1. Introduction
Aging is a natural and multifactorial process determined by both genetic and environmental factors that begins even before birth [1]. One of the key characteristics of aging is a steady increase in Oxidative Stress (OS) and inflammatory responses. These phenomena are associated with an enhancement of cellular senescence and organ dysfunction resulting, in turn, in a gradual decline in human physical and mental faculties. OS, indeed, can influence and modify the homeostatic balances and significantly alter cellular responses to injuries [2]. Since peri-conceptional oxidative imbalance can even affect fetal development, as well as later health status, we can state that the aging process begins before birth [3]. Indeed, OS occurs clearly during the early stages of pregnancy and then continues during the postnatal period and throughout the lifespan.
To date, several theories have been proposed to explain the aging process, but none of them have yet to be completely accepted by the scientific community. Among these, the “free radical theory”, also known as the “Mitochondrial Free Radical Theory of Aging” (MFRTA), has been, and continues to be, the basis of extensive research on the interplay between OS and the onset of degenerative conditions associated with the aging process [4]. MFRTA proposes that aging is caused by general and prolonged damage to macromolecules caused by Reactive Oxygen Species (ROS) produced in mitochondria, through a vicious cycle in which ROS damage to mitochondrial constituents lead to further generation of other ROS [5]. The strengths of this theory are the following: (i) a strong correlation between chronological age and the levels of both ROS generation and oxidative damage, (ii) the gradual loss of mitochondrial functions during aging, (iii) the enhancement in ROS production due to the inhibition of mitochondrial functions, and (iv) the association between a severe increase of OS and several age-dependent conditions and diseases [6]. Partially contrasting with the MFRTA, evidence emerged in recent years which hypothesized that ROS may also be potentially lifespan-promoting, signalling molecules transducing messages from the mitochondria to other organelles in the cell [7,8]. According to this theory, low-level oxidative damage can culminate in increased stress resistance and, ultimately, in longevity. This adaptive response is marked by biphasic dose–response patterns to the ROS-related stress in mitochondria and can be considered a case of hormesis [9,10,11].
Among factors able to upregulate and modulate OS during the lifespan, an important role is played by sexual hormones. These molecules can have opposite and diverse systemic effects: they can be involved in cellular protection, via their anti-oxidant properties [12,13], and in cellular toxicity, via their pro-oxidant properties [14,15,16,17]. Sexual hormones are produced throughout the lifespan of an organism, including during prenatal development, puberty, and aging [18,19].
In post-menopausal women, the progressive depletion of estrogen and its protective effect, combined with deficient antioxidant defence, can lead to a pronounced redox imbalance, in addition to the known symptoms [20,21]. Indeed, compared to pre-menopausal women, post-menopausal women have higher levels of lipoperoxide [22], pro-inflammatory cytokines [23] and, in general, higher levels of OS biomarkers [24]. Unfortunately, while many studies have focused on the relationship between sex hormones and OS during the menopausal window, only a few studies have analyzed the same relationship during childhood and adolescence. Specifically, even puberty is a crucial phase in human growth and development, and the possible positive or negative mediating roles of sex hormones on OS during this stage is still incomplete.
In this perspective, the main purpose of this work was to analyze the following: (i) the trend of OS during a lifespan, from age seven to sixty years old; (ii) the peculiar trend of OS during two delicate and sensitive hormonal windows, namely, puberty and menopause. The introduction briefly places the study in its broad context and highlights why it is important. It defines the purpose of the work and its significance. The current state of the research field is carefully reviewed and key publications cited. Controversial and diverging hypotheses are highlighted when necessary. Finally, the main aim of the work and the principal conclusions are highlighted.
2. Materials and Methods
2.1. Epidemiological Sample
The epidemiological sample for the present study was constituted by a combination of subjects enrolled in 5 previous studies, carried out between 2009 and 2015 [25,26,27,28,29]. The general purpose of the relevant projects was to investigate OS levels in humans, according to two different expositive approaches, namely working and living environments. All the studies were characterized by a similar protocol, requiring the following: (i) a standardized questionnaire, focusing on personal characteristics and lifestyle habits; (ii) a spot urine sample for the OS biomarker analyses. In studies enrolling workers, only healthy white-collar subjects, and not occupationally exposed subjects, were included in the present study.
2.2. OS Biological Measurements
All the subjects were asked to give a spot of urine to measure OS stress levels through a well-known biomarker, namely, 15-F2t-isoprostane (15-F2t-Isop).
