Book Review

Molecular Epidemiology: Applications in Cancer and Other Human Diseases

N Engl J Med 2008; 359:1971-1972October 30, 2008

Article

Molecular Epidemiology: Applications in Cancer and Other Human Diseases
Edited by Timothy R. Rebbeck, Christine B. Ambrosone, and Peter G. Shields. 302 pp., illustrated. New York, Informa Healthcare, 2008. $199.95. ISBN: 978-1-4200-5291-6

Molecular epidemiology extends traditional epidemiology studies based on questionnaires by incorporating genetic and molecular measures as biomarkers of exposure, risk, and prognosis. The explosion of genetic information and laboratory methods for high-throughput genotyping, gene expression, and proteomics requires new approaches to the design of studies in molecular epidemiology. The design and conduct of large, powerful studies of multiple biomarkers calls for a collaborative approach, and the integration of epidemiology, genomics, proteomics, metabolomics, biostatistics, and bioinformatics requires a shared language. In Molecular Epidemiology, Timothy Rebbeck, Christine Ambrosone, and Peter Shields bring together experts who present to a wide audience of readers the nuances and language of molecular epidemiology.

The book's initial chapters cover study designs that are the mainstay of epidemiologic research. The authors of some of these chapters discuss alterations to well-established approaches to the study of risk and prognosis, emphasizing where special attention is needed in the study of biomarkers. These chapters should provide molecular biologists and geneticists with a solid understanding of alternative study designs for the assessment of biomarkers in epidemiologic studies as well as with the language that is needed to engage epidemiologists. Subsequent chapters provide epidemiologists with a broader understanding of laboratory methods and sample preparation to ensure the validity of study results.

Beyond setting out the common language that is needed for multidisciplinary studies in molecular epidemiology, this book moves nicely into a discussion of the challenges researchers face in the interpretation of results. During the past 15 to 20 years, studies of genetic contributions to risk have included biology-informed studies of single-nucleotide polymorphisms (SNPs) in one candidate gene and multiple SNPs within pathways, as well as agnostic approaches that use family-based linkage studies and genomewide association studies. The discussion of the most appropriate study design, including the selection of controls and SNPs to genotype, is well referenced. Each of these approaches has required the development of bioinformatics methods for the selection of pathways to study and for the interpretation of results from genomewide approaches, as well as the development of biostatistical methods for the analysis of large, complex data sets with multiple comparisons. This book gives appropriate space to the discussion of how to handle seemingly infinite data points and caveats to data interpretation. Especially important are the chapters about assessing causality, reporting results, and informing risk prediction. Chapter 18, “Reporting and Interpreting Results,” includes discussion of the assessment of causality in epidemiologic studies and further illustrates the complexity of the design and interpretation of studies in molecular epidemiology.

The success of research in molecular epidemiology is nicely defined in chapter 12, “Novel Analytical Methods for Association Studies,” as depending on “our ability to embrace, rather than ignore, complexity in the genotype-to-phenotype mapping relationship for any given human ecology.” We are limited by our current knowledge of the function of selected genes and discovered gene regions. As our ability to measure human genetic variation increases, so will the difficulties of studies that are aimed at understanding how genetic variation affects the risk and prognosis of disease. This book provides a guidepost for where we are today and what we need to keep in mind while moving the field of molecular epidemiology forward.

Ann G. Schwartz, Ph.D., M.P.H.
Karmanos Cancer Institute, Detroit, MI 48201
schwarta@karmanos.org