Data in brief 27 (2019) 104787 Contents lists available at ScienceDirect Data in brief journal homepage: www.elsevier.com/locate/dib Data Article Data on the endogenous conversion of tyrosol into hydroxytyrosol in humans Anna Boronat a, b, Julian Mateus a, Natalia Soldevila-Domenech a, b, Merce  Guerra b, Jose Rodríguez-Morato b ~ oz d, e,  , Carlota Varon c, Daniel Mun Francina Barbosa , Juan Carlos Morales , Andreas Gaedigk h, f g Klaus Langohr a, i, Maria-Isabel Covas d, j, Clara Perez-Man~a k, l, Montserrat Fito d , e m , Rachel F. Tyndale , Rafael de la Torre a, b, e, * a Integrative Pharmacology and Systems Neuroscience Research Group, Neurosciences Research Program, IMIM-Institut Hospital del Mar d’Investigacions M ediques, Dr. Aiguader 88, 08003, Barcelona, Spain b Department of Experimental and Health Sciences, Universitat Pompeu Fabra (CEXS-UPF), Dr. Aiguader 80, 08003, Barcelona, Spain c Department of Pharmacy, Vall d’Hebron Barcelona Hospital Campus, Passeig de Vall d’Hebron 119-129, 08035, Barcelona, Spain d Cardiovascular Risk and Nutrition Research Group, IMIM (Hospital del Mar Research Institute), Dr. Aiguader 88, 08003, Barcelona, Spain e CIBER de Fisiopatología de la Obesidad y Nutricio n (CIBEROBN, CB06/03/028), Monforte de Lemos 3-5, 28029, Madrid, Spain f CAP Barceloneta, Parc Sanitari Rovira Virgili, Passeig Marítim, 25 08003, Barcelona, Spain g Department of Biochemistry and Molecular Pharmacology, Instituto de Parasitología y Biomedicina Lo pez Neyra, CSIC, PTS Granada, Avda. del Conocimiento, 17, 18016, Armilla, Granada, Spain h Division of Clinical Pharmacology, Toxicology, and Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, MO, USA i Department of Statistics and Operations Research, Polytechnic University of Catalonia, Barcelona, Spain j NUPROAS Handesbolag (NUPROAS HB), Nacka, Sweden k noma de Barcelona, Bellaterra, Spain School of Medicine, Universitat Auto l Hospital Universitari Germans Trias i Pujol (IGTP), Badalona, Spain m Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Departments of Pharmacology & Toxicology, and Psychiatry, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8, Canada DOI of original article: https://doi.org/10.1016/j.freeradbiomed.2019.08.032. * Corresponding author. Integrative Pharmacology and Systems Neuroscience Research Group, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. E-mail address: rtorre@imim.es (R. de la Torre). https://doi.org/10.1016/j.dib.2019.104787 2352-3409/© 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). 2 A. Boronat et al. / Data in brief 27 (2019) 104787 a r t i c l e i n f o a b s t r a c t Article history: Here we present new and original data on the endogenous con- Received 4 October 2019 version of tyrosol (Tyr) into hydroxytyrosol (OHTyr) in humans Received in revised form 30 October 2019 and its effects on the cardiovascular system. A randomized, Accepted 4 November 2019 crossover, controlled clinical trial was performed with individuals Available online 12 November 2019 at cardiovascular risk (n ¼ 33). They received white wine (WW) (females 1, males 2 standard drinks/day), WW plus Tyr capsules Keywords: (WW þ Tyr) (25mg Tyr capsule, one per WW drink), and water Tyrosol Hydroxytyrosol (control) ad libitum. Intervention periods were of 4 weeks pre- Endogenous conversion ceded by three-week wash-out periods. We assessed the conver- CYP2A6 sion of Tyr to OHTyr, its interaction with a polygenic activity score CYP2D6 (PAS) from CYP2A6 and CYP2D6 genotypes, and the effects on Cardiovascular risk cardiovascular risk markers. For further details and experimental findings please refer to the article “Cardiovascular benefits of tyrosol and its endogenous conversion into hydroxytyrosol in humans. A randomized, controlled trial” [1]. © 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/). Specifications Table Subject Nutrition Specific subject area Nutritional biochemistry and genotype interaction Type of data Tables, Figures, File text How data were acquired HPLC-MS-MS for Tyr and OHTyr Genotyping of allelic variants of CYP2A6 and CYP2D6 .A polygenic score activity was calculated Reactive hyperemia index, RHI for endothelial function Automated methods, HPLC, and ELISA for cardiovascular risk biomarkers Real-time polymerase chain reaction (PCR) for gene expression Data format Raw data collection and analysis Parameters for data collection Before and after each one of the three interventions with 1) white wine (WW) (females 1, males 2 standard drinks/day), 2) WW plus Tyr capsules (WW þ Tyr) (25mg Tyr capsule, one per WW drink), and 3) water (control) ad libitum. Intervention periods were of 4 weeks preceded by 3-weeks washout periods. Description of data collection Biological samples were collected and processed in the context of a randomized controlled intervention trial by field investigators Data source location Barcelona, Spain Data accessibility With the article Related research article Boronat A et al. Cardiovascular benefits of tyrosol and its endogenous conversion into hydroxytyrosol in humans. A randomized, controlled trial. Free Radical Biol Med, 2019 Aug 31;143:471-481. https://doi.org/10.1016/j.freeradbiomed.2019.08.032. Value of the Data  The presented data provide further details on how the polygenic activity score to evaluate the efficiency of Tyr to OHTyr conversion was generated.  This report describes the effects on cardiovascular biomarkers of an intervention with white wine and white wine enriched with Tyr.  They are useful to predict the effects of nutritional interventions rich in Tyr (olive oil, wine, beer …) considering the interaction with individual's genetic background.  The present data are of interest for the effects of Tyr alone and in the future within Tyr rich foods  These data can be used for the design of new nutraceutical based on Tyr ingestion in humans A. Boronat et al. / Data in brief 27 (2019) 104787 3 1. Data Thirty-three participants (21 men and 12 women) were randomly allocated to participate in a clinical trial, and 32 participants completed the trial. Initially, 192 subjects were assessed for eligibility, 157 were excluded for 1) not meeting the inclusion criteria, 2) refusing to participate, 3) taking medication non compatible with the interventions, 4) suffering from a coronary heart disease, 5) having undergone bariatric surgery, 6) intestinal alterations, 7) mobility problems, 8) chronic in- flammatory diseases, 9) dysregulated hypertension, 10) illicit drug consumption, 11) heavy alcohol consumption, and 12) hepatic alterations. The 33 volunteers were randomly allocated to receive the following treatments for 4 weeks: WW, WW þ Tyr and control intervention [1] (Fig. 1). Baseline characteristics of the participants are shown in Table 1. No dietary differences were observed among interventions (Table 2). Volunteers were genotyped for multiple allelic variants of CYP2A6 and CYP2D6 (Table 3). For each enzyme, an activity score was given to each volunteer according to the alleles identified (Table 4). A pooled polygenic activity score (PAS) was calculated by adding the two activity scores together. On the basis of PAS, 11 individuals were categorized as low (LA, PAS range: 1e2.5), 19 as normal (NA, PAS range: 3e4), and 2 as rapid (RA, PAS range ¼ 5) activity metabolizers. Due to their low number, RAs were excluded for analyses. Age and gender were equally distributed among the three groups. The conversion of Tyr into OHTyr was assessed by measuring OHTyr and Tyr urinary recovery following each treatment. No changes were observed in lipid biomarkers (Table 5) with exception of HDL- cholesterol (HDLc) which increased after WW and WW þ Tyr. HDL-c increased in a dose-dependent manner with the content of alcohol plus Tyr administered in all participants (p ¼ 0.027 for linear trend), among men (p ¼ 0.001 for linear trend), and with a borderline significance in the NA group (p ¼ 0.082) (Fig. 2). Endothelin-1 levels at the end of WW þ Tyr were lower than at the end of WW intervention (Table 6). Table 7 outlines the transcriptomic changes observed in genes related with endothelial function. Changes are grouped by sex and PAS. Fig. 3 compares the effects observed in WW and WW þ Tyr intervention. Fig. 1. Schema of the clinical trial. Intervention periods of 4 weeks. WO: wash-out period (3 weeks) without alcohol and following a low-phenolic content diet. WW (white wine): 2 glasses (270 mL, 27 g of alcohol, 2.8 mg of Tyr and 0.4 mg of OHTyr) for men, and 1 glass (135 mL, 13.5 mg, 1.4 mg of Tyr, and 0.2 mg of OHTyr) for women. WW þ Tyr (white wine plus tyrosol): 2 glasses of wine: 270 mL, 27 g of alcohol, 2.8 þ 50 mg of Tyr (2 capsules), and 0.4 mg of OHTyr for men, and 1 glass:135 mL, 13.5 g of alcohol, 1.4 mg þ 25 mg of Tyr (1 capsule), and 0.2 mg of OHTyr for women. 4 A. Boronat et al. / Data in brief 27 (2019) 104787 Table 1 Baseline characteristics of the participants. Variable Values Age, y 65.3 ± 6.2 Gender, n (%) Women 12 (36.4%) Men 21 (63.6%) BMI, kg/m2 32.6 ± 4.2 LDL cholesterol, mg/dL 118 ± 34.4 HDL cholesterol, mg/dL 50.2 ± 12.9 Total cholesterol, mg/dL 192 ± 39.3 Triglycerides, mg/dL 120 ± 72.2 Cardiovascular Risk factors, n (%) Current smokers 6 (18.2%) Family history of premature CHD 6 (19.4%) Obesity (BMI  25kg/m2) 32 (97.0%) Type 2 Diabetes 13 (39.4%) Hypertension 28 (84.8%) High LDL cholesterol (>130 mg/dL) 25 (75.6%) Low HDL cholesterol (<40 mg/dL for men or <50 mg/dL for women) 8 (24.2%) Medications, n (%) Alfa blockers 2 (6.1%) Beta blockers 6 (18.2%) ACE inhibitors 14 (42.4%) Angiotensin II receptor antagonists 11 (33.3%) Diuretics 13 (39.4%) Statins 16 (48.5%) Oral hypoglycemic drugs 12 (36.4%) Acetylsalicylic acid 10 (30.3%) Data presented as mean ± SD or n (%) (n ¼ 33). BMI, body mass index; LDL, low density lipoproteins; HDL, high density lipoproteins; CHD, coronary heart disease. 2. Experimental design, materials, and methods 2.1. Study design A randomized, controlled, clinical trial with 33 individuals at cardiovascular risk (21 men and 12 women) was performed (Fig. 1). Inclusion criteria were to be at high risk for coronary heart disease (CHD) with 3 or more risk factors including: current smoking (>1 cig/day during the last month), hypertension (140/90 mmHg or antihypertensive medication), high LDL cholesterol (>130 mg/dl or lipid-lowering therapy), low HDL-cholesterol (40 mg/dl in men and 50 mg/dl in women), over- weight/obesity (body mass index 25 kg/m2), a family history of premature CHD, and/or type II dia- betes treated with oral hypoglycemic agents; and to have a social or recreational use of ethanol/wine consumption at least once during lifetime. Exclusion criteria were participants with a history of car- diovascular disease or severe chronic illness, chronic inflammatory diseases, BMI > 40 kg/m2, suffered from any severe illness or undergone major surgery in the last three months prior to the clinical trial, an alcohol consumption exceeding 8 units or 80 g per day, a history of alcohol hypersensitivity/intoler- ance, illicit drug consumption, intake of antioxidant supplement(s), the taking of sedative drugs that could potentially interact with alcohol, multiple allergies or intestinal diseases, being vegetarian of following special diets, a history of food allergies or intolerances, illiteracy, and any condition that limited mobility making trial visits impossible or worsening adherence to treatments. Participants were asked to follow a controlled diet with a moderate content of antioxidants and to abstain of any alcoholic drinks (except in the framework of treatment allocations) thorough the trial. The consumption of certain food was limited to a maximum of 1) vegetables (including pulses): one serving/day, 2) fruits (or juices): 2 pieces/day, 3) ordinary olive oil: maximum 25 mL/day, 4) drinks containing xanthines (coffee, tea, cola, energy drinks …): maximum 3 cups/day, 5) chocolate: A. Boronat et al. / Data in brief 27 (2019) 104787 5 Table 2 Energy, nutrients, and fiber at the beginning and at the end of the clinical trial. Variable Treatment P* Control P WW P WWþTYR P Energy, kcal/day Baseline 1695 ± 446 1663 ± 421 1624 ± 370 NS 12-week 1643 ± 361 0.616 1650 ± 354 0.868 1737 ± 450 0.082 HC, % energy Baseline 38.2 ± 8.6 40.2 ± 6.4 38.8 ± 6.3 NS 12-week 38.3 ± 7.3 0.906 37.6 ± 7.7 0.095 37.8 ± 7.5 0.360 HC, grams Baseline 159 ± 48 165± 43 157 ± 38 NS 12-week 156 ± 41 0.811 153 ± 40 0.209 163 ± 45 0.532 Protein, % energy Baseline 20.9 ± 4.0 19.2 ± 3.0 21.5 ± 4.5 NS 12-week 21.2 ± 4.1 0.578 19.5 ± 4.8 0.028 19.0± 3.9 0.142 Protein, grams Baseline 88 ± 25 79 ± 19 86 ± 24 NS 12-week 87 ± 25 0.939 81 ± 30 0.651 82 ± 23 0.184 Total Fat, % energy Baseline 40.7 ± 7.5 40.3 ± 6.2 39.2 ± 6.6 NS 12-week 40.2 ± 7.2 0.625 36.7 ± 9.0 0.496 38.6 ± 6.3 0.230 Total Fat, grams Baseline 78 ± 29 76 ± 28 72 ± 24 NS 12-week 74 ± 23 0.489 68 ± 24 0.015 76± 28 0.809 SFA, % energy Baseline 11.4± 3.8 10.1 ± 3.0 11.4 ± 4.2 NS 12-week 10.7 ± 3.7 0.526 10.1 ± 3.9 0.953 10.4 ± 3.7 0.272 SFA, grams Baseline 22 ± 12 19 ± 9 21 ± 12 NS 12-week 20 ± 10 0.428 19 ± 10 0.873 21 ± 11 0.855 MUFA,% energy Baseline 19.8 ± 5.0 19.7 ± 4.2 18.6 ± 5.0 NS 12-week 20.1 ± 4.2 0.893 18.4 ± 5.1 0.177 19.6 ± 3.5 0.172 MUFA, grams Baseline 53.3 ± 