An 8-week freeze-dried blueberry supplement impacts immune-related pathways: a randomized, double-blind placebo-controlled trial

Michèle Rousseau, Justine Horne, Frédéric Guénard, Juan de Toro-Martín, Véronique Garneau, Valérie Guay, Michèle Kearney, Geneviève Pilon, Denis Roy, Patrick Couture, Charles Couillard, André Marette, Marie-Claude Vohl, Michèle Rousseau, Justine Horne, Frédéric Guénard, Juan de Toro-Martín, Véronique Garneau, Valérie Guay, Michèle Kearney, Geneviève Pilon, Denis Roy, Patrick Couture, Charles Couillard, André Marette, Marie-Claude Vohl

Abstract

Background: Blueberries contain high levels of polyphenolic compounds with high in vitro antioxidant capacities. Their consumption has been associated with improved vascular and metabolic health.

Purpose: The objective was to examine the effects of blueberry supplement consumption on metabolic syndrome (MetS) parameters and potential underlying mechanisms of action.

Methods: A randomized double-blind placebo-controlled intervention trial was conducted in adults at risk of developing MetS. Participants consumed 50 g daily of either a freeze-dried highbush blueberry powder (BBP) or a placebo powder for 8 weeks (n = 49). MetS phenotypes were assessed at weeks 0, 4 and 8. Fasting blood gene expression profiles and plasma metabolomic profiles were examined at baseline and week 8 to assess metabolic changes occurring in response to the BBP. A per-protocol analysis was used.

Results: A significant treatment effect was observed for plasma triglyceride levels that was no longer significant after further adjustments for age, sex, BMI and baseline values. In addition, the treatment*time interactions were non-significant therefore suggesting that compared with the placebo, BBP had no statistically significant effect on body weight, blood pressure, fasting plasma lipid, insulin and glucose levels, insulin resistance (or sensitivity) or glycated hemoglobin concentrations. There were significant changes in the expression of 49 genes and in the abundance of 35 metabolites following BBP consumption. Differentially regulated genes were clustered in immune-related pathways.

Conclusion: An 8-week BBP intervention did not significantly improve traditional markers of cardiometabolic health in adults at risk of developing MetS. However, changes in gene expression and metabolite abundance suggest that clinically significant cardiometabolic changes could take longer than 8 weeks to present and/or could result from whole blueberry consumption or a higher dosage. BBP may also have an effect on factors such as immunity even within a shorter 8-week timeframe.

Clinical trial registration: clinicaltrials.gov, NCT03266055 , 2017.

Keywords: Blueberry; Gene expression; Immunity; Metabolic syndrome; Metabolomics; Nutrition; Overweight/obesity; Transcriptomics.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Graphical representation of the study protocol. Study design graphical representation from recruitment to the end of the supplementation period. The blue line represents the intervention period. Abbreviation: OGTT, oral glucose tolerance test
Fig. 2
Fig. 2
CONSORT 2010 Flow Diagram
Fig. 3
Fig. 3
Global gene expression change between pre- and post-supplementation states in the blueberry group. MA plot shows the log2 average abundance of transcripts in counts per million mapped reads (log CPM) on the x-axis and the log2-fold change (log FC) on the y-axis. Non-significant genes are represented by grey dots. Over- and under-expressed genes (FC > 1.25) with unadjusted significant differences (paired t test P value < 0.05) are coloured in green and red, respectively. Significant differentially expressed genes from paired t tests (FDR-adjusted P value < 0.05) and showing at least a 1.25 FC are labelled with gene names. The dashed lines represent 1.25 FC
Fig. 4
Fig. 4
Top differentially expressed genes between pre- and post-supplementation states in the blueberry group. Box and whisker plots show median, first, and third quartiles, and maximum and minimum values for the 24 sample pairs before (Pre) and after (Post) the blueberry supplementation. The three transcripts which exhibited the most significant (FDR-adjusted P value < 0.05) over- and under-expression derived from paired t tests (Post vs Pre) are shown on the top and bottom rows, respectively. Green and red lines stand for increasing or decreasing gene expression levels between pre- and post-supplementation states within individual paired samples
