Digital health-enabled genomics: Opportunities and challenges.

Digital health solutions, with apps, virtual care, and electronic medical records, are gaining momentum across all medical disciplines, and their adoption has been accelerated, in part, by the COVID-19 pandemic. Personal wearables, sensors, and mobile technologies are increasingly being used to identify health risks and assist in diagnosis, treatment, and monitoring of health and disease. Genomics is a vanguard of digital healthcare as we witness a convergence of the fields of genomic and digital medicine. Spurred by the acute need to increase health literacy, empower patients' preference-sensitive decisions, or integrate vast amounts of complex genomic data into the clinical workflow, there has been an emergence of digital support tools in genomics-enabled care. We present three use cases that demonstrate the application of these converging technologies: digital genomics decision support tools, conversational chatbots to scale the genetic counseling process, and the digital delivery of comprehensive genetic services. These digital solutions are important to facilitate patient-centered care delivery, improve patient outcomes, and increase healthcare efficiencies in genomic medicine. Yet the development of these innovative digital genomic technologies also reveals strategic challenges that need to be addressed before genomic digital health can be broadly adopted. Alongside key evidentiary gaps in clinical and cost-effectiveness, there is a paucity of clinical guidelines, policy, and regulatory frameworks that incorporate digital health. We propose a research agenda, guided by learning healthcare systems, to realize the vision of digital health-enabled genomics to ensure its sustainable and equitable deployment in clinical care.

A Randomized Trial of Two Remote Health Care Delivery Models on the Uptake of Genetic Testing and Impact on Patient-Reported Psychological Outcomes in Families With Pancreatic Cancer: The Genetic Education, Risk Assessment, and Testing (GENERATE) Study.

BACKGROUND & AIMS: Genetic testing uptake for cancer susceptibility in family members of patients with cancer is suboptimal. Among relatives of patients with pancreatic ductal adenocarcinoma (PDAC), The GENetic Education, Risk Assessment, and TEsting (GENERATE) study evaluated 2 online genetic education/testing delivery models and their impact on patient-reported psychological outcomes. METHODS: Eligible participants had ≥1 first-degree relative with PDAC, or ≥1 first-/second-degree relative with PDAC with a known pathogenic germline variant in 1 of 13 PDAC predisposition genes. Participants were randomized by family, between May 8, 2019, and June 1, 2021. Arm 1 participants underwent a remote interactive telemedicine session and online genetic education. Arm 2 participants were offered online genetic education only. All participants were offered germline testing. The primary outcome was genetic testing uptake, compared by permutation tests and mixed-effects logistic regression models. We hypothesized that Arm 1 participants would have a higher genetic testing uptake than Arm 2. Validated surveys were administered to assess patient-reported anxiety, depression, and cancer worry at baseline and 3 months postintervention. RESULTS: A total of 424 families were randomized, including 601 participants (n = 296 Arm 1; n = 305 Arm 2), 90% of whom completed genetic testing (Arm 1 [87%]; Arm 2 [93%], P = .014). Arm 1 participants were significantly less likely to complete genetic testing compared with Arm 2 participants (adjusted ratio [Arm1/Arm2] 0.90, 95% confidence interval 0.78-0.98). Among participants who completed patient-reported psychological outcomes questionnaires (Arm 1 [n = 194]; Arm 2 [n = 206]), the intervention did not affect mean anxiety, depression, or cancer worry scores. CONCLUSIONS: Remote genetic education and testing can be a successful and complementary option for delivering genetics care. (Clinicaltrials.gov, number NCT03762590).

Model-driven mitigation measures for reopening schools during the COVID-19 pandemic.

Reopening schools is an urgent priority as the COVID-19 pandemic drags on. To explore the risks associated with returning to in-person learning and the value of mitigation measures, we developed stochastic, network-based models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in primary and secondary schools. We find that a number of mitigation measures, alone or in concert, may reduce risk to acceptable levels. Student cohorting, in which students are divided into two separate populations that attend in-person classes on alternating schedules, can reduce both the likelihood and the size of outbreaks. Proactive testing of teachers and staff can help catch introductions early, before they spread widely through the school. In secondary schools, where the students are more susceptible to infection and have different patterns of social interaction, control is more difficult. Especially in these settings, planners should also consider testing students once or twice weekly. Vaccinating teachers and staff protects these individuals and may have a protective effect on students as well. Other mitigations, including mask wearing, social distancing, and increased ventilation, remain a crucial component of any reopening plan.

The epithelial-mesenchymal transition generates cells with properties of stem cells.

The epithelial-mesenchymal transition (EMT) is a key developmental program that is often activated during cancer invasion and metastasis. We here report that the induction of an EMT in immortalized human mammary epithelial cells (HMLEs) results in the acquisition of mesenchymal traits and in the expression of stem-cell markers. Furthermore, we show that those cells have an increased ability to form mammospheres, a property associated with mammary epithelial stem cells. Independent of this, stem cell-like cells isolated from HMLE cultures form mammospheres and express markers similar to those of HMLEs that have undergone an EMT. Moreover, stem-like cells isolated either from mouse or human mammary glands or mammary carcinomas express EMT markers. Finally, transformed human mammary epithelial cells that have undergone an EMT form mammospheres, soft agar colonies, and tumors more efficiently. These findings illustrate a direct link between the EMT and the gain of epithelial stem cell properties.

Association of Genetic Variation With Cirrhosis: A Multi-Trait Genome-Wide Association and Gene-Environment Interaction Study.

BACKGROUND & AIMS: In contrast to most other common diseases, few genetic variants have been identified that impact risk of cirrhosis. We aimed to identify new genetic variants that predispose to cirrhosis, to test whether such variants, aggregated into a polygenic score, enable genomic risk stratification, and to test whether alcohol intake or body mass index interacts with polygenic predisposition. METHODS: We conducted a multi-trait genome-wide association study combining cirrhosis and alanine aminotransferase levels performed in 5 discovery studies (UK Biobank, Vanderbilt BioVU, Atherosclerosis Risk in Communities study, and 2 case-control studies including 4829 individuals with cirrhosis and 72,705 controls and 362,539 individuals with alanine aminotransferase levels). Identified variants were replicated in 3 studies (Partners HealthCare Biobank, FinnGen, and Biobank Japan including 3554 individuals with cirrhosis and 343,826 controls). A polygenic score was tested in Partners HealthCare Biobank. RESULTS: Five previously reported and 7 newly identified genetic variants were associated with cirrhosis in both the discovery studies multi-trait genome-wide association study (P < 5 × 10-8) and the replication studies (P < .05), including a missense variant in the APOE gene and a noncoding variant near EFN1A. These 12 variants were used to generate a polygenic score. Among Partners HealthCare Biobank individuals, high polygenic score-defined as the top quintile of the distribution-was associated with significantly increased risk of cirrhosis (odds ratio, 2.26; P < .001) and related comorbidities compared with the lowest quintile. Risk was even more pronounced among those with extreme polygenic risk (top 1% of the distribution, odds ratio, 3.16; P < .001). The impact of extreme polygenic risk was substantially more pronounced in those with elevated alcohol consumption or body mass index. Modeled as risk by age 75 years, probability of cirrhosis with extreme polygenic risk was 13.7%, 20.1%, and 48.2% among individuals with no or modest, moderate, and increased alcohol consumption, respectively (Pinteraction < .001). Similarly, probability among those with extreme polygenic risk was 6.5%, 10.3%, and 19.5% among individuals with normal weight, overweight, and obesity, respectively (Pinteraction < .001). CONCLUSIONS: Twelve independent genetic variants, 7 of which are newly identified in this study, conferred risk for cirrhosis. Aggregated into a polygenic score, these variants identified a subset of the population at substantially increased risk who are most susceptible to the hepatotoxic effects of excess alcohol consumption or obesity.

Vision, Driving Exposure, and Collisions in Bioptic Drivers.

SIGNIFICANCE: Lack of knowledge regarding the mileage driven by drivers with low vision who use bioptic telescopes could obscure the relationship between vision and road safety. This study provides data suggesting that worse vision is correlated with less mileage driven but more collisions per mile in bioptic drivers. PURPOSE: The purpose of this study was to determine whether vision or demographic factors predict mileage driven in bioptic drivers and per-mile motor vehicle collision rate and also to compare the collision rate of bioptic drivers with previous estimates for the general population. METHODS: Driver data were collected retrospectively from clinic records. Collision data were collected from the Ohio Bureau of Motor Vehicles database. Subjects were also asked to estimate their yearly mileage. Regression models were used to investigate relationships between vision and collision rates. RESULTS: Seventy-three licensed Ohio bioptic drivers (36 male) were included. Mean ± standard deviation age was 51 ± 16 years. Mean logMAR visual acuity was 0.67 (approximately 20/100). Mean log contrast sensitivity was 1.57. Mean reported annual mileage was 9746. Age, sex, and previous (nonbioptic) driving experience were not associated with mileage. LogMAR visual acuity was inversely related to mileage (P = .02), and contrast sensitivity (P = .01) and horizontal visual field (P = .02) were directly associated with mileage. Visual acuity (P = .02) and visual field (P = .005), but not contrast sensitivity (P = .19), were associated with number of collisions. CONCLUSIONS: Visual acuity, visual field, and contrast sensitivity were associated with driving exposure in bioptic drivers (with drivers with poorer vision reporting lower annual mileage), and poorer visual acuity and visual field were associated with more collisions. The per-mile collision rate for bioptic drivers was within the range of that previously reported for fully sighted drivers, although higher than would be expected for fully sighted drivers of similar age distribution.

Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells.

Despite major advances in understanding the molecular and genetic basis of cancer, metastasis remains the cause of >90% of cancer-related mortality. Understanding metastasis initiation and progression is critical to developing new therapeutic strategies to treat and prevent metastatic disease. Prevailing theories hypothesize that metastases are seeded by rare tumour cells with unique properties, which may function like stem cells in their ability to initiate and propagate metastatic tumours. However, the identity of metastasis-initiating cells in human breast cancer remains elusive, and whether metastases are hierarchically organized is unknown. Here we show at the single-cell level that early stage metastatic cells possess a distinct stem-like gene expression signature. To identify and isolate metastatic cells from patient-derived xenograft models of human breast cancer, we developed a highly sensitive fluorescence-activated cell sorting (FACS)-based assay, which allowed us to enumerate metastatic cells in mouse peripheral tissues. We compared gene signatures in metastatic cells from tissues with low versus high metastatic burden. Metastatic cells from low-burden tissues were distinct owing to their increased expression of stem cell, epithelial-to-mesenchymal transition, pro-survival, and dormancy-associated genes. By contrast, metastatic cells from high-burden tissues were similar to primary tumour cells, which were more heterogeneous and expressed higher levels of luminal differentiation genes. Transplantation of stem-like metastatic cells from low-burden tissues showed that they have considerable tumour-initiating capacity, and can differentiate to produce luminal-like cancer cells. Progression to high metastatic burden was associated with increased proliferation and MYC expression, which could be attenuated by treatment with cyclin-dependent kinase (CDK) inhibitors. These findings support a hierarchical model for metastasis, in which metastases are initiated by stem-like cells that proliferate and differentiate to produce advanced metastatic disease.

LEAP: Using machine learning to support variant classification in a clinical setting.

Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical significance can be limited or conflicting. Here, we present Learning from Evidence to Assess Pathogenicity (LEAP), a machine learning model that utilizes a variety of feature categories to classify variants, and achieves high performance in multiple genes and different health conditions. Feature categories include functional predictions, splice predictions, population frequencies, conservation scores, protein domain data, and clinical observation data such as personal and family history and covariant information. L2-regularized logistic regression and random forest classification models were trained on missense variants detected and classified during the course of routine clinical testing at Color Genomics (14,226 variants from 24 cancer-related genes and 5,398 variants from 30 cardiovascular-related genes). Using 10-fold cross-validated predictions, the logistic regression model achieved an area under the receiver operating characteristic curve (AUROC) of 97.8% (cancer) and 98.8% (cardiovascular), while the random forest model achieved 98.3% (cancer) and 98.6% (cardiovascular). We demonstrate generalizability to different genes by validating predictions on genes withheld from training (96.8% AUROC). High accuracy and broad applicability make LEAP effective in the clinical setting as a high-throughput quality control layer.

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

BACKGROUND: Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable. However, a small subset of difficult-to-call variants that still do require orthogonal confirmation exist. For this reason, many clinical laboratories confirm NGS results using orthogonal technologies such as Sanger sequencing. Here, we report the development of a deterministic machine-learning-based model to differentiate between these two types of variant calls: those that do not require confirmation using an orthogonal technology (high confidence), and those that require additional quality testing (low confidence). This approach allows reliable NGS-based calling in a clinical setting by identifying the few important variant calls that require orthogonal confirmation. RESULTS: We developed and tested the model using a set of 7179 variants identified by a targeted NGS panel and re-tested by Sanger sequencing. The model incorporated several signals of sequence characteristics and call quality to determine if a variant was identified at high or low confidence. The model was tuned to eliminate false positives, defined as variants that were called by NGS but not confirmed by Sanger sequencing. The model achieved very high accuracy: 99.4% (95% confidence interval: +/- 0.03%). It categorized 92.2% (6622/7179) of the variants as high confidence, and 100% of these were confirmed to be present by Sanger sequencing. Among the variants that were categorized as low confidence, defined as NGS calls of low quality that are likely to be artifacts, 92.1% (513/557) were found to be not present by Sanger sequencing. CONCLUSIONS: This work shows that NGS data contains sufficient characteristics for a machine-learning-based model to differentiate low from high confidence variants. Additionally, it reveals the importance of incorporating site-specific features as well as variant call features in such a model.

Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors.

Genome-wide association studies have identified over 70 single-nucleotide polymorphisms (SNPs) associated with breast cancer. A subset of these SNPs are associated with quantitative expression of nearby genes, but the functional effects of the majority remain unknown. We hypothesized that some risk SNPs may regulate alternative splicing. Using RNA-sequencing data from breast tumors and germline genotypes from The Cancer Genome Atlas, we tested the association between each risk SNP genotype and exon-, exon-exon junction- or transcript-specific expression of nearby genes. Six SNPs were associated with differential transcript expression of seven nearby genes at FDR < 0.05 (BABAM1, DCLRE1B/PHTF1, PEX14, RAD51L1, SRGAP2D and STXBP4). We next developed a Bayesian approach to evaluate, for each SNP, the overlap between the signal of association with breast cancer and the signal of association with alternative splicing. At one locus (SRGAP2D), this method eliminated the possibility that the breast cancer risk and the alternate splicing event were due to the same causal SNP. Lastly, at two loci, we identified the likely causal SNP for the alternative splicing event, and at one, functionally validated the effect of that SNP on alternative splicing using a minigene reporter assay. Our results suggest that the regulation of differential transcript isoform expression is the functional mechanism of some breast cancer risk SNPs and that we can use these associations to identify causal SNPs, target genes and the specific transcripts that may mediate breast cancer risk.

Inherited predisposition to breast and ovarian cancer in non-Jewish populations in Israel.

PURPOSE: The contribution of genetic factors to cancer in non-Jewish populations in Israel is understudied. Yet the early, mostly premenopausal age at breast cancer diagnosis is suggestive of an inherited predisposition. METHODS: High-risk cancer cases of non-Jewish origin who were counseled at the Oncogenetics unit, Sheba Medical Center and the oncology institute at the Ziv medical center from January 1, 2000 to December 31 2016 were eligible. DNA extracted from leukocytes was subjected to massive parallel, next-generation sequencing using the Color Genomics platform. Data were analyzed for pathogenic and likely pathogenic mutations using existing pipelines. RESULTS: Overall, 68 cases, each representing a unique high-risk breast/ovarian family, were genotyped: 32 Druze, 26 Muslim Arabs, and 10 Christian Arabs. Fifty-nine had breast cancer (mean age at diagnosis 42.7 ± 7.6 years), and 9 had ovarian cancer (51.6 ± 9.7 years). Overall three pathogenic mutations one each in BRCA1, PALB2, and BRIP1 genes were detected mostly in Druze families. In addition, 29 variants of unknown significance were also detected, and in 36 cases no sequence variants were noted in any of the genotyped genes. CONCLUSION: The contribution of the known cancer susceptibility genes to the burden of inherited breast/ovarian cancer predisposition in non-Jews in Israel is modest. Other genes or molecular mechanisms account for the familial breast/ovarian cancer clustering in this population.

Phosphorylation of the tumor suppressor CYLD by the breast cancer oncogene IKKepsilon promotes cell transformation.

The noncanonical IKK family member IKKepsilon is essential for regulating antiviral signaling pathways and is a recently discovered breast cancer oncoprotein. Although several IKKepsilon targets have been described, direct IKKepsilon substrates necessary for regulating cell transformation have not been identified. Here, we performed a screen for putative IKKepsilon substrates using an unbiased proteomic and bioinformatic approach. Using a positional scanning peptide library assay, we determined the optimal phosphorylation motif for IKKepsilon and used bioinformatic approaches to predict IKKepsilon substrates. Of these potential substrates, serine 418 of the tumor suppressor CYLD was identified as a likely site of IKKepsilon phosphorylation. We confirmed that CYLD is directly phosphorylated by IKKepsilon and that IKKepsilon phosphorylates serine 418 in vivo. Phosphorylation of CYLD at serine 418 decreases its deubiquitinase activity and is necessary for IKKepsilon-driven transformation. Together, these observations define IKKepsilon and CYLD as an oncogene-tumor suppressor network that participates in tumorigenesis.

Sounding out solutions: using SONAR to connect participants with relevant healthcare resources.

OBJECTIVE: This article outlines a scalable system developed by the All of Us Research Program's Genetic Counseling Resource to vet a large database of healthcare resources for supporting participants with health-related DNA results. MATERIALS AND METHODS: After a literature review of established evaluation frameworks for health resources, we created SONAR, a 10-item framework and grading scale for health-related participant-facing resources. SONAR was used to review clinical resources that could be shared with participants during genetic counseling. RESULTS: Application of SONAR shortened resource approval time from 7 days to 1 day. About 256 resources were approved and 8 rejected through SONAR review. Most approved resources were relevant to participants nationwide (60.0%). The most common resource types were related to support groups (20%), cancer care (30.6%), and general educational resources (12.4%). All of Us genetic counselors provided 1161 approved resources during 3005 (38.6%) consults, mainly to local genetic counselors (29.9%), support groups (21.9%), and educational resources (21.0%). DISCUSSION: SONAR's systematic method simplifies resource vetting for healthcare providers, easing the burden of identifying and evaluating credible resources. Compiling these resources into a user-friendly database allows providers to share these resources efficiently, better equipping participants to complete follow up actions from health-related DNA results. CONCLUSION: The All of Us Genetic Counseling Resource connects participants receiving health-related DNA results with relevant follow-up resources on a high-volume, national level. This has been made possible by the creation of a novel resource database and validation system.

Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes.

The epithelial-to-mesenchymal transition (EMT) produces cancer cells that are invasive, migratory, and exhibit stem cell characteristics, hallmarks of cells that have the potential to generate metastases. Inducers of the EMT include several transcription factors (TFs), such as Goosecoid, Snail, and Twist, as well as the secreted TGF-beta1. Each of these factors is capable, on its own, of inducing an EMT in the human mammary epithelial (HMLE) cell line. However, the interactions between these regulators are poorly understood. Overexpression of each of the above EMT inducers up-regulates a subset of other EMT-inducing TFs, with Twist, Zeb1, Zeb2, TGF-beta1, and FOXC2 being commonly induced. Up-regulation of Slug and FOXC2 by either Snail or Twist does not depend on TGF-beta1 signaling. Gene expression signatures (GESs) derived by overexpressing EMT-inducing TFs reveal that the Twist GES and Snail GES are the most similar, although the Goosecoid GES is the least similar to the others. An EMT core signature was derived from the changes in gene expression shared by up-regulation of Gsc, Snail, Twist, and TGF-beta1 and by down-regulation of E-cadherin, loss of which can also trigger an EMT in certain cell types. The EMT core signature associates closely with the claudin-low and metaplastic breast cancer subtypes and correlates negatively with pathological complete response. Additionally, the expression level of FOXC1, another EMT inducer, correlates strongly with poor survival of breast cancer patients.

Internet-Based Germline Genetic Testing for Men With Metastatic Prostate Cancer.

PURPOSE: Germline mutations in DNA repair genes are present in approximately 10% of men with metastatic prostate cancer (mPC), and guidelines recommend genetic germline testing. Notable barriers exist, including access to genetic counseling, insurance coverage, and out-of-pocket costs. The GENTleMEN study was designed to determine the feasibility of an Internet-based, patient-driven germline genetic testing approach for men with mPC. PATIENTS AND METHODS: In this prospective cohort study, men with mPC provided informed consent via an Internet-based platform and completed a questionnaire including demographics and family cancer history. Supporting medical data were also collected. Genetic testing was performed using the Color Genomics 30-gene targeted panel of cancer predisposition genes on a mailed saliva sample. Men whose test results identified a germline pathogenic or likely pathogenic variant received results by phone or telehealth genetic counseling; other participants received results by email with an option for phone-based or telehealth genetic counseling. RESULTS: As of August 18, 2021, 816 eligible men were consented, of whom 68% (551) completed genetic testing, and 8.7% (48 of 551) were found to carry a pathogenic or likely pathogenic variant in a germline DNA repair gene: CHEK2 (17), BRCA2 (15), ATM (6), NBN1 (3), BRCA1 (2), PALB2 (2), PMS2 (2), and MSH6 (1). Participants were more likely to complete the testing process if they were non-Hispanic White, married, highly educated, or from a higher-income bracket. CONCLUSION: Here, we show the feasibility of delivering germline (inherited) genetic testing by a voluntary, patient-driven, Internet-based platform to men with mPC. Preliminary results show rates of germline DNA repair mutations, consistent with other cohorts. Although feasible for some, reduced steps for participation, more dedicated diverse outreach and participant support, and identification and addressing of additional barriers is needed to ensure equitable access and optimization.

Investigating the prevalence of pathogenic variants in Saudi Arabian patients with familial cancer using a multigene next generation sequencing panel.

Family history is an important factor in determining hereditary cancer risk for many cancer types. The emergence of next-generation sequencing (NGS) has expedited the discovery of many hereditary cancer susceptibility genes and the development of rapid, affordable testing kits. Here, a 30-gene targeted NGS panel for hereditary cancer risk assessment was tested and validated in a Saudi Arabian population. A total of 310 subjects were screened, including 57 non-cancer patients, 110 index patients with cancer and 143 of the cancer patients' family members, 16 of which also had cancer. Of the 310 subjects, 119 (38.4%) were carriers of pathogenic or likely pathogenic variants (PVs) affecting one or more of the following genes: TP53, ATM, CHEK2, CDH1, CDKN2A, BRCA1, BRCA2, PALB2, BRIP1, RAD51D, APC, MLH1, MSH2, MSH6, PMS2, PTEN, NBN/NBS1 and MUTYH. Among 126 patients and relatives with a history of cancer, 49 (38.9%) were carriers of PVs or likely PVs. Two variants in particular were significantly associated with the occurrence of a specific cancer in this population (APC c.3920T>A - colorectal cancer/Lynch syndrome (p = 0.026); TP53 c.868C>T; - multiple colon polyposis (p = 0.048)). Diverse variants in BRCA2, the majority of which have not previously been reported as pathogenic, were found at higher frequency in those with a history of cancer than in the general patient population. There was a higher background prevalence of genetic variants linked to familial cancers in this cohort than expected based on prevalence in other populations.

Remotely Delivered Cancer Genetic Testing in the Making Genetic Testing Accessible (MAGENTA) Trial: A Randomized Clinical Trial.

Importance: Requiring personalized genetic counseling may introduce barriers to cancer risk assessment, but it is unknown whether omitting counseling could increase distress. Objective: To assess whether omitting pretest and/or posttest genetic counseling would increase distress during remote testing. Design, Setting, and Participants: Making Genetic Testing Accessible (MAGENTA) was a 4-arm, randomized noninferiority trial testing the effects of individualized pretest and/or posttest genetic counseling on participant distress 3 and 12 months posttest. Participants were recruited via social and traditional media, and enrollment occurred between April 27, 2017, and September 29, 2020. Participants were women aged 30 years or older, English-speaking, US residents, and had access to the internet and a health care professional. Previous cancer genetic testing or counseling was exclusionary. In the family history cohort, participants had a personal or family history of breast or ovarian cancer. In the familial pathogenic variant (PV) cohort, participants reported 1 biological relative with a PV in an actionable cancer susceptibility gene. Data analysis was performed between December 13, 2020, and May 31, 2023. Intervention: Participants completed baseline questionnaires, watched an educational video, and were randomized to 1 of 4 arms: the control arm with pretest and/or posttest genetic counseling, or 1 of 3 study arms without pretest and posttest counseling. Genetic counseling was provided by phone appointments and testing was done using home-delivered saliva kits. Main Outcomes and Measures: The primary outcome was participant distress measured by the Impact of Event Scale 3 months after receiving the results. Secondary outcomes included completion of testing, anxiety, depression, and decisional regret. Results: A total of 3839 women (median age, 44 years [range 22-91 years]), most of whom were non-Hispanic White and college educated, were randomized, 3125 in the family history and 714 in the familial PV cohorts. In the primary analysis in the family history cohort, all experimental arms were noninferior for distress at 3 months. There were no statistically significant differences in anxiety, depression, or decisional regret at 3 months. The highest completion rates were seen in the 2 arms without pretest counseling. Conclusions and Relevance: In the MAGENTA clinical trial, omitting individualized pretest counseling for all participants and posttest counseling for those without PV during remote genetic testing was not inferior with regard to posttest distress, providing an alternative care model for genetic risk assessment. Trial Registration: ClinicalTrials.gov Identifier: NCT02993068.

Clinical Implementation of Combined Monogenic and Polygenic Risk Disclosure for Coronary Artery Disease.

BACKGROUND: State-of-the-art genetic risk interpretation for a common complex disease such as coronary artery disease (CAD) requires assessment for both monogenic variants-such as those related to familial hypercholesterolemia-as well as the cumulative impact of many common variants, as quantified by a polygenic score. OBJECTIVES: The objective of the study was to describe a combined monogenic and polygenic CAD risk assessment program and examine its impact on patient understanding and changes to clinical management. METHODS: Study participants attended an initial visit in a preventive genomics clinic and a disclosure visit to discuss results and recommendations, primarily via telemedicine. Digital postdisclosure surveys and chart review evaluated the impact of disclosure. RESULTS: There were 60 participants (mean age 51 years, 37% women, 72% with no known CAD), including 30 (50%) referred by their cardiologists and 30 (50%) self-referred. Two (3%) participants had a monogenic variant pathogenic for familial hypercholesterolemia, and 19 (32%) had a high polygenic score in the top quintile of the population distribution. In a postdisclosure survey, both the genetic test report (in 80% of participants) and the discussion with the clinician (in 89% of participants) were ranked as very or extremely helpful in understanding the result. Of the 42 participants without CAD, 17 or 40% had a change in management, including statin initiation, statin intensification, or coronary imaging. CONCLUSIONS: Combined monogenic and polygenic assessments for CAD risk provided by preventive genomics clinics are beneficial for patients and result in changes in management in a significant portion of patients.

Whole-genome sequencing as an investigational device for return of hereditary disease risk and pharmacogenomic results as part of the All of Us Research Program.

BACKGROUND: The All of Us Research Program (AoURP, "the program") is an initiative, sponsored by the National Institutes of Health (NIH), that aims to enroll one million people (or more) across the USA. Through repeated engagement of participants, a research resource is being created to enable a variety of future observational and interventional studies. The program has also committed to genomic data generation and returning important health-related information to participants. METHODS: Whole-genome sequencing (WGS), variant calling processes, data interpretation, and return-of-results procedures had to be created and receive an Investigational Device Exemption (IDE) from the United States Food and Drug Administration (FDA). The performance of the entire workflow was assessed through the largest known cross-center, WGS-based, validation activity that was refined iteratively through interactions with the FDA over many months. RESULTS: The accuracy and precision of the WGS process as a device for the return of certain health-related genomic results was determined to be sufficient, and an IDE was granted. CONCLUSIONS: We present here both the process of navigating the IDE application process with the FDA and the results of the validation study as a guide to future projects which may need to follow a similar path. Changes to the program in the future will be covered in supplementary submissions to the IDE and will support additional variant classes, sample types, and any expansion to the reportable regions.