Momentum - Seeking Ponce's Dream

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Ponce may have gone home empty-handed, but scientists today believe a fountain of youth may exist. Not as an external body of water, but as a biological capability within each person. In our genetic code, they say, lie the keys to ending all disease and physical suffering. This is the promise of predictive health, an emerging paradigm that emphasizes maintaining health by detecting the genetic risk factors for illness and taking steps to prevent disease or illness before it even starts.
The newly established Emory-Georgia Tech Predictive Health Initiative is conducting some of the first explorations in this new clinical frontier. At this early stage, the discipline also goes by a variety of other names—systems biology, prospective health, personalized medicine. But all of these terms refer to the same basic thing: a gigantic shift in the way we think about health, health care, and medicine. In the future, providers will combine an individual’s genetic information with cutting-edge biotechnology to keep that person healthy. Eventually, many experts say, the occurrence of disease will be seen as a failure of the health care system, rather than its main focus.
“There is a sea change coming,” predicts pulmonologist Kenneth Brigham, vice chair of research in Emory’s Department of Medicine and leader of the interdisciplinary faculty effort that developed the new initiative. “No doubt about it.”

Michael Johns, CEO of the Woodruff Health Sciences Center (WHSC) and chairman of the Emory Healthcare Board, agrees.
“The medicine of the very near future involves the ability to rapidly decode hundreds of millions of genome sequences and isolate the information that will tell us about a person’s risk of future disease,” says Johns. “We will be able to forecast the future and see where patients stand in the trajectory of disease. Our great hope is to use the new genetic tools being developed in bioengineering to intervene in the disease process very early, before disease is manifest. Instead of doctors reacting to the presence and damage of disease, we will be in the driver’s seat. The doctors of tomorrow will have tools at their disposal that doctors of my generation have only dreamed of. And the hope is that patients one day will never have to be patients at all.”

What keeps people healthy?

At an international symposium called “Seeking Ponce’s Dream: the Promise of Predictive Health” held this past December, Emory and Georgia Tech declared their intent to develop a world-class center dedicated to exploring the potential of this new approach.
     In many ways, the initiative is a logical outgrowth of an already fruitful partnership between Emory and Georgia Tech. Their joint Department of Biomedical Engineering, formed in 1997, was ranked third in the nation in 2005 by U.S. News & World Report. Faculty all across the WHSC already are collaborating with Georgia Tech’s biomedical engineering researchers on many projects, including studies of genetic and molecular changes linked to heart disease and different types of cancer and the development of new vaccine administration technologies.
     With a projected budget of $51 million over the next five years, the Predictive Health Initiative will add eight more pilot research studies supported by the WHSC’s Woodruff Fund.
     One large project will examine how common physical reactions like inflammation play a role in causing or exacerbating different chronic conditions. Another study examines genetic prediction of schizophrenia in children. Researchers from the Winship Cancer Institute are studying the behavior of proteins in tumors. And many of these studies will examine why some people genetically predisposed to a disease never become ill.

“It’s kind of like the dog that didn’t bark,” says Brigham. “There’s a lot to learn from people who stay healthy in spite of their genetics. This line of thought is completely opposed to the way medical research has been conducted in the past, where we have studied sick people, not healthy people. Keeping people healthy is the focus of predictive health.”
At the same time, researchers at the Rollins School of Public Health (RSPH) are studying the economic, epidemiologic, and behavioral implications of the predictive health movement. For example: What will people do with the information about their risk factors? How should such information be responsibly maintained and communicated?

     The initiative funding will support the different research endeavors by bringing together experts from a broad range of disciplines: computer science, nanotechnology, basic and applied biology, medicine, ethics, sociology, public health, business, law, and behavioral science.
     Developing a new predictive health model will require a mind-boggling mix of cutting-edge research and new technology. And leaders must wrestle with many difficult social and ethical issues as well. How accessible will personalized genetic information be to those of limited financial means? What will be the consequences for people found to be at high risk for a particular condition or disease? Are there diseases or conditions that we may be able to predict but not prevent? These are some of the compelling issues posed by this new era in medicine.
     “We have had vigorous and open discussions, and the symposium was a culmination of that,” Brigham says. “The idea of predictive health incites passions in many different directions, including the scientific, social, legal, economic, and health policy implications.”

Mapping our inner frontiers

The seeds of this new revolution were planted in 1953, when Cambridge researchers James Watson and Francis Crick first described the structure of DNA. Since the mapping of the human genome in 2003, understanding of genes and the capacity to manipulate them have exploded. The ability to use genetic information to predict, diagnose, and treat a vast array of diseases in individuals grows exponentially by the day, and rapidly improving technology and computers that can analyze vast amounts of genetic data have created enormous potential.
     Molecular biologist Lee Hood, founder and CEO of the Institute for Systems Biology in Seattle, WA, is a leading pioneer in this new way of looking at health and disease prevention. He and colleagues at Caltech pioneered four instruments—the DNA gene sequencer and synthesizer and the protein sequencer and synthesizer—that were key to the successful mapping of the human genome. He now envisions computer chips that can create profiles of an individual’s disease risks based on a single blood sample.
     “I predict that within 10 years, we’ll be making billions of genetic measurements in individuals,” said Hood, in his opening presentation at the December symposium. “This requires biology, technology, and computational power. Genes are complex molecular machines. They encode proteins. Gene regulation and transcription factors can control the working of other transcription factors. Medicine in the future will be able to use this information to engineer disease mechanisms to make them behave in a way to lessen disease.”
     Modern molecular biology has reduced the study of disease to Lilliputian dimensions, with the key unit of measure a billion times smaller than a meter—the nanometer. At this level, genes and the proteins they
produce are observed to detect subtle changes over time and variations from person to person.

Biomedical engineers are developing new tools to complement this new knowledge. The term nanotechnology refers to the development of tools small enough to latch onto genes and proteins and make them visible to the human eye as well as able to be manipulated. For example, a team led by Emory researchers Shuming Nie and Leland Chung have developed specialized “quantum dots,” nanoparticles that target specific molecules on the surface of cancer cells when injected into the body. Eventually, the dots could be used to detect cancerous cells at extremely early stages and deliver targeted treatments that would eliminate the cells without damaging their healthy neighbors. These tools and targets are 100,000 times smaller than the diameter of a human hair.

Steve Warren, chairman of Emory’s Department of Human Genetics, says these capacities have created new ways to think about diagnosis, therapy, and drugs. “Fifteen years ago, we thought genetics would only help diagnose disease,” he says. “Now we know if we delve deep enough into individual genes, we can uncover logical interventions to prevent and treat diseases. The entire concept of predictive medicine evolved from the discipline of human genetics, and the concept of genomic medicine relates to all disciplines of medicine. It is the rare and exceptional disorder with no known genetic risk.”
The aim of predictive medicine is to use genetic information to better understand normal biological networks at the molecular level and then engineer or manipulate disease mechanisms to make them behave in a way to lessen disease. Patterns of gene expression are altered in disease. Normal protein secretion patterns can provide “molecular blueprints” of what healthy cells should look like, yielding new diagnostic tests and tools. Some of these proteins also will lead to new drugs and treatments targeted to an individual person’s genetic makeup.


