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2016 Webinar Series | Thursday, October 20, 2016 | 1:00 PM Eastern
Webinar with Christopher Armstrong
Christopher Armstrong
University of Melbourne
www.SolveCFS.org
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• Welcome to the 2016 webinar series!
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• The Solve ME/CFS Initiative is a research
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Save the Dates!
• Thursday, November 10: Anthony Komaroff, MD
• Anthony Komaroff, MD, Simcox-Clifford-Higby
professor of medicine at Harvard Medical School and
senior physician at Brigham and Women’s Hospital in
Boston, Massachusetts
• Thursday, December 15: Zaher Nahle, PhD, MPA
• Zaher Nahle, PhD, MPA , Vice President for research
and scientific programs at Solve ME/CFS Initiative
2016 Webinar Series | Thursday, October 20, 2016 | 1:00 PM Eastern
Webinar with Christopher Armstrong
Christopher Armstrong
University of Melbourne
www.SolveCFS.org
Melbourne Group
A/Prof Paul Gooley
University of Melbourne
Protein Biochemist
Expertise in NMR
Dr Neil McGregor
Once editor of Journal of Chronic Fatigue Syndrome
Researching ME/CFS for 20+ years
Expertise in metabolism
Dr Henry Butt
Formed Bioscreen Medical company that screens fecal
samples for intestinal dysbiosis
Researching ME/CFS for 20+ years
Dr Don Lewis
Formed CFS Discovery clinic
Specialist clinic for managing and treating people with ME/CFS
Treating people with ME/CFS for 20+ years
Our metabolomics work in ME/CFS
Recent metabolomics studies and
other associated studies
What is metabolomics?
Metabolites are any small organic molecule or chemical (amino acids, sugars, drugs, etc.)
Metabolomics is the study of metabolites
External environment
Alter
Metabolites
Alter
Initiate
Alter
Proteins
Instructions to
make
Genes
Genes and the extension of genes (proteins) evolved to move
around metabolites like scientists in a lab
*Images extracted from lecture by David Wishart from University of Alberta - 2016 Informatics
and Statistics for Metabolomics workshop hosted by the Canadian Bioinformatics Workshops
Value of metabolomics to ME/CFS
Stress on a biological system produces symptoms that vary upon the individual.
May cause variations between people with ME/CFS .
ME/CFS still may be an umbrella term for a number of similar disorders (spectrum disorder).
ME/CFS is diagnosed by symptoms. Metabolites are closely linked to symptoms.
Developed metabolite tests can be used in clinical studies to test effectiveness of treatments.
Metabolomics produce a large picture from which we are able to look for potential cause.
History of metabolomics in ME/CFS
Went through hundreds of papers to find metabolite studies
Summarised some studies in tables (pictured)
Comparing multiple metabolomics studies:
• Oxidative stress environment
• Sub-maximal usage of mitochondria for energy
• Decrease of amino acids
• Issues with nitrogen metabolism (urea cycle)
Our metabolomics work in ME/CFS
Blood and Urine Metabolites
METABOLITES
Blood
Urine
Increased in ME/CFS
Decreased in ME/CFS
Significant
Glucose
Hypoxanthine
Phenylalanine
Lactate
Glutamate
Aspartate
Acetate
Formate
Proline
METABOLITES
Alanine
Citrulline
Creatinine
Pyruvate
