Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress & inflammation: a randomized controlled trial

Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress & inflammation: a randomized controlled trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress & inflammation: a randomized controlled trial Digar Singh, Dongwoo Ham, Seong-Ah Kim, Damini Kothari, Yu Jin Park, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4142606/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Dietary biomarkers in urine are elusive in the context of diet induced oxidative stress & inflammation. Previously, we reported the effects of short-term (4-week) dietary interventions for Balanced Korean Diet (BKD) and Western diets including 2010 Dietary Guidelines for Americans (2010 DGA) and Typical American Diets (TAD) on various metabolic indices among the Korean adults with obesity. In particular, this research investigates the impact of these interventions on biomarkers related to oxidative stress and inflammation in both serum and concurrent urine metabolomes. Each dietary regimen was in silico and experimentally examined for their antioxidant levels. We assessed post-intervention variations in oxidative stress and inflammation biomarkers in serum, as well as the urine metabolite profiles for the participants ( n = 48). Antioxidant contents and associated total antioxidant capacity (TAC) were significantly higher for the recommended diets (BKD and 2010 DGA) compared to TAD ( p < 0.05). Butanol extracts from recommended diets (BKD and 2010 DGA) showed significantly higher antioxidant activity compared to TAD in ABTS (p < 0.01), DPPH, and FRAP (p < 0.05) assays. Consistent results were observed in total phenolic and flavonoid contents, mirroring their respective antioxidant activities. Following the intervention period, oxidative stress & inflammation markers in serum varied marginally, however, the urine metabolite profiles were clearly demarcated for the BKD and Western dietary groups (PC1 = 5.41%). For BKD group, the pre- and post-intervention urine metabolite profiles were clearly segregated (PLS2 = 2.93%). Compared to TAD, urine extracts from the recommended dietary group showed higher abundance of benzoic acid & phenolic derivatives (VIP > 0.7, p < 0.05). Metabolites associated with oxidative stress were observed higher in the urine samples from western dietary groups compared to BKD. Urine metabolomics data delineated the post-intervention effects of three dietary interventions which corroborates the respective findings for their effects on metabolic indices. Biological sciences/Biochemistry Biological sciences/Biological techniques Health sciences/Biomarkers Balanced Korean diet Western diet oxidative stress serum biomarkers urine metabolomics LC-MS/MS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Studies have shown that both the long- & short-term dietary interventions influence the oxidative stress and systemic chronic inflammations (SCI) in humans. A higher imbalance in the ratio of free radicals to the antioxidant species either through nutritional or endogenous factors is considered as the oxidative stress, which influences the progression of inflammatory chronic diseases 1 . Healthy dietary preferences are key to manage chronic inflammatory diseases which roughly accounts for approximately 50% of all the annual deaths and disabilities worldwide 2 . Diet induced SCI is associated with various metabolic disorders including cardiovascular diseases (CVD), stroke, insulin resistance, obesity, and cancer, among others 3 . Different dietary regimens are studied worldwide toward achieving a sustainable health with particular emphasis on oxidative stress and associated SCI, and their impact on etiological factors. In addition to the endogenous factors, the diet induced oxidative stress play a pivotal role in maneuvering various pathophysiological conditions. In particular, the unbalanced consumption of macronutrients, especially the animal-derived fats, promote oxidative stress, and subsequent inflammation through promoting the release of pro-inflammatory cytokines 4,5 . Though the effects of different dietary regimens on anthropometric parameters are well studied, their correlations with the oxidative stress biomarkers in serum and urine metabolomes are largely unknown. The effects of dietary intakes and their metabolic implications for oxidative stress are mostly examined using the serum samples. However, the non-invasive and low-cost nature of urinary sample collection coupled with the unprecedented advancements in the mass spectrometry (MS) and spectroscopy (NMR) platforms makes it ideal for dietary intervention studies. In recent years, urine metabolomics has increasingly been used to monitor the effects of human exposure to drugs, toxins, pathogens, and related pathophysiological states 6 . Hence, a comprehensive data integration correlating the quantitative urinary metabolite profile with the blood indices of oxidative stress and the associated anthropometric parameters may help indicate the real-time clinical outcomes of dietary intakes. Moreover, the respective data may be subjected to translational assessment of diet induced SCI and predicting its likely clinical implications. Hence, the exploratory urinary metabolomics towards probing the effects of varying dietary regimens and the associated metabolic markers of SCI can help predict and mitigate the early onset of chronic diseases. The greater adherence to the balanced dietary recommendations lowers the risk of SCI pertaining to the higher antioxidant capacity of dietary components 7 . Though the health beneficiary functions of the balanced Korean diet (BKD) rich in dietary phytochemicals are largely acknowledged, its metabolomic implications are relatively unknown owing to the lack of randomized crossover longitudinal studies. A quintessential BKD is mainly composed of plant-derived components (whole grains, vegetables, fruits, and fermented beans) with relatively lesser proportions of animal-derived and processed foods. Previously, we have demonstrated that the BKD significantly improves the obesity-related metabolic risk factors and blood lipid profiles in participants from a randomized controlled trial 8 . This work explores the effects of short-term dietary interventions of the BKD and the Western diets in participants, and correlates the untargeted urine metabolite profiles with oxidative stress biomarkers in serum. Results 2.1. Characteristics of the three different dietary regimens (BKD, 2010 DGA, and TAD) 2.1.1. Micronutrients We estimated the micronutrient contents including the antioxidant vitamins and phenolic compounds for each study diet ( Fig. 1 & Supplementary Table S.1 ). Notwithstanding their equivalent calorific values (~2000 Kcal/day), BKD was characterized by the significantly higher relative abundance of total carbohydrates ( p < 0.01) with least relative abundance of fats ( p 2010 DGA; p < 0.01). However, the protein contents in all three dietary regimens were marginally varied (Supplementary Fig. S.1) . For the micronutrients,vitamins and phenolic compounds were markedly varied among the three different dietary interventions. Most notably, vitamin A variants were lower in the BKD compared to the 2010 DGA and TAD, although the differences were not observed statistically significant. However, the vitamin A subtypes including α-carotene, β-carotene, β-cryptoxanthin, and lutein/zeaxanthin were relatively higher in the BKD and the 2010 DGA compared to TAD. Vitamin C contents were significantly higher in the 2010 DGA ( p TAD) compared to the BKD ( p < 0.01), except for their γ-tocopherol contents. Meanwhile, the BKD was characterized by the higher relative abundance of flavonols and isoflavones ( p < 0.01), compared to the 2010 DGA and the TAD. On the other hand, the 2010 DGA was observed having higher relative levels of most phenolic compounds including flavones, flavanones, flavan-3-ols ( p < 0.05), anthocyanidins, and proanthocyanidins ( p < 0.05). Altogether, the dietary TAC was considerably higher in the 2010 DGA ( p < 0.05) and the BKD, compared to the TAD. 2.1.2. Antioxidants We examined the levels of antioxidants for the pooled sample menus representing the three different diets examined in this study. Notably, the butanol sample extracts from both the recommended diets (BKD and 2010 DGA) displayed relatively higher antioxidant activities compared to TAD in ABTS ( p <0.01), DPPH, and FRAP assays ( p <0.05) (Fig. 2.a- c) . Conversely, the ethyl acetate (EA) extracts showed relatively higher antioxidant levels for both the American diets (2010 DGA and TAD) compared to BKD in all three antioxidant assays (ABTS, p <0.05; DPPH, p <0.05; FRAP, p <0.01). The inherent differences in polarity and metabolite distribution between EA and butanol extracts suggest their divergent bioactivities. Given n-Butanol's higher polarity (0.552) in contrast to ethyl acetate (0.228), it's expected that butanol extracts would harbor a greater concentration of polar antioxidant compounds, notably polyphenols. These compounds are likely to constitute a substantial portion of the essential nutrients found in recommended diets. The observed disparity in the antioxidant levels of EA (ethyl acetate) and butanol extracts can be attributed to their different polarity which allows varying metabolite partitioning during the extraction procedure. However, this gives a more comprehensive outlook of the total antioxidant capacity of the dietary sample extracts. 2.1.3. Phenolic and flavonoids Total phenolic and flavonoids compositions for the pooled sample extracts of each study diet were further examined. We observed the significantly higher levels of TPC for the BKD compared to the 2010 DGA and the TAD from butanol extracts ( p <0.01). Similar trends were observed for the TFC from the butanol extracts of the three dietary regimens although their levels were marginally varied across the three dietary extracts ( Fig. 2.d & e ). 2.2. Characteristics of the study subjects 2.2.1. Baseline characteristics Table 1 shows the baseline characteristics of the 48 study subjects before the onset of the dietary intervention trials. There were 25 males and 23 females’ participants enrolled in this study. Considering their baseline oxidative stress markers in serum, higher d-ROMs and lower BAP levels were recorded for female participants compared to males. The inflammatory markers, CRP and TNF-α levels were observed higher for female participants compared to males, whereas those for IL-6 and MCP-1 were relatively lower in female than male subjects. Table 1. Baseline characteristics of the study subjects before the onset of the trials. Parameters Total (n=48) Male (n=25) Female (n=23) Age (years) 25–39 24 16 8 40–64 24 9 15 Monthly household income < 2 million KRW 9 6 3 2–6 million KRW 29 14 15 ≥ 6 million KRW 10 5 5 Education level High School 11 2 9 College+ 37 23 14 Alcohol consumption 1 No 12 3 9 Moderate 34 21 13 Heavy 2 1 1 Physical activity 2 No 39 21 18 Moderate 1 0 1 Vigorous 8 4 4 Oxidative stress indices (mean ± SD) d-ROMs (U. CARR. 3 ) 381.25 ± 72.38 345.04 ± 54.01 420.61 ± 70.00 BAP (μmol/L) 2,122.73 ± 267.59 2,218.56 ± 224.39 2,018.57 ± 276.15 Inflammatory indices (mean ± SD) CRP (mg/L) 2.06 ± 3.70 1.83 ± 3.88 2.31 ± 3.57 TNF-α (pg/mL) 2.18 ± 1.31 2.14 ± 1.24 2.23 ± 1.41 IL-6 (pg/mL) 1.85 ± 1.23 1.91 ± 1.40 1.78 ± 1.03 IL-1β (pg/mL) 0.06 ± 0.11 0.04 ± 0.04 0.08 ± 0.15 MCP-1 (pg/mL) 402.94 ± 130.65 418.06 ± 105.44 386.51 ± 154.26 † Abbreviations: KRW, Korean Won; SD, standard deviation; d-ROMs, diacron reactive oxygen metabolites; U. CARR., Carratelli Unit; BAP, biological antioxidant potential; CRP, C-reactive protein; TNF-α, tumor necrosis factor-α; IL-6, interleukin-6; IL-1β, interleukin-1β; MCP-1, monocyte chemoattractant protein-1. 1 Moderate alcohol consumption was defined as drinking < 2 times/week, or drinking ≥ 2 times/week but < 7 cups/time for males and < 5 cups/time for female. Heavy alcohol consumption was defined as drinking ≥ 2 times/week and ≥ 7 cups/time for males and ≥ 5 cups/time for females. 2 Moderate physical activity was defined as performing moderate-intensity physical activity for ≥ 30 min/time for ≥ 5 days/week. Vigorous physical activity was defined as performing vigorous intensity physical activity for ≥ 20 min/time for ≥ 3 days/week. 3 1 U. CARR. = 0.08 mg/100 mL H 2 O 2 . 2.2.2. Oxidative stress and inflammatory biomarkers in serum Oxidative stress and inflammatory indices in the serum samples varied marginally among the participants from three different study groups subjected to different dietary regimens (Table 2) . Most notably, we observed higher relative levels of d-ROM and BAP for the recommended dietary (2010 DGA > BKD) groups compared to TAD. This was corroborated by the reduced levels of CRP in BKD and 2010 DGA dietary groups compared to TAD. Notably, serum samples from the 2010 DGA participants were characterized with reduced levels of inflammatory biomarker IL-6 followed by the BKD and TAD group. In contrast, IL-1β and MCP-1 levels were lowered most among the TAD group participant compared to those enrolled in 2010 DGA and BKD. Table 2. Changes in serum oxidative stress and inflammatory indices after 4-weeks of dietary interventions 1 BKD 2010 DGA TAD Mean ± SE p value Mean ± SE p value Mean ± SE p value d-ROMs (U. CARR. 2 ) 7.02 ± 7.83 0.3722 10.65 ± 7.82 0.1767 4.04 ± 7.83 0.6069 BAP (μmol/L) 53.78 ± 45.04 0.2355 68.40 ± 45.02 0.1321 39.35 ± 45.05 0.3847 CRP (mg/L) -0.33 ± 0.52 0.5179 -0.21 ± 0.52 0.6803 0.05 ± 0.52 0.9168 TNF-α (pg/mL) -0.14 ± 0.19 0.4453 0.17 ± 0.19 0.3736 0.01 ± 0.19 0.9404 IL-6 (pg/mL) -0.18 ± 0.20 0.3693 -0.57 ± 0.20 0.0050 -0.21 ± 0.20 0.3047 IL-1β (pg/mL) 0.08 ± 0.07 0.2138 0.04 ± 0.07 0.5225 -0.02 ± 0.07 0.7735 MCP-1 (pg/mL) -47.54 ± 13.07 0.0005 -38.56 ± 13.05 0.0040 -54.12 ± 13.07 <0.0001 † Abbreviations: BKD, balanced Korean diet; 2010 DGA, diet recommended by the 2010 Dietary Guidelines for Americans; TAD, typical American diet; SE, standard error; d-ROMs, diacron reactive oxygen metabolites; U. CARR., Carratelli Unit; BAP, biological antioxidant potential; CRP, C-reactive protein; TNF-α, tumor necrosis factor-α; IL-6, interleukin-6; IL-1β, interleukin-1β; MCP-1, monocyte chemoattractant protein-1. 1 All analyses accounted for the crossover randomized control design using a mixed effect model adjusted for diet sequence effect and period effect. 2 1 U. CARR. = 0.08 mg/100 mL H 2 O 2 . 