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Enregistrement W4402091390 · doi:10.1002/ptr.8313

Polyphenols in clinical trials: Current trends

2024· letter· en· W4402091390 sur OpenAlexaboutno aff
Francisco Alejandro Lagunas‐Rangel

Notice bibliographique

RevuePhytotherapy Research · 2024
Typeletter
Langueen
DomaineMedicine
ThématiquePhytochemicals and Antioxidant Activities
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPolyphenolBioavailabilityGentisic acidBiologyBiochemistryChemistryFood sciencePharmacologyAntioxidant

Résumé

récupéré en direct d'OpenAlex

Polyphenols are natural compounds abundant in plants and currently of great interest to the scientific community because of their potential health benefits (Lagunas-Rangel & Bermúdez-Cruz, 2020). These compounds are commonly found in a wide variety of plant-based foods, such as fruits, vegetables, and whole grains. They are also present in beverages made from these plants, such as tea, chocolate and wine (Rana et al., 2022). Currently, more than 500 diverse polyphenols have been identified in a broad spectrum of more than 400 foods. These compounds are abundantly synthesized as part of the secondary metabolism of plants through the shikimate pathway or the polyketide pathway (Shen et al., 2022). Some polyphenols play essential roles in plant physiological functions, others serve in defense mechanisms against various stress factors and stimuli such as soil, water, and light conditions (Marranzano et al., 2019). Polyphenols are capable of regulating numerous physiological processes, such as cellular redox potential, enzyme activity, cell proliferation, and signal transduction pathways (Lagunas-Rangel, 2023). Despite their pivotal role, it is important to recognize that polyphenols often have low oral bioavailability. This is mainly due to their extensive biotransformation, facilitated by phase I and phase II reactions in enterocytes and liver, as well as interactions with the intestinal microbiota. However, despite these difficulties, its metabolites play an important role in providing health benefits (Luca et al., 2020). Polyphenols have been associated with a lower risk of stroke, myocardial infarction, and diabetes, along with improvements in various health markers, such as lipid profiles, blood pressure, insulin sensitivity, and systemic inflammation. In particular, the flavonoid quercetin and the stilbene resveratrol stand out for their positive effects on cardiometabolic health. Finally, although polyphenols have been associated with an increase in cerebral blood flow that could have a benefit on cognition, this remains doubtful with the available evidence (Fraga et al., 2019). Polyphenols have a wide range of chemical structures, which has led to their classification into different groups. The four main families of polyphenols are flavonoids, lignans, stilbenes, and phenolic acids (Tsao, 2010). In this context, the present study aimed to investigate the number and characteristics of clinical studies conducted on polyphenols, with special attention to the identification of trends in their research. Several polyphenols were identified in the natural products section of the International Union of Basic and Clinical Pharmacology (IUPHAR)/British Pharmacological Society (BPS) Guide to Pharmacology (Harding et al., 2024). Subsequently, a comprehensive analysis of clinical trials included in the ClinicalTrials.gov database (Zarin et al., 2016) was conducted for these polyphenols. The titles and full texts of all identified clinical trials (up to April 2024) were reviewed to collect relevant data, including the type of polyphenol used, the countries participating in the study, the status of the study, and the medical context of the research. In addition, efforts were made to identify and eliminate any duplicate studies or erroneous results. Overall, 1258 clinical trials studying the actions of polyphenols in different contexts were identified (Table 1), of which the majority (60.02%) were completed studies (Figure 1a). The main subgroups of polyphenols studied were flavanols (37.36%), stilbenes (16.93%), and other polyphenols (39.19%) (Figure 2). In particular, curcumin and resveratrol became the most investigated polyphenols, together accounting for 43.8% of all polyphenol-related studies. It should be noted that the United States leads the research on polyphenols, with almost one third of the studies (33.06%), followed by Italy (5.64%), the United Kingdom (4.53%), Canada (3.66%), and Egypt (3.34%) (Figure 1b). Regarding the objectives of clinical studies, a considerable portion is devoted to cancer research (18.20%), closely followed by research on the safety and pharmacokinetics of polyphenol use (14.55%). Other notable areas are research on inflammatory processes (9.78%), cardiovascular diseases (7.15%), diabetes (6.36%), and obesity (5.41%) (Figure 1c). Clinical trials within the flavonoid subclass cover a number of compounds (Figure 2). For example, assays were identified for flavonols (27.87%) such as quercetin, myricetin, and kaempferol; isoflavonoids (6.38%) such as daidzein; flavones (7.66%) such as nobiletin, luteolin, baicalein, and apigenin; dihydrochalcones (0.21%) such as phloretin; and flavanols (57.87%) such as catechin, epicatechin, epicatechin gallate, epigallocatechin, epigallocatechin gallate, theaflavin, and theaflavin gallate. In particular, no clinical studies on anthocyanins, chalcones, dihydroflavonols, or flavanones were found. Notably, research on these compounds is mainly focused on cancer (27%), safety and pharmacokinetics (16%), cardiovascular disease (8%), obesity (8%), and inflammation (7%). Within the subgroup of phenolic acids, clinical trials have been conducted with several compounds (Figure 2). For example, trials were identified for hydroxybenzoic acids (79.25%) such as gallic acid, ellagic acid, and benzoic acid, as well as for hydroxycinnamic acids (20.75%) such as verbascoside, rosmarinic acid, and caffeic acid. However, no clinical studies were found for hydroxyphenylacetic, hydroxyphenylpropanoic, or hydroxyphenylpentanoic acids within this section. Research on these compounds is mainly focused on safety and pharmacokinetics (37%), followed by cancer (18%), inflammation (7%), obesity (7%), and diabetes (6%). Within the lignan subgroup (0.48%), only sesamin was identified, while resveratrol was found within the stilbene subgroup (16.93%). The few studies on lignans predominantly addressed cardiovascular and coronary heart disease, along with influenza infection. Meanwhile, research on stilbenes (entirely resveratrol) explored various aspects such as safety and pharmacokinetics (14.83%), diabetes (12.17%), cardiovascular disease (9.13%), obesity (8.37%), inflammation (8.37%), and cancer (7.22%). Finally, other polyphenols considered in the analysis include curcuminoids (68.56%) such as curcumin, furanocoumarins (0.41%) such as bergaptene, hydroxybenzaldehydes (1.62%) such as vanillin, hydroxyphenylpropenes (18.26%) such as eugenol and gingerol, phenolic terpenes (7.30%) such as thymol and carvacrol, and tyrosols (3.85%) such as oleuropein. Most of the clinical studies on these compounds focus mainly on cancer (31%), safety and pharmacokinetics (13%), inflammation (12%), cardiovascular disease (8%), and diabetes (7%) (Figure 2). Curcumin and resveratrol are the most researched polyphenols, accounting for 43.8% of all studies related to polyphenols. Quercetin follows as the third most studied polyphenol, with 9.7% of the clinical studies focused on it. Figure 3 illustrates the main topics of the clinical trials related to these three compounds and indicates the phases of the trials. In summary, polyphenols are among the most studied natural compounds in clinical trials, which have evaluated their efficacy in various conditions such as cancer, cardiovascular disease, diabetes, obesity, and inflammation, among many others. Even in the midst of the COVID-19 pandemic, some were considered as prophylactic measures to prevent SARS-CoV-2 infection and as potential treatment adjuvants. Thus, its broad spectrum of health benefits has attracted a great deal of attention in the scientific community. In general, its metabolic benefits often outweigh its potential in the fight against cancer, mainly because reaching the high concentrations needed for the latter objective is hampered by its low bioavailability. Francisco Alejandro Lagunas-Rangel: Conceptualization; data curation; formal analysis; investigation; writing – original draft; writing – review and editing. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The author declares no conflict of interest. Data available on request from the author.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,393
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0110,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,012
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,508
Tête enseignante GPT0,599
Écart entre enseignants0,091 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

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