ABSTRACT
Coronary artery disease (CAD) is a preeminent cause of death, and smoking is a strong risk factor for CAD. Genetic factors contribute to the development of CAD, but the interplay between genetic predisposition and smoking history in CAD remains unclear. Using data from the UK Biobank, we constructed several genetic risk scores (GRSs) based on known CAD loci and assessed their interactions with smoking for the development of incident CAD in 307,147 participants of European ancestry who were free of CAD. We fitted Cox proportional hazard models and assessed gene-smoking interaction on both multiplicative and additive scales. Overall, we found no multiplicative interactions, but observed a synergistic additive interaction of GRS with both smoking status and pack-years of smoking, finding that the absolute CAD risk due to smoking was higher for those with high genetic risk. Trait-based sub-GRSs suggested smoking status and smoking intensity measured by pack-years might confer gene-smoking interaction effects with different intermediate risk factors for CAD. Our study results suggest that genetics could modify the effects of smoking on CAD and highlight the value of addressing gene-lifestyle interactions on both additive and multiplicative scales.
Subject(s)
Coronary Artery Disease , Coronary Artery Disease/epidemiology , Coronary Artery Disease/genetics , Genetic Predisposition to Disease , Humans , Models, Genetic , Risk Factors , Smoking/adverse effects , Smoking/geneticsABSTRACT
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.
Subject(s)
Disease Outbreaks , Foodborne Diseases/epidemiology , Genomics , High-Throughput Nucleotide Sequencing , Influenza, Human/epidemiology , Public Health , Tuberculosis/epidemiology , Animals , Bacteria/genetics , Foodborne Diseases/diagnosis , Foodborne Diseases/microbiology , Foodborne Diseases/parasitology , Humans , Influenza, Human/diagnosis , Influenza, Human/microbiology , Metagenomics , Parasites/genetics , Tuberculosis/diagnosis , Viruses/geneticsABSTRACT
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 .
Subject(s)
COVID-19 , Artificial Intelligence , COVID-19/epidemiology , Genomics , Humans , Pandemics , Precision Medicine , SARS-CoV-2/geneticsABSTRACT
Thioredoxin-interacting protein (TXNIP) plays a key role in diabetes development and prognosis through its role in pancreatic ß-cell dysfunction and death as well as in upregulating the inflammatory response in hyperglycemia. DNA methylation (DNAm) of TXNIP (TXNIP-cg19693031) is associated with the prevalence and incidence of type 2 diabetes (T2D); however, its role in inflammation and its relationship with T2D remain unclear. We aimed to investigate the epigenetic associations of TXNIP-cg19693031 with a panel of inflammatory biomarkers and to examine whether these inflammatory biomarkers modify the association between TXNIP-cg19693031 methylation and diabetes in 218 middle-aged male twins from the Emory Twin Study. We confirmed the association of TXNIP-cg19693031 DNAm with T2D, as well as with HbA1c, insulin and fasting glucose. We found that hypomethylation at TXNIP-cg19693031 is strongly associated with both type 2 diabetes and higher levels of inflammatory biomarkers (VCAM-1, ICAM-1, MMP-2, sRAGE and P-selectin); however, the relationship between TXNIP-cg19693031 and T2D is independent of the levels of these inflammatory biomarkers. Our results suggest that DNA methylation of TXNIP is linked with multiple biological processes, through which the TXNIP may have broad influence on chronic disease risk.
Subject(s)
DNA Methylation , Diabetes Mellitus, Type 2 , Biomarkers , Carrier Proteins/genetics , Carrier Proteins/metabolism , DNA Methylation/genetics , Diabetes Mellitus, Type 2/genetics , Humans , Inflammation/genetics , Male , Middle AgedABSTRACT
BACKGROUND: People living with human immunodeficiency virus (HIV) infection have higher risk for chronic kidney disease (CKD), defined by a reduced estimated glomerular filtration rate (eGFR). Previous studies have implicated epigenetic changes related to CKD; however, the mechanism of HIV-related CKD has not been thoroughly investigated. METHODS: We conducted an epigenome-wide association study of eGFR among 567 HIV-positive and 117 HIV-negative male participants in the Veterans Aging Cohort Study to identify epigenetic signatures of kidney function. RESULTS: By surveying more than 400 000 cytosine guanine dinucleotide (CpG) sites measured from peripheral blood mononuclear cells, we identified 15 sites that were significantly associated with eGFR (false discovery rate Q value < 0.05) among HIV-positive participants. The most significant CpG sites, located at MAD1L1, TSNARE1/BAI1, and LTV1, were all negatively associated with eGFR (cg06329547, P = 5.25 × 10-9; cg23281907, P = 1.37 × 10-8; cg18368637, P = 5.17 × 10-8). We also replicated previously reported eGFR-associated CpG sites including cg17944885 (P = 2.5 × 10-5) located between ZNF788 and ZNF20 on chromosome 19 in the pooled population. CONCLUSIONS: In this study we uncovered novel epigenetic associations with kidney function among people living with HIV and suggest potential epigenetic mechanisms linked with HIV-related CKD risk.
Subject(s)
HIV Infections , Renal Insufficiency, Chronic , Cell Cycle Proteins , Cohort Studies , Epigenesis, Genetic , Glomerular Filtration Rate , HIV Infections/complications , HIV Infections/genetics , Humans , Leukocytes, Mononuclear , Male , Renal Insufficiency, Chronic/geneticsABSTRACT
BACKGROUND: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. METHODS: We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles. RESULTS: A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. CONCLUSIONS: CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible.
Subject(s)
Information Storage and Retrieval/methods , Models, Theoretical , Publications/statistics & numerical data , Research Design/statistics & numerical data , Humans , Journal Impact Factor , Reproducibility of ResultsABSTRACT
Epigenetic modifications such as DNA methylation are associated with both human immunodeficiency virus (HIV) infection and type 2 diabetes mellitus (T2DM). We investigated epigenetic associations with T2DM according to HIV infection status and assessed interaction effects among 681 male participants of the Veterans Aging Cohort Study. Methylation at previously reported sites, cg1963031 (TXNIP), cg18181703 (SOCS3), and cg09152259 (PROC), was significantly associated with T2DM in HIV-infected individuals. We identified 3 novel associations with suggestive statistical significance: cg1231141 (ADAMTS2), cg19534769 (HGFAC), and cg13163919 (TLE3). Suggestive interaction with HIV infection status was found at cg17862404 (TSC22D1). The implicated genes are involved in inflammation, pancreatic ß-cell function, and T2DM pathogenesis.
Subject(s)
DNA Methylation/genetics , Diabetes Mellitus, Type 2/genetics , Epigenesis, Genetic/genetics , HIV Infections/genetics , Veterans/statistics & numerical data , Cohort Studies , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/epidemiology , Genetic Markers/genetics , HIV Infections/complications , HIV Infections/epidemiology , Humans , Male , Middle Aged , Prospective StudiesABSTRACT
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.
Subject(s)
Public Health/trends , Genomics/trends , Humans , Precision Medicine/trends , United StatesABSTRACT
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 U.S. 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.
Subject(s)
Microbiological Techniques/methods , Molecular Diagnostic Techniques/methods , Public Health Administration/methods , Humans , United StatesABSTRACT
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.Genet Med 18 12, 1312-1314.
Subject(s)
Databases, Genetic , Genomics , Knowledge Bases , Humans , Internet , Public HealthABSTRACT
Networks of investigators have begun sharing best practices, tools and methods for analysis of associations between genetic variation and common diseases. A Network of Investigator Networks has been set up to drive the process, sponsored by the Human Genome Epidemiology Network. A workshop is planned to develop consensus guidelines for reporting results of genetic association studies. Published literature databases will be integrated, and unpublished data, including 'negative' studies, will be captured by online journals and through investigator networks. Systematic reviews will be expanded to include more meta-analyses of individual-level data and prospective meta-analyses. Field synopses will offer regularly updated overviews.
Subject(s)
Epidemiologic Methods , Genome, Human , Databases, Factual , Genetic Predisposition to Disease , Human Genome Project , Humans , MEDLINE , Research DesignABSTRACT
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.
Subject(s)
Decision Support Techniques , Evidence-Based Medicine , Genomics , Translational Research, Biomedical , Cross-Sectional Studies , Humans , Information Dissemination , Meta-Analysis as TopicABSTRACT
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.
