Purpose:Type 1 hereditary hemochromatosis (HH) can result in iron overload and liver disease if not detected and treated early. Most cases are found among people homozygous for HFE p.Cys282Tyr variants. Compound heterozygosity with the HFE p.His63Asp variant is associated with disease to a lesser degree. We sought to examine the association of HFE variation with HH-related phenotypes and assess the prevalence of testing and diagnosis of HH using All of Us data. Methods:We used data from 133,978 participants with genetic information linked to medical records. For different HFE genotypes, we examined the prevalence of HH diagnosis codes and related biochemical and clinical phenotypes. Results:Among participants who were p.Cys282Tyr homozygotes, the prevalence of HH diagnosis codes was 22.6% among males and 15.6% among females. Serum transferrin-iron saturation measures were available only for 31.4% of males and 21.1% of females who were p.Cys282Tyr homozygotes. Liver disease, including cirrhosis or hepatocellular carcinoma, was present more among males who were p.Cys282Tyr homozygotes compared with males with no p.Cys282Tyr or p.His63Asp variants (15.5% vs 8.5%, P = .0001). Of the 71 participants who were p.Cys282Tyr homozygotes with indication of liver disease, 32 (45.1%) did not have a serum transferrin-iron saturation measure, and 37 (52.1%) did not have diagnosis codes for HH. Conclusion:Limited serum transferrin-iron saturation measures or HH diagnosis codes among p.Cys282Tyr homozygotes, even those with liver disease, suggests potential undertesting and underdiagnosis of type 1 HH in clinical practice and a need for improved awareness, education, and testing around HH.

Purpose: We used data from the All of Us Research Program to examine sociodemographic differences in family health history (FHH) survey access, availability of electronic health records (EHR) data, FHH knowledge, FHH in the survey and EHR data, and concordance of FHH in survey and EHR data for breast cancer, colorectal cancer, and diabetes. Methods: We calculated percentages and standard errors of participants who accessed the FHH survey, reported no FHH knowledge, had EHR data available, had FHH data in the survey and EHR, and had FHH in the survey or EHR that was not captured in the other data source for breast cancer, colorectal cancer, and diabetes. We stratified by age, race and ethnicity, sex, sexual orientation, household income, employment status, education level, marital status, and health insurance status. To determine significant differences, we calculated absolute and relative disparity, Z-tests, and P values with the significance threshold adjusted for multiple comparisons using the Bonferroni correction. Results: We found significant disparities in accessing the survey and reporting no FHH knowledge across almost all sociodemographic subgroups. Most FHH reported in the survey was not captured in the EHR data, most significantly for participants who were aged 20 to 29, were students, did not graduate high school, were never married, or had no health insurance. Conclusion: Our study showed significant sociodemographic disparities in FHH survey access, FHH knowledge, and FHH captured in EHR structured data, which could widen inequities in access to FHH-based interventions.

Recent reviews have emphasized the need for a health equity agenda in genomics research. To ensure that genomic discoveries can lead to improved health outcomes for all segments of the population, a health equity agenda needs to go beyond research studies. Advances in genomics and precision medicine have led to an increasing number of evidence-based applications that can reduce morbidity and mortality for millions of people (tier 1). Studies have shown lower implementation rates for selected diseases with tier 1 applications (familial hypercholesterolemia, Lynch syndrome, hereditary breast and ovarian cancer) among racial and ethnic minority groups, rural communities, uninsured or underinsured people, and those with lower education and income. We make the case that a public health agenda is needed to address disparities in implementation of genomics and precision medicine. Public health actions can be centered on population-specific needs and outcomes assessment, policy and evidence development, and assurance of delivery of effective and ethical interventions. Crucial public health activities also include engaging communities, building coalitions, improving genetic health literacy, and building a diverse workforce. Without concerted public health action, further advances in genomics with potentially broad applications could lead to further widening of health disparities in the next decade.

A better understanding of COVID-19 in people with primary immunodeficiency (PI), rare inherited defects in the immune system, is important for protecting this population, especially as population-wide approaches to mitigation change. COVID-19 outcomes in the PI population could have broader public health implications because some people with PI might be more likely to have extended illnesses, which could lead to increased transmission and emergence of variants. We performed a systematic review on COVID-19-associated morbidity and mortality in people with PI. Of the 1114 articles identified through the literature search, we included 68 articles in the review after removing 1046 articles because they were duplicates, did not involve COVID-19, did not involve PI, were not in English, were commentaries, were gene association or gene discovery studies, or could not be accessed. The 68 articles included outcomes for 459 people with PI and COVID-19. Using data from these 459 people, we calculated a case fatality rate of 9%, hospitalization rate of 49%, and oxygen supplementation rate of 29%. Studies have indicated that a number of people with PI showed at least some immune response to COVID-19 vaccination, with responses varying by type of PI and other factors, although vaccine effectiveness against hospitalization was lower in the PI population than in the general population. In addition to being up-to-date on vaccinations, current strategies for optimizing protection for people with PI can include pre-exposure prophylaxis for those eligible and use of therapeutics. Overall, people with PI, when infected, tested positive and showed symptoms for similar lengths of time as the general population. However, a number of people with X-linked agammaglobulinemia (XLA) or other B-cell pathway defects were reported to have prolonged infections, measured by time from first positive SARS-CoV-2 test to first negative test. As prolonged infections might increase the likelihood of genetic variants emerging, SARS-CoV2 isolates from people with PI and extended illness would be good candidates to prioritize for whole genome sequencing.

Despite growing awareness about the potential for genomic information to improve population health, lingering communication challenges remain in describing the role of genomics in public health programs. Identifying and addressing these challenges provide an important opportunity for appropriate communication to ensure the translation of genomic discoveries for public health benefits. In this commentary, we describe 5 common communication challenges encountered by the Centers for Disease Control and Prevention's Office of Genomics and Precision Public Health based on over 20 years of experience in the field. These include (1) communicating that using genomics to assess rare diseases can have an impact on public health; (2) providing evidence that genetic factors can add important information to environmental, behavioral, and social determinants of health; (3) communicating that although genetic factors are nonmodifiable, they can increase the impact of public health programs and communication strategies; (4) addressing the concern that genomics is not ready for clinical practice; and (5) communicating that genomics is valuable beyond the domain of health care and can be integrated as part of public health programs. We discuss opportunities for addressing these communication challenges and provide examples of ongoing approaches to communication about the role of genomics in public health to the public, researchers, and practitioners.

