Physical activity affects plasma coenzyme Q10 levels ... - Springer Link

Biogerontology (2014) 15:199–211 DOI 10.1007/s10522-013-9491-y

RESEARCH ARTICLE

Physical activity affects plasma coenzyme Q10 levels differently in young and old humans Jesu´s Del Pozo-Cruz • Elisabet Rodrı´guez-Bies • Manuel Ballesteros-Simarro • Ignacio Navas-Enamorado • Bui Thanh Tung • Plaćido Navas • Guillermo Lo´pez-Lluch

Received: 10 October 2013 / Accepted: 29 December 2013 / Published online: 3 January 2014 Ó Springer Science+Business Media Dordrecht 2014

Abstract Coenzyme Q (Q) is a key lipidic compound for cell bioenergetics and membrane antioxidant activities. It has been shown that also has a central role in the prevention of oxidation of plasma lipoproteins. Q has been associated with the prevention of cholesterol oxidation and several aging-related diseases. However, to date no clear data on the levels of plasma Q during aging are available. We have measured the levels of plasmatic Q10 and cholesterol in young and old individuals showing different degrees of physical activity. Our results indicate that plasma Q10 levels in old people are higher that the levels found in young people. Our analysis also indicates that there is no a relationship between the degree of physical activity and Q10 levels when the general population is studied. However, very interestingly, we have found a different tendency between Q10 levels and physical activity depending on the age of individuals. In young people, higher activity correlates with lower Q10 levels in plasma whereas in older adults this ratio changes and higher activity is related to higher plasma Q10 levels and higher Q10/Chol

J. Del Pozo-Cruz E. Rodrı´guez-Bies M. Ballesteros-Simarro I. Navas-Enamorado B. T. Tung P. Navas G. Lo´pez-Lluch (&) Dpto. Fisiologıá, Anatomıá y Biologıá Celular, Centro Andaluz de Biologıá del Desarrollo, CIBERER, Instituto de Salud Carlos III, Universidad Pablo de Olavide-CSICJA, Carretera de Utrera km. 1, 41013 Seville, Spain e-mail: [email protected]

ratios. Higher Q10 levels in plasma are related to lower lipoperoxidation and oxidized LDL levels in elderly people. Our results highlight the importance of life habits in the analysis of Q10 in plasma and indicate that the practice of physical activity at old age can improve antioxidant capacity in plasma and help to prevent cardiovascular diseases. Keywords Coenzyme Q Blood Plasma Cholesterol Exercise Physical activity Aging

Introduction Coenzyme Q (Q) is a lipidic compound present in all cell membranes that has essential functions in metabolism, antioxidant systems and cell survival mechanisms (Lo´pez-Lluch et al. 2010). Apart of its known key function in mitochondrial electron transport chain (Crane et al. 1957), it is also an important factor in the prevention of oxidative damage in cell membranes (Navas et al. 2007), regulation of oxidative stressdependent cell signaling (Lo´pez-Lluch et al. 1999; Barroso et al. 1997), improvement of endothelial function or prevention of oxidative damage in lipoproteins (Turunen et al. 2004). In plasma membrane, a Q-dependent electron transport chain regulates several intracellular and extracellular processes and prevents oxidative damage and cell death (Crane et al. 1993; Fernańdez-Ayala et al. 2000; Go´mez-Dıáz et al. 1997; Hyun et al. 2006; Navas et al. 2007).

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In plasma, low-density lipoproteins (LDLs) contain high levels of a-tocopherol but also important amounts of Q (Esterbauer et al. 1991). It has been also demonstrated that Q is as potent as a-tocopherol in prevention of lipoperoxidation in membranes (Frei et al. 1990a) being considered the main antioxidant in LDLs (Stocker et al. 1991) together with ascorbic acid (Frei et al. 1990b). Interestingly, in plasma membrane Q is the main antioxidant able to maintain both, atocopherol and ascorbate at the active reduced state (Lo´pez-Lluch et al. 2010). Then, it seems clear that Q exert a key role in the prevention of lipid oxidation in all cell membranes and its role as LDL antioxidant confers to Q an important role in the prevention of cardiovascular diseases. Then, higher levels of Q10 in plasma are related to lower levels of lipoperoxidation. The anti-atherogenic effect of Q has been demonstrated in several models including apoE mice where Q prevents the accumulation of lipid peroxidation in aorta (Witting et al. 2000). In patients showing neuropathies, treatment with exogenous Q10 reduced significantly the levels of lipoperoxidation in plasma after 12 weeks of treatment (Hernandez-Ojeda et al. 2012) or supplementation of olive oil with Q10 also reduce lipid peroxidation levels in human plasma (Bruge et al. 2012). Furthermore, Q10 also prevents endothelial oxidative injuries by regulating protective mechanisms in endothelial cells (Tsai et al. 2011). During aging and related-diseases concentration of Q10 changes influencing different cellular functions. In general, it is considered that Q synthesis varies throughout the life of the organisms being reduced in some circumstances after the initial phases of aging (Turunen et al. 2004). However, this effect is not general and in rats, no changes in Q levels after an initial rise during the first months of life were found (Zhang et al. 1996). In mouse, mitochondrial Q content was studied in heart, skeletal muscle, kidney and brain but only was reduced in skeletal muscle in old animals (Lass et al. 1999). In human blood, the relationship between plasma Q10 levels and aging are no clear. To our knowledge, no study has been performed to compare possible differences in plasmatic levels between healthy young and older adults. Only one study (Wada et al. 2007), indicates that elderly people present a bit higher Q10 levels in plasma than young people. However, in human brain, a general decrease of Q was found in elderly people (Soderberg et al. 1990). In skin, a rise occurs from childhood to maturity to

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Biogerontology (2014) 15:199–211

decrease again during aging (Passi et al. 2002). And in heart and liver, a clear decrease in Q10 levels was found in 80 year old people in comparison with young people (Turunen et al. 2004). As a multifactorial process, aging develops at different rates depending on the individual, environment factors and life style (Peel et al. 2005). Sedentarism is one of the main risk factors for age-related diseases being involved in obesity, diabetes, hypertension and cardiovascular diseases (Stewart 2005). On the other hand, the physical exercise exerts beneficial effects at very different physiological and psychological levels in elderly people (Fleg 2012). It is also clear that exercise improves cardiovascular function at different levels (Golbidi and Laher 2012). Taken into consideration the physiological importance of Q10, its antioxidant capacity in plasma and its protective effect against cardiovascular diseases, the aim of the present study has been to determine whether the degree of physical activity performed by individuals is able to modify the parameters related to Q10 in human plasma and it these changes are affected by the age of the population.

Materials and methods Participants and study design A cross-sectional study design was conducted. Volunteers were recruited (between February 1st and June 30th, 2011) from different local associations, day centers or universities around Seville, Spain). A total of 66 healthy subjects (18 young and 48 old), with an age range of 19–85 years having no history of cognitive impairment, severe heart, liver or kidney disease, diabetes or hypercholesterolemia and having no smoking or alcohol drinking habits participate in the research after their consent was obtained. Subjects were also excluded from the study if they were on antioxidant or lipid-lowering medication such as statins. In addition, those who answered ‘‘yes’’ to any question on the Physical Activities Readiness Questionnaire (Thomas et al. 1992) were also excluded from the study since this questionnaire indicate doctor checking before performing physical activity. Information about weekly diet was selfreported using a questionnaire. The research has been carried out in accordance with the Declaration of


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Table 1 Characterization of studied population Parameter

Groups Young

Old

Age (year)

20.38 ± 1.94

65.40 ± 14.75

Men (%)

61.1

44.7

Women (%)

38.9

55.3

Weight (Kg)

66.87 ± 9.07

77.19 ± 19.25

Height (cm)

172.84 ± 9.60

160.45 ± 9.84

BMI

22.45 ± 2.49

29.86 ± 7.82

WHR

0.775 ± 0.048

0.932 ± 0.008

METS/week

3,555.16 ± 750.18

1,592.19 ± 1,886.25

N

21

49

Data represent the mean ± Standard Error

Helsinki of the World Medical Association; and has been approved by the Ethics Committee of the Pablo de Olavide University. Characterization of the studied population separated in young and old groups is shown in Table 1.