Subject(s)
Chronic Disease/prevention & control , Community Health Planning , Genomics/trends , Outcome Assessment, Health Care/methods , Public Health/trends , State Government , Capacity Building , Centers for Disease Control and Prevention, U.S. , Genetic Testing , Genomics/education , Human Genome Project , Humans , Leadership , Michigan , Minnesota , Oregon , Pilot Projects , Population Surveillance , Program Development , United States , Utah , WorkforceABSTRACT
Inflammation underlies many conditions causing excess morbidity and mortality among people with HIV (PWH). A handful of single-trait epigenome-wide association studies (EWAS) have suggested that inflammation is associated with DNA methylation (DNAm) among PWH. Multi-trait EWAS may further improve statistical power and reveal pathways in common between different inflammatory markers. We conducted single-trait EWAS of three inflammatory markers (soluble CD14, D-dimers, and interleukin 6) in the Veteran Aging Cohort Study (n = 920). The study population was all male PWH with an average age of 51 years, and 82.3% self-reported as Black. We then applied two multi-trait EWAS methods-CPASSOC and OmniTest-to combine single-trait EWAS results. CPASSOC and OmniTest identified 189 and 157 inflammation-associated DNAm sites respectively, of which 112 overlapped. Among the identified sites, 56% were not significant in any single-trait EWAS. Top sites were mapped to inflammation-related genes including IFITM1, PARP9 and STAT1. These genes were significantly enriched in pathways such as "type I interferon signaling" and "immune response to virus". We demonstrate that multi-trait EWAS can improve the discovery of inflammation-associated DNAm sites, genes, and pathways. These DNAm sites suggest molecular mechanisms in response to inflammation associated with HIV and might hold the key to addressing persistent inflammation in PWH.
ABSTRACT
Introduction: People with HIV (PWH) of African ancestry have faster decline of kidney function and faster progression to end-stage renal disease than PWH of European ancestry. DNA methylation have been associated with kidney function in the general population, however, their relationships are unclear for PWH of African ancestry. Methods: We performed epigenome-wide association studies (EWAS) of estimated glomerular filtration rate (eGFR) among PWH of African ancestry in 2 subsets of the Veterans Aging Cohort Study cohort (N = 885), followed by a meta-analysis to combine the results. Replication was conducted among independent African American samples without HIV. Results: DNA methylation sites cg17944885 near Zinc Finger Family Member 788 (ZNF788) and Zinc Finger Protein 20 (ZNF20), and cg06930757 in SHANK1 were significantly associated with eGFR among PWH of African ancestry (false discovery rate < 0.05). DNA methylation site cg17944885 was also associated with eGFR among different populations including African Americans without HIV. Conclusions: Our study attempted to address an important gap in the literature and to understand the role of DNA methylation in renal diseases in PWH of African ancestry. Replication of cg17944885 among different populations suggests there may be a common pathway for renal diseases progression among PWH and people without HIV, and across different ancestral groups. Our results suggest that genes ZNF788/ZNF20 and SHANK1 could be involved in a pathway linking DNA methylation to renal diseases among PWH and are worth further investigation.
ABSTRACT
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.
Subject(s)
Databases, Genetic , Genetics, Population , Genome, Human , Molecular Epidemiology/methods , Public Health , Gene-Environment Interaction , Genome-Wide Association Study , Humans , Macular Degeneration/epidemiology , Macular Degeneration/genetics , Molecular Epidemiology/trendsABSTRACT
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.
Subject(s)
Genomics/methods , Knowledge Management , Translational Research, Biomedical , Decision Support Techniques , Evidence-Based Medicine , Humans , Information Dissemination , Meta-Analysis as Topic , Research Design , Review Literature as TopicABSTRACT
A decade after the sequencing of the human genome, the National Human Genome Research Institute announced a strategic plan for genomic medicine. It calls for evaluating the structure and biology of genomes, understanding the biology of disease, advancing the science of medicine, and improving the effectiveness of health care. Fulfilling the promise of genomics urgently requires a population perspective to complement the bench-to-bedside model of translation. A population approach should assess the contribution of genomics to health in the context of social and environmental determinants of disease; evaluate genomic applications that may improve health care; design strategies for integrating genomics into practice; address ethical, legal, and social issues; and measure the population health impact of new technologies.