Epigenome-wide association studies of prenatal maternal mental health and infant epigenetic profiles: a systematic review.

Prenatal stress and poor maternal mental health are associated with adverse offspring outcomes; however, the biological mechanisms are unknown. Epigenetic modification has linked maternal health with offspring development. Epigenome-wide association studies (EWAS) have examined offspring DNA methylation profiles for association with prenatal maternal mental health to elucidate mechanisms of these complex relationships. The objective of this study is to provide a comprehensive, systematic review of EWASs of infant epigenetic profiles and prenatal maternal anxiety, depression, or depression treatment. We conducted a systematic literature search following PRISMA guidelines for EWAS studies between prenatal maternal mental health and infant epigenetics through May 22, 2023. Of 645 identified articles, 20 fulfilled inclusion criteria. We assessed replication of CpG sites among studies, conducted gene enrichment analysis, and evaluated the articles for quality and risk of bias. We found one repeated CpG site among the maternal depression studies; however, nine pairs of overlapping differentially methylatd regions were reported in at least two maternal depression studies. Gene enrichment analysis found significant pathways for maternal depression but not for any other maternal mental health category. We found evidence that these EWAS present a medium to high risk of bias. Exposure to prenatal maternal depression and anxiety or treatment for such was not consistently associated with epigenetic changes in infants in this systematic review and meta-analysis. Small sample size, potential bias due to exposure misclassification and statistical challenges are critical to address in future efforts to explore epigenetic modification as a potential mechanism by which prenatal exposure to maternal mental health disorders leads to adverse infant outcomes.

Association Between a First-Degree Family History and Self-Reported Personal History of Obesity, Diabetes, and Heart and Blood Conditions: Results From the All of Us Research Program.

Background Family history reflects the complex interplay of genetic susceptibility and shared environmental exposures and is an important risk factor for obesity, diabetes, and heart and blood conditions (ODHB). However, the overlap in family history associations between various ODHBs has not been quantified. Methods and Results We assessed the association between a self-reported family history of ODHBs and their risk in the adult population (age ≥20 years) of the AoU (All of Us) Research Program, a longitudinal cohort study of diverse participants across the United States. We conducted a family history-wide association study to systematically assess the association of a first-degree family history of 15 ODHBs in AoU. We performed stratified analyses based on racial and ethnic categories, education, household income and gender minority status, and quantified associations by type of affected relatives. Of 125 430 participants, 76.8% reported a first-degree family history of any ODHB, most commonly hypertension (n=64 982, 51.8%), high cholesterol (49 753, 39.7%), and heart attack (29 618, 23.6%). We use the FamWAS method to estimate 225 familial associations among 15 ODHBs. The results include overlapping associations between family history of different types of cardiometabolic conditions (such as type 2 diabetes and coronary artery disease), and their risk factors (obesity, hypertension), where adults with a family history of 1 ODHB exhibited 1.1 to 5.6 times (1.5, on average) the odds of having a different ODHB. Conclusions Our findings inform the utility of family history data as a risk assessment and screening tool for the prevention of ODHBs and to provide additional insights into shared risk factors and pathogenic mechanisms.

Severity Outcomes among Adult Patients with Primary Immunodeficiency and COVID-19 Seen in Emergency Departments, United States, April 2020-August 2021.

Primary immunodeficiencies (PIs) are a group of diseases that increase susceptibility to infectious diseases. Few studies have examined the relationship between PI and COVID-19 outcomes. In this study, we used Premier Healthcare Database, which contains information on inpatient discharges, to analyze COVID-19 outcomes among 853 adult PI and 1,197,430 non-PI patients who visited the emergency department. Hospitalization, intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), and death had higher odds in PI patients than in non-PI patients (hospitalization aOR: 2.36, 95% CI: 1.87-2.98; ICU admission aOR: 1.53, 95% CI: 1.19-1.96; IMV aOR: 1.41, 95% CI: 1.15-1.72; death aOR: 1.37, 95% CI: 1.08-1.74), and PI patients spent on average 1.91 more days in the hospital than non-PI patients when adjusted for age, sex, race/ethnicity, and chronic conditions associated with severe COVID-19. Of the largest four PI groups, selective deficiency of the immunoglobulin G subclass had the highest hospitalization frequency (75.2%). This large study of United States PI patients provides real-world evidence that PI is a risk factor for adverse COVID-19 outcomes.

Understanding the Process of Family Cancer History Collection and Health Information Seeking.

PROBLEM ADDRESSED: To better understand the factors associated with family cancer history (FCH) information and cancer information seeking, we model the process an individual undergoes when assessing whether to gather FCH and seek cancer information and compare models by sociodemographics and family history of cancer. We used cross-sectional data from the Health Information National Trends Survey (HINTS 5, Cycle 2) and variables (e.g., emotion and self-efficacy) associated with the Theory of Motivated Information Management to assess the process of FCH gathering and information seeking. We completed path analysis to assess the process of FCH gathering and stratified path models. RESULTS: Those who felt they could lower their chances of getting cancer (emotion) were more confident in their ability to complete FCH on a medical form (self-efficacy; B = 0.11, p < .0001) and more likely to have discussed FCH with family members (B = 0.07, p < .0001). Those who were more confident in their ability to complete a summary of their family history on a medical form were more likely to have discussed FCH with family members (B = 0.34, p < .0001) and seek other health information (B = 0.24, p < .0001). Stratified models showed differences in this process by age, race/ethnicity, and family history of cancer. IMPLICATIONS FOR PUBLIC HEALTH RESEARCH AND PRACTICE: Tailoring outreach and education strategies to address differences in perceived ability to lower chances of getting cancer (emotion) and confidence in the ability to complete FCH (self-efficacy) could help encourage less engaged individuals to learn about their FCH and gather cancer information.

COVID-19 Scientific Publications From the Centers for Disease Control and Prevention, January 2020-January 2022.

OBJECTIVE: High-quality scientific evidence underpins public health decision making. The Centers for Disease Control and Prevention (CDC) agency provides scientific data, including during public health emergencies. To understand CDC's contributions to COVID-19 science, we conducted a bibliometric evaluation of publications authored by CDC scientists from January 20, 2020, through January 20, 2022, by using a quality improvement approach (SQUIRE 2.0). METHODS: We catalogued COVID-19 articles with ≥1 CDC-affiliated author published in a scientific journal and indexed in the World Health Organization's COVID-19 database. We identified priority topic areas from the agency's COVID-19 Public Health Science Agenda by using keyword scripts in EndNote and then assessed the impact of the published articles by using Scopus and Altmetric. RESULTS: During the first 2 years of the agency's pandemic response, CDC authors contributed to 1044 unique COVID-19 scientific publications in 208 journals. Publication topics included testing (n = 853, 82%); prevention strategies (n = 658, 63%); natural history, transmission, breakthrough infections, and reinfections (n = 587, 56%); vaccines (n = 567, 54%); health equity (n = 308, 30%); variants (n = 232, 22%); and post-COVID-19 conditions (n = 44, 4%). Publications were cited 40 427 times and received 81 921 news reports and 1 058 893 social media impressions. As the pandemic evolved, CDC adapted to address new scientific questions, including vaccine effectiveness, safety, and access; viral variants, including Delta and Omicron; and health equity. CONCLUSION: The agency's COVID-19 Public Health Science Agenda helped guide impactful scientific activities. CDC continues to evaluate COVID-19 priority topic areas and contribute to development of new scientific work. CDC is committed to monitoring emerging issues and addressing gaps in evidence needed to improve health.

COVID-19-Related manuscripts: lag from preprint to publication.

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.

The Joint Public Health Impact of Family History of Diabetes and Cardiovascular Disease among Adults in the United States: A Population-Based Study.

INTRODUCTION: Family history is an established risk factor for both cardiovascular disease (CVD) and diabetes; however, no study has presented population-based prevalence estimates of family histories of CVD and diabetes and examined their joint impact on prevalence of diabetes, CVD, cardiometabolic risk factors, and mortality risk. METHODS: We analyzed data from a representative sample of the US adult population including 29,440 participants from the National Health and Nutrition Examination Survey (2007-2018) and assessed self-reported first-degree family history of diabetes and CVD (premature heart disease before age of 50 years) as well as meeting criteria and/or having risk factors for CVD and diabetes. RESULTS: Participants with joint family history exhibit 6.5 greater odds for having both diseases and are diagnosed with diabetes 6.6 years earlier than participants without family history. Healthy participants without prevalent CVD or diabetes but with joint family history exhibit a greater prevalence of diabetes risk factors compared to no family history counterparts. Joint family history is associated with an increase in all-cause mortality, but with no interactive effect. CONCLUSION: Over 44% of the US adult population has a family history of CVD and/or diabetes that is comparable in risk to common cardiometabolic risk factors. This wide presence of high-risk family history and its simplicity of ascertainment suggests that clinical and public health efforts should collect and act on joint family history of CVD and diabetes to improve population efforts in the prevention and early detection of these common chronic diseases.