(IPAQ3), moderate activity (IPAQ2) or insufficiently active (IPAQ1). IPAQ3: vigorous activity C 3 days week-1, totaling C 1,500 MET min week-1, or C7 days week-1 of any combination of walking, moderate-intensity, or vigorous activities, totaling [ 3,000 METs week-1. IPAQ2: C3 days week-1 of vigorous activity of C20 min days-1, or C5 days week-1 of moderate-intensity activity or walking C30 min days-1, or C5 days week-1 of any combination of walking, moderate-intensity, or vigorous activities, totaling C 600 MET min week-1. IPAQ1: not belonging to either of the above categories. To correlate IPAQ results with cardiovascular fitness, the 6 min walk test (6MWT) was performed (Rikli 2001). Subjects were instructed to walk at a fast and comfortable pace as far as they could in 6 min. The maximum distance (meters) walked was recorded as the score of the test. Participants were discouraged from talking during the test and were notified of each passing minute. In the case of young people, they were recruited from University students performing Biogerontology of Sport Sciences degrees.

Procedures and outcomes measures Blood collection Assessment of participants was performed in two separate occasions 24 h apart. The first one consisted of questions on socio-demographic variables including age or gender as well as clinical characteristic predictor variables (i.e. systolic and diastolic blood pressure and heart rate) and lifestyle variables (alcohol and smoke habits). Their weight, height, waist and hip circumferences were measured so their body-mass index (BMI; kg/m2) and waist to hip ratio (WHR) were calculated. To obtain information on physical activity level, the International Physical Activity Questionnaire (IPAQ) was used (Craig et al. 2003). The short (self-administered, seven items), last-week version of the IPAQ was provided, asking about the time spent being physically active in the last 7 days. Minutes of sitting, walking, moderate-intensity (walking not included), and vigorous-intensity activities were computed for the last week. Total METs were calculated as follows: (daily minutes of walking 9 days per week with walking 9 3.3) ? (daily minutes of moderate-intensity activity 9 days per week with moderate-intensity activity 9 4.0) ? (daily minutes of vigorous activity 9 days per week with vigorous activity 9 8.0). Physical activity level was then coded into three categories representing active

Volunteers were required to fast 12 h prior to donation of peripheral venous blood from antecubital vein. Blood was placed in a test tube containing heparin and immediately centrifuged at 3,000g using an eppendorf bench top centrifuge (Model 5810 R) for 10 min at room temperature. Plasma fraction was taken, removed and stored at -80 °C until analysis. Clinical chemistry analysis Serum samples were analyzed using a Reflotron plus (2008, Roche Diagnostics, S.L) that was calibrated and optimized according to manufacturer guidelines. Each serum sample was assayed for a lipid standard panel (triglycerides, total cholesterol and high-density lipoprotein (HDL). Low-density lipoprotein (LDL) was determined using the Friedewald’s formula (Friedewald et al. 1972). Q10 determination Q10 plasma levels were assessed using a protocol described elsewhere (Fernańdez-Ayala et al. 2005). A mixture of ethanol: isopropanol (95:5) was added to

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plasma sample and mixture vortexed for 1 min. Q10 was recovered with 5 ml of hexane and samples were centrifuged at 1,000g for 5 min at 4 °C. The upper phase from three extractions was recovered and dried using a rotary evaporator (Bu¨chi, Switzerland). Dried lipid extract was suspended in 1 ml of ethanol, dried in a speed-vac and stored at -20 °C until analysis. Samples were suspended in the suitable volume of ethanol prior to HPLC injection. Lipid components were separated by a Beckman 166-126 HPLC system equipped with a 15-cm Kromasil C-18 column in a column oven set to 40 °C, with a flow rate of 1 ml/min and mobile phase containing 65:35 methanol/n-propanol and 1.42 mM lithium perchlorate. Q10 levels were analyzed with ultraviolet (System Gold 168) based detectors and an electrochemical detector Coulochem III (ESA, USA) with a guard cell 5,020 at ?500 mV and an analytical cell 5,010 with channel one at -500 mV and channel two at ?500 mV as necessary. Q9 was used as internal standard. Q10 content was determined as nmol/L and then related with cholesterol and LDL-C concentrations. Plasma lipid oxidation determinations To assess the whole level lipid peroxidation degree in plasma, the levels of MDA were determined by using the Cayman’s TBARS Assay Kit following the instructions of the manufacturer (Cayman Chemicals, USA). LDL oxidation levels were determined by ELISA by using the Oxidized LDL ELISA kit as indicated by the manufacturer (Mercodia, Sweden). Detection of protein carbonylation Protein carbonilation was performed as indicated previously (Robinson et al. 1999), based on a combination of 2,4-dinitrophenylhydrazine (DNPH) derivatization and dot blotting. Blanks were prepared by treatment with 20 mM NaBH4 and incubation at 37 °C for 90 min. Samples and corresponding blanks were prepared at final concentration 0.5 mg/mL by dilution with 70 % trifluoroacetic acid. One lL protein samples were slot-blotted onto a polyvinylidene difluoride (PVDF) membrane. This membrane was incubated with 50 mL of 0.1 mg/mL DNPH in acetic acid for 15 min, then washed extensively in acetic acid (3 9 5 min) and immersed in a solution of 7 % acetic acid, 10 % methanol for 15 min at room temperature.