2.2.3. Urine metabolite profiles Principal component analysis (PCA) score plot based on the negative ESI mode LC-MS datasets for the urine samples indicated a clear segregation between the study groups subjected to the BKD and western diets (2010 DGA and the TAD) across PC 1 (5.41%) with few outliers ( Fig. 3 ). However, the datasets for pre- and post-intervention stages were not clearly segregated for each of the study group in the respective PCA plot. Supervised partial least squared – discriminant analysis (PLS-DA) score plot displayed a clearly clustered pattern for the BKD and western dietary regimens (2010 DGA and TAD) across PLS 1 (4.96%) whereas the respective pre- and post-intervention sample datasets were segregated across PLS 2 (2.93%). PLS-DA model was validated against the data overfitting with Q 2 = 0.69, while its predictive accuracy was verified with R 2 X (0.28) and R 2 Y (0.96). In addition, Similar multivariate statistical patterns were evident for the urine metabolite profiles in positive ion mode (Supplementary Fig. S.2) . We conducted cross-validation analysis to ensure the robustness of the described PLS-DA models and prevent the potential data overfitting (Supplementary Fig. S.3) . Herein, the metabolite profiling data substantiates a multiparametric variability among the urine metabolite profiles highlighting the effects of short-term dietary interventions. Based on the PLS-DA model, we selected 54 significantly discriminant metabolites (VIP > 0.7, p < 0.05) which contribute maximally toward the observed variance among the urine metabolite profiles from the three dietary intervention groups. Among the selected candidates, 34 metabolites were putatively characterized mainly as the derivatives of amino acids & peptides (3), benzoic acid & phenolic (8), fatty acid & lipids (17), and six miscellaneous compounds ( Fig. 4 ). The remaining 20 features were not characterized and labelled as non-identified (N.I). The LC-MS characteristics and the raw data peak intensities for each of the significantly discriminant metabolites are shown in supplementary data 1 . We showed the fold-change relative abundance of the significantly discriminant metabolites using the tabular heatmap ( Fig. 4 ). Most notably, the urine metabolite profile from participants subjected to the 2010 DGA and TAD displayed significantly higher post-intervention abundance of the amino acid & peptide derivatives (creatinine, L-isoleucyl-L-proline, and phenylacetylglutamine) compared to those enrolled for BKD. Compared to the western dietary regimens, participants enrolled in BKD displayed higher relative abundance of most benzoic acid & phenolic derivatives (enterodiol-glucuronide, enterolactone-3’-glucuronide, and gingerol) except argenteane in corresponding urinary extracts. Notably, the participant enrolled with 2010 DGA group also displayed a higher urinary abundance of few plant-derived phenolics including vanillic acid 4-O-sulfate, hippuric acid, and caffeic acid 4-O-sulfate. Most benzoic acid & phenolic derivatives were least abundant in the urinary samples from the participants in TAD group. Considering the fatty acid & lipid derivatives, a higher relative abundance of most steroidal glycosides was evident in the post-intervention urine samples representing the participants in TAD group followed by 2010 DGA. However, the acylcarnitine compounds (cis-5-tetradecenoylcarnitine and myristoylcarnitine) were significantly higher in the post- intervention urinary samples from the BKD participants. Most sphingolipid derivatives were significantly higher in the post-intervention urinary samples from BKD groups. A fatty acid alcohol 8-hydroxyfalcarinone was significantly higher in post- intervention urine samples from the western dietary (2010 DGA and TAD) groups. Miscellaneous categories of metabolites including uric acid, propenyl propyl disulfide, piperamide-C5:1, cichorioside G, and chondroitin were more abundant in the post- intervention urine samples for the participant groups enrolled in western dietary regimens compared to those with BKD. In contrast, Austalide G, a metabolite derived from the soy-food fermentation, was significantly higher in the post- intervention urine samples from the BKD group. Considering the non-identified (N.I) features, post- intervention urinary samples from the participants from enrolled with western dietary regimens displayed higher relative abundance of features ranging N.I.1 – N.I.10, while those from the BKD groups were more abundant in N.I. 13-20. Discussion Metabolic disorders related to oxidative stress and SCI can be effectively managed using the evidence-based dietary recommendations in which the higher abundance of antioxidant compounds ought to assuage cellular injuries mediated by free radicals. Herein, we examined the comparative effects of the short-term dietary interventions involving BKD, 2010 DGA, and TAD on oxidative stress & inflammatory indices among the Korean adults with obesity. Further, we examined the urinary biomarkers to examine the health effects of these dietary interventions using the untargeted metabolomics approach. Previously, we have shown that BKD effectively improves the three major metabolic indices including the BMI, body fat percent, and blood lipid profiles 8 . We assume that such different outcomes after 4-weeks of dietary interventions are associated to their varying antioxidant compositions which are primarily derived from the phytochemical components. Dietary intakes of phytochemicals with antioxidant functions have been extensively reported to be inversely linked with metabolic disorders in several epidemiological studies 9-15 . 3.1. Recommended diets (BKD and 2010 DGA) provided more antioxidants than TAD Recommended dietary regimens (BKD and 2010 DGA) had larger proportions of fruits, vegetables, legumes, whole grains & cereals, nuts, and unprocessed dairy with relatively lesser proportions of meat and poultry. However, a relatively larger portion of TAD included refined grains, processed meat, canned foods, and processed dairy ingredients 8 . Considering the varying levels of antioxidants in each of the dietary regimens, we examined the contents of antioxidant vitamins and polyphenols in each dietary regimen using in silico methods (Fig. 1) . Higher relative abundance of vitamin A subtypes was evident for the recommended diets (BKD and 2010 DGA) which can be associated with their higher antioxidant potentials compared to TAD. Vitamin A and its various subtypes functions as provitamin carotenoid derivatives which inhibit the production of pro-inflammatory cytokines, prostaglandin E2, and nitric oxide in the body, and hence alleviate oxidative stress 16,17 . Higher titers of vitamin C and most vitamin E subtypes in recommended diets can be linked with their antioxidant potentials owing to their inhibitory activities against the production of pro-inflammatory cytokines like IL-4, IL-5, and IL-13 18,19 . Phenolic compounds are often touted as nutraceuticals owing to their ROS-scavenging effects and are reported from a variety of plant-derived foods including herbs, vegetables, fruits, spices, and associated beverages 20 . BKD was characterized with higher relative levels of most flavonols (quercetin, kaempferol, isorhamnetin) except myricetin (2010 DGA > BKD) which can be attributed to a variety of plant-derived dietary menu components including onions, apples, and various green leaf and cruciferous family vegetables 21 . Moreover, higher levels of isoflavones (daidzein, genistein, and glycitein) in the BKD compared to western diets is ascribed to the fermented soy-foods in Korean cuisines. Most other polyphenols (flavones, flavanones, flavan-3-ols, and anthocyanidins) were observed relatively higher in recommended diets (BKD and 2010 DGA) compared to TAD owing to the higher proportions of the plant-derived components 22 . We retrospectively examined the in vitro antioxidant levels for the weekly menus provided in each dietary regimen to the study participants. Intriguingly, the sample extracts for BKD and 2010 DGA rich in plant-derived nutrients displayed significantly higher antioxidant activities as well as total phenolic (TPC) and total flavonoid (TFC) contents compared to TAD (Fig. 2) . Hence, the in vitro antioxidant activities and TPC & TFC levels for each dietary regimen extracts substantiated their in-silico micronutrient compositions. 3.2. Short-term dietary interventions had minimal impact on serum biomarkers of oxidative stress and inflammation Considering the effects of dietary interventions in serum biomarkers of oxidative stress & inflammation, MCP-1 levels of the participants significantly declined after intervention periods with all three diets. Notably, 2010 DGA was also found to have an improving effect on serum IL-6 levels. However, most of the serum indices of the oxidative stress (dROM, BAP, CRP) and inflammation (TNF-α, IL-6, and IL-1β) did not varied significantly among the participants following the 4-weeks of three different dietary interventions. Here, we conjecture a possibility of data misinterpretation under the condition where even TAD could also work better for participants who were taking relatively unhealthier diet prior to their enrollment in the trial. This becomes more relevant considering the equivalent calorific values and rationalized macronutrient compositions provided under each dietary regimen with rationed serving portions. However, the undesired and long-term carry-over effects of the participants’ usual dietary habits could not be completely ruled out. To overcome this limitation of interpreting the fragmentary results involving short-term dietary interventions, we investigated the complementary changes in the urinary metabolite profiles of the participants. 3.3. Urine metabolomics unraveled subtle effects of short-term dietary interventions Untargeted urine metabolomics data suggested a marked variation in the baseline metabolic fingerprints of the participants enrolled in Western (2010 DGA and TAD) and Korean (BKD) diets. We analyzed the significantly discriminant metabolites with known associations with the characteristic dietary intake and physiological functions linked with oxidative stress. Of the 54 significantly discriminant metabolites, 34 metabolites were identified while 20 remained non-identified, and therefore, we limited our discussion on the likely implications of the characterized metabolites. Participants subjected to western dietary regimens displayed higher urinary abundance of the amino acid & peptide derivatives compared to the BKD group. Especially, the peptides including creatinine and L-isoleucyl-L-Proline are often correlated with an increased dietary intake of red meat or the endogenous catabolism of proteins & muscle turnover in humans 23,24 . Higher urinary titers of phenylacetylglutamine are often linked with heightened ROS generation and metabolic disorder including obesity 25,26 . Benzoic acid & polyphenol derivatives were relatively higher in the urine extracts from the participants enrolled with the recommended dietary regimens (BKD and 2010 DGA) compared to those with TAD. Higher abundance of phytoestrogen derivatives including the lignans (enterodiol-glucuronide and enterolactone 3’-glucuronide) in urine are the known biomarkers of whole grain (barley, rye, wheat) consumption and signifies their anti-inflammatory functions. In addition, flaxseeds, nuts, legumes, and sesame seeds also contain the considerably high proportions of dietary lignans which constitute an important portion of the traditional Korean diet as well as BKD 27 . In addition, the higher post- intervention levels of gingerol (a methoxyphenol compound) in urinary samples from the BKD group is ascribed to the introduction of herbs and spices including ginger in the diet. Gingerol is known for its antioxidant functions through inhibiting the release of pro-inflammatory cytokines in the blood 28 . We observed weak positive correlations between the polyphenol abundance in urine and the pro-inflammatory cytokines (TNF-α and IL-6) in serum samples from BKD enrolled participants which suggest their possible role in inflammatory response (Fig. 5) . Participants subjected to the 2010 DGA showed higher urinary abundance of phenolic derivatives including vanillic acid 4-O sulfate, hippuric acid, and caffeic acid 4-O-sulfate which can be linked with the consumption of plant-derived components and whole grains. Hippuric acid levels in urine indicate their positive effects on antioxidant enzyme systems including CoQ (Co-enzyme Q10) and β-carotene in plasma. However, hippuric acid influences the inhibition of the endogenous antioxidative systems in humans which include Nrf2, thioredoxin, and superoxide dismutase, suggesting a balance between the blood and urinary levels of hippuric acid 29 . Urinary abundance of fatty acid & lipid derivatives including most steroidal glycoside, acyl-carnitines, sterols, and terpene glycosides in the study group subjected to western diets (2010 DGA and TAD) were higher than those provided with BKD which can again be attributed to their different dietary compositions. Notably, elevated levels of urinary isobutyryl-L-carnitine and estrone (steroid lipid) are associated with higher consumption of red meat & animal products which constitute a major portion of western diets (www.foodb.ca). These lipid derivatives are known to induce oxidative stress through promoting the fatty acid oxidation and/or ROS generation in body 30,31 . Higher abundance of most steroidal- and terpene- glycosides in the urinary samples from participants enrolled with western diets suggest their higher dietary compositions and in situ biotransformation. Most notably, cortolone-3-glucuronide, tetrahydroaldosterone-3-glucuronide, 11-β-hydroxyandosterone-3-glucuronide, ethyl-7-epi-12-hydroxyjasmonate glucoside, and androsterone sulfate are produced by the endocrine transformation of food-derived nutrients. Most fatty acid & lipid derivatives in urine samples displayed weak positive correlations with pro-inflammatory cytokines (TNF-α and IL-1β) which suggest their role in oxidative stress (Fig. 5) . Urine samples from the participants enrolled in BKD were more abundant in acylcarnitine compounds (cis-5-tetradecenoylcarnitine and myristoylcarnitine) associated with fatty acid oxidation and ROS generation 32,33 . However, higher relative levels of sphingolipids in post- intervention urine samples from BKD group suggests their ameliorating effects against obesity related malfunctions 34 . Elevated levels of uric acid in body, an endogenous antioxidant metabolite and a ROS-scavenger, indicate the systematic oxidative stress in humans 35 . As we enrolled the healthy participants in this study and subjected them to the short-term dietary interventions, the higher urinary levels of uric acid indicate that oxidative stress build-up following the course of western dietary (TAD > 2010 DGA) interventions, and not the BKD (Fig. 5) . Remaining metabolites including organic disulfide, piperamide, and cichorioside are the biomarkers of respective plant-derived food sources including onions, peppers & herbs, chicory, and endives served in all dietary regimens at various proportions (www.foodb.ca). Most of these compounds have a known antioxidant functions when taken as dietary component. Higher post- intervention abundance of Austalide G in urinary samples from participant subjected to BKD might be associated with unique inclusion of Aspergillus fermented food components. Austalide G is a polycyclic aromatic metabolite belonging to the chemical class of xanthenes which are reportedly produced by certain Aspergillus species however their health effects are largely unreported and hard to associate with oxidative stress. Considering the strengths of this work, it’s arguably the first study focusing on the associations between the oxidative stress indices in serum, urinary metabolites, and dietary intervention comparing the BKD and western diets. The results may provide scientific evidence and rationale toward the establishment of novel dietary guidelines for the peoples with SCI and associated metabolic disorders. The present study involved crossover randomized controlled trials which could increase the statistical power and minimize the possible confounding effects even with the relatively small number of participants. However, we also acknowledge certain limitations such as the analysis of serum and urine samples following a brief period of storage. Though, the samples were quenched and stored under standard conditions (-80 ˚C), we assume the degradation of certain unstable compounds. Further, the study diets used in the trials do not represent the typical dietetics patterns & habits of either the Koreans and/or Americans per se but rather designed based on the respective government guidelines and references. In summary, the present study explores the associations between short-term dietary interventions and their effects on oxidative stress biomarkers in serum and metabolic signatures in urine. The plant-derived components (fruits, vegetables, legumes, nuts, and whole grains) in the BKD and 2010 DGA likely alleviated the oxidative stress in the participants, compared to those subjected to the TAD. However, varying degrees of animal-derived components (red meat, poultry, and processed dairy products) and processed foods in western dietary regimens also influenced oxidative stress and related biomarkers in body fluids. Overall, the nutritional quality of diets isn't solely reliant on including minimally processed whole food components and plant-derived antioxidants as observed for the recommended diets in this study. It's equally important to consider the proportions of ultra-processed animal-derived products, as they can significantly contribute to the oxidative stress. Diets recommended for their fine balance of healthy dietary components, such as the BKD and 2010 DGA, are considered better in this regard compared to the TAD. Besides perceived complications involving sample preparations and data analysis, we believe that the untargeted urine metabolomics approach use in this study can be leveraged to measure the effects of short-term dietary interventions and their physiological impacts in clinical trials or population studies. Materials & Methods 4.1. Study subjects As depicted in the participant flow chart (Fig. 6) , all 148 participants affiliated to this study were voluntarily recruited through e-mail and poster advertisements as described previously by Kim et al. 8 . Anthropometric measurement, blood test, and face-to-face survey were initially performed for screening among 132 attendees. The inclusion criteria of the trial were Korean adults aged 25–65 years with body mass index (BMI) ≥ 23 kg/m 2 and the blood low-density lipoprotein (LDL) cholesterol ≥120 mg/dL. Participants were excluded if they were smoking regularly and/or having the alcohol or substance abuse problems. We also excluded the participants which were consuming the prebiotics, probiotics, or antibiotics during the past 6 months before the onset of trials. Participants who reported a significant weight loss (≥ 10% of body weight) during the last 12 months before the trial period or those with any metabolic disorders including the cardiovascular diseases (CVD), diabetes, and kidney ailments were screened-out of the study. Sixty-one eligible individuals were selected for participation while only 54 of them completed the trials. The detailed information for this trial can be retrieved from our previous publications 8, 36 . Following the trial period, our research staffs responsible for maintaining the personal information contacted every subject to seek their approval for further analyses of oxidative stress and inflammatory biomarkers in serum samples, and their urine metabolite profiling. Of the total participants, 48 participants voluntarily approved their serum and urine analyses. We had confirmed using power analysis that a total of 30 participants were sufficient to detect a mean difference of LDL cholesterol, which is one of the major indices of blood lipid profile, in our previous study (α = 0.05, β = 0.20) 8 . All the steps in this trial were approved by the Institutional Review Board of Seoul National University (IRB No. 1506/002-014 & IRB No. 1805/003-010). The first date of study participant registration was 11/09/2015, and informed consents were obtained from all the participants. The whole processes of this study were performed in accordance with the relevant guidelines and regulations. The trial was registered at the clinical research registry, Clinical Research Information Service (CRIS) in Korea, which is the primary registry of the World Health Organization international clinical trial registry platform (registration No. KCT0002437). This trial was registered at the clinical research registry, Clinical Research Information Service (CRIS) in Korea, which is the primary registry of the World Health Organization international clinical trial registry platform (registration No. KCT0002437; https://cris.nih.go.kr/cris/search/detailSearch.do?search_lang=E&focus=reset_12&search_page=L&pageSize=10&page=undefined&seq=8598&status=5&seq_group=8598). This study was conducted following the CONSORT 2010 guidelines for reporting randomized controlled trials 37 . 4.2. Design of study Study design was adapted from the previous trial for dietary interventions conducted by Schroeder et al. 38 with some modifications and described elsewhere in details 8, 36 . It was a crossover randomized controlled trial with three intervention periods conducted over a period of from 2015 to 2017. Participants were stratified based on sex, BMI, and blood LDL cholesterol levels, and were randomly assigned into 6 groups according to the order of the three different dietary patterns. This included dietary regimens with balanced Korean diet (BKD), diet recommended by the 2010 Dietary Guidelines for Americans (2010 DGA), and typical American diet (TAD) for 4 weeks each. During the intervention periods, the subjects had to consume only the dishes provided in the study diets. For all the participants, alcohol consumption was prohibited and maintaining the usual physical activity levels was strongly recommended to minimize the possible confounding effects. Between each intervention period, the subjects had a 2-week interval as washout period in which they were allowed to have their usual diets & lifestyle. At the beginning and the end of each intervention, the participants received physical examinations following a fasting period (≥ 8 hour) and provided the first morning urine samples. Metabolic indices including the BMI, body fat percent, waist circumference, blood pressure, blood triglyceride & cholesterol, blood glucose, and blood insulin levels were obtained from anthropometric measurement and blood test. We have previously reported the effects of these dietary regimens on the above-mentioned metabolic indices of the participants 8 . 4.3. Study diets Details for dietary regimens including the BKD, 2010 DGA, and TAD and their components are described previously by Kim et al. 8 and Shin et al. 36 . Each standardized dietary regimen was designed to supply 2,000 kcal/day including the whole meals of breakfast, lunch, supper, and snack on a 7-day cycle. We have reported the calorific values for different nutritional components in each dietary regimen using the CAN-Pro 5.0 (Computer Aided Nutritional analysis program 5.0, The Korean Nutrition Society, Seoul, Korea) with each component analyzed according to the protocols from the Korean Food Standards Codex 8 . Each subject’s serving size was determined by the individual estimated energy requirement that was calculated based on the participant’s information for sex, age, body weight, height, and physical activity level using the formulas established by the Dietary Reference Intakes for Koreans (KDRI) 39 . The BKD was developed based on the food guidance of the KDRIs and the dietary guidelines for Korean adults published by the Ministry of Health and Welfare, Republic of Korea 39, 40 . The ratios of the energy supply from macronutrients in BKD were as follows: 60–65% from carbohydrate, 20–25% from fat, and 15% from protein. It included multi-grain rice, soup, 120 g/day of kimchi, and side dishes containing relatively large amounts of vegetables and legume products with 15 g/day of fermented ingredients such as red pepper paste and soybean paste. The 2010 DGA was developed based on the sample menus recommended by the 2010 Dietary Guidelines for Americans issued by the US Department of Agriculture (USDA) 41 . The proportion of the energy supply from the carbohydrate was 55%, whereas those from the fat and protein were 30% and 15%, respectively. It contained whole grains, vegetables, fruits, lean meat, seafood, and skim milk. The TAD was developed based on the data from the ‘What We Eat in America’ published by the National Health and Nutrition Examination Survey, 2001–2004 42 . The ratios of energy supply from macronutrients were as follows: 50% from carbohydrate, 35% from fat, and 15% from protein. It was mainly consisted of refined grains and processed foods with relatively small amounts of vegetables, fruits, and lean meat. The sample menus for each study are introduced in our previous study 8 . 4.4. Antioxidant contents for the study diets To estimate the antioxidant contents and dietary TAC (vitamin C equivalents) for the three study diets, we associated the recipes of each regimen to the databases of antioxidant capacity, antioxidant vitamins, and flavonoid contents available for commonly consumed Korean foods 43-46 . The following antioxidants components of the study diets were included in the databases: retinol, carotenoids (α-carotene, β-carotene, lycopene, β-cryptoxanthin, lutein/zeaxanthin), vitamin C, tocopherols (α-tocopherol, β-tocopherol, γ-tocopherol, δ-tocopherol), flavonols (quercetin, kaempferol, isorhamnetin, myricetin), isoflavones (daidzein, genistein, glycitein), flavones (apigenin, luteolin), flavanones (eriodictyol, hesperetin, naringenin), flavan-3-ols (catechin, epicatechin, epigallocatechin), anthocyanidins (cyanidin, delphinidin, pelargonidin, malvidin, peonidin, petunidin), and proanthocyanidins (dimers, trimers, 4–6mers, 7–10mers, 10+ polymers). Vitamin A and vitamin E levels were calculated in retinol activity equivalent (RAE) and α-tocopherol equivalent (α-TE), respectively, using the following formulas: The experimental analyses of the total phenolic contents (TPC), the total flavonoid contents (TFC), and overall antioxidant levels of the study diets were conducted using the methods adapted from 47 . Daily menus of each of the study diet were blended, homogenized, and stored immediately at -80℃ until analyses. Prior to the extraction, the samples were lyophilized using a freeze dryer (Bondiro, Ilshin Lab Co., Gyeonggi-do, Korea). Eight grams of dried samples from each dietary menu were subjected to initial extraction with 70% ethanol (1:1, w/v) by incubating them at 300 rpm for 1 hour at 24°C. Subsequently, the samples were centrifuged (8000 rpm for 10 minutes at 4°C) and the resulting supernatants were filtered, and further dried using a speed vacuum concentrator (Hanil Scientific, Korea). The ethanolic extracts were then dissolved in water (1:1, w/v) and divided into ethyl acetate (EA) and butanol partitions. Both the EA and butanol fractions were isolated, dried using a speed vacuum concentrator, and subsequently reconstituted in their respective solvents to attain a final concentration of 10 mg/mL, before conducting bioactivity assays. TPC, TFC, and the antioxidant levels (ABTS assay, DPPH assay, and FRAP assay) for the dietary sample extracts were determined using the method adapted from our previous stud 48 . 4.5. Analyses of oxidative stress and inflammatory markers in serum samples Serum samples were collected on the days of physical examination and were immediately stored at -80℃ until analyses. Oxidative stress biomarkers in serum including d-ROMs (diacron reactive oxygen metabolites) and BAP (biological antioxidant potential) were measured using an automatic chemistry analyzer (Diacron International s.r.l., Grosetto, Italy). The levels of inflammatory biomarkers in serum including C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1β (IL-1β), and monocyte chemoattractant protein-1 (MCP-1) were determined using Multiplex Luminex Assay (R&D Systems, Minneapolis, MN, USA). 4.6. Metabolite profiling of urine samples Pooled urine samples (400 μL) were extracted with 1 mL of absolute methanol and centrifuged at 13,000 rpm for 10 min at 4˚C. Supernatants were collected and dried using speed vacuum concentrator. Dry sample extracts were reconstituted in methanol at the concentration of 50 mg/mL and passed through 0.2 μm filter prior to the untargeted LC-MS analysis. Samples were on run on the UHPLC-LTQ-Orbitrap-MS/MS system coupled with Vanquish binary pump H system (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Reverse phase chromatographic separation of metabolites was performed on Phenomenex KINETEX ® C18 column (100 mm × 2.1 mm, 1.7 μm particle size; Torrance, CA, USA). The mobile phase composed of water (solvent A) and acetonitrile (solvent B) with 0.1% formic acid in each. The 14 min gradient run program commenced with 5% solvent B for 1 min followed by its linear increase to 100% in next 9 min, maintained for 1 min, and re-equilibrated to initial condition (5% solvent B) in the final 3 min. The chromatographic run program maintained a constant flow rate of 0.3 mL/min with a sample injection volume of 5 μL and the column temperature at 40 °C. The tandem MS was performed on LTQ-Orbitrap-Velos Pro with ion-trap (IT) MS and heated ESI or HESI-II probe (Thermo Fisher Scientific). The MS parameters were fixed at probe heater temperature of 300 °C, capillary temperature of 350 °C, and the capillary voltages of 2.5 kV (-ESI) and 3.7 kV (+ESI). The samples were analyzed over a mass range (m/z) ranging from 150-100 under both positive and negative ESI modes. 4.7. Data processing and multivariate statistical analyses Changes in oxidative stress and inflammatory indices in the serum samples for each dietary intervention group were investigated using a ‘mixed effect model’ adjusted for the dietary sequences and the washing period, which accounted for the crossover design. Post hoc analysis using Tukey’s HSD (honest significant difference) test was performed to examine the differences between the diets. The analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC, USA). A two-sided p value < 0.05 was considered statistically significant. The raw data files obtained from UHPLC-LTQ-Orbitrap-MS/MS system were converted to NetCDF (network Common Data Form) file formats. The converted files ( .cdf ) were pre-processed for peak list alignment, peak detection, retention time (RT), normalized peak intensities, and accurate masses comparing their full scan nominal mass using the MetAlign TM software. The aligned data were further subjected to multivariate analyses to evaluate the class-wise variance in datasets and determining the significantly discriminant metabolites (VIP > 0.7, p < 0.05) based on the PLS-DA model made with SIMCA-P+ (version 12.0, Umetrics, Umea, Sweden). The heat map expressions for the metabolite levels and corresponding pair-wise correlation (PASW statistics) were made on Microsoft Excel 2016. 4.8. Metabolite annotations The significantly discriminant features were classified based on the PLS-DA model for LC-MS datasets, and the metabolites were putatively identified based on their RT, mass to charge ratios (m/z), MS n fragmentation patterns, and elemental compositions (error window<10 ppm) with corresponding standards, in house libraries, associated web databases. The food derived and urinary metabolites were characterized using a variety of databases and associated literature sources, but all are represented together according to their levels at the beginning and the end of each intervention. Abbreviations BKD, Balanced Korean Diet; 2010 DGA, 2010 Dietary Guidelines for Americans; TAD, Typical American Diet; TAC, Total Antioxidant Capacity; SCI, systemic chronic inflammations. Declarations Conflict of interest All authors report no conflict of interest. Funding This work was supported by the Research Program for Agricultural Science and Technology Development, National Academy of Agricultural Science, Rural Development Administration, Republic of Korea (Project no. PJ013475022019) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2023R1A2C1004930). Author Contribution Conceptualization: DS, DH, SAK, HJ, CHL; Data curation: DS, DH, YJP; Formal analysis: DS, DH, SAK, YJP; Funding acquisition: HJ, CHL; Investigation: DS, DH, HJ, DK, CHL; Methodology: DS, DH, SAK, HJ, CHL; Project administration: DH, HJ, CHL; Resources: DH, SAK, HJ; Software: DS, DK, DH, YJP; Supervision: HJ, CHL; Validation: HJ, CHL; Visualization: DS, YJP; Writing – original draft: DS, DH, DK; Writing – reviewing & editing: DS, DK, DH, HJ, CHL. Acknowledgement We acknowledge many individuals who contributed at various steps of this study and manuscript writing. Kyungho Ha, Shinyoung Jun, Jiyoon Kim, Seoeun Ahn, and Subeen Kim contributed to conducting the dietary trial and anthropometric measurement procedures. ChangHyuk Hwang helped in metabolite profiling data curation. We also acknowledge the subjects who participated in the trial. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Rupérez, A. I., Gil, A. & Aguilera, C. M. Genetics of oxidative stress in obesity. Int. J. Mol. Sci. 15, 3118–3144 (2014). Furman, D. et al . Chronic inflammation in the etiology of disease across the life span. Nat. Med. 25, 1822–1832 (2019). Zhong, X. et al. Inflammatory potential of diet and risk of cardiovascular disease or mortality: A meta-analysis. Sci. Rep. 7, 6367 (2017). de Souza, R. J., Swain, J. F., Appel, L. J. & Sacks, F. M. 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Supplementary Files Supplementarydata1.xlsx Supplementarytableandfigures.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Jun, 2024 Reviews received at journal 02 Jun, 2024 Reviewers agreed at journal 22 May, 2024 Reviews received at journal 04 May, 2024 Reviewers agreed at journal 11 Apr, 2024 Reviewers invited by journal 09 Apr, 2024 Editor assigned by journal 09 Apr, 2024 Editor invited by journal 08 Apr, 2024 Submission checks completed at journal 03 Apr, 2024 First submitted to journal 21 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4142606","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":287050799,"identity":"77f76182-20b7-423c-82fe-4e33fe451ef2","order_by":0,"name":"Digar Singh","email":"","orcid":"","institution":"Hemvati Nandan Bahuguna Garhwal University","correspondingAuthor":false,"prefix":"","firstName":"Digar","middleName":"","lastName":"Singh","suffix":""},{"id":287050800,"identity":"f13c2758-b993-49f1-ac1f-b50e144a2cbb","order_by":1,"name":"Dongwoo Ham","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Dongwoo","middleName":"","lastName":"Ham","suffix":""},{"id":287050801,"identity":"c21a42eb-b731-4eb3-b7ed-6db24f4ac069","order_by":2,"name":"Seong-Ah Kim","email":"","orcid":"","institution":"The Seoul Institute","correspondingAuthor":false,"prefix":"","firstName":"Seong-Ah","middleName":"","lastName":"Kim","suffix":""},{"id":287050802,"identity":"b7030055-a8a3-480c-9cf9-c000e51127c0","order_by":3,"name":"Damini Kothari","email":"","orcid":"","institution":"Hemvati Nandan Bahuguna Garhwal University","correspondingAuthor":false,"prefix":"","firstName":"Damini","middleName":"","lastName":"Kothari","suffix":""},{"id":287050803,"identity":"351733a9-51c9-4c2d-ba3c-d507eaedb3a2","order_by":4,"name":"Yu Jin Park","email":"","orcid":"","institution":"Konkuk University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"Jin","lastName":"Park","suffix":""},{"id":287050804,"identity":"3374c599-a755-44c7-90bf-57785040b7e5","order_by":5,"name":"Hyojee Joung","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Hyojee","middleName":"","lastName":"Joung","suffix":""},{"id":287050805,"identity":"28ec686b-4999-4c95-aa1b-e969d942b045","order_by":6,"name":"Choong Hwan Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYDACCeYGBgYDGzt+HgYGxgaGBJAYMwEtQHUMBWnJkj2kaflwmHHDGWK18M9ubHzwwYCZ2fjM4WMPZ7alMfC3H2A2rsBnyZ2DzYYzDNj4zM62pRtubMthkDiTwJx4Bo8WA4nENmkeAx5ms/M8ZpIP24DG32BgPtiAX0v77z8GEoyb+6Fa5InQ0sbMYGDAuIG3x0wS5DADoJZEfFokbiQ2S/YYJCRLnDmWJjnjXBqP4ZnEZkN8WvhnJB/88OPPfzv+nuRjkj1lyXJyxw8flsSnBQNAEsEoGAWjYBSMAsoAAGHbTBsTD7x2AAAAAElFTkSuQmCC","orcid":"","institution":"Konkuk University","correspondingAuthor":true,"prefix":"","firstName":"Choong","middleName":"Hwan","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2024-03-21 10:07:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4142606/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4142606/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54314818,"identity":"12ccb1a9-9319-4a43-b6fa-71c9de58f67c","added_by":"auto","created_at":"2024-04-08 17:40:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":417273,"visible":true,"origin":"","legend":"\u003cp\u003eStacked bar graph indicating micronutrient contents for the three dietary regimens used in the study; \u003cstrong\u003e(a)\u003c/strong\u003e BKD – Balanced Korean diet, \u003cstrong\u003e(b)\u003c/strong\u003e2010 DGA – Dietary guidelines for Americans, and \u003cstrong\u003e(c)\u003c/strong\u003e TAD – Typical American diet. The box and whisker plot show the varying levels of \u003cstrong\u003e(d)\u003c/strong\u003etotal antioxidant capacity (TAC) estimated for each of the diet with their statistical significance were expressed based on the Tukey’s post-hoc test. These components were computed based on the corresponding theoretical values estimated for the food components in each dietary regimen provide four times a day per week. All three diets were designed to provide ~2000 Kcal of energy per day from three meals.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/6bed6c9bee189fbe04997417.jpg"},{"id":54314817,"identity":"e194be78-1294-4e8d-af69-1f819f688863","added_by":"auto","created_at":"2024-04-08 17:40:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":273229,"visible":true,"origin":"","legend":"\u003cp\u003eBox and whisker plots representing the varying antioxidant levels determined using the (a) ABTS, (b) DPPH, (c) FRAP assays, and the (d) total phenolic contents (TPC), and (e) total flavonoid contents (TFC) for the three different dietary regimen extracts. Plots a-e represents the bioactivities for butanol extracts of the corresponding food components from the week-long dietary menus given to the participants. The data shown here was recorded for 21 different meal samples representing 3 meals per day for 7 days under each dietary regimen. Abbreviations: BKD, balanced Korean diet; 2010 DGA, 2010 Dietary Guidelines for Americans; TAD, typical American diet. The data was subjected to Tukey’s post-hoc test to examine their statistical significance.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/7e2f9b78c9a3d9994382e443.jpg"},{"id":54316262,"identity":"351e898f-0b2e-43e3-a263-30b3836fa52d","added_by":"auto","created_at":"2024-04-08 17:48:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":383154,"visible":true,"origin":"","legend":"\u003cp\u003eThe (a) PCA and (b) PLS-DA score plots based on the negative ESI mode UHPLC-LTQ-Orbitrap-MS/MS datasets representing metabolite profiles for the pre- (filled circles) and post-intervention (empty circles) urine samples collected from the participants enrolled under three different dietary regimens. The urine sample datasets representing the participant enrolled in three different dietary regimens is indicated with color codes, Blue color: BKD (Balanced Korean diet), Green color: 2010 DGA (2010 Dietary Guidelines for Americans), and Red color: TAD (typical American diet).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/f611794d6aca2a410197d130.jpg"},{"id":54314822,"identity":"107d970c-b992-43aa-a8d7-8c53a445e643","added_by":"auto","created_at":"2024-04-08 17:40:59","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1260554,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap representing the fold-change relative abundance of the significantly discriminant metabolites for the urine samples collected from the participants enrolled in BKD (Balanced Korean Diet), 2010 DGA (2010 Dietary Guidelines for Americans), and TAD (typical American diet). The sub-columns under each dietary group represent the pre- and post- intervention levels of each metabolite where the corresponding fold-change levels are indicated with the numerical values inside the corresponding box. The significantly discriminant metabolites were selected based on their VIP \u0026gt; 0.7 and \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 from the PLS-DA models build using the datasets acquired in the negative and positive ESI mode in UHPLC-LTQ-Orbitrap MS/MS.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/948c6f2736ac514658bf58f4.jpg"},{"id":54316669,"identity":"8e0bfa6d-bdcb-409b-8f18-76fc0acb8cae","added_by":"auto","created_at":"2024-04-08 17:56:59","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1355266,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the Pearson's correlations between the significantly discriminant (VIP\u0026gt;0.7, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) urinary metabolites and the serum biomarkers of oxidative stress \u0026amp; inflammation representing the pre- and post-intervention samples from participants enrolled in dietary trials. The level of significance (2-tailed) for these correlations are indicated with **0.01 and *0.05.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/b69523a850bfe44be3e8f46d.jpg"},{"id":54314821,"identity":"4bca3169-4d93-4fa1-b575-92b1e478d236","added_by":"auto","created_at":"2024-04-08 17:40:59","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":426132,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart illustrating the design of the study and participants at different stages of the dietary trials. The schematics was adopted from our previous study \u003cstrong\u003e(ref. 36)\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/21ef339c81d9e104f2eff4bf.jpg"},{"id":54317149,"identity":"5bea775f-1de2-4e9e-a6f3-d69817c14b45","added_by":"auto","created_at":"2024-04-08 18:05:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1105959,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/87252728-ec53-43a7-aeb0-ee1b7deae0f4.pdf"},{"id":54314824,"identity":"48454edd-5a87-4325-a213-edc33bcb78f5","added_by":"auto","created_at":"2024-04-08 17:40:59","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":183563,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/6130b6eeccf4655fef914880.xlsx"},{"id":54314823,"identity":"766ef01e-2875-4d65-8de8-749d903abf22","added_by":"auto","created_at":"2024-04-08 17:40:59","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":269243,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytableandfigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-4142606/v1/972d63de48a070c1967b903d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress \u0026 inflammation: a randomized controlled trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStudies have shown that both the long- \u0026amp; short-term dietary interventions influence the oxidative stress and systemic chronic inflammations (SCI) in humans. A higher imbalance in the ratio of free radicals to the antioxidant species either through nutritional or endogenous factors is considered as the oxidative stress, which influences the progression of inflammatory chronic diseases\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e. Healthy dietary preferences are key to manage chronic inflammatory diseases which roughly accounts for approximately 50% of all the annual deaths and disabilities worldwide\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e. Diet induced SCI is associated with various metabolic disorders including cardiovascular diseases (CVD), stroke, insulin resistance, obesity, and cancer, among others\u003cstrong\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e. Different dietary regimens are studied worldwide toward achieving a sustainable health with particular emphasis on oxidative stress and associated SCI, and their impact on etiological factors. In addition to the endogenous factors, the diet induced oxidative stress play a pivotal role in maneuvering various pathophysiological conditions. In particular, the unbalanced consumption of macronutrients, especially the animal-derived fats, promote oxidative stress, and subsequent inflammation through promoting the release of pro-inflammatory cytokines\u003cstrong\u003e\u003csup\u003e4,5\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Though the effects of different dietary regimens on anthropometric parameters are well studied, their correlations with the oxidative stress biomarkers in serum and urine metabolomes are largely unknown. The effects of dietary intakes and their metabolic implications for oxidative stress are mostly examined using the serum samples. However, the non-invasive and low-cost nature of urinary sample collection coupled with the unprecedented advancements in the mass spectrometry (MS) and spectroscopy (NMR) platforms makes it ideal for dietary intervention studies. In recent years, urine metabolomics has increasingly been used to monitor the effects of human exposure to drugs, toxins, pathogens, and related pathophysiological states\u003cstrong\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/strong\u003e. Hence, a comprehensive data integration correlating the quantitative urinary metabolite profile with the blood indices of oxidative stress and the associated anthropometric parameters may help indicate the real-time clinical outcomes of dietary intakes. Moreover, the respective data may be subjected to translational assessment of diet induced SCI and predicting its likely clinical implications. Hence, the exploratory urinary metabolomics towards probing the effects of varying dietary regimens and the associated metabolic markers of SCI can help predict and mitigate the early onset of chronic diseases.