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Biennial Report of the Director
National Institutes of Health Fiscal Years 2008 & 2009

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Biennial Report of the Director

Summary of Research Activities by Key Approach and Resource
Genomics








When the United States launched a massive effort to sequence the human genome in 1990, many said it could not—or should not—be done. Skeptics feared that the cost would be too high, draining funds from other, more promising research. They warned that adequate technology did not exist to complete the project, and that the cost of developing the necessary technology was unsupportable. Methods of sequencing DNA were barely past the laboratory-bench stage and cost about $10 for each base pair (bp); at that rate, sequencing a human genome would cost at least $30 billion. Moreover, the prevailing wisdom was that most of the genome was meaningless "junk" that could be ignored, rather than "coding areas"—the genes—that instruct cells in the body how to make proteins.

But one of the earliest goals of the Human Genome Project was to boost the speed and cut the cost of sequencing DNA. By 2004, newly developed technology could sequence a full genome for just $20 million. By 2009, even newer sequencing machinery could do the job for $100,000. Now, NIH is on track to achieve its goal of technology that can sequence an individual patient's DNA for $1,000—less than the price tag of some high-tech medical tests today—which will usher in a new era of medicine. (And along the way, scientists are learning that the "junk" is very important indeed.)


Introduction

Genomics is the study of an organism’s entire genome—the complete assembly of DNA (deoxyribonucleic acid), or in some cases RNA (ribonucleic acid)—that transmits the instructions for developing and operating a living organism. Genomic research focuses not just on individual genes but also on the functioning of the entire genome as a network and, importantly, on how this network interacts with environmental factors to influence health and cause disease. Genomics is a new and challenging discipline that is increasingly used in virtually every field of biological and medical research.

DNA is made up of four chemical compounds called "nucleotides"—adenine, thymine, guanine, and cytosine—denoted by the letters A, T, G, and C respectively. These nucleotides are assembled in two parallel strands in the form of a double helix. Each nucleotide in one strand always links to the same partner on the other strand: A always pairs with T; C always pairs with G. Each of these pairings is referred to as a "base pair." The human genome consists of about 3 billion base pairs, packaged in 23 sets of chromosomes, wrapped extremely tightly into the nucleus of virtually every cell in the body. Identifying the base pairs—and thus the letters—and the order in which they appear on any stretch of DNA is called "sequencing" that segment.

DNA’s double helical structure was discovered in 1953. The human genome was fully sequenced 50 years later, in 2003, by a 13-year, U.S.-led multinational effort called the Human Genome Project, which ended ahead of schedule and under budget. The sequencing of the human genome generated immense scientific excitement. It provided a new means of analyzing the functions of cells, tissues, and systems in the body and offered new tools for understanding the causes of disease. It laid the foundation for broad new scientific disciplines such as proteomics, the study of the structure and function of all the proteins produced by the body (in response to instructions carried by the genes). Recent studies have demonstrated that the genome contains more information than can be interpreted from just its sequence. It is more complex, more variable in its structure, and more complicated in its internal interactions than anyone imagined just a few years ago.

Almost every human disease or disorder has a genetic component and an environmental component. The genetic component for some heritable diseases, such as sickle cell disease or cystic fibrosis, result from mutations in single genes—changes that disrupt the function of the protein they encode. However, in most diseases the role of genes and the environment is more complicated. Some diseases arise as a result of spontaneous gene mutations that occur during a person’s lifetime; others are caused by complex cascades of changes in gene expression triggered, perhaps, by environmental factors. Differences as small as one letter in our 3 billion pairs of DNA letters can cause disease directly or make people respond differently to particular pathogens or drugs. Multiple genetic and environmental factors play a role in myriad common diseases, such as heart disease, cancer, and asthma, but for no common disease have all the genes involved yet been identified.

Educational resources, including multimedia presentation, to help the public understand genomics are available on the NIH website.

As a result of the overwhelming influence of the genome on human health, virtually every NIH Institute and Center now engages in genome-related research.

As a result of the overwhelming influence of the genome on human health, virtually every NIH IC now engages in genome-related research. Like many NIH Institutes, NCI supports a huge array of gene-oriented projects, including Genome-Wide Association Studies (GWAS)—in effect, full-body DNA scans—that recently detected new genetic factors involved in breast, prostate, and colon cancers. Over the past 2 years, NHLBI and NIGMS have sponsored a research consortium that combined both genetic and clinical data to devise a computer algorithm for setting the proper dose of the blood-thinner warfarin, commonly prescribed for heart patients and others.14 A major clinical trial began in early 2009 to test whether that new algorithm is better than the current trial-and-error method. NIMH-supported researchers recently identified a stretch of DNA (on chromosome 6) that appears to be implicated in both schizophrenia and bipolar disorder—a finding that may aid the search for treatments and suggests that both disorders flow from errors in wiring the brain during fetal development, potentially opening a new line of research.15,16,17 NIAID now has sequenced the genomes of thousands of infectious microorganisms, including 4,000 influenza viruses; within a few months of the emergence of the 2009 H1N1 influenza—the so-called "swine flu" virus—in early 2009, it had sequenced nearly 1,000 separate H1N1strains.

Within a few months of the emergence of the 2009-H1N1 influenza—the so-called "swine flu" virus—in early 2009, NIH had sequenced nearly 1,000 separate H1N1strains.

NIH researchers and grant recipients also have increased the pace of sequencing other nonhuman genomes. Full sequences of nearly 200 organisms now have been completed or are underway, and not just the genomes of our close primate relatives such as the chimpanzee. Between 2007 and 2009, NIH-supported scientists completed sequencing the genomes of 16 invertebrates, 1 mammal, and the egg-laying duck-billed platypus—whose genome retains many reptilian features—and selected 34 new organisms for full-genome sequencing. Comparing the human genome to the genomes of other creatures, including insects and even single-celled organisms, reveals stretches of DNA that have remained similar over millions of years of evolution. These "conserved" sequences are thought to play an important role in the functioning of a living organism, even if scientists do not yet know what that role is.

Genes themselves, the "coding regions" of DNA that direct cells to make particular proteins, account for only about 2 percent of the human genome. Locating the noncoding but functional sequences throughout the rest of the genome is the main mission of the ENCODE research consortium (the acronym stands for ENCyclopedia Of DNA Elements). NIH also has pressed ahead with the Model ENCODE project (modENCODE) to identify all the functional elements in the genomes of two hugely important and widely used laboratory model organisms—the fruit fly Drosophila melanogaster and the roundworm Caenorhabditis elegans.18 The strategy is that identifying genomic mechanisms in these model organisms will elucidate novel research directions for human genomic and other researchers. (Also see the section on Molecular Biology and Basic Research in Chapter 3.)


14 International Warfarin Pharmacogenetics Consortium. N Engl J Med 2009;360:753-64. PMID: 19228618. PMCID: PMC2722908.
15 Shi J, et al. Nature 2009;460(7256):753-7. PMID: 19571809. PMCID: PMC2775422.
16 Stefansson H, et al. Nature 2009;460(7256):744-7. PMID: 19571808.
17 Purcell SM, et al. Nature 2009;460(7256):748-52. PMID: 19571811.
18 Celniker SE, et al. Nature 2009:459(7249):927-30. PMID: 19536255. PMCID: PMC2843545.


Approaching the Era of Personalized Medicine

DNA sequencing and analysis projects serve another purpose as well: advancement of technology and bioinformatics that may soon bring revolutionary improvements to the practice of medicine. The development of new methods to sequence DNA faster and more cheaply is the central goal of some NIH-sponsored projects, and as NIH has continued to fund technological innovation in this area, the costs have continued to fall remarkably. Soon, when a patient’s full genome can be sequenced for less than the cost of other routine medical tests, and when ongoing genomic research programs have further broadened and deepened our understanding of the genome’s functioning, medical science will stand on a new plateau. The practice of medicine will move beyond a one-size-fits-all approach—and the promise of personalized medicine will be realized. One application of personalized medicine is pharmacogenomics, which seeks to understand the inherited variations in genes that dictate drug response. Furthermore, it explores the ways these variations can be used to predict whether a patient will have a good response to a drug, a poor or adverse response to a drug, or no response at all. By understanding the differences in the genetic basis of drug responses, scientists hope to enable doctors to prescribe the drugs and doses best suited for each individual. The mission of the NIH Pharmacogenetics Research Network (PGRN) is to better understand the genetic basis for variable drug responses and identify safe and effective drug therapies designed for individual patients.

The mission of the NIH Pharmacogenetics Research Network is to better understand the genetic basis for variable drug responses and identify safe and effective drug therapies designed for individual patients.

Most of the genome research that will yield direct clinical implications, improve our understanding of human health, and change clinical practice still lies ahead. However, over the next decade, research will unlock the true potential of this foundational work, leading scientists closer to better means for preventing, diagnosing, and treating disease.


