2. Brief Background
Authors: Manoj Bhasin, Jeffery Dusek, Bei-Hung Chang,
Marie Joseph, John Denninger, Gregory Fricchione, Herbert
Benson, Towia Libermann
Published: May 2013
Grant Funding: H75/CCH123424 and R01 DP000339 from
the Centers for Disease Control and Prevention (CDC) (HB),
RO1 AT006464-01 from the National Center for
Complementary and Alternative Medicine (NCCAM)(HB),
M01 RR01032 from the NCRR, National Institutes of Health
(The Harvard-Thorndike GCRC). These grant funders had
“no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.”
Conflicts of Interest: None.
3. Relaxation Response (RR)
This is the opposite response of the stress response (better
known as “flight or fight” response) which produces specific
psychological and physiological reactions in the mind and body. This
response often activates the parasympathetic nervous system whereas
the stress response activates the sympathetic nervous system. Over
time, over heightened activity of the sympathetic nervous system can
activate the inflammatory response and lead to chronic disease where
as the activation of the parasympathetic response is responsible for
helping to bring the body and mind into a state of equilibrium and
health.
The RR is activated by (1) focusing on a word, prayer, phrase,
sound, or movement, and (2) “disregarding everyday thoughts”
Examples of activities that activate RR: meditation, yoga,
movement practices, biofeedback, breathing exercises, progressive
muscle relaxation
Physiological changes associated with RR activation:
biochemical changes; < oxygen consumption, CO2 elimination, blood
pressure, heart and respiratory rate, and norepinephrine
responsiveness, >heart rate variability, and changes in cortical and
subcortical brain regions
4. Previous Research,
Purpose of This Study
Previous Research Findings:
Activation of the RR has shown to be an effective therapeutic
intervention to counteract stress associated with hypertension,
anxiety, aging, diabetes, rheumatoid arthritis, and insomnia;
however, the cellular evidence for this effect has not been fully
defined.
Previous study by authors established changes in genetic
expression with a similar design, specific with genes associated
with oxygen phosphorylation, antigen processing/presentation,
and apoptosis with short and long term practitioners when
compared to novices
This same previous study also found psychobiological changes
only in long term practitioners during one session of RR
What is unique for this Research?
It is examining acute genetic changes within one RR session and how
the length of previous practices affects this genetic expression.
5. Hypotheses of Study
(1) One Relaxation Response session for both short and
long-term practitioners would make specific changes in gene
expression that would be linked specific biological
pathways in comparison to a control group with no
experience
(2) More significant genetic changes would be found in long
term practitioners of Relaxation Response sessions in
comparison to short term practitioners of RR.
6. Study Sample
Study enrolled 26 healthy subjects with no previous
formal RR activation experience (ie. no formal practices of
RR) which were considered the control group, Novices (N1).
These subjects then took 8 weeks of RR training and then
became the first comparison as Short-term Practitioners (N2)
A second group of 26 healthy subjects with prior practices
in RR (4-20 years experience) were to compared with the
Novice (N1) group and Short-term Practitioners (N2). This
group was named Long-term Practitioners (M).
All subjects were recruited within Boston, MA
7. N1 (control group): Listened to a 20 minute Health
Education CD on first visit
N2 (control group which became N2) and M: Listened to
20 minute RR activating CD
Blood samples (to be used for gene expression profiles) and
biological measurements were taken before the session (T0),
after the session (T1) and 15 minutes after the session was
complete.
Fractional exhaled nitric oxide (FeNO) were collected at the
3 time points, which helps to assess physiological effects of
RR (such as reduction in blood pressure) and has shown
that RR typical increases FeNO levels which can influence
immune system responses.
Methods
9. Techniques
RNA was isolated from peripheral blood mononuclear cells
(PBMCs) in blood samples
Real-time FeNO (exhaled) was measured with a rapid response
chemoluminescent Nitric Oxide Analyzer before each session
Transcriptional Profiling: Done by Affymetrix human genome
high throughput array plates. These plates contained 96 arrays
and 22,000 transcripts. Array images were analyzed with dChip.
Types of Gene Analyses: The purpose was to identify RR
affected genes/sets of genes with a hierarchy of bioinformatic
techniques including Individual Gene Analysis, Gene Ontology
(GO) enrichment analysis, Gene Set Enrichment Analysis,
Pathways and Interactive network analysis, Systems Biology
analysis
10. Results Explained
RR leads to qualitative and quantitative temporal transcriptome changes:
Individual Gene Analysis
RR elicits distinct temporal patterns of differential gene expression: Self-
Organizing Map (SOM) Analysis
RR progressively affected energy metabolism and inflammation pathways:
Canonical pathways: Gene Set Enrichment Analysis (GSEA)
Upregulated Progressive changes induced by RR are linked to energy
production in mitochondria: Systems Biology Analysis
Upregulated Long-term changes induced by RR are linked to telomerase
stability and maintenance: Systems Biology Analysis
Progressive and Long-term Downregulated gene expression changes induced
by RR are linked to alteration of NF-kB-dependent pathways: Systems Biology
Analysis
Immune response and telomere maintenance related pathways are affected
among Long-term RR practitioners: GSEA
RR affected pathways are correlated with Fractional exhaled Nitric Oxide
(FeNO) levels : Correlation Analysis
11. Results
Across Group:
At T (0): Greatest differentiated genes between N1 vs. N2
At T (1): Greatest differentiated genes between N1 vs. M
At T (2): Greatest differentiated genes between N1 vs. M
What about Within Groups, what is the greatest differentiation?
17. Results: FeNO Gene Regulation
Table S3: Correlation analysis of NO levels and Selected 10 pathways affected progressively or only in long term manner
by RR (Bold).
The correlation analysis was performed both by comparing FeNO and gene expression levels at particular time point (e.g.
T0, T1, T2) as well as changes in gene expression and FeNO levels within a group. The significance of the correlation
was determined on the basis of P value (P < 0.05) and FDR (<25%). The positive and negative correlations between
FeNO and gene expression levels are indicated by red and green color respectively.
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19. Discussion: Inflammation Relationships
Significant research has shown that activation of the RR can reduce chronic stress
and promote wellness and these authors have provided some of the first evidence of
prolonged gene level changes that are opposite of the transcriptional changes that
accompany chronic stress.
This research specifically looked at transient transcriptome changes in temporal
analysis because it focuses on indentifying genes affected by RR at time points and
reduces the likelihood of false positives.
It is suspected that with upregulation of gene sets with RR for oxidation might
improve efficiency of oxidation-reduction reactions and reduce oxidative stress.
Upregulation of the ATP synthase pathway with RR can play an important role in
understanding the biological supportive evidence of RR.
Critical pro-inflammatory transcriptor factors were downregulated by RR thus
having an influential effect on the inflammatory response, which can reduce
oxidative stress, insulin resistance, and apoptosis.
Psychological stress can cause chronic mitochondrial oxidative stress that can lead
to metabolic syndrome and activate NF-kB (pro-inflammatory factor) which can
make this worse.
Understanding the NF-kB relationship in inflammation is important for
understanding the molecular/cellular mechanisms for health benefits for RR.
20. Long term RR practice helped to upregulate pathways associated with gene
stability especially with telemere packing, telemere maintenance, and tight
junction interaction. Since telemere breakdown can affect mitochondria function
and lead to apoptosis.
The psychological stress is linked to deregulated immune system function and
DNA repair that may be influenced by RR and thus RR may be able to reverse
stress related transcriptome changes.
RR practice may create mitochondrial resiliency or mitochondrial reserve capacity
which can create cellular benefits in relationship to health and reducing
psychological stress and chronic disease.
Mitochondria are considered the energy powerhouse of a cell and also „master
regulators of danger signaling‟ to help protect cellular health and life of an
organism.
Certain mitochondria also experience differential reserve capacity to help work
with the different pathogenic effects of oxidative stress. Mitochondrial reserve
capacity and resiliency begins to fail when there is high cellular metabolic
demands, which contributes to high disease vulnerability.
The Future of This Research:
To continue to clinically define the in-depth cellular/molecular
pathways and genetic connections related to RR with secondary
biochemical testing.
Discussion: Mitochondria Relationships
21. Reference
Bhasin M., Dusek J., Chang B., Joseph M., Denninger J., Fricchione G.,
Benson H., Libermann T. (2013). Relaxation response induces temporal
transcriptome changes in energy metabolism, insulin secretion, and
inflammatory pathways. Retreived from PlosOne on March 6, 2014:
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.
0062817
Hinweis der Redaktion
Why did I choose this research?Previous cardiovascular medicine research with a great interest in inflammation and what reverses the inflammatory process that can lead to chronic disease. I have approached this from Traditional Chinese Medicine looking at emotional, mental, physical, and spiritual components and this research allows me to approach it from physiological and genetic approaches and make larger and deeper connections.
Stress Response: highly activated by our fears, anxiety, the unknown, frustration, excesses, overwork, etc…..sound familiar?Relaxation Response: turns down the stress response and takes us into that happy medium where we can cope, understand, comprehend, listen, work well with others, and make good choices, and our immune system has the ability to respond correctly to maintain equilibrium and thus we process well on emotional, mental, physical, and spiritual levels.
RR training included: diaphragmatic breathing, body scan, mantra repetition, mindfulness meditation while ignoring intrusive thoughts20 minute CD was listened to once a day
Affymetrix human genomehigh throughput arrays plates with 96 arrays (HT U133A),containing more than 22,000 transcripts, were used. Scannedarray images were analyzed by dChip [31]. The raw probe leveldata were normalized using the smoothing-spline invariant setmethod, and the signal value for each transcript was summarizedusing the PM-only based signal modeling algorithm in which thesignal value corresponds to the absolute level of expression of atranscriptData analysis for identifying RR affected genes and gene setswas conducted first based on individual genes then on biologicallyrelated gene sets using a hierarchy of bioinformatics techniquesdescribed below and outlined in Figure 1. We then conductedcorrelation analysis to examine whether the gene expression of RR affected gene sets are associated with the changes in biologicalmeasurement, FeNO.
At T0: The greatest amount of differentiated genes happened with the comparison between N1 (novices) vs N2 (short-term)At T1: The greatest amount of differentiated genes occurred with the comparison between N1 (novices) vs M (long-term)At T3: The greatest amount of differentiated genes occurred with the comparison between N1 vs M.Figure 1. Individual gene-based differential expression analysis. Differentially expressed genes identified by 3 across-group comparisons(N1 vs. N2, N1 vs. M, and N2 vs. M) at T0, T1 and T2. Venn diagrams depict the overlap of genes identified by these 3 comparisons at each time point.B) Heat map of genes that were significantly differentially expressed comparing N1 vs. N2 and N1 vs. M at T1 and T2 (marked with arrow in Venndiagrams). Gene expression is shown with a pseudocolor scale (21 to 1) with red color denoting increased and green color denoting decreased foldchange in gene expression. The rows represent the genes and columns represent subjects in N1, N2 and M groups at T0, T1 and T2. Differentiallyexpressed genes identified by 3 within-group comparisons at different time points (T0 vs. T1, T0 vs. T2 and T1 vs. T2). Venn diagrams depict theoverlap of genes identified by the 3 comparisons within each group.
Figure 2. Temporal genomic expression patterns during one session of RR elicitation. Genes that were differentially expressed eitheracross or within groups comparisons at different time points were used as the seed set of genes for Self-Organizing Map (SOM) analysis. Thesedifferentially expressed genes were partitioned to 18 separate maps according to Pearson correlation coefficient based distance metrics (Figure S2).Selected biologically interesting SOM maps were manually clustered into 4 biologically relevant categories based on the gene expression of N1, N2and M groups at the 3 time points in one session of RR elicitation: Long-term Downregulation; Long-term Upregulation; Progressive Upregulation;and Progressive Downregulation. One representative pattern for each of these 4 biologically relevant categories is shown in the figure. The figuredisplays the box plot of the gene expression with X-axis representing time points and groups, and Y-axis representing scaled gene expression datafrom 21 to +1.
Figure 3. Significantly enriched pathways with progressive patterns identified using gene set enrichment analysis. UpregulatedPathways Downregulated Pathways. The solid dots indicate significantly affected pathways (False Discovery Rate ,25%) identified from acrossgroup comparisons (N1 vs. N2, N1 vs. M and N2 vs. M) at a particular time point (T0, T1 and T2). The asterisks represent significance and directionalityof enrichment (P value,0.09 *, P value,0.05 **, P value,0.01 ***) identified from within group comparisons at different time points (T0 vs. T1, T0 vs.T2, T1 vs. T2). The red and green color asterisks indicate up- and down-regulated enrichment of pathways respectively. The heatmaps depictingrelative expression of selected genes from representative pathways are shown in panels on the right side. Gene expression is shown with a pseudocolor scale (23 to 3) with red and green colors denoting increased and decreased relative expression respectively. Pathways with progressivepatterns were enriched (up- or down- regulated) in N2 and M groups with greater significance of enrichments in M group. Furthermore, increasingenrichment over time within one session of RR elicitation was observed in M group.
Figure 4. Significantly enriched pathways with long-term patterns identified using gene set enrichment analysis. UpregulatedPathwaysDownregulated Pathways. The solid dots indicate significantly affected pathways (False Discovery Rate ,25%) identified from acrossgroup comparisons (N1 vs. N2, N1 vs. M and N2 vs. M) at a particular time point (T0, T1 and T2). The asterisks represent significance and directionalityof enrichment (P value,0.09 *, P value,0.05 **, P value,0.01 ***) identified from within group comparisons at different time points (T0 vs. T1, T0 vs.T2, T1 vs. T2). The red and green color asterisks indicate up- and down-regulated enrichment of pathways respectively. The heatmaps depictingrelative expression of selected genes from representative pathways are shown in panels on the right side. Gene expression is shown with a pseudocolor scale (23 to 3) with red and green colors denoting increased and decreased relative expression respectively. Pathways with long-term patternswere enriched (up- or down- regulated) only in M group. Furthermore, increasing enrichment over time within one session of RR elicitation wasobserved in M group
Figure 5. Interactive network and top focus gene hubs identified from significantly affected pathways. The figure represents the topfocus genes. A) Progressive upregulated Pathways, B) Progressive downregulated Pathways, and C) Integrated network of Long-term and Progressiveaffected pathways. The top focus hubs were identified from complex interactive networks generated from pathways with progressive and long-termpatterns. The focus gene hubs were identified using the bottleneck algorithm for identification of the most interactive molecules with tree liketopological structure. The bottleneck algorithm ranks genes on the basis of significance level with smaller rank indicating increasing confidence. Thepseudocolor scale from red to green represents the bottleneck ranks from 1 to 20.
Oxidative Gene sets and the ATP synthase pathways have central roles in mitochondrial energy mechanics, oxidative phosphorylation, and cell aging---this can prevent an overactive cellular activity expending too much mitochondrial energy.