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The greater adherence to the balanced dietary recommendations lowers the risk of SCI pertaining to the higher antioxidant capacity of dietary components\u003cstrong\u003e\u003csup\u003e7\u003c/sup\u003e\u003c/strong\u003e. Though the health beneficiary functions of the balanced Korean diet (BKD) rich in dietary phytochemicals are largely acknowledged, its metabolomic implications are relatively unknown owing to the lack of randomized crossover longitudinal studies. A quintessential BKD is mainly composed of plant-derived components (whole grains, vegetables, fruits, and fermented beans) with relatively lesser proportions of animal-derived and processed foods. Previously, we have demonstrated that the BKD significantly improves the obesity-related metabolic risk factors and blood lipid profiles in participants from a randomized controlled trial\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e. This work explores the effects of short-term dietary interventions of the BKD and the Western diets in participants, and correlates the untargeted urine metabolite profiles with oxidative stress biomarkers in serum. \u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003e2.1. Characteristics of the three different dietary regimens (BKD, 2010 DGA, and TAD)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.1.1. Micronutrients\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe estimated the micronutrient contents including the antioxidant vitamins and phenolic compounds for each study diet (\u003cstrong\u003eFig. 1 \u0026amp; Supplementary Table S.1\u003c/strong\u003e). Notwithstanding their equivalent calorific values (~2000 Kcal/day), BKD was characterized by the significantly higher relative abundance of total carbohydrates (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01) with least relative abundance of fats (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01). On the other hand, both the 2010 DGA and TAD were characterized by relatively higher fat contents (TAD \u0026gt; 2010 DGA; \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01). However, the protein contents in all three dietary regimens were marginally varied \u003cstrong\u003e(Supplementary Fig. S.1)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eFor the micronutrients,vitamins and phenolic compounds were markedly varied among the three different dietary interventions. Most notably, vitamin A variants were lower in the BKD compared to the 2010 DGA and TAD, although the differences were not observed statistically significant. \u0026nbsp;However, the vitamin A subtypes including \u0026alpha;-carotene, \u0026beta;-carotene, \u0026beta;-cryptoxanthin, and lutein/zeaxanthin were relatively higher in the BKD and the 2010 DGA compared to TAD. Vitamin C contents were significantly higher in the 2010 DGA (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05), followed by the BKD and TAD, respectively. Similarly, vitamin E and its derivatives were also observed significantly higher for the western dietary regimens (2010 DGA \u0026gt; TAD) compared to the BKD (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01), except for their \u0026gamma;-tocopherol contents. Meanwhile, the BKD was characterized by the higher relative abundance of flavonols and isoflavones (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01), compared to the 2010 DGA and the TAD. On the other hand, the 2010 DGA was observed having higher relative levels of most phenolic compounds including flavones, flavanones, flavan-3-ols (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05), anthocyanidins, and proanthocyanidins (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). Altogether, the dietary TAC was considerably higher in the 2010 DGA (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) and the BKD, compared to the TAD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.1.2. Antioxidants\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe examined the levels of antioxidants for the pooled sample menus representing the three different diets examined in this study. Notably, the butanol sample extracts from both the recommended diets (BKD and 2010 DGA) displayed relatively higher antioxidant activities compared to TAD in ABTS (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01), DPPH, and FRAP assays (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) \u003cstrong\u003e(Fig. 2.a- c)\u003c/strong\u003e. Conversely, the ethyl acetate (EA) extracts showed relatively higher antioxidant levels for both the American diets (2010 DGA and TAD) compared to BKD in all three antioxidant assays (ABTS, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; DPPH, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; FRAP, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01). The inherent differences in polarity and metabolite distribution between EA and butanol extracts suggest their divergent bioactivities. Given n-Butanol\u0026apos;s higher polarity (0.552) in contrast to ethyl acetate (0.228), it\u0026apos;s expected that butanol extracts would harbor a greater concentration of polar antioxidant compounds, notably polyphenols. These compounds are likely to constitute a substantial portion of the essential nutrients found in recommended diets.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe observed disparity in the antioxidant levels of EA (ethyl acetate) and butanol extracts can be attributed to their different polarity which allows varying metabolite partitioning during the extraction procedure. However, this gives a more comprehensive outlook of the total antioxidant capacity of the dietary sample extracts.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.1.3. Phenolic and flavonoids\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTotal phenolic and flavonoids compositions for the pooled sample extracts of each study diet were further examined. We observed the significantly higher levels of TPC for the BKD compared to the 2010 DGA and the TAD from butanol extracts (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01). Similar trends were observed for the TFC from the butanol extracts of the three dietary regimens although their levels were marginally varied across the three dietary extracts (\u003cstrong\u003eFig. 2.d \u0026amp; e\u003c/strong\u003e). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2. Characteristics of the study subjects\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.1. Baseline characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e shows the baseline characteristics of the 48 study subjects before the onset of the dietary intervention trials. There were 25 males and 23 females\u0026rsquo; participants enrolled in this study. Considering their baseline oxidative stress markers in serum, higher d-ROMs and lower BAP levels were recorded for female participants compared to males. The inflammatory markers, CRP and TNF-\u0026alpha; levels were observed higher for female participants compared to males, whereas those for IL-6 and MCP-1 were relatively lower in female than male subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eBaseline\u0026nbsp;characteristics of the study subjects before the onset of the trials.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=48)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale (n=25)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale (n=23)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e25\u0026ndash;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e40\u0026ndash;64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly household income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 2 million KRW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e2\u0026ndash;6 million KRW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 6 million KRW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eCollege+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical activity\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eVigorous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.847133757961785%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOxidative stress indices (mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003ed-ROMs (U. CARR.\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e381.25 \u0026plusmn; 72.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e345.04 \u0026plusmn; 54.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e420.61 \u0026plusmn; 70.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eBAP (\u0026mu;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2,122.73 \u0026plusmn; 267.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2,218.56 \u0026plusmn; 224.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e2,018.57 \u0026plusmn; 276.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"56.847133757961785%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInflammatory indices (mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2.06 \u0026plusmn; 3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e1.83 \u0026plusmn; 3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e2.31 \u0026plusmn; 3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eTNF-\u0026alpha; (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2.18 \u0026plusmn; 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e2.14 \u0026plusmn; 1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e2.23 \u0026plusmn; 1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e1.85 \u0026plusmn; 1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e1.91 \u0026plusmn; 1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e1.78 \u0026plusmn; 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eIL-1\u0026beta; (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e0.06 \u0026plusmn; 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e0.04 \u0026plusmn; 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e0.08 \u0026plusmn; 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.50955414012739%\" valign=\"top\"\u003e\n \u003cp\u003eMCP-1 (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e402.94 \u0026plusmn; 130.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.337579617834393%\"\u003e\n \u003cp\u003e418.06 \u0026plusmn; 105.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.81528662420382%\"\u003e\n \u003cp\u003e386.51 \u0026plusmn; 154.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e Abbreviations: KRW, Korean Won; SD, standard deviation; d-ROMs, diacron reactive oxygen metabolites; U. CARR., Carratelli Unit; BAP, biological antioxidant potential; CRP, C-reactive protein; TNF-\u0026alpha;, tumor necrosis factor-\u0026alpha;; IL-6, interleukin-6; IL-1\u0026beta;, interleukin-1\u0026beta;; MCP-1, monocyte chemoattractant protein-1.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Moderate alcohol consumption was defined as drinking \u0026lt; 2 times/week, or drinking \u0026ge; 2 times/week but \u0026lt; 7 cups/time for males and \u0026lt; 5 cups/time for female. Heavy alcohol consumption was defined as drinking \u0026ge; 2 times/week and \u0026ge; 7 cups/time for males and \u0026ge; 5 cups/time for females.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Moderate physical activity was defined as performing moderate-intensity physical activity for \u0026ge; 30 min/time for \u0026ge; 5 days/week. Vigorous physical activity was defined as performing vigorous intensity physical activity for \u0026ge; 20 min/time for \u0026ge; 3 days/week.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e 1 U. CARR. = 0.08 mg/100 mL H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.2. Oxidative stress and inflammatory biomarkers in serum \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOxidative stress and inflammatory indices in the serum samples varied marginally among the participants from three different study groups subjected to different dietary regimens \u003cstrong\u003e(Table 2)\u003c/strong\u003e. Most notably, we observed higher relative levels of d-ROM and BAP for the recommended dietary (2010 DGA \u0026gt; BKD) groups compared to TAD. This was corroborated by the reduced levels of CRP in BKD and\u0026nbsp;2010 DGA dietary groups compared to TAD. Notably, serum samples from the 2010 DGA participants were characterized with reduced levels of\u0026nbsp;inflammatory biomarker IL-6 followed by the BKD and TAD group. In contrast, IL-1\u0026beta; and MCP-1 levels were lowered most among the TAD group participant compared to those enrolled in 2010 DGA and BKD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eChanges in serum oxidative stress and inflammatory indices after 4-weeks of dietary interventions\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"684\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"26.31578947368421%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eBKD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.31578947368421%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010 DGA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.31578947368421%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTAD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003eMean \u0026plusmn; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003eMean \u0026plusmn; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003eMean \u0026plusmn; SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003ed-ROMs (U. CARR.\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e7.02 \u0026plusmn; 7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.3722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e10.65 \u0026plusmn; 7.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.1767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e4.04 \u0026plusmn; 7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e0.6069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eBAP (\u0026mu;mol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e53.78 \u0026plusmn; 45.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.2355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e68.40 \u0026plusmn; 45.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.1321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e39.35 \u0026plusmn; 45.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e0.3847\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e-0.33 \u0026plusmn; 0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.5179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e-0.21 \u0026plusmn; 0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.6803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e0.05 \u0026plusmn; 0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e0.9168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eTNF-\u0026alpha; (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e-0.14 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.4453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e0.17 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.3736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e0.01 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e0.9404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e-0.18 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.3693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e-0.57 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.0050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e-0.21 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e0.3047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIL-1\u0026beta; (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e0.08 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.2138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e0.04\u0026nbsp;\u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.5225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e-0.02 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e0.7735\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.05263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eMCP-1 (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.29824561403509%\"\u003e\n \u003cp\u003e-47.54 \u0026plusmn; 13.