---
title: "Phenomic profiles and disease patterns in 1.9 million participants from Our Future Health"
id: "nature-4-phenomic-profiles-and-disease-patterns-of-1-9-million-participants-from-our"
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specialty: "General"
source_name: "Nature Medicine"
source_url: "https://www.nature.com/articles/s41591-026-04602-4"
published_at: "2026-09-10T09:50:37.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Phenomic profiles and disease patterns in 1.9 million participants from Our Future Health
## Provenance & Clinical Metadata
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- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** Nature Medicine
- **Source URL:** [Original Journal Publication](https://www.nature.com/articles/s41591-026-04602-4)
- **Published At:** 2026-09-10T09:50:37.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- Our Future Health (OFH) is a UK prospective cohort study aiming to recruit 5 million adults to support discovery and translation in disease prevention, detection and treatment. - At the time of the reported data release, >2.5 million people had registered and baseline phenotypic data were available for more than **1.9 million** participants. - OFH collects broad **phenotypes** including self-reported health behaviours, geolocation, diagnoses and medication, inpatient and outpatient visits, cancer registry entries and cause-of-death data. - Sociodemographic, lifestyle and health-related characteristics in OFH broadly reflected UK population patterns, but most minority ethnic groups and the most socioeconomically deprived groups were underrepresented. - Prevalence of several major self-reported conditions—especially mental health conditions such as **depression** and **anxiety**—was higher than national estimates and showed directional concordance with the **UK Biobank** (correlation r = 0.78 reported). - Associations with known clinical correlates replicated across OFH and UK Biobank (reported correlation r = 0.80). - Medication-use patterns and cancer prevalence followed expected age-related gradients; lung cancer rates in OFH were lower than national data. - OFH is positioned as a large, multi-ethnic resource with particular coverage of younger adults (18–40), working-age populations and people over 60, and includes a clinical research recruitment service to help translate findings. - The study acknowledges common cohort limitations, including selection biases and potential impacts on generalizability; electronic health record linkage is expected to refine disease pattern estimates and assess biases as recruitment continues. - Some methodological and numerical details, and parts of figures and tables, were not reported in the provided source extract.
## Clinical Analysis & Structured Key Points
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[nature](https://www.nature.com/) 2. [nature medicine](https://www.nature.com/nm) 3. [resources](https://www.nature.com/nm/articles?type=resource) 4. article Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health [ Download PDF ](https://www.nature.com/articles/s41591-026-04602-4.pdf) [ Download PDF ](https://www.nature.com/articles/s41591-026-04602-4.pdf) * Resource * [Open access](https://www.springernature.com/gp/open-science/about/the-fundamentals-of-open-access-and-open-research) * Published: 10 September 2026 # Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health * [Vincent J. Straub](https://www.nature.com/articles/s41591-026-04602-4#auth-Vincent_J_-Straub-Aff1) [ORCID: orcid.org/0000-0003-3393-6027](https://orcid.org/0000-0003-3393-6027)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1), * [Stefania Benonisdottir](https://www.nature.com/articles/s41591-026-04602-4#auth-Stefania-Benonisdottir-Aff1-Aff2) [ORCID: orcid.org/0000-0001-5019-514X](https://orcid.org/0000-0001-5019-514X)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1),[2](https://www.nature.com/articles/s41591-026-04602-4#Aff2), * [Giovanni Scotti Bentivoglio](https://www.nature.com/articles/s41591-026-04602-4#auth-Giovanni_Scotti-Bentivoglio-Aff1-Aff3) [ORCID: orcid.org/0009-0004-8381-6079](https://orcid.org/0009-0004-8381-6079)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1),[3](https://www.nature.com/articles/s41591-026-04602-4#Aff3), * [Neil Wary](https://www.nature.com/articles/s41591-026-04602-4#auth-Neil-Wary-Aff1) [ORCID: orcid.org/0000-0002-0712-276X](https://orcid.org/0000-0002-0712-276X)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1), * [Robert Campbell](https://www.nature.com/articles/s41591-026-04602-4#auth-Robert-Campbell-Aff1) [ORCID: orcid.org/0009-0002-0212-224X](https://orcid.org/0009-0002-0212-224X)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1), * [Augustine Kong](https://www.nature.com/articles/s41591-026-04602-4#auth-Augustine-Kong-Aff1) [ORCID: orcid.org/0000-0001-8193-5438](https://orcid.org/0000-0001-8193-5438)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1) & * … * [Melinda C. Mills](https://www.nature.com/articles/s41591-026-04602-4#auth-Melinda_C_-Mills-Aff1-Aff3-Aff4) [ORCID: orcid.org/0000-0003-1704-0001](https://orcid.org/0000-0003-1704-0001)[1](https://www.nature.com/articles/s41591-026-04602-4#Aff1),[3](https://www.nature.com/articles/s41591-026-04602-4#Aff3),[4](https://www.nature.com/articles/s41591-026-04602-4#Aff4) Show authors [_Nature Medicine_](https://www.nature.com/nm) (2026) [Cite this article](https://www.nature.com/articles/s41591-026-04602-4#citeas) [ Save article ](https://www.nature.com/articles/s41591-026-04602-4/save-research?_csrf=sGNIf72MyIXDLgmAd7OI3JMKSbUB2SOj) [ View saved research ](https://www.nature.com/saved-research) ## 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. ### Explore related subjects Discover the latest articles and news in related subjects. * [Databases](https://www.nature.com/subjects/databases) * [Epidemiology](https://www.nature.com/subjects/epidemiology) * [Medical research](https://www.nature.com/subjects/medical-research) ## Main Healthcare systems face mounting challenges to building a healthier future for their populations, including a growing burden of chronic disease driven by aging, lifestyle changes and environmental exposures, alongside persistent health inequities and reliance on fragmented data[1](https://www.nature.com/articles/s41591-026-04602-4#ref-CR1 "Building healthy populations. Nat. Med. 29, 1579–1580 \(2023\)."). Biomedical research increasingly involves combining diverse data to consider the interplay of multiomics data, lifestyle factors, social determinants and the environment to assess population health and identify populations at higher risk of disease[2](https://www.nature.com/articles/s41591-026-04602-4#ref-CR2 "Roberts, M. C. et al. Precision public health in the era of genomics and big data. Nat. Med. 30, 1865–1873 \(2024\)."). Large-scale cohort studies and biobanks[3](https://www.nature.com/articles/s41591-026-04602-4#ref-CR3 "Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 \(2015\)."),[4](https://www.nature.com/articles/s41591-026-04602-4#ref-CR4 "The All of Us Research Program Investigators The ‘All of Us’ research program. N. Engl. J. Med. 381, 668–676 \(2019\)."),[5](https://www.nature.com/articles/s41591-026-04602-4#ref-CR5 "Feng, Y. C. A. et al. Taiwan Biobank: a rich biomedical research database of the Taiwanese population. Cell Genom. 2, 100197 \(2022\)."),[6](https://www.nature.com/articles/s41591-026-04602-4#ref-CR6 "Kurki, M. I. et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 613, 508–518 \(2023\)."),[7](https://www.nature.com/articles/s41591-026-04602-4#ref-CR7 "Milani, L. et al. The Estonian Biobank’s journey from biobanking to personalized medicine. Nat. Commun. 16, 3270 \(2025\)."), which systematically collect, store and manage health and biological data over time, have come to play a leading role in shaping developments in biomedical research[8](https://www.nature.com/articles/s41591-026-04602-4#ref-CR8 "Coppola, L. et al. Biobanking in health care: evolution and future directions. J. Transl. Med. 17, 172 \(2019\)."). Through deep data integration, these resources provide scientific insights into the determinants of health and disease[9](https://www.nature.com/articles/s41591-026-04602-4#ref-CR9 "Gallagher, C. S., Ginsburg, G. S. & Musick, A. Biobanking with genetics shapes precision medicine and global health. Rev. Genet. 