Summary of NIH Activities

Among NIH’s key activities and accomplishments in the field of genomics in FYs 2008-2009 were those involving the following:

  • New Genome-Wide Association Studies (GWAS). Using DNA from tissue samples, GWAS scan and compare entire genomes of people with and without a particular disease, looking for single-base differences (known as single nucleotide polymorphisms, or SNPs) that might signal the presence of a gene or some other functional sequence implicated in the disease. GWAS are based on the Haplotype Map (HapMap) of the human genome, produced via an NIH-led international research team earlier in the decade that identified more than 3 million relatively common SNPs in human genomes that serve as markers for larger neighborhoods of DNA sequences. GWAS scans point to regions of the genome that are worthy of closer study in seeking the genetic cause of a disease. Hundreds of such studies have been conducted since the technique was first developed in 2005, flagging genetic areas that may be linked with at least 80 different diseases and disorders including heart disease, diabetes, obesity, and many types of cancer. In 2008 alone, GWAS identified more than 130 genetic factors involved in human disease. Among the GWAS currently under way is an effort to determine the genes involved in HIV disease progression and susceptibility to HIV acquisition.
  • The 1,000 Genomes Project. This international research consortium assembled and led by NIH began sequencing the genomes of at least 1,000 people to improve dramatically on the current HapMap. The HapMap pinpoints DNA variations that are present in 5 percent or more of humans. The 3-year, 1,000 Genomes Project will achieve a finer resolution, creating a catalog of variations that are present in as few as 1 percent of people. It will focus even more tightly on the coding regions of genes, locating variations that are present in as few as 0.5 percent of individuals. Importantly, the new project will catalog not just SNPs but also structural variations in human DNA, such as deletions, duplications, and rearrangements of DNA sequences.
  • Structural variation. Scientists have gathered increasing evidence that the genome is not a string of independently operating genes, but rather is a hugely complicated, integrated whole, and that variations in the structure of the chromosomes have a major impact on human health. Yet, the mechanisms involved are not fully understood. In 2008, an NIH-supported research consortium produced the first sequence-based map of large-scale structural variations, ranging from a few thousand bases to several million.19 These include deletions of whole genes, repetitions of sequences (sometimes multiple repetitions), and rearrangements of stretches of DNA. Some variants already have been linked to diseases, such as coronary heart disease, schizophrenia, and autism, and to differences in susceptibility to HIV infection.
  • New disease genes. NIH researchers have identified individual genes or regions of DNA associated with, among other diseases and disorders: schizophrenia and bipolar disorder; cancers of the skin, lung, brain, pancreas, breast, prostate, and testicle, and acute lymphoblastic leukemia; diabetes; periodontitis in African Americans; asthma; high blood pressure; heart arrhythmias; Crohn’s disease; obesity; and many others.
  • Clinical genomics. NIH began a large pilot project to test ways that high-throughput genome sequencing might be used in a clinical setting for diagnosing and treating patients. Using the NIH Clinical Center, the trial, dubbed "ClinSeq" (for clinical sequencing) will enroll an initial 1,000 patients with a spectrum of coronary artery calcification from normal to diseased and will sequence 200 to 400 areas of their DNA that contain genes suspected of involvement in heart disease. Patients will have the option of learning the outcome of their tests, and those who carry a variant of a gene that has been linked to disease will be counseled and followed up, possibly for years. The study is designed both as a pilot project to explore ways of using genome sequencing in patient treatment and as an effort to develop new data about particular genes’ involvement in heart disease. The project may expand in its later stages to cover other diseases.
  • Consumer interest. ClinSeq is not the only way that NIH is exploring whether people want to know what genomics might have to tell them. In a program known as the Multiplex Initiative, individuals ages 25 to 40 are offered free testing for 15 genes associated with higher risk for type 2 diabetes, heart disease, high cholesterol, high blood pressure, osteoporosis, lung cancer, colorectal cancer, and malignant melanoma. Those who are offered the testing use an interactive, Internet-based program designed by NIH researchers that helps participants ask questions about the genetic testing, get information, and decide whether to receive the testing. Meanwhile, Multiplex Initiative researchers monitor the participants’ decision process every step of the way. Those who decide to submit blood samples for the tests will be followed for some time afterward to see whether they change their behavior (for example, by adopting a healthier lifestyle or diet) in response to their test results.20 Researchers involved with this study have found that individuals who discuss their genetic information with their doctors may be among the most motivated to take steps toward more healthy choices.
  • Pharmacogenetics. NIH launched a major clinical trial to test a gene-based me thod of prescribing warfarin, a blood thinner that is widely used to prevent life-threatening blood clots. About 2 million Americans start taking warfarin each year, but the drug’s effect on individual patients is notoriously variable. Regular blood tests are needed both to establish an initial dose level and to maintain the proper level as time goes on—for months and often for years. In early 2009, an international research consortium combined patients’ genetic and clinical data to produce a computer algorithm that appeared to be more accurate than basing the initial dose on a patient’s clinical condition alone and then increasing or decreasing the dose to achieve the optimal blood level.1 NIH quickly began a multicenter clinical trial, known as the Clarification of Optimal Anticoagulation through Genetics (COAG) trial, to compare the gene-based method with the current trial and error approach in a much wider pool of patients. COAG will enroll 1,200 patients of varying backgrounds at 12 sites and will follow them for 6 months. Its outcome could improve protection against heart attacks and strokes for millions of Americans.
  • Nonhuman genomes. NIH completed full sequencing and analysis of multiple vertebrate and invertebrate animal genomes in 2008-2009. These include the platypus, domestic cattle, the wasp, other insects, and a large number of disease-causing organisms—such as the malaria-causing parasite Plasmodium vivax, the common intestinal parasite Giardia lamblia, the Lyme disease-causing tick Ixodes scapularis, and two species of the parasitic flatworms that cause schistosomiasis. Also sequenced were thousands of separate strains of the constantly changing human influenza viruses. Molecular comparisons of the 2009 H1N1 influenza and other flu strains may help scientists learn how 2009 H1N1 is evolving, how it is interacting with other strains, and whether it is gaining or declining in virulence.
  • Health Disparities. NIH-funded analysis of genomic data from 121 African populations, 4 African American populations, and 60 non-African populations revealed that all African populations descended from 14 ancestral groups. Most African Americans trace the majority of their ancestry to West Africa, a finding that will improve scientists’ ability to identify genetic risk factors in African and African American populations.

19 Kidd JM, et al. Nature 2008;453(7191):56-64. PMID: 18451855. PMCID: PMC2424287.
20 For more information, see http://www.genome.gov/pfv.cfm?pageID=25521052 and http://genome.gov/pvf.cfm?pageID=25521955.


Identifying Microbial Free-Riders: The Human Microbiome Project

Among the newer NIH initiatives is the 5-year Human Microbiome Project (HMP), an NIH-led international undertaking that seeks to identify and sequence the vast populations of microbes that live on and within the human body. Some scientists estimate that microbial cells outnumber human cells in a healthy adult by 10 to 1, but few of these fellow travelers have been characterized, and their role in human health largely is a mystery. Many, if not most, of these microbes cannot be grown in a laboratory dish; they are dependent on their natural environment—us. Therefore, to sequence their genomes, HMP researchers will use a new method called metagenomics, which involves sequencing and analysis of genetic material drawn from whole microbial communities in their natural setting.

Among the newer NIH initiatives is the 5-year Human Microbiome Project, an NIH-led international undertaking that seeks to identify and sequence the vast populations of microbes that live on and within the human body.

Initially, the project plans to analyze more than 250 samples from five human body sites—the skin, mouth, airways, gastrointestinal tract, and vagina—and produce a reference set of 1,000 microbial genomes. These will serve as a benchmark against which to compare further sequence data. The project also will test whether metagenomics can be used to link changes in the microbiome with human health.

In one early result from HMP, NIH researchers reported in May 2009 that human skin plays host to an even wider array of bacteria than anticipated.21 Drawing on just 20 skin sites from 10 volunteers, the researchers found more than 112,000 bacterial gene sequences representing 19 phyla, 205 genera, and great species diversity. The widest variety of microbes roams the forearm, with 44 species there on average. The least populated site is behind the ear, with 19 species. The major determinant of what bacteria live where seems to be the same factor that governs human real estate prices: location, location, location. Bacteria from any particular body site are more like bacteria from that site in other people than to bacteria elsewhere on the original donor’s body. In other words, donor A’s mouth bacteria are more like other people’s mouth bacteria than they are to bacteria living on donor A’s forearm.

Findings such as these will be useful, of course, in developing new treatments for many human diseases. For instance, the study may contribute to efforts to control methicillin-resistant Staphylococcus aureus (MRSA), a dangerous bacterium that is resistant to current antibiotics and thus is a growing threat to human health. Scientists had known that many people harbored S. aureus in their nostrils; the HMP study detected very similar microbial communities in the crease of skin outside the nose, offering new clues about how the virus is spread, and possibly offering new approaches to preventive measures.9


21 Grice EA, et al, Science 2009;324(5931):1190-2. PMID: 19478181. PMCID: PMC2805064. For more information, see http://genome.gov/pfv.cfm?pageID=27532034.


Decoding Cancer

Genomics research has moved the battle against cancer into new, exciting territory. In FY 2008 and FY 2009, GWAS led to the detection of new genes or DNA regions associated with a variety of human cancers. In addition, sequencing of the abnormal DNA within tumors provided new clues about cancer development and potential treatment.

NIH supports a wide variety of such studies, including: the Cancer Genetic Markers of Susceptibility (CGEMS) project, which has been expanded from an initial study of breast and prostate cancer; the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program, which uses genomics in an effort to develop treatments for childhood cancers; and The Cancer Genome Atlas (TCGA), which sequences the DNA within tumors and is being expanded because of the success of its original pilot stage.

Overall, more than 100 genetic variations associated with cancer risk now have been identified. Among the discoveries in FY 2008 and FY 2009 were: a link between pancreatic cancer and the gene that determines ABO blood type22 identification of a gene that appears to increase the risk of relapse in children treated for acute lymphoblastic leukemia23 and variations within several DNA regions that appear to raise the risk of breast,24 colorectal,25 and prostate cancers26–including, intriguingly, one stretch that contains no genes at all, but that may contain a regulatory sequence that controls a faraway gene (or genes), and may suggest a novel mechanistic pathway of cancer susceptibility shared by a variety of cancers involving this region.

More than 100 genetic variations associated with cancer risk now have been identified.

Sequencing the scrambled DNA within tumors has led to additional discoveries. In one-fourth of melanoma tumors, a gene known as MMP was damaged, indicating that MMP is a tumor suppressor and opening a new approach to treatment of melanoma and other cancers.27 Analysis of glioblastomas (a form of brain tumors) uncovered three disrupted genes and several damaged molecular pathways, suggesting an explanation of why some glioblastomas are resistant to chemotherapy.28 Sequencing of tissue from lung adenocarcinomas, the most common form of lung cancer, detected 26 frequently mutated genes, more than doubling the number of genes linked to the disease.29 Tumor sequencing has proved so fruitful that NIH has plans underway to carry out similar comprehensive analyses of 20 to 25 different cancer subtypes.

The rich lode of data produced by large-scale genomics studies in FY 2008 and FY 2009 may reveal yet more secrets. Much of the raw data is still being analyzed. Moreover, in late 2009, NIH held a workshop involving its own intramural researchers, university researchers, and private-sector officials to discuss the next steps: how to go about combining and analyzing the different data sets being produced, and how to cope with the flood of new data that is being produced as technology improvements make large-scale sequencing faster and cheaper. The advent of massively parallel sequencing technologies has opened an extensive new vista of research possibilities—elucidation of the human microbiome, discovery of polymorphisms and mutations in individual genomes, mapping of protein-DNA interactions, and positioning of nucleosomes—to name just a few. To store, access, and manipulate the enormous volume of read data generated from massively parallel sequencing experiments, NIH has created the Sequence Read Archive, which already contains more than 8,000 billion bases of DNA data.


22 Amundadottir L, et al. Nat Genet 2009;41(9):986-90. PMID: 19648918. PMCID: PMC2839871. For more information, see. http://www.cancer.gov/newscenter/pressreleases/ABOvariantPanScan.
23 Mullighan CG, et al. N Engl J Med 2009;360(5):470-80. PMID: 19129520. PMCID: PMC2674612. For more information, see http://www.nih.gov/news/health/jan2009/nci-07.htm.
24 Thomas G, et al. Nat Genet 2009;41(5):579-84. PMID: 19330030.
25 Yeager M, et al. Hum Genet 2008;124(2):161-70. PMID: 18704501. PMCID: PMC2525844.
26 Thomas G, et al,. Nat Genet 2008;40(3):310-5. PMID: 18264096.
27 Palavalli LH, et al. Nat Genet 2009;41(5):518-20. PMID: 19330028. PMCID: PMC2748394. www.nih.gov/news/health/mar2009/nhgri-29.htm.
28 Cancer Genome Atlas Research Network. Nature 2008;455(7216):1061-8. PMID: 18772890. PMCID: PMC2671642. http://www.genome.gov/27527925.
29 Ding L, et al. Nature 2008;455(7216):1069-75. PMID: 18948947. PMCID: PMC2694412. http://genome.gov/pfv.cfm?pageID=27528559.


Revolution in Technology

When the Human Genome Project was first conceived, the cost of sequencing DNA was about $10 per base pair, and the process was hands-on and painfully slow. If the technology had not been improved and automated, sequencing the genome would have taken more than 100 years and been impossibly expensive. As recently as 2004, the cost of sequencing a person’s genome with the then-existing technology would have been about $20 million. That year, NIH adopted the Advanced DNA Sequencing Technology program and set a target of reducing the cost of sequencing a human genome to about $100,000 in 2009 and to just $1,000 in 2014. The goal of a $100,000 genome was achieved in 2009; the drive toward a $1,000 genome is on track. That is comparable to the cost of many high-technology medical tests and would make individual genome sequencing tests feasible for hospital patients, ushering in—or at least opening the door to—the era of personalized medicine.

Through the Advanced DNA Sequencing Technology program NIH set a target of reducing the cost of sequencing a human genome. The goal of a $100,000 genome was achieved in 2009; the drive toward a $1,000 genome is on track for 2014.

The speed of sequencing also is being dramatically accelerated. Although producing the first full human genome sequence took 13 years and required an international consortium of many laboratories, by 2009 the job could be done in a few weeks on a single sequencing machine. The latest sequencing machines can achieve three times the throughput of the most recent previous platforms, and sequencing capacity is expected to continue growing exponentially. Moreover, the new technologies can detect not just single base changes but also structural variations—rearrangements, duplications, and deletions. The capacity for full genome sequencing is now a possibility for any research laboratory.

A 2009 NIH workshop concluded that these rapid gains in sequencing technology, encouraged and in many cases funded by NIH, will yield a flood of new data to analyze, on top of a data stream that is already testing the limits of current analytic abilities. Improved technology spurs new applications of genomic science. Bioinformatics—that is, computational biology methods, resources, and infrastructure—is a critical tool for the understanding of this wealth of data.30 This is a tremendous challenge, and opportunity, for 2010. (Also see the section on Disease Registries, Databases, and Biomedical Information Systems in Chapter 3.)

We look toward a future where individual genome sequencing will become both commonplace and affordable, and where primary care physicians will routinely consult their patients’ genome analyses for predictions of risk, diagnosis, and drug and dosage selections. As we educate the public and the medical community about the significance and limitations of genomic information, it will be possible to apply genomic knowledge to lessen the burden of disease through better screening, diagnostic, therapeutic, and prevention programs. (Also see the section on Ensuring Responsible Research in Chapter 3.)


30 Also see the section on Disease Registries, Databases, and Biomedical Information Systems in Chapter 3.


Notable Examples of NIH Activity
Key
E = Supported through Extramural research
I = Supported through Intramural research
O = Other (e.g., policy, planning, or communication)
COE = Supported through a congressionally mandated Center of Excellence program
GPRA Goal = Concerns progress tracked under the Government Performance and Results Act
ARRA = American Recovery and Reinvestment Act

IC acronyms in bold face indicate lead IC(s)

Functional Genomics of Disease

Medical Sequencing: As more is learned about the genetic contributions to disease, DNA sequence information will become even more important for providing medically relevant information to individuals and their health care providers. When it becomes practical to sequence each patient's genome, genetic information will be used to provide more individualized outlooks of disease risk and improve the prevention, diagnosis, and treatment of disease. NHGRI's medical sequencing program, initiated in 2006, aims to drive continued improvement in DNA sequencing technologies and to produce data important to biomedical research. Seven studies currently are underway to identify the genes responsible for several relatively rare disorders and to survey the range of gene variants that contribute to certain common diseases.
Genomic Medicine: One of the promises of the Human Genome Project is the personalization of medicine. The time rapidly is approaching when health care providers will be able to use information about each person's unique genetic makeup to develop individualized strategies for detecting, treating, and, ultimately, preventing disease. A number of initiatives are underway to explore this area, including the Multiplex Initiative, the Surgeon General's Family History Initiative, and the ClinSeq project. The Multiplex Initiative, a collaboration between NIH researchers, the Group Health Cooperative in Seattle, and the Henry Ford Health System in Detroit, studied the interest levels of healthy young adults in receiving genetic testing for eight common conditions. The purpose was to understand better how patients respond to the results of genetic tests. The U.S Surgeon General's Family History online tool, created through a collaborative effort involving the Office of the Surgeon General, NIH, the Centers for Disease Control and Prevention, the Agency for Healthcare Research and Quality, and the Health Resources and Services Administration, allows people to record health conditions that have affected their relatives. The tool uses a three-generation pedigree to organize family health information in a format that people can easily share with their health care providers and other family members. Such information can lead to more proactive strategies for preventing disease and improving health. Finally, NIH researchers and their collaborators are enrolling volunteers in the ClinSeq project, which is piloting large-scale medical sequencing in a clinical setting, with a focus on cardiovascular disease.
Developmental Genomics: Neural tube defects are a class of birth defects affecting the brain and spinal cord. Taking folic acid during the weeks before and after conception greatly can reduce a woman's chances of having a child with a neural tube defect. Still, researchers have not yet fully defined the complex relationship that exists between folic acid and vitamin B12, which is essential for synthesizing DNA during growth and development. Because Ireland has a particularly high rate of neural tube defects, NIH researchers collaborated with Irish researchers to look more closely at the role of vitamin B12 in the developmental disorder. They found that children born to women who have low blood levels of vitamin B12 shortly before and after conception have an increased risk of a neural tube defect. In light of their discovery, researchers said it would be wise for all women of childbearing age to consume the recommended amount of vitamin B12 in addition to folic acid. In a study looking at a different type of birth defect, a trans-NIH team found that about 20 percent of the incidence of isolated cleft lip may be due to a very tiny alteration in a gene involved in facial development. Oral-facial clefts are among the most common birth defects in the United States, arising from disruptions in a dynamic but still poorly understood interplay of genes, diet, and environment.
  • Molloy AM, et al. Pediatrics 2009;123(3):917-23. PMID: 19255021.
    Rahimov F, et al. Nat Genet 2008 Nov;40(11):1341-7. PMID: 18836445. PMCID: PMC2691688.
  • For more information, see  http://www.genome.gov/27530477
  • For more information, see  http://www.genome.gov/27528380
  • This example also appears in Chapter 2: Neuroscience and Disorders of the Nervous System and Chapter 2: Life Stages, Human Development, and Rehabilitation
  • (E, I) (NHGRI, NICHD, NIDCR)
Study Finds Unexpected Bacterial Diversity on Human Skin: One of the NIH Roadmap initiatives, the Human Microbiome Project (HMP) is a trans-NIH program that aims to expand upon traditional microbiology and discover what microbial communities exist in different parts of the human body and how they might change with disease. In a healthy adult, microbial cells far outnumber those of the human host, but remarkably little has been known until now about how these microbes behave in the body. HMP makes use of a metagenomic approach that reveals data about entire human-associated microbial communities. In 2009, data gathered by a trans-NIH team revealed unexpected bacterial diversity on human skin that, it is hoped, will lead to advances in understanding a range of disorders, such as eczema, psoriasis, and acne.
  • Grice EA, et al. Science 2009;324(5931):1190-2. PMID: 19478181.
  • For more information, see  http://nihroadmap.nih.gov/hmp/index.asp
  • This example also appears in Chapter 3: Molecular Biology and Basic Research
  • (I) (NHGRI, Common Fund - all ICs participate, NCI)
ENCODE: The ENCyclopedia Of DNA Elements (ENCODE) is an international research consortium organized by NIH that seeks to identify all functional elements in the human genome. Until now, most studies have concentrated on the 1 percent of the genome that contains protein-coding genes, overlooking the many other parts of the human genetic blueprint that are important to biological function. ENCODE's exciting discoveries may well reshape the way scientists think about the genome and pave the way for more effective approaches to understanding and improving human health. Efforts to uncover functional elements also extend to some of the organisms most often used in biomedical research. The model organism ENCyclopedia of DNA Elements (modENCODE) Project is analyzing the genomes of the fruit fly, Drosophila melanogaster; and the round worm, Caenorhabditis elegans. The data that are expected to result from modENCODE project will provide important insights into the biology of these model organisms, as well as provide a valuable tool for comparative studies aimed at understanding human biology.
Genetics of Diabetes: Diabetes is a common, potentially deadly and debilitating chronic disease that poses an enormous health care burden. Both of the most common forms of diabetes, type 1 and type 2, are caused by an intersection of genetic and environmental risk factors. Although genetic effects on developing diabetes are profound, they are not simple, as there are many genes that influence the likelihood of developing type 1 or type 2 diabetes. Further, ethnicity impacts both genetic and environmental risk factors. To learn more about diabetes genetics, particularly through new genomic technologies, NIH supports the Type 1 Diabetes Genetics Consortium to study type 1 diabetes, and several major grants to study the genetics of type 2 diabetes. These programs now have identified at least 40 genetic regions linked to type 1 diabetes and at least 38 type 2 diabetes genes. Other studies are refining our understanding of how these genes affect diabetes risk. Many of these projects are geared to collect data from multiple ethnic groups, but a recent initiative sought to advance knowledge of diabetes risk genes in specific racial and ethnic groups disproportionately affected by type 2 diabetes, to understand how different genes affect different populations.
Advances in Understanding the Genomic Risk for Schizophrenia: Three genome-wide studies have pinpointed a vast array of genetic variation that cumulatively poses the greatest risk for schizophrenia yet reported. All three studies implicate an area of chromosome 6 (6p22.1), which is known to harbor genes involved in immunity and genes that control how and when genes turn on and off. Among sites showing the strongest associations with schizophrenia was a suspect area on chromosome 22 and more than 450 variations in the suspect area on chromosome 6. Individually, these variants' effects statistically were insignificant, but cumulatively they were very powerful. Additionally, one of the studies traced schizophrenia and bipolar disorder, in part, to the same chromosomal neighborhoods. These findings suggest that if some of the same genetic risks underlie schizophrenia and bipolar disorder, then these disorders may originate from a common vulnerability in brain development.
  • Shi J, et al. Nature 2009;460(7256):753-7. PMID: 19571809. PMCID: PMC2775422.
    Stefansson H, et al. Nature 2009;460(7256):744-7. PMID: 19571808.
    International Schizophrenia Consortium, et al. Nature 2009;460(7256):748-52. PMID: 19571811.
  • This example also appears in Chapter 2: Chronic Diseases and Organ Systems
  • (E) (NIMH)
The Collaborative Study on the Genetics of Alcoholism (COGA): In its 20th year, COGA is a multisite, multidisciplinary family study with the overall goal of identifying and characterizing genes that contribute to the risk for alcohol dependence and related phenotypes. COGA investigators have collected data from more than 300 extended families (consisting of more than 3,000 individuals) that are densely affected by alcoholism, enabling researchers to take a multigenerational perspective. A recent COGA study focusing on adolescents follows individuals longitudinally as they transition through the age of risk. Investigators have identified several genes, including GABRA2, ADH4, ADH5, CHRM2, GRM8, GABRR1, and GABRR2 (Rho 1 and 2) that influence the risk for alcoholism and related behaviors, such as anxiety, depression, and other drug dependence. In addition to genetic data, extensive clinical neuropsychological, electrophysiological, and biochemical data have been collected, and a repository of immortalized cell lines from these individuals has been established to serve as a permanent source of DNA for genetic studies. These data and biomaterials are distributed to qualified investigators in the greater scientific community to accelerate the identification of genes that influence vulnerability to alcoholism. COGA will continue to identify genes and variations within the genes that are associated with an increased risk for alcohol dependence and will perform functional studies of the identified genes to examine the mechanisms by which the identified genetic variations influence risk.
  • Xuei X, et al. Am J Med Genet B Neuropsychiatr Genet 2009;150B(3):359-68. PMID: 19536785. PMCID: 2829340.
  • For more information, see  http://zork.wustl.edu/niaaa
  • This example also appears in Chapter 2: Neuroscience and Disorders of the Nervous System and Chapter 2: Chronic Diseases and Organ Systems
  • (E) (NIAAA) (GPRA)
New Genetics/Epigenetic Tools Shed Light on Addiction: NIH-supported research is taking full advantage of expanding databases and fast technologies to identify links between genetic variations and disease, health, and behavior. Such genetic studies are critical to teasing apart the molecular mechanisms underlying complex diseases like addiction, which genes strongly influence. Investigators studying various neurological and psychiatric illnesses have already linked certain genes with specific diseases using custom screening tools known as "gene chips" (e.g., the neurexin gene has been found to play a role in drug addiction). Applying these tools to addiction and other brain disorders advances our understanding not only of vulnerability to addiction and its frequent comorbidities, but also of ways to target treatments based on a patient's genetic profile. To complement these efforts, NIH is investing in the equally important field of epigenetics, which focuses on the lasting modifications to the DNA structure and function that result from exposure to various stimuli. Attention to epigenetic phenomena is crucial to understanding the interactions between genes and the environment, including the deleterious long-term changes to brain circuits from drug abuse. For example, using a powerful new technique known as ChIP-on-chip to monitor epigenetic changes correlated with gene activity, investigators recently have mapped the genomic effects of chronic cocaine use in the reward center of the mouse brain. Such analyses provide needed information about which genes are altered by cocaine and can point to new targets for medications development. Epigenetic discoveries also can inform ways to smartly alter environmental factors so as to decrease the risk for drug abuse and addiction.
Regulation of Gene Expression by Chemically Marking DNA: Studies by NIH intramural scientists of how genes are turned on (expressed) or off have provided insight into gene regulation and the overall organization of the genome. For example, a recent study indicated the importance of a mammalian protein called Vezf1 in maintaining the integrity of the genome. This protein previously had been identified by research on an "insulator" element—a segment of DNA that marks boundaries in the genome and allows neighboring genes to be regulated independently. Research on insulator elements—found in fruit flies, chickens, and mammals—has provided great insight into the molecular mechanisms used by the cell to turn on certain genes while keeping other genes turned off. In studies of Vezf1, the scientists discovered that deletion of the gene encoding the Vezf1 protein in a mouse embryonic stem cell line led to loss of specific chemical marks on the DNA at widespread sites in the genome. This type of chemical mark, known as DNA methylation, is a signal used by the cell to turn a gene off. The scientists also demonstrated that the loss of DNA methylation observed when Vezf1 was deleted was due to a decrease in the amount of a specific protein that puts this mark on the DNA. Therefore, Vezf1 is required for the DNA methylation pattern in these cells. Continued studies of insulators and their associated proteins will lead to further understanding of the regulation of genes, an essential process for health and development.
  • Gowher H, et al. Genes Dev 2008;22(15):2075-84. PMID: 18676812. PMCID: PMC2492749.
  • This example also appears in Chapter 3: Molecular Biology and Basic Research
  • (I) (NIDDK)
Genetics of Chronic Kidney Disease: Researchers recently have made progress in uncovering the role of genetics in chronic kidney disease (CKD) arising from various causes. Scientists recently have identified a genetic region that is strongly associated with CKD in African Americans that arises as a consequence of conditions other than diabetes, such as high blood pressure and HIV-associated kidney disease. Several variants associated with the MYH9 gene were identified as major contributors to excess risk of this kind of CKD among African Americans. This finding suggests that CKD may proceed along different paths depending on whether diabetes or another condition is the underlying disorder. The Consortium for Radiologic Imaging Studies of PKD (CRISP) was established to study progression of an inherited form of kidney disease, polycystic kidney disease (PKD). Phase I of the study demonstrated that magnetic resonance imaging accurately could track structural changes in the kidneys; Phase II showed that patients with mutations in the PKD1 gene have more cysts and larger kidneys than patients with PKD2 mutations. A planned third phase of CRISP will provide critical information about the validity of changes in kidney volume as a surrogate marker for loss of kidney function. NIH also has launched a study to identify and validate biomarkers and risk assessment tools for kidney function, injury, and disease progression in patients with CKD, to predict risk, aid early diagnosis, and assess disease progression.
  • Kopp JB, et al. Nat Genet 2008;40(10):1175-84. PMID: 18794856.
    Kao WHL, et al. Nat Genet 2008;40(10):1185-92. PMID: 18794854. PMCID: PMC2614692.
    Grantham JJ, et al. New Engl J Med 2006;354(20):2122-30. PMID: 16707749.
    Rule AD, et al. J Am Soc Nephrol 2006;17(3):854-62. PMID: 16452494.
  • For more information, see  http://www.nih.gov/news/health/sep2008/niddk-14.htm
  • For more information, see  http://www.nih.gov/news/pr/may2006/niddk-17.htm
  • This example also appears in Chapter 2: Chronic Diseases and Organ Systems and Chapter 2: Minority Health and Health Disparities
  • (E/I) (NIDDK, AHRQ, NCI, NCRR, NHLBI)
Genotyping Information for Use in Warfarin Therapy: The Pharmacogenetics and Pharmacogenomics Knowledge Base (PharmGKB), a component of the Pharmacogenetics Research Network (PGRN), sponsors data-sharing consortia. In 2009, one of the consortia, the International Warfarin Pharmacogenetics Consortium (IWPC), completed its first project: Clinical and genetic data from more than 4,000 patients worldwide who received warfarin were assembled into a large dataset to create a universal dose algorithm that incorporated genetic factors along with clinical factors. This established a better method to calculate the initial dose of the anticoagulant, and NIH will use the information for a prospective clinical trial to determine the value of pre-prescription genotyping. Further genomic analyses of the warfarin data set are underway. Based upon the success in this endeavor, more consortia were created in 2009. The International Tamoxifen Pharmacogenetics Consortium (ITPC) was formed to gather genetic and clinical data on the efficacy and toxicity of tamoxifen from patients around the world to test for specific associations between genetic variants and clinical effects, and the International Severe Irinotecan Neutropenia Consortium (INSINC) was formed to assemble a large dataset to answer questions definitively relating to genetic effects on adverse outcomes of irinotecan therapy, and to provide tools for evaluating toxicity risk.
Understanding the Progression from a Skin Disorder to Asthma in Children: NIH-funded researchers investigating basic biochemical mechanisms involved in development have discovered a mechanism that can explain how 50-70 percent of young children affected with the skin rashes of atopic dermatitis (a type of eczema) eventually become asthmatic. The process involves the overproduction of a specific signaling molecule by inflamed skin cells that can trigger the hypersensitivity characteristic of asthma in lung cells. This mechanism and possible ways to prevent this "atopic march" and the development of asthma in general are being actively evaluated in animal models as well as in early human studies.
Genetic Epidemiology of COPD (COPDGene): This investigator-initiated research program is performing genetic testing in more than 10,000 current or former smokers to identify genes that are associated with the presence of COPD (chronic obstructive pulmonary disease). In this large and diverse cohort, half of the subjects will be women and one-third will be African American. Although COPD is the fourth most common cause of death in the United States, understanding why some smokers develop serious lung disease and others do not is lacking. Genetics studies may reveal factors that determine this differential susceptibility to disease. The COPDGene study will help to identify individuals at greatest risk, point to particular molecular pathways that may be involved in pathogenesis, and suggest possible targets for prevention and drug therapy. The phenotypic and genetic data generated by the program will be made available through an NIH data repository to allow additional research analyses by other investigators. COPDGene has thus far enrolled more than 4,000 subjects at 17 sites across the United States.
  • This example also appears in Chapter 2: Chronic Diseases and Organ Systems
  • (E) (NHLBI)
Challenge Program in Integrative Research: Mechanisms of Susceptibility to Oxidative-Stress Disease: This project is an interdisciplinary, collaborative effort to combine the use of simple eukaryotic systems, mouse models, genetic polymorphisms, genomics, clinical research, and patient samples to investigate the mechanisms of susceptibility to the development of oxidative stress-induced disease. The initial phase of the program is focused on bronchopulmonary dysplasia (BPD) and retinopathy of prematurity (ROP), chronic diseases associated with very low birth weight infants. This program consists of three interactive projects: (1) positional cloning of BPD/ROP susceptibility genes in inbred mice; (2) investigating the role of mitochondrial reactive oxygen species in hyperoxia-induced tissue injury; and (3) searching for oxidant susceptibility genes and neonatal diseases in prospective case-parent triad cohorts. Together this group will identify stress response networks, develop and validate early biomarkers of disease, and identify candidate genes and genetic polymorphisms that influence susceptibility to oxidative stress. This program has established a highly collaborative research team uniting bench science with clinical research and patient outcomes. The long-term goal of this program is to understand the role of specific genes that increase human susceptibility to oxidant stress-induced diseases. Thus, this team has the potential to affect a large number of environmentally induced diseases associated with inflammation and reactive oxygen species, including asthma, atherosclerosis, cancer, cardiovascular disorders, and neurodegenerative diseases.
  • This example also appears in Chapter 2: Chronic Diseases and Organ Systems and Chapter 3: Clinical and Translational Research
  • (I) (NIEHS)
Longevity Assurance Gene (LAG) Initiative and Interactive Network: The NIH-supported LAG Initiative has been one of the most successful research initiatives in the field of aging biology and has generated a number of highly significant advances in our understanding of the biological pathways and mechanisms responsible for extension of life span and health span in model organisms. Notably, the LAG initiative has led to the identification of more than 100 new longevity-associated genes, along with many other conserved biological processes and pathways that regulate longevity in a host of divergent species, including humans. Several longevity genes and pathways identified in model organisms as part of the LAG Initiative now are being studied in human populations to determine if analogous genes/pathways are involved in determining human longevity and health span.
  • (E) (NIA)
Confronting the Challenge of Antimicrobial Resistance: Antimicrobial resistance has become a major public health threat that is severely jeopardizing the utility of many "first-line" antimicrobial agents. The development of resistance can be caused by many factors, including the inappropriate use of antibiotics. NIH supports a robust basic research portfolio on antimicrobial resistance, including studies of how bacteria develop and share resistance genes. NIH also is pursuing translational and clinical research in this area, including clinical studies to test interventions for community-acquired methicillin-resistant Staphylococcus aureus (MRSA) infection and to evaluate the efficacy of off-patent antimicrobial agents. NIH laboratories are at the forefront of understanding the fundamental causes of resistance—from studies of the disease-causing organisms and the progression of disease to research on the advantages and shortcomings of current antibiotics. Specific research foci of NIH researchers and NIH-supported grantees include MRSA and vancomycin-resistant Staphylococcus aureus (VRSA) (commonly acquired in community settings), and drug-resistant malaria and tuberculosis. NIH supports genomic sequencing through its Microbial Sequencing Centers; researchers at these centers have sequenced the genomes of numerous disease-causing bacteria, viruses, parasites, and fungi, which may help identify mechanisms of resistance and when and where resistance emerges.
The Multi-Ethnic Study of Atherosclerosis: The Multi-Ethnic Study of Atherosclerosis (MESA) is a multicenter epidemiological study of cardiovascular disease (CVD) in 6,914 men and women from 4 ethnic groups—white, African-American, Hispanic, and Chinese—who have been followed for almost 10 years to identify predictors of progression of subclinical CVD. The study originally was funded from 1999 to 2008 and subsequently renewed through 2015. It has measured and compared the predictive value of chest computed tomography, cardiac magnetic resonance imaging, carotid ultrasound, arterial compliance, endothelial function, biochemical markers, and genetic and environmental factors for the development of CVD. MESA has major ongoing ancillary studies in the areas of air pollution (funded by the EPA), chronic lung disease, and genetics. MESA SHARe (SNP Health Association Resource) will combine genome-wide scans with detailed phenotypic information and share these data with the scientific community for genome-wide association analyses.
  • For more information, see  http://mesa-nhlbi.org
  • This example also appears in Chapter 2: Chronic Diseases and Organ Systems, Chapter 2: Minority Health and Health Disparities and Chapter 3: Epidemiological and Longitudinal Studies
  • (E) (NHLBI, NEI)

Genome Sequencing and Technology

Genome Technology and the $100,000 and $1,000 Genome Initiatives: Taking the discoveries made in genetic research initiatives and delivering them to patients on a much wider basis will require significant decreases in the cost and time needed to sequence an entire human genome. Rapid gains have been made on this front since the start of the Human Genome Project, and costs continue to fall dramatically. However, it still remains prohibitively expensive to sequence the genomes of individual patients in the clinic. Developing technology to make genome sequencing more affordable is essential for making genomic information part of routine medical care. NIH's Genome Technology program supports research to develop rapid, low-cost methods, technologies, and instruments that will:
  • Read DNA sequences
  • Check sequences for genetic variations (SNP genotyping)
  • Aid research to understand the effects of genetic variations on genomic function.

In 2004, NIH began funding research to develop technologies specifically intended to lower the cost of sequencing the amount of DNA in a human genome, about 3 billion base pairs. These efforts include:

  • "Near-Term Development for Genome Sequencing" Grants. These awards support research to enable the sequencing of a human-sized genome for about $100,000.
  • Revolutionary Genome Sequencing Technologies Grants. These awards aim to develop breakthrough technologies that will enable an individual's genome to be sequenced for $1,000 or less.
    NIH Roadmap Technology Development in Epigenetics: The key focus of the Technology Development in Epigenetics initiative is to foster the development of revolutionary technologies with the potential to change significantly how epigenomics research is performed in the future. Although the technologies and tools for evaluating epigenetic events are improving, existing constraints impede even more rapid progress. Nine grants were funded in 2009 as the result of this initiative. Five of the funded R01 scientists were new investigators. In the future, technological improvements in epigenome-wide mapping and related technologies may enable epigenomic changes to be used to diagnose and investigate the effects of environmental exposures (e.g., drugs of abuse, toxins, infection) on disease (e.g., cancer, neuropsychiatric disorders, aging).
    DNA in 3-D: The sequence of the 3 billion DNA base pairs that make up the human genome holds the answers to many questions related to human development, health, and disease. Consequently, much research aimed at understanding the genome has focused on decoding the information conveyed by the linear order of DNA bases. Now, a team that includes an NIH intramural researcher has devised a new way of analyzing functional regions in the human genome. The novel approach involves looking at the three-dimensional shape of the genome’s DNA, rather than just the base pair sequence. By combining chemical and computer analyses, the researchers survey the landscape, or topography, of DNA structure for areas likely to play a key role in biological function. The method involves identifying all of the grooves, bumps, and turns of the DNA that make up the human genome and then comparing those structural features to those seen in the genomes of other animal species. Structural features that have been preserved across many species are likely to play important roles in how the human body functions, while those that have changed a great deal over the course of evolution may play a less central role or no role at all.
    • Parker SC, et al. Science 2009324(5925):389-92. PMID: 19286520. PMCID: PMC2749491.
    • For more information, see  http://www.genome.gov/27530624
    • (I) (NHGRI) (ARRA)
    Scientists Accomplish Initial Catalogue of the Human Salivary Proteome: Secretions from the major salivary glands (parotid, submandibular, and sublingual) contain many peptides and proteins. They contribute to saliva's important roles in maintaining oral health, including antimicrobial, lubricating, buffering, and digestive properties. Salivary gland disorders, which result in severe dry mouth, compromise quality of life because they often lead to decay and periodontal diseases, mucosal infections, halitosis, taste impairment, and difficulties in swallowing and speaking. Saliva is a complex fluid; over the years, a number of salivary proteins have been reported but a systematic approach to catalogue all the proteins present in saliva was only initiated in 2004. NIH supported three teams of investigators to conduct the first comprehensive analysis of the salivary proteome. After samples were collected and analyzed, the data were standardized and integrated, yielding a salivary proteome that comprises 1,166 proteins. Of these proteins, 152 parotid and 139 submandibular/sublingual proteins were identified by all 3 research groups; these proteins form the core proteome. Most proteins identified were extracellular or secretory proteins, and involved in numerous molecular and cellular processes. A significant number of proteins represented in the salivary proteome also have been found to exist in the plasma or tear proteomes. This initial catalogue of the salivary proteome is a significant first step toward a comprehensive understanding of what the functions of saliva are, and how salivary composition is dependent on physiological variations, including on health and disease. This proteome could be the source of potential diagnostic and prognostic biomarkers for oral and systemic conditions.
    • Denny P, et al. J Proteome Res 2008;7:1994-2006. PMID: 18361515.
    • This example also appears in Chapter 3: Molecular Biology and Basic Research and Chapter 3: Technology Development
    • (E) (NIDCR)
    Increased Efficiency for Genetic Engineering Research Methods: Gene therapy—the ability to cure a genetic disease by replacing or destroying the faulty copy of a gene—has been limited by the difficulty of designing chemical "bullets" that will zap the defective gene without affecting any of the other genes in a person's cells. Recently, NIH-supported researchers have developed a method, called OPEN, for creating gene-specific chemical bullets that is much faster, easier, and cheaper than alternative technologies. OPEN has the potential to revolutionize genetic engineering, and it also will greatly enhance the progress of genetic research in all organisms.
    • Maeder M, et al. Mol Cell 2008;31(2):294-301. PMID: 18657511. PMCID: PMC2535758.
    • (E) (NIGMS)

    The Big Picture: Genome-Wide Association Studies

    Genome-Wide Association Studies: With unprecedented speed, researchers have used an approach called genome-wide association studies (GWAS) to explore genetic variants and their complex relationships to human health and disease. GWAS research has linked a stunning number of genetic variants to common conditions—more than 130 in 2008 alone. For example, the obesity epidemic and its related health conditions pose a great challenge for the Nation. In 2008, the Genetic Investigation of Anthropometric Traits consortium identified six genes associated with body mass index, a key indicator for obesity. Also in 2008, three GWAS of lung cancer implicated several genes already known to be linked to nicotine addiction. In a feat that would not have been possible without the power of whole genome analysis, the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium in 2009 gathered data from participants in long-running studies to reveal genetic variants associated with an increased risk of stroke. Identification of genetic variants associated with common diseases opens new windows into the biology of health and disease. This work also raises the possibility of someday using genetic testing, in combination with family history, to identify at-risk, pre-symptomatic individuals who might benefit from personalized screening and preventive therapies.
    Population Genomics, GAIN, and GEI: In 2006, HHS announced the creation of two groundbreaking initiatives for population genomics research in which NIH played a leading role. The Genetic Association Information Network (GAIN) was a public-private partnership involving NIH, the Foundation for NIH, Pfizer, Affymetrix, Perlegen, the Broad Institute, and Abbott. GAIN supported a series of genome-wide association studies designed to identify specific points of DNA variation associated with the occurrence of common diseases. Investigators from existing clinical studies were invited to submit samples and data on roughly 2,000 participants for genomic assays designed to capture roughly 80 percent of the common changes in the human genome. GAIN successfully concluded in November 2008, with the third and final public workshop on the project. At this meeting, investigators from across the research community shared their findings and discussed how they had used the data generated through GAIN in their own research. Data from the GAIN studies have been deposited into the NIH database of Genotype and Phenotype (dbGaP) for the broad use of the research community. Access is controlled by the GAIN Data Access Committee. Additionally, NIH funds the Genes, Environment, and Health Initiative (GEI), an NIH-wide effort combining comprehensive genetic analysis and environmental technology development to understand the causes of common diseases. GEI has held a number of workshops to identify novel ways of analyzing the wealth of information gathered and to use that data to improve human health.
    Genome-Wide Association Studies of Autoimmune Disease Risk: In recent years, genome-wide association studies (GWAS) have transformed the identification of gene regions related to disease risk, through an unbiased analysis of patients with a disease, in comparison with people who don't have it. These GWAS require large numbers of patients and individuals without the disease to obtain statistically significant results. Long-term NIH support of disease registries and repositories of biological samples have been essential to successful projects, in addition to productive, multisite collaborations across the United States, including international researchers and contributions from the NIH Intramural Research Program. GWAS have yielded important information about disease risk, as well as understanding of disease pathways and potential therapeutic targets, in several autoimmune diseases in the past 2 years. Diseases studied include psoriasis, rheumatoid arthritis, systemic lupus erythematosus (or lupus), ankylosing spondylitis, and type 1 diabetes. Initial results from GWAS require confirmation by replication in additional groups of patients. More detailed localization of disease risk genes can be achieved through comprehensive DNA sequencing of candidate gene regions. New NIH initiatives are supporting these follow-up studies, which are critical to validating GWAS findings.
    Lupus: There have been significant advances in identifying disease risk genes for systemic lupus erythematosus (lupus) in recent years. Genome-wide association, linkage analysis, and direct sequencing have revealed genetic variations in lupus patients for molecules involved in immune mechanisms and regulation, inflammation, and vascular cell activities. The disease affects women disproportionately, with female lupus patients outnumbering males nine to one. African American women are three times as likely to get lupus as Caucasian women, and it also is common more in Hispanic, Asian, and American Indian women. These results are being replicated in distinct racial and ethnic populations. Long-term NIH support of disease registries and repositories of biological samples have been essential to successful projects. Another critical factor in these and future studies is the collaboration between U.S. and European researchers, supported by government agencies, private foundations, and industry. The numerous genes uncovered in these studies reflect the complex expression of lupus, which varies from patient to patient. For example, a variant in an immune regulatory gene specifically is associated with severe forms of lupus that include kidney disease, but not skin manifestations. Methods to analyze patients' blood samples are being developed to group disease-specific variations in gene expression according to pathogenic mechanisms. This system may be used to predict flares of lupus activity in the future and guide individualized treatment. Lupus risk genes also have been discovered on the X chromosome and reproduced in animal models of the disease. These important findings shed light on the female predominance of lupus.
    • Edberg JC, et al. Hum Mol Genet 2008 Apr 15;17(8):1147-55. PMID: 18182444.
      Hom G, et al. N Engl J Med 2008;358(9):900-9. PMID: 18204098.
      Nath SK, et al. Nat Genet 2008;40(2):152-4. PMID: 18204448.
      International Consortium for Systemic Lupus Erythematosus Genetics (SLEGEN), et al. Nat Genet 2008;40(2):204-10. PMID: 18204446.
      Taylor KE, et al. PLoS Genet 2008;4(5):e1000084. PMID: 18516230. PMCID: PMC2377340.
      Chaussabel D, et al. Immunity 2008;29(1):150-64. PMID: 18631455. PMCID: PMC2727981.
      Smith-Bouvier DL, et al. J Exp Med 2008;205(5):1099-108. PMID: 18443225. PMCID: PMC2373842.
      Scofield RH, et al. Arthritis Rheum 2008;58(8):2511-7. PMID: 18668569.
      Jacob CO, et al. Proc Natl Acad Sci U S A 2009;106(15):6256-61. PMID: 19329491. PMCID: PMC2669395.
    • This example also appears in Chapter 2: Autoimmune Diseases, Chapter 2: Minority Health and Health Disparities, Chapter 3: Molecular Biology and Basic Research and Chapter 3: Clinical and Translational Research
    • (E/I) (NIAMS, NCI, NCRR, NHLBI, NIAID, NIDCR, NINDS)
    Psoriasis: Early studies of families of psoriasis patients indicated a genetic susceptibility for the disease. Genome-wide association studies (GWAS) have revealed genetic variations in psoriasis patients for previously identified immune system proteins. New disease risk genes, which are associated with inflammation and immune function, also have been found. Some of these variations occur in or near gene regions associated with other autoimmune diseases, such as rheumatoid arthritis, lupus, and Crohn's disease, although in distinctly independent genes. In addition to variations in genes associated with immune function, GWAS have uncovered differences among psoriasis patients in genes involved with skin differentiation and regulation of inflammation.
    • Liu Y, et al. PLoS Genet 2008;4(3):e1000041. PMID: 18369459. PMCID: PMC2274885.
      Nair RP, et al. Nat Genet 2009;41(2):199-204. PMID: 19169254. PMCID: PMC2745122.
    • This example also appears in Chapter 2: Autoimmune Diseases
    • (E) (NIAMS, NIDA)
    Seeking Solutions for People with Sjogren's Syndrome: Sjogren's syndrome is one of the most prevalent autoimmune disorders, affecting as many as 4 million people in the United States. Nine out of 10 patients affected are female. It is an autoimmune disease that progressively destroys salivary and lachrymal glands. The most common symptoms include dry eyes, dry mouth, fatigue, and musculoskeletal pain. A significant roadblock for moving discoveries ahead in the field of Sjogren's syndrome is the lack of data and biospecimens available for research. Recognizing the problem, NIH spearheaded an effort to establish Sjogren's patient registries at two extramural institutions as well as through its own intramural program. These groups are working together to generate and share with the general research community the genome-wide genotyping data and clinical information from the cohorts enrolled through these efforts. This resource should jumpstart efforts to understand genetic contributions to Sjogren's syndrome and the etiologic overlap with related autoimmune conditions such as lupus and rheumatoid arthritis. In addition to participating in the patient registry and genotyping efforts described above, the Sjogren's Syndrome Clinic, located in the NIH CC, collects systematic clinical and laboratory data on the Sjogren's syndrome (and salivary dysfunction) population. Gene therapy and bioengineering hold promise for the repair or even replacement of salivary glands ravaged by Sjogren's syndrome. More than 300 patient visits occur annually, and the clinic is expanding its patient recruitment to accelerate the conduct of clinical trials that might shed light on this disorder.
    • Korman BD, et al. Genes Immun 2008;9(3):267-70. PMID: 18273036.
      Roescher N, et al. Oral Dis 2009;15(8):519-26. PMID: 19519622. PMCID: PMC2762015.
      Nikolov NP, Illei GG. Curr Opin Rheumatol 2009;21(5):465-70. PMID: 19568172. PMCID: PMC2766246.
    • For more information, see  http://www.sjogrens.org/
    • This example also appears in Chapter 2: Autoimmune Diseases and Chapter 3: Disease Registries, Databases, and Biomedical Information Systems
    • (E/I) (NIDCR, CC, ORWH)
    SNP-Health Association Resource (SHARe): SHARe conducts genome-wide association studies in several large NIH cohort studies to identify genes underlying cardiovascular and lung diseases and other disorders such as obesity and diabetes. The resulting genotype data along with the cohort phenotype data are made available to researchers around the world through the NIH dbGAP database. Framingham SHARe, with 9,000 participants, was the first cohort released in this initiative due to its uniqueness in including 3 generations of participants with comparable data obtained from each generation at the same age. As of October 31, 2009, 95 projects to use these data had been approved. A modified version of the dataset was distributed to 72 approved research projects as the focus of a Southwest Foundation Genetic Analysis Workshop. The second cohort released was the SHARe Asthma Resource Project, which includes genotype data from more than 2,500 adults and children who have participated in NIH clinical research trials on asthma. As of October 31, 2009, 11 projects to use these data had been approved. Data from more than 12,000 African-American and Hispanic women from the Women's Health Initiative and approximately 8,300 participants from the Multi-Ethnic Study of Atherosclerosis were released in January 2010.
    Unraveling the Complexity of the Genetics of Glaucoma: Glaucoma is a group of eye disorders that share a distinct type of optic nerve damage, which can lead to blindness. It is the leading cause of blindness in African Americans. More than 2 million Americans have been diagnosed with glaucoma, and the prevalence of the disease will rise to a projected 3 million by 2020. Glaucoma research aims to understand the complex genetic factors that lead to common forms of the disease and to develop treatments that protect ganglion cells of the retina from the damage that leads to vision loss. Under GPRA, NIH set a goal by 2012 to identify the genes that control the risk of glaucoma. To achieve this goal, NIH launched a large genome-wide association study to identify glaucoma risk genes. NEIGHBOR (NEI Glaucoma Human Genetics CollaBORation) is a unique collaborative effort involving 22 investigators at 12 institutions throughout the United States. Approximately 2,000 cases and 2,000 age, sex, and ethnically matched controls will have their complete genome sequenced (genotyped) for a genome-wide association study to identify genetic variants associated with the disease. Genetic data and associated disease characteristics collected from NEIGHBOR will be made available to the research community through the NIH database of Genotypes and Phenotypes (dbGaP).

