A.
Pedret
ab,
E.
Llauradó
*ab,
L.
Calderón-Pérez
c,
J.
Companys
a,
L.
Pla-Pagà
a,
P.
Salamanca
a,
B. A.
Sandoval-Ramírez
a,
M.
Besora-Moreno
a,
Ú.
Catalán
a,
S.
Fernández-Castillejo
a,
I.
Ludwig‡
d,
A.
Macià
d,
L.
Rubió-Piqué
d,
M.
Sampson
e,
A. T.
Remaley
ef,
R. M.
Valls
*ab,
M. J.
Motilva§
g and
R.
Solà§
abh
aUniversitat Rovira i Virgili, Facultat de Medicina i Ciències de la Salut, Functional Nutrition, Oxidation and Cardiovascular Diseases Group (NFOC-Salut), Reus, Spain. E-mail: elisabet.llaurado@urv.cat; rosamaria.valls@urv.cat
bInstitut Investigació Sanitària Pere i Virgili (IISPV), Reus-Tarragona 43204, Spain
cEurecat, Centre Tecnològic de Catalunya, Unitat de Nutrició i Salut, Reus, 43204, Spain
dUniversity of Lleida-Agrotecnio CERCA Center, Av. Alcalde Rovira Roure 191, Lleida, 25198, Spain
eDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA
fLipoprotein Metabolism Section, Cardio-Pulmonary Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
gInstituto de Ciencias de la Vid y del Vino (CSIC, Gobierno de la Rioja, Universidad de La Rioja), Logroño, Spain
hHospital Universitari Sant Joan de Reus, Reus, Spain
First published on 14th February 2025
Our aim was to assess the effect of intake of anthocyanin biofortified red-fleshed apples (RFA) versus that of common white apples (WFA) without anthocyanins on the NMR lipoprotein subfraction profile and other NMR metabolites. Additionally, an aronia infusion (AI) arm, matching the anthocyanin content and profile of the RFA, was included. A 6-week, randomized, parallel study was conducted in hypercholesterolemic subjects (n = 121). Anthocyanin-rich products (RFA and AI) decreased LDLc; ApoB; total, large, and small LDL-P; LDL size; TG/HDL ratio; and large TRL, versus WFA. All treatments significantly decreased HDLc, ApoA1, and total HDL-P, with the most significant reductions after RFA treatment. RFA significantly decreased large HDL-P compared to WFA and AI, while medium HDL-P decreased significantly after AI compared to WFA. Anthocyanin-rich products decreased GlycA and alanine and increased acetoacetate versus WFA. WFA and RFA decreased plasma citrate versus AI. Thus, anthocyanin-rich products provided greater protection against CVD risk than WFA.
The diet followed in Western countries does not appear to guarantee an adequate intake of flavonoids.7 Metabolic engineering of plant secondary metabolite pathways for improving human health is a focus of many current plant biotechnology and breeding programs. “Biofortification” is the genetic improvement of food crops to achieve health outcomes.8 Plant cultivars biofortified with specific secondary metabolites have also been produced through traditional breeding programs as an alternative to genetic modification. In this sense, ACNs are the most intensively studied group of secondary plant metabolites. The knowledge of the key genes involved in anthocyanin synthesis has allowed the production of new red cultivars by traditional breeding methods, without genetic modification, and with an enhanced content of ACNs.9
The apple is one of the most widely consumed fruits globally,10 the decrease in LDL cholesterol (LDLc) being the main impact of anthocyanin consumption on CVD markers.5,11 Due to this, our aim was to assess the effect of the intake of ACN biofortified red-fleshed apples (RFA), without genetic modifications versus that of common white-fleshed apples (WFA) without ACN on the NMR lipoprotein subfraction profile and other NMR metabolites. Additionally, we included an aronia infusion (AI) arm, which matched the ACN content and profile of the RFA, to assess the apple matrix effect. We aim to explore the benefits of LDL and other lipoprotein markers beyond LDLc.
Aronia fruit, selected for its high content of cyanidin-3-O-galactoside and cyanidin-O-arabinoside (the main ACNs in RFA), was used in powdered form (Aronia Pulver, BIOJOY, Nuremberg, Germany) to prepare a daily cold-water infusion. Volunteers prepared the infusion by mixing 50 g of aronia fruit powder with 1 L of mineral water (Bezoya mineral water, Calidad Pascual, Aranda de Duero, Burgos, Spain), homogenizing the mixture energetically in a glass bottle for 3 minutes, filtering it with a cloth, and storing the filtered infusion in a light-protected bottle for daily consumption. This preparation provided a daily dose of ACNs equivalent to that found in the daily RFA dose. Daily doses of 80 g of WFA and RFA snacks and 1 L of AI provided 0 mg day−1, 34.5 mg day−1 and 37.4 mg day−1 of total ACNs, respectively. ESI Table 1† shows the phenolic composition present in the products used in the study and the daily dose of macronutrients (g) and other phytochemicals (mg).
During the intervention period, subjects were instructed to preserve their lifestyle, physical activity, and dietary habits, to completely refrain from consuming ACN-rich foods (berries, grapefruit, plums, figs, pomegranate, green and red apples, black olives, red and black beans and red wine), and to avoid eating functional foods for reducing cholesterol levels. The adherence of the volunteers to their dietary habits through the study was assessed by a 3-day food record at the baseline and at the end of the study. At each visit, subjects also underwent a physical examination by a general practitioner, completed a Physical Activity Questionnaire Class AF14 and had anthropometric and blood pressure measurements recorded. Plastic and seal containers for RFA and WFA and the daily dose bag of aronia powder were returned after intervention by volunteers to check their compliance. Outcomes were assessed at the beginning of the study (baseline) and at the end (6 weeks) of intervention periods. Primary outcome measures were changes in lipoprotein subclasses and subfractions, and secondary outcomes were other parameters included in the LP4 NMR MetaboProfile™ profile.
Blood samples, collected at the beginning and at the end of the study, were stored at −80 °C in the central laboratory's Biobanc of HUSJ (biobanc.reus@iispv.cat) until required for batch analyses. Serum samples were shipped to the National Heart, Lung and Blood Institute, National Institutes of Health (NIH; Bethesda, MD, USA).
Lipoprotein subclass measurement was performed by nuclear magnetic resonance (NMR) in a Vantera clinical spectrometer, produced by LipoScience (Raleigh, NC, U.S.A.). The NMR LipoProfile test by LipoScience involves measurement of the 400 MHz proton NMR spectrum of samples and uses the characteristic signal amplitude of the lipid methyl group broadcast by every lipoprotein subfraction as the basis for quantification.15 NMR by using the LipoProfile-4 algorithm was performed to quantify the average particle size and concentrations of triglyceride rich lipoproteins (TRL), LDL, and high-density lipoproteins (HDL). NMR LipoProfile spectra use a further-optimized deconvolution algorithm (LP4) to simultaneously measure a novel NMR inflammation biomarker (GlycA). The LP4 deconvolution algorithm also allows the measurement of 7 different HDL particle subspecies, prompted by emerging evidence for the functional and proteomic diversity of different-sized HDL particles.
Variable | WFA (n = 41) | AI (n = 40) | RFA (n = 40) | P |
---|---|---|---|---|
Data expressed as mean ± standard deviation or percentages. WFA, white-fleshed apple; AI, aronia infusion; RFA, red-fleshed apple; SBP, systolic blood pressure; DBP, diastolic blood pressure; pulse pressure = SBP-DBP; BMI, body mass index (weight/(height in meters)2); pl, plasma; LDL, low density lipoproteins; HDL, high density lipoproteins * median (25th–75th percentiles). AU, arbitrary units: 0–1, inactive; 2–3, very low activity; 4–5, low activity; 6–11, moderately active; > or ≥12, very active. P for ANOVA with logarithmic transformation for triglycerides. A p-value < 0.05 was considered statistically significant. | ||||
Age, years | 49.8 ± 13.6 | 49.6 ± 13.3 | 46.7 ± 16.3 | 0.566 |
Females, % | 67.5 | 50 | 55.3 | 0.287 |
SBP, mm Hg | 127 ± 16.7 | 127 ± 14.4 | 132 ± 16.5 | 0.285 |
DPB, mm Hg | 76 ± 11.1 | 77 ± 10.1 | 79 ± 9.7 | 0.317 |
Weight, kg | 68.7 ± 12.4 | 71.8 ± 11.1 | 74.2 ± 11.6 | 0.123 |
BMI, kg m−2 | 24.6 ± 3.2 | 26.3 ± 4.5 | 26.3 ± 3.8 | 0.078 |
Waist circumference, cm | 86.9 ± 11.5 | 89.3 ± 9.6 | 90.9 ± 9.1 | 0.253 |
Waist/height, cm | 0.52 ± 0.06 | 0.54 ± 0.06 | 0.54 ± 0.06 | 0.281 |
Conicity index | 1.24 ± 0.09 | 1.25 ± 0.07 | 1.26 ± 0.07 | 0.836 |
Glucose, pl, mg dL−1 | 91 ± 11.3 | 93 ± 6.0 | 92 ± 8.4 | 0.506 |
Cholesterol, pl, mg dL−1 | ||||
Total | 220 ± 48 | 223 ± 26 | 213 ± 54 | 0.611 |
LDL | 145 ± 25.9 | 144 ± 20.3 | 147 ± 19.6 | 0.835 |
HDL | 60.0 ± 17.1 | 60.0 ± 16.4 | 53.8 ± 16.6 | 0.143 |
Triglycerides* pl, mg dL−1 | 82 (60–117) | 81 (64–108) | 87 (58–128) | 0.836 |
Physical activity, AU | 4.34 ± 2.24 | 5.10 ± 1.68 | 4.35 ± 1.95 | 0.146 |
Δ Concentration (At the end of intervention (6-weeks) – basal value (day 0); in plasma) | |||
---|---|---|---|
WFA snack | RFA snack | AI | |
Anthocyanins | |||
Peonidin-3-O-galactoside (nM ± SEM) | n.d. | 0.73 ± 0.03 | 0.63 ± 0.02 |
Dihydrochalcones | |||
Phloretin-2′-O-glucuronide (nM ± SEM) | 0.36 ± 0.34 | 8.83 ± 0.37 | n.d. |
Δ Concentration (At the end of intervention (6-weeks) – basal value (day 0); in 24 h urine excretion) | |||
---|---|---|---|
n.d., non-detectable. | |||
Anthocyanins | |||
Peonidin-3-O-galactoside (nmols ± SEM) | n.d. | 4.94 ± 0.36 | 18.4 ± 0.22 |
Dihydrochalcones | |||
Phloretin-2′-O-glucuronide (μmols ± SEM) | 0.63 ± 0.03 | 1.50 ± 0.03 | −0.06 ± 0.03 |
Treatment | Changes among treatments | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | WFA (n = 40) | AI (n = 40) | RFA (n = 39) | AI vs. WFA | RFA vs. WFA | RFA vs. AI | ||||||
Post-int | Change | Post-int | Change | Post-int | Change | Mean (95%CI) | P | Mean (95%CI) | P | Mean (95%CI) | P | |
Post-int, post-treatment values. Change, change from the baseline. WFA, white-fleshed apple; AI, aronia infusion; RFA, red-fleshed apple; Apo, apolipoproteins; LDL, low density lipoproteins; HDL, high density lipoproteins; TG, triglycerides; TRL, triglyceride rich lipoproteins; TRLC, TRL cholesterol; TRLTG, TRL triglycerides; LDL-P/HDL-P, LDL particles/HDL particles ratio; s-HDL/l-HDL, small HDL/large HDL ratio; HDL-C/HDL-P, HDL cholesterol/HDL particles ratio; TG/HDL, triglycerides/HDL cholesterol ratio; Log, logarithm. Data expressed as mean ± standard deviation or mean (95% confidence interval, CI). * (n = 77). Non-parametric data expressed as median (25th–75th percentile), with Wilcoxon and Mann–Whitney tests for intra- (†P = 0.015) and inter-treatment differences, respectively. Log, logarithm. ANCOVA model adjusted for sex, age, initial body mass index, and baseline values. A p-value < 0.05 was considered statistically significant. | ||||||||||||
LDL measures | ||||||||||||
LDL cholesterol, mg dL−1 | 128 ± 23 | −1.86 (−6.0; 2.3) | 117 ± 21 | −8.50 (−12; −4.6) | 119 ± 19 | −4.23 (−8.4; −0.03) | −6.64 (−12; −0.9) | 0.025 | −2.37 (−8.5; 3.7) | 0.441 | 4.27 (−1.4; 10) | 0.142 |
ApoB, mg dL−1 | 108 ± 20 | −0.043 (−3.5; 3.4) | 99 ± 19 | −6.25 (−9.5; −3.0) | 102 ± 19 | −1.45 (−4.9; 2.0) | −6.20 (−11; −1.4) | 0.012 | −1.41 (−6.5; 3.7) | 0.583 | 4.80 (0.06; 9.5) | 0.047 |
NMR LDL particle concentration (nmol L−1) | ||||||||||||
Total | 1469 ± 608 | −9.15 (−68; 50) | 1141 ± 641 | −125 (−181; −69) | 1234 ± 646 | −54.8 (−114; 4.9) | −116 (−199; −33) | 0.006 | −45.6 (−132; 41) | 0.300 | 70.4 (−11; 152) | 0.089 |
Large | 571 ± 226 | −15.8 (−52; 21) | 444 ± 220 | −141 (−176; −106) | 494 ± 178 | −62 (−99; −24) | −125 (−177; −74) | <0.001 | −45.7 (−99; 7.5) | 0.092 | 79.5 (28; 131) | 0.003 |
Medium (log) | 2.41 ± 1.27 | −0.070 (−0.2; 0.4) | 2.40 ± 0.95 | 0.187 (−0.1; 0.5) | 2.68 ± 0.25 | 0.496 (0.2–0.8) | 0.117 (−0.29; 0.53) | 0.573 | 0.426 (−0.01–0.9) | 0.053 | 0.309 (−0.10; 0.7) | 0.138 |
Small | 712 ± 426 | −17.3 (−95; 60) | 734 ± 309 | −24.9 (−100; 50) | 658 ± 430 | −166 (−246; −85) | −7.55 (−116; 101) | 0.891 | −148 (−262; −34) | 0.011 | −141 (−250; −31) | 0.012 |
Average NMR LDL particle size (nm) | 21.3 ± 0.44 | −0.027 (−0.1; 0.03) | 21.2 ± 0.35 | −0.075 (−0.13; −0.02) | 21.3 ± 0.42 | 0.044 (−0.01; 0.10) | −0.048 (−0.13; 0.03) | 0.233 | 0.071 (−0.12; 0.15) | 0.092 | 0.119 (0.04; 0.20) | 0.004 |
LDL-P/HDL-P ratio | 80.5 ± 17 | 1.99 (−1.2; 5.2) | 74.4 ± 16 | −1.73 (−4.7; 1.3) | 78.0 ± 15 | 4.21 (0.96; 7.5) | −3.71 (−8.1; 0.73) | 0.100 | 2.22 (−2.5; 6.9) | 0.352 | 5.94 (1.5; 10) | 0.009 |
HDL measures | ||||||||||||
HDL cholesterol (mg dL−1) | 59 ± 12 | −2.59 (−4.6; −0.5) | 55 ± 11 | −3.76 (−5.7; −1.8) | 53.5 ± 8.8 | −6.00 (−8.0; −3.9) | −1.17 (−4.0; 1.7) | 0.416 | −3.38 (−6.3; −0.4) | 0.026 | −2.20 (−5.1; 0.6) | 0.129 |
ApoA1, mg dL−1 | 145 ± 18 | −5.43 (−9.7; −1.1) | 140 ± 19 | −8.29 (−12; −4.1) | 137 ± 17 | −12.3 (−17; −7.9) | −2.85 (−8.9; 3.2) | 0.349 | −6.88 (−13; −0.6) | 0.032 | −4.03 (−10; 2.0) | 0.188 |
NMR HDL particle concentration (μmol L−1) | ||||||||||||
Total | 22 ± 2.2 | −0.689 (−1.3; −0.07) | 22 ± 2.4 | −1.20 (−1.80; −0.61) | 22 ± 2.8 | −1.89 (−2.5; −1.3) | −0.515 (−1.4; 0.34) | 0.236 | −1.20 (−2.1; 0.31) | 0.009 | −0.685 (−1.5; 0.18) | 0.119 |
Large | 2.83 ± 1.7 | −0.243 (−0.43; −0.06) | 2.71 ± 1.3 | −0.112 (−0.29; 0.07) | 2.00 ± 0.9 | −0.731 (−0.9; −0.54) | 0.131 (−0.13; 0.39) | 0.317 | −0.488 (−0.8; −0.2) | <0.001 | −0.619 (−0.9; −0.36) | <0.001 |
Medium | 5.26 ± 2.2 | 0.017 (−0.44; 0.48) | 4.72 ± 1.7 | −0.692 (−1.1; −0.25) | 5.57 ± 1.7 | 0.140 (−0.33; 0.61) | −0.709 (−1.3; −0.06) | 0.031 | 0.123 (−0.55; 0.8) | 0.718 | 0.831 (0.19; 1.5) | 0.012 |
Small | 14.4 ± 3.0 | −0.477 (−1.1; 0.15) | 14.4 ± 2.8 | −0.374 (−0.98; 0.23) | 14.0 ± 2.9 | −1.30 (−1.9; −0.67) | 0.103 (−0.77; 0.98) | 0.817 | −0.827 (−1.7; 0.08) | 0.074 | −0.930 (−1.8; −0.05) | 0.039 |
Average NMR HDL particle size (nm) | 9.1 ± 0.36 | −0.023 (−0.08; 0.03) | 9.0 ± 0.36 | −0.030 (−0.08; 0.02) | 8.9 ± 0.27 | −0.092 (−0.1; −0.04) | −0.007 (−0.08; 0.07) | 0.856 | −0.069 (−0.1; 0.01) | 0.083 | −0.062 (−0.14; 0.01) | 0.104 |
s-HDL/l-LDL | 7.94 ± 6.6 | 0.007 (−0.30; 032) | 6.65 ± 3.4 | 0.189 (−0.11; 0.49) | 8.39 ± 3.8 | −0.021 (−0.34; 0.29) | −0.505 (−1.3; 0.3) | 0.240 | −0.028 (−0.48; 0.4) | 0.901 | −0.210 (−0.4; 0.22) | 0.337 |
HDL-C/HDL-P | 2.60 ± 0.43 | −0.046 (−0.11; 0.01) | 2.52 ± 0.37 | −0.044 (−0.10; 0.01) | 2.49 ± 0.33 | −0.038 (−0.10; 0.02) | 0.001 (−0.1; 0.1) | 0.976 | 0.007 (−0.1; 0.1) | 0.868 | 0.006 (−0.1; 0.1) | 0.886 |
TRL measures | ||||||||||||
TG (log), mg dL−1 | 2.04 ± 0.18 | 0.021 (−0.01; 0.05) | 2.02 ± 0.14 | −0.009 (−0.03; 0.02) | 2.01 ± 0.16 | −0.005 (−0.02; 0.03) | −0.031 (−0.1; 0.01) | 0.078 | −0.026 (−0.1; 0.01) | 0.152 | 0.004 (−0.03; 0.04) | 0.802 |
TRLC, mg dL−1 | 29 ± 15 | 1.18 (−0.9; 3.2) | 29 ± 10 | −0.083 (−2.0; 1.9) | 28 ± 11 | −0.057 (−2.1; 2.0) | −1.26 (−4.1; 1.6) | 0.383 | −1.24 (−4.2; 1.8) | 0.417 | 0.026 (−2.8; 2.9) | 0.985 |
TRLTG (log), mg dL−1 | 1.79 ± 0.29 | 0.053 (0.01; 0.09) | 1.80 ± 0.22 | 0.016 (−0.02; 0.06) | 1.78 ± 0.24 | 0.024 (−0.02; 0.1) | −0.037 (−0.1; 0.2) | 0.205 | −0.030 (−0.1; 0.03) | 0.338 | 0.008 (−0.05; 0.07) | 0.795 |
NMR TRL particle concentration (nmol L−1) | ||||||||||||
Total | 164 ± 69 | 0.826 (−11; 13) | 163 ± 49 | −3.15 (−15; 8.3) | 167 ± 56 | 1.42 (−11; 13) | −3.97 (−20; 13) | 0.636 | 0.595 (−17; 18) | 0.946 | 4.57 (−12; 21) | 0.586 |
Very small | 70 ± 56 | −3.41 (−15; 8.8) | 65 ± 46 | −6.64 (−18; 4.9) | 71 ± 50 | −1.38 (−13; 11) | −3.50 (−20; 13) | 0.679 | 1.76 (−16; 19) | 0.841 | 5.26 (−11; 22) | 0.534 |
Small | 77 ± 34 | 1.36 (−8.2; 11) | 83 ± 35 | 3.28 (−6.0; 12) | 80 ± 34 | −0.749 (−10; 9) | 1.92 (−11; 15) | 0.777 | −2.11 (−16; 12) | 0.766 | −4.03 (−12; 9.4) | 0.554 |
Medium | 10.7 (5.5; 19) | 0.014 (−0.29; 0.22) | 10.5 (3.4; 18) | 0.089 (−0.11; 0.29) | 11.8 (7.4; 18) | 0.182 (−0.04; 0.4) | −0.075 (−0.21; 0.36) | 0.606 | 0.167 (−0.14; 0.47) | 0.283 | 0.092 (−0.20; 0.39) | 0.536 |
Large* | 0.30 (0.0; 3.1) | 0.20† (0.0; 0.6) | 0.10 (0.0; 0.70) | 0.001 (−0.7; 0.1) | 0.35 (−0.02; 4.0) | 0.25 (0.0; 0.6) | −0.190 (−0.7; 0.5) | 0.064 | 0.050 (0.0; 0.1) | 0.847 | 0.240 (0.0; 0.5) | 0.086 |
Very large* | 0.10 (0.0; 0.1) | 0.10 (0.0; 0.1) | 0.10 (0.0; 0.2) | 0.00 (0.0; 0.1) | 0.10 (0.0; 0.1) | 0.00 (0.0; 0.0) | −0.100 (0.0; 0.1) | 0.909 | −0.100 (0.0; 0.1) | 0.954 | 0.00 (0.0; 0.1) | 0.971 |
Average NMR TRL particle size (nm) | 40.1 ± 6.9 | 1.09 (−0.07; 2.2) | 38.8 ± 5.6 | −0.305 (−1.4; 0.80) | 39.6 ± 5.8 | 0.963 (−0.21; 2.1) | −1.39 (−3.0; 0.22) | 0.089 | −0.125 (−1.8; 1.6) | 0.884 | 1.27 (−0.34; 2.9) | 0.122 |
TG/HDL | 2.27 ± 1.48 | 0.295 (−0.13; 0.45) | 2.09 ± 1.07 | 0.026 (−0.13; 0.18) | 2.18 ± 1.12 | 0.157 (−0.01; 0.32) | −0.269 (−0.49; −0.04) | 0.019 | −0.138 (−0.37; 0.10) | 0.253 | 0.131 (−0.10; 0.36) | 0.254 |
Fig. 1 shows the changes in HDL subspecies after treatments. The significant decrease in HP1, HP5, and HP7 after RFA treatment reached significance versus changes after WFA treatment (P = 0.021, P = 0.002 and P = 0.001 for HP1, HP5, and HP7, respectively) and AI (P = 0.002, P < 0.001, and P = 0.038 for HP1, HP5, and HP7, respectively). HP3 significantly decreased after AI treatment and H6P after all treatments without intertreatment differences. Neither intra- nor inter-treatment changes were observed for H2P or H4P.
NMR biomarker/compliance biomarker | Compliance biomarker | β | 95%CI | SE | Beta | p |
---|---|---|---|---|---|---|
LDLc | ||||||
Peonidin-3-O-galactoside (plasma), μM | AI and RFA | −5.62 | −9.98 to −1.92 | 2.191 | −0.249 | 0.011 |
Total LDL particle | ||||||
Peonidin-3-O-galactoside (plasma), μM | AI and RFA | −86.4 | −152.815 to 20.1 | 33.4 | −0.250 | 0.011 |
Peonidin-3-O-galactoside (urine), μM | −6.13 | −12.3 to 0.090 | 3.13 | −0.198 | 0.053 | |
Large LDL particle | ||||||
Phloretin-O-xylosyl glucoside (urine), mM | RFA | −13.1 | −23.9 to −2.33 | 5.43 | −0.243 | 0.018 |
Cyanidin-3-O-galactoside (urine), μM | AI | −1.22 | −2.50 to 0.057 | 0.64 | −0.193 | 0.061 |
LDL particle/HDL particle | ||||||
Peonidin-3-O-galactoside (plasma), μM | AI and RFA | −3.23 | −6.49 to 18.3 | 1.64 | −0.194 | 0.051 |
LDL size | ||||||
Phloretin-O-xylosyl glucoside (urine), mM | RFA | −0.021 | −0.039 to 0.002 | 0.009 | −0.225 | 0.028 |
Cyanidin-3-O-galactoside (urine), μM | AI | −0.003 | −0.005 to −0.001 | 0.001 | −0.314 | 0.002 |
In multiple regression analysis, global changes in GlycA were directly associated with medium TRL-P levels in men (R = 0.364, P = 0.016), but not in women, after adjustment for age and BMI values (ESI Fig. 2†). Although no intra-treatment changes were observed in ketone bodies, changes in acetone were significantly higher after AI treatment in comparison with WFA treatment (P = 0.034), whereas the values of β-OH-butyrate and total ketone bodies were significantly lower after RFA treatment versus AI treatment (P = 0.017 and P = 0.033, respectively) (Table 5). No inter-treatment differences were observed for total branched-chain amino acids or the individual ones examined, although significant decreases were obtained in valine values after RFA and AI treatments and in isoleucine after RFA treatment, with a significant increase in leucine after AI treatment (Table 6).
Treatment | Changes among treatments | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | WFA (n = 40) | AI (n = 40) | RFA (n = 39) | AI vs. WFA | RFA vs. WFA | RFA vs. AI | ||||||
Post-int | Change | Post-int | Change | Post-int | Change | Mean (95%CI) | P | Mean (95%CI) | P | Mean (95%CI) | P | |
Post-int, post-treatment values. Change, change from the baseline. β-OH-butyrate, beta-OH-butyrate; KedBod, sum of all ketone bodies. Data expressed as mean ± standard deviation or mean (95% confidence interval, CI). Log, logarithm. ANCOVA model adjusted for sex, age, body mass index, and baseline values. | ||||||||||||
β-OH-butyrate (log), μmol L−1 | 1.87 ± 0.20 | −0.013 (−0.07; 0.05) | 1.95 ± 0.21 | 0.056 (−0.001; 0.11) | 1.84 ± 0.20 | −0.046 (−0.11; 0.01) | 0.069 (−0.01; 0.15) | 0.103 | −0.033 (−0.12; 0.05) | 0.446 | −0.102 (−0.18; −0.02) | 0.017 |
Acetoacetate (log), μmol L−1 | 1.40 ± 0.37 | −0.036 (−0.12; 0.05) | 1.50 ± 0.26 | 0.045 (−0.04; 0.13) | 1.44 ± 0.22 | −0.043 (−0.13; 0.04) | 0.081 (−0.04; 0.20) | 0.187 | −0.007 (−0.13; 0.12) | 0.917 | −0.088 (−0.21; 0.03) | 0.152 |
Acetone (log), μmol L−1 | 1.32 ± 0.21 | −0.076 (−0.18; 0.03) | 1.43 ± 0.28 | 0.084 (−0.02; 0.19) | 1.34 ± 0.26 | −0.042 (−0.15; 0.07) | 0.161 (0.01; 0.31) | 0.034 | 0.034 (−0.12; 0.19) | 0.634 | −0.127 (−0.28; 0.02) | 0.095 |
KetBod (log), μmol L−1 | 2.11 ± 1.80 | 0.008 (−0.04; 0.06) | 2.16 ± 0.19 | 0.045 (−0.05; 0.10) | 2.07 ± 0.15 | −0.035 (−0.09; 0.02) | 0.037 (−0.03; 0.11) | 0.311 | −0.043 (−0.12; 0.03) | 0.270 | −0.080 (−0.15; −0.01) | 0.033 |
Treatment | Changes among treatments | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Variable | WFA (n = 40) | AI (n = 40) | RFA (n = 39) | AI vs. WFA | RFA vs. WFA | RFA vs. AI | ||||||
Post-int | Change | Post-int | Change | Post-int | Change | Mean (95%CI) | P | Mean (95%CI) | P | Mean (95%CI) | P | |
Post-int, post-treatment values. Change, change from the baseline. vs., versus. Val, valine; Leu, leucine; Ileu, isoleucine; BCAA, sum of branched amino acids (Val + Leu + Ileu). Data expressed as mean ± standard deviation or mean (95% confidence interval, CI). Log, logarithm. ANCOVA model adjusted for sex, age, body mass index, and baseline values. | ||||||||||||
Val, μmol L−1 | 232 ± 41 | −7.43 (−16; 1.1) | 236 ± 43 | −10.3 (−18; −2.1) | 239 ± 34 | −10.9 (−20; −2.1) | −2.89 (−15; 9.0) | 0.631 | −3.44 (−16; 9.1) | 0.586 | −0.551 (−12; 11) | 0.928 |
Leu, μmol L−1 | 148 ± 30 | 7.70 (−0.91; 14) | 154 ± 33 | 7.69 (1.1; 14) | 148 ± 26 | 0.818 (−6.1; 7.7) | −0.013 (−9.5; 9.5) | 0.998 | −6.88 (−17; 3.0) | 0.170 | −6.87 (−16; 2.6) | 0.155 |
Ileu, μmol L−1 | 57 ± 13 | −0.855 (−4.7; 3.0) | 61 ± 21 | −2.21 (−5.9; 1.5) | 58 ± 14 | −3.89 (−7.8; −0.01) | −1.36 (−6.7; 4.0) | 0.617 | −3.04 (−8.6; 2.5) | 0.282 | −1.68 (−7.0; 3.7) | 0.535 |
BCAA, μmol L−1 | 436 ± 79 | −0.522 (−18; 16) | 452 ± 96 | −3.65 (−20; 13) | 445 ± 68 | −13.2 (−31; 4.2) | −3.13 (−27; 21) | 0.795 | −12.7 (−37; 12) | 0.316 | −9.52 (−33; 14) | 0.432 |
In agreement with other reports, in our study, the ACN-rich products decreased LDL-c,5,11 as well as other LDL related parameters, which are considered to be better markers for CVD such as LDL-P, particularly when hypertriglyceridemia is involved.18 LDL-c, Apo B, total LDL-P, and the LDL-P/HDL-P ratio have all been shown to be directly associated with the risk of coronary heart disease (CHD).11,19 Concerning LDL-P heterogeneity, although controversial data exist, an abundance of small LDL-P has been associated with a 2–3-fold increase in CHD risk in a primary prevention population and is linked to atherosclerosis in many conditions, such as hyperlipidemia, metabolic syndrome, diabetes, and other disorders.18 The need to monitor the small LDL-P concentration is reflected by many guidelines, such as the 2016 Chinese guidelines and 2019 ESC/EAS guidelines.20 In contrast, in type 2 diabetes mellitus individuals, medium LDL-P has been inversely associated with all-cause mortality, but not with CVD mortality,21 and higher concentrations of large LDL-P have been associated with a lower risk of developing diabetes.22 Although LDL size has previously been inversely related to CHD, this association does not remain after adjustment for LDL-P.23 The atherogenicity of small LDL-P seems to be associated with an increased cellular uptake in the arterial tissue due to a higher affinity for the LDL binding site, as has been shown in experimental studies.24 Thus, overall changes in NMR LDL biomarkers after RFA and AI treatments, as ACN-rich products, improved CVD risk versus changes observed after WFA consumption.
Epidemiologic studies have consistently shown that low serum HDLc is a risk factor for atherosclerotic cardiovascular disease. This concept, however, has failed to be translated into clinical benefits in terms of drug development. Recent studies also suggest that very high HDLc levels can be associated with adverse cardiovascular outcomes and all-cause mortality risk in coronary artery disease individuals.25 HDL comprises a family of lipoproteins whose individual particles differ widely in density, size, charge, protein, and lipid composition, and it is still unclear which HDL specific subclasses or subspecies are more cardioprotective.26,27 In most population studies, small HDL particles are considered to be more strongly associated with an increased CHD risk than the large HDL ones.28,29 Controversial data exist, however, concerning the associations between large and medium HDL-P subclasses and cardiovascular risk.21,30 Therefore, we observed opposite potential effects concerning HDL subclasses in our study. On one hand, the highest decrease in small HDL-P after RFA treatment appears as a protective one; on the other hand, the large and medium HDL-P decreases after the consumption of ACN-rich products versus WFA treatment could exert an opposite effect, although this remains to be elucidated. Decreases in large and medium HDL particles have been observed in the postprandial state after ingestion of black rice fortified with ACNs.31
The controversy surrounding the role of HDL subclasses in CVD has evolved to focus on HDL subspecies differentiation27 for clarifying the role of the different HDL lipoproteins. From our data, the decrease in small HDL-P after RFA treatment is mainly dependent on that of H1P subspecies; the decrease of medium HDL after AI treatment is linked to the H3P ones; and that in large HDL-P after RFA treatment is linked to all H5P, H6P and H7P subspecies; however, significance versus WFA and AI treatments was dependent on the decrease of H5P and H7P subspecies. H7P has been shown to be directly related to interferon gamma, PCSK9 (an HDL proteome component linked to accelerated atherosclerosis),32 and a higher DNA methylation phenotypic age.33 Thus, in this sense, the decrease in H7P after RFA would have a protective character versus CVD risk.
An increase in several proatherogenic subclasses of very low-density lipoproteins (VLDL) after aronia sustained consumption has been recently reported.34 In our study, however, we observed a trend toward a better TRL profile of large particles after AI treatment. All TRL particles have been shown to be directly associated with GlycA, an inflammatory marker,35,36 and TRLs together with GlycA mainly account for myocardial dysfunction in type I diabetes subjects.37 In this study, a decrease in GLycA after the consumption of both ACN-rich products was observed, and changes in GlycA were directly related to the levels of medium TRL particles in men. GlycA is a composite biomarker of systemic inflammation, which reflects the degree of glycosylation of various acute phase proteins. The observed decrease of GlycA after consuming ACN-rich products agrees with our previous data concerning the decrease in inflammatory markers (IL6, CRP and the complement system) observed in the frame of the AppleCOR study.38 Beyond capturing cardiovascular risk, increases in GlycA have been associated with mortality, chronic inflammatory-related severe hospitalization, cancer incidence, and incidence of type 2 diabetes, revealing GlycA as a global marker for cardiometabolic risk.39 In our study, the TG/HDL ratio was lower after AI treatment versus WFA treatment. This ratio has been directly related to hypertension, particularly in women with a low BMI and individuals with type 2 diabetes, and with cardiovascular events and death.39
Concerning other NMR markers, citrate, the first product following acetyl coenzyme A generation from different energy sources, has been directly associated with cardiovascular and all-cause mortality,40 atrial failure,41 and mortality in acute heart failure patients.42 Recently, metabolomic data from the Framingham Study showed an inverse relationship between blood citrate levels and the “ideal cardiovascular health” index.43 In our study, both apples, WFA and RFA, decreased plasma citrate concentrations versus AI treatment. This reinforces the importance of apple pulp consumption for obtaining benefits concerning reduction in citrate levels. Alanine levels decreased after AI and RFA treatments. In previous studies with CVD patients, it was difficult to establish whether the increased levels of alanine observed were predictors or a consequence of the disease.44,45 In a recent cohort study, however, alanine levels were higher in diabetic patients and directly associated with the development of atherosclerotic disease after a 10-year follow-up.46 Increased levels of circulating BCAAs are associated with type 2 diabetes.47 Anthocyanins have been shown to decrease BCAAs in Zucker diabetic fatty rats.48 In our study, we observed intra-treatment decreases in valine and isoleucine after the consumption of anthocyanin-rich products, as well as an increase in leucine after AI treatment. The lack of inter-treatment differences, however, impairs any conclusive results.
Comparison between the two ACN-rich treatments showed that for LDL measures, AI was more effective than RFA in decreasing total and LDL cholesterol, ApoB, total LDL-P and the LDL-P/HDL-P ratio, whereas RFA was more effective in decreasing s-LDL-P and in causing a smaller decrease in large LDL-P. Concerning HDL measures, AI promoted less decrease of HDL-c, ApoA1, and total, large, and medium HDL-P, whereas a higher decrease in the small HDL-P subclass and the H7P subspecies was observed after RFA treatment. AI promoted a better large TRL-P profile, as well as a higher decrease in the TG/HDL-C ratio, than RFA. RFA decreased citrate versus AI, and AI was more effective than RFA in decreasing alanine. RFA decreased beta-OH-butyrate and total ketone bodies compared to AI, but the role of ketone bodies in health and disease remains to be elucidated.49 Thus, both types of ACN-rich products were effective on different lipoprotein particle or other CVD biomarkers, and although AI showed a larger spectrum of benefits than RFA, the latter has benefits on key parameters such as small LDL-P and HDL-P.
Footnotes |
† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4fo02949f |
‡ Current address: Center for Nutrition Research, University of Navarra, Pamplona, Spain. |
§ Senior authors. |
This journal is © The Royal Society of Chemistry 2025 |