Oxidative Stress in Elderly with Different Cognitive Status: My Mind Project

Abstract

Background:

Biomarkers of oxidative stress have been associated with cognitive status in humans and have been proposed to guide prognosis/treatment in Alzheimer’s disease (AD) and mild cognitive impairment (MCI).

Objective:

The aim of this study was to compare oxidative stress status in the plasma of mild-moderate AD, MCI, and healthy elderly with normal cognition (HE) undergoing a non-pharmacological intervention including multi-modal cognitive training (“My Mind Project”).

Methods:

A prospective randomized trial involving 321 elderly people enrolled in Marche Region, Italy. Each subject was randomly assigned to an experimental (cognitive training) or to a control group. Cognitive performances and biomarkers have been analyzed before intervention (baseline), immediately after termination (follow-up 1), after 6 months (follow-up 2), and after 2 years (follow-up 3). The biological antioxidant potential (BAP) to Diacron reactive oxygen metabolites (d-ROM) ratio has been used as an indicator of oxidative stress status and as outcome variable.

Results:

We have found no differences in the oxidative status among AD, MCI, and HE. Neither did we find a significant effect of the intervention within experimental groups. Gender was the sole factor with a strong significant effect on BAP/d-ROM.

Conclusions:

Based on these results, the utility of biomarkers of oxidative stress to guide prognosis/treatment in AD or MCI seems to be limited by lack of specificity, large interindividual variability, and gender bias.

Keywords

Aging Alzheimer’s disease cognitive dysfunction oxidative stress

INTRODUCTION

Alzheimer’s disease (AD) is the most common dementia of the elderly population and is characterized by the progressive deterioration of behavior, cognition, and functionality, which significantly impairs daily living activities [1]. Although AD pathogenesis is complex and multifactorial, it has been proposed that oxidative stress plays a key role in the development of the disease [2 –4]. The brain, while representing only 2% of body weight, utilizes 20% of the oxygen supplied by the respiratory system [5]: this high energy-consumption makes it particularly susceptible to oxidative stress compared to any other organ. Brain contains a large amount of polyunsaturated fatty acids that interact with free radical of reactive oxygen species (ROS) [6], while it has low levels of antioxidants like glutathione [7]. These features make the brain particularly vulnerable to oxidative stress.

Under physiological conditions, there is a balance between oxidant and antioxidant species [8]. During oxidative stress conditions, there is a shift toward oxidant molecules production (nucleic acids, proteins, lipids) causing cellular/tissue oxidative damage [9, 10]. Specifically, ROS and reactive nitrogen species (RNS) are responsible of peroxidation of cell membrane lipids: 1) modifying the biological properties of the membrane, such as its fluidity and inactivating the membrane-bound receptors or enzymes, 2) impairing normal cellular function, 3) increasing cellular damage, and 4) generating new oxidized products that can be chemically reactive and modify other macromolecules. Several studies have found that the amount of ROS and RNS, and the production of oxidized macromolecules are increased in blood, cerebrospinal fluid (CSF), and also in postmortem brain samples of AD patients [11 –15]. Numerous studies argue that oxidative stress originates from mitochondrial dysfunction [16 –18], inflammatory status [19, 20], metals [16 , 22], amyloid-β (Aβ) [16, 18], and hyperphosphorylated tau accumulation [23, 24]. Moreover, dysregulation of enzymatic components of the antioxidant systems in the cytosol (CU-Zn-SOD or SOD1), mitochondria (MN-SOD or SOD2), and the extracellular milieu (SOD3, glutathione peroxidase and catalase), is likely to play a role in oxidative stress associated with age-related pathologies [20 , 25–27].

Conceivably, any assessment of the oxidative stress must take into account both the pro-oxidizing and antioxidant components.

In the present study, we evaluated the global oxidative stress status in the plasma by measuring ROS metabolites derivative compounds (d-ROMs), biological antioxidant potential (BAP), and their ratio.

The d-ROMs test represents a measurement of the oxidative stress status by determining the levels of hydroperoxides of global organic compounds (lipids, proteins, nucleic acids, etc.) [28]. The BAP test provides a global measurement of many antioxidants, including uric acid, ascorbic acid, proteins, α-tocopherol, and bilirubin [29, 30]. Prospective studies have provided evidence that the combined measurement of oxidative status with antioxidant potential can be used to identify subjects at risk of cognitive decline, suggesting that these changes are likely involved in the process of neurodegeneration [3, 31].