Fig. 5
Fig. 5
Network plots of enriched terms following the blueberry supplementation. The network plot depicts the linkages among differentially expressed gene clusters and functional enriched terms in the Gene Ontology Biological Processes (GO-BP) (a) and Reactome (b) pathway databases. The size of the grey dots is proportional to the number of genes in the enriched pathway (from 3 to 16) and the red-to-green color gradient of gene dots represents the direction of the gene expression fold change following the blueberry supplementation from down- to up-regulation, respectively
Fig. 6
Fig. 6
Impact of BBP supplementation on blood metabolite levels. Volcano plot of paired comparisons between metabolite blood levels in pre- and post-supplementation groups. On the x-axis, a count of significant sample pairs is shown. On the y-axis, the minus logarithm of paired t test P values is shown. Blood levels of a given metabolite were considered significantly different between pre- and post-supplementation states when the paired t test P value was < 0.05, the change in metabolite blood levels was higher than 25% (> 1.25-fold change), and the count of significant pairs was higher than the 50% of the total count of pairs. Each dot represents a metabolite. Metabolites showing statistically significant changes following the blueberry supplementation are depicted as blue dots on the right (increase) and left (decrease) top corners. Top-ten significantly different metabolites are labelled. Orn ornithine, DG diacylglycerol, Cer ceramide, Ind-SO4 indoxyl sulfate, TG triglyceride, HipAcid hippuric acid
Fig. 7
Fig. 7
Top metabolites showing significant changes following BBP supplementation. Box and whisker plots show median, first, and third quartiles and maximum and minimum values for the 24 sample pairs before (Pre) and after (Post) the blueberry supplementation. The five metabolites which exhibited the most significant increases and decreases following the supplementation are shown on the top and bottom rows, respectively. Green and red lines stand for increasing or decreasing metabolite blood levels between pre- and post-supplementation states within individual paired samples. Orn ornithine, DG diacylglycerol, Cer ceramide, Ind-SO4 indoxyl sulfate, TG triglyceride, HipAcid hippuric acid
Fig. 8
Fig. 8
Identification of metabolites using Sparse multilevel partial least squares-discriminant analysis (smPLS-DA). A bi-dimensional score plot is shown on the left panel. The score plot reveals the distinct blood metabolomic profile between pre- (red dots) and post-supplementation (green dots) paired participants. The two principal components of the smPLS-DA model along with their corresponding variance in group discrimination are shown on y- and x-axes, respectively. The loading plot representing the top 10 metabolites selected on the first component of the smPLS-DA model is shown on the right. Horizontal bars represent the loading weights of each metabolite. Most important metabolites in group discrimination are ordered according to their loading weights, from bottom to top. Bar colour represents either an increase following supplementation (green bars) or decrease following supplementation (red bars). TG triglyceride, Cer ceramide, DG diacylglycerol, SM sphingolipid, Orn ornithine

References

    1. Aguilar M, Bhuket T, Torres S, Liu B, Wong RJ. Prevalence of the metabolic syndrome in the United States, 2003-2012. JAMA. 2015;313(19):1973–1974. doi: 10.1001/jama.2015.4260.
    1. Riediger ND, Clara I. Prevalence of metabolic syndrome in the Canadian adult population. Can Med Assoc J. 2011;183(15):E1127–E1134. doi: 10.1503/cmaj.110070.
    1. O’Neill S, O’Driscoll L. Metabolic syndrome: a closer look at the growing epidemic and its associated pathologies: metabolic syndrome. Obes Rev. 2015;16(1):1–12. doi: 10.1111/obr.12229.
    1. Rani V, Deep G, Singh RK, Palle K, Yadav UCS. Oxidative stress and metabolic disorders: pathogenesis and therapeutic strategies. Life Sci. 2016;148:183–193. doi: 10.1016/j.lfs.2016.02.002.
    1. Kehrer JP, Klotz L-O. Free radicals and related reactive species as mediators of tissue injury and disease: implications for health. Crit Rev Toxicol. 2015;45(9):765–798. doi: 10.3109/10408444.2015.1074159.
    1. Kasote DM, Katyare SS, Hegde MV, Bae H. Significance of antioxidant potential of plants and its relevance to therapeutic applications. Int J Biol Sci. 2015;11(8):982–991. doi: 10.7150/ijbs.12096.
