Single Nucleotide Polymorphisms
Arthur M. Lesk
Bologna Winter School 2011
1
What are SNPs and why are they
important?
• SNP = Single nucleotide polymorphism, an isolated
change in a single nucleotide
• SNPs are one type of mutation
• Some have obvious functional consequences
• Sickle-cell haemoglobin: gag→gtg (β6 Gln→Val)
• First “molecular disease”
sickle-cell anaemia
• Some are ‘silent’
• Some are in non-coding regions
• affect splice sites?
• affect regulatory sites?
• some have no known phenotypic effect
•2
What is a SNP?
• The genomes of individuals in a population contain a
particular base at some position most of the time.
• That is, there is a “normal” sequence
• A SNP is a deviation from the normal sequence.
– Many people require that a variation occur in at least
1% of the population, to be considered a SNP
• But: what population? What if two distinct populations
have a consistent polymorphism?
3
SNPs in human genomes
• SNPs are about 90% of all inter-human
variation
• Occur on the average once in every 300
bases
• 2/3 of SNPs are C→T changes (perhaps
because C can easily deaminate)
cytosine
→
uracil
4
SNP density varies across human
genome
• Some high-density patches
• Some ‘deserts’
• SNPs in coding regions ~1/3 as many as in
non-coding regions
• SNP density correlated with recombination
rate (which causes which??)
• AT microsatellites: long (AT)n repeat tracts
tend to appear in regions of low SNP density
5
Figure 14 SNP density in each 100-kbp interval as determined with Celera-PFP SNPs.
J C Venter et al. Science 2001;291:1304-1351
Published by AAAS
What is normal?
• Obviously we all differ genomically
• Swedes and Chinese have obviously different
phenotypes
• Most Swedes and Chinese are healthy indviduals
• Therefore genetic differences do not necessarily
cause disease
• Pointless to check for differences from a single
‘reference sequence’
• Of course, many genetic differences not just SNPs
7
Variation in human and other species
• Any two humans ~99.5% identical in sequence
• Chimpanzees, gorillas: twice as variable,
despite much smaller population size
• Implies prehistoric bottleneck in human
population, recent common origin
• Most SNPs (> 5%) shared among human
populations from around the world
• Most populations (e.g. British) contain 85-90%
of all known variation
8
Variation in human and other species
• Some variation is population-specific
• In some cases, there is local selective pressure
• For example, adult lactose tolerance, malaria
resistance
• African populations have greatest genetic
diversity
• Supports ‘Out of Africa’ theory of human
origin and migration
9
Identification of geographical origin,
phenotype
• A criminal leaves a blood sample at a crime
scene
• How much can we tell about him or her?
• Not perfectly, but:
– Ethnic group
– Eye and hair colour (hair colour easier to change)
– Family name?
10
Types of SNPs
• Transitions:
– purine ↔ purine
– pyrimidine ↔ pyrimidine
(cytosine→uracil)
• Transversions:
– purine ↔ pyrimidine
• Transitions are more common than
transversions
11
Prevalence of SNPs in human
genomes
• approximately 1 in 300 bp (0.001%)
• compare difference between human /
chimpanzee genomes:
• 4% different (not all SNPs!)
12
‘Life cycle’ of a SNP
• Generation of a mutation
• Initial survival, against ‘sampling loss’
• Increase in frequency – survival until become
homozygous in some individuals;
• chance of loss reduced
(helped by bottlenecks, founder effects –
population size dependent)
• Fixation
13
Initial survival of a SNP
• Suppose a person is heterozygous for a novel,
selectively-neutral mutation.
• Suppose the person has 2 children that
survive to reproductive age. The probability
of loss of the mutation is 25%.
• If each descendant has 2 children that survive
to reproductive age, probability of loss in 200
years = 94%
14
Where do SNPs occur in the human
genome?
• Distributed throughout the genome
• 50% in non-coding regions
– NOT the same as non-functional!!!
• 25% missense mutations (amino acid substitution)
• 25% silent
(amino acid unchanged)
– silent = no change in encoded amino-acid sequence
– NOT the same as no phenotypic effect!!!
– would be better to call them synonomous SNPs rather
than silent SNPs
15
SNPs in non-human genomes
• Of course other species have SNPs
• Here we will focus on human SNPs because of
relevance to human disease
• However, SNPs in pathogens are sometimes
associated with antibiotic resistance, and
therefore related to human disease
• SNPs in some plants give clues to
domestication
16
Organised efforts to collect SNPs
• The HapMap is a catalogue of common human
genetic variants
• HapMap Project = international collaboration
among Japan, the United Kingdom, Canada,
China, Nigeria, and the United States
• NOT Europe
• Carry out measurements, provide database
• Other projects collect SNPs in other species
17
HapMap project
• International consortium: International
HapMap Project
– http://hapmap.ncbi.nlm.nih.gov/
• Catalogue of human genetic variants :
– What sites?
– How distributed – frequency in different
populations
– Raw material for linking genomics with disease
18
Origin of samples
•
•
•
•
•
Total of 270 people.
The Yoruba people of Ibadan, Nigeria
Japan (Tokyo)
China (Beijing)
U.S. residents with Northern and Western
European ancestry
19
What is a haplotype?
• Often, a set of SNPs appear nearby on the same
chromosome
• In absence of recombination, they will be
inherited in blocks
• Pattern of SNPs in a block is called a haplotype
• A block may contain many SNPs, but only a few
are needed to identify a haplotype
• These signature SNPs within a haplotype block
are called `tag SNPs’
20
http://www.riken.go.jp/engn/r-world/info/release/news/2003/nov/image/frol_06.gif
21
http://img.medscape.com/fullsize/migrated/553/400/ncpcard553400.fig1.gif
22
Guide to SNP databases
•
•
•
•
•
SNPlinks:
http://www.snpforid.org/snpdata.html
NCBI dbSNP
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=snp
The SNP Consortium
http://snp.cshl.org/
HapMap
http://www.hapmap.org/
Applied Biosystems
http://myscience.appliedbiosystems.com/cdsEntry
Assays-on-Demand
/Form/assay_search_basic.jsp
• Ensembl
http://www.ensembl.org/Homo_sapiens/
• HGVBase
http://hgvbase.cgb.ki.se/
• SeattleSNPs
https://gvs.gs.washington.edu/GVS/
23
dbSNP database at NCBI
• non-redundant dataset
• nomenclature: rs number
• rs = reference SNP.
24
General human mutations
• Human Gene Mutation Database
http://www.hgmd.cf.ac.uk
• over 100000 mutations, in 3700 genes
• 6.2% of total ~23000 genes
• about 10000 new mutations found per year
• OMIM (Online Mendelian Inheritance in Man)
– database of mutations associated with human disease
• OMIA (Online Mendelian Inheritance in Animal)
Databases with important related
information
• Online Mendelian Inheritance in Man (OMIM) [NCBI]
– Comprehensive compendium of human genes and
associated phenotypes
– Not limited to SNPs
• SNPs3D
http://www.snps3d.org/
– SNPs3D assigns molecular functional effects to nonsynonymous SNPs based on structure and sequence
analysis.
• SNPper
http://snpper.chip.org/
– Retrieve SNPs by position or gene association
26
Quality of sequence information is
important
• SNPs appear in human genome at
approximately 1 in 300 bases
• Obviously error rate in resequencing must be
substantially lower than this if SNP data are to
be meaningful
• Measure of DNA sequencing quality: PHRED
27
PHRED – measure of sequence quality
• Phred scores accepted to characterize the
quality of DNA sequences
• Originally Phred was a program, that
determined accurate quality scores indicating
error probabilities.
• Accepted as general standard
• Phred quality score Q. Let P = probability of
base error
Q = -10 log10 P
28
Phred
quality
score Q
10
20
30
40
50
Probability
of incorrect
base call
1 in 10
1 in 100
1 in 1000
1 in 10000
1 in 100000
Base call
accuracy
90%
99%
99.9%
99.99%
99.999%
29
Phred quality
score Q
10
20
30
40
50
Probability of
incorrect base
call
1 in 10
1 in 100
1 in 1000
1 in 10000
1 in 100000
Base call accuracy
90%
99%
99.9%
99.99%
99.999%
A method that gave an averaged phred
score Q = 30 would give approximately
as many errors as there are SNPs!
30
What can SNPs tell us?
• Causes of disease -- dysfunctional protein
• Correlation with disease prognosis, success of
particular treatment
• Useful genetic markers, to locate some gene of
phenotypic interest; for instance, a gene
correlated with a disease
• Characterise individuals
• Characterise populations (SNP distribution)
• Applications in anthropology -- tracing of
migrations, human evolution
31
Use of SNPs as genetic markers



Before 1980, genetic maps were constructed
by measuring recombination frequencies
between genes giving measurable phenotypic
traits
This goes back at least to Sturtevandt and
Morgan, if not to Mendel
At that time, phenotypes were the only visible
aspect of the genome
Use of SNPs as genetic markers





In 1980, Botstein, Davis, Skolnick & White
proposed using polymorphic DNA markers for
genetic mapping, even if they had no known
phenotypic effect
Example: (then) restriction sites
SNPs → restriction fragment length
polymorphisms (RFLPs)
Did linkage mapping with restriction sites
Now we can use SNPs
Traits depending on multiple loci
• Use of SNPs to identify traits, including but not
limited to diseases, that depend on multiple
loci
• Single genes for diseases showing simple
Mendelian inheritance (for instance, cystic
fibrosis) can be isolated
• Diseases that depend on interaction with
multiple loci can be studied with enough SNP
linkage information
34
SNPs tell us about human history
• Development of ability to digest lactose past
infancy correlated with domestication of
cattle, increased (non-fermented) dairy
products in human diet
• Source of calcium and calories
• Many Asian populations retain adult lactose
intolerance
• Where do they get calcium?
“The soybean is the cow of Asia.”
35
Ability to digest lactose in adulthood
• Digestion of lactose depends on enzyme
lactase-phlorizin hydrolase, which catalyzes
hydrolysis of lactose → glucose + galactose
36
Ability to digest lactose in adulthood
• In many people, the ability to digest lactose is
a juvenile characteristic
• Expression declines after age 2
– varies among individuals
• Consistent with lifestyle involving breast
feeding until this age, followed by weaning
followed by diet not including (nonfermented) milk and other dairy products
– To form yoghurt, bacteria cleave lactose
37
Evolution of adult lactase expression
• Domestication of cattle, with
concomitant rise of milk in the
diet, led to selective pressure for
lactose tolerance
• Mutation arose among cattleraising people:
– the Funnel Beaker culture
– north-central Europe ~5,0006,000 years ago
• Most common mutations in
Europeans: SNPs
– C/T-13910
– G/A-22018
• Not surprisingly, in control
regions for lactase gene
38
http://gseorlando.files.wordpress.com/2010/09/j.jpg
Prevalance of lactose-tolerance SNP
Danes and Swedes
Spanish and French
Chinese
90%
50%
1%
Group Study Exchange
39
Multiple development of lactose
tolerance
• Development of lactose tolerance apparently
appeared four times, independently
– Europe: C/T-13910 and G/A-22018
• Pastoral areas of Africa – three independent
mutations:
– G/C-14010
– T/G-13915
– C/G-13907
East Africa
North Sudan
North Kenya
40
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672153/bin/ukmss-4417-f0002.jpg
41
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672153/bin/ukmss-4417-f0001.jpg
42
SNPs in anthropology
• Useful in tracing relationships between
populations, migration routes
• Initially used mitochondrial DNA (16569 bp)
• Maternal inheritance only
– (Y chromosome gives paternal inheritance only)
• Important argument for “out of Africa” theory of
human origins and dispersal
• Can choose non-selected regions, in contrast to
previous work on blood groups, MHC haplotypes
43
Migration routes into Asia and the
Pacific based on SNPs
http://i49.tinypic.com/2d0j2py.jpg
44
DNA sequences and language groups
• Proposal by L. L. Cavalli-Sforza
• Showed consistency between trees based on
genetic markers and trees based on linguistic
groupings
• Controversial!
• In some cases, genomics has confirmed
hypotheses of population affinity based on
language similarity / dissimilarity
• Basques are outliers in both genes and language
45
Recommended reading
Tomasz Kamusella
The Politics of Language and Nationalism in
Modern Central Europe
Palgrave Macmillan, 2008
46
What happens after invasions?
• Hungary invaded by Magyars in 896 AD. Country
converted to speaking Uralic language
• Rome fell to vandals in 476 AD but did NOT
impose their language. (Perhaps recognising
superiority of Italian culture – which their
descendants don’t)
• England invaded by Anglo-Saxons in about 5th
century. Anglo-Saxon pushed Celtic languages to
far reaches of British Isles + Brittany
• Norman invasion of 1066 did NOT entirely
replace Anglo-Saxon by French.
47
Possible effects of SNPs
• In protein-coding sequences
–
–
–
–
–
silent
missense
coding → stop codon
stop codon → coding
SNPs can → dysfunctional proteins
• In splice sites
– 15% of disease-causing mutations in human genome
are point mutations in vicinity of mRNA splice
junctions
• In regulatory sequences
48
What are possible effects of SNPs in
coding sequences?
• Change in amino acid
• Example: sickle-cell anaemia
• sense codon → stop codon
– protein truncated
• stop codon → sense codon
– protein extended
49
50
SNPs in coding regions can do more
than change one amino acid
• Change of codon for an amino acid to STOP
codon produces truncated protein
– Example: common mutation causing phenylketonuria
• Change of STOP codon to codon for an amino
acid produces extended protein
• Example: haemoglobin Constant Spring
– α-chain variant
– termination codon TAA is mutated to CAA (glutamine)
– produces extension of haemoglobin α-chain from 142
to 172 amino acids
– causes mild anaemia
51
Possible consequences of silent
(synonymous) SNPs
• Nothing detectable
• Change in proportions of variable spliced
proteins
• Change in stability of mRNA
• Effect on protein folding (translational
pausing)
52
SNPs can affect variable splicing
• Almost all multiexonic genes show variable
splicing
• Change in isoform can have severe effects
• Susceptibility to West Nile Virus
– SNP in 2',5'-oligoadenylate synthetase-like gene
common in susceptible individuals
– oligoadenylate synthetase implicated in viral
resistance
– SNP present in exonic splice enhancer
– Increases level of truncated protein →
enhanced susceptibility to virus
53
SNPs can affect mRNA stability
• Expression levels of proteins depend on mRNA
half-life (among other things)
• ATP-binding-cassette (ABC) transporters are
membrane proteins
• function in translocation of compounds out of
cells
• Disease associates with SNP in this family
54
Dubin-Johnson syndrome
• autosomal recessive disorder
• increase in conjugated bilirubin
• defect in hepatocyte secretion of conjugated bilirubin
into bile
• many patients asymptomatic
• hormonal birth control or pregnancy can → jaundice
• Some cases caused by synonymous SNP in gene for
ABCC2
→ increased mRNA stability
→ increased expression levels
55
Synonymous SNPs can affect protein
folding and even native structure
• Synonymous SNPs do not affect amino acid
sequence
• Therefore should not alter native structure
• However, affects kinetics of folding
• mRNA secondary structure affect translational
pausing
56
Cotranslational folding is affected by
translational pausing
• Can affect not only kinetics but tertiary structure
• Example: SNPs in Multidrug Resistance1 MDR1
– Encodes P-glycoprotein, an ABC transporter
– Function to pump molecules out, including
chemotheraputic agents used in cancer
– Haplotype C1236T, G2677T (nonsynonymous), C3435T
– Affects interactions of protein with:
• cyclosporine A -- fungal cyclic peptide,
immunosuppressant, used post-transplant
• verapamil -- calcium channel blocker, used in treatment
of high blood pressure
Ref: Kimchi-Sarfaty C, Oh JM, Kim IW, Sauna ZE, Calcagno AM, Ambudkar SV, Gottesman MM
(2007). A "silent" polymorphism in the MDR1 gene changes substrate specificity. Science. 315,
525-528.
57
Verapamil
Cyclosporin A
58
References
• Kimchi-Sarfaty C, Oh JM, Kim IW, Sauna ZE,
Calcagno AM, Ambudkar SV, Gottesman MM
(2007). A "silent" polymorphism in the MDR1
gene changes substrate specificity. Science. 315,
525-528.
• Erratum in: * Science. 2007 Nov
30;318(5855):1382-3.
• Comment in: Science. 2007 Jan
26;315(5811):466-7.
• Bioessays. 2007 Jun;29(6):515-9.
• * Epilepsia. 2007 Dec;48(12):2369-70.
59
Prediction of functional effects of
non-synonymous SNPs
• PolyPhen: (EMBL, Heidelberg)
http://coot.embl.de/PolyPhen/
• SNPs3D (Baltimore)
http://www.snps3d.org/
• Pmut (Barcelona)
http://mmb2.pcb.ub.es:8080/PMut/
• SIFT (University of Washington)
http://blocks.fhcrc.org/sift/SIFT.html
• MAPP (Stanford)
http://mendel.stanford.edu/SidowLab/downloads/MAPP/index.html
60
Sorting Intolerant From Tolerant
• Database and server at University of
Washington
• SIFT predicts whether an amino acid
substitution affects protein function based on
sequence homology and the physical
properties of amino acids
• Limited to non-synonymous SNPs (or more
generally, amino acid substitutions)
61
SNPs in Medicine



Genomic sequence analysis can provide a lot
of information about health risks of any
individual
So far, part of the problem is that sequences
usually just give bad news
Indications of optimal therapy useful: the U.S.
health care industry faces huge costs in
treatment of side effects of medication
SNPs and disease
• Some SNPs (and of course other mutations) are
consistent with a healthy life, and typical life-span,
provided the individual carries on a reasonable lifestyle.
• Some SNPs directly and unavoidably cause disease
• Others cause disease only in combination with unusual
lifestyle or specific events
– Example: fever in children with Z-mutation of α1-antitrypsin
– protein somewhat unstable, denatures and aggregates
– Essential to keep infants free of high fever
• In many cases we can’t tell extent of genetic basis of
disease or how it interacts with environmental effects
63
Copy-number variations may mask
disease genes
• Genes in which nonsense SNPs detected
belong to gene families of higher than average
size.
• Genetic robustness
• Every individual is heterozygous for some
deleterious mutations that, if homozygous,
would be lethal.
Interaction of SNPs with
environment/experience
• α1-antitrypsin is a natural elastase inhibitor in the lung
• elastase in lung protects against bacteria
• inhibitor prevents elastase from acting on human
tissues, notably elastin in the lung
• Z-mutation of α1-antitrypsin: glu342→lys
• Causes enhanced risk of emphysema
• Z-mutation + smoking = GUARANTEE of early death
from emphysema
“Genetics loads the gun; environment pulls the trigger”
(J. Stern)
Discussion of following diseases
•
•
•
•
Sickle-cell anaemia
Phenylketonuria
Alzheimer’s disease
Cancer
66
SNP causing disease: Sickle-cell anaemia
• β6Val→Gln creates hydrophobic (sticky) patch
on surface of β chains of haemoglobin
• Common SNP: gag → gtg
• causes aggregation of deoxyhaemoglobin
67
Phenylketonuria
• Inborn deficiency in phenylalanine
hydroxylase
• Autosomal recessive
(12q24.1)
• 1/10000
sufferers
• 1/50 carriers
• Subject of
neonatal screening in many countries
68
Mutations causing PKU
• Phenylalanine hydroxylase is a tetramer
• Known mutations include:
– Over 200 affecting catalysis
– About 50 affecting regulation
– About 10 affecting tetramerization
(Some involve cofactor -- tetrahydrobiopterin -- processing)
• Most common mutation in Caucasians:
– g→a in intron 12
– causes truncation (sense codon to stop codon)
– fails to tetramerize
• McGill database: http://www.pahdb.mcgill.ca/
69
Testing for PKU
• Phenylalanine, and degradation products such as
phenylpyruvate build up in blood and urine
(Phenylpyruvate is a ketone, hence the name of the disease.)
• Blood sample from neonate, mass spec to detect phe, tyr
levels
• Can also do genomic sequencing – detection of carriers,
counselling of potential parents
70
Symptoms if untreated
• developmental defects:
– mental retardation
– microcephaly
• seizures
71
• Low phenylalanine diet
– not entirely satisfactory (unpalatable?)
– tricky to manage PKU women in pregnancy
• Gene therapy (works in mice …)
• Enzyme replacement therapy
http://newenglandconsortium.org/wp-content/uploads/2009/12/PKU-Food-Diagram-copy.jpg
Treatment
72
PKU in pregnancy
• Remember that PKU is an autosomal recessive trait
• A woman with PKU must be homozygous for
defective phenylalanine hydroxylase (not necessarily
same mutation)
• If such a woman becomes pregnant, it is likely that
the foetus is only a carrier (unless father also a
carrier)
• Tricky to control phe levels in mother to give foetus
adequate nutrition but not toxic levels
73
Enzyme replacement therapy for PKU
(1) administer functional phenylalanine hydroxylase itself
But: requires cofactor, complex regulatory controls
(2) phenylalanine ammonia-lyase
• converts phenylalanine to trans-cinnamic acid
• trans-cinnamic acid:
– has low toxicity and does not cause developmental defects
– converted by liver to benzoic acid, detoxified and excreted in
urine
– stable
• phenylalanine ammonia-lyase found in many plants; and
fungi, including yeasts
• Anabaena variabilis enzyme in phase II clinical trials
74
Comparison of reactions catalysed by
phenylalanine hydroxylase (PAH) and
phenylalanine ammonia-lyase (PAL)
http://www.nature.com/mt/journal/v10/n2/images/mt20041219f1.jpg
75
Genomics of phenylalanine hydroxylase
• Rhesus macaque and chimpanzee phenylalanine
hydroxylases differ from normal human PAH
• On difference:
Human Y356 = H in macaque and chimp
• The mutant is in the list of mutations in the PKU
database: http://www.pahdb.mcgill.ca/
• But chimps and rhesus macaques do not suffer
from PKU
• Why not?
76
Alzheimer’s disease
• Loss of cognitive function, characterised by:
– Loss of train of thought
– Progressive memore problems
– Miss important appointments
• Early-onset
– Appears at age < 65
• Late-onset Alzheimer’s – most common type
– Affects people over the age 65
– ~50% of people over age 85 suffer from it.
• Familial Alzheimer’s
– < 1% of cases, appears at age 40-60
Alzheimer’s disease
• Early-onset -- age < 65
– associated with mutations in presenilin 1, presenilin 2
and amyloid precursor protein
• Late-onset Alzheimer’s – age > 65
– most common type: ~50% of people over age of 85
suffer from it.
– Propensity associated with ApoE (apolipoprotein E SNPs)
• Familial Alzheimer’s
– < 1% of cases, appears at age 40-60
ApoE SNPs and risk of late-onset
Alzheimer disease
• ApoE = apolipoprotein E
– Gene on chromosome 19; therefore we have two alleles
– Basic function: remove cholesterol from blood
• Four common alleles, differ by SNPs:
– ApoE1 [minor variant], ApoE2, ApoE3 [~55%], ApoE4
• E3 most prevalent(“ normal”)
• At least one E4 allele  increased risk of Alzheimer’s
• At least one E2 allele  decreased risk of Alzheimer’s
ApoE alleles
• ApoE = 317-residue protein
• Four common ApoE alleles, differ by SNPs:
– ApoE1 = rs429358(C) + rs7412(T) [minor variant]
– ApoE2 = rs429358(T) + rs7412(T)
– ApoE3 = rs429358(T) + rs7412(C) [~55%]
– ApoE4 = rs429358(C) + rs7412(C)
Allele 112
E1
Arg
168
Cys
E2
Cys
Cys
E3
E4
Cys
Arg
Arg
Arg
SNPs and Cancer


SNPs are relevant to cancer research and
treatment in several ways:
Mutations detectable in the genome indicate
propensity for development of cancers




Mutations in BRCA1 and BRCA2, as indicators for
likelihood of breast/ovarian cancer development
probably best known
Sequence analysis can predict progression and
outcome
Sequence analysis can help choose optimal
treatment
Progression of tumour often involves mutations
and divergence of cell lines
Formation of cancer associated with
loss of genome integrity

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

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Cancer results from accumulated mutations
that break down the controls on cell growth
Three classes of genes can promote cancer:
Genes that regulate cell proliferation
Genes required for repair of DNA damage
Genes that control apoptosis
Retinoblastoma






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Rare childhood tumour of eye
Sporadic / familial (30-40%)
Characteristics of familial retinoblastoma:
Early onset
Multiple tumours
Affect both eyes
Autosomal dominant inheritance pattern
‘Two-hit’ hypothesis



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Non-familial cases require inactivation of both
copies of retinoblastoma gene
Require separate and independent mutations
Familial cases inherit one defective copy, one
functional copy
That is, ‘first hit’ is inherited, all that is needed
is ‘second hit’
85
SNPs and cancer
• A number of genes are known as ‘tumour
suppressor genes’
– Well-known examples: BRCA1, BRCA2
– Not all common mutations are SNPs
• Some SNPs in tumour suppressor genes cause
predisposition to development of cancer
• Other SNPs correlated with
– Progression of disease
– Efficacy of certain drugs
86
Tumour suppressor genes



Encode proteins that inhibit tumor formation
Normal function: inhibit cell growth
Mutations take “foot off cell-growth brake”
Mutations in BRCA1 and BRCA2
• In general population:
~ 12% of women will develop breast cancer
• Women with harmful mutation in BRCA1 or BRCA2:
~ 60% will develop breast cancer
• In general population:
~1.4% of women will develop ovarian cancer
• Women with harmful mutation in BRCA1 or BRCA2:
~ 15-40% will develop breast cancer
88
Some common BRCA1 mutations
• Varies with population: showing strong
‘founder’ effect
• Many not SNPs
• Not all of these are necessarily harmful
mutations
Population
Common mutation
Ashkenazi Jewish
185delAG, 188del11, 5382insC
Italian
5083del19
African-Americans
943ins10, M1775R
Spanish
R71G
French
3600del11, G1710X
French Canadians
C4446T
89
Other tumour suppressor genes correlated
with predisposition to develop cancer
• TP53, PTEN, STK11/LKB1, CDH1, CHEK2, ATM,
MLH1, and MSH2
• But BRCA1 and BRCA2 have the strongest
correlation with predisposition to breast and
ovarian cancer
• Importance of early detection in treatment of
cancer
• At-risk individuals should be sure to undergo
frequent checkups
90
Pharmacogenomics
• Tailoring of treatment to individual patient,
based on genetic sequences
91
Pharmacogenomics
• Tailoring of treatment to individual patient, based
on genetic sequences
• Choice of optimal drug, and dosage
• Use of drugs inappropriate for the patient:
– risks side effects: discomfort or even death
– loses time in treating a condition which may become
progressively worse
– at best, wastes money and health care resources; may
require additional resources to cure side effects and
more severe conditions
92
Thiopurine methyltransferase
• Acute lymphoblastic leukemia is a childhood
cancer treated by thiopurines
• Thiopurine methyltransferase breaks down
the drugs
• Genetic variant leading to inactive enzyme
threatens toxic levels of drug in patient
• Screening patients for deficiency allows
monitoring to determine appropriate dosage
levels
93
Sensitivity to abacavir
• Abacavir used in
treatment of AIDS
• 4-8% of patients have
serious, potentially-fatal
hypersensitivity reaction
• Hypersensitivity correlated with MHC allele
HLA-B*5701
• Genetic screening can detect, guide treatment
94
Cytochrome P450 and drug metabolism
• Cytochrome P450 is a family of enzymes in the liver
• Responsible for metabolizing a wide variety of drugs
• Variations in sequences affect activity of these
enzymes
• Lowered activity or loss of activity can cause drug
toxicity
• Genetic tests for variations in cytochrome P450 genes
warn of potential overdose dangers
• Pharmaceutical companies screen compounds for rates
of metabolism by cytochrome P450 enzymes
95
J.D. Watson – lessons from genome
• The sequence of J.D. Watson’s DNA has been
determined.
• He is homozygous for an unusual allele of the
important drug metabolizing cytochrome gene
(CYP2D6)
• Individuals with his genotype metabolise some drugs
more slowly than other people.
• Watson has been taking β blockers to lower his blood
pressure.
• Side effect: made him unacceptably sleepy.
• Now he is taking a lower dosage.
96