number of probes. Sequencing, by contrast, is thought to have less bias, although the sequencing
bias of different sequencing technologies is not yet fully understood.
Example: ChIP-seq was used to compare conservation of TFs in the forebrain and heart tissue in
embryonic mice. The authors identified and validated the heart functionality of transcription
enhancers, and determined that transcription enhancers for the heart are less conserved than those
for the forebrain during the same developmental stage.
Summary: When you sequence a patient, you will find many abnormalities. So in order to find
out the cause of the disease, we compare all the patients with the same disease and look at the
overlap in abnormalities. If the abnormality is only present in a few of the patients most likely
not the cause of the disease (but there could be an exception). The genes you end up with, that
overlap in most of the patients = candidate genes. After some further investigation and research,
you can narrow down the candidate gene population. For 1 disease, you will usually have
mutations in 1 gene region. So when you identify a gene, you do not need WES for the other
patients – you’ll only have to look at the gene of interest.
Chapter 6: Pharmacogenetics and genomics
We don’t all react in the same way to medication, because we are all different.
Pharmacogenetics: how genetic variants/modifications explain how different we react to
pharmacologic agents.
Personalized medicine: Current health care: patient diagnosis treatment. New diagnosis
and treatment if needed. With personalized medicine, you take into account the (1) individual
risk for complex diseases and (2) individual reaction to the drugs.
Aim of pharmacogenetics: improve therapeutic efficacy, reducing drug toxicity, and reducing
cost.
Is personalized medicine feasible? Relative recent field in medicine. Because first of all (a) you
need to have insights into individual genetic and environmental risk factors. If genetic factors
play a role logical that analysis of genome is needed to estimate genetic background of patient
(this has become feasible). And (b) there should be clear guidelines for use and interpretation of
risk analysis by the clinician /geneticist.
But is there a need for pharmacological analysis? Reasons why it is useful:
• Drugs response rate for many between only 25 – 75%. Outside this range the drug might
not work for the patient treatment failure (does not benefit recipient of the drug)
• You can generate adverse drug effects: overall incidence of adverse drug effects for
prescribed drug is 5 – 10% adverse effects lead to 2 million people hospitalized/year
of which many die (major issue to be addressed)
, Evidence for genetic determinants for drug effect:
• Link between ethnicity and aberrant drug responses
• Link between inheritance and aberrant drug responses
• Evidence for heritability by family and twin studies
What happens when we give certain medication to a patient (theoretically)
You hope to get to therapeutic range/window
drug effective. Should not be too high toxic levels
(side effects) and not too low therapeutic failure
(no effects).
With the help of pharmacogenetics, aim to reach
therapeutic range for the patients: improving
therapeutic efficacy by reducing drug toxicity
can also reduce cost.
Possible explanations for differences in drug response:
o Genetic differences in absorption and transport of drugs
o Genetic differences in metabolization of drugs
o Genetic differences in drug target
o Differentiation between subtypes of a disease
Drug metabolism:
• Pharmacologists classify pathways of drug metabolism as either phase I reactions (I.e.,
oxidation, reduction, and hydrolysis) or phase II, conjugation reactions (e.g., acetylation,
glucuronidation, sulfation, and methylation).
• purely historical, so phase II reactions can precede phase I reactions and often occur
without prior oxidation, reduction, or hydrolysis.
bias of different sequencing technologies is not yet fully understood.
Example: ChIP-seq was used to compare conservation of TFs in the forebrain and heart tissue in
embryonic mice. The authors identified and validated the heart functionality of transcription
enhancers, and determined that transcription enhancers for the heart are less conserved than those
for the forebrain during the same developmental stage.
Summary: When you sequence a patient, you will find many abnormalities. So in order to find
out the cause of the disease, we compare all the patients with the same disease and look at the
overlap in abnormalities. If the abnormality is only present in a few of the patients most likely
not the cause of the disease (but there could be an exception). The genes you end up with, that
overlap in most of the patients = candidate genes. After some further investigation and research,
you can narrow down the candidate gene population. For 1 disease, you will usually have
mutations in 1 gene region. So when you identify a gene, you do not need WES for the other
patients – you’ll only have to look at the gene of interest.
Chapter 6: Pharmacogenetics and genomics
We don’t all react in the same way to medication, because we are all different.
Pharmacogenetics: how genetic variants/modifications explain how different we react to
pharmacologic agents.
Personalized medicine: Current health care: patient diagnosis treatment. New diagnosis
and treatment if needed. With personalized medicine, you take into account the (1) individual
risk for complex diseases and (2) individual reaction to the drugs.
Aim of pharmacogenetics: improve therapeutic efficacy, reducing drug toxicity, and reducing
cost.
Is personalized medicine feasible? Relative recent field in medicine. Because first of all (a) you
need to have insights into individual genetic and environmental risk factors. If genetic factors
play a role logical that analysis of genome is needed to estimate genetic background of patient
(this has become feasible). And (b) there should be clear guidelines for use and interpretation of
risk analysis by the clinician /geneticist.
But is there a need for pharmacological analysis? Reasons why it is useful:
• Drugs response rate for many between only 25 – 75%. Outside this range the drug might
not work for the patient treatment failure (does not benefit recipient of the drug)
• You can generate adverse drug effects: overall incidence of adverse drug effects for
prescribed drug is 5 – 10% adverse effects lead to 2 million people hospitalized/year
of which many die (major issue to be addressed)
, Evidence for genetic determinants for drug effect:
• Link between ethnicity and aberrant drug responses
• Link between inheritance and aberrant drug responses
• Evidence for heritability by family and twin studies
What happens when we give certain medication to a patient (theoretically)
You hope to get to therapeutic range/window
drug effective. Should not be too high toxic levels
(side effects) and not too low therapeutic failure
(no effects).
With the help of pharmacogenetics, aim to reach
therapeutic range for the patients: improving
therapeutic efficacy by reducing drug toxicity
can also reduce cost.
Possible explanations for differences in drug response:
o Genetic differences in absorption and transport of drugs
o Genetic differences in metabolization of drugs
o Genetic differences in drug target
o Differentiation between subtypes of a disease
Drug metabolism:
• Pharmacologists classify pathways of drug metabolism as either phase I reactions (I.e.,
oxidation, reduction, and hydrolysis) or phase II, conjugation reactions (e.g., acetylation,
glucuronidation, sulfation, and methylation).
• purely historical, so phase II reactions can precede phase I reactions and often occur
without prior oxidation, reduction, or hydrolysis.
