In a recent study published in Nutrients, researchers conducted a blueberry intervention using quartile divisions to determine interindividual responses in vascular and cognitive endpoints following a specific dietary intervention.
survey: Interindividual responses to a blueberry intervention across multiple endpoints. Image credit: Bukhta Yurii/Shutterstock.com
Background
Individual health improvement requires an understanding of interindividual heterogeneity in dietary response and endpoints associated with vascular disease and cognitive impairment. Absorption, metabolism, tissue distribution, bioavailability and nutritional functioning influence dispersion.
Blueberries are considered a “super fruit” due to their high polyphenol content and antioxidant activity, and have been associated with a lower risk of obesity, cardiovascular disease, type 2 diabetes, cognitive support, and neuroprotection.
A recent meta-analysis by the authors of the present study demonstrated variability in fruit response in cardioprotection and cognition across different clinical outcomes.
The results showed a 4.0% increase in systolic blood pressure, a 15% increase in total cholesterol, a 9.0% increase in memory and a 10% increase in executive function. However, there are no data to support consistency or inconsistency.
About the research
In the present study, the researchers performed a metabolomic analysis of urine to compare interindividual differences following consumption of blueberries as whole fruit and powder to identify predictors of response.
In a one-week single-blind crossover randomized controlled trial (RCT) in a healthy population, researchers examined two types of blueberries: whole fresh blueberries (160 g), lyophilized blueberry powder (20 g), and a placebo control (microcrystalline cellulose).
They calculated response to the intervention for each endpoint as percentage change (±%) from baseline.
The researchers instructed participants to take one tablespoon of the powder mixed with water once a day, ideally before lunch. They also listed polyphenol-rich foods to avoid and a food diary to measure blueberry intake.
The researchers measured seven cognitive and nine vascular function endpoints. Vascular function endpoints included systolic and diastolic blood pressure (SBP and DBP) and carotid and radial artery pulse wave velocity (crPWV).
They measure the heart rhythm using an electrocardiogram (ECG). They collected serum samples from the participants to assess blood sugar levels and lipid profiles [total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides] and monitors the NO metabolite nitrite (NO2-) by chemiluminescence.
Cognitive endpoints included working memory assessed using 3 s and 7 s tasks; episodic memory assessed by word recognition and delayed and immediate word recall tasks; attention assessed based on moods (alertness, calmness, and content) and digit alertness; and mental fatigue assessed using a visual analog scale.
Each day of the study, the researchers administered computerized cognitive tests lasting about 30 minutes. They examined urine samples provided by the participants using ultra-high pressure liquid chromatography (UHPLC).
They used an untargeted profiling technique and ROC analysis to explore the biomarker potential of urinary metabolites in response to vascular and cognitive endpoints.
Results
The study included 40 individuals with an average age of 26 years and a body mass index (BMI) of 23 kg/m2. After the intervention, subjects demonstrated significant interindividual variation in measures of vascular health and cognitive domains.
For each endpoint examined, there was no consistent response after the two therapies, both within and within subjects. The observed multivariate analysis revealed no significant potential for discriminating urinary metabolites between treatments.
After controlling for baseline covariate and serum triglycerides, total cholesterol, LDL, HDL, nitrites, and glucose, treatments did not affect SBP, DBP, or PWV levels.
Consumption of whole bilberry or its powder resulted in higher nitrite levels (+69% and +4.30%, respectively) than baseline, while placebo supplementation resulted in a decrease (9.10%); however, the effect was not statistically significant.
Treatments did not affect cognitive measures, but both cognitive and vascular endpoints showed variability, and participants were randomized to the intervention and placebo control.
There was limited consistency in cognitive and vascular endpoint responses across each intervention, including identical blueberry treatments. There was no association between sex, BMI, sequence of visits or response.
Urinary metabolite profiling of baseline samples revealed a predictor of response with an area under the curve (AUC) value of 0.7 and a predictive accuracy of 61%.
Conclusions
A study of blueberry therapies found variable responses across outcomes, with no predictive biomarker to differentiate responders.
The findings highlight the need for more techniques to characterize responses in human intervention studies and link data with metabolomic, genotypic and lifestyle behavior feedback.
A unique approach is needed to identify healthy foods or dietary categories. The study also found interindividual differences in clinical outcomes, with 31% to 71% of subjects reporting improved responses and 29% to 66% reporting worsening responses.
Cerebral blood flow patterns, neurological correlates, heredity, physical and social environment, and personality may contribute to these differences.