What is Evolutionary Epidemiology?:
Adding another “why” to the “who, what, when, where, and why” of modern epidemiology
Chris Reiber & John H Holmes
The term “evolution” often conjures up images of a litany of prehistorical forms culminating in modern humans, and the relevance of this array of data points to modern medicine and epidemiology can be very hard to see at face value. But the terms “evolutionary medicine” and “evolutionary epidemiology” imply much more. These emerging fields focus on applying an understanding of the evolutionary process to modern biomedical issues. Thinking about organisms—humans included—as both products of, and active participants in, the ongoing evolutionary process can provide novel insights. Why are we the way we are? Why are we vulnerable to particular diseases/disorders and not others? Why do our biophysiological processes work the way they do? Answers to questions such as these are the starting point for evolutionists, and can lead the epidemiological detective down new and exciting pathways to discovery and understanding.
This workshop is intended to provide evolutionary basics for use in epidemiology. It will cover topics including: what is evolutionary epidemiology, and why should you care?; a modern understanding of the evolutionary process; how this understanding is applied to medicine and epidemiology; the history of using evolution in epidemiology (with some examples); and where the field is going in the future.
Evolution and Surveillance
John H Holmes & Chris Reiber
Evolutionary theory offers a potentially useful paradigm for epidemiologic
surveillance, regardless of the outcome under investigation. Characteristics of populations such as extended interpersonal contact through networks and systems of networks, frequent migration by such means as air travel, ever-increasing exposure to information, and growing population complexity overall suggest the need for new thinking about epidemiologic surveillance and the ways we approach it. This is especially intriguing given the development of new computational approaches to signal detection and pattern recognition that can provide theoretical models for surveillance as well as useful analytic tools for the epidemiologist. Inspired by evolution, complex systems science, and population biology, these computational approaches include neural networks, artificial immune systems, and evolutionary computation. Given their metaphorical link to biological phenomena, they are a natural fit with monitoring population health and disease.
This workshop will examine evolution as a model for epidemiologic surveillance. Specific topics that will be covered in the workshop include epidemiologic surveillance as an evolutionary process, populations as complex adaptive systems, emergence of disease patterns over networks, and biologically-inspired computational models for
surveillance. A real-world example applying evolutionary computation-based system to analysis of surveillance data will be presented and discussed.
Introduction to Genomewide Association Studies (GWAS)
Genomewide association studies use the genetic variation across the entire human genome to identify associations with observable traits. This workshop will introduce the essentials of genomewide association studies, followed by presentations describing results of genomewide association studies by leaders in the field.
- Essentials of genome wide association studies for epidemiologists (Tasha Fingerlin
- Genome wide association studies of type II diabetes and associated traits (Michael Boehnke, Richard J. Cornell Collegiate Professor of Biostatistics, Director Center for Statistical Genetics, University of Michigan)
- Genome-wide association studies for cardiac repolarization and Sudden Cardiac Death (Aravinda Chakravarti, Director Center for Complex Disease Research, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University)
"Measuring our success: Evaluating impact of epidemiologic findings in the age of genomewide association studies"
D. Winn, Moderator
Epidemiologic findings can sometimes lead to immediate or dramatic clinical or public health impacts. For the most part, however, documenting success has relied on how well cited a particular epidemiologic finding is or the impact factor of the journal where it is published. This approach fails to capture how epidemiologic findings get used by the range of constituencies who move those findings forward into developing clinical guidelines, making public policy, or using the information to improve one's own personal health or ameliorate one's risk of disease. The metrics are further changed with the emergence of genomewide association studies, which pose their own set of interpretation challenges. This session will explore how a transdisciplinary model approach can be used to evaluate the success of a research enterprise, and identify problems and solutions to measuring the impact of epidemiologic research in the age of genomewide association studies.
Session Agenda
| 1:30-2:15 |
Current approaches to evaluating impact of epidemiologic findings: Nurses Health Study Example - Deborah Winn, Ph.D. (National Cancer Institute, Rockville, MD) |
| 2:15-2:45 |
Genome-wide association studies of cancer: Recent results and future directions - Daniela Seminara, Ph.D. (National Cancer Institute, Rockville, MD) |
| 2:45-3:00 |
Validation of GWAs findings: When do we know we have found it? - Emily Harris, Ph.D., MPH (National Institute for Dental and Craniofacial Research, Bethesda, MD) |
| 3:00-3:15 |
Break |
| 3:15-4:00 |
Paradigms for translation of genomic findings into clinical utility and public health applications – Deborah Winn, Ph.D. (National Cancer Institute, Rockville, MD) |
| 4:00-4:30 |
Clinical and public health utility – Where to go from here? Daniela Seminara, Ph.D. (National Cancer Institute, Rockville, MD) and Emily Harris, Ph.D., MPH (National Institute for Dental and Craniofacial Research, Bethesda, MD) |
The NIH Grant Review Process
The purpose of this workshop is to discuss the review of investigator-initiated grant applications submitted to the National Institutes of Health (NIH). NIH grants are awarded based on a system of peer review that has its goal evaluating the scientific and technical merit of an application through a process that is fair, competent and thorough. There have been many changes to the policies and practice of peer review at the NIH Center for Scientific Review (CSR), such as special opportunities for principal investigators who have never had an NIH R01 grant application, the option to have multiple principal investigators on an application, more rapid receipt of scores and summary statements, electronic approaches to peer review and new incentives for reviewers. Examples of changes planned for the future include shortening and streamlining applications, restructuring summary statements and shortening the review cycle. This workshop will focus on these changes and other special issues. Information on the six chartered epidemiology study sections will be presented.
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