21.0 53.8 ± 15.5 53.0 ± 16.6 NS 12-week 51.9 ± 21.2 0.475 46.5 ± 13.3 0.274 50.0 ± 14.3 0.054 PUFA, % energy Baseline 6.1 ± 2.6 6.8 ± 2.5 6.0 ± 2.1 NS 12-week 5.9 ± 2.3 0.697 5.2 ± 2.1 0.222 5.4 ± 1.9 0.179 PUFA, grams Baseline 12 ± 6 13 ± 8 11 ± 4 NS 12-week 11 ± 7 0.901 10 ± 5 0.025 11 ± 6 0.960 Fiber, g/day Baseline 20 ± 7 23 ± 11 20 ± 8 NS 12-week 20 ± 8 0.894 23 ± 11 0.848 21 ± 9 0.408 Dietary data is expressed as mean ± SD (N ¼ 32). HC, carbohydrates; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids. P Intra-treatment comparisons by Student's t-test. *P value for ANOVA repeated measures adjusted by age and sex. maximum one piece (small 15 gr)/day, 6) nuts: maximum 30 g (a small handful)/week, and 7) fish: maximum 3 times per week (150 g/serving). During the control intervention participants were allowed to only drink water (no alcohol. wine or supplemented Tyr or OHTyr). The reason for different WW doses for men and women was in order to follow the American Heart Association (AHA) guidelines, which limit alcohol consumption to one drink in women and two in men, preferably taken at meals [2]. The doses of wine administered are within those recommended by the AHA. A 24 h food recall was performed to assess dietary intake before and after each intervention period. Physical activity was recorded at the beginning and end of the clinical trial and assessed by the Minnesota Leisure Time Physical Activity Questionnaire, validated for the Spanish population [3]. 6 A. Boronat et al. / Data in brief 27 (2019) 104787 Table 3 Characteristics of CYP2A6 and CYP2D6 SNPs tested. Tested Allelic Variants Reference Number Nucleotide Substitution Amino acid substitution TaqMan Assay ID CYP2A6 rs1801272 479T > A Leu160His C_27861808_60 rs28399433 - 48T > G Upstream C_30634332_10 CYP2D6 rs1135840 4181G > C Ser486Thr C_27102414_10 rs16947 2851C > T Arg296Cys C_27102425_10 rs3892097 1847G > A Intron Variant C_27102431_DO rs5030656 2616_2618delAAG Lys281del C_32407229_60 rs1065852 100C > T Pro34Ser C_11484460_40 rs769258 31G > A Val11Met C_27102444_80 rs28371725 2989G > A Intron Variant C_34816116_20 Table 4 Activity score assigned to each tested variant in the PAS model. Tested Allelic Variants Functional consequence Activity score Defining SNP CYP2A6 *2 No function 0 479T > A *4 No expression 0 Gene deletion *9 Decreased þ0.5 - 48T > G *12 Decreased þ0.5 Hybrid allele with CYP2A7 *1xN Increased þ2 Multiple copies CYP2D6 *2 Normal þ1 2851C > T 4181 G > C *4 No function 0 1847 G > Aa *5 No expression 0 Gene deletion *9 Decreased þ0.5 2616 del AGG *10 Decreased þ0.5 100C > T 4181 G > C *35 Normal þ1 31G > A 2851C > T 4181 G > C *41 Decreased þ0.5 2989 G > A 2851C > T 4181 G > C *1xN Increased þ2 Multiple copies *2xN *35xN a *4 sub-alleles can commonly present other SNPs such as 100C > T, 4181 G > C and/or 2851C > T. Table 5 Changes in lipid and inflammatory biomarkers (mg/dL). Interventions Control WW WW þ TYR P value for WW þ Tyr vs Control vs WW Total Cholesterol 1.8 ± 12.5 2.9 ± 21.8 7.7 ± 24.4 0.665 0.753 LDL cholesterol 1.0 ± 14.1 0.1 ± 17.8 4.7 ± 22.3 0.511 0.761 Triglycerides 14.7 ± 62.0 6.0 ± 25.9 0.9 ± 25.7 0.290 0.788 Glucose 0.9 ± 13.4 2.7 ± 10.3 2.6 ± 12.0 0.849 0.999 hsCRP 0.2 ± 1.3 0.02 ± 0.3 0.01 ± 0.2 0.443 0.516 Changes expressed as mean ± SD (N ¼ 32). LDL, low density lipoprotein; hsCRP, high sensitivity C reactive protein. ANOVA adjusted by age, sex and smoking habits, LDL cholesterol at the beginning of the clinical trial, and baseline levels. A general physical examination, and routine urine, blood chemical and hematological analyses, were performed at the beginning and end of the trial. Blood and 24h-urine samples were collected at fasting state before and after each intervention period. Blood was collected into 10 mL tubes containing EDTA and centrifuged (1700g, 15 min, 4  C), and plasma and buffy coat samples were then isolated. Pe- ripheral blood mononuclear cells (PBMC) were isolated using a Vacutainer Cell Preparation Tube A. Boronat et al. / Data in brief 27 (2019) 104787 7 Fig. 2. Changes in HDL cholesterol (HDL-c) after interventions. Change in HDL-c compared to the baseline of the intervention expressed as mean and SD in all participants (A), only men (B) and only normal activity metabolizers (C). ANOVA adjusted by age, sex and smoking habits, LDL cholesterol at the beginning of the clinical trial, and baseline levels * P < 0,05; **P < 0,01. 8 A. Boronat et al. / Data in brief 27 (2019) 104787 Table 6 Endothelin concentrations (ng/dL) after interventions. Interventions Control WW WW þ TYR P value for WW þ Tyr vs Control vs WW All participants 2.15 ± 0.90 2.33 ± 1.07 2.03 ± 0.82 0.572 0.031 Women 2.38 ± 1.07 2.57 ± 1.11 2.12 ± 0.81 0.479 0.108 Men 2.01 ± 0.80 2.16 ± 1.08 1.99 ± 0.87 0.990 0.463 Genotype interaction LA 1.93 ± 0.69 2.25 ± 0.96 1.89 ± 0.72 0.981 0.203 NA 2.24 ± 0.95 2.48 ± 1.32 2.13 ± 1.07 0.747 0.068 Endothelin-1 concentrations are expressed as mean ± SD (N ¼ 32). WW, white wine; WW þ Tyr, white wine plus tyrosol (Tyr) capsules; LA, low activity group metabolizers; NA, normal activity group metabolizers. ANOVA adjusted by age, sex, smoking, acetylsalicylic acid consumption, and baseline levels. *P < 0.05 versus its baseline; P value, significance for inter-intervention comparisons. (CPT™) and kept for RNA extraction. Plasma, urine, and PBMC samples were frozen at 80  C until analysis. Genomic DNA isolation from buffy coat was performed with QIAamp DNA Blood Midi Kit (Qiagen, Dusseldorf, Germany). 2.2. Tyr and OHTyr metabolites analysis The urinary concentrations of Tyr and OHTyr metabolites were determined from samples collected before and after each intervention following a validated methodology [4]. Briefly, 0.5 mL of urine was diluted with 0.5 mL of purified water, spiked with 10 mL of internal standard mixture (containing 10 mg/mL of 3-(4-hydroxyphenyl)-1-propanol, 3-(4-hydroxyphenyl)-1-propanol glucuronide and 10 mg/ mL HT-10 -O-sulfate) and stabilized with 1 mL of phosphoric acid 4%. Thereafter, samples went under a solid-phase extraction using Oasis HLB columns 3 mL, 60-mg cartridges from Waters Corporation (Milford, MA USA). First, samples were loaded into cartridges then washed with 2 mL of purified water. Thereafter, the compounds of interest were eluted from the cartridge with 2 mL of pure methanol. The methanol extracts were then evaporated until dryness under a stream of nitrogen (29  C, 10e15 psi). Finally, the dried extracts were reconstituted with a mixture of mobile phases (95% A and 5% B v/v), transferred into HPLC microvials, and analyzed using LC-MS/MS. To prepare blank samples and cali- bration curves, urine from volunteers after consuming a diet poor in Tyr and OHTyr- Tyr and OHTyr metabolite concentrations were below quantification limits in these blank samples. Blank urine was spiked with increasing concentrations of the metabolites of interest, and then processed in the same manner as samples (described above). Identification and quantification of the metabolites was per- formed using an Agilent 1200 series HPLC system coupled to a triple quadrupole (6410 Triple Quad LC/MS) mass spectrometer with an electrospray interface from Agilent Technologies (Santa Clara, CA, USA). For the chromatographic separation, an Acquity UPLC®BEH C18 column (100 mm  3.0 mm i.d., 1.7 mm particle size) from Waters Corporation (Milford, MA, USA) was used at 40  C. The composition of mobile phase A was 0.01% (v/v) formic acid in water, and mobile phase B was acetonitrile with 0.01% (v/v) of formic acid. Injection volume was 10 mL and the flow rate was set at 0.25 mL/min. The ion source operated in negative ionization for 27 minutes. Finally, urinary concentrations of each metabolite were standardized with the total urinary excretion volume to obtain the total recovery of each metabolite. Quantified Tyr metabolites included Tyr -4-sulfate and Tyr -4-glucuronide. OHTyr metabolites quantified were OHTyr -3-sulfate, OHTyr-4-sulfate, OHTyr-acetate-3-sulfate, OHTyr-3- glucuronide, OHTyr-4-glucuronide, and homovanillyl alcohol (HVAL)-4-glucuronide. Total Tyr and total OHTyr correspond to the molar sum of their respective quantified metabolites. 