ArticleJournal of the American Medical Informatics Association : JAMIA2024
Comparison of phenomic profiles in the All of Us Research Program against the US general population and the UK Biobank.
Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- The average individual genome: a survey of nearly 1 million whole-genome sequences.Genome medicine · 2026Article
- Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health.Nature medicine · 2026Article
- Assessing the generalizability of prevalence estimates from the All of Us Research Program.American journal of epidemiology · 2026Article
- Machine Learning Predicts Hepatocellular Carcinoma Risk from Routine Clinical Data: A Large Population-Based Multicentric Study.Cancer discovery · 2026Article
- Glucagon-Like Peptide-1 Receptor Agonist Use and Liver-Related Outcomes in Metabolic Dysfunction-Associated Steatotic Liver Disease and Type 2 Diabetes in the All of Us Research Program.The American journal of gastroenterology · 2026Article
- Clonal Hematopoiesis and Risk of Incident Pericarditis and Myocarditis in 2 US Biobank Cohorts.JAMA cardiology · 2026Article
- Downward bias in the association between APOE and Alzheimer's disease using prevalent and by-proxy disease sampling in the All of Us research program.BMC medical genomics · 2026Article
- Patterns and Clinical Outcomes of Physical Activity and Sedentary Behavior Across 20 Million Days of Wearable Monitoring in U.S. Adults.medRxiv : the preprint server for health sciences · 2026Article
- Healthcare utilization among adults with co-occurring substance use and mental health disorders (2018-2023): A study based on All of Us program.medRxiv : the preprint server for health sciences · 2026Article
- Article
- A deep ensemble encoder network method for improved polygenic risk score prediction.BioData mining · 2026Article
- Using large biobanks for psychiatric genomic research: Consistency of clinical and genetic aspects of recorded depression across US states in the All of Us Research Program.Psychological medicine · 2026Article
- Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.BMC medicine · 2026Article
- Article
- Genome-wide Association Study IdentifiesAllergy, asthma & immunology research · 2026Article
- Robust replication of associations across patient-mediated and provider-sourced EHR data in thenpj digital public health · 2026Article
- Article
- Association between neutrophil to lymphocyte ratio and Alzheimer's disease in large biobank cohorts.Journal of Alzheimer's disease : JAD · 2025Article
- Exploring depression treatment response by using polygenic risk scoring across diverse populations.American journal of human genetics · 2025Article
- Diseases Common in Persons With Cystic Fibrosis Among CFTR Heterozygotes.JAMA internal medicine · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
importanceKnowledge gained from cohort studies has dramatically advanced both public and precision health. The All of Us Research Program seeks to enroll 1 million diverse participants who share multiple sources of data, providing unique opportunities for research. It is important to understand the phenomic profiles of its participants to conduct research in this cohort.
objectivesMore than 280 000 participants have shared their electronic health records (EHRs) in the All of Us Research Program. We aim to understand the phenomic profiles of this cohort through comparisons with those in the US general population and a well-established nation-wide cohort, UK Biobank, and to test whether association results of selected commonly studied diseases in the All of Us cohort were comparable to those in UK Biobank. MATERIALS AND
methodsWe included participants with EHRs in All of Us and participants with health records from UK Biobank. The estimates of prevalence of diseases in the US general population were obtained from the Global Burden of Diseases (GBD) study. We conducted phenome-wide association studies (PheWAS) of 9 commonly studied diseases in both cohorts.
resultsThis study included 287 012 participants from the All of Us EHR cohort and 502 477 participants from the UK Biobank. A total of 314 diseases curated by the GBD were evaluated in All of Us, 80.9% (N = 254) of which were more common in All of Us than in the US general population [prevalence ratio (PR) >1.1, P < 2 × 10-5]. Among 2515 diseases and phenotypes evaluated in both All of Us and UK Biobank, 85.6% (N = 2152) were more common in All of Us (PR >1.1, P < 2 × 10-5). The Pearson correlation coefficients of effect sizes from PheWAS between All of Us and UK Biobank were 0.61, 0.50, 0.60, 0.57, 0.40, 0.53, 0.46, 0.47, and 0.24 for ischemic heart diseases, lung cancer, chronic obstructive pulmonary disease, dementia, colorectal cancer, lower back pain, multiple sclerosis, lupus, and cystic fibrosis, respectively. DISCUSSION: Despite the differences in prevalence of diseases in All of Us compared to the US general population or the UK Biobank, our study supports that All of Us can facilitate rapid investigation of a broad range of diseases.
conclusionMost diseases were more common in All of Us than in the general US population or the UK Biobank. Results of disease-disease association tests from All of Us are comparable to those estimated in another well-studied national cohort.
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