Learn how advances in biomedicine hold the potential to revolutionize drug development, drug treatments, and disease prevention: where are we now, and what does the future hold? This course will present short primers in genetics and mechanisms underlying variability in drug responses. A series of case studies will be used to illustrate principles of how genetics are being brought to bear on refining diagnoses and on personalizing treatment in rare and common diseases. The ethical and operational issues around how to implement large scale genomic sequencing in clinical practice will be addressed. After completing this course, learners will understand 1. The ways in which genetic variants can contribute to human disease susceptibility 2. How to choose among drug therapies based on genetic factors 3. That the functional consequences of the vast majority of genetic variants discovered by modern sequencing are unknown. This course is targeted primarily at physicians 5+ years out of training. Other healthcare providers, medical/health sciences students, and members of the public may also be interested. Course launches January 15, 2016. * The information presented in “Case Studies in Personalized Medicine” is offered for educational and informational purposes only, and should not be construed as personal medical advice. If you have questions or concerns about a medical matter, please consult your doctor or other professional healthcare provider.
Muscle Pains During Statin Therapy (Myopathy)
Loading...
來自 Vanderbilt University 的課程
Case Studies in Personalized Medicine
132 個評分
從本節課中
UNIT 3: CASE STUDIES IN PERSONALIZED MEDICINE, PART 1
In Module 5 we will begin to discuss specific cases as these apply to personalized medicine. We will first look very closely at a case of familial hypercholesterolemia as we investigate how we use genomic medicine to move from a rare disease to a common medication, using genomics to find new drug targets, and a discussion of the side effects of statin therapy. In Module 6 we will look at a collection of "high risk pharmacogenetics"cases that illustrate adverse reactions due to drug metabolism and variable drug responses.
與講師見面
Dan Roden, M.D.Professor of Medicine and Pharmacology
Assistant Vice Chancellor for Personalized Medicine
[MUSIC]
>> In this module, we're going to continue exploring the story of the 42-year
old man who has a very high LD cholesterol due to heterozygous familial
hypercholesterolemia detected on a routine physical examination and
clearly has a very strong family history of high cholesterol and coronary disease.
He started on an HMG-CoA reductase inhibitor simvastatin and
the does is increased to 80 milligrams per day.
I will say that we don't that kind of does anymore, but
at the time this story happened that that's what happened.
He reports muscle aches and his CK, an index of potential
myopathy due to the statin is elevated at 510.
So the question that you have to ask yourself is the physician taking care
of this patient is what are the risk factors for stain related myopathy?
Statin related myopathy is one of the commoner symptoms during treatment
with these drugs, depending on who you talk to the incidents is very, very,
very, very small and that's one end of the spectrum that includes patients
who have rhabdomyolysis and can die of kidney failure during an episode.
All the way through to patients that have mild muscle aches that come and
go and that may or may not be related to the statin, but
more often than not seem to be.
So here are the risk factors, elderly patients and
patients who are women appear to have higher risks.
There's no question that certain statins do this more than others.
Pravastatin is at one end of the spectrum and seems to do this relatively rarely.
There is the argument that says that prevastatin is actually a less potent
statin agent and that might be part of the explanation and part of the explanation
might be pharmacokinetics as I'll come to in a moment.
There was one statin called cerivastatin that was actually withdrawn
from the market, because of a much higher incidence of serious
myopathy than compared to other statins.
One of the most important factors that determines statin related myopathy is drug
interactions and those drug interactions target the drug metabolizing enzymes,
they cytochrome 450s or the CYPs.
The glucuronyl transferases that may be important for fibrated statin myopathy.
Fibrates are notorious for increasing the risk for myopathy during stratin
treatment, although the pharmacokinetics mechanism and
it appears to be a pharmacokinetics mechanism is not very well worked out.
It's probably not through CYPs, but maybe through other enzymes that are responsible
for statin metabolism and then there is a story around transporter molecules and
the transporter protein is OATP1B1.
