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