    1. Wu X, Beecher GR, Holden JM, Haytowitz DB, Gebhardt SE, Prior RL. Concentrations of anthocyanins in common foods in the United States and estimation of normal consumption. J Agric Food Chem. 2006;54(11):4069–4075. doi: 10.1021/jf060300l.
    1. Martineau LC, Couture A, Spoor D, Benhaddou-Andaloussi A, Harris C, Meddah B, Leduc C, Burt A, Vuong T, Mai le P, Prentki M, Bennett SA, Arnason JT, Haddad PS. Anti-diabetic properties of the Canadian lowbush blueberry Vaccinium angustifolium Ait. Phytomedicine. 2006;13(9-10):612–623. doi: 10.1016/j.phymed.2006.08.005.
    1. Wolfe KL, Kang X, He X, Dong M, Zhang Q, Liu RH. Cellular antioxidant activity of common fruits. J Agric Food Chem. 2008;56(18):8418–8426. doi: 10.1021/jf801381y.
    1. DeFuria J, Bennett G, Strissel KJ, Perfield JW, II, Milbury PE, Greenberg AS, Obin MS. Dietary blueberry attenuates whole-body insulin resistance in high fat-fed mice by reducing adipocyte death and its inflammatory sequelae. J Nutr. 2009;139(8):1510–1516. doi: 10.3945/jn.109.105155.
    1. Basu A, Du M, Leyva MJ, Sanchez K, Betts NM, Wu M, Aston CE, Lyons TJ. Blueberries decrease cardiovascular risk factors in obese men and women with metabolic syndrome. J Nutr. 2010;140(9):1582–1587. doi: 10.3945/jn.110.124701.
    1. Johnson SA, Figueroa A, Navaei N, Wong A, Kalfon R, Ormsbee LT, Feresin RG, Elam ML, Hooshmand S, Payton ME, Arjmandi BH. Daily blueberry consumption improves blood pressure and arterial stiffness in postmenopausal women with pre- and stage 1-hypertension: a randomized, double-blind, placebo-controlled clinical trial. J Acad Nutr Diet. 2015;115(3):369–377. doi: 10.1016/j.jand.2014.11.001.
    1. Bowtell JL, Aboo-Bakkar Z, Conway ME, Adlam A-LR, Fulford J. Enhanced task-related brain activation and resting perfusion in healthy older adults after chronic blueberry supplementation. Appl Physiol Nutr Metab. 2017;42(7):773–779. doi: 10.1139/apnm-2016-0550.
    1. Miller MG, Hamilton DA, Joseph JA, Shukitt-Hale B. Dietary blueberry improves cognition among older adults in a randomized, double-blind, placebo-controlled trial. Eur J Nutr. 2018;57(3):1169–1180. doi: 10.1007/s00394-017-1400-8.
    1. Cassidy A, Mukamal KJ, Liu L, Franz M, Eliassen AH, Rimm EB. High Anthocyanin intake is associated with a reduced risk of myocardial infarction in young and middle-aged women. Circulation. 2013;127(2):188–196. doi: 10.1161/CIRCULATIONAHA.112.122408.
    1. Muraki I, Imamura F, Manson JE, Hu FB, Willett WC, van Dam RM, Sun Q. Fruit consumption and risk of type 2 diabetes: results from three prospective longitudinal cohort studies. BMJ. 2013;347(aug28 1):f5001. doi: 10.1136/bmj.f5001.
    1. Stull AJ, Cash KC, Johnson WD, Champagne CM, Cefalu WT. Bioactives in blueberries improve insulin sensitivity in obese, insulin-resistant men and women. J Nutr. 2010;140(10):1764–1768. doi: 10.3945/jn.110.125336.
    1. Stull AJ, Cash KC, Champagne CM, Gupta AK, Boston R, Beyl RA, Johnson WD, Cefalu WT. Blueberries improve endothelial function, but not blood pressure, in adults with metabolic syndrome: a randomized, double-blind, placebo-controlled clinical trial. Nutrients. 2015;7(6):4107–4123. doi: 10.3390/nu7064107.
    1. Riso P, Klimis-Zacas D, Del Bo’ C, Martini D, Campolo J, Vendrame S, Møller P, Loft S, De Maria R, Porrini M. Effect of a wild blueberry (Vaccinium angustifolium) drink intervention on markers of oxidative stress, inflammation and endothelial function in humans with cardiovascular risk factors. Eur J Nutr. 2013;52(3):949–961. doi: 10.1007/s00394-012-0402-9.
    1. Curtis PJ, van der Velpen V, Berends L, Jennings A, Feelisch M, Umpleby AM, Evans M, Fernandez BO, Meiss MS, Minnion M, Potter J, Minihane AM, Kay CD, Rimm EB, Cassidy A. Blueberries improve biomarkers of cardiometabolic function in participants with metabolic syndrome—results from a 6-month, double-blind, randomized controlled trial. Am J Clin Nutr. 2019;109(6):1535–1545. doi: 10.1093/ajcn/nqy380.
    1. Cutler BR, Petersen C, Anandh Babu PV. Mechanistic insights into the vascular effects of blueberries: evidence from recent studies. Mol Nutr Food Res. 2016;61:1600271. doi: 10.1002/mnfr.201600271.
    1. Peña-Romero AC, Navas-Carrillo D, Marín F, Orenes-Piñero E. The future of nutrition: nutrigenomics and nutrigenetics in obesity and cardiovascular diseases. Crit Rev Food Sci Nutr. 2018;58(17):3030–3041. doi: 10.1080/10408398.2017.1349731.
    1. Scarsella C, Alméras N, Mauriège P, Blanchet C, Sauvé L, Dewailly E, Bergeron J, Després J-P. Prevalence of metabolic alterations predictive of cardiovascular disease risk in the Québec population. Can J Cardiol. 2003;19(1):51–57.
    1. Labonté M-È, Cyr A, Baril-Gravel L, Royer M-M, Lamarche B. Validity and reproducibility of a web-based, self-administered food frequency questionnaire. Eur J Clin Nutr. 2012;66(2):166–173. doi: 10.1038/ejcn.2011.163.
    1. Willett W. Nutritional epidemiology. 3. New York: Oxford University Press; 2013.
    1. Loham T, Roche A, Martorel R. Standardization of anthropometric measurements. The Airlie (VA) Consensus Conference. 1988. p. 39–80.
    1. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18(6):499–502. doi: 10.1093/clinchem/18.6.499.
    1. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412–419. doi: 10.1007/BF00280883.
    1. Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22(9):1462–1470. doi: 10.2337/diacare.22.9.1462.
    1. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016;34(5):525–527. doi: 10.1038/nbt.3519.
    1. McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 2012;40(10):4288–4297. doi: 10.1093/nar/gks042.
    1. Yu G, Wang LG, Han Y, He QY. ClusterProfiler: an R package for comparing biological themes among gene clusters. OMICS A J Integr Biol. 2012;16:284–287. doi: 10.1089/omi.2011.0118.
    1. Chong J, Xia J. MetaboAnalystR: an R package for flexible and reproducible analysis of metabolomics data. Bioinformatics. 2018;34:4313–4314. doi: 10.1093/bioinformatics/bty528.
    1. Cao MD, Giskeødegård GF, Bathen TF, Sitter B, Bofin A, Lønning PE, Lundgren S, Gribbestad IS. Prognostic value of metabolic response in breast cancer patients receiving neoadjuvant chemotherapy. 2012.
    1. Westerhuis JA, van Velzen EJJ, Hoefsloot HCJ, Smilde AK. Multivariate paired data analysis: multilevel PLSDA versus OPLSDA. Metabolomics. 2010;6(1):119–128. doi: 10.1007/s11306-009-0185-z.
    1. Lê Cao KA, Boitard S, Besse P. Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems. BMC Bioinformatics. 2011;12:253. doi: 10.1186/1471-2105-12-253.
    1. Rohart F, Gautier B, Singh A, Lê Cao KA. mixOmics: an R package for ‘omics feature selection and multiple data integration. PLoS Comput Biol. 2017;13:e1005752. doi: 10.1371/journal.pcbi.1005752.
    1. Gutch M, Kumar S, Razi S, Gupta K, Gupta A. Assessment of insulin sensitivity/resistance. Indian J Endocrinol Metab. 2015;19(1):160–164. doi: 10.4103/2230-8210.146874.
    1. Rodriguez-Mateos A, Istas G, Boschek L, Feliciano RP, Mills CE, Boby C, Gomez-Alonso S, Milenkovic D, Heiss C. Circulating anthocyanin metabolites mediate vascular benefits of blueberries: insights from randomized controlled trials, metabolomics, and nutrigenomics. J Gerontol A. 2019;74(7):967–976. doi: 10.1093/gerona/glz047.
    1. Zhu Y, Sun J, Lu W, Wang X, Wang X, Han Z, Qiu C. Effects of blueberry supplementation on blood pressure: a systematic review and meta-analysis of randomized clinical trials. J Hum Hypertens. 2017;31(3):165–171. doi: 10.1038/jhh.2016.70.
    1. Huang H, Chen G, Liao D, Zhu Y, Xue X. Effects of berries consumption on cardiovascular risk factors: a meta-analysis with trial sequential analysis of randomized controlled trials. Sci Rep. 2016;6.
    1. Lee I-C, Kim DY, Choi BY. Antioxidative activity of blueberry leaf extract prevents high-fat diet-induced obesity in C57BL/6 mice. J Cancer Prev. 2014;19(3):209–215. doi: 10.15430/JCP.2014.19.3.209.
    1. Aranaz P, Romo-Hualde A, Zabala M, Navarro-Herrera D, Ruiz de Galarreta M, Gil AG, Martinez JA, Milagro FI, González-Navarro CJ. Freeze-dried strawberry and blueberry attenuates diet-induced obesity and insulin resistance in rats by inhibiting adipogenesis and lipogenesis. Food Funct. 2017;8(11):3999–4013. doi: 10.1039/c7fo00996h.
    1. Wu T, Gao Y, Guo X, Zhang M, Gong L. Blackberry and blueberry anthocyanin supplementation counteract high-fat-diet-induced obesity by alleviating oxidative stress and inflammation and accelerating energy expenditure. Oxidative Med Cell Longev. 2018;2018:1–9.
    1. Elks CM, Terrebonne JD, Ingram DK, Stephens JM. Blueberries improve glucose tolerance without altering body composition in obese postmenopausal mice: blueberries and postmenopausal obesity. Obesity. 2015;23(3):573–580. doi: 10.1002/oby.20926.
    1. Liu W, Mao Y, Schoenborn J, Wang Z, Tang G, Tang X. Whole blueberry protects pancreatic beta-cells in diet-induced obese mouse. Nutr Metab. 2019;16(1):34. doi: 10.1186/s12986-019-0363-6.
    1. Vendrame S, Daugherty A, Kristo AS, Klimis-Zacas D. Wild blueberry (Vaccinium angustifolium )-enriched diet improves dyslipidaemia and modulates the expression of genes related to lipid metabolism in obese Zucker rats. Br J Nutr. 2014;111(2):194–200. doi: 10.1017/S0007114513002390.
    1. Jiao X, Wang Y, Lin Y, Lang Y, Li E, Zhang X, Zhang Q, Feng Y, Meng X, Li B. Blueberry polyphenols extract as a potential prebiotic with anti-obesity effects on C57BL/6 J mice by modulating the gut microbiota. J Nutr Biochem. 2019;64:88–100. doi: 10.1016/j.jnutbio.2018.07.008.
    1. Kalea AZ, Clark K, Schuschke DA, Kristo AS, Klimis-Zacas DJ. Dietary enrichment with wild blueberries (Vaccinium angustifolium) affects the vascular reactivity in the aorta of young spontaneously hypertensive rats. J Nutr Biochem. 2010;21(1):14–22. doi: 10.1016/j.jnutbio.2008.09.005.
    1. Mykkänen OT, Huotari A, Herzig K-H, Dunlop TW, Mykkänen H, Kirjavainen PV. Wild blueberries (Vaccinium myrtillus) alleviate inflammation and hypertension associated with developing obesity in mice fed with a high-fat diet. PLoS ONE. 2014;9:e114790. doi: 10.1371/journal.pone.0114790.
    1. Nair AR, Elks CM, Vila J, Del Piero F, Paulsen DB, Francis J. A blueberry-enriched diet improves renal function and reduces oxidative stress in metabolic syndrome animals: potential mechanism of TLR4-MAPK signaling pathway. PLoS ONE. 2014;9:e111976. doi: 10.1371/journal.pone.0111976.
