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Employers have begun to offer voluntary workplace genomic testing (wGT) as part of employee wellness benefit programs, but few empirical studies have examined the ethical, legal, and social implications (ELSI) of wGT. To better understand employee perspectives on wGT, employees were surveyed at a large biomedical research institution. Survey respondents were presented with three hypothetical scenarios for accessing health-related genomic testing: via (1) their doctor; (2) their workplace; and 3) a commercial direct-to-consumer (DTC) genetic testing company. Overall, 594 employees (28%) responded to the survey. Respondents indicated a preference for genomic testing in the workplace setting (70%; 95% CI 66–74%), followed by doctor’s office (54%; 95% CI 50–58%), and DTC testing (20%; 95% CI 17–24%). Prior to participating in wGT, respondents wanted to know about confidentiality of test results (79%), existence of relevant laws and policies (70%), and privacy protection (64%). Across scenarios, 92% of respondents preferred to view the test results with a genetic counselor. These preliminary results suggest that many employees are interested and even prefer genetic testing in the workplace and would prefer testing with support from genetic health professionals. Confirmation in more diverse employer settings will be needed to generalize such findings.

IMPORTANCE: Less than 10% of patients with cancer have detectable pathogenic germline alterations, which may be partially due to incomplete pathogenic variant detection. OBJECTIVE: To evaluate if deep learning approaches identify more germline pathogenic variants in patients with cancer. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional study of a standard germline detection method and a deep learning method in 2 convenience cohorts with prostate cancer and melanoma enrolled in the US and Europe between 2010 and 2017. The final date of clinical data collection was December 2017. EXPOSURES: Germline variant detection using standard or deep learning methods. MAIN OUTCOMES AND MEASURES: The primary outcomes included pathogenic variant detection performance in 118 cancer-predisposition genes estimated as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The secondary outcomes were pathogenic variant detection performance in 59 genes deemed actionable by the American College of Medical Genetics and Genomics (ACMG) and 5197 clinically relevant mendelian genes. True sensitivity and true specificity could not be calculated due to lack of a criterion reference standard, but were estimated as the proportion of true-positive variants and true-negative variants, respectively, identified by each method in a reference variant set that consisted of all variants judged to be valid from either approach. RESULTS: The prostate cancer cohort included 1072 men (mean [SD] age at diagnosis, 63.7 [7.9] years; 857 [79.9%] with European ancestry) and the melanoma cohort included 1295 patients (mean [SD] age at diagnosis, 59.8 [15.6] years; 488 [37.7%] women; 1060 [81.9%] with European ancestry). The deep learning method identified more patients with pathogenic variants in cancer-predisposition genes than the standard method (prostate cancer: 198 vs 182; melanoma: 93 vs 74); sensitivity (prostate cancer: 94.7% vs 87.1% [difference, 7.6%; 95% CI, 2.2% to 13.1%]; melanoma: 74.4% vs 59.2% [difference, 15.2%; 95% CI, 3.7% to 26.7%]), specificity (prostate cancer: 64.0% vs 36.0% [difference, 28.0%; 95% CI, 1.4% to 54.6%]; melanoma: 63.4% vs 36.6% [difference, 26.8%; 95% CI, 17.6% to 35.9%]), PPV (prostate cancer: 95.7% vs 91.9% [difference, 3.8%; 95% CI, –1.0% to 8.4%]; melanoma: 54.4% vs 35.4% [difference, 19.0%; 95% CI, 9.1% to 28.9%]), and NPV (prostate cancer: 59.3% vs 25.0% [difference, 34.3%; 95% CI, 10.9% to 57.6%]; melanoma: 80.8% vs 60.5% [difference, 20.3%; 95% CI, 10.0% to 30.7%]). For the ACMG genes, the sensitivity of the 2 methods was not significantly different in the prostate cancer cohort (94.9% vs 90.6% [difference, 4.3%; 95% CI, –2.3% to 10.9%]), but the deep learning method had a higher sensitivity in the melanoma cohort (71.6% vs 53.7% [difference, 17.9%; 95% CI, 1.82% to 34.0%]). The deep learning method had higher sensitivity in the mendelian genes (prostate cancer: 99.7% vs 95.1% [difference, 4.6%; 95% CI, 3.0% to 6.3%]; melanoma: 91.7% vs 86.2% [difference, 5.5%; 95% CI, 2.2% to 8.8%]). CONCLUSIONS AND RELEVANCE: Among a convenience sample of 2 independent cohorts of patients with prostate cancer and melanoma, germline genetic testing using deep learning, compared with the current standard genetic testing method, was associated with higher sensitivity and specificity for detection of pathogenic variants. Further research is needed to understand the relevance of these findings with regard to clinical outcomes.

