Last data update: Apr 22, 2024. (Total: 46599 publications since 2009)
Records 1-18 (of 18 Records) |
Query Trace: Clyne M [original query] |
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Adolescent with COVID-19 as the Source of an Outbreak at a 3-Week Family Gathering - Four States, June-July 2020.
Schwartz NG , Moorman AC , Makaretz A , Chang KT , Chu VT , Szablewski CM , Yousaf AR , Brown MM , Clyne A , DellaGrotta A , Drobeniuc J , Korpics J , Muir A , Drenzek C , Bandy U , Kirking HL , Tate JE , Hall AJ , Lanzieri TM , Stewart RJ . MMWR Morb Mortal Wkly Rep 2020 69 (40) 1457-1459 There is increasing evidence that children and adolescents can efficiently transmit SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) (1-3). During July-August 2020, four state health departments and CDC investigated a COVID-19 outbreak that occurred during a 3-week family gathering of five households in which an adolescent aged 13 years was the index and suspected primary patient; 11 subsequent cases occurred. |
Limited Secondary Transmission of SARS-CoV-2 in Child Care Programs - Rhode Island, June 1-July 31, 2020.
Link-Gelles R , DellaGrotta AL , Molina C , Clyne A , Campagna K , Lanzieri TM , Hast MA , Palipudi K , Dirlikov E , Bandy U . MMWR Morb Mortal Wkly Rep 2020 69 (34) 1170-1172 On June 1, 2020, with declines in coronavirus disease 2019 (COVID-19) cases and hospitalizations in Rhode Island,* child care programs in the state reopened after a nearly 3-month closure implemented as part of mitigation efforts. To reopen safely, the Rhode Island Department of Human Services (RIDHS) required licensed center- and home-based child care programs to reduce enrollment, initially to a maximum of 12 persons, including staff members, in stable groups (i.e., staff members and students not switching between groups) in physically separated spaces, increasing to a maximum of 20 persons on June 29. Additional requirements included universal use of masks for adults, daily symptom screening of adults and children, and enhanced cleaning and disinfection according to CDC guidelines.(†) As of July 31, 666 of 891 (75%) programs were approved to reopen, with capacity for 18,945 children, representing 74% of the state's January 2020 child care program population (25,749 children). |
Tracking human genes along the translational continuum.
Lee K , Clyne M , Yu W , Lu Z , Khoury MJ . NPJ Genom Med 2019 4 25 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. |
Using deep learning to identify translational research in genomic medicine beyond bench to bedside.
Hsu YY , Clyne M , Wei CH , Khoury MJ , Lu Z . Database (Oxford) 2019 2019 Tracking scientific research publications on the evaluation, utility and implementation of genomic applications is critical for the translation of basic research to impact clinical and population health. In this work, we utilize state-of-the-art machine learning approaches to identify translational research in genomics beyond bench to bedside from the biomedical literature. We apply the convolutional neural networks (CNNs) and support vector machines (SVMs) to the bench/bedside article classification on the weekly manual annotation data of the Public Health Genomics Knowledge Base database. Both classifiers employ salient features to determine the probability of curation-eligible publications, which can effectively reduce the workload of manual triage and curation process. We applied the CNNs and SVMs to an independent test set (n = 400), and the models achieved the F-measure of 0.80 and 0.74, respectively. We further tested the CNNs, which perform better results, on the routine annotation pipeline for 2 weeks and significantly reduced the effort and retrieved more appropriate research articles. Our approaches provide direct insight into the automated curation of genomic translational research beyond bench to bedside. The machine learning classifiers are found to be helpful for annotators to enhance the efficiency of manual curation. |
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.
Mensah GA , Yu W , Barfield WL , Clyne M , Engelgau MM , Khoury MJ . Genet Med 2018 21 (3) 519-524 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. |
Proposed outcomes measures for state public health genomic programs.
Doyle DL , Clyne M , Rodriguez JL , Cragun DL , Senier L , Hurst G , Chan K , Chambers DA . Genet Med 2018 20 (9) 995-1003 PurposeTo assess the implementation of evidence-based genomic medicine and its population-level impact on health outcomes and to promote public health genetics interventions, in 2015 the Roundtable on Genomics and Precision Health of the National Academies of Sciences, Engineering, and Medicine formed an action collaborative, the Genomics and Public Health Action Collaborative (GPHAC). This group engaged key stakeholders from public/population health agencies, along with experts in the fields of health disparities, health literacy, implementation science, medical genetics, and patient advocacy.MethodsIn this paper, we present the efforts to identify performance objectives and outcome metrics. Specific attention is placed on measures related to hereditary breast ovarian cancer (HBOC) syndrome and Lynch syndrome (LS), two conditions with existing evidence-based genomic applications that can have immediate impact on morbidity and mortality.ResultsOur assessment revealed few existing outcome measures. Therefore, using an implementation research framework, 38 outcome measures were crafted.ConclusionEvidence-based public health requires outcome metrics, yet few exist for genomics. Therefore, we have proposed performance objectives that states might use and provided examples of a few state-level activities already under way, which are designed to collect outcome measures for HBOC and LS.GENETICS in MEDICINE advance online publication, 4 January 2018; doi:10.1038/gim.2017.229. |
From public health genomics to precision public health: a 20-year journey.
Khoury MJ , Bowen MS , Clyne M , Dotson WD , Gwinn ML , Green RF , Kolor K , Rodriguez JL , Wulf A , Yu W . Genet Med 2017 20 (6) 574-582 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. |
The current state of funded NIH grants in implementation science in genomic medicine: a portfolio analysis.
Roberts MC , Clyne M , Kennedy AE , Chambers DA , Khoury MJ . Genet Med 2017 21 (5) 1218-1223 PurposeImplementation 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.MethodsWe 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.ResultsForty-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.ConclusionWe 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.Genetics in Medicine advance online publication, 26 October 2017; doi:10.1038/gim.2017.180. |
Trends in published meta-analyses in cancer research, 2008-2013.
Qadir XV , Clyne M , Lam TK , Khoury MJ , Schully SD . Cancer Causes Control 2016 28 (1) 5-12 In order to capture trends in the contribution of epidemiology to cancer research, we describe an online meta-analysis database resource for cancer clinical and population research and illustrate trends and descriptive detail of cancer meta-analyses from 2008 through 2013. A total of 4,686 cancer meta-analyses met our inclusion criteria. During this 6-year period, a fivefold increase was observed in the yearly number of meta-analyses. Fifty-six percent of meta-analyses concerned observational studies, mostly of cancer risk, more than half of which were genetic studies. The major cancer sites were breast, colorectal, and digestive. This online database for Cancer Genomics and Epidemiology Navigator will be continuously updated to allow investigators to quickly navigate the meta-analyses emerging from cancer epidemiology studies and cancer clinical trials. |
A knowledge base for tracking the impact of genomics on population health.
Yu W , Gwinn M , Dotson WD , Green RF , Clyne M , Wulf A , Bowen S , Kolor K , Khoury MJ . Genet Med 2016 18 (12) 1312-1314 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. |
The Cancer Genomics and Epidemiology Navigator: An NCI online tool to enhance cancer epidemiology research.
Schully SD , Rogers SD , Lam TK , Chang CQ , Clyne M , Cyr J , Watson D , Khoury MJ . Cancer Epidemiol Biomarkers Prev 2014 23 (11) 2610-1 The Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) has undergone strategic planning in an effort to transform the practice of cancer epidemiology in the 21st century [1]. Through these efforts, the program has focused on the need for knowledge integration across the various disciplines that comprise cancer epidemiology [2]. To this end, EGRP has released an online tool for the cancer epidemiology community; the Cancer Genomics and Epidemiology Navigator (CGEN, http://epi.grants.cancer.gov/cgen/) which is an integrated, searchable, and regularly updated knowledge base intended to facilitate cancer epidemiologic research. | CGEN collates linked data on EGRP-funded grants, peer-reviewed publications on cancer epidemiology, publications on human genome epidemiology, and genomic evidence-based guidelines and recommendations into a centralized search engine to assess the impact of genomic, environmental and clinical factors on cancer occurrence and outcomes. CGEN has full text searching and filtering capabilities that make it possible to search data fields across all data sources within the database. Additionally, filtering options equipped with graphs and real-time counts permit users to fine-tune searches, or export faceted (filtered) data for further processing. An advanced search is available to perform phrase matching or matching on any/all/none of the provided terms, or when field-level search granularity is necessary. CGEN also identifies links between publications and grants, and between publications and other sources of data. |
A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes.
Chang CQ , Yesupriya A , Rowell JL , Pimentel CB , Clyne M , Gwinn M , Khoury MJ , Wulf A , Schully SD . Eur J Hum Genet 2014 22 (3) 402-8 Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities≤0.2) and accounting for indirect overlap, we found 202 associations, with 27 of those appearing in both meta-analyses and GWAS. Our findings suggest that meta-analyses of well-conducted candidate gene studies may continue to add to our understanding of the genetic associations in the post-GWAS era. |
Horizon scanning for translational genomic research beyond bench to bedside.
Clyne M , Schully SD , Dotson WD , Douglas MP , Gwinn M , Kolor K , Wulf A , Bowen MS , Khoury MJ . Genet Med 2014 16 (7) 535-8 PURPOSE: The dizzying pace of genomic discoveries is leading to an increasing number of clinical applications. In this report, we provide a method for horizon scanning and 1 year data on translational research beyond bench to bedside to assess the validity, utility, implementation, and outcomes of such applications. METHODS: We compiled cross-sectional results of ongoing horizon scanning of translational genomic research, conducted between 16 May 2012 and 15 May 2013, based on a weekly, systematic query of PubMed. A set of 505 beyond bench to bedside articles were collected and classified, including 312 original research articles; 123 systematic and other reviews; 38 clinical guidelines, policies, and recommendations; and 32 articles describing tools, decision support, and educational materials. RESULTS: Most articles (62%) addressed a specific genomic test or other health application; almost half of these (n = 180) were related to cancer. We estimate that these publications account for 0.5% of reported human genomics and genetics research during the same time. CONCLUSION: These data provide baseline information to track the evolving knowledge base and gaps in genomic medicine. Continuous horizon scanning of the translational genomics literature is crucial for an evidence-based translation of genomics discoveries into improved health care and disease prevention. |
Prioritizing genomic applications for action by level of evidence: a horizon-scanning method.
Dotson WD , Douglas MP , Kolor K , Stewart AC , Bowen MS , Gwinn M , Wulf A , Anders HM , Chang CQ , Clyne M , Lam TK , Schully SD , Marrone M , Feero WG , Khoury MJ . Clin Pharmacol Ther 2013 95 (4) 394-402 As evidence accumulates on the use of genomic tests and other health-related applications of genomic technologies, decision makers may increasingly seek support in identifying which applications have sufficiently robust evidence to suggest they might be considered for action. As an interim working process to provide such support, we developed a horizon-scanning method that assigns genomic applications to tiers defined by availability of synthesized evidence. We illustrate an application of the method to pharmacogenomics tests. |
Genetic epidemiology with a capital E, ten years after.
Khoury MJ , Gwinn M , Clyne M , Yu W . Genet Epidemiol 2011 35 (8) 845-52 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.) |
Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies.
Schully SD , Yu W , McCallum V , Benedicto CB , Dong LM , Wulf A , Clyne M , Khoury MJ . Eur J Hum Genet 2011 19 (8) 928-30 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. |
Trends in pharmacogenomic epidemiology: 2001-2007.
Guessous I , Gwinn M , Yu W , Yeh J , Clyne M , Khoury MJ . Public Health Genomics 2009 12 (3) 142-8 BACKGROUND: Pharmacogenomic epidemiology (PGxE) assesses the range of responses to pharmacologic agents in relation to genetic variation in population groups. We analyzed publication trends to describe the emerging field of PGxE. METHODS: We analyzed PGxE literature published from 2001 to 2007 by using the HuGE Navigator, a curated database of abstracts on human genome epidemiology extracted from PubMed. We summarized trends by gene and study design and, for the 4 most cited genes, by associated health outcomes and drugs. RESULTS: In all, 1,855 PGxE articles were indexed from 2001 through 2007, with annual publications increasing more than 15-fold during this period. Observational studies outnumbered clinical trials by a ratio of 10 to 1 (1,660 vs. 178). Just 4 genes together accounted for nearly one-fifth of all publications: ABCB1, CYP2C9, CYP2C19, and CYP2D6. For these 4 genes, the most frequently cited therapeutic category was antineoplastic agent, followed by anticoagulant, antiulcer, and antidepressant. Warfarin was the single most frequently cited drug. CONCLUSIONS: The field of PGxE is growing rapidly, encompassing a large spectrum of diseases and drugs important in clinical practice. Systematic tracking and synthesis of the published literature in PGxE can help identify promising applications and guide translation research. |
Phenopedia and Genopedia: disease-centered and gene-centered views of the evolving knowledge of human genetic associations.
Yu W , Clyne M , Khoury MJ , Gwinn M . Bioinformatics 2009 26 (1) 145-6 SUMMARY: We developed Web-based applications that encourage the exploration of the literature on human genetic associations by using a database that is continuously updated from PubMed. These applications provide user-friendly interfaces for searching summarized information on human genetic associations, using either genes or diseases as the starting point. AVAILABILITY: Phenopedia and Genopedia can be freely accessed at http://www.hugenavigator.net/HuGENavigator/startPagePhenoPedia.do and http://www.hugenavigator.net/HuGENavigator/startPagePedia.do, respectively. CONTACT: wby0@cdc.gov. |
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