Iceland OKs private health databank

Models of biobanks and implications for reproductive health innovation

Biobanks are designed with particular purposes in mind. These purposes are reflected in the governance frameworks that define the conditions for participation and access by researchers. In this paper, I analyse two different models: the commercially aligned deCODE biobank and the 'public good' framework of UK Biobank. These diametric models have both featured 'the public interest' as pivotal to their achievements. However, if properly understood, the public interest rhetoric of deCODE actually conflicts with any professed community interest. The reasons why are explained, and the effects this has on conditions for participation are critiqued, before reflecting on how each model might have an impact on reproductive health research.

The Emergence of Biobanks: Practical Design Considerations for Large Population-Based Studies of Gene-Environment Interactions

The completion of the human genome project has spurred new thinking about launching large-scale cohort studies; as proposed, these studies will differ from past large-scale cohort studies and will focus primarily on how genetic variation interacts with environmental exposures to affect the risk for common human diseases. There is no single 'best design' for large-scale studies of gene-environment interactions. Some studies are best performed in cohort studies where unbiased information can be collected on individuals years before disease onset. Other studies may be most efficiently done with a case-control design using currently available automated data. Population-based biobanks with nested case-control or case-cohort studies offer distinct advantages to some of the resource-intensive large-scale cohort studies under consideration, and may be more acceptable to many of the countries around the world currently considering such projects.

Genes and spleens: property, contract, or privacy rights in the human body?

This article compares three frameworks for legal regulation of the human body. Property law systematically favors those who use the body to create commercial products. Yet contract and privacy rights cannot compete with the property paradigm, which alone affords a complete bundle of rights enforceable against the whole world. In the face of researchers' property rights, the theoretical freedom to contract and the meager interest in privacy leave those who supply body parts vulnerable to exploitation.

Harnessing the mouse to unravel the genetics of human disease

Complex traits, i.e. those with multiple genetic and environmental determinants, represent the greatest challenge for genetic analysis, largely due to the difficulty of isolating the effects of any one gene amid the noise of other genetic and environmental influences. Methods exist for detecting and mapping the Quantitative Trait Loci (QTLs) that influence complex traits. However, once mapped, gene identification commonly involves reduction of focus to single candidate genes or isolated chromosomal regions. To reach the next level in unraveling the genetics of human disease will require moving beyond the focus on one gene at a time, to explorations of pleiotropism, epistasis and environment-dependency of genetic effects. Genetic interactions and unique environmental features must be as carefully scrutinized as are single gene effects. No one genetic approach is likely to possess all the necessary features for comprehensive analysis of a complex disease. Rather, the entire arsenal of behavioral genomic and other approaches will be needed, such as random mutagenesis, QTL analyses, transgenic and knockout models, viral mediated gene transfer, pharmacological analyses, gene expression assays, antisense approaches and importantly, revitalization of classical genetic methods. In our view, classical breeding designs are currently underutilized, and will shorten the distance to the target of understanding the complex genetic and environmental interactions associated with disease. We assert that unique combinations of classical approaches with current behavioral and molecular genomic approaches will more rapidly advance the field.