Mindfulness and meditation techniques have proven successful for the reduction of stress and improvement in general health. In addition, meditation is linked to longevity and longer telomere length, a proposed biomarker of human aging. Interestingly, DNA methylation changes have been described at specific subtelomeric regions in long-term meditators compared to controls. However, the molecular basis underlying these beneficial effects of meditation on human health still remains unclear. Here we show that DNA methylation levels, measured by the Infinium HumanMethylation450 BeadChip (Illumina) array, at specific subtelomeric regions containing GPR31 and SERPINB9 genes were associated with telomere length in long-term meditators with a strong statistical trend when correcting for multiple testing. Notably, age showed no association with telomere length in the group of long-term meditators. These results may suggest that long-term meditation could be related to epigenetic mechanisms, in particular gene-specific DNA methylation changes at distinct subtelomeric regions.
In recent years, the use of mindfulness and meditation techniques have been increasing in western societies with the aim of reducing stress and improving overall health1,2,3,4. Mindfulness-based interventions have proved their beneficial effect on a number of medical and psychological conditions, including depression, anxiety, and immune disorders5,6,7,8. In addition, it has been proposed that meditation techniques could positively affect longevity9,10. In fact, intensive meditation training has been associated with an increase in telomerase activity11 and longer telomere length in blood cells12,13,14,15,16, which is considered a candidate biomarker of human aging.
Telomeres are DNA-protein complexes that protect the end of linear chromosomes from degradation, fusion, or DNA repair processes17,18,19. Telomeres shorten with every somatic cell division because of the end replication problem19,20, but this erosion is partially compensated by the action of telomerase, an enzyme complex that adds TTAGGG hexanucleotide repeats to the telomeric DNA17,21. However, telomerase expression levels in mammalian adult cells are not sufficient to preserve the original length of telomeres, resulting in the progressive shortening of chromosomes throughout life20,22,23,24. Telomere shortening has been associated with age-related conditions25,26,27,28, and telomere length is hypothesized to be a biomarker of aging and age-related morbidity29,30,31,32,33,34.
In line with other reports, our group previously observed a positive relationship between meditation practice and longer telomere length in peripheral blood cells13. Moreover, in a previous work to gain insight into the molecular mechanisms of meditation, we profiled genome-wide DNA methylation changes in long-term meditators and identified a set of 64 differentially methylated regions (DMRs), corresponding to 43 genes, when compared to controls35. Almost half of the DMRs (48.4%) were directly linked to common human diseases, including neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. Surprisingly, up to 23.4% of these DMRs were found to be located at subtelomeric regions (hypergeometric test fold-enrichment = 1.3; p-value < 0.05). However, the importance of these epigenetic changes within the subtelomeric regions in meditators remains unclear.
Increasing evidence supports the idea that epigenetic changes in subtelomeric regions may be linked to telomere length. For instance, in blood cells from healthy middle-aged men it was found that CpG sites whose methylation level was associated with telomere length were significantly enriched at subtelomeric regions36. Most importantly, TET (Ten-eleven translocation) enzymes which are responsible of converting 5-methylcytosine to 5-hydroxymethylcytosine, have been proved crucial in telomere maintenance by modulating subtelomeric methylation levels37. Additional evidence on the potential role of DNA methylation in telomere homeostasis shows that mouse embryonic stem cells lacking DNA methyltransferases have decreased global methylation in subtelomeric regions and dramatically elongated telomeres38. On the contrary, telomere shortening to a critically short length leads to epigenetic defects at mammalian telomeres and subtelomeres, such as decreased subtelomeric DNA methylation39,40.
A number of pathological conditions support the possible involvement of subtelomeric DNA methylation in telomere length stability. Human mutations on the DNA methyltransferase DNMT3B [OMIM, * 602900], which cause immunodeficiency-centromeric instability-facial anomalies syndrome 1, are associated with subtelomeric global hypomethylation along with accelerated telomere shortening of fibroblasts41,42. Both direct and inverse correlation has been described for various types of human cancer between subtelomeric DNA methylation levels and telomere length43,44. To sum up, DNA methylation levels at subtelomeric regions might play a role in maintaining telomere length, among other mechanisms. However, the potential effect that subtelomeric DNA methylation levels may exert on telomere length and the underlying mechanisms remain unknown.
The aim of the present study was to better understand the relevance of subtelomeric DNA methylation changes in long-term meditators. To that end, we tested the association of telomere length with DNA methylation levels and age in long-term meditators and controls for this set of DMRs.
The general characteristics of subjects included in the study are shown in Table 1. Socio-demographic characteristics including age, gender, ethnicity, and BMI were equally distributed between groups. However, as expected, there were significant differences in the amount of practical experience of meditation and also in all the psychological health-related variables referred to below (see Methods section).
Relationship between DNA methylation levels and telomere length
From our genome-wide DNA methylation differential analysis between long-term MMs and controls35, we selected the group of 14 DMRs located in subtelomeric regions, involving chromosomes 2, 4, 5, 6, 7, 8, 16, 19, and 20. We define subtelomeric regions as those regions at either end of each chromosome with a length of 3000 kb. We selected this subtelomeric length as an operational definition in order to perform the bioinformatics analysis, since the exact bounderies for subtelomeres have not yet been well established. This group represents 23.4% of the total DMRs (hypergeometric test fold-enrichment = 1.3; p-value < 0.05) that were identified in long-term MMs compared to controls. Genes and DNA methylation levels for these regions are shown in Table 2.