Persons with a family history (FH) of colorectal cancer (CRC) or adenomas that are not due to known hereditary syndromes have an increased risk for CRC. An understanding of these risks, screening recommendations, and screening behaviors can inform strategies for reducing the CRC burden in these families. A comprehensive review of the literature published within the past 10 years has been performed to assess what is known about cancer risk, screening guidelines, adherence and barriers to screening, and effective interventions in persons with an FH of CRC and to identify FH tools used to identify these individuals and inform care. Existing data show that having 1 affected first-degree relative (FDR) increases the CRC risk 2-fold, and the risk increases with multiple affected FDRs and a younger age at diagnosis. There is variability in screening recommendations across consensus guidelines. Screening adherence is

This study examines the analytic validity of a software tool designed to provide individuals with risk assessments for colorectal cancer based on personal health and family history information. The software is compatible with the US Surgeon General's My Family Health Portrait (MFHP).An algorithm for risk assessment was created using accepted colorectal risk assessment guidelines and programmed into a software tool (MFHP). Risk assessments derived from 150 pedigrees using the MFHP tool were compared with "gold standard" risk assessments developed by three expert cancer genetic counselors.Genetic counselor risk assessments showed substantial, but not perfect, agreement. MFHP risk assessments for colorectal cancer yielded a sensitivity for colorectal cancer risk of 81% (95% confidence interval: 54-96%) and specificity of 90% (95% confidence interval: 83-94%), as compared with genetic counselor pedigree review. The positive predictive value for risk for MFHP was 48% (95% confidence interval: 29-68%), whereas the negative predictive value was 98% (95% confidence interval: 93-99%). Agreement between MFHP and genetic counselor pedigree review was moderate (κ = 0.54).The analytic validity of the MFHP colorectal cancer risk assessment software is similar to those of other types of screening tools used in primary care. Future investigations should explore the clinical validity and utility of the software in diverse population groups.Genet Med 17 9, 753-756.

The US health care system has seen significant changes over the last decade resulting from diverse factors including the widespread adoption of electronic health records, the opioid crisis, and the roll-out of the Affordable Care Act. Such changes have buffeted the day-to-day work of physicians and other health care practitioners, leaving many finding it challenging to address demands placed on them. Looking forward in 2017, it seems that the future will hold more turbulence.1 In this milieu, it is easily possible to overlook that medicine has been undergoing a much more gradual and deeper transformation. This shift is inexorably moving medicine from an endeavor in which care for individual patients is driven by trial and error informed by studies designed to measure population outcomes to one in which care is selected based on a deep understanding of health and disease attributes unique to each individual. Accelerated by the completion of the Human Genome Project, this transformation has been variably called genomic medicine, genomic health care, personalized medicine, precision medicine, and precision health. The extent to which it ultimately alters medicine remains unclear.