	Too much of a good thing
	The human body can take pretty good care of itself. Thanks to the immune system, the human race has survived for millions of years in the face of ever-present and evolving microbial threats. When bacteria or viruses invade, white blood cells, T-cells, and a host of other immune actors keep invaders at bay. But immune protection doesn’t come without a price. Sometimes the hyper-vigilant defense system doesn’t know when to stop. The effects can be as benign as nagging runny noses and itchy rashes or as deadly as anaphylactic shock or sepsis. The swelling or inflammation that occurs when immune cells do their duty sometimes damages the body more than the initial threat itself, says David Stephens, an infectious disease expert. Chronic inflammation causes disorders like rheumatoid arthritis and Crohn’s disease and is increasingly linked to prevalent killers like atherosclerosis, heart disease, cancer, and Alzheimer’s. Emory researchers are seeking new ways to detect unhealthy inflammatory states. Stephens is leading a cross-disciplinary study supported in part by the Woodruff Fund. Leading immunologists including Rafi Ahmed, director of the Emory Vaccine Center, are collaborating. “Science is now making a transition from looking at first-generation biomarkers for inflammation like white count, sedimentation rate, and C-reactive protein to more sophisticated and precise measures,” Stephens says. “The next generation of inflammation biomarkers will include a variety of cytokine markers for chronic infection.” Cytokines are immune-signaling proteins produced by lymphocytes that accumulate where there is chronic injury, irritation, or invasion. Stephens’ study aims to understand markers of innate immunity, or the initial response of the host against infection, as opposed to adaptive immunity, which teaches the body to recognize and attack certain recurring infections. “Identifying certain differences in these receptors that mark innate immunity will provide clues about who will be at risk for increased or decreased inflammatory response,” he says.

We are not alone

It’s not just the human genome we have to worry about, warns David Stephens, director of infectious diseases in the Department of Medicine and executive associate dean for research in the medical school. The challenge of truly predicting what biologic changes are linked to future disease may be much more complicated than we realize.

The human body plays host to many tiny creatures: bacteria, viruses, and a host of other microscopic elements yet to be discovered. They live in our guts, our hair, our skin, between our teeth, and under our fingernails. They make us sick. They keep us well. They are in and around us all the time, interacting with every aspect of our being, including our genes.
“We live in a microbial world,” he says. “There is incredible biodiversity among microbes, and even with all the enthusiasm in the 1960s about eliminating diseases with antibiotics, vaccines, and sanitation, new and ever-more threatening infections are emerging all the time. Microbial mutation and recombination occurs at an astonishing rate. Microbes are perhaps the most adept organisms at adaptation. And most of the microbes in the world have yet to be defined.”

     Stephens maintains that human genetics and proteomics are insufficient to predict disease. The interactions between the environment and all the other forms of life we come in contact with have a profound effect on our bodies and our health. To make accurate predictions about genetic disease, the genetics of microorganisms and the way they interact with human cells must be unraveled as well.
     To illustrate his point, Stephens describes an unintended consequence of a once highly publicized medical breakthrough—the discovery that Helicobacter pylori causes stomach ulcers and is linked to the development of gastric cancer. Treatment of stomach ulcers with antibiotics has yielded a steep decline in rates of gastric cancer. But in the decades following wide acceptance of antibiotic treatment, a disturbing increase in cases of esophageal cancer occurred.
     Killing off H. pylori, Stephens says, has in some way upset a delicate gastrointestinal balance in some patients, perhaps also ridding the body of a yet-unidentified bacteria in the esophagus that provides a protective effect. Tinkering with the delicate balance our bodies have achieved with the microbial world over the past million years can have many unintended consequences.
     Any foray into predictive medicine must include charting the genomes of microbes and elucidating their interactions with human genes and proteins as well, Stephens says.

Who will benefit?

