Improving reporting standards for polygenic scores in risk prediction studies.

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

COVID-19-related health outcomes in people with primary immunodeficiency: A systematic review.

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.

Health equity in the implementation of genomics and precision medicine: A public health imperative.

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.

COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response.

The scientific response to the COVID-19 pandemic has produced an abundance of publications, including peer-reviewed articles and preprints, across a wide array of disciplines, from microbiology to medicine and social sciences. Genomics and precision health (GPH) technologies have had a particularly prominent role in medical and public health investigations and response; however, these domains are not simply defined and it is difficult to search for relevant information using traditional strategies. To quantify and track the ongoing contributions of GPH to the COVID-19 response, the Office of Genomics and Precision Public Health at the Centers for Disease Control and Prevention created the COVID-19 Genomics and Precision Health database (COVID-19 GPH), an open access knowledge management system and publications database that is continuously updated through machine learning and manual curation. As of February 11, 2022, COVID-GPH contained 31,597 articles, mostly on pathogen and human genomics (72%). The database also includes articles describing applications of machine learning and artificial intelligence to the investigation and control of COVID-19 (28%). COVID-GPH represents about 10% (22983/221241) of the literature on COVID-19 on PubMed. This unique knowledge management database makes it easier to explore, describe, and track how the pandemic response is accelerating the applications of genomics and precision health technologies. COVID-19 GPH can be freely accessed via https://phgkb.cdc.gov/PHGKB/coVInfoStartPage.action .

Emerging Concepts in Precision Medicine and Cardiovascular Diseases in Racial and Ethnic Minority Populations.

Cardiovascular diseases remain the leading cause of mortality and a major contributor to preventable deaths worldwide. The dominant modifiable risk factors and the social and environmental determinants that increase cardiovascular risk are known, and collectively, are as important in racial and ethnic minority populations as they are in majority populations. Their prevention and treatment remain the foundation for cardiovascular health promotion and disease prevention. Genetic and epigenetic factors are increasingly recognized as important contributors to cardiovascular risk and provide an opportunity for advancing precision cardiovascular medicine. In this review, we explore emerging concepts at the interface of precision medicine and cardiovascular disease in racial and ethnic minority populations. Important among these are the lack of racial and ethnic diversity in genomics studies and biorepositories; the resulting misclassification of benign variants as pathogenic in minorities; and the importance of ensuring ancestry-matched controls in variant interpretation. We address the relevance of epigenetics, pharmacogenomics, genetic testing and counseling, and their social and cultural implications. We also examine the potential impact of precision medicine on racial and ethnic disparities. The National Institutes of Health's All of Us Research Program and the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine Initiative are presented as examples of research programs at the forefront of precision medicine and diversity to explore research implications in minorities. We conclude with an overview of implementation research challenges in precision medicine and the ethical implications in minority populations. Successful implementation of precision medicine in cardiovascular disease in minority populations will benefit from strategies that directly address diversity and inclusion in genomics research and go beyond race and ethnicity to explore ancestry-matched controls, as well as geographic, cultural, social, and environmental determinants of health.

The intersection of genomics and big data with public health: Opportunities for precision public health.

Muin Khoury and co-authors discuss anticipated contributions of genomics and other forms of large-scale data in public health.

Evidence-based medicine and big genomic data.

Genomic and other related big data (Big Genomic Data, BGD for short) are ushering a new era of precision medicine. This overview discusses whether principles of evidence-based medicine hold true for BGD and how they should be operationalized in the current era. Major evidence-based medicine principles include the systematic identification, description and analysis of the validity and utility of BGD, the combination of individual clinical expertise with individual patient needs and preferences, and the focus on obtaining experimental evidence, whenever possible. BGD emphasize information of single patients with an overemphasis on N-of-1 trials to personalize treatment. However, large-scale comparative population data remain indispensable for meaningful translation of BGD personalized information. The impact of BGD on population health depends on its ability to affect large segments of the population. While several frameworks have been proposed to facilitate and standardize decision making for use of genomic tests, there are new caveats that arise from BGD that extend beyond the limitations that were applicable for more simple genetic tests. Non-evidence-based use of BGD may be harmful and result in major waste of healthcare resources. Randomized controlled trials will continue to be the strongest arbitrator for the clinical utility of genomic technologies, including BGD. Research on BGD needs to focus not only on finding robust predictive associations (clinical validity) but also more importantly on evaluating the balance of health benefits and potential harms (clinical utility), as well as implementation challenges. Appropriate features of such useful research on BGD are discussed.

Correction to: Communication about Hereditary Cancers on Social Media: a Content Analysis of Tweets about Hereditary Breast and Ovarian Cancer and Lynch Syndrome.

The original version of this article unfortunately contained mistakes.

Communication About Hereditary Cancers on Social Media: A Content Analysis of Tweets About Hereditary Breast and Ovarian Cancer and Lynch Syndrome.

Social media is increasingly being used as an information source and tool for individuals and organizations to share resources and engage in conversations about health topics. Because the public tends to learn about health topics and genetics from online social media sources, it is imperative to understand the amount, type, and quality of information being shared. We performed a retrospective analysis of tweets related to hereditary breast and ovarian cancer (HBOC) and Lynch syndrome (LS) between January 1, 2017 and December 31, 2017. A total of 63,770 tweets were included in our dataset. The majority were retweets (59.9%) and users came from 744 different cities. Most tweets were considered "informational" (51.4%) and were designed to provide resources to the public. Online communities (25%), organizations (20%), and providers or researchers (15%) were among the most common contributors. Our results demonstrated that conversations were primarily focused on information and resource sharing, along with individuals discussing their personal stories and testimonials about their experiences with these HBOC and LS. Future studies could consider ways to harness Twitter to help tailor and deliver health communication campaigns and education interventions to improve the public's understanding of these complex topics.

Prevalence and Predictors of Cholesterol Screening, Awareness, and Statin Treatment Among US Adults With Familial Hypercholesterolemia or Other Forms of Severe Dyslipidemia (1999-2014).

BACKGROUND: Familial hypercholesterolemia (FH) and other extreme elevations in low-density lipoprotein cholesterol significantly increase the risk of atherosclerotic cardiovascular disease; however, recent data suggest that prescription rates for statins remain low in these patients. National rates of screening, awareness, and treatment with statins among individuals with FH or severe dyslipidemia are unknown. METHODS: Data from the 1999 to 2014 National Health and Nutrition Examination Survey were used to estimate prevalence rates of self-reported screening, awareness, and statin therapy among US adults (n=42 471 weighted to represent 212 million US adults) with FH (defined using the Dutch Lipid Clinic criteria) and with severe dyslipidemia (defined as low-density lipoprotein cholesterol levels ≥190 mg/dL). Logistic regression was used to identify sociodemographic and clinical correlates of hypercholesterolemia awareness and statin therapy. RESULTS: The estimated US prevalence of definite/probable FH was 0.47% (standard error, 0.03%) and of severe dyslipidemia was 6.6% (standard error, 0.2%). The frequency of cholesterol screening and awareness was high (>80%) among adults with definite/probable FH or severe dyslipidemia; however, statin use was uniformly low (52.3% [standard error, 8.2%] of adults with definite/probable FH and 37.6% [standard error, 1.2%] of adults with severe dyslipidemia). Only 30.3% of patients with definite/probable FH on statins were taking a high-intensity statin. The prevalence of statin use in adults with severe dyslipidemia increased over time (from 29.4% to 47.7%) but not faster than trends in the general population (from 5.7% to 17.6%). Older age, health insurance status, having a usual source of care, diabetes mellitus, hypertension, and having a personal history of early atherosclerotic cardiovascular disease were associated with higher statin use. CONCLUSIONS: Despite the high prevalence of cholesterol screening and awareness, only ≈50% of adults with FH are on statin therapy, with even fewer prescribed a high-intensity statin; young and uninsured patients are at the highest risk for lack of screening and for undertreatment. This study highlights an imperative to improve the frequency of cholesterol screening and statin prescription rates to better identify and treat this high-risk population. Additional studies are needed to better understand how to close these gaps in screening and treatment.

Family History-Wide Association Study to Identify Clinical and Environmental Risk Factors for Common Chronic Diseases.

Family history is a strong risk factor for many common chronic diseases and summarizes shared environmental and genetic risk, but how this increased risk is mediated is unknown. We developed a "family history-wide association study" (FamWAS) to systematically and comprehensively test clinical and environmental quantitative traits (CEQTs) for their association with family history of disease. We implemented our method on 457 CEQTs for association with family history of diabetes, asthma, and coronary heart disease (CHD) in 42,940 adults spanning 8 waves of the 1999-2014 US National Health and Nutrition Examination Survey. We conducted pooled analyses of the 8 survey waves and analyzed trait associations using survey-weighted logistic regression. We identified 172 (37.6% of total), 32 (7.0%), and 78 (17.1%) CEQTs associated with family history of diabetes, asthma, and CHD, respectively, in subcohorts of individuals without the respective disease. Twenty associated CEQTs were shared across family history of diabetes, asthma, and CHD, far more than expected by chance. FamWAS can examine traits not previously studied in association with family history and uncover trait overlap, highlighting a putative shared mechanism by which family history influences disease risk.

The current state of funded NIH grants in implementation science in genomic medicine: a portfolio analysis.

PURPOSE: Implementation science offers methods to evaluate the translation of genomic medicine research into practice. The extent to which the National Institutes of Health (NIH) human genomics grant portfolio includes implementation science is unknown. This brief report's objective is to describe recently funded implementation science studies in genomic medicine in the NIH grant portfolio, and identify remaining gaps. METHODS: We identified investigator-initiated NIH research grants on implementation science in genomic medicine (funding initiated 2012-2016). A codebook was adapted from the literature, three authors coded grants, and descriptive statistics were calculated for each code. RESULTS: Forty-two grants fit the inclusion criteria (~1.75% of investigator-initiated genomics grants). The majority of included grants proposed qualitative and/or quantitative methods with cross-sectional study designs, and described clinical settings and primarily white, non-Hispanic study populations. Most grants were in oncology and examined genetic testing for risk assessment. Finally, grants lacked the use of implementation science frameworks, and most examined uptake of genomic medicine and/or assessed patient-centeredness. CONCLUSION: We identified large gaps in implementation science studies in genomic medicine in the funded NIH portfolio over the past 5 years. To move the genomics field forward, investigator-initiated research grants should employ rigorous implementation science methods within diverse settings and populations.

HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders.

Recent dramatic advances in multiomics research coupled with exponentially increasing volume, complexity, and interdisciplinary nature of publications are making it challenging for scientists to stay up-to-date on the literature. Strategies to address this challenge include the creation of online databases and warehouses to support timely and targeted dissemination of research findings. Although most of the early examples have been in cancer genomics and pharmacogenomics, the approaches used can be adapted to support investigators in heart, lung, blood, and sleep (HLBS) disorders research. In this article, we describe the creation of an HLBS population genomics (HLBS-PopOmics) knowledge base as an online, continuously updated, searchable database to support the dissemination and implementation of studies and resources that are relevant to clinical and public health practice. In addition to targeted searches based on the HLBS disease categories, cross-cutting themes reflecting the ethical, legal, and social implications of genomics research; systematic evidence reviews; and clinical practice guidelines supporting screening, detection, evaluation, and treatment are also emphasized in HLBS-PopOmics. Future updates of the knowledge base will include additional emphasis on transcriptomics, proteomics, metabolomics, and other omics research; explore opportunities for leveraging data sets designed to support scientific discovery; and incorporate advanced machine learning bioinformatics capabilities.

Evaluating the role of public health in implementation of genomics-related recommendations: a case study of hereditary cancers using the CDC Science Impact Framework.

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.

Cancer communication research in the era of genomics and precision medicine: a scoping review.

Effective use of genetic and genomic data in cancer prevention and treatment depends on adequate communication with patients and the public. Although relevant empirical work has emerged, the scope and outcomes of this communication research have not been characterized. We conducted a comprehensive scoping review of recent published research (2010-2017) on communication of cancer-related genetic and genomic testing (CGT) information. Searches in six databases revealed 9243 unique records; 513 papers were included. Most papers utilized an observational quantitative design; fewer utilized an experimental design. More attention has been paid to outcomes of CGT results disclosure than to decision making regarding CGT uptake or the process of results disclosure. Psychosocial outcomes were most common across studies. This literature has a strong focus on BRCA1/2, with few papers focused on Lynch syndrome or next-generation technologies. Women, Caucasians, older adults, and those of higher socioeconomic status were overrepresented. Research gaps identified include the need for studies on the process of CGT communication; examining behavioral, decision making, and communication outcomes; and inclusion of diverse populations. Addressing these gaps can help improve the use of genomics in cancer control and reduce disparities in access to and use of CGT.

Reproducible Research Practices and Transparency across the Biomedical Literature.

There is a growing movement to encourage reproducibility and transparency practices in the scientific community, including public access to raw data and protocols, the conduct of replication studies, systematic integration of evidence in systematic reviews, and the documentation of funding and potential conflicts of interest. In this survey, we assessed the current status of reproducibility and transparency addressing these indicators in a random sample of 441 biomedical journal articles published in 2000-2014. Only one study provided a full protocol and none made all raw data directly available. Replication studies were rare (n = 4), and only 16 studies had their data included in a subsequent systematic review or meta-analysis. The majority of studies did not mention anything about funding or conflicts of interest. The percentage of articles with no statement of conflict decreased substantially between 2000 and 2014 (94.4% in 2000 to 34.6% in 2014); the percentage of articles reporting statements of conflicts (0% in 2000, 15.4% in 2014) or no conflicts (5.6% in 2000, 50.0% in 2014) increased. Articles published in journals in the clinical medicine category versus other fields were almost twice as likely to not include any information on funding and to have private funding. This study provides baseline data to compare future progress in improving these indicators in the scientific literature.

Correction: A collaborative translational research framework for evaluating and implementing the appropriate use of human genome sequencing to improve health.

[This corrects the article DOI: 10.1371/journal.pmed.1002631.].

A collaborative translational research framework for evaluating and implementing the appropriate use of human genome sequencing to improve health.

In a Policy Forum, Muin Khoury and colleagues discuss research on the clinical application of genome sequencing data.

The contribution of family history to the burden of diagnosed diabetes, undiagnosed diabetes, and prediabetes in the United States: analysis of the National Health and Nutrition Examination Survey, 2009-2014.

PURPOSE: Given the importance of family history in the early detection and prevention of type 2 diabetes, we quantified the public health impact of reported family health history on diagnosed diabetes (DD), undiagnosed diabetes (UD), and prediabetes (PD) in the United States. METHODS: We used population data from the National Health and Nutrition Examination Survey 2009-2014 to measure the association of reported family history of diabetes with DD, UD, and PD. RESULTS: Using polytomous logistic regression and multivariable adjustment, family history prevalence ratios were 4.27 (confidence interval (CI): 3.57, 5.12) for DD, 2.03 (CI: 1.56, 2.63) for UD, and 1.26 (CI: 1.09, 1.44) for PD. In the United States, we estimate that 10.1 million DD cases, 1.4 million UD cases, and 3.9 million PD cases can be attributed to having a family history of diabetes. CONCLUSION: These findings confirm that family history of diabetes has a major public health impact on diabetes in the United States. In spite of the recent interest and focus on genomics and precision medicine, family health history continues to be an integral component of public health campaigns to identify persons at high risk for developing type 2 diabetes and early detection of diabetes to prevent or delay complications.

A proposed approach to accelerate evidence generation for genomic-based technologies in the context of a learning health system.

Genomic technologies should demonstrate analytical and clinical validity and clinical utility prior to wider adoption in clinical practice. However, the question of clinical utility remains unanswered for many genomic technologies. In this paper, we propose three building blocks for rapid generation of evidence on clinical utility of promising genomic technologies that underpin clinical and policy decisions. We define promising genomic tests as those that have proven analytical and clinical validity. First, risk-sharing agreements could be implemented between payers and manufacturers to enable temporary coverage that would help incorporate promising technologies into routine clinical care. Second, existing data networks, such as the Sentinel Initiative and the National Patient-Centered Clinical Research Network (PCORnet) could be leveraged, augmented with genomic information to track the use of genomic technologies and monitor clinical outcomes in millions of people. Third, endorsement and engagement from key stakeholders will be needed to establish this collaborative model for rapid evidence generation; all stakeholders will benefit from better information regarding the clinical utility of these technologies. This collaborative model can create a multipurpose and reusable national resource that generates knowledge from data gathered as part of routine care to drive evidence-based clinical practice and health system changes.