Comparison of family health history in surveys vs electronic health record data mapped to the observational medical outcomes partnership data model in the All of Us Research Program

OBJECTIVE: Family health history is important to clinical care and precision medicine. Prior studies show gaps in data collected from patient surveys and electronic health records (EHRs). The All of Us Research Program collects family history from participants via surveys and EHRs. This Demonstration Project aims to evaluate availability of family health history information within the publicly available data from All of Us and to characterize the data from both sources. MATERIALS AND METHODS: Surveys were completed by participants on an electronic portal. EHR data was mapped to the Observational Medical Outcomes Partnership data model. We used descriptive statistics to perform exploratory analysis of the data, including evaluating a list of medically actionable genetic disorders. We performed a subanalysis on participants who had both survey and EHR data. RESULTS: There were 54 872 participants with family history data. Of those, 26% had EHR data only, 63% had survey only, and 10.5% had data from both sources. There were 35 217 participants with reported family history of a medically actionable genetic disorder (9% from EHR only, 89% from surveys, and 2% from both). In the subanalysis, we found inconsistencies between the surveys and EHRs. More details came from surveys. When both mentioned a similar disease, the source of truth was unclear. CONCLUSIONS: Compiling data from both surveys and EHR can provide a more comprehensive source for family health history, but informatics challenges and opportunities exist. Access to more complete understanding of a person\u27s family health history may provide opportunities for precision medicine

Examining sociodemographic correlates of opioid use, misuse, and use disorders in the All of Us Research Program

BACKGROUND: The All of Us Research Program enrolls diverse US participants which provide a unique opportunity to better understand the problem of opioid use. This study aims to estimate the prevalence of opioid use and its association with sociodemographic characteristics from survey data and electronic health record (EHR). METHODS: A total of 214,206 participants were included in this study who competed survey modules and shared EHR data. Adjusted logistic regressions were used to explore the associations between sociodemographic characteristics and opioid use. RESULTS: The lifetime prevalence of street opioids was 4%, and the nonmedical use of prescription opioids was 9%. Men had higher odds of lifetime opioid use (aOR: 1.4 to 3.1) but reduced odds of current nonmedical use of prescription opioids (aOR: 0.6). Participants from other racial and ethnic groups were at reduced odds of lifetime use (aOR: 0.2 to 0.9) but increased odds of current use (aOR: 1.9 to 9.9) compared with non-Hispanic White participants. Foreign-born participants were at reduced risks of opioid use and diagnosed with opioid use disorders (OUD) compared with US-born participants (aOR: 0.36 to 0.67). Men, Younger, White, and US-born participants are more likely to have OUD. CONCLUSIONS: All of Us research data can be used as an indicator of national trends for monitoring the prevalence of receiving prescription opioids, diagnosis of OUD, and non-medical use of opioids in the US. The program employs a longitudinal design for routinely collecting health-related data including EHR data, that will contribute to the literature by providing important clinical information related to opioids over time. Additionally, this data will enhance the estimates of the prevalence of OUD among diverse populations, including groups that are underrepresented in the national survey data

Hypertension and increased endothelial mechanical stretch promote monocyte differentiation and activation: roles of STAT3, interleukin 6 and hydrogen peroxide