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

A better understanding of COVID-19 in people with primary immunodeficiency (PI), rare inherited defects in the immune system, is important for protecting this population, especially as population-wide approaches to mitigation change. COVID-19 outcomes in the PI population could have broader public health implications because some people with PI might be more likely to have extended illnesses, which could lead to increased transmission and emergence of variants. We performed a systematic review on COVID-19-associated morbidity and mortality in people with PI. Of the 1114 articles identified through the literature search, we included 68 articles in the review after removing 1046 articles because they were duplicates, did not involve COVID-19, did not involve PI, were not in English, were commentaries, were gene association or gene discovery studies, or could not be accessed. The 68 articles included outcomes for 459 people with PI and COVID-19. Using data from these 459 people, we calculated a case fatality rate of 9%, hospitalization rate of 49%, and oxygen supplementation rate of 29%. Studies have indicated that a number of people with PI showed at least some immune response to COVID-19 vaccination, with responses varying by type of PI and other factors, although vaccine effectiveness against hospitalization was lower in the PI population than in the general population. In addition to being up-to-date on vaccinations, current strategies for optimizing protection for people with PI can include pre-exposure prophylaxis for those eligible and use of therapeutics. Overall, people with PI, when infected, tested positive and showed symptoms for similar lengths of time as the general population. However, a number of people with X-linked agammaglobulinemia (XLA) or other B-cell pathway defects were reported to have prolonged infections, measured by time from first positive SARS-CoV-2 test to first negative test. As prolonged infections might increase the likelihood of genetic variants emerging, SARS-CoV2 isolates from people with PI and extended illness would be good candidates to prioritize for whole genome sequencing.

Addressing the routine failure to clinically identify monogenic cases of common disease.

Changes in medical practice are needed to improve the diagnosis of monogenic forms of selected common diseases. This article seeks to focus attention on the need for universal genetic testing in common diseases for which the recommended clinical management of patients with specific monogenic forms of disease diverges from standard management and has evidence for improved outcomes.We review evidence from genomic screening of large patient cohorts, which has confirmed that important monogenic case identification failures are commonplace in routine clinical care. These case identification failures constitute diagnostic misattributions, where the care of individuals with monogenic disease defaults to the treatment plan offered to those with polygenic or non-genetic forms of the disease.The number of identifiable and actionable monogenic forms of common diseases is increasing with time. Here, we provide six examples of common diseases for which universal genetic test implementation would drive improved care. We examine the evidence to support genetic testing for common diseases, and discuss barriers to widespread implementation. Finally, we propose recommendations for changes to genetic testing and care delivery aimed at reducing diagnostic misattributions, to serve as a starting point for further evaluation and development of evidence-based guidelines for implementation.

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

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

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

Recent reviews have emphasized the need for a health equity agenda in genomics research. To ensure that genomic discoveries can lead to improved health outcomes for all segments of the population, a health equity agenda needs to go beyond research studies. Advances in genomics and precision medicine have led to an increasing number of evidence-based applications that can reduce morbidity and mortality for millions of people (tier 1). Studies have shown lower implementation rates for selected diseases with tier 1 applications (familial hypercholesterolemia, Lynch syndrome, hereditary breast and ovarian cancer) among racial and ethnic minority groups, rural communities, uninsured or underinsured people, and those with lower education and income. We make the case that a public health agenda is needed to address disparities in implementation of genomics and precision medicine. Public health actions can be centered on population-specific needs and outcomes assessment, policy and evidence development, and assurance of delivery of effective and ethical interventions. Crucial public health activities also include engaging communities, building coalitions, improving genetic health literacy, and building a diverse workforce. Without concerted public health action, further advances in genomics with potentially broad applications could lead to further widening of health disparities in the next decade.

Improving reporting standards for polygenic scores in risk prediction studies.

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

Challenges and Opportunities for Communication about the Role of Genomics in 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.

A scoping review of social and behavioral science research to translate genomic discoveries into population health impact.

Since the completion of the Human Genome Project, progress toward translating genomic research discoveries to address population health issues has been limited. Several meetings of social and behavioral scientists have outlined priority research areas where advancement of translational research could increase population health benefits of genomic discoveries. In this review, we track the pace of progress, study size and design, and focus of genomics translational research from 2012 to 2018 and its concordance with five social and behavioral science recommended priorities. We conducted a review of the literature following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Guidelines for Scoping Reviews. Steps involved completing a search in five databases and a hand search of bibliographies of relevant literature. Our search (from 2012 to 2018) yielded 4,538 unique studies; 117 were included in the final analyses. Two coders extracted data including items from the PICOTS framework. Analysis included descriptive statistics to help identify trends in pace, study size and design, and translational priority area. Among the 117 studies included in our final sample, nearly half focused on genomics applications that have evidence to support translation or implementation into practice (Centers for Disease Control and Prevention Tier 1 applications). Common study designs were cross-sectional (40.2%) and qualitative (24.8%), with average sample sizes of 716 across all studies. Most often, studies addressed public understanding of genetics and genomics (33.3%), risk communication (29.1%), and intervention development and testing of interventions to promote behavior change (19.7%). The number of studies that address social and behavioral science priority areas is extremely limited and the pace of this research continues to lag behind basic science advances. Much of the research identified in this review is descriptive and related to public understanding, risk communication, and intervention development and testing of interventions to promote behavior change. The field has been slow to develop and evaluate public health-friendly interventions and test implementation approaches that could enable health benefits and equitable access to genomic discoveries. As the completion of the human genome approaches its 20th anniversary, full engagement of transdisciplinary efforts to address translation challenges will be required to close this gap.

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

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