Updated Information of the Effects of (Poly)phenols against Type-2 Diabetes Mellitus in Humans: Reinforcing the Recommendations for Future Research

Nutrients. 2022 Aug 30;14(17):3563. doi: 10.3390/nu14173563.

Abstract

(Poly)phenols have anti-diabetic properties that are mediated through the regulation of the main biomarkers associated with type 2 diabetes mellitus (T2DM) (fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), insulin resistance (IR)), as well as the modulation of other metabolic, inflammatory and oxidative stress pathways. A wide range of human and pre-clinical studies supports these effects for different plant products containing mixed (poly)phenols (e.g., berries, cocoa, tea) and for some single compounds (e.g., resveratrol). We went through some of the latest human intervention trials and pre-clinical studies looking at (poly)phenols against T2DM to update the current evidence and to examine the progress in this field to achieve consistent proof of the anti-diabetic benefits of these compounds. Overall, the reported effects remain small and highly variable, and the accumulated data are still limited and contradictory, as shown by recent meta-analyses. We found newly published studies with better experimental strategies, but there were also examples of studies that still need to be improved. Herein, we highlight some of the main aspects that still need to be considered in future studies and reinforce the messages that need to be taken on board to achieve consistent evidence of the anti-diabetic effects of (poly)phenols.

Keywords: bioavailability; blood glucose; diabetes; glycated hemoglobin; interindividual variability; metabolites; polyphenols.

Publication types

  • Review

MeSH terms

  • Blood Glucose / metabolism
  • Diabetes Mellitus, Type 2* / drug therapy
  • Fasting
  • Glycated Hemoglobin / metabolism
  • Humans
  • Phenols / pharmacology

Substances

  • Blood Glucose
  • Glycated Hemoglobin A
  • Phenols

Grants and funding

This study was supported by the Fundação para a Ciência e Tecnologia (FCT)/Ministério da Ciência e do Ensino Superior; grant numbers PTDC/BIA-MOL/31104/2017 (RM), UID/QUI/50006/2020 (MF), UIDB/04567/2020 and UIDP/04567/2020 (CBIOS); UIDB/04539/2020 and UIDBP/4539/2020 (CIBB). COMPETE-FEDER funds (POCI-01-0145-FEDER-007440 and POCI-01-0145-FEDER-031712). The authors would like to acknowledge the support of the iNOVA4Health Research Unit (LISBOA—01–0145—FEDER—007344), which is co-funded by the FCT/Ministério da Ciência e do Ensino Superior and by FEDER under the PT2020 Partnership Agreement. The authors would also like to acknowledge the COFAC/ILIND–Cooperativa De Formação E Animação Cultural CRL/Instituto Lusófono de Investigação e Desenvolvimento (grant COFAC/ILIND/CBIOS/2/2021), and the FCT for the financial support to RM (CEEC/04567/CBIOS/2020) and to MF (2020.04126.CEECIND/CP1596/CT0006). MF also thanks LAQV/EQUIMTE for her contract under the reference LA/P/0008/2020. This research was additionally supported by the National Research Project GREENCOF (Ref.: PID2020-114102RB-I00) funded by the Spanish Ministry of Science and Innovation.