Jessica Mozersky

Variants of uncertain significance in BRCA: a harbinger of ethical and policy issues to come?

After two decades of genetic testing and research, the BRCA1 and BRCA2 genes are two of the most well-characterized genes in the human genome. As a result, variants of uncertain significance (VUS; also called variants of unknown significance) are reported less frequently than for genes that have been less thoroughly studied. However, VUS continue to be uncovered, even for BRCA1/2. The increasing use of multi-gene panels and whole-genome and whole-exome sequencing will lead to higher rates of VUS detection because more genes are being tested, and most genomic loci have been far less intensively characterized than BRCA1/2. In this article, we draw attention to ethical and policy-related issues that will emerge. Experience garnered from BRCA1/2 testing is a useful introduction to the challenges of detecting VUS in other genetic testing contexts, while features unique to BRCA1/2 suggest key differences between the BRCA experience and the current challenges of multi-gene panels in clinical care. We propose lines of research and policy development, emphasizing the importance of pooling data into a centralized open-access database for the storage of gene variants to improve VUS interpretation. In addition, establishing ethical norms and regulated practices for sharing and curating data, analytical algorithms, interpretive frameworks and patient re-contact are important policy areas.

Cell-free fetal DNA testing: who is driving implementation?

The introduction of noninvasive cell-free fetal DNA (cffDNA) testing to detect fetal Down syndrome, and several other aneuploidy syndromes, signals a major shift in prenatal screening and diagnostic practice. Its arrival comes 15 years after Lo and colleagues reported the presence of circulating fetal DNA in maternal plasma. It has received much attention, both expectant and cautionary. The cffDNA testing enables prospective parents to obtain information about common survivable fetal aneuploidies with a high level of accuracy and without the risk of a diagnostic procedure. In comparison with other methods of aneuploidy screening, cffDNA testing offers several advantages. It usually involves testing of a single blood sample that may be obtained as early as 10 weeks of gestation and does not require ultrasound data. The cffDNA testing has higher sensitivity and a lower falsepositive rate as compared with other screening methods and is therefore likely to result in less anxiety and fewer invasive tests. Eventual adoption of cffDNA testing as the primary method for aneuploidy screening could greatly streamline the process and result in important benefits to women. Noninvasive testing for fetal aneuploidy is commercially lucrative, potentially worth up to one billion USD/year.1 This has fueled a competitive rush to bring this testing to market. In the past 12 months, three companies have launched cffDNA testing in the United States, and a fourth plans to do so later this year. Sequenom was the first company to market the test, and its MaterniT21 test (Sequenom Center for Molecular Medicine, San Diego, CA) (renamed MaterniT21 PLUS when trisomies 18 and 13 were added) was the only one available between October 2011 and March 2012. In March 2012, Verinata (Verinata Health, Red Wood City, CA) launched the Verifi test, followed by Ariosa’s Harmony test (Ariosa Diagnostics, San Jose, CA) in May 2012. All three companies are embroiled in legal battles over patent infringement, prompting concerns that if one company gains a monopoly on testing, it could dictate cost and potentially limit access.1 Despite the fact that organizations such as the American Congress of Obstetricians and Gynecologists and the American College of Medical Genetics and Genomics have not issued practice guidelines, some clinicians have begun to selectively offer cffDNA testing as a part of the screening process. Without this guidance, the rapid introduction of cffDNA testing from several competing companies has created practical challenges for clinicians and patients, which are described in this article. First, how should providers and patients choose from among the available cffDNA tests? All three companies have published validation studies in peer-reviewed journals that coincided with the commercial launch of their tests.2–4 Although there are differences in study design and laboratory methods, each reports similarly high sensitivities and low false-positive rates. These studies were conducted on samples from patients undergoing invasive prenatal diagnosis. In two studies, entry was based on specific high-risk criteria, whereas a third involved patients having invasive prenatal diagnosis for “any indication.” The sample size in each publication, particularly of aneuploid pregnancies, has been progressively smaller, perhaps due to commercial pressure to rapidly bring the test to market. Performance characteristics of cffDNA testing in clinical practice have not been reported thus far; unfortunately, there is no systematic followup being sought by the laboratories offering the test. Should the provider’s confidence in a particular test and selection for clinical use be based solely on critical review of these studies? Second, what importance should differences in reporting method play in selecting a test? Clinicians need to be mindful that interpretation of the test is based on quantitative analysis of DNA fragments. Although discrimination between affected and euploid fetuses is excellent, each laboratory has established its own “cutoffs” that will necessarily be associated with falsepositive and false-negative results. These different cutoffs make comparison of the performance of each laboratory test difficult. Sequenom reports dichotomous results, i.e., either positive or negative, on the basis of a z-score cutoff of 3. Ariosa uses a priori risk based on maternal age, provides a risk estimate that ranges from <1/10,000 to a >99% chance that the fetus is affected, and arbitrarily defines a positive cutoff as 1% risk. Verinata’s interpretations are reported as aneuploidy detected or not, except for those results with a “normalized chromosome value” >2.5 but <4. These are reported as “equivocal for the determination of aneuploidy,” which results in 100% sensitivity but at the expense of more results being unclassifiable. A specific risk estimate or clinical guidance for this category is not provided. The frequency of aneuploidies among the small number of patients in each group with unclassified results would justify offering an invasive diagnostic test (1/7, 2/5, and 2/2 for trisomies 21, 18, and 13, respectively). These reporting differences could be relevant for patient care because some clinicians or patients may prefer to receive positive/negative results rather than a Cell-free fetal DNA testing: who is driving implementation?

Who’s to blame? Accounts of genetic responsibility and blame among Ashkenazi Jewish women at risk of BRCA breast cancer

Genetic knowledge of disease risk may induce a sense of genetic responsibility whereby those who are at risk feel an obligation to take certain actions not only in relation to their own personal health but also to their family, their children and many other aspects of their life. This article examines genetic responsibility among Ashkenazi Jewish women at increased risk of BRCA genetic breast cancer. It demonstrates the ways in which accounts of blame help to mitigate or allocate genetic responsibility and in particular focuses on the temporal nature of womens accounts. Women locate responsibility or blame for genetic disease in the collective reproductive history of Ashkenazi Jews, currently among specific groups of Ashkenazi Jews, and this knowledge can have potential future reproductive consequences. A contradiction may arise between a pre-existing sense of responsibility to produce future generations of Jews with that of producing future breast cancer free children. The research is based on in-depth qualitative interviews with 14 high-risk Ashkenazi Jewish women in London, England.

Comprehension of an Elevated Amyloid Positron Emission Tomography Biomarker Result by Cognitively Normal Older Adults

Importance The goal of Alzheimer disease (AD) prevention together with advances in understanding the pathophysiology of AD have led to clinical trials testing drugs in cognitively unimpaired persons who show evidence of AD biomarkers. Data are needed to inform the processes of describing AD biomarkers to cognitively normal adults and assessing their understanding of this knowledge. Objective To determine the comprehension of an elevated amyloid positron emission tomographic (PET) biomarker result by cognitively unimpaired adults. Design, Setting, and Participants The Study of Knowledge and Reactions to Amyloid Testing, a substudy of an AD prevention trial, involved 2 semistructured telephone interviews with 80 participants recruited from 9 study sites: 50 received elevated and 30 received not elevated amyloid PET scan results. Interviews were conducted 4 to 12 weeks after result disclosure and again 1 year later. Data presented here were collected from November 5, 2014, through December 10, 2015. The 50 participants included in this study were cognitively normal, aged 65 to 85 years, evenly distributed by gender, and had elevated amyloid PET results. Subsequent reports will examine persons with “not elevated” results and compare the influence of the different results. Main Outcomes and Measures Participant comprehension of an elevated amyloid result was assessed by analyzing their responses to the following questions: “What was the result of your amyloid PET scan?” (followed by “Can you tell me in your own words what that means?” or “How would you explain it to a friend?”), “Was it the result you expected?” and “Did the result teach you anything or clarify anything for you?” Results Of the 50 participants aged 65 to 85 years, 49 (98%) were white, 40 (80%) reported a family history of AD, and 30 (60%) had a postgraduate educational level. Most participants (31 [62%]) understood that elevated amyloid conferred an increased but uncertain risk of developing AD. Some desired understanding of the term elevated other than its being a categorical result enabling trial entry eligibility; they wanted information regarding how elevated their amyloid was, how close to the study threshold they were, or percentages, numbers, or a scale to help them make sense of the result. Conclusions and Relevance Including an explanation of how and why a dimensional biomarker is converted to a categorical classification would enhance future AD biomarker clinical trials and educational materials.

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

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.