Genomic data in the All of Us Research Program

Nature, Год журнала: 2024, Номер 627(8003), С. 340 - 346

Опубликована: Фев. 19, 2024

Abstract Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for field genetics 1–4 . The All Us Research Program longitudinal cohort study aiming to enrol group at least one million USA accelerate biomedical research and improve health 5,6 Here we describe programme’s genomics data release 245,388 clinical-grade genome sequences. This resource unique in its diversity as 77% participants are from communities that historically under-represented 46% racial ethnic minorities. identified more than 1 billion variants, including 275 previously unreported 3.9 which had coding consequences. Leveraging linkage between genomic electronic record, evaluated 3,724 variants associated with 117 diseases found high replication rates both European ancestry African ancestry. Summary-level publicly available, individual-level can be accessed by researchers through Researcher Workbench using passport model median time initial researcher registration access 29 hours. We anticipate this dataset will advance promise medicine all.

Язык: Английский

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Principles and methods for transferring polygenic risk scores across global populations

Nature Reviews Genetics, Год журнала: 2023, Номер 25(1), С. 8 - 25

Опубликована: Авг. 24, 2023

Язык: Английский

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Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization

Circulation Genomic and Precision Medicine, Год журнала: 2024, Номер 17(3)

Опубликована: Фев. 21, 2024

Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD;

Язык: Английский

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Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores

JAMA, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 16, 2024

Importance Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing provide similar individual-level assessments of susceptibility remains incompletely characterized. Objective To characterize the agreement CHD PRSs that perform similarly at population level. Design, Setting, Participants Cross-sectional study participants from diverse backgrounds enrolled in All Us Research Program (AOU), Penn Medicine BioBank (PMBB), University California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record genotyping data. Exposures published new developed separately testing samples. Main Outcomes Measures performed population-level prediction were identified by comparing calibration discrimination models prevalent CHD. Individual-level was tested intraclass correlation coefficient (ICC) Light κ. Results A total 48 calculated 171 095 AOU participants. The mean (SD) age 56.4 (16.8) years. 104 947 (61.3%) female. 35 590 (20.8%) most genetically to an African reference population, 29 801 (17.4%) admixed American 100 493 (58.7%) European remaining Central/South Asian, East Middle Eastern populations. There 17 589 (10.3%) 153 506 without (89.7%) When included model CHD, 46 had practically equivalent Brier area under receiver operator curves (region practical equivalence ±0.02). Twenty percent least 1 score both top bottom 5% risk. Continuous individual predictions poor (ICC, 0.373 [95% CI, 0.372-0.375]). κ, used evaluate consistency assignment, did not exceed 0.56. Analysis among 41 193 PMBB 53 092 yielded different sets scores, which also lacked agreement. Conclusions Relevance level demonstrated highly variable estimates Recognizing may generate incongruent estimates, effective implementation will require refined statistical methods quantify uncertainty strategies communicate this patients clinicians.

Язык: Английский

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Human embryo editing against disease is unsafe and unproven — despite rosy predictions

Nature, Год журнала: 2025, Номер 637(8046), С. 554 - 556

Опубликована: Янв. 8, 2025

Язык: Английский

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Subcontinental Genetic Diversity in the All of Us Research Program: Implications for Biomedical Research

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Янв. 10, 2025

ABSTRACT The All of Us Research Program ( ) seeks to accelerate biomedical research and address the underrepresentation minorities by recruiting over one million ethnically diverse participants across United States. A key question is how self-identification with discrete, predefined race ethnicity categories compares genetic diversity at continental subcontinental levels. To contextualize in , we analyzed ∼2 common variants from 230,016 unrelated whole genomes using classical population genetics methods, alongside reference panels such as 1000 Genomes Project, Human Genome Diversity Simons Project. Our analysis reveals that within self-identified groups exhibit a gradient rather than discrete clusters. distributions ancestries show considerable variation ethnicity, both nationally states, reflecting historical impacts U.S. colonization, transatlantic slave trade, recent migrations. samples filled most gaps along top five principal components current global panels. Notably, “Hispanic or Latino” spanned much three-way (African, Native American, European) admixture spectrum. Ancestry was significantly associated body mass index (BMI) height, even after adjusting for socio-environmental covariates. In particular, West-Central East African showed opposite associations BMI. This study emphasizes importance assessing ancestries, approach insufficient control confounding association studies.

Язык: Английский

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Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Human Genomics, Год журнала: 2025, Номер 19(1)

Опубликована: Янв. 31