Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-30 (of 62 Records) |
Query Trace: Gwinn M[original query] |
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Navigating epigenetic epidemiology publications
Yu Wei , Drzymalla Emily , Gyorfy Matheus Fernandes , Khoury Muin J , Sun Yan V , Gwinn Marta . Epigenetics Commun 2023 3 (1) 8 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. |
Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement.
Little J , Higgins JP , Ioannidis JP , Moher D , Gagnon F , von Elm E , Khoury MJ , Cohen B , Davey-Smith G , Grimshaw J , Scheet P , Gwinn M , Williamson RE , Zou GY , Hutchings K , Johnson CY , Tait V , Wiens M , Golding J , van Duijn C , McLaughlin J , Paterson A , Wells G , Fortier I , Freedman M , Zecevic M , King R , Infante-Rivard C , Stewart AF , Birkett N . J Clin Epidemiol 2009 62 (6) 597-608.e4 Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis. |
STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement.
Little J , Higgins JP , Ioannidis JP , Moher D , Gagnon F , von Elm E , Khoury MJ , Cohen B , Davey-Smith G , Grimshaw J , Scheet P , Gwinn M , Williamson RE , Zou GY , Hutchings K , Johnson CY , Tait V , Wiens M , Golding J , van Duijn C , McLaughlin J , Paterson A , Wells G , Fortier I , Freedman M , Zecevic M , King R , Infante-Rivard C , Stewart A , Birkett N . Ann Intern Med 2009 150 (3) 206-15 Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis. |
Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement.
Little J , Higgins JP , Ioannidis JP , Moher D , Gagnon F , von Elm E , Khoury MJ , Cohen B , Davey-Smith G , Grimshaw J , Scheet P , Gwinn M , Williamson RE , Zou GY , Hutchings K , Johnson CY , Tait V , Wiens M , Golding J , van Duijn C , McLaughlin J , Paterson A , Wells G , Fortier I , Freedman M , Zecevic M , King R , Infante-Rivard C , Stewart A , Birkett N . Hum Genet 2009 125 (2) 131-51 Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis. |
STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement.
Little J , Higgins JP , Ioannidis JP , Moher D , Gagnon F , von Elm E , Khoury MJ , Cohen B , Davey-Smith G , Grimshaw J , Scheet P , Gwinn M , Williamson RE , Zou GY , Hutchings K , Johnson CY , Tait V , Wiens M , Golding J , van Duijn C , McLaughlin J , Paterson A , Wells G , Fortier I , Freedman M , Zecevic M , King R , Infante-Rivard C , Stewart A , Birkett N . PLoS Med 2009 6 (2) e22 Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis. |
Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement.
Little J , Higgins JP , Ioannidis JP , Moher D , Gagnon F , von Elm E , Khoury MJ , Cohen B , Davey-Smith G , Grimshaw J , Scheet P , Gwinn M , Williamson RE , Zou GY , Hutchings K , Johnson CY , Tait V , Wiens M , Golding J , van Duijn C , McLaughlin J , Paterson A , Wells G , Fortier I , Freedman M , Zecevic M , King R , Infante-Rivard C , Stewart A , Birkett N . Eur J Epidemiol 2009 24 (1) 37-55 Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis. |
STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement.
Little J , Higgins JP , Ioannidis JP , Moher D , Gagnon F , von Elm E , Khoury MJ , Cohen B , Davey-Smith G , Grimshaw J , Scheet P , Gwinn M , Williamson RE , Zou GY , Hutchings K , Johnson CY , Tait V , Wiens M , Golding J , van Duijn C , McLaughlin J , Paterson A , Wells G , Fortier I , Freedman M , Zecevic M , King R , Infante-Rivard C , Stewart A , Birkett N . Eur J Clin Invest 2009 39 (4) 247-66 Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis. |
COVID-19-Related manuscripts: lag from preprint to publication.