Serine
Creatine
Alanine
Citrate
Allantoin
Betaine
Acetate
Tyrosine
Creatinine
Serine
Formate
Arginine
Valine
Threonine
Hypoxanthine
ABSOLUTE CONCENTRATION
RELATIVE ABUNDANCE
ME/CFS non-ME/CFS Median Average
μM
μM
Fold C Fold C p-value
4893
4010
1.22
1.24 0.011
16
62
0.25
0.38 0.001
67
82
0.82
0.81 0.001
1434
2637
0.54
0.57 0.006
149
184
0.81
0.80 0.029
69
62
1.11
1.08 0.272
33
64
0.52
0.75 0.040
22
29
0.78
0.71 0.145
190
224
0.85
0.85 0.145
ABSOLUTE CONCENTRATION
467 non-ME/CFS
514 Median
0.91 Average
0.87 0.145
ME/CFS
76
83
0.92
1.03
0.900
μM
μM
Fold C Fold
C p-value
75
77
0.98
0.87 0.034
0.077
61
83
0.73
0.69
991
1669
0.59
0.67
30
32
0.96
1.16 0.034
0.951
255
393
0.65
0.65
101
100
1.00
1.01 0.049
0.707
161
150
1.07
1.27
49
51
0.97
1.04 0.168
0.837
205
353
0.58
0.56
59
64
0.92
0.88 0.003
0.145
6186
4256
1.45
1.22
158
173
0.91
0.98 0.330
0.707
135
323
0.42
0.44
0.002
161
189
0.85
0.88 0.182
53
57
0.92
0.82
0.171
175
192
0.91
0.90 0.079
ME/CFS non-ME/CFS Median Average
%
%
Fold C Fold C p-value
50.4%
36.9%
1.36
1.29 0.002
0.1%
0.6%
0.26
0.39 0.003
0.6%
0.7%
0.88
0.87 0.003
12.8%
24.2%
0.53
0.61 0.004
1.4%
1.5%
0.90
0.85 0.036
0.6%
0.5%
1.20
1.17 0.049
0.3%
0.5%
0.60
0.78 0.105
0.2%
0.2%
0.83
0.78 0.607
1.8% RELATIVE
2.0% ABUNDANCE
0.91
0.90 0.607
4.4% non-ME/CFS
4.7% Median
0.93 Average
0.94 0.607
ME/CFS
0.7%
0.8%
0.94
1.10
0.607
%
%
Fold C Fold
C p-value
0.7%
0.7%
1.00
0.91 0.001
0.607
0.2%
0.3%
0.72
0.74
4.1%
6.0%
0.68
0.75
0.3%
0.3%
1.13
1.24 0.008
0.607
1.0%
1.5%
0.68
0.76
0.9%
0.9%
0.98
1.08 0.008
0.629
0.8%
0.4%
1.69
1.67
0.5%
0.4%
1.18
1.14 0.011
0.662
0.9%
1.5%
0.60
0.68
0.5%
0.6%
0.95
0.94 0.025
0.665
28.0%
21.7%
1.29
1.42
1.5%
1.5%
1.01
1.05 0.025
0.682
0.6%
1.1%
0.49
0.57
0.026
1.4%
1.5%
0.95
0.93 0.686
0.2%
0.2%
0.81
0.91
0.026
1.6%
1.6%
0.99
0.96 0.741
38
66
0.58
0.77
0.063
0.2%
0.2%
0.72
0.73
0.079
Creatinine normalisation
Urine metabolites when corrected by creatinine.
It may be possible that there is an extreme reduction in
metabolite excretion.
Need to do 24 hour urine collection.
As glycolysis was inhibited we suggest it’s likely that
creatinine is increased to compensate.
Energy without oxygen
Glycolysis inhibition
Creatinine replacement?
Too much oxygen/reperfusion
Hypoxanthine to allantoin
Creates reactive oxygen species
AST
Increase
Decrease
Energy production with oxygen
Reduced acetate -> Reduced lipolysis
Amino acids used for energy
Aspartate Transaminase (AST)
Increased Aspartate Transaminase
Aspartate Transaminase (AST) increased 3-fold.
Top enzymes involved in using amino acids and lipids
to fuel the TCA cycle.
Enzymes of electron transport were reduced.
Hypometabolism
~30 metabolites in both the blood and urine of 59 women (34 ME/CFS vs 25 age-matched controls)
6 metabolites were significant altered in blood and 5 were decreased (83%)
5 metabolites were significantly altered in urine and 5 were decreased (100%)
Comparable to Naviaux et al. that found 84% of altered metabolites in blood were decreased.
In NMR we only saw water-soluble metabolites (no lipids).
Advantage of NMR is that you can see all the atoms within a sample, we quantitated about 95%.
Metabolites are made of carbon, hydrogen, oxygen, nitrogen.
Total C, H, O in blood were equal between ME/CFS and controls.
Total N was significantly decreased in blood of ME/CFS.
Total C, H, O, N in urine were equal between ME/CFS and controls.
We’re all on a similar page!
Metabolite studies of the past and most recent
Increased oxidative stress
Increased use of lipids for ATP
Issues of purine metabolism
Issue with folate cycle and methionine
Reduced glycolysis/increase sugars
Increased use of amino acids for ATP
What could it mean?
Well these findings aren’t unique.
This set of findings are actually similar to two acute disorders:
- Starvation
- Sepsis
Differences between them and ME/CFS seems to align with both in some capacity.
Similar mechanisms involved with ME/CFS but at a slow chronic pace.
Provides clues.
Sepsis and Starvation
Similarities to ME/CFS.
Infection or stressor (both)
Cytokine release (sepsis)
Oxidative stress (both, more in sepsis)
Mitochondrial dysfunction at oxidative phosphorylation site (both)
Low blood volume (both)
Hypometabolism (starvation)
Hyperglycemia (starvation)
Mitochondria use lipids and amino acids for ATP production
Collagen breakdown - POTS, hypermobility, slow gastric motility?
Key difference to ME/CFS.
Increased glycolysis (sepsis)
Hypermetabolism (sepsis)
Recovery?
Yes people recover from sepsis and starvation.
Monitored and drip fed because recovery has it’s own limiting factors.
Refeeding syndrome.
Food given to help starvation causes a sudden increase in metabolites in the blood,
these metabolites can lower phosphate, potassium, magnesium, calcium, etc.
Metabolism requires cofactors, minerals and vitamins to function. These deplete as
metabolites deplete, reintroducing increases of metabolites can exhaust these even more.
Our current studies: Longitudinal monitoring of people with ME/CFS to understand which
combination of metabolites, cofactors, vitamins and minerals may have positive affects.
Our metabolomics work in ME/CFS
Microbes in fecal samples
• Live microbial count from fecal samples
• Clostridium spp. and Bacteroides spp. ferment digested compounds to SCFA
• Species of Clostridium have a wider variety of substrates for SCFA production
• Clostridium can make SCFA from peptides and amino acids
Metabolites in fecal samples
• Increased SCFA and isovalerate with decreased amino acids in fecal samples
• Production of fatty acids from proteins may create damaging byproducts in the gut
Metabolite correlations
Abnormal energy metabolites in blood positively correlated with amino acids in fecal
samples of ME/CFS patients.
No significant correlations of increased SCFA with metabolites in blood or urine in
ME/CFS.
Significant negative correlations of fecal SCFA with metabolites in blood involved in energy
metabolism.
Metabolite correlations
Short chain fatty acids appear to cause hypometabolism event in controls.
Studies show that SCFA have this effect by triggering AMPK.
AMPK is the master switch that increases lipid and amino acid production of ATP.
Expected the increase in SCFA to also indicate an effect on hypometabolism in ME/CFS.
Maybe something more at work.
Reduced amino acids in feces appears linked to altered energy metabolism in ME/CFS.
What could it mean?
Gut ties in with both starvation and sepsis.
Bacterial translocation and leaky gut -> inflammation.
Bacterial translocation is normal, however altered bacteria may pose a threat.
pH of the gut and blood may be very important here.
During starvation, proteolysis of proteins occurs. First are proteins in the gut.
Could this be responsible for slow gut motility or reduced dietary protein breakdown?
Limitations
Metabolite studies have been on blood and urine so far.
We can only make inferences on what is occurring in cells. Until we look at the
metabolites in cells and mitochondria we can’t be sure of what is occurring.
Metabolome is dynamic
Your metabolome changes constantly and is individual.
Taking a snapshot of dynamics in biology doesn’t tell you nearly enough.
Patient vary and will show differences based on sample collection parameters.
ME/CFS is dynamic
Symptoms change over the day and over the course of the illness.
Current/Future Studies
Longitudinal metabolomics and genomics study on ME/CFS patients with monitored
intervention.
Metabolomics of ME/CFS cells.
Production of large symptom survey database for potential patient stratification.
Genetic markers and metabolite population studies.
Acknowledgements
Questions…?
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