Moreover, previous findings demonstrated that specific non-pharmacological treatments, such as cognitive training and comprehensive intervention in the elderly, were associated with an improvement in neurophysiological and neuropsychological aspects [32, 33] as well as in reducing systemic oxidative burden in aging [34].

For this reason, the “My Mind Project” analyzed several aspects related to cognitive performances before and after a cognitive and comprehensive intervention, as well as possible changes in potentially related peripheral biomarkers including oxidative stress status. The innovative contribution of this project consisted in identifying a comprehensive intervention with the scope of developing a multidisciplinary approach to cognitive disease in elderly people with different cognitive status. In details, we chose the use of multidimensional assessment that includes the analysis of interrelationships among cognitive, lifestyle, psycho-social and biochemical aspects.

The specific aim of the present study was to compare oxidative stress and the antioxidant activity in the plasma of subjects with mild-moderate AD and mild cognitive impairment (MCI) versus healthy elderly with normal cognitive functions (HE). The potential modulation of these parameters by a comprehensive intervention on cognitive performance was also evaluated.

MATERIALS AND METHODS

Study design

Data were collected on behalf of the “My Mind Project” (grant n. 154/GR-2009-1584108 founded by the Italian Ministry of Health and the Marche Region), a prospective, randomized intervention study with 3 follow-up phases for the assessment of the effects of a comprehensive intervention in three groups of elderly subjects having different cognitive statuses, using a multidisciplinary approach. The research was approved by the Institutional Ethical Committee (code SC/12/301) and each participant provided informed consent to participate to the study.

Subjects

Participants, living in Marche Region, were enrolled from the Evaluation of Alzheimer’s Unit of Geriatrics Operative Unit at the INRCA Hospital in Fermo (Italy). Subjects were diagnosed with AD, MCI, and HE by means of an extended neuropsychological and functional evaluation, neuroimaging, and laboratory tests, according to diagnostic guidelines and criteria. Diagnosis of MCI was carried out by using Petersen’s criteria [35]. Diagnosis for possible or probable mild-moderate AD was carried out by using the DSM-IV or NINCDS-ADRDA criteria [36]. HE were subjects with absence of relevant cognitive diseases.

After the enrolment, subjects were randomly assigned to the experimental groups (EG) or the control groups (CG). Randomization was performed separately for each group by using a computerized random number generator. Description of inclusion and exclusion criteria and diagnosis of cognitive status are reported elsewhere [37]. Three hundred and twenty-one community-dwelling elderly subjects were recruited and divided into three groups, according to their cognitive status: 111 HE, 109 subjects with MCI, and 101 subjects affected by mild-moderate AD. Twenty-eight participants were excluded due to outliers in oxidative stress and in the antioxidant activity in the plasma, leaving a final sample of 293:101 HE, 100 subjects with MCI, and 92 subjects affected by mild-moderate AD. Two hundred and thirty-seven participants (80.9% ) completed the study, of which 81 were healthy (80.2% ), 80 were MCI (80.0% ), and 76 were AD (82.6% ). The remaining 56 subjects (19.1% ) were dropouts, of which 10 died during the study.

Intervention

Each experimental group received a weekly comprehensive intervention for 2 months, including a training program addressing cognitive functions [37]. The main aim of the intervention was to improve different cognitive functions, in order to activate and to motivate participants to ameliorate their cognitive health behavior by remaining cognitively active and compensating deficits with learned mnemonic strategies after training. According to cognitive status, different comprehensive training methods have been applied to the different groups of subjects. Interventions were focalized both in cognitive enhancement, and other aspects, such as advice and psycho-education about healthy lifestyle strategies to maintain cognitive reserves and engagement in leisure activities. Training has been individually applied for subjects with MCI and with mild-moderate AD, in order to identify their individual goals and practice strategies focused on them. All participants were also asked to perform homework exercises each day prior to the subsequent session. To perform this activity, the support of a caregiver was required to help subjects with MCI and AD.

The treatment for HE consisted of 10 sessions of 90 minutes in groups of about 10 participants, to maximizing social participation. The LAB-I methodology [38], which includes the learning of some effective mnemonics and techniques, was used to enhance in particular working memory and learning processes. A metacognitive and motivational approach was used.

