Introduction

From the official beginning of the Human Genome Project in 1990 to the present, genomic and genetic research has been characterized by its enormous scale. Genome researchers often analyze and manipulate vast data sets derived from the 3.2 billion base-pair human genome. Other new “omics” fields, such as proteomics, transcriptomics, and metabonomics, also involve large-scale research undertakings. To facilitate these efforts, research biobanks containing many thousands of biological specimens are used to provide statistically significant numbers of even rare genomic variants. Genome research also requires sophisticated, high-speed computational technology for genome-wide association studies and other analytical techniques. The phenotypic data for researchers increasingly come from electronic health records (EHR), another automated and large-scale contribution to the scientific enterprise.

Some areas of genome research involve especially sensitive or stigmatizing health conditions, such as behavioral health. For example, substantial genetic research has established correlations between certain genes and a propensity to addictive behavior, including gambling and the use of alcohol, tobacco, and various licit and illicit substances (Blum et al., 2000; Caron et al., 2005; Goldman et al., 2005). When large-scale biomedical research and powerful computational technologies are combined and applied to research involving sensitive health conditions, a range of important privacy issues are raised. These issues include: the consent needed for using biological specimens and health records, even if de-identified; the tangible and intangible harms, including group-based harms, that can flow from disclosure of genetic information; and the autonomy interests of individuals in controlling the uses of their specimens and health records.