26, 191–202 \(2025\).") as well as offering opportunities to address clinical and public health challenges[10](https://www.nature.com/articles/s41591-026-04602-4#ref-CR10 "Pagán, J. A., Wang, V. H.-C. & Sur, H. Time to use large-scale biobank databases in health policy and public health research. Health Aff. Sch. 3, qxaf158 \(2025\)."). In the UK, an established health and biomedical research infrastructure[11](https://www.nature.com/articles/s41591-026-04602-4#ref-CR11 "Sebire, N. J., Cake, C. & Morris, A. D. HDR UK supporting mobilising computable biomedical knowledge in the UK. BMJ Health Care Inform. 27, e100122 \(2020\).") has facilitated the successes of existing cohorts[3](https://www.nature.com/articles/s41591-026-04602-4#ref-CR3 "Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 \(2015\)."),[12](https://www.nature.com/articles/s41591-026-04602-4#ref-CR12 "Wadsworth, M. E. J. et al. Cohort profile: the 1946 national birth cohort \(MRC National Survey of Health and Development\). Int. J. Epidemiol. 35, 49–54 \(2006\)."),[13](https://www.nature.com/articles/s41591-026-04602-4#ref-CR13 "Green, J. et al. Cohort profile: the million women study. Int. J. Epidemiol. 48, 28–29e \(2019\)."). These resources have catalyzed a broad array of clinical and translational research, in addition to connecting researchers and participants; 1 in 30 people in the UK are estimated to take part in cohort studies[14](https://www.nature.com/articles/s41591-026-04602-4#ref-CR14 "Pell, J., Valentine, J. & Inskip, H. One in 30 people in the UK take part in cohort studies. Lancet 383, 1015–1016 \(2014\)."). Yet, existing volunteer-based studies are not always representative of their target population[15](https://www.nature.com/articles/s41591-026-04602-4#ref-CR15 "Fry, A. et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am. J. Epidemiol. 186, 1026–1034 \(2017\)."); findings may not always extrapolate to all communities owing to a lack of diversity[16](https://www.nature.com/articles/s41591-026-04602-4#ref-CR16 "Mills, M. C. & Rahal, C. The GWAS Diversity Monitor tracks diversity by disease in real time. Nat. Genet. 52, 242–243 \(2020\)."),[17](https://www.nature.com/articles/s41591-026-04602-4#ref-CR17 "Quattroni, P. et al. Five ways to enhance the diversity and quality of health data. Nat. Med. 31, 1747–1750 \(2025\)."), and, despite their depth, existing cohorts may not be sufficient in size to power discovery research, especially on less common diseases. Alongside these known data limitations, there are also several well-studied sampling and surveying issues that can impact the composition of cohorts, most notably, various selection biases (see box 1 in the [Supplementary Information](https://www.nature.com/articles/s41591-026-04602-4#MOESM1) for more details). Such biases can confound interpretation of analysis results and may reduce the generalizability of exposure–disease associations[18](https://www.nature.com/articles/s41591-026-04602-4#ref-CR18 "Keyes, K. M. & Westreich, D. UK Biobank, big data, and the consequences of non-representativeness. Lancet 393, 1297 \(2019\)."), as has long been discussed[19](https://www.nature.com/articles/s41591-026-04602-4#ref-CR19 "Swanson, J. M. The UK Biobank and selection bias. Lancet 380, 110 \(2012\)."),[20](https://www.nature.com/articles/s41591-026-04602-4#ref-CR20 "Richiardi, L., Pizzi, C. & Pearce, N. Commentary: representativeness is usually not necessary and often should be avoided. Int. J. Epidemiol. 42, 1018–1022 \(2013\)."). Our Future Health (OFH) is a recently established prospective cohort study supported by the UK Government, industry and charity sectors (see box 1 in ref. [21](https://www.nature.com/articles/s41591-026-04602-4#ref-CR21 "Straub, V. J. et al. Realizing the full potential of Our Future Health through data linkage and trans-biobank efforts. Nat. Genet. 57, 2341–2348 \(2025\).")) to enable the discovery and translation of more effective approaches to disease prevention, detection and treatment (Fig. [1](https://www.nature.com/articles/s41591-026-04602-4#Fig1)). Its ambition is to recruit a sample of 5 million UK-resident adults from a target population of _n_ = 53,108,969 (approximately the UK adult population in 2021–22), which is reflective of the UK population in terms of age, sex and ethnicity. If OFH achieves its sample ambition (Extended Data Table [1](https://www.nature.com/articles/s41591-026-04602-4#Tab3)), its cohort will cover approximately 10% of the UK adult population. Since recruitment began in late 2022, more than 2.5 million individuals have registered to participate in OFH (Extended Data Table [2](https://www.nature.com/articles/s41591-026-04602-4#Tab4)), and baseline phenotypic data are currently available on >1.9 million participants (Fig. [1a](https://www.nature.com/articles/s41591-026-04602-4#Fig1)). This makes OFH, at the time of writing, the largest multi-ethnic cohort and largest cohort of young people (18–40 years of age), working-age populations and people over 60 years of age in the world[22](https://www.nature.com/articles/s41591-026-04602-4#ref-CR22 "Cook, M. B. et al. Our Future Health: a unique global resource for discovery and translational research. Nat. Med. 31, 728–730 \(2025\)."). Although data collection is ongoing, the scale and population coverage means OFH already offers opportunities to advance health research and genomic medicine[21](https://www.nature.com/articles/s41591-026-04602-4#ref-CR21 "Straub, V. J. et al. Realizing the full potential of Our Future Health through data linkage and trans-biobank efforts. Nat. Genet. 57, 2341–2348 \(2025\)."). In terms of clinical potential, additional features of OFH, specifically its clinical research recruitment service[23](https://www.nature.com/articles/s41591-026-04602-4#ref-CR23 "Cook, M. B. et al. Cohort profile: Our Future Health. Int. J. Epidemiol. 54, dyaf171 \(2025\).") (Extended Data Fig. [1](https://www.nature.com/articles/s41591-026-04602-4#Fig5)), make it well-positioned to help address traditional translational bottlenecks often faced by biobanks[9](https://www.nature.com/articles/s41591-026-04602-4#ref-CR9 "Gallagher, C. S., Ginsburg, G. S. & Musick, A. Biobanking with genetics shapes precision medicine and global health. Rev. Genet. 26, 191–202 \(2025\)."), helping to differentiate it from other existing national, large-scale initiatives[15](https://www.nature.com/articles/s41591-026-04602-4#ref-CR15 "Fry, A. et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am. J. Epidemiol. 186, 1026–1034 \(2017\)."),[24](https://www.nature.com/articles/s41591-026-04602-4#ref-CR24 "Zeng, C. et al. Comparison of phenomic profiles in the All of Us Research Program against the US general population and the UK Biobank. J. Am. Med. Inform. Assoc. 31, 846–854 \(2024\)."),[25](https://www.nature.com/articles/s41591-026-04602-4#ref-CR25 "Chen, Z. et al. China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up. Int. J. Epidemiol. 40, 1652–1666 \(2011\)."),[26](https://www.nature.com/articles/s41591-026-04602-4#ref-CR26 "Gaziano, J. M. et al. Million Veteran Program: a mega-biobank to study genetic influences on health and disease. J. Clin. Epidemiol. 70, 214–223 \(2016\)."). **Fig. 1: Overview of OFH data and cohort.** ![Fig. 1: Overview of OFH data and cohort.](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41591-026-04602-4/MediaObjects/41591_2026_4602_Fig1_HTML.png) [Full size image](https://www.nature.com/articles/s41591-026-04602-4/figures/1) **a** , The timeline of data collection and data available in data release 13, released on 11 December 2025. **b** , An overview of available data in release 13. **c** , Locations of OFH pop-up clinics across the UK, overlaid on a regional heat map of life expectancy. **d** , The self-reported ethnicity composition compared wit
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