The gene that encodes that protein, as I will show you in a moment,
is called SLCO1B1.
And genetic variants in these pathways or another pathways may contribute to
statin-related myopathy as I will show you in a moment.
So, it's important to recognize that the individual statin drugs
are metabolized through different pathways.
We'll come back to that over and over through subsequent modules, but
here is a short list of the metabolic pathways.
The specific drugs and
the major inhibitors of metabolism I study arrhythmia.
So of course, amiodarone is at the top of the list for every drug metabolizing
pathway, because it's a potent inhibitor of many, many pathways.
3A4 is the most common cytochrome that is involved in drug metabolism and
there are a number of important inhibitors that are commonly used in patients
with coronary artery disease.
So diltazem, for example and then there's the problem of grape fruit juice.
It turns out grape fruit juice, not other kinds of citrus juices,
not orange juice, has in it, inhibitors of CYP3A4.
So there are occasional patients who will develop muscle aches when they receive
grapefruit juice in combination with statin drugs that use CYP3A4 and
the other drugs that are listed on this slide.
So, it's important when you're taking care of a patient with statins to be aware of
the possibility of drug interactions.
And again, the fibrates are probably the most important,
because they're often used in combination in terms of lipid lowering.
The pathway is not really all that well worked out, but
is presumably a pharmacokinetic pathway.
This is an illustration from the site called PharmGKB
that includes a number of drug action pathways,
drug metabolism and pharmacodynamic pathways.
And you can see here, there's a number of statin drugs that are taken up to
an intestinal cell that are metabolized to act and metabolize transit to the liver
where they are taken up to the liver undergo further metabolism and
then excretion into the bile through transporter molecules.
So the most important transporter molecule that I want to talk about in this
particular story is SLCO1B1, which is the uptake transporter for
a number of statins into the hepatic site from the portal circulation.
Notice again, that there are a number of statins and
they don't use all of these pathways, but some of them use some of these pathways.
So about ten years ago, people started to get interested in
the idea that sequence variation in transporter molecules
might be an important determinant of outcome of drug therapy.
This is a very small study from Finland where they studied 31 normal
volunteers and looked at the plasma concentrations of simvastatin and
simvastatin acid as a function of time after a single 40-milligram dose of drug.
Now simvastatin turns out to be inactive and
requires metabolism to its acid metabolite to lower LDL cholesterol.
Some statins are like that, some statins are not.
Simvastatin requires bioactivation, atorvastatin,
another very widely used statin drug does not.
And what these investigators were interested in is the effect
of a known relatively common polymorphism in the SLCO1B1 gene and
it affects on acid and simvastatin concentrations.
And you could see that subjects with the CC genotype, which is thought to be
a loss of function genotype had much higher concentration of the acid Compared
to subjects with the TT genotype and the people with the CT genotype.
That's the genotype that has one C allele and
one T allele are intermediate, but mostly closer to the TT variant.
So that was known in the 2004, 2005, 2006 area.
And then in 2008, a group of investigators studying a very, very,
very large cohort of subjects exposed to either 20 milligrams,
a relatively low dose of the simvastatin.
Or 80 milligrams, a relatively high dose of simvastatin ask the question
are there genetic predictors of myopathy.
So one of the major take home messages of this slide is not the GWAS,
not the Manhattan plot on the bottom, but
the data that are shown in the text at the top.
They had almost a hundred cases of real or incipient myopathy.
Their definitions for those real myopathies is a high CK and muscle pain.
Incipient is high CK without muscle pains yet.
Out of the 6,000 patients receiving 80 milligrams a day.
They had a total of 8 cases, 2 definite and
6 incipient among patients receiving 20 milligrams a day.
That illustrates the risk for myopathy is clearly dose related and
that's one of the reasons that the FDA has recommended that patients no longer get
80 milligrams of simvastatin.
They ended up with 96 cases that they analyzed and they chose 96 controls.
So again, a very, very small genome wide association study.