Concentrations of urinary OS biomarkers proposed as an effective biomarker to survey populations exposed to xenobiotics, such as particulates, and more information on the 15-F2t-Isop, can be found elsewhere [30,31]. The biomarker, 15-F2t-Isop, is relatively stable in urine [32] and can be measured by two main analytical approaches: mass-based techniques (Gas Chromatography (GC) or Liquid Chromatography (LC)) and immunological techniques. Even if Gas Chromatography–Mass Spectrometry (GC–MS) is the gold standard, immunological techniques are widely used to measure 15-F2t-Isop, because these assays are cost-effective, rapid, and easy to quantify. In all the biological samples, 15-F2t-Isop was analyzed through a competitive enzyme-linked immunoassay (ELISA) (EA85, Oxford biomedical, Oxford, MI, USA), following the manufacturer’s instructions. To normalize the excretion rate of 15-F2t-IsoP, an aliquot of fresh urine was used to quantify the concentration of creatinine (CREA) by means of the kinetic Jaffè procedure.
Our previous papers report all the details of this procedure [27,33,34].
2.3. Confounding Factors
To control the most important confounding factors of OS imbalance, we evaluated the living environment, the Body Mass Index (BMI), and smoking habits.
-
-. BMI: self-reported height and weight were used to calculate BMI ([Weight (kg)]/[(Height (m))2]) and the epidemiological sample was classified as Underweight, Normal, Overweight, or Obese according to the reference values provided by the OMS for the different age groups [35]. In the present study, we grouped the subjects as Overweight or Obese (OwO) and not overweight or obese (not OwO).
-
-. Smoking habit: subjects were asked to indicate whether they were exposed or not to tobacco smoke and, consequently, each subject was categorized as a non-smoker or an active smoker.
2.4. Statistical Analyses
The demographic, personal and biological characteristics and measurements of the subjects were summarized as absolute and relative frequencies for categorical variables and as mean (±SD) for continuous variables. The age variable was categorized in two different hormonal windows: puberty [36] (>10 years old = pre-puberty/11–14 years old = puberty/15–20 years old = post-puberty) and menopause [37] (39–45 years old = pre-menopause/46–50 years old = early menopause/50–60 years old = late menopause). Due to the hierarchical structure of our data (815 subjects from 5 different studies), a regression model was performed to assess the association between 15-F2t-Isop, as the dependent variable, linear and categorized age, sex, being OwO, and smoking habit, as independent variables. All the models were performed in the sample and then stratified for sex and age class. The results were reported as B coefficients (B) with 95% Confidence Intervals (CIs). All analyses were carried out using the STATA 16.1 software (Stata Corp LLC: College Station, TX, USA).
3. Results
Table 1 reports demographic, individual and biological characteristics of all the epidemiological samples and of sub-groups, according to the two hormonal windows of puberty and menopause.
Eight Hundred and Fifteen subjects, aged from 7 to 60 years of age were analyzed, of whom 49.2% were males. Thirty-two percent of the whole sample were classified as being OwO, of whom 39.6% were male and 24.6% female. The tobacco smoking habit, according to Italian trends [38], showed a prevalence of around 19%, higher in males. Finally, the OS level, quantified through 15-F2t-Isop, is reported in Table 1, following the same classification employed above. Figure 1 shows the increasing trend observed during the lifespans of all enrolled subjects.
A regression model was performed, with 15-F2t-Isop as the dependent variable, and age, sex, being OwO, and smoking habits, as the independent variables (Table 2). In the whole sample, the model showed a significant association with sex [B = 1.2 95% CI 0.81–1.6, p < 0.001] and age [B = 0.02 95% CI 0.02–0.04, p < 0.001], respectively. Instead, OwO and smoke did not show significant associations. The same model, stratified by means of sex, showed a statistical association between OS and age, but only in females [B = 0.06 95% CI 0.05–0.08, p < 0.001].
Since the purpose of this work was to analyze the possible mediator role of hormones on redox modulation, additional statistical analyses were performed focusing on the two hormonal windows previously mentioned.
In subjects in the pubertal age group, the regression model did not show any significant association, while it revealed a positive association in the female subgroup [B= −0.06 95% CI −0.07–−0.04, p = 0.41]. To deepen the insight into this association, the sample was stratified in terms of sex (Figure 2). The pairwise comparisons of means with equal variance (Table 3) showed a significant V-shape decrease of OS levels, but only in females (Tukey’s test 1 (pre-puberty) vs. 2 (puberty): −2.8, p < 0.001 95% CI [−1.1/−0.4]; 2 (puberty) vs. 3 (post-puberty): 2.4, p = 0.01 95% CI [0.5/4.4]).
The same pattern of statistical analyses was adopted concerning the menopausal window. In this case too, the regression did not show any significant association in the whole epidemiological sample. Conversely, in the female subgroup, the association between OS and age turned out to be significant [B= −1.01 95% CI −1.5–−0.5, p < 0.001]. After the stratification in terms of sex (Figure 3), the pairwise comparisons of means with equal variance (Table 4) showed the same significant V-shape decrease of OS levels in females (Tukey’s contrast 4 (pre-menopause) vs. 5 (menopause): −1.5, p = 0.03 95% CI [−3.8/−0.8]; Tukey’s contrast 5 (menopause) vs. 6 (post-menopause): 0.4, p = 0.04 95% CI [0.2/2.3]).
4. Discussion
Our results confirmed an association between OS and aging. The 15-F2t-Isop levels increased with increasing age. However, our research had a cross-sectional design and this could represent a limitation, as it did not allow the assessment of a causal direction of the observed associations.
However, our results enabled us to lay the groundwork for future analyses. Consistently with previous studies, our findings attested to a direct and positive trend between OS and aging. This process is a time-dynamic mechanism, characterized by the gradual accumulation of damage, progressive functional decline and increased vulnerability to diseases [39]. OS plays a key role in this phenomenon, mainly due to the overproduction of free radicals, such as ROS, overwhelming the body’s antioxidant defences [21]. The free radical theory of aging is based on a structural damage-based hypothesis in which age-associated functional losses are due to the accumulation of oxidative injury to macromolecules (lipids, DNA, and proteins) induced by ROS [40]. Nevertheless, the exact mechanism behind this relationship is still not clear, but is probably related to the onset of cellular senescence, a physiological mechanism that stops cellular proliferation in response to damage occurring during replication. In physiological conditions, antioxidants neutralize ROS, preventing the subsequent increase of oxidative damage [1]. However, as the body ages, antioxidant levels and activities decline, leaving the human body susceptible to the onset of several age-related pathologies [39,41].
The most important result of our research was the V-shape OS trend in females in the age windows associated with key hormonal changes: puberty and menopause. In fact, after the stratification by sex, the statistical analyses showed a V-shape association between the 15-F2t-Isop levels and age classes, with a significant decrease in subjects belonging to puberty and early menopause classes. The literature provides some evidence that OS influences the entire reproductive span, even more in women. This OS imbalance, indeed, is frequently combined with a gradual modification in the hormonal profile, particularly in females [42,43]. Recently, many studies have investigated the relationship between hormonal changing and OS during aging and, in particular, during the menopausal window. On the contrary, few researches have investigated the same association in the puberty window [44,45], mainly focusing on pathological conditions (e.g., diabetes and obesity) [46,47] or infertility [48,49]. These studies revealed that the physiologically marked reduction in estrogen during puberty or menopause can result in unbalanced OS in the body, mainly related to the concentration and chemical structure of the estrogen hormone [15]. Specifically, at high concentrations, estrogen tends to have a beneficial antioxidant effect by inhibiting the 8-hydroxylation of guanine DNA bases [21]. On the contrary, low levels of this hormone have pro-oxidant effects, especially when its chemical structure contains a catechol, leading to breaks in genetic material, formation of DNA adducts, and oxidation of bases [50].
Strengths and Limitations
This study has several strengths. First, the use of big data from five different cross-sectional studies, following standardized and homogeneous protocols [25,26,27,28,29], allowed the analysis of a representative sample aged from seven to sixty years of age. Moreover, according to our knowledge, this is the first study investigating the association between hormones and OS simultaneously in puberty and menopausal windows, providing specific data, which matches the important issue of investigating the relationship between hormonal mediations and redox upregulation and balance. In line with previous studies [15,21,22], we provided evidence that hormones, and, in particular, estrogen in females, could mediate and upregulate OS with different results, and this could offer important implications for future research and policies.
The cross-sectional design of the present study and the deficiency of a common protocol represented the main limitations, as these limitations did not allow us to assess the causal direction of the associations, with consequences on the interpretation of the data/results. Another limitation was the lack of precise and hormonally-addressed exclusion/inclusion criteria (e.g., hormonal therapy and contraception, hormonal disorder, premature ovarian failure, and alkaloid therapy), and this must be taken into account for the future analyses.
5. Conclusions
In this perspective, our results supported the fact that hormones, and specifically estrogen, could modulate the 15-F2t-Isop levels, especially during age windows associated with puberty and menopause. Our findings suggested that the V-shape trend in the temporal trajectories of OS may be related to the intrinsic characteristics of estrogen, which is able to modulate and upregulate OS pro- and anti-oxidant mechanisms. A growing number of studies to date have pointed towards the importance of the role of OS in female reproduction, and this evidence must be taken into account. Further investigations are needed to better understand the specific mechanisms through which hormones may interact with oxidative status, to offer valuable knowledge for future studies targeting disease prevention and public health promotion strategies.
Conceptualization, R.B., G.S. and V.B.; methodology, R.B. and V.B.; software and formal analysis, R.I.C., P.D. and V.B.; writing—original draft preparation, R.B., F.G. and V.B.; writing—review and editing, G.S., F.G., M.P., R.I.C. and P.D. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Bioethical Committee of the University of Turin (Protocol number 60344) and Ethics Committee “San Luigi Gonzaga Hospital”, protocol number 826/13/08.)
Informed consent was obtained from all subjects involved in the study.
The data that support the findings of this study are available on request from the corresponding author (G.S.).
We are grateful to all subjects who actively participated in the studies.
The authors declare no conflict of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Enlarge this image.Figure 2. The 15-F2t-Isop levels in the age of puberty (>10 years old = pre-puberty/11–14 years old = puberty /15–20 years old = post-puberty), stratified by sex (** = p < 0.001).
Enlarge this image.Figure 3. The 15-F2t-Isop levels in the menopause age groups (39–45 years old = pre-menopause/46–50 years old = early menopause/50–60 years old = late menopause), stratified by sex (** = p < 0.001).
Descriptive of the characteristics of all the samples and sub-grouped into hormonal windows (puberty and menopause).
| All sample (N = 815) | Puberty |
Menopause |
|||
|---|---|---|---|---|---|
| Gender (%) | Male: 401 (49.2%) |
Pre-puberty | Male: 43 (57.3%) |
Pre-menopause | Male: 53 (42.4%) |
| Puberty | Male: 80 (50.3%) |
Early menopause | Male: 45 (38.8%) |
||
| Post-puberty | Male: 33 (58.9%) |
Late menopause | Male: 61 (45.5%) |
||
|
Age (years)
|
32.6 ± 0.6 |
Pre-puberty | 8.9 ± 0.1 | Pre-menopause | 41.8 ± 0.1 |
| Puberty | 12.8 ± 0.08 | Early menopause | 47.7 ± 0.1 | ||
| Post-puberty | 17.7 ± 0.1 | Late menopause | 55.1 ± 0.2 | ||
| OwO (%) | 261 (32%) |
Pre-puberty | Male: 8 (18.6%) |
Pre-menopause | Male: 14 (26.4%) |
| Puberty | Male: 17 (21.2%) |
Early menopause | Male: 11 (24.4%) |
||
| Post-puberty | Male: 8 (24.2%) |
Late menopause | Male: 16 (26.2%) |
||
| Tobacco Smoke (%) | No: 654 (80.2%) |
Pre-puberty | No: 75 (100%) |
Pre-menopause | No: 83 (66.4%) |
| Puberty | No: 156 (98.1%) |
Early menopause | No: 90 (77.6%) |
||
| Post-puberty | No: 43 (76.8%) |
Late menopause | No: 99 (73.9%) |
||
|
15-F2t-Isop [ng/mgCREA]
|
4.6 ± 5.2 |
Pre-puberty | 5.5 ± 0.9 |
Pre-menopause | 5.8 ± 5.7 |
| Puberty | 4.8 ± 0.4 |
Early menopause | 4.1 ± 3.2 |
||
| Post-puberty | 5.1 ± 0.8 |
Late menopause | 5.2 ± 5 |
||
Regression model in the whole sample between 15-F2t-Isop (dependent variable) and sex, being OwO, smoking habit and age (continuous) as independent variables.
| Regression Model (All Sample) | |||||
|---|---|---|---|---|---|
| F2t-Isop [ng/mgCREA] | B Coef. | Std.Err. | z | p > |z| | C.I. [95%] |
| Sex | 1.2 | 0.2 | 6.1 | <0.001 | 0.81/1.6 |
| OwO | −0.3 | 0.2 | −1.4 | 0.16 | −0.7/0.11 |
| Smoke | 0.09 | 0.07 | 1.3 | 0.19 | −0.05/0.24 |
| Age | 0.02 | 0.005 | 4.9 | <0.001 | 0.02/0.04 |
Pairwise comparisons of means with equal variances in puberty classes (1 = pre-puberty/2 = puberty/3 = post-puberty), stratified by sex.
| Pairwise Comparisons of Means with Equal Variances | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | |||||||||
| Puberty Classes | Tukey Contrast | Std.Err. | Tukey t | p > |t| | C.I. [95%] | Tukey Contrast | Std.Err. | Tukey t | p > |t| | C.I. [95%] |
| 2 vs. 1 | −1.8 | 0.6 | −2.8 | 0.2 | −3.4/0.3 | −2.8 | 0.7 | −3.9 | 0.001 | −3.1/−0.4 |
| 3 vs. 1 | 0.6 | 0.8 | 0.7 | 0.7 | −1.3/2.5 | −0.4 | 0.9 | −0.4 | 0.9 | −2.6/1.8 |
| 3 vs. 2 | 2.4 | 0.7 | 3.4 | 0.3 | −0.7/4.1 | 2.4 | 0.8 | 2.9 | 0.01 | 0.5/4.4 |
Pairwise comparisons of means with equal variances in menopause classes (4 = pre-menopause/5 = menopause/6 = post-menopause), stratified by sex.
