Management of Secondary Genomic Findings

International policies guiding the selection, analysis, and clinical management of secondary findings from genomic sequencing: A systematic review

Secondary findings (SFs) from genomic sequencing can have significant impacts on patient health, yet existing practices guiding their clinical investigation are inconsistent. We systematically reviewed existing SFs policies to identify variations and gaps in guidance. We cataloged and appraised international policies from academic databases (n = 5, inception-02/2022) and international human genetic societies (n = 64; inception-05/2022), across the continuum of SFs selection, analysis, and clinical management. We assessed quality using AGREE-II and interpreted results using qualitative description. Of the 63 SFs policies identified, most pertained to clinical management of SFs (98%; n = 62; primarily consent and disclosure), some guided SFs analysis (60%; n = 38), while fewer mentioned SFs selection (48%; n = 30). Overall, policies recommend (1) identifying clinically actionable, pathogenic variants with high positive predictive values for disease (selection), (2) bioinformatically filtering variants using evidence-informed gene lists (analysis), and (3) discussing with affected individuals the SFs identified, their penetrance, expressivity, medical implications, and management (clinical management). Best practices for SFs variant analysis, clinical validation, and follow-up (i.e., surveillance, treatment, etc.) were minimally described. Upon quality assessment, policies were highly rated for scope and clarity (median score, 69) but were limited by their rigor and applicability (median scores, 27 and 25). Our review represents a comprehensive international synthesis of policy guiding SFs across the continuum of selection, analysis, and clinical management. Our synthesis will help providers navigate critical decision points in SFs investigation, although significant work is needed to address gaps in SFs analysis, clinical validation, and follow-up processes and to support evidence-based practice.

Evaluating large language models on medical, lay-language, and self-reported descriptions of genetic conditions

Large language models (LLMs) are generating interest in medical settings. For example, LLMs can respond coherently to medical queries by providing plausible differential diagnoses based on clinical notes. However, there are many questions to explore, such as evaluating differences between open- and closed-source LLMs as well as LLM performance on queries from both medical and non-medical users. In this study, we assessed multiple LLMs, including Llama-2-chat, Vicuna, Medllama2, Bard/Gemini, Claude, ChatGPT3.5, and ChatGPT-4, as well as non-LLM approaches (Google search and Phenomizer) regarding their ability to identify genetic conditions from textbook-like clinician questions and their corresponding layperson translations related to 63 genetic conditions. For open-source LLMs, larger models were more accurate than smaller LLMs: 7b, 13b, and larger than 33b parameter models obtained accuracy ranges from 21%-49%, 41%-51%, and 54%-68%, respectively. Closed-source LLMs outperformed open-source LLMs, with ChatGPT-4 performing best (89%-90%). Three of 11 LLMs and Google search had significant performance gaps between clinician and layperson prompts. We also evaluated how in-context prompting and keyword removal affected open-source LLM performance. Models were provided with 2 types of in-context prompts: list-type prompts, which improved LLM performance, and definition-type prompts, which did not. We further analyzed removal of rare terms from descriptions, which decreased accuracy for 5 of 7 evaluated LLMs. Finally, we observed much lower performance with real individuals' descriptions; LLMs answered these questions with a maximum 21% accuracy.

An integrated approach for improving clinical management of non-obstructive azoospermia

BACKGROUND

Non-obstructive azoospermia is the most severe form of male infertility. A testicular biopsy is required for the diagnosis of non-obstructive azoospermia, and the causal factors for non-obstructive azoospermia remain unknown.

OBJECTIVES

To reduce the risk of multiple biopsies and identify factors that contribute to non-obstructive azoospermia, we proposed an integrated approach for the preoperative diagnosis and clinical management of non-obstructive azoospermia by applying the chromosome-spreading technique and whole-exome sequencing.

MATERIALS AND METHODS

Between July 2020 and December 2022, after ruling out definitive obstructive azoospermia and non-obstructive azoospermia patients with testicular volume < 6 mL, 20 patients with non-obstructive azoospermia who underwent preoperative testicular diagnostic biopsy using testicular sperm aspiration were subjected to retrospective analysis.

RESULTS

Microscopic examination identified four patients with sperm cells, and 16 without sperm cells. Routine pathological analysis classified one patient as normal spermatogenesis, three as hypospermatogenesis, five as maturation arrest, nine as Sertoli cell-only, and two as unable to judge. With chromosome-spreading technology using routine cell suspension samples for microscopic examination, 18 patient diagnoses were validated, and two patients without a definitive diagnosis were supplemented. Detection of the Y chromosome and a well-organized whole-exome sequencing analysis revealed potential genetic factors.

DISCUSSION AND CONCLUSION

The full use of testicular biopsy is beneficial for the diagnosis of azoospermia, as it avoids the risk of multiple biopsies. Moreover, in combination with whole-exome sequencing, clinicians can obtain more information regarding the pathogenesis of non-obstructive azoospermia, which may guide treatment.

Diagnostic findings and yield of investigations for children with developmental regression

Childhood conditions that feature developmental regression are poorly understood. Phenotype-genotype characterization and diagnostic yield data are needed to inform clinical decision-making. The aim of this study was to report the conditions featuring developmental regression and assess diagnostic yields of investigations. A retrospective chart review of children presenting with developmental regression to a tertiary pediatric genetic clinic between 2018 and 2021 was performed. Of 99 children, 30% (n = 30) had intellectual disability (ID), 21% (n = 21) were autistic, 39% (n = 39) were autistic with ID, and 9% (n = 9) did not have ID or autism. Thirty-two percent (n = 32) of children received a new diagnosis, including eight molecular findings not previously reported to feature developmental regression. Of the children investigated, exome sequencing (ES) provided the highest diagnostic yield (51.1%, n = 24/47), highest (63.6%, n = 14/22) for children with ID, 50% for autistic children with ID (n = 6/12) and children without autism or ID (n = 3/6), and 14.3% (n = 1/7) for autistic children without ID. We highlight the conditions that feature developmental regression and report on novel phenotypic expansions. The high diagnostic yield of ES, regardless of autism or ID diagnosis, indicates the presence of developmental regression as an opportunity to identify the cause, including for genetic differences not previously reported to include regression.

Actionability and familial uptake following opportunistic genomic screening in a pediatric cancer cohort

The care for patients with serious conditions is increasingly guided by genomic medicine, and genomic medicine may equally transform care for healthy individual if genomic population screening is implemented. This study examines the medical impact of opportunistic genomic screening (OGS) in a cohort of patients undergoing comprehensive genomic germline DNA testing for childhood cancer, including the impact on their relatives. Medical actionability and uptake after cascade testing in the period following disclosure of OGS results was quantified. A secondary finding was reported to 19/595 (3.2%) probands primarily in genes related to cardiovascular and lipid disorders. After a mean follow up time of 1.6 years (Interquartile range (IQR): 0.57-1.92 yrs.) only 12 (63%) of these variants were found to be medically actionable. Clinical follow up or treatment was planned in 16 relatives, and as in the probands, the prescribed treatment was primarily betablockers or cholesterol lowering therapy. No invasive procedures or implantation of medical devices were performed in probands or relatives, and no reproductive counseling was requested. After an average of 1.6 years of follow-up 2.25 relatives per family with an actionable finding had been tested. This real-world experience of OGS grants new insight into the practical implementation effects and derived health care demands of genotype-first screening. The resulting health care effect and impact on demand for genetic counseling and workup in relatives extends beyond the effect in the probands.

Critical assessment of missense variant effect predictors on disease-relevant variant data

Regular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction. To explore a variety of settings that are relevant for different clinical and research applications, we assess performance within different subsets of the evaluation data and within high-specificity and high-sensitivity regimes. We find strong performance of many predictors across multiple settings. Meta-predictors tend to outperform their constituent individual predictors; however, several individual predictors have performance similar to that of commonly used meta-predictors. The relative performance of predictors differs in high-specificity and high-sensitivity regimes, suggesting that different methods may be best suited to different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors supervised on pathogenicity labels from curated variant databases often learn label imbalances within genes. Overall, we find notable advances over the oldest and most cited missense variant effect predictors and continued improvements among the most recently developed tools, and the CAGI Annotate-All-Missense challenge (also termed the Missense Marathon) will continue to assess state-of-the-art methods as the field progresses. Together, our results help illuminate the current clinical and research utility of missense variant effect predictors and identify potential areas for future development.

Parents and Provider Perspectives on the Return of Genomic Findings for Cleft Families in Africa

BACKGROUND

Inadequate knowledge among health care providers (HCPs) and parents of affected children limits the understanding and utility of secondary genetic findings (SFs) in under-represented populations in genomics research. SFs arise from deep DNA sequencing done for research or diagnostic purposes and may burden patients and their families despite their potential health importance. This study aims to evaluate the perspective of both groups regarding SFs and their choices in the return of results from genetic testing in the context of orofacial clefts.

METHODS

Using an online survey, we evaluated the experiences of 252 HCPs and 197 parents across participating cleft clinics in Ghana and Nigeria toward the return of SFs across several domains.

RESULTS

Only 1.6% of the HCPs felt they had an expert understanding of when and how to incorporate genomic medicine into practice, while 50.0% agreed that all SFs should be returned to patients. About 95.4% of parents were willing to receive all the information from genetic testing (including SFs), while the majority cited physicians as their primary information source (64%).

CONCLUSIONS

Overall, parents and providers were aware that genetic testing could help in the clinical management of diseases. However, they cited a lack of knowledge about genomic medicine, uncertain clinical utility, and lack of available learning resources as barriers. The knowledge gained from this study will assist with developing guidelines and policies to guide providers on the return of SFs in sub-Saharan Africa and across the continent.

Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results

Importance

Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs.

Objective

To identify factors associated with postdisclosure genetics visits in a genomic screening cohort.

Design, Setting, and Participants

This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022.

Exposure

Clinically confirmed P/LP result disclosed by phone or letter.

Main Outcomes and Measures

Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review.

Results

Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]).

Conclusions and Relevance

This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.

Secondary (additional) findings from the 100,000 Genomes Project: Disease manifestation, health care outcomes, and costs of disclosure

PURPOSE

The UK 100,000 Genomes Project offered participants screening for additional findings (AFs) in genes associated with familial hypercholesterolemia (FH) or hereditary cancer syndromes including breast/ovarian cancer (HBOC), Lynch, familial adenomatous polyposis, MYH-associated polyposis, multiple endocrine neoplasia (MEN), and von Hippel-Lindau. Here, we report disclosure processes, manifestation of AF-related disease, outcomes, and costs.

METHODS

An observational study in an area representing one-fifth of England.

RESULTS

Data were collected from 89 adult AF recipients. At disclosure, among 57 recipients of a cancer-predisposition-associated AF and 32 recipients of an FH-associated AF, 35% and 88%, respectively, had personal and/or family history evidence of AF-related disease. During post-disclosure investigations, 4 cancer-AF recipients had evidence of disease, including 1 medullary thyroid cancer. Six women with an HBOC AF, 3 women with a Lynch syndrome AF, and 2 individuals with a MEN AF elected for risk-reducing surgery. New hyperlipidemia diagnoses were made in 6 FH-AF recipients and treatment (re-)initiated for 7 with prior hyperlipidemia. Generating and disclosing AFs in this region cost £1.4m; £8680 per clinically significant AF.

CONCLUSION

Generation and disclosure of AFs identifies individuals with and without personal or familial evidence of disease and prompts appropriate clinical interventions. Results can inform policy toward secondary findings.

Systematic review of the uptake and outcomes from returning secondary findings to adult participants in research genomic testing

The increasing use of genomic sequencing in research means secondary findings (SF) is more frequently detected and becoming a more pressing issue for researchers. This is reflected by the recent publication of multiple guidelines on this issue, calling for researchers to have a plan for managing SF prior to commencing their research. A deeper understanding of participants' experiences and outcomes from receiving SF is needed to ensure that the return of SF is conducted ethically and with adequate support. This review focuses on the uptake and outcomes of receiving actionable SF for research participants. This review included studies from January 2010 to January 2023. Databases searched included Medline, Embase, PsycINFO, and Scopus. Of the 3903 studies identified, 29 were included in the analysis. The uptake of SF ranged between 20% and 97%, and outcomes were categorized into psychological, clinical, lifestyle and behavioral, and family outcomes. The results indicate there is minimal psychological impact from receiving SF. Almost all participants greatly valued receiving SF. These findings highlight considerations for researchers when returning results, including the importance of involving genetic health professionals in consenting, results return process, and ensuring continuity of care by engaging healthcare providers.

The future of commercial genetic testing

PURPOSE OF REVIEW

There are thousands of different clinical genetic tests currently available. Genetic testing and its applications continue to change rapidly for multiple reasons. These reasons include technological advances, accruing evidence about the impact and effects of testing, and many complex financial and regulatory factors.

RECENT FINDINGS

This article considers a number of key issues and axes related to the current and future state of clinical genetic testing, including targeted versus broad testing, simple/Mendelian versus polygenic and multifactorial testing models, genetic testing for individuals with high suspicion of genetic conditions versus ascertainment through population screening, the rise of artificial intelligence in multiple aspects of the genetic testing process, and how developments such as rapid genetic testing and the growing availability of new therapies for genetic conditions may affect the field.

SUMMARY

Genetic testing is expanding and evolving, including into new clinical applications. Developments in the field of genetics will likely result in genetic testing becoming increasingly in the purview of a very broad range of clinicians, including general paediatricians as well as paediatric subspecialists.

Low adenoma burden in unselected patients with a pathogenic APC variant

PURPOSE

Genomic screening can improve clinical outcomes, but presentation of individuals with risk for polyposis identified via genomic screening is unknown. To inform assessment of clinical utility of genomic screening for polyposis risk, clinical presentation of individuals in an unselected health care system cohort with an APC pathogenic or likely pathogenic (P/LP) variant causative of familial adenomatous polyposis are described.

METHODS

Electronic health records of individuals with an APC P/LP variant identified via the MyCode program (MyCode APC+) were reviewed to assess adenoma burden and compare it among individuals with a clinical diagnosis of familial adenomatous polyposis and matched variant-negative controls.

RESULTS

The prevalence of APC P/LP variants in this health care cohort is estimated to be 1 in 2800. Twenty-four MyCode APC+ individuals were identified during the study period. Median age at result disclosure was 53 years. Rate of clinical polyposis was 8%. Two of six participants with a classic region variant and none of those with an attenuated region variant had polyposis. MyCode APC+ participants did not differ from controls in cumulative adenoma count.

CONCLUSION

APC P/LP variant prevalence estimate in the MyCode cohort is higher than prior published prevalence rates. Individuals with APC P/LP variants identified via genomic screening had a low adenoma burden.

Artificial intelligence and the impact on medical genetics

Virtually all areas of biomedicine will be increasingly affected by applications of artificial intelligence (AI). We discuss how AI may affect fields of medical genetics, including both clinicians and laboratorians. In addition to reviewing the anticipated impact, we provide recommendations for ways in which these groups may want to evolve in light of the influence of AI. We also briefly discuss how educational and training programs can play a key role in preparing the future workforce given these anticipated changes.

A model for the return and referral of all clinically significant secondary findings of genomic sequencing

Secondary findings (SFs) identified through genomic sequencing (GS) can offer a wide range of health benefits to patients. Resource and capacity constraints pose a challenge to their clinical management; therefore, clinical workflows are needed to optimise the health benefits of SFs. In this paper, we describe a model we created for the return and referral of all clinically significant SFs, beyond medically actionable results, from GS. As part of a randomised controlled trial evaluating the outcomes and costs of disclosing all clinically significant SFs from GS, we consulted genetics and primary care experts to determine a feasible workflow to manage SFs. Consensus was sought to determine appropriate clinical recommendations for each category of SF and which clinician specialist would provide follow-up care. We developed a communication and referral plan for each category of SFs. This involved referrals to specialised clinics, such as an Adult Genetics clinic, for highly penetrant medically actionable findings. Common and non-urgent SFs, such as pharmacogenomics and carrier status results for non-family planning participants, were directed back to the family physician (FP). SF results and recommendations were communicated directly to participants to respect autonomy and to their FPs to support follow-up of SFs. We describe a model for the return and referral of all clinically significant SFs to facilitate the utility of GS and promote the health benefits of SFs. This may serve as a model for others returning GS results transitioning participants from research to clinical settings.

DiscoVari: A Web-Based Precision Medicine Tool for Predicting Variant Pathogenicity in Cardiomyopathy- and Channelopathy-Associated Genes

BACKGROUND

With genetic testing advancements, the burden of incidentally identified cardiac disease-associated gene variants is rising. These variants may carry a risk of sudden cardiac death, highlighting the need for accurate diagnostic interpretation. We sought to identify pathogenic hotspots in sudden cardiac death-associated genes using amino acid-level signal-to-noise (S:N) analysis and develop a web-based precision medicine tool, DiscoVari, to improve variant evaluation.

METHODS

The minor allele frequency of putatively pathogenic variants was derived from cohort-based cardiomyopathy and channelopathy studies in the literature. We normalized disease-associated minor allele frequencies to rare variants in an ostensibly healthy population (Genome Aggregation Database) to calculate amino acid-level S:N. Amino acids with S:N above the gene-specific threshold were defined as hotspots. DiscoVari was built using JavaScript ES6 and using open-source JavaScript library ReactJS, web development framework Next.js, and JavaScript runtime NodeJS. We validated the ability of DiscoVari to identify pathogenic variants using variants from ClinVar and individuals clinically evaluated at the Duke University Hospitals with cardiac genetic testing.

RESULTS

We developed DiscoVari as an internet-based tool for S:N-based variant hotspots. Upon validation, a higher proportion of ClinVar likely pathogenic/pathogenic variants localized to DiscoVari hotspots (43.1%) than likely benign/benign variants (17.8%; P<0.0001). Further, 75.3% of ClinVar variants reclassified to likely pathogenic/pathogenic were in hotspots, compared with 41.3% of those reclassified as variants of uncertain significance (P<0.0001) and 23.4% of those reclassified as likely benign/benign (P<0.0001). Of the clinical cohort variants, 73.1% of likely pathogenic/pathogenic were in hotspots, compared with 0.0% of likely benign/benign (P<0.01).

CONCLUSIONS

DiscoVari reliably identifies disease-susceptible amino acid residues to evaluate variants by searching amino acid-specific S:N ratios.

Clinical exome-based panel testing for medically actionable secondary findings in a cohort of 383 Italian participants

Background: Next-generation sequencing-based genetic testing represents a great opportunity to identify hereditary predispositions to specific pathological conditions and to promptly implement health surveillance or therapeutic protocols in case of disease. The term secondary finding refers to the active search for causative variants in genes associated with medically actionable conditions.

Methods: We evaluated 59 medically actionable ACMG genes using a targeted in silico analysis of clinical exome sequencing performed in 383 consecutive individuals referred to our Medical Genetics Unit. A three-tier classification system of SFs for assessing their clinical impact and supporting a decision-making process for reporting was established.

Results: We identified SFs with high/moderate evidence of pathogenicity in 7.0% (27/383) of analyzed subjects. Among these, 12/27 (44.4%) were carriers of a high-risk recessive disease allele. The most represented disease domains were cancer predisposition (33.3%), cardiac disorders (16.7%), and familial hypercholesterolemia (12.5%).

Conclusion: Although still debated, ensuring during NGS-based genetic testing an opportunistic screening might be valuable for personal and familial early management and surveillance of medically actionable disorders, the individual’s reproductive choices, and the prevalence assessment of underestimated hereditary genetic diseases.

Scoping review and classification of deep learning in medical genetics

Deep learning (DL) is applied in many biomedical areas. We performed a scoping review on DL in medical genetics. We first assessed 14,002 articles, of which 133 involved DL in medical genetics. DL in medical genetics increased rapidly during the studied period. In medical genetics, DL has largely been applied to small data sets of affected individuals (mean = 95, median = 29) with genetic conditions (71 different genetic conditions were studied; 24 articles studied multiple conditions). A variety of data types have been used in medical genetics, including radiologic (20%), ophthalmologic (14%), microscopy (8%), and text-based data (4%); the most common data type was patient facial photographs (46%). DL authors and research subjects overrepresent certain geographic areas (United States, Asia, and Europe). Convolutional neural networks (89%) were the most common method. Results were compared with human performance in 31% of studies. In total, 51% of articles provided data access; 16% released source code. To further explore DL in genomics, we conducted an additional analysis, the results of which highlight future opportunities for DL in medical genetics. Finally, we expect DL applications to increase in the future. To aid data curation, we evaluated a DL, random forest, and rule-based classifier at categorizing article abstracts.

The ACMG SF v3.0 gene list increases returnable variant detection by 22% when compared with v2.0 in the ClinSeq cohort

PURPOSE

The American College of Medical Genetics and Genomics (ACMG) recommends the return of pathogenic and likely pathogenic (P/LP) secondary findings from exome and genome sequencing. The latest version (ACMG secondary finding [SF] v3.0) includes 14 additional genes. We interrogated the ClinSeq cohort for variants in these genes to determine the additional yield in unselected individuals.

METHODS

Exome data from 1473 individuals (60% White, 34% African American or Black, 6% other) were analyzed. We restricted our analyses to coding variants; +1,+2,-1, and -2 splice site variants; and the pathogenic GAA variant, NM_000152.5:c.-32-13T>G. Variants were assessed with slightly modified ACMG/Association of Molecular Pathology guidelines.

RESULTS

A total of 25 P/LP variants were identified. In total, 7 individuals had P/LP variants in genes recommended for return of heterozygous variants, namely HNF1A (1), PALB2 (3), TMEM127 (1), and TTN (2). In total, 4 individuals had a homozygous variant in a gene recommended for biallelic variant return, namely HFE, NM_000410.3(HFE):c.845G>A p.Cys282Tyr. A total of 17 P/LP variants were identified in the heterozygous state in genes recommended only for biallelic variant reporting and were not returned. The frequency of returnable P/LP variants did not significantly differ by race.

CONCLUSION

Using the ACMG SF v3.0, the returnable P/LP variant frequency increased in the ClinSeq cohort by 22%, from 3.4% (n = 50, ACMG SF v2.0) to 4.1% (n = 61, ACMG SF v3.0).

Genetic Testing for Heritable Cardiovascular Diseases in Pediatric Patients: A Scientific Statement From the American Heart Association

Genetic diseases that affect the cardiovascular system are relatively common and include cardiac channelopathies, cardiomyopathies, aortopathies, hypercholesterolemias, and structural diseases of the heart and great vessels. The rapidly expanding availability of clinical genetic testing leverages decades of research into the genetic origins of these diseases, helping inform diagnosis, clinical management, and prognosis. Although a number of guidelines and statements detail best practices for cardiovascular genetic testing, there is a paucity of pediatric-focused statements addressing the unique challenges in testing in this vulnerable population. In this scientific statement, we seek to coalesce the existing literature around the use of genetic testing for cardiovascular disease in infants, children, and adolescents.

A systematic literature review of disclosure practices and reported outcomes for medically actionable genomic secondary findings

Purpose:

Secondary findings (SF) are present in 1–4% of individuals undergoing genome/exome sequencing. A review of how SF are disclosed and what outcomes result from their receipt is urgent and timely.

Methods:

We conducted a systematic literature review of SF disclosure practices and outcomes after receipt including cascade testing, family and provider communication, and healthcare actions. Of the 1,184 non-duplicate records screened we summarize findings from 27 included research articles describing SF disclosure practices, outcomes after receipt, or both.

Results:

The included articles reported 709 unique SF index recipients/families. Referrals and/or recommendations were provided 647 SF recipients and outcome data were available for 236. At least one recommended evaluation was reported for 146 SF recipients; 16 reports of treatment or prophylactic surgery were identified. We found substantial variations in how the constructs of interest were defined and described.

Conclusion:

Variation in how SF disclosure and outcomes were described limited our ability to compare findings. We conclude the literature provided limited insight into how the ACMG guidelines have been translated into precision health outcomes for SF recipients. Robust studies of SF recipients are needed and should be prioritized for future research.

Interpretation of Incidental Genetic Findings Localizing to Genes Associated With Cardiac Channelopathies and Cardiomyopathies

Recent advances in next-genetic sequencing technology have facilitated an expansion in the use of exome and genome sequencing in the research and clinical settings. While this has aided in the genetic diagnosis of individuals with atypical clinical presentations, there has been a marked increase in the number of incidentally identified variants of uncertain diagnostic significance in genes identified as clinically actionable by the American College of Medical Genetics guidelines. Approximately 20 of these genes are associated with cardiac diseases, which carry a significant risk of sudden cardiac death. While identification of at-risk individuals is paramount, increased discovery of incidental variants of uncertain diagnostic significance has placed a burden on the clinician tasked with determining the diagnostic significance of these findings. Herein, we describe the scope of this emerging problem using cardiovascular genetics to illustrate the challenges associated with variants of uncertain diagnostic significance interpretation. We review the evidence for diagnostic weight of these variants, discuss the role of clinical genetics providers in patient care, and put forward general recommendations about the interpretation of incidentally identified variants found with clinical genetic testing.

The impact of unsolicited findings in clinical exome sequencing, a qualitative interview study

Unsolicited findings (UFs) in clinical exome sequencing are variants that are unrelated to the initial clinical question the DNA test was performed for, but that may nonetheless be of medical relevance to patients and/or their families. There is limited knowledge about the impact of UFs on patients' lives. In order to characterise patient perceptions of the impact of an UF, we conducted 20 semi-structured face-to-face interviews with patients and/or their relatives to whom an UF predisposing to oncological disease (n = 10) or predisposing to a cardiac condition (n = 10) had been disclosed. We have identified a psychological, physical and financial aspect of the perceived impact of UF disclosure in exome sequencing. Actionability, understanding, patients' pre-test health and social context were influencing factors, according to our participants. Although most expressed considerable psychological impact initially, all but one participant would choose to undergo genetic testing again, knowing what they know now. These novel findings provide insight in patients' perspectives on the impact of UF disclosure. Our study highlights the value of incorporating patients' perceptions in UF disclosure policy.

Genetic counseling for patients with positive genomic screening results: Considerations for when the genetic test comes first

Emerging genetic testing delivery models have enabled individuals to receive testing without a medical indication. This article will highlight key considerations for patient care in the setting of adult patients with positive results for monogenic disease identified through genomic screening. Suggestions for how to adapt genetic counseling to a genomic screening population will encompass topics such as phenotyping, risk assessments, and the use of existing guidelines and resources. Case examples will demonstrate principles of genotype-first patient care.

Evaluating the resource implications of different service delivery models for offering additional genomic findings

PURPOSE

To evaluate the resource implications of different delivery models for the provision of additional findings (AF) in genomics from a health-care purchaser perspective.

METHODS

Data from the Additional Findings study were used to develop and validate a discrete event simulation model that represented the pathway of delivering AF. Resource implications were estimated by microcosting the consultations, sample verifications, bioinformatics, curation, and multidisciplinary case review meetings. A proof-of-concept model was used to generate costing, and then the simulation model was varied to assess the impact of an automated analysis pipeline, use of telehealth consultation, full automation with electronic decision support, and prioritizing case review for cases with pathogenic variants.

RESULTS

For the proof-of-concept delivery model, the average total cost to report AF was US$430 per patient irrespective of result pathogenicity (95% confidence interval [CI] US$375-US$489). However, the cost of per AF diagnosis was US$4349 (95% CI US$3794-US$4953). Alternative approaches to genetic counseling (telehealth, decision support materials) and to multidisciplinary case review (pathogenic AF cases only) lowered the total per patient cost of AF analysis and reporting by 41-51%.

CONCLUSION

Resources required to provide AF can be reduced substantially by implementing alternative approaches to counseling and multidisciplinary case review.