ArticleNature medicine2026
Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health.
Article in Nature medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Our Future Health is a prospective study aiming to recruit 5 million UK-resident adults to enable discovery and translation of disease prevention, detection and treatment approaches. So far, more than 2.5 million have enrolled, and baseline phenotypic data are available for >1.9 million participants. Here we provide an assessment of phenotypes-self-reported health-related behaviors, geolocation, diagnoses and medication, in- and outpatient visits, cancer registry and cause of death-and comparison of disease patterns against national estimates and the UK Biobank cohort. Sociodemographic, lifestyle and health-related characteristics reflected UK population patterns; all but one minority ethnic group and the most socioeconomically deprived groups were underrepresented. The prevalence of several major self-reported conditions, particularly mental health conditions such as depression and anxiety, was higher than national estimates and directionally concordant with the UK Biobank (r = 0.78). Associations with known clinical correlates replicated across both cohorts (r = 0.80). Medication-use patterns and cancer prevalence followed expected age-related gradients, with lower lung cancer rates than national data. As recruitment progresses, electronic health records can help specify disease patterns and systematically assess biases.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.