PDF Download - Laborwelt

B L I T Z L I C H T
Fig. 2: Array manufacturing. Affymetrix production operator loads a wafer into the modular oligosynthesizer,
which performs sequential addition of phosphor ammodites to the wafer.
genotype. By examining these combinations of
colors for as many as 10,000 SNPs on a single
array, researchers can determine the exact
genotype for each targeted SNP detected and
imaged on the microarray.
Discovering the genetics
of complex disease
High-density genotyping microarrays enable
scientists to conduct whole-genome
association studies today to understand
the genetics of complex disease or drug
response. Scientists like Josephine Hoh at
the Yale University are able to home in on
disease-associated mutations by using 100K
SNP microarrays that provide the genetic
information processing power needed to
identify a key mutation associated with agerelated
macular degeneration. Hoh’s recent
study, published in the April 2005 issue of
Science, scanned 100,000 SNPs from just 146
people; previous technologies that looked at
far fewer SNPs would have required Hoh to
study thousands of people to generate results
with the same scientific significance.
Larger association studies can also be designed
to help identify the comprehensive
catalog of genes, pathways, and predictive
biomarkers associated with disease. The Serono
Institute used the Mapping 100K Set to
identify 80 genes related to multiple sclerosis
(MS). Serono scientists expect to find many
more genes with the Mapping 500K Set, that
they expect will fall into five to ten different
disease pathways.
Often the ideal experiment tests a preexisting
hypothesis about particular genes,
pathways, or regions of the genome. Dr. John
Todd of Cambridge University’s Juvenile
Diabetes Research Foundation/Wellcome
Trust Diabetes and Inflammation Laboratory
(DIL) is among the first to use MegAllele pan-
els of 10,000 non-synonymous SNPs - SNPs
that change the sequences of proteins – for
a whole-genome association study to find
genes contributing to type 1 diabetes. Todd’s
research group is comparing the SNP profiles
between 1,000 control samples and 1,000 diabetic
samples; he plans to analyze more than
20,000 DNA samples already collected from
diabetes patients and their relatives.
Discovering the genetics
of variable drug response
Studies to identify genes associated with drug
response, efficacy and toxicity may become
one of the most promising applications for
whole-genome DNA analysis. Microarrays
able to genotype more than 500,000 SNPs
distributed across the genome now allow
researchers to readily genotype large populations
of responders vs. non-responders to a
given drug for phenotypes including efficacy
and toxicity. With these kinds of genetic studies,
scientists hope to elucidate the genes
contributing to variable drug response.
In late-stage clinical trials for example,
microarray genotype analysis could be used to
stratify patient populations to eliminate poor
or toxic responders from key Phase III trials.
Such stratification would help ensure maximum
effectiveness through clearer statistical
differentiation between drug and placebo,
while also reducing size and cost of trials and
improving the odds of drug approval. In addition,
once a drug is on the market, patient
stratification could be used to accelerate drug
expansion into new indications through faster,
smaller, more definitive Phase IV trials, or to
establish medical superiority of a late-to-market
drug relative to entrenched competitors in
an important class of patients. Genome-wide
genotype information will also fuel future
research. By better understanding genetic
mechanisms of drug response in patients, researchers
will have made significant progress
on finding the next generation drug.
Already, leading pharmaceutical, biotech,
and university researchers have embraced
microarray genotyping technology. Researchers
in a pharmacogenomic study at the Mayo
Clinic are using the 100K to investigate the
genetic basis for differential responses to
antihypertensive drugs in different patients
and populations. The scientists hope to
identify genes influencing drug response and
ultimately tailor antihypertensive therapy for
individual patients.
The way ahead
Whole-genome genotyping microarrays provide
scientists with a way of examining the
underlying genetics of responders and nonresponders
without any of the assumptions or
limitations used in a candidate-gene approach.
For most drugs with variable responses, little
is known about why they work in some
patients and why not in others. Genotyping
microarrays enable scientists to explore the
whole genome and identify predictive markers
of disease and drug-response, that may
ultimately provide more tailored, effective
and safer courses of treatment and help avoid
the more than 100,000 annual fatalities from
adverse drug reactions in the US alone 11 .
References
[1] Fodor, S. P. et al. Light-directed, spatially addressable parallel chemical
synthesis. Science 251, 767-73 (1991).
[2] Fodor, S. P. et al. Multiplexed biochemical assays with biological chips.
Nature 364, 555-6 (1993).
[3] Pease, A. C. et al. Light-generated oligonucleotide arrays for rapid DNA
sequence analysis. Proc Natl Acad Sci U S A 91, 5022-6 (1994).
[4] Gissen, P. et al. Mutations in VPS33B, encoding a regulator of SNAREdependent
membrane fusion, cause arthrogryposis-renal dysfunctioncholestasis
(ARC) syndrome. Nat Genet 36, 400-4 (2004).
[5] Middleton, F. A. et al. Genomewide linkage analysis of bipolar disorder by
use of a high-density single-nucleotide-polymorphism (SNP) genotyping
assay: a comparison with microsatellite marker assays and finding of
significant linkage to chromosome 6q22. Am J Hum Genet 74, 886-97 (2004).
[6] Puffenberger, E. G. et al. Mapping of sudden infant death with dysgenesis
of the testes syndrome (SIDDT) by a SNP genome scan and identification of
TSPYL loss of function. Proc Natl Acad Sci U S A (2004).
[7] Sellick, G. S., Garrett, C. & Houlston, R. S. A novel gene for neonatal diabetes
maps to chromosome 10p12.1-p13. Diabetes 52, 2636-8 (2003).
[8] Uhlenberg, B. et al. Mutations in the Gene Encoding Gap Junction Protein
alpha 12 (Connexin 46.6) Cause Pelizaeus-Merzbacher-Like Disease. Am J
Hum Genet 75 (2004).
[9] Klein, R. J. et al. Complement factor H polymorphism in age-related macular
degeneration. Science 308, 385-9 (2005).
[10] Kennedy, G. C. et al. Large-scale genotyping of complex DNA. Nat Biotechnol
21, 1233-7 (2003).
[11] Lazarou, J., Pomeranz, B. H. & Corey, P. N. Incidence of adverse drug reactions
in hospitalized patients: a meta-analysis of prospective studies. Jama
279, 1200-5 (1998).
Contact
Greg Yap, Affymetrix Inc.
Vice President DNA Products
3380 Central Expressway
Santa Clara, CA 95051
Tel: +1-408-731-5000
Fax: +1-408-731-5380
www.affymetrix.com
30 | 6. Jahrgang | Nr. 6/2005 LABORWELT