{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T17:10:20Z","timestamp":1788801020760,"version":"build-2803163510"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000051","name":"National Human Genome Research Institute","doi-asserted-by":"crossref","award":["ZIA HG200417"],"award-info":[{"award-number":["ZIA HG200417"]}],"id":[{"id":"10.13039\/100000051","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000051","name":"National Human Genome Research Institute","doi-asserted-by":"crossref","award":["ZIA HG200417"],"award-info":[{"award-number":["ZIA HG200417"]}],"id":[{"id":"10.13039\/100000051","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Public Health"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The\n                    <jats:italic>All of Us<\/jats:italic>\n                    Research Program is assembling a nationwide cohort with electronic health record (EHR) resources through two complementary pathways: healthcare provider organization (HPO)-sourced EHRs and patient-mediated EHR (PME) contributed through patient portal linkages. The comparative research utility of these two data sources has not been systematically evaluated. Here, we compared PME and HPO EHRs with respect to disease prevalence, phenotype\u2013phenotype associations, and replication of established genotype-phenotype associations using data from 19,703 PME and 373,887 HPO participants. We benchmarked disease prevalence against national estimates, conducted phenome-wide association studies for 10 commonly studied diseases, and tested replication of more than 5000 established genotype-phenotype associations across multiple ancestral groups. Disease prevalence was consistently lower in PME than in HPO, although prevalence of most diseases in both cohorts exceeded national estimates. Both data sources reproduced known phenotype\u2013phenotype associations and showed moderate-to-strong concordance in effect sizes across the phenome. The overall genotype-phenotype replication rate was 49.1% (5399\/10,999) in HPO and 5.9% (381\/6482) in PME across ancestral groups, with effect sizes strongly correlated among well-powered associations (\n                    <jats:italic>R<\/jats:italic>\n                    \u2009=\u20090.84,\n                    <jats:italic>P<\/jats:italic>\n                    \u2009&lt;\u20090.001). To disentangle the impact of sample size from data quality, we performed 1:1 propensity score matching. After matching, the replication gap in genotype-phenotype associations narrowed from 8.3-fold to 1.3-fold, with equivalent replication rates among adequately powered associations and strongly concordant effect sizes; comorbidity patterns were also consistent across all 10 diseases tested. These findings demonstrate that both data sources are valuable for clinical and genomic research and can inform other cohorts integrating provider-derived and patient-mediated EHRs.\n                  <\/jats:p>","DOI":"10.1038\/s44482-026-00032-8","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T04:20:31Z","timestamp":1788754831000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Robust replication of associations across patient-mediated and provider-sourced EHR data in the All of Us research program"],"prefix":"10.1038","volume":"1","author":[{"given":"Chenjie","family":"Zeng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bennett J.","family":"Waxse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua C.","family":"Denny","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,7]]},"reference":[{"key":"32_CR1","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1056\/NEJMp1006114","volume":"363","author":"D Blumenthal","year":"2010","unstructured":"Blumenthal, D. & Tavenner, M. The \"meaningful use\" regulation for electronic health records. N. Engl. J. Med. 363, 501\u2013504 (2010).","journal-title":"N. Engl. J. Med."},{"key":"32_CR2","doi-asserted-by":"publisher","first-page":"1781","DOI":"10.1056\/NEJMp1917640","volume":"382","author":"KD Mandl","year":"2020","unstructured":"Mandl, K. D. & Kohane, I. S. Data citizenship under the 21st Century Cures Act. N. Engl. J. Med. 382, 1781\u20131783 (2020).","journal-title":"N. Engl. J. Med."},{"key":"32_CR3","unstructured":"International, H. L. S. FHIR Overview https:\/\/www.hl7.org\/fhir\/overview.html (2025)."},{"key":"32_CR4","doi-asserted-by":"publisher","first-page":"e58445","DOI":"10.2196\/58445","volume":"12","author":"P Tabari","year":"2024","unstructured":"Tabari, P., Costagliola, G., De Rosa, M. & Boeker, M. State-of-the-Art Fast Healthcare Interoperability Resources (FHIR)-based data model and structure implementations: systematic scoping review. JMIR Med. Inf. 12, e58445 (2024).","journal-title":"JMIR Med. Inf."},{"key":"32_CR5","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1056\/NEJMsr1809937","volume":"381","author":"AURP Investigators","year":"2019","unstructured":"Investigators, A. U. R. P. The \"All of Us\" research program. N. Engl. J. Med. 381, 668\u2013676 (2019).","journal-title":"N. Engl. J. Med."},{"key":"32_CR6","first-page":"79","volume":"1168","author":"AN Kho","year":"2020","unstructured":"Kho, A. N. et al. Privacy-preserving record linkage to identify fragmented electronic medical records in the All of Us research program. Comm. Com. Inf. Sc. 1168, 79\u201387 (2020).","journal-title":"Comm. Com. Inf. Sc."},{"key":"32_CR7","unstructured":"International, H. L. S. C-CDA Online: A Navigation Website for C-CDA 2.1 https:\/\/www.hl7.org\/ccdasearch\/ (2025)."},{"key":"32_CR8","doi-asserted-by":"publisher","first-page":"184","DOI":"10.3389\/fgene.2014.00184","volume":"5","author":"DC Crawford","year":"2014","unstructured":"Crawford, D. C. et al. eMERGEing progress in genomics-the first seven years. Front. Genet. 5, 184 (2014).","journal-title":"Front. Genet."},{"key":"32_CR9","unstructured":"Ramirez, A. H. et al. The All of Us research program: data quality, utility, and diversity. Patterns 3, 100570 (2022)."},{"key":"32_CR10","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.1038\/nbt.2749","volume":"31","author":"JC Denny","year":"2013","unstructured":"Denny, J. C. et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotechnol. 31, 1102\u20131110 (2013).","journal-title":"Nat. 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The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice. J. Am. Med Inf. Assoc. 31, 1479\u20131492 (2024).","journal-title":"J. Am. Med Inf. Assoc."},{"key":"32_CR20","doi-asserted-by":"publisher","first-page":"e037405","DOI":"10.1136\/bmjopen-2020-037405","volume":"10","author":"D Dedman","year":"2020","unstructured":"Dedman, D. et al. Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies. BMJ Open 10, e037405 (2020).","journal-title":"BMJ Open"},{"key":"32_CR21","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1038\/s41746-025-01815-8","volume":"8","author":"A Newbury","year":"2025","unstructured":"Newbury, A., Elhussein, A. & Gursoy, G. 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Phenome-wide association studies across large population cohorts support drug target validation. Nat. Commun. 9, 4285 (2018).","journal-title":"Nat. Commun."},{"key":"32_CR28","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1001\/jama.2021.20356","volume":"327","author":"L Bastarache","year":"2022","unstructured":"Bastarache, L., Denny, J. C. & Roden, D. M. Phenome-wide association studies. 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