The last vignette I'd like to present is on personalized care for chronic pain.
This is a new and an emerging area that promises to
impact diagnostics, our, our ability to diagnose and to
create sub-diagnoses within pain populations.
Prognostics, and we believe that that an understanding of both phenotype
and genotype will provide us with information that will help us predict
responses to drugs, and also predict who's at risk for poor outcomes to common
procedures, common surgical procedures, who's at risk for whiplash, PTSD.
We believe that, that prognostic markers are not
too far off for a variety of pain conditions.
And finally, unraveling I think genetics and phenotypic
measures will lead to new targets, new therapeutic targets.
And I'll show you some examples of some
emerging areas that are, that are currently in process.
And again it goes back to this rather complex slide that I showed earlier.
So [COUGH] in order to create, if you will, strata or
sub-populations of patients, where we can apply diagnostic
instruments, where we have prognostic measures, and
where we can identify novel therapeutic targets we need to
take the population of a specific chronic pain condition.
And let's take for example TMD,
so individuals suffering from Temporal Mandibular disorders.
There are really sub-populations of patients who meet the case
definition of TMD, of, of pain in the temples, masseter and joint.
And they show different signs and symptoms in
the clinic related to mood, autonomic balance, pain sensitivity.
And again we believe they have different genetic profiles, which lead to different
signs and symptoms which are expressing in the individual at any one point in time.
And which become temporally dynamic over time as
environmental events begin to accumulate in the individual.
So for example, a TMD patient comes in with a certain set of signs and symptoms.
If they begin to experience greater psychological stress, this leads to a
change in the genetic expression pattern leading to protein changes that control
these intermediate phenotypes leading to a pattern of signs and symptoms for
that patient, at that point in
time, who's experienced a specific environmental exposure.
So, what we and many others have been attempting to do is to try to
use signs and symptoms, phenotypes in psychological domains and in the
pain domain to identify sub-populations of
patients and to determine what their characteristics
are within the context of the overall population of a given pain condition.
And an example of how we've been doing this is
in the prospective study that we've been conducting called OPPERA.
In this study that where we enrolled 3,200 individuals initially free of TMD.
We assess their pain sensitivity.
We assess their psychological function, autonomic function.
And we then ask, based on these signs and symptoms that we collect, if we could
identify clusters, sub-clusters of patients before they develop TMD.
And then we asked the question if you are associated
with a specific cluster, are you more likely to develop TMD?
And then within the TMD population we also, determined whether there
were different clusters of TMD
with established, with the established condition.
And not going through all of the bioinfomatic approaches
we have been able to identify three fundamental sub-populations
or clusters within the normal population that we can define by their
sensitivity to pain and by their psychological, status.
And so cluster one, shown here in blue, where we,
map, basically pain sensitivity on the x-axis.
So this is just a metric of pain sensitivity to a variety of pain-evoking
stimuli, heat pain, pinprick pain, mechanical pain.
So a whole host of modalities were assessed in
the individual, and each individual received a pain sensitivity score.
And then we also assessed a variety of the psychological phenotypes, anxiety,
depression, somatic awareness, and each individual
received a psychological measure as well.
And then the 3,200 individuals were plotted and statistical measures were
developed, and validated, that lead to the separation of three distinct clusters.
In cluster one in blue were relatively insensitive to pain compared to the other
two clusters and were not psychologically distressed relative to cluster three.
So cluster one relatively, if you will, normal from a psychosocial
perspective and from a pain sensitivity and autonomic perspective.
There are more males than females in this cluster and we find that there are very
few chronic TMD patients, and very few chronic
pain patients, in this, in this, cluster as well.
Cluster two, these individuals were more pain sensitive than cluster
one, but their psychological profile was essentially the same.
They're about equal numbers of males and females.
A few more chronic pain patients populate this cluster compared to cluster one.
And they have relatively normal again psychological and
autonomic profiles, but a little bit more pain sensitive.
Cluster three most of our TMD chronic pain patients fall in this cluster, more
females than males very pain sensitive and have higher psychological scores.
So, we have developed methods, and we now have basically, we're in the
process of developing a rather, a simple questionnaire with a couple of of
neurological tests that can be used that will allow us in the clinic in
fairly rapid manner, to cluster a patient into cluster one, two, or three.
And this method, we believe, will be not only useful
for clustering TMD patients, but most of these patients who
have overlapping conditions, we believe we can apply them to
a cluster solution as we've done here for TMD patients.
Now, if we look at the cluster analysis with respect to prognostic events,
and if we asked a question of the 3,200 individuals who are initially free of
TMD, who we followed for about a five-year period, and if we asked the
question, if you started out in cluster
three, what's the likelihood that you're going to develop
TMD compared to if you started out in clusters one or two.
So remember one and two, now one's normal, two's a little bit more pain-sensitive.
Cluster three is pain-sensitive, psychologically distressed, if you will.
And so what you see, that if you started out in cluster three you're
over three times more likely to develop, to develop TMD over the
observational period compared to if you started out in clusters one or two.
So, this algorithm has prognostic properties as well.
So not only can we develop sub-populations, we can also
identify individuals who are likely to develop the condition.
So this has, I think, potentially long term impact
on public health issues related to prevention, trying to
identify novel ways of preventing and potentially moving someone
from a cluster three to a cluster one or two.
We also know that these clusters, clusters one, two,
and three from a genetic perspective have different portraits.
Cluster three has a very different genetic portrait than clusters one and two.
And we think this genetic portrait is revealing new therapeutic targets
that we can go after for the treatment of patients who are in cluster three.
Finally, I'd like to talk to you about approaches that, we and others
are taking at identifying novel therapeutics, that are going
to be tailored we think to the individual, to the sub-populations
based on the strata or the cluster that they identify with.
And the approach that we've used is shown here.
It's called the translational research clock that's
been recently published by my colleague Dr. Dietchenko.
And the basic principle is to identify a gene either by
hypothesis-driven research or by discovery research
by genome-wide analysis or sequencing of the genome.
But taking an approach where we have either hypothesis
or discovery, identifying through those a genetic
polymorphism of interest and then migrating that
discovery, or that hypothesis-driven genetic
variant through a set of translational studies.
And [COUGH] this shows an example of of a set of
studies that we conducted starting in 2005 and ending in 2010.
A five-year process that lead to target identification and actually
now the development of a new drug, which is much
more rapid than, than what industry currently pursues for target
identification, and bringing a, a drug to a phase one trial.
So [COUGH] in this case I'll talk about
the studies that we've done to identify the
beta two, beta three adrenergic pathway as an
important pathway in a variety of chronic pain conditions.
So it starts out in 2005 where we conducted a number of genetic associations
using a hypothesis-driven approach, looking at initially
the gene that codes for catechol-O-methyl transferase.
So in this study, we looked at a handful of genes.
One of them, the gene that codes for catechol-O-methyl tranferase and what
we were able to show is that genetic polymorphisms in the gene that codes for
COMT were associated with increased or alterations
in human pain perception, and the risk
for the development of chronic pain conditions,
primarily TMD in this, in this study.
And we showed that individuals who harbored
certain genetic polymorphisms in the gene for
COMT if that genetic polymorphism led to low levels of the enzyme COMT, that
these individuals were more pain sensitive and
they were, more likely, about two times,
eight times more likely to develop TMD,
than if they harbored polymorphisms that led to
a lot of the enzyme.
And so this enzyme, as you know, is
involved in breaking down
catecholamines, like norepinephrine, epinephrine, dopamine.
And, as such, low levels of this enzyme are likely to lead
to increased levels of these catacolamines in the blood and in the brain.
And, the elevation of these catacolamines are then likely to activate adrenergic
receptors such as the beta two, beta one, beta three, and dopamine receptors.
And [COUGH] in a series of parallel studies we were able to show
that in the same pathway, the
COMT catecholamine pathway, the polymorphisms in the
gene that codes for the beta
two adrenergic receptor, that these polymorphisms were
also associated with psychological profiles, autonomic profiles
associated with the risk of developing TMD.
So two genes, COMT and beta two, we've identified
as being important players from a genetic perspective to
be associated with the phenotypes associated with TMD, pain
sensitivity, and psychological status and the risk for developing TMD.
So, these association studies pointed towards the likelihood or
the possibility that there is a COMT beta two pathway that's involved in
human pain perception and the risk of developing TMD conditions.
And then to further evaluate that, we moved in 2006, into a series
of studies trying to determine whether these association studies that we
had conducted in fact had any functional relevance to the organism.
Why, the question is were these merely associations, or did
these polymorphisms in some way influence the biology of the
organism to make them more susceptible to the perception of
pain and to make them more susceptible to conditions like TMD?
So in 2006 we began to look at the underlying cellular mechanisms whereby
these polymorphisms could influence the expression of
COMT, this enzyme that's breaking down catacolamines.
And this led to a, a very interesting paper that we published in
2006, which showed that specific polymorphisms in the gene that codes
for catechol-o-mino, o-methyltransferase, that these polymorphisms
could influence the expression of the
protein by influencing the secondary structure
of messenger RNA, the transcripts that
are created by, by the, transcription, process.
And so, the, the transcription of messenger RNA, by these different,
genetic variants of the gene that codes for catecholomino-O-methyltransferase
lead to messenger RNA that had different folding patterns and different free
energy requirements for unfolding and for translation into protein.
So, the individuals who harbored a certain polymorphisms that led
to low levels of COMT, these individuals had secondary structures of
the transcript which were tightly coiled and difficult to unwind, leading
to low expression patterns, low translation of transcript into protein.
And so this is a very novel mechanism by
which you could control protein expression, and low levels of
COMT, as I've just mentioned, can lead to catecholamine burdens
that we think lead to pain sensitivity and psychological distress.
We then wanted to test directly in in vivo models whether we
could modify the COMT pathway and produce
in rodents a human phenotype that mimicked TMD and fibromyalgia.
If our theory is correct about COMT inhibition
and low levels of COMT leading to increased catecholamines,
and in doing so through this novel molecular mechanism
then we should be able to see phenotypic changes.
We should be able to produce a
phenotype in rodents which mimics TMD and fibromyalgia.
So we then undertook a series of in
vivo animal studies, rodent studies in, in a rat.
And showed that when we inhibit the enzyme catechol-amino-methyltransferase,
with different inhibitors, we can in fact produce
a phenotype in rat that mimics, TMD and fibromyalgia that,
following inhibition these animals, become very pain sensitive.
They're sensitive to thermal, they're sensitive
to tactile, they're sensitive to mechanical
stimulation just like a good percentage of our TMD and fibromyalgia patients are.
They also showed changes in locomotor activity, anxiety behaviors,
changes in bowel function, IBS-like phenomenon if you will.
So, we created a phenotype which mimicked in many ways
a complex, persistent, pain condition associated with TMD and fibromyalgia.
And when we then looked at what types of antagonists of the adrenergic system could
rescue or reverse this phenotype, we found that antagonists that block beta two
and beta three adrenergic receptors were able to partially reverse in each case and
totally reverse when combined, the the phenotype
restoring them back to a normal phenotype.
In contrast beta one receptor antagonist, and alpha adrenergic, as well
as dopaminergic receptor antagonists, failed to rescue the phenotype,
suggesting that there is this COMT beta two, beta three
pathway that is important in creating a very, very complex phenotype.
So this then gave us proof of principle that we have identified a, an
important pathway, again starting out with Human Genetic Association
studies, and now having migrated to in vivo rodent studies.
This then lead to a clinical study, a small phase two study
that was conducted by a program by Dr. Inna Tchivileva in our
program where we examined in 40 chronic TMD patients whether
the non-selective beta antagonist propranolol, which
blocks beta two, beta three, as well as beta one receptors,
whether this could ameliorate the pain in, in symptomatic TMD.
Now this is a 40-patient randomized, cross-over design, receiving
either low-dose propranolol, 20 milligrams BID or placebo.
And what we found in this study was in fact for the population of, of 40
individuals, we did see a, an effect of propranolol on the outcome
measure of pain density, which is a, basically a measure of pain severity in
this population where propranolol for the entire
population showed effect on what we call their
pain density or pain index score.
And that one could show greater effect sizes if we stratified by one's genetic
makeup for the gene that codes for catecholamin-O-methyl transferase.
And so that individuals who harbored polymorphisms that lead to low
levels of COMT, they have
greater catecholamine burden, greater catecholamine storms,
and they were, in fact, more responsive to propranolol, compared to
those individuals who had, polymorphisms that had high levels of COMT.
So, based on genetic stratification, we have been able
to identify in an individualized way, a drug therapy
that we can use a gene test to provide prognostic information about
the, the likelihood of response to an agent like propranolol.
And also helps us stratify the population with respect to, to treatment.
So these are still very early days, and this information is,
these findings have to be verified and validated in larger studies.
But it begins to show the power of using genotype and phenotype
to provide stratification schemes to subdivide populations for
diagnostics, for prognostics and therapeutics as well.
So, in this series I've gone through the following vignettes.
We've talked about chronic pain, the scope, nature of the problem.
We've talked about peripheral and central neural mechanisms associated with pain.
We've talked about the molecular pathways that lead to persistent pain.
We've talked about features that contribute to
overlapping or co-morbid conditions in chronic pain states.
And I've just now provided you with a, detailed discussion on some of the
new emerging ways of approaching personalized care for chronic pain.
And so, finally, I'd like to, to, you know,
thank many who have contributed to, to this presentation.
To the NIH for the support they have given us over the years for our investigations.
To UNC Chapel Hill for providing a home and the resources to conduct much of
the work that we've done, and the resources
that were needed to put this presentation together.
Finally I'd like to thank the thousands of patients
and volunteers who have contributed to our understanding of
the nature of these problems and have contributed to
our understanding of these five vignettes that I've just presented.
And finally I'd like to provide you with my contact information
in the event that you need any additional information from me.
Thank you for, thank you very much for your attention.
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