Whole Genome Sequencing: A Considered Approach to Clinical Implementation

Division of Genetics, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin.
Current protocols in human genetics / editorial board, Jonathan L. Haines ... [et al.] 04/2013; Chapter 9:Unit9.22. DOI: 10.1002/0471142905.hg0922s77
Source: PubMed


The recent entry of "whole" exome/"whole" genome sequencing into limited clinical practice has led to a progression of the availability of genome-scale testing beyond deletion/duplication copy number arrays. This unit provides a considered approach to the implementation of such testing in routine clinical practice. Specifically, we will highlight the challenges in patient selection and consent, and the technical issues surrounding test interpretation and reporting. The unit will then provide practical solutions that allow for genome-wide sequencing to be implemented in current clinical practice. Curr. Protoc. Hum. Genet. 77:9.22.1-9.22.7. © 2013 by John Wiley & Sons, Inc.

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    • "We did query the subjects about their experience with other packages throughout the evaluations, such that the user perspectives presented in this study are not restricted to the evaluated tools but also informed by exposure to various commercial and open-source platforms. As access to low-cost DNA sequencing grows, it is anticipated that whole genome sequence analysis will become a standard diagnostic tool for many fields [49] [50]. The complexity of genome data and annotations will continue to increase as the technologies mature, making it imperative to develop better interfaces that streamline analyses and improve quality. "
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    ABSTRACT: Objectives: New DNA sequencing technologies have revolutionized the search for genetic disruptions. Targeted sequencing of all protein coding regions of the genome, called exome analysis, is actively used in research-oriented genetics clinics, with the transition to exomes as a standard procedure underway. This transition is challenging; identification of potentially causal mutation(s) amongst ∼10(6) variants requires specialized computation in combination with expert assessment. This study analyzes the usability of user interfaces for clinical exome analysis software. There are two study objectives: (1) To ascertain the key features of successful user interfaces for clinical exome analysis software based on the perspective of expert clinical geneticists, (2) To assess user-system interactions in order to reveal strengths and weaknesses of existing software, inform future design, and accelerate the clinical uptake of exome analysis. Methods: Surveys, interviews, and cognitive task analysis were performed for the assessment of two next-generation exome sequence analysis software packages. The subjects included ten clinical geneticists who interacted with the software packages using the "think aloud" method. Subjects' interactions with the software were recorded in their clinical office within an urban research and teaching hospital. All major user interface events (from the user interactions with the packages) were time-stamped and annotated with coding categories to identify usability issues in order to characterize desired features and deficiencies in the user experience. Results: We detected 193 usability issues, the majority of which concern interface layout and navigation, and the resolution of reports. Our study highlights gaps in specific software features typical within exome analysis. The clinicians perform best when the flow of the system is structured into well-defined yet customizable layers for incorporation within the clinical workflow. The results highlight opportunities to dramatically accelerate clinician analysis and interpretation of patient genomic data. Conclusion: We present the first application of usability methods to evaluate software interfaces in the context of exome analysis. Our results highlight how the study of user responses can lead to identification of usability issues and challenges and reveal software reengineering opportunities for improving clinical next-generation sequencing analysis. While the evaluation focused on two distinctive software tools, the results are general and should inform active and future software development for genome analysis software. As large-scale genome analysis becomes increasingly common in healthcare, it is critical that efficient and effective software interfaces are provided to accelerate clinical adoption of the technology. Implications for improved design of such applications are discussed.
    Journal of Biomedical Informatics 05/2014; 51. DOI:10.1016/j.jbi.2014.05.004 · 2.19 Impact Factor
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    • "Aside from costs, there remain several issues to be addressed as these unbiased genetic technologies are offered more commonly [73]. Discriminating whether an identified abnormality is disease-causing or a benign variant is a major obstacle that has been addressed by the American College of Medical Genetics and Genomics [74]. "
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    ABSTRACT: Growth evaluations are among the most common referrals to pediatric endocrinologists. Although a number of pathologies, both primary endocrine and non-endocrine, can present with short stature, an estimated 80% of evaluations fail to identify a clear etiology, leaving a default designation of idiopathic short stature (ISS). As a group, several features among children with ISS are suggestive of pathophysiology of the GH-IGF-1 axis, including low serum levels of IGF-1 despite normal GH secretion. Candidate gene analysis of rare cases has demonstrated that severe mutations of genes of the GH-IGF-1 axis can present with a profound height phenotype, leading to speculation that a collection of mild mutations or polymorphisms of these genes can explain poor growth in a larger proportion of patients. Recent genome-wide association studies have identified ~180 genomic loci associated with height that together account for approximately 10% of height variation. With only modest representation of the GH-IGF-1 axis, there is little support for the long-held hypothesis that common genetic variants of the hormone pathway provide the molecular mechanism for poor growth in a substantial proportion of individuals. The height-associated common variants are not observed in the anticipated frequency in the shortest individuals, suggesting rare genetic factors with large effect are more plausible in this group. As we advance towards establishing a molecular mechanism for poor growth in a greater percentage of those currently labeled ISS, we highlight two strategies that will likely be offered with increasing frequency: (1) unbiased genetic technologies including array analysis for copy number variation and whole exome/genome sequencing and (2) epigenetic alterations of key genomic loci. Ultimately data from subsets with similar molecular etiologies may emerge that will allow tailored interventions to achieve the best clinical outcome.
    International Journal of Pediatric Endocrinology 11/2013; 2013(1):19. DOI:10.1186/1687-9856-2013-19
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    ABSTRACT: What's already known about this topic? Incidental findings can occur in many areas of diagnostic testing. Incidental findings, including those of uncertain significance, have many complicated aspects or prenatal diagnosis and are not limited to genetic testing. Whereas guidelines for which findings should be reported and how to report them are being developed in the pediatric and adult genetic testing, little to no guidance exists for prenatal diagnosis. What does this study add? We report two opinions on how to address incidental findings on the basis of a debate at the 17th annual conference of the International Society for Prenatal Diagnosis.
    Prenatal Diagnosis 01/2014; 34(1). DOI:10.1002/pd.4275 · 3.27 Impact Factor