Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health
BOOK REVIEWS |
Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease
Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205
Edited by Muin J. Khoury, Julian Little, and Wylie Burke
ISBN 0-19-514674-3, Oxford University Press, New York, New York (Telephone: 800-451-7556, Fax: 919-677-1303, E-mail: cusserv.us{at}oup.com, Website: http://www.oup.com/), 2003, 576 pp., $65.00 (hardcover)
In recent years, there has been considerable interest in the Human Genome Project and a fair amount of hyperbole about its potential applications in biology and medicine. The completion of the first draft of the human genome in 2001 did mark the legitimate beginning of a new scientific era, one in which the wealth of sequence information on the human genome (as well as the genomes of other species) must be incorporated into many (if not all) areas of biologic research. However, in disciplines using solely observational studies of humans, it remains a significant challenge to identify the best and most efficient ways of incorporating this information.
The period just before the completion of the Human Genome Project was characterized by a "gene-of-the-week" approach, wherein studies were proposed (and some were carried out) on the theory that if one could just collect enough multiplex families or affected sibling pairs, it would be feasible to map the gene for almost any disease or condition. This led to the belief that all genes could be mapped, cloned, and perhaps patented for commercialization following some standard design. This strategy proved to be viable for Mendelian diseases in which there is one causal gene or just a few causal genes. If one could assume that "multifactorial" or "complex" diseases were simply poorly behaved versions of Mendelian diseases, why shouldn’t it work for them? Once causal mutations or even strong genetic risk factors were identified, it would just be a matter of time before an individual’s genotype at one or several genes could be used to predict his/her lifetime risk of these "complex diseases" with an accuracy that would make preventive steps feasible (either prevention of the disease phenotype through early intervention and treatment or prevention of the genotype in the setting of prenatal screening) or to tailor pharmaceutical interventions to his/her specific genotype. Collins and McKusick (1) projected that this type of risk prediction could become feasible as early as 2010 and that it should be widely incorporated into clinical medicine by 2020. However, there are several obstacles that must be overcome before this potential can be achieved, and this book (2) addresses many of them in a thorough, if roundabout, manner.
The first section of the book ("Fundamentals") does an excellent job of laying out the depth of the problems involved in dealing with complex diseases (where genes partly control risk) and correctly points out the importance of having basic epidemiologic information about such genes and their impact on risk from valid epidemiologic studies based on representative samples of subjects. In this section, Ellsworth and O’Donnell summarize available techniques for genotyping different types of genetic markers, including expression arrays. Peyser and Burns provide a comprehensive review of conventional strategies for genetic analysis, and Beskow summarizes the ethical, legal, and social issues relevant to genetic epidemiology studies in humans.
The second section ("Assessing Disease Associations and Interactions") covers technical issues, such as collection of DNA, as well as issues of study designs and analytical strategies. This may be the most useful section, along with the last section. Currently, we are still in the phase of identifying genetic risk factors for most complex diseases. Some of these variant alleles will eventually be shown to be truly causal and some of them may never be elevated beyond the status of "risk factor." We should not underestimate the levels of complexity underlying "complex" diseases, because multiple mutations at any one gene and multiple genes can produce disease. Furthermore, these different genes may interact with one another and with environmental factors to increase risk. Carefully designed population-based and/or family-based studies will be necessary to identify which genes consistently influence risk; it is likely that meta-analyses or pooled analyses from multiple studies will be needed to confirm many of these associations, and possibly all putative interactions. Many readers will find the three chapters on study design by Thomas, Botto and Khoury, and Garcia-Closis et al. particularly useful. The chapter by Kelada et al. reviewing how environmental health science has incorporated genetic markers into studies of disease risk is itself a useful resource. Little’s chapter reviewing human genome epidemiology studies clearly lays out the principles that should guide interpretation of associations found in observational studies. A strength of this book is the set of examples of genes that have proven to be involved in the etiology of various complex diseases.
The future directions of human genome epidemiology are still evolving, but the third section ("Assessing Genetic Tests for Disease Prevention") offers a structured guideline for potential applications. Epidemiologic measures of the analytical validity of a genetic test (including the sensitivity, specificity, and predictive value, both positive and negative, of tests identifying the high-risk genotype) are a prerequisite for effectively applying a genetic test to populations, but it is also necessary to consider the clinical validity (these same measures, but relevant to the true risk for individuals carrying the high-risk genotype) and the clinical utility of the test in the current setting (e.g., the estimated benefits and risks for positive and negative test results, respectively). The chapter on evidence-based approaches to genetic testing by Vineis also lays out useful criteria for deciding when testing is appropriate for a population and when it is not. Two national examples (in the United States and the United Kingdom) of how genetic tests are implemented provide real-world examples. In this section, the uncertainty about even the best examples of gene-disease associations and the underlying heterogeneity of "complex" diseases become painfully obvious, and these limitations can be daunting. Caution should be exercised when trying to predict how rapidly new genetic information can be effectively incorporated into clinical medicine or public health, because even the best-known examples of genes’ controlling risk of complex diseases (such as the BRCA1/2 gene and breast cancer and the APC, MSH2, and MLH1 genes and colorectal cancer) are far from clean. Simplistic predictions of disease risk based on genotype are not currently feasible, and may not become so until a much fuller understanding of the relevant biology is attained.
The last section of this book is valuable because it provides actual case studies of where human genome epidemiology stands with regard to a wide range of complex diseases, including colon cancer, deep vein thrombosis, congenital deafness, and hemochromatosis. These dozen reviews of current knowledge on various complex diseases are generally very good, and they represent some remarkable instances of real progress in our scientific understanding of how genes control disease. Still, they represent a cautionary tale of what we should expect from genetic studies of complex diseases and how hard it will be to achieve the goal of tailoring medicine to personal genomic data, let alone public health. There will be an enormous amount of complexity and heterogeneity at virtually every level (both different alleles at one gene and different genes, plus probable interactions) on top of variability across populations in both genetic and environmental risk factors. For example, hemochromatosis is genetically relatively simple (one gene with multiple allelic mutations accounting for most cases); yet the variation in allele frequencies across populations, the gender differences in severity of disease, and the ever-present issue of "incomplete penetrance" among the high-risk genotypes complicate the design of large-scale screening programs.
These challenges to public health are daunting but should not be viewed as either overwhelming or paralyzing. The wealth of genomic data now available will not instantly produce valid predictions of lifetime risk of every disease based on one’s genetic makeup, but continued investigation aimed at incorporating genetic information into public health research and practice holds the promise of major scientific gains and eventually public health gains. This book lays out the requirements and tools needed to achieve that goal.
REFERENCES
REFERENCES
- Collins FS, McKusick VA. Implications of the Human Genome Project for medical science. JAMA 2001;285:540–4.
[Abstract/Free Full Text] - Khoury MJ, Little J, Burke W, eds. Human genome epidemiology: a scientific foundation for using genetic information to improve health and prevent disease. New York, NY: Oxford University Press, 2003.
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