PURPOSE: We used data from the All of Us Research Program to examine sociodemographic differences in family health history (FHH) survey access, availability of electronic health records (EHR) data, FHH knowledge, FHH in the survey and EHR data, and concordance of FHH in survey and EHR data for breast cancer, colorectal cancer, and diabetes. METHODS: We calculated percentages and standard errors of participants who accessed the FHH survey, reported no FHH knowledge, had EHR data available, had FHH data in the survey and EHR, and had FHH in the survey or EHR that was not captured in the other data source for breast cancer, colorectal cancer, and diabetes. We stratified by age, race and ethnicity, sex, sexual orientation, household income, employment status, education level, marital status, and health insurance status. To determine significant differences, we calculated absolute and relative disparity, Z-tests, and P values with the significance threshold adjusted for multiple comparisons using the Bonferroni correction. RESULTS: We found significant disparities in accessing the survey and reporting no FHH knowledge across almost all sociodemographic subgroups. Most FHH reported in the survey was not captured in the EHR data, most significantly for participants who were aged 20 to 29, were students, did not graduate high school, were never married, or had no health insurance. CONCLUSION: Our study showed significant sociodemographic disparities in FHH survey access, FHH knowledge, and FHH captured in EHR structured data, which could widen inequities in access to FHH-based interventions.

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.

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.

OBJECTIVE: The aim was to estimate odds ratios of associations between family history of arthritis, osteoporosis, and carpal tunnel syndrome and prevalence in a real-world population, uncovering family histories of related conditions that may increase risk due to shared heritability, condition pathophysiology, or social/environmental factors. METHODS: Using data from 156,307 participants in the All of Us (AoU) Research Program, we examined associations between self-reported first-degree family history of 5 common types of arthritis (fibromyalgia, gout, osteoarthritis (OA), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE)), osteoporosis, and carpal tunnel syndrome and prevalence. We evaluate associations across 7 conditions and performed stratified analyses by race and ethnicity, sex, socioeconomic differences, body mass index, and type of affected relative. RESULTS: Over 38% of AoU participants reported a family history of any arthritis, osteoporosis, or carpal tunnel syndrome. Adults with a family history of any arthritis, osteoporosis, and carpal tunnel syndrome exhibited 3.68 to 7.59 (4.90, on average) odds of having the same condition, and 0.70 to 2.10 (1.24, on average) odds of having a different condition. The strongest associations observed were between family history of OA and prevalence of OA (OR 7.59, 95%CI 7.32-7.88), and family history of SLE and prevalence of SLE (OR 6.34, 95%CI 5.17-7.74). We additionally uncover race and ethnicity and sex disparities in family history associations. CONCLUSION: Family history of several related conditions was associated with increased risk for arthritis, osteoporosis, and carpal tunnel syndrome, underscoring the importance of family history of related conditions for primary prevention.

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.

Family history is a strong risk factor for many common chronic diseases and summarizes shared environmental and genetic risk, but how this increased risk is mediated is unknown. We developed a "Family History-Wide Association Study" (FamWAS) to systematically and comprehensively test Clinical and Environmental Quantitative Traits (CEQTs) for their association with family history of disease. We implemented our method on 457 CEQTs for association with family history of diabetes, asthma, and coronary heart disease (CHD) in 42,940 adults spanning 8 waves of the 1999-2014 National Health and Nutrition Examination Survey (NHANES). We conducted pooled analyses of the 8 survey waves and analyzed trait associations using survey-weighted logistic regression. We identified 172 (37.6% of total), 32 (7.0%), and 78 (17.1%) CEQTs associated with family history of diabetes, asthma, and CHD, respectively, in sub-cohorts of individuals without the respective disease. 20 associated CEQTs were shared across family history of diabetes, asthma, and CHD, far more than expected by chance. FamWAS can examine traits not previously studied in association with family history and uncover trait overlap, highlighting a putative shared mechanism by which family history influences disease risk.

BACKGROUND: The global burden of pediatric severe respiratory illness is substantial, and influenza viruses contribute to this burden. Systematic surveillance and testing for influenza among hospitalized children has expanded globally over the past decade. However, only a fraction of the data has been used to estimate influenza burden. In this analysis, we use surveillance data to provide an estimate of influenza-associated hospitalizations among children worldwide. METHODS AND FINDINGS: We aggregated data from a systematic review (n = 108) and surveillance platforms (n = 37) to calculate a pooled estimate of the proportion of samples collected from children hospitalized with respiratory illnesses and positive for influenza by age group (<6 mo, <1 y, <2 y, <5 y, 5-17 y, and <18 y). We applied this proportion to global estimates of acute lower respiratory infection hospitalizations among children aged <1 y and <5 y, to obtain the number and per capita rate of influenza-associated hospitalizations by geographic region and socio-economic status. Influenza was associated with 10% (95% CI 8%-11%) of respiratory hospitalizations in children <18 y worldwide, ranging from 5% (95% CI 3%-7%) among children <6 mo to 16% (95% CI 14%-20%) among children 5-17 y. On average, we estimated that influenza results in approximately 374,000 (95% CI 264,000 to 539,000) hospitalizations in children <1 y-of which 228,000 (95% CI 150,000 to 344,000) occur in children <6 mo-and 870,000 (95% CI 610,000 to 1,237,000) hospitalizations in children <5 y annually. Influenza-associated hospitalization rates were more than three times higher in developing countries than in industrialized countries (150/100,000 children/year versus 48/100,000). However, differences in hospitalization practices between settings are an important limitation in interpreting these findings. CONCLUSIONS: Influenza is an important contributor to respiratory hospitalizations among young children worldwide. Increasing influenza vaccination coverage among young children and pregnant women could reduce this burden and protect infants <6 mo.

The authors describe the rationale and initial development of a new collaborative initiative, the Genomic Applications in Practice and Prevention Network. The network convened by the Centers for Disease Control and Prevention and the National Institutes of Health includes multiple stakeholders from academia, government, health care, public health, industry and consumers. The premise of Genomic Applications in Practice and Prevention Network is that there is an unaddressed chasm between gene discoveries and demonstration of their clinical validity and utility. This chasm is due to the lack of readily accessible information about the utility of most genomic applications and the lack of necessary knowledge by consumers and providers to implement what is known. The mission of Genomic Applications in Practice and Prevention Network is to accelerate and streamline the effective integration of validated genomic knowledge into the practice of medicine and public health, by empowering and sponsoring research, evaluating research findings, and disseminating high quality information on candidate genomic applications in practice and prevention. Genomic Applications in Practice and Prevention Network will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development process, (3) translation research to evaluate validity, utility and impact in the real world and how to disseminate and implement recommended genomic applications, and (4) programs to enhance practice, education, and surveillance.

The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed.