pharmacogenomics

Question 1

Applications and main focus areas of
genomic medicine ?

Answer 1

Precision oncology ( Sequencing is by now routine in clinical
oncology)
Genetic disease diagnostics
Pharmacogenomics(Genetic variation impacts drug response , for example ADME genes , MHC genes, Drug receptor genes )
Complex diseases

Question 2

how can Variability data guide diagnostic strategies ?

Answer 2

if with the interogation of little variants we knwo alot about pathogenicity then we know that the rest of the variability is not that important for example

Question 3

what can be the Impact of genetic variants on drug response ?

Answer 3

Altered pharmacokinetics

if the parent compound is active and the metabolite inactive then ultrarapid metabolisers ( incresed functionality of the enzyme) have less of an effect but is the metabolite is active and the parent compound not then we see the opposite .

Altered pharmacodynamics

the binding site of a drug might be affected positively or negatively

there is a spectrume of the posible changes in fanctionality of the protein

Altered immune response

might affect binding to HLA ( HUMAN LEUCOCYTE ANTIGEN) and activation of T cells

Question 4

Preemptive genetic testing on a national level? iS IT AN OPTION ?

Answer 4

• First-line therapy for all patients
• Management of ADRs
  VS
• Universal genetic testing
• First-line therapy to negative patients
• Alternative therapy to positive patients

Question 5

From population genomic data to public health recommendations, WHAT NEEDS TO BE DONE ?

Answer 5

Building a universal model for cost-effectiveness estimation

Preemptive genetic testing on a national level?
* First-line therapy for all patients
* Management of ADRs
VS
* Universal genetic testing
* First-line therapy to negative patients
* Alternative therapy to positive patients
For each country:
* The number of patients needed to test to prevent one ADR case (NNT)
* The number of patients would be unnecessarily denied the first-line drug (NUD)
* The maximum cost difference between first-line and alternative drug that allows preemptive genetic
testing cost-effective (incremental cost threshold, ICT)

Question 6

Approaches to decode the human genetic
variation?

Answer 6

1. PCR-based (candidate SNPs)
2. MS-based (candidate SNPs)
3. Chip-based (candidate SNPs and limited discovery)
4. Sequencing-based (candidate SNPs and discovery)

Question 7

how can we use PCR and what are some advantages

Answer 7

-for example in Allelic discrimination

*Gene expression analysis
* Cancer research
* Drug research
*Disease diagnosis and
management
Viral quantification
*Food testing
* GMO food
* Animal and plant breeding
* Gene copy number

Advantages of qPCR
1. High throughput: Samples & Targets
2. Efficient
3. Quantification abolute (standard curve) and relative (ΔΔCt)
4. Faster

Question 8

Pharmacogenetic profiling paradigms –
chips vs sequencing ?

Answer 8

inexpensive, less info, requires less patients vs expensive, more info, requires more patients

Question 9

Sequencing strategies ?

Answer 9

whole genome sequencing

Whole exome sequencing

Targeted sequencing

Sequencing region :
whole genome
Sequencing Depth:
>30X
Covers everything-
can identify all kinds
of variants including
SNPs, INDELs and SV.

Sequencing region:
whole exome
Sequencing Depth :
>50X ~ 100X
Identify all kinds of
variants including
SNPs, INDELs and SV
in coding region.
Cost effective

Sequencing region:
specific regions
(could be customized)
Sequencing Depth :
>500X
Identify all kinds of
variants including
SNPs, INDELs in
specific regions
Most Cost effective

WES has become very widely used but it has major limitations for the analysis of
common pharmacogenetic variants

Question 10

Conclusions and take-home messages on sequencing

Answer 10

• There are various technical approaches to study pharmacogenetic variation
• Choice of method depends on throughput, “validation-vs-discovery” & costsensitivity
• Genotyping of candidate SNPs allows the probing of established
  associations (however, even for those many are not implemented)
• Extensive missing heritability when only common SNPs are considered
• Sequencing is generally more expensive than PCR or chip-based approaches
  at the per-sample level
• Sequencing allows identification of all variants in the analyzed loci,
  including rare and novel variants
• WES misses various common pharmacogenetic variants of relevance

-Short-read sequencing is prone to misalignments in complex loci, such as
CYP2B6 and CYP2D6, which is solved by long read NGS

Question 11

Definition of Pharmacogenetics/Pharmacogenomics (PGx)

Answer 11

“Pharmacogenetics deals with genetically determined variation in how
individuals respond to drugs. ”

“The study of the variability in drug response because of heredity”

“Pharmacogenomics focuses on the identification of genetic variants that
influence drug effects, typically through alterations in pharmacokinetics or
pharmacodynamics.”

Study How Genetic Variations Affect Drug Response

Pharmacogenomics is an extension of pharmacogenetics, a science
described in terms of five stages of development:
Dr. Werner Kalow
1. some clinical observations predicted genetic alterations of drug response
2. additional case discoveries led to the term “pharmacogenetics”
3. many systemic case studies, and the realization of its wide applicability
4. the recognition of systematic pharmacogenetic differences between human populations
5. most human drug-response differences were multifactorial, caused by many genetic
alterations plus environmental factors

Question 12

Why Pharmacogenomics?

Answer 12

One drug does not fit all
* Only 50-75% of patients respond adequately to
medications
* Abnormal response accounts for around 6% of all
hospitalisations
* Adverse drug reactions (ADRs) cost up to $30 billion/year
in US alone
* Around 32% Drugs were affected by a post-market safety
event
PGx explains 20-30% of abnormal drug response

Question 13

By studying pharmacogenomics, we would like to…

Answer 13

• Understand genetically induced inter-individual variability in drug response
• Improve drug efficacy and minimize adverse drug reactions
• Assist drug development process by
• Guiding the design of candidate drugs for the least variable drug response
• Defining patient groups that can benefit from specific drugs (cancer drugs)
• Identifying alternative drugs for patients experiencing advese drug reactions when
  taking first-line treatments
• Identifying novel drug targets (PCSK9)

Question 14

Pharmacogenes ?

Answer 14

• Pharmacokinetic (PK) genes – genes related to drug absorption, distribution,
  metabolism and excretion (ADME)
  (what body does to the drug)
• Pharmacodynamic (PD) genes – genes encode drug targets
  (what drug does to the body)
• Other genes related to off-target effects

Question 15

Pharmacokinetic (PK) genes?

Answer 15

• Phase I
  E.g., Cytochrome P450 (CYP)
  enzymes, others (DPYD, CES1 etc.)
• Phase II
  E.g., UDP-glucuronosyltransferase
  (UGT) family, glutathione Stransferase
  (GST), sulfotransferase
  (SULT) family
• Transporters
  E.g., Solute carrier (SLC) family, ATPbinding
  cassette (ABC) family

Clinically important PK genes
* CYP gene family: involved in >90% of drug metabolism, highly relevant to adverse drug
reactions
* 57 CYP genes in the human genome, 8 of the encoded enzymes cover the majority of
drug metabolism

Question 16

conservation of CYP genes ?

Answer 16

EXAMPLE
Duplicated CYP2D6 can increase
capability for detoxification of
alkaloids in plants
Selection of CYP2D6 duplication
carriers in Africa

Question 17

Different types of genetic variations ?

Answer 17

Single Nucleotide Polymorphism (SNPs)/ Single Nucleotide variations (SNVs)
- A>T, C>G
* Small insertion/deletion (indel)
- A>AT, C>CCTTTTT, AT>A, ATATAT>A
* Structural variations (SVs)
- genomic deletions, duplications, insertions, inversions and other complex
rearrangements that affect >50bp
* Based on genomic location: exonic/intronic variants, regulatory variants,
intergenic variants
* Based on consequence: coding/non-coding variants; missense variants,
synonymous variants, splicing variants

Question 18

what is Important to know about genetic variations ?

Answer 18

• Reference genome/assembly (DNA sequence assembled from a number of
  individual donors)
• GRCh38/hg38, released by Genome Reference Consortium in 2017
• GRCh37/hg19, released in 2009
• RS number/RSID (Reference SNP, a unique label to identify a specific SNP)
• rsxxxxxx

Question 19

Allele frequency
how to calculate?

Answer 19

F1 = 6/10 = 0.6 (60%)
F2 = 4/10 = 0.4 (40%)

1/1
1/2
2/2
1/1
1/2

F1 + F2 = 1

or

1/1
2/3
2/2
3/3
1/2

F1 = 3/10 = 0.3 (30%)
F2 = 4/10 = 0.4 (40%)
F*3 = 3/10 = 0.3 (30%)

F1 + F2 + F*3=1

Question 20

Will the frequency of CYP2D6*4,
one of the most well-studied
CYP2D6 allele, differ between
Europeans and Asians?

Answer 20

Yes. Europeans (20%) and Asians
(2%).
* Genetic isolation

Question 21

Will the frequency of CYP2D6*4,
one of the most well-studied
CYP2D6 allele, differ between East
Asians and South Asians?

Answer 21

Yes. East Asians (0.3%) and South
Asians (10.4%).
* Genetic isolation?

Question 22

Will the frequency of CYP2D6*4,
one of the most well-studied
CYP2D6 allele, differ between
Swedish and Bulgarian?

Answer 22

No . Swedish (19.2%) and Bulgarian
(19.3%).
* Same ethnicity

Question 23

Will the frequency of CYP2D6*4,
one of the most well-studied
CYP2D6 allele, differ between
Swedish and Finnish?

Answer 23

Yes. Swedish (19.2%) and Finnish
(10%).
* Genetic isolation

Question 24

For some countries, calculating the
national frequency could be
complicated. What are these
countries?

Answer 24

The United States, Brazil,
Singapore
* Population admixture

Question 25

Which ethnicity has the most
complex genetic composition (high
numbers and high frequency of
genetic variants)?

Answer 25

• African
• Human origin?

Question 26

Which ethnicity/population has the
highest numbers of novel genetic
variants that are not observed in
other ethnicities/populations ?

Answer 26

• Ashkenazi Jews
• Culture isolation, population
  bottleneck (~ 350 individuals

Question 27

what do you know about CYP genetic variants ?

Answer 27

• Pharmacokinetic (PK) genes, particularly CYPs, are polymorphic and harbor
  many genetic variants.

Around 8 CYP genes are clinically most important with CYP2D6 being most
polymorphic.

Star (*) alleles are used to name well-characterized (mostly common) CYP
variants.

Allele frequency of CYP alleles differ substantially across ethnicities and
populations.

Question 28

Why are CYP star alleles important?

Answer 28

• Common
• Have impact on activity of encoding enzymes
• Decrease enzyme function (deceased function allele)
• Abolish enzyme function (Loss-of-function allele)
  -Increase enzyme function (Gain-of-function allele)

Question 29

enzyme Function alleles and drug exposure, what is it dependent on ?

Answer 29

it is dependent on where the enzyme acts, the produg to metabilise it into the active compound or to the drug deactivating it

general dogma though is :
Changes in allele function - Changes in enzyme activity - Changes in drug
exposure

Question 30

PharmVar database

Answer 30

-Data source for the categorical function of star alleles
Star allele functions are well-characterized and can be looked up in PharmVar

PharmVar, short for Pharmacogene Variation Consortium, is a global initiative focused on cataloging and standardizing genetic variations within genes that encode proteins involved in drug metabolism and response. These variations can influence an individual’s response to pharmaceutical drugs, affecting factors such as drug efficacy and potential adverse reactions.

The PharmVar database provides curated information on pharmacogenetic variations, including their frequencies in different populations, clinical significance, and recommendations for drug dosing or selection based on an individual’s genetic profile. This information is valuable for healthcare professionals in personalized medicine, allowing them to tailor drug treatments to individual patients based on their genetic makeup, ultimately leading to better therapeutic outcomes and reduced risks of adverse drug reactions.

Question 31

what is The Clinical Pharmacogenetics Implementation Consortium
(CPIC) ?

Answer 31

CPIC (and others) publishes guidelines to translate genotypes into metabolizer
phenotypes and provide therapeutic recommendations.

*A group of international pharmacogeneticists who are
interested in facilitating use of pharmacogenetic tests
for patient care.
* Curates pharmacogenetic data from the literature.
- Allele definition
-Allele function
- Allele frequency
-Evidence linking Genotype to Phenotype
* Publishes detailed gene/drug clinical practice
guidelines
- From variant function to allele function to protein
function to patient response to dose/drug
recommendation

Allele function and activity score,
Translate an individual’s genotype into phenotype,
From metabolizer phenotype to dose recommendations

Question 32

what are the possible activity scores for a metabolier of one drug ?

Answer 32

0-2 but it can be more than 2 for ultrarapid metabolisers

Ultrarapid metabolizers (UM),Rapid metabolizers (RM) =Duplicated allele or increase function allele

Normal metabolizers (NM)

Intermediate metabolizers (IM)= Decreased function allele or LOF allele

Poor metabolizers (PM)=Two LOF alleles

Question 33

Other resources for genotype-phenotype translation

Answer 33

• The Dutch Pharmacogenetics Working Group (DPWG)
• The Canadian Pharmacogenomics Network for Drug Safety (CPNDS)
• The French National Network of Pharmacogenetics (RNPGx)
• Drug labels
• FDA (Table of Pharmacogenetic Associations; Table of Pharmacogenomic
  Biomarkers in Drug Labeling)
• EMA
• Pharmaceuticals and Medical Devices Agency, Japan (PMDA)
• Swiss Agency of Therapeutic Products (Swissmedic)
• Health Canada (Santé Canada) (HCSC)

Question 34

FDA_Table of Pharmacogenetic Associations ?

Answer 34

Section 1: Pharmacogenetic Associations for
which the Data Support Therapeutic Management
Recommendations

e.g abacavir ( maybe the only one )

Section 2: Pharmacogenetic Associations for
which the Data Indicate a Potential Impact on
Safety or Response
e.g codein

Section 3: Pharmacogenetic Associations for
which the Data Demonstrate a Potential Impact on
Pharmacokinetic Properties Only
e.g. amitriptyine

Question 35

make a Comparison between drug labels and guideline
recommendations

Why discrepent?

Answer 35

one might say that knowing the PGx an action should be taken while the other might only be recomending or not saying anything

CPIC and DPWG
- >20% differences in therapeutic recommendations were identified (Bank PCD. et al.
Clin Pharmacol Ther. 2018)
* DPWG, CPIC, CPNDS, and RNPGx
- Discordances in fluoropyrimidines, irinotecan, clopidogrel, warfarin and statins
(Abdullah-Koolmees H. et al. Front Pharmacol. 2021)
* FDA and EMA
- Only 54% overlap in drug-gene interactions (Ingelman-Sundberg M. Pharmacol Res.
2020)
* FDA, EMA, CPIC and DPWG
- Only 18% concordance Source of information considered
- Clinical study/Preclinical study/Case report
* Time point when the evidence was collected
* Therapeutic recommendations vary between countries
* Update of the gene-drug information
- English version of DPWG recommendations hasn’t been updated since 2011
* Activity score assignment

Question 36

PharmGKB what is it ?

Answer 36

PharmGKB is a comprehensive resource for pharmacogenomic information.

• PharmGKB (The Pharmacogenomics Knowledgebase) collects, curates and
  disseminates knowledge about clinically actionable gene-drug associations and
  genotype-phenotype relationships.

it give you info form all databases , as it may vary

it can also show you the pathways

you can Browse Drugs with Variant Annotations

Question 37

Well-established pharmacognomic biomarkers can be related to …

Answer 37

Associated with Adverse Drug Reactions

Modulate Drug Efficacy

Question 38

Summarize the allele frequency-related databases

Answer 38

• Allele frequency
• gnomAD
• dbSNP
• The literature
• SNP information (genomic coordinate, variant type, nucleotide substitution)
• dbSNP

Question 39

User
gnomAD ns dbSNP

Answer 39

In summary, while both gnomAD and dbSNP contain information about genetic variants in humans, gnomAD focuses on allele frequency data from large-scale sequencing studies, particularly rare variants, while dbSNP is a comprehensive database that catalogs various types of genetic variants and provides unique identifiers for each variant.

Question 40

how do I go From allele frequency to diplotype frequency ?

Answer 40

• Allele: *1, *2, *3…
• Diplotype: 1/1, 1/2, 2/3…
• Assume in a cohort people are either wild-type or CYP2C19*2 carriers
• Allele frequency: CYP2C19*2 = 0.2
• Diplotype frequency
  CYP2C192/2 = ?
  CYP2C191/1 = ?
  CYP2C191/2 = ?

for hoozygous we just do: 0,2^2 for example but for heterozygus we have to do: 2* 0,2*0,8

Question 41

how do I go From allele frequency to metabolizer phenotype frequency?

Answer 41

If the numbers dont add up to 1 then the *1 is missing

add all the same variant functions together

multiply and add together all the possible allele combinations that give you every functional group

Question 42

where does the Substantial pharmacogenetic variability come from ?

Answer 42

• Pharmacogenes are polymorphic
• Star alleles
• Inter-population differences in star allele frequencies
• Consequent metabolizer phenotypes

Question 43

Approaches identifying genotype-phenotype relationship

Answer 43

Forward genetics Phenotype to Genotype
Reverse genetics the opposite

Question 44

First generation sequencing (Sanger sequencing) details and uses ?

Answer 44

• Read length: 400 to 1200 bp
• High accuracy
• Easy to perform in a common genetic laboratory
• Low-throughput
• Time-consuming
• Trained staff required
• Still used today in small scale project or validate result from more advance
  sequencing technologies

Question 45

Second generation sequencing (Massive parallel sequencing,
next-generation sequencing, short-read sequencing)

Answer 45

• Defined by methods in which millions of DNA templates are sequenced
  spontaneously in a single reaction
• Emerged around 1995 and commercially available since 2005
• Principle (Video)
  -DNA fragmentation
  -Amplification of DNA fragment by PCR
• Short-read sequencing
• Short reads assembly
• Read length: 50 to 600 bp
• High-throughput, cost-effective
• Automation
• Can be very accurate
• Difficult to analyze complex genomic loci (repetitive regions, structure variants)
• Widely-used in industry and academia

Question 46

Third generation sequencing (long-read sequencing)

Answer 46

• Defined by methods that can produce substantially longer reads than second
  generation sequencing
• Developed after 2011
• Two long-read sequencing platforms
• Nanopore sequencing by Oxford Nanopore Technology
• Single molecule real time (SMRT) sequencing by Pacific Biosciences (PacBio)
• Read length: 5,000 to 30,000 bp
• No amplification bias from PCR
• Suitable to analyze complex genomic loci
• Expensive
• Much less downstream bioinformatic tools coupled
• Getting more used in detecting genetic variations in disease genes and complex
  pharmacogenes, e.g. CYP2D6

Question 47

Sequencing a human genome cost
?

Answer 47

Before: 3 billion USD, 13 years
Now: 500 USD, half a day

Question 48

Sequencing projects across the globe,Sequencing projects across the globe

what is true about those

Answer 48

multiple around the world , in many different palces

Question 49

Sequencing reveals large number of rare genetic variants , what do we know on this ?

Answer 49

• 2,504 human genomes (1KGP, 2015)
  88M variants, 76M variants with frequency < 5%, 64M variants with frequency < 0.5%
• 76,156 human genomes (gnomAD v3, 2023)
  > 644M short nuclear variants, >390M variants with frequency < 0.1%
• Pharmacogenomic variations

rare variants are also important

CYP2D6 has the most variants

The majority of sequencing identified variants have low frequencies. gnomAD is
a good resource to analyze these variants.

Question 50

From genotype to phenotype
* Are star alleles sufficient to inform metabolizer phenotype?

Answer 50

No cause we see that the phenotypic spectrum is overlapping between different diplotypes
* Are star alleles sufficient to inform metabolizer phenotype?
* No. Something is missing in genetic factors that can explain the variability in
drug response (missing heritability).
* What is missing?

20-30%
genetic factors

~50% known variants

~50% missing
heritability :
rare variants

log read sequencing of complex loci

haplotypes of specific CYP genes
Two variants in the same allele – we call that haplotype

specific polimorphic gene regulation

Question 51

SIFT (Sorts Intolerant From Tolerant substitutions) how does it work ?

Answer 51

• Searches for similar amino acid sequences
• Chooses closely related sequences that may share similar function
• Obtains the multiple alignment of these chosen sequences
• Calculates normalized probabilities for all possible substitutions at each position
  from the alignment
  Normalized probabilities < cutoff : Deleterious
  Normalized probabilities >= cutoff : Tolerated

Here’s how SIFT works:

Sequence Alignment: SIFT starts by aligning protein sequences from different species that are evolutionarily related to the protein of interest. This alignment helps identify conserved regions and residues within the protein.

Calculation of Conservation Scores: SIFT calculates a conservation score for each amino acid residue in the protein based on the degree of conservation observed in the sequence alignment. Highly conserved residues are assigned higher conservation scores, indicating that changes to these residues are less likely to be tolerated without affecting protein function.

Substitution Prediction: When presented with a query amino acid substitution (mutation), SIFT evaluates the conservation score of the wild-type (original) amino acid residue and predicts the impact of the substitution based on this score. If the substitution involves a highly conserved residue (high conservation score), SIFT predicts that it is likely to be deleterious or damaging to protein function. Conversely, if the substitution involves a less conserved residue (low conservation score), SIFT predicts that it is more likely to be tolerated without significant effects on protein function.

Threshold Determination: SIFT uses a predetermined threshold (typically 0.05 or 0.1) to classify substitutions as tolerated or intolerant. Substitutions with a SIFT score below the threshold are predicted to be deleterious (intolerant), while substitutions with a score above the threshold are predicted to be tolerated (tolerant).

Output: The output of SIFT typically includes the predicted impact of the substitution (tolerated or deleterious) along with a numerical SIFT score indicating the degree of conservation at the affected residue.

Question 52

what is Polyphen-2 (Polymorphism Phenotyping V2)?

Answer 52

A method and server for predicting damaging missense mutations

Based on a machine learning method (Naive Bayes
classifier)
Two training datasets:
* HumDiv, 3,155 damaging variants, 6,321 nondamaging
variants
* HumVar, 13,032 damaging variants, 8,946 nondamaging
variants

Question 53

what is CADD (Combined Annotation–Dependent Depletion)?

Answer 53

A general framework for estimating the relative
pathogenicity of human genetic variants

• Machine-learning method to train 14.7 million highfrequency
  human-derived variants and 14.7 million
  simulated variants
• Integrating many diverse annotations into a single
  score for each variant (higher score à more
  deleterious)

Question 54

what is ANNOVAR?

Answer 54

Generate missense variant predictions from a collection of
tools

Question 55

VEP
(Ensembl Variant Effect Predictor)

Answer 55

Generate predictions from a collection of tools

Question 56

Are General variant predictors suitable for assessing functions
of pharmacogenomic variants ?

Answer 56

NO

Sequence conservation
Allele frequency
Disease-related features

are not enough

to find

Disease causing
variants

around 75 % prediction accuracy for CADD

Question 57

Computational tools to predict functional consequences of
pharmacogenomic variants

Answer 57

better results for ADME optimised

• DPYD gene
• DPYD-Varifier (variant function
  prediction)
• CYP2D6 gene
  -Enzyme activity prediction based
  on sequences (long-read)
• Hubble.2D6 (haplotype function
  prediction)
• Few other tools

Question 58

Challenges for computational prediction

Answer 58

• Overfitting: overlap between training variants and testing variants
• Lack of training data (for predictors designed for specific type of variants, e.g.,
  PGx variants)
• Method selection

Question 59

Genotype to phenotype using computational prediction ?

Answer 59

through Aggregated
frequency and then calculating and adding all the probabilities of every diffferent diplotype that is in this cagegory e.g. intermidiate metaboliser

Question 60

what are the Pharmacodynamic (PD) genes ?

Answer 60

• PD genes encode drug targets that can trigger therapeutic response upon drug
  binding
• The number of drug targets are not well-defined.

Question 61

Example of clinically important variations in PD genes:

Answer 61

• Vitamin K epoxide reductase
  (VKOR, encoded by VKORC1)
  is the target of warfarin
• VKORC1 -1639G>A (rs9923231, G3673A)
• Variant carriers have decreased activity of VKOR, thus are more
  sensitive to warfarin and require lower dose
• MAF = 32.6%, dominant in East Asians

CFTR
* CFTR (cystic fibrosis transmembrane
conductance regulator) encodes a chloride
channel and play important role in ion and water
secretion and absorption in epithelial tissues.

• Abnormal CFTR function is the cause of
  cystic fibrosis (CF), a genetic disorder
  that induce sticky and thick mucus
  secretion and cause difficulty in
  breathing and frequent inflammation.
• CF occurs in 1 in 2,500 to 3,500 white
  newborns
• Five classes of CFTR
  mutation and
  corresponding therapies
  different functionalities of the protein
  e.g. missfolded , shortened etc

Question 62

Variants in PD genes can guide drug development
* The PCSK9 case , what happened ?

Answer 62

Two French families with an autosomal
dominant form of familial
hypercholesterolemia (FH)
“gain-of-function”
mutations identified in PCSK9 in
these and other FH patients

Development of PCSK9 inhibitor

Question 63

what else can genetic variants affect ?

Answer 63

1)Genetic variants in drug-target binding sites
* GPCRs
* 108 GPCRs targeted by 475 (34%)
FDA-approved drugs

• Natural occurring variants in GPCR binding site impact drug response and bias
  signaling

1 in 6 individuals carries at least one missense variant in the binding sites

• Binding site variants can impact drug response and be used for drug
  development

2) Drug off-target effect: HLA genes related hypersensitivity
reactions

• HLA (Human Leukocyte Antigen)
  encodes major histocompatibility
  complex (MHC)
• MHC molecules have peptide
  binding grooves

binding sites affected:

HLA-B*57:01 and abacavir induced abacavir hypersensitivity
syndrome

HLA-B*15:02 and carbamazepine induced Stevens-Johnson
syndrome/toxic epidermal necrolysis (SJS/TEN)

• Genetic variations in drug targets are important determinants of drug response
• Genetic variations in HLA genes can trigger drug-induced hypersensitivity
  reaction
• HLA-B*57:01 is a strong risk allele for abacavir hypersensitivity syndrome

Question 64

How much impact does pharmacogenomic
testing currently have in clinical practice?

Answer 64

Overall implementation of pharmacogenomic
labels however remains poor particularly for
CYP genes
In total there are 25 guidelines with actionable recommendation affecting 140
medications.
Of these, only 2-3 are implemented in clinical routine
These are testing of:
HLA-B57:01 and abacavir
DPYD and fluoropyrimidines
HLA-B15:02 and carbamazepine in patients of Asian ethnicity

Abacavir hypersensitivity
Manifests as
Morbilliform/maculopapular rash
Fever (often precedes rash)
Myalgias, fatigue
Mucosal ulceration
More rarely (<5%) also as hepatitis and nephritis

Fluoropyrimidine toxicity
Up to 30% of patients have severe treatment-related toxicity, including diarrhea, mucositis,
myelosuppression and hand foot syndrome.

Anti-cancer drugs, such as fluorouracil and capecitabine
Prospective trial showed that genotype-guided dose reduction was beneficial

HLA-B*15:02 and carbamazepine-induced
Steven-Johnson syndrome (SJS)
SJS when <30% of skin surface area is affected
Toxic epidermal necrolysis (TEN) when >30% are affected

Very severe skin reaction
Zhou et al., CPT 2020
Mortality rates: 2-15% for SJS and 25% for TEN

Question 65

Why is implementation of pharmacogenomic
biomarkers not more widespread?

Answer 65

Overall implementation of pharmacogenomic
labels however remains poor particularly for
CYP genes
Contributing factors:
* Lack of reproducibility (underpowered studies dilute the literature)
* Large variability within genotype groups; effects are stochastic rather than deterministic

Many outliers in the studies make the results less deterministic

• TDM instead of PGx
• Strong effects on pharmacokinetics, weak effects on clinical outcomes/ADRs
• Unclear added value (lack of clinical trials, alternative medications; e.g. DOACs)

Pharmacogenetic expert groups are dominated by pharmacists and pharmacogeneticists
but lack involvement of physicians

Poor congruence between “expert”
recommendations and regulatory guidance
(SmPCs)

• (Lack of pharmacogenetic education)
• Practical limitations in clinical routine
• Lack of cost and reimbursement considerations

Question 66

UPGx – PREPARE trial

Answer 66

Multi-center, multi-gene, multidrug,
multi-ethnic, and multihealthcare
system trial.

The PREPARE trial involves recruiting patients from primary care practices and providing pharmacogenomic testing to guide medication selection and dosing for selected drugs.

The PREPARE trial involves recruiting patients from primary care practices and providing pharmacogenomic testing to guide medication selection and dosing for selected drugs.

Question 67

Overall implementation of pharmacogenomic
labels however remains poor particularly for
CYP genes , possible mitigation ?

Answer 67

Incorporation of rare variability to increase the predictive power

• Clinical trials to evaluate the added value
• Fostering of inter-disciplinarity
• Increased cost consideration and feasibility trials in primary care

Question 68

For CYPs, the most promising PHARMACOGENETIC associations are:

Answer 68

1. CYP2C19 for clopidogrel and escitalopram
2. CYP2D6 for risperidone and tamoxifen
3. CYP2C9 for warfarin