As if genes, proteins, and an invisible world of microbes were not enough, the ethical issues surrounding predictive medicine are daunting. Personal privacy and data security issues are just the beginning. How a university should concentrate its resources to help humanity get the most bang for the buck was a recurring theme at the predictive health symposium. No punches were pulled, and the discussion was rigorous.
     Howard Kushner, who holds dual appointments in history and public health, considers himself an applied historian of medicine. He believes medical knowledge should be viewed in historical and cultural perspectives. At the predictive health symposium, he suggested committing more resources to the “bigger picture” of health care.
     “Our medical system is broken,” he says. “In the richest country in the world, 30% of Americans have no access to regular preventive health care. Increasingly, we find we can’t even trust the information coming out in medical journals. Behavioral aspects of health have not been well studied and factored into the equation of this new predictive health model. We already have many good health care technologies and lots of knowledge, but they’re not effective because of noncompliance and a lack of will to provide equity.”
     Indeed, ensuring the integrity and reliability of the information obtained will be central to the success of predictive medicine. Storing, retrieving, and using the vast amounts of medical data that could soon be available for every individual will be a monumental computer science challenge, notes Kathy Kinlaw, director of the Emory Ethics Center. To be useful for predicting future illness, the data collected must be standardized. Physical characteristics are deemed “normal” or “abnormal” by comparison with population averages, she notes. Without that information, the genome of a particular individual may not yield much diagnostic information. The potential for human error in interpreting genetic information must also be factored into the predictive medicine equation.
     “Once we have determined a biomarker, will the information be specific enough to have any value?” Kinlaw asks. “Will all patients want to know the information and will there be therapeutic interventions to offer them once they have this knowledge? Ethics must be a key part of this initiative because these questions will accompany this movement all the way.”


	Looking at the big picture
	When many people think of the future of predictive medicine, they think of personalized treatments tailored to an individual’s specific genetic code. But the real promise of predictive medicine, many researchers say, lies in its potential to help society determine the best use of limited health care resources. “We need to know how to find the high-risk people,” says Kimberly Rask, professor of health policy and management at the Rollins School of Public Health (RSPH). “It costs more to screen everyone than it does to screen a sub-sample of people, and the number of at-risk people identified will determine the cost-effectiveness of screening.” Rask and other Emory researchers are exploring how to incorporate economics, epidemiology, and the intricacies of human behavior into the predictive health equation. Ongoing studies of large groups of people at risk for Parkinson’s disease and type 2 diabetes offer opportunities for finding new population-based strategies for disease prediction. “They are both common chronic diseases that irreversibly damage the body over time, but effective treatments are available,” says Rask. “Diabetes involves both behavioral and genetic risk factors, with rising rates of obesity correlated with the recent explosion of diabetes among Americans.” Parkinson’s disease involves a complex interplay between genetic and environmental factors. A small percentage of cases occur in young people and are thought to be purely genetic. But the majority of cases are diagnosed in people older than 55 and probably stem from environmental or a combination of genetic and environmental factors. Gary Miller and Scott Bartell, professors of environmental and occupational health at the RSPH, are working with Emory neurologists and scientists in the Emory/Georgia Tech Department of Biomedical Engineering to develop a model of Parkinson’s disease based on systems biology. They are developing a set of complementary computational models to seek connections between permutations of genotypes, environmental exposures, lifestyle factors, and the occurrence of Parkinson’s. They hope to develop predictive algorithms to help clinicians diagnose the disease earlier. They then can aim prevention strategies at the populations at greatest risk.

Miller says early intervention is crucial. “By the time a patient is diagnosed with Parkinson’s, more than 80% of the dopamine-producing neurons in the brain have already been lost,” he says. “This leaves only a very small window of opportunity for interventions aimed at slowing or halting the progression of the disease. Our computational approach may lead to earlier detection and treatment of the disease and possibly complete prevention.
“Many clinical trials of drugs to treat Parkinson’s disease have failed

over the past decade, possibly because the disease had progressed too far for these drugs to be effective,” he says. “However, some of these may work well if started earlier.”

     A similar approach is being used to study diabetes. Now the sixth leading cause of death in the United States, rates of type 2 diabetes—the most common kind—are skyrocketing. The Centers for Disease Control and Prevention reports that diabetes incidence increased by 33% from 1990 to 1998. Currently, an estimated 7% of the population has it.
     Rask, who directs the Emory Center for Health Outcomes and Quality, is studying interactions between genetic and behavioral risk factors for diabetes. She is analyzing data from the Third National Health and Nutrition Examination Survey (NHANES III) as well as data from a group of diabetes patients at Grady Memorial Hospital.
     “Health outcomes studies show that even after diagnosis many patients do not receive recommended care for many clinical conditions,” she says. “When disease prevention involves behavior change such as losing weight or exercising, patients often don’t follow through. Economic barriers to health care can also keep patients from early diagnosis and proper follow-up treatment.”
     In the Grady portion of Rask’s work, she will collect a comprehensive set of biologic, behavioral, and environmental risk data for health outcomes in diabetic patients. Their health care-seeking behavior will be monitored and correlated with behavioral and environmental factors to find the best predictors of healthy outcomes.
     “The challenges are daunting,” Rask says. “Persuading insurance companies to cover extensive, and perhaps expensive, predictive health testing will be difficult. That’s why we require strong cost-effectiveness data for predictive health models.”

Finding the method to the madness

Doctors and scientists have known for years that many mental disorders have a strong genetic component. Population studies indicate that people who have a family history of bipolar disorder or schizophrenia, for example, face a higher risk of developing the illness themselves. But researchers are only just beginning to discover which genes and mutations are associated with mental illness and what role environmental exposures and life experiences might play.
Emory psychiatrist Joseph Cubells is studying a group of children at high risk for schizophrenia because they have a genetic condition called 22q11 deletion syndrome (22q11DS). This syndrome arises from deletion of some DNA from a portion of chromosome 22, resulting in only one copy of these genes, rather than the normal two copies. Of

adults with molecularly confirmed 22q11DS, 20% to 30% meet the standard diagnostic criteria for schizophrenia. These percentages indicate an association between the deletion and the disease, but not all patients with the deletion end up with schizophrenia.
Cubells and coworkers are studying a group of adolescents and children with 22q11DS, in the hopes of identifying new behavioral and molecular predictors of schizophrenia risk. By pairing neuropsychologic tests of cognitive function, attention, and working memory with detection of certain enzymes and genetic variations sometimes associated with schizophrenia, Cubells hopes to identify sequence variants (biomarkers) in these genes that predict whether children with 22q11DS will develop schizophrenia.
Identifying early signs of the illness could lead to earlier intervention with medication, psycho-education, and other behavioral measures to slow the progression of schizophrenia. “Complex brain disorders like schizophrenia are usually chronic and recurrent,” says Cubells. “As time passes, patients not only contend with the primary symptoms of the illness, they develop coping strategies and self-images often warped by the illness. Even after recovery, they often have to unlearn maladaptive habits and patterns of thinking that developed during symptomatic periods.”

Biomarkers for mental illnesses like depression or bipolar disorder have been elusive, but new genetic and neuroimaging tools hold great promise. “Early detection of mental illness through biologic markers will put to rest the vicious myth that brain disorders are associated with moral failure or weakness of will,” Cubells says. “Erasing that stigma will bring us closer to parity in insurance coverage for brain disorders as we demonstrate that complex brain disorders are every bit as ‘medical’ as diabetes or heart disease.”

Will it work?

Jeffrey Koplan, vice president for academic health affairs at WHSC and former director of the U.S. Centers for Disease Control and Prevention, concurs. At the symposium, he asked the audience whether they had drunk clean water, worn a seatbelt, or had unprotected sex with a stranger that morning. (RSPH Dean and HIV expert James Curran raised his hand in jest to the last question.)
     “Public health aims for the big, quick impact health interventions can have on large populations,” Koplan says. “I would argue that public health achievements are the most significant medical achievements made during the past 100 years. We must ask: Will this technology be available to all? In public health we value equity. The concerns I have are the existing disparities in care at home and abroad, the issue of privacy, and the problems posed by giving people disturbing information years before they can do anything about it.”
     Deryk Yach, professor of global health at Yale School of Medicine and a native of South Africa, questioned whether many people—given information about future disease risk—would still follow through with the necessary steps to prevent disease.
     “Strong economic forces are driving global changes in health and culture,” he says. “The countries that are experiencing the most rapid income increases also are having increasing levels of cholesterol and body mass index. And we have no example in the world—no success story—where rising obesity has been reversed in the population. This leads to an old age full of disability and disease, with low quality of life.”
     Yach says that along with more economic opportunity, the developing world is importing risky behaviors from the West, such as smoking and high-fat, high-sugar diets. “Yet levels of hunger and underweight are at 50% in many parts of Africa and Southeast Asia, and life expectancy has been declining among Russian men,” he says. “I think that the current obesity epidemic in the western world has affirmed the theory of flawed self assessments. We know what to do to stay healthy, yet we always fail to do what’s best for us.”
     He also issued a grave warning about creating vast databanks of predictive health information. “I have no doubt that insurance agencies will cherry pick at the highest levels when we get such data.”
     The Emory/Georgia Tech Predictive Health Institute must help society face these challenges in the new age of medicine that is coming, whether we like it or not, says Johns. In fact, academic institutions are the best places to make sure ethical and public health implications are integrated into the practice of this “new medicine.”
     U.S. government health officials recognize this coming “sea change” but acknowledge that dealing with it will take time and political willpower. Currently, the U.S. Senate has twice passed a genetics discrimination bill, and the House of Representatives has refused to pick it up.
     Johns acknowledged the difficulty and complexity of the task ahead. “The work ahead of us is monumental but of crucial importance for the world,” he says.
“We aim to be among the premier universities, and we must be up
for this challenge.”

Valerie Gregg is a freelance writer in Atlanta.

Exploring the cancer connection
Predictive medicine is also the focus of a new federally funded initiative at Emory’s Winship Cancer Institute.

Scientists at Emory and Georgia Tech are working in tandem to develop nanotechnology tools to detect and manipulate cancer at the molecular level. Their efforts recently earned them status as one of eight National Centers of Cancer Nanotechnology Excellence (CCNE) designated by the National Cancer Institute. This award carries nearly $27 million in federal and state funding over the next five years.

	The grant created a new center called the Emory-Georgia Tech Nanotechnology Center for Personalized and Predictive Oncology. Housed at both Winship and Tech, the center aims to integrate nanotechnology into personalized cancer treatments and early detection and deliver these tools to patients within the next decade. The joint Department of Biomedical Engineering at Georgia Tech and Emory, established in 1997, was a key factor in gaining the CCNE designation. The CCNE’s director and principal investigator is Shuming Nie, the Wallace H. Coulter Distinguished Chair and Professor. Nie’s work involves both quantum dots and raman tags, computer chips so tiny that they can attach themselves to the proteins produced by certain genetic changes. With new digital imaging technology, these chips can identify the markers of genetic change and make them visible to the human eye. Along with biomedical engineer Gang Bao and others, Nie plans to create particles that can zoom in on pre-cancerous cells and ultimately deliver targeted therapeutics to halt the genetic changes that lead to cancer. The Emory/Georgia Tech collaboration is one of the largest federally funded programs in biomedical nanotechnology, biomolecular and cellular engineering, cancer bioinformatics and biocomputing, and translational cancer research. The CCNE now encompasses six projects with five core areas of study. Other current projects include
	Development of tumor-targeted infrared quantum dots with optical and magnetic imaging capabilities. “Smart” nanoparticle probes for intracellular drug delivery and gene expression imaging. Antibody-conjugated quantum dots to detect and quantify human breast cancer biomarkers. Nanoparticle tags for tracking multiple biomarkers in biologic specimens using surface-enhanced raman spectroscopy. Nanoparticles to deliver therapeutics to bone metastases.
	“We have a truly collaborative environment for research to help translate biomedical engineering discoveries into clinical medicine,” says Nie. “This center will help cancer patients all over the world.”