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Drug Metabolism and Variable Drug Responses – Four More Examples

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个性化医疗案例研究

范德堡大学

4.8（190 个评分） | 15K 名学生已注册

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.

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4.8（190 个评分）

5 stars
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MT

Apr 24, 2017

I learned more about pharmacogenomics and its application, which is crucial for my career development as a young graduate in biology who is pursuing health sciences.

CZ

Nov 13, 2016

Thank you! I think I'm going to review/re-take this course at least one more time as the lectures are really interesting and insightful.

从本节课中

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.

HLA-Mediated Immune Reactions (Skin Rash)9:55

Long QT Syndromes, Part 115:49

Long QT Syndromes, Part 218:17

**Inside VUMC: Studying Cardiac Arrhythmias in Cells4:09

A Second Heart Attack a Month After a First15:24

Headache During Venlafaxine (Antidepressant)16:50

Respiratory Arrest After Tonsillectomy10:15

A Bleeding Complication 5 Days After Starting Warfarin21:53

**Inside VUMC: Genotyping1:47

Drug Metabolism and Variable Drug Responses – Four More Examples17:17

教学方

Dan Roden, M.D.
Professor of Medicine and Pharmacology

脚本

[MUSIC]

So, this is the last in a series of modules that have illustrated the problem

of high risk pharmacokinetics both in terms of pro drugs as well as drugs

with narrow therapeutic indexes and one pathway for metabolism.

There's a problem of genetics in those pathways,

there's a problem of drug interactions in those pathways.

And in this particular module we're going to run through them.

When I say run through,

we're going to go through quite quickly four different examples of different drugs

in different therapeutic areas that have the same kind of story.

I don't want to spend all of our modules going over each individual drug because

we have other things to talk about in the broad space of personalized medicine.

So, I'm going to do this by presenting you four cases and

I'm going to read the cases as I do them.

So, here are the four cases.

We'll come to the next ones in a second.

The first case is a six year old girl being treated for ALL who develops

profound bone marrow suppression and life threatening infection.

It turns out the drug that is the culprit in this particular story is

6-Mercaptopurine which is part of the regiment for all children with ALL,

6MP is metabolized by HPRT to an intermediate called TIMP.

Lots of lots of initials in there but

I'd rather do the initials than the full names.

And then through an enzyme called thiopurine methyl transferase or

TPMT, is bio-inactivated.

From the TIMP intermediate,

you can either go through the TPMT pathway or you can go up to 6-thioguanines.

6-thioguanines are the stuff of which

the anti-cancer effect of 6-mercaptopurine is generated.

So, you want to generate the 6-thioguanines,

but too much 6-thioguanines will turn off the bone marrow.

There's also an alternate 6-MP pathway which goes directly from 6-MP down to

6-methyl-mercaptopurine, shown in the middle of this slide.

So, it turns out there are variations in the TPMT gene.

This set of variations were actually discovered in the early 1980's.

The commonest of the variant alleles and none of these are very common is the so

called *3A allele which is actually two, separate snips that are in linkage to this

equilibrium, both of them non synonymous as shown on this cartoon at the top.

And if you look at population frequencies, the population frequency for

the *1/*1 is high, the population frequency for

the intermediate metabolizers is relatively low.

And the *3A/*3A homozygous where the ones who have no TPMT activity is a very,

very, very small set of subjects, probably something like one in 300.

So, one in 300 children exposed to 6-mercaptopurine will fail

to generate TPMT activity, and therefore all the 6-MP shunts to 6-thioguanines and

they have dramatically increased anti-cancer effect and

it also dramatically increased side effects.

So, in cartoon form, this is what it looks like.

If you give everyone the same dose without thinking about the genetics, the systemic

exposure, that's the 6-thioguanines, is highest in the *3A/*3A and

lowest in the wild type, the *1/*1.

And the frequency of toxicity is a function of time

is shown in the middle panel, or in the right hand panel.

Very little toxicity in the extensive metabolizers, a lot of toxicity

in the poor metabolizers, but there are very few of them.

Imagine a situation where in fact what you do is you dosage us.

You know the genetics, and so you reduce the dosage in the *3A/*3A, and

in fact you think, maybe you should increase the dose

a little bit in the *1/*1s, because they're the ones that need more

anti-cancer effect because they're shunting away from the 6-thioguanines.

That way the systemic exposure is roughly the same and

the incidents of toxicity will be reduced.

That's the hope and

there are some studies that show that that's actually what happens.

You can certainly avoid the severe bone marrow toxicity this way.

And the argument is one in 300, is that worth doing?

Some places do it as a routine, some places don't.

Another drug that follows exactly the same pathway as Azathioprine,

widely used in controlled immunologic diseases from

inflammatory bowel disease to a number of settings and liver disease for example.

Azathioprine is actually hydrolyzed to 6-mercaptopurine and

follows the same path way.