Some of the studies I've shown you have had tens of thousands,
occasionally hundreds of thousands of subjects to find a signal.
Here's a study that has less than 100 cases, less than 100 controls and
find a signal at genome-y significance.
That signal is in an entronic snip in SLC1B1, but
it turns out to be in perfect linkage to equilibrium
with the CCTT story that I just told you before and
that snip encodes a non-synonymous change availing to alanine at position 174.
So here's the risk for developing simvastatin related myopathy
as a function of time after starting 80 milligrams a day.
And you can see that if you carry the CC genotype,
that's 2.1% of the population, your odds ratio is almost 18 and
your risk of getting the myopathy is almost 20% over 5 years.
Whereas if we carry the common genotype, the TT genotype, 73% of the population.
These are all Caucasians I should add, 73% of the population your risk is
vanishingly small and the CT genotype has a modestly increase risk.
Of course there's always the idea that with a modestly increased risk,
if you take a fibrate on top of it, your risk will increase.
If you increase the dose, your risk will increase.
So this genetics set the stage for other kinds of drug interactions, as well.
So this is an interesting way of going from a known pharmacokinetics
to a GWAS that actually has the same pharmacokinetics variant and
confirms that it plays a role In statin-related myopathy.
This is another study that I was of two minds whether to show,
because it's relatively complicated,
but statin-induced myopathy is more complicated than a single SNP.
That single SNP predicts with an odds ratio that's pretty high, but
this is a different approach.
And I thought I would show this study mainly to highlight for
you the idea that it's not always about genomes,
but there are other ways in which we can use high-dimensional data to
try to understand what the pathways are that lead to myopathy.
So what these investigators did was they started with a group of patients who had
been participants in a study of statin efficacy.
They had cells from those patients, they expose those cells to simvastatin and
then ask the question, what gene has increased expression during
simvastatin exposure, but not during not simvastation exposure?
They look for genes that had highly deferentially expressed,
path expression patterns.
They found those regions and then they ask the question.
Do SNPs in or around those genes predict statin related myopothy and
they did further biochemical studies, including knocking down the expression of
those genes in the cell lines that they had from those patients.
So the nice thing about this study is not only do you do genomics, but
you do expression at the messenger RNA level to understand a new signal
around a statin-related myopathy.
Now whether GATM variance will ever come to clinical practice remains to
be determined, but this is an approach that actually identifies a new way
of getting new genes that might be involved in important human phenotypes.
The SLCO1B1 story has been taken up by a number of other investigators.
This is a study from Duke.
Relatively a small number of subjects around 500 who received pravastatin,
atorvastatin or simvastatin and
then the question was not that they get myopathy, but do they continue the drug?
If they stop the drug for whatever reason, they were discontinuers.
If they continue the drug, they were continuers.
The discontinuers fall into a group called composite adverse events and
you can see that without worrying about whether it was myopathy or something else,
more people stopped simvastatin if they had the risk allele compared to not.
Less so with the statin again, pravastatin, there's no genetic signal.
But then again, there's not much myopathy with pravastatin and
you have to ask yourself why those patients stopped statin.
And the bottom panel, just shows that the effect of gender on this adverse effect.
And some people say, the gender effect is merely, because we give women higher
doses and they have smaller body habitus, but these datas suggest that there may be
an additional gender effect beyond simply body size.
So what does this all have to do with personalizing medicine?
This is one example of a genetic variant that is
relatively common that may modulate risk for an adverse drug effect.
So this raises the idea that if you knew someone was a CC genotype,
would you prescribe simvastatin or would you prescribe an alternate statin?
And the way in which we think about those kinds of questions,
the way in which we deliver that kind of information to physicians and
to patients is something that the field of personalized medicine is grappling with.
And clearly, we all have a vision that in the future,
we'll have that information and how to deliver it and how to evaluate and
how to use it in clinical practice will be an important step.
So this is one step in that long journey.
[MUSIC]
>> [APPLAUSE]
