The cost of whole genome sequencing is dropping rapidly. There has been a great deal of enthusiasm about the potential for this technological advance to transform clinical care. Given the interest and significant investment in genomics, this seems an ideal time to consider what the evidence tells us about potential benefits and harms, particularly in the context of health care policy. The scale and pace of adoption of this powerful new technology should be driven by clinical need, clinical evidence, and a commitment to put patients at the centre of health care policy.

Although increasingly global, data-driven genomics and other 'omics'-focused research hold great promise for health discoveries, current research ethics review systems around the world challenge potential improvements in human health from such research. To overcome this challenge, we propose a 'Safe Harbor Framework for International Ethics Equivalency' that facilitates the harmonization of ethics review of specific types of data-driven international research projects while respecting globally transposable research ethics norms and principles. The Safe Harbor would consist in part of an agency supporting an International Federation for Ethics Review (IFER), formed by a voluntary compact among countries, granting agencies, philanthropies, institutions, and healthcare, patient advocacy, and research organizations. IFER would be both a central ethics review body, and also a forum for review and follow-up of policies concerning ethics norms for international research projects. It would be built on five principle elements: (1) registration, (2) compliance review, (3) recognition, (4) monitoring and enforcement, and (5) public participation. The Safe Harbor would create many benefits for researchers, countries, and the general public, and may eventually have application beyond (gen)omics to other areas of biomedical research that increasingly engage in secondary use of data and present only negligible risks.

To develop and validate VisCap, a software program targeted to clinical laboratories for inference and visualization of germ-line copy-number variants (CNVs) from targeted next-generation sequencing data.

Genomic medicine applications have the potential to considerably improve health care in developing countries in the coming years. However, if developing countries do not improve their capacity for research and development (R&D) in the field, they might be left out of the genomics revolution. Large-scale and widely accessible databases for storing and analyzing genomic data are crucial tools for the advancement of genomic medicine. Building developing countries' capacity in genomics is accordingly closely linked to their involvement in international human genomics research initiatives. The purpose of this paper is to conduct a pilot study on the impact of international open science genomics projects on capacity building in R&D in developing countries. Using indicators we developed in previous work to measure the performance of international open science genomics projects, we analyse the policies and practices of four key projects in the field: the International HapMap Project, the Human Heredity and Health in Africa Initiative, the Malaria Genomic Epidemiology Network and the Structural Genomics Consortium. The results show that these projects play an important role in genomics capacity building in developing countries, but play a more limited role with regard to the potential redistribution of the benefits of research to the populations of these countries. We further suggest concrete initiatives that could facilitate the involvement of researchers from developing countries in the international genomics research community and accelerate capacity building in the developing world.

Great uncertainty exists about the costs associated with whole-genome sequencing (WGS).

As clinical testing for Mendelian causes of colorectal cancer (CRC) is largely driven by recognition of family history and early age of onset, the rates of such findings among individuals with prevalent CRC not recognized to have these features is largely unknown. We evaluated actionable genomic findings in community-based participants ascertained by three phenotypes: (1) CRC, (2) one or more adenomatous colon polyps, and (3) control participants over age 59 years without CRC or colon polyps. These participants underwent sequencing for a panel of genes that included colorectal cancer/polyp (CRC/P)-associated and actionable incidental findings genes. Those with CRC had a 3.8% rate of positive results (pathogenic or likely pathogenic) for a CRC-associated gene variant, despite generally being older at CRC onset (mean 72 years). Those ascertained for polyps had a 0.8% positive rate and those with no CRC/P had a positive rate of 0.2%. Though incidental finding rates unrelated to colon cancer were similar for all groups, our positive rate for cardiovascular findings exceeds disease prevalence, suggesting that variant interpretation challenges or low penetrance in these genes. The rate of HFE c.845G>A (p.Cys282Tyr) homozygotes in the CRC group reinforces a previously reported, but relatively unexplored, association between hemochromatosis and CRC. These results in a general clinical population suggest that current testing strategies could be improved in order to better detect Mendelian CRC-associated conditions. These data also underscore the need for additional functional and familial evidence to clarify the pathogenicity and penetrance of variants deemed pathogenic or likely pathogenic, particularly among the actionable genes associated with cardiovascular disease.

Congenital anomalies of the kidney and urinary tract (CAKUT) constitute one of the most frequent birth defects and represent the most common cause of chronic kidney disease in the first three decades of life. Despite the discovery of dozens of monogenic causes of CAKUT, most pathogenic pathways remain elusive. We performed whole-exome sequencing (WES) in 551 individuals with CAKUT and identified a heterozygous de novo stop-gain variant in ZMYM2 in two different families with CAKUT. Through collaboration, we identified in total 14 different heterozygous loss-of-function mutations in ZMYM2 in 15 unrelated families. Most mutations occurred de novo, indicating possible interference with reproductive function. Human disease features are replicated in X. tropicalis larvae with morpholino knockdowns, in which expression of truncated ZMYM2 proteins, based on individual mutations, failed to rescue renal and craniofacial defects. Moreover, heterozygous Zmym2-deficient mice recapitulated features of CAKUT with high penetrance. The ZMYM2 protein is a component of a transcriptional corepressor complex recently linked to the silencing of developmentally regulated endogenous retrovirus elements. Using protein-protein interaction assays, we show that ZMYM2 interacts with additional epigenetic silencing complexes, as well as confirming that it binds to FOXP1, a transcription factor that has also been linked to CAKUT. In summary, our findings establish that loss-of-function mutations of ZMYM2, and potentially that of other proteins in its interactome, as causes of human CAKUT, offering new routes for studying the pathogenesis of the disorder.

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

Although there are a number of online platforms for patient-level clinical trial data sharing from industry sponsors, they are not very harmonized regarding the role of local ethics approval in the research proposal review process. The first and largest of these platforms is ClinicalStudyDataRequest.com (CSDR), which includes over three thousand trials from thirteen sponsors including GlaxoSmithKline, Novartis, Roche, Sanofi, and Bayer. CSDR asks applicants to state whether they have received ethics approval for their research proposal, but in most cases does not require that they submit evidence of approval. However, the website does require that applicants without ethical approval state the reason it was not required. In order to examine the perspectives of researchers on this topic, we coded every response to that question received by CSDR between June 2014 and February 2017. Of 111 applicants who stated they were exempt from ethics approval, 63% mentioned de-identification, 57% mentioned the use of existing data, 33% referred to local or jurisdictional regulations, and 20% referred to the approvals obtained by the original study. We conclude by examining the experience of CSDR within the broader context of the access mechanisms and policies currently being used by other data sharing platforms, and discuss how our findings might be used to help clinical trial data providers design clear and informative access documents.

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.

The ClinVar database is a useful tool for patients and physicians to view variant interpretations submitted by clinical and nonclinical labs. However, variants of uncertain significance (VUS) in ClinVar can pose a significant burden on patients. If possible, it is important to resolve discrepancies and uncertainties surrounding interpreted variants. Here we highlight a case of a family who received a report of a variant (c.622A>G, p.Ile208Val) in BRAF following prenatal RASopathy testing. The variant had been previously classified by our laboratory as a VUS, so the mother contacted our laboratory via ClinVar for further information, which prompted reevaluation of the variant. Multiple sources of case-level data as well as the presence of the variant in the general population yielded sufficient evidence to reclassify the variant as likely benign. This reclassification alleviated significant concern for the family, and the child was born healthy with no clinical manifestations of Noonan syndrome or a RASopathy.

Over 100 million research participants around the world have had research array-based genotyping (GT) or genome sequencing (GS), but only a small fraction of these have been offered return of actionable genomic findings (gRoR). Between 2017 and 2021, we analyzed genomic results from 36,417 participants in the Mass General Brigham Biobank and offered to confirm and return pathogenic and likely pathogenic variants (PLPVs) in 59 genes. Variant verification prior to participant recontact revealed that GT falsely identified PLPVs in 44.9% of samples, and GT failed to identify 72.0% of PLPVs detected in a subset of samples that were also sequenced. GT and GS detected verified PLPVs in 1% and 2.5% of the cohort, respectively. Of 256 participants who were alerted that they carried actionable PLPVs, 37.5% actively or passively declined further disclosure. 76.3% of those carrying PLPVs were unaware that they were carrying the variant, and over half of those met published professional criteria for genetic testing but had never been tested. This gRoR protocol cost approximately $129,000 USD per year in laboratory testing and research staff support, representing $14 per participant whose DNA was analyzed or $3,224 per participant in whom a PLPV was confirmed and disclosed. These data provide logistical details around gRoR that could help other investigators planning to return genomic results.

Medical genetic services are facing an unprecedented demand for counseling and testing for hereditary breast and ovarian cancer (HBOC) in a context of limited resources. To help resolve this issue, a collaborative oncogenetic model was recently developed and implemented at the CHU de Québec-Université Laval; Quebec; Canada. Here, we present the protocol of the C-MOnGene (Collaborative Model in OncoGenetics) study, funded to examine the context in which the model was implemented and document the lessons that can be learned to optimize the delivery of oncogenetic services. Within three years of implementation, the model allowed researchers to double the annual number of patients seen in genetic counseling. The average number of days between genetic counseling and disclosure of test results significantly decreased. Group counseling sessions improved participants' understanding of breast cancer risk and increased knowledge of breast cancer and genetics and a large majority of them reported to be overwhelmingly satisfied with the process. These quality and performance indicators suggest this oncogenetic model offers a flexible, patient-centered and efficient genetic counseling and testing for HBOC. By identifying the critical facilitating factors and barriers, our study will provide an evidence base for organizations interested in transitioning to an oncogenetic model integrated into oncology care; including teams that are not specialized but are trained in genetics.

Precision medicine faces many challenges, including the gap of knowledge between disease genetics and pharmacogenomics (PGx). Disease genetics interprets the pathogenicity of genetic variants for diagnostic purposes, while PGx investigates the genetic influences on drug responses. Ideally, the quality of health care would be improved from the point of disease diagnosis to drug prescribing if PGx is integrated with disease genetics in clinical care. However, PGx genes or variants are usually not reported as a secondary finding even if they are included in a clinical genetic test for diagnostic purposes. This happens even though the detection of PGx variants can provide valuable drug prescribing recommendations. One underlying reason is the lack of systematic classification of the knowledge overlap between PGx and disease genetics. Here, we address this issue by analyzing gene and genetic variant annotations from multiple expert-curated knowledge databases, including PharmGKB, CPIC, ClinGen and ClinVar. We further classified genes based on the strength of evidence supporting a gene's pathogenic role or PGx effect as well as the level of clinical actionability of a gene. Twenty-six genes were found to have pathogenic variation associated with germline diseases as well as strong evidence for a PGx association. These genes were classified into four sub-categories based on the distinct connection between the gene's pathogenic role and PGx effect. Moreover, we have also found thirteen RYR1 genetic variants that were annotated as pathogenic and at the same time whose PGx effect was supported by a preponderance of evidence and given drug prescribing recommendations. Overall, we identified a nontrivial number of gene and genetic variant overlaps between disease genetics and PGx, which laid out a foundation for combining PGx and disease genetics to improve clinical care from disease diagnoses to drug prescribing and adherence.

Genome sequencing is now available as a clinical test on the National Health Service (NHS) through the Genome Medicine Service (GMS). The GMS have set out an analytical strategy that predominantly filters genome data on a pre-selected gene panel(s). Whilst this approach reduces the number of variants requiring assessment by reporting laboratories, pathogenic variants outside of the gene panel applied may be missed, and candidate variants in novel genes are largely ignored. This study sought to compare a research exome analysis to an independent clinical genome analysis performed through the NHS for the same group of patients. When analysing the exome data, we applied a panel agnostic approach filtering for variants with Hi gh P athogenic Po tential (HiPPo) using ClinVar, allele frequency, and in silico prediction tools. We then compared this gene agnostic analysis to the panel-based approach as applied by the GMS to genome data. Later we restricted HiPPo variants to a panel of the Gene Curation Coalition (GenCC) morbid genes and compared the diagnostic yield with the variants filtered using the GMS strategy. 24 patients from 8 families underwent parallel research exome sequencing and GMS genome sequencing. HiPPo analysis applied to research exome data identified a similar number of variants as the gene panel-based approach applied by the GMS. GMS clinical genome analysis identified and returned 2 pathogenic variants and 3 variants of uncertain significance. HiPPo research exome analysis identified the same variants plus an additional pathogenic variant and a further 3 de novo variants of uncertain significance in novel genes, where case series and functional studies are underway. When HiPPo was restricted to GenCC disease genes (strong or definitive), the same pathogenic variants were identified yet statistically fewer variants required assessment to identify more diagnostic variants than reported by the GMS genome strategy. This gave a diagnostic rate per variant assessed of 20% for HiPPo restricted to GenCC versus 3% for the GMS panel-based approach. With plans to sequence 5 million more NHS patients, strategies are needed to optimise the full potential of genome data beyond gene panels whilst minimising the burden of variants that require clinical assessment.

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.

Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed.

We examined 454,712 exomes for genes associated with a wide spectrum of complex traits and common diseases and observed that rare, penetrant mutations in genes implicated by genome-wide association studies confer ∼10-fold larger effects than common variants in the same genes. Consequently, an individual at the phenotypic extreme and at the greatest risk for severe, early-onset disease is better identified by a few rare penetrant variants than by the collective action of many common variants with weak effects. By combining rare variants across phenotype-associated genes into a unified genetic risk model, we demonstrate superior portability across diverse global populations compared to common variant polygenic risk scores, greatly improving the clinical utility of genetic-based risk prediction.

A major obstacle faced by rare disease families is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years, and causal variants are identified in under 50%. The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing (GS) for diagnosis and gene discovery. Families are consented for sharing of sequence and phenotype data with researchers, allowing development of a Critical Assessment of Genome Interpretation (CAGI) community challenge, placing variant prioritization models head-to-head in a real-life clinical diagnostic setting.

To exploit contemporary sequencing technologies for targeted genetic analyses, we developed a hybridization enrichment strategy for DNA capture that uses PCR products as subgenomic traps. We applied this strategy to 115 kilobases of the human genome encompassing 47 genes implicated in cardiovascular disease. Massively parallel sequencing of captured subgenomic libraries interrogated 99.8% of targeted nucleotides >or=20 times ( approximately 40,000-fold enrichment), enabling sensitive and specific detection of sequence variation and copy-number variation.