Genomic Research and Data-Mining Technology: Implications for Personal Privacy and Informed Consent

Abstract

This essay examines issues involving personal privacy and informed consent that arise at the intersection of information and communication technology (ICT) and population genomics research. I begin by briefly examining the ethical, legal, and social implications (ELSI) program requirements that were established to guide researchers working on the Human Genome Project (HGP). Next I consider a case illustration involving deCODE Genetics, a privately owned genetics company in Iceland, which raises some ethical concerns that are not clearly addressed in the current ELSI guidelines. The deCODE case also illustrates some ways in which an ICT technique known as data mining has both aided and posed special challenges for researchers working in the field of population genomics. On the one hand, data-mining tools have greatly assisted researchers in mapping the human genome and in identifying certain “disease genes” common in specific populations (which, in turn, has accelerated the process of finding cures for diseases that affect those populations). On the other hand, this technology has significantly threatened the privacy of research subjects participating in population genomics studies, who may, unwittingly, contribute to the construction of new groups (based on arbitrary and non-obvious patterns and statistical correlations) that put those subjects at risk for discrimination and stigmatization. In the final section of this paper I examine some ways in which the use of data mining in the context of population genomics research poses a critical challenge for the principle of informed consent, which traditionally has played a central role in protecting the privacy interests of research subjects participating in epidemiological studies.

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Tavani, H.T. Genomic Research and Data-Mining Technology: Implications for Personal Privacy and Informed Consent. Ethics and Information Technology 6, 15–28 (2004). https://doi.org/10.1023/B:ETIN.0000036156.77169.31

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  • data mining
  • deCODE Genetics
  • distributional group profiles
  • epidemiology
  • genetic exceptionalism
  • genomic research
  • informed consent
  • non-distributional group profiles
  • personal privacy
  • population genomics