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.017543859649122%\"\u003e\n \u003cp\u003e0.0005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.859649122807017%\"\u003e\n \u003cp\u003e-38.56 \u0026plusmn; 13.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.456140350877193%\"\u003e\n \u003cp\u003e0.0040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.42105263157895%\"\u003e\n \u003cp\u003e-54.12 \u0026plusmn; 13.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.894736842105263%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eAbbreviations: BKD, balanced Korean diet; 2010 DGA, diet recommended by the 2010 Dietary Guidelines for Americans; TAD, typical American diet; SE, standard error; d-ROMs, diacron reactive oxygen metabolites; U. CARR., Carratelli Unit; BAP, biological antioxidant potential; CRP, C-reactive protein; TNF-\u0026alpha;, tumor necrosis factor-\u0026alpha;; IL-6, interleukin-6; IL-1\u0026beta;, interleukin-1\u0026beta;; MCP-1, monocyte chemoattractant protein-1.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e All analyses accounted for the crossover randomized control design using a mixed effect model adjusted for diet sequence effect and period effect.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e 1 U. CARR. = 0.08 mg/100 mL H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2.3. Urine metabolite profiles\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA) score plot based on the negative ESI mode LC-MS datasets for the urine samples indicated a clear segregation between the study groups subjected to the BKD and western diets (2010 DGA and the TAD) across PC 1 (5.41%) with few outliers (\u003cstrong\u003eFig. 3\u003c/strong\u003e). However, the datasets for pre- and post-intervention stages were not clearly segregated for each of the study group in the respective PCA plot. Supervised partial least squared \u0026ndash; discriminant analysis (PLS-DA) score plot displayed a clearly clustered pattern for the BKD and western dietary regimens (2010 DGA and TAD) across PLS 1 (4.96%) whereas the respective pre- and post-intervention sample datasets were segregated across PLS 2 (2.93%). PLS-DA model was validated against the data overfitting with \u003cem\u003eQ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.69, while its predictive accuracy was verified with \u003cem\u003eR\u003csup\u003e2\u003c/sup\u003eX\u003c/em\u003e (0.28) and \u003cem\u003eR\u003csup\u003e2\u003c/sup\u003eY\u003c/em\u003e (0.96). In addition, Similar multivariate statistical patterns were evident for the urine metabolite profiles in positive ion mode \u003cstrong\u003e(Supplementary Fig. S.2)\u003c/strong\u003e. We conducted cross-validation analysis to ensure the robustness of the described PLS-DA models and prevent the potential data overfitting \u003cstrong\u003e(Supplementary Fig. S.3)\u003c/strong\u003e. Herein, the metabolite profiling data substantiates a multiparametric variability among the urine metabolite profiles highlighting the effects of short-term dietary interventions. Based on the PLS-DA model, we selected 54 significantly discriminant metabolites (VIP \u0026gt; 0.7, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) which contribute maximally toward the observed variance among the urine metabolite profiles from the three dietary intervention groups. Among the selected candidates, 34 metabolites were putatively characterized mainly as the derivatives of amino acids \u0026amp; peptides (3), benzoic acid \u0026amp; phenolic (8), fatty acid \u0026amp; lipids (17), and six miscellaneous compounds (\u003cstrong\u003eFig. 4\u003c/strong\u003e). The remaining 20 features were not characterized and labelled as non-identified (N.I). The LC-MS characteristics and the raw data peak intensities for each of the significantly discriminant metabolites are shown in \u003cstrong\u003esupplementary data 1\u003c/strong\u003e. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe showed the fold-change relative abundance of the significantly discriminant metabolites using the tabular heatmap (\u003cstrong\u003eFig. 4\u003c/strong\u003e). Most notably, the urine metabolite profile from participants subjected to the 2010 DGA and TAD displayed significantly higher post-intervention abundance of the amino acid \u0026amp; peptide derivatives (creatinine, L-isoleucyl-L-proline, and phenylacetylglutamine) compared to those enrolled for BKD. Compared to the western dietary regimens, participants enrolled in BKD displayed higher relative abundance of most benzoic acid \u0026amp; phenolic derivatives (enterodiol-glucuronide, enterolactone-3\u0026rsquo;-glucuronide, and gingerol) except argenteane in corresponding urinary extracts. Notably, the participant enrolled with 2010 DGA group also displayed a higher urinary abundance of few plant-derived phenolics including vanillic acid 4-O-sulfate, hippuric acid, and caffeic acid 4-O-sulfate. Most benzoic acid \u0026amp; phenolic derivatives were least abundant in the urinary samples from the participants in TAD group. Considering the fatty acid \u0026amp; lipid derivatives, a higher relative abundance of most steroidal glycosides was evident in the post-intervention urine samples representing the participants in TAD group followed by 2010 DGA. However, the acylcarnitine compounds (cis-5-tetradecenoylcarnitine and myristoylcarnitine) were significantly higher in the post- intervention urinary samples from the BKD participants. Most sphingolipid derivatives were significantly higher in the post-intervention urinary samples from BKD groups. A fatty acid alcohol 8-hydroxyfalcarinone was significantly higher in post- intervention urine samples from the western dietary (2010 DGA and TAD) groups. Miscellaneous categories of metabolites including uric acid, propenyl propyl disulfide, piperamide-C5:1, cichorioside G, and chondroitin were more abundant in the post- intervention urine samples for the participant groups enrolled in western dietary regimens compared to those with BKD. In contrast, Austalide G, a metabolite derived from the soy-food fermentation, was significantly higher in the post- intervention urine samples from the BKD group. Considering the non-identified (N.I) features, post- intervention urinary samples from the participants from enrolled with western dietary regimens displayed higher relative abundance of features ranging N.I.1 \u0026ndash; N.I.10, while those from the BKD groups were more abundant in N.I. 13-20.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMetabolic disorders related to oxidative stress and SCI can be effectively managed using the evidence-based dietary recommendations in which the higher abundance of antioxidant compounds ought to assuage cellular injuries mediated by free radicals. Herein, we examined the comparative effects of the short-term dietary interventions involving BKD, 2010 DGA, and TAD on oxidative stress \u0026amp; inflammatory indices\u0026nbsp;among the Korean adults with obesity. Further, we examined the urinary biomarkers to examine the health effects of these dietary interventions using the untargeted metabolomics approach. Previously, we have shown that BKD effectively improves the three major metabolic indices including the BMI, body fat percent, and blood lipid profiles\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e. We assume that such different outcomes after 4-weeks of dietary interventions are associated to their varying antioxidant compositions which are primarily derived from the phytochemical components. Dietary intakes of phytochemicals with antioxidant functions have been extensively reported to be inversely linked with metabolic disorders in several epidemiological studies\u003cstrong\u003e\u003csup\u003e9-15\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.1. Recommended diets (BKD and 2010 DGA) provided more antioxidants than TAD\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRecommended dietary regimens (BKD and 2010 DGA) had larger proportions of fruits, vegetables, legumes, whole grains \u0026amp; cereals, nuts, and unprocessed dairy with relatively lesser proportions of meat and poultry. However, a relatively larger portion of TAD included refined grains, processed meat, canned foods, and processed dairy ingredients\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e. Considering the varying levels of antioxidants in each of the dietary regimens, we examined the contents of antioxidant vitamins and polyphenols in each dietary regimen using \u003cem\u003ein silico\u003c/em\u003e methods \u003cstrong\u003e(Fig. 1)\u003c/strong\u003e. Higher relative abundance of vitamin A subtypes was evident for the recommended diets (BKD and 2010 DGA) which can be associated with their higher antioxidant potentials compared to TAD. Vitamin A and its various subtypes functions as provitamin carotenoid derivatives which inhibit the production of pro-inflammatory cytokines, prostaglandin E2, and nitric oxide in the body, and hence alleviate oxidative stress\u003cstrong\u003e\u003csup\u003e16,17\u003c/sup\u003e\u003c/strong\u003e. Higher titers of vitamin C and most vitamin E subtypes in recommended diets can be linked with their antioxidant potentials owing to their inhibitory activities against the production of pro-inflammatory cytokines like IL-4, IL-5, and IL-13\u003cstrong\u003e\u003csup\u003e18,19\u003c/sup\u003e\u003c/strong\u003e. Phenolic compounds\u0026nbsp;are often touted as nutraceuticals owing to their ROS-scavenging effects and are reported from a variety of plant-derived foods including herbs, vegetables, fruits, spices, and associated beverages\u003cstrong\u003e\u003csup\u003e20\u003c/sup\u003e\u003c/strong\u003e. BKD was characterized with higher relative levels of most flavonols (quercetin, kaempferol, isorhamnetin) except myricetin (2010 DGA \u0026gt; BKD) which can be attributed to a variety of plant-derived dietary menu components including onions, apples, and various green leaf and cruciferous family vegetables\u003cstrong\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/strong\u003e. Moreover, higher levels of isoflavones (daidzein, genistein, and glycitein) in the BKD compared to western diets is ascribed to the fermented soy-foods in Korean cuisines. Most other polyphenols (flavones, flavanones, flavan-3-ols, and anthocyanidins) were observed relatively higher in recommended diets (BKD and 2010 DGA) compared to TAD owing to the higher proportions of the plant-derived components\u003cstrong\u003e\u003csup\u003e22\u003c/sup\u003e\u003c/strong\u003e. We retrospectively examined the \u003cem\u003ein vitro\u003c/em\u003e antioxidant levels for the weekly menus provided in each dietary regimen to the study participants. Intriguingly, the sample extracts for BKD and 2010 DGA rich in plant-derived nutrients displayed significantly higher antioxidant activities as well as total phenolic (TPC) and total flavonoid (TFC) contents compared to TAD \u003cstrong\u003e(Fig. 2)\u003c/strong\u003e. Hence, the \u003cem\u003ein vitro\u003c/em\u003e antioxidant activities and TPC \u0026amp; TFC levels for each dietary regimen extracts substantiated their \u003cem\u003ein-silico\u003c/em\u003e micronutrient compositions. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2. Short-term dietary interventions had minimal impact on serum biomarkers of oxidative stress and inflammation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConsidering the effects of dietary interventions in serum biomarkers of oxidative stress \u0026amp; inflammation, MCP-1 levels of the participants significantly declined after intervention periods with all three diets. Notably, 2010 DGA was also found to have an improving effect on serum IL-6 levels. However, most of the serum indices of the oxidative stress (dROM, BAP, CRP) and inflammation (TNF-\u0026alpha;, IL-6, and IL-1\u0026beta;) did not varied significantly among the participants following the 4-weeks of three different dietary interventions. Here, we conjecture a possibility of data misinterpretation under the condition where even TAD could also work better for participants who were taking relatively unhealthier diet prior to their enrollment in the trial. This becomes more relevant considering the equivalent calorific values and rationalized macronutrient compositions provided under each dietary regimen with rationed serving portions. However, the undesired and long-term carry-over effects of the participants\u0026rsquo; usual dietary habits could not be completely ruled out. To overcome this limitation of interpreting the fragmentary results involving short-term dietary interventions, we investigated the complementary changes in the urinary metabolite profiles of the participants.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.3. Urine metabolomics unraveled subtle effects of short-term dietary interventions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUntargeted urine metabolomics data suggested a marked variation in the baseline metabolic fingerprints of the participants enrolled in Western (2010 DGA and TAD) and Korean (BKD) diets. We analyzed the significantly discriminant metabolites with known associations with the characteristic dietary intake and physiological functions linked with oxidative stress. Of the 54 significantly discriminant metabolites, 34 metabolites were identified while 20 remained non-identified, and therefore, we limited our discussion on the likely implications of the characterized metabolites. Participants subjected to western dietary regimens displayed higher urinary abundance of the amino acid \u0026amp; peptide derivatives compared to the BKD group. Especially, the peptides including creatinine and L-isoleucyl-L-Proline are often correlated with an increased dietary intake of red meat or the endogenous catabolism of proteins \u0026amp; muscle turnover in humans\u003cstrong\u003e\u003csup\u003e23,24\u003c/sup\u003e\u003c/strong\u003e. Higher urinary titers of phenylacetylglutamine are often linked with heightened ROS generation and metabolic disorder including obesity\u003cstrong\u003e\u003csup\u003e25,26\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBenzoic acid \u0026amp; polyphenol derivatives were relatively higher in the urine extracts from the participants enrolled with the recommended dietary regimens (BKD and 2010 DGA) compared to those with TAD. Higher abundance of phytoestrogen derivatives including the lignans (enterodiol-glucuronide and enterolactone 3\u0026rsquo;-glucuronide) in urine are the known biomarkers of whole grain (barley, rye, wheat) consumption and signifies their anti-inflammatory functions. In addition, flaxseeds, nuts, legumes, and sesame seeds also contain the considerably high proportions of dietary lignans which constitute an important portion of the traditional Korean diet as well as BKD\u003cstrong\u003e\u003csup\u003e27\u003c/sup\u003e\u003c/strong\u003e. In addition, the higher post- intervention levels of gingerol (a methoxyphenol compound) in urinary samples from the BKD group is ascribed to the introduction of herbs and spices including ginger in the diet. Gingerol is known for its antioxidant functions through inhibiting the release of pro-inflammatory cytokines in the blood\u003cstrong\u003e\u003csup\u003e28\u003c/sup\u003e\u003c/strong\u003e. We observed weak positive correlations between the polyphenol abundance in urine and the pro-inflammatory cytokines (TNF-\u0026alpha; and IL-6) in serum samples from BKD enrolled participants which suggest their possible role in inflammatory response \u003cstrong\u003e(Fig. 5)\u003c/strong\u003e. Participants subjected to the 2010 DGA showed higher urinary abundance of phenolic derivatives including vanillic acid 4-O sulfate, hippuric acid, and caffeic acid 4-O-sulfate which can be linked with the consumption of plant-derived components and whole grains. Hippuric acid levels in urine indicate their positive effects on antioxidant enzyme systems including CoQ (Co-enzyme Q10) and \u0026beta;-carotene in plasma. However, hippuric acid influences the inhibition of the endogenous antioxidative systems in humans which include Nrf2, thioredoxin, and superoxide dismutase, suggesting a balance between the blood and urinary levels of hippuric acid\u003cstrong\u003e\u003csup\u003e29\u003c/sup\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eUrinary abundance of fatty acid \u0026amp; lipid derivatives including most steroidal glycoside, acyl-carnitines, sterols, and terpene glycosides in the study group subjected to western diets (2010 DGA and TAD) were higher than those provided with BKD which can again be attributed to their different dietary compositions. Notably, elevated levels of urinary isobutyryl-L-carnitine and estrone (steroid lipid) are associated with higher consumption of red meat \u0026amp; animal products which constitute a major portion of western diets (www.foodb.ca). These lipid derivatives are known to induce oxidative stress through promoting the fatty acid oxidation and/or ROS generation in body\u003cstrong\u003e\u003csup\u003e30,31\u003c/sup\u003e\u003c/strong\u003e. Higher abundance of most steroidal- and terpene- glycosides in the urinary samples from participants enrolled with western diets suggest their higher dietary compositions and \u003cem\u003ein situ\u003c/em\u003e biotransformation. Most notably, cortolone-3-glucuronide, tetrahydroaldosterone-3-glucuronide, 11-\u0026beta;-hydroxyandosterone-3-glucuronide, ethyl-7-epi-12-hydroxyjasmonate glucoside, and androsterone sulfate are produced by the endocrine transformation of food-derived nutrients. Most fatty acid \u0026amp; lipid derivatives in urine samples displayed weak positive correlations with pro-inflammatory cytokines (TNF-\u0026alpha; and IL-1\u0026beta;) which suggest their role in oxidative stress \u003cstrong\u003e(Fig. 5)\u003c/strong\u003e. Urine samples from the participants enrolled in BKD were more abundant in acylcarnitine compounds (cis-5-tetradecenoylcarnitine and myristoylcarnitine) associated with fatty acid oxidation and ROS generation\u003cstrong\u003e\u003csup\u003e32,33\u003c/sup\u003e\u003c/strong\u003e. However, higher relative levels of sphingolipids in post- intervention urine samples from BKD group suggests their ameliorating effects against obesity related malfunctions\u003cstrong\u003e\u003csup\u003e34\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eElevated levels of uric acid in body, an endogenous antioxidant metabolite and a ROS-scavenger, indicate the systematic oxidative stress in humans\u003cstrong\u003e\u003csup\u003e35\u003c/sup\u003e\u003c/strong\u003e. As we enrolled the healthy participants in this study and subjected them to the short-term dietary interventions, the higher urinary levels of uric acid indicate that oxidative stress build-up following the course of western dietary (TAD \u0026gt; 2010 DGA) interventions, and not the BKD \u003cstrong\u003e(Fig. 5)\u003c/strong\u003e. Remaining metabolites including organic disulfide, piperamide, and cichorioside are the biomarkers of respective plant-derived food sources including onions, peppers \u0026amp; herbs, chicory, and endives served in all dietary regimens at various proportions (www.foodb.ca). Most of these compounds have a known antioxidant functions when taken as dietary component. Higher post- intervention abundance of Austalide G in urinary samples from participant subjected to BKD might be associated with unique inclusion of \u003cem\u003eAspergillus\u003c/em\u003e fermented food components. Austalide G is a polycyclic aromatic metabolite belonging to the chemical class of xanthenes which are reportedly produced by certain \u003cem\u003eAspergillus\u003c/em\u003e species however their health effects are largely unreported and hard to associate with oxidative stress. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering the strengths of this work, it\u0026rsquo;s arguably the first study focusing on the associations between the oxidative stress indices in serum, urinary metabolites, and dietary intervention comparing the BKD and western diets. The results may provide scientific evidence and rationale toward the establishment of novel dietary guidelines for the peoples with SCI and associated metabolic disorders. The present study involved crossover randomized controlled trials which could increase the statistical power and minimize the possible confounding effects even with the relatively small number of participants. However, we also acknowledge certain limitations such as the analysis of serum and urine samples following a brief period of storage. Though, the samples were quenched and stored under standard conditions (-80 ˚C), we assume the degradation of certain unstable compounds. Further, the study diets used in the trials do not represent the typical dietetics patterns \u0026amp; habits of either the Koreans and/or Americans \u003cem\u003eper se\u003c/em\u003e but rather designed based on the respective government guidelines and references.\u003c/p\u003e\n\u003cp\u003eIn summary, the present study explores the associations between short-term dietary interventions and their effects on oxidative stress biomarkers in serum and metabolic signatures in urine. The plant-derived components (fruits, vegetables, legumes, nuts, and whole grains) in the BKD and 2010 DGA likely alleviated the oxidative stress in the participants, compared to those subjected to the TAD. However, varying degrees of animal-derived components (red meat, poultry, and processed dairy products) and processed foods in western dietary regimens also influenced oxidative stress and related biomarkers in body fluids. Overall, the nutritional quality of diets isn\u0026apos;t solely reliant on including minimally processed whole food components and plant-derived antioxidants as observed for the recommended diets in this study. It\u0026apos;s equally important to consider the proportions of ultra-processed animal-derived products, as they can significantly contribute to the oxidative stress. Diets recommended for their fine balance of healthy dietary components, such as the BKD and 2010 DGA, are considered better in this regard compared to the TAD. Besides perceived complications involving sample preparations and data analysis, we believe that the untargeted urine metabolomics approach use in this study can be leveraged to measure the effects of short-term dietary interventions and their physiological impacts in clinical trials or population studies.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003e\u003cem\u003e4.1. Study subjects\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs depicted in the participant flow chart \u003cstrong\u003e(Fig. 6)\u003c/strong\u003e, all 148\u0026nbsp;participants affiliated to this study were voluntarily recruited through e-mail and poster advertisements\u0026nbsp;as described previously by Kim et al.\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e. Anthropometric measurement, blood test, and face-to-face survey were initially performed for screening among 132 attendees. The inclusion criteria of the trial were Korean adults aged 25–65 years with body mass index (BMI) ≥ 23 kg/m\u003csup\u003e2\u003c/sup\u003e and the blood low-density lipoprotein (LDL) cholesterol ≥120 mg/dL. Participants were excluded if they were smoking regularly and/or having the alcohol or substance abuse problems. We also excluded the participants which were consuming the prebiotics, probiotics, or antibiotics during the past 6 months before the onset of trials. Participants who reported a significant weight loss (≥ 10% of body weight) during the last 12 months before the trial period or those with any metabolic disorders including the cardiovascular diseases (CVD), diabetes, and kidney ailments were screened-out of the study. Sixty-one eligible individuals were selected for participation while only 54 of them completed the trials. The detailed information for this trial can be retrieved from our previous publications\u003cstrong\u003e\u003csup\u003e8, 36\u003c/sup\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eFollowing the trial period, our research staffs responsible for maintaining the personal information contacted every subject to seek their approval for further analyses of oxidative stress and inflammatory biomarkers in serum samples, and their urine metabolite profiling. Of the total participants, 48 participants voluntarily approved their serum and urine analyses. We had confirmed using power analysis that a total of 30 participants were sufficient to detect a mean difference of LDL cholesterol, which is one of the major indices of blood lipid profile, in our previous study (α = 0.05, β = 0.20)\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e. All the steps in this trial were approved by the Institutional Review Board of Seoul National University (IRB No. 1506/002-014 \u0026amp; IRB No. 1805/003-010). The first date of study participant registration was 11/09/2015, and informed consents were obtained from all the participants. The whole processes of this study were performed in accordance with the relevant guidelines and regulations. The trial was registered at the clinical research registry, Clinical Research Information Service (CRIS) in Korea, which is the primary registry of the World Health Organization international clinical trial registry platform (registration No. KCT0002437). This trial was registered at the clinical research registry, Clinical Research Information Service (CRIS) in Korea, which is the primary registry of the World Health Organization international clinical trial registry platform (registration No. KCT0002437; https://cris.nih.go.kr/cris/search/detailSearch.do?search_lang=E\u0026amp;focus=reset_12\u0026amp;search_page=L\u0026amp;pageSize=10\u0026amp;page=undefined\u0026amp;seq=8598\u0026amp;status=5\u0026amp;seq_group=8598).\u003c/p\u003e\n\u003cp\u003eThis study was conducted following the CONSORT 2010 guidelines for reporting randomized controlled trials\u003csup\u003e37\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.2. Design of study\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudy design was adapted from the previous trial for dietary interventions conducted by Schroeder et al.\u003cstrong\u003e\u003csup\u003e38\u003c/sup\u003e\u003c/strong\u003e with some modifications and described elsewhere in details\u003cstrong\u003e\u003csup\u003e8, 36\u003c/sup\u003e\u003c/strong\u003e. It was a crossover randomized controlled trial with three intervention periods conducted over a period of from 2015 to 2017. Participants were stratified based on sex, BMI, and blood LDL cholesterol levels, and were randomly assigned into 6 groups according to the order of the three different dietary patterns. This included dietary regimens with balanced Korean diet (BKD), diet recommended by the 2010 Dietary Guidelines for Americans (2010 DGA), and typical American diet (TAD) for 4 weeks each. During the intervention periods, the subjects had to consume only the dishes provided in the study diets. For all the participants, alcohol consumption was prohibited and maintaining the usual physical activity levels was strongly recommended to minimize the possible confounding effects. Between each intervention period, the subjects had a 2-week interval as washout period in which they were allowed to have their usual diets \u0026amp; lifestyle. At the beginning and the end of each intervention, the participants received physical examinations following a fasting period (≥ 8 hour) and provided the first morning urine samples. Metabolic indices including the BMI, body fat percent, waist circumference, blood pressure, blood triglyceride \u0026amp; cholesterol, blood glucose, and blood insulin levels were obtained from anthropometric measurement and blood test. We have previously reported the effects of these dietary regimens on the above-mentioned metabolic indices of the participants\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.3. Study diets\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDetails for dietary regimens including the BKD, 2010 DGA, and TAD and their components are described previously by Kim et al.\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e and Shin et al.\u003cstrong\u003e\u003csup\u003e36\u003c/sup\u003e\u003c/strong\u003e. Each standardized dietary regimen was designed to supply 2,000 kcal/day including the whole meals of breakfast, lunch, supper, and snack on a 7-day cycle. We have reported the calorific values for different nutritional components in each dietary regimen using the CAN-Pro 5.0 (Computer Aided Nutritional analysis program 5.0, The Korean Nutrition Society, Seoul, Korea) with each component analyzed according to the protocols from the Korean Food Standards Codex\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e. Each subject’s serving size was determined by the individual estimated energy requirement that was calculated based on the participant’s information for sex, age, body weight, height, and physical activity level using the formulas established by the Dietary Reference Intakes for Koreans (KDRI)\u003cstrong\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe BKD was developed based on the food guidance of the KDRIs and the dietary guidelines for Korean adults published by the Ministry of Health and Welfare, Republic of Korea\u003cstrong\u003e\u003csup\u003e39, 40\u003c/sup\u003e\u003c/strong\u003e. The ratios of the energy supply from macronutrients in BKD were as follows: 60–65% from carbohydrate, 20–25% from fat, and 15% from protein. It included multi-grain rice, soup, 120 g/day of kimchi, and side dishes containing relatively large amounts of vegetables and legume products with 15 g/day of fermented ingredients such as red pepper paste and soybean paste. The 2010 DGA was developed based on the sample menus recommended by the 2010 Dietary Guidelines for Americans issued by the US Department of Agriculture (USDA)\u003cstrong\u003e\u003csup\u003e41\u003c/sup\u003e\u003c/strong\u003e. The proportion of the energy supply from the carbohydrate was 55%, whereas those from the fat and protein were 30% and 15%, respectively. It contained whole grains, vegetables, fruits, lean meat, seafood, and skim milk. The TAD was developed based on the data from the ‘What We Eat in America’ published by the National Health and Nutrition Examination Survey, 2001–2004\u003cstrong\u003e\u003csup\u003e42\u003c/sup\u003e\u003c/strong\u003e. The ratios of energy supply from macronutrients were as follows: 50% from carbohydrate, 35% from fat, and 15% from protein. It was mainly consisted of refined grains and processed foods with relatively small amounts of vegetables, fruits, and lean meat. The sample menus for each study are introduced in our previous study\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.4. Antioxidant contents for the study diets\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo estimate the antioxidant contents and dietary TAC (vitamin C equivalents) for the three study diets, we associated the recipes of each regimen to the databases of antioxidant capacity, antioxidant vitamins, and flavonoid contents available for commonly consumed Korean foods\u003cstrong\u003e\u003csup\u003e43-46\u003c/sup\u003e\u003c/strong\u003e. The following antioxidants components of the study diets were included in the databases: retinol, carotenoids (α-carotene, β-carotene, lycopene, β-cryptoxanthin, lutein/zeaxanthin), vitamin C, tocopherols (α-tocopherol, β-tocopherol, γ-tocopherol, δ-tocopherol), flavonols (quercetin, kaempferol, isorhamnetin, myricetin), isoflavones (daidzein, genistein, glycitein), flavones (apigenin, luteolin), flavanones (eriodictyol, hesperetin, naringenin), flavan-3-ols (catechin, epicatechin, epigallocatechin), anthocyanidins (cyanidin, delphinidin, pelargonidin, malvidin, peonidin, petunidin), and proanthocyanidins (dimers, trimers, 4–6mers, 7–10mers, 10+ polymers). Vitamin A and vitamin E levels were calculated in retinol activity equivalent (RAE) and α-tocopherol equivalent (α-TE), respectively, using the following formulas:\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental analyses of the total phenolic contents (TPC), the total flavonoid contents (TFC), and overall antioxidant levels of the study diets were conducted using the methods adapted from\u003cstrong\u003e\u003csup\u003e47\u003c/sup\u003e\u003c/strong\u003e. Daily menus of each of the study diet were blended, homogenized, and stored immediately at -80℃ until analyses. Prior to the extraction, the samples were lyophilized using a freeze dryer (Bondiro, Ilshin Lab Co., Gyeonggi-do, Korea).\u0026nbsp;Eight grams of dried samples from each dietary menu were subjected to initial extraction with 70% ethanol (1:1, w/v) by incubating them at 300 rpm for 1 hour at 24°C. Subsequently, the samples were centrifuged (8000 rpm for 10 minutes at 4°C) and the resulting supernatants were filtered, and further dried using a speed vacuum concentrator (Hanil Scientific, Korea). The ethanolic extracts were then dissolved in water (1:1, w/v) and divided into ethyl acetate (EA) and butanol partitions. Both the EA and butanol fractions were isolated, dried using a speed vacuum concentrator, and subsequently reconstituted in their respective solvents to attain a final concentration of 10 mg/mL, before conducting bioactivity assays.\u0026nbsp;TPC, TFC, and the antioxidant levels (ABTS assay, DPPH assay, and FRAP assay) for the dietary sample extracts were determined using the method adapted from our previous stud\u003cstrong\u003e\u003csup\u003e48\u003c/sup\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.5. Analyses of oxidative stress and inflammatory markers in serum samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSerum samples were collected on the days of physical examination and were immediately stored at -80℃ until analyses. Oxidative stress biomarkers in serum including d-ROMs (diacron reactive oxygen metabolites) and BAP (biological antioxidant potential) were measured using an automatic chemistry analyzer (Diacron International s.r.l., Grosetto, Italy). The levels of inflammatory biomarkers in serum including C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1β (IL-1β), and monocyte chemoattractant protein-1 (MCP-1) were determined using Multiplex Luminex Assay (R\u0026amp;D Systems, Minneapolis, MN, USA).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.6. Metabolite profiling of urine samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePooled urine samples (400 μL) were extracted with 1 mL of absolute methanol and centrifuged at 13,000 rpm for 10 min at 4˚C. Supernatants were collected and dried using speed vacuum concentrator. Dry sample extracts were reconstituted in methanol at the concentration of 50 mg/mL and passed through 0.2 μm filter prior to the untargeted LC-MS analysis. Samples were on run on the UHPLC-LTQ-Orbitrap-MS/MS system coupled with Vanquish binary pump H system (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Reverse phase chromatographic separation of metabolites was performed on Phenomenex KINETEX\u003csup\u003e®\u003c/sup\u003e C18 column (100 mm × 2.1 mm, 1.7 μm particle size; Torrance, CA, USA). The mobile phase composed of water (solvent A) and acetonitrile (solvent B) with 0.1% formic acid in each. The 14 min gradient run program commenced with 5% solvent B for 1 min followed by its linear increase to 100% in next 9 min, maintained for 1 min, and re-equilibrated to initial condition (5% solvent B) in the final 3 min. The chromatographic run program maintained a constant flow rate of 0.3 mL/min with a sample injection volume of 5 μL and the column temperature at 40 °C. The tandem MS was performed on LTQ-Orbitrap-Velos Pro with ion-trap (IT) MS and heated ESI or HESI-II probe (Thermo Fisher Scientific). The MS parameters were fixed at probe heater temperature of 300 °C, capillary temperature of 350 °C, and the capillary voltages of 2.5 kV (-ESI) and 3.7 kV (+ESI). The samples were analyzed over a mass range (m/z) ranging from 150-100 under both positive and negative ESI modes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.7. Data processing and multivariate statistical analyses\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eChanges in oxidative stress and inflammatory indices in the serum samples for each dietary intervention group were investigated using a ‘mixed effect model’ adjusted for the dietary sequences and the washing period, which accounted for the crossover design. Post hoc analysis using Tukey’s HSD (honest significant difference) test was performed to examine the differences between the diets. The analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC, USA). A two-sided \u003cem\u003ep\u003c/em\u003e value \u0026lt; 0.05 was considered statistically significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe raw data files obtained from UHPLC-LTQ-Orbitrap-MS/MS system were converted to NetCDF (network Common Data Form) file formats. The converted files (\u003cem\u003e.cdf\u003c/em\u003e) were pre-processed for peak list alignment, peak detection, retention time (RT), normalized peak intensities, and accurate masses comparing their full scan nominal mass using the MetAlign\u003csup\u003eTM\u003c/sup\u003e software. The aligned data were further subjected to multivariate analyses to evaluate the class-wise variance in datasets and determining the significantly discriminant metabolites (VIP \u0026gt; 0.7, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) based on the PLS-DA model made with SIMCA-P+ (version 12.0, Umetrics, Umea, Sweden). The heat map expressions for the metabolite levels and corresponding pair-wise correlation (PASW statistics) were made on Microsoft Excel 2016.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.8. Metabolite annotations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe significantly discriminant features were classified based on the PLS-DA model for LC-MS datasets, and the metabolites were putatively identified based on their RT, mass to charge ratios (m/z), MS\u003csup\u003en\u003c/sup\u003e fragmentation patterns, and elemental compositions (error window\u0026lt;10 ppm) with corresponding standards, \u003cem\u003ein house\u003c/em\u003e libraries, associated web databases. The food derived and urinary metabolites were characterized using a variety of databases and associated literature sources, but all are represented together according to their levels at the beginning and the end of each intervention.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBKD, Balanced Korean Diet; 2010 DGA, 2010 Dietary Guidelines for Americans; TAD, Typical American Diet; TAC, Total Antioxidant Capacity; SCI, systemic chronic inflammations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eAll authors report no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Research Program for Agricultural Science and Technology Development, National Academy of Agricultural Science, Rural Development Administration, Republic of Korea (Project no. PJ013475022019) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2023R1A2C1004930).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: DS, DH, SAK, HJ, CHL; Data curation: DS, DH, YJP; Formal analysis: DS, DH, SAK, YJP; Funding acquisition: HJ, CHL; Investigation: DS, DH, HJ, DK, CHL; Methodology: DS, DH, SAK, HJ, CHL; Project administration: DH, HJ, CHL; Resources: DH, SAK, HJ; Software: DS, DK, DH, YJP; Supervision: HJ, CHL; Validation: HJ, CHL; Visualization: DS, YJP; Writing \u0026ndash; original draft: DS, DH, DK; Writing \u0026ndash; reviewing \u0026amp; editing: DS, DK, DH, HJ, CHL.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge many individuals who contributed at various steps of this study and manuscript writing. Kyungho Ha, Shinyoung Jun, Jiyoon Kim, Seoeun Ahn, and Subeen Kim contributed to conducting the dietary trial and anthropometric measurement procedures. ChangHyuk Hwang helped in metabolite profiling data curation. We also acknowledge the subjects who participated in the trial.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRup\u0026eacute;rez, A. I., Gil, A. \u0026amp; Aguilera, C. M. Genetics of oxidative stress in obesity. Int. J. Mol. Sci. 15, 3118\u0026ndash;3144 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFurman, D. \u003cem\u003eet al\u003c/em\u003e. Chronic inflammation in the etiology of disease across the life span. Nat. 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Food Chem. 66, 2694\u0026ndash;2703 (2018).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Balanced Korean diet, Western diet, oxidative stress, serum biomarkers, urine metabolomics, LC-MS/MS","lastPublishedDoi":"10.21203/rs.3.rs-4142606/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4142606/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDietary biomarkers in urine are elusive in the context of diet induced oxidative stress \u0026amp; inflammation. Previously, we reported the effects of short-term (4-week) dietary interventions for Balanced Korean Diet (BKD) and Western diets including 2010 Dietary Guidelines for Americans (2010 DGA) and Typical American Diets (TAD) on various metabolic indices among the Korean adults with obesity. In particular, this research investigates the impact of these interventions on biomarkers related to oxidative stress and inflammation in both serum and concurrent urine metabolomes. Each dietary regimen was \u003cem\u003ein silico\u003c/em\u003e and experimentally examined for their antioxidant levels. We assessed post-intervention variations in oxidative stress and inflammation biomarkers in serum, as well as the urine metabolite profiles for the participants (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;48). Antioxidant contents and associated total antioxidant capacity (TAC) were significantly higher for the recommended diets (BKD and 2010 DGA) compared to TAD (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Butanol extracts from recommended diets (BKD and 2010 DGA) showed significantly higher antioxidant activity compared to TAD in ABTS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), DPPH, and FRAP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) assays. Consistent results were observed in total phenolic and flavonoid contents, mirroring their respective antioxidant activities. Following the intervention period, oxidative stress \u0026amp; inflammation markers in serum varied marginally, however, the urine metabolite profiles were clearly demarcated for the BKD and Western dietary groups (PC1\u0026thinsp;=\u0026thinsp;5.41%). For BKD group, the pre- and post-intervention urine metabolite profiles were clearly segregated (PLS2\u0026thinsp;=\u0026thinsp;2.93%). Compared to TAD, urine extracts from the recommended dietary group showed higher abundance of benzoic acid \u0026amp; phenolic derivatives (VIP\u0026thinsp;\u0026gt;\u0026thinsp;0.7, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Metabolites associated with oxidative stress were observed higher in the urine samples from western dietary groups compared to BKD. Urine metabolomics data delineated the post-intervention effects of three dietary interventions which corroborates the respective findings for their effects on metabolic indices.\u003c/p\u003e","manuscriptTitle":"Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress \u0026amp; inflammation: a randomized controlled trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 17:40:54","doi":"10.21203/rs.3.rs-4142606/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-03T07:51:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-03T00:27:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"86810133760329972406577371929149414098","date":"2024-05-22T08:09:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-04T12:45:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"f365a28e-6be8-4c5b-89a1-1060d9701cd5","date":"2024-04-11T11:52:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-09T10:46:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-09T10:44:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-08T17:57:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-03T10:28:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-03-21T10:06:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e2ae4a6-6c3e-4f34-90f8-dd0d8c447852","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":30214840,"name":"Biological sciences/Biochemistry"},{"id":30214841,"name":"Biological sciences/Biological techniques"},{"id":30214842,"name":"Health sciences/Biomarkers"}],"tags":[],"updatedAt":"2024-06-24T05:56:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 17:40:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4142606","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4142606","identity":"rs-4142606","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}