| Pairwise Comparisons of Means with Equal Variances | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | |||||||||
| Puberty Classes | Tukey Contrast | Std.Err. | Tukey t | p > |t| | C.I. [95%] | Tukey Contrast | Std.Err. | Tukey t | p > |t| | C.I. [95%] |
| 5 vs. 4 | −1.9 | 1.1 | −1.8 | 0.17 | −4.6/0.6 | −1.5 | 0.9 | −1.5 | 0.03 | −3.8/−0.8 |
| 6 vs. 4 | 1.1 | 1.09 | 0.9 | 0.6 | −1.5/3.6 | −1.1 | 1.1 | −1 | 0.6 | −3.7/1.5 |
| 6 vs. 5 | 3.1 | 1.1 | 2.7 | 0.2 | −0.35/5.7 | 0.4 | 1.1 | 0.3 | 0.04 | 0.2/2.3 |
References
1. Marseglia, L.; D’Angelo, G.; Manti, S.; Arrigo, T.; Barberi, I.; Reiter, R.J.; Gitto, E. Oxidative Stress-Mediated Aging during the Fetal and Perinatal Periods. Oxid. Med. Cell. Longev.; 2014; 2014, 358375. [DOI: https://dx.doi.org/10.1155/2014/358375] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25202436]
2. Haines, D.D.; Juhasz, B.; Tosaki, A. Management of multicellular senescence and oxidative stress. J. Cell. Mol. Med.; 2013; 17, pp. 936-957. [DOI: https://dx.doi.org/10.1111/jcmm.12074] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23789967]
3. Lewis, R.M.; Cleal, J.K.; Hanson, M.A. Review: Placenta, evolution and lifelong health. Placenta; 2012; 33, pp. S28-S32. [DOI: https://dx.doi.org/10.1016/j.placenta.2011.12.003] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22205051]
4. Hekimi, S.; Lapointe, J.; Wen, Y. Taking a ‘good’ look at free radicals in the aging process. Trends Cell Biol.; 2011; 21, pp. 569-576. [DOI: https://dx.doi.org/10.1016/j.tcb.2011.06.008]
5. Balaban, R.S.; Nemoto, S.; Finkel, T. Mitochondria, oxidants, and aging. Cell; 2005; 120, pp. 483-495. [DOI: https://dx.doi.org/10.1016/j.cell.2005.02.001]
6. Park, C.B.; Larsson, N.G. Mitochondrial DNA mutations in disease and aging. J. Cell Biol.; 2011; 193, pp. 809-818. [DOI: https://dx.doi.org/10.1083/jcb.201010024]
7. Finley, L.W.S.; Haigis, M.C. The coordination of nuclear and mitochondrial communication during aging and calorie restriction. Ageing Res. Rev.; 2009; 8, pp. 173-188. [DOI: https://dx.doi.org/10.1016/j.arr.2009.03.003]
8. Ristow, M.; Zarse, K.; Oberbach, A.; Klöting, N.; Birringer, M.; Kiehntopf, M.; Stumvoll, M.; Kahn, C.R.; Blüher, M. Antioxidants prevent health-promoting effects of physical exercise in humans. Proc. Natl. Acad. Sci. USA; 2009; 106, pp. 8665-8670. [DOI: https://dx.doi.org/10.1073/pnas.0903485106]
9. Calabrese, E.J.; Bachmann, K.A.; Bailer, A.J.; Bolger, P.M.; Borak, J.; Cai, L.; Cedergreen, N.; Cherian, M.G.; Chiueh, C.C.; Clarkson, T.W. et al. Biological stress response terminology: Integrating the concepts of adaptive response and preconditioning stress within a hormetic dose-response framework. Toxicol. Appl. Pharmacol.; 2007; 222, pp. 122-128. [DOI: https://dx.doi.org/10.1016/j.taap.2007.02.015]
10. Ristow, M.; Zarse, K. How increased oxidative stress promotes longevity and metabolic health: The concept of mitochondrial hormesis (mitohormesis). Exp. Gerontol.; 2010; 45, pp. 410-418. [DOI: https://dx.doi.org/10.1016/j.exger.2010.03.014]
11. Bjelakovic, G.; Nikolova, D.; Gluud, L.L.; Simonetti, R.G.; Gluud, C. Mortality in randomized trials of antioxidant supplements for primary and secondary prevention: Systematic review and meta-analysis. JAMA; 2007; 297, pp. 842-857. [DOI: https://dx.doi.org/10.1001/jama.297.8.842]
12. Nicks, K.M.; Fowler, T.W.; Gaddy, D. Reproductive hormones and bone. Curr. Osteoporos. Rep.; 2010; 8, pp. 60-67. [DOI: https://dx.doi.org/10.1007/s11914-010-0014-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20425612]
13. Moreau, K.L. Modulatory influence of sex hormones on vascular aging. Am. J. Physiol. Heart Circ. Physiol.; 2019; 316, pp. H522-H526. [DOI: https://dx.doi.org/10.1152/ajpheart.00745.2017] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30632767]
14. Tenkorang, M.A.; Snyder, B.; Cunningham, R.L. Sex-related differences in oxidative stress and neurodegeneration. Steroids; 2018; 133, pp. 21-27. [DOI: https://dx.doi.org/10.1016/j.steroids.2017.12.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29274405]
15. Duong, P.; Tenkorang, M.A.A.; Trieu, J.; McCuiston, C.; Rybalchenko, N.; Cunningham, R.L. Neuroprotective and neurotoxic outcomes of androgens and estrogens in an oxidative stress environment. Biol. Sex Differ.; 2020; 11, 12. [DOI: https://dx.doi.org/10.1186/s13293-020-0283-1]
16. Holmes, S.; Singh, M.; Su, C.; Cunningham, R.L. Effects of Oxidative Stress and Testosterone on Pro-Inflammatory Signaling in a Female Rat Dopaminergic Neuronal Cell Line. Endocrinology; 2016; 157, pp. 2824-2835. [DOI: https://dx.doi.org/10.1210/en.2015-1738]
17. Snyder, B.; Duong, P.; Trieu, J.; Cunningham, R.L. Androgens modulate chronic intermittent hypoxia effects on brain and behavior. Horm. Behav.; 2018; 106, pp. 62-73. [DOI: https://dx.doi.org/10.1016/j.yhbeh.2018.09.005]
18. Decaroli, M.C.; Rochira, V. Aging and sex hormones in males. Virulence; 2017; 8, pp. 545-570. [DOI: https://dx.doi.org/10.1080/21505594.2016.1259053]
19. Auyeung, B.; Lombardo, M.V.; Baron-Cohen, S. Prenatal and postnatal hormone effects on the human brain and cognition. Pflugers Arch.; 2013; 465, pp. 557-571. [DOI: https://dx.doi.org/10.1007/s00424-013-1268-2]
20. Rao, P.M.; Kelly, D.M.; Jones, T.H. Testosterone and insulin resistance in the metabolic syndrome and T2DM in men. Nat. Rev. Endocrinol.; 2013; 9, pp. 479-493. [DOI: https://dx.doi.org/10.1038/nrendo.2013.122]
21. Doshi, S.; Agarwal, A. The role of oxidative stress in menopause. J. Midlife. Health; 2013; 4, 140. [DOI: https://dx.doi.org/10.4103/0976-7800.118990]
22. Sánchez-Rodríguez, M.A.; Zacarías-Flores, M.; Arronte-Rosales, A.; Correa-Muñoz, E.; Mendoza-Núñez, V.M. Menopause as risk factor for oxidative stress. Menopause; 2012; 19, pp. 361-367. [DOI: https://dx.doi.org/10.1097/gme.0b013e318229977d] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21971210]
23. Vural, P.; Canbaz, M.; Akgul, C. Effects of menopause and postmenopausal tibolone treatment on plasma TNFalpha, IL-4, IL-10, IL-12 cytokine pattern and some bone turnover markers. Pharmacol. Res.; 2006; 53, pp. 367-371. [DOI: https://dx.doi.org/10.1016/j.phrs.2006.01.005] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16503406]
24. Signorelli, S.S.; Neri, S.; Sciacchitano, S.; Di Pino, L.; Costa, M.P.; Marchese, G.; Celotta, G.; Cassibba, N.; Pennisi, G.; Caschetto, S. Behaviour of some indicators of oxidative stress in postmenopausal and fertile women. Maturitas; 2006; 53, pp. 77-82. [DOI: https://dx.doi.org/10.1016/j.maturitas.2005.03.001] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16325025]
25. Bono, R.; Capacci, F.; Cellai, F.; Sgarrella, C.; Bellisario, V.; Trucco, G.; Tofani, L.; Peluso, A.; Poli, C.; Arena, L. et al. Wood dust and urinary 15-F2t isoprostane in Italian industry workers. Environ. Res.; 2019; 173, pp. 300-305. [DOI: https://dx.doi.org/10.1016/j.envres.2019.03.058]
