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The article summarizes research published within the issue, titled "The Impact of Whole-Genome Sequencing on the Primary Care and Outcomes of Healthy Adult Patients," by J. L. Vassy, K. D. Christensen, E. F. Schonman and colleagues. Topics discussed include whole-genome sequencing (WGS) in primary care, research methodology, and limitations of the study.

Efforts to implement and evaluate genome sequencing (GS) as a screening tool for newborns and infants are expanding worldwide. The first iteration of the BabySeq Project (2015-2019), a randomized controlled trial of newborn sequencing, produced novel evidence on medical, behavioral, and economic outcomes. The second iteration of BabySeq, which began participant recruitment in January 2023, examines GS outcomes in a larger, more diverse cohort of more than 500 infants up to one year of age recruited from pediatric clinics at several sites across the United States. The trial aims for families who self-identify as Black/African American or Hispanic/Latino to make up more than 50% of final enrollment, and key aspects of the trial design were co-developed with a community advisory board. All enrolled families receive genetic counseling and a family history report. Half of enrolled infants are randomized to receive GS with comprehensive interpretation of pathogenic and likely pathogenic variants in more than 4,300 genes associated with childhood-onset and actionable adult-onset conditions, as well as larger-scale chromosomal copy number variants classified as pathogenic or likely pathogenic. GS result reports include variants associated with disease (Mendelian disease risks) and carrier status of autosomal-recessive and X-linked disorders. Investigators evaluate the utility and impacts of implementing a GS screening program in a diverse cohort of infants using medical record review and longitudinal parent surveys. In this perspective, we describe the rationale for the second iteration of the BabySeq Project, the outcomes being assessed, and the key decisions collaboratively made by the study team and community advisory board., Competing Interests: Declaration of interests H.S.S. has received consulting income from Illumina unrelated to this work. N.D.S. is a member of the Scientific Advisory Board for Neuberg Center for Genomic Medicine. A.L.M. is a paid advisor for Nurture Genomics. B.R.K. is a member of medical advisory boards for Alexion, SpringWorks, Healx, Infixion, and Recursion and has stock options in GenomeMedical. R.C.G. has received compensation for advising Allelica, Atria, Fabric, Genome Web, and Genomic Life and is a cofounder of Genome Medical and Nurture Genomics., (Copyright © 2024 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Purpose: Novel uses of genome sequencing (GS) present an opportunity for return of results to healthy individuals, prompting the need for scalable genetic counseling strategies. We evaluate the effectiveness of a genomic counseling model (GCM) and explore preferences for GS findings in the general population., Methods: Participants (N = 466) completed GS and our GCM (digital genomics platform and group-based webinar) and indicated results preferences. Surveys were administered before (T0) and after (T1) GCM. Change in knowledge and decisional conflict (DC) were evaluated using paired-sample T and Wilcoxon tests. Factors influencing knowledge and results preferences were evaluated using linear and logistic regression models., Results: Participants were 56% female, 58% white, and 53% ≥40 years of age. Mean knowledge scores increased (Limitations: 3.73 to 5.63; Benefits: 4.34 to 5.48, P < .0001), and DC decreased (-21.9, P < .0001) at T1 versus T0. Eighty-six percent of participants wished to learn all GS findings at T1 vs 78% at T0 (P < .0001). Older age, negative/mixed attitudes toward genetics and greater DC were associated with change in preferences after intervention., Conclusion: In a population-based cohort undergoing GS interested in learning GS findings, our GCM increased knowledge and reduced DC, illustrating the GCM's potential effectiveness for GS counseling in the general population., Competing Interests: Conflict of Interest Yvonne Bombard holds the Canada Research Chair in Genomics Health Services and Policy. Yvonne Bombard and Marc Clausen are co-founders of the Genetics Adviser. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. All rights reserved.)

African Americans (AAs) have been underrepresented in polygenic risk score (PRS) studies. Here, we integrated genome-wide data from multiple observational studies on type 2 diabetes (T2D), encompassing a total of 101,987 AAs, to train and optimize an AA-focused T2D PRS (PRSAA), using a Bayesian polygenic modeling method. We further tested the score in three independent studies with a total of 7,275 AAs and compared the PRSAA with other published scores. Results show that a 1-SD increase in the PRSAA was associated with 40-60% increase in the odds of T2D (odds ratio [OR] 1.60, 95% CI 1.37-1.88; OR 1.40, 95% CI 1.16-1.70; and OR 1.45, 95% CI 1.30-1.62) across three testing cohorts. These models captured 1.0-2.6% of the variance (R2) in T2D on the liability scale. The positive predictive values for three calculated score thresholds (the top 2%, 5%, and 10%) ranged from 14 to 35%. The PRSAA, in general, performed similarly to existing T2D PRS. The need remains for larger data sets to continue to evaluate the utility of within-ancestry scores in the AA population., (© 2024 by the American Diabetes Association.)

Genetic counseling for patients who are pursuing genetic testing in the absence of a medical indication, referred to as elective genomic testing (EGT), is becoming more common. This type of testing has the potential to detect genetic conditions before there is a significant health impact permitting earlier management and/or treatment. Pre- and post-test counseling for EGT is similar to indication-based genetic testing. Both require a complete family and medical history when ordering a test or interpreting a result. However, EGT counseling has some special considerations including greater uncertainties around penetrance and clinical utility and a lack of published guidelines. While certain considerations in the selection of a high-quality genetic testing laboratory are universal, there are some considerations that are unique to the selection of a laboratory performing EGT. This practice resource intends to provide guidance for genetic counselors and other healthcare providers caring for adults seeking pre- or post-test counseling for EGT. Genetic counselors and other genetics trained healthcare providers are the ideal medical professionals to supply accurate information to individuals seeking counseling about EGT enabling them to make informed decisions about testing and follow-up., (© 2023 National Society of Genetic Counselors.)

Rapid advancements of genome sequencing (GS) technologies have enhanced our understanding of the relationship between genes and human disease. To incorporate genomic information into the practice of medicine, new processes for the analysis, reporting, and communication of GS data are needed. Blood samples were collected from adults with a PCR-confirmed SARS-CoV-2 (COVID-19) diagnosis (target N = 1500). GS was performed. Data were filtered and analyzed using custom pipelines and gene panels. We developed unique patient-facing materials, including an online intake survey, group counseling presentation, and consultation letters in addition to a comprehensive GS report. The final report includes results generated from GS data: (1) monogenic disease risks; (2) carrier status; (3) pharmacogenomic variants; (4) polygenic risk scores for common conditions; (5) HLA genotype; (6) genetic ancestry; (7) blood group; and, (8) COVID-19 viral lineage. Participants complete pre-test genetic counseling and confirm preferences for secondary findings before receiving results. Counseling and referrals are initiated for clinically significant findings. We developed a genetic counseling, reporting, and return of results framework that integrates GS information across multiple areas of human health, presenting possibilities for the clinical application of comprehensive GS data in healthy individuals., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: This study aimed to explore whether evidence of pathogenicity from prior variant classifications in ClinVar could be used to inform variant interpretation using the American College of Medical Genetics and Genomics/Association for Molecular Pathology clinical guidelines., Methods: We identified distinct single-nucleotide variants (SNVs) that are either similar in location or in functional consequence to pathogenic variants in ClinVar and analyzed evidence in support of pathogenicity using 3 interpretation criteria., Results: Thousands of variants, including many in clinically actionable disease genes (American College of Medical Genetics and Genomics secondary findings v3.0), have evidence of pathogenicity from existing variant classifications, accounting for 2.5% of nonsynonymous SNVs within ClinVar. Notably, there are many variants with uncertain or conflicting classifications that cause the same amino acid substitution as other pathogenic variants (PS1, N = 323), variants that are predicted to cause different amino acid substitutions in the same codon as pathogenic variants (PM5, N = 7692), and loss-of-function variants that are present in genes in which many loss-of-function variants are classified as pathogenic (PVS1, N = 3635). Most of these variants have similar computational predictions of pathogenicity and splicing effect as their associated pathogenic variants., Conclusion: Broadly, for >1.4 million SNVs exome wide, information from previously classified variants could be used to provide evidence of pathogenicity. We have developed a pipeline to identify variants meeting these criteria that may inform interpretation efforts., Competing Interests: Conflict of Interest C.A.C. has served as a consultant or received honoraria from gWell Health, Athenahealth, and Data Sentry Solutions. All other authors declare no conflicts of interest., (Copyright © 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Genome sequencing holds the promise for great public health benefits. It is currently being used in the context of rare disease diagnosis and novel gene identification, but also has the potential to identify genetic disease risk factors in healthy individuals. Genome sequencing technologies are currently being used to identify genetic factors that may influence variability in symptom severity and immune response among patients infected by SARS-CoV-2. The GENCOV study aims to look at the relationship between genetic, serological, and biochemical factors and variability of SARS-CoV-2 symptom severity, and to evaluate the utility of returning genome screening results to study participants. Study participants select which results they wish to receive with a decision aid. Medically actionable information for diagnosis, disease risk estimation, disease prevention, and patient management are provided in a comprehensive genome report. Using a combination of bioinformatics software and custom tools, this article describes a pipeline for the analysis and reporting of genetic results to individuals with COVID-19, including HLA genotyping, large-scale continental ancestry estimation, and pharmacogenomic analysis to determine metabolizer status and drug response. In addition, this pipeline includes reporting of medically actionable conditions from comprehensive gene panels for Cardiology, Neurology, Metabolism, Hereditary Cancer, and Hereditary Kidney, and carrier screening for reproductive planning. Incorporated into the genome report are polygenic risk scores for six diseases-coronary artery disease; atrial fibrillation; type-2 diabetes; and breast, prostate, and colon cancer-as well as blood group genotyping analysis for ABO and Rh blood types and genotyping for other antigens of clinical relevance. The genome report summarizes the findings of these analyses in a way that extensively communicates clinically relevant results to patients and their physicians. © 2022 Wiley Periodicals LLC. Basic Protocol 1: HLA genotyping and disease association Basic Protocol 2: Large-scale continental ancestry estimation Basic Protocol 3: Dosage recommendations for pharmacogenomic gene variants associated with drug response Support Protocol: System setup., (© 2022 Wiley Periodicals LLC.)

The All of Us Research Program (AoURP) is a historic effort to accelerate research and improve healthcare by generating and collating data from one million people in the United States. Participants will have the option to receive results from their genome analysis, including actionable findings in 59 gene-disorder pairs for which disorder-associated variants are recommended for return by the American College of Medical Genetics and Genomics. To ensure consistent reporting across the AoURP, in a prelaunch study the four participating clinical laboratories shared all variant classifications in the 59 genes of interest from their internal databases. Of the 11,813 unique variants classified by at least two of the four laboratories, classifications were concordant with regard to reportability for 99.1% (11,711), with only 0.9% (102) having reportability differences. Through variant reassessment, data sharing, and discussion of rationale, participating laboratories resolved all 102 reportable differences. These approaches will be maintained during routine AoU reporting to ensure continuous classification harmonization and consistent reporting within AoURP., (© 2021 The Authors. Human Mutation published by Wiley Periodicals LLC.)

Importance: Pathogenic variants associated with inherited cardiomyopathy are recognized as important and clinically actionable when identified, leading some clinicians to recommend population-wide genomic screening., Objective: To determine the prevalence and clinical importance of pathogenic variants associated with inherited cardiomyopathy within the context of contemporary clinical care., Design, Setting, and Participants: This was a genetic association study of participants in Atherosclerosis in Risk Communities (ARIC), recruited from 1987 to 1989, with median follow-up of 27 years, and the UK Biobank, recruited from 2006 to 2010, with median follow-up of 10 years. ARIC participants were recruited from 4 sites across the US. UK Biobank participants were recruited from 22 sites across the UK. Participants in the US were of African and European ancestry; those in the UK were of African, East Asian, South Asian, and European ancestry. Statistical analyses were performed between August 1, 2021, and February 9, 2022., Exposures: Rare genetic variants predisposing to inherited cardiomyopathy., Main Outcomes and Measures: Pathogenicity of observed DNA sequence variants in sequenced exomes of 13 genes (ACTC1, FLNC, GLA, LMNA, MYBPC3, MYH7, MYL2, MYL3, PRKAG2, TNNI3, TNNT2, TPM1, and TTN) associated with inherited cardiomyopathies were classified by a blinded clinical geneticist per American College of Medical Genetics recommendations. Incidence of all-cause mortality, heart failure, and atrial fibrillation were determined. Cardiac magnetic resonance imaging, echocardiography, and electrocardiogram measures were assessed in a subset of participants., Results: A total of 9667 ARIC participants (mean [SD] age, 54.0 [5.7] years; 4232 women [43.8%]; 2658 African [27.5%] and 7009 European [72.5%] ancestry) and 49 744 UK Biobank participants (mean [SD] age, 57.1 [8.0] years; 27 142 women [54.5%]; 1006 African [2.0%], 173 East Asian [0.3%], 939 South Asian [1.9%], and 46 449 European [93.4%] European ancestry) were included in the study. Of those, 59 participants (0.61%) in ARIC and 364 participants (0.73%) in UK Biobank harbored an actionable pathogenic or likely pathogenic variant associated with dilated or hypertrophic cardiomyopathy. Carriers of these variants were not reliably identifiable by imaging. However, the presence of these variants was associated with increased risk of heart failure (hazard ratio [HR], 1.7; 95% CI, 1.1-2.8), atrial fibrillation (HR, 2.9; 95% CI, 1.9-4.5), and all-cause mortality (HR, 1.5; 95% CI, 1.1-2.2) in ARIC. Similar risk patterns were observed in the UK Biobank., Conclusions and Relevance: Results of this genetic association study suggest that approximately 0.7% of study participants harbored a pathogenic variant associated with inherited cardiomyopathy. These variant carriers would be challenging to identify within clinical practice without genetic testing but are at increased risk for cardiovascular disease and all-cause mortality.

Age is the dominant risk factor for infectious diseases, but the mechanisms linking age to infectious disease risk are incompletely understood. Age-related mosaic chromosomal alterations (mCAs) detected from genotyping of blood-derived DNA, are structural somatic variants indicative of clonal hematopoiesis, and are associated with aberrant leukocyte cell counts, hematological malignancy, and mortality. Here, we show that mCAs predispose to diverse types of infections. We analyzed mCAs from 768,762 individuals without hematological cancer at the time of DNA acquisition across five biobanks. Expanded autosomal mCAs were associated with diverse incident infections (hazard ratio (HR) 1.25; 95% confidence interval (CI) = 1.15-1.36; P = 1.8 × 10 -7 ), including sepsis (HR 2.68; 95% CI = 2.25-3.19; P = 3.1 × 10 -28 ), pneumonia (HR 1.76; 95% CI = 1.53-2.03; P = 2.3 × 10 -15 ), digestive system infections (HR 1.51; 95% CI = 1.32-1.73; P = 2.2 × 10 -9 ) and genitourinary infections (HR 1.25; 95% CI = 1.11-1.41; P = 3.7 × 10 -4 ). A genome-wide association study of expanded mCAs identified 63 loci, which were enriched at transcriptional regulatory sites for immune cells. These results suggest that mCAs are a marker of impaired immunity and confer increased predisposition to infections.

Diagnostic laboratories gather phenotypic data through requisition forms, but there is no consensus as to which data are essential for variant interpretation. The ClinGen Cardiomyopathy Variant Curation Expert Panel defined a phenotypic data set for hypertrophic cardiomyopathy (HCM) variant interpretation, with the goal of standardizing requisition forms. Phenotypic data elements listed on requisition forms from nine leading cardiomyopathy testing laboratories were compiled to assess divergence in data collection. A pilot of 50 HCM cases was implemented to determine the feasibility of harmonizing data collection. Laboratory directors were surveyed to gauge potential for adoption of a minimal data set. Wide divergence was observed in the phenotypic data fields in requisition forms. The 50-case pilot showed that although demographics and assertion of a clinical diagnosis of HCM had 86% to 98% completion, specific phenotypic features, such as degree of left ventricular hypertrophy, ejection fraction, and suspected syndromic disease, were completed only 24% to 44% of the time. Nine data elements were deemed essential for variant classification by the expert panel. Participating laboratories unanimously expressed a willingness to adopt these data elements in their requisition forms. This study demonstrates the value of comparing and sharing best practices through an expert group, such as the ClinGen Program, to enhance variant interpretation, providing a foundation for leveraging cumulative case-level data in public databases and ultimately improving patient care., (Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.

Testing asymptomatic individuals for unsuspected conditions is not new to the medical and public health communities. Protocols to develop screening tests are well established. However, the application of screening principles to inherited diseases presents unique challenges. Unlike most screening tests, the natural history and disease prevalence of most rare inherited diseases in an unselected population are unknown. It is difficult or impossible to obtain a truth set cohort for clinical validation studies. As a result, it is not possible to accurately calculate clinical positive and negative predictive values for likely pathogenic variants, which are commonly returned in genetic screening assays. In addition, many of the genetic conditions included in screening panels do not have clinical confirmatory tests. All these elements are typically required to justify the development of a screening test, according to the World Health Organization screening principles. Nevertheless, as the cost of DNA sequencing continues to fall, more individuals are opting to undergo genomic testing in the absence of a clinical indication. Despite the challenges, reasonable estimates can be deduced and used to inform test design strategies. Herein, we review basic test design principles and apply them to genetic screening., (Copyright © 2020 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Background: RASopathies are a group of disorders caused by disruptions to the RAS-MAPK pathway. Despite being in the same pathway, Neurofibromatosis Type 1 (NF1) and Legius syndrome (LS) typically present with phenotypes distinct from Noonan spectrum disorders (NSDs). However, some NF1/LS individuals also exhibit NSD phenotypes, often referred to as Neurofibromatosis-Noonan syndrome (NFNS), and may be mistakenly evaluated for NSDs, delaying diagnosis, and affecting patient management., Methods: A derivation cohort of 28 patients with a prior negative NSD panel and either NFNS or a suspicion of NSD and café-au-lait spots underwent NF1 and SPRED1 sequencing. To further determine the utility and burden of adding these genes, a validation cohort of 505 patients with a suspected RASopathy were tested on a 14-gene RASopathy-associated panel., Results: In the derivation cohort, six (21%) patients had disease-causing NF1 or SPRED1 variants. In the validation cohort, 11 (2%) patients had disease-causing variants and 15 (3%) had variants of uncertain significance in NF1 or SPRED1. Of those with disease-causing variants, 5/17 only had an NSD diagnosis., Conclusions: Adding NF1 and SPRED1 to RASopathy panels can speed diagnosis and improve patient management, without significantly increasing the burden of inconclusive results., (© 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

Importance: Pathogenic DNA variants associated with familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and Lynch syndrome are widely recognized as clinically important and actionable when identified, leading some clinicians to recommend population-wide genomic screening., Objectives: To assess the prevalence and clinical importance of pathogenic or likely pathogenic variants associated with each of 3 genomic conditions (familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and Lynch syndrome) within the context of contemporary clinical care., Design, Setting, and Participants: This cohort study used gene-sequencing data from 49 738 participants in the UK Biobank who were recruited from 22 sites across the UK between March 21, 2006, and October 1, 2010. Inpatient hospital data date back to 1977; cancer registry data, to 1957; and death registry data, to 2006. Statistical analysis was performed from July 22, 2019, to November 15, 2019., Exposures: Pathogenic or likely pathogenic DNA variants classified by a clinical laboratory geneticist., Main Outcomes and Measures: Composite end point specific to each genomic condition based on atherosclerotic cardiovascular disease events for familial hypercholesterolemia, breast or ovarian cancer for hereditary breast and ovarian cancer syndrome, and colorectal or uterine cancer for Lynch syndrome., Results: Among 49 738 participants (mean [SD] age, 57 [8] years; 27 144 female [55%]), 441 (0.9%) harbored a pathogenic or likely pathogenic variant associated with any of 3 genomic conditions, including 131 (0.3%) for familial hypercholesterolemia, 235 (0.5%) for hereditary breast and ovarian cancer syndrome, and 76 (0.2%) for Lynch syndrome. Presence of these variants was associated with increased risk of disease: for familial hypercholesterolemia, 28 of 131 carriers (21.4%) vs 4663 of 49 607 noncarriers (9.4%) developed atherosclerotic cardiovascular disease; for hereditary breast and ovarian cancer syndrome, 32 of 116 female carriers (27.6%) vs 2080 of 27 028 female noncarriers (7.7%) developed associated cancers; and for Lynch syndrome, 17 of 76 carriers (22.4%) vs 929 of 49 662 noncarriers (1.9%) developed colorectal or uterine cancer. The predicted probability of disease at age 75 years despite contemporary clinical care was 45.3% for carriers of familial hypercholesterolemia, 41.1% for hereditary breast and ovarian cancer syndrome, and 38.3% for Lynch syndrome. Across the 3 conditions, 39.7% (175 of 441) of the carriers reported a family history of disease vs 23.2% (34 517 of 148 772) of noncarriers., Conclusions and Relevance: The findings suggest that approximately 1% of the middle-aged adult population in the UK Biobank harbored a pathogenic variant associated with any of 3 genomic conditions. These variants were associated with an increased risk of disease despite contemporary clinical care and were not reliably detected by family history.

Background: Sudden cardiac death occurs in ∼220,000 U.S. adults annually, the majority of whom have no prior symptoms or cardiovascular diagnosis. Rare pathogenic DNA variants in any of 49 genes can pre-dispose to 4 important causes of sudden cardiac death: cardiomyopathy, coronary artery disease, inherited arrhythmia syndrome, and aortopathy or aortic dissection., Objectives: This study assessed the prevalence of rare pathogenic variants in sudden cardiac death cases versus controls, and the prevalence and clinical importance of such mutations in an asymptomatic adult population., Methods: The authors performed whole-exome sequencing in a case-control cohort of 600 adult-onset sudden cardiac death cases and 600 matched controls from 106,098 participants of 6 prospective cohort studies. Observed DNA sequence variants in any of 49 genes with known association to cardiovascular disease were classified as pathogenic or likely pathogenic by a clinical laboratory geneticist blinded to case status. In an independent population of 4,525 asymptomatic adult participants of a prospective cohort study, the authors performed whole-genome sequencing and determined the prevalence of pathogenic or likely pathogenic variants and prospective association with cardiovascular death., Results: Among the 1,200 sudden cardiac death cases and controls, the authors identified 5,178 genetic variants and classified 14 as pathogenic or likely pathogenic. These 14 variants were present in 15 individuals, all of whom had experienced sudden cardiac death-corresponding to a pathogenic variant prevalence of 2.5% in cases and 0% in controls (p < 0.0001). Among the 4,525 participants of the prospective cohort study, 41 (0.9%) carried a pathogenic or likely pathogenic variant and these individuals had 3.24-fold higher risk of cardiovascular death over a median follow-up of 14.3 years (p = 0.02)., Conclusions: Gene sequencing identifies a pathogenic or likely pathogenic variant in a small but potentially important subset of adults experiencing sudden cardiac death; these variants are present in ∼1% of asymptomatic adults., (Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Although genome sequencing is increasingly available in clinical and research settings, many questions remain about the interpretation of sequencing data. In the MedSeq Project, we explored how much effort is required to evaluate and report on more than 4,500 genes reportedly associated with monogenic conditions, as well as pharmacogenomic (PGx) markers, blood antigen serotyping, and polygenic risk scores in 100 individuals (50 with cardiomyopathy and 50 healthy) randomized to the sequencing arm. We defined the quality thresholds for determining the need for Sanger confirmation. Finally, we examined the effort needed and new findings revealed by reanalyzing each genome (6-23 months after initial analysis; mean 13 months). Monogenic disease risk and carrier status were reported in 21% and 94% of participants, respectively. Only two participants had no monogenic disease risk or carrier status identified. For the PGx results (18 genotypes in six genes for five drugs), the identified diplotypes prompted recommendation for non-standard dosing of at least one of the analyzed drugs in 95% of participants. For blood antigen studies, we found that 31% of participants had a rare blood antigen genotype. In the cardiomyopathy cohort, an explanation for disease was identified in 48% of individuals. Over the course of the study, 14 variants were reclassified and, upon reanalysis, 18 new variants met criteria for reporting. These findings highlight the quantity of medically relevant findings from a broad analysis of genomic sequencing data as well as the need for periodic reinterpretation and reanalysis of data for both diagnostic indications and secondary findings., (Copyright © 2019 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Recent advances in DNA sequencing have expanded our understanding of the molecular basis of genetic disorders and increased the utilization of clinical genomic tests. Given the paucity of evidence to accurately classify each variant and the difficulty of experimentally evaluating its clinical significance, a large number of variants generated by clinical tests are reported as variants of unknown clinical significance. Population-scale variant databases can improve clinical interpretation. Specifically, pathogenicity prediction for novel missense variants can use features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant data set. Here, we introduce one variant data set derived from clinical sequencing panels and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This data set is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further use this data set to demonstrate the necessity of disease-specific classifiers and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant-level features. PathoPredictor achieves an average precision >90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. The accumulation of larger clinical variant training data sets can significantly enhance their performance in a disease- and gene-specific manner., (© 2019 Evans et al.; Published by Cold Spring Harbor Laboratory Press.)

Comprehensive next-generation sequencing (NGS) tests are increasingly used as first-line tests in the evaluation of patients with suspected heritable disease. Despite major technical simplifications, these assays still pose significant challenges for molecular testing laboratories. Existing professional guidelines and recommendations provide a framework for laboratories implementing such tests, but in-depth, concrete guidance is generally not provided. Consequently, there is variability in how laboratories interpret and subsequently implement these regulatory frameworks. To address the need for more detailed guidance, the College of American Pathologists with representation from the Association for Molecular Pathologists assembled a working group to create a practical resource for clinical laboratories. This initial work is focused on variant detection in the setting of inherited disease and provides structured worksheets that guide the user through the entire life cycle of an NGS test, including design, optimization, validation, and quality management with additional guidance for clinical bioinformatics. This resource is designed to be a living document that is publicly available and will be updated with user and expert feedback as the wet bench and bioinformatic landscapes continue to evolve. It is intended to facilitate the standardization of NGS testing across laboratories and therefore to improve patient care., (Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment., (Copyright © 2019. Published by Elsevier Inc.)

The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome-wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single-nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA-B herpes zoster (shingles) association and discovered a novel zoster-associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29)., (© 2018 The Authors. Genetic Epidemiology Published by Wiley Periodicals, Inc.)

PurposeArrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart disease. Clinical follow-up of incidental findings in ARVC-associated genes is recommended. We aimed to determine the prevalence of disease thus ascertained.MethodsIndividuals (n = 30,716) underwent exome sequencing. Variants in PKP2, DSG2, DSC2, DSP, JUP, TMEM43, or TGFβ3 that were database-listed as pathogenic or likely pathogenic were identified and evidence-reviewed. For subjects with putative loss-of-function (pLOF) variants or variants of uncertain significance (VUS), electronic health records (EHR) were reviewed for ARVC diagnosis, diagnostic criteria, and International Classification of Diseases (ICD-9) codes.ResultsEighteen subjects had pLOF variants; none of these had an EHR diagnosis of ARVC. Of 14 patients with an electrocardiogram, one had a minor diagnostic criterion; the rest were normal. A total of 184 subjects had VUS, none of whom had an ARVC diagnosis. The proportion of subjects with VUS with major (4%) or minor (13%) electrocardiogram diagnostic criteria did not differ from that of variant-negative controls. ICD-9 codes showed no difference in defibrillator use, electrophysiologic abnormalities or nonischemic cardiomyopathies in patients with pLOF or VUSs compared with controls.ConclusionpLOF variants in an unselected cohort were not associated with ARVC phenotypes based on EHR review. The negative predictive value of EHR review remains uncertain.

Background: As DNA sequencing costs decline, genetic testing options have expanded. Whole exome sequencing and whole genome sequencing (WGS) are entering clinical use, posing questions about their incremental value compared with disease-specific multigene panels that have been the cornerstone of genetic testing., Methods and Results: Forty-one patients with hypertrophic cardiomyopathy who had undergone targeted hypertrophic cardiomyopathy genetic testing (either multigene panel or familial variant test) were recruited into the MedSeq Project, a clinical trial of WGS. Results from panel genetic testing and WGS were compared. In 20 of 41 participants, panel genetic testing identified variants classified as pathogenic, likely pathogenic, or uncertain significance. WGS identified 19 of these 20 variants, but the variant detection algorithm missed a pathogenic 18 bp duplication in myosin binding protein C ( MYBPC3 ) because of low coverage. In 3 individuals, WGS identified variants in genes implicated in cardiomyopathy but not included in prior panel testing: a pathogenic protein tyrosine phosphatase, non-receptor type 11 ( PTPN11 ) variant and variants of uncertain significance in integrin-linked kinase ( ILK ) and filamin-C ( FLNC ). WGS also identified 84 secondary findings (mean=2 per person, range=0-6), which mostly defined carrier status for recessive conditions., Conclusions: WGS detected nearly all variants identified on panel testing, provided 1 new diagnostic finding, and allowed interrogation of posited disease genes. Several variants of uncertain clinical use and numerous secondary genetic findings were also identified. Whereas panel testing and WGS provided similar diagnostic yield, WGS offers the advantage of reanalysis over time to incorporate advances in knowledge, but requires expertise in genomic interpretation to appropriately incorporate WGS into clinical care., Clinical Trial Registration: URL: https://clinicaltrials.gov. Unique identifier: NCT01736566., (© 2017 American Heart Association, Inc.)

Background: Whole-genome sequencing (WGS) in asymptomatic adults might prevent disease but increase health care use without clinical value., Objective: To describe the effect on clinical care and outcomes of adding WGS to standardized family history assessment in primary care., Design: Pilot randomized trial. (ClinicalTrials.gov: NCT01736566)., Setting: Academic primary care practices., Participants: 9 primary care physicians (PCPs) and 100 generally healthy patients recruited at ages 40 to 65 years., Intervention: Patients were randomly assigned to receive a family history report alone (FH group) or in combination with an interpreted WGS report (FH + WGS group), which included monogenic disease risk (MDR) results (associated with Mendelian disorders), carrier variants, pharmacogenomic associations, and polygenic risk estimates for cardiometabolic traits. Each patient met with his or her PCP to discuss the report., Measurements: Clinical outcomes and health care use through 6 months were obtained from medical records and audio-recorded discussions between PCPs and patients. Patients' health behavior changes were surveyed 6 months after receiving results. A panel of clinician-geneticists rated the appropriateness of how PCPs managed MDR results., Results: Mean age was 55 years; 58% of patients were female. Eleven FH + WGS patients (22% [95% CI, 12% to 36%]) had new MDR results. Only 2 (4% [CI, 0.01% to 15%]) had evidence of the phenotypes predicted by an MDR result (fundus albipunctatus due to RDH5 and variegate porphyria due to PPOX). Primary care physicians recommended new clinical actions for 16% (CI, 8% to 30%) of FH patients and 34% (CI, 22% to 49%) of FH + WGS patients. Thirty percent (CI, 17% to 45%) and 41% (CI, 27% to 56%) of FH and FH + WGS patients, respectively, reported making a health behavior change after 6 months. Geneticists rated PCP management of 8 MDR results (73% [CI, 39% to 99%]) as appropriate and 2 results (18% [CI, 3% to 52%]) as inappropriate., Limitation: Limited sample size and ancestral and socioeconomic diversity., Conclusion: Adding WGS to primary care reveals new molecular findings of uncertain clinical utility. Nongeneticist providers may be able to manage WGS results appropriately, but WGS may prompt additional clinical actions of unclear value., Primary Funding Source: National Institutes of Health.

Purpose: Classification of novel variants is a major challenge facing the widespread adoption of comprehensive clinical genomic sequencing and the field of personalized medicine in general. This is largely because most novel variants do not have functional, genetic, or population data to support their clinical classification., Methods: To improve variant interpretation, we leveraged the Exome Aggregation Consortium (ExAC) data set (N = ~60,000) as well as 7,000 clinically curated variants in 132 genes identified in more than 11,000 probands clinically tested for cardiomyopathies, rasopathies, hearing loss, or connective tissue disorders to perform a systematic evaluation of domain level disease associations., Results: We statistically identify regions that are most sensitive to functional variation in the general population and also most commonly impacted in symptomatic individuals. Our data show that a significant number of exons and domains in genes strongly associated with disease can be defined as disease-sensitive or disease-tolerant, leading to potential reclassification of at least 26% (450 out of 1,742) of variants of uncertain clinical significance in the 132 genes., Conclusion: This approach leverages domain functional annotation and associated disease in each gene to prioritize candidate disease variants, increasing the sensitivity and specificity of novel variant assessment within these genes.Genet Med advance online publication 22 September 2016.

Purpose: Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications., Methods: This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols., Results: Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing., Conclusion: This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.

Objectives: Noonan spectrum disorders (NSDs) occur in 1:1000-2500 live births. Currently, there are no guidelines for prenatal molecular genetic testing for NSDs. Recent studies recommend prenatal testing for NSDs when ultrasonography detects two or more associated abnormalities. A stronger association between ultrasound findings and NSDs would enable more informed prenatal genetic testing., Methods: A total of 212 newborns (0-12 weeks) with prenatal ultrasound findings and a clinical suspicion of a NSD were referred for molecular genetic testing. Of these, 159/212 newborns tested had a single ultrasound abnormality and 53/212 newborns had two or more. Testing was performed by either a microarray-based resequencing assay or next generation sequencing of RAS/MAPK pathway genes associated with NSDs. Prenatal ultrasound findings in positive and negative cases were compared., Results: A disease-causing variant was identified in 21.7% (46/212) of newborns tested. Of these positive cases, 67.4% (31/46) had only one ultrasound abnormality reported. The rate of detecting a disease-causing variant in cases with one ultrasound finding was 19.5% (31/159), which was not significantly different (p-value = 0.36) than that in cases with two or more ultrasound findings (28.3%; 15/53)., Conclusions: Prenatal molecular testing for NSDs should be considered even in the presence of a single associated abnormal ultrasound finding. © 2016 John Wiley & Sons, Ltd., (© 2016 John Wiley & Sons, Ltd.)

Academic medical centers require many interconnected systems to fully support genetic testing processes. We provide an overview of the end-to-end support that has been established surrounding a genetic testing laboratory within our environment, including both laboratory and clinician facing infrastructure. We explain key functions that we have found useful in the supporting systems. We also consider ways that this infrastructure could be enhanced to enable deeper assessment of genetic test results in both the laboratory and clinic.

Glycosaminoglycans (GAGs) such as chondroitin are ubiquitous disaccharide carbohydrate chains that contribute to the formation and function of proteoglycans at the cell membrane and in the extracellular matrix. Although GAG-modifying enzymes are required for diverse cellular functions, the role of these proteins in human development and disease is less well understood. Here, we describe two sisters out of seven siblings affected by congenital limb malformation and malignant lymphoproliferative disease. Using Whole-Genome Sequencing (WGS), we identified in the proband deletion of a 55 kb region within chromosome 12q23 that encompasses part of CHST11 (encoding chondroitin-4-sulfotransferase 1) and an embedded microRNA (MIR3922). The deletion was homozygous in the proband but not in each of three unaffected siblings. Genotyping data from the 1000 Genomes Project suggest that deletions inclusive of both CHST11 and MIR3922 are rare events. Given that CHST11 deficiency causes severe chondrodysplasia in mice that is similar to human limb malformation, these results underscore the importance of chondroitin modification in normal skeletal development. Our findings also potentially reveal an unexpected role for CHST11 and/or MIR3922 as tumor suppressors whose disruption may contribute to malignant lymphoproliferative disease.