Aims: Monocytes play an important role in hypertension. Circulating monocytes in humans exist as classical, intermediate and non-classical forms. Monocyte differentiation can be influenced by the endothelium, which in turn is activated in hypertension by mechanical stretch. We sought to examine the role of increased endothelial stretch and hypertension on monocyte phenotype and function. Methods and Results: Human monocytes were cultured with confluent human aortic endothelial cells undergoing either 5% or 10% cyclical stretch. We also characterized circulating monocytes in normotensive and hypertensive humans. In addition, we quantified accumulation of activated monocytes and monocyte-derived cells in aortas and kidneys of mice with Angiotensin II-induced hypertension. Increased endothelial stretch enhanced monocyte conversion to CD14++CD16+ intermediate monocytes and monocytes bearing the CD209 marker and markedly stimulated monocyte mRNA expression of interleukin (IL)-6, IL-1β, IL-23, chemokine (C-C motif) ligand 4 and tumor necrosis factor α. STAT3 in monocytes was activated by increased endothelial stretch. Inhibition of STAT3, neutralization of IL-6 and scavenging of hydrogen peroxide prevented formation of intermediate monocytes in response to increased endothelial stretch. We also found evidence that nitric oxide inhibits formation of intermediate monocytes and STAT3 activation. In vivo studies demonstrated that humans with hypertension have increased intermediate and non-classical monocytes and that intermediate monocytes demonstrate evidence of STAT3 activation. Mice with experimental hypertension exhibit increased aortic and renal infiltration of monocytes, dendritic cells and macrophages with activated STAT3. Conclusions: These findings provide insight into how monocytes are activated by the vascular endothelium during hypertension. This is likely in part due to a loss of nitric oxide signaling and increased release of IL-6 and hydrogen peroxide by the dysfunctional endothelium and a parallel increase in STAT activation in adjacent monocytes. Interventions to enhance bioavailable nitric oxide, reduce IL-6 or hydrogen peroxide production or to inhibit STAT3 may have anti-inflammatory roles in hypertension and related conditions

Dendritic Cell Amiloride-Sensitive Channels Mediate Sodium-Induced Inflammation and Hypertension

Summary: Sodium accumulates in the interstitium and promotes inflammation through poorly defined mechanisms. We describe a pathway by which sodium enters dendritic cells (DCs) through amiloride-sensitive channels including the alpha and gamma subunits of the epithelial sodium channel and the sodium hydrogen exchanger 1. This leads to calcium influx via the sodium calcium exchanger, activation of protein kinase C (PKC), phosphorylation of p47phox, and association of p47phox with gp91phox. The assembled NADPH oxidase produces superoxide with subsequent formation of immunogenic isolevuglandin (IsoLG)-protein adducts. DCs activated by excess sodium produce increased interleukin-1β (IL-1β) and promote T cell production of cytokines IL-17A and interferon gamma (IFN-γ). When adoptively transferred into naive mice, these DCs prime hypertension in response to a sub-pressor dose of angiotensin II. These findings provide a mechanistic link between salt, inflammation, and hypertension involving increased oxidative stress and IsoLG production in DCs. : Barbaro et al. describe a pathway by which increased extracellular sodium activates dendritic cells. This pathway potentially explains the link between excessive salt intake, inflammation, and high blood pressure. Keywords: hypertension, sodium chloride, dendritic cells, isolevuglandins, oxidative stress, NADPH oxidase, amiloride, ENaC, calciu

Predictive Analytics for Glaucoma Using Data From the All of Us Research Program

PurposeTo (1) use All of Us (AoU) data to validate a previously published single-center model predicting the need for surgery among individuals with glaucoma, (2) train new models using AoU data, and (3) share insights regarding this novel data source for ophthalmic research.DesignDevelopment and evaluation of machine learning models.MethodsElectronic health record data were extracted from AoU for 1,231 adults diagnosed with primary open-angle glaucoma. The single-center model was applied to AoU data for external validation. AoU data were then used to train new models for predicting the need for glaucoma surgery using multivariable logistic regression, artificial neural networks, and random forests. Five-fold cross-validation was performed. Model performance was evaluated based on area under the receiver operating characteristic curve (AUC), accuracy, precision, and recall.ResultsThe mean (standard deviation) age of the AoU cohort was 69.1 (10.5) years, with 57.3% women and 33.5% black, significantly exceeding representation in the single-center cohort (P = .04 and P < .001, respectively). Of 1,231 participants, 286 (23.2%) needed glaucoma surgery. When applying the single-center model to AoU data, accuracy was 0.69 and AUC was only 0.49. Using AoU data to train new models resulted in superior performance: AUCs ranged from 0.80 (logistic regression) to 0.99 (random forests).ConclusionsModels trained with national AoU data achieved superior performance compared with using single-center data. Although AoU does not currently include ophthalmic imaging, it offers several strengths over similar big-data sources such as claims data. AoU is a promising new data source for ophthalmic research

Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort

The World Health Organization recently defined hypertension and type 2 diabetes (T2D) as modifiable comorbidities leading to dementia and Alzheimer's disease. In the United States (US), hypertension and T2D are health disparities, with higher prevalence seen for Black and Hispanic minority groups compared to the majority White population. We hypothesized that elevated prevalence of hypertension and T2D risk factors in Black and Hispanic groups may be associated with dementia disparities. We interrogated this hypothesis using a cross-sectional analysis of participant data from the All of Us (AoU) Research Program, a large observational cohort study of US residents. The specific objectives of our study were: (1) to compare the prevalence of dementia, hypertension, and T2D in the AoU cohort to previously reported prevalence values for the US population, (2) to investigate the association of hypertension, T2D, and race/ethnicity with dementia, and (3) to investigate whether race/ethnicity modify the association of hypertension and T2D with dementia. AoU participants were recruited from 2018 to 2019 as part of the initial project cohort (R2019Q4R3). Participants aged 40-80 with electronic health records and demographic data (age, sex, race, and ethnicity) were included for analysis, yielding a final cohort of 125,637 individuals. AoU participants show similar prevalence of hypertension (32.1%) and T2D (13.9%) compared to the US population (32.0% and 10.5%, respectively); however, the prevalence of dementia for AoU participants (0.44%) is an order of magnitude lower than seen for the US population (5%). AoU participants with dementia show a higher prevalence of hypertension (81.6% vs. 31.9%) and T2D (45.9% vs. 11.4%) compared to non-dementia participants. Dominance analysis of a multivariable logistic regression model with dementia as the outcome shows that hypertension, age, and T2D have the strongest associations with dementia. Hispanic was the only race/ethnicity group that showed a significant association with dementia, and the association of sex with dementia was non-significant. The association of T2D with dementia is likely explained by concurrent hypertension, since > 90% of participants with T2D also had hypertension. Black race and Hispanic ethnicity interact with hypertension, but not T2D, to increase the odds of dementia. This study underscores the utility of the AoU participant cohort to study disease prevalence and risk factors. We do notice a lower participation of aged minorities and participants with dementia, revealing an opportunity for targeted engagement. Our results indicate that targeting hypertension should be a priority for risk factor modifications to reduce dementia incidence

Geographic Variation in Obesity at the State Level in the All of Us Research Program.

INTRODUCTION: National obesity prevention strategies may benefit from precision health approaches involving diverse participants in population health studies. We used cohort data from the National Institutes of Health All of Us Research Program (All of Us) Researcher Workbench to estimate population-level obesity prevalence. METHODS: To estimate state-level obesity prevalence we used data from physical measurements made during All of Us enrollment visits and data from participant electronic health records (EHRs) where available. Prevalence estimates were calculated and mapped by state for 2 categories of body mass index (BMI) (kg/m2): obesity (BMI >30) and severe obesity (BMI >35). We calculated and mapped prevalence by state, excluding states with fewer than 100 All of Us participants. RESULTS: Data on height and weight were available for 244,504 All of Us participants from 33 states, and corresponding EHR data were available for 88,840 of these participants. The median and IQR of BMI taken from physical measurements data was 28.4 (24.4- 33.7) and 28.5 (24.5-33.6) from EHR data, where available. Overall obesity prevalence based on physical measurements data was 41.5% (95% CI, 41.3%-41.7%); prevalence of severe obesity was 20.7% (95% CI, 20.6-20.9), with large geographic variations observed across states. Prevalence estimates from states with greater numbers of All of Us participants were more similar to national population-based estimates than states with fewer participants. CONCLUSION: All of Us participants had a high prevalence of obesity, with state-level geographic variation mirroring national trends. The diversity among All of Us participants may support future investigations on obesity prevention and treatment in diverse populations