Drzymalla E , Yu W , Khoury MJ , Gwinn M . BMC Res Notes 2022 15 (1) 340 OBJECTIVE: Preprints have had a prominent role in the swift scientific response to COVID-19. Two years into the pandemic, we investigated how much preprints had contributed to timely data sharing by analyzing the lag time from preprint posting to journal publication. RESULTS: To estimate the median number of days between the date a manuscript was posted as a preprint and the date of its publication in a scientific journal, we analyzed preprints posted from January 1, 2020, to December 31, 2021 in the NIH iSearch COVID-19 Portfolio database and performed a Kaplan-Meier (KM) survival analysis using a non-mixture parametric cure model. Of the 39,243 preprints in our analysis, 7712 (20%) were published in a journal, after a median lag of 178 days (95% CI: 175-181). Most of the published preprints were posted on the bioRxiv (29%) or medRxiv (65%) servers, which allow authors to choose a subject category when posting. Of the 20,698 preprints posted on these two servers, 7358 (36%) were published, including approximately half of those categorized as biochemistry, biophysics, and genomics, which became published articles within the study interval, compared with 29% categorized as epidemiology and 26% as bioinformatics. |
Epigenome-wide association study of biomarkers of liver function identifies albumin-associated DNA methylation sites among male veterans with HIV.
Titanji BK , Lee M , Wang Z , Chen J , Hui Q , Lo Re Iii V , So-Armah K , Justice AC , Xu K , Freiberg M , Gwinn M , Marconi VC , Sun YV . Front Genet 2022 13 1020871 Background: Liver disease (LD) is an important cause of morbidity and mortality for people with HIV (PWH). The molecular factors linked with LD in PWH are varied and incompletely characterized. We performed an epigenome-wide association study (EWAS) to identify associations between DNA methylation (DNAm) and biomarkers of liver function-aspartate transaminase, alanine transaminase, albumin, total bilirubin, platelet count, FIB-4 score, and APRI score-in male United States veterans with HIV. Methods: Blood samples and clinical data were obtained from 960 HIV-infected male PWH from the Veterans Aging Cohort Study. DNAm was assessed using the Illumina 450K or the EPIC 850K array in two mutually exclusive subsets. We performed a meta-analysis for each DNAm site measured by either platform. We also examined the associations between four measures of DNAm age acceleration (AA) and liver biomarkers. Results: Nine DNAm sites were positively associated with serum albumin in the meta-analysis of the EPIC and 450K EWAS after correcting for multiple testing. Four DNAm sites (cg16936953, cg18942579, cg01409343, and cg12054453), annotated within the TMEM49 and four of the remaining five sites (cg18181703, cg03546163, cg20995564, and cg23966214) annotated to SOCS3, FKBP5, ZEB2, and SAMD14 genes, respectively. The DNAm site, cg12992827, was not annotated to any known coding sequence. No significant associations were detected for the other six liver biomarkers. Higher PhenoAA was significantly associated with lower level of serum albumin (β = -0.007, p-value = 8.6 × 10(-4), CI: -0.011116, -0.002884). Conclusion: We identified epigenetic associations of both individual DNAm sites and DNAm AA with liver function through serum albumin in men with HIV. Further replication analyses in independent cohorts are warranted to confirm the epigenetic mechanisms underlying liver function and LD in PWH. |
COVID-19 GPH: tracking the contribution of genomics and precision health to the COVID-19 pandemic response.
Yu W , Drzymalla E , Gwinn M , Khoury MJ . BMC Infect Dis 2022 22 (1) 402 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 . |
Sexual Differences in Genetic Predisposition of Coronary Artery Disease.
Huang Yunfeng, Hui Qin, Gwinn Marta, Hu Yi-Juan, Quyyumi Arshed A, Vaccarino Viola, Sun Yan V. Circulation. Genomic and precision medicine 2020 14(1) e003147 . Circulation. Genomic and precision medicine 2020 14(1) e003147 Huang Yunfeng, Hui Qin, Gwinn Marta, Hu Yi-Juan, Quyyumi Arshed A, Vaccarino Viola, Sun Yan V. Circulation. Genomic and precision medicine 2020 14(1) e003147 |
Invited review: human air-liquid-interface organotypic airway tissue models derived from primary tracheobronchial epithelial cells-overview and perspectives
Cao X , Coyle JP , Xiong R , Wang Y , Heflich RH , Ren B , Gwinn WM , Hayden P , Rojanasakul L . In Vitro Cell Dev Biol Anim 2020 57 (2) 1-29 The lung is an organ that is directly exposed to the external environment. Given the large surface area and extensive ventilation of the lung, it is prone to exposure to airborne substances, such as pathogens, allergens, chemicals, and particulate matter. Highly elaborate and effective mechanisms have evolved to protect and maintain homeostasis in the lung. Despite these sophisticated defense mechanisms, the respiratory system remains highly susceptible to environmental challenges. Because of the impact of respiratory exposure on human health and disease, there has been considerable interest in developing reliable and predictive in vitro model systems for respiratory toxicology and basic research. Human air-liquid-interface (ALI) organotypic airway tissue models derived from primary tracheobronchial epithelial cells have in vivo-like structure and functions when they are fully differentiated. The presence of the air-facing surface allows conducting in vitro exposures that mimic human respiratory exposures. Exposures can be conducted using particulates, aerosols, gases, vapors generated from volatile and semi-volatile substances, and respiratory pathogens. Toxicity data have been generated using nanomaterials, cigarette smoke, e-cigarette vapors, environmental airborne chemicals, drugs given by inhalation, and respiratory viruses and bacteria. Although toxicity evaluations using human airway ALI models require further standardization and validation, this approach shows promise in supplementing or replacing in vivo animal models for conducting research on respiratory toxicants and pathogens. |
Novel citation-based search method for scientific literature: a validation study.
Janssens A Cecile J W, Gwinn Marta, Brockman J Elaine, Powell Kimberley, Goodman Michael. BMC medical research methodology 2020 20(1) 25 . BMC medical research methodology 2020 20(1) 25 Janssens A Cecile J W, Gwinn Marta, Brockman J Elaine, Powell Kimberley, Goodman Michael. BMC medical research methodology 2020 20(1) 25 |
Pathogen Genomics in Public Health.
Armstrong GL , MacCannell DR , Taylor J , Carleton HA , Neuhaus EB , Bradbury RS , Posey JE , Gwinn M . N Engl J Med 2019 381 (26) 2569-2580 Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies. |
Next-Generation Sequencing of Infectious Pathogens.
Gwinn M , MacCannell D , Armstrong GL . JAMA 2019 321 (9) 893-894 Next generation sequencing (NGS) holds potential for improving clinical and public health microbiology.1 In addition to identifying pathogens faster and more precisely, high-throughput technologies and bioinformatics can provide new insights into disease transmission, virulence, and antimicrobial resistance. The US public health system is integrating pathogen genome sequencing into infectious disease surveillance with support from the Advanced Molecular Detection (AMD) program established by Congress at the Centers for Disease Control and Prevention (CDC) in 2014.2 Population-level data on pathogen genomes in turn supports the development of more precise and efficient clinical diagnostics. In time, laboratories may be able to replace many traditional microbiology processes with a single workflow that accommodates a wide array of pathogens.3 |
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. |
Integrating advanced molecular technologies into public health.
Gwinn M , MacCannell DR , Khabbaz RF . J Clin Microbiol 2016 55 (3) 703-714 Advances in laboratory and information technologies are transforming public health microbiology. High-throughput genome sequencing and bioinformatics are enhancing our ability to investigate and control outbreaks, detect emerging infectious diseases, develop vaccines, and combat antimicrobial resistance-all with increased accuracy, timeliness, and efficiency. The Advanced Molecular Detection (AMD) initiative has allowed the Centers for Disease Control and Prevention (CDC) to provide leadership and coordination in integrating new technologies into routine practice throughout the US public health laboratory system. Collaboration and partnerships are the key to navigating this transition and to leveraging the next generation of methods and tools most effectively for public health. |
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. |
Erratum to: Novel citation-based search method for scientific literature: application to meta-analyses.
Janssens A Cecile J W, Gwinn M. BMC medical research methodology 2015 Nov 1597 . BMC medical research methodology 2015 Nov 1597 Janssens A Cecile J W, Gwinn M. BMC medical research methodology 2015 Nov 1597 |
Novel citation-based search method for scientific literature: application to meta-analyses.
Janssens A Cecile J W, Gwinn M. BMC medical research methodology 2015 Oct 1584 . BMC medical research methodology 2015 Oct 1584 Janssens A Cecile J W, Gwinn M. BMC medical research methodology 2015 Oct 1584 |
Editorial: Updated guidance on human genome epidemiology (HuGE) reviews and meta-analyses of genetic associations.
Gwinn M , Ioannidis JP , Little J , Khoury MJ . Am J Epidemiol 2014 180 (6) 559-61 Even before the human genome was sequenced, Khoury and Dorman published an editorial in the American Journal of Epidemiology (AJE) calling for a population-based approach to health-related discoveries that stemmed from the Human Genome Project (1). The approach was termed “human genome epidemiology” (HuGE for short) and led to the formation of an informal collaboration (HuGENet) (2) to explore the systematic use of epidemiologic methods to investigate the role of genetic variation in health and disease. That inaugural editorial outlined the goals of human genome epidemiology, which ranged from estimating the population prevalence of gene variants to evaluating genetic tests and services. |
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. |
Strategies, actions, and outcomes of pilot state programs in public health genomics, 2003-2008.
St Pierre J , Bach J , Duquette D , Oehlke K , Nystrom R , Silvey K , Zlot A , Giles R , Johnson J , Anders HM , Gwinn M , Bowen S , Khoury MJ . Prev Chronic Dis 2014 11 E97 State health departments in Michigan, Minnesota, Oregon, and Utah explored the use of genomic information, including family health history, in chronic disease prevention programs. To support these explorations, the Office of Public Health Genomics at the Centers for Disease Control and Prevention provided cooperative agreement funds from 2003 through 2008. The 4 states' chronic disease programs identified advocates, formed partnerships, and assessed public data; they integrated genomics into existing state plans for genetics and chronic disease prevention; they developed projects focused on prevention of asthma, cancer, cardiovascular disease, diabetes, and other chronic conditions; and they created educational curricula and materials for health workers, policymakers, and the public. Each state's program was different because of the need to adapt to existing culture, infrastructure, and resources, yet all were able to enhance their chronic disease prevention programs with the use of family health history, a low-tech "genomic tool." Additional states are drawing on the experience of these 4 states to develop their own approaches. |
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. |
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. |
Viral hepatitis C gets personal--the value of human genomics to public health.
Zhang L , Gwinn M , Hu DJ . Public Health Genomics 2013 16 (4) 192-7 About 180 million people worldwide are chronically infected with hepatitis C virus (HCV), with 3-4 million newly infected each year. Only 15-25% of acute HCV infections clear spontaneously, and the remainder persists as chronic HCV infection. More than 350,000 people die every year from hepatitis C-related liver failure and cancer. There is currently no vaccine and the standard-of-care therapies - peg-interferon alpha (pegIFN) plus ribavirin (RBV) - are expensive and have serious side effects. Also, they may be effective in only 40-50% of patients infected with HCV genotype 1, the most common HCV genotype in the US. Interleukin 28B (IL28B) genotype was recently and convincingly associated with response to pegIFN and RBV therapy. It has emerged as a robust pretreatment predictor of sustained virological response (SVR, i.e. virologic clearance) to pegIFN and RBV as well as to new triple therapy regimens that include a direct-acting antiviral agent with pegIFN and RBV and increase SVR rates as much as 75% in patients infected with HCV genotype 1. Testing for IL28B genotype may contribute to clinical decision-making and could inform clinical guidelines and public health policies. |
A population approach to precision medicine.
Khoury MJ , Gwinn ML , Glasgow RE , Kramer BS . Am J Prev Med 2012 42 (6) 639-45 The term P4 medicine is used to denote an evolving field of medicine that uses systems biology approaches and information technologies to enhance wellness rather than just treat disease. Its four components include predictive, preventive, personalized, and participatory medicine. In the current paper, it is argued that in order to fulfill the promise of P4 medicine, a "fifth P" must be integrated -the population perspective- into each of the other four components. A population perspective integrates predictive medicine into the ecologic model of health; applies principles of population screening to preventive medicine; uses evidence-based practice to personalize medicine; and grounds participatory medicine on the three core functions of public health: assessment, policy development, and assurance. Population sciences-including epidemiology; behavioral, social, and communication sciences; and health economics, implementation science, and outcomes research- are needed to show the value of P4 medicine. Balanced strategies that implement both population- and individual-level interventions can best maximize health benefits, minimize harm, and avoid unnecessary healthcare costs. |
Knowledge integration at the center of genomic medicine.
Khoury MJ , Gwinn M , Dotson WD , Schully SD . Genet Med 2012 14 (7) 643-7 Three articles in this issue of Genetics in Medicine describe examples of "knowledge integration," involving methods for generating and synthesizing rapidly emerging information on health-related genomic technologies and engaging stakeholders around the evidence. Knowledge integration, the central process in translating genomic research, involves three closely related, iterative components: knowledge management, knowledge synthesis, and knowledge translation. Knowledge management is the ongoing process of obtaining, organizing, and displaying evolving evidence. For example, horizon scanning and "infoveillance" use emerging technologies to scan databases, registries, publications, and cyberspace for information on genomic applications. Knowledge synthesis is the process of conducting systematic reviews using a priori rules of evidence. For example, methods including meta-analysis, decision analysis, and modeling can be used to combine information from basic, clinical, and population research. Knowledge translation refers to stakeholder engagement and brokering to influence policy, guidelines and recommendations, as well as the research agenda to close knowledge gaps. The ultrarapid production of information requires adequate public and private resources for knowledge integration to support the evidence-based development of genomic medicine. (Genet Med advance online publication 3 May 2012.) |
Trends in population-based studies of human genetics in infectious diseases.
Rowell JL , Dowling NF , Yu W , Yesupriya A , Zhang L , Gwinn M . PLoS One 2012 7 (2) e25431 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. |
Meeting report: mode(s) of action of asbestos and related mineral fibers
Gwinn MR , Devoney D , Jarabek AM , Sonawane B , Wheeler J , Weissman DN , Masten S , Thompson C . Environ Health Perspect 2011 119 (12) 1806-10 BACKGROUND: Although asbestos in general is well known to cause a range of neoplastic and non-neoplastic human health effects, not all asbestos fiber types have the same disease-causing potential, and the mode of action (MOA) of specific types of asbestos and related fibers for various health outcomes are not well understood.OBJECTIVES: A workshop was held to discuss the state of the science of the MOA for asbestos-related disease. The objective was to review the range of asbestos-induced health effects (including those at sites remote to the respiratory tract). We sought to identify existing knowledge gaps and define what research is needed to address these gaps and advance asbestos research.DISCUSSION: Discussions centered on areas of uncertainty in the field, including the ways asbestos is defined and characterized, the role of different fiber characteristics (e.g., length and mineralogy) in disease, and the impact of low-dose exposures on human health. Studying the dosimetry and mode of action of multiple fiber types would enhance our understanding of asbestos-related disease. To better elucidate the MOA of specific asbestos fibers, the risk assessor requires data as to specific characteristics of asbestos in determining fiber toxicity (e.g., surface area, mineral type), which may inform efforts to assess and control exposures and prevent adverse human health outcomes for the diverse range of fiber types. Specific research aims were defined for these topics and for overarching issues to be addressed, including the use of standardized terminology, test materials, and better experimental models to aid in data extrapolation to humans.CONCLUSION: To resolve these and other issues, participants agreed that diverse scientific disciplines must coordinate to better understand the MOA leading to the various asbestos-related disease end points. |
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