Evidence supports the beneficial effects of berries on glucoregulation, possibly related to flavonoid content, fiber content, or both. The purpose of this study was to assess the potential of mixed berries to improve insulin sensitivity and to identify the potential role of flavonoids and fiber. In a randomized cross-over trial with four treatment periods, overweight/obese men and women were fed a controlled 45% fat diet for one week prior to a meal-based glucose tolerance test. The same base diet was provided during each feeding period with the addition of one of four treatments: whole mixed berries, sugar matched mixed berry juice, sugar matched gelatin, and sugar/fiber matched gelatin. Subjects then completed a meal-based oral glucose tolerance test. Serum glucose, insulin and non-esterified fatty acids were not different between individual treatments. However, in a secondary analysis, the combined berry preparations resulted in a lower serum insulin area under the curve (difference of 0.15 ± 0.066 ln pmol min/mL, mean ± SE, p = 0.0228), compared to the combined gelatin treatments, while the difference for serum glucose did not quite meet statistical significance (difference of 0.17 ± 0.093 ln mg·min/dL, mean ± SE, p = 0.0738). These results suggest the potential for mixed berry preparations to improve post-prandial insulin response.

Epidemiology studies evaluate associations between the metabolome and disease risk. Urine is a common biospecimen used for such studies due to its wide availability and non-invasive collection. Evaluating the robustness of urinary metabolomic profiles under varying preanalytical conditions is thus of interest. Here we evaluate the impact of sample handling conditions on urine metabolome profiles relative to the gold standard condition (no preservative, no refrigeration storage, single freeze thaw). Conditions tested included the use of borate or chlorhexidine preservatives, various storage and freeze/thaw cycles. We demonstrate that sample handling conditions impact metabolite levels, with borate showing the largest impact with 125 of 1048 altered metabolites (adjusted P < 0.05). When simulating a case–control study with expected inconsistencies in sample handling, we predicted the occurrence of false positive altered metabolites to be low (< 11). Predicted false positives increased substantially (≥63) when cases were simulated to undergo alternate handling. Finally, we demonstrate that sample handling impacts on the urinary metabolome were markedly smaller than those in serum. While changes in urine metabolites incurred by sample handling are generally small, we recommend implementing consistent handling conditions and evaluating robustness of metabolite measurements for those showing significant associations with disease outcomes.

Epidemiology studies evaluate associations between the metabolome and disease risk. Urine is a common biospecimen used for such studies due to its wide availability and non-invasive collection. Evaluating the robustness of urinary metabolomic profiles under varying preanalytical conditions is thus of interest. Here we evaluate the impact of sample handling conditions on urine metabolome profiles relative to the gold standard condition (no preservative, no refrigeration storage, single freeze thaw). Conditions tested included the use of borate or chlorhexidine preservatives, various storage and freeze/thaw cycles. We demonstrate that sample handling conditions impact metabolite levels, with borate showing the largest impact with 125 of 1,048 altered metabolites (adjusted P < 0.05). When simulating a case-control study with expected inconsistencies in sample handling, we predicted the occurrence of false positive altered metabolites to be low (< 11). Predicted false positives increased substantially (≥63) when cases were simulated to undergo alternate handling. Finally, we demonstrate that sample handling impacts on the urinary metabolome were markedly smaller than those in serum. While changes in urine metabolites incurred by sample handling are generally small, we recommend implementing consistent handling conditions and evaluating robustness of metabolite measurements for those showing significant associations with disease outcomes.

Background/Objectives: Accurate knowledge of the energy (calorie) value of foods is important for food labeling, food policy, and diet planning to support health. Virtually no data are available on the energy values of chickpeas and lentils,—two pulses that help control blood glucose and body weight. The objective of this study was to measure the metabolizable energy value of chickpeas and lentils when fed as part of a diet and compare those values to Atwater values. Methods: A randomized controlled crossover intervention was conducted to measure the energy value of chickpeas and lentils in humans (n = 18). Total 7-day fecal and urine collections were conducted after a 10-day adaptation to the controlled diet. Results: The metabolizable energy (ME) of the chickpeas is 515 ± 17 kJ/serving (123 ± 4 kcal/serving) (serving mass = 85.5 g), which is 10.4% lower (p = 0.002) and 8.0% lower (p = 0.02) than the ME calculated using Atwater General or Specific Factors, respectively. The metabolizable energy of the lentils is 498 ± 17 kJ/serving (119 ± 4 kcal/serving) (serving mass = 98.5 g), which is 16.0% lower (p < 0.0001) and 13.6% lower (p = 0.003) than the ME calculated using Atwater General or Specific Factors, respectively. Conclusions: Using Atwater Factors to calculate the metabolizable energy value of chickpeas and lentils overestimates their available calories.

Background/Objectives: Oats and barley are β-glucan-rich grains that may reduce risk factors for cardiovascular disease in adults. This study was conducted to evaluate the effects of products made with either whole grain barley or whole grain oats on CVD risk factors in adults. Methods: A 6-week, double-blind, parallel-design, randomized, controlled feeding trial was conducted with 68 adults. Subjects were randomly assigned to either: (1) a control diet containing 0.8 daily servings of whole grain per 2000 kcal, (2) a diet containing 4 daily servings of whole grain oats per 2000 kcal, or (3) a diet containing 4 daily servings of whole grain barley per 2000 kcal. Markers of cardiovascular disease risk were assessed before and after treatment. Results: LDL cholesterol concentrations show a trend of statistical significance across diets (p = 0.0638), with a lowering of 8.9 mg/dL (barley) and 11.2 mg/dL (oats) compared to the control. Both whole grain diets significantly lowered total VLDL and chylomicron particles (p = 0.0272). The oat diet significantly lowered total LDL particles (p = 0.0014), small LDL particles (p = 0.0008), medium–small LDL particles (p = 0.0008), and very small LDL particles (p = 0.0009) and increased LDL particle size (p = 0.0451). The barley diet significantly lowered diastolic blood pressure (p = 0.0388) and vascular cell adhesion molecule concentrations (p = 0.0320). Conclusions: Diets containing products made from whole grain oats may improve blood lipid profiles, while diets containing products made from whole grain barley may provide additional benefits for blood pressure and inflammation.