PowerPoint-Pr

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Significance of SNPs for human disease
Dr. Almut Nebel  Dept. of Human
Genetics University of the Witwatersrand Johannesb
urg South Africa
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DNA the stuff of life
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Human genomic variation
On average, the difference between any two
homologous human DNA sequences has been
estimated to be lt 0.1.
For the human genome, this translates into 3
million nucleotides!
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Single nucleotide polymorphisms ( SNPs)
account for 90 of all human DNA variation.
SNP a locus in the DNA at which different
people have a different nucleotide (allele)
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SNPing away at the genome ....

• The US Human Genome Project (HGP)
• 2. The SNP Consortium (TSC)

• Aims
• to identify informative SNPs
• to create SNP maps across the genome
• to determine SNP allele frequencies in
  different
• populations
• to make the data publicly and freely available
  

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15 February 2001
A map of human genome sequence variation
containing 1.42 million single nucleotide
polymorphisms
The International SNP Map Working Group (HGP, TSC
and others)
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SNP fact sheet

• number of loci HGP 4.2 million
• TSC 1.8 million
  (year 2002)
• estimated density every 300 - 1000 bp through-
• out the genome, except sex chromosomes
• only 1 of SNPs are in genes and 0.1 of
• SNPs are functional ( mutations)
• mostly bi-allelic
• suitable for automated analysis

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SNP discovery and screening
to type many DNA samples for known SNPs
to identify new SNPs in the genome

• automated high-throughput
• technologies
• software for efficient
• database management

• availability of and access
• to sequence data
• bioinformatic tools

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SNPs as genetic signposts for human disease
Research mapping disease genes (monogenic,
complex)
Diagnostics diagnosing predisposition to
complex diseases
Pharmacogenetics predicting responses to drugs
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haplotype
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Strategies for gene mapping
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SNPs in linkage analysis
identify SNP haplotypes that segregate together
with the disease
family pedigree

fine mapping
SNP typing using DNA of affected and unaffected
family members
candidate gene
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SNPs in association studies
to test whether a particular SNP allele /
haplotype is enriched in patients compared to
healthy controls
SNP X allele A allele C
frequency of C in patients gt controls
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SNPs associated with complex diseases
disease gene SNP allele
Alzheimer apolipoprotein E (APOE)
e4 allele Diabetis
mellitus peroxisome proliferator-
pro 12 ala Type 2 activated recepto-g
(PPARG) Venous thrombosis Factor V
Leiden G 1691 A
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Problems with association studies
Example Factor V Leiden
Factor V mutation
Factor V mutation
venous thrombosis
other genes
lifestyle
oral contraceptives
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SNPs and pharmacogenetics (1)
the study of variability in drug responses
due to genetic factors in individuals
drug efficacy
adverse effects (acute toxic events, drug
interactions)
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SNPs and pharmacogenetics (2)
Clinical trial of a drug
association study testing SNPs in genes coding
for drug- metabolizing enzymes (eg. cytochrome
P450 mono-oxygenase gene family)
to identify a SNP allele / haplotype that
predisposes individuals to an adverse drug
effect
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SNPs and population genetics
There are considerable differences in SNP allele
frequencies among populations classified acc. to
geographic, racial and ethnic criteria
population-specific SNPs
Allele Frequency Project of TSC
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Conclusions (1)
SNP revolution SNPs are being used to
identify genes involved in both monogenic and
complex diseases SNPs have the potential for
predicting disease and for identifying
individuals at risk for drug toxicities, but
there is still uncertainty surrounding their use
in clinical molecular diagnostics
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Conclusions (2)
SNP revolution SNPs are being used to
identify genes involved in both monogenic and
complex diseases SNPs have started to play an
important role in the administration of drugs
and in identifying individuals at risk for
toxicities SNPs have the potential for
predicting disease, but there is uncertainty
surrounding their use in clinical molecular
diagnostics
The full clinical potential of SNPs has yet to be
realized
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Prospects for the post-genomic era
SNP analysis gene expression (SNP-related)
functional proteomics

• more accurate predictive models for complex
• diseases
• tailored or personalized medicine with
  better,
• safer medication
• financial, ethical, personal issues

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