A Systematic Literature Review of Individuals\u27 Perspectives on Privacy and Genetic Information in the United States

Concerns about genetic privacy affect individuals\u27 willingness to accept genetic testing in clinical care and to participate in genomics research. To learn what is already known about these views, we conducted a systematic review, which ultimately analyzed 53 studies involving the perspectives of 47,974 participants on real or hypothetical privacy issues related to human genetic data. Bibliographic databases included MEDLINE, Web of Knowledge, and Sociological Abstracts. Three investigators independently screened studies against predetermined criteria and assessed risk of bias. The picture of genetic privacy that emerges from this systematic literature review is complex and riddled with gaps. When asked specifically are you worried about genetic privacy, the general public, patients, and professionals frequently said yes. In many cases, however, that question was posed poorly or only in the most general terms. While many participants expressed concern that genomic and medical information would be revealed to others, respondents frequently seemed to conflate privacy, confidentiality, control, and security. People varied widely in how much control they wanted over the use of data. They were more concerned about use by employers, insurers, and the government than they were about researchers and commercial entities. In addition, people are often willing to give up some privacy to obtain other goods. Importantly, little attention was paid to understanding the factor-sociocultural, relational, and media - that influence people\u27s opinions and decisions. Future investigations should explore in greater depth which concerns about genetic privacy are most salient to people and the social forces and contexts that influence those perceptions. It is also critical to identify the social practices that will make the collection and use of these data more trustworthy for participants as well as to identify the circumstances that lead people to set aside worries and decide to participate in research

Orthod Craniofac Res

Malocclusions affect individuals worldwide, resulting in compromised function and esthetics. Understanding the etiological factors contributing to the variation in dentofacial morphology associated with malocclusions is the key to develop novel treatment approaches. Advances in dentofacial phenotyping, which is the comprehensive characterization of hard and soft tissue variation in the craniofacial complex, together with the acquisition of large-scale genomic data have started to unravel genetic mechanisms underlying facial variation. Knowledge on the genetics of human malocclusion is limited even though results attained thus far are encouraging, with promising opportunities for future research. This review summarizes the most common dentofacial variations associated with malocclusions and reviews the current knowledge of the roles of genes in the development of malocclusions. Lastly, this review will describe ways to advance malocclusion research, following examples from the expanding fields of phenomics and genomic medicine, which aim to better patient outcomes.2 UL1 TR000442-06/TR/NCATS NIH HHS/United StatesCDCR01D000295/PHS HHS/United StatesR01 DD000295/DD/NCBDD CDC HHS/United StatesR90 DE024296/DE/NIDCR NIH HHS/United StatesT32 DE014678/DE/NIDCR NIH HHS/United StatesT32-DEO14678-09/PHS HHS/United StatesT90 DE023520/DE/NIDCR NIH HHS/United StatesUL1 TR000442/TR/NCATS NIH HHS/United States2016-04-01T00:00:00Z25865537PMC441821

Interpretations of the Term “Actionable” when Discussing Genetic Test Results: What you Mean Is Not What I Heard

In genomic medicine, the familiarity and inexactness of the term “actionable” can lead to multiple interpretations and mistaken beliefs about realistic treatment options. As part of a larger study focusing on public attitudes toward policies for the return of secondary genomic results, we looked at how members of the lay public interpret the term “medically actionable” in the context of genetic testing. We also surveyed a convenience sample of oncologists as part of a separate study and asked them to define the term “medically actionable.” After being provided with a definition of the term, 21 out of 60 (35%) layperson respondents wrote an additional action not specified in the provided definition (12 mentioned “cure” and 9 mentioned environment or behavioral change) and 17 (28%) indicated “something can be done” with no action specified. In contrast, 52 surveyed oncologists did not mention environment, behavioral change, or cure. Based on our findings, we propose that rather than using the term “actionable” alone, providers should also say “what they mean” to reduce miscommunication and confusion that could negatively impact medical decision‐making. Lastly, to guide clinicians during patient‐ provider discussion about genetic test results, we provide examples of phrasing to facilitate clearer communication and understanding of the term “actionable.”Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149289/1/jgc41064.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149289/2/jgc41064_am.pd

The nuanced negative: Meanings of a negative diagnostic result in clinical exome sequencing

Genomic sequencing technology is moving rapidly from the research setting into clinical medicine but significant technological and interpretive challenges remain. Whole exome sequencing (WES) in its recent clinical application provides a genetic diagnosis in about 25% of cases (Berg 2014). While this diagnostic yield is substantial, it also indicates that in a majority of cases, patients are receiving negative results (i.e., no explanatory genetic variant found) from this technology. There are a number of uncertainties regarding the meaning of a negative result in the current context of WES. A negative result may be due to current technological limitations that hinder detection of disease-causing variants or to gaps in the knowledge base that prohibit accurate interpretation of their pathogenicity; or it may indicate that there is not a genetic etiology for the disorder. In this paper we examine the uncertainties and nuances of the negative result from genome sequencing and how both clinicians and patients make meaning of it as revealed in ethnographic observations of the clinic session where results are returned, and in interviews with patients. We find that clinicians and patients construct the meaning of a negative result in ways that are uncertain, contingent, and multivalent; but invested with optimism, promise, and potentiality

Master of Science

thesisLack of information is a serious concern for clinicians. Information resources can address this problem, leading to improvements in decision making and patient outcomes. Genomics is an information-rich domain where searching for information can be complex. For example, most physicians agree that pharmacogenomics can be used to improve the quality of care, and there is evidence that many patients harbor actionable pharmacogenomic variation. However, surveys have shown that physicians feel their knowledge of pharmacogenomics to be inadequate. This represents an information need. A natural approach to meet this need is to provide context-aware access to the precise information needed. The Health Level 7 Context-Aware Knowledge Retrieval Standard, a.k.a the Infobutton, offers a modality to deliver context-aware knowledge into electronic health record (EHR) systems. OpenInfobutton is a reference implementation of this standard that offers an open-source instantiation. In this thesis, we aimed to provide insight into pharmacogenomics information needs and an automated mechanism for addressing these needs. Such work can aid the design of tools that support clinical decisions in genomics

Computational analysis of genetic variation

High throughput sequences are generating increasingly detailed catalogues of genetic variation both in human disease and within the larger population. To effectively utilise this rich data set for maximum research benefit, as a discipline we require robust, flexible, and reproducible analysis pipelines capable of accurately detecting and prioritising variants. While data-specific computational algorithms aimed at deriving accurate data from these technologies have reached maturity, two major challenges remain in order to realise the goals of elucidating the underlying genetic causes of disease as a means of developing custom treatment options. The first challenge is the creation of high-throughput variant detection pipelines able to reliably detect sample variation from a variety of sequence data types. Such a system needs to be scalable, flexible, robust, highly automated, and able to support reproducible analyses in order to support both default and custom variant detection workflows. The second challenge is the effective prioritisation of the huge number of variants detected in each sample, a task required to reduce the large search space for causal variants down to variant lists suitable for manual interrogation. This thesis describes six publications describing components of the larger informatics framework I have developed over the last four years to address these challenges, a framework designed from the onset to effectively manage and process large data sets with an end goal of utilising computational analysis of sequence data to further understand the relationship between genetic variation and human disease. The first publication “Reliably detecting clinically important variants requires both combined variant calls and optimized filtering strategies” describes a variant detection strategy designed to minimize false negative variants as is desired when utilising patient variation data in the clinic. The next four publications describe custom workflows developed for detecting variants in sequence data from different sample types, namely paired cancer samples (“Tumour procurement, DNA extraction, coverage analysis and optimisation of mutation-calling algorithms for human melanoma genomes”), pedigrees (“Reducing the search space for causal genetic variants with VASP: Variant Analysis of Sequenced Pedigrees”), mixed cell populations containing ultra-rare mutations (“DeepSNVMiner: A sequence analysis tool to detect emergent, rare mutations in sub-sets of cell populations”) and mouse exome data containing ENU mutations (“Massively parallel sequencing of the mouse exome to accurately identify rare, induced mutations: an immediate source for thousands of new mouse models”) . The last publication, “Comparison of predicted and actual consequences of missense mutations” focuses on the validation of computational tools that predict functional impact of missense mutations and further attempts to explain why many missense mutations predicted to be damaging do not result in an observable phenotype as might be expected. Collectively these publications detail efforts to reliably detect and prioritise variants across a wide variety of data types, efforts all based around the significant underlying software framework I have developed to better elucidate the link between genetic variation and disease

Array comparative genomic hybridisation and the newborn intensive care unit: Sociological perspectives on mainstreaming medical genetics

This thesis presents the findings of a UK-based ethnography of the mainstreaming of array comparative genomic hybridisation in the neonatal intensive care unit. Mainstreaming refers to the strategies employed to embed genetic/genomic technologies for patient benefit, incorporating genome-wide methods in everyday, mundane clinical work, beyond the specialist genetic realm. It draws on observations in the laboratory and the clinic alongside interviews with members of the extended bioclinical collective (Bourett, 2005). This constructs an ethnography of the activity of doing chromosomal microarray (Mol, 2002). I describe how three important traditions in sociological thought – namely (medical) uncertainty, processes of classification and categorisation and expertise – can be applied to the activity of mainstreaming. In the laboratory, I explore the role of standardisation and how despite calls for rigid adherence to technical rules, it is the subversion of standards – through appeals to expertise – that renders the technology workable for the messy clinical context. I continue by describing the dividing practices of the clinic, which designate infants as (potentially) genetically problematic, demonstrating how discourses between professionals and with parents serve to seek the assent of parents for chromosomal microarray testing through a highly directive process. I show how rhetorical discourse devices are using in ‘consent conversations’ as a tool in information sharing and as a means of persuasion. For the parents of infants having aCGH testing, uncertainty around decisions to test and the information genetic testing can generate are woven into personal narratives of restitution, chaos and quest (Frank,1995). I conclude by reflecting upon how the ability and means by which uncertainty is tolerated differs vastly between the laboratory, the clinic and the family and the way in which diverging practices enact ontology in medicine as bound to specific sites and situations (Mol, 2002)

Characterizing genetic variants for clinical action

Genome-wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome-scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop