434 Unit 2 Lec 13-14

Monogenic Diseases

•Large effect gene variants

•Clearly traced through family pedigrees

•The huntington associated variant was identifying by cutting human DNA with a sequence specific enzyme

Genetic Locus

site on the DNA, contains multiple genes

Genome wide association studies

•Goal is to associate genes with traits

•Individual genes likely only have small effects

•scan for markers across entire genomes

•current approach to understanding polygenic diseases

Population

For disease, you want people with and without the disease, and for traits, you want people along the continuum of that trait 

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•Certain traits have less or more of a genetic impact- need a large population size

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•ancestry is a critical factor to consider - compare people from the same ancestry to get the right SNPs

GWAS compares….

Compare SNPs in people with and without disease to see if theres a difference between them

Do SNPs cause disease?

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SNPs dont necessarily cause disease, they’re just associated with the disease

Next gene sequencing

needed for finding rare SNPs (find your own SNPs) but its more expensive 

Whole Exome Sequencing

Selective sequencing of exons (coding)

→misses out on changes to introns 

Polygenic Risk Scores

•attempt to determine the relative risk for complex diseases

•consdiers potentially hundreds of genetic variants that modulate disease risk

•Can assess risk for individuals or populations

•Can identify cohorts for further analysis of gene-disease connections

•Can include environmental risk or utilize biomarkers

Polygenic Risk Scores incorporate information from…

GWAS studies

How do non coding variants contribute to genetic disease

•Non coding genome can alter the amount of RNA or protein produced by a gene (gene expression)

→Promoters, enhancers, silencers, insulators

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Promoters

initiate gene expression

Promoters are acted on by

Enhancers, Silencers, Insulators

Enhancers

increase gene expression

Silencers

reduce gene expression

Insulators

block the effect of enhancers at adjacent genes

Personalized Genomics:

“One size fits all” approaches don’t work for everyone

•Using genomics to define or predict disease 

•Based on individuals DNA sequence or other biomarkers 

Precision Medicine

•Allows for more accurate treatment and prevention strategies

•Use of polygenic risk scores to improve patient outcomes is an example

Pharmacogenomics, PGx

how a persons genetic background effects drug response is a subfield of precision medicine

Uses of precision medicine

•Make a diagnosis

•Plan a treatment

•Determine treatment efficacy

•Make a prognosis

Biomarkers

DNA/RNA/protein features that correlate with disease risk or therapy efficacy, can be used to specify treatment

Pembrolizumab(Keytruda)

•Targets tumors based on two biomarkers: tumor microsatellilite (short DNA repeats) instability (MSI) and DNA mismatch repair deficiency(dMMR)

1)T cells normally attack tumor cells

2)T cells can be inactivated by tumors that express the PD-L pathway

3)Prembrolizumab blocks PD1 receptors on T cells, allowing T cells to attack the tumor

Actually personalized medicine:

•mRNA vaccines can be reprogrammed to target tumors from specific patients

•engineerred mRNAs express neoantigens: new proteins found on the outside of tumor cells due to DNA mutations

1)Tissue samples

2)Next generation sequencing

3)Vaccine design

4)Manufacturing

5)Administration 

PGx Goals

•Avoid adverse reactions

•Decide dosage

•Overall patient health improvement 

Pharmacogenes:

•Genes with variants that affect drug pharmacokinetics or pharmacodynamics 

•Pharmacokinetic genes:

→normal metabolziers

→poor metabolziers

→intermediate metabolizers

→ultrarapid metabolizers

Pharmacodynamic genes

positive or negative for high risk allele

Drug receptors

Varying numbers of drug receptors on cells can produce varying responses

Drug uptake

Drug entry into target cells can be impacted by genotype

Drug breakdown

Genotype impacts the rate of drug breakdown, which affects dosing

Allele specific

•Variant specific therapy

•Pharmacodynamic effect 

CYP2D6

•Structural variants or large scale deletions or duplications affect drug metabolism

•Deletion of CYP2D6 created a null allele that has no activity or less drug metabolism

•Duplications CYP2D6 have increased activity