 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 association. This is the famous tidal wave of Hokusai, and what you've probably been seeing in the journals and papers have been a whole series, just a slew of genome-wide association studies coming down the pike. 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 before that, and 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. And a few weeks before that, three studies on diabetes in Finns, in Swedes, in 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 Complement 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, the single-letter base pair spellings across the human genome. 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 all 10 million points in the blocks we recognize are shorter in 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 shorter areas of linkage than had been 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 SCR has very heavily involved in. And this is the kind of data that you sometimes see. This is a display from the diabetes study done by the Broad MIT here in Massachusetts, and this 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 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's the genetics and 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 base factors and HAPMAP and cell files and inversions and epistasis, and sort of like this fellow in this 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 chasm. So the structure of the session today, we're going from 8.30 to 5, so it'll be a 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. And we have a lunch break, then promoting collaborations. Bob Hoover, data deposition and access by Jim Ostell, community concerns from Dan Levy in Framingham, data sharing and collaborations, Andy Singleton, synthesizing findings from Marta Gwyn at the CDC, and then a summary panel discussion of sort of best practices that we've discussed and identified during the session and other, you know, questions or issues that have come up and possible additional research or tools that are needed as identified by y'all. 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 partly through the, it is actually wholly through the Genes and 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 government to use kind of thing. And you will find that the website 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 2007, so this year. There are 40 million dollars that are committed to identifying genetic and environmental contributions to common diseases. 26 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 webpage through this somewhat cryptic number here, 1951-866-0. I think if you search this in 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 population-based technologies, sorry, 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 and epidemiologists. And 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 in that run by my colleague Emily Harris. So again, we thank SER for allowing us to do this in collaboration with them, especially Mike Bracken, the president, and Peggy Christensen, 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 o'clock. So please do be back on time. And you do have a little homework assignment during the session. 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 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 Epidemologic 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 come to the microphones, it'll make it easier to call on you. But if you don't know what a SNP is and they haven't explained it, or there's some other jargon that's gone by, just feel free to ask. And remember, there are no stupid questions. Well, maybe there's 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 in the video that will be on the Jeans and Environment website. 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 are any questions. If not.