MCI group received a comprehensive multi-modal training of 10 individual sessions of 45 minutes, once a week, which included also psycho-education about memory loss and restorative and compensatory cognitive training. Treatments were focalized in learning strategies for orientation, memory, categorization, and clustering. Moreover, the effect of metacognition and of anxiety, stress, and/or depression often due to consciousness of cognitive decline in MCI subjects, was evaluated to analyze the role on cognitive performances.

The AD group received a comprehensive intervention of 10 sessions of 45 minutes each, including restorative cognitive training addressed in particular to the empowerment of attention functions, orientation, planning of activities of daily living, and episodic and prospective memory. The intervention also aimed to decrease functional disability of subjects with dementia, maximizing functionality status, engagement in activities of daily living, and healthy lifestyle and to support patients and their caregivers for psychological disorders.

Control groups received a general psychoeducational approach, including some suggestions and strategies on how to improve memory and health status. We have chosen this approach in order to attenuate the intervention effects and to minimize the cognitive engagement of subjects, as indicated in other our study [32]. All subjects of control groups were tested at baseline and during three follow-up phases by using the identical assessments of the experimental groups.

Neuropsychological assessment

The neuropsychological test battery (Table 1), chosen in accordance with studies for assessment of distinctive domains, comprised instruments sensitive to age-related cognitive decline and with good reliability and validity. All measures were considered targets for the evaluation of intervention effects. The same assessment was carried out before and after intervention and repeated at each follow-up phases (after 6 months and after 2 years).

Table 1

Neuropsychological assessment

Instrument	Description and Assessment
Mini-Mental State Examination [39]	Assessment of global cognitive abilities
Alzheimer’s Disease Assessment Scale [40]	Assessment of cognitive decline in dementia. It consists of 12 sub-tests for evaluation of memory, orientation, language, praxis; attention and concentration
Clinical Dementia Rating Scale [41]	Assessment of overall dementia severity
Supra-Span of Corsi [42]	Assessment of orientation and spatial attention
Backward and Forward Span [43]	Assessment of span of immediate verbal recall and working memory
List of Words [44]	Assessment of memory and learning processes of a list of words
Questionnaire of confidence [44]	Assessment of subjective confidence in own cognition and memory
Memory Assessment Complain Questionnaire [45]	Assessment of subjective memory complaints
Word Pairing Learning Test [46]	Assessment of verbal memory and learning of word pairs.
Prose Memory test [47]	Assessment of the long term memory on immediate recall
Attentive Matrices [47]	Assessment of selective and the sustained attention.
Semantic Word Fluency Test [48]	Assessment of lexical access and semantic fluency for a specific category (for example, fruits, animals).
Phonemic Word Fluency Test [48]	Assessment of lexical access and phonemic fluency beginning with a particular letter of the alphabet.
Geriatric Depression Scale [49]	Screening and assessment of mood status and depression
Perceived Stress Scale [50]	Assessment of psychological instrument for measuring perceived psychological stress
Activity of Daily Living [51]	Assessment of functional status of basic activities of daily living
Instrumental Activity of Daily Living [52]	Assessment of functional status of instrumental activities of daily living

For analyzing cognitive status in this study, we chose the Mini-Mental State Examination (MMSE) because of its widespread use and its applicability in both patients and HE subjects [3 , 53–55], enabling us to describe cognitive changes with a single measure. However, since MMSE does not represent a sensitive measure to define dementia and cognitive decline, we carried out diagnosis of cognitive decline with the diagnostic criteria and the specific neuropsychological instruments indicated above, including Alzheimer’s Disease Assessment Scale and Clinical Dementia Rating Scale scores.

Measurements of d-ROM and BAP

Blood samples were drawn from the participants between 8:00 and 9:00 AM in fasting state, then they were centrifuged and plasma was used to detect reactive oxygen metabolites (d-ROM) and BAP (Diacron, Grosseto, Italy).

The d-ROM test measures hydroperoxides and is based on the principle that the level of organic hydroperoxides present in blood is related to the amount of free radicals from which they are formed. Measurement of plasma d-ROM levels was performed using a spectrophotometer (FREE Carpe Diem, Diacron S.r.l., Grosseto, Italy). The instrument outputs the results directly expressed as U-CARR (Carratelli units) [55]. The value of one U-CARR corresponds to a concentration of 0.8 mg/L of hydrogen peroxide. The BAP test was also performed by a spectrophotometer (FREE Carpe Diem, Diacron S.r.l., Grosseto, Italy). This test measures the plasma and serum antioxidant, or reducing, power by measuring the capacity of the sample to reduce the iron content from its ferric to ferrous form. The BAP assay is expressed as μmol/L. The BAP/d-ROM, calculated on the values obtained by the BAP test and d-ROM test, indicates the degree of latent antioxidant potential that, in turn, represents the balance between oxidative stress and antioxidant potential.

