Effects of long-term meditation on the expression of genes related to inflammation and their methylation status: A case-control study

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This study explored the hypothesis that long-term meditation practice downregulates the expression of genes associated with stress-induced inflammation. The expression of selected inflammation-related genes and their promoter methylation status were compared between long-term meditators and controls. Methods: Thirty experienced meditators and 30 age- and gender-matched non mediators participated in this case-control study. RNA and DNA were extracted from blood samples. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) with GAPDH normalization was used to measure the expression of eight inflammation-related genes ( IFN-γ, IL-6, CCL-2, CCR-7, TNF-α, NF-κB, CXCL8, and COX-2) . Additionally, bisulfite-specific PCR and Sanger sequencing were performed to assess the methylation status of five of these genes (IL-6, TNF-α, IFN-γ, COX-2, and CXCL8 ) in their promoter regions. Results : The mean age of participants was 43.83 ± 9.92 years, and 63.34% in each group were male. Compared to controls, meditators showed significantly lower relative gene expression for IFN -γ (Fold change (FC)=7,p=0.045), IL -6 (FC=3.6,p=0.045), TNF -α (FC=2.73,p=0.038), NF - ƘB (FC=3.2,p=0.045), CXCL8 (FC=3.3,p=0.047), and COX -2 (FC=9.5,p=0.013). Furthermore, meditators exhibited significantly higher promoter region methylation in IL-6 (p < 0.001) and CXCL8 (p = 0.001). The methylation level at specific CpG sites showed that four out of 16 sites in IL -6 and five out of twelve sites in CXCL -8 gene had significantly higher methylation in meditators. Although no significant difference in the overall methylation level in the promoter regions of TNF -α and IFN -γ genes were detected, two out of 12 sites and one out of 27 sites in the TNF -α and IFN -γ genes, respectively, showed significantly higher methylation in meditators. Conclusion: These findings suggest that long-term meditation practice may contribute to reduced inflammation by downregulating the expression of specific inflammatory pathway genes and increasing their promoter methylation. Further research is needed to explore these potential mechanisms and their long-term health implications. Figures Figure 1 Figure 2 Background Meditation is a technique that has been practiced for thousands of years to promote physical and mental well-being. It involves focusing the mind on a specific object or activity to achieve a state of deep relaxation and heightened awareness ( 1 ). The practice of meditation can be traced back to ancient Eastern traditions, such as Hinduism and Buddhism, where it was used as a means of spiritual development and enlightenment ( 2 ). There are many different forms of meditation, each with its own unique techniques including mantra meditation, loving-kindness meditation, walking meditation, Zen meditation etc ( 3 ). While these techniques may differ in their specific methodologies and philosophies, their ultimate goal remains consistent to guide individuals towards a state of profound inner awakening and liberation ( 4 ). However, the knowledge of the molecular mechanisms by which they affect a wide array of biological processes, from genes to the immune system, is still unclear. Gene expression is a complex process that allows cells to synthesize the proteins and RNA molecules necessary for their function by converting genetic information stored in DNA ( 5 ). Chronic inflammation has been implicated in the development and progression of numerous diseases, including cardiovascular disease, neurodegenerative disorders, and certain cancers ( 6 ). Inflammation primarily occurs through genetic pathways, activating key transcription factors like NF-κB and AP-1, along with the Toll-like receptor pathway, thereby orchestrating the expression of pro-inflammatory genes such as interleukins (IL) and tumor necrosis factor-alpha (TNF-α). The rate of gene expression is regulated by a complex interplay of various factors, including transcription factors, epigenetic modifications, and signalling pathways ( 7 ). A microarray containing 12,000 genes was employed to assess gene expression patterns by Quan-Zhen Li and colleagues with six long-term practitioners of Falun Gong Qigong and six healthy individuals serving as controls. The findings revealed that Qigong practitioners exhibited 132 downregulated genes and 118 upregulated genes compared to the control group ( 8 ). Another case control study investigated the gene expression patterns related to oxidative stress, specifically focusing on genes such as COX2 and showed that COX2 exhibited notably lower expression levels in the Sudarshan Kriya practitioners compared to the control group ( 9 ). In a mindfulness-based stress reduction (MBSR) interventional study conducted by Creswell et al. in 2013, reduced pro-inflammatory gene expression patterns were observed. However, despite the influence on gene expression patterns, the levels of IL -6 gene did not show substantial alterations due to the MBSR intervention ( 10 ). A recent intervention found that the practice of Kirtan Kriya Meditation led to a decrease in the expression of pro-inflammatory genes related to the NF-κB pathway ( 11 ). Another study, carried out on the impact of Tai Chi on inflammation, found a significant reduction in the expression of TNF-α genes and a marginal reduction in the expression of IL-6 genes ( 12 ). Kaliman et al., 2014 observed non-significant differences in gene expression, including CCR7, CXCL8, TNF-α , and IL -6, in experienced meditators after conducting eight hours of mindfulness meditation ( 13 ). Environmental signals interact with the epigenetic machinery through both extracellular and intracellular routes, influencing a broad range of biological activities, including behavior and the stress response ( 14 ). DNA methylation is a type of epigenetic modification that involves the addition of a methyl group (-CH3) to the cytosine residue of a DNA molecule ( 15 ). Chaix et al. 2019, investigated the impact of intensive meditation practice on the methylome of peripheral blood mononuclear cells and found an enrichment in genes primarily associated with immune cell metabolism ( 16 ). Another study obtained positive effects of meditation on the methylation levels of certain genes related to inflammation such as IL -6 and TNF -α ( 17 ). The existing body of research predominantly focuses on investigating the impact of meditation either on the expression of genes or on the DNA methylation of inflammation-related genes in isolation. Consequently, a comprehensive understanding of the underlying molecular mechanisms remains elusive. Moreover, the majority of these studies primarily rely on short-term interventions, limiting the scope for observing significant outcomes. To address this gap, our study intended to explore the long-term effects of meditation, seeking a more holistic comprehension of its influence on gene expression and DNA methylation, thereby contributing to a more nuanced understanding of the molecular pathways involved. Therefore, the aim of this study was to compare the expression of selected genes related to inflammation such as IL-6, TNF- α, IFN-Ɣ, CXCL-8, COX-2, CCL-2, CCR-7 and NF-ƙB and the methylation status in the promoter regions of these genes between long-term meditators and controls. Methods Study design and participants This case-control study involved 30 experienced, skilled meditators who were selected from the community practising at several meditation centers in Sri Lanka. They were matched for age (± 2 years), gender, and educational level, with 30 non-meditator controls. A total of 60 participants, equally divided between meditators and controls (30 in each group), were chosen to ensure 80% statistical power and an alpha error of 0.05, with the goal of detecting an effect size of 0.8. This decision was informed by reported fold change (FC) levels from prior studies ( 18 , 19 ). The process of recruiting participants has been previously documented ( 20 ). In summary, participants aged 18 to 65 years were included in the study. Meditators were defined as individuals who consistently practiced meditation for over 6 hours per week for at least three years. The study employed purposive sampling to choose non-meditators (controls) from the same community. The inclusion criteria required that the controls had either never meditated or had only sometimes (less than once per three months) practiced meditation or other mind-body intervention methods. Exclusion criteria included smokers, those with a history of sickness or chronic medication use, and women who were pregnant or breast-feeding. The study obtained ethics approval from the Ethics Review Committee, Faculty of Medicine, University of Colombo (EC-19-067) and was carried out in accordance with the Declaration of Helsinki. The period of recruitment was from August 2020 to December 2021. Written, informed consent was obtained from each participant. Procedures The procedures for analysing telomere length-related gene expression and DNA methylation data, previously published ( 21 ), share the same laboratory protocols as described here. Despite this article focusing on inflammation, the gene expression and DNA methylation analysis maintain consistent laboratory procedures. The following briefly describes the procedures. Initially, potential participants were contacted at meditation centres located in various parts of the island. The study recruited long-term meditators who had attained pre-determined skill levels, as assessed by a questionnaire-based scoring system ( 22 ). Participants from both groups provided their written consent upon their initial visit and proceeded to submit their blood samples. Measures and covariates The sociodemographic data, which included age, gender, educational attainment, marital status, sleeping and working hours, and lifestyle factors including alcohol intake, food preferences, and amount of time spent exercising (in hours), was gathered via an interviewer-administered questionnaire. Standard scales were used to measure the height and weight, and the body mass index (BMI) was computed. Blood collection 5 ml of blood from each participant was collected to Ethylenediamine Tetraacetic Acid (EDTA) tubes, and immediately centrifuged at 1400 rpm for 10 minutes at 4°C. After centrifugation, the plasma and the whole blood were divided into 1.5 ml microcentrifuge tubes that had already been labelled. The samples were kept at -80°C until the assay, and they were defrosted only immediately before the analysis. Gene expression assay The SV Total RNA Isolation System (Promega, USA) was used to extract RNA from whole blood in accordance with the manufacturer's instructions. To create cDNA, 1 µg of RNA from each sample was reverse transcribed using the GoScriptTM Reverse Transcription System (Promega, USA). 50ng of the resultant cDNAs were subjected to real-time qPCR using the primers for the genes described previously ( 23 – 25 ), utilizing Quantitech® SYBR® Green PCR master mix. Table 1 provides specifics about primer sequences for the selected genes. The RT-PCR conditions were based on published protocols ( 26 ) and were further optimised. In summary, 10 µl of 2× Quantitech SYBR Green RT-PCR master mix, 2 µl primers, 50 ng of sample cDNA, and nuclease-free water were added to RT-PCR procedures to bring the reaction volume to 20 µl. The thermal cycling profile was as follows: An initial denaturation at 95°C for 10 minutes (1 cycle) was followed by denaturation at 95°C for 20 seconds, gene-specific annealing temperatures as detailed in Table 1 for 20 seconds, and extension at 72°C for 45 seconds, repeated for 45 cycles. The process concluded with a 1-minute hold at 60°C. The target gene cDNA level was measured using relative quantification in relation to the level of the GAPDH reference gene cDNA. The relative gene expression level was determined using the 2-ΔΔCt technique ( 27 ). Table 1 Primer Sequences and Annealing Temperatures for Gene Expression Assay Gene Forward primer 5’ – 3’ Reverse primer 5’ – 3’ Annealing temperature ( 0 C) IFN-Ɣ CTAATTATTCGGTAACTGACTTGA ACAGTTCAGGCCATCACATTGGA 59 TNF-α GAGTGACAAGCCTGTAGCCCATGTTGTAGC GCAATGATCCCAAAGTAGACCTGCCCAGACT 60 IL-6 CAAATTCGGTACATCCTC CTGGCTTGTTCCTCACTA 59 CXCL8 TCCTGCATCCCCCATAGTTA CTTCAGGAACAGCCACCAGT 58 CCR7 ACTGTGGTGTTGTCTCCGAT TGGTGGCTCTCCTTGTCATT 56 NF-kB TCTCCCTGGTCACCAAGGAC TCATAGAAGCCATCCCGGC 58 COX-2 CCGGGTACAATCGCACTTAT GGCGCTCAGCCATACAG 55 CCL2 AAGCAGAAGTGGGTTCAGGA TGGGTTGTGGAGTGAGTGTT 54 GAPDHP65 TGGGTGGCAGTGATGGCA GGAGAAGGCTGGGGCTCAT 52 DNA methylation assay The MethylEdgeTM Bisulfite conversion system (Promega, USA) was used to treat genomic DNA with bisulphite following the manufacturer's instructions. We checked for methylation at CpG sites of the promoters, which span 500 bases from the transcriptional start site to the translational start site. The primers used to amplify the bisulphite-modified DNA that targeted the promoter regions of the selected genes are detailed in Table 2 . The thermocycling conditions involved an initial step at 95°C for 5 minutes, followed by 45 cycles of the following steps: 95°C for 60 seconds, gene-specific annealing temperatures (ranging from 55°C to 65°C) for 30 seconds (Table 2 ), and extension at 72°C for 35 seconds. A 1.5% agarose gel was used to visualize 3 µl of the PCR products. Using the forward primer, each PCR product was sequenced using a Thermofisher, US-based SeqStudioTM Genetic Analyzer System with SmartStart. The program Bio Edit Sequence Alignment Editor was used to view the sequence readings ( 28 ). After being trimmed, sequences with noisy data backgrounds were sent into the BiQ analyzer program, which shows the methylation and unmethylated sites independently ( 29 ). Table 2 Primer Sequences for Amplification of Bisulfite-Modified DNA in Selected Gene Promoter Regions Gene Forward primer 5’ – 3’ Reverse primer 5’ – 3’ Annealing temperature (•C) IFN-Ɣ TATAAATAAAAAATCAACATTTTACCAAAA TTGGTAGTAATAGTTAAGAGAATTTA 50 TNF-α TTAAAAGAAATGGAGGTAATAG CTTCTCTCCCTCTTAACTAATC 58 IL-6 TATTATTTTGAGGGAAGAGGGTTTT TACTCTCCCCACTACCACTAAATCT 56 CXCL8 ATTAGGAATGGTGAGTTTATGAGTTT TTCCATTTAATAACAACAAATTATCAATAT 56 COX-2 GTTTAGTTATATAGGTGAGTATTTGG AATAACTAACTCATAATAATCAATACTTAT 47 Statistical analysis The normality of the data was examined using the Shapiro-Wilk test ( 30 ). Frequencies or percentages were used to represent discrete variables and mean ± SD was used to represent continuous variables. The independent t-test was used to compare continuous variables like gene expressions, and sociodemographic factors like age, BMI, and sleeping hours. The chi-square test was used to compare categorical variables The fold change in gene expression between meditators and controls was compared using an independent t-test. To determine the degree of methylation at certain CpG sites in the gene's promoter region, Sanger sequencing analysis was employed. It was determined what the average methylation percentage was across all promoter CpG sites. Methylation percentage was divided into two groups based on the control group's median level of methylation. A category was classified as high methylation if its overall methylation at the promoter region exceeded the control group's median methylation, and as low methylation if its overall methylation was less than the control group's median methylation. Consequently, after controlling for age, sex, and diet, the methylation levels of the genes in meditators and non-meditators were compared. The results were shown as odds ratios with 95% confidence intervals. The statistical analyses were carried out utilizing IBM SPSS (Version 23.0), and p-values less than 0.05 were used to assess significance. Results Characteristics of study population The baseline characteristics of the research population that have previously been reported are included in Table 3 ( 20 ). In summary, 19 out of the 30 participants in each group (63.34%) were men, with a mean age of 43 years ± 9.92 SD for the cohort. All the participants were Sinhalese, and only three were identified as Christians. The rest of the participants practiced Theravada Buddhism. The average lifetime duration of meditation carried out by the meditators was 6.8 years (± 3.27), and their reported daily meditation duration was 5.82 hours (± 3.45). The meditators mentioned that they frequently engaged in body scanning, breathing, and loving-kindness meditation, among other types of meditation. There was no significant difference in the baseline characteristics between the meditators and controls. Table 3 Socio-demographic and health characteristics of the study sample Demographic data Meditators (n = 30) Controls (n = 30) p value Mean SD No. % Mean SD No. % Age a 43.83 9.92 43.51 9.92 0.892 BMI 26.5 5.23 23.39 2.61 0.227 Sleeping hours per day 6.27 1.56 6.22 1.92 0.987 Gender (male) a 19 63.34 19 63.34 1 Married 19 63.34 14 46.6 0.407 Educational level- Tertiary 24 80 24 80 1 Educational level -Secondary 6 20 6 20 1 Alcohol b 7 23.3 8 26.67 1 Smokers 0 0 0 0 1 Non-vegetarian diet 29 96.67 30 100 1 Exercise (> 1h/week) 8 26.67 13 43.34 0.601 a Matched variables b Consume alcohol occasionally % - percentage SD – Standard deviation Expression levels of genes related to inflammation Several genes showed significant reductions in expression in long-term meditators compared to controls, including the CXCL -8 (FC = 3.3, p = 0.047), IFN -Ɣ (FC = 7.0, p = 0.045), TNF -α (FC = 2.73, p = 0.038), IL -6 (FC = 6.87, p = 0.035), NF - ƙB (FC = 3.2, p = 0.045), and COX-2 (FC = 9.5, p = 0.013) genes. In contrast, CCR -7 (FC = 6.1, p = 0.503) and CCL -2 (FC = 4.9, p = 0.842) genes did not exhibit statistically significant differences (Fig. 1 ). Methylation status of promoter regions of the selected inflammatory pathway genes In the − 500 to + 500 nucleotide range around the transcriptional start site, methylation status was assessed in the promoter region of the selected genes. Meditators exhibited significantly higher methylation levels in the IL6 gene promoter (meditator: mean ± SD = 90.72 ± 9.67%, control: mean ± SD = 80.81 ± 11.07%, odds ratio-68.444, 95% CI, 8.052 to 581.801; p < 0.001). Further analysis at 16 CpG sites within this region confirmed significantly elevated methylation at 2 CpG sites in long-term meditators, persisting even after adjusting for age, sex, and diet. Meditators also showed higher TNF -α gene promoter methylation (meditator: mean ± SD = 58.62 ± 9.5%, control: mean ± SD = 23.23 ± 10.12%, odds ratio-38.77, 95% CI, 4.66 to 322.47; p = 0.001), confirmed at 2 CpG sites out of 11 CpG sites after controlling for the same covariates. In the IFN-Ɣ gene promoter, no significant difference was observed after adjustment (meditator: mean ± SD = 44.44 ± 14.05%, control: mean ± SD = 31.48 ± 10.41%, odds ratio-0.167, 95% CI, 4.66 to 322.47; p = 0.100), despite higher methylation at 1 CpG site out of 27 CpG sites. The CXCL-8 gene promoter displayed significantly higher methylation in meditators (meditator: mean ± SD = 72.31 ± 9.5%, control: mean ± SD = 23.23 ± 10.12%, odds ratio-7.34, 95% CI, 4.66 to 121.47; p = 0.001), confirmed at 5 CpG sites out of 12 CpG sites. Conversely, no significant difference in COX2 gene promoter methylation was observed between meditators and controls (meditator: mean ± SD = 77.31 ± 7.5%, control: mean ± SD = 63.23 ± 8.12%, odds ratio-9.13, 95% CI, 15.67 to 101.46; p = 0.602) across 2 CpG sites out of 12 CpG sites (Fig. 2 ). Details of the CpG sites can be found in Supplementary file 1. Discussion In this study, the expression profiles of CXCL-8, IFN-Ɣ, TNF-a, IL-6, COX-2 , and NF-ƙB genes exhibited significant alterations in meditators compared to controls. Moreover, differential methylation was observed in the IL-6, TNF- α, and CXCL-8 genes among meditators compared to controls. In line with these results, a study conducted by Epel et al. (2016) investigated the gene expression of TNF -α in 51 participants who underwent a six-day meditation retreat program. They observed no change in TNF -α gene expression in the meditation group and an increase in the control group (Epel et al., 2016). However, our findings of significantly lowered expression levels of IL -6 in meditators compared to controls differ from the results reported by Cresswell and colleagues, who observed no significant difference in the expression of IL -6 gene between meditators and controls. The contrasting outcome could be attributed to variations in the study design as it is a randomized controlled trial which had introduced an 8-week meditation intervention to meditation naïve older adults. As our study recruited 3 years of long-term meditation experienced participants, they may have acquired more beneficial effects of meditation than an 8-week intervention. Furthermore, we found significantly lower expression in IFN -Ɣ gene in meditators group while another study has shown that the Qigong practitioners had significantly higher IFN -Ɣ expression ( 8 ). These contrasting findings could be attributed to several factors, including differences in the specific mind-body practice (Qigong vs. meditation) and variations in the sample sizes. It is worth noting that Quan-Zhen Li’s study had relatively small sample size (n = 6), which may have impacted the varied results ( 8 ). The expression of COX-2 and NF-ƙB was also significantly lower in meditators compared to controls. COX - 2 encodes the cyclooxygenase-2 enzyme, which is involved in inflammation and pain responses, while NF-ƙB is a transcription factor that regulates numerous genes involved in the immune response and inflammation. Previous studies have also reported similar findings. For instance, Cresswell et al., 2012 and Kaliman et al., 2014 have shown decreased expression of NF-ƙB and COX-2 genes (Creswell et al., 2013; Kaliman et al., 2014). Preliminary research shows that meditation changes the amount of cortisol produced during the day (Carlson et al., 2004; Witek-Janusek et al., 2008; Brand et al., 2012). The hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system, which both produce stress mediators like cortisol, norepinephrine, and epinephrine that can influence NF-ƙB activity and pro-inflammatory gene expression, may be affected by meditation (Michael R. Irwin & Steven W. Cole, 2011; Steve W. Cole, 2009). Cytosines before guanine nucleotides, often known as CpG sites, are where most of the DNA methylation takes place. Approximately 70% of all gene promoters are found inside CpG islands ( 31 ). In general, DNA methylation suppresses the expression of genes, particularly when it is found at CpG sites upstream of the gene. As a result, a lower level of gene expression in the pro-inflammatory genes could be linked to some of the methylation alterations. Five inflammation pathway associated pro-inflammatory genes which showed significant reduction in gene expression were selected for further analysis of the methylation status. Our findings corroborate with the previously published studies which have also shown higher methylation level at the promoter regions ( 16 , 17 ). Furthermore, we obtained non-significant changes in the methylation level of the COX-2 gene which is inconsistent with our gene expression analysis results as it showed a significant decrease. However, consistent with the methylation results obtained in our study, a recent study also highlighted non-significant changes in the methylation level of the COX2 gene ( 16 ). It is hypothesized that the practise of meditation could potentially regulate the expression of this gene via altering the activity of regulatory transcription factors, rather than changing the methylation modifications. DNA methylation is generally confounded by different environmental factors including exposure to radiation and lifestyle factors such as age, gender, diet, behaviour, stress, physical activity, working habits, voluntary alcohol, and smoking ( 32 ). Age, gender, and diet adjustments were made during our analysis to mitigate the confounding effects. Downregulation of genes associated with inflammation, including TNF-α, IL-6, IFN-Ɣ, CXCL8 , and COX -2, holds significant therapeutic potential for managing a spectrum of inflammatory disorders. By attenuating the expression of TNF-α, IL-6, IFN-Ɣ , and CXCL-8 genes, immune cell recruitment and activation diminishes, leading to a reduction in inflammation at sites of injury or infection. This is particularly pertinent in chronic inflammatory conditions such as Rheumatoid Arthritis, Inflammatory Bowel Disease, Psoriasis, and others, where persistent inflammation is implicated. Moreover, downregulating these pro-inflammatory genes not only minimizes tissue damage but also fosters a conducive environment for tissue repair and regeneration. This may suggest that long-term meditation practice affects the methylation status and the expression of the genes related to inflammation. Conclusion The compelling findings of this study shed light on the potential benefits of long-term meditation practice in reducing inflammation. The observed significant reduction in inflammatory markers appears to be linked to the downregulation of specific genes within inflammatory pathways such as NF-kB pathway. Interestingly, the increased promoter methylation observed in these genes indicates a novel regulatory mechanism by which meditation may exert its anti-inflammatory effects. However, further study is recommended to fully comprehend how meditation impacts gene expression and its implications for long-term health. This ongoing research may lead to new discoveries on how to use meditation as a preventative measure against chronic inflammation. Declarations Ethics approval and consent to participate The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of Faculty of Medicine, University of Colombo (protocol code EC-19-067 and date of approval-20th June 2019) Consent for publication Not applicable Availability of data and materials The datasets presented in this study can be found in online repositories. DOI: 10.6084/m9.figshare.23537952. Competing interest The authors declare that no competing interest. Funding This work was supported by a grant from the Accelerating Higher Education Expansion and Development (AHEAD) Operation of the Ministry of Higher Education funded by the World Bank (Grant No. 6026-LK/8743-LK). Author contributions The authors confirm contribution to the paper as follows. NS and NSi: study conception and design. ND: data collection, analysis, and interpretation of results. ND, NSi, and NSa: draft manuscript preparation. All authors contributed to the article and approved the submitted version. Acknowledgement D.A.W.H. Jayasooriya and D.P. Madhusanka for assistance with sample collection References West M. Meditation. Vol. 135, The British journal of psychiatry : the journal of mental science. 1979. Jevning R, Wallace RK, Beidebach M. The physiology of meditation: A review. A wakeful hypometabolic integrated response. Neurosci Biobehav Rev. 1992;16(3):415–24. Manocha R. Why meditation? Aust Fam Physician. 2000 Dec;29(12):1135–8. Yates J, Immergut M, Graves J. The Mind Illuminated. New York: Dharma Tressure Press; 2015. Emilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, et al. Genetics of gene expression and its effect on disease. Nature. 2008;452(7186). Ferrucci L, Fabbri E. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4456071","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323961859,"identity":"8c9d0655-c032-469d-8408-9a15cfb651fe","order_by":0,"name":"Nirodhi Namika Dasanayaka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYDACZiDmbZCQA1IGQHwAJMZ4sIEILcbIWhjwa2EAa2FIbCBaizk778MHb3dYpK9tb97A8DPnDgN/+wGGgzPwaLFsZjc2nHtGInfbmWMFjL3bnjFInElgOLgBjxaDw2xs0rxtQC03cgyYGbcdZmC4AXTYAyK0pJvdfwPRIk+slgSzGzwQLQYgLQQcxmw4t03CcNuZtIKDQL/wGJ5JbMDrfYPzxxgfvG2rkzc7fnjjg5/b7sjJHT988GEPHi0o4AAQ8wAjv4FYDaNgFIyCUTAKcAAACPBTERvsElwAAAAASUVORK5CYII=","orcid":"","institution":"University of Colombo","correspondingAuthor":true,"prefix":"","firstName":"Nirodhi","middleName":"Namika","lastName":"Dasanayaka","suffix":""},{"id":323961861,"identity":"5087ed8a-177f-44b9-845d-5c93dbda24e0","order_by":1,"name":"Nirmala Dushyanthi Sirisena","email":"","orcid":"","institution":"University of Colombo","correspondingAuthor":false,"prefix":"","firstName":"Nirmala","middleName":"Dushyanthi","lastName":"Sirisena","suffix":""},{"id":323961864,"identity":"64877fc0-979a-4455-b64c-ff34891eae9f","order_by":2,"name":"Nilakshi Samaranayake","email":"","orcid":"","institution":"University of Colombo","correspondingAuthor":false,"prefix":"","firstName":"Nilakshi","middleName":"","lastName":"Samaranayake","suffix":""}],"badges":[],"createdAt":"2024-05-21 16:08:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4456071/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4456071/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60614806,"identity":"b72a92b0-5e2c-4e3f-854b-a0e02ca49b8d","added_by":"auto","created_at":"2024-07-18 20:05:27","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46872,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of gene expression between meditators and controls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of eight genes related to inflammation, five genes including \u003cem\u003eCXCL\u003c/em\u003e-8, \u003cem\u003eIFN\u003c/em\u003e-Ɣ, \u003cem\u003eTNF\u003c/em\u003e-α, \u003cem\u003eIL\u003c/em\u003e-6, \u003cem\u003eNF\u003c/em\u003e-\u003cem\u003eƙB\u003c/em\u003e and \u003cem\u003eCOX-2\u003c/em\u003e had significantly reduced expression in meditators compared to controls. Horizontal lines show standard deviation.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4456071/v1/3c169c9d7fa00e65f723f79a.jpg"},{"id":60614807,"identity":"9892b7e6-13c7-4c4f-b115-2fb2cc53b437","added_by":"auto","created_at":"2024-07-18 20:05:27","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67127,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap visualization of methylation differences between meditators and controls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeatmap shows the -log\u003csub\u003e10 \u003c/sub\u003e(p value) for each CpG site of each gene. We checked 16, 27,11,12, and 12 CpG sites of \u003cem\u003eIL-6\u003c/em\u003e, \u003cem\u003eIFN-Ɣ\u003c/em\u003e, \u003cem\u003eTNF-α\u003c/em\u003e, \u003cem\u003eCXCL-8\u003c/em\u003e, and \u003cem\u003eCOX-2\u003c/em\u003e genes, respectively.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4456071/v1/86da6ef9a3846328aa80e803.jpg"},{"id":77969973,"identity":"a62a8fcf-632f-49fa-917f-6cc3417dd55a","added_by":"auto","created_at":"2025-03-07 10:39:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1021260,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4456071/v1/1984abad-fd29-424a-8886-eb20db2ad868.pdf"},{"id":60614805,"identity":"37cd12d2-959d-49ff-8132-6a5b8a4233bd","added_by":"auto","created_at":"2024-07-18 20:05:27","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":25208,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4456071/v1/e266fa9059efe686e588e9cb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of long-term meditation on the expression of genes related to inflammation and their methylation status: A case-control study","fulltext":[{"header":"Background","content":"\u003cp\u003eMeditation is a technique that has been practiced for thousands of years to promote physical and mental well-being. It involves focusing the mind on a specific object or activity to achieve a state of deep relaxation and heightened awareness (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The practice of meditation can be traced back to ancient Eastern traditions, such as Hinduism and Buddhism, where it was used as a means of spiritual development and enlightenment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). There are many different forms of meditation, each with its own unique techniques including mantra meditation, loving-kindness meditation, walking meditation, Zen meditation etc (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). While these techniques may differ in their specific methodologies and philosophies, their ultimate goal remains consistent to guide individuals towards a state of profound inner awakening and liberation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, the knowledge of the molecular mechanisms by which they affect a wide array of biological processes, from genes to the immune system, is still unclear.\u003c/p\u003e \u003cp\u003eGene expression is a complex process that allows cells to synthesize the proteins and RNA molecules necessary for their function by converting genetic information stored in DNA (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Chronic inflammation has been implicated in the development and progression of numerous diseases, including cardiovascular disease, neurodegenerative disorders, and certain cancers (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Inflammation primarily occurs through genetic pathways, activating key transcription factors like NF-κB and AP-1, along with the Toll-like receptor pathway, thereby orchestrating the expression of pro-inflammatory genes such as interleukins (IL) and tumor necrosis factor-alpha (TNF-α). The rate of gene expression is regulated by a complex interplay of various factors, including transcription factors, epigenetic modifications, and signalling pathways (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA microarray containing 12,000 genes was employed to assess gene expression patterns by Quan-Zhen Li and colleagues with six long-term practitioners of Falun Gong Qigong and six healthy individuals serving as controls. The findings revealed that Qigong practitioners exhibited 132 downregulated genes and 118 upregulated genes compared to the control group (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Another case control study investigated the gene expression patterns related to oxidative stress, specifically focusing on genes such as \u003cem\u003eCOX2\u003c/em\u003e and showed that \u003cem\u003eCOX2\u003c/em\u003e exhibited notably lower expression levels in the Sudarshan Kriya practitioners compared to the control group (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a mindfulness-based stress reduction (MBSR) interventional study conducted by Creswell et al. in 2013, reduced pro-inflammatory gene expression patterns were observed. However, despite the influence on gene expression patterns, the levels of \u003cem\u003eIL\u003c/em\u003e-6 gene did not show substantial alterations due to the MBSR intervention (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). A recent intervention found that the practice of Kirtan Kriya Meditation led to a decrease in the expression of pro-inflammatory genes related to the NF-κB pathway (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Another study, carried out on the impact of Tai Chi on inflammation, found a significant reduction in the expression of \u003cem\u003eTNF-α\u003c/em\u003e genes and a marginal reduction in the expression of \u003cem\u003eIL-6\u003c/em\u003e genes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Kaliman et al., 2014 observed non-significant differences in gene expression, including \u003cem\u003eCCR7, CXCL8, TNF-α\u003c/em\u003e, and \u003cem\u003eIL\u003c/em\u003e-6, in experienced meditators after conducting eight hours of mindfulness meditation (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEnvironmental signals interact with the epigenetic machinery through both extracellular and intracellular routes, influencing a broad range of biological activities, including behavior and the stress response (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). DNA methylation is a type of epigenetic modification that involves the addition of a methyl group (-CH3) to the cytosine residue of a DNA molecule (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Chaix et al. 2019, investigated the impact of intensive meditation practice on the methylome of peripheral blood mononuclear cells and found an enrichment in genes primarily associated with immune cell metabolism (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Another study obtained positive effects of meditation on the methylation levels of certain genes related to inflammation such as \u003cem\u003eIL\u003c/em\u003e-6 and \u003cem\u003eTNF\u003c/em\u003e-α (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The existing body of research predominantly focuses on investigating the impact of meditation either on the expression of genes or on the DNA methylation of inflammation-related genes in isolation. Consequently, a comprehensive understanding of the underlying molecular mechanisms remains elusive. Moreover, the majority of these studies primarily rely on short-term interventions, limiting the scope for observing significant outcomes. To address this gap, our study intended to explore the long-term effects of meditation, seeking a more holistic comprehension of its influence on gene expression and DNA methylation, thereby contributing to a more nuanced understanding of the molecular pathways involved. Therefore, the aim of this study was to compare the expression of selected genes related to inflammation such as \u003cem\u003eIL-6, TNF- α, IFN-Ɣ, CXCL-8, COX-2, CCL-2, CCR-7\u003c/em\u003e and \u003cem\u003eNF-ƙB\u003c/em\u003e and the methylation status in the promoter regions of these genes between long-term meditators and controls.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design and participants\u003c/h2\u003e\n \u003cp\u003eThis case-control study involved 30 experienced, skilled meditators who were selected from the community practising at several meditation centers in Sri Lanka. They were matched for age (\u0026plusmn;\u0026thinsp;2 years), gender, and educational level, with 30 non-meditator controls. A total of 60 participants, equally divided between meditators and controls (30 in each group), were chosen to ensure 80% statistical power and an alpha error of 0.05, with the goal of detecting an effect size of 0.8. This decision was informed by reported fold change (FC) levels from prior studies (\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e). The process of recruiting participants has been previously documented (\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e). In summary, participants aged 18 to 65 years were included in the study. Meditators were defined as individuals who consistently practiced meditation for over 6 hours per week for at least three years. The study employed purposive sampling to choose non-meditators (controls) from the same community. The inclusion criteria required that the controls had either never meditated or had only sometimes (less than once per three months) practiced meditation or other mind-body intervention methods. Exclusion criteria included smokers, those with a history of sickness or chronic medication use, and women who were pregnant or breast-feeding. The study obtained ethics approval from the Ethics Review Committee, Faculty of Medicine, University of Colombo (EC-19-067) and was carried out in accordance with the Declaration of Helsinki. The period of recruitment was from August 2020 to December 2021. Written, informed consent was obtained from each participant.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eProcedures\u003c/h2\u003e\n \u003cp\u003eThe procedures for analysing telomere length-related gene expression and DNA methylation data, previously published (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e), share the same laboratory protocols as described here. Despite this article focusing on inflammation, the gene expression and DNA methylation analysis maintain consistent laboratory procedures. The following briefly describes the procedures. Initially, potential participants were contacted at meditation centres located in various parts of the island. The study recruited long-term meditators who had attained pre-determined skill levels, as assessed by a questionnaire-based scoring system (\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e). Participants from both groups provided their written consent upon their initial visit and proceeded to submit their blood samples.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eMeasures and covariates\u003c/h2\u003e\n \u003cp\u003eThe sociodemographic data, which included age, gender, educational attainment, marital status, sleeping and working hours, and lifestyle factors including alcohol intake, food preferences, and amount of time spent exercising (in hours), was gathered via an interviewer-administered questionnaire. Standard scales were used to measure the height and weight, and the body mass index (BMI) was computed.\u003c/p\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003eBlood collection\u003c/h2\u003e\n \u003cp\u003e5 ml of blood from each participant was collected to Ethylenediamine Tetraacetic Acid (EDTA) tubes, and immediately centrifuged at 1400 rpm for 10 minutes at 4\u0026deg;C. After centrifugation, the plasma and the whole blood were divided into 1.5 ml microcentrifuge tubes that had already been labelled. The samples were kept at -80\u0026deg;C until the assay, and they were defrosted only immediately before the analysis.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003eGene expression assay\u003c/h2\u003e\n \u003cp\u003eThe SV Total RNA Isolation System (Promega, USA) was used to extract RNA from whole blood in accordance with the manufacturer\u0026apos;s instructions. To create cDNA, 1 \u0026micro;g of RNA from each sample was reverse transcribed using the GoScriptTM Reverse Transcription System (Promega, USA). 50ng of the resultant cDNAs were subjected to real-time qPCR using the primers for the genes described previously (\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e), utilizing Quantitech\u0026reg; SYBR\u0026reg; Green PCR master mix. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e provides specifics about primer sequences for the selected genes. The RT-PCR conditions were based on published protocols (\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e) and were further optimised. In summary, 10 \u0026micro;l of 2\u0026times; Quantitech SYBR Green RT-PCR master mix, 2 \u0026micro;l primers, 50 ng of sample cDNA, and nuclease-free water were added to RT-PCR procedures to bring the reaction volume to 20 \u0026micro;l. The thermal cycling profile was as follows: An initial denaturation at 95\u0026deg;C for 10 minutes (1 cycle) was followed by denaturation at 95\u0026deg;C for 20 seconds, gene-specific annealing temperatures as detailed in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e for 20 seconds, and extension at 72\u0026deg;C for 45 seconds, repeated for 45 cycles. The process concluded with a 1-minute hold at 60\u0026deg;C. The target gene cDNA level was measured using relative quantification in relation to the level of the \u003cem\u003eGAPDH\u003c/em\u003e reference gene cDNA. The relative gene expression level was determined using the 2-\u0026Delta;\u0026Delta;Ct technique (\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrimer Sequences and Annealing Temperatures for Gene Expression Assay\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eForward primer\u003c/p\u003e\n \u003cp\u003e5\u0026rsquo; \u0026ndash; 3\u0026rsquo;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReverse primer\u003c/p\u003e\n \u003cp\u003e5\u0026rsquo; \u0026ndash; 3\u0026rsquo;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAnnealing temperature (\u003csup\u003e0\u003c/sup\u003eC)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIFN-Ɣ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCTAATTATTCGGTAACTGACTTGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACAGTTCAGGCCATCACATTGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTNF-\u0026alpha;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGAGTGACAAGCCTGTAGCCCATGTTGTAGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGCAATGATCCCAAAGTAGACCTGCCCAGACT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIL-6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCAAATTCGGTACATCCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCTGGCTTGTTCCTCACTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCXCL8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTCCTGCATCCCCCATAGTTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCTTCAGGAACAGCCACCAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCCR7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACTGTGGTGTTGTCTCCGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTGGTGGCTCTCCTTGTCATT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNF-kB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTCTCCCTGGTCACCAAGGAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTCATAGAAGCCATCCCGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCOX-2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCGGGTACAATCGCACTTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGCGCTCAGCCATACAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCCL2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAAGCAGAAGTGGGTTCAGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTGGGTTGTGGAGTGAGTGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGAPDHP65\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTGGGTGGCAGTGATGGCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGAGAAGGCTGGGGCTCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eDNA methylation assay\u003c/h2\u003e\n \u003cp\u003eThe MethylEdgeTM Bisulfite conversion system (Promega, USA) was used to treat genomic DNA with bisulphite following the manufacturer\u0026apos;s instructions. We checked for methylation at CpG sites of the promoters, which span 500 bases from the transcriptional start site to the translational start site. The primers used to amplify the bisulphite-modified DNA that targeted the promoter regions of the selected genes are detailed in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The thermocycling conditions involved an initial step at 95\u0026deg;C for 5 minutes, followed by 45 cycles of the following steps: 95\u0026deg;C for 60 seconds, gene-specific annealing temperatures (ranging from 55\u0026deg;C to 65\u0026deg;C) for 30 seconds (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), and extension at 72\u0026deg;C for 35 seconds. A 1.5% agarose gel was used to visualize 3 \u0026micro;l of the PCR products. Using the forward primer, each PCR product was sequenced using a Thermofisher, US-based SeqStudioTM Genetic Analyzer System with SmartStart. The program Bio Edit Sequence Alignment Editor was used to view the sequence readings (\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e). After being trimmed, sequences with noisy data backgrounds were sent into the BiQ analyzer program, which shows the methylation and unmethylated sites independently (\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrimer Sequences for Amplification of Bisulfite-Modified DNA in Selected Gene Promoter Regions\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eForward primer\u003c/p\u003e\n \u003cp\u003e5\u0026rsquo; \u0026ndash; 3\u0026rsquo;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReverse primer\u003c/p\u003e\n \u003cp\u003e5\u0026rsquo; \u0026ndash; 3\u0026rsquo;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAnnealing temperature (\u0026bull;C)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIFN-Ɣ\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTATAAATAAAAAATCAACATTTTACCAAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTTGGTAGTAATAGTTAAGAGAATTTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTNF-\u0026alpha;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTTAAAAGAAATGGAGGTAATAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCTTCTCTCCCTCTTAACTAATC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eIL-6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTATTATTTTGAGGGAAGAGGGTTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTACTCTCCCCACTACCACTAAATCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCXCL8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATTAGGAATGGTGAGTTTATGAGTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTTCCATTTAATAACAACAAATTATCAATAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCOX-2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGTTTAGTTATATAGGTGAGTATTTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAATAACTAACTCATAATAATCAATACTTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe normality of the data was examined using the Shapiro-Wilk test (\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e). Frequencies or percentages were used to represent discrete variables and mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD was used to represent continuous variables. The independent t-test was used to compare continuous variables like gene expressions, and sociodemographic factors like age, BMI, and sleeping hours. The chi-square test was used to compare categorical variables The fold change in gene expression between meditators and controls was compared using an independent t-test.\u003c/p\u003e\n \u003cp\u003eTo determine the degree of methylation at certain CpG sites in the gene\u0026apos;s promoter region, Sanger sequencing analysis was employed. It was determined what the average methylation percentage was across all promoter CpG sites. Methylation percentage was divided into two groups based on the control group\u0026apos;s median level of methylation. A category was classified as high methylation if its overall methylation at the promoter region exceeded the control group\u0026apos;s median methylation, and as low methylation if its overall methylation was less than the control group\u0026apos;s median methylation. Consequently, after controlling for age, sex, and diet, the methylation levels of the genes in meditators and non-meditators were compared. The results were shown as odds ratios with 95% confidence intervals.\u003c/p\u003e\n \u003cp\u003eThe statistical analyses were carried out utilizing IBM SPSS (Version 23.0), and p-values less than 0.05 were used to assess significance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eCharacteristics of study population\u003c/h2\u003e\n \u003cp\u003eThe baseline characteristics of the research population that have previously been reported are included in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e (\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e). In summary, 19 out of the 30 participants in each group (63.34%) were men, with a mean age of 43 years\u0026thinsp;\u0026plusmn;\u0026thinsp;9.92 SD for the cohort. All the participants were Sinhalese, and only three were identified as Christians. The rest of the participants practiced Theravada Buddhism. The average lifetime duration of meditation carried out by the meditators was 6.8 years (\u0026plusmn;\u0026thinsp;3.27), and their reported daily meditation duration was 5.82 hours (\u0026plusmn;\u0026thinsp;3.45). The meditators mentioned that they frequently engaged in body scanning, breathing, and loving-kindness meditation, among other types of meditation. There was no significant difference in the baseline characteristics between the meditators and controls.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocio-demographic and health characteristics of the study sample\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDemographic data\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eMeditators (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eControls (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSleeping hours per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (male)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducational level- Tertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducational level -Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcohol\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmokers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-vegetarian diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExercise (\u0026gt;\u0026thinsp;1h/week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003csup\u003ea\u003c/sup\u003eMatched variables\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003csup\u003eb\u003c/sup\u003eConsume alcohol occasionally\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e% - percentage\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003eSD \u0026ndash; Standard deviation\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eExpression levels of genes related to inflammation\u003c/h2\u003e\n \u003cp\u003eSeveral genes showed significant reductions in expression in long-term meditators compared to controls, including the \u003cem\u003eCXCL\u003c/em\u003e-8 (FC\u0026thinsp;=\u0026thinsp;3.3, p\u0026thinsp;=\u0026thinsp;0.047), \u003cem\u003eIFN\u003c/em\u003e-Ɣ (FC\u0026thinsp;=\u0026thinsp;7.0, p\u0026thinsp;=\u0026thinsp;0.045), \u003cem\u003eTNF\u003c/em\u003e-\u0026alpha; (FC\u0026thinsp;=\u0026thinsp;2.73, p\u0026thinsp;=\u0026thinsp;0.038), \u003cem\u003eIL\u003c/em\u003e-6 (FC\u0026thinsp;=\u0026thinsp;6.87, p\u0026thinsp;=\u0026thinsp;0.035), \u003cem\u003eNF\u003c/em\u003e-\u003cem\u003eƙB\u003c/em\u003e (FC\u0026thinsp;=\u0026thinsp;3.2, p\u0026thinsp;=\u0026thinsp;0.045), and \u003cem\u003eCOX-2\u003c/em\u003e (FC\u0026thinsp;=\u0026thinsp;9.5, p\u0026thinsp;=\u0026thinsp;0.013) genes. In contrast, \u003cem\u003eCCR\u003c/em\u003e-7 (FC\u0026thinsp;=\u0026thinsp;6.1, p\u0026thinsp;=\u0026thinsp;0.503) and \u003cem\u003eCCL\u003c/em\u003e-2 (FC\u0026thinsp;=\u0026thinsp;4.9, p\u0026thinsp;=\u0026thinsp;0.842) genes did not exhibit statistically significant differences (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eMethylation status of promoter regions of the selected inflammatory pathway genes\u003c/h2\u003e\n \u003cp\u003eIn the \u0026minus;\u0026thinsp;500 to +\u0026thinsp;500 nucleotide range around the transcriptional start site, methylation status was assessed in the promoter region of the selected genes. Meditators exhibited significantly higher methylation levels in the \u003cem\u003eIL6\u003c/em\u003e gene promoter (meditator: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;90.72\u0026thinsp;\u0026plusmn;\u0026thinsp;9.67%, control: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;80.81\u0026thinsp;\u0026plusmn;\u0026thinsp;11.07%, odds ratio-68.444, 95% CI, 8.052 to 581.801; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Further analysis at 16 CpG sites within this region confirmed significantly elevated methylation at 2 CpG sites in long-term meditators, persisting even after adjusting for age, sex, and diet. Meditators also showed higher \u003cem\u003eTNF\u003c/em\u003e-\u0026alpha; gene promoter methylation (meditator: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;58.62\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5%, control: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;23.23\u0026thinsp;\u0026plusmn;\u0026thinsp;10.12%, odds ratio-38.77, 95% CI, 4.66 to 322.47; p\u0026thinsp;=\u0026thinsp;0.001), confirmed at 2 CpG sites out of 11 CpG sites after controlling for the same covariates. In the \u003cem\u003eIFN-Ɣ\u003c/em\u003e gene promoter, no significant difference was observed after adjustment (meditator: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;44.44\u0026thinsp;\u0026plusmn;\u0026thinsp;14.05%, control: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;31.48\u0026thinsp;\u0026plusmn;\u0026thinsp;10.41%, odds ratio-0.167, 95% CI, 4.66 to 322.47; p\u0026thinsp;=\u0026thinsp;0.100), despite higher methylation at 1 CpG site out of 27 CpG sites. The \u003cem\u003eCXCL-8\u003c/em\u003e gene promoter displayed significantly higher methylation in meditators (meditator: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;72.31\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5%, control: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;23.23\u0026thinsp;\u0026plusmn;\u0026thinsp;10.12%, odds ratio-7.34, 95% CI, 4.66 to 121.47; p\u0026thinsp;=\u0026thinsp;0.001), confirmed at 5 CpG sites out of 12 CpG sites. Conversely, no significant difference in \u003cem\u003eCOX2\u003c/em\u003e gene promoter methylation was observed between meditators and controls (meditator: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;77.31\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5%, control: mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;63.23\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12%, odds ratio-9.13, 95% CI, 15.67 to 101.46; p\u0026thinsp;=\u0026thinsp;0.602) across 2 CpG sites out of 12 CpG sites (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Details of the CpG sites can be found in Supplementary file 1.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the expression profiles of \u003cem\u003eCXCL-8, IFN-Ɣ, TNF-a, IL-6, COX-2\u003c/em\u003e, and \u003cem\u003eNF-ƙB\u003c/em\u003e genes exhibited significant alterations in meditators compared to controls. Moreover, differential methylation was observed in the \u003cem\u003eIL-6, TNF-\u003c/em\u003eα, and \u003cem\u003eCXCL-8\u003c/em\u003e genes among meditators compared to controls.\u003c/p\u003e \u003cp\u003eIn line with these results, a study conducted by Epel et al. (2016) investigated the gene expression of \u003cem\u003eTNF\u003c/em\u003e-α in 51 participants who underwent a six-day meditation retreat program. They observed no change in \u003cem\u003eTNF\u003c/em\u003e-α gene expression in the meditation group and an increase in the control group (Epel et al., 2016). However, our findings of significantly lowered expression levels of \u003cem\u003eIL\u003c/em\u003e-6 in meditators compared to controls differ from the results reported by Cresswell and colleagues, who observed no significant difference in the expression of \u003cem\u003eIL\u003c/em\u003e-6 gene between meditators and controls. The contrasting outcome could be attributed to variations in the study design as it is a randomized controlled trial which had introduced an 8-week meditation intervention to meditation na\u0026iuml;ve older adults. As our study recruited 3 years of long-term meditation experienced participants, they may have acquired more beneficial effects of meditation than an 8-week intervention. Furthermore, we found significantly lower expression in \u003cem\u003eIFN\u003c/em\u003e-Ɣ gene in meditators group while another study has shown that the Qigong practitioners had significantly higher \u003cem\u003eIFN\u003c/em\u003e-Ɣ expression (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These contrasting findings could be attributed to several factors, including differences in the specific mind-body practice (Qigong vs. meditation) and variations in the sample sizes. It is worth noting that Quan-Zhen Li\u0026rsquo;s study had relatively small sample size (n\u0026thinsp;=\u0026thinsp;6), which may have impacted the varied results (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The expression of \u003cem\u003eCOX-2\u003c/em\u003e and \u003cem\u003eNF-ƙB\u003c/em\u003e was also significantly lower in meditators compared to controls. \u003cem\u003eCOX\u003c/em\u003e-\u003cem\u003e2\u003c/em\u003e encodes the cyclooxygenase-2 enzyme, which is involved in inflammation and pain responses, while \u003cem\u003eNF-ƙB\u003c/em\u003e is a transcription factor that regulates numerous genes involved in the immune response and inflammation. Previous studies have also reported similar findings. For instance, Cresswell et al., 2012 and Kaliman et al., 2014 have shown decreased expression of \u003cem\u003eNF-ƙB\u003c/em\u003e and \u003cem\u003eCOX-2\u003c/em\u003e genes (Creswell et al., 2013; Kaliman et al., 2014).\u003c/p\u003e \u003cp\u003ePreliminary research shows that meditation changes the amount of cortisol produced during the day (Carlson et al., 2004; Witek-Janusek et al., 2008; Brand et al., 2012). The hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system, which both produce stress mediators like cortisol, norepinephrine, and epinephrine that can influence NF-ƙB activity and pro-inflammatory gene expression, may be affected by meditation (Michael R. Irwin \u0026amp; Steven W. Cole, 2011; Steve W. Cole, 2009).\u003c/p\u003e \u003cp\u003eCytosines before guanine nucleotides, often known as CpG sites, are where most of the DNA methylation takes place. Approximately 70% of all gene promoters are found inside CpG islands (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In general, DNA methylation suppresses the expression of genes, particularly when it is found at CpG sites upstream of the gene. As a result, a lower level of gene expression in the pro-inflammatory genes could be linked to some of the methylation alterations.\u003c/p\u003e \u003cp\u003eFive inflammation pathway associated pro-inflammatory genes which showed significant reduction in gene expression were selected for further analysis of the methylation status. Our findings corroborate with the previously published studies which have also shown higher methylation level at the promoter regions (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Furthermore, we obtained non-significant changes in the methylation level of the \u003cem\u003eCOX-2\u003c/em\u003e gene which is inconsistent with our gene expression analysis results as it showed a significant decrease. However, consistent with the methylation results obtained in our study, a recent study also highlighted non-significant changes in the methylation level of the \u003cem\u003eCOX2\u003c/em\u003e gene (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). It is hypothesized that the practise of meditation could potentially regulate the expression of this gene via altering the activity of regulatory transcription factors, rather than changing the methylation modifications. DNA methylation is generally confounded by different environmental factors including exposure to radiation and lifestyle factors such as age, gender, diet, behaviour, stress, physical activity, working habits, voluntary alcohol, and smoking (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Age, gender, and diet adjustments were made during our analysis to mitigate the confounding effects.\u003c/p\u003e \u003cp\u003eDownregulation of genes associated with inflammation, including \u003cem\u003eTNF-α, IL-6, IFN-Ɣ, CXCL8\u003c/em\u003e, and \u003cem\u003eCOX\u003c/em\u003e-2, holds significant therapeutic potential for managing a spectrum of inflammatory disorders. By attenuating the expression of \u003cem\u003eTNF-α, IL-6, IFN-Ɣ\u003c/em\u003e, and \u003cem\u003eCXCL-8\u003c/em\u003e genes, immune cell recruitment and activation diminishes, leading to a reduction in inflammation at sites of injury or infection. This is particularly pertinent in chronic inflammatory conditions such as Rheumatoid Arthritis, Inflammatory Bowel Disease, Psoriasis, and others, where persistent inflammation is implicated. Moreover, downregulating these pro-inflammatory genes not only minimizes tissue damage but also fosters a conducive environment for tissue repair and regeneration. This may suggest that long-term meditation practice affects the methylation status and the expression of the genes related to inflammation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe compelling findings of this study shed light on the potential benefits of long-term meditation practice in reducing inflammation. The observed significant reduction in inflammatory markers appears to be linked to the downregulation of specific genes within inflammatory pathways such as NF-kB pathway. Interestingly, the increased promoter methylation observed in these genes indicates a novel regulatory mechanism by which meditation may exert its anti-inflammatory effects. However, further study is recommended to fully comprehend how meditation impacts gene expression and its implications for long-term health. This ongoing research may lead to new discoveries on how to use meditation as a preventative measure against chronic inflammation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of Faculty of Medicine, University of Colombo (protocol code EC-19-067 and date of approval-20th June 2019)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets presented in this study can be found in online repositories. DOI: 10.6084/m9.figshare.23537952.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by a grant from the Accelerating Higher Education Expansion and Development (AHEAD) Operation of the Ministry of Higher Education funded by the World Bank (Grant No. 6026-LK/8743-LK).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm contribution to the paper as follows. NS and NSi: study conception and design. ND: data collection, analysis, and interpretation of results. ND, NSi, and NSa: draft manuscript preparation. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eD.A.W.H. Jayasooriya and D.P. Madhusanka for assistance with sample collection\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWest M. Meditation. Vol. 135, The British journal of psychiatry : the journal of mental science. 1979. \u003c/li\u003e\n\u003cli\u003eJevning R, Wallace RK, Beidebach M. The physiology of meditation: A review. A wakeful hypometabolic integrated response. Neurosci Biobehav Rev. 1992;16(3):415\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eManocha R. Why meditation? Aust Fam Physician. 2000 Dec;29(12):1135\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eYates J, Immergut M, Graves J. The Mind Illuminated. New York: Dharma Tressure Press; 2015. \u003c/li\u003e\n\u003cli\u003eEmilsson V, Thorleifsson G, Zhang B, Leonardson AS, Zink F, Zhu J, et al. Genetics of gene expression and its effect on disease. Nature. 2008;452(7186). \u003c/li\u003e\n\u003cli\u003eFerrucci L, Fabbri E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Vol. 15, Nature Reviews Cardiology. 2018. \u003c/li\u003e\n\u003cli\u003eGibney ER, Nolan CM. Epigenetics and gene expression. Vol. 105, Heredity. 2010. \u003c/li\u003e\n\u003cli\u003eLi Q zhen, Ph D, Li P, Ph D, D GEGM, Johnson RJ, et al. Genomic Profiling of Neutrophil Transcripts in Asian Qigong Practitioners : A Pilot Study in Gene Regulation by Mind \u0026ndash; Body Interaction. 2005;11(1):29\u0026ndash;39. \u003c/li\u003e\n\u003cli\u003eSingh N, Sharma H, Datta P. Gene Expression Profiling in Practitioners of Sudarshan Kriya Introduction : 2009;50\u0026ndash;3. \u003c/li\u003e\n\u003cli\u003eCreswell JD, Irwin MR, Burklund LJ, Lieberman MD, Arevalo MG, Ma J, et al. Mindfulness-Based Stress Reduction Training Reduces Loneliness and Pro-Inflammatory Gene Expression in Older Adults: A Small Randomized Controlled Trial. 2013;26(7):1095\u0026ndash;101. \u003c/li\u003e\n\u003cli\u003eBlack DS, Cole SW, Irwin MR, Breen E, St. Cyr NM, Nazarian N, et al. Yogic meditation reverses NF-\u0026kappa;B and IRF-related transcriptome dynamics in leukocytes of family dementia caregivers in a randomized controlled trial. Psychoneuroendocrinology. 2013;38(3). \u003c/li\u003e\n\u003cli\u003eIrwin MR, Olmstead R, Carrillo C, Sadeghi N, Breen EC, Witarama T, et al. Cognitive behavioral therapy vs. Tai Chi for late life insomnia and inflammatory risk: A randomized controlled comparative efficacy trial. Sleep. 2014;37(9). \u003c/li\u003e\n\u003cli\u003eKaliman P, Cosı M, Lutz A, Davidson RJ. ScienceDirect Rapid changes in histone deacetylases and inflammatory gene expression in expert meditators. 2014;96\u0026ndash;107. \u003c/li\u003e\n\u003cli\u003eGr\u0026auml;ff J, Kim D, Dobbin MM, Li-Huei T. Epigenetic Regulation of Gene Expression in Physiological and Pathological Brain Processes. Physiol Rev. 2011;91(2). \u003c/li\u003e\n\u003cli\u003eJin B, Li Y, Robertson KD. DNA methylation: Superior or subordinate in the epigenetic hierarchy? Vol. 2, Genes and Cancer. 2011. \u003c/li\u003e\n\u003cli\u003eChaix R, Fagny M, Lemee L, Regnault B, Davidson RJ, Lutz A, et al. Differential DNA methylation in experienced meditators after anintensive day of mindfulness-based practice:implications for immune-related pathways. Brain Behav Immun [Internet]. 2019; Available from: https://doi.org/10.1016/j.bbi.2019.11.003\u003c/li\u003e\n\u003cli\u003eHarkess KN, Ryan J, Delfabbro PH, Cohen-Woods S. Preliminary indications of the effect of a brief yoga intervention on markers of inflammation and DNA methylation in chronically stressed women. Transl Psychiatry. 2016;6(11). \u003c/li\u003e\n\u003cli\u003eQu S, Olafsrud SM, Meza-zepeda LA, Saatcioglu F. Rapid Gene Expression Changes in Peripheral Blood Lymphocytes upon Practice of a Comprehensive Yoga Program. 2013;8(4):1\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eLi QZ, Li P, Garcia GE, Johnson RJ, Feng L. Genomic profiling of neutrophil transcripts in Asian Qigong practitioners: A pilot study in gene regulation by mind-body interaction. Journal of Alternative and Complementary Medicine. 2005;11(1):29\u0026ndash;39. \u003c/li\u003e\n\u003cli\u003eDasanayaka NN, Sirisena ND, Samaranayake N. Impact of Meditation-Based Lifestyle Practices on Mindfulness , Wellbeing , and Plasma Telomerase Levels : A Case-Control Study. Front Psychol. 2022;13(March). \u003c/li\u003e\n\u003cli\u003eDasanayaka NN, Sirisena ND, Samaranayake N. Associations of meditation with telomere dynamics: a case\u0026ndash;control study in healthy adults. Front Psychol. 2023;14. \u003c/li\u003e\n\u003cli\u003eOutschoorn NO, Somarathne EASK, Dasanayaka NN, Karunarathne LJU, Vithanage KK, Dalpatadu KPC, et al. The development of a tool to identify skilled meditators among meditation practitioners - \u0026lsquo;The University of Colombo Intake Interview to identify Skilled Meditators for scientific research (UoC-IISM).\u0026rsquo; Journal of the College of Community Physicians of Sri Lanka. 2022;28(4). \u003c/li\u003e\n\u003cli\u003eRana A, Minz RW, Aggarwal R, Anand S, Pasricha N, Singh S. Gene expression of cytokines (TNF-\u0026alpha;, IFN-\u0026gamma;), serum profiles of IL-17 and IL-23 in paediatric systemic lupus erythematosus. Lupus. 2012;21(10):1105\u0026ndash;12. \u003c/li\u003e\n\u003cli\u003eYang C, Yu H, Chen RUI, Tao KAI, Jian LEI, Peng M, et al. CXCL1 stimulates migration and invasion in ER ‑ negative breast cancer cells via activation of the ERK / MMP2 / 9 signaling axis. Int J Oncol. 2019;55(2019):684\u0026ndash;96. \u003c/li\u003e\n\u003cli\u003eRoelofs HMJ, te Morsche RHM, van Heumen BWH, Nagengast FM, Peters WHM. Over-expression of COX-2 mRNA in colorectal cancer. BMC Gastroenterol. 2014;14(1):3\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eDuraimani S, Schneider RH, Randall OS, Nidich SI, Xu S, Ketete M, et al. Effects of Lifestyle Modification on Telomerase Gene Expression in Hypertensive Patients : A Pilot Trial of Stress Reduction and Health Education Programs in African Americans. 2015;1\u0026ndash;18. \u003c/li\u003e\n\u003cli\u003eRao X, Huang X, Zhou Z, Xin Lin. An improvement of the 2\u0026circ;(\u0026ndash;delta delta CT) method for quantitative real-time polymerase chain reaction data analysis Xiayu. NIH public access. 2013;3(3):71\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eHall T, Biosciences I, Carlsbad C. BioEdit: An important software for molecular biology. GERF Bulletin of Biosciences. 2011;2(June). \u003c/li\u003e\n\u003cli\u003eAkg\u0026uuml;n M, Pfeifer N, Kohlbacher O. Efficient privacy-preserving whole-genome variant queries. Bioinformatics. 2022;38(8). \u003c/li\u003e\n\u003cli\u003eGhasemi A, Zahediasl S. Normality tests for statistical analysis: A guide for non-statisticians. Int J Endocrinol Metab. 2012;10(2):486\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eBlackledge NP, Klose R. CpG island chromatin. Epigenetics. 2011;6(2). \u003c/li\u003e\n\u003cli\u003ePacchierotti F, Span\u0026ograve; M. Environmental Impact on DNA Methylation in the Germline: State of the Art and Gaps of Knowledge. Vol. 2015, BioMed Research International. Hindawi Limited; 2015. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4456071/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4456071/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003eDespite established benefits for mental and physical well-being, the precise underlying molecular mechanisms of the effects of meditation remain unclear. This study explored the hypothesis that long-term meditation practice downregulates the expression of genes associated with stress-induced inflammation. The expression of selected inflammation-related genes and their promoter methylation status were compared between long-term meditators and controls.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eThirty experienced meditators and 30 age- and gender-matched non mediators participated in this case-control study. RNA and DNA were extracted from blood samples. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) with GAPDH normalization was used to measure the expression of eight inflammation-related genes (\u003cem\u003eIFN-γ, IL-6, CCL-2, CCR-7, TNF-α, NF-κB, CXCL8, \u003c/em\u003eand\u003cem\u003eCOX-2)\u003c/em\u003e. Additionally, bisulfite-specific PCR and Sanger sequencing were performed to assess the methylation status of five of these genes \u003cem\u003e(IL-6, TNF-α, IFN-γ, COX-2, \u003c/em\u003eand\u003cem\u003e CXCL8\u003c/em\u003e) in their promoter regions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The mean age of participants was 43.83 ± 9.92 years, and 63.34% in each group were male. Compared to controls, meditators showed significantly lower relative gene expression for \u003cem\u003eIFN\u003c/em\u003e-γ (Fold change (FC)=7,p=0.045), \u003cem\u003eIL\u003c/em\u003e-6 (FC=3.6,p=0.045), \u003cem\u003eTNF\u003c/em\u003e-α (FC=2.73,p=0.038), \u003cem\u003eNF\u003c/em\u003e-\u003cem\u003eƘB\u003c/em\u003e(FC=3.2,p=0.045), \u003cem\u003eCXCL8\u003c/em\u003e (FC=3.3,p=0.047), and \u003cem\u003eCOX\u003c/em\u003e-2 (FC=9.5,p=0.013). Furthermore, meditators exhibited significantly higher promoter region methylation in IL-6 (p \u0026lt; 0.001) and \u003cem\u003eCXCL8\u003c/em\u003e (p = 0.001). The methylation level at specific CpG sites showed that four out of 16 sites in \u003cem\u003eIL\u003c/em\u003e-6 and five out of twelve sites in \u003cem\u003eCXCL\u003c/em\u003e-8 gene had significantly higher methylation in meditators. Although no significant difference in the overall methylation level in the promoter regions of \u003cem\u003eTNF\u003c/em\u003e-α and \u003cem\u003eIFN\u003c/em\u003e-γ genes were detected, two out of 12 sites and one out of 27 sites in the \u003cem\u003eTNF\u003c/em\u003e-α and \u003cem\u003eIFN\u003c/em\u003e-γ genes, respectively, showed significantly higher methylation in meditators.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eThese findings suggest that long-term meditation practice may contribute to reduced inflammation by downregulating the expression of specific inflammatory pathway genes and increasing their promoter methylation. Further research is needed to explore these potential mechanisms and their long-term health implications.\u003c/p\u003e","manuscriptTitle":"Effects of long-term meditation on the expression of genes related to inflammation and their methylation status: A case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 20:05:22","doi":"10.21203/rs.3.rs-4456071/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b5fd04b-de7c-4a73-8a39-ce4d803b8bd3","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-07T10:39:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-18 20:05:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4456071","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4456071","identity":"rs-4456071","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}