Next Article in Journal
Innovation as a Factor Increasing Fruit Consumption: The Case of Poland
Next Article in Special Issue
Selected Organ and Endocrine Complications According to BMI and the Metabolic Category of Obesity: A Single Endocrine Center Study
Previous Article in Journal
Effect of Camel Milk on Glucose Homeostasis in Patients with Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Previous Article in Special Issue
The Impact of Bisphenol A on Thyroid Function in Neonates and Children: A Systematic Review of the Literature
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Nutrients
Volume 14
Issue 6
10.3390/nu14061244
nutrients-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Association between Telomere Length and Pediatric Obesity: A Systematic Review

by
Christina Raftopoulou
1,
George Paltoglou
2 and
Evangelia Charmandari
1,2,*
1
Division of Endocrinology and Metabolism, Center of Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece
2
Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, Aghia Sophia Children’s Hospital, 11527 Athens, Greece
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(6), 1244; https://doi.org/10.3390/nu14061244
Submission received: 24 January 2022 / Revised: 8 March 2022 / Accepted: 10 March 2022 / Published: 15 March 2022
(This article belongs to the Special Issue Nutrition and Endocrine Disorders)
Browse Figure
Versions Notes

Abstract

:
Objective: Telomere length (TL) is a robust marker of biological aging, and increased telomere attrition is noted in adults with obesity. The primary objective of this systematic review was to summarize current knowledge on the effects of childhood obesity in TL. The secondary objective was to assess the effect of weight management interventions in TL. Methods: The following databases were searched: PubMed, Scopus, Web of Science and Heal-link.gr from inception to September 2021. The search was performed using the following combinations of terms: “telomer*” [All Fields] AND (“length” [All Fields] OR “lengths” [All Fields]) AND “obes*” [All Fields] AND (“child*” [All Fields] OR “adolescen*” [All Fields]). Results: A total of 16 original articles were included in this systematic review. Eleven of them were cross-sectional and five were lifestyle interventions. Conclusions: There was a tendency towards a negative association between childhood obesity and TL. Life-style interventions in children have been associated with increased TL peripherally, indicating a possible association of the redistribution of younger cells in the periphery with the favorable effect of these interventions. Further prospective studies with larger sample sizes that employ other markers of cell aging would potentially elucidate this important mechanistic relation.

1. Introduction

Telomeres in humans are the natural end of chromosomes and consist of highly conserved hexameric (5′-TTAGGG-3′) tandem repeat DNA sequences and proteins, that cap and protect eukaryotic chromosome ends from being processed as DNA double-strand breaks (DSBs) [1]. Telomeres shorten progressively with age as a result of the end replication problem, which indicates that during cell division the ends of linear DNA cannot be replicated completely during lagging strand DNA synthesis [2]. Furthermore, oxidative stress is associated with telomere shortening and dysfunction [2]. In humans, telomere length (TL) can vary from 3 to 20 kilobase pairs (kb) [3]. Cells are able to maintain TL with telomerase, a ribonucleoprotein enzyme complex that synthesizes telomeric DNA at the 3′ end of linear chromosomes [4]. It is composed of the enzymatic reverse transcriptase protein TERT (telomeric reverse transcriptase) and the RNA template TERC (telomeric RNA component) [4]. Early in human development, telomerase is constitutively active in all body cells. However, after birth it is active predominately in germline cells, activated lymphocytes, and certain types of stem cell populations, with most somatic tissues having no telomerase activity [5]. Cancer cells, on the other hand, can restore their telomeres through two known pathways, either through telomerase that is widely expressed in malignant cells, or with alternative lengthening of telomeres (ALT) [6]. The alternative lengthening pathway is rarer and based on the elongation of telomeres upon recombination. Thus, it is characterized by continuous cell growth in the absence of telomerase [7].
Telomere length is highly variable in adults, as well as in children [8]. After birth, TL starts to decrease rapidly, indicating that during pregnancy TL is maintained with specific to life in utero mechanisms [9,10,11]. It is important to note that in adulthood, gender influences TL with women demonstrating longer TL than men [12,13,14]. Furthermore, although TL is highly variable in somatic tissues of adults, it has been shown that telomeres shorten at equivalent rates [15,16]. The rate of telomere shortening is high during the first three years of life (approximately 250 bp/year) and reaches a plateau at the age of four years. From the age of four years onwards and till young adulthood, this rate of telomere attrition is either stable or declines (up to 50 bp/year), and reduces further in older individuals (approximately 50 bp/year) [17,18,19,20,21]. Different periods of childhood are characterized by differences in telomere attrition rates owing to an increased cell replication rate in infants, especially during the accelerated development of the immune system, while in adults with obesity, telomere attrition rate was greater in those with higher TL prior to a lifestyle intervention [13,22,23]. In the early stages of life and adulthood, short TL or high rates of telomere attrition have been associated with lower life expectancy and higher disease risk in humans, as well as in other species [24,25,26,27,28,29,30,31]. As previously stated, during embryonic development, the telomerase is active in the embryo, enabling the maintenance of equally long telomeres in all tissue cells and causing cells of different tissues to have similar TL [32,33,34]. With ageing, different tissue cells lose the similarity in TL mainly due to the respective differences in their proliferative activity [16]. However, similar rates of age-dependent attrition have been reported in leucocytes, skin, fat, and muscle cells [16]. A child or an adult with long leukocyte telomere length (LTL) will have long muscle telomere length (MTL), indicative of the existence of a synchrony across these somatic tissues in the same individual [35].
Telomere length is a highly heritable trait (36–86% in family and twin studies) [36,37,38,39,40,41] and in newborns, it appears to be associated with parental TL [41,42,43,44]. Apart from genetic factors, TL can be altered by factors, such as gender (women have longer TL than men) [45], race (African Americans have longer TL than Europeans) [46,47], paternal age (older age of the father is associated with longer TL) [48,49], smoking (smokers have shorter TL than non-smokers) [50,51], physical activity (non-active subjects have shorter TL than active subjects) [52], traumatic events (cause shortening of TL) [53,54,55,56], obesity (causes shortening of TL) [51], and oxidative stress (causes shortening of TL) [57,58]. Moreover, specific conditions may accelerate TL attrition even in children via oxidative, immune, hormonal, and metabolic pathways, linking these pathophysiological mechanisms and TL with the development or susceptibility to disease [59,60].
The prevalence of obesity has been increasing rapidly worldwide during the last four decades, with a concomitant rise in the prevalence of obesity in childhood and adolescence [61]. Obesity is characterized by “abnormal” or excessive body fat accumulation, with complications that include insulin resistance, glucose intolerance, diabetes mellitus type 2, dyslipidemia, hypertension, early onset atherosclerotic cardiovascular disease, endothelial dysfunction, orthopedic problems, hypogonadism, social stigmatization, fatty liver disease, cholecystitis, and increased incidence of certain malignancies [62,63,64,65,66,67,68]. Overweight and obesity in childhood results in obesity in adulthood and is associated with significant morbidity and mortality early in adult life [69]. The recognition of adipose tissue as an endocrine organ capable of secreting adipokines, which facilitate communication between adipose tissue and other organs and influence whole-body energy homeostasis, increased our understanding on the pathophysiology of obesity [70]. Adipokines have pro- and anti-inflammatory actions that might contribute to the onset and progression of obesity-related disorders [71]. Obesity in childhood is also associated with chronic inflammation, which is mediated by cytokines (and adipocytokines), increased reactive oxygen and nitrogen species (RONS) production (pro-oxidation, decreased anti-oxidation), and increased systemic oxidative stress [51,72,73,74,75].
Furthermore, obesity may accelerate telomere attrition rates and biological ageing, and BMI in adulthood is inversely associated with TL, an important fact given that the increase of telomere attrition and reduced telomere length in various age-related diseases is associated with increased morbidity and mortality [76,77]. Increased BMI results in higher blood volume, increased proliferation of blood cells, and telomere shortening, whereas weight loss has been positively correlated with telomere lengthening [51]. As previously noted, obesity is mechanistically associated with chronic, low-grade inflammation and increased oxidative stress [69,72]. At the same time chronic inflammation and oxidative stress, even in the absence of obesity (e.g., aging associated morbidity), are associated with increased telomere attrition and shorter TL [78,79,80]. The strong association of obesity with low-grade inflammation and oxidative stress underlines the importance of the study of the impact of telomere attrition during childhood on later life, particularly given that there is an inverse correlation between TL and BMI, total fat, and waist circumference, and that abdominal adipose tissue is directly related to TL attrition and promotion of the aging process [81]. It is important to note that adequate treatment of obesity in childhood potentially prevents complications of obesity in adulthood [82]. In addition, individuals who have shorter TL before intervention benefit from the most pronounced rate of telomere lengthening after weight loss [74], while better compliance to a Mediterranean diet is also associated with longer TL [51,72,73,74].
In order to systematically summarize current knowledge on the association between childhood obesity and TL, we undertook the present systematic review. The primary objective of the present systematic review was to summarize the current knowledge on the effects of childhood obesity (<18 years) on TL. The secondary objective was to assess the effect of weight management interventions on TL in childhood obesity (<18 years).

2. Materials and Methods

2.1. Study Design

The present study was conducted according to the Preferred Reporting Items for Systematic Reviews (PRISMA) protocol [83]. The systematic review was registered in the OSF registries with Registration DOI 10.17605/OSF.IO/Q5BTG. The study protocol included the following consecutive stages: (i) primary research of the systematic literature using search engines; and (ii) selection of studies to be included according to our inclusion and exclusion criteria.

2.2. Eligibility Criteria

The eligibility criteria were predetermined by the authors (Table 1). We included all original studies that assessed the relation between TL and obesity, overweight or normal-BMI in children and adolescents aged <18 years old. In some studies, the population included both adults and children; we evaluated only those that assessed children separately. In order to prevent language bias, our search was not limited by language. There was no date or country restriction. Reviews were excluded from our study selection.

2.3. Literature Search

Two independent reviewers used the PubMed, Scopus, Web of Science and www.Heal-link.gr (accessed on 20 January 2022) search engines in primary search prior to September 2021.
Our search strategy for the primary objective included the terms: “telomer*” [All Fields] AND (“length” [All Fields] OR “lengths” [All Fields]) AND “obes*” [All Fields] AND (“child*” [All Fields] OR “adolescen*” [All Fields]).
A second search with the search terms for weight management interventions (secondary objective search) was also performed: “telomer*” [All Fields] AND (“length” [All Fields] OR “lengths” [All Fields]) AND “obes*” [All Fields] AND (“child*” [All Fields] OR “adolescen*” [All Fields]) AND ((“weight s” [All Fields] OR “weighted” [All Fields] OR “weighting” [All Fields] OR “weightings” [All Fields] OR “weights and measures” [MeSH Terms] OR (“weights” [All Fields] AND “measures” [All Fields]) OR “weights and measures” [All Fields] OR “weight” [All Fields] OR “body weight” [MeSH Terms] OR (“body” [All Fields] AND “weight” [All Fields]) OR “body weight” [All Fields] OR “weights” [All Fields]) AND (“manage” [All Fields] OR “managed” [All Fields] OR “managements” [All Fields] OR “managements” [All Fields] OR “manager” [All Fields] OR “manager s” [All Fields] OR “managers” [All Fields] OR “manages” [All Fields] OR “managing” [All Fields] OR “managment” [All Fields] OR “organization and administration” [MeSH Terms] OR (“organization” [All Fields] AND “administration” [All Fields]) OR “organization and administration” [All Fields] OR “management” [All Fields] OR “disease management” [MeSH Terms] OR (“disease” [All Fields] AND “management” [All Fields]) OR “disease management” [All Fields])). Articles together with reference lists from included studies were retrieved.

2.4. Study Selection

After the initial search, all obtained documents were screened independently by the two reviewers. The two reviewers used a standard Excel extraction datasheet to exclude all duplicates and examined eligibility for the studies based on the relevance of their title and abstract. For the relevant articles, full text was assessed based on the inclusion and exclusion criteria. All included studied were of ‘very good quality’ (9–10 points: 4 cross-sectional and 2 intervention) and ‘good quality’ (7–8 points: 7 cross sectional and 3 intervention). Therefore, the overall risk of bias was not high (Table 2). During the whole procedure, each reviewer remained blinded to the other investigator’s selection and finally, after consensus, 16 articles were used in the qualitative analysis of this review.

3. Results

3.1. Literature Search

A total of 236 articles were identified by two independent researchers using the search terms listed above. After removing 96 duplicates, 110 irrelevant papers were excluded after the title and abstract screening. A total of 29 papers were eligible for full-text review. Among these full-text articles, 13 were excluded for the following reasons: namely reviews/systematic reviews, duplicate papers, other age group or information that did not meet the eligibility criteria and the purpose of this systematic review. Finally, 16 full-text articles [84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99] were considered eligible and were included to our qualitative synthesis. The study selection procedure is detailed in the respective flow chart (Figure 1).

3.2. Study Characteristics

In the systematic review for the primary objective, ten cross-sectional studies [84,85,86,87,88,89,90,91,93,94] and one case control [92] were included (Table 3). The age ranged from 2 to 18 years and the percentage of boys was between 46.0% and 67.7%. The majority of the included studies (15/16) used quantitative real-time PCR (qPCR) to evaluate telomere length [84,85,86,87,88,89,90,91,92,93,95,96,97,98,99], while one study (1/16) used terminal restriction fragmentation (TRF) method [94]. Most studies (8/11) measured telomere length from leukocytes.
As for the obesity definition, only one study divided subjects in three groups (obese, overweight and of normal-BMI) according to the IOTF criteria [89]. When the overweight group was not included, three studies compared obese and normal-BMI children according to the IOTF and WHO criteria [74,85,86,92]. In five studies, the overweight and obese children were grouped together, according to the CDC and WHO criteria [84,87,88,90,91]. Of the included studies, five showed significantly shorter TL in overweight and obese children compared to children with normal-BMI [85,86,88,89,92], while five did not find any significant differences [84,87,90,91,94]. One study revealed shorter TL only in obese boys compared with their normal-BMI counterparts, but not in girls [93].
In the systematic review for the secondary objective, we included five intervention studies shown in Table 4. The ages ranged from 7 to 16 years and the percentage of boys was between 36.0% and 48.6%. All of the included studies used quantitative real-time PCR (qPCR) to evaluate telomere length and measured telomere length from leukocytes [95,96,97,98,99]. Lifestyle interventions in all five studies included dietary and physical activity interventions, and in all of them, participants are reported to have lost weight. Of the five studies that evaluated the effect of a lifestyle intervention program in obese or overweight children, three demonstrated a significant increase in TL as a result of a decrease in BMI [95,98,99]. In two of the studies, TL increased following two months of intervention, while in the study conducted by our group, TL increased in all subjects following twelve months of intervention [95]. In two studies, TL did not show a significant change [96,97]. Both studies had an intervention period of two months that may be too short a time (depending on the intervention) to result in TL increase [96,97].

4. Discussion

Among the studies assessed in this systematic review, there was only one study that showed a significantly greater TL in normal-BMI than in overweight and obese children. In this study, there was no difference in TL between the overweight and obese groups [89]. When the overweight group was not included, three studies showed significantly shorter TL in obese than in normal-BMI children [85,86,92,93]. In four studies, no difference in TL between normal-BMI and the combined overweight/obese children was found [84,87,90,91], while in one study TL was greater in normal-BMI children [88]. It is important to note that, in the four studies that showed no difference in TL among groups, the CDC criteria were used for the definition of overweight and obesity, while the fifth one used the WHO criteria for the definition of overweight and obesity. The growth charts designed by WHO are more sensitive in identifying obesity in a population at risk, which has important implications for the prevention and management of the condition [100]. It has been shown that the WHO growth charts yield a higher prevalence estimate of being overweight and obesity since the reference population is intended to be a non-obese sample, whereas CDC and IOTF are derived using more recent data in which the BMI distribution of the reference populations is already shifted toward the right due to the recent increase in the BMI in childhood and adolescence [101]. Thus, more children with obesity are classified as having a normal BMI via the CDC and IOTF criteria, and this limitation should be taken into account when making comparisons between the two groups.
When assessing the correlation between BMI and TL in two of the included studies, a statistically significant negative correlation was found [85,88]. In the other two included studies that assessed the respective correlations, no association was reported [86,92]. It has been shown previously that TL correlates with anthropometric outcomes, such as BMI in adults, with the majority of studies reporting an inverse relation between BMI and TL in adulthood [102,103,104]. However, according to the systematic review and meta-analysis of Guyatt et al., there was no strong evidence for an association between any adiposity measure in neonates and children and TL [105].
The exact mechanisms underlying the association between measures of obesity and short TL still needs to be elucidated. Increased oxidative stress and the persistent activation of inflammatory processes [72,106] are the key factors that may explain the association between telomere attrition and obesity, as well as cardiometabolic disorders in adulthood [107,108,109,110,111]. Oxidative stress is a state of imbalance between pro- and anti- oxidation within the cell [112,113]. Pro-oxidation refers to mitochondrial and non-mitochondrial mechanisms, which generate reactive oxygen and nitrogen species [112,113]. Antioxidation is the adaptive activation of enzymatic and nonenzymatic mechanisms that counterbalance pro-oxidation by activating the scavengers of pro-oxidants and their products within cells and in extracellular body fluids [112,113,114]. Obesity and its comorbidities in humans are associated with increased pro- and decreased anti-oxidation, respectively, even in childhood [72,113,115,116]. Increased levels of oxidative stress are considered detrimental to cell signal transduction [117], potentially explaining the reported correlation between increased oxidative stress and shorter TL [118,119,120]. The adipose tissue plays a role in the production of inflammatory cytokines and chemokines, as well as in host defense, immunity, and injury response [121]. Furthermore, adipose tissue-related aseptic low-grade inflammation might contribute to increased production of reactive oxygen and nitrogen species (RONS) and reduced antioxidant capacity [72,75,122,123,124,125]. Another proposed mechanism links the proinflammatory state that accompanies obesity with hyperplasia and hypertrophy of adipocytes, which can induce adipose tissue hypoxia [126]. This adipose tissue dysfunction causes secretion of prostaglandins, C-reactive protein, and proinflammatory cytokines, such as interleukin-6, tumor necrosis factor, and adipokines, such as leptin [69,127]. It also lowers the concentrations of anti-inflammatory adipokines, such as adiponectin, even in childhood [75]. The increased BMI in childhood and adolescence may be associated with accelerated biological ageing and may have an adverse impact on future health in adulthood, such as cardiometabolic diseases [79,89,128,129]. Obesity is regarded as a crucial factor in the regulation of adipose tissue aging and further metabolic outcomes, such as increased proinflammatory cytokines, insulin resistance, diabetes mellitus type 2, and cardiovascular disease [79,128,129]. The p53 pathway in adipose tissue, which is a key factor in the aging process of adipose tissue and increased inflammation, may play an important role in relation to obesity and obesity-mediated aging [129,130]. These DNA damage responses are defined by the consequences of genomic instability, a reaction of cells to damaged DNA to prevent negative health conditions, such as the initiation of mitotic senescence, arrest, repair, and cell death [131,132,133].
Although BMI is an important indicator of adiposity, studies examining the impact of specific markers of adiposity have shown that there is a negative correlation between TL and waist circumference [86,88,93], as well as between TL and skinfold thickness [88] (although Ooi et al. found a positive correlation between TL and skinfold measurements) [86]. Studies in adults showed a negative correlation between adiposity markers and TL [76]. It is important to note that several previous studies have suggested that the relationship between TL and adiposity is stronger in younger adults than in older adults [13,104,134,135]. This has been attributed to the accumulated damage due to inflammatory processes and oxidative stress over the life course, which may be greater in the elderly [104]. Indeed, increased adipose tissue markers, such as increased waist circumference and adipose tissue, as assessed by skinfold thickness, have been associated with markers of cardiovascular risk, chronic inflammatory state and oxidative stress. Therefore, they could be associated with shorter TL [72]. Inflammatory process-induced DNA damage may explain the association between obesity and telomere shortening [110]. Previous studies have shown a significant inverse relation between the levels of inflammation and TL in both adults [78] and children [136]. In obesity, increased adipose tissue results in increased production of pro-inflammatory adipokines and cytokines [137] and potentially TL shortening [106,119].
Of the five studies that evaluated the effect of a lifestyle intervention program in obese or overweight children, three demonstrated a significant increase in TL as a result of a decrease in BMI [95,98,99]. Two studies had an intervention period of two months that may be too short a time (depending on the intervention) to result in TL increase [96,97]. In addition, in both studies the sample size was small (≈100) [96,97]. Physical activity and exercise are important interventions that support and accelerate the process of weight loss in addition to an effective diet plan. They have protective and restorative effects and, therefore, improve well-being and increase longevity. Physical activity stimulates the metabolism, including oxidative, inflammatory, and neuroendocrinological adaptive systems [80]. Several exercise-only interventions have demonstrated a reduction in the biomarkers of oxidative stress [80,138,139,140,141]. Little is known about the differences of oxidative stress-related processes between obese and non-obese individuals [116,142]. In addition to physical activity, weight loss itself may reverse telomere attrition. Increased consumption of healthy foods typical of the traditional Mediterranean diet (vegetables, fruits, nuts, wine, and coffee, foods rich in antioxidants, and other phytochemicals) has been consistently associated with telomere lengthening, whereas increased consumption of processed meat and sweetened beverages has quite the opposite effect [143]. Also, intake of foods rich in antioxidants leads to healthy cell aging, which can delay telomeric friction [144]. The consumption of foods rich in antioxidants and anti-inflammatory compounds plant-based foods has beneficial effects on several anti-inflammatory markers and in reducing oxidative stress and cardiovascular risk factors [145,146].
Telomere length from peripheral white blood cells correlates very well with their bone marrow residing precursors, justifying the quantification of TL from peripheral blood cells as an indicator of stem cell divisions [147]. Telomere lengthening could be explained by mechanisms involved in either the reduction of biological stress (inflammation or oxidative stress) [148,149] or the redistribution in circulating immune cells (naïve T cells) regardless of cell type (including diverse populations), such as large numbers of younger cells with longer telomeres [150,151]. Within redistribution, there can be increases in numbers of specific types of naive cells regardless of cell type. Biegler and colleagues’ findings suggest that lengthening was associated with an influx of naive T cells [152]. Naive T cells naturally have longer TL than memory T cells, but may also have longer TL than granulocytes [19]. Any factors that stimulate greater naive T-cell influx may lead to lengthening of average TL (mimicking the reversal typically associated with telomerase-mediated per cell increases in base pairs). Thus, rather than elongation of TL on a per cell basis, it seemed to be in part due to replenishment of cells in circulation. Younger cells in the circulation were shown to positively influence longevity in experimental animals via an unknown mechanism [153]. This observation may lead to future studies examining the potential mechanisms with which lifestyle intervention/weight management can lead to redistribution of younger cells in the body.
Improvements in health behaviors might promote short-term lengthening. Exercise may be one of the important factors shaping apparent or actual lengthening, as it is related to greater numbers of naive cells, as well as longer TL [154,155]. Improving well-being through decreasing stress and concomitant increases in growth and restorative factors might induce a specific pattern of adhesion molecule-stimulated trafficking patterns and result in cells with longer telomeres, either more naive cells or fewer senescent cells. Accordingly, age-dependent decline in TL of mononuclear bone marrow cells was similar to peripheral blood cells, suggesting an ageing process already in stem and progenitor cells, indicating that changes in the periphery might reflect changes in hematopoiesis [147].

5. Limitations

The main limitation of our study was the variations in study size and age structure of the study population that can both contribute towards the heterogeneity of the results [96,97]. In addition, the different approaches in obesity definition may also contribute to the heterogeneity of the results. In addition, the heterogeneity between populations should be considered, given that TL is influenced by both genetic factors and ethnicity [46,84]. Furthermore, the TRF assay provides a readily quantifiable distribution of TLs in kb units, which can be compared across populations and species and used to estimate both mean, medians, and variance in TLs within a sample of cells [156]. On the other hand, qPCR provides only average TL as a relative ratio. Comparing the results of the two techniques will provide limited comparability. It is important to note that the study that compared TL using the TRF technique in normal-BMI and obese children, showed no difference in TL between the two groups [94].

6. Conclusions

The results of this systematic review are consistent with the proposed biological mechanism that increased adiposity leads to telomere shortening, which can hasten the ageing process even in childhood. However, the available data are still sparse and some individual studies report contradicting associations that may be inherent to the variability in study design (and particularly the definition of obesity).
Furthermore, increasing evidence supports the hypothesis that the beneficial effects of lifestyle intervention processes can be associated with increased TL in the periphery. The apparent reversal of the well-documented age-dependent decline in measured telomere length from peripheral leukocytes reflects changes in hematopoiesis and the possible redistribution of younger cells in the periphery, indicating a potential contributing mechanistic factor to these beneficial effects.

Author Contributions

C.R. and G.P. Conceptualized the study, outlined the methodology, performed the original systematic search and study selection. C.R. performed the original draft preparation. G.P. and E.C. reviewed and edited the manuscript. E.C. supervised the study. All authors have read and agreed to the published version of the manuscript.

Funding

This research was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE (project code: T1EDK-01386, MIS: 5030543, Acronym: PEDOBESITY).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. De Lange, T. Shelterin: The protein complex that shapes and safeguards human telomeres. Genes Dev. 2005, 19, 2100–2110. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Lindsey, J.; McGill, N.I.; Lindsey, L.A.; Green, D.K.; Cooke, H.J. In vivo loss of telomeric repeats with age in humans. Mutat. Res. 1991, 256, 45–48. [Google Scholar] [CrossRef]
  3. Moyzis, R.K.; Buckingham, J.M.; Cram, L.S.; Dani, M.; Deaven, L.L.; Jones, M.D.; Meyne, J.; Ratliff, R.L.; Wu, J.R. A highly conserved repetitive DNA sequence, (TTAGGG)n, present at the telomeres of human chromosomes. Proc. Natl. Acad. Sci. USA 1988, 85, 6622–6626. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Greider, C.W.; Blackburn, E.H. Identification of a specific telomere terminal transferase activity in Tetrahymena extracts. Cell 1985, 43 Pt 1, 405–413. [Google Scholar] [CrossRef]
  5. Hiyama, E.; Hiyama, K. Telomere and telomerase in stem cells. Br. J. Cancer 2007, 96, 1020–1024. [Google Scholar] [CrossRef] [Green Version]
  6. Kim, N.W.; Piatyszek, M.A.; Prowse, K.R.; Harley, C.B.; West, M.D.; Ho, P.L.; Coviello, G.M.; Wright, W.E.; Weinrich, S.L.; Shay, J.W. Specific association of human telomerase activity with immortal cells and cancer. Science 1994, 266, 2011–2015. [Google Scholar] [CrossRef]
  7. Cesare, A.J.; Reddel, R.R. Alternative lengthening of telomeres: Models, mechanisms and implications. Nat. Rev. Genet. 2010, 11, 319–330. [Google Scholar] [CrossRef] [PubMed]
  8. Okuda, K.; Bardeguez, A.; Gardner, J.P.; Rodriguez, P.; Ganesh, V.; Kimura, M.; Skurnick, J.; Awad, G.; Aviv, A. Telomere length in the newborn. Pediatric Res. 2002, 52, 377–381. [Google Scholar] [CrossRef]
  9. Friedrich, U.; Schwab, M.; Griese, E.U.; Fritz, P.; Klotz, U. Telomeres in neonates: New insights in fetal hematopoiesis. Pediatric Res. 2001, 49, 252–256. [Google Scholar] [CrossRef] [Green Version]
  10. Menon, R.; Yu, J.; Basanta-Henry, P.; Brou, L.; Berga, S.L.; Fortunato, S.J.; Taylor, R.N. Short fetal leukocyte telomere length and preterm prelabor rupture of the membranes. PLoS ONE 2012, 7, e31136. [Google Scholar] [CrossRef] [Green Version]
  11. Vasu, V.; Turner, K.J.; George, S.; Greenall, J.; Slijepcevic, P.; Griffin, D.K. Preterm infants have significantly longer telomeres than their term born counterparts. PLoS ONE 2017, 12, e0180082. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Sanders, J.L.; Newman, A.B. Telomere length in epidemiology: A biomarker of aging, age-related disease, both, or neither? Epidemiol. Rev. 2013, 35, 112–131. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Nordfjall, K.; Eliasson, M.; Stegmayr, B.; Melander, O.; Nilsson, P.; Roos, G. Telomere Length Is Associated With Obesity Parameters but With a Gender Difference. Obesity 2008, 16, 2682–2689. [Google Scholar] [CrossRef] [PubMed]
  14. Willeit, P.; Willeit, J.; Brandstatter, A.; Ehrlenbach, S.; Mayr, A.; Gasperi, A.; Weger, S.; Oberhollenzer, F.; Reindl, M.; Kronenberg, F.; et al. Cellular aging reflected by leukocyte telomere length predicts advanced atherosclerosis and cardiovascular disease risk. Arter. Thromb. Vasc. Biol. 2010, 30, 1649–1656. [Google Scholar] [CrossRef] [Green Version]
  15. Friedrich, U.; Griese, E.; Schwab, M.; Fritz, P.; Thon, K.; Klotz, U. Telomere length in different tissues of elderly patients. Mech. Ageing Dev. 2000, 119, 89–99. [Google Scholar] [CrossRef]
  16. Daniali, L.; Benetos, A.; Susser, E.; Kark, J.D.; Labat, C.; Kimura, M.; Desai, K.K.; Granick, M.; Aviv, A. Telomeres shorten at equivalent rates in somatic tissues of adults. Nat. Commun. 2013, 4, 1597. [Google Scholar] [CrossRef] [PubMed]
  17. Frenck, R.W., Jr.; Blackburn, E.H.; Shannon, K.M. The rate of telomere sequence loss in human leukocytes varies with age. Proc. Natl. Acad. Sci. USA 1998, 95, 5607–5610. [Google Scholar] [CrossRef] [Green Version]
  18. Zeichner, S.L.; Palumbo, P.; Feng, Y.; Xiao, X.; Gee, D.; Sleasman, J.; Goodenow, M.; Biggar, R.; Dimitrov, D. Rapid telomere shortening in children. Blood 1999, 93, 2824–2830. [Google Scholar] [CrossRef]
  19. Rufer, N.; Brummendorf, T.H.; Kolvraa, S.; Bischoff, C.; Christensen, K.; Wadsworth, L.; Schulzer, M.; Lansdorp, P.M. Telomere fluorescence measurements in granulocytes and T lymphocyte subsets point to a high turnover of hematopoietic stem cells and memory T cells in early childhood. J. Exp. Med. 1999, 190, 157–167. [Google Scholar] [CrossRef] [Green Version]
  20. Takubo, K.; Nakamura, K.; Izumiyama, N.; Furugori, E.; Sawabe, M.; Arai, T.; Esaki, Y.; Mafune, K.; Kammori, M.; Fujiwara, M.; et al. Telomere shortening with aging in human liver. J. Gerontol. A Biol. Sci. Med. Sci. 2000, 55, B533–B536. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Lansdorp, P.M. Telomeres, stem cells, and hematology. Blood 2008, 111, 1759–1766. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Aviv, A.; Chen, W.; Gardner, J.P.; Kimura, M.; Brimacombe, M.; Cao, X.; Srinivasan, S.R.; Berenson, G.S. Leukocyte telomere dynamics: Longitudinal findings among young adults in the Bogalusa Heart Study. Am. J. Epidemiol. 2009, 169, 323–329. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Benetos, A.; Kark, J.D.; Susser, E.; Kimura, M.; Sinnreich, R.; Chen, W.; Steenstrup, T.; Christensen, K.; Herbig, U.; von Bornemann Hjelmborg, J.; et al. Tracking and fixed ranking of leukocyte telomere length across the adult life course. Aging Cell 2013, 12, 615–621. [Google Scholar] [CrossRef]
  24. Lopez-Otin, C.; Blasco, M.A.; Partridge, L.; Serrano, M.; Kroemer, G. The hallmarks of aging. Cell 2013, 153, 1194–1217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Cawthon, R.M.; Smith, K.R.; O’Brien, E.; Sivatchenko, A.; Kerber, R.A. Association between telomere length in blood and mortality in people aged 60 years or older. Lancet 2003, 361, 393–395. [Google Scholar] [CrossRef]
  26. Haussmann, M.F.; Vleck, C.M.; Nisbet, I.C. Calibrating the telomere clock in common terns, Sterna hirundo. Exp. Gerontol. 2003, 38, 787–789. [Google Scholar] [CrossRef] [Green Version]
  27. Heidinger, B.J.; Blount, J.D.; Boner, W.; Griffiths, K.; Metcalfe, N.B.; Monaghan, P. Telomere length in early life predicts lifespan. Proc. Natl. Acad. Sci. USA 2012, 109, 1743–1748. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Boonekamp, J.J.; Simons, M.J.P.; Hemerik, L.; Verhulst, S. Telomere length behaves as biomarker of somatic redundancy rather than biological age. Aging Cell 2013, 12, 330–332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Boonekamp, J.J.; Mulder, G.A.; Salomons, H.M.; Dijkstra, C.; Verhulst, S. Nestling telomere shortening, but not telomere length, reflects developmental stress and predicts survival in wild birds. Proc. R. Soc. B Biol. Sci. 2014, 281, 3287. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  30. Barrett, E.L.; Burke, T.A.; Hammers, M.; Komdeur, J.; Richardson, D.S. Telomere length and dynamics predict mortality in a wild longitudinal study. Mol. Ecol. 2013, 22, 249–259. [Google Scholar] [CrossRef]
  31. Fairlie, J.; Holland, R.; Pilkington, J.G.; Pemberton, J.M.; Harrington, L.; Nussey, D.H. Lifelong leukocyte telomere dynamics and survival in a free-living mammal. Aging Cell 2016, 15, 140–148. [Google Scholar] [CrossRef] [PubMed]
  32. Youngren, K.; Jeanclos, E.; Aviv, H.; Kimura, M.; Stock, J.; Hanna, M.; Skurnick, J.; Bardeguez, A.; Aviv, A. Synchrony in telomere length of the human fetus. Hum. Genet. 1998, 102, 640–643. [Google Scholar] [CrossRef] [PubMed]
  33. Kimura, M.; Gazitt, Y.; Cao, X.J.; Zhao, X.Y.; Lansdorp, P.M.; Aviv, A. Synchrony of telomere length among hematopoietic cells. Exp. Hematol. 2010, 38, 854–859. [Google Scholar] [CrossRef] [Green Version]
  34. Wright, D.L.; Jones, E.L.; Mayer, J.F.; Oehninger, S.; Gibbons, W.E.; Lanzendorf, S.E. Characterization of telomerase activity in the human oocyte and preimplantation embryo. Mol. Hum. Reprod. 2001, 7, 947–955. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Sabharwal, S.; Verhulst, S.; Guirguis, G.; Kark, J.D.; Labat, C.; Roche, N.E.; Martimucci, K.; Patel, K.; Heller, D.S.; Kimura, M.; et al. Telomere length dynamics in early life: The blood-and-muscle model. FASEB J. 2018, 32, 529–534. [Google Scholar] [CrossRef] [Green Version]
  36. Andrew, T.; Aviv, A.; Falchi, M.; Surdulescu, G.L.; Gardner, J.P.; Lu, X.B.; Kimura, M.; Kato, B.S.; Valdes, A.M.; Spector, T.D. Mapping genetic loci that determine leukocyte telomere length in a large sample of unselected female sibling pairs. Am. J. Hum. Genet 2006, 78, 480–486. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Atzmon, G.; Cho, M.; Cawthon, R.M.; Budagov, T.; Katz, M.; Yang, X.; Siegel, G.; Bergman, A.; Huffman, D.M.; Schechter, C.B.; et al. Evolution in health and medicine Sackler colloquium: Genetic variation in human telomerase is associated with telomere length in Ashkenazi centenarians. Proc. Natl. Acad. Sci. USA 2010, 107 (Suppl. S1), 1710–1717. [Google Scholar] [CrossRef] [Green Version]
  38. Bakaysa, S.L.; Mucci, L.A.; Slagboom, P.E.; Boomsma, D.I.; McClearn, G.E.; Johansson, B.; Pedersen, N.L. Telomere length predicts survival independent of genetic influences. Aging Cell 2007, 6, 769–774. [Google Scholar] [CrossRef]
  39. Vasa-Nicotera, M.; Brouilette, S.; Mangino, M.; Thompson, J.R.; Braund, P.; Clemitson, J.R.; Mason, A.; Bodycote, C.L.; Raleigh, S.M.; Louis, E.; et al. Mapping of a major locus that determines telomere length in humans. Am. J. Hum. Genet 2005, 76, 147–151. [Google Scholar] [CrossRef] [Green Version]
  40. Slagboom, P.E.; Droog, S.; Boomsma, D.I. Genetic determination of telomere size in humans: A twin study of three age groups. Am. J. Hum. Genet 1994, 55, 876–882. [Google Scholar]
  41. Njajou, O.T.; Cawthon, R.M.; Damcott, C.M.; Wu, S.H.; Ott, S.; Garant, M.J.; Blackburn, E.H.; Mitchell, B.D.; Shuldiner, A.R.; Hsueh, W.C. Telomere length is paternally inherited and is associated with parental lifespan. Proc. Natl. Acad. Sci. USA 2007, 104, 12135–12139. [Google Scholar] [CrossRef] [Green Version]
  42. Akkad, A.; Hastings, R.; Konje, J.C.; Bell, S.C.; Thurston, H.; Williams, B. Telomere length in small-for-gestational-age babies. BJOG 2006, 113, 318–323. [Google Scholar] [CrossRef] [PubMed]
  43. Factor-Litvak, P.; Susser, E.; Kezios, K.; McKeague, I.; Kark, J.D.; Hoffman, M.; Kimura, M.; Wapner, R.; Aviv, A. Leukocyte Telomere Length in Newborns: Implications for the Role of Telomeres in Human Disease. Pediatrics 2016, 137, e20153927. [Google Scholar] [CrossRef] [Green Version]
  44. Nordfjall, K.; Larefalk, A.; Lindgren, P.; Holmberg, D.; Roos, G. Telomere length and heredity: Indications of paternal inheritance. Proc. Natl. Acad. Sci. USA 2005, 102, 16374–16378. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Gardner, M.; Bann, D.; Wiley, L.; Cooper, R.; Hardy, R.; Nitsch, D.; Martin-Ruiz, C.; Shiels, P.; Sayer, A.A.; Barbieri, M.; et al. Gender and telomere length: Systematic review and meta-analysis. Exp. Gerontol. 2014, 51, 15–27. [Google Scholar] [CrossRef] [PubMed]
  46. Hansen, M.E.; Hunt, S.C.; Stone, R.C.; Horvath, K.; Herbig, U.; Ranciaro, A.; Hirbo, J.; Beggs, W.; Reiner, A.P.; Wilson, J.G.; et al. Shorter telomere length in Europeans than in Africans due to polygenetic adaptation. Hum. Mol. Genet. 2016, 25, 2324–2330. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Lynch, S.M.; Peek, M.K.; Mitra, N.; Ravichandran, K.; Branas, C.; Spangler, E.; Zhou, W.; Paskett, E.D.; Gehlert, S.; DeGraffinreid, C.; et al. Race, Ethnicity, Psychosocial Factors, and Telomere Length in a Multicenter Setting. PLoS ONE 2016, 11, e0146723. [Google Scholar] [CrossRef] [Green Version]
  48. Kimura, M.; Cherkas, L.F.; Kato, B.S.; Demissie, S.; Hjelmborg, J.B.; Brimacombe, M.; Cupples, A.; Hunkin, J.L.; Gardner, J.P.; Lu, X.; et al. Offspring’s leukocyte telomere length, paternal age, and telomere elongation in sperm. PLoS Genet. 2008, 4, e37. [Google Scholar] [CrossRef] [Green Version]
  49. Prescott, J.; Du, M.; Wong, J.Y.Y.; Han, J.; De Vivo, I. Paternal age at birth is associated with offspring leukocyte telomere length in the nurses’ health study. Hum. Reprod. 2012, 27, 3622–3631. [Google Scholar] [CrossRef] [Green Version]
  50. Muzzinler, A.; Mons, U.; Dieffenbach, A.K.; Butterbach, K.; Saum, K.U.; Schick, M.; Stammer, H.; Boukamp, P.; Holleczek, B.; Stegmaier, C.; et al. Smoking habits and leukocyte telomere length dynamics among older adults: Results from the ESTHER cohort. Exp. Gerontol. 2015, 70, 18–25. [Google Scholar] [CrossRef]
  51. Valdes, A.M.; Andrew, T.; Gardner, J.P.; Kimura, M.; Oelsner, E.; Cherkas, L.F.; Aviv, A.; Spector, T.D. Obesity, cigarette smoking, and telomere length in women. Lancet 2005, 366, 662–664. [Google Scholar] [CrossRef]
  52. Sassenroth, D.; Meyer, A.; Salewsky, B.; Kroh, M.; Norman, K.; Steinhagen-Thiessen, E.; Demuth, I. Sports and Exercise at Different Ages and Leukocyte Telomere Length in Later Life—Data from the Berlin Aging Study II (BASE-II). PLoS ONE 2015, 10, e0142131. [Google Scholar] [CrossRef] [Green Version]
  53. Price, L.H.; Kao, H.T.; Burgers, D.E.; Carpenter, L.L.; Tyrka, A.R. Telomeres and early-life stress: An overview. Biol. Psychiatry 2013, 73, 15–23. [Google Scholar] [CrossRef] [Green Version]
  54. Coimbra, B.M.; Carvalho, C.M.; Moretti, P.N.; Mello, M.F.; Belangero, S.I. Stress-related telomere length in children: A systematic review. J. Psychiatr. Res. 2017, 92, 47–54. [Google Scholar] [CrossRef] [PubMed]
  55. Edmonds, G.W.; Hampson, S.E.; Cote, H.C.; Hill, P.L.; Klest, B. Childhood Personality, Betrayal Trauma, and Leukocyte Telomere Length in Adulthood: A Lifespan Perspective on Conscientiousness and Betrayal Traumas as Predictors of a Biomarker of Cellular Aging. Eur. J. Personal. 2016, 30, 426–437. [Google Scholar] [CrossRef]
  56. Lindqvist, D.; Epel, E.S.; Mellon, S.H.; Penninx, B.W.; Revesz, D.; Verhoeven, J.E.; Reus, V.I.; Lin, J.; Mahan, L.; Hough, C.M.; et al. Psychiatric disorders and leukocyte telomere length: Underlying mechanisms linking mental illness with cellular aging. Neurosci. Biobehav. Rev. 2015, 55, 333–364. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Ma, D.; Zhu, W.; Hu, S.; Yu, X.; Yang, Y. Association between oxidative stress and telomere length in Type 1 and Type 2 diabetic patients. J. Endocrinol. Investig. 2013, 36, 1032–1037. [Google Scholar]
  58. Babizhayev, M.A.; Vishnyakova, K.S.; Yegorov, Y.E. Oxidative damage impact on aging and age-related diseases: Drug targeting of telomere attrition and dynamic telomerase activity flirting with imidazole-containing dipeptides. Recent Pat. Drug Deliv. Formul. 2014, 8, 163–192. [Google Scholar] [CrossRef] [PubMed]
  59. Entringer, S.; de Punder, K.; Buss, C.; Wadhwa, P.D. The fetal programming of telomere biology hypothesis: An update. Philos. Trans. R. Soc. B Biol. Sci. 2018, 373, 20170151. [Google Scholar] [CrossRef] [PubMed]
  60. Aviv, A. The mitochondrial genome, paternal age and telomere length in humans. Philos. Trans. R. Soc. B Biol. Sci. 2018, 373, 20170210. [Google Scholar] [CrossRef] [Green Version]
  61. De Onis, M.; Blossner, M.; Borghi, E. Global prevalence and trends of overweight and obesity among preschool children. Am. J. Clin. Nutr. 2010, 92, 1257–1264. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Gungor, N.K. Overweight and Obesity in Children and Adolescents. J. Clin. Res. Pediatric Endocrinol. 2014, 6, 129–143. [Google Scholar] [CrossRef] [PubMed]
  63. Valle, M.; Martos, R.; Gascon, F.; Canete, R.; Zafra, M.A.; Morales, R. Low-grade systemic inflammation, hypoadiponectinemia and a high concentration of leptin are present in very young obese children, and correlate with metabolic syndrome. Diabetes Metab. 2005, 31, 55–62. [Google Scholar] [CrossRef]
  64. Skinner, A.C.; Perrin, E.M.; Moss, L.A.; Skelton, J.A. Cardiometabolic Risks and Severity of Obesity in Children and Young Adults. N. Engl. J. Med. 2015, 373, 1307–1317. [Google Scholar] [CrossRef]
  65. Bjerregaard, L.G.; Jensen, B.W.; Angquist, L.; Osler, M.; Sorensen, T.I.A.; Baker, J.L. Change in Overweight from Childhood to Early Adulthood and Risk of Type 2 Diabetes. N. Engl. J. Med. 2018, 378, 1302–1312. [Google Scholar] [CrossRef]
  66. Geserick, M.; Vogel, M.; Gausche, R.; Lipek, T.; Spielau, U.; Keller, E.; Pfaffle, R.; Kiess, W.; Korner, A. Acceleration of BMI in Early Childhood and Risk of Sustained Obesity. N. Engl. J. Med. 2018, 379, 1303–1312. [Google Scholar] [CrossRef] [PubMed]
  67. Han, J.C.; Lawlor, D.A.; Kimm, S.Y.S. Childhood obesity. Lancet 2010, 375, 1737–1748. [Google Scholar] [CrossRef]
  68. WHO. Obesity and Overweight Fact Sheet N°311. January 2015. Retrieved 2 February 2016. Available online: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed on 20 January 2022).
  69. Das, U.N. Is obesity an inflammatory condition? Nutrition 2001, 17, 953–966. [Google Scholar] [CrossRef]
  70. Pogodzinski, D.; Ostrowska, L.; Smarkusz-Zarzecka, J.; Zysk, B. Secretome of Adipose Tissue as the Key to Understanding the Endocrine Function of Adipose Tissue. Int. J. Mol. Sci. 2022, 23, 2309. [Google Scholar] [CrossRef]
  71. Ouchi, N.; Parker, J.L.; Lugus, J.J.; Walsh, K. Adipokines in inflammation and metabolic disease. Nat. Rev. Immunol. 2011, 11, 85–97. [Google Scholar] [CrossRef]
  72. Furukawa, S.; Fujita, T.; Shimabukuro, M.; Iwaki, M.; Yamada, Y.; Nakajima, Y.; Nakayama, O.; Makishima, M.; Matsuda, M.; Shimomura, I. Increased oxidative stress in obesity and its impact on metabolic syndrome. J. Clin. Investig. 2004, 114, 1752–1761. [Google Scholar] [CrossRef] [PubMed]
  73. Das, U.N. Metabolic syndrome X: An inflammatory condition? Curr. Hypertens. Rep. 2004, 6, 66–73. [Google Scholar] [CrossRef] [PubMed]
  74. Carulli, L.; Anzivino, C.; Baldelli, E.; Zenobii, M.F.; Rocchi, M.B.; Bertolotti, M. Telomere length elongation after weight loss intervention in obese adults. Mol. Genet. Metab. 2016, 118, 138–142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. 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, 925–933. [Google Scholar] [CrossRef]
  76. Mundstock, E.; Sarria, E.E.; Zatti, H.; Mattos Louzada, F.; Kich Grun, L.; Herbert Jones, M.; Guma, F.T.; Mazzola In Memoriam, J.; Epifanio, M.; Stein, R.T.; et al. Effect of obesity on telomere length: Systematic review and meta-analysis. Obesity 2015, 23, 2165–2174. [Google Scholar] [CrossRef]
  77. Wang, Q.; Zhan, Y.; Pedersen, N.L.; Fang, F.; Hagg, S. Telomere Length and All-Cause Mortality: A Meta-analysis. Ageing Res. Rev. 2018, 48, 11–20. [Google Scholar] [CrossRef]
  78. O’Donovan, A.; Pantell, M.S.; Puterman, E.; Dhabhar, F.S.; Blackburn, E.H.; Yaffe, K.; Cawthon, R.M.; Opresko, P.L.; Hsueh, W.C.; Satterfield, S.; et al. Cumulative Inflammatory Load Is Associated with Short Leukocyte Telomere Length in the Health, Aging and Body Composition Study. PLoS ONE 2011, 6, e19687. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Trayhurn, P.; Wood, I.S. Adipokines: Inflammation and the pleiotropic role of white adipose tissue. Br. J. Nutr. 2004, 92, 347–355. [Google Scholar] [CrossRef] [Green Version]
  80. Slattery, K.; Bentley, D.; Coutts, A.J. The role of oxidative, inflammatory and neuroendocrinological systems during exercise stress in athletes: Implications of antioxidant supplementation on physiological adaptation during intensified physical training. Sports Med. 2015, 45, 453–471. [Google Scholar] [CrossRef]
  81. Shin, Y.A. How Does Obesity and Physical Activity Affect Aging?: Focused on Telomere as a Biomarker of Aging. J. Obes. Metab. Syndr. 2019, 28, 92–104. [Google Scholar] [CrossRef]
  82. Crocker, M.K.; Yanovski, J.A. Pediatric Obesity: Etiology and Treatment. Pediatric Clin. 2011, 58, 1217. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Shamseer, L.; Moher, D.; Clarke, M.; Ghersi, D.; Liberati, A.; Petticrew, M.; Shekelle, P.; Stewart, L.A.; Group, P.-P. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ 2015, 350, g7647. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Selvaraju, V.; Phillips, M.; Fouty, A.; Babu, J.R.; Geetha, T. Telomere Length as a Biomarker for Race-Related Health Disparities. Genes 2021, 12, 78. [Google Scholar] [CrossRef] [PubMed]
  85. Liu, X.; Liu, X.; Shi, Q.; Fan, X.; Qi, K. Association of telomere length and telomerase methylation with n-3 fatty acids in preschool children with obesity. BMC Pediatrics 2021, 21, 24. [Google Scholar] [CrossRef]
  86. Ooi, D.S.Q.; Dorajoo, R.; Gurung, R.L.; Dehghan, R.; Lim, Y.Y.; Ho, C.W.L.; Tay, V.; Karuppiah, V.; Loke, K.Y.; Lim, S.C.; et al. Association of leukocyte telomere length with obesity-related traits in Asian children with early-onset obesity. Pediatric Obes. 2021, 16, e12771. [Google Scholar] [CrossRef] [PubMed]
  87. Licea-Cejudo, R.C.; Arenas-Sandoval, L.K.; Salazar-Leon, J.; Martinez-Martinez, M.V.; Carreon-Rodriguez, A.; Pedraza-Alva, G.; Perez-Martinez, L. A dysfunctional family environment and a high body fat percentage negatively affect telomere length in Mexican boys aged 8-10 years. Acta Paediatr. 2020, 109, 2091–2098. [Google Scholar] [CrossRef] [PubMed]
  88. Clemente, D.B.P.; Maitre, L.; Bustamante, M.; Chatzi, L.; Roumeliotaki, T.; Fossati, S.; Grazuleviciene, R.; Gutzkow, K.B.; Lepeule, J.; Martens, D.S.; et al. Obesity is associated with shorter telomeres in 8 year-old children. Sci. Rep. 2019, 9, 18739. [Google Scholar] [CrossRef] [Green Version]
  89. Lamprokostopoulou, A.; Moschonis, G.; Manios, Y.; Critselis, E.; Nicolaides, N.C.; Stefa, A.; Koniari, E.; Gagos, S.; Charmandari, E. Childhood obesity and leucocyte telomere length. Eur. J. Clin. Investig. 2019, 49, e13178. [Google Scholar] [CrossRef] [PubMed]
  90. Theall, K.P.; Chaparro, M.P.; Denstel, K.; Bilfield, A.; Drury, S.S. Childhood obesity and the associated roles of neighborhood and biologic stress. Prev. Med. Rep. 2019, 14, 100849. [Google Scholar] [CrossRef]
  91. Zhu, H.; Bhagatwala, J.; Pollock, N.K.; Parikh, S.; Gutin, B.; Stallmann-Jorgensen, I.; Thomas, J.; Harshfield, G.A.; Dong, Y. High sodium intake is associated with short leukocyte telomere length in overweight and obese adolescents. Int. J. Obesity 2015, 39, 1249–1253. [Google Scholar] [CrossRef]
  92. Buxton, J.L.; Walters, R.G.; Visvikis-Siest, S.; Meyre, D.; Froguel, P.; Blakemore, A.I. Childhood obesity is associated with shorter leukocyte telomere length. J. Clin. Endocrinol. Metab. 2011, 96, 1500–1505. [Google Scholar] [CrossRef] [Green Version]
  93. Al-Attas, O.S.; Al-Daghri, N.; Bamakhramah, A.; Shaun Sabico, S.; McTernan, P.; Huang, T.T. Telomere length in relation to insulin resistance, inflammation and obesity among Arab youth. Acta Paediatr. 2010, 99, 896–899. [Google Scholar] [CrossRef] [PubMed]
  94. Zannolli, R.; Mohn, A.; Buoni, S.; Pietrobelli, A.; Messina, M.; Chiarelli, F.; Miracco, C. Telomere length and obesity. Acta Paediatr. 2008, 97, 952–954. [Google Scholar] [CrossRef] [PubMed]
  95. Paltoglou, G.; Raftopoulou, C.; Nicolaides, N.C.; Genitsaridi, S.M.; Karampatsou, S.I.; Papadopoulou, M.; Kassari, P.; Charmandari, E. A Comprehensive, Multidisciplinary, Personalized, Lifestyle Intervention Program Is Associated with Increased Leukocyte Telomere Length in Children and Adolescents with Overweight and Obesity. Nutrients 2021, 13, 2682. [Google Scholar] [CrossRef]
  96. Ojeda-Rodriguez, A.; Morell-Azanza, L.; Martin-Calvo, N.; Zalba, G.; Chueca, M.; Azcona-Sanjulian, M.C.; Marti, A. Association between favourable changes in objectively measured physical activity and telomere length after a lifestyle intervention in pediatric patients with abdominal obesity. Appl. Physiol. Nutr. Metab. 2021, 46, 205–212. [Google Scholar] [CrossRef] [PubMed]
  97. Morell-Azanza, L.; Ojeda-Rodriguez, A.; Azcona-SanJulian, M.C.; Zalba, G.; Marti, A. Associations of telomere length with anthropometric and glucose changes after a lifestyle intervention in abdominal obese children. Nutr. Metab. Cardiovasc. Dis. 2020, 30, 694–700. [Google Scholar] [CrossRef]
  98. Ojeda-Rodriguez, A.; Morell-Azanza, L.; Zalba, G.; Zazpe, I.; Azcona-Sanjulian, M.C.; Marti, A. Associations of telomere length with two dietary quality indices after a lifestyle intervention in children with abdominal obesity: A randomized controlled trial. Pediatric Obes. 2020, 15, e12661. [Google Scholar] [CrossRef]
  99. Garcia-Calzon, S.; Moleres, A.; Marcos, A.; Campoy, C.; Moreno, L.A.; Azcona-Sanjulian, M.C.; Martinez-Gonzalez, M.A.; Martinez, J.A.; Zalba, G.; Marti, A.; et al. Telomere Length as a Biomarker for Adiposity Changes after a Multidisciplinary Intervention in Overweight/Obese Adolescents: The EVASYON Study. PLoS ONE 2014, 9, e89828. [Google Scholar] [CrossRef] [Green Version]
  100. Oliveira, G.J.; Barbiero, S.M.; Cesa, C.C.; Pellanda, L.C. Comparison of NCHS, CDC, and WHO curves in children with cardiovascular risk. Rev. Assoc. Med. Bras. 2013, 59, 375–380. [Google Scholar] [CrossRef] [Green Version]
  101. Gonzalez-Casanova, I.; Sarmiento, O.L.; Gazmararian, J.A.; Cunningham, S.A.; Martorell, R.; Pratt, M.; Stein, A.D. Comparing three body mass index classification systems to assess overweight and obesity in children and adolescents. Rev. Panam. Salud. Publica. 2013, 33, 349–355. [Google Scholar] [CrossRef]
  102. Batsis, J.A.; Mackenzie, T.A.; Vasquez, E.; Germain, C.M.; Emeny, R.T.; Rippberger, P.; Lopez-Jimenez, F.; Bartels, S.J. Association of adiposity, telomere length and mortality: Data from the NHANES 1999–2002. Int. J. Obes. 2018, 42, 198–204. [Google Scholar] [CrossRef]
  103. Chen, S.F.; Yeh, F.; Lin, J.; Matsuguchi, T.; Blackburn, E.; Lee, E.T.; Howard, B.V.; Zhao, J.Y. Short leukocyte telomere length is associated with obesity in American Indians: The strong heart family study. Aging 2014, 6, 380–389. [Google Scholar] [CrossRef] [Green Version]
  104. Lee, M.; Martin, H.; Firpo, M.A.; Demerath, E.W. Inverse Association between Adiposity and Telomere Length: The Fels Longitudinal Study. Am. J. Hum. Biol. 2011, 23, 100–106. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Guyatt, A.L.; Rodriguez, S.; Gaunt, T.R.; Fraser, A.; Anderson, E.L. Early life adiposity and telomere length across the life course: A systematic review and meta-analysis. Wellcome Open Res. 2017, 2, 118. [Google Scholar] [CrossRef] [PubMed]
  106. Rode, L.; Nordestgaard, B.G.; Weischer, M.; Bojesen, S.E. Increased body mass index, elevated C-reactive protein, and short telomere length. J. Clin. Endocrinol. Metab. 2014, 99, E1671–E1675. [Google Scholar] [CrossRef] [Green Version]
  107. Ping, F.; Li, Z.Y.; Lv, K.; Zhou, M.C.; Dong, Y.X.; Sun, Q.; Li, Y.X. Deoxyribonucleic acid telomere length shortening can predict the incidence of non-alcoholic fatty liver disease in patients with type 2 diabetes mellitus. J. Diabetes Investig. 2017, 8, 174–180. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Brouilette, S.W.; Moore, J.S.; McMahon, A.D.; Thompson, J.R.; Ford, I.; Shepherd, J.; Packard, C.J.; Samani, N.J.; West of Scotland Coronary Prevention Study, G. Telomere length, risk of coronary heart disease, and statin treatment in the West of Scotland Primary Prevention Study: A nested case-control study. Lancet 2007, 369, 107–114. [Google Scholar] [CrossRef]
  109. Houben, J.M.; Moonen, H.J.; van Schooten, F.J.; Hageman, G.J. Telomere length assessment: Biomarker of chronic oxidative stress? Free Radic. Biol. Med. 2008, 44, 235–246. [Google Scholar] [CrossRef]
  110. Wolkowitz, O.M.; Mellon, S.H.; Epel, E.S.; Lin, J.; Dhabhar, F.S.; Su, Y.; Reus, V.I.; Rosser, R.; Burke, H.M.; Kupferman, E.; et al. Leukocyte telomere length in major depression: Correlations with chronicity, inflammation and oxidative stress--preliminary findings. PLoS ONE 2011, 6, e17837. [Google Scholar] [CrossRef] [Green Version]
  111. Zhao, J.; Zhu, Y.; Lin, J.; Matsuguchi, T.; Blackburn, E.; Zhang, Y.; Cole, S.A.; Best, L.G.; Lee, E.T.; Howard, B.V. Short leukocyte telomere length predicts risk of diabetes in american indians: The strong heart family study. Diabetes 2014, 63, 354–362. [Google Scholar] [CrossRef] [Green Version]
  112. Finkel, T.; Holbrook, N.J. Oxidants, oxidative stress and the biology of ageing. Nature 2000, 408, 239–247. [Google Scholar] [CrossRef] [PubMed]
  113. Paltoglou, G.; Avloniti, A.; Chatzinikolaou, A.; Stefanaki, C.; Papagianni, M.; Papassotiriou, I.; Fatouros, I.G.; Chrousos, G.P.; Kanaka-Gantenbein, C.; Mastorakos, G. In early pubertal boys, testosterone and LH are associated with improved anti-oxidation during an aerobic exercise bout. Endocrine 2019, 66, 370–380. [Google Scholar] [CrossRef] [PubMed]
  114. Alleman, R.J.; Katunga, L.A.; Nelson, M.A.; Brown, D.A.; Anderson, E.J. The “Goldilocks Zone” from a redox perspective-Adaptive vs. deleterious responses to oxidative stress in striated muscle. Front. Physiol. 2014, 5, 358. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  115. Fisher-Wellman, K.; Bloomer, R.J. Acute exercise and oxidative stress: A 30 year history. Dyn. Med 2009, 8, 1. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  116. Paltoglou, G.; Fatouros, I.G.; Valsamakis, G.; Schoina, M.; Avloniti, A.; Chatzinikolaou, A.; Kambas, A.; Draganidis, D.; Mantzou, A.; Papagianni, M.; et al. Antioxidation improves in puberty in normal weight and obese boys, in positive association with exercise-stimulated growth hormone secretion. Pediatric Res. 2015, 78, 158–164. [Google Scholar] [CrossRef] [Green Version]
  117. Barnes, R.P.; Fouquerel, E.; Opresko, P.L. The impact of oxidative DNA damage and stress on telomere homeostasis. Mech. Ageing Dev. 2019, 177, 37–45. [Google Scholar] [CrossRef] [PubMed]
  118. Demissie, S.; Levy, D.; Benjamin, E.J.; Cupples, L.A.; Gardner, J.P.; Herbert, A.; Kimura, M.; Larson, M.G.; Meigs, J.B.; Keaney, J.F.; et al. Insulin resistance, oxidative stress, hypertension, and leukocyte telomere length in men from the Framingham Heart Study. Aging Cell 2006, 5, 325–330. [Google Scholar] [CrossRef] [PubMed]
  119. Lin, L.; Qin, K.; Chen, D.Z.; Lu, C.Y.; Chen, W.Q.; Guo, V.Y. Systematic review and meta-analysis of the association between paediatric obesity and telomere length. Acta Paediatr. 2021, 110, 2695–2703. [Google Scholar] [CrossRef]
  120. Salpea, K.D.; Talmud, P.J.; Cooper, J.A.; Maubaret, C.G.; Stephens, J.W.; Abelak, K.; Humphries, S.E. Association of telomere length with type 2 diabetes, oxidative stress and UCP2 gene variation. Atherosclerosis 2010, 209, 42–50. [Google Scholar] [CrossRef] [Green Version]
  121. Dusserre, E.; Moulin, P.; Vidal, H. Differences in mRNA expression of the proteins secreted by the adipocytes in human subcutaneous and visceral adipose tissues. Biochim. Biophys. Acta 2000, 1500, 88–96. [Google Scholar] [CrossRef] [Green Version]
  122. Fuentes, E.; Fuentes, F.; Vilahur, G.; Badimon, L.; Palomo, I. Mechanisms of chronic state of inflammation as mediators that link obese adipose tissue and metabolic syndrome. Mediat. Inflamm. 2013, 2013, 136584. [Google Scholar] [CrossRef] [PubMed]
  123. Korner, A.; Kratzsch, J.; Gausche, R.; Schaab, M.; Erbs, S.; Kiess, W. New predictors of the metabolic syndrome in children--role of adipocytokines. Pediatric Res. 2007, 61, 640–645. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Marseglia, L.; Manti, S.; D’Angelo, G.; Nicotera, A.; Parisi, E.; Di Rosa, G.; Gitto, E.; Arrigo, T. Oxidative Stress in Obesity: A Critical Component in Human Diseases. Int. J. Mol. Sci. 2015, 16, 378–400. [Google Scholar] [CrossRef] [Green Version]
  125. Soares, A.F.; Guichardant, M.; Cozzone, D.; Bernoud-Hubac, N.; Bouzaidi-Tiali, N.; Lagarde, M.; Geloen, A. Effects of oxidative stress on adiponectin secretion and lactate production in 3T3-L1 adipocytes. Free Radic. Biol. Med. 2005, 38, 882–889. [Google Scholar] [CrossRef] [PubMed]
  126. Cinti, S.; Mitchell, G.; Barbatelli, G.; Murano, I.; Ceresi, E.; Faloia, E.; Wang, S.; Fortier, M.; Greenberg, A.S.; Obin, M.S. Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans. J. Lipid Res. 2005, 46, 2347–2355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  127. Ellulu, M.S.; Khaza’ai, H.; Rahmat, A.; Patimah, I.; Abed, Y. Obesity can predict and promote systemic inflammation in healthy adults. Int. J. Cardiol. 2016, 215, 318–324. [Google Scholar] [CrossRef]
  128. Despres, J.P.; Lemieux, I. Abdominal obesity and metabolic syndrome. Nature 2006, 444, 881–887. [Google Scholar] [CrossRef]
  129. Minamino, T.; Orimo, M.; Shimizu, I.; Kunieda, T.; Yokoyama, M.; Ito, T.; Nojima, A.; Nabetani, A.; Oike, Y.; Matsubara, H.; et al. A crucial role for adipose tissue p53 in the regulation of insulin resistance. Nat. Med. 2009, 15, 1082–1087. [Google Scholar] [CrossRef] [PubMed]
  130. Palmai-Pallag, T.; Bachrati, C.Z. Inflammation-induced DNA damage and damage-induced inflammation: A vicious cycle. Microbes. Infect. 2014, 16, 822–832. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  131. Erol, A. Systemic DNA Damage Response and Metabolic Syndrome as a Premalignant State. Curr. Mol. Med. 2010, 10, 321–334. [Google Scholar] [CrossRef] [PubMed]
  132. Shimizu, I.; Yoshida, Y.; Suda, M.; Minamino, T. DNA Damage Response and Metabolic Disease. Cell Metab. 2014, 20, 967–977. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  133. Caldon, C.E. Estrogen signaling and the DNA damage response in hormone dependent breast cancers. Front. Oncol. 2014, 4, 106. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  134. Fitzpatrick, A.L.; Kronmal, R.A.; Gardner, J.P.; Psaty, B.M.; Jenny, N.S.; Tracy, R.P.; Walston, J.; Kimura, M.; Aviv, A. Leukocyte telomere length and cardiovascular disease in the cardiovascular health study. Am. J. Epidemiol. 2007, 165, 14–21. [Google Scholar] [CrossRef] [PubMed]
  135. Muezzinler, A.; Zaineddin, A.K.; Brenner, H. Body mass index and leukocyte telomere length in adults: A systematic review and meta-analysis. Obes. Rev. 2014, 15, 192–201. [Google Scholar] [CrossRef]
  136. Masi, S.; Nightingale, C.M.; Day, I.N.; Guthrie, P.; Rumley, A.; Lowe, G.D.; von Zglinicki, T.; D’Aiuto, F.; Taddei, S.; Klein, N.; et al. Inflammation and not cardiovascular risk factors is associated with short leukocyte telomere length in 13- to 16-year-old adolescents. Arterioscler. Thromb. Vasc. Biol. 2012, 32, 2029–2034. [Google Scholar] [CrossRef] [Green Version]
  137. Weisberg, S.P.; McCann, D.; Desai, M.; Rosenbaum, M.; Leibel, R.L.; Ferrante, A.W., Jr. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Investig. 2003, 112, 1796–1808. [Google Scholar] [CrossRef]
  138. Arikawa, A.Y.; Thomas, W.; Gross, M.; Smith, A.; Phipps, W.R.; Kurzer, M.S.; Schmitz, K.H. Aerobic training reduces systemic oxidative stress in young women with elevated levels of F2-isoprostanes. Contemp. Clin. Trials. 2013, 34, 212–217. [Google Scholar] [CrossRef] [Green Version]
  139. Campbell, P.T.; Gross, M.D.; Potter, J.D.; Schmitz, K.H.; Duggan, C.; Mctiernan, A.; Ulrich, C.M. Effect of Exercise on Oxidative Stress: A 12-Month Randomized, Controlled Trial. Med. Sci. Sport Exerc. 2010, 42, 1448–1453. [Google Scholar] [CrossRef] [Green Version]
  140. Laufs, U.; Wassmann, S.; Czech, T.; Munzel, T.; Eisenhauer, M.; Bohm, M.; Nickenig, G. Physical inactivity increases oxidative stress, endothelial dysfunction, and atherosclerosis. Arterioscl. Throm. Vas. 2005, 25, 809–814. [Google Scholar] [CrossRef] [Green Version]
  141. Sarifakioglu, B.; Guzelant, A.Y.; Guzel, E.C.; Guzel, S.; Kiziler, A.R. Effects of 12-week combined exercise therapy on oxidative stress in female fibromyalgia patients. Rheumatol. Int. 2014, 34, 1361–1367. [Google Scholar] [CrossRef]
  142. Himbert, C.; Thompson, H.; Ulrich, C.M. Effects of Intentional Weight Loss on Markers of Oxidative Stress, DNA Repair and Telomere Length—a Systematic Review. Obes. Facts 2017, 10, 648–665. [Google Scholar] [CrossRef] [PubMed]
  143. Galie, S.; Canudas, S.; Muralidharan, J.; Garcia-Gavilan, J.; Bullo, M.; Salas-Salvado, J. Impact of Nutrition on Telomere Health: Systematic Review of Observational Cohort Studies and Randomized Clinical Trials. Adv. Nutr. 2020, 11, 576–601. [Google Scholar] [CrossRef] [PubMed]
  144. Leung, C.W.; Fung, T.T.; McEvoy, C.T.; Lin, J.; Epel, E.S. Diet Quality Indices and Leukocyte Telomere Length Among Healthy US Adults: Data From the National Health and Nutrition Examination Survey, 1999–2002. Am. J. Epidemiol. 2018, 187, 2192–2201. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  145. de la Puente, M.F.; Hernandez-Alonso, P.; Canudas, S.; Marti, A.; Fito, M.; Razquin, C.; Salas-Salvado, J. Modulation of Telomere Length by Mediterranean Diet, Caloric Restriction, and Exercise: Results from PREDIMED-Plus Study. Antioxidants 2021, 10, 1596. [Google Scholar]
  146. Tosti, V.; Bertozzi, B.; Fontana, L. Health Benefits of the Mediterranean Diet: Metabolic and Molecular Mechanisms. J. Gerontol. a-Biol. 2018, 73, 318–326. [Google Scholar] [CrossRef] [Green Version]
  147. Spyridopoulos, I.; Erben, Y.; Brummendorf, T.H.; Haendeler, J.; Dietz, K.; Seeger, F.; Kissel, C.K.; Martin, H.; Hoffmann, J.; Assmus, B.; et al. Telomere gap between granulocytes and lymphocytes is a determinant for hematopoetic progenitor cell impairment in patients with previous myocardial infarction. Arterioscl. Throm. Vas. 2008, 28, 968–974. [Google Scholar] [CrossRef] [Green Version]
  148. Starkweather, A.R.; Alhaeeri, A.A.; Montpetit, A.; Brumelle, J.; Filler, K.; Montpetit, M.; Mohanraj, L.; Lyon, D.E.; Jackson-Cook, C.K. An Integrative Review of Factors Associated with Telomere Length and Implications for Biobehavioral Research. Nurs. Res. 2014, 63, 36–50. [Google Scholar] [CrossRef] [Green Version]
  149. Turner, K.J.; Vasu, V.; Griffin, D.K. Telomere Biology and Human Phenotype. Cells 2019, 8, 73. [Google Scholar] [CrossRef] [Green Version]
  150. Lin, J.; Cheon, J.; Brown, R.; Coccia, M.; Puterman, E.; Aschbacher, K.; Sinclair, E.; Epel, E.; Blackburn, E.H. Systematic and Cell Type-Specific Telomere Length Changes in Subsets of Lymphocytes. J. Immunol. Res. 2016, 2016, 1–9. [Google Scholar] [CrossRef]
  151. Epel, E. How “Reversible” Is Telomeric Aging? Cancer Prev. Res. 2012, 5, 1163–1168. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  152. Biegler, K.A.; Anderson, A.K.L.; Wenzel, L.B.; Osann, K.; Nelson, E.L. Longitudinal Change in Telomere Length and the Chronic Stress Response in a Randomized Pilot Biobehavioral Clinical Study: Implications for Cancer Prevention. Cancer Prev. Res. 2012, 5, 1173–1182. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  153. Conboy, I.M.; Conboy, M.J.; Wagers, A.J.; Girma, E.R.; Weissman, I.L.; Rando, T.A. Rejuvenation of aged progenitor cells by exposure to a young systemic environment. Nature 2005, 433, 760–764. [Google Scholar] [CrossRef]
  154. Kim, J.H.; Ko, J.H.; Lee, D.C.; Lim, I.; Bang, H. Habitual physical exercise has beneficial effects on telomere length in postmenopausal women. Menopause 2012, 19, 1109–1115. [Google Scholar] [CrossRef] [PubMed]
  155. Simpson, R.J.; Lowder, T.W.; Spielmann, G.; Bigley, A.B.; LaVoy, E.C.; Kunz, H. Exercise and the aging immune system. Ageing Res. Rev. 2012, 11, 404–420. [Google Scholar] [CrossRef] [PubMed]
  156. Nussey, D.H.; Baird, D.; Barrett, E.; Boner, W.; Fairlie, J.; Gemmell, N.; Hartmann, N.; Horn, T.; Haussmann, M.; Olsson, M.; et al. Measuring telomere length and telomere dynamics in evolutionary biology and ecology. Methods Ecol. Evol. 2014, 5, 299–310. [Google Scholar] [CrossRef]
Nutrients 14 01244 g001 550
Figure 1. Flow diagram of the study selection process.
Figure 1. Flow diagram of the study selection process.
Nutrients 14 01244 g001
Table
Table 1. Inclusion and exclusion criteria.
Table 1. Inclusion and exclusion criteria.
Inclusion CriteriaExclusion Criteria
  • Age < 18 years old
  • Studies from any geographic location
  • Any publication date
  • Any language
  • Assessing the relationship between telomere length and obese, overweight and normal-BMI children and adolescents
  • Age ≥ 18 years old
  • Reviews, editorials, abstracts, case controls, expert opinions
  • In vitro or animal experiments
Primary objective
  • Observational studies
Secondary objective
  • Interventional studies
Table
Table 2. Ottawa scale.
Table 2. Ottawa scale.
Primary Objective: Cross-Sectional Studies
Author/YearSelectionComparabilityOutcomeOverall Score
Selvaraju 2021 [84]** *******9
Liu 2021 [85]** ******8
Ooi 2021 [86]** ******8
Licea-Cejudo 2020 [87]** ******8
Clemente 2019 [88]** *******9
Lamprokostopoulou 2019 [89]*********9
Theall 2019 [90]** ******8
Zhu 2015 [91]** *******9
Buxton 2011 [92]** ******8
Al-Attas 2010 [93]** ******8
Zannolli 2008 [94]* ******7
Secondary Objective: Interventional Studies
Author/YearSelectionComparabilityOutcomeOverall Score
Paltoglou 2021 [95]** ******8
Ojeda-Rodríguez 2021 [96]*********9
Morell-Azanza 2020 [97]** ******8
Ojeda-Rodríguez 2020 [98]** ******8
García-Calzón 2014 [99]*********9
The Newcastle-Ottawa Scale quality instrument is scored by awarding a point for each answer that is marked with an asterisk (*). Each asterisk represents the fact that an individual criterion within the subsection was fulfilled.
Table
Table 3. Characteristics of the cross-sectional studies included in the systematic review.
Table 3. Characteristics of the cross-sectional studies included in the systematic review.
Author YearNationalityStudy DesignSample SizeObesity DefinitionAge (Years)
Mean ± SD
or Range		Male
(%)		Method/TissueTL Outcome
TotalOB & OW (%)Reference
Grouping
Selvaraju 2021 [84]European American, African AmericanCross-sectional127NACDC
[NW]-([OW] & [OB])		6–10NAqPCR
Saliva
▪
No differences in the TL among obese, overweight and normal-BMI groups of either race
Liu 2021 [85]ChineseCross-sectional9250% OBWHO
[NW]-[OB]		3–4NAqPCR
Leukocytes
▪
Significantly shorter TL in obese children compared to children with normal BMI
▪
Negative correlation between TL and BMI
Ooi 2021 [86]SingaporeanCross-sectional39494.2% OBWHO + 2SD
[NW]-[OB]		14.0 ± 3.02 OB
13.1 ± 3.40 NW		67.7qPCR
Leukocytes
▪
Significantly shorter TL in obese children compared to children with normal BMI
▪
Negative correlation between TL and waist circumference
▪
Positive correlation between TL and skinfold measurements
Licea-Cejudo 2020 [87]MexicanCross-sectional13465.7% OBCDC
[NW]-([OW] & [OB])		8–1052qPCR
Saliva
▪
No differences in the TL among obese, overweight and normal-BMI children
▪
Significantly shorter TL were associated with high BF% in boys, but not in girls
Clemente 2019 [88]EuropeanCross-sectional1.3966% OB
15.4% OW		WHO
[NW]-([OW]&[OB])		6–11
8.0 ± 1.5		53.9qPCR
Leukocytes
▪
Significantly shorter TL in overweight and obese children compared to children with normal BMI
Lamprokostopoulou 2019 [89]GreekCross-sectional91913.5% OB
30.0% OW		Greek Ref. Chart IOTF
[NW]-[OW]-[OB]		9–1350.2qPCR
Leukocytes
▪
Significantly shorter TL in overweight and obese children and adolescents compared to children with normal BMI
▪
Multivariable linear regression revealed increasing weight category was inversely associated with TL in children and adolescents
Theall 2019 [90]AmericanCross-sectional9032.2%
OW&OB		CDC
[NW]-([OW] & [OB])		5–1646%qPCR
Buccal swab
▪
No differences in the TL among obese, overweight and normal-BMI children
Zhu 2015 [91]Caucasian and Afro-AmericanCross-sectional76624.9%
OW&OB		CDC
[NW]-([OW] & [OB])		14–18
16.1 ± 0.0		49.7qPCR
Leukocytes
▪
No differences in the TL among obese, overweight and normal-BMI children
▪
Significantly shorter TL in overweight and obese adolescents is associated with higher dietary sodium intake
Buxton 2011 [92]FrenchCase-control79359.4% OBFrench Ref. Chart
[NW]-[OB]		2–1753.9qPCR
Leukocytes
▪
Significantly shorter TL in obese girls and boys compared with their non-obese counterparts
Al-Attas 2010 [93]Saudi ArabianCross-sectional14835.1% OBIOTF
[NW]-[OB]		5–12
8.5 ± 2.1 boys
9.7 ± 2.6 girls		46.6qPCR
Leukocytes
▪
Significantly shorter TL in obese boys compared with their normal-BMI counterparts, but not in girls
Zannolli 2008 [94]ItalianCross-sectional5322.6% OBItalian Ref. Chart
[NW]-[OB]		8.2 ± 3.5NATRF
PBMC
▪
No differences in the TL between obese and normal-BMI children
Abbreviations: NA, not available; TL, telomere length; OW, overweight; OB, obese; NW, normal weight; non obese, normal (BMI) weight and overweight; CDC: Center of Diseases Control and Prevention; WHO, World Health Organization; IOTF, International Obesity Task Force; PCR, polymerase chain reaction.
Table
Table 4. Characteristics of the lifestyle intervention studies included in the systematic review.
Table 4. Characteristics of the lifestyle intervention studies included in the systematic review.
Author YearNationalityDietary and Physical Activity InterventionsSample SizeObesity DefinitionAge (Years)
Mean ± SD or Range		Male
(%)		Method/
Tissue		TL Outcome
PeriodTelomere MeasureTotalOB & OW (%)Reference Grouping
Paltoglou 2021 [95]Greek12 monthsBaseline
12 months		50852.6% OB
34.2% OW		Greek Ref. Chart
[NW][OW] [OB]		10.14 ± 0.1347qPCR
Leukocytes
▪
A significant increase in TL irrespective of gender, pubertal status, or BMI after a lifestyle intervention program of healthy diet and physical exercise
Ojeda-Rodríguez 2021 [96]Spanish2 monthsBaseline
2, 12 months		102 OW&OB75
Intervent.
27
usual care		Spanish Ref. Chart
[OW&OB]		7–1636qPCR
Leukocytes
▪
TL did not change after intervention
▪
TL increase was positively associated with energy expenditure as assessed by metabolic equivalents (METs), moderate physical activity (MVPA) level and number of steps in the intervention group after the intensive phase
▪
TL increase was inversely associated with secondary and light physical activity (PA) levels in the intervention group after the intensive phase
Morell-Azanza 2020 [97]Spanish2 monthsBaseline
2 months		106 OW&OB Spanish Ref. Chart
[OW&OB]		7–16
11.30 ± 2.49		37qPCR
Leukocytes
▪
TL did not change after intervention
▪
A negative TL correlation with BMI at baseline
▪
TL at baseline predicted changes in blood glucose levels after the intervention
Ojeda-Rodríguez 2020 [98]Spanish2 monthsBaseline
2, 12 months		87 OW&OB64 intervent.
23
usual care		Spanish Ref. Chart
[OW&OB]		7–1639qPCR
Leukocytes
▪
A significant increase in TL in the follow up period 2–12 months of intervention, in children with abdominal obesity enrolled in an intensive lifestyle intervention
García-Calzón 2014 [99]Spanish2 monthsBaseline
2 months
Follow-up 6 months		74 OW&OB96% OB
4% OW		Spanish Ref. Chart
[OW&OB]		12–1648.6qPCR
Leukocytes
▪
A significant increase in TL in overweight & obese adolescents after a weight loss intervention
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Raftopoulou, C.; Paltoglou, G.; Charmandari, E. Association between Telomere Length and Pediatric Obesity: A Systematic Review. Nutrients 2022, 14, 1244. https://doi.org/10.3390/nu14061244

AMA Style

Raftopoulou C, Paltoglou G, Charmandari E. Association between Telomere Length and Pediatric Obesity: A Systematic Review. Nutrients. 2022; 14(6):1244. https://doi.org/10.3390/nu14061244

Chicago/Turabian Style

Raftopoulou, Christina, George Paltoglou, and Evangelia Charmandari. 2022. "Association between Telomere Length and Pediatric Obesity: A Systematic Review" Nutrients 14, no. 6: 1244. https://doi.org/10.3390/nu14061244

APA Style

Raftopoulou, C., Paltoglou, G., & Charmandari, E. (2022). Association between Telomere Length and Pediatric Obesity: A Systematic Review. Nutrients, 14(6), 1244. https://doi.org/10.3390/nu14061244

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop