 to BRCA1 (31); Alzheimer's disease in relation to the Apolipoprotein E-E4 allele (32); and iron overload in relation to the hemochromatosis gene (33). Given the paucity of population-based epidemiologic data regarding the frequency of and disease risks and environmental interactions for many newly discovered human gene variants, there is concern that appropriate health policy on the use of genetic tests may not be possible.
Human Genome Epidemiology
The term "human genome epidemiology" (HuGE) denotes an evolving field of inquiry that systematically applies epidemiologic methods and approaches in population-based studies of the impact of human genetic variation on health and disease. HuGE can be viewed as the intersection between genetic epidemiology and molecular epidemiology (34). Whereas genetic epidemiology has traditionally focused on techniques to find disease genes using linkage and segregation analysis, and molecular epidemiology focuses on using biological markers in epidemiologic studies.
The wide spectrum of topics addressed by investigators working on human genome epidemiology and selected examples are shown in Table 4(36). The spectrum ranges from population-based epidemiologic research on gene variants to evaluation of genetic tests and services. Ultimately, HuGE represents the application of clinical and molecular research to a population setting and involves the collaboration and contribution of numerous specialties.
In 1998, a collaboration of individuals and organizations launched the Human Genome Epidemiology Network (HuGE Net). This global effort seeks to (1) promote collaboration in developing and disseminating of peer-reviewed epidemiologic information on human genes; (2) develop an updated and accessible knowledge base on the World Wide Web; and (3) promote use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic tests and services for disease prevention and health promotion (34-35).
II. Evaluation of genetic testing
The book we will focus on two main types of evaluation-related activities: (1) the assessment of how and when genetic tests can be or are used to promote health and to diagnose and prevent human disease; and (2) the development of standards and guidelines for assuring quality genetic testing. As defined by the Task Force on Genetic Testing, genetic tests include the analysis of human DNA, RNA, chromosomes, proteins, and certain metabolites in order to detect a person's genotype for clinical purposes, including predicting risk of disease, identifying carriers, and establishing prenatal and clinical diagnosis or prognosis (37).
The Task Force on Genetic Testing recognized the need to evaluate several types of data parameters (analytic validity, clinical validity, and clinical utility as defined in Table 5) for each genetic test before transitioning the test from research to clinical practice. Since evaluation of genetic tests used in the prediction of adult-onset diseases may require years of follow up, the Task Force also outlined the need for post-market reevaluation of the same three parameters for genetic tests in the context of "real-world" use and to reevaluate policies and recommendations on the use of genetic tests. These and other parameters of the pre-analytic and post-analytic testing process need to be continuously evaluated in population-based settings.
The second main area of evaluation concerns the development of standards, regulations, and guidelines to ensure the accuracy, validity, and precision of laboratory procedures and to ensure that other quality assurance issues are addressed as well.
All clinical laboratories in the United States that provide information to referring physicians are certified under the Clinical Laboratory Improvement Act (CLIA) Amendments of 1988 (38). CLIA standards for quality control, proficiency testing, personnel, and other quality assurance practices apply to all genetic tests. CLIA regulations, which are jointly developed and administered by the