So, physicians who use Azathioprine is a matter of course have a choice of not

monitoring at all, monitoring by assessing 6-thioguanine

plasma concentrations and that's done, or knowing up front which patients to be most

worried about by knowing the TPMT genetics, and that's part of the story.

Now, of course it's a little more complicated, but by now you're used to

getting a little more complicated because there is another metabolic pathway for

6MP, and that's through an enzyme called xanthine oxidase to 6-thiouric acid.

And the problem there is that xanthine oxidase is an inhibitable by allopurinol.

Allopurinol, a pretty commonly used drug in some cancer chemotherapy settings,

so not unusual to get allopurinol in these kinds of patients.

Allopurinol a potent inhibitor of xanthine oxidase, and again, you eliminate that

pathway of 6-mercaptopurine elimination, you increase the likelihood that things

flow through the 6-thioguanine pathway, and therefore cause toxicity.

So, a complicated pathway, with multiple implications for

genetics as well as for monitoring plasma concentrations of the 6-thioguanines and

for these two important drugs.

Another story is a 57 year old man being treated for

metastatic colon cancer with a drug called irinotecan develops severe diarrhea.

So again we need to know a little bit about irinotecan disposition here.

Irinotecan is a pro drug.

It's bio-activated by carboxyesterases to a compound called

SN-38 that is active and in the liver SN-38 is eliminated, not by metabolism,

but by conjugation by glucuronides by an enzyme called UGT 1A1.

So UGT1A1 is one of the so called phase two enzymes, and in fact it's the largest

part of that phase two pie that I showed you in one of the earlier lectures.

It turns out there are the variants in the promoter region of UGT1A1,

the common variant is the so called 6TA repeat variant.

The variant is the 7TA repeat variant if you count the number of TAs there's

six on the top one and seven on the bottom.

And so, it turns out that individuals with six repeats,

have normal UGT1A1 expression.

Individuals with seven repeats, have markedly reduced UGT1A1 expression.

Of course, just to make things complicated, this is called UGT1A1*28,

and individuals who are homozygous for the *28 have less UGT1A1.

Now, interestingly, one of the things that UGT1A1 metabolizes normally,

in all of us, is bilirubin.

Bilirubin gets conjugated to glucuronide, and that's well known.

And so individuals who have the UGT1A1*28

allele tend to have higher bilirubin levels because they don't conjugate as

efficiently and that's know as Gilbert's syndrome.

Some small number of normal medical students, I always ask the medical

students, see whether anybody has Gilbert's syndrome, some years somebody

sticks their heads up and other years two people, other years no people.

So, it's relatively common and it's manifest as mild hyperbilirubinemia,

often getting worse with things like fever.

But, that's not the problem with irinotecan.

The problem is that irinotecan undergoes, or

SN-38 undergoes bio-inactiviation by UGT1A1.

So, if you don't have UGT1A1 you'll have much more toxicity, so

much higher SN-38 concentrations and drug toxicity as a consequence.

So again, some people advocate UGT1A1 genetic testing prior to

using your irinotecan and other people say well if they get severe diarrhea I guess

they were a UGT1A1*28 carrier and let me try something else.

So, here's another story.

A 35 year old African American with a kidney transplant has persistently low

concentrations of the anti rejection drug tacrolimus.

So, the problem here is in an enzyme called CYP3A5.

CYP3A5 is a member of the CYP3A superfamily, the commonest one is CYP3A4.

CYP3A5 has been known for a long time, and the common wisdom,

the conventional wisdom is that CYP3A5 activity is absent in most individuals.

Of course, what we really mean by that is absent in most Caucasian individuals,

because those are the ones who were participants in the first studies.

There's a snip, an intronic snip, in the CYP3A5.

I've shown here a cartoon of the genomic structure of CYP3A5.

There are 13 exons and there's a snip in intron 3 that's indicated by the arrow.

Now, if you have a variant, you then

create an alternative splicing event and insert an extra exon out of that intron.

So people with the variant have 14 exons, people without the variant have 13 exons.

When that messenger RNA gets process into protein,

the message it creates either *3 or *1.

*3 is a message that results in a non functional protein.

*1 is a message that results in a functional protein.

Most Caucasians are *3.

*1 is expressed, *3 is not.

These are data again from our own center showing the ancestry

dependence of the *1 or *3 expression as a function and

its relationship to tacrolimus concentration.

So, what I'm showing you here is something called the principal components analysis.

The details are not all that important but

what you can do is analyze large scale genomic data and

get a sense of what ancestry it is the subjects are coming from.

The big cloud on the right of this is a cloud of mostly Caucasians.

The smaller cloud on the left of this plot illustrates where

African American subjects are.

So, you can look at this plot and readily distinguish Caucasians from

African Americans and that becomes important in our study.

Because if we're going to say African Americans do this or Caucasians do that,

we need to be able to define who they are.

We can define that by asking them or

we can define that by genetic criteria like on this slide here.

And when we looked at 446 kidney transplant patients,

tacrolimus concentrations were strongly associated with the *3 allele.

And what's really interesting is the *3 allele is present in 92%

of European Americans, but only 30% of African Americans.

So, what that means is that African Americans have CYP3A5 activity,

European Americans do not, in general.

So, if you're a subject who's taking a drug that's a CYP3A5 substrate, like

tacrolimus, and you're African American, your concentrations will be lower.

Now, there are two ways to manage that.

One is to know the genetics and to adjust the dose appropriately.

The other is measure plasma concentrations.

In either case, something has to be done to adjust the dose

to make sure that patients don't reject their precious kidney transplants.

And so this is a mechanism for ancestry dependent variability in

plasma concentrations and response to an important drug in the therapeutic

armamentarium of physicians caring for patients with kidney transplants.

So, the last case is actually not a genetic case, but

is important conceptionally, so, I really think it's important to put it in here.

An 82 year old women on chronic sotalol therapy develops renal failure,

marked QT interval prolongation.

And perhaps it arrhythmias of the type that I've spoken about before.

So, I showed you this slide in one of the earlier talks and

it illustrates the idea of pre-systemic drug metabolism.

A drug as absorbed, it can be metabolized in the intestine.

The metabolite and the drug go off to the liver, where further drug metabolism and

perhaps excretion into the bile occur.

Then this drug and its metabolite reach the systemic circulation,

where it's eliminated through the kidneys with its metabolite.

Now, Sotalol is a little different.

Sotalol does not undergo metabolism.

So, the cartoon is even easier because there's no metabolites

contaminating this cartoon.

Basically all the sotalol that you ever take goes through the portal circulation,

gets into the systemic circulation and

is excreted in the urine as an unchanged drug.

And we don't know the processes exactly, there may be transporters involved,

but this is the way it works.

So, in a patient who develops renal failure, this is what happens.

There's less excretion and much more drug in the systemic circulation, and

when that happens, toxicity with QT interval prolongation and

perhaps arrhythmias of the type I talked to you about can occur.

So, this is conceptually important and

the reason that it's conceptually important is shown on this slide.

So, this is a summary of the problem of high-risk pharmacokinetics.

We can have drugs that are either pro-drugs on the left, or

parent drug that is bio-inactivated, and we can have the situation in which

they're rapid metabolizers indicated by the red arrows and

we get excess drug effect in that case.

Codeine and clopidogrel are examples of that with different enzymes CYP2C9,

CYP2C19, and CYP2D6.

So, the other problem is the problem of inhibition of those pathways.

So, the pathways can be inhibited by genetic polymorphisms,

they can be inhibited by interactions as I've shown you before.

And now the sotalol example is exactly the same thing but

it's the parent drug on the right being excreted by a single pathway,

in this case, the excretion is through the kidneys.

There's no metabolism involved, but

when that excretory pathway fails, parent drug accumulates and you get toxicity.

So, not only does that apply to drug metabolism,

it applies to excretion of unchanged drug and the multiple examples that are shown.

Here are examples that I've talked about in previous modules where variability and

these kinds of processes lead to variability in effect and

sometimes really severe adverse drug effect.

So, that's the story around high-risk pharmacokinetics, with multiple,

multiple examples.

And each time we use a drug that is known to be an inhibitor of a pathway,

we have to think about whether we're going to alter the affect of a drug

in a patient that we're taking care of.

Each time we start a new drug that has this problem

of single pathway disposition,

we have to think about whether we're going to run into trouble this way.

The other problem is that a number of the drugs that I've talked

about in the past couple of modules have other ways of being monitored, and

there's an argument that says, well, why should I pay attention to the genetics?

Why don't I just pay attention to for example the INR with warfarin or

platelet function testing with clopidogrel?

Or 6-thioguanines concentrations with azathioprine or 6-mercaptopurine or

drug concentrations with tacrolimus?

And I accept those arguments and

my contention is that those are important parts of monitoring patients

if they're validated and very helpful at managing them.

The genetic information doesn't change.

So, I think the genetic information, if it's going to contribute to the way in

which we manage patients, is best used at the beginning of therapy when you

actually have a handle on what it is this patient might do or

might not do based on the genetics that you have in hand.

Then you can start to drag it an appropriate dose and monitor them using

those complementary monitoring techniques that are shown on the right hand column.

So, the major teaching point at the end of these several modules

is that high-risk pharmacokinetics are a problem.

There are ways around that for a number of drugs, including genetic monitoring,

complementary monitoring methods and the question then is,

how good is the evidence that you have the genetics affects the outcome?

Do you have alternate therapies for people with variant genetics?

And what are the outcomes when you deploy those alternate therapies?

Some cases we have great data.

In other cases we have less great data.

[APPLAUSE]

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