| Literature DB >> 30621298 |
Seunghee Kang1, Yeni Lim2, You Jin Kim3, Eun Sung Jung4, Dong Ho Suh5, Choong Hwan Lee6, Eunmi Park7, Jina Hong8, Rodney A Velliquette9, Oran Kwon10, Ji Yeon Kim11.
Abstract
Phytonutrients and vitamin and mineral supplementation have been reported to provide increased antioxidant capacity in humans; however, there is still controversy. In the current clinical trial, we examined the antioxidant and DNA protection capacity of a plant-based, multi-vitamin/mineral, and phytonutrient (PMP) supplementation in healthy adults who were habitually low in the consumption of fruits and vegetables. This study was an eight-week, double-blind, randomized, parallel-arm, and placebo-controlled trial. PMP supplementation for eight weeks reduced reactive oxygen species (ROS) and prevented DNA damage without altering endogenous antioxidant system. Plasma vitamins and phytonutrients were significantly correlated with ROS scavenging and DNA damage. In addition, gene expression analysis in PBMC showed subtle changes in superoxide metabolic processes. In this study, we showed that supplementation with a PMP significantly improved ROS scavenging activity and prevented DNA damage. However, additional research is still needed to further identify mechanisms of actions and the role of circulating phytonutrient metabolites.Entities:
Keywords: DNA damage; ROS scavenging; antioxidant capacity; human clinical study; phytonutrients
Mesh:
Substances:
Year: 2019 PMID: 30621298 PMCID: PMC6356358 DOI: 10.3390/nu11010101
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1CONSORT flow diagram summarizing the subject’s disposition for the study.
Baseline characteristics of subjects 1.
| Variable | Placebo | PMP | |
|---|---|---|---|
| ( | ( | ||
| Age (year) | 41.6 ± 1.7 | 38.2 ± 1.7 | 0.169 |
| Gender (male/female, | 13/29 | 13/29 | 1.000 |
| Recommended food score | 19.5 ± 1.3 | 19.1 ± 1.5 | 0.830 |
| Body weight (kg) | 67.4 ± 2.1 | 65.1 ± 2.2 | 0.462 |
| Body mass index (kg/m2) | 24.8 ± 0.6 | 23.7 ± 0.6 | 0.202 |
| Percent of body fat (%) | 31.7 ± 0.9 | 30.1 ± 1.0 | 0.258 |
| Smoker, | 3 (7.1) | 4 (9.5) | 0.693 |
| Alcohol drinker, | 22 (52.4) | 24 (57.1) | 0.661 |
| Blood pressure (mmHg) | |||
| Systolic blood pressure | 119.1 ± 2.1 | 116.7 ± 2.0 | 0.414 |
| Diastolic blood pressure | 79.5 ± 1.6 | 79.0 ± 1.5 | 0.786 |
| Blood lipid profiles (mg/dL) | |||
| Total triglyceride | 142.2 ± 18.1 | 121.4 ± 9.2 | 0.311 |
| Total cholesterol | 189.5 ± 5.7 | 187.0 ± 4.3 | 0.729 |
| LDL cholesterol | 119.4 ± 5.7 | 120.6 ± 4.2 | 0.856 |
| HDL cholesterol | 53.2 ± 2.2 | 54.1 ± 1.8 | 0.752 |
1 Data are expressed as mean ± SE for continuous variables or as frequency and percentage for categorical variables. LDL, low density lipoprotein; HDL, high density lipoprotein. 2 Differences between the placebo and PMP groups were evaluated using the Student’s t-test for continuous variables and chi-square test for categorical variables.
Figure 2Effect of eight-week supplementation on DNA damage and repair: (A) Comet assay on PBMC; and (B) Representative Western blot of plasma phosphorylated checkpoint kinase 1 (pCHK1-Ser345). Change in DNA damage and repair mechanism are presented as a box and scatter plots. The ends of the box are the upper and lower quartiles. The medians are marked by a vertical line inside the boxes. The whiskers are the two lines outside the box that extend to the highest and lowest value. Dots are individual values of each subjects. For Western blot, representative samples (n = 8 for placebo and n = 6 for PMP) were analyzed. CT (a sample from the PMPgroup) indicates a loading control for analyzing quantitate data, 0 indicates before supplementation and 8 indicates after supplementation. Statistical significance of comet assay was determined by linear mixed-effects model. In the case of Western blot, linear mixed-effect model was used to compare the difference within each group (* p < 0.05). LS means (◆).
Figure 3Box and scatter plot of the change in plasma ROS AUC after eight-week supplementation. ROS AUC was calculated by the trapezoidal rule. The ends of the boxes are the upper and lower quartiles. The median is marked by a vertical line inside the box. The whiskers are the two lines outside the box that extend to the highest and lowest value. Dots are individual values of each subjects. Statistical significance was determined by linear mixed-effects model (* p < 0.05). Reactive oxygen species (ROS); area under the curve (AUC); LS means (◆).
The effect of placebo and PMP supplementation on lipid oxidation and endogenous antioxidant defense 1.
| Variable | Placebo ( | PMP ( | Estimate 2 | |||
|---|---|---|---|---|---|---|
| Week 0 | Week 8 | Week 0 | Week 8 | |||
| Erythrocyte | ||||||
| SOD activity (U/mL) | 200.25 ± 4.32 | 192.76 ± 3.63 | 205.87 ± 4.32 | 206.02 ± 3.63 | 7.637 | 0.250 |
| GPx activity (µmol/min/mL) | 1.12 ± 0.04 | 1.10 ± 0.04 | 1.11 ± 0.04 | 1.11 ± 0.04 | 0.017 | 0.559 |
| Plasma | ||||||
| MDA (µmol/L) | 2.97 ± 0.14 | 2.99 ± 0.14 | 2.96 ± 0.14 | 3.02 ± 0.14 | 0.040 | 0.774 |
| Oxidized LDL (U/L) | 41.18 ± 1.84 | 39.89 ± 1.73 | 43.25 ± 1.84 | 41.78 ± 1.73 | −0.176 | 0.914 |
1 All values are LS mean ± SE. superoxide dismutase (SOD); glutathione peroxidase (GPx); malondialdehyde (MDA). 2 Estimates were determined for each variable by calculating β, the estimated slope, from linear mixed-effects model. p-values were derived from a linear mixed-effects model. p-value < 0.05 was considered significant.
Figure 4Network of up-regulated genes changed by eight-week PMP supplementation. Genes were selected based on differential expression pattern compared to placebo. Each node represents a physical entity. Each edge represents a gene regulatory interaction. Blue circles are genes that are targeted and analyzed by PCR analysis. Red circles are genes related process given by EnrichNet database (http://enrichnet.org), but not analyzed. Green circles denote overlapped gene between blue and red genes.
Figure 5(A) The UPLC-Q-TOF-MS chromatographic fingerprint of the PMP study product; and (B) change in plasma after eight-week supplementation. The y-axis of box plots indicates the change in the relative peak area of each vitamin and phytonutrient. Statistical significances were determined by linear mixed-effects model (* p < 0.05). LSmeans (◆).
Figure 6Heat map illustrating Pearson correlation coefficients between plasma and erythrocyte biomarkers and plasma vitamin and phytonutrients. Reactive oxygen species (ROS); area under the curve (AUC); superoxide dismutase (SOD); glutathione peroxidase (GPx); malondialdehyde (MDA); oxidized low-density lipoprotein (Ox-LDL). * p < 0.05.
Correlation between biomarkers and plasma vitamins and phytonutrients 1.
| Pantothenic Acid | Ascorbic Acid | Folic Acid | Rosmarinic Acid | Hesperidin | Tuberonic Acid Glucoside | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| r |
| r |
| r |
| r |
| r |
| r |
| |
| ROS AUC | −0.227 | 0.0549 | −0.194 | 0.1022 | −0.233 | 0.0485 | −0.029 | 0.8070 | −0.365 | 0.0016 | −0.113 | 0.3431 |
| Tail intensity | −0.148 | 0.1969 | −0.471 | <0.0001 | 0.006 | 0.9618 | −0.338 | 0.0025 | −0.127 | 0.2680 | −0.038 | 0.7397 |
| Tail length | −0.187 | 0.0921 | −0.390 | 0.0003 | −0.032 | 0.7777 | −0.221 | 0.0464 | −0.217 | 0.0497 | −0.178 | 0.1100 |
| Tail moment | −0.238 | 0.0367 | −0.608 | <0.0001 | −0.087 | 0.4529 | −0.158 | 0.1713 | −0.211 | 0.0659 | −0.186 | 0.1061 |
| SOD activity | 0.121 | 0.2730 | −0.222 | 0.0420 | −0.019 | 0.8667 | −0.268 | 0.0139 | 0.073 | 0.5088 | 0.026 | 0.8170 |
| GPx activity | 0.008 | 0.9417 | −0.138 | 0.2109 | 0.074 | 0.5013 | 0.058 | 0.6020 | 0.073 | 0.5081 | −0.021 | 0.8484 |
| Plasma MDA | 0.075 | 0.4964 | 0.165 | 0.1329 | −0.073 | 0.5102 | 0.138 | 0.2118 | −0.125 | 0.2578 | −0.001 | 0.9919 |
| Ox-LDL | −0.078 | 0.4786 | 0.036 | 0.7422 | −0.039 | 0.7261 | 0.069 | 0.5358 | 0.111 | 0.3150 | 0.046 | 0.6794 |
1 Reactive oxygen species (ROS); area under the curve (AUC); superoxide dismutase (SOD); glutathione peroxidase (GPx); malondialdehyde (MDA); oxidized low-density lipoprotein (Ox-LDL). 2 p-values were calculated using Pearson correlation coefficient analysis.