Study shows no consistent pattern was found in health responses to blueberry interventions

Study shows no consistent pattern was found in health responses to blueberry interventions

In a recent study published in Nutrients, researchers conducted a bilberry intervention using quartile divisions to define inter-individual responses to vascular and cognitive endpoints following a specific nutritional intervention.

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Improving individual health requires an understanding of interindividual heterogeneity in food response and endpoints associated with vascular disease and cognitive impairment. Absorption, metabolism, tissue distribution, bioavailability and nutritional function influence variance.

Blueberries are considered a “superfruit” due to their high polyphenol content and antioxidant activity and are associated with a lower risk of obesity, cardiovascular disease, type 2 diabetes mellitus, cognitive maintenance and neuroprotection.

A recent meta-analysis by the authors of the current study demonstrated variability in response to fruit in cardioprotection and cognition across various clinical outcomes.

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 is no data to support consistency or inconsistency.

About the study

In the present study, researchers conducted a urinary metabolomic analysis to compare interindividual differences after ingestion of blueberries as a whole fruit and powder to identify response predictors.

In a week-long, single-blind, cross-over, randomized controlled trial (RCT) in a healthy population, researchers examined two types of blueberries: whole fresh blueberries (160 g), freeze-dried blueberry powder (20 g), and a placebo control (microcrystalline cellulose).

They calculated the intervention response for each outcome as a percentage change (±%) relative to baseline.

The researchers instructed participants to take a tablespoon of the powder mixed with water once a day, ideally before lunch. They also listed polyphenol-rich foods to avoid and kept 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 measured the heart rhythm using an electrocardiogram (ECG) pad. They collected serum samples from participants to assess blood glucose levels and lipid profiles [total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides] and monitored the NO metabolite nitrite (NO2-) by chemiluminescence.

Cognitive endpoints included working memory, assessed using 3-second and 7-second tasks; episodic memory assessed by word recognition tasks and delayed and immediate word recall; Attention is assessed by moods (alert, calm, and content) and finger alertness; and mental fatigue assessed using a visual analogue scale.

On each study day, researchers administered computer-based cognitive tests that lasted about 30 minutes. They examined urine samples submitted by participants using ultra-high pressure liquid chromatography (UHPLC).

They used an untargeted profiling technique and ROC analysis to examine the biomarker potential of urinary metabolites in response to vascular and cognitive endpoints.

Results

40 people with an average age of 26 years and a body mass index (BMI) of 23 kg/m2 took part in the study. After the intervention, subjects showed significant interindividual differences in vascular health indicators and cognitive domains.

For each endpoint examined, there was no consistent response after the two therapies either within or within subjects. Supervised multivariate analysis revealed no significant potential for distinguishing urinary metabolites between treatments.

After controlling for baseline covariance and serum triglycerides, total cholesterol, LDL, HDL, nitrite, and glucose, therapies had no effect on SBP, DBP, or PWV values.

Consumption of whole blueberries or their 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.

The treatments had no effect on cognitive measures, but both cognitive and vascular endpoints showed variability and participants responded randomly to the intervention and the placebo control.

Across all interventions, including identical blueberry treatments, there was limited consistency in responses across cognitive and vascular endpoints. There was no association between gender, BMI, visit order, or response.

Analysis of urine metabolites from baseline samples revealed a predictor of response with an area under the curve (AUC) of 0.7 and a prediction accuracy of 61%.

Conclusions

The blueberry therapy study found variable responses across different endpoints, with no predictive biomarker to distinguish responders.

The results highlight the need for additional techniques to characterize responses in human intervention research and data coupling with metabolomic, genotypic and lifestyle behavioral feedback.

Identifying healthy foods or nutritional categories requires a unique approach. The study also discovered inter-individual differences in clinical outcomes: 31% to 71% of subjects reported better responses and 29% to 66% reported worse responses.

Cerebral blood flow patterns, neurological correlates, heredity, the physical and social environment, and personality could contribute to these differences.

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