    Decoding Cancer

    Genomic Research on Tumor Cells: In addition to supporting The Cancer Genome Atlas with NCI, NHGRI operates a number of other cancer-focused research programs, both intramural and extramural. The Tumor Sequencing Project (TSP) is a multicenter effort to characterize the genomic changes that occur in lung adenocarcinoma, the most common type of lung cancer in the United States. In 2008, TSP researchers identified 26 genes that often are mutated in these lung tumors, more than doubling the list previously known to scientists and clinicians. In other efforts, a team of NHGRI intramural and NHGRI-funded researchers recently identified an inherited gene alteration linked to increased susceptibility to lung cancer. With further investigation, the researchers said it may be possible to use this genetic information to identify high-risk people who could benefit from earlier, more aggressive screening for lung cancer, in much the same way as women who inherit BRCA1 and BRCA2 breast cancer genes may benefit from early mammography and other tests. Other NHGRI work has focused on the most deadly type of skin cancer, melanoma. In 2009, an NHGRI intramural researcher discovered a gene that acts as a tumor suppressor in melanoma. This finding is significant because researchers previously thought drugs that blocked that gene or its protein might offer a new way to treat melanoma, when, in fact, a better strategy might be to activate the gene.
    Genome-Wide Association Studies of Cancer Risk: The Cancer Genetic Markers of Susceptibility (CGEMS) project is a signature initiative that uses genome-wide association studies (GWAS) to identify genetic variants and mechanisms associated with cancer risk. Understanding these variants and mechanisms may lead to new preventive, diagnostic, and therapeutic interventions. CGEMS investigators have pinpointed genetic variants associated with elevated prostate cancer risk as well as variants associated with increased breast cancer risk. The same genetic variant was shown to be involved in increased prostate, colon, and other cancers, suggesting a common mechanistic pathway for susceptibility to a variety of cancers. Another GWAS project, the Cohort Consortium, is a unique extramural/intramural collaboration that enables Consortium partners to share access to data on 37 cohorts comprised of 4 million people from diverse populations. Each cohort contains extensive information on known or suspected risk factors and biospecimens collected pre- and post-diagnosis. The large number of study subjects permits the detection of modest genetic effects, as well as studies of variants involved in less common cancers. One cohort within the Consortium, the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort, includes about 2.9 million specimens. These pre-diagnostic specimens provide a valuable resource for studies of cancer etiology and early detection. Researchers can correlate changes in molecular profiles associated with the onset of different types of disease, thereby providing valuable insights into the actual mechanisms of human carcinogenesis.
    Research Tools for Genomic Studies of Cancer: The Cancer Genome Atlas (TCGA) is developing a publicly accessible, comprehensive catalog of the many genetic changes that occur in cancers. Tumor and matched normal samples are analyzed for genetic changes such as chromosome rearrangements and gene mutations; gene expression changes, including changes in expression patterns of microRNAs, as well as epigentic modifications (differences in the chemical modifications of DNA that influence gene expression). All data, including pre-publication data, are freely available through the TCGA website and are compatible with the cancer Bioinformatics Grid (caBIG®). The first TCGA project, which focused on brain cancer (glioblastoma multiforme), demonstrated the feasibility and impact of large-scale NIH-coordinated cancer genome analysis. Comprehensive characterization of ovarian cancer with other tumor types will follow. The goal of the Cancer Genome Anatomy Project (CGAP) is to provide cancer researchers with tools, resources, and information derived from studies that are characterizing differences between cancer and normal cells. The CGAP website provides access to data, bioinformatic tools, and information about available full-length cDNAs and short hairpin RNA clones. These resources are helping scientists conduct the research necessary to improve detection, diagnosis, and treatment of cancer. In the past year, new projects that explore molecular characterization through novel technologies were added as part of the Cancer Genomic Technology Initiative (CGTI). REMBRANDT is the national portal for molecular, genetic, and clinical data associated with several thousand primary brain tumors. This framework provides researchers the ability to answer basic questions related to a patient or patient populations and view integrated datasets in a variety of contexts.

    Ethical, Legal, Social and Behavioral Issues

    NIH Revision Awards for Studying Interactions Among Social, Behavioral, and Genetic Factors in Health: NIH issued three program announcements with review (PARs) to support competitive supplements for NIH grantees to study how interactions among genetic and behavioral/social factors influence health and disease. NIH is committing $7.9 million to support 11 applications submitted in response to these announcements, which will enable the addition of a genetics/genomics component to ongoing behavioral or social science research projects. The knowledge gained by such research will improve our understanding of the determinants of disease as well as inform efforts to reduce health risks and provide treatment.

    Nonhuman Genomes

    Microbial Genomics: NIH has made significant investments in large-scale, whole-genome sequencing of pathogens over the last decade. NIH also provides comprehensive genomic, bioinformatic, and proteomic resources and reagents to the scientific community:
    • The NIH Genome Sequencing Centers of Infectious Diseases rapidly produce high-quality genome sequences of human pathogens and invertebrate vectors of diseases. Over the last decade, NIH has supported large-scale, whole-genome sequencing of pathogens and vectors. Thousands of bacteria, fungi, parasites, invertebrate vectors of diseases, and viruses have been sequenced, including pathogens that cause anthrax, influenza, aspergillosis, TB, gonorrhea, chlamydia, and cholera. For example, more than 3,733 human and avian influenza isolates have been sequenced including almost 500 for H1N1 (as of December 2009).
    • The Pathogen Functional Genomics Resource Center generates and distributes genomic data sets, reagents, resources, bioinformatic analysis tools, and technologies for functional analysis of pathogens and vectors.
    • Clinical Proteomics Centers for Infectious Diseases and Biodefense apply state-of-the art proteomics technologies for the discovery, quantification, and verification of protein biomarkers in infectious diseases. These data are released to the scientific community and may aid in the production of vaccines, diagnostics, and therapeutics.
    • Systems Biology Centers for Infectious Diseases bring together a diverse group of scientists to analyze, identify, quantify, model, and predict the overall dynamics of microbial organisms' molecular networks and their host interactions using both computational and experimental methodologies.
    Comparative Genomics: One of the primary objectives of today's biomedical research is to define and understand how the human genome functions, how malfunction leads to disease, and how that knowledge can be used to develop new preventive strategies, diagnostic methods, and therapies. Comparison of the genome sequence of humans with those of other organisms identifies regions of similarity and difference, providing insight into the evolution, structure, and function of human genes and pointing to new pathways to combat human disease. Currently, the genome sequences of 197organisms are either in the pipeline or have been completed through NHGRI funding. Ongoing sequencing targets include mammals, fungi, multiple strains of yeast, and additional nonhuman primates. NHGRI funds this work by supporting three large-scale sequencing centers that are world-renowned for their cost-effective, high-quality work. Recent highlights of this sequencing program include the publication of the genome of domestic cattle, the first livestock mammal to have its genetic blueprint sequenced and analyzed.
    • Bovine Genome Sequencing and Analysis Consortium, et al. Science 2009;324(5926):522-8. PMID: 19390049.
    • For more information, see  http://www.genome.gov/10001691
    • (E) (NHGRI)

    Resources

    NIMH Center for Collaborative Genetic Studies: Over the last decade, NIH has built the infrastructure for large-scale genetic studies by creating the NIMH Center for Collaborative Genetic Studies (CCGC), a repository of DNA, cell cultures, and clinical data that serves as a national resource for researchers studying the genetics of complex mental disorders. In FY 2008, NIH launched a number of initiatives to enrich the repository through the collection of new biomaterials and clinical data from large cohorts. The CCGC will be enhanced through the creation of a genomic cyberinfrastructure that will integrate and manage data to accelerate genetic analyses. NIH also issued a RFA to encourage studies that will tease apart the complex genetic components of mental disorders, using resources within the CCGC. Projects will study the relationship between genes and illness-specific characteristics, interactions between multiple vulnerability genes, and the role of environmental and experiential influences on gene expression. Through these collective efforts, this research may give us the tools to predict vulnerability, validate diagnosis, and identify targets for new, effective, and personalized mental health treatments.
    Genetic and Genomic Resources for Emerging Non-Mammalian Model Organisms: In FYs 2008 and 2009, NIH funded 13 grants that create genetic and genomic resources for model organisms whose genomes recently have been sequenced. These organisms include fish, invertebrates, and microbes used to understand human health, development, and disease. The resources include reagents and mutant lines, a center for high-throughput mutagenesis, genetic maps, databases, and stock centers.
    Reference Epigenome Mapping Centers: The Reference Epigenome Mapping Centers (REMCs), one of the Roadmap Epigenomics initiatives, are developing resources in reference epigenomes that the field has been requesting for the last 5 years, as indicated by recommendations made at several workshops and conferences focused on epigenetics and human health and disease. The funded centers form a network collaborating to provide comprehensive maps of all known epigenetic marks across a set of mutually agreed-upon reference cell types. This consortium, with input from advisors, will identify the most appropriate cell populations and determine standardized methods for growing or acquiring the cells so that data can be compared and integrated maps can be generated. The network of REMCs will produce comprehensive, high resolution, experimental data on epigenetic marks in specific cell populations, such as high-quality, pluripotent human embryonic stem cells, other human differentiating stem cells, and differentiated cell types including human cell types relevant to complex diseases of high public health significance. In addition, it will provide an informatics pipeline to generate high-quality reference epigenome maps from the centers' data; facilitate additional data analyses, in collaboration with the Epigenome Data Analysis and Coordinating Center, to integrate data from maps generated by REMCs from a specific cell type for different epigenetic marks; and conduct ancillary studies to develop limited data on functional aspects of epigenetic control of gene activity.
    Discovery of Novel Epigenetic Marks in Mammalian Cells: The NIH Roadmap Epigenomics Program aims to accelerate the promise of epigenetics into applications that affect human health and a wide range of common complex human diseases by fostering the development of novel resources for research in this field. Epigenetics refers to various modifications to DNA, its associated proteins, or overall chromosome structure that influence whether genes are active or silent, independent of the DNA sequence. Research supported by this program will characterize the "epigenome," a catalog of the stable epigenetic modifications or "marks" that occur in the genome (and which may differ in different types of cells) and its impact on health and disease. One component of the program is an initiative to support research to identify novel epigenetic marks in mammalian cells and assess their role in the regulation of gene activity. It is anticipated that the results of these studies will be translated quickly to global epigenome mapping in human cells (conducted by the Epigenomics Roadmap Program's Reference Epigenome Mapping Centers). The eight research grants funded by this component of the program are expected to yield results that could have a significant impact on our understanding of gene regulation in mammals. In the long term, advances in these areas will enhance our ability to investigate, diagnose, and ameliorate human disease with a significant epigenetic component. For instance, NIH plans to build on these studies to examine the role of epigenomics in diabetes complications and to study effects of the intrauterine environment on the development of diabetes. Other research will examine epigenetic markers of beta cell differentiation.
    Rodent Model Resources for Translational Research: Mouse and rat models are the primary testbed for preclinical research and have played a vital role in most medical advances in the last century. Rodent models comprise about 90 percent of all animal studies, enabling a wide range of genetic and physiological research on human disease. NIH plays a major role in supporting the availability of normal and mutant mice and rats for translational research. Recent accomplishments include:
    • Knockout Mouse Project (KOMP)—A trans-NIH initiative to individually inactivate approximately 8,500 protein-coding mouse genes to better understand their genetic functions, which are, in many cases, very similar to human genes. High throughput production started in 2006, and international distribution of validated embryonic stem cell lines with specific knockouts from the KOMP Repository became fully operational in 2008. The KOMP is supported by 19 ICs and Offices.
    • Mutant Mouse Regional Resource Centers—More than 1,700 mutant mouse lines, and 27,000 mutant embryonic cell lines, are available from the consortium, which comprises three centers across the United States.
    • Rat Resource and Research Center—Acquisition and distribution of rat models increased dramatically in FY 2008, because of adaptation of novel technologies to make directed mutations.
    Database of Genotype and Phenotype (dbGaP): Research on the connection between genetics and human health and disease has grown exponentially since completion of the Human Genome Project in 2003, generating high volumes of data. Building on its established research resources in genetics, genomics, and other scientific data, NIH established dbGAP to house the results of genome-wide association studies (GWAS), which examine genetic data of de-identified subjects with and without a disease or specific trait to identify potentially causative genes. By the end of 2009, dbGaP included results from more than 40 GWAS, including genetic analyses related to such diseases as Parkinson's disease, ALS, diabetes, alcoholism, lung cancer, and Alzheimer's disease. dbGaP is the central repository for many NIH-funded GWAS to provide for rapid and widespread distribution of such data to researchers and accelerate the understanding of how genes affect the susceptibility to and severity of disease.
    • For more information, see  http://view.ncbi.nlm.nih.gov/dbgap
    • This example also appears in Chapter 3: Epidemiological and Longitudinal Studies and Chapter 3: Disease Registries, Databases, and Biomedical Information Systems
    • (I) (NLM)
    Ethical, Legal, and Social Implications (ELSI) Centers of Excellence: NHGRI's ELSI program has established a network of Centers of Excellence in ELSI Research. Currently, four full Centers and three exploratory Centers are bringing together investigators of diverse expertise to investigate issues related to:
    • Intellectual property of genetic information
    • Translation of genetic information to health care
    • Genetic research that involves human participants
    • Use of genetic information and technologies in non-health care settings, such as employment, insurance, education, criminal justice, or civil litigation
    • Impact of genomics on the concepts of race, ethnicity, and individual and/or group identity
    • Implications of uncovering genomic contributions to human traits and behaviors, such as aging or addictions
    • How different individuals, cultures, and religious traditions view the ethical boundaries for the uses of genomics
    Breast Cancer and the Environment Research Centers: Researchers at the Breast Cancer and Environment Research Centers (BCERC) are investigating mammary gland development in animals, as well as in young girls, to determine vulnerability to environmental agents that may influence breast cancer development in adulthood. These efforts hopefully will lead to strategies that better prevent breast cancer. The purpose of the centers' program is to answer questions on how chemical, physical, biological, and social factors in the environment work together with genetic factors to cause breast cancer. Functioning as a consortium at four grantee institutions, the centers bring together basic scientists, epidemiologists, research translational units, community outreach experts, and community advocates. At one center, a sophisticated genomics and proteomics approach explores the impact of estrogenically active chemicals such as TCDD, bisphenol A, and phthalates, during early, critical periods of development. This is facilitated by advanced informatics at another major research institution. At another center, novel approaches to studying the impact of environmental exposures on interactions between epithelial cells and stromal cells are being studied. Normal and cancer-prone mice are being examined during various stages of development to determine the effects of exposure to multiple stressors as researchers are developing more sensitive screens for carcinogenicity. In concert with these studies, an epidemiological multi-ethnic study is examining and following through puberty a cohort of 7- and 8-year-old girls from the Kaiser Foundation Health Plan. Other researchers are studying a population of white and African American public school students to see how diet affects adipose tissue and alters hormonal control of sexual maturation. Endocrine distruptors, irradiation, and psychosocial elements also will be studied for effects.
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      Kouros-Mehr H, et al. Cancer Cell 2008;13(2):141-52. PMID: 18242514. PMCID: PMC2262951.
      Welm BE, et al. Cell Stem Cell 2008;2(1):90-102. PMID: 18371425. PMCID: PMC2276651.
      Kouros-Mehr H, et al. Curr Opin Cell Biol 2008;20(2):164-70. PMID: 18358709. PMCID: PMC2397451.
      Ewald AJ, et al. Dev Cell 2008;14(4):570-81. PMID: 18410732. PMCID: PMC2773823.
      Sternlicht MD, Sunnarborg SW. J Mammary Gland Biol Neoplasia 2008;13(2):181-94. PMID: 18470483. PMCID: PMC2723838.
      Egeblad M, et al. Dis Model Mech 2008;1(2-3):155-67; discussion 165. PMID: 19048079. PMCID: PMC2562195.
      Aupperlee MD, et al. Endocrinology 2009;150(3):1485-94. PMID: 18988671. PMCID: PMC2654739.
      Lu P, et al. Dev Biol 2008;321(1):77-87. PMID: 18585375. PMCID: PMC2582391.
      Jenkins S, et al. Environ Health Perspect 2009;117(6):910-5. PMID: 19590682. PMCID: PMC2702405.
      Teitelbaum SL, et al. Environ Res 2008;106(2):257-69. PMID: 17976571.
      Moral R, et al. J Endocrinol 2008;196(1):101-12. PMID: 18180321. 
      Santos SJ, et al. J Steroid Biochem Mol Biol 2009;115(3-5):161-72. PMID: 19383543. PMCID: PMC2729057.
      Yang C, et al Reprod Toxicol 2009;27(3-4):299-306. PMID: 19013232.
      Smith SW, et al. J Health Commun 2009;14(3):293-307. PMID: 19440911. PMCID: PMC2718320.
      J Health Psychol 2008;13(8):1180-9. PMID: 18987091.
      Atkin CK, et al. J Health Commun 2008;13(1):3-19. PMID: 18307133.
      Kariagina A, et al. Crit Rev Eukaryot Gene Expr 2008;18(1):11-33. PMID: 18197783.
      Medvedovic M, et al. Physiol Genomics 2009;38(1):80-8. PMID: 19351911. PMCID: PMC2696152.
      Biro FM, et al. J Pediatr Adolesc Gynecol 2009;22(1):3-6. PMID: 19232295. PMCID: PMC2744147.
    • For more information, see  http://www.bcerc.org/
    • This example also appears in Chapter 2: Cancer, Chapter 2: Life Stages, Human Development, and Rehabilitation, Chapter 3: Epidemiological and Longitudinal Studies, Chapter 3: Molecular Biology and Basic Research and Chapter 3: Clinical and Translational Research
    • (E) (NIEHS, NCI) (GPRA)