Updated Information of the Effects of (Poly)phenols against Type-2 Diabetes Mellitus in Humans: Reinforcing the Recommendations for Future Research.
Regina MenezesPaulo N MatafomeMarisa FreitasMaría-Teresa García ConesaPublished in: Nutrients (2022)
(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.
Keyphrases
- insulin resistance
- oxidative stress
- type diabetes
- endothelial cells
- meta analyses
- glycemic control
- randomized controlled trial
- systematic review
- case control
- wound healing
- adipose tissue
- metabolic syndrome
- dna damage
- machine learning
- induced pluripotent stem cells
- high fat diet
- electronic health record
- blood pressure
- cardiovascular disease
- clinical practice
- ischemia reperfusion injury
- health information
- artificial intelligence
- cardiovascular risk factors
- data analysis