The raw differences between groups showed that telomere length was longer in meditators (Mn = 10.47; SD = 0.86) compared to controls (Mn = 9.87; SD = 0.94), without any statistical significance, but showing a strong trend (t = −1.94; df = 32; p = 0.061), with a moderately high ES (d = 0.67). However, the differences appeared to be significant (t = −3.44; df = 32; p = 0.002) after controlling for age, with a very high ES (d = 1.25). We then asked whether telomere length was correlated with gene-specific DNA methylation levels. In the group of long-term MMs, we found a positive raw correlation between telomere length and DNA methylation levels at the GPR31 gene (r = 0.58, p = 0.014), whereas an inverse correlation was shown between telomere length and DNA methylation levels at two distinct loci: SERPINB9 gene (r = −0.64, p = 0.006) and an intergenic CpG island within the subtelomeric region of chromosome 4 short arm (chr4:1514317–1514621, GRCh37/hg19 assembly) (r = −0.51, p = 0.036) (Fig. 1). After correction for age, the significant correlations remained (Table 3). To test for multiple comparisons, we draw at random 1000 sub-samples of 14 not differentially methylated regions within subtelomeric regions. The proportion of such random sets showing 3 or more hits with absolute r value greater than or equal to 0.51 (the minimum value for our selection) was 0.052 (>0.05). Therefore, the possibility of a false positive result cannot be completely excluded.
Maps of these DMRs and differential DNA methylation levels between long-term MMs and controls are shown in Fig. 2. In contrast, no significant correlation was found between DNA methylation levels of any gene and telomere length in the control group, either before or after controlling for age (Table 3, Fig. 1).
Relationship between age and telomere length
Since age is well known to be associated with progressive telomere shortening, we further checked the correlation between age and telomere length separately for each group. We found that age showed a strong inverse correlation with telomere length in the control group (r = −0.95, p < 0.001), as expected. In fact, the great explanatory power of multivariate models to explain telomere length in the control group was exclusively due to the intervention of age (Table 3). However, this inverse correlation between age and telomere length, although with a moderately low effect, was no longer seen to be significant for the meditation group (r = −0.38, p = 0.127), in which multivariate models were less powered to explain telomere length, and only some DNA methylation levels showed significant contributions (Table 3).
Relationship between DNA methylation and mRNA expression
We measured GPR31 and SERPIN9 mRNA expression levels by real time quantitative PCR (RT-qPCR) in peripheral blood of long-term meditators compared to controls. Three control samples did not pass the RNA quality threshold (see Methods section) and so were not included in the experiments. Eventually, 17 long-term meditators were compared to 14 controls. After normalizing mRNA expression levels to the geometric mean of 2 housekeeping genes (ACTB & TBP), we found that blood expression was very low for GPR31 (CTs >30), so no reliable differential analysis could be performed. In the case of SERPIN9, differential analysis showed no statistical significant difference in mRNA expression levels between meditators and controls (p = 0.493).
In this cross-sectional study, we have shown that telomere length is associated with DNA methylation levels in long-term MMs at three distinct subtelomeric regions, involving the GPR31 and SERPINB9 genes. Notably, telomere length did not correlate with age in the group of meditators, in contrast with the significant inverse correlation between telomere length and age in the comparison group.
Telomere length is involved in molecular and cellular senescence and has been proposed as a biomarker of human aging29,30,31,32,33,34. The progressive decrease in telomere length with age has long been known22,23,24. Short telomeres contribute to genomic instability that is permissive for cancer initiation and progression17. In addition, leukocyte telomere shortening has been associated with several age-related conditions, such as cardiovascular events, including stroke and myocardial infarction25,26, and cognitive performance27. In this scenario, telomerase-based therapies are emerging as novel approaches for the treatment of age-related diseases45,46.
While stressful life events and psychological stress have been consistently associated with leukocyte telomere erosion47,48,49,50, some healthy habits and behaviors have been related to longer telomere length or reported to reduce the rate of telomere shortening, e.g., physical activity and training51,52,53. In line with the previous factors, yoga practice and meditation are related to longer telomere length in blood cells12,14,15,16, as a previous work by our group has also shown13. Also in the case of cancer patients, such as distressed breast cancer survivors, mindfulness-based therapy is associated with telomere length maintenance54. Furthermore, it has been observed that mindfulness meditation leads to increased telomerase activity in PBMCs15. All this evidence suggests that some interventions may help to buffer the negative impact of stress on health and telomere length. A number of mechanisms have been postulated to mediate the effect of meditation on telomere stability, such as the modulation of the hypothalamic-pituitary-adrenal axis55 or reduction in oxidative stress and inflammatory pathways20,56,57. However, the biological substrate underlying this relationship remains largely unknown.
In the present study, differences between meditators and controls on telomere length were not significant before controlling for age, and thus did not replicate the raw findings from Alda et al.13. However, this could be due to the smaller sample size used that could reduce statistical power. In fact, results of the present study showed a trend very close to statistical significance, with a moderately high effect size, and differences appeared clearer and significant after controlling for age. Anyway, as expected, our study found a strong inverse correlation between age and telomere length in the control group. Interestingly, we observed that age was no longer related to telomere length in the group of long-term MMs. Due to the limited sample size, this finding may cautiously be interpreted as suggesting that long-term meditation may somewhat counteract the effect of biological aging on telomere length. This could be accounted for, at least in part, the fact that meditation significantly reduces stress and the biological correlates of stress on the human body58,59. Consistent with this idea, meditation has also been associated with longevity60,61. Anyhow, this is an exploratory study and the underlying molecular changes still need further investigation. This work will guide future research using more powered designs to control for possible errors.
Remarkably, we also found that telomere length was associated with gene-specific subtelomeric DNA methylation changes in the group of long-term MMs. The fact that no correlation was found between the DNA methylation levels of the selected genes and the telomere length in the control group is intriguing. First, we cannot preclude in the controls that other genes undergo changes in DNA methylation levels in relation to telomere length, since we have studied a very small number of genes. Second, these genes were found to be differentially methylated in meditation practitioners and meditation may be related to the maintenance of telomere length12,13,14,15,16. Thus, finding a relationship between methylation of these genes and telomere length is interesting and opens up the venue to further study these genes as targets of epigenetic changes in meditation practitioners.
As mention above, these genomic spots were found to be differentially methylated in meditators compared to controls in our previous work35. In the present study, DNA methylation levels at the GPR31 gene were positively correlated to telomere length. GPR31 (G protein-coupled receptor 31) encodes a high-affinity cell membrane receptor for 12-S-HETE, which is an arachidonic acid metabolite secreted by platelets and tumor cells that induces endothelial cell retraction and plays a role in extravasation and metastasis62. Notably, GPR31 has been proposed as a target of oncology therapies since GPR31 mediates KRAS (Kirsten rat sarcoma viral oncogene homolog) membrane association35,63, an important mechanism of tumorigenesis. More recently, GPR31 was reported to underlie hepatic ischemia-reperfusion injury64.
In addition, DNA methylation levels at the SERPINB9 gene were inversely related to telomere length. SERPINB9 (Serpin B9) encodes a member of the serine protease inhibitor family, also known as serpins. SERPINB9 inhibits the activity of the pro-apoptotic effector molecule granzyme B65 and therefore protects cytotoxic T-lymphocytes from apoptosis66. It is also expressed in accessory immune cells, such as dendritic cells, where it plays a role in presenting antigens67. SERPINB9 could contribute to immune evasion in leukemia cells68 and to overcoming intracellular cytotoxicity in neuroectodermal tumors69. It has also been involved in autoimmune diseases70, such as celiac disease71. Interestingly, SERPINB9 expression is reduced in atherosclerotic lesions72, and the axis SERPINB9/granzyme B has been proposed to modulate inflammation and insulin resistance in coronary atherosclerosis68. A previous report found SERPINB9 to be differentially methylated in blood cells of patients with abdominal aortic aneurysms71. SERPINB9 involvement in inflammatory pathways makes it biologically plausible the reported link with telomere length since inflammation is one of the postulated mechanisms to underlie the effect of meditation on improving human health33,53.
Still, the association of DNA methylation levels on those particular genes and telomere length is interesting even though the underlying mechanisms are far to be unraveled. It may be that these particular genes display a function on the general biology of telomeres that is still not known. Further investigations on ablation or overexpression of these genes in in vitro or in vivo models and their effect on telomere length would be of help to elucidate this point. On the other hand, the relationship between DNA methylation levels and mRNA expression levels for these genes is still not clear. For example, a report showed an inverse correlation between methylation and expression for SERPINB973 while a direct correlation was found in other work74. In any case, as those genes were differentially methylated in long-term meditators, we could hypothesize that these particular genes may be a biological target of meditation. However, whether those genes are definitely involved in telomere biology can only be investigated by other type of experiments such as silencing or overexpressing them in cell or animal models. As for the mechanisms by which meditation changes DNA methylation at particular genes are still far to be understood.
Finally, telomere length inversely correlated with DNA methylation levels at a CpG island located in the subtelomeric region of the short arm of chromosome 4. This result is intriguing, as this locus is a gene desert, a region devoid of protein-coding genes. The differentially methylated CpG island is conserved across vertebrate species (Fig. 3). It seems to overlap an enhancer region in human embryonic stem cells (H1-hESCs) and is only 400 bp apart from an insulator region conserved across different cell lines. Further research will be needed to elucidate the role of this subtelomeric region on influencing telomere length maintenance.
However, this study is greatly exploratory and very limited in terms of not only statistical power but also regarding the possibility of establishing causal relationships. Judging by the effect sizes detected, significant relationships between age and telomere length might be observed in meditators when using larger samples. Nevertheless, we have observed that the effect size of the relationship between age and telomere length was drastically reduced in meditators when compared with non-meditator controls. In summary, this exploratory study will serve as a guide of future fully powered designs to clarify the true nature of all of these possible relationships.
We had previously observed that differential DNA methylation changes in long-term meditators involved subtelomeric regions. Here, we show that DNA methylation levels at distinct subtelomeric regions encompassing GPR31 and SERPINB9 genes are associated with telomere length only in the group of long-term meditators. However, we should be cautious about this result since it is above the threshold we used to correct for multiple-testing and therefore, it should be considered an exploratory study. In addition, age is no longer associated with telomere length in this group. The results of this exploratory study suggest that long-term meditation may be related to the age-related erosion of telomeres. Although the underlying mechanisms are not yet well understood, changes in DNA methylation arise as a factor that could contribute to this effect. Validation in an independent cohort would strengthen the results of the present study.
A group of long-term mindfulness meditators (MMs) (n = 17) was recruited from among members of the Spanish Association of Mindfulness and students enrolled in the Master of Mindfulness program at the University of Zaragoza. A comparison group of healthy controls (n = 17) was recruited from among healthy relatives and friends of the long-term MMs who had a similar lifestyle, and it was matched by gender, age (±2 years) and ethnic group. All the participants were Caucasian (European ancestry). Long-term MMs were required to have practiced meditation continuously for more than 10 years before the start of the study (including the previous 10 years) with a mean of at least 60 min/day of formal practice during the entire period. Information on participants´ meditation experience was also assessed, including the number of months that the participants had practiced meditation throughout their lifetime. The procedure and inclusion and exclusion criteria, along with socio-demographic, psychological, and health-related questionnaires, have been described elsewhere35.
Telomere length measurement
From each subject, blood was obtained by venous puncture from the antecubital vein in sodium heparin tubes and processed within 24 h of collection to isolate peripheral blood mononuclear cells (PBMCs) using a Ficoll-Hypaque gradient. PBMC samples were rinsed in phosphate buffer solution, counted and resuspended at 10 million cells per milliliter in a freezing medium processed and stored in liquid nitrogen until further use. Telomere length assessment was performed as previously described13.
In brief, aliquots were thawed and diluted to plate 3.5 × 104 cells/well by quintuple in 384-well plates. Cells were fixed with methanol/acetic acid (3/1, v/v), treated with pepsin to digest the cytoplasm and the nuclei were then processed for in situ hybridization with a fluorescent Peptide Nucleic Ncid (PNA) probe that recognizes telomere repeats (sequence: Alexa488-OO-CCCTAACCCTAACCCTAA, Panagene). After several washing steps, as described by the standard DAPI incubation procedures for DNA staining, the wells were filled with mounting medium, and the plate was stored overnight at 4 °C.
Quantitative image acquisition and analysis were performed using the Opera High-Content Screening System (Perkin Elmer) with Acapella software, version 1.8 (Perkin Elmer, Waltham, MA, USA). Images were captured using a ×40 0.95 NA water immersion objective. UV and 488-nm excitation wavelengths were used to detect the DAPI and A488 signals, respectively. The results of the intensity of each foci identified were exported from the Acapella software (Perkin Elmer). Telomere length distribution and median telomere length were calculated with software from Life Length (www.lifelength.com). Samples with coefficients of variation lesser than 10% were accepted for the study.
DNA methylation levels and differential methylation analysis
DNA was isolated from peripheral blood leukocytes by standardized methods75. DNA methylation data was generated using the Infinium HumanMethylation450 BeadChip array (Illumina, Inc., San Diego, CA, USA) at the Roswell Park Cancer Institute Genomics Shared Resource (Buffalo, NY, USA). 500 ng of genomic DNA from each sample was bisulfite treated and hybridized onto the BeadChip according to the manufacturer’s protocol. The percentage of methylation (β value) at each interrogated CpG site was calculated after quality control and normalization steps as described elsewhere35. In brief, image processing was carried out using the GenomeStudio Methylation Module (Illumina, Inc.). Background was corrected and adjustment was performed to avoid type I/II assay chemistry bias. To minimize technical variation and improve data quality we used the Dasen method76 as a normalization tool. Before performing differential methylation analysis, we removed probes overlapping common single nucleotide polymorphisms (SNPs) based on NCBI dbSNP Build 137 along with those probes classified as internal controls of the Illumina microarray. Additionally, probes located on the X and Y chromosomes were discarded along with probes that hybridized to multiple locations in the genome77,78. Probes that technically did not pass the Illumina quality threshold (1567 probes with beadcount <3 in >5% of samples and 535 probes having 1% of samples with a detection p-value > 0.05) were also removed. In the end, a total of 263 495 probes (representing CpG sites) were analyzed for differential methylation.
Differential methylation analysis was performed to identify differentially methylated regions (DMRs), defined as loci containing concordant and significant changes for neighboring CpGs (≥2 CpGs)79. We applied a Bioconductor package, DMRcate, that detect concordant and significant changes for neighboring CpGs by a kernel function to identify DMRs80. Methylation differences were prioritized by lowest p-values to ensure the most consistent DMRs between meditators and controls were included. These analyses identified sets of candidate loci with consistent differences in methylation in MM versus controls. An extended version of this section is included in Supplemental File 1.
Mindfulness and psychological health-related variables
The Mindful Attention Awareness Scale (MAAS) is a 15-item scale used to measure awareness as a dispositional characteristic of paying attention to what is occurring in the present moment81. We used the Spanish version of the MAAS, which has displayed the appropriate psychometrics, with an internal consistency of α = 0.8982.
The Five Facet Mindfulness Questionnaire (FFMQ) is a 39-item questionnaire that evaluates five components of mindfulness: observing, describing, acting with awareness, non-judging of inner experience, and non-reactivity to inner experience83. The Spanish validated version of the FFMQ84, which has demonstrated adequate consistency values (α ≥ 0.80 in all the facets), was used.
The Hospital Anxiety and Depression Scale (HADS) is a 14-item questionnaire used to measure anxiety and depression85. The validity and reliability of the Spanish version of the HADS has shown to be adequate86, with internal consistency values in the corresponding subscales of anxiety and depression of α = 0.84 and α = 0.85, respectively.
The Connor-Davidson Resilience Scale (CD-RISC) is a 10-item scale used to measure resilience, defined as the psychological ability to successfully cope with adversity87. We used the Spanish validated version of the CD-RISC88, which has shown good psychometric characteristics (α = 0.85).
The Subjective Happiness Scale (SHS) is a 4-item scale used to measure subjective global happiness89. The Spanish version of the SHS90 was used, which has demonstrated good validity and also appropriate reliability values (α = 0.72).
The Self-Compassion Scale (SCS) is a 26-item scale that measures three facets of self-compassion (including negative aspects that are reverse coded): self-kindness, common humanity, and mindfulness (defined as the specific ability to keep emotions in balance when something is upsetting)91. We used the Spanish version of the SCS, with alpha values ranging from α = 0.72 to α = 0.7992.
The Satisfaction With Life Scale (SWLS) is a 5-item scale through which participants rate their overall satisfaction with their lives93. This questionnaire has been validated in Spanish94 with good validity and reliability parameters (α = 0.86).
The Experiential Avoidance Questionnaire (AAQ-II) is a 7-item scale that assesses one’s unwillingness to experience emotions and thoughts, and the inability to be in the present and engage in valued behavior when unwanted emotions/thoughts are present95. The Spanish translated and validated version of the AAQ-II96, which has presented adequate psychometrics (α = 0.93), was used.
mRNA expression analysis by RT-qPCR
Total RNA was isolated from blood samples using RNeasy Lipid Tissue Mini kit (QIAGEN, Redwood City, CA, USA), following manufacturer’s instructions. Genomic DNA was removed with recombinant DNase (TURBO DNA-free™ Kit, Ambion, Inc., Austin, TX, USA). RNA integrity was checked by 1.25% agarose gel electrophoresis under denaturing conditions. Concentration and purity of RNA were both evaluated with NanoDrop spectrophotometer. Only RNA samples showing a minimum quality index (260 nm/280 nm absorbance ratios between 1.8 and 2.2 and 260 nm/230 nm absorbance ratios higher than 1.8) were included in the study. Complementary DNA (cDNA) was reverse transcribed from 1500 ng total RNA with SuperScript® III First-Strand Synthesis Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA) after priming with oligo-d (T) and random primers. RT-qPCR reactions were performed in triplicate with Power SYBR Green PCR Master Mix (Invitrogen, Carlsbad, CA, USA) in a QuantStudio 12K Flex Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). Sequences of primer pair were designed using Real Time PCR tool (IDT, Coralville, IA, USA). Relative expression level of genes mRNA in a particular sample was calculated as previously described  and the geometric mean of ACTB and TBP genes was used as the reference gene to normalize expression values.
Statistical data analysis
The socio-demographic data and psychological health-related variables were described using either means and standard deviations (SDs), or frequencies and percentages, depending on their nature. Hypergeometric test (cumulative) was used to test for DMRs enrichment in subtelomeric regions. The comparisons between groups (MMs and healthy controls) in these variables were performed using the corresponding Student’s t and chi-squared tests. We also used the Student’s t test to compare the telomere length between groups, and we incorporated an ANCOVA to the same comparison to adjust for age. The effect size (ES) of differences was estimated by means of Cohen’s d. Values from 0.10 to 0.30 are considered to be small; from 0.31 to 0.50 intermediate; and 0.51 and higher, strong97. The level of relationships between age and telomere length, as well as between telomere length and DNA methylation levels, was assessed by means of Pearson’s r correlations separately for each group. We also calculated multiple regression models to control for age the relationships between telomere length and DNA methylation. Standardized regression coefficients (beta) were used to assess the individual contribution of DNA methylation and age in explaining telomere length, and the Wald test was used to evaluate the statistical significance of influences. Determination coefficients (R2) were used to evaluate the raw explanatory power of DNA methylation on the telomere length, while adjusted multiple determination coefficients (R2y.12) were used to observe the grouped explanatory power of age and DNA methylation. Their significance was assessed using analysis of variance. All of the tests used were bilateral, and the significance level was α < 0.05. As an alternative to multiple testing correction, we draw at random 1000 sub-samples of 14 not-DMRs and compute the proportion of such random sets that exhibit a lower number of correlations with telomere length (in the meditators group) than when considering the 14 meditation-related DMRs. This analysis was built with replacement and by using a set of 32830 non DMRs. SPSS-19 (IBM, Inc., USA) statistical software package was used. There were corrections for multiple comparisons but this study is of a highly exploratory nature98.
Ethics approval and consent to participate
The study was approved by the Regional Ethics Committee of Aragon (number PI13/0056) and was conducted in accordance with the ethical standards of the 1964 Convention norms of Helsinki and later modifications. All of the participants provided their written informed consent before participating in the study.
Demarzo, M. M. et al. Mindfulness-based stress reduction (MBSR) in perceived stress and quality of life: an open, uncontrolled study in a Brazilian healthy sample. Explore 10, 118–120, https://doi.org/10.1016/j.explore.2013.12.005 (2014).
Sharma, M. & Rush, S. E. Mindfulness-based stress reduction as a stress management intervention for healthy individuals: a systematic review. Journal of evidence-based complementary & alternative medicine 19, 271–286, https://doi.org/10.1177/2156587214543143 (2014).
Grossman, P., Niemann, L., Schmidt, S. & Walach, H. Mindfulness-based stress reduction and health benefits. A meta-analysis. Journal of psychosomatic research 57, 35–43, https://doi.org/10.1016/S0022-3999(03)00573-7 (2004).
Keng, S. L., Smoski, M. J. & Robins, C. J. Effects of mindfulness on psychological health: a review of empirical studies. Clinical psychology review 31, 1041–1056, https://doi.org/10.1016/j.cpr.2011.04.006 (2011).
Rouleau, C. R., Garland, S. N. & Carlson, L. E. The impact of mindfulness-based interventions on symptom burden, positive psychological outcomes, and biomarkers in cancer patients. Cancer management and research 7, 121–131, https://doi.org/10.2147/CMAR.S64165 (2015).
Moynihan, J. A. et al. Mindfulness-based stress reduction for older adults: effects on executive function, frontal alpha asymmetry and immune function. Neuropsychobiology 68, 34–43, https://doi.org/10.1159/000350949 (2013).
Zhang, M. F. et al. Effectiveness of Mindfulness-based Therapy for Reducing Anxiety and Depression in Patients With Cancer: A Meta-analysis. Medicine 94, e0897–0890, https://doi.org/10.1097/MD.0000000000000897 (2015).
Serpa, J. G., Taylor, S. L. & Tillisch, K. Mindfulness-based stress reduction (MBSR) reduces anxiety, depression, and suicidal ideation in veterans. Medical care 52, S19–24, https://doi.org/10.1097/MLR.0000000000000202 (2014).
Olivo, E. L. Protection throughout the life span: the psychoneuroimmunologic impact of Indo-Tibetan meditative and yogic practices. Annals of the New York Academy of Sciences 1172, 163–171, https://doi.org/10.1111/j.1749-6632.2009.04415.x (2009).
Bushell, W. C. Longevity: potential life span and health span enhancement through practice of the basic yoga meditation regimen. Annals of the New York Academy of Sciences 1172, 20–27, https://doi.org/10.1111/j.1749-6632.2009.04538.x (2009).
Jacobs, T. L. et al. Intensive meditation training, immune cell telomerase activity, and psychological mediators. Psychoneuroendocrinology 36, 664–681, https://doi.org/10.1016/j.psyneuen.2010.09.010 (2011).
Conklin, Q. A. et al. Insight meditation and telomere biology: The effects of intensive retreat and the moderating role of personality. Brain, behavior, and immunity https://doi.org/10.1016/j.bbi.2018.03.003 (2018).
Alda, M. et al. Zen meditation, Length of Telomeres, and the Role of Experiential Avoidance and Compassion. Mindfulness 7, 651–659, https://doi.org/10.1007/s12671-016-0500-5 (2016).
Krishna, B. H., Keerthi, G. S., Kumar, C. K. & Reddy, N. M. Association of leukocyte telomere length with oxidative stress in yoga practitioners. Journal of clinical and diagnostic research: JCDR 9, CC01–03, https://doi.org/10.7860/JCDR/2015/13076.5729 (2015).
Schutte, N. S. & Malouff, J. M. A meta-analytic review of the effects of mindfulness meditation on telomerase activity. Psychoneuroendocrinology 42, 45–48, https://doi.org/10.1016/j.psyneuen.2013.12.017 (2014).
Thimmapuram, J. et al. Effect of heartfulness meditation on burnout, emotional wellness, and telomere length in health care professionals. Journal of community hospital internal medicine perspectives 7, 21–27, https://doi.org/10.1080/20009666.2016.1270806 (2017).
Martinez, P. & Blasco, M. A. Telomeric and extra-telomeric roles for telomerase and the telomere-binding proteins. Nature reviews. Cancer 11, 161–176, https://doi.org/10.1038/nrc3025 (2011).
de Lange, T. Protection of mammalian telomeres. Oncogene 21, 532–540, https://doi.org/10.1038/sj.onc.1205080 (2002).
Blackburn, E. H. Structure and function of telomeres. Nature 350, 569–573, https://doi.org/10.1038/350569a0 (1991).
Bar, C. & Blasco, M. A. Telomeres and telomerase as therapeutic targets to prevent and treat age-related diseases. F1000Research 5, https://doi.org/10.12688/f1000research.7020.1 (2016).
Greider, C. W. & Blackburn, E. H. Identification of a specific telomere terminal transferase activity in Tetrahymena extracts. Cell 43, 405–413 (1985).
Harley, C. B., Futcher, A. B. & Greider, C. W. Telomeres shorten during ageing of human fibroblasts. Nature 345, 458–460, https://doi.org/10.1038/345458a0 (1990).
Hastie, N. D. et al. Telomere reduction in human colorectal carcinoma and with ageing. Nature 346, 866–868, https://doi.org/10.1038/346866a0 (1990).
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 256, 45–48 (1991).
D’Mello, M. J. et al. Association between shortened leukocyte telomere length and cardiometabolic outcomes: systematic review and meta-analysis. Circulation. Cardiovascular genetics 8, 82–90, https://doi.org/10.1161/CIRCGENETICS.113.000485 (2015).
Haycock, P. C. et al. Leucocyte telomere length and risk of cardiovascular disease: systematic review and meta-analysis. BMJ (Clinical research ed.) 349, g4227, https://doi.org/10.1136/bmj.g4227 (2014).
Hagg, S. et al. Short telomere length is associated with impaired cognitive performance in European ancestry cohorts. Translational psychiatry 7, e1100, https://doi.org/10.1038/tp.2017.73 (2017).
Blasco, M. A. Telomere length, stem cells and aging. Nature chemical biology 3, 640–649, https://doi.org/10.1038/nchembio.2007.38 (2007).
Wright, W. E. & Shay, J. W. Telomere positional effects and the regulation of cellular senescence. Trends Genet 8, 193–197 (1992).
Blasco, M. A. Telomeres and human disease: ageing, cancer and beyond. Nature reviews. Genetics 6, 611–622, https://doi.org/10.1038/nrg1656 (2005).
Mather, K. A., Jorm, A. F., Parslow, R. A. & Christensen, H. Is telomere length a biomarker of aging? A review. The journals of gerontology. Series A, Biological sciences and medical sciences 66, 202–213, https://doi.org/10.1093/gerona/glq180 (2011).
Muezzinler, A., Zaineddin, A. K. & Brenner, H. A systematic review of leukocyte telomere length and age in adults. Ageing research reviews 12, 509–519, https://doi.org/10.1016/j.arr.2013.01.003 (2013).
Rizvi, S., Raza, S. T. & Mahdi, F. Telomere length variations in aging and age-related diseases. Current aging science 7, 161–167 (2014).
Sanders, J. L. & Newman, A. B. Telomere length in epidemiology: a biomarker of aging, age-related disease, both, or neither? Epidemiologic reviews 35, 112–131, https://doi.org/10.1093/epirev/mxs008 (2013).
Javier García-Campayo et al. Epigenetic response to mindfulness in peripheral blood leukocytes involves genes linked to common human diseases. Mindfulness, https://doi.org/10.1007/s12671-017-0851-6 (2017).
Buxton, J. L. et al. Human leukocyte telomere length is associated with DNA methylation levels in multiple subtelomeric and imprinted loci. Scientific reports 4, 4954, https://doi.org/10.1038/srep04954 (2014).
Yang, J. et al. Tet Enzymes Regulate Telomere Maintenance and Chromosomal Stability of Mouse ESCs. Cell reports 15, 1809–1821, https://doi.org/10.1016/j.celrep.2016.04.058 (2016).
Gonzalo, S. et al. DNA methyltransferases control telomere length and telomere recombination in mammalian cells. Nature cell biology 8, 416–424, https://doi.org/10.1038/ncb1386 (2006).
Blasco, M. A. The epigenetic regulation of mammalian telomeres. Nature reviews. Genetics 8, 299–309, https://doi.org/10.1038/nrg2047 (2007).
Benetti, R., Garcia-Cao, M. & Blasco, M. A. Telomere length regulates the epigenetic status of mammalian telomeres and subtelomeres. Nature genetics 39, 243–250, https://doi.org/10.1038/ng1952 (2007).
Yehezkel, S., Segev, Y., Viegas-Pequignot, E., Skorecki, K. & Selig, S. Hypomethylation of subtelomeric regions in ICF syndrome is associated with abnormally short telomeres and enhanced transcription from telomeric regions. Human molecular genetics 17, 2776–2789, https://doi.org/10.1093/hmg/ddn177 (2008).
Toubiana, S. et al. Subtelomeric methylation distinguishes between subtypes of Immunodeficiency, Centromeric instability and Facial anomalies syndrome. Human molecular genetics 27, 3568–3581, https://doi.org/10.1093/hmg/ddy265 (2018).
Choudhury, S. R., Cui, Y., Milton, J. R., Li, J. & Irudayaraj, J. Selective increase in subtelomeric DNA methylation: an epigenetic biomarker for malignant glioma. Clinical epigenetics 7, 107, https://doi.org/10.1186/s13148-015-0140-y (2015).
Oh, B. K., Um, T. H., Choi, G. H. & Park, Y. N. Frequent changes in subtelomeric DNA methylation patterns and its relevance to telomere regulation during human hepatocarcinogenesis. International journal of cancer 128, 857–868, https://doi.org/10.1002/ijc.25398 (2011).
Martinez, P. & Blasco, M. A. Telomere-driven diseases and telomere-targeting therapies. J Cell Biol 216, 875–887, https://doi.org/10.1083/jcb.201610111 (2017).
Egusquiaguirre, S. P., Pedraz, J. L., Hernandez, R. M. & Igartua, M. Emerging therapeutic approaches based on nanotechnology for the treatment of diseases associated with telomere dysfunction. Mini reviews in medicinal chemistry 15, 490–502 (2015).
van Ockenburg, S. L. et al. Stressful life events and leukocyte telomere attrition in adulthood: a prospective population-based cohort study. Psychological medicine 45, 2975–2984, https://doi.org/10.1017/S0033291715000914 (2015).
Verhoeven, J. E., van Oppen, P., Puterman, E., Elzinga, B. & Penninx, B. W. The Association of Early and Recent Psychosocial Life Stress With Leukocyte Telomere Length. Psychosomatic medicine 77, 882–891, https://doi.org/10.1097/PSY.0000000000000226 (2015).
Shalev, I. et al. Stress and telomere biology: a lifespan perspective. Psychoneuroendocrinology 38, 1835–1842, https://doi.org/10.1016/j.psyneuen.2013.03.010 (2013).
Epel, E. S. et al. Accelerated telomere shortening in response to life stress. Proc Natl Acad Sci USA 101, 17312–17315, https://doi.org/10.1073/pnas.0407162101 (2004).
Denham, J., O’Brien, B. J. & Charchar, F. J. Telomere Length Maintenance and Cardio-Metabolic Disease Prevention Through Exercise Training. Sports medicine 46, 1213–1237, https://doi.org/10.1007/s40279-016-0482-4 (2016).
Ludlow, A. T., Ludlow, L. W. & Roth, S. M. Do telomeres adapt to physiological stress? Exploring the effect of exercise on telomere length and telomere-related proteins. BioMed research international 2013, 601368, https://doi.org/10.1155/2013/601368 (2013).
Arsenis, N. C., You, T., Ogawa, E. F., Tinsley, G. M. & Zuo, L. Physical activity and telomere length: Impact of aging and potential mechanisms of action. Oncotarget 8, 45008–45019, https://doi.org/10.18632/oncotarget.16726 (2017).
Carlson, L. E. et al. Mindfulness-based cancer recovery and supportive-expressive therapy maintain telomere length relative to controls in distressed breast cancer survivors. Cancer 121, 476–484, https://doi.org/10.1002/cncr.29063 (2015).
Rathore, M. & Abraham, J. Implication of Asana, Pranayama and Meditation on Telomere Stability. International journal of yoga 11, 186–193, https://doi.org/10.4103/ijoy.IJOY_51_17 (2018).
Valdes, A. M. et al. Obesity, cigarette smoking, and telomere length in women. Lancet 366, 662–664, https://doi.org/10.1016/S0140-6736(05)66630-5 (2005).
Babizhayev, M. A., Savel’yeva, E. L., Moskvina, S. N. & Yegorov, Y. E. Telomere length is a biomarker of cumulative oxidative stress, biologic age, and an independent predictor of survival and therapeutic treatment requirement associated with smoking behavior. American journal of therapeutics 18, e209–226, https://doi.org/10.1097/MJT.0b013e3181cf8ebb (2011).
Michaels, R. R., Huber, M. J. & McCann, D. S. Evaluation of transcendental meditation as a method of reducing stress. Science 192, 1242–1244 (1976).
Wenneberg, S. R. et al. A controlled study of the effects of the Transcendental Meditation program on cardiovascular reactivity and ambulatory blood pressure. Int J Neurosci 89, 15–28 (1997).
Bushell, W. C. & Theise, N. D. Toward a unified field of study: longevity, regeneration, and protection of health through meditation and related practices. Ann N Y Acad Sci 1172, 5–19, https://doi.org/10.1111/j.1749-6632.2009.04959.x (2009).
Alexander, C. N., Langer, E. J., Newman, R. I., Chandler, H. M. & Davies, J. L. Transcendental meditation, mindfulness, and longevity: an experimental study with the elderly. J Pers Soc Psychol 57, 950–964 (1989).
Guo, Y. et al. Identification of the orphan G protein-coupled receptor GPR31 as a receptor for 12-(S)-hydroxyeicosatetraenoic acid. J Biol Chem 286, 33832–33840, https://doi.org/10.1074/jbc.M110.216564 (2011).
Fehrenbacher, N. & Philips, M. R. Targeting RAS - will GPR31 deliver us a new path forward? Molecular & cellular oncology 4, e1359228, https://doi.org/10.1080/23723556.2017.1359228 (2017).
Zhang, X. J. et al. An ALOX12-12-HETE-GPR31 signaling axis is a key mediator of hepatic ischemia-reperfusion injury. Nature medicine 24, 73–83, https://doi.org/10.1038/nm.4451 (2018).
Sun, J. et al. A cytosolic granzyme B inhibitor related to the viral apoptotic regulator cytokine response modifier A is present in cytotoxic lymphocytes. J Biol Chem 271, 27802–27809 (1996).
Bird, C. H. et al. Selective regulation of apoptosis: the cytotoxic lymphocyte serpin proteinase inhibitor 9 protects against granzyme B-mediated apoptosis without perturbing the Fas cell death pathway. Molecular and cellular biology 18, 6387–6398 (1998).
Mangan, M. S. et al. Serpinb9 is a marker of antigen cross-presenting dendritic cells. Molecular immunology 82, 50–56, https://doi.org/10.1016/j.molimm.2016.12.011 (2017).
Fritsch, K., Finke, J. & Grullich, C. Suppression of granzyme B activity and caspase-3 activation in leukaemia cells constitutively expressing the protease inhibitor 9. Annals of hematology 92, 1603–1609, https://doi.org/10.1007/s00277-013-1846-6 (2013).
Vermeulen, J. F. et al. Pediatric Primitive Neuroectodermal Tumors of the Central Nervous System Differentially Express Granzyme Inhibitors. PLoS One 11, e0151465, https://doi.org/10.1371/journal.pone.0151465 (2016).
van der Burgh, R. et al. Reduced serpinB9-mediated caspase-1 inhibition can contribute to autoinflammatory disease. Oncotarget 7, 19265–19271, https://doi.org/10.18632/oncotarget.8086 (2016).
Pohjanen, V. M. et al. Decreased expression of protease inhibitor 9, a granzyme B inhibitor, in celiac disease: a potential mechanism in enterocyte destruction and villous atrophy. International journal of immunopathology and pharmacology 26, 897–905, https://doi.org/10.1177/039463201302600408 (2013).
Hendel, A. et al. Proteinase inhibitor 9 is reduced in human atherosclerotic lesion development. Cardiovascular pathology: the official journal of the Society for Cardiovascular Pathology 21, 28–38, https://doi.org/10.1016/j.carpath.2010.12.002 (2012).
Li, Z., Zhuang, X., Zeng, J. & Tzeng, C. M. Integrated Analysis of DNA Methylation and mRNA Expression Profiles to Identify Key Genes in Severe Oligozoospermia. Frontiers in physiology 8, 261, https://doi.org/10.3389/fphys.2017.00261 (2017).
Toghill, B. J., Saratzis, A., Freeman, P. J., Sylvius, N. & Bown, M. J. SMYD2 promoter DNA methylation is associated with abdominal aortic aneurysm (AAA) and SMYD2 expression in vascular smooth muscle cells. Clinical epigenetics 10, 29, https://doi.org/10.1186/s13148-018-0460-9 (2018).
Miller, S. A., Dykes, D. D. & Polesky, H. F. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 16, 1215 (1988).
Pidsley, R. et al. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics 14, 293.
Chen, Y. A. et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 8, 203–209, https://doi.org/10.4161/epi.23470 (2013).
Price, M. E. et al. Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array. Epigenetics & chromatin 6, 4, https://doi.org/10.1186/1756-8935-6-4 (2013).
Jaffe, A. E. et al. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. International journal of epidemiology 41, 200–209, https://doi.org/10.1093/ije/dyr238 (2012).
Peters, T. J. et al. De novo identification of differentially methylated regions in the human genome. Epigenetics Chromatin 8, 6, https://doi.org/10.1186/1756-8935-8-6 (2015).
Brown, K. W. & Ryan, R. M. The benefits of being present: mindfulness and its role in psychological well-being. Journal of personality and social psychology 84, 822–848 (2003).
Soler, J. et al. Psychometric proprieties of Spanish version of Mindful Attention Awareness Scale (MAAS). Actas espanolas de psiquiatria 40, 19–26 (2012).
Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J. & Toney, L. Using self-report assessment methods to explore facets of mindfulness. Assessment 13, 27–45, https://doi.org/10.1177/1073191105283504 (2006).
Cebolla, A. et al. Psychometric properties of the Spanish validation of the Five Facets of Mindfulness Questionnaire (FFMQ). The European Journal of Psychiatry 26, 118–126 (2012).
Zigmond, A. S. & Snaith, R. P. The hospital anxiety and depression scale. Acta psychiatrica Scandinavica 67, 361–370 (1983).
Herrero, M. J. et al. A validation study of the hospital anxiety and depression scale (HADS) in a Spanish population. General hospital psychiatry 25, 277–283 (2003).
Campbell-Sills, L. & Stein, M. B. Psychometric analysis and refinement of the Connor-davidson Resilience Scale (CD-RISC): Validation of a 10-item measure of resilience. Journal of traumatic stress 20, 1019–1028, https://doi.org/10.1002/jts.20271 (2007).
Notario-Pacheco, B. et al. Reliability and validity of the Spanish version of the 10-item Connor-Davidson Resilience Scale (10-item CD-RISC) in young adults. Health and quality of life outcomes 9, 63, https://doi.org/10.1186/1477-7525-9-63 (2011).
Lyubomirsky, S. L. & Lepper, H. S. A Measure of Subjective Happiness: Preliminary Reliability and Construct Validation. Social Indicators Research. 46, 137, https://doi.org/10.1023/A:1006824100041 (1999).
Extremera, N. & Fernández-Berrocal, P. The Subjective Happiness Scale: Translation and Preliminary Psychometric Evaluation of a Spanish Version. Soc Indic Res, https://doi.org/10.1007/s11205-013-0497-2 (2014).
Neff, K. D. Development and validation of a scale to measure self-compassion. Self and Identity, 223–250.
Garcia-Campayo, J. et al. Validation of the Spanish versions of the long (26 items) and short (12 items) forms of the Self-Compassion Scale (SCS). Health and quality of life outcomes 12, 4, https://doi.org/10.1186/1477-7525-12-4 (2014).
Diener, E., Emmons, R. A., Larsen, R. J. & Griffin, S. The Satisfaction With Life Scale. Journal of personality assessment 49, 71–75, https://doi.org/10.1207/s15327752jpa4901_13 (1985).
Vazquez, C., Duque, A. & Hervas, G. Satisfaction with life scale in a representative sample of Spanish adults: validation and normative data. The Spanish journal of psychology 16, E82, https://doi.org/10.1017/sjp.2013.82 (2013).
Bond, F. W. et al. Preliminary psychometric properties of the Acceptance and Action Questionnaire-II: a revised measure of psychological inflexibility and experiential avoidance. Behavior therapy 42, 676–688, https://doi.org/10.1016/j.beth.2011.03.007 (2011).
Ruiz, F. J., Langer Herrera, A. I., Luciano, C., Cangas, A. J. & Beltran, I. Measuring experiential avoidance and psychological inflexibility: The Spanish version of the Acceptance and Action Questionnaire - II. Psicothema 25, 123–129, https://doi.org/10.7334/psicothema2011.239 (2013).
Cohen, J. (Hillsdale, N. J.: L. Erlbaum Associates, 1988).
Feise, R. J. Do multiple outcome measures require p-value adjustment? BMC medical research methodology 2, 8 (2002).
The project has received funding from the Network for Prevention and Health Promotion in primary Care (RD12/0005 and RD16/0007/0005) grant and a FIS grant (PI16/00962) from the Instituto de Salud Carlos III of the Spanish Ministry of Economy and Competitiveness, co-financed with European Union ERDF funds. The funding source had no influence on the design of the study, data collection and analysis, or the writing of the manuscript. MM has received a grant “intensificación” from Fundación LaCaixa.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Mendioroz, M., Puebla-Guedea, M., Montero-Marín, J. et al. Telomere length correlates with subtelomeric DNA methylation in long-term mindfulness practitioners. Sci Rep 10, 4564 (2020). https://doi.org/10.1038/s41598-020-61241-6
Progress in Pediatric Cardiology (2020)
Journal of Cardiovascular Development and Disease (2020)