    1. Vendrame S, Daugherty A, Kristo AS, Riso P, Klimis-Zacas D. Wild blueberry (Vaccinium angustifolium) consumption improves inflammatory status in the obese Zucker rat model of the metabolic syndrome. J Nutr Biochem. 2013;24(8):1508–1512. doi: 10.1016/j.jnutbio.2012.12.010.
    1. Vendrame S, Tsakiroglou P, Kristo AS, Schuschke DA, Klimis-Zacas D. Wild blueberry consumption attenuates local inflammation in the perivascular adipose tissue of obese Zucker rats. Appl Physiol Nutr Metab. 2016;41(10):1045–1051. doi: 10.1139/apnm-2016-0160.
    1. Muniyappa R, Lee S, Chen H, Quon MJ. Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage. Am J Physiol-Endocrinol Metab. 2008;294(1):E15–E26. doi: 10.1152/ajpendo.00645.2007.
    1. Chai SC, Davis K, Wright RS, Kuczmarski MF, Zhang Z. Impact of tart cherry juice on systolic blood pressure and low-density lipoprotein cholesterol in older adults: a randomized controlled trial. Food Funct. 2018;9(6):3185–3194. doi: 10.1039/C8FO00468D.
    1. Huang H, Liao D, Chen G, Chen H, Zhu Y. Lack of efficacy of pomegranate supplementation for glucose management, insulin levels and sensitivity: evidence from a systematic review and meta-analysis. Nutr J. 2017;16(1):67. doi: 10.1186/s12937-017-0290-1.
    1. Woerdeman J, Del Rio D, Calani L, Eringa EC, Smulders YM, Serné EH. Red wine polyphenols do not improve obesity-associated insulin resistance: a randomized controlled trial. Diabetes Obes Metab. 2018;20(1):206–210. doi: 10.1111/dom.13044.
    1. Ma Y, Li Y, Chiriboga DE, Olendzki BC, Hebert JR, Li W, Leung K, Hafner AR, Ockene IS. Association between carbohydrate intake and serum lipids. J Am Coll Nutr. 2006;25(2):155–163. doi: 10.1080/07315724.2006.10719527.
    1. Sivashanmugam M, Jaidev J, Umashankar V, Sulochana KN. Ornithine and its role in metabolic diseases: an appraisal. Biomed Pharmacother. 2017;86:185–194. doi: 10.1016/j.biopha.2016.12.024.
    1. Heller JS, Chen KY, Kyriakidis DA, Fong WF, Canellakis ES. The modulation of the induction of ornithine decarboxylase by spermine, spermidine and diamines. J Cell Physiol. 1978;96(2):225–234. doi: 10.1002/jcp.1040960211.
    1. Neto CC. Cranberry and blueberry: evidence for protective effects against cancer and vascular diseases. Mol Nutr Food Res. 2007;51(6):652–664. doi: 10.1002/mnfr.200600279.
    1. Farthing DE, Farthing CA, Xi L. Inosine and hypoxanthine as novel biomarkers for cardiac ischemia: from bench to point-of-care. Exp Biol Med. 2015;240(6):821–831. doi: 10.1177/1535370215584931.
    1. Rodriguez-Mateos A, Del Pino-García R, George TW, Vidal-Diez A, Heiss C, Spencer JPE. Impact of processing on the bioavailability and vascular effects of blueberry (poly)phenols. Mol Nutr Food Res. 2014;58(10):1952–1961. doi: 10.1002/mnfr.201400231.
    1. de Ferrars RM, Cassidy A, Curtis P, Kay CD. Phenolic metabolites of anthocyanins following a dietary intervention study in post-menopausal women. Mol Nutr Food Res. 2014;58(3):490–502. doi: 10.1002/mnfr.201300322.
    1. Nieman DC, Kay CD, Rathore AS, Grace MH, Strauch RC, Stephan EH, Sakaguchi CA, Lila MA. Increased plasma levels of gut-derived phenolics linked to walking and running following two weeks of flavonoid supplementation. Nutrients. 2018;10:1718. doi: 10.3390/nu10111718.
    1. Parks EJ, Hellerstein MK. Carbohydrate-induced hypertriacylglycerolemia: historical perspective and review of biological mechanisms. Am J Clin Nutr. 2000;71(2):412–433. doi: 10.1093/ajcn/71.2.412.
    1. Andrianjafimasy M, Zerimech F, Akiki Z, Huyvaert H, Le Moual N, Siroux V, Matran R, Dumas O, Nadif R. Oxidative stress biomarkers and asthma characteristics in adults of the EGEA study. Eur Respir J. 2017;50(6):1701193. doi: 10.1183/13993003.01193-2017.
    1. Rudkowska I, Paradis A-M, Thifault E, Julien P, Tchernof A, Couture P, Lemieux S, Barbier O, Vohl M-C. Transcriptomic and metabolomic signatures of an n-3 polyunsaturated fatty acids supplementation in a normolipidemic/normocholesterolemic Caucasian population. J Nutr Biochem. 2013;24(1):54–61. doi: 10.1016/j.jnutbio.2012.01.016.
    1. van Breda SGJ, Wilms LC, Gaj S, Jennen DGJ, Briedé JJ, Helsper JP, Kleinjans JCS, de Kok TMCM. Can transcriptomics provide insight into the chemopreventive mechanisms of complex mixtures of phytochemicals in humans? Antioxid Redox Signal. 2014;20(14):2107–2113. doi: 10.1089/ars.2013.5528.
    1. Nair AR, Mariappan N, Stull AJ, Francis J. Blueberry supplementation attenuates oxidative stress within monocytes and modulates immune cell levels in adults with metabolic syndrome: a randomized, double-blind, placebo-controlled trial. Food Funct. 2017;8(11):4118–4128. doi: 10.1039/C7FO00815E.
    1. Ahmed M, Henson DA, Sanderson MC, Nieman DC, Gillitt ND, Lila MA. The protective effects of a polyphenol-enriched protein powder on exercise-induced susceptibility to virus infection. Phytother Res. 2014;28(12):1829–1836. doi: 10.1002/ptr.5208.
    1. McAnulty LS, Collier SR, Landram MJ, Whittaker DS, Isaacs SE, Klemka JM, Cheek SL, Arms JC, McAnulty SR. Six weeks daily ingestion of whole blueberry powder increases natural killer cell counts and reduces arterial stiffness in sedentary males and females. Nutr Res. 2014;34(7):577–584. doi: 10.1016/j.nutres.2014.07.002.
    1. Charles A, Janeway J, Travers P, Walport M, Shlomchik MJ. The components of the immune system. Immunobiology: the immune system in health and disease 5th edition [Internet] New York: Garland Science; 2001.
    1. Rudkowska I, Raymond C, Ponton A, Jacques H, Lavigne C, Holub BJ, Marette A, Vohl M-C. Validation of the use of peripheral blood mononuclear cells as surrogate model for skeletal muscle tissue in nutrigenomic studies. OMICS. 2011;15(1-2):1–7. doi: 10.1089/omi.2010.0073.
    1. Schisterman EF, Mumford SL, Sjaarda LA. Failure to consider the menstrual cycle phase may cause misinterpretation of clinical and research findings of cardiometabolic biomarkers in premenopausal women. Epidemiol Rev. 2014;36(1):71–82. doi: 10.1093/epirev/mxt007.
    1. Kawano H, Motoyama T, Kugiyama K, Hirashima O, Ohgushi M, Yoshimura M, Ogawa H, Okumura K, Yasue H. Menstrual cyclic variation of endothelium-dependent vasodilation of the brachial artery: possible role of estrogen and nitric oxide. Proc Assoc Am Physicians. 1996;108(6):473–480.
    1. Serafini M, Testa MF, Villaño D, Pecorari M, van Wieren K, Azzini E, Brambilla A, Maiani G. Antioxidant activity of blueberry fruit is impaired by association with milk. Free Radic Biol Med. 2009;46(6):769–774. doi: 10.1016/j.freeradbiomed.2008.11.023.
    1. Michalska A, Łysiak G. Bioactive compounds of blueberries: post-harvest factors influencing the nutritional value of products. Int J Mol Sci. 2015;16(8):18642–18663. doi: 10.3390/ijms160818642.
    1. Nemzer B, Vargas L, Xia X, Sintara M, Feng H. Phytochemical and physical properties of blueberries, tart cherries, strawberries, and cranberries as affected by different drying methods. Food Chem. 2018;262:242–250. doi: 10.1016/j.foodchem.2018.04.047.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe