Creating genetic reports that are understood by nonspecialists: a case study.

PURPOSE: Guidelines recommend that genetic reports should be clear to nonspecialists, including patients. We investigated the feasibility of creating reports for cystic fibrosis carrier testing through a rapid user-centered design process that built on a previously developed generic template. We evaluated the new reports' communication efficacy and effects on comprehension against comparable reports used in current clinical practice. METHODS: Thirty participants took part in three rounds of interviews. Usability problems were identified and rectified in each round. One hundred ninety-three participants took part in an evaluation of the resulting reports measuring subjective comprehension, risk probability comprehension, perceived communication efficacy, and other factors, as compared with standard reports. RESULTS: Participants viewing the user-centered reports rated them as clearer, easier to understand, and more effective at communicating key information than standard reports. Both groups ended up with equivalent knowledge of risk probabilities, although we observed differences in how those probabilities were perceived. CONCLUSION: Our findings demonstrate that by starting with a patient-friendly generic report template and modifying it for specific scenarios with a rapid user-centered design process, reports can be produced that are more effective at communicating key information. The resulting reports are now being implemented into clinical care.

Correction: Creating genetic reports that are understood by nonspecialists: a case study.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Recommendations for designing genetic test reports to be understood by patients and non-specialists.

Patients and non-specialist healthcare professionals are increasingly expected to understand and interpret the results of genetic or genomic testing. These results are currently reported using a variety of templates, containing different amounts, levels, and layouts of information. We set out to establish a set of recommendations for communicating genetic test results to non-expert readers. We employed a qualitative-descriptive study design with user-centred design principles, including a mixture of in-person semi-structured interviews and online questionnaires with patients, healthcare professionals and the general public. The resulting recommendations and example template include providing at-a-glance comprehension of what the test results mean for the patient; suggested next steps; and details of further information and support. Separation and inclusion of technical methodological details enhances non-specialists' understanding, while retaining important information for specialists and the patients' records. The recommendations address the high-level needs of patients and their non-specialist clinicians when receiving genetic test results. These recommendations provide a solid foundation for the major content and structure of reports, and we recommend further engagement with patients and clinicians to tailor reports to specific types of test and results.

Disease Variant Landscape of a Large Multiethnic Population of Moyamoya Patients by Exome Sequencing.

Moyamoya disease (MMD) is a rare disorder characterized by cerebrovascular occlusion and development of hemorrhage-prone collateral vessels. Approximately 10-12% of cases are familial, with a presumed low penetrance autosomal dominant pattern of inheritance. Diagnosis commonly occurs only after clinical presentation. The recent identification of the RNF213 founder mutation (p.R4810K) in the Asian population has made a significant contribution, but the etiology of this disease remains unclear. To further develop the variant landscape of MMD, we performed high-depth whole exome sequencing of 125 unrelated, predominantly nonfamilial, ethnically diverse MMD patients in parallel with 125 internally sequenced, matched controls using the same exome and analysis platform. Three subpopulations were established: Asian, Caucasian, and non-RNF213 founder mutation cases. We provided additional support for the previously observed RNF213 founder mutation (p.R4810K) in Asian cases (P = 6.01×10(-5)) that was enriched among East Asians compared to Southeast Asian and Pacific Islander cases (P = 9.52×10(-4)) and was absent in all Caucasian cases. The most enriched variant in Caucasian (P = 7.93×10(-4)) and non-RNF213 founder mutation (P = 1.51×10(-3)) cases was ZXDC (p.P562L), a gene involved in MHC Class II activation. Collapsing variant methodology ranked OBSCN, a gene involved in myofibrillogenesis, as most enriched in Caucasian (P = 1.07×10(-4)) and non-RNF213 founder mutation cases (P = 5.31×10(-5)). These findings further support the East Asian origins of the RNF213 (p.R4810K) variant and more fully describe the genetic landscape of multiethnic MMD, revealing novel, alternative candidate variants and genes that may be important in MMD etiology and diagnosis.

Achieving high-sensitivity for clinical applications using augmented exome sequencing.

BACKGROUND: Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate for clinical assessment. METHODS: Using sequence data obtained from the NA12878 reference sample and pre-defined lists of medically-relevant protein-coding and noncoding sequences, we compared the breadth and depth of coverage obtained among four commercial exome capture platforms and whole genome sequencing. In addition, we evaluated the performance of an augmented exome strategy, ACE, that extends coverage in medically relevant regions and enhances coverage in areas that are challenging to sequence. Leveraging reference call-sets, we also examined the effects of improved coverage on variant detection sensitivity. RESULTS: We observed coverage shortfalls with each of the conventional exome-capture and whole-genome platforms across several medically interpretable genes. These gaps included areas of the genome required for reporting recently established secondary findings (ACMG) and known disease-associated loci. The augmented exome strategy recovered many of these gaps, resulting in improved coverage in these areas. At clinically-relevant coverage levels (100 % bases covered at ≥20×), ACE improved coverage among genes in the medically interpretable genome (>90 % covered relative to 10-78 % with other platforms), the set of ACMG secondary finding genes (91 % covered relative to 4-75 % with other platforms) and a subset of variants known to be associated with human disease (99 % covered relative to 52-95 % with other platforms). Improved coverage translated into improvements in sensitivity, with ACE variant detection sensitivities (>97.5 % SNVs, >92.5 % InDels) exceeding that observed with conventional whole-exome and whole-genome platforms. CONCLUSIONS: Clinicians should consider analytical performance when making clinical assessments, given that even a few missed variants can lead to reporting false negative results. An augmented exome strategy provides a level of coverage not achievable with other platforms, thus addressing concerns regarding the lack of sensitivity in clinically important regions. In clinical applications where comprehensive coverage of medically interpretable areas of the genome requires higher localized sequencing depth, an augmented exome approach offers both cost and performance advantages over other sequencing-based tests.

Variant priorization and analysis incorporating problematic regions of the genome.

In case-control studies of rare Mendelian disorders and complex diseases, the power to detect variant and gene-level associations of a given effect size is limited by the size of the study sample. Paradoxically, low statistical power may increase the likelihood that a statistically significant finding is also a false positive. The prioritization of variants based on call quality, putative effects on protein function, the predicted degree of deleteriousness, and allele frequency is often used as a mechanism for reducing the occurrence of false positives, while preserving the set of variants most likely to contain true disease associations. We propose that specificity can be further improved by considering errors that are specific to the regions of the genome being sequenced. These problematic regions (PRs) are identified a-priori and are used to down-weight constitutive variants in a case-control analysis. Using samples drawn from 1000-Genomes, we illustrate the utility of PRs in identifying true variant and gene associations using a case-control study on a known Mendelian disease, cystic fibrosis (CF).