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After washing with deionized water four times for 5 min each, membrane was incubated in SYPRO Ruby blot stain reagent for 15 min to determine protein loading. Membrane was washed again with deionized water (3 9 1 min) and fluorescence monitored for quantification of the total protein loading. After that, membrane was blocked with 5 % skim milk dissolved in 0.5 mM Tris–HCl (pH 7.5), 150 mM NaCl, and 0.1 % Tween-20 for 1 h at room temperature. Further, it was incubated with the primary antibody anti-DNPH (Sigma, Spain) at a 1:5,000 dilution overnight at 4 °C. After three washes with Tris-buffered saline with 0.1 % Tween-20, membrane was incubated with secondary horseradish peroxidase conjugated goat anti-rabbit antibody (Sigma, Spain) in TBST with 5 % skim milk at a 1:10,000 dilution for 1 h at room temperature. Slot blot detection was developed using an enhanced chemiluminescence detection substrate ImmobilonTM Western Chemiluminescent HRP Substrate (Millipore, USA). Carbonylated proteins were visualized and quantified by the ChemiDocTM XRS ? System and compiled with Image LabTM 4.0.1 Software (Bio-Rad Laboratories, USA). Statistical analysis All tests were performed using SPSS version 17.0 (SPSS Inc., Chicago, IL, USA). The distribution of the data was examined by the Kolmogorov–Smirnov test with Lilliefors correction. Descriptive statistics are presented as mean ± SE. For the study purposes, data were organized in different sub-groups according to the age (young and old-) and level of physical activity (IPAQ1, IPAQ2 and IPAQ3). After confirming the normal distribution of the data for all variables, differences between groups were performed using Student’s t test for independent samples. When more than three groups existed (i.e. level of physical activity), one-way ANOVA with Bonferroni post hoc analyses was used for differences between groups testing. Pearson correlations were performed to better depict the relationship between the different variables of the study. The level of relationship was determined based on the recommendations of Cohen (Cohen 1988), a coefficient between 0.1 and 0.29 was considered low; a coefficient between 0.3 and 0.49 were considered moderate and more than 0.5 was considered high. Graphics were performed by using


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Sigma Plot version 10.0. The critical significance level a was established at 0.050 and, then, statistical significance was defined as p \ 0.05.

Results Plasma Q10 levels are higher in old individuals Plasma cholesterol related parameters were not different between young and older adults. However we found significant higher levels of triglycerides in old people in comparison with young individuals (Table 2). Very interestingly, levels of plasma Q10 in young people were significantly lower than in old group. When related to cholesterol, Q10 amount was higher in old group but only significantly when related to LDL content. However, as TGs levels were higher in elderly people, the ratio Q10/TGs was significantly lower in this group in comparison with younger people (Table 2). Plasma Q levels depends on physical activity Cholesterol, TGs and Q10 in plasma were measured in the young group distributed according their physical activity. Young people performing more intense physical effort showed significant lower levels of TGs in plasma but surprisingly lower levels of Q10. Furthermore, the ratio Q10/HDL, Q10/LDL and Q10/

TGs in plasma was also significantly lower in this group (Table 3). We did not find young people showing so low physical activity for them to be considered into the group IPAQ1. When these parameters were studied in the old group different effects related to of physical activity were found. No changes in total cholesterol were recorded but old people practicing more intense physical activity showed less levels of HDL. TGs levels decreased in the group performing moderated activity (IPAQ2) in comparison to the other groups. Interestingly, Q10 levels rise in plasma depending on the physical activity showing the IPAQ3 group the highest levels of Q10. This increase also significantly affected Q10/Chol, Q10/HDL and Q10/LDL ratios (Table 4). IPAQ questionnaire is a validated method to determine the amount of physical activity in humans, however, to corroborate the results obtained from the questionnaire in elderly people, we performed a fitness test consisting in the 6 min walk test (6MWT) in which voluntaries were instructed to walk at a fast and comfortable pace as far as they could in 6 min (Rikli 2001). We found a moderated but significant relationship between METs determined by the questionnaire and the exercise test validating the classification obtained (Fig. 1). Very interestingly, we found a different effect of exercise when comparing young and old people. In young people, higher physical activity was related to a

Table 2 Lipid content in plasma comparison between young and old people Parameter

Groups Young

Cholesterol (mg/dL)

p value Old

161.70 ± 11.14

180.14 ± 7.77

0.297

HDL cholesterol (mg/dL)

46.59 ± 5.27

53.08 ± 2.52

0.279

LDL cholesterol (mg/dL)

193.58 ± 5.36

205.93 ± 8.37

0.526

4.43 ± 0.20

4.11 ± 1.26

0.310

Ratio LDL/HDL

75.70 ± 4.80

139.58 ± 8.57

0.001*

Coenzyme Q10 (nmol/L)

TGs (mg/dL)

942.39 ± 57.39

1,188.67 ± 69.96

0.030*

Q10/Chol (nmol/mmol)

217.08 ± 13.06

265.06 ± 22.70

0.180

Q10/HDL Chol (nmol/mmol)

800.06 ± 45.19

945.36 ± 70.48

0.203

Q10/LDL Chol (nmol/mmol)

183.06 ± 10.62

241.61 ± 18.78

0.049*

1,134.97 ± 72.56

852.63 ± 60.61

0.007*

Q10/TGs (nmol/mmol) N

21

49

Data represent the mean ± Standard Error * p value indicates the significant difference between both groups

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Table 3 Effect of physical activity level on plasmatic lipid content in young population Parameters

IPAQ levels

p value

Moderate level (IPAQ 2)

High level (IPAQ 3)

Age (years)

21.56 ± 0.74

20.07 ± 0.52

(Range)

(19–25)

(19–24)

NS

Cholesterol (mg/dL)

180.11 ± 7.00

161.70 ± 11.14

0.190

HDL cholesterol (mg/dL)

48.04 ± 3.69

46.59 ± 5.25

0.827

LDL cholesterol (mg/dL)

212.53 ± 8.51

193.58 ± 15.36

0.310

Ratio LDL/HDL

4.55 ± 0.27

4.32 ± 0.30

0.586

TGs (mg/dL)

78.12 ± 3.36

65.37 ± 3.67

0.020*


1,127.43 ± 67.51

775.87 ± 48.03

0.001*


243.18 ± 13.74

193.59 ± 19.17

0.071


919.85 ± 36.61

692.22 ± 62.93

0.007*


205.21 ± 9.09

163.12 ± 16.41

0.044*

Q10/TGs (nmol/mmol)

1,296.20 ± 103.18

989.87 ± 80.95

0.030*

N

10

11

Data represent the mean ± Standard Error NS no significant * p value indicates the significant difference between both groups Table 4 Effect of physical activity level on plasmatic lipid content in old population Parameters

IPAQ level

p values

Low Level (IPAQ 1)

Moderate Level (IPAQ 2)

High Level (IPAQ 3)

Age (years)

65.75 ± 2.12

68.13 ± 2.46

71.50 ± 2.13

(Range)

(48–83)

(52–85)

(63–83)

NS

Cholesterol (mg/dL)

189.76 ± 10.55

183.61 ± 8.53

195.55 ± 13.06

NS

HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)

51.09 ± 3.79 208.91 ± 12.44

58.05 ± 3.25 215.49 ± 10.61

43.69 ± 3.59 214.94 ± 16.22

0.009c NS

Ratio LDL/HDL

4.27 ± 0.24

3.86 ± 0.30

4.97 ± 0.38

0.040c

TGs (mg/dL)

159.71 ± 14.63

103.93 ± 11.48

150.80 ± 8.08

0.004a,b


975.94 ± 112.41

1,210.70 ± 105.92

1,658.16 ± 66.08

0.004b,c


198.76 ± 19.29

303.96 ± 52.96

350.85 ± 33.85

0.010a,b


761.06 ± 81.62

863.98 ± 104.26

1,436.52 ± 140.81

0.003b,c


181.330 ± 18.05

259.92 ± 39.26

322.98 ± 34.78

0.001b

Q10/TGs (nmol/mmol)

598.32 ± 67.72

1,203.44 ± 167.02

1,000.61 ± 72.49

0.008a,b

N

22

16

11

Data represent the mean ± standard error NS no significant differences among groups Significant differences are indicated between a IPAQ1 and IPAQ2;

lower level of Q10 and Q10/Chol ratio in plasma whereas in old people, this relationship was the opposite, higher levels of physical activity correlated to higher levels of Q10 in plasma (Fig. 2). When the

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b

IPAQ 1 and IPAQ 3; c IPAQ2 and IPAQ3

whole Q10 content levels was taken as reference, a different relationship between IPAQ2 (around a 20 % higher) and IPAQ3 (around a 20 % lower) was found in young people (Fig. 3). However, in old individuals,


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tendency to an inverse ratio between physical activity and Q10 in plasma in young people whereas in old people the same ratio was both direct and significant (Fig. 4). Oxidative damage in young and older adults depends on physical activity

Fig. 1 Relationship between METs and 6MWT results. METs determined by cumplimenting the questionnaire of physical activity were correlated with the score obtained in a 6 min walking test of elderly people. Pearson’s R and significance (p) are indicated

sedentary people showed a 25 % decrease of Q10 levels in plasma whereas high active individuals showed a 40 % of increase in comparison with the levels found in the whole population (Fig. 3). Plasma of elderly people performing moderated activity contained similar concentration of Q10 comparing to the whole elderly population. Very interestingly, we did not find any connection between physical activity measured as METS/ week and Q10 levels in the whole population, but when we took young and older adults separately we found opposite relationships. We observed a

Levels of whole lipid peroxidation in plasma and specific LDL oxidation were measured. Old group showed significant higher levels of both, MDA and LDL oxidation in plasma in comparison with young people (Fig. 5). When we determined the level of MDA in plasma related to physical activity degree we found that young people performing a more intense physical activity showed significant lower levels of lipid peroxidation in plasma (Fig. 6a). Levels of oxidized LDL were also lower in very active young people although the difference with IPAQ2 group was not statistically significant (Fig. 6b). On the other hand, older adults showed a trend to decrease whole lipid peroxidation level in plasma in high active population, although no significant differences were found (Fig. 6a). However, when we measured the levels of oxidized LDL in plasma, we did find a very significant decrease depending on the physical activity of the individuals (Fig. 6b).

Fig. 2 Plasma Q10 and Q10/ cholesterol levels in young and older adults. a Plasma Q10 levels in plasma in young (left) and older adults (right) in relationship with their respective level of physical activity. b Ratio of Q10/cholesterol (nmol/ mmol) levels in plasma of young (left) and old (right) people. Data represent the median ± SE. Statistic significant differences are indicated between boxes. N = as indicated in Table 3

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Fig. 3 Percentage of variation of plasma Q10 levels respecting whole population levels in physical activity groups. The percentage of variation in whole plasma Q10 levels in young (a) and old (b) population is shown respecting the levels found in the whole population. *Statistic significant differences versus reference levels

Fig. 4 Correlation between Q10 levels and physical activity. Spearman rank correlation was performed between Q10 levels in plasma and physical activity determined in METS/week in

whole population (a), or young (b) and old (c) population separately. Spearman r and statistical significance (p) are indicated

Respecting protein carbonylation in plasma, no definitive results were found. However, a trend to decrease in highly active young people was found

again, whereas in old people this trend was shifted towards an increase depending on physical activity (Fig. 7). Taken together, our results indicate that aged

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Fig. 5 Oxidative damage in plasma. a Plasma whole lipoperoxidative damage measured by MDA determination in young and old people. b Oxidized LDL levels in young and elderly people. Statistic significant differences between groups are indicated. N = as indicated in Table 2

Fig. 6 Physical activity effect on lipid peroxidation in plasma in young and older adults. a Whole lipid peroxidation in young (left) and old (right) population measured as MDA levels. b Oxidized LDL levels in plasma from young (left) and old (right) population. Statistic significant differences are indicated. N = as indicated in Table 3

people show higher Q10 levels in plasma in a way to protect plasma lipoproteins against oxidation although without affecting protein oxidation.

Discussion Our results indicate that the practice of physical activity produces different effects on plasma Q10

levels depending on the age of the individual. To our knowledge, this is the first work that demonstrates that Q10 varies in plasma elderly people directly depending on physical activity. Importantly, our results indicate that high levels of physical activity correlate with high content of Q10 in plasma in elderly people and with lower lipid oxidative damage and especially lower LDL oxidation in plasma leading to a greater protection against cardiovascular diseases. Modulation of

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Fig. 7 Physical activity effect on protein carbonilation in plasma in young and older adults. a Representative protein carbonilation levels in young plasma (n = 10). b Representative protein carbonilation levels in old plasma (n = 10)

Q10 content can be then added to the diverse cardiovascular beneficial effects of exercise especially in aged people (Golbidi and Laher 2012). Plasma Q10 levels varies depending on the health status of the individual. Variations of plasma Q10 these levels have been related to several age-related diseases (Kontush et al. 1999; Buhmann et al. 2004; Sohmiya et al. 2004; Mancini et al. 2005). It is believed that Q10 levels in plasma diminish in aged individuals although only a few reports have studied the evolution of plasma Q10 during aging in healthy humans. Surprisingly, only a few studies have reported changes of Q10 in human plasma during aging but without showing significant differences between young and old people. Wada and coworkers reported that elderly people show a bit higher Q10 levels in plasma than young people (Wada et al. 2007). Moreover, an early study also showed small and non-significant increases in plasma Q10 level in elderly people although a in this study a range of people aged between 20 and 55 years was used as young population whereas old people was between 71 and 90 years (Ravaglia et al. 1996). Further, in a pilot study, Pedersen et al. demonstrated a significant positive association of Q10 with age in male Inuit of Greenland (Pedersen et al. 1999), a population showing low incidence of cardiovascular diseases. Our study did show a clear increase in plasma Q10 in elderly people in comparison with young individuals probably by the narrower interval of age used in comparison with previous studies. One of the reasons has been related to higher LDL (Johansen et al. 1991) and the higher levels of LDL normally found in elderly people, although this was not the case in our study. Our results also demonstrate that physical activity produces different effect on plasma Q10 depending on

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the age. Highly active young people showed lower Q10 levels than moderate active fellows. However, in elderly people, physical activity was directly related to the levels of Q10 in plasma. The results found in young people agree with previous studies that demonstrate that exercise in young people decreases Q10 levels. Higher levels of Q10 in plasma were found in healthy sedentary male subjects in comparison with trained athletes (Karlsson et al. 1992). Moreover, in free living community people, Battino et al. found that higher aerobic capacity was associated with lower levels of plasma Q10 but specially in young people (35–44 years old) in comparison with an older group (45–54 years) (Battino et al. 1997). Interestingly, to our knowledge, no data relating the physical activity with Q10 levels in people over 65 years have been previously published. Our results indicate that exercise induces an increase of Q10 in plasma in elderly people. Any mechanisms causing an increase in Q levels in elderly people would be very interesting since Q10 has an important protective role in several chronic and age-dependent diseases (Hernandez-Ojeda et al. 2012; Bruge et al. 2012; Tsai et al. 2011). Treatments with Q10 have shown beneficial effects in many aging-related diseases such as cardiovascular diseases, neuropathies, inflammation, metabolic syndrome, hypercholesterolemia or diabetes (Kagan and Quinn 2001). Furthermore, a recent study have reported that dietary supplementation with Q10 in elderly people shows preventive effects on oxidative processes associated with aging (Gutierrez-Mariscal et al. 2012). However, we don’t know the mechanism involved in the increase of plasma Q10 in elderly people practicing higher physical activity. It has been demonstrated that peroxisome proliferator-activated


receptor (PPAR) affects the expression of lipid metabolism-related genes including apolipoproteins and Q synthesis (Lee et al. 1995; Lemberger et al. 1996). Moreover, inducers of PPAR are able to increase Q synthesis in young rats to sixfold although this effect decreases along age being ineffective in old animals (Turunen and Dallner 1998). On the other hand, exercise activates PPARc in muscle and monocytes regulating genes related to lipid metabolism (Thomas et al. 2012). Furthermore, low-intensity exercise modulates lipid metabolism through PPARc and liver X receptor stimulating reverse cholesterol transport and then, contributing to cardiovascular benefits (Butcher et al. 2008). Some exercised models such as swim training in mice have demonstrated also transcriptional activation of hepatic PPARa (Oh et al. 2006). Taken together, physical activity in elderly people could induce the activity of PPAR mediators in liver and then modulate cholesterol metabolism and the amount of Q10 in plasma lipoproteins. We cannot discard that physical activity is also affecting Q10 levels in other tissues and organs. In mice, aerobic training together with caloric restriction moderately increase total Q levels in gastrocnemius muscle in young mice (Rodrı´guez-Bies et al. 2010), these changes are even more significant in old animals (Rodrı´guez-Bies et al., unpublished results). An age-dependent effect of exercise on the levels of Q10 in several organs would enhance the importance of exercise on the maintenance of many physiological functions during aging. In fact, animal models demonstrate the importance of Q10 on the aging process. When SAMP1 mice model showing accelerated senescence was fed with a diet supplemented with reduced Q10 interesting effects on the regulation of cholesterol synthesis, fat assimilation, lipoprotein metabolism and inflammation in liver interesting effects were found probably explaining the decelerating effects of Q10 on these mice (Schmelzer et al. 2010). Moreover, in a mouse model of Alzheimer’s disease, treatment with Q10 reduces the intracellular deposition of amyloid plaque indicating Q10 as a therapeutic candidate for Alzheimer Disease (Yang et al. 2010). In humans, prolonged Q10 treatment of Down syndrome patients reduces DNA oxidation in lymphocytes probably by activating DNA reparation mechanisms or avoiding oxidative damage (Tiano et al. 2012). Supplementation of Mediterranean diet with Q10 has reported important reduction of

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oxidative damage in plasma and modulation of the expression of proinflammatory and stress genes in elderly people (Yubero-Serrano et al. 2011, 2012). Furthermore, Q levels raise in oxidative stress related diseases as a protective response (Bentinger et al. 2010). However, other studies have reported controversial results. Supplementation with Q10 before exercise did not affected the level of lipid peroxidation although, in agreement with our results, chronic training reduced plasma lipid peroxidation levels (Braun et al. 1991). As dietary uptake of this lipid is limited although new formulations are being studied to improve assimilation (Villalba et al. 2010). Therefore, upregulation of its biosynthetic pathway by non pharmaceutical therapies is of considerable clinical interest. For this reason, our findings showing higher levels of Q10 in plasma in elderly people practicing higher physical activity are of importance in therapies focus on aging. Added to the known beneficial effects of exercise on many age-related disturbances, its capacity to further increase Q10 levels in plasma of elderly people and reduce lipoperoxidative damage enhances the importance of the maintenance of a high physical activity in this population. The practice of exercise at advance age would improve also many functions depending on Q10 in different organs. Acknowledgments We want to thank the participants for their patience, devotion and participation. This study has been supported by funds from the Andalusian Government as the BIO177 group through FEDER funds (European Commission). The Centro Andaluz de Biologıá del Desarrollo and the Universidad Pablo de Olavide provided human and infrastructure resources. Jesu´s del Pozo-Cruz was awarded a pre-doctoral fellowship and the study were funded by the project IMD2010-SC002 from the Centro Andaluz de Medicina del Deporte on behalf of the Government of Andalusia. Tung Bui Thanh received a fellowship from the AECID program (Spanish Ministry of Foreing Affair). ERB, MBS, PN and GLL are also members of the Centro de Investigacioń Biome´dica en Red de Enfermedades Raras (CIBERER), Instituto Carlos III.

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