Newborn screening (NBS) programs have been successful in identifying infants with rare, treatable, congenital conditions. While current programs rely largely on biochemical analysis, some predict that in the future, genome sequencing may be used as an adjunct. The purpose of this exploratory pilot study was to begin to characterize genetics professionals' opinions of the use of whole-genome sequencing (WGS) in NBS. We surveyed members of the American College of Medical Genetics and Genomics (ACMG) via an electronic survey distributed through email. The survey included questions about results disclosure, the current NBS paradigm, and the current criteria for adding a condition to the screening panel. The response rate was 7.3 % (n = 113/1549). The majority of respondents (85 %, n = 96/113) felt that WGS should not be currently used in NBS, and that if it were used, it should not be mandatory (86.5 %, n = 96/111). However, 75.7 % (n = 84/111) foresee it as a future use of WGS. Respondents felt that accurate interpretation of results (86.5 %, n = 83/96), a more extensive consent process (72.6 %, n = 69/95), pre- (79.2 %, n = 76/96) and post-test (91.6 %, n = 87/95) counseling, and comparable costs (70.8 %, n = 68/96) and turn-around-times (64.6 %, n = 62/96) to current NBS would be important for using WGS in NBS. Participants were in favor of disclosing most types of results at some point in the lifetime. However, the majority (87.3 %, n = 96/110) also indicated that parents should be able to choose what results are disclosed. Overall, respondents foresee NBS as a future use of WGS, but indicated that WGS should not occur within the framework of traditional NBS. They agreed with the current criteria for including a condition on the recommended uniform screening panel (RUSP). Further discussion about these criteria is needed in order to better understand how they could be utilized if WGS is incorporated into NBS.

“The Pregnancy and Health Profile,” (PHP) is a free genetic risk assessment software tool for primary prenatal providers that collects patient-entered family (FHH), personal, and obstetrical health history, performs risk assessment, and presents the provider with clinical decision support during the prenatal encounter. The tool is freely available for download at www.hughesriskapps.net. We evaluated the implementation of PHP in four geographically diverse clinical sites. Retrospective chart reviews were conducted for patients seen prior to the study period and for patients who used the PHP to collect data on documentation of FHH, discussion of cystic fibrosis (CF) and hemoglobinopathy (HB) carrier screening, and CF and HB interventions (tests, referrals). Five hundred pre-implementation phase and 618 implementation phase charts were reviewed. Documentation of a 3-generation FHH or pedigree improved at three sites; patient race/ethnicity at three sites, father of the baby (FOB) race/ethnicity at all sites, and ancestry for the patient and FOB at three sites (P

Purpose: This article reports on recommendations arising from an invitational workshop series held at the National Institutes of Health for the purposes of identifying critical genomics problems important to the health of the public that can be addressed through nursing science. The overall purpose of the Genomic Nursing State of the Science Initiative is to establish a nursing research blueprint based on gaps in the evidence and expert evaluation of the current state of the science and through public comment. Organizing Constructs: A Genomic Nursing State of the Science Advisory Panel was convened in 2012 to develop the nursing research blueprint. The Advisory Panel, which met via two webinars and two in-person meetings, considered existing evidence from evidence reviews, testimony from key stakeholder groups, presentations from experts in research synthesis, and public comment. Findings: The genomic nursing science blueprint arising from the Genomic Nursing State of Science Advisory Panel focuses on biologic plausibility studies as well as interventions likely to improve a variety of outcomes (e.g., clinical, economic, environmental). It also includes all care settings and diverse populations. The focus is on (a) the client, defined as person, family, community, or population; (b) the context, targeting informatics support systems, capacity building, education, and environmental influences; and (c) cross-cutting themes. It was agreed that building capacity to measure the impact of nursing actions on costs, quality, and outcomes of patient care is a strategic and

Implementation of genomic discoveries into health care optimally includes evaluation of outcomes for recipients of care, providers, payers, and health care systems. However, the influence of specific aspects of the implementation process on observed outcomes may be missed if assessment of implementation success is not built into the implementation design. The intersection of implementation science with genomics may provide new insights on how to maximize the benefits of emerging genomic technologies in health care. In this summary, members of the Roundtable on Genomics and Precision Health, formerly the Roundtable on Translating Genomic-Based Research for Health, of the National Academies of Sciences, Engineering, and Medicine and the American Academy of Nursing explore challenges and opportunities for nurses to participate in implementing genomic discoveries into their practice informed by the principles of implementation science. Implementation requires collaboration across disciplines. Nurses can take leadership roles in engaging key stakeholders in health care organizations, assuring that communications regarding implementation are consistent with genomic literacy for each group of stakeholders, and planning for evaluation of data to assess how each component of the implementation process affected the overall outcome for health care.

Summary Pharmacists are increasingly expected to incorporate an understanding of the genomic contributions to medication management in their daily practice, and a general consensus exists that many pharmacists are not adequately prepared to effectively make use of genomic information. In November 2011, the National Human Genome Research Institute of the National Institutes of Health convened a meeting to discuss the status of genomics education for pharmacists. A variety of pharmacist organizations and other stakeholder groups attended the 2-day event and explored the current status of pharmacist genomic education, barriers and facilitators to enhanced education, and important next steps to ensure that pharmacists are prepared for the coming decades. This report summarizes the background, content, and outcomes from this meeting.

Purpose: Develop a trans-disciplinary repository of genomics education resources using a Web-based learning management system. The repository maps and organizes genetic-genomic information and materials relevant to educators by healthcare discipline-specific competencies and performance indicators. Methods: An interdisciplinary project team was established to guide toolkit repository building and usability testing. The toolkit was built using the X-CREDIT software on the Moodle learning management platform, which includes a mapping matrix and browsing function that captures teaching resources in a searchable database linked to competencies, knowledge areas, performance indicators, learning activities and resources, and outcome assessments. Discipline-specific advisory groups assisted in resource identification, competency mapping, and peer review. The toolkit is multidisciplinary, currently including physician assistants and nurses, and provides a resource crosslink to discipline-specific competencies. All resources have a detailed description, and users may contribute new resources, which are peer reviewed for relevance and accuracy by an editorial board. Alpha and beta testing using online usability surveys that included toolkit exercises helped refine the structure, look, and navigation of the final website. Findings: One hundred thirty faculty—124 nursing and 6 physician assistant faculty—agreed to participate. Of those, 59 users (45.4% response rate) completed the online usability survey. Nearly all users (94.9%) were able to find a competency that was relevant to their topic, and 85.4% were able to locate the relevant performance indicators. The majority (86.5%) felt the model adequately described the relationships between competencies, performance indicators, learning activities-resources, and assessments, and made conceptual sense. Survey respondents reported font color and size made the information difficult to read, windows were not large enough, and the “shopping cart” concept was confusing; all of these areas have been modified for the final toolkit version. Conclusions: Alpha and beta testing of the toolkit revealed that users can successfully obtain educational materials by searching competencies and performance indicators. The platform is accessible on the Internet at http://www.g-2-c-2.org and can be continually updated as new resources become available. Clinical Relevance: Faculty members need easy access to a wide range of accurate, current resources to facilitate integration of genomics into the curriculum.

The authors describe the rationale and initial development of a new collaborative initiative, the Genomic Applications in Practice and Prevention Network. The network convened by the Centers for Disease Control and Prevention and the National Institutes of Health includes multiple stakeholders from academia, government, health care, public health, industry and consumers. The premise of Genomic Applications in Practice and Prevention Network is that there is an unaddressed chasm between gene discoveries and demonstration of their clinical validity and utility. This chasm is due to the lack of readily accessible information about the utility of most genomic applications and the lack of necessary knowledge by consumers and providers to implement what is known. The mission of Genomic Applications in Practice and Prevention Network is to accelerate and streamline the effective integration of validated genomic knowledge into the practice of medicine and public health, by empowering and sponsoring research, evaluating research findings, and disseminating high quality information on candidate genomic applications in practice and prevention. Genomic Applications in Practice and Prevention Network will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development process, (3) translation research to evaluate validity, utility and impact in the real world and how to disseminate and implement recommended genomic applications, and (4) programs to enhance practice, education, and surveillance.

The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed. Genet Med 2009:11(8):559-567.

The prevalence of paternal and maternal genetic conditions that affect pregnancy varies according to many factors that include parental age, medical history, and family history. Although some genetic conditions that affect pregnancy are identified easily early in life, other conditions are not and may require additional diagnostic testing. A complete 3-generation family medical history that includes ethnicity information about both sides of the family is arguably the single best genetic "test" that is applicable to preconception care. Assessment of genetic risk by an experienced professional has been shown to improve the detection rate of identifiable risk factors. Learning about possible genetic issues in the preconception period is ideal, because knowledge permits patients to make informed reproductive decisions. Options that are available to couples before conception include adoption, surrogacy, use of donor sperm, in vitro fertilization after preimplantation genetic diagnosis, and avoidance of pregnancy. Future technologic advances will increase the choices that are available to couples.

Family health history is a complex, multifaceted tool for assessing disease risk that can offer insight into the interplay between inherited and social factors relevant to patient care. Family health history tools in electronic health records can enable the user to collect, represent, and interpret structured data that properly supports clinical decisions. If these data can be made interoperable, important health information can be shared with minimal duplication of effort among entities involved in the continuum of patient care. This paper reviews the efforts by the American Health Information Community's Family Health History Multi-Stakeholder Workgroup to create a core data set for family health history information and to determine requirements to promote incorporation of such information in electronic health records. The Workgroup is a component of the U.S. Department of Health and Human Services' Personalized Health Care Initiative.

Genomic research has generated much new knowledge into mechanisms of human disease, with the potential to catalyze novel drug discovery and development, prenatal and neonatal screening, clinical pharmacogenomics, more sensitive risk prediction, and enhanced diagnostics. Genomic medicine, however, has been limited by critical evidence gaps, especially those related to clinical utility and applicability to diverse populations. Genomic medicine may have the greatest impact on health care if it is integrated into primary care, where most health care is received and where evidence supports the value of personalized medicine grounded in continuous healing relationships. Redesigned primary care is the most relevant setting for clinically useful genomic medicine research. Taking insights gained from the activities of the Institute of Medicine (IOM) Roundtable on Translating Genomic-Based Research for Health, we apply lessons learned from the patient-centered medical home national experience to implement genomic medicine in a patient-centered, learning health care system.

The current series of Genomic Medicine review articles concludes in this issue of the Journal with the publication of an article on cognitive impairment and autism by Mefford and colleagues.1 The topic of this article is an appropriate capstone for the Genomic Medicine series: it highlights the clinical advances in genomics regarding the care of patients with neurologic conditions, and it shows the potential of genomic science to further accelerate the pace of discovery in the neurosciences. The power of genomic technologies — in particular, DNA sequencing — is extraordinary. These techniques have led to a precipitous plunge in the . . .

described the outcomes of a workshop convened by the National Human Genome Research Institute to discuss the growing opportunities for educating nongeneticist physi-cians and other health-care providers in genomics. As a result of the workshop, an Inter-Society Coordinating Committee on Practitioner Education in Genomics was formed to facilitate interactions among professional societies intended to increase the expertise of practitioners in applying genomics in clinical care. This represents a renewed US national attempt to increase genomics competency among a key group of critical decision makers. In this commentary, we explore some of the key con-textual issues that are likely to mediate genomics educational demand and ultimately determine the success of genomics edu-cational programs for nongeneticist health professionals, espe-cially physicians.Physicians comprise a highly heterogeneous population. In the United States alone, there are 24 medical specialties recog-nized by the American Board of Medical Specialties and hun-dreds of professional societies and organizations that play a role in the educational pipeline of physicians from undergraduate education through retirement. Widespread adoption of even simple interventions with the best evidence of health bene-fits—such as ensuring that aspirin and -blockers are routinely βemployed in secondary prevention of coronary heart disease—is surprisingly difficult to attain. Genomic science and the clinical technologies that have arisen from its application are dauntingly complex, leading a former director of the National Heart Lung and Blood Institute of the National Institutes of Health to quip regarding the translation of genomic discover-ies to patient care, “If we didn’t do it with aspirin, how can we expect to do it with DNA?”

“The Pregnancy and Health Profile” (PHP) is a free prenatal genetic screening and clinical decision support (CDS) software tool for prenatal providers. PHP collects family health history (FHH) during intake and provides point-of-care risk assessment for providers and education for patients. This pilot study evaluated patient and provider responses to PHP and effects of using PHP in practice. PHP was implemented in four clinics. Surveys assessed provider confidence and knowledge and patient and provider satisfaction with PHP. Data on the implementation process were obtained through semi-structured interviews with administrators. Quantitative survey data were analyzed using Chi square test, Fisher’s exact test, paired t tests, and multivariate logistic regression. Open-ended survey questions and interviews were analyzed using qualitative thematic analysis. Of the 83 % (513/618) of patients that provided feedback, 97 % felt PHP was easy to use and 98 % easy to understand. Thirty percent (21/71) of participating physicians completed both pre- and post-implementation feedback surveys [13 obstetricians (OBs) and 8 family medicine physicians (FPs)]. Confidence in managing genetic risks significantly improved for OBs on 2/6 measures (p values ≤0.001) but not for FPs. Physician knowledge did not significantly change. Providers reported value in added patient engagement and reported mixed feedback about the CDS report. We identified key steps, resources, and staff support required to implement PHP in a clinical setting. To our knowledge, this study is the first to report on the integration of patient-completed, electronically captured and CDS-enabled FHH software into primary prenatal practice. PHP is acceptable to patients and providers. Key to successful implementation in the future will be customization options and interoperability with electronic health records.

There is growing interest in developing systems to overcome barriers for acquiring and interpreting family health histories in primary care.To examine the capacity of three different electronic portals to collect family history from patients and deposit valid data in an electronic health record (EHR).Pilot trial.Patients were enrolled from four primary care practices and were asked to collect family health history before a physical exam using either telephone-based interactive voice response (IVR) technology, a secure Internet portal, or a waiting room laptop computer, with portal assigned by practice. Intervention practices were compared to a "usual care" practice, where there was no standard workflow to document family history (663 participants in the three intervention arms were compared to 296 participants from the control practice).New documentation of any family history in a coded EHR field within 30 days of the visit. Secondary outcomes included participation rates and validity.Demographics varied by clinic. Documentation of new family history data was significantly higher, but modest, in each of the three intervention clinics (7.5 % for IVR clinic, 20.3 % for laptop clinic, and 23.1 % for patient portal clinic) versus the control clinic (1.7 %). Patient-entered data on common conditions in first degree relatives was confirmed as valid by a genetic counselor for the majority of cases (ranging from 64 to 82 % in the different arms).Within primary care practices, valid patient entered family health history data can be obtained electronically at higher rates than a standard of care that depends on provider-entered data. Further research is needed to determine how best to match different portals to individual patient preference, how the tools can best be integrated with provider workflow, and to assess how they impact the use of screening and prevention.

April 14, 2013, marks the 10-year anniversary of the official completion of the entire Human Genome Project.1 This genomics theme issue celebrates recent remarkable advances made possible by one of the greatest biological research projects ever conducted. During the last decade, understanding the complexity of the genome has moved beyond infancy into early childhood, a precarious age of exploration filled with an increasing number of triumphs and the occasional mishap. For the field of genomics, this developmental period has been marked by rapid advances in technologies for dissecting genome function in health and disease. Perhaps most surprisingly, the cost of sequencing the genome has decreased by 5 orders of magnitude through roughly the last 10 years,2 a pace that has exceeded expectations.

The recent exponential decline in the cost of sequencing human genomes to within an order of magnitude of $1000 has led to increased use of this technology in a variety of research and clinical settings. Examples of clinical sequencing success stories for diagnosing rare conditions are increasingly common and sequencing of tumor samples is being performed in many academic cancer centers to help guide care.

This Viewpoint discusses the integration of precision medicine discoveries with the learning health care system via implementation science.

RECENT GENOMIC DISCOVERIES HAVE BROUGHT ABOUT far-reaching advances in understanding the molecular basis of human health and disease. The vision for the future of genomics research developed by the National Human Genome Research Institute suggests more discoveries are likely to occur over the next few decades. These insights have helped reveal remarkable and unexpected complexities of human biology; however, this scientific reality has slowed the immediate translation of genomic discoveries to health benefits. Nevertheless, the early implementation of genomic medicine has brought clinically important advances that rival any other period of discovery in the history of Western medicine. For example, in 1990 the genetic and molecular basis was understood for fewer than 2% of the estimated 7000 suspected mendelian conditions; in 2011, approximately 40% of mendelian conditions have a known molecular basis. This 20-fold increase in disease-gene discovery has had immediate benefits for myriad affected individuals and families who now have access to accurate diagnostic testing, and the horizon holds hope for novel treatments in many cases. Likewise, advanced genomic technologies are helping to unravel the multifaceted nature of cancer and common complex conditions, such as heart disease and diabetes. More than a thousand newly identified genetic variants have been shown to be associated with such conditions, and many of these variants point to previously unsuspected biological pathways. Although much work remains, these discoveries offer promising avenues for clinical applications informed by genomic discoveries. The appropriate use of such applications will require that clinicians be sufficiently versed in genomics to understand when it should be applied and to communicate the potential limitations and benefits to their patients. Calls for enhanced genomics education for health care professionals predate completion of the Human Genome Project. Despite this, recent evidence suggests that large segments of the physician community are not adequately trained to make appropriate use of genomic advances. This lack of training has not escaped the public’s attention: a national poll of 1000 US adults revealed that 90% lacked confidence in their clinician’s ability to understand and use genomic information. Past efforts to enhance the genomics literacy of health care professionals have often taken the form of a push of information from the genomics community to other professional groups. The underlying assumption of these efforts has been that spontaneous interest in additional genomics education would follow. The push approach has met with reasonable success in the nursing and physician assistant communities. For example, the nursing profession has internally developed genomics education competencies, which have now been broadly adopted across 50 organizations. Linking these competencies with program accreditation and individual certification has been a major driver for the incorporation of genomics into the training and continuing education of the nursing profession. However, the push approach to genomics education has not been particularly successful in physician communities. The reasons for this are complex, but can be distilled into 4 interrelated issues. First, physicians are relentlessly practical. Until recently, most genomic advances were relevant to a very small subset of clinicians; this is changing rapidly. Second, the initial fruits of genomic medicine, such as testing for hereditary cancer syndromes, arrived at a time when the health care ecosystem was under great stress. This virtually guaranteed that any new idea, unless simple and easily adopted, would face passive neglect (if not outright active resistance). Third, the clinical application of genomics does not have a tradition of adherence to the precepts of evidence-based medicine. The first forays of genomics into clinical medicine related to rare genetic diseases, for which it is often impossible to undertake large, prospective, placebocontrolled, blinded trials of diagnostics and therapeutics. Therefore, as new genomic technologies have emerged, the genomics community has often accepted them as beneficial based on little direct clinical evidence. The rapid pace of genomic discovery has compounded the problem, because clinical trials can take years to complete. Often a lack of robust evidence has impeded adoption of genomic ad

Purpose: To assess the ability of My Family Health Portrait to accurately collect family history for six common heritable disorders. Background: Family history is useful to assess disease risk but is not widely used. We compared the pedigree from My Family Health Portrait, an online tool for collection of family history, to a pedigree supplemented by a genetics professional. Methods: One hundred fifty volunteers collected their family histories using My Family Health Portrait. A genetic counselor interviewed the volunteers to validate the entries and add diagnoses, as needed. The content and the affection assignments of the pedigrees were compared. The pedigrees were entered into Family HealthwareTM to assess risks for the diseases. Results: The sensitivity of My Family Health Portrait varied among the six diseases (67–100%) compared to the supplemented pedigree. The specificities ranged from 92 to 100%. When the pedigrees were used to generate risk scores, My Family Health Portrait yielded identical risks to the supplemented pedigree for 94–99% of the volunteers for diabetes and colon, breast, and ovarian cancer. The agreement was lower for coronary artery disease (68%) and stroke (83%). Conclusions: These data support the validity of My Family Health Portrait pedigrees for four common conditions—diabetes and colon, breast, and ovarian cancer. The tool performed less well for coronary artery disease and stroke. We recommend that the tool be improved to better capture information for these two common conditions.

This article reviews the medical conditions that are associated with adverse pregnancy outcomes for women and their offspring. We also present the degree to which specific preconception interventions and treatments can impact the effects of the condition on birth outcomes. Because avoiding, delaying, or achieving optimal timing of a pregnancy is often an important component of the preconception care of women with medical conditions, contraceptive considerations particular to the medical conditions are also presented.

Much has been learned over the past 1 0 years about the relevance of genomic variation to health, to the risk for both rare and common diseases, and to treatment responsiveness (Feero, Guttmacher, & Collins, 2010). The identification of genomic differences that play a role in disease provides information that is enhancing our understanding about the biology of disease, resulting in new and more personalized therapies and influencing healthcare decisions. Experts predict that expanding research discoveries coupled with new technologies will be effectively translated into approaches for clinical care (Green & Guyer, 2011). As this Journal of Nursing Scholarship (JNS) issue illustrates, it is important for the practicing nurse to be aware of this information now. Through its focus on health promotion, caring, and the understanding of individuals, including their relationships with families, the community, and society, nursing brings an important perspective to the application of genomics. Nurses have a responsibility to be informed and to inform other healthcare professionals, individuals, families, and communities of the potential benefits and challenges of genomics.Understanding the genomic science behind care decisions for conditions commonly seen by the practicing nurse has the potential to improve care outcomes. Many of these opportunities already exist (Figure), but much work remains to ensure the effective integration of genomic information in routine clinical practice. For example, the hypothetical patient Gabe has been admitted to the hospital for atrial fibrillation and is a candidate for pharmacogenomic testing to inform his warfarin dosing. The patient asks the nurse whether or not he should have this test. That nurse needs to know about the nature of the test, whether the results will influence decisions made about Gabe's treatment, the potential implications of test results for his family, and where to find more information to answer his questions and to contribute to his plan of care. Evidence suggests that the majority of nurses are unprepared to deal with these questions (Thompson & Brooks, 2011). Nurses play a role in creating an infrastructure that supports the delivery of services that utilize genomic information. They can also influence policies related to the utilization of genomic information through appreciation of the associated ethical, legal, and social issues. With a full understanding of the relevance as well as limitations of genomic information, nurses can play an important role in the application of genomics to clinical care.In the past, genetic and genomic testing was focused on small areas within the genome. However, the advent of "next-generation" DNA sequencing methods has led to remarkable reductions in the costs of genome sequencing (Pettersson, Lundeberg, &· Ahmadian, 2009; Snyder, Jiang Du, & Gerstein, 2010). Indeed, we are entering the era of the "$1,000 genome"- that is, the ability to sequence someone's entire genome for $1,000 or less (National Human Genome Research Institute, 2010), a cost rivaling many diagnostic tests and thus deemed realistic for routine clinical application. While these technology advances have to date outpaced our capacity for harnessing this information to improve health, the coming decade will bring a steady stream of examples where genomic information is shown to be a valued component of clinical practice (Phimister, Feero, & Guttmacher, 2012).The purpose of this Genomic Special Issue is to provide evidence reviews about the genomics of common healthcare conditions with relevance for nursing practice and services. This issue consists of articles that provide an overview of:* the current and emerging science and technology, such as whole-genome sequencing (with implications for international healthcare);* the state of the evidence about genomic variation and clinical applications for common diseases (e. …

‘Knockout' mice have been developed that lack the Huntington's disease gene, in an effort to gain insight into the disorder and into the pathophysiological effects of tri-nucleotide repeat expansion.

T’STHE“YEAROFPERFECTVISION,”2020.AMY,AGE21YEARS, visits with her physician and elects to have complete genomesequencing.Atafollow-upvisit,Amychoosesto learnofhergeneticriskfactorsforheartdisease,diabetes, breastcancer,andcoloncancer.Amy’sphysicianprovidesher with risk scores for those disorders, and with suggestions for lifestylemodifications.Specifically,Amyisalertedtoherparticularlyhighriskofdevelopingtype2diabetes,andherphy