New Gene Tool May Unlock Root Causes of Disease
by Rita Jenkins
zone3
Genetic researchers have made substantial advances in understanding
the root causes of common diseases and the history of human evolution. An
international consortium of more than 200 scientists has concluded that
genetic variants located physically close to each other are inherited
collectively as groups, called haplotypes. The comprehensive catalog of
all of these blocks is known as the "HapMap." Genetic researchers
have made substantial advances in understanding the root causes of common
diseases and the history of human evolution, according to a series of
reports published in scientific journals this week.
Chief among these accomplishments is the work of an international
consortium of more than 200 scientists from Canada, China, Japan, Nigeria,
the United Kingdom and the United States published in the October 27 issue
of the journal Nature.
The team studied DNA samples from four different parts of the world and
concluded that genetic variants located physically close to each other are
inherited collectively as groups, called haplotypes. The comprehensive
catalog of all of these blocks is known as the "HapMap."
"Built upon the foundation laid by the human genome sequence, the
HapMap is a powerful new tool for exploring the root causes of common
diseases," says David Altshuler, MD, PhD, director of the program in
Medical and Population Genetics at the Broad Institute of Harvard and MIT.
"Such understanding is required for researchers to develop new and
much-needed approaches to understand the still-elusive root causes of
common diseases, such as diabetes, bipolar disorder, cancer and many
others," he adds.
Altshuler and Peter Donnelly, PhD, of the University of Oxford in
England are the corresponding authors of the Nature paper.
Greatest Information in Most Efficient MannerIt has been known for a
long time that diseases run in families, with perhaps half the risk of any
given common disease explained by genetic differences inherited from one's
parents. Inheritance also can play a role in different responses to a drug
or to an environmental factor.
Because the underlying causes of these common diseases and therapeutic
responses remain largely unknown -- and because knowing this information
is necessary for successful development of new approaches to prevention,
diagnosis and treatment -- identifying the genetic contributors to human
health is a fundamental goal of biomedicine.
A new genomics-based approach to human genetics was proposed nearly a
decade ago to catalog common human DNA sequence variations comprehensively
and to test them systematically for their association to disease in human
populations.
Although it is theoretically possible to capture all of this
information by sequencing every individual human genome, this is neither
technically nor financially feasible.
"The data from the HapMap project allows scientists to select the
particular DNA variants that provide the greatest information in the most
efficient manner, lowering the costs and increasing the power of genetic
research to identify the origin of disease," says Mark Daly, an associate
member of the Broad Institute of Harvard and MIT. Daly led the Boston
team's statistical and analytical work, and was a member of the writing
group for the Nature paper.
Millions of SNPs a DayMoreover, the HapMap project helped spur a
remarkable advance in the technology for testing genetic variations in
DNA, making it possible to undertake comprehensive studies in large
patient samples.
A single nucleotide polymorphism, or SNP (pronounced "snip"), is a
small genetic change, or variation, that can occur within a person's DNA
sequence.
"When we started doing this work a number of years ago, determining the
genotype of a SNP in a patient cost nearly a dollar, and we could do
hundreds a day," notes Stacey Gabriel, director of the Broad Institute's
Genetic Analysis platform and an author of the Nature paper.
"Today the prices have dropped in many cases to a fraction of a penny
per genotype, and we can do millions a day," Gabriel notes. "This is the
difference between not being able to do the studies, and getting them done
rapidly and well.
"Tag SNPsThe HapMap provides excellent power to capture most human
variation and link it to disease or other traits, according to a related
paper published in the November issue of Nature Genetics.
Paul de Bakker, Roman Yalensky and their colleagues demonstrated this
finding by developing and evaluating methods to select "tag SNPs" that
capture the genetic variation in each neighborhood with a minimum amount
of work.
Using these tags, scientists can compare the SNP patterns of people
affected by a disease with those unaffected far more efficiently than
previously has been possible.
"Compared to directly genotyping all common SNPs in the genome in all
individuals of a disease study, we observe that selected tag SNPs based on
HapMap can save genotyping costs by almost an order of magnitude without
losing much power to detect a true association," says de Bakker, a
postdoctoral fellow in Altshuler and Daly's group at the Broad Institute.
The widely used tool for tag SNP selection was developed by de Bakker
and colleagues.
Previous Computer Models Too SimplisticAnother important observation
revealed by the availability of the HapMap data is that previous computer
models of human genetics are too simplistic and can lead to false
conclusions about the role of genes or genetic loci in different diseases.
Stephen Schaffner, Altshuler and their colleagues at the Broad
Institute describe the limitations of these prior models in a paper
published in the November issue of Genome Research. They also provide the
entire scientific community with updated models that more closely
approximate reality, based on the empirical data generated by the HapMap
Consortium.
"Better computer models can be valuable tools in understanding the
nature of human DNA variation, past changes in human populations size, and
evolutionary selection," says Schaffner, a computational biologist in
Broad's program in Medical and Population Genetics.
Candidates for Natural SelectionThe public availability of HapMap's
genome-wide variation data set also makes it possible for scientists to
make systematic examinations of potential natural selection sites in the
human genome, as well as to re-evaluate previous claims for such
selection.
Pardis Sabeti, Eric Lander and their colleagues at the Broad Institute,
together with Stephen O'Brien and his colleagues at the National Cancer
Institute, used the HapMap data to examine a prominent reported case of
natural selection related to HIV infection.
A genetic variation in a T-cell receptor called CCR5-?32, which confers
strong resistance to infection by HIV and has been implicated in
resistance to the bubonic plague, did not arise recently in the human
population, they report in the November issue of PLoS Biology.
"With the benefit of greater genotyping and empirical comparisons from
the HapMap, we were able to show that the pattern of genetic variation
seen at CCR5-?32 does not stand out as exceptional relative to other loci
across the genome and is consistent with neutral evolution," says Sabeti,
a postdoctoral fellow at the Broad Institute.
"In fact, the CCR5-?32 allele is likely to have arisen more than 5,000
years ago, rather than during the last 1,000 years as was previously
thought," Sabeti adds.
In addition to allowing the re-examination of previous claims of
selection, the HapMap data give scientists a new way to identify novel
candidates for natural selection.
Attainment of GoalThe successful completion of the HapMap has its roots
not only in the completion of the human genome sequence in 2001, but also
in the massive effort to characterize and catalog the millions of SNPs
across the genome.
Based on these initial data, the haplotype structure of the human
genome was recognized as early as 2001, leading directly to the formation
of the International HapMap Consortium. Finally, methods for identifying
the influence of natural selection on the human genome were described in
2003.
Altshuler, Lander, Gabriel, Daly and many other Broad Institute
scientists led or contributed significantly to all of these efforts, in
addition to their role in the completion of the HapMap and demonstrations
of its utility, as outlined above.
In October 2002, the International HapMap Consortium set the ambitious
goal of creating the HapMap within three years. The Nature paper marks the
attainment of that goal with its detailed description of the Phase I
HapMap, consisting of more than 1 million SNPs.
The consortium also is nearing completion of the Phase II HapMap, which
will contain nearly three times more SNPs than the initial version and
will enable researchers to focus their gene searches even more precisely
on specific regions of the genome.
In line with the Broad Institute's commitment to building critical
resources for the scientific community, HapMap data are freely available
in several public databases, including the HapMap Data Coordination Center
(http://www.hapmap.org/) the
NIH-funded National Center for Biotechnology Information's dbSNP (http://www.ncbi.nlm.nih.gov/SNP/index.html)
and the JSNP Database (http://snp.ims.u-tokyo.ac.jp/) in
Japan.
ABOUT THE AUTHOR
Rita Jenkins is a health journalist for Daily News Central, an online
publication that delivers breaking news and reliable health information to
consumers, healthcare providers and industry professionals: http://www.dailynewscentral.com/
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