Since its beginning more than 75 years ago [1], epigenetics has been an evolving field with growing applications to the study of cancer, aging, and gene expression in response to environmental exposures. The emergence of high-throughput technology for measuring epigenetic markers has enabled population-based studies [2]. The relatively new field of epigenetic epidemiology investigates epigenetic associations from a population perspective for insights into disease risk, prevention, and progression. Unlike genetic variants, epigenetic markers are dynamic, offering epidemiologists a new approach to linking early life and environmental exposures with disease risk [3]. | | Scientific publications on epigenetic epidemiology have been rapidly increasing in number and variety over the past 20 years. The literature now includes studies of epigenetic markers beyond DNA methylation (DNAm), such as histone modification and non-coding RNA, and consists of a variety of study designs including epigenome-wide association studies (EWAS), candidate gene studies, and clinical trials. Epigenetic markers are investigated as risk factors, such as DNAm in association with type 2 diabetes incidence [4], or outcomes, such as DNAm changes in response to air pollution [5]. The objective of the Epigenetic Epidemiology Publications Database (EEPD) is to offer a user-friendly website to explore the expanding literature in epigenetics, epidemiology, and public health.

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.

Understanding the drivers of research on human genes is a critical component to success of translation efforts of genomics into medicine and public health. Using publicly available curated online databases we sought to identify specific genes that are featured in translational genetic research in comparison to all genomics research publications. Articles in the CDC's Public Health Genomics and Precision Health Knowledge Base were stratified into studies that have moved beyond basic research to population and clinical epidemiologic studies (T1: clinical and population human genome epidemiology research), and studies that evaluate, implement, and assess impact of genes in clinical and public health areas (T2+: beyond bench to bedside). We examined gene counts and numbers of publications within these phases of translation in comparison to all genes from Medline. We are able to highlight those genes that are moving from basic research to clinical and public health translational research, namely in cancer and a few genetic diseases with high penetrance and clinical actionability. Identifying human genes of translational value is an important step towards determining an evidence-based trajectory of the human genome in clinical and public health practice over time.

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.

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.GENETICS in MEDICINE advance online publication, 14 December 2017; doi:10.1038/gim.2017.211.

OBJECTIVE: This study leveraged a state workers' compensation claims database and machine learning techniques to target prevention efforts by injury causation and industry. METHODS: Injury causation auto-coding methods were developed to code more than 1.2 million Ohio Bureau of Workers' Compensation claims for this study. Industry groups were ranked for soft-tissue musculoskeletal claims that may have been preventable with biomechanical ergonomic (ERGO) or slip/trip/fall (STF) interventions. RESULTS: On the basis of the average of claim count and rate ranks for more than 200 industry groups, Skilled Nursing Facilities (ERGO) and General Freight Trucking (STF) were the highest risk for lost-time claims (>7 days). CONCLUSION: This study created a third, major causation-specific U.S. occupational injury surveillance system. These findings are being used to focus prevention resources on specific occupational injury types in specific industry groups, especially in Ohio. Other state bureaus or insurers may use similar methods.

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.

Pathogen genetics is already a mainstay of public health investigation and control efforts; now advances in technology make it possible to investigate the role of human genetic variation in the epidemiology of infectious diseases. To describe trends in this field, we analyzed articles that were published from 2001 through 2010 and indexed by the HuGE Navigator, a curated online database of PubMed abstracts in human genome epidemiology. We extracted the principal findings from all meta-analyses and genome-wide association studies (GWAS) with an infectious disease-related outcome. Finally, we compared the representation of diseases in HuGE Navigator with their contributions to morbidity worldwide. We identified 3,730 articles on infectious diseases, including 27 meta-analyses and 23 GWAS. The number published each year increased from 148 in 2001 to 543 in 2010 but remained a small fraction (about 7%) of all studies in human genome epidemiology. Most articles were by authors from developed countries, but the percentage by authors from resource-limited countries increased from 9% to 25% during the period studied. The most commonly studied diseases were HIV/AIDS, tuberculosis, hepatitis B infection, hepatitis C infection, sepsis, and malaria. As genomic research methods become more affordable and accessible, population-based research on infectious diseases will be able to examine the role of variation in human as well as pathogen genomes. This approach offers new opportunities for understanding infectious disease susceptibility, severity, treatment, control, and prevention.

More than a decade after Duncan Thomas gave his presidential address at the International Society for Genetic Epidemiology entitled "Genetic Epidemiology with a Capital E," genetic epidemiology has gone mainstream. Epidemiology has taken its place not only in gene discovery studies but also in characterizing genetic effects and gene-environment interactions in populations. Furthermore, epidemiologic principles are being applied to the evaluation of genetic tests. We used an online informatics tool, the HuGE Navigator, to describe the growth in the field in the past decade. We developed the HuGE Navigator as a means to continuously monitor the evolving information obtained from epidemiologic studies of the human genome. Between 2001 and 2010, the HuGE Navigator included 57,005 articles published in 2,396 journals. During that period, the annual number of publications increased almost four-fold. The articles included 986 genome-wide association studies and 1,879 meta-analyses of gene-disease associations. The total number of authors of published studies grew from 12,907 in 2001 to 48,389 in 2010. The number of diseases also increased over time, from 697 medical subject headings in 2001 to 1,404 in 2010. Gene-environment interaction was mentioned explicitly in 17% of published abstracts, almost half of which focused on gene-drug interactions. Clearly, genetic epidemiology has gone "capital E" in the past decade; however, the ever-expanding volume and variety of genomic information poses a formidable challenge for developing appropriate methods for analysis, synthesis, and inference on complex genetic and environmental effects. We extend Duncan Thomas' capital E to include "Evaluation" as the tools of epidemiology are increasingly used to assess how genome-based information can be applied in medicine and public health. (Genet. Epidemiol. 35:845-852, 2011. (c) 2011 Wiley Periodicals, Inc.)

In the field of cancer, genetic association studies are among the most active and well-funded research areas, and have produced hundreds of genetic associations, especially in the genome-wide association studies (GWAS) era. Knowledge synthesis of these discoveries is the first critical step in translating the rapidly emerging data from cancer genetic association research into potential applications for clinical practice. To facilitate the effort of translational research on cancer genetics, we have developed a continually updated database named Cancer Genome-wide Association and Meta Analyses database that contains key descriptive characteristics of each genetic association extracted from published GWAS and meta-analyses relevant to cancer risk. Here we describe the design and development of this tool with the aim of aiding the cancer research community to quickly obtain the current updated status in cancer genetic association studies.

Genome-wide association studies (GWAS) have successfully identified numerous genetic loci that are associated with phenotypic traits and diseases. GWAS Integrator is a bioinformatics tool that integrates information on these associations from the National Human Genome Research institute (NHGRI) Catalog, SNAP (SNP Annotation and Proxy Search), and the Human Genome Epidemiology (HuGE) Navigator literature database. This tool includes robust search and data mining functionalities that can be used to quickly identify relevant associations from GWAS, as well as proxy single-nucleotide polymorphisms (SNPs) and potential candidate genes. Query-based University of California Santa Cruz (UCSC) Genome Browser custom tracks are generated dynamically on the basis of users' selected GWAS hits or candidate genes from HuGE Navigator literature database (http://www.hugenavigator.net/HuGENavigator/gWAHitStartPage.do). The GWAS Integrator may help enhance inference on potential genetic associations identified from GWAS studies. European Journal of Human Genetics advance online publication, 25 May 2011; doi:10.1038/ejhg.2011.91.

PURPOSE: The development of health-related genomic tests is decentralized and dynamic, involving government, academic, and commercial entities. Consequently, it is not easy to determine which tests are in development, currently available, or discontinued. We developed and assessed the usefulness of a systematic approach to identifying new genomic tests on the Internet. METHODS: We devised targeted queries of Web pages, newspaper articles, and blogs (Google Alerts) to identify new genomic tests. We finalized search and review procedures during a pilot phase that ended in March 2010. Queries continue to run daily and are compiled weekly; selected data are indexed in an online database, the Genomic Applications in Practice and Prevention Finder. RESULTS: After the pilot phase, our scan detected approximately two to three new genomic tests per week. Nearly two thirds of all tests (122/188, 65%) were related to cancer; only 6% were related to hereditary disorders. Although 88 (47%) of the tests, including 2 marketed directly to consumers, were commercially available, only 12 (6%) claimed United States Food and Drug Administration licensure. CONCLUSION: Systematic surveillance of the Internet provides information about genomic tests that can be used in combination with other resources to evaluate genomic tests. The Genomic Applications in Practice and Prevention Finder makes this information accessible to a wide group of stakeholders.