LC-MS based metabolomic approach for the efficient identification and relative quantification of bioavailable cocoa phenolics in human urine

Said, Inamullah Hakeem; Heidorn, Christina; Petrov, Dimitar D.; Retta, Mihella B.; Truex, Johnathan Douglas; Haka, Sara; Ullrich, Matthias S.; Kuhnert, Nikolai

doi:10.1016/j.foodchem.2021.130198

Cited by 7 publications

(15 citation statements)

References 47 publications

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“…Procedure of human feeding study and design conducted is already mentioned in our previous paper 25 . Briefly, there were a total of eight volunteers in the coffee group and six volunteers in the control group.…”

Section: Methodsmentioning

confidence: 99%

“…For the experiments, an Agilent 1260 UHPLC system coupled to a Bruker Daltonics Q‐TOF Impact mass spectrometer was used. The UHPLC‐ESI‐QTOF‐MS method was used with a slight modification from previously established techniques 25 . The MS operating conditions were performed with a capillary temperature of 200°C, a drying gas flow rate of 10 L/min, nebulizer pressure of 3 bars, funnel 1RF of 450 Vpp, funnel 2 RF of 450 Vpp, and hexapole RF of 50 Vpp, transfer time 80.0 μs, and pre‐pulse storage 7.0 μs.…”

Section: Methodsmentioning

confidence: 99%

“…This situation is identical to a human volunteer study on cocoa consumption recently presented by our group. 25 In the case of coffee, a significant set of CGA metabolites in plasma has been published by the group of Crozier, 2 with many derivatives from gut microbial and hepatic metabolism already identified and quantified. 3 Knowledge on the structure and human body fluid concentrations of such metabolites is crucial to allow a deeper understanding of mechanisms underlying beneficial health effects leading to scientifically sound dietary advice to the consumer.…”

Section: Relevance Of Changes Of Steroid Hormone Changes Following Co...mentioning

confidence: 99%

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Unbiased and biased chemometric analysis of LC‐MS data from human urine following coffee intake

Said,

Truex,

Haka

et al. 2023

J Mass Spectrom

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We carried out a human volunteer study with 14 participants, eight of whom were asked to consume one cup of coffee at four different time points. Urine samples were collected at eight time points and analyzed by HPLC‐MS analysis. The LC‐MS data were subjected to unsupervised multivariate statistical analysis (principal component analysis) followed by supervised multivariate analysis (linear discriminant analysis). In an unbiased approach, in the absence of data preselection and filtering, the most important features explaining differences between coffee consumers and the control group observed showed variations in endogenous human hormonal steroid metabolites as well as xanthine derivatives. Only after a biased data treatment data revealed differences between the sample groups based on literature reported chlorogenic acid metabolites resulting directly from coffee intake. Such analysis could confirm the presence of 21 previously reported chlorogenic acid plasma metabolites as urinary metabolites. The application of tandem MS molecular networking revealed the presence of five bioavailable chlorogenic acid derivatives in urine previously not reported, including both quinic acid lactone and dimethoxy caffeoyl esters. Selected cinnamic acids were quantified in urine.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Relevance Of Changes Of Steroid Hormone Changes Following Co...mentioning

confidence: 99%

See 1 more Smart Citation

Unbiased and biased chemometric analysis of LC‐MS data from human urine following coffee intake

Said,

Truex,

Haka

et al. 2023

J Mass Spectrom

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“…This strategy employed multivariate methods such as principal component analysis (PCA) and partial least square discriminate analysis (PLSDA) to identify marker compounds characterizing the difference in two sample groups, here a control group and a cocoa‐consuming group. [ 42 ] However, multivariate methods reveal extensive lists of biomarkers in loading and most important feature plots, of which many are a consequence of background diet and not causally linked to cocoa consumption. Before embarking on this exercise, of multivariate statistical interpretation we designed a human trial avoiding pitfalls of complex samples.…”

Section: Artificial Intelligence and Big Data Strategies For Novel Co...mentioning

confidence: 99%

A Practitioner's Dilemma Mass Spectrometry‐Based Annotation and Identification of Human Plasma and Urinary Polyphenol Metabolites

Kuhnert

Clifford

2022

Molecular Nutrition Food Res

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The practitioner's dilemma in metabolite assignment can be described as follows: for compound and metabolite identification, strict guidelines should be followed using authentic standards only, or uncertainties in structure assignment of compounds with the certainty of consequential errors should be accepted. These uncertainties arise due to limitation of software and databases in combination with the complexity of the human body fluid samples.

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“…The preliminary overview of the data accumulated so far identifies several trends that need to be further confirmed in clinical studies and isolated cultures/mixed fecal cultures fermentation experiments, and specifically the notion that different classes of polyphenols may be associated with distinct biochemical signatures of small phenolic metabolites that affect their downstream distribution and function. Novel combinations of LC-MS-based chemometrics visualization strategies may improve untargeted discovery and analysis of additional phenolic metabolites in human tissues and fluids …”

Section: Structure–activity Relationships: Focus On Methylationmentioning

confidence: 99%

All Polyphenols Are Not Created Equal: Exploring the Diversity of Phenolic Metabolites

Vong

Rathinasabapathy

Moncada

et al. 2022

J. Agric. Food Chem.

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Dietary intake of plant polyphenols is significant, and many of them enter a human body as a highly diverse pool of ring-fission phenolic metabolites arising from digestion and microbial catabolism of the parental structures. Difficulty in designing the uniform intervention studies and limited tools calibrated to detect and quantify the inherent complexity of phenolic metabolites hindered efforts to establish and validate protective health effects of these molecules. Here, we highlight the recent findings that describe novel complex downstream metabolite profiles with a particular focus on dihydrophenolic (phenylpropanoic) acids of microbial origin, ingested and phase II-transformed methylated phenolic metabolites (methylated sinks), and small phenolic metabolites derived from the breakdown of different classes of flavonoids, stilbenoids, and tannins. There is a critical need for precise identification of the individual phenolic metabolite signatures originating from different polyphenol groups to enable future translation of these findings into break-through nutritional interventions and dietary guidelines.

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LC-MS based metabolomic approach for the efficient identification and relative quantification of bioavailable cocoa phenolics in human urine

Cited by 7 publications

References 47 publications

Unbiased and biased chemometric analysis of LC‐MS data from human urine following coffee intake

Unbiased and biased chemometric analysis of LC‐MS data from human urine following coffee intake

A Practitioner's Dilemma Mass Spectrometry‐Based Annotation and Identification of Human Plasma and Urinary Polyphenol Metabolites

All Polyphenols Are Not Created Equal: Exploring the Diversity of Phenolic Metabolites

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