Dr. Almut Nebel Dept. of Human Genetics University of the Witwatersrand Johannesburg South Africa
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Transcript of Dr. Almut Nebel Dept. of Human Genetics University of the Witwatersrand Johannesburg South Africa
Dr. Almut Nebel
Dept. of Human GeneticsUniversity of the Witwatersrand
JohannesburgSouth Africa
Significance of SNPs for human disease
DNA –
´the stuff of life´
Human genomic variation
On average, the difference between any two
homologous human DNA sequences has been
estimated to be
< 0.1%.
For the human genome, this translates
into~ 3 million nucleotides!
account for ~ 90% of all human DNA variation.
SNP = a locus in the DNA at which different people have a different nucleotide (allele)
AGAGATTAGTCTGCATC-CG
AGTGATTAGTTTGCATCGCG
Single nucleotide polymorphisms ( = SNPs)
´SNPing away´ at the genome ....
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
1. The US Human Genome Project (HGP)
2. The SNP Consortium (TSC)
15 February 2001
Nature 409, 928 - 933 (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)
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
to type many DNA samplesfor known SNPs
to identify new SNPs in the genome
availability of and access to sequence data
bioinformatic tools
automated high-throughput technologies
software for efficient database management
SNP discovery and screening
´in silico´
Research
mapping disease genes (monogenic, complex)
Diagnostics
diagnosing predisposition to complex diseases
Pharmacogenetics
predicting responses to drugs
SNPs as genetic signposts for human disease
Linkage Disequilibrium (LD)
SNP 1 SNP 1SNP 2 SNP 2
SNP 1 SNP 2
haplotype
Strategies for gene mapping
1. linkage analysis
to map genes responsible for highly penetrant disorders (monogenic)
2. association studies
to examine the genetic basis of complex (multifactorial) diseases
SNPs in linkage analysis
~ location
candidate gene
+
SNP typing using DNA of affected and unaffected family members
fine mapping
family pedigreeidentify SNP haplotypes that segregate
together with the disease
to test whether a particular SNP allele / haplotype is enriched in patients compared
to healthy controls
SNPs in association studies
frequency of C in patients > controls
SNP X
allele Aallele C
disease gene SNP allele
Alzheimer apolipoprotein E (APOE) 4 allele
Diabetis mellitus peroxisome proliferator- pro 12 alaType 2 activated recepto-PPARG
Venous thrombosis Factor V Leiden G 1691 A
SNPs associated with complex diseases
Problems with association studies
Example: Factor V Leiden
patients controls (venous thrombosis)
50 % 3 - 4 %
venous thrombosis
other genes lifestyleoral
contraceptives
Factor V mutationFactor V mutation
SNPs and pharmacogenetics (1)
= the study of variability in drug responses due to genetic factors in individuals
adverse effects(acute toxic events, drug interactions)
drug efficacy
SNPs and pharmacogenetics (2)
to identify a SNP allele / haplotype that predisposes individuals to an adverse drug effect
association study: testing SNPsin genes coding for drug-metabolizing enzymes
(eg. cytochrome P450 mono-oxygenase gene family)
Clinical trial of a drug
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
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
´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
Conclusions (2)
The full c
linical p
otential o
f
SNPs has yet to be re
alized
more accurate predictive models for complex diseases
´tailored´ or personalized medicine with better, safer medication
financial, ethical, personal issues
Prospects for the post-genomic era
SNP analysis + gene expression +
(SNP-related) functional proteomics