Defining the Clinical Value of a Genomic Diagnosis in the Era of Next-Generation Sequencing

Natasha T Strande, Jonathan S Berg, Natasha T Strande, Jonathan S Berg

Abstract

As with all fields of medicine, the first step toward medical management of genetic disorders is obtaining an accurate diagnosis, which often requires testing at the molecular level. Unfortunately, given the large number of genetic conditions without a specific intervention, only rarely does a genetic diagnosis alter patient management-which raises the question, what is the added value of obtaining a molecular diagnosis? Given the fast-paced advancement of genomic technologies, this is an important question to address in the context of genome-scale testing. Here, we address the value of establishing a diagnosis using genome-scale testing and highlight the benefits and drawbacks of such testing. We also review and compare recent major studies implementing genome-scale sequencing methods to identify a molecular diagnosis in cohorts manifesting a broad range of Mendelian monogenic disorders. Finally, we discuss potential future applications of genomic sequencing, such as screening for rare conditions.

Keywords: clinical diagnostics; genomic medicine; monogenic disorders; next-generation sequencing; whole-exome sequencing; whole-genome sequencing.

Figures

Figure 1:
Figure 1:
Factors that influence the diagnostic yield of multigene testing. (a) Characteristics of the cohort being tested that influence the yield of diagnostic testing include demographic information, the conditions included in the cohort, the likelihood that the individuals being tested have a genetic disease, and any prior diagnostic testing. (b) The diagnostic yield varies depending on the amount of information provided by the sequencing strategy, which may be proband only, trio whole-exome sequencing (WES), extended family WES, or candidate variant follow-up with Sanger sequencing. (c) Aspects of the sequencing approach and data analysis that influence yield include the DNA capture method for exome sequencing, sequencing platform, alignment software, and prioritization of variants (gene lists derived from a general phenotype as opposed to patient-specific phenotypic information).
Figure 2:
Figure 2:
Variant-and case-level interpretation. (a) Variant-level interpretation is influenced by multiple criteria that determine the pathogenicity of the variant. The color bar depicts the subjectivity involved in assigning a level of pathogenicity to variants, particularly with regard to the boundaries of the variant of uncertain significance category. The dashed lines and arrows represent the different thresholds that may be used by various groups to assign pathogenicity assertions. (b) Case-level interpretation incorporates both the pathogenicity of the variant(s) and how well the variant or combination of variants matches the patient’s phenotype. Whether results are returned to a patient depends on the inheritance pattern of the condition of interest. The dashed lines and arrows indicate subjectivity regarding the boundaries of these categories among different groups. The asterisk indicates that next-generation sequencing may not be able to identify whether two variants identified in a given gene are in cis or in trans. When the phase is unknown, the case-level result may be reported as an uncertain result until compound heterozygosity can be confirmed. Abbreviations: AD, autosomal dominant; AR, autosomal recessive; B, benign; IF, incidental finding; LB, likely benign; LP, likely pathogenic; MAF, minor allele frequency; NR, not reported; P, pathogenic; VUS, variant of uncertain significance.

Source: PubMed

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