Strategic vision for improving human health at The Forefront of Genomics

A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources

OBJECTIVE

The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings.

MATERIALS AND METHODS

Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy.

RESULTS

Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address.

DISCUSSION

Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

An Approach to Solving the Complex Clinicogenomic Data Landscape in Precision Oncology: Learnings From the Design of WAYFIND-R, a Global Precision Oncology Registry

Precision oncology, where patients are given therapies based on their genomic profile and disease trajectory, is rapidly evolving to become a pivotal part of cancer management, supported by regulatory approvals of biomarker-matched targeted therapies and cancer immunotherapies. However, next-generation sequencing (NGS)-based technologies have revealed an increasing number of molecular-based cancer subtypes with rare patient populations, leading to difficulties in executing/recruiting for traditional clinical trials. Therefore, approval of novel therapeutics based on traditional interventional studies may be difficult and time consuming, with delayed access to innovative therapies. Real-world data (RWD) that describe the patient journey in routine clinical practice can help elucidate the clinical utility of NGS-based genomic profiling, multidisciplinary case discussions, and targeted therapies. We describe key learnings from the setup of WAYFIND-R (NCT04529122), a first-of-its-kind global cancer registry collecting RWD from patients with solid tumors who have undergone NGS-based genomic profiling. The meaning of 'generalizability' and 'high quality' for RWD across different geographic areas was revisited, together with patient recruitment processes, and data sharing and privacy. Inspired by these learnings, WAYFIND-R's design will help physicians discuss patient treatment plans with their colleagues, improve understanding of the impact of treatment decisions/cancer care processes on patient outcomes, and provide a platform to support the design and conduct of further clinical/epidemiologic research. WAYFIND-R demonstrates user-friendly, electronic case report forms, standardized collection of molecular tumor board-based decisions, and a dashboard providing investigators with access to local cohort-level data and the ability to interact with colleagues or search the entire registry to find rare populations. Overall, WAYFIND-R will inform on best practice for NGS-based treatment decisions by clinicians, foster global collaborations between cancer centers and enable robust conclusions regarding outcome data to be drawn, improve understanding of disparities in patients' access to advanced diagnostics and therapies, and ultimately drive advances in precision oncology.

Strategies of inclusion: The tradeoffs of pursuing "baked in" diversity through place-based recruitment

US funding agencies have begun to institutionalize expectations that biomedical studies achieve defined thresholds for diversity among research participants, including in precision medicine research (PMR). In this paper, we examine how practices of recruitment have unfolded in the wake of these diversity mandates. We find that a very common approach to seeking diverse participants leverages understandings of spatial, geographic, and site diversity as proxies and access points for participant diversity. That is, PMR investigators recruit from a diverse sampling of geographic areas, neighborhoods, sites, and institutional settings as both opportunistic but also meaningful ways to "bake in" participant diversity. In this way, logics of geographic and institutional diversity shift the question from who to recruit, to where. However, despite seeing geographic and site diversity as social and scientific 'goods' in the abstract and as key to getting diverse participants, PMR teams told us that working with diverse sites was often difficult in practice due to constraints in funding, time, and personnel, and inadequate research infrastructures and capacity. Thus, the ways in which these geographic and institutional diversity strategies were implemented resulted ultimately in limiting the meaningful inclusion of populations and organizations that had not previously participated in biomedical research and reproduced the inclusion of institutions that are already represented. These prevailing assumptions about and practices of "baked-in" diversity in fact exacerbate and produce other forms of inequity, in research capacity and research representation. These findings underscore how structural inequities in research resources must be addressed for diversity to be achieved in both research sites and research participants.

Addressing the routine failure to clinically identify monogenic cases of common disease

Changes in medical practice are needed to improve the diagnosis of monogenic forms of selected common diseases. This article seeks to focus attention on the need for universal genetic testing in common diseases for which the recommended clinical management of patients with specific monogenic forms of disease diverges from standard management and has evidence for improved outcomes.We review evidence from genomic screening of large patient cohorts, which has confirmed that important monogenic case identification failures are commonplace in routine clinical care. These case identification failures constitute diagnostic misattributions, where the care of individuals with monogenic disease defaults to the treatment plan offered to those with polygenic or non-genetic forms of the disease.The number of identifiable and actionable monogenic forms of common diseases is increasing with time. Here, we provide six examples of common diseases for which universal genetic test implementation would drive improved care. We examine the evidence to support genetic testing for common diseases, and discuss barriers to widespread implementation. Finally, we propose recommendations for changes to genetic testing and care delivery aimed at reducing diagnostic misattributions, to serve as a starting point for further evaluation and development of evidence-based guidelines for implementation.

Interpreting ciliopathy-associated missense variants of uncertain significance (VUS) in Caenorhabditis elegans

Better methods are required to interpret the pathogenicity of disease-associated variants of uncertain significance (VUS), which cannot be actioned clinically. In this study, we explore the use of an animal model (Caenorhabditis elegans) for in vivo interpretation of missense VUS alleles of TMEM67, a cilia gene associated with ciliopathies. CRISPR/Cas9 gene editing was used to generate homozygous knock-in C. elegans worm strains carrying TMEM67 patient variants engineered into the orthologous gene (mks-3). Quantitative phenotypic assays of sensory cilia structure and function (neuronal dye filling, roaming and chemotaxis assays) measured how the variants impacted mks-3 gene function. Effects of the variants on mks-3 function were further investigated by looking at MKS-3::GFP localization and cilia ultrastructure. The quantitative assays in C. elegans accurately distinguished between known benign (Asp359Glu, Thr360Ala) and known pathogenic (Glu361Ter, Gln376Pro) variants. Analysis of eight missense VUS generated evidence that three are benign (Cys173Arg, Thr176Ile and Gly979Arg) and five are pathogenic (Cys170Tyr, His782Arg, Gly786Glu, His790Arg and Ser961Tyr). Results from worms were validated by a genetic complementation assay in a human TMEM67 knock-out hTERT-RPE1 cell line that tests a TMEM67 signalling function. We conclude that efficient genome editing and quantitative functional assays in C. elegans make it a tractable in vivo animal model for rapid, cost-effective interpretation of ciliopathy-associated missense VUS alleles.

Global health systems' data science approach for precision diagnosis of sepsis in early life

Neonates and children in low-income and middle-income countries (LMICs) contribute to the highest number of sepsis-associated deaths globally. Interventions to prevent sepsis mortality are hampered by a lack of comprehensive epidemiological data and pathophysiological understanding of biological pathways. In this review, we discuss the challenges faced by LMICs in diagnosing sepsis in these age groups. We highlight a role for multi-omics and health care data to improve diagnostic accuracy of clinical algorithms, arguing that health-care systems urgently need precision medicine to avoid the pitfalls of missed diagnoses, misdiagnoses, and overdiagnoses, and associated antimicrobial resistance. We discuss ethical, regulatory, and systemic barriers related to the collection and use of big data in LMICs. Technologies such as cloud computing, artificial intelligence, and medical tricorders might help, but they require collaboration with local communities. Co-partnering (joint equal development of technology between producer and end-users) could facilitate integration of these technologies as part of future care-delivery systems, offering a chance to transform the global management and prevention of sepsis for neonates and children.

Where is genetic medicine headed? Exploring the perspectives of Canadian genetic professionals on future trends using the Delphi method

Driven by technological and scientific advances, the landscape of genetic medicine is rapidly changing, which complicates strategic planning and decision-making in this area. To address this uncertainty, we sought to understand genetic professionals' opinions about the future of clinical genetic and genomic services in Canada. We used the Delphi method to survey Canadian genetic professionals about their perspectives on whether scenarios about changes in service delivery and the use of genomic testing would be broadly implemented in their jurisdiction by 2030. We conducted two survey rounds; the response rates were 32% (27/84) and 67% (18/27), respectively. The most likely scenario was the universal use of noninvasive prenatal screening. The least likely scenarios involved population-based genome-wide sequencing for unaffected individuals. Overall, the scenarios perceived as most likely were those that have existing evidence about their benefit and potential medical necessity, whereas scenarios were seen as unlikely if they involved emerging technologies. Participants expected that the need for genetic healthcare services would increase by 2030 owing to changes in clinical guidelines and increased use of genome-wide sequencing. This study highlights the uncertainty in the future of genetic and genomic service provision and contributes evidence that could be used to inform strategic planning in clinical genetics.

Identification of the hormetic dose-response and regulatory network of multiple metals co-exposure-related hypertension via integration of metallomics and adverse outcome pathways

Environmental stressors, including heavy metals, can be associated with hypertension development. However, little information regarding the dose-response relationship and toxicity mechanisms of metal mixtures with hypertension development is currently available. Therefore, we recruited 940 participants from six factories in northeastern China and measured the urinary concentrations of 19 metals. Then, we used Bayesian kernel machine regression (BKMR) to explore associations between metals co-exposure and hypertension. The BKMR model indicated a hermetic dose-response relationship between eight urinary metals (Co, Cr, Ni, Cd, As, Fe, Zn, and Pb) and hypertension risk. Moreover, heterogeneous and non-linear association patterns were detected across different metals/metalloids concentrations. Next, for the first time, we analyzed data of chemicals containing specific metal elements in the Comparative Toxicogenomics Database (CTD) from a disease perspective and provided insights from various biological levels to explain heavy metal co-exposure-related hypertension. On the molecular scale, 43 chemical components and 112 potential target genes were detected for metal exposure-related hypertension. Further, the network topology analysis indicated that target genes such as insulin (INS, degree = 78), albumin (ALB, degree = 74), renin (REN, degree = 71), interleukin-6 (IL6, degree = 70), endothelin 1 (EDN1, degree = 70), and endothelial nitric oxide synthase (NOS3, degree = 69) have a strong correlation with heavy metals co-exposure. Finally, we used integrative analyses in the adverse outcome pathway (AOP) wiki to analyze the co-exposure of heavy metals and hypertension and support an integrated metallomics approach. We selected the AOP 149 as the framework and found that the molecular initiating events (MIEs) of hypertension stems from the oxidation of AA residues on critical peptides of the NO pathway. The NOS3 was particularly promising since its subunit has three metal ion cross-linking domains with Zn²⁺, Fe²⁺, and Ga³⁺, which might serve as a binding site for heavy metal ions.

Multi-modality machine learning predicting Parkinson's disease

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Identification of human gene research articles with wrongly identified nucleotide sequences

Nucleotide sequence reagents underpin molecular techniques that have been applied across hundreds of thousands of publications. We have previously reported wrongly identified nucleotide sequence reagents in human research publications and described a semi-automated screening tool Seek & Blastn to fact-check their claimed status. We applied Seek & Blastn to screen >11,700 publications across five literature corpora, including all original publications in Gene from 2007 to 2018 and all original open-access publications in Oncology Reports from 2014 to 2018. After manually checking Seek & Blastn outputs for >3,400 human research articles, we identified 712 articles across 78 journals that described at least one wrongly identified nucleotide sequence. Verifying the claimed identities of >13,700 sequences highlighted 1,535 wrongly identified sequences, most of which were claimed targeting reagents for the analysis of 365 human protein-coding genes and 120 non-coding RNAs. The 712 problematic articles have received >17,000 citations, including citations by human clinical trials. Given our estimate that approximately one-quarter of problematic articles may misinform the future development of human therapies, urgent measures are required to address unreliable gene research articles.

Pharmacists Leading the Way to Precision Medicine: Updates to the Core Pharmacist Competencies in Genomics

Genomics is becoming an increasingly important part of health care, and pharmacists are well-positioned to be practice-based leaders in pharmacogenomics and precision medicine. Competencies available through the Genetics/Genomics Competency Center provide a framework for pharmacogenomics instruction in both pharmacy school curricula and continuing education programs. Given the significant advancements in pharmacogenomics over the past decade, the 2019-2020 American Association of Colleges of Pharmacy Pharmacogenomics Special Interest Group updated the pharmacist competencies. The process used a systematic approach which included mapping pharmacogenomics-specific competencies to the entrustable professional activities for pharmacists and seeking consensus from key stakeholders. The result is an expansion to 30 competencies that reflect the contemporary roles pharmacists play in the application of pharmacogenomics in clinical practice. When implemented into curricula, these competencies will ensure that learners are "practice ready" to integrate pharmacogenomics into patient care. Additional postgraduate training is needed for advanced roles in pharmacogenomics implementation, education, and research.

Ultra-deep Sequencing of Hadza Hunter-Gatherers Recovers Vanishing Microbes.. [PMID: 36238714 PMCID: PMC9558438 DOI: 10.1101/2022.03.30.486478]

The gut microbiome is a key modulator of immune and metabolic health. Human microbiome data is biased towards industrialized populations, providing limited understanding of the distinct and diverse non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing and strain cultivation on 351 fecal samples from the Hadza, hunter-gatherers in Tanzania, and comparative populations in Nepal and California. We recover 94,971 total genomes of bacteria, archaea, bacteriophages, and eukaryotes, 43% of which are absent from existing unified datasets. Analysis of in situ growth rates, genetic pN/pS signatures, high-resolution strain tracking, and 124 gut-resident species vanishing in industrialized populations reveals differentiating dynamics of the Hadza gut microbiome. Industrialized gut microbes are enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource that expands our understanding of microbes capable of colonizing the human gut and clarifies the extensive perturbation brought on by the industrialized lifestyle.

Bibliometric review of ATAC-Seq and its application in gene expression

With recent advances in high-throughput next-generation sequencing, it is possible to describe the regulation and expression of genes at multiple levels. An assay for transposase-accessible chromatin using sequencing (ATAC-seq), which uses Tn5 transposase to sequence protein-free binding regions of the genome, can be combined with chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) and ribonucleic acid sequencing (RNA-seq) to provide a detailed description of gene expression. Here, we reviewed the literature on ATAC-seq and described the characteristics of ATAC-seq publications. We then briefly introduced the principles of RNA-seq, ChIP-seq and ATAC-seq, focusing on the main features of the techniques. We built a phylogenetic tree from species that had been previously studied by using ATAC-seq. Studies of Mus musculus and Homo sapiens account for approximately 90% of the total ATAC-seq data, while other species are still in the process of accumulating data. We summarized the findings from human diseases and other species, illustrating the cutting-edge discoveries and the role of multi-omics data analysis in current research. Moreover, we collected and compared ATAC-seq analysis pipelines, which allowed biological researchers who lack programming skills to better analyze and explore ATAC-seq data. Through this review, it is clear that multi-omics analysis and single-cell sequencing technology will become the mainstream approach in future research.

Beyond inclusion: Enacting team equity in precision medicine research

PURPOSE

To identify meanings of and challenges to enacting equitable diversification of genomics research, and specifically precision medicine research (PMR), teams.

METHODS

We conducted in-depth interviews with 102 individuals involved in three U.S.-based precision medicine research consortia and conducted over 400 observation hours of their working group meetings, consortium-wide meetings, and conference presentations. We also reviewed published reports on genomic workforce diversity (WFD), particularly those relevant to the PMR community.

RESULTS

Our study finds that many PMR teams encounter challenges as they strive to achieve equitable diversification on scientific teams. Interviewees articulated that underrepresented team members were often hired to increase the study's capacity to recruit diverse research participants, but are limited to on-the-ground staff positions with little influence over study design. We find existing hierarchies and power structures in the academic research ecosystem compound challenges for equitable diversification.

CONCLUSION

Our results suggest that meaningful diversification of PMR teams will only be possible when team equity is prioritized as a core value in academic research communities.

The Utility of Genomic Testing for Hyperphenylalaninemia

Hyperphenylalaninemia (HPA), the most common amino acid metabolism disorder, is caused by defects in enzymes involved in phenylalanine metabolism, with the consequent accumulation of phenylalanine and its secondary metabolites in body fluids and tissues. Clinical manifestations of HPA include mental retardation, and its early diagnosis with timely treatment can improve the prognosis of affected patients. Due to the genetic complexity and heterogeneity of HPA, high-throughput molecular technologies, such as next-generation sequencing (NGS), are becoming indispensable tools to fully characterize the etiology, helping clinicians to promptly identify the exact patients’ genotype and determine the appropriate treatment. In this review, after a brief overview of the key enzymes involved in phenylalanine metabolism, we represent the wide spectrum of genes and their variants associated with HPA and discuss the utility of genomic testing for improved diagnosis and clinical management of HPA.

A framework for research into continental ancestry groups of the UK Biobank

BACKGROUND

The UK Biobank is a large prospective cohort, based in the UK, that has deep phenotypic and genomic data on roughly a half a million individuals. Included in this resource are data on approximately 78,000 individuals with "non-white British ancestry." While most epidemiology studies have focused predominantly on populations of European ancestry, there is an opportunity to contribute to the study of health and disease for a broader segment of the population by making use of the UK Biobank's "non-white British ancestry" samples. Here, we present an empirical description of the continental ancestry and population structure among the individuals in this UK Biobank subset.

RESULTS

Reference populations from the 1000 Genomes Project for Africa, Europe, East Asia, and South Asia were used to estimate ancestry for each individual. Those with at least 80% ancestry in one of these four continental ancestry groups were taken forward (N = 62,484). Principal component and K-means clustering analyses were used to identify and characterize population structure within each ancestry group. Of the approximately 78,000 individuals in the UK Biobank that are of "non-white British" ancestry, 50,685, 6653, 2782, and 2364 individuals were associated to the European, African, South Asian, and East Asian continental ancestry groups, respectively. Each continental ancestry group exhibits prominent population structure that is consistent with self-reported country of birth data and geography.

CONCLUSIONS

Methods outlined here provide an avenue to leverage UK Biobank's deeply phenotyped data allowing researchers to maximize its potential in the study of health and disease in individuals of non-white British ancestry.

Fetal therapies and trials for lysosomal storage diseases: a survey of attitudes of parents and patients

Background

Lysosomal storage diseases (LSDs) are inherited metabolic disorders that may lead to severe multi-organ disease. Current ERTs are limited by anti-drug antibodies, the blood–brain barrier, and early disease onset and progression before ERT is started. We have opened a phase I clinical trial of enzyme replacement therapy (ERT) for fetuses with LSDs (NCT04532047). We evaluated the attitudes of parents and patients with LSDs towards fetal clinical trials and therapies.

Methods

A multidisciplinary team designed a survey which was distributed by five international patient advocacy groups. We collected patients’ demographic, diagnostic, and treatment information. Associations between respondent characteristics and attitudes towards fetal therapies/trials were analyzed using multivariate ordinal logistic regression.

Results

The survey was completed by 181 adults from 19 countries. The majority of respondents were mothers from the United States. The most common diseases were MPS1 (26%), MPS3 (19%), and infantile-onset Pompe (14%). Most patients (88%) were diagnosed after birth, at a median of 21 months. Altogether, 65% of participating patients and children of participants had received ERT, 27% a stem cell transplant, and 4% gene therapy. We found that half (49%) of respondents were unlikely to terminate a future affected pregnancy, 55% would enroll in a phase I clinical trial for fetal ERT, and 46% would enroll in a fetal gene therapy trial. Respondents who received postnatal ERT were significantly more likely enroll in a trial for fetal ERT or gene therapy (ERT OR 4.48, 95% CI 2.13–9.44, p < 0.0001; gene therapy OR 3.03, 95% CI 1.43–6.43, p = 0.0038). Respondents who used clinicaltrials.gov as a main source of information were more likely to choose to participate in a fetal trial (ERT OR 2.43, 95% CI 1.18–5.01, p = 0.016; gene therapy OR 2.86, 95% CI 1.27–6.46, p = 0.011).

Conclusions

Familiarity with postnatal ERT increased respondents’ likelihood of pursuing fetal therapies. Families who use clinicaltrials.gov may be more receptive to innovative fetal treatments. The patient community has a favorable attitude towards fetal therapy; over half of respondents would enroll in a phase I clinical trial to assess the safety and efficacy of fetal ERT.

The QChip1 knowledgebase and microarray for precision medicine in Qatar

Risk genes for Mendelian (single-gene) disorders (SGDs) are consistent across populations, but pathogenic risk variants that cause SGDs are typically population-private. The goal was to develop "QChip1," an inexpensive genotyping microarray to comprehensively screen newborns, couples, and patients for SGD risk variants in Qatar, a small nation on the Arabian Peninsula with a high degree of consanguinity. Over 108 variants in 8445 Qatari were identified for inclusion in a genotyping array containing 165,695 probes for 83,542 known and potentially pathogenic variants in 3438 SGDs. QChip1 had a concordance with whole-genome sequencing of 99.1%. Testing of QChip1 with 2707 Qatari genomes identified 32,674 risk variants, an average of 134 pathogenic alleles per Qatari genome. The most common pathogenic variants were those causing homocystinuria (1.12% risk allele frequency), and Stargardt disease (2.07%). The majority (85%) of Qatari SGD pathogenic variants were not present in Western populations such as European American, South Asian American, and African American in New York City and European and Afro-Caribbean in Puerto Rico; and only 50% were observed in a broad collection of data across the Greater Middle East including Kuwait, Iran, and United Arab Emirates. This study demonstrates the feasibility of developing accurate screening tools to identify SGD risk variants in understudied populations, and the need for ancestry-specific SGD screening tools.

Neural network classifiers for images of genetic conditions with cutaneous manifestations

Neural networks have shown strong potential in research and in healthcare. Mainly due to the need for large datasets, these applications have focused on common medical conditions, where more data are typically available. Leveraging publicly available data, we trained a neural network classifier on images of rare genetic conditions with skin findings. We used approximately 100 images per condition to classify 6 different genetic conditions. We analyzed both preprocessed images that were cropped to show only the skin lesions as well as more complex images showing features such as the entire body segment, the person, and/or the background. The classifier construction process included attribution methods to visualize which pixels were most important for computer-based classification. Our classifier was significantly more accurate than pediatricians or medical geneticists for both types of images and suggests steps for further research involving clinical scenarios and other applications.

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types.

When Not to Ask: A Defense of Choice-Masking Nudges in Medical Research

In this article, we examine the legality and ethics of a controversial but widespread practice in clinical research: choice-masking nudges. A choice-masking nudge (CMN) exists when a research team explicitly obscures a meaningful choice from participants by presenting a default decision as the standard way forward. Even though an easy-to-use opt-out mechanism is available for participants who independently express concerns with the standard default, the fact that a default has been pre-selected is not made obvious to research participants. To opt out of the nudge, a participant must overtly request non-standard treatment. We argue that use of such nudges in medical research can be justified by their individual, collective, and social benefits, provided that they respect autonomy and satisfy our four further acceptability conditions. The structure of this Article is as follows. In Part II, we describe three controversial cases of CMNs in medical research. In Part III, we provide background on nudging and explain how our proposed CMNs fit into the existing literature on nudging and libertarian paternalism. In Part IV, we explain how the reasonable person standard as employed by United States research regulations can be used to support CMNs. In Part IV, we anticipate some of the strongest objections to CMNs by explaining how CMNs are compatible with a wide range of plausible accounts of autonomy. Finally, in Part VI, we discuss four additional core considerations an acceptable CMN must meet: legitimate policy goals; benefits outweighing harms; burdens distributed fairly; and absence of ethically superior feasible alternatives. We also analyze the three existing controversies explored in Part II and show how each would benefit from the conceptual clarity offered by our analytic framework. Medical research is complicated and can be difficult for participants to understand; thoughtfully designed CMNs can play an important role in gently guiding large numbers of research participants toward decision outcomes that really are best for them and their communities.

Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization

The combination of diverse data types and analysis tasks in genomics has resulted in the development of a wide range of visualization techniques and tools. However, most existing tools are tailored to a specific problem or data type and offer limited customization, making it challenging to optimize visualizations for new analysis tasks or datasets. To address this challenge, we designed Gosling-a grammar for interactive and scalable genomics data visualization. Gosling balances expressiveness for comprehensive multi-scale genomics data visualizations with accessibility for domain scientists. Our accompanying JavaScript toolkit called Gosling.js provides scalable and interactive rendering. Gosling.js is built on top of an existing platform for web-based genomics data visualization to further simplify the visualization of common genomics data formats. We demonstrate the expressiveness of the grammar through a variety of real-world examples. Furthermore, we show how Gosling supports the design of novel genomics visualizations. An online editor and examples of Gosling.js, its source code, and documentation are available at https://gosling.js.org.

Barriers and Facilitators for Population Genetic Screening in Healthy Populations: A Systematic Review

Studies suggest that 1-3% of the general population in the United States unknowingly carry a genetic risk factor for a common hereditary disease. Population genetic screening is the process of offering otherwise healthy patients in the general population testing for genomic variants that predispose them to diseases that are clinically actionable, meaning that they can be prevented or mitigated if they are detected early. Population genetic screening may significantly reduce morbidity and mortality from these diseases by informing risk-specific prevention or treatment strategies and facilitating appropriate participation in early detection. To better understand current barriers, facilitators, perceptions, and outcomes related to the implementation of population genetic screening, we conducted a systematic review and searched PubMed, Embase, and Scopus for articles published from date of database inception to May 2020. We included articles that 1) detailed the perspectives of participants in population genetic screening programs and 2) described the barriers, facilitators, perceptions, and outcomes related to population genetic screening programs among patients, healthcare providers, and the public. We excluded articles that 1) focused on direct-to-consumer or risk-based genetic testing and 2) were published before January 2000. Thirty articles met these criteria. Barriers and facilitators to population genetic screening were organized by the Social Ecological Model and further categorized by themes. We found that research in population genetic screening has focused on stakeholder attitudes with all included studies designed to elucidate individuals' perceptions. Additionally, inadequate knowledge and perceived limited clinical utility presented a barrier for healthcare provider uptake. There were very few studies that conducted long-term follow-up and evaluation of population genetic screening. Our findings suggest that these and other factors, such as prescreen counseling and education, may play a role in the adoption and implementation of population genetic screening. Future studies to investigate macro-level determinants, strategies to increase provider buy-in and knowledge, delivery models for prescreen counseling, and long-term outcomes of population genetic screening are needed for the effective design and implementation of such programs. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020198198.

Genetic correction strategies for Duchenne Muscular Dystrophy and their impact on the heart

Background

Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder with early childhood onset characterized by profound loss of muscle strength and associated cardiomyopathy. DMD affects is most often caused by deletions involving single or multiple exons that disrupt the open reading frame of the DMD gene. Mutations causing loss or premature truncation of dystrophin result in dystrophin protein deficiency, which renders the plasma membrane of skeletal myofibers and cardiomyocytes weakened.

Aim of Review

Genetic correction is in use to treat DMD, since several drugs have been already approved which partially restore dystrophin production through the use of antisense oligonucleotides. There are multiple ongoing clinical trials to evaluate the efficacy of treating DMD with micro-dystrophins delivered by adeno-associated viruses. Future approaches entail gene editing to target the single copy of the DMD gene on the X-chromosome. The primary, near-term goal is restoration of skeletal muscle dystrophin, and for some of these treatments, the efficacy in the heart is not fully known. Here, we discuss the anticipated cardiac outcomes of dystrophin-targeted therapies, and how this information informs genomic medicine for cardiomyopathies, especially in childhood.

Key Scientific Concepts of Review

Many genetic treatment strategies are being implemented to treat DMD. Since most preclinical testing has focused on skeletal muscle, there is a gap in knowledge about the expected effects of these approaches on cardiac genetic correction and cardiomyopathy progression in DMD. Additional study is needed.

Evolving use of ancestry, ethnicity, and race in genetics research-A survey spanning seven decades

To inform continuous and rigorous reflection about the description of human populations in genomics research, this study investigates the historical and contemporary use of the terms "ancestry," "ethnicity," "race," and other population labels in The American Journal of Human Genetics from 1949 to 2018. We characterize these terms' frequency of use and assess their odds of co-occurrence with a set of social and genetic topical terms. Throughout The Journal's 70-year history, "ancestry" and "ethnicity" have increased in use, appearing in 33% and 26% of articles in 2009-2018, while the use of "race" has decreased, occurring in 4% of articles in 2009-2018. Although its overall use has declined, the odds of "race" appearing in the presence of "ethnicity" has increased relative to the odds of occurring in its absence. Forms of population descriptors "Caucasian" and "Negro" have largely disappeared from The Journal (<1% of articles in 2009-2018). Conversely, the continental labels "African," "Asian," and "European" have increased in use and appear in 18%, 14%, and 42% of articles from 2009-2018, respectively. Decreasing uses of the terms "race," "Caucasian," and "Negro" are indicative of a transition away from the field's history of explicitly biological race science; at the same time, the increasing use of "ancestry," "ethnicity," and continental labels should serve to motivate ongoing reflection as the terminology used to describe genetic variation continues to evolve.

Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project

BACKGROUND

Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications.

MATERIALS AND METHODS

Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values.

RESULTS

Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples.

CONCLUSIONS

Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

Genomic medicine in the Middle East

We discuss the current state of genomic medicine in Arab countries of the Middle East, a region with outsized contribution to Mendelian genetics due to inbreeding yet has poor representation in global variome datasets. We focus on genomic testing, clinical genetics, and genetic counseling services along with associated training and research programs. Finally, we highlight opportunities for improvement in genomic medicine services in this region.

The difficulties of broad data sharing in genomic medicine: Empirical evidence from diverse participants in prenatal and pediatric clinical genomics research

PURPOSE

This study aimed to understand broad data sharing decisions among predominantly underserved families participating in genomic research.

METHODS

Drawing on clinic observations, semistructured interviews, and survey data from prenatal and pediatric families enrolled in a genomic medicine study focused on historically underserved and underrepresented populations, this paper expands empirical evidence regarding genomic data sharing communication and decision-making.

RESULTS

One-third of parents declined to share family data, and pediatric participants were significantly more likely to decline than prenatal participants. The pediatric population was significantly more socioeconomically disadvantaged and more likely to require interpreters. Opt-in was tied to altruism and participants' perception that data sharing was inherent to research participation. Opt-out was associated with privacy concerns and influenced by clinical staff's presentation of data handling procedures. The ability of participants to make informed choices during enrollment about data sharing was weakened by suboptimal circumstances, which was revealed by poor understanding of data sharing in follow-up interviews as well as discrepancies between expressed participant desires and official recorded choices.

CONCLUSION

These empirical data suggest that the context within which informed consent process is conducted in clinical genomics may be inadequate for respecting participants' values and preferences and does not support informed decision-making processes.

Mitochondrial "dysmorphology" in variant classification

Mitochondrial disorders are challenging to diagnose. Exome sequencing has greatly enhanced the diagnostic precision of these disorders although interpreting variants of uncertain significance (VUS) remains a formidable obstacle. Whether specific mitochondrial morphological changes can aid in the classification of these variants is unknown. Here, we describe two families (four patients), each with a VUS in a gene known to affect the morphology of mitochondria through a specific role in the fission-fusion balance. In the first, the missense variant in MFF, encoding a fission factor, was associated with impaired fission giving rise to a characteristically over-tubular appearance of mitochondria. In the second, the missense variant in DNAJA3, which has no listed OMIM phenotype, was associated with fragmented appearance of mitochondria consistent with its published deficiency states. In both instances, the highly specific phenotypes allowed us to upgrade the classification of the variants. Our results suggest that, in select cases, mitochondrial "dysmorphology" can be helpful in interpreting variants to reach a molecular diagnosis.

Racial and Ethnic Disparities Among Participants in Precision Oncology Clinical Studies

IMPORTANCE

Precision oncology is revolutionizing cancer care, allowing for personalized treatments to improve outcomes. Cancer research has benefitted from well-designed studies incorporating precision medicine objectives, but it is unclear if these studies are representative of the diverse cancer population.

OBJECTIVE

To evaluate racial and ethnic representation in breast, prostate, lung, and colorectal cancer studies incorporating precision oncology objectives in the Clinicaltrials.gov registry and compare with the incidence of these cancer types in racial and ethnic minority groups in the US population.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study identified US-based breast, prostate, lung, and colorectal cancer studies incorporating precision oncology objectives for reporting of race and ethnicity. The Surveillance, Epidemiology, and End Results and US Census databases were used to determine cancer incidence by race and ethnicity, linked with cancer type and median year of enrollment for each trial. Data were collected and analyzed between December 2020 and April 2021.

MAIN OUTCOMES AND MEASURES

The expected number of participants per study by each racial and ethnic group was calculated based on the corresponding US-based proportion. Under- and overrepresentation was defined as the ratio of the actual number of enrolled cases to the expected number of cases for each trial by cancer type. Ratios above 1 indicated overrepresentation while a ratio below 1 indicated underrepresentation. Random-effects meta-analysis of representation ratios of individual trials was performed to weigh each individual study.

RESULTS

Of 93 studies encompassing 5867 enrollees with race and ethnicity data; 4826 participants (82.3%) were non-Hispanic White, 587 (10.0%) were Black, and 238 (4.1%) were Asian. Per observed-to-expected ratios, White participants were overrepresented in all studies, with a ratio of 1.35 (95% CI, 1.30-1.37), as well as Asian participants, with a ratio of 1.46 (95% CI, 1.28-1.66), while Black participants (ratio, 0.49; 95% CI, 0.45-0.54), Hispanic participants (ratio, 0.24; 95% CI, 0.20-0.28), and American Indian and Alaskan Native participants (ratio, 0.43; 95% CI, 0.24-0.78) were underrepresented. By individual cancer site, White participants were consistently overrepresented in all studies, while Black and Hispanic participants were underrepresented.

CONCLUSIONS AND RELEVANCE

This analysis found that precision oncology studies for breast, lung, prostate, and colorectal cancers vastly underrepresent racial and ethnic minority populations relative to their cancer incidence in the US population. It is imperative to increase diversity among enrollees so that all individuals may benefit from cancer research breakthroughs and personalized treatments.

Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects

Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass.Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990'sThe paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population.The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.

Metabolomics for Crop Breeding: General Considerations

The development of new, more productive varieties of agricultural crops is becoming an increasingly difficult task. Modern approaches for the identification of beneficial alleles and their use in elite cultivars, such as quantitative trait loci (QTL) mapping and marker-assisted selection (MAS), are effective but insufficient for keeping pace with the improvement of wheat or other crops. Metabolomics is a powerful but underutilized approach that can assist crop breeding. In this review, basic methodological information is summarized, and the current strategies of applications of metabolomics related to crop breeding are explored using recent examples. We briefly describe classes of plant metabolites, cellular localization of metabolic pathways, and the strengths and weaknesses of the main metabolomics technique. Among the commercialized genetically modified crops, about 50 with altered metabolic enzyme activities have been identified in the International Service for the Acquisition of Agri-biotech Applications (ISAAA) database. These plants are reviewed as encouraging examples of the application of knowledge of biochemical pathways. Based on the recent examples of metabolomic studies, we discuss the performance of metabolic markers, the integration of metabolic and genomic data in metabolic QTLs (mQTLs) and metabolic genome-wide association studies (mGWAS). The elucidation of metabolic pathways and involved genes will help in crop breeding and the introgression of alleles of wild relatives in a more targeted manner.

The National Academies' Roundtable on Genomics and Precision Health: Where we have been and where we are heading

The clinical application of genetics and genomics to advance precision health is one of the most dynamic and promising areas of medicine. In 2020, building on nearly 15 years of work, the Roundtable on Genomics and Precision Health of the National Academies of Sciences, Engineering, and Medicine undertook a strategic planning process to assess its strengths, consider the current challenges facing the field, and set out new goals for its future work. As a result, the Roundtable has updated its vision and mission and prioritized four major areas of inquiry-innovation, dialogue, equity, and adoption-while keeping true to its founding goal of providing a neutral convening space for the diversity of stakeholders in genomics and precision health. The Roundtable is unique for its breadth of membership and is committed to fostering a new era for precision health built on decades of expanding knowledge and the emergence of new technologies. To achieve its goals, the Roundtable seeks to broaden its membership's diversity and to engage with new audiences. Roundtable members explore how evidence-based discoveries in genomics could be adopted and used in innovative ways to better serve human health, how equitable access to genomic and precision health technologies can be ensured, and how the Roundtable and broader genomics and precision health community can communicate more effectively to inform the public regarding genomics and precision health. As a first principle, the Roundtable is working to support the overall goal that all people benefit from genomics for precision health.

The National Academies' Roundtable on Genomics and Precision Health: Where we have been and where we are heading

The clinical application of genetics and genomics to advance precision health is one of the most dynamic and promising areas of medicine. In 2020, building on nearly 15 years of work, the Roundtable on Genomics and Precision Health of the National Academies of Sciences, Engineering, and Medicine undertook a strategic planning process to assess its strengths, consider the current challenges facing the field, and set out new goals for its future work. As a result, the Roundtable has updated its vision and mission and prioritized four major areas of inquiry-innovation, dialogue, equity, and adoption-while keeping true to its founding goal of providing a neutral convening space for the diversity of stakeholders in genomics and precision health. The Roundtable is unique for its breadth of membership and is committed to fostering a new era for precision health built on decades of expanding knowledge and the emergence of new technologies. To achieve its goals, the Roundtable seeks to broaden its membership's diversity and to engage with new audiences. Roundtable members explore how evidence-based discoveries in genomics could be adopted and used in innovative ways to better serve human health, how equitable access to genomic and precision health technologies can be ensured, and how the Roundtable and broader genomics and precision health community can communicate more effectively to inform the public regarding genomics and precision health. As a first principle, the Roundtable is working to support the overall goal that all people benefit from genomics for precision health.

The Propagation of Racial Disparities in Cardiovascular Genomics Research

Genomics research has improved our understanding of the genetic basis for human traits and diseases. This progress is now being translated into clinical care as we move toward a future of precision medicine. Many hope that expanded use of genomic testing will improve disease screening, diagnosis, risk stratification, and treatment. In many respects, cardiovascular medicine is leading this charge. However, most cardiovascular genomics research has been conducted in populations of primarily European ancestry. This bias has critical downstream effects. Here, we review the current disparities in cardiovascular genomics research, and we outline how these disparities propagate forward through all phases of the translational pipeline. If not adequately addressed, biases in genomics research will further compound the existing health disparities that face underrepresented and marginalized populations.

Decision-making about genetic health information among family dyads: a systematic literature review

Decisions involving two individuals (i.e., dyadic decision-making) have been increasingly studied in healthcare research. There is evidence of bi-directional influences in decision-making processes among spousal, provider-patient and parent-child dyads. Genetic information can directly impact biologically related individuals. Thus, it is important to understand dyadic decision-making about genetic health information among family members. This systematic literature review aimed to identify literature examining decision-making among family dyads. Peer-reviewed publications were included if they reported quantitative empirical research on dyadic decision-making about genetic information, published between January 1998 and August 2020 and written in English. The search was conducted in 6 databases and returned 3167 articles, of which 15 met the inclusion criteria. Most studies were in the context of cancer genetic testing (n = 8) or reproductive testing or screening (n = 5). Studies reported two broad categories of decisions with dyadic influence: undergoing screening or testing (n = 10) and sharing information with family (n = 5). Factors were correlated between dyads such as attitudes, knowledge, behaviors and psychological wellbeing. Emerging evidence shows that dyad members influence each other when making decisions about receiving or sharing genetic information. Our findings emphasize the importance of considering both members of a dyad in intervention design and clinical interactions.

Prognostic value of polygenic risk scores for adults with psychosis

Polygenic risk scores (PRS) summarize genetic liability to a disease at the individual level, and the aim is to use them as biomarkers of disease and poor outcomes in real-world clinical practice. To date, few studies have assessed the prognostic value of PRS relative to standards of care. Schizophrenia (SCZ), the archetypal psychotic illness, is an ideal test case for this because the predictive power of the SCZ PRS exceeds that of most other common diseases. Here, we analyzed clinical and genetic data from two multi-ethnic cohorts totaling 8,541 adults with SCZ and related psychotic disorders, to assess whether the SCZ PRS improves the prediction of poor outcomes relative to clinical features captured in a standard psychiatric interview. For all outcomes investigated, the SCZ PRS did not improve the performance of predictive models, an observation that was generally robust to divergent case ascertainment strategies and the ancestral background of the study participants.

Genomics governance: advancing justice, fairness and equity through the lens of the African communitarian ethic of Ubuntu

There is growing interest for a communitarian approach to the governance of genomics, and for such governance to be grounded in principles of justice, equity and solidarity. However, there is a near absence of conceptual studies on how communitarian-based principles, or values, may inform, support or guide the governance of genomics research. Given that solidarity is a key principle in Ubuntu, an African communitarian ethic and theory of justice, there is emerging interest about the extent to which Ubuntu could offer guidance for the governance of genomics research in Africa. To this effect, we undertook a conceptual analysis of Ubuntu with the goal of identifying principles that could inform equity-oriented governance of genomics research. Solidarity, reciprocity, open sharing, accountability, mutual trust, deliberative decision-making and inclusivity were identified as core principles that speak directly to the different macro-level ethical issues in genomics research in Africa such as: the exploitation of study populations and African researchers, equitable access and use of genomics data, benefit sharing, the possibility of genomics to widen global health inequities and the fair distribution of resources such as intellectual property and patents. We use the identified the principles to develop ethical guidance for genomics governance in Africa.

Perception of personalized medicine, pharmacogenomics, and genetic testing among undergraduates in Hong Kong

BACKGROUND

The global development and advancement of genomic medicine in the recent decade has accelerated the implementation of personalized medicine (PM) and pharmacogenomics (PGx) into clinical practice, while catalyzing the emergence of genetic testing (GT) with relevant ethical, legal, and social implications (ELSI).

RESULTS

The perception of university undergraduates with regards to PM and PGx was investigated, and 80% of undergraduates valued PM as a promising healthcare model with 66% indicating awareness of personal genome testing companies. When asked about the curriculum design towards PM and PGx, compared to undergraduates in non-medically related curriculum, those studying in medically related curriculum had an adjusted 7.2 odds of perceiving that their curriculum was well-designed for learning PGx (95% CI 3.6-14.6) and a 3.7 odds of perceiving that PGx was important in their study (95% CI 2.0-6.8). Despite this, only 16% of medically related curriculum undergraduates would consider embarking on future education on PM. When asked about their perceptions on GT, 60% rated their genetic knowledge as "School Biology" level or below while 76% would consider undergoing a genetic test. As for ELSI, 75% of undergraduates perceived that they were aware of ethical issues of GT in general, particularly on "Patient Privacy" (80%) and "Data Confidentiality" (68%). Undergraduates were also asked about their perceived reaction upon receiving an unfavorable result from GT, and over half of the participants perceived that they would feel "helpless or pessimistic" (56%), "inadequate or different" (59%), and "disadvantaged at job seeking" (59%), while older undergraduates had an adjusted 2.0 odds of holding the latter opinion (95% CI 1.1-3.5), compared to younger undergraduates.

CONCLUSION

Hong Kong undergraduates showed a high awareness of PM but insufficient genetic knowledge and low interest in pursuing a career towards PM. They were generally aware of ethical issues of GT and especially concerned about patient privacy and data confidentiality. There was a predominance of pessimistic views towards unfavorable testing results. This study calls for the attention to evaluate education and talent development on genomics, and update existing legal frameworks on genetic testing in Hong Kong.

Cancer Biomarkers in the era of precision oncology: Addressing the needs of patients and health systems

Cancer Biomarkers are the key to unlocking the promise of precision oncology, selecting which patients will respond to a more personalised treatment while sparing non-responders the therapy-related toxicity. In this paper, we highlight the primacy of cancer biomarkers, but focus on their importance to patients and to health systems. We also highlight how cancer biomarkers represent value for money. We emphasise the need for cancer biomarkers infrastructure to be embedded into European health systems. We also highlight the need to deploy multiple biomarker testing to deliver the optimal benefit for patients and health systems and consider cancer biomarkers from the perspective of cost, value and regulation. Cancer biomarkers must also be situated in the context of the upcoming In Vitro Diagnostics Regulation, which may pose certain challenges (e.g. non-compliance of laboratory developed tests, leading to cancer biomarker shortages and increased costs) that need to be overcome. Cancer biomarkers must be embedded in the real world of oncology delivery and testing must be implemented across Europe, with the intended aim of narrowing, not widening the inequity gap for patients. Cancer patients must be placed firmly at the centre of a cancer biomarker informed precision oncology care agenda.

Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision

Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.

Genetic counseling and testing for Asian Americans: a systematic review

PURPOSE

Asian Americans have been understudied in the literature on genetic and genomic services. The current study systematically identified, evaluated, and summarized findings from relevant qualitative and quantitative studies on genetic health care for Asian Americans.

METHODS

A search of five databases (1990 to 2018) returned 8,522 unique records. After removing duplicates, abstract/title screening, and full text review, 47 studies met inclusion criteria. Data from quantitative studies were converted into "qualitized data" and pooled together with thematic data from qualitative studies to produce a set of integrated findings.

RESULTS

Synthesis of results revealed that (1) Asian Americans are under-referred but have high uptake for genetic services, (2) linguistic/communication challenges were common and Asian Americans expected more directive genetic counseling, and (3) Asian Americans' family members were involved in testing decisions, but communication of results and risk information to family members was lower than other racial groups.

CONCLUSION

This study identified multiple barriers to genetic counseling, testing, and care for Asian Americans, as well as gaps in the research literature. By focusing on these barriers and filling these gaps, clinical genetic approaches can be tailored to meet the needs of diverse patient groups, particularly those of Asian descent.