2.3. Genotyping Volunteers were genotyped for multiple allelic variants of CYP2A6 and CYP2D6 using TaqMan genotyping assays (Applied Biosystems, Foster City, CA, USA) SNP genotyping was performed with a A. Boronat et al. / Data in brief 27 (2019) 104787 9 Table 7 Transcriptomic changes (% change versus baseline) after interventions. Intervention Control WW WW þ Tyr P value for WW þ Tyr vs Control vs WW CD40L All participants 8.9 ± 60.6 21.7 ± 62.3 26.8 ± 34.2y 0.042 0.003 Women 10.7 ± 75.4 28.8 ± 59.5 29.9 ± 33.7* 0.743 0.063 Men 24.6 ± 47.2 20.4 ± 66.2 25.5 ± 35.8* 0.016 0.024 Genotype interaction LA 4.8 ± 66.7 11.1 ± 59.8 17.1 ± 35.6 0.874 0.514 NA 20.1 ± 60.0 16.7. ± 56.5 28.2 ± 33.9y 0.011 0.020 P65/RElA All participants 1.1 ± 0.5 1.18 ± 0.5 0.9 ± 0.30 0.229 0.048 Women 7.6 ± 54.0 26.9 ± 63.3 16.9 ± 29.8 0.896 0.089 Men 22.9 ± 41.9 13.4 ± 48.2 2.2 ± 28.6 0.157 0.484 Genotype interaction LA 16.7 ± 63.5 6.3 ± 45.3 3.0 ± 43.4 0.584 0.886 NA 6.7 ± 41.1 22.5 ± 58.3 -.12,5 ± 20.9 0.414 0.054 CFH All participants 19.8 ± 57.6 28.8 ± 56.5* 9.1 ± 51.5 0.115 0.025 Women 9.2 ± 57.5 48.4 ± 51.9* 11.9 ± 63.2 0.994 0.334 Men 27.9 ± 59.5 16.6 ± 58.9 18.1 ± 40.9* 0.013 0.048 Genotype interaction LA 21.4 ± 77.7 35.2 ± 74.8 16.7 ± 29.5 0.359 0.150 NA 22.4 ± 46.9 22.6 ± 45.1 0.0 ± 62.8 0.438 0.433 iNOS All participants 5.0 ± 38.3 36.7 ± 82.6* 19.7 ± 62.4 0.734 0.007 Women 16.9 ± 28.8 56.1 ± 109.4 2.3 ± 24.1 0.897 0.303 Men 2.7 ± 41.2 29.9 ± 71.3 27.5 ± 70.4 0.470 0.019 Genotype interaction LA 6.3 ± 36.2 17.0 ± 66.9 33.0 ± 52.4 0.299 0.091 NA 4.7 ± 38.1 46.2 ± 26.7 10.4 ± 69.6 0.996 0.080 eNOS All participants 11.7 ± 65.6 34.9 ± 72.2* 8.2 ± 50.2 0.509 0.035 Women 13.2 ± 71.7 42.2 ± 42.1* 14.7 ± 48.8 0.997 0.565 Men 12.9 ± 65.5 26.4 ± 83.7 20.5 ± 49.4 0.351 0.115 Genotype interaction LA 4.8 ± 54.9 28.9 ± 77.8 16.2 ± 62.6 0.910 0.344 NA 28.3 ± 72.9 34.8 ± 74.6 0.2 ± 44.8 0.536 0.334 VEGFA All participants 14.3 ± 58.1 32.2 ± 69.7* 6.2 ± 45.2 0.398 0.045 Women 12.6 ± 59.0 30.4 ± 68.9 3.0 ± 61.6 0.533 0.112 Men 9.4 ± 55.4 26.2 ± 67.9 10.0 ± 36.3* 0.870 0.500 Genotype interaction LA 26.3 ± 65.9 19.4 ± 75.6 3.0 ± 40.6 0.497 0.665 NA 7,7 ± 57.6 27.7 ± 60.1 1.1 ± 46.5 0.896 0.256 Changes are expressed as mean ± SD (N ¼ 32). WW, white wine; WW þ Tyr, white wine plus tyrosol (Tyr) capsules; LA, low activity group metabolizers; NA, normal activity group metabolizers. CD40L, CD40 ligand; CFH, complement factor H; eNOS, endothelial nitric oxide synthase 3; iNOS, inducible nitric oxide synthase; p65/RELA, transcription factor p65 (RELA); VEGFA, vascular endothelial growth factor. ANOVA adjusted by age and sex. *P < 0.05, yP < 0.001 versus its baseline; P value, significance for inter-intervention comparisons. TaqMan allelic discrimination system (Applied Biosystems, Foster City, CA, USA). Copy-number vari- ations (CYP2A6 *4, *12, and CYP2D6 *5, and duplications) were analyzed with specific copy number assays. When these allelic variants were not detected, a designation of *1 (e.g. wildtype) was assigned. 2.3.1. SNP genotyping Table 3 shows the characteristics of CYP2A6 and CYP2D6 tested allelic variants. The following SNPs were analyzed: for CYP2A6 *2 and *9, and for CYP2D6 *2, *4, *9, *10, *35, and *41. TaqMan SNP geno- typing assay were used, which included FAM™ and VIC™ dye-labeled TaqMan pre-designed proves 10 A. Boronat et al. / Data in brief 27 (2019) 104787 Fig. 3. Comparison of the effects of white wine (WW) (blue) versus those of white wine plus tyrosol (WW þ Tyr) (Green), CD40L, CD40 ligand; NF-KB, nuclear factor kappa B; CFH, complement factor H; iNOS, inducible nitric oxide synthase; eNOS, endothelial nitric oxide synthase. specifics for each SNP. PCR was performed in a QuantStudio™ 12K Flex Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). Reactions were prepared with 10 ng of DNA, 0.25 mL of TaqMan SNP Genotyping Assay, and 2.5 mL of TaqMan Genotyping Master Mix (Applied Biosystems, Foster City, CA, USA). SNP determination was made using allelic discrimination plots with TaqMan Genotyper Software (Applied Biosystems, Foster City, CA, USA). 2.4. Copy number variation (CNV) detection analysis TaqMan CNV assays were used to analyze CYP2A6 allelic variants *4, *12 (Hs07545274_cn; Hs07545275_cn), and CYP2D6 allelic variants *5 (deletion),*1xN, *2xN, and *35xN (Hs00010001_cn). Real time qPCR was performed using the specific TaqMan assays. Quantitative PCR was performed in QuantStudio™ 12K Flex Real-Time PCR System (Applied Biosystems, Foster City, USA). Reaction was carried in 384-well plates with a mixture of TaqMan Master Mix (Applied Biosystems, Foster City, CA, USA), CNV assays, 10 ng DNA/well and RNase P as reference (Applied Biosystems, Foster City, CA, USA). Reactions were performed in duplicates. Copy number calls were made with the Expression Suite Software v1.0.3 (Applied Biosystems, Foster City, CA USA). CYP2D6 gene duplications as previously described [5]. First, a specific 6.6 kb long piece of CYP2D6 was amplified. Second, a 3.5 kb fragment was amplified from alleles carrying gene duplications. Every duplication-positive sample was further analyzed using two long-range PCR reactions that allow to discriminate among CYP2D6*1xN, *2xN, and *4xN duplications to determine allele-defining SNPs. 2.5. Polygenic activity score Tested allelic variants were categorized into: those with no-function (CYP2A6 *2, *4; CYP2D6 *4,*5); decreased function (CYP2A6 *9,*12; CYP2D6 *9,*10,*11); normal function (CYP2A6 *1; CYP2D6 *1,*2,*35); and increased function (CYP2A6 *1xN; CYP2D6 *1xN,*2xN,*35xN). A score of 0, 0.5, 1 or 2 was assigned for the presence of each allele (Table 4). For each enzyme, an activity score was given to each volunteer according to the identified alleles and classified as detailed above based on the method described by Gaedigk et al. [6]. A pooled polygenic activity score (PAS) was calculated by adding together the activity A. Boronat et al. / Data in brief 27 (2019) 104787 11 scores of both enzymes. Finally, according to their PAS, individuals were placed into three groups of predicted activity: low (LA), normal (NA), and rapid activity (RA) groups. 2.6. Endothelial function measurement Endothelial function was assessed before and after interventions by monitoring endothelium- mediated changes (reactive hyperemia index, RHI) in the digital pulse waveform, known as the Pe- ripheral Arterial Tone (PAT) signal (EndoPAT 2000; Itamar Medical Inc., Caesarea, Israel). Specially designed finger probes were placed on the middle finger of each subject's dominant hand. The probes comprised a system of inflatable latex air cuffs connected by pneumatic tubes to an inflating device controlled through a computer algorithm. A constant counter pressure (pre-determined by baseline DBP) was applied through the air cushions. Pulsatile volume changes of the distal digit induced pressure alterations in the finger cuff, which were sensed by pressure transducers and transmitted to and recorded by the EndoPAT 2000 device. EndoPAT 2000 also provides the augmentation index (AI), a measurement of arterial stiffness via pulse-wave analysis, which was normalized to 75 bpm heart rate. Measurements were performed by a trained professional with the participants in resting supine conditions, in a quiet room at a constant temperature after 10 minutes of stabilization. Hyperemic reactivity index measured by EndoPAT 2000 has been shown to predict cardiovascular disease [7]. 2.7. Gene expression measurements On the basis of their relationship with endothelial health and atherosclerosis, and the available data of gene expression response after VOO ingestion several candidate genes were selected. Candidate genes were AKT serine/threonine kinase 2 (AKT2), arachidonate 5-lipoxygenase (ALOX5), CD40 ligand (CD40L), complement factor H (CFH), endothelial nitric oxide synthase 3 (eNOS), endothelial plas- minogen activator inhibitor (SERPINE1), inducible nitric oxide synthase (iNOS), interferon gamma (IFNG), interleukins (IL)1B (IL1B) and 6 (IL6), matrix metalloproteinases (MMP) 2 (MMP2) and 9 (MMP9), mitogen-activated protein kinase 14 (MAPK14), monocyte chemoattractant protein 1 (MCP1), nuclear factor (NF) (erythroid-derived 2)-like 2 (NEF2L2), NF-kappa B inhibitor alpha (NFKBIA), platelet-derived growth factor subunit B (PDGFB), peroxisome proliferator-activated receptor alpha (PPARɑ), sirtuins (SIRT) 1 (SIRT1), 2 (SIRT2), and 6 (SIRT6), transcription factor p65 (p65/RELA), tumor necrosis factor alpha (TNF-ɑ), and vascular endothelial growth factor (VEGFA). Glyceraldehyde 3-phosphate dehy- drogenase (GAPDH) and B-actin were used as endogenous controls to correct changes in gene expression. Isolation of RNA from PBMC was performed with the RNeasy Mini Kit (Qiagen, Duesseldorf, Germany). DNA complementary conversion was then carried out with the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA). Gene expression was measured, before and after interventions, by a real-time polymerase chain reaction with a QuantStudio™ 12K Flex Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and SYBR Green dye-based analysis. Samples were analyzed in duplicate. Results were obtained with the Expression Suite Software v1.0.3 (Applied Biosystems, Foster City, CA, USA). Changes in gene expression were assessed first by calculating the relative quantification, applying the 2eDDCT of each sample. Thereafter, the fold change of each intervention was extracted by calculating the ratio between values at the end and at baseline of each intervention period. 2.8. Sample size and power analyses A total sample of 32 participants would allow at least 80% power to detect a statistically significant difference among groups of 0.205 units in the RHI measurement, assuming a dropout rate of 5% and type I error of 0.005 (2-sided). The standard deviation of the measurement was assumed 0.4 [7]. 2.9. Statistical analyses Normality of continuous variables was assessed by normal probability plots and data were log transformed when required. Intra-treatment comparisons were assessed by Student's t-test for paired 12 A. Boronat et al. / Data in brief 27 (2019) 104787 samples. Comparisons among treatments were made by an ANOVA for repeated measures and adjusted by age, gender, smoking, AAS medication, and baseline concentrations. In the case of lipids an additional adjustment for LDL cholesterol values at the beginning of the clinical trial was performed. A general lineal model was used to assess linear and quadratic trends. For the post-hoc pairwise com- parison, the Tuckey test was used. Statistical analyses were performed with R (R Foundation for Sta- tistical Computing, Vienna, Austria). version 3.0.2., and R package multcomp. Significance was defined as p < 0.05. Acknowledgments This research was funded by the Instituto de Salud Carlos III (PI14/00072) and by grants from DIUE of Generalitat de Catalunya (2107 SGR 138). AB is recipient of a PFIS predoctoral fellowship from the Instituto Carlos III (PFIS-FI16/00106). JM is recipient of a Rio Hortega fellowship from the Instituto Carlos III (CM17/00024). NS is recipient of fellowship from Centro de Informacio  n Cerveza y Salud, Fundacio  n Manuel de Oya. CIBER de Fisiopatología de la Obesidad y Nutricio  n (CIBEROBN) is an initiative of the ISCIII, Madrid, Spain. RFT is a recipient of a Canada Research Chair in Pharmacoge- nomics and her work is supported by Canadian Institutes of Health Research (FDN-154294). Conflict of Interest RFT has been consulted by Quinn Emanuel, Ethismos and Apotex on unrelated topics. The other authors declare they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.dib.2019.104787. References [1] A. Boronat, J. Mateus, N. Soldevila-Domenech, M. Guerra, J. Rodríguez-Morato , C. Varo n, D. Mun ~ oz, F. Barbosa, J.C. Morales, K. Langohr, M.I. Covas, C. Pe rez-Man~a, M. Fito , R.F. Tyndale, R. de la Torre, Cardiovascular benefits of tyrosol and its endogenous conversion into hydroxytyrosol in humans, A randomized, controlled trial, Free Radic. Biol. Med. 143 (2019 Aug 31) 471e481, https://doi.org/10.1016/j.freeradbiomed.2019.08.032. [2] A.H. Lichtenstein, L.J. Appel, M. Brands, M. Carnethon, S. Daniels, H.A. Franch, et al., Summary of American heart association diet and lifestyle recommendations revision 2006, Arterioscler. Thromb. Vasc. Biol. 26 (2006) 2186e2191, https://doi.org/ 10.1161/01.ATV.0000238352.25222.5e. [3] R. Elosua, M. Garcia, A. Aguilar, L. Molina, M.I. Covas, J. Marrugat, Validation of the Minnesota leisure time physical activity questionnaire in Spanish women, Med. Sci. Sport. Exerc. 32 (2000) 1431e1437, https://doi.org/10.1097/00005768- 200008000-00011. [4] A. Kotronoulas, N. Pizarro, A. Serra, P. Robledo, J. Joglar, L. Rubio , A. Hernae z, C. Tormos, M.J. Motilva, M. Fito  , M.I. Covas, R. Sol a, M. Farre, G. Saez, R. de la Torre, Dose-dependent metabolic disposition of hydroxytyrosol and formation of mercap- turates in rats, Pharmacol. Res. 77 (2013 Nov) 47e56, https://doi.org/10.1016/j.phrs.2013.09.001. [5] A. Gaedigk, L. Ndjountche , K. Divakaran, L. Dianne Bradford, I. Zineh, T.F. Oberlander, D.C. Brousseau, D.G. McCarver, J.A. Johnson, S.W. Alander, K. Wayne Riggs, J. Steven Leeder, Cytochrome P4502D6 (CYP2D6) gene locus heterogeneity: char- acterization of gene duplication events, Clin. Pharmacol. Ther. 81 (2) (2007 Feb) 242e251. [6] A. Gaedigk, J.C. Dinh, H. Jeong, B. Prasad, J.S. Leeder, Ten years' experience with the CYP2D6 activity score: a perspective on future investigations to improve clinical predictions for precision therapeutics, J. Personalized Med. 8 (2018) 15, https://doi. org/10.3390/jpm8020015. [7] R. Rubinshtein, J.T. Kuvin, M. Soffler, R.J. Lennon, S. Lavi, R.E. Nelson, et al., Assessment of endothelial function by non- invasive peripheral arterial tonometry predicts late cardiovascular adverse events, Eur. Heart J. 31 (2010) 1142e1148, https://doi.org/10.1093/eurheartj/ehq010.