (FSS) have reduced quality of life and increased health care costs. Recognising these early is a challenge. The aim is to develop and internally validate a clinical prediction rule for repeated consultations with FSS.Design and settingRecords from the longitudinal population-based (‘Lifelines’) cohort study were linked to electronic health records from general practitioners (GPs).ParticipantsWe included patients consulting a GP with FSS within 1 year after baseline assessment in the Lifelines cohort.Outcome measuresThe outcome is repeated consultations with FSS, defined as ≥3 extra consultations for FSS within 1 year after the first consultation. Multivariable logistic regression, with bootstrapping for internal validation, was used to develop a risk prediction model from 14 literature-based predictors. Model discrimination, calibration and diagnostic accuracy were assessed.Results18 810 participants were identified by database linkage, of whom 2650 consulted a GP with FSS and 297 (11%) had ≥3 extra consultations. In the final multivariable model, older age, female sex, lack of healthy activity, presence of generalised anxiety disorder and higher number of GP consultations in the last year predicted repeated consultations. Discrimination after internal validation was 0.64 with a calibration slope of 0.95. The positive predictive value of patients with high scores on the model was 0.37 (0.29–0.47).ConclusionsSeveral theoretically suggested predisposing and precipitating predictors, including neuroticism and stressful life events, surprisingly failed to contribute to our final model. Moreover, this model mostly included general predictors of increased risk of repeated consultations among patients with FSS. The model discrimination and positive predictive values were insufficient and preclude clinical implementation.

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Gut and microbial resveratrol metabolite profiling after moderate long-term consumption of red wine versus dealcoholized red wine in humans by an optimized ultra-high-pressure liquid chromatography tandem mass spectrometry method

Journal of Chromatography A ◽

10.1016/j.chroma.2012.09.093 ◽

2012 ◽

Vol 1265 ◽

pp. 105-113 ◽

Cited By ~ 42

Author(s):

Maria Rotches-Ribalta ◽

Mireia Urpi-Sarda ◽

Rafa Llorach ◽

Maria Boto-Ordoñez ◽

Olga Jauregui ◽

...

Keyword(s):

Mass Spectrometry ◽

High Pressure ◽

Metabolite Profiling ◽

Red Wine ◽

Tandem Mass ◽

Spectrometry Method ◽

Ultra High Pressure ◽

Chromatography Tandem Mass Spectrometry ◽

Liquid Chromatography Tandem Mass

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Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study

BMC Health Services Research ◽

10.1186/s12913-021-06762-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Lisa M. Lix ◽

Shamsia Sobhan ◽

Audray St-Jean ◽

Jean-Marc Daigle ◽

Anat Fisher ◽

...

Keyword(s):

Cohort Study ◽

Cardiovascular Mortality ◽

Population Based ◽

Vital Statistics ◽

Practice Research ◽

Clinical Practice Research Datalink ◽

Health Records ◽

Predictive Values ◽

Site Specific ◽

Hospital Deaths

Abstract Background Cardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data. Methods Administrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age. Results The cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths. Conclusions A cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.

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