26. Bellisario, V.; Piccioni, P.; Bugiani, M.; Squillacioti, G.; Levra, S.; Gulotta, C.; Mengozzi, G.; Perboni, A.; Grignani, E.; Bono, R. Tobacco smoke exposure, urban and environmental factors as respiratory disease predictors in Italian adolescents. Int. J. Environ. Res. Public Health; 2019; 16, 4048. [DOI: https://dx.doi.org/10.3390/ijerph16204048]
27. Bellisario, V.; Mengozzi, G.; Grignani, E.; Bugiani, M.; Sapino, A.; Bussolati, G.; Bono, R. Towards a formalin-free hospital. Levels of 15-F2t-isoprostane and malondialdehyde to monitor exposure to formaldehyde in nurses from operating theatres. Toxicol. Res.; 2016; 5, pp. 1122-1129. [DOI: https://dx.doi.org/10.1039/C6TX00068A]
28. Bono, R.; Bellisario, V.; Romanazzi, V.; Pirro, V.; Piccioni, P.; Pazzi, M.; Bugiani, M.; Vincenti, M. Oxidative stress in adolescent passive smokers living in urban and rural environments. Int. J. Hyg. Environ. Health; 2014; 217, pp. 287-293. [DOI: https://dx.doi.org/10.1016/j.ijheh.2013.06.008]
29. Jacquemin, B.; Siroux, V.; Sanchez, M.; Carsin, A.-E.; Schikowski, T.; Adam, M.; Bellisario, V.; Buschka, A.; Bono, R.; Brunekreef, B. et al. Ambient air pollution and adult asthma incidence in six european cohorts (Escape). Environ. Health Perspect.; 2015; 123. [DOI: https://dx.doi.org/10.1289/ehp.1408206]
30. Hopf, N.B.; Bourgkard, E.; Demange, V.; Hulo, S.; Sauvain, J.J.; Levilly, R.; Jeandel, F.; Robert, A.; Guichard, Y.; Pralong, J.A. et al. Early Effect Markers and Exposure Determinants of Metalworking Fluids Among Metal Industry Workers: Protocol for a Field Study. JMIR Res. Protoc.; 2019; 8, e13744. [DOI: https://dx.doi.org/10.2196/13744]
31. Romanazzi, V.; Pirro, V.; Bellisario, V.; Mengozzi, G.; Peluso, M.; Pazzi, M.; Bugiani, M.; Verlato, G.; Bono, R. 15-F2t isoprostane as biomarker of oxidative stress induced by tobacco smoke and occupational exposure to formaldehyde in workers of plastic laminates. Sci. Total Environ.; 2013; 442, pp. 20-25. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2012.10.057] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23178760]
32. Roberts, L.J.; Morrow, J.D. Measurement of F(2)-isoprostanes as an index of oxidative stress in vivo. Free Radic. Biol. Med.; 2000; 28, pp. 505-513. [DOI: https://dx.doi.org/10.1016/S0891-5849(99)00264-6] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/10719231]
33. Bono, R.; Bellisario, V.; Tassinari, R.; Squillacioti, G.; Manetta, T.; Bugiani, M.; Migliore, E.; Piccioni, P. Bisphenol a, tobacco smoke, and age as predictors of oxidative stress in children and adolescents. Int. J. Environ. Res. Public Health; 2019; 16, 2025. [DOI: https://dx.doi.org/10.3390/ijerph16112025] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31174388]
34. Squillacioti, G.; Bellisario, V.; Grignani, E.; Mengozzi, G.; Bardaglio, G.; Dalmasso, P.; Bono, R. The Asti Study: The Induction of Oxidative Stress in A Population of Children According to Their Body Composition and Passive Tobacco Smoking Exposure. Int. J. Environ. Res. Public Health; 2019; 16, 490. [DOI: https://dx.doi.org/10.3390/ijerph16030490]
35. WHO. WHO European Regional Obesity Report 2022; WHO: Geneva, Switzerland, 2022.
36. Sacks, D. Age limits and adolescents. Paediatr. Child Health; 2003; 8, 577. [DOI: https://dx.doi.org/10.1093/pch/8.9.577]
37. Weismiller, D.G. Menopause. Prim. Care Clin. Off. Pract.; 2009; 36, pp. 199-226. [DOI: https://dx.doi.org/10.1016/j.pop.2008.10.007]
38. Abitudine al Fumo Dati Sorveglianza Passi. Available online: https://www.epicentro.iss.it/passi/dati/fumo#dati (accessed on 16 September 2022).
39. Luo, J.; Mills, K.; le Cessie, S.; Noordam, R.; van Heemst, D. Ageing, age-related diseases and oxidative stress: What to do next?. Ageing Res. Rev.; 2020; 57, 100982. [DOI: https://dx.doi.org/10.1016/j.arr.2019.100982]
40. Agarwal, A.; Aponte-Mellado, A.; Premkumar, B.J.; Shaman, A.; Gupta, S. The effects of oxidative stress on female reproduction: A review. Reprod. Biol. Endocrinol.; 2012; 10, 49. [DOI: https://dx.doi.org/10.1186/1477-7827-10-49]
41. Liguori, I.; Russo, G.; Curcio, F.; Bulli, G.; Aran, L.; Della-Morte, D.; Gargiulo, G.; Testa, G.; Cacciatore, F.; Bonaduce, D. et al. Oxidative stress, aging, and diseases. Clin. Interv. Aging; 2018; 13, pp. 757-772. [DOI: https://dx.doi.org/10.2147/CIA.S158513]
42. Agarwal, A.; Gupta, S.; Sharma, R.K. Role of oxidative stress in female reproduction. Reprod. Biol. Endocrinol.; 2005; 3, 28. [DOI: https://dx.doi.org/10.1186/1477-7827-3-28]
43. Aitken, R.J.; Baker, M.A. Oxidative stress and male reproductive biology. Reprod. Fertil. Dev.; 2004; 16, pp. 581-588. [DOI: https://dx.doi.org/10.1071/RD03089] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/15367373]
44. Wu, H.C.; Brennan, L.A.; Goldberg, M.; Chung, W.K.; Wei, Y.; Santella, R.M.; Terry, M.B. Influence of pubertal development on urinary oxidative stress biomarkers in adolescent girls in the New York LEGACY cohort. Free Radic. Res.; 2020; 54, pp. 431-441. [DOI: https://dx.doi.org/10.1080/10715762.2020.1798001] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32686531]
45. Rupérez, A.I.; Mesa, M.D.; Anguita-Ruiz, A.; González-Gil, E.M.; Vázquez-Cobela, R.; Moreno, L.A.; Gil, Á.; Gil-Campos, M.; Leis, R.; Bueno, G. et al. Antioxidants and Oxidative Stress in Children: Influence of Puberty and Metabolically Unhealthy Status. Antioxidants; 2020; 9, 618. [DOI: https://dx.doi.org/10.3390/antiox9070618] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32679739]
46. Paltoglou, G.; Schoina, M.; Valsamakis, G.; Salakos, N.; Avloniti, A.; Chatzinikolaou, A.; Margeli, A.; Skevaki, C.; Papagianni, M.; Kanaka-Gantenbein, C. et al. Interrelations among the adipocytokines leptin and adiponectin, oxidative stress and aseptic inflammation markers in pre- and early-pubertal normal-weight and obese boys. Endocrine; 2017; 55, pp. 925-933. [DOI: https://dx.doi.org/10.1007/s12020-017-1227-3]
47. Elhadd, T.A.; Khan, F.; Kirk, G.; McLaren, M.; Newton, R.W.; Greene, S.A.; Belch, J.J.F. Influence of puberty on endothelial dysfunction and oxidative stress in young patients with type 1 diabetes. Diabetes Care; 1998; 21, pp. 1990-1996. [DOI: https://dx.doi.org/10.2337/diacare.21.11.1990]
48. Amro, B.; Aristondo, M.E.R.; Alsuwaidi, S.; Almaamari, B.; Hakim, Z.; Tahlak, M.; Wattiez, A.; Koninckx, P.R. New Understanding of Diagnosis, Treatment and Prevention of Endometriosis. Int. J. Environ. Res. Public Health; 2022; 19, 6725. [DOI: https://dx.doi.org/10.3390/ijerph19116725]
49. Barradas, V.; Antoniassi, M.P.; Intasqui, P.; Nichi, M.; Bertolla, R.P.; Spaine, D.M. Evaluation of oxidative stress in seminal plasma of adolescents with varicocele. Reprod. Fertil.; 2021; 2, pp. 141-150. [DOI: https://dx.doi.org/10.1530/RAF-20-0048]
50. Wang, Z.; Chandrasena, E.R.; Yuan, Y.; Peng, K.W.; Van Breemen, R.B.; Thatcher, G.R.J.; Bolton, J.L. Redox cycling of catechol estrogens generating apurinic/apyrimidinic sites and 8-oxo-deoxyguanosine via reactive oxygen species differentiates equine and human estrogens. Chem. Res. Toxicol.; 2010; 23, pp. 1365-1373. [DOI: https://dx.doi.org/10.1021/tx1001282]
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Squillacioti, Giulia 1
; Ghelli, Federica 1
; Panizzolo, Marco 1
; Comoretto, Rosanna Irene 1
; Dalmasso, Paola 1
; Bellisario, Valeria 2 1 Department of Public Health and Pediatrics, University of Torino, Via Santena 5 bis, 10126 Torino, Italy
2 Department of Public Health and Pediatrics, University of Torino, Via Santena 5 bis, 10126 Torino, Italy; Post Graduate School of Medical Statistics, University of Torino, Via Santena 5 bis, 10126 Torino, Italy