The opinions expressed in the paper are those of the authors and do not necessarily reflect those of the Centers for Disease Control and Prevention. Recognizing the emerging role of genomics as a tool for population screening, the American College of Medical Genetics and Genomics (ACMG) has generated two companion guidance documents on DNA-based screening of healthy individuals that appear in the present issue of Genetics in Medicine.1.Murray, M. F. et al. DNA-based screening and population health: a points to consider statement for programs and sponsoring organizations from the American College of Medical Genetics and Genomics (ACMG). Genet. Med.https://doi.org/10.1038/s41436-020-01082-w (2021).Google Scholar,2.Bean, L. J. H. et al. DNA-based screening and personal health: a points to consider document for individuals and healthcare providers from the American College of Medical Genetics and Genomics (ACMG). Genet. Med.https://doi.org/10.1038/s41436-020-01083-9 (2021).Google Scholar In this commentary, we offer a brief public health perspective on these documents in the context of recent work from the Centers for Disease Control and Prevention (CDC) Office of Genomics and Precision Public Health (OGPPH). Since the start of the Human Genome Project, there has been a strong belief by scientists and the public that at some point in the future, all of us will have our genomes sequenced in routine health care. In 1999, Dr. Francis Collins articulated a vision for the practice of medicine in 2010 in a hypothetical case of a 23-year-old man who presents to his health-care provider as part of a health checkup and is offered genetic testing for various diseases, to develop a personalized plan for disease prevention and screening.3.Collins F.S. Shattuck lecture: medical and societal consequences of the Human Genome Project.1:STN:280:DyaK1M3psVelug%3D%3D10.1056/NEJM199907013410106N. Engl. J. Med. 1999; 341: 28-37Google Scholar However, the complexities of the science and the cost of technology, the need for large scale clinical and population studies, and a host of ethical, legal, and social issues (ELSI) have prevented this prediction from becoming a reality. Nevertheless, steady progress in science and technology, the conduct of clinical and population studies around clinical validity and utility of genetic information, as well as numerous investigations around ELSI, have helped us move closer to this vision. So much so that the new National Human Genome Research Institute (NHGRI) 2020 strategic vision for improving health at the forefront of genomics includes a bold prediction for 2030: “The regular use of genomic information will have transitioned from boutique to mainstream in all clinical settings, making genomic testing as routine as complete blood counts.”4.Green, E. D. et al. Strategic vision for improving human health at the forefront of genomics. Nature.586, 683–692 (2020).Google Scholar In the United States, the vision presented above has begun to be realized in multiple health systems and population studies carrying out large scale population sequencing in biobanks and learning health systems research settings, such as Geisinger Health System and the Nevada Genome Project.5.Murray M.F. Giovanni M.A. Bringing monogenic disease screening to the clinic.1:CAS:528:DC%2BB3cXhsV2mtbfJ10.1038/s41591-020-1017-yNat. Med. 2020; 26: 1172-1174Google Scholar Nevertheless, in 2020, almost all the implemented applications in genomics in routine clinical care occur in diagnostic settings, most notably in the diagnosis of rare genetic diseases, noninvasive prenatal testing, and cancer genomics to guide cancer therapy. In addition, there are limited data on the implementation of testing and its impact on public health.6.Phillips, K. A., Douglas, M. P. & Marshall D. A. Expanding use of clinical genome sequencing and the need for more data on implementation. JAMA. 324, 2029–2030 (2020).Google Scholar The use of genomics as a population screening tool long predates the Human Genome Project. Newborn screening is considered as one of the ten great public health achievements of the twentieth century.7.Centers for Disease Control and Prevention Ten great public health achievements. United States: 2001–2010.MMWR Morb. Mortal. Wkly Rep. 2011; 60: 619-623PubMed Google Scholar For more than 60 years, newborn screening has been a component of public health programs and has led to major improvements in outcomes for infants with various genetic, metabolic, and other conditions. In the United States, newborn screening identifies >13,000 newborns annually who will require lifelong specialized health care.8.Centers for Disease Control and Prevention Public Health Grand Rounds Newborn screening and improved outcomes.MMWR Morb. Mortal. Wkly Rep. 2012; 61: 390-393PubMed Google Scholar Recognizing the emerging role of genomics as a screening tool across the lifespan, in 2013 Evans et al. called for scientific investigation of the application of genomics in adults in a similar way to newborn screening.9.Evans J.P. et al.We screen newborns, don’t we? Realizing the promise of public health genomics.10.1038/gim.2013.11Genet. Med. 2013; 15: 332-334Google Scholar The authors urged that a partnership be developed between the genomics and public health communities to better identify individuals who have genetic variants with a high risk of preventable diseases. In 2014, CDC developed a relatively simple horizon-scanning method based on a three-tier classification system:•“Tier 1 […] genomic applications have a base of synthesized evidence that supports implementation in practice.•Tier 2 […] genomic applications have synthesized evidence that is insufficient to support their implementation in routine practice. Nevertheless, the evidence may be useful for informing selective use strategies […]•Tier 3 […] applications either (i) have synthesized evidence that supports recommendations against […] use, or (ii) no relevant synthesized evidence is available.”10.Dotson W.D. et al.Prioritizing genomic applications for action by level of evidence: a horizon-scanning method.1:STN:280:DC%2BC2czjtVSnuw%3D%3D10.1038/clpt.2013.226Clin. Pharmacol. Ther. 2014; 95: 394-402Google Scholar For the past few years, CDC has worked with health-care organizations and public health programs to implement evidence-based recommendations for three primary tier 1 applications involving screening for hereditary breast and ovarian cancer (HBOC), Lynch syndrome (LS), and familial hypercholesterolemia (FH). This work has included public and provider education, special programs that address disparities in access to testing and services, conducting public health surveillance, and policy development.11.Khoury M.J. et al.From public health genomics to precision public health: a twenty-year journey.10.1038/gim.2017.211Genet. Med. 2018; 20: 574-582Google Scholar It is important to note that the CDC tier 1 designation is associated with the clinical scenario for testing, not the underlying condition. For example, we are not aware of any current recommendations, or synthesized evidence, to support population screening for BRCA1 and BRCA2 pathogenic variants, but there are evidence-based recommendations for screening based on family history and ethnicity.11.Khoury M.J. et al.From public health genomics to precision public health: a twenty-year journey.10.1038/gim.2017.211Genet. Med. 2018; 20: 574-582Google Scholar The former application of screening for BRCA1 and BRCA2 pathogenic variants could thus be considered tier 3, and the latter application tier 1. Increasingly, accepted evidence-based approaches using family history–based screening do not identify most individuals with genetic conditions associated with the three primary CDC tier 1 applications. Several studies have shown that a minority of adults with pathogenic BRCA1/2 variants are aware that they carry these variants.5.Murray M.F. Giovanni M.A. Bringing monogenic disease screening to the clinic.1:CAS:528:DC%2BB3cXhsV2mtbfJ10.1038/s41591-020-1017-yNat. Med. 2020; 26: 1172-1174Google Scholar This may be due to limitations to the uptake of family history and the sensitivity of the family history–based approach. The evidence of failure to identify at-risk individuals is occurring in the context of rapidly declining costs of DNA testing, and improved ability for interpreting pathogenicity of DNA.5.Murray M.F. Giovanni M.A. Bringing monogenic disease screening to the clinic.1:CAS:528:DC%2BB3cXhsV2mtbfJ10.1038/s41591-020-1017-yNat. Med. 2020; 26: 1172-1174Google Scholar It is estimated that about 1% of the population carries a pathogenic DNA variant associated with familial hypercholesterolemia (LDLR, APOB, PCSK9), HBOC (BRCA1, BRCA2), or LS (MLH1, MSH2, MSH6, PMS2).5.Murray M.F. Giovanni M.A. Bringing monogenic disease screening to the clinic.1:CAS:528:DC%2BB3cXhsV2mtbfJ10.1038/s41591-020-1017-yNat. Med. 2020; 26: 1172-1174Google Scholar DNA-based population screening for these genes can potentially offer short-term benefit for the estimated 3 million individuals in the United States with one of these risks, and longer-term benefit to more people as the number of genes proposed for population screening increases. It is important to note that population screening is distinct from diagnostic testing. Population screening should be evidence-based and adhere to the screening criteria established by Wilson and Jungner several decades ago.5.Murray M.F. Giovanni M.A. Bringing monogenic disease screening to the clinic.1:CAS:528:DC%2BB3cXhsV2mtbfJ10.1038/s41591-020-1017-yNat. Med. 2020; 26: 1172-1174Google Scholar In 2018, the Genomics and Population Health Action Collaborative (GPHAC) of the Roundtable on Genomics and Precision Health of the National Academies of Sciences, Engineering, and Medicine evaluated the potential for DNA-based screening programs in healthy adults. This group developed a roadmap for implementation that should be considered when developing a population-based sequencing program.12.Murray, J. F., Evans, J. M., Angrist, M. & Genomics and Population Health Action Collaborative. A proposed approach for implementing genomics-based screening programs for healthy adults. National Academy of Medicine, Round Table on Genomics and Precision Health. https://nam.edu/a-proposed-approach-for-implementing-genomics-based-screening-programs-for-healthy-adults/ (2018).Google Scholar The group also identified important issues to address such as feasibility of screening, potential benefits and harms, outcomes, costs, and ultimately, clinical utility. The first ACMG points to consider (PTC) document offers guidance for programs and sponsoring organizations that are considering DNA-based health screening,1.Murray, M. F. et al. DNA-based screening and population health: a points to consider statement for programs and sponsoring organizations from the American College of Medical Genetics and Genomics (ACMG). Genet. Med.https://doi.org/10.1038/s41436-020-01082-w (2021).Google Scholar and the second offers guidance to individuals and health-care providers around DNA-based screening.2.Bean, L. J. H. et al. DNA-based screening and personal health: a points to consider document for individuals and healthcare providers from the American College of Medical Genetics and Genomics (ACMG). Genet. Med.https://doi.org/10.1038/s41436-020-01083-9 (2021).Google Scholar Taken together, the two documents mark an important milestone on the road to public health genomics. They also appropriately reflect the complexities inherent in applying genomic information to healthy populations. The first document has seven points to help guide programs and sponsoring organizations. The authors review the evolving evidence around DNA-based screening in relation to the well-known Wilson and Jungner criteria13.Wilson J.M. Jungner Y.G. Principles and practice of mass screening for disease.1:STN:280:DyaF1M%2FhsVWquw%3D%3D4234760Bol. Oficina Sanit. Panam. 1968; 65: 281-393Google Scholar for population screening. The document concludes that DNA-based screening efforts have the potential to improve population health, but only if risk identification is effectively combined with evidence-based risk-reducing clinical care. The document embraces the list of genes associated with the CDC tier 1 genomic applications as a core list for consideration in the context of population screening. The conditions involved in the three primary tier 1 genomic applications are specifically associated with risk for breast, ovarian, colon, and endometrial cancers; coronary artery disease; and stroke and are therefore consistent with Wilson and Jungner’s guidance to focus health screening on “important health problems.” The seven points to consider are detailed and clearly articulated throughout. The authors are to be commended in attempting to deal with the challenging, shifting terrain of increasing use of DNA-based health screening, in programs and organizations, even in the absence of adequate evidence. We fully agree with the statement that “the health service delivery options for DNA-based health screening are currently in flux.… Much of the health services and economic research needed to address the DNA-based screening issues are yet to be done.” The second guidance document is addressed to individuals and health-care providers. It acknowledges at the outset that while the clinical utility of genome sequencing in apparently healthy people has not been established, accessibility to sequencing has increased, including use by the public without any specific clinical indication. The document explores opportunities and challenges presented by the changing models for delivery of genetic testing services. These include (1) a traditional genetic health-care model of services between genetics health-care providers and a patient’s referring provider, (2) a nontraditional genetic health-care model where genetic services are integrated within primary care and other specialties, and (3) a consumer-directed genetic health-care model in which consumers initiate the process on their own without involvement of health-care providers. The document offers a framework for the delivery of DNA testing according to the well-known preanalytical, analytical, and postanalytical phases of the testing process. It considers opportunities and challenges for each step of the process and for each health-care model, and strategies to address them. One of the most useful aspects of the second ACMG guidance document are the detailed steps identified in the pre- and postanalytical phases, which can allow exploration of important components (e.g., preanalytical education step, informed consent, and others). The detailed descriptions in the document allow comparison between different delivery models. This framework provides a helpful analytic tool to evaluate the strengths and weaknesses of each delivery model, and a careful summary of what we know about the delivery models in the three phases, and their strengths and weaknesses. Nevertheless, by acknowledging that the traditional delivery model is being replaced by the nontraditional, such as consumer genetic testing, the document appears to acknowledge the inexorable march toward DNA screening for healthy populations even in the absence of data on clinical utility, economic considerations, and adequate dealing with ethical, legal, and social issues. The two ACMG documents taken together reflect a new approach by marrying the importance of an evidence-based approach of the first document invoking principles of population screening with the importance of ensuring the integrity, quality, and outcomes of the testing process in the context of changing models of implementation. But the striking differences in the guidance document’s presentation and recommendations for individuals and providers versus programs and organizations may be inadvertently confusing to organizations, providers, and individuals, as it may be misinterpreted as DNA-based population screening can proceed without evidence, since it seems to be the only way such evidence can be gathered. As the first ACMG document clearly shows, there are key knowledge gaps in fulfilling criteria for population screening. One important gap is the incomplete understanding of the “natural history of the condition.” Natural history is concerned with the course of disease in the absence of treatment, and it involves both penetrance, the proportion of individuals with a given genomic risk who will show evidence of the associated clinical problems, and expressivity, the range of clinical manifestations associated with a specific genomic risk. While we have a detailed understanding of many genetic conditions in patients identified by diagnostic testing, natural history data are limited for persons identified via DNA-based screening. If DNA-based screening is to improve the public’s health, it must be combined with evidence-based care that reduces the burden of disease (e.g., screening, pharmacologic prevention). Management guidelines will need regular reanalysis of DNA variants informed by the most updated curated databases, regular clinical evaluation in screened individuals, the availability of updated clinical decision support tools and linkages with electronic health records, as well as regular assessment of the effectiveness, benefits, and potential harms of testing and prevention strategies. The two documents focus on DNA-based screening and population health related to a limited number of common and well-studied genetic disorders. Other areas where the evidence is more limited (tier 2 or tier 3) include pharmacogenomics, polygenic risk scores (PRS), and additional monogenic conditions. Ongoing research is needed to evaluate genotype–phenotype correlations in longitudinal studies and biobanks, and clinical utility studies to evaluate the effectiveness of risk-reducing interventions in screened persons with pathogenic variants in associated genes. We have previously proposed a collaborative implementation research agenda embedded in learning health systems14.Khoury M.J. et al.A collaborative translational research framework for evaluating and implementing the appropriate use of human genome sequencing to improve health.10.1371/journal.pmed.1002631PLoS Med. 2018; 15: e1002631Google Scholar to create an adequate evidence base to support DNA-based screening to improve population health. The translational research framework outlines collaboration among multiple health systems with available genome sequencing data and clinical outcomes. The framework is based on evaluating the impact of genetic information on improving health outcomes through research that incorporates levels of evidence for each intended use. Both observational studies and randomized controlled trials may be required to adequately evaluate health benefits, harms, and costs based on returning or not returning the results of gene variants to patients and providers. The proposed approach encourages learning health systems to collect clinical utility evidence in a research environment and develop the capacity for integration of sequencing with other clinical services.14.Khoury M.J. et al.A collaborative translational research framework for evaluating and implementing the appropriate use of human genome sequencing to improve health.10.1371/journal.pmed.1002631PLoS Med. 2018; 15: e1002631Google Scholar Important implementation questions related to DNA-based population health screening need to be answered.15.Murray M.F. Evans J.S. Khoury M.J. DNA-based population screening: potential suitability and important knowledge gaps.10.1001/jama.2019.18640JAMA. 2019; 323: 307-308Google Scholar These include, among others: How should screening be designed to offer inclusive benefits for the whole population? What are the appropriate population characteristics for screening? (e.g., age, gender). Who should pay for DNA-based screening and clinical follow-up? How often should data be reanalyzed? What are the clinical workforce needs related to delivering DNA-based results and clinical follow-up at population scale?15.Murray M.F. Evans J.S. Khoury M.J. DNA-based population screening: potential suitability and important knowledge gaps.10.1001/jama.2019.18640JAMA. 2019; 323: 307-308Google Scholar Given the relatively low frequency of individuals with genetic risk in the population, pilot studies will require large collaboration to begin to address some of these evidence gaps. Without large pilot studies, opportunities to evaluate evidence of clinical utility and economic feasibility will be delayed. There are no shortcuts on the long road to evidence-based genomic medicine. The same can be said about any population screening program. It is sobering to note that the now well-established population screening for colorectal cancer took several decades to lead to an evidence-based recommendation.11.Khoury M.J. et al.From public health genomics to precision public health: a twenty-year journey.10.1038/gim.2017.211Genet. Med. 2018; 20: 574-582Google Scholar DNA-based screening is a relatively new approach for identifying disease risks, and it has the potential to become a population screening program in the years ahead. While we may not be ready for population-based DNA screening, the ACMG guidance documents represent a leap forward in acknowledging the reality on the ground that such screening may already be happening, with or without evidence of clinical utility. The two documents represent a valiant effort in providing guidance and points to consider to health-care organizations, providers, and individuals considering DNA-based screening but should not be construed to imply that we are ready for population-based screening. These efforts should be conducted in the context of research enterprises and learning health systems, which have already started in multiple locations around the country. A collaborative approach will provide a faster approach to answer important outstanding questions of utility and implementation. We hope that collaborative studies including cohort studies and clinical trials can be adequately resourced and vigorously pursued. Finally, more efforts are needed to engage public health systems, professional societies, and health-care organizations in the dialogue around DNA-based population screening. The two ACMG documents provide a great starting point for awareness and integration of this rapidly changing practice landscape. The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Background: Although uniform colonoscopy screening reduces colorectal cancer (CRC) mortality, risk-based screening may be more efficient. We investigated whether CRC screening based on polygenic risk is a cost-effective alternative to current uniform screening, and if not, under what conditions it would be. Methods: The MISCAN-Colon model was used to simulate a hypothetical cohort of US 40-year-olds. Uniform screening was modeled as colonoscopy screening at ages 50, 60, and 70 years. For risk-stratified screening, individuals underwent polygenic testing with current and potential future discriminatory performance (area under the receiver-operating curve [AUC] of 0.60 and 0.65-0.80, respectively). Polygenic testing results were used to create risk groups, for which colonoscopy screening was optimized by varying the start age (40-60 years), end age (70-85 years), and interval (1-20 years). Results: With current discriminatory performance, optimal screening ranged from once-only colonoscopy at age 60 years for the lowest-risk group to six colonoscopies at ages 40-80 years for the highest-risk group. While maintaining the same health benefits, risk-stratified screening increased costs by $59 per person. Risk-stratified screening could become cost-effective if the AUC value would increase beyond 0.65, the price per polygenic test would drop to less than $141, or risk-stratified screening would lead to a 5% increase in screening participation. Conclusions: Currently, CRC screening based on polygenic risk is unlikely to be cost-effective compared with uniform screening. This is expected to change with a greater than 0.05 increase in AUC value, a greater than 30% reduction in polygenic testing costs, or a greater than 5% increase in adherence with screening.

Cascade testing is the process of offering genetic counseling and testing to at-risk relatives of an individual who has been diagnosed with a genetic condition. It is critical for increasing the identification rates of individuals with these conditions and the uptake of appropriate preventive health services. The process of cascade testing is highly varied in clinical practice, and a comprehensive understanding of factors that hinder or enhance its implementation is necessary to improve this process. We conducted a systematic review to identify barriers and facilitators for cascade testing and searched PubMed, CINAHL via EBSCO, Web of Science, EMBASE, and the Cochrane Library for articles published from the databases’ inception to November 2018. Thirty articles met inclusion criteria. Barriers and facilitators identified from these studies at the individual-level were organized into the following categories: (1) demographics, (2) knowledge, (3) attitudes, beliefs, and emotional responses of the individual, and (4) perceptions of relatives, relatives’ responses, and attitudes toward relatives. At the interpersonal-level, barriers and facilitators were categorized as (1) family communication-, support- and dynamics-, and (2) provider-factors. Finally, barriers at the environmental-level relating to accessibility of genetic services were also identified. Our findings suggest that several individual, interpersonal and environmental factors may play a role in cascade testing. Future studies to further investigate these barriers and facilitators are needed to inform future interventions for improving the implementation of cascade testing for genetic conditions in clinical practice.

Public health plays an important role in ensuring access to interventions that can prevent disease, including the implementation of evidence-based genomic recommendations. We used the Centers for Disease Control and Prevention (CDC) Science Impact Framework to trace the impact of public health activities and partnerships on the implementation of the 2009 Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Lynch Syndrome screening recommendation and the 2005 and 2013 United States Preventive Services Task Force (USPSTF) BRCA1 and BRCA2 testing recommendations.

Public health plays an important role in ensuring access to interventions that can prevent disease, including the implementation of evidence-based genomic recommendations. We used the Centers for Disease Control and Prevention (CDC) Science Impact Framework to trace the impact of public health activities and partnerships on the implementation of the 2009 Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Lynch Syndrome screening recommendation and the 2005 and 2013 United States Preventive Services Task Force (USPSTF) BRCA1 and BRCA2 testing recommendations.The EGAPP and USPSTF recommendations have each been cited by >300 peer-reviewed publications. CDC funds selected states to build capacity to integrate these recommendations into public health programs, through education, policy, surveillance, and partnerships. Most state cancer control plans include genomics-related goals, objectives, or strategies. Since the EGAPP recommendation, major public and private payers now provide coverage for Lynch Syndrome screening for all newly diagnosed colorectal cancers. National guidelines and initiatives, including Healthy People 2020, included similar recommendations and cited the EGAPP and USPSTF recommendations. However, disparities in implementation based on race, ethnicity, and rural residence remain challenges. Public health achievements in promoting the evidence-based use of genomics for the prevention of hereditary cancers can inform future applications of genomics in public health.

Michael F. Murray, MD, FACMG, FACP, Yale University; James P. Evans, MD, PhD, University of North Carolina at Chapel Hill; Misha Angrist, PhD, Duke University; Kee Chan, PhD, University of Illinois at Chicago; Wendy R. Uhlmann, MS, CGC, University of Michigan; Debra Lochner Doyle, MS, LCGC, Washington State Department of Health; Stephanie M. Fullerton, DPhil, University of Washington; Theodore G. Ganiats, MD, University of California at San Diego; Jill Hagenkord, MD, Color Genomics; Sara Imhof, PhD, North Carolina Biotechnology Center; Sun Hee Rim, PhD, MPH, Centers for Disease Control and Prevention; Leonard Ortmann, PhD, Centers for Disease Control and Prevention; Nazneen Aziz, PhD, Kaiser Permanente; W. David Dotson, PhD, Centers for Disease Control and Prevention; Ellen Matloff , MS, MyGene Counsel; Kristen Young, Northwestern University; Kimberly Kaphingst, ScD, University of Utah; Angela Bradbury, MD, University of Pennsylvania; Joan Scott, MS, CGC, Health Resources and Services Administration; Catharine Wang, PhD, Boston University; Ann Zauber, PhD, Memorial Sloan Kettering Cancer Center; Marissa Levine, MD, MPH, University of South Florida; Bruce Korf, MD, PhD, University of Alabama at Birmingham; Debra G. Leonard, MD, PhD, University of Vermont; Catherine Wicklund, MS, Northwestern University; George Isham, MD, HealthPartners; and Muin J. Khoury, MD, PhD, Centers for Disease Control and Prevention

Cascade screening is the process of contacting relatives of people who have been diagnosed with certain hereditary conditions. Its purpose is to identify, inform, and manage those who are also at risk. We conducted a scoping review to obtain a broad overview of cascade screening interventions, facilitators and barriers to their use, relevant policy considerations, and future research needs. We searched for relevant peer-reviewed literature in the period 1990-2017 and reviewed 122 studies. Finally, we described 45 statutes and regulations related to the use and release of genetic information across the fifty states. We sought standardized best practices for optimizing cascade screening across various geographic and policy contexts, but we found none. Studies in which trained providers contacted relatives directly, rather than through probands (index patients), showed greater cascade screening uptake; however, policies in some states might limit this approach. Major barriers to cascade screening delivery include suboptimal communication between the proband and family and geographic barriers to obtaining genetic services. Few US studies examined interventions for cascade screening or used rigorous study designs such as randomized controlled trials. Moving forward, there remains an urgent need to conduct rigorous intervention studies on cascade screening in diverse US populations, while accounting for state policy considerations.

PurposeWe examined 12-year trends in BRCA testing rates and costs in the context of clinical guidelines, national policies, and other factors.MethodsWe estimated trends in BRCA testing rates and costs from 2003 to 2014 for women aged 18-64 years using private claims data and publicly reported revenues from the primary BRCA testing provider.ResultsThe percentage of women with zero out-of-pocket payments for BRCA testing increased during 2013-2014, after 7 years of general decline, coinciding with a clarification of Affordable Care Act coverage of BRCA genetic testing. Beginning in 2007, family history accounted for an increasing proportion of women with BRCA tests compared with personal history, coinciding with BRCA testing guidelines for primary care settings and direct-to-consumer advertising campaigns. During 2013-2014, BRCA testing rates based on claims grew at a faster rate than revenues, following 3 years of similar growth, consistent with increased marketplace competition. In 2013, BRCA testing rates based on claims increased 57%, compared with 11% average annual increases over the preceding 3 years, coinciding with celebrity publicity.ConclusionThe observed trends in BRCA testing rates and costs are consistent with possible effects of several factors, including the Affordable Care Act, clinical guidelines and celebrity publicity.

PROBLEM/CONDITION:Genetic testing for breast cancer 1 (BRCA1) and breast cancer 2 (BRCA2) gene mutations can identify women at increased risk for breast and ovarian cancer. These testing results can be used to select preventive interventions and guide treatment. Differences between nonmetropolitan and metropolitan populations in rates of BRCA testing and receipt of preventive interventions after testing have not previously been examined.PERIOD COVERED:2009-2014.DESCRIPTION OF SYSTEM:Medical claims data from Truven Health Analytics MarketScan Commercial Claims and Encounters databases were used to estimate rates of BRCA testing and receipt of preventive interventions after BRCA testing among women aged 18-64 years with employer-sponsored health insurance in metropolitan and nonmetropolitan areas of the United States, both nationally and regionally.RESULTS:From 2009 to 2014, BRCA testing rates per 100,000 women aged 18-64 years with employer-sponsored health insurance increased 2.3 times (102.7 to 237.8) in metropolitan areas and 3.0 times (64.8 to 191.3) in nonmetropolitan areas. The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased from 37% in 2009 (102.7 versus 64.8) to 20% in 2014 (237.8 versus 191.3). The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased more over time in younger women than in older women and decreased in all regions except the West. Receipt of preventive services 90 days after BRCA testing in metropolitan versus nonmetropolitan areas throughout the period varied by service: the percentage of women who received a mastectomy was similar, the percentage of women who received magnetic resonance imaging of the breast was lower in nonmetropolitan areas (as low as 5.8% in 2014 to as high as 8.2% in 2011) than metropolitan areas (as low as 7.3% in 2014 to as high as 10.3% in 2011), and the percentage of women who received mammography was lower in nonmetropolitan areas in earlier years but was similar in later years.INTERPRETATION:Possible explanations for the 47% decrease in the relative difference in BRCA testing rates over the study period include increased access to genetic services in nonmetropolitan areas and increased demand nationally as a result of publicity. The relative differences in metropolitan and nonmetropolitan BRCA testing rates were smaller among women at younger ages compared with older ages.PUBLIC HEALTH ACTION:Improved data sources and surveillance tools are needed to gather comprehensive data on BRCA testing in the United States, monitor adherence to evidence-based guidelines for BRCA testing, and assess receipt of preventive interventions for women with BRCA mutations. Programs can build on the recent decrease in geographic disparities in receipt of BRCA testing while simultaneously educating the public and health care providers about U.S. Preventive Services Task Force recommendations and other clinical guidelines for BRCA testing and counseling.

In this paper, we review the evolution of the field of public health genomics in the United States in the past two decades. Public health genomics focuses on effective and responsible translation of genomic science into population health benefits. We discuss the relationship of the field to the core public health functions and essential services, review its evidentiary foundation, and provide examples of current US public health priorities and applications. We cite examples of publications to illustrate how Genetics in Medicine reflected the evolution of the field. We also reflect on how public-health genomics is contributing to the emergence of “precision public health” with near-term opportunities offered by the US Precision Medicine (AllofUs) Initiative.

Purpose: We examined the utilization of precision medicine tests among Medicare beneficiaries through analysis of gene-specific tier 1 and 2 billing codes developed by the American Medical Association in 2012. Methods: We conducted a retrospective cross-sectional study. The primary source of data was 2013 Medicare 100% fee-for-service claims. We identified claims billed for each laboratory test, the number of patients tested, expenditures, and the diagnostic codes indicated for testing. We analyzed variations in testing by patient demographics and region of the country. Results: Pharmacogenetic tests were billed most frequently, accounting for 48% of the expenditures for new codes. The most common indications for testing were breast cancer, long-term use of medications, and disorders of lipid metabolism. There was underutilization of guideline-recommended tumor mutation tests (e.g., epidermal growth factor receptor) and substantial overutilization of a test discouraged by guidelines (methylenetetrahydrofolate reductase). Methodology-based tier 2 codes represented 15% of all claims billed with the new codes. The highest rate of testing per beneficiary was in Mississippi and the lowest rate was in Alaska. Conclusions: Gene-specific billing codes significantly improved our ability to conduct population-level research of precision medicine. Analysis of these data in conjunction with clinical records should be conducted to validate findings. Genet Med advance online publication 26 January 2017

Purpose: We created an online knowledge base (the Public Health Genomics Knowledge Base (PHGKB)) to provide systematically curated and updated information that bridges population-based research on genomics with clinical and public health applications. Methods: Weekly horizon scanning of a wide variety of online resources is used to retrieve relevant scientific publications, guidelines, and commentaries. After curation by domain experts, links are deposited into Web-based databases. Results: PHGKB currently consists of nine component databases. Users can search the entire knowledge base or search one or more component databases directly and choose options for customizing the display of their search results. Conclusion: PHGKB offers researchers, policy makers, practitioners, and the general public a way to find information they need to understand the complicated landscape of genomics and population health. Genet Med 18 12, 1312–1314.

Should diagnoses, and corresponding changes in disease management, be sufficient demonstration of clinical utility, even in the absence of evidence for improved clinical outcomes? This question is posed to the health-care payer community in a recent American College of Medical Genetics and Genomics (ACMG) position statement on the clinical utility of genetic and genomic services.1.ACMG Board of Directors Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics.Genet Med. 2015; 17: 506-507Google Scholar Affirmative arguments could be drawn from examples of individually rare, highly penetrant, single-gene disorders. We fully support the ACMG's call for inclusion of individual, familial, and societal levels of impact in the evaluation of testing. Nevertheless, broadening the definition of clinical utility for all cases may be less helpful in the evaluation of genetic tests than promoting more context-dependent and transparent decision-making, with less rigidity and dogmatic adherence to artificial logic models. In the statement, the ACMG reports that "coverage decision-making policy is now driven by a narrowed perspective that clinical benefit accrues only to the individual receiving the services," so neither etiological diagnosis nor changes in treatment that lack corresponding proven health-outcome benefit qualify as demonstration of clinical utility.1.ACMG Board of Directors Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics.Genet Med. 2015; 17: 506-507Google Scholar Furthermore, familial and societal level benefits are ignored.1.ACMG Board of Directors Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics.Genet Med. 2015; 17: 506-507Google Scholar To exemplify a narrow view of clinical utility, the ACMG1.ACMG Board of Directors Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics.Genet Med. 2015; 17: 506-507Google Scholar cites the MolDX Clinical Test Evaluation Process,2.Palmetto GBA. MolDX Clinical Test Evaluation Process (CTEP) M00096, version 2.0. 2014. http://www.palmettogba.com/Palmetto/Moldx.Nsf/files/MolDX_Clinical_Test_Evaluation_Process_(CTEP)_M00096.pdf/$File/MolDX_Clinical_Test_Evaluation_Process_(CTEP)_M00096.pdf. Accessed 5 May, 2015.Google Scholar which is based on the Analytic Validity, Clinical Validity, Clinical Utility, Ethical, Legal, Social Implications (ACCE) model process.3.CDC Office of Public Health Genomics website. ACCE Model Process for Evaluating Genetic Tests. http://www.cdc.gov/genomics/gtesting/ACCE/. Accessed 5 May, 2015.Google Scholar Although ACCE was not the first to characterize clinical utility in terms of health outcomes, it established a nested model in which clinical utility encompasses, and adds to, all other components assessed. In addition to MolDX, groups such as the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG),4.EGAPP Working Group The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP Working Group.10.1097/GIM.0b013e318184137cGenet Med. 2009; 11: 3-14Google Scholar the Secretary's Discretionary Advisory Committee on Heritable Disorders of Newborns and Children,5.Advisory Committee on Heritable Disorders in Newborns and Children Committee report: method for evaluating conditions nominated for population-based screening of newborns and children.10.1097/GIM.0b013e3181d2af04Genet Med. 2010; 12: 153-159Google Scholar and the United Kingdom Genetic Testing Network6.Sanderson S. Zimmern R. Kroese M. Higgins J. Patch C. Emery J. How can the evaluation of genetic tests be enhanced? Lessons learned from the ACCE framework and evaluating genetic tests in the United Kingdom.10.1097/01.gim.0000179941.44494.73Genet Med. 2005; 7: 495-500Google Scholar have drawn on their own interpretations of ACCE, along with other sources, in developing methods for evaluation. Although the EWG used ACCE as an aid in organizing and better understanding questions for evaluation, they also leveraged the inherent flexibility of the model to create and customize their methods and outcome definitions.4.EGAPP Working Group The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP Working Group.10.1097/GIM.0b013e318184137cGenet Med. 2009; 11: 3-14Google Scholar,7.EGAPP Working Group Outcomes of interest in evidence-based evaluations of genetic tests.10.1097/GIM.0b013e3181cdde04Genet Med. 2010; 12: 228-235Google Scholar The Centers for Disease Control and Prevention's Office of Public Health Genomics founded the EGAPP initiative in 2004 and launched the EWG as an independent panel in 2005. As early as 2009, published EGAPP methods suggested consideration of information that may be helpful in personal decision making and for ending diagnostic odysseys in evaluating the clinical utility of tests used in clinical diagnostic scenarios.4.EGAPP Working Group The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP Working Group.10.1097/GIM.0b013e318184137cGenet Med. 2009; 11: 3-14Google Scholar The following year, the EWG published its framework for considering relevant outcomes in four categories of impact: (i) diagnostic thinking/health information, (ii) therapeutic choice, (iii) patient outcome, and (iv) familial/societal.8.Evaluation of Genomic Applications in Practice and Prevention Working Group Recommendations from the EGAPP Working Group: genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from Lynch syndrome in relatives.10.1097/GIM.0b013e31818fa2ffGenet Med. 2009; 11: 35-41Google Scholar Likewise, the methods of the Secretary's Discretionary Advisory Committee on Heritable Disorders of Newborns and Children stipulate that, in addition to reductions in morbidity and mortality, "Broader benefits to the individual infant, such as nonclinical interventions or benefits to family and community, such as avoiding a diagnostic odyssey or informing nonmedical decision making, may also be considered" in assessing clinical utility.5.Advisory Committee on Heritable Disorders in Newborns and Children Committee report: method for evaluating conditions nominated for population-based screening of newborns and children.10.1097/GIM.0b013e3181d2af04Genet Med. 2010; 12: 153-159Google Scholar To broaden the definition of clinical utility in a meaningful way, both benefits and potential harms at the individual, familial, and societal levels would need to be assessed. The weighting of these types of broader outcomes is often not amenable to quantitative description or analysis. Instead, these elements may sometimes be presented qualitatively, as important considerations or contextual factors. Nevertheless, the potential weight of familial and societal impact by the EWG was demonstrated in its 2009 recommendation that all patients with newly diagnosed colorectal cancer be tested for Lynch syndrome, to benefit family members through cascade screening.8.Evaluation of Genomic Applications in Practice and Prevention Working Group Recommendations from the EGAPP Working Group: genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from Lynch syndrome in relatives.10.1097/GIM.0b013e31818fa2ffGenet Med. 2009; 11: 35-41Google Scholar Potential benefits to family members include clear, "hard" outcomes of reduced morbidity and mortality, whereas individual-level benefits to patients are not as discernible (at least, based on the evidence considered). With recommended testing of individual patients as a means to improve outcomes in relatives, it follows that familial and societal level values would necessarily have been influential factors. The EWG reported the following as key contextual issues: consideration of potential for distress and related psychosocial outcomes following testing, intervention uptake and surveillance rates among relatives, and limitations in patient-level benefit; the last issue has been reported to have directly influenced the group's recommendation for informed consent antecedent to immunohistochemistry and microsatellite instability testing.8.Evaluation of Genomic Applications in Practice and Prevention Working Group Recommendations from the EGAPP Working Group: genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from Lynch syndrome in relatives.10.1097/GIM.0b013e31818fa2ffGenet Med. 2009; 11: 35-41Google Scholar This recommendation represents a particularly complex clinical scenario, and it is noteworthy that EGAPP methods allow for different approaches to assessing clinical utility based on how the test is to be used (i.e., diagnostic, screening, prognostic, risk assessment, or pharmacogenomics scenarios).4.EGAPP Working Group The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP Working Group.10.1097/GIM.0b013e318184137cGenet Med. 2009; 11: 3-14Google Scholar While testing would be diagnostic of Lynch syndrome for patients, for family members testing the colorectal cancer (CRC) patient would fall under the category of risk assessment. If the clinical scenario had involved screening for Lynch syndrome among people with a family history of CRC or diagnostic application of testing to the patient alone, then a different recommendation might result. Consideration of how testing is to be applied can be an important determinant of how clinical utility is assessed and therefore whether an actionable recommendation can be made. Elements of clinical utility in the ACCE model extend beyond clinical effectiveness of interventions.3.CDC Office of Public Health Genomics website. ACCE Model Process for Evaluating Genetic Tests. http://www.cdc.gov/genomics/gtesting/ACCE/. Accessed 5 May, 2015.Google Scholar The EWG has acknowledged viewing many ACCE elements pertaining to testing implementation (such as availability of appropriate facilities and educational materials) as "information that should not be included in the consideration of clinical utility, but may be considered as contextual factors in developing recommendation statements."4.EGAPP Working Group The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Initiative: methods of the EGAPP Working Group.10.1097/GIM.0b013e318184137cGenet Med. 2009; 11: 3-14Google Scholar Assessing clinical utility in its Lynch syndrome recommendation, the EWG created a chain of indirect evidence consisting of assessments of studies showing alteration of patient management (considering both proband and family members) and the influence these changes had on outcomes; they found only "limited but promising evidence suggesting that testing can improve outcomes."7.EGAPP Working Group Outcomes of interest in evidence-based evaluations of genetic tests.10.1097/GIM.0b013e3181cdde04Genet Med. 2010; 12: 228-235Google Scholar Together, these findings suggest that, although the EWG may take a more restrictive view of clinical utility than described in the ACCE model, in some respects the group takes a broader view on contextual issues, and the overall weighting of these issues can influence the outcome of recommendations. Rather than considering expansion of the definition of clinical utility, it may be more practicable to ask whether interventions whose clinical utility is not backed by adequately powered studies directly assessing health outcomes can be recommended through evidence-based evaluation processes. We believe that the example of the EGAPP Lynch syndrome recommendation suggests that the answer is—sometimes—yes. Practice associated with rare disorders, such as many inborn errors of metabolism, has also begun to innovate in addressing this question. There are frameworks incorporating more practice-based evidence in evaluating interventions at the levels of both health care systems and patients, to address shortcomings in more traditional evidence-based medicine in this area.9.Canadian Inherited Metabolic Diseases Research Network Achieving the "triple aim" for inborn errors of metabolism: a review of challenges to outcomes research and presentation of a new practice-based evidence framework.10.1038/gim.2012.153Genet Med. 2013; 15: 415-422Google Scholar Widening the scope of contextual and other issues considered in decision making, beyond the strict confines of clinical context, is an idea that may already be gaining traction. This type of approach could include, for example, utility of information in its own right and factors important in local context, such as inequities that increase variability in follow-up services. Reporting on exactly how such factors are considered is critical and can be more challenging than reporting more quantitatively assessable outcomes. For example, to arrive at the EWG Lynch syndrome recommendation, evaluators would have needed to take into account the fact that the mechanics of cascade screening remain controversial in terms of relative autonomy, privacy, and other issues at familial and societal levels, with different approaches in screening-program management potentially affecting the magnitude of potential harms.10.de Wert G. Cascade screening: whose information is it anyway?.10.1038/sj.ejhg.5201373Eur J Hum Genet. 2005; 13: 397-398Google Scholar From the EGAPP recommendation, however, it is not possible to ascertain the influence of each of these variables on the ultimate decisions that were made. For the intended purpose of guiding practice, it may be sufficient to state that such factors were considered. For the purposes of informing future research and guideline development by other groups, more detail on the specific contextual variables considered, along with estimated ranges of potential and actual influence on decisions attributable to each of these factors, would be useful. Instead of broadening definitions, we believe that it would be more helpful for guidelines to consistently include and describe consideration of contextual and other relevant issues, extending beyond clinical outcomes to factors such as the value of information in planning and in preventing additional unnecessary testing. Guidelines should be more specific in reporting the extent to which these kinds of issues are allowed to affect final decisions. Without this type of transparent reporting on individual decisions, allowing readers to see the sometimes messy application of formal methods, we have no reliable basis on which to determine the degree to which contextual factors influence results and a poorer ability to understand nuances that may be critical in implementing testing strategies. Professional societies should promote the rigorous, evidence-based evaluation of health technologies that are within their scope of influence while understanding that the results may not tell the complete story. In cases in which contextual and other relevant issues can be convincingly argued to outweigh clinical outcome–based demonstration of clinical utility, recommendations in favor of testing should be acceptable to proponents of evidence-based medicine. All authors are employed by CDC Office of Public Health Genomics, which maintains the EGAPP initiative and provides support for the independent EGAPP Working Group. The findings and conclusions in this report are those of the authors and do not necessarily reflect the views of the Centers for Disease Control and Prevention or the Department of Health and Human Services.

Genetic testing has grown dramatically in the past decade and is becoming an integral part of health care. Genetic nondiscrimination laws have been passed in many states, and the Genetic Information Nondiscrimination Act (GINA) was passed at the federal level in 2008. These laws generally protect individuals from discrimination by health insurers or employers based on genetic information, including test results. In 2010, Connecticut, Michigan, Ohio, and Oregon added four questions to their Behavioral Risk Factor Surveillance System (BRFSS) survey to assess interest in genetic testing, awareness of genetic nondiscrimination laws, concern about genetic discrimination in determining life insurance eligibility and cost, and perceived importance of genetic nondiscrimination laws that address life insurance. Survey results showed that awareness of genetic nondiscrimination laws was low (less than 20 % of the adult population), while perceived importance of these types of laws was high (over 80 % of respondents rated them as very or somewhat important). Over two-thirds of respondents indicated they were very or somewhat concerned about life insurance companies using genetic test results to determine life insurance coverage and costs. Results indicate a need for more public education to raise awareness of protections provided through current genetic nondiscrimination laws. The high rate of concern about life insurance discrimination indicates an additional need for continued dialogue regarding the extent of legal protections in genetic nondiscrimination laws.