Researching COVID to enhance recovery (RECOVER) pediatric study protocol: Rationale, objectives and design.

Importance: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or "Long COVID") in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults.

Observations: We describe the protocol for the Pediatric Observational Cohort Study of the NIH's REsearching COVID to Enhance Recovery (RECOVER) Initiative.

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.

Pragmatic evaluation of events and benefits of lipid lowering in older adults (PREVENTABLE): Trial design and rationale.

Whether initiation of statins could increase survival free of dementia and disability in adults aged ≥75 years is unknown. PREVENTABLE, a double-blind, placebo-controlled randomized pragmatic clinical trial, will compare high-intensity statin therapy (atorvastatin 40 mg) with placebo in 20,000 community-dwelling adults aged ≥75 years without cardiovascular disease, disability, or dementia at baseline. Exclusion criteria include statin use in the prior year or for >5 years and inability to take a statin.

Achieving a Representative Sample of Asian Americans in Biomedical Research Through Community-Based Approaches: Comparing Demographic Data in the Research Program With the American Community Survey.

Background: Underrepresented persons are often not included in biomedical research. It is unknown if the general Asian American population is being represented in . The purpose of this study was to compare the Asian demographic data in the cohort with the Asian nationally representative data from the American Community Survey.

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.

Concordance of SARS-CoV-2 Antibody Results during a Period of Low Prevalence.

Accurate, highly specific immunoassays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to evaluate seroprevalence. This study investigated the concordance of results across four immunoassays targeting different antigens for sera collected at the beginning of the SARS-CoV-2 pandemic in the United States. Specimens from All of Us participants contributed between January and March 2020 were tested using the Abbott Architect SARS-CoV-2 IgG (immunoglobulin G) assay (Abbott) and the EuroImmun SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) (EI).

An Overview of Cancer in the First 315,000 All of Us Participants.

Introduction: The NIH All of Us Research Program will have the scale and scope to enable research for a wide range of diseases, including cancer. The program's focus on diversity and inclusion promises a better understanding of the unequal burden of cancer. Preliminary cancer ascertainment in the All of Us cohort from two data sources (self-reported versus electronic health records (EHR)) is considered.

The Research Program: Data quality, utility, and diversity.

The Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races.

Epidemiology of atrial fibrillation in the All of Us Research Program.

Background: The prevalence, incidence and risk factors of atrial fibrillation (AF) in a large, geographically and ethnically diverse cohort in the United States have not been fully described.

Methods: We analyzed data from 173,099 participants of the All of Us Research Program recruited in the period 2017-2019, with 92,318 of them having electronic health records (EHR) data available, and 35,483 having completed a medical history survey. Presence of AF at baseline was identified from self-report and EHR records.

Pediatric data from the research program: demonstration of pediatric obesity over time.

Objective: To describe and demonstrate use of pediatric data collected by the Research Program.

Materials And Methods: participant physical measurements and electronic health record (EHR) data were analyzed including investigation of trends in childhood obesity and correlation with adult body mass index (BMI).

Results: We identified 19 729 participants with legacy pediatric EHR data including diagnoses, prescriptions, visits, procedures, and measurements gathered since 1980.

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.

Racial, ethnic, and gender differences in obesity and body fat distribution: An All of Us Research Program demonstration project.

Differences in obesity and body fat distribution across gender and race/ethnicity have been extensively described. We sought to replicate these differences and evaluate newly emerging data from the All of Us Research Program (AoU). We compared body mass index (BMI), waist circumference, and waist-to-hip ratio from the baseline physical examination, and alanine aminotransferase (ALT) from the electronic health record in up to 88,195 Non-Hispanic White (NHW), 40,770 Non-Hispanic Black (NHB), 35,640 Hispanic, and 5,648 Asian participants.

Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research.

The All of Us Research Program was designed to enable broad-based precision medicine research in a cohort of unprecedented scale and diversity. Hypertension (HTN) is a major public health concern. The validity of HTN data and definition of hypertension cases in the All of Us (AoU) Research Program for use in rule-based algorithms is unknown.

Antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in All of Us Research Program Participants, 2 January to 18 March 2020.

Background: With limited severe acute respiratory syndrome coronavirus (SARS-CoV-2) testing capacity in the United States at the start of the epidemic (January-March 2020), testing was focused on symptomatic patients with a travel history throughout February, obscuring the picture of SARS-CoV-2 seeding and community transmission. We sought to identify individuals with SARS-CoV-2 antibodies in the early weeks of the US epidemic.

Methods: All of Us study participants in all 50 US states provided blood specimens during study visits from 2 January to 18 March 2020.

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

Purpose: To (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.

Design: Development and evaluation of machine learning models.

Methods: Electronic health record data were extracted from AoU for 1,231 adults diagnosed with primary open-angle glaucoma.

Mini-Review of Laboratory Operations in Biobanking: Building Biobanking Resources for Translational Research.

Biobanks have become integral to improving population health. We are in a new era in medicine as patients, health professionals, and researchers increasingly collaborate to gain new knowledge and explore new paradigms for diagnosing and treating disease. Many large-scale biobanking efforts are underway worldwide at the institutional, national, and even international level.

Impact of Diverse Data Sources on Computational Phenotyping.

Electronic health records (EHRs) are widely adopted with a great potential to serve as a rich, integrated source of phenotype information. Computational phenotyping, which extracts phenotypes from EHR data automatically, can accelerate the adoption and utilization of phenotype-driven efforts to advance scientific discovery and improve healthcare delivery. A list of computational phenotyping algorithms has been published but data fragmentation, i.

Characteristics Associated With Recruitment and Re-contact in Mayo Clinic Biobank.

To better understand the characteristics associated with a participant's willingness to consent to the Mayo Clinic Biobank (MCB) and examine factors associated with willingness to participate in follow-up studies embedded within MCB that require re-contact and participant approval. Consent rates were compared across patient demographics to the MCB. Rates of participation to follow-up studies were also compared across demographics and request types.

The impact of sample processing on inflammatory markers in serum: Lessons learned.

To investigate the effect of sample handling on inflammatory cytokines in serum and highlight challenges with using samples pre-collected from biobanks for biomarker research. Cytokine concentrations (IL-1β, IL-2, IL-6, IL-8, IL-10, TNFα, and IFNγ) were measured in serum samples of 205 patients with bipoldar disorder (BD) from the Mayo Clinic Bipolar Disorder Biobank and 205 non-psychiatric controls from the Mayo Clinic Biobank. As cytokine concentrations varied by recruitment site, models were used to test the effect of clinical variables and pre-processing time on cytokines.

Characteristics and utilisation of the Mayo Clinic Biobank, a clinic-based prospective collection in the USA: cohort profile.

Purpose: The Mayo Clinic Biobank was established to provide a large group of patients from which comparison groups (ie, controls) could be selected for case-control studies, to create a prospective cohort with sufficient power for common outcomes and to support electronic health record (EHR) studies.

Participants: A total of 56 862 participants enrolled (21% response rate) into the Mayo Clinic Biobank from Rochester, Minnesota (77%, n=43 836), Jacksonville, Florida (18%, n=10 368) and La Crosse, Wisconsin (5%, n=2658). Participants were all Mayo Clinic patients, 18 years of age or older and US residents.

Association of mitochondrial DNA copy number with self-rated health status.

Purpose: In aging adults, mitochondrial dysfunction may be an important contributor. We evaluated the association between mitochondrial DNA (mtDNA) copy number, which is a biomarker for mitochondrial function, and self-rated health status.

Patients And Methods: We conducted a cross-sectional study of patients enrolled within the Mayo Clinic Biobank.

Germline whole exome sequencing and large-scale replication identifies as a likely high grade serous ovarian cancer susceptibility gene.

We analyzed whole exome sequencing data in germline DNA from 412 high grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas Project and identified 5,517 genes harboring a predicted deleterious germline coding mutation in at least one HGSOC case. Gene-set enrichment analysis showed enrichment for genes involved in DNA repair (p = 1.8×10).

PPM1D Mosaic Truncating Variants in Ovarian Cancer Cases May Be Treatment-Related Somatic Mutations.

Mosaic truncating mutations in the protein phosphatase, Mg(2+)/Mn(2+)-dependent, 1D (PPM1D) gene have recently been reported with a statistically significantly greater frequency in lymphocyte DNA from ovarian cancer case patients compared with unaffected control patients. Using massively parallel sequencing (MPS) we identified truncating PPM1D mutations in 12 of 3236 epithelial ovarian cancer (EOC) case patients (0.37%) but in only one of 3431 unaffected control patients (0.