[Dr. Teri Manolio] I thought we would, sort of, focus on
genome-wide association studies because it's been said that
2007 may be the year of genome-wide associations.
This is the famous tidal wave of hook's eye,
and what you probably have been seeing in the journals
and papers have been a whole series,
just a slew of genome-wide association studies,
coming down the pipe.
So most recently there was the report from the Wellcome
Trust Case Control Consortium on 14,000 cases of seven
common diseases and 3,000 shared controls.
That was in Nature, I believe.
And then, two follow-up papers published at the
same time on Crohn's Disease and Type 1 diabetes.
Just about two weeks before there was a genome-wide
association study of breast cancer,
and then two other papers on breast cancer.
Just before that there were two papers on coronary disease:
one from Iceland, one from Texas.
A few weeks before that: three studies on diabetes
in Fins and Swedes and a group in the UK.
And shortly before that there was a series of
papers on prostate cancer, again, three papers coming
out together, very nicely coordinated.
And even though these aren't 2007 papers,
very soon, or recently before that -- this one paper on
inflammatory bowel disease in October, the other on
age-related macular degeneration.
And perhaps the one that started it all,
the compliment factor H paper shown here, which came in,
in March of 2005, and really kind of
got the field rolling.
So that we're all sure what we're talking about.
A genome-wide association study is a method for interrogating
all, roughly 10 million variable points,
those single letter base pair spellings
across the human genome.
Well maybe not all of those spots are interrogated,
but probably a good proportion of them are
in this technology.
Variations are inherited in groups so you don't have
to test at all 10 million points.
In the blots we recognized are shorter on populations
that are older like those of recent African ancestry.
So you have to test more SNPs or more variants in those.
But now the technology really allows us to do this kind
of work in unrelated persons, assuming a shorter area
of linkage than had previously relied upon for family-based
linkage studies, which means that they are available for
population-based cohort studies, clinical trials, surveys,
et cetera, the kinds of work that the SER is very heavily
involved in.
And this is the kind of data that you sometimes see this
is a display from the diabetes study and done
by the Bird MIT here in Massachusetts.
And it just shows all of the associations that they saw
across 500,000 SNPs shown by chromosome -- very colorful,
pretty slide -- and these being the associations that
look like they're somewhat suggestive and worth looking
forward into.
So we do recognize then that understanding the
genome structure and being able to do this kind of typing
really gives us unprecedented opportunities to define genetic
contributions to disease.
But there has been some slowness in applying
these kinds of knowledge, partly because there are
significant differences between disciplines.
There is the genetics of genomics field,
which is very technology-driven,
population based epidemiology, which is very population
and person driven, and we need to bring
those two fields together.
One of the challenges is some of the language differences.
Geneticists talk about copy number variants,
about gene deserts, about based factors,
and HapMap, and cell files, and inversions and epistasis.
Sort of like this fellow in the Larson cartoon,
"Understanding only German, Fritz was unaware that the
clouds were becoming threatening,"
and here the clouds say, "Hey, what are you looking
at, buddy?
You want trouble?
You found it."
So hopefully we'll be able to do a little bit of translation
while we're here and also identify some of the cultural
challenges that there may be in bridging this.
This somewhat [unintelligible], so.
So the structure of the session, we're going from 8:30 to 5:00,
so it will be full day.
We'll have Wendy Post and Debbie Nickerson
start with talking about their experiences in bridging
these fields.
Then David Hunter on initial and replication studies,
Elizabeth Pugh on genotyping platforms and quality control,
Nancy Cox on selection of markers to carry forward
after your initial study, Laura Scott on managing
and analyzing data.
Then we have a lunch break.
Then promoting collaborations: Bob Hoover.
Data deposition and access by Jim Ostell;
community concerns from Dan Levy;
and Framingham, data sharing, and collaborations:
Sandy Singleton.
Synthesizing findings from Martin Gwinn at the CDC,
and then a summary panel discussion of sort of best
practices that we've discussed and identified
during this session.
And other, you know, questions or issues that have come up,
and possible additional research or tools that
are needed as identified by ya'll, and a word from
our sponsor.
This is not a drug company or industry-sponsored group.
This is entirely your tax dollars at work.
This is actually wholly through the Genes, Environment,
and Health Initiative.
Don't ask me why this has an acronym of GEI when it has
four words in the title, but that's another
governmentees kind of thing.
And you will find that the Web site for this
is shown here.
If you just search for genes and environment,
it will pop up.
And as shown here there are two parts to that,
the genetics program and the exposure biology program.
Just to say a few words about that.
It's an NIH-wide initiative that actually was begun
by the secretary of HHS in fiscal '07,
so this year.
There are $40 million that are committed to identifying
genetic and environmental contributions to
common diseases.
Twenty-six million of that is dedicated
to the genetic component, and $14 million is dedicated
to developing innovative exposure biology,
measures of environmental exposures.
Also the NHGRI office of population genomics,
which is where my group is located, is findable through
the NHGRI Web page through this somewhat cryptic number
here, 19518660.
I think if you search this on Google you can find us,
but at any rate, what that describes
is the goals of our office, which are to bring
epidemiology and genomics together and to apply
genomic technologies to population-based studies.
So we were established basically to do that.
And one of our key goals is to support cross-disciplinary
training of geneticists in epidemiologists.
So this meeting is critical to that.
We also have a meeting sort of annually throughout NIH
where we try to get the institutes and centers,
or ICs as we call them, to discuss how we can
approach applying genomic technologies to population
studies throughout NIH.
And genome-wide studies, for the rest of us,
is this session here in June, and we will be having another
session more for the genetics folks at the
Society for Human Genetics in San Diego in October,
which will really be sort of a primer on epidemiologic study
design, and that will be run by my colleague,
Emily Harris.
So again, we thank SCER for allowing us to do this
in collaboration with them, especially Mike Bracken,
the president, and Peggy Christiansen,
who's been very helpful in putting this together.
A few housekeeping issues: videotaping, we are doing
videotaping for this because we want to make this available
to others who weren't able to be here today,
and we will be Web archiving it on the
Genes and Environment site.
So, be aware that you're being taped,
and please use the microphones during the discussion sessions.
We'll have a 20-minute discussion after each
two talks.
So there are also two 20-minute breaks,
and then a 45-minute lunch.
We would ask people, sort of, not to congregate in the back
where the food is, except at the breaks,
and then to come back up to the front.
I'm sorry that we're not able to give you lunch,
but we do have a local lunch list provided there,
and there are a few places here.
It's only 45 minutes, and Bob Hoover will be
very cranky if you don't come back on time at 1:00.
So, please do be back on time.
And you do have a little homework assignment
during the sessions.
Since we're having a closing discussion on best practices
and research tools needed, it would really be of great
value if you could identify things that you can then,
you know, raise during that discussion with us.
And we're also asking the speakers to identify one
to two things during the course of the day
that we will then be discussing,
in terms of new needs, research needs and other
kinds of needs, communication consent forms, whatever it
might be, which would be of great value to the
Genome Institute, to the Genes and Environment Initiative,
and we will share them with the Society for Epidemiological
Research, so it may be of use to them,
as well.
We selected speakers specifically for their
strongly expressing laid-back genes, and if you have
questions, just ask, if you need to know
something in order to go further.
Feel free to raise your hand from your seat.
During the discussion session, if you'd come to the
microphones, it will make it easier to call on you.
But, you know, if you don't know what a SNP is,
and they haven't explained it, or there is some other jargon
that's gone by, just feel free to ask.
And remember there are no stupid questions.
Well maybe there is one, here's a Gary Larson,
"Say what's a mountain goat doing up here,
way up here in a cloud bank?"
So hopefully those of you who have flown over here
won't run into that.
And do watch for the PowerPoints and the video
that will be on the Genes and Environment Web site.
We have a special section for that,
meetings and workshops.
And ours will be appearing very shortly.
So, I think I'll stop at that point,
ask if there's any questions.
Okay, if not.