The effect of mindfulness-based interventions on immunity-related biomarkers: a comprehensive meta-analysis of randomised controlled trials

Dunn, Thomas J.; Dimolareva, Mirena

doi:10.1016/j.cpr.2022.102124

Cited by 26 publications

(24 citation statements)

References 104 publications

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“…However, subgroup analysis showed TNF-α (8-12 wk, 3000-4800 minutes), IL-6 (yoga-meditationpranayama), and cortisol (6-12 wk, 1000-2000 minutes) statistically significant reductions favouring intervention. Our findings are in line with earlier conducted metaanalyses in which both IL-6 and TNF-α were reduced in the intervention group following the yoga and meditation [86,87]. e change was significant in one study reporting IL-6 [86], whereas there was an insignificant decrease in IL-6 and TNF-α [87], which could have been due to smaller number of studies (n � 2) included in the analysis.…”

Section: Discussionsupporting

confidence: 91%

“…Our findings are in line with earlier conducted metaanalyses in which both IL-6 and TNF-α were reduced in the intervention group following the yoga and meditation [86,87]. e change was significant in one study reporting IL-6 [86], whereas there was an insignificant decrease in IL-6 and TNF-α [87], which could have been due to smaller number of studies (n � 2) included in the analysis. Recent reviews on the effects of phytosterols and the effect of an herb, Nigella sativa, have also been shown to reduce the cytokine storm; however, these are beyond the scope of this review and so, further suggested [8,88].…”

Section: Discussionsupporting

confidence: 91%

See 1 more Smart Citation

Yoga, Meditation, Breathing Exercises, and Inflammatory Biomarkers with Possible Implications in COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Shah

Adhikari

Sharma

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Introduction. COVID-19, a multisystem disease, has implications for various immunity and infection biomarkers. Yoga (Y), meditation (M), and pranayama (P), and their combinations have shown positive changes on those biomarkers among other than COVID-19 patients and healthy people. So, we aimed to document the evidence of possible implication in a systematic way. Materials and Methods. We screened 84 full texts, published in the last ten years, from three databases, from which only 44 met the eligibility criteria, and then extracted the data related to demographic characteristics, intervention, results, and strengths and limitations in two MS-Excel grids, and then presented them in tables and figures. Furthermore, we carried out meta-analysis including subgroup and sensitivity analysis using a random effects model of 11 RCTs and reported the mean difference, heterogeneity, and p value with 95% CI and presented them with forest and funnel plots and the tables. Results. Twenty-five biomarkers of 4023 participants (range, 15–413) from 13 countries, healthy and clinical, from both sexes above 18 years, and from mainly clinical settings, were reported. YMP intervention, in solitary or in different possible combinations with varied durations among clinical and pregnant (range, 960–4800 minutes) and healthy (960–8400 minutes, excluding two studies of 20 minutes only) participants, was reported. It was revealed that 25 biomarkers, nine among the apparently healthy, 14 among the patients, and two among the pregnant, changed favourably ( p < 0.05 ). Furthermore, either in meta- or subgroup-analysis, mean differences of IL-6 (−1.44 pg/ml) (95% CI) (−2.33, −0.55), ( p = 0.002 , I2 = 82%), Cortisol (−40.75 pg/ml) (95% CI) (−64.13, −17.38), ( p = 0.0006 , I2 = 87%), and TNF-α (−3.40 pg/ml) (95% CI) (−4.83, −1.98), ( p < 0.0001 , I2 = 79%) showed statistically significant changes. Nonetheless, considerable heterogeneity and publication bias were observed among the studies. Conclusion. Although more than two dozens of biomarkers in individual studies showed favourable changes, only IL-6, Cortisol, and TNF-α produced significant combined results, even then with much less certainty. Further meta-analysis of biomarkers of COVID-19 patients is highly recommended. Registration: CRD42021283894.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Yoga, Meditation, Breathing Exercises, and Inflammatory Biomarkers with Possible Implications in COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Shah

Adhikari

Sharma

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“…Due to the heterogeneity of findings, it was not possible to quantify the magnitude of mind-body interventions upon inflammatory markers using meta-analysis, for example. Although during the time our report was in peer-review, a meta-analysis into immunity-related biomarkers associated with mindfulness-based practices was also published [100], examining a mix of clinical conditions and healthy populations. The authors conceded small sample sizes and reduced statistical power limited their meta-analyses, although proposed that mindfulness practices may facilitate salutogenesis through improved immune function [100].…”

Section: Discussionmentioning

confidence: 99%

“…Although during the time our report was in peer-review, a meta-analysis into immunity-related biomarkers associated with mindfulness-based practices was also published [100], examining a mix of clinical conditions and healthy populations. The authors conceded small sample sizes and reduced statistical power limited their meta-analyses, although proposed that mindfulness practices may facilitate salutogenesis through improved immune function [100]. Back to our review, only studies that included a control group and reported statistical analyses comparing mean change pre-to-post intervention were included, that may have eliminated the inclusion of all possible studies.…”

Section: Discussionmentioning

confidence: 99%

Systematic Review of High-Dimensional Omics in Mind-Body Medicine

Schoenberg¹,

Gonzalez²

2022

OBM Integr Complement Med

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The multi-dimensional measurement of complex biological systems and sub-systems is made possible by high-dimensional omics technologies. This frontier of research is promising for elucidating disease processes, physiological parameters, and therapeutic action mechanisms. Omics have potential merit for the integrative medicine field that is relatively early in terms of mechanistic research towards understanding the underlining therapeutic processes of mind-body interventions that show to affect multiple systems simultaneously. An inflammatory theory of disease has brought to light molecular and epidemiological evidence proposing that inflammation could be considered a unitary predictor across most disease typologies which may be treated as a central clinical entity. Relatively recent theorizations of disease have built upon epigenetic data showing that complex “interactomes”, or disease networks where genetic factors that have downward chain effects on transcriptional, proteomic domains, dynamically modulate in response to environmental, microbial, and immunological domains. Thus, complex conditions underlined by interactive disease networks and dynamics essentially require complex multi-levelled interventions. This is particularly germane for complex patient cases often seen in the integrative medicine clinic. Mind-body medicine may be part of such care programs that can be made accessible for all. To shed further light on the possibility of building the evidence base in integrative health towards this direction, we reviewed the current use of omics technologies in mind-body medicine within the last 5-years. Use of omics approaches within the field is still developing. Early findings appear to show beneficial impact upon genomic, transcriptional, and proteomic biomarkers across varied chronic inflammatory conditions, including disorders of the cardiovascular, central nervous, endocrine, immune, musculoskeletal, and respiratory, systems.

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“…This general stress adaptation might be most efficiently therapeutically targeted by intervening with the stressors itself. Such interventions could include mindfulness-based stress reduction protocols, which have shown promise in reducing stress in pregnant ( 52 , 53 ) and non-pregnant women ( 54 ), with a recent meta-analysis demonstrating their beneficial post-interventional impact on immunity-related biomarkers in non-pregnant participants ( 55 ). Pregnancy-adapted protocols continue to be subject of clinical trials ( 56 , 57 ).…”

Section: Discussionmentioning

confidence: 99%

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

et al. 2022

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Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.ObjectivesThe primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.Materials and MethodsIn a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).ResultsJointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.ConclusionsElucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics.

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The effect of mindfulness-based interventions on immunity-related biomarkers: a comprehensive meta-analysis of randomised controlled trials

Cited by 26 publications

References 104 publications

Yoga, Meditation, Breathing Exercises, and Inflammatory Biomarkers with Possible Implications in COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Yoga, Meditation, Breathing Exercises, and Inflammatory Biomarkers with Possible Implications in COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Systematic Review of High-Dimensional Omics in Mind-Body Medicine

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

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