Analytic approach

Statistical analysis was carried out by SPSS24 for Windows (SPSS Inc, Chicago, IL, USA). Descriptive statistics were used to compare baseline data by the three groups (HE, MCI, AD) and gender, using one-way ANOVA followed by Bonferroni and t-test for means respectively, and Chi-square test for frequencies. BAP/d-ROM was normalized using ln transformation; outliers were checked and identified separately for each group by box-plot and then excluded from the analysis. The presence of time intervals that could lead to batch effects on BAP/d-ROM data was checked by visual inspection of dot plots versus the withdrawal date and by cluster tree analysis (using CHAID algorithm) on the whole dataset, in the dataset of control group and in the dataset within each follow-up separately. The potential influence of a seasonal effect on BAP/d-ROM data mimicking batch effects was investigated including “season” as variable in the cluster tree analysis. Batch effects were corrected using residuals of generalized linear models (GLM) [56] using BAP/d-ROM as dependent variable and the time intervals identified in the cluster tree analysis as independent variable. BAP/d-ROM values corrected for batch effect were used as outcome variable for a generalized linear mixed effects model (GLMM) for repeated measures to assess if BAP/d-ROM changed over time by cognitive group and intervention. The model included an interaction term between intervention, cognitive group and time and was estimated using the Satterthwaite approximation for unbalanced samples and robust covariances. Correction of batch effect was also performed including the time intervals as random effect in a GLMM model using log of BAP/d-ROM as dependent variable.

The model was also computed separately for BAP and d-ROM. A p-value of <0.05 was regarded as significant.

RESULTS

The main characteristics of the participants are showed in Table 2. At baseline, AD subjects were older and had lower MMSE score, mean Activities of Daily Living, and Instrumental Activities of Daily Living than HE and MCI. Moreover, AD participants were also less frequently educated compared to HE. There were no significant differences in drug use among groups as well as no gender-related differences were found.

Table 2

Demographic and clinical characteristics of study patients divided according to the cognitive status at baseline and by gender (n = 293)

	Total (n = 293)	HE (n = 101)	MCI (n = 100)	AD (n = 92)	p	Male (n = 88)	Female (n = 205)	p
Age, y	75.4±0.4	72.3±0.6	76.1±0.6	77.9±0.6	<0.001^a,b	75.8±0.7	75.2±0.4	0.409
Gender, female	205 (70.0)	78 (77.2)	64 (64.0)	63 (68.5)	0.115	–	–	–
MMSE	23.2±0.3	27.8±0.2	25.8±0.2	19.9±0.4	<0.001^b,c	23.6±0.5	23.0±0.4	0.328
ADL	5.6±0.0	5.9±0.0	5.8±0.0	5.1±0.1	<0.001^b,c	5.6±0.1	5.6±0.1	0.729
IADL	6.3±0.1	7.9±0.1	7.5±0.1	3.3±0.2	<0.001^a,b,c	6.1±0.3	6.4±0.2	0.268
Education (y)	6.6±0.3	9.1±0.6	5.7±0.4	5.3±0.5	<0.001^a,b	7.3±0.4	6.7±0.3	0.303
AChEi	45 (16.5)	–	–	45 (49.5)	–	17 (21.0)	29 (15.2)	0.243
Lipid lowering medications	60 (22.1)	17 (18.9)	26 (28.6)	17 (18.7)	0.185	20 (24.7)	40 (20.9)	0.495
Antihypertensive	154 (56.6)	52 (57.8)	50 (54.9)	52 (57.1)	0.922	52 (64.2)	102 (53.4)	0.100
NSAIDs	8 (2.9)	5 (5.6)	2 (2.2)	1 (1.1)	0.182	2 (2.5)	6 (3.1)	0.764

Data are mean±SE or number of cases (percentage); ADL, Activities of Daily Living; IADL, Instrumental Activities of Daily Living; MMSE, Mini-Mental State Examination; AChEi, acetylcholinesterase inhibitors; NSAIDs, nonsteroidal anti-inflammatory drugs. ^ap < 0.05 for Healthy versus MCI; ^b p < 0.05 for Healthy versus AD; ^c p < 0.05 for MCI versus AD.

Raw BAP/d-ROM data versus measurement date, subdivided by cognitive status for both control and experimental groups are shown as scatterplots in Fig. 1. A GLMM was used to identify differences in the mean levels of BAP/d-ROM in relation to intervention and among cognitive groups. We observed significant differences of BAP/d-ROM mean levels between control and experimental groups within HE and AD at baseline, as well as in experimental versus control group within AD at 1st follow-up (Fig. 1). Since BAP/d-ROM levels showed increasing values over measurement date in both control and experimental groups at baseline and at 1st follow-up (Fig. 1), we suspected that the observed differences could have arisen from seasonal variations or batch effects. Since no association was found between BAP/d-ROM data and seasonal variations, which could have mimicked a batch effect (data not shown), we performed the same model after removal of batch effects (as indicated in methods). Once batch effects were removed, we failed to observe any significant difference between control and experimental groups either at baseline or at any follow-up by GLMM (Fig. 2). The GLMM was significant (F = 1.664; p = 0.023) and showed no differences across time (F = 2.495; p = 0.059), cognitive groups (F = 0.548; p = 0.579), and intervention (F = 0.000; p = 0.991). Moreover, there were no significant effects of intervention and time among the groups (F = 0.478; p = 0.963). Females showed a lower level of BAP/d-ROM respect to males (F = 20.152; p < 0.001). This result was independent by the method used to identify and correct batches. Correlation analysis also failed to identify any relationship between MMSE and oxidative stress.

The results of the GLM were not affected even after including as independent variables the frequency of subjects undergoing drug therapy with pharmacological categories potentially influencing oxidative stress levels (i.e., acetylcholinesterase inhibitors, lipid lowering medications, antihypertensive, nonsteroidal anti-inflammatory drugs (data not shown). Estimated marginal means of both BAP and d-ROM data showed a similar pattern across groups and time, with no significant variation between experimental and control groups. However, d-ROM data corrected for batch effects presented a clear distinction between men and women, with positive values for women in each time-point (Fig. 3), explaining the lower level of BAP/d-ROM for women.

Fig.1

Scatterplots of Log (BAP/d-ROM) data by measurement date, intervention and cognitive status (n = 1004). Lines represent mean of Log (BAP/d-ROM) for control and experimental groups (continuous lines for control and dashed lines for experimental groups), at each observation, calculated on raw data. Dots represent single values of Log (BAP/d-ROM). Significance is referred to pairwise comparison with Bonferroni correction of a generalized linear model using Log (BAP/d-ROM) as dependent variable.

Fig.2

Estimated means of batch corrected Log (BAP/d-ROM) data obtained from a generalized linear mixed effects model by time [Baseline, first follow-up at the end of the training (F1); second follow-up after 6 months from the end of the training (F2); third follow-up after 2 years from the end of the training (F3)], cognitive group (AD, MCI, and HE) and intervention (control and experimental groups). Estimated means are displayed as open circles connected by grey lines for control and as filled circles connected by dark lines for experimental groups. Bars show the 95 % confidence interval of the mean. No significant differences were observed within and between cognitive and intervention groups during the trial.

Fig.3

Log (BAP) and Log (d-ROM) by gender (M = males, represented by black circles and lines; F = females, represented as grey circles and lines) and time [Baseline, first follow-up at the end of the training (F1); second follow-up after 6 months from the end of the training (F2); third follow-up after 2 years from the end of the training (F3)]. Log (BAP) and Log (d-ROM) were corrected for batch effect before the analysis. Data are means with error bars showing 95 % confidence interval of the mean. ^*p < 0.05 compared to males.

DISCUSSION

An imbalance in pro-oxidant and antioxidant defenses has been proposed in the pathophysiology of AD [10]. The evaluation of oxidative stress markers has been additionally suggested as useful tool to evaluate the efficacy of intervention and the progression of the disease [57, 58].

There are several biomarkers of oxidative status that can be measured in blood including end-products of lipid peroxidation (malondialdehyde), damaged proteins (protein carbonyls), products related to early oxidative damage (organic hydroperoxides) or biomarkers related to enzymatic or non-enzymatic antioxidants and repair molecules [6, 59].

The d-ROMs test has recently emerged as one of the favored assays for the quantification of serum/plasma oxidative status. The test provides an indirect estimate of organic hydroperoxides, which are the primary products of lipid peroxidation [60]. In the present study, we evaluated BAP/d-ROM in AD, MCI, and healthy subjects, but we have found no significant association among cognitive status, intervention, and time of follow-up.

By contrast, a Japanese study [61] comparing AD versus controls, found a lower BAP/d-ROM in AD, suggesting the presence of imbalance in pro-oxidant and antioxidant defenses in this disease and that interventions targeting oxidative stress could be considered an appropriate therapy in AD. However, in the latter study, the sample size was limited and the control group consisted of 82% male subjects versus the 44% of the AD group. This large discrepancy, combined with our observation of a gender-related effect on the BAP/d-ROM, could explain the contrasting results.

In another study assessing oxidative stress with different methods, the proportion of females in the AD group was also higher (70% ) than the control group (60% ) [62]. Although the authors corrected the data for gender, it is likely that the small sample size (n = 30 per group) and the high variability (approximately 50% as % RSD) of the measurement (as also observed in our study) might have affected the results. Small sample size, strict selection of participants and the use of data non-corrected for batch effects (which is usually necessary in long term studies with follow-up) may have affected also another recent observation related to a significant effect of memory training on oxidative stress parameters [34]. Moreover, a recent report on a large population sample of older adults found a modest association between d-ROMs and cognitive functions both cross-sectionally and at 3-year follow-up in early old age and no association between BAP status and cognitive performance [63]. In addition, antioxidant clinical trials in AD or MCI patients report no evidence that vitamin E prevents progression to dementia, or improves cognitive function [64, 65], suggesting that oxidative stress damage does not play a predominant role in cognitive decline and AD pathogenesis. On the other hand, there is still a controversy on the validity of the measurement of d-ROM test as valuable assay for the quantification of plasma or serum early oxidative damage molecules [66]. Some authors defend the reliability of the measurement [67], while others reported that the d-ROMs test can determine ceruloplasmin activity with additional potential interferences from hydroperoxides, iron, thiols, and albumin levels [68, 69]. In any case, even the authors defending the d-ROM test validity to detect hydroperoxides, propose that ceruloplasmin may account for a 6–7% of the measurement [67], which in human studies may still affect the results when comparing large number of subjects with different ceruloplasmin levels. We observed a significant lower BAP to d-ROM in females which depends on increased d-ROM levels in women. Our data are in agreement with previous observation on a higher oxidative stress in females compared to males [70, 71]. Interestingly, a common feature of these studies is that they evaluated oxidative stress by the d-ROM test. The higher concentrations of d-ROMs measured in females may thus be consistent with the increased copper and ceruloplasmin levels that characterize females compared to males [72, 73]. While an increase of copper was also reported in AD [74], in our population we did not observe a difference in plasma copper among AD, MCI, and healthy subjects at baseline (data not shown).

Strengths of the present study include the longitudinal study design, the relative large population-based study sample, the repeated measurements of BAP/d-ROM at four time points and the association with a comprehensive intervention. One limitation of the study is the absence of a combination of oxidative stress biomarkers.

It is noteworthy to mention that our previous studies, which evaluated the effect of the intervention in some cognitive and noncognitive outcomes, evidenced a significant effect in experimental groups respect to control groups [32]. In particular, at the end of the treatment, we found a positive effect of the intervention on the Alzheimer’s Disease Assessment Scale score in subjects with dementia. The My Mind study showed that, in subjects with MCI, intervention affected selectively platelet total phospholipases A2 activity, modulating only individuals with deregulated values in comparison to HE [75]. In another of our recent studies, which compared demented subjects and HE, the intervention was found to induce positive short-term effects on BDNF [76]. In conclusion, while we cannot still exclude a role of oxidative stress in AD, our findings highlight the limit of d-ROM test in clinical settings as diagnostic or prognostic biomarker and exclude the possibility to modulate the BAP to d-ROM ratio with the intervention.

Footnotes

ACKNOWLEDGMENTS

The authors thank Dr. Domenico Venarucci for the support with data collection and scientific activities. The study was supported by the “Ricerca Finalizzata” grant 154/GR-2009-1584108 funded by the Italian Ministry of Health and the Marche Region.

Authors’ disclosures available online ().

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