“Use it or lose it” as an alternative approach to protect genetic privacy in personalized medicine

Abstract

Scholars have spent considerable time discussing the challenges and importance of protecting privacy in the context of genomic medicine [see, e.g., 1]. There is a great deal of research and clinical potential to be gained from storing massive amounts of genotypic data but this must be weighed against the possible risks to individual privacy, a quandary some have described as “privacy versus the gold-mine” [2]. DNA is a unique identifier and has the potential to reveal medical (and non-medical) information about individuals and by consequence their family members. For instance, genomic data could reveal undesired pre-symptomatic health information, non-paternity, or even be used to frame a suspect at a crime scene [3]. Access to, or disclosure of, this information, whether authorized or not, could lead to various forms of misuse and discrimination (e.g. employment, insurance, and financial). The advent of whole genome sequencing has compounded privacy concerns because it could reveal entirely unanticipated information particularly as our ability to (re)interpret genomic sequence data is continually improving [1; see also 4-6]. In addition, genomic information could have consequences beyond the individual from whom it was derived, including both lineal relatives (e.g., children and grandchildren) and collateral relatives (e.g., siblings, cousins, nieces, and nephews) who may be unaware that the individual is undergoing sequencing. Intra-familial privacy issues are complex and vary from one family to another; however, in the clinical context physicians typically give precedence to individual patient privacy and autonomy over the interests of a patient’s relatives. For example, one patient who is found to carry a mutation in the BRCA1 or 2 genes, which increases the risk of breast and/or ovarian cancer, may not want this information revealed to family members for a variety of reasons whereas another patient receiving the same may choose to share this with all of his/her family members, only specific family members he/she worries may be at heightened risk, or even complete strangers to advance biomedical research [see, e.g., 7]. A patient’s care might be improved if the health care provider were able to ascertain genetic information of the relatives as well as that limited information on family medical history known to and shared by a specific patient; however, the idea of linking genomic records between family members or creating joint accounts containing certain genetic data to which multiple patients’ records have access has not yet garnered strong support. A frequent if not ubiquitous assumption in these discussions has been that the integration of whole genome sequencing (WGS)1 in health care would consist of a one-time sequencing of the patient’s genome and subsequent storage of the WGS data in the patient’s electronic health record (EHR) [e.g. 8-10]. Those WGS data could then be interpreted and reinterpreted by health care providers over the patient’s lifetime (or collaboratively “managed” by patients and clinicians [11]) as knowledge about the clinical relevance of genomic variants increases. One of the biggest clinical challenges to interpretation of an individual’s genome currently is the uncertain significance of many DNA variants, although this will likely improve over time. This ongoing need for reinterpretation of an individual’s genome has raised additional clinical concerns such as who is responsible for re-contacting patients when and if new information emerges, and how patients can be expected to give informed consent when the potential implications of WGS are unknown currently [12]. With such access to WGS data alongside scientific and technological capabilities for health care providers to mine those WGS data (sometimes for information that exceeds the scope of patient expectations or immediate health concerns), policy discussions have focused on risk management of “the incidentalome” [e.g., 13-14]. Discovering multiple abnormal incidental findings, including the dreaded variants of unknown significance (VUS), could place many undue burdens on clinicians and patients alike. Discussions that center on incorporating all genomic data into the EHR have the effect of medicalizing the genome [see also 16] by assuming all genomic information is relevant for determining medical risk when some portions of the genome have no known medical relevance whatsoever, despite being useful for non-healthcare purposes (such as ancestral or forensic information). Here, in contemplating patient privacy in personalized medicine, we question the medicalization of genomes in a broad sense, not only questioning the restriction of an individual’s access to genomic information by requiring such data to be obtained only through a health care provider, but also questioning the a priori medical relevance of all genomic sequence data. While genomic data can, and do, provide clinically relevant information, the entire genomic sequence will not be relevant or necessary in most contexts. Each locus in the genome has its own evolutionary story and an anthropological (not just medical) genetics perspective is necessary. Some specific loci in the genome may be medically relevant for some individuals, in some contexts, and during some stages of development while irrelevant for other individuals, in other contexts, or during other stages of development. Assessing the medical relevance of genomic data is limited by our present understanding of normal human genomic variation, reporting biases of positive results in the literature, and the under-representation of genomic research involving individuals from racial and ethnic minorities. Thus, the determination of medical relevance of genomic data is appropriately a locus-by-locus, patient-by-patient, visit-by-visit, case-by-case decision. We further question the assumption that WGS data should be incorporated into the EHR without deliberate consideration given to privacy and standard of care problems that may accompany the “hoarding” of genomic data in clinical systems. We emphasize that our suggestion relates to the storage of clinical data as opposed to research data, where storage of the entire genome may indeed be necessary.