In clinical exome and genome sequencing, there is potential for the recognition and reporting of incidental or secondary findings unrelated to the indication for ordering the sequencing but of medical value for patient care. The American College of Medical Genetics and Genomics (ACMG) recently published a policy statement on clinical sequencing, which emphasized the importance of disclosing the possibility of such results in pretest patient discussions, clinical testing, and reporting of results. The ACMG appointed a Working Group on Incidental Findings in Clinical Exome and Genome Sequencing to make recommendations about responsible management of incidental findings when patients undergo exome or genome sequencing. This Working Group conducted a year-long consensus process, including review by outside experts, and produced recommendations that have been approved by the ACMG Board. Specific and detailed recommendations, and the background and rationale for these recommendations, are described herein. We recommend that laboratories performing clinical sequencing seek and report mutations of the specified classes or types in the genes listed here. This evaluation and reporting should be performed for all clinical germline (constitutional) exome and genome sequencing, including the ‘normal’ of tumor-normal subtractive analyses in all subjects, irrespective of age, but excluding fetal samples. We recognize that there are insufficient data on clinical utility to fully support these recommendations and we encourage the creation of an ongoing process for updating these recommendations at least annually as further data are collected.

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To assess public attitudes and interest in pharmacogenetic (PGx) testing, we conducted a random-digit-dial telephone survey of U.S. adults, achieving a response rate of 42% (n=1139). Most respondents expressed interest in PGx testing to predict mild or serious side effects (73% ±3.29% and 85% ±2.91%, respectively), guide dosing (91%) and assist with drug selection (92%). Younger individuals (ages 18–34) were more likely to be interested in PGx testing to predict serious side effects (vs. ages 55+), as well as Whites, those with a college degree, and who had experienced side effects from medications. However, most respondents (78% ±3.14%) were not likely to have a PGx test if there was a risk that their DNA sample or test result could be shared without their permission. Given differences in interest among some groups, providers should clearly discuss the purpose of testing, alternative testing options (if available), and policies to protect patient privacy and confidentiality.

With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship, and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semi-quantitative measurement for the strength of evidence of a gene-disease relationship which correlates to a qualitative classification: “Definitive”, “Strong”, “Moderate”, “Limited”, “No Reported Evidence” or “Conflicting Evidence.” Within the ClinGen structure, classifications derived using this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings.

BACKGROUND: Genomic risk profiling involves the analysis of genetic variations linked through statistical associations to a range of disease states. There is considerable controversy as to how, and even whether, to incorporate these tests into routine medical care. OBJECTIVE: To assess physician attitudes and uptake of genomic risk profiling among an 'early adopter' practice group. DESIGN: We surveyed members of MDVIP, a national group of primary care physicians (PCPs), currently offering genomic risk profiling as part of their practice. POPULATION: All physicians in the MDVIP network (N =356) RESULTS: We obtained a 44% response rate. One third of respondents had ordered a test for themselves and 42% for a patient. The odds of having ordered personal testing were 10.51-fold higher for those who felt well-informed about genomic risk testing (p < 0.0001). Of those who had not ordered a test for themselves, 60% expressed concerns for patients regarding discrimination by life and longterm/disability insurers, 61% about test cost, and 62% about clinical utility. The odds of ordering testing for their patients was 8.29-fold higher among respondents who had ordered testing for themselves (p < 0.0001). Of those who had ordered testing for patients, concerns about insurance coverage (p = 0.014) and uncertain clinical utility (p = 0.034) were associated with a lower relative frequency of intention to order testing again in the future. CONCLUSIONS: Our findings demonstrate that respondent familiarity was a key predictor of physician ordering behavior and clinical utility was a primary concern for genomic risk profiling. Educational and interpretive support may enhance uptake of genomic risk profiling.

Purpose As genome-scale sequencing is increasingly applied in clinical scenarios, a wide variety of genomic findings will be discovered as secondary or incidental findings, and there is debate about how they should be handled. The clinical actionability of such findings varies, thus necessitating standardized frameworks for a priori decision-making about their analysis. Methods We established a semi-quantitative metric to assess five elements of actionability: severity and likelihood of the disease outcome, efficacy and burden of intervention, and knowledge base, with a total score from 0–15. Results The semi-quantitative metric was applied to a list of putative actionable conditions, the list of genes recommended by the American College of Medical Genetics (ACMG) for return when deleterious variants are discovered as secondary/incidental findings, and a random sample of 1000 genes. Scores from the list of putative actionable conditions (median = 12) and the ACMG list (median = 11) were both statistically different than the randomly selected genes (median = 7) (two-tailed Mann-Whitney test P<0.0001). Conclusion Gene-disease pairs having a score of 11 or higher represent the top quintile of actionability. The semi-quantitative metric effectively assesses clinical actionability, promotes transparency, and may facilitate assessments of clinical actionability by various groups and in diverse contexts.

PurposeGenome and exome sequencing can identify variants unrelated to the primary goal of sequencing. Detecting pathogenic variants associated with an increased risk of a medical disorder allows the possibility of clinical interventions to improve future health outcomes in patients and their at-risk relatives. The Clinical Genome Resource, or ClinGen, aims to assess clinical actionability of genes and associated disorders as part of a larger effort to build a central resource on the clinical relevance of genomic variation for use in precision medicine and research.MethodsWe developed a practical, standardized protocol to identify available evidence and generate qualitative summary reports of actionability for disorders and associated genes. We applied a semi-quantitative metric to score actionability.ResultsWe generated summary reports and actionability scores for the 56 genes and associated disorders recommended by the American College of Medical Genetics and Genomics for return as secondary findings from clinical genome-scale sequencing. We also describe the challenges that arose during the development of the protocol which highlight important issues in characterizing actionability across a range of disorders.ConclusionThe ClinGen framework for actionability assessment will assist research and clinical communities in making clear, efficient, and consistent determinations of actionability based on transparent criteria to guide analysis and reporting of findings from clinical genome-scale sequencing.

Objective-To assess the performance of a standardized age-based metric for scoring clinical actionability to evaluate conditions for inclusion in newborn screening (NBS), and compare it with the results from other contemporary methods. Study design-The North Carolina Newborn Exome Sequencing for Universal Screening (NC NEXUS) study developed an age-based, semi-quantitative metric (ASQM) to assess the clinical actionability of gene-disease pairs and classify them with respect to age of onset or timing of interventions. This categorization was compared with the gold standard Recommended Uniform Screening Panel (RUSP) and other methods to evaluate gene-disease pairs for newborn genomic sequencing. Results-We assessed 822 gene-disease pairs, enriched for pediatric onset of disease and suspected actionability. Of these, 466 were classified as having childhood onset and high actionability, analogous to conditions selected for the RUSP core panel. Another 245 were classified as having childhood onset and low to no actionability, 25 were classified as having adult onset and high actionability, 19 were classified as having adult onset and low to no actionability, and 67 were excluded due to controversial evidence and/or prenatal onset.