Genetic analyses of diverse populations improves discovery for complex traits.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Medical genetics and genomic medicine in Japan.

Since 1961, all Japanese citizens have belonged to one of the available medical care insurance systems. This "universal care" system has contributed to the maintenance of health: the life expectancy at birth was 84 years in 2016, and the infant mortality rate (the number of infants dying before reaching 1 year of age) was 2.0 per 1,000 live births, which is one of the lowest rates in the world. The Japanese government initiated the National Program on Rare and Intractable Diseases in 1972. This program has promoted research and expanded support for patients with rare and intractable diseases. Registered patients are eligible for a subsidy scheme that helps to cover medical care costs. Among the 331 diseases that are currently included in this program, more than half of the diseases are Mendelian disorders. The National Program on Rare and Intractable Diseases has fostered research in medical genetics in Japan and many causative genes for Mendelian diseases have been identified by Japanese geneticists. Recently, the Japanese government has determined to support several genomic medicine initiatives including the undiagnosed disease program (Initiative on Rare and Undiagnosed Diseases) and pathogenic variant databases.

Integrating Genomics into Healthcare: A Global Responsibility.

Genomic sequencing is rapidly transitioning into clinical practice, and implementation into healthcare systems has been supported by substantial government investment, totaling over US$4 billion, in at least 14 countries. These national genomic-medicine initiatives are driving transformative change under real-life conditions while simultaneously addressing barriers to implementation and gathering evidence for wider adoption. We review the diversity of approaches and current progress made by national genomic-medicine initiatives in the UK, France, Australia, and US and provide a roadmap for sharing strategies, standards, and data internationally to accelerate implementation.

Genomic diagnostics within a medically underserved population: efficacy and implications.

PurposeWe integrated whole-exome sequencing (WES) and chromosomal microarray analysis (CMA) into a clinical workflow to serve an endogamous, uninsured, agrarian community.MethodsSeventy-nine probands (newborn to 49.8 years) who presented between 1998 and 2015 remained undiagnosed after biochemical and molecular investigations. We generated WES data for probands and family members and vetted variants through rephenotyping, segregation analyses, and population studies.ResultsThe most common presentation was neurological disease (64%). Seven (9%) probands were diagnosed by CMA. Family WES data were informative for 37 (51%) of the 72 remaining individuals, yielding a specific genetic diagnosis (n = 32) or revealing a novel molecular etiology (n = 5). For five (7%) additional subjects, negative WES decreased the likelihood of genetic disease. Compared to trio analysis, "family" WES (average seven exomes per proband) reduced filtered candidate variants from 22 ± 6 to 5 ± 3 per proband. Nineteen (51%) alleles were de novo and 17 (46%) inherited; the latter added to a population-based diagnostic panel. We found actionable secondary variants in 21 (4.2%) of 502 subjects, all of whom opted to be informed.ConclusionCMA and family-based WES streamline and economize diagnosis of rare genetic disorders, accelerate novel gene discovery, and create new opportunities for community-based screening and prevention in underserved populations.

Translational Genomics in Low- and Middle-Income Countries: Opportunities and Challenges.

Translation of genomic discoveries into patient care is slowly becoming a reality in developed economies around the world. In contrast, low- and middle-income countries (LMIC) have participated minimally in genomic research for several reasons including the lack of coherent national policies, the limited number of well-trained genomic scientists, poor research infrastructure, and local economic and cultural challenges. Recent initiatives such as the Human Heredity and Health in Africa (H3Africa), the Qatar Genome Project, and the Mexico National Institute of Genomic Medicine (INMEGEN) that aim to address these problems through capacity building and empowerment of local researchers have sparked a paradigm shift. In this short communication, we describe experiences of small-scale medical genetics and translational genomic research programs in LMIC. The lessons drawn from these programs drive home the importance of addressing resource, policy, and sociocultural dynamics to realize the promise of precision medicine driven by genomic science globally. By echoing lessons from a bench-to-community translational genomic research, we advocate that large-scale genomic research projects can be successfully linked with health care programs. To harness the benefits of genomics-led health care, LMIC governments should begin to develop national genomics policies that will address human and technology capacity development within the context of their national economic and sociocultural uniqueness. These policies should encourage international collaboration and promote the link between the public health program and genomics researchers. Finally, we highlight the potential catalytic roles of the global community to foster translational genomics in LMIC.

Community dissemination and genetic research: moving beyond results reporting.

The community-based participatory research (CBPR) literature notes that researchers should share study results with communities. In the case of human genetic research, results may be scientifically interesting but lack clinical relevance. The goals of this study were to learn what kinds of information community members want to receive about genetic research and how such information should be conveyed. We conducted eight focus group discussions with Yup'ik Alaska Native people in southwest Alaska (N = 60) and 6 (N = 61) with members of a large health maintenance organization in Seattle, Washington. Participants wanted to receive genetic information they "could do something about" and wanted clinically actionable information to be shared with their healthcare providers; they also wanted researchers to share knowledge about other topics of importance to the community. Although Alaska Native participants were generally less familiar with western scientific terms and less interested in web-based information sources, the main findings were the same in Alaska and Seattle: participants wished for ongoing dialogue, including opportunities for informal, small-group conversations, and receiving information that had local relevance. Effective community dissemination is more than a matter of presenting study results in lay language. Community members should be involved in both defining culturally appropriate communication strategies and in determining which information should be shared. Reframing dissemination as a two-way dialogue, rather than a one-way broadcast, supports the twin aims of advancing scientific knowledge and achieving community benefit.

Assessing multilevel determinants of adoption and implementation of genomic medicine: an organizational mixed-methods approach.

PURPOSE: Adoption and implementation of evidence-based genetic and genomic medicine have been slow. We describe a methodology for identifying the influence of organizational factors on adoption and implementation of these services in health-care organizations. METHODS: We illustrate a three-component, mixed-methods health services research approach, including expert panels, qualitative interviews with key informants, and quantitative surveys completed by key informants. RESULTS: This research approach yielded a baseline assessment of existing genetic health-care models in the Veterans Health Administration and identified organizational barriers to and facilitators of adoption. In aggregate, the panel and key informant strategies created a communication network of relevant organizational stakeholders and a detailed foundation of organizational knowledge from which to design tools and models for implementation-level genetic/genomic translation. CONCLUSION: Expert panel and key informant strategies can be used to create a backdrop of stakeholder involvement and baseline organizational knowledge within which to plan translation research and to inform strategic planning and policies for adoption and implementation of genetic services in health-care organizations.

Implementing family health history risk stratification in primary care: impact of guideline criteria on populations and resource demand.

UNLABELLED: The Genomic Medicine Model aims to facilitate patient engagement, patient/provider education of genomics/personalized medicine, and uptake of risk-stratified evidence-based prevention guidelines using MeTree, a patient-facing family health history (FHH) collection and clinical decision support (CDS) program. Here we report the number of increased risk (above population-level risk) patients identified for breast/ovarian cancer, colon cancer, hereditary syndrome risk, and thrombosis; the prevalence of FHH elements triggering increased-risk status; and the resources needed to manage their risk. STUDY DESIGN: hybrid implementation-effectiveness study of adults with upcoming well-visits in 2 primary care practices in Greensboro, NC. PARTICIPANTS: 1,184, mean age = 58.8, female = 58% (N = 694), non-white = 20% (N = 215). Increased Risk: 44% (N = 523). RECOMMENDATIONS: genetic counseling = 26% (N = 308), breast MRI = 0.8% (N = 10), breast chemoprophylaxis = 5% (N = 58), early/frequent colonoscopies = 19% (N = 221), ovarian cancer screening referral = 1% (N = 14), thrombosis testing/counseling = 2.4% (N = 71). FHH elements: 8 FHH elements lead to 37.3% of the increased risk categorizations (by frequency): first-degree-relative (FDR) with polyps age ≥60 (7.1%, N = 85), three relatives with Lynch-related cancers (5.4%, N = 65), FDR with polyps age <60 (5.1%, N = 61), three relatives on same side of family with same cancer (4.9%, N = 59), Gail score ≥1.66% (4.9%, N = 58), two relatives with breast cancer (one ≤age 50) (4.1%, N = 49), one relative with breast cancer ≤age 40 (4.1%, N = 48), FDR with colon cancer age ≥60 (1.7%, N = 20). MeTree identifies a high percentage of individuals in the general primary care population needing non-routine risk management/prevention for the selected conditions. Implementing risk-stratification in primary care will likely increase demand for related-resources, particularly colon screening and GC. Understanding the prevalence of FHH elements helps predict resource needs and may aid in guideline development.

Implementation of genomic medicine in a health care delivery system: a value proposition?

The United States health care system is undergoing significant change and is seeking innovations in care delivery and reimbursement models that will lead to improved value for patients, providers, payers, and employers. Genomic medicine has the potential to be a disruptive innovation that if implemented intelligently can improve value. The article presents the perspective of the leaders of a large integrated healthcare delivery system regarding the decision to invest in implementation of genomic medicine.

Pseudonymization of patient identifiers for translational research.

BACKGROUND: The usage of patient data for research poses risks concerning the patients' privacy and informational self-determination. Next-generation-sequencing technologies and various other methods gain data from biospecimen, both for translational research and personalized medicine. If these biospecimen are anonymized, individual research results from genomic research, which should be offered to patients in a clinically relevant timeframe, cannot be associated back to the individual. This raises an ethical concern and challenges the legitimacy of anonymized patient samples. In this paper we present a new approach which supports both data privacy and the possibility to give feedback to patients about their individual research results. METHODS: We examined previously published privacy concepts regarding a streamlined de-pseudonymization process and a patient-based pseudonym as applicable to research with genomic data and warehousing approaches. All concepts identified in the literature review were compared to each other and analyzed for their applicability to translational research projects. We evaluated how these concepts cope with challenges implicated by personalized medicine. Therefore, both person-centricity issues and a separation of pseudonymization and de-pseudonymization stood out as a central theme in our examination. This motivated us to enhance an existing pseudonymization method regarding a separation of duties. RESULTS: The existing concepts rely on external trusted third parties, making de-pseudonymization a multistage process involving additional interpersonal communication, which might cause critical delays in patient care. Therefore we propose an enhanced method with an asymmetric encryption scheme separating the duties of pseudonymization and de-pseudonymization. The pseudonymization service provider is unable to conclude the patient identifier from the pseudonym, but assigns this ability to an authorized third party (ombudsman) instead. To solve person-centricity issues, a collision-resistant function is incorporated into the method. These two facts combined enable us to address essential challenges in translational research. A productive software prototype was implemented to prove the functionality of the suggested translational, data privacy-preserving method. Eventually, we performed a threat analysis to evaluate potential hazards connected with this pseudonymization method. CONCLUSIONS: The proposed method offers sustainable organizational simplification regarding an ethically indicated, but secure and controlled process of de-pseudonymizing patients. A pseudonym is patient-centered to allow correlating separate datasets from one patient. Therefore, this method bridges the gap between bench and bedside in translational research while preserving patient privacy. Assigned ombudsmen are able to de-pseudonymize a patient, if an individual research result is clinically relevant.

Clinical genomics information management software linking cancer genome sequence and clinical decisions.

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician.

Genetic service delivery: infrastructure, assessment and information.

Identification of genomic determinants of complex disorders such as cancer, diabetes and cardiovascular disease has prompted public health systems to focus on genetic service delivery for prevention of these disorders, adding to their previous efforts in birth defects prevention and newborn screening. This focus is consistent with previously identified obligations of the public health system as well as the core functions of public health identified by the Institute of Medicine. Models of service delivery include provision of services by the primary care provider in conjunction with subspecialists, provision of services through the medical home with co-management by genetics providers, provision of services in conjunction with disorder-specific treatment centers, and provision of services through a network of genetics clinics linked to medical homes. Whatever the model for provision of genetic services, tools to assist providers include facilities for outreach and telemedicine, information technology, just-in-time management plans, and emergency management tools. Assessment tools to determine which care is best are critical for quality improvement and development of best practices. Because the workforce of genetics providers is not keeping pace with the need for services, an understanding of the factors contributing to this lag is important, as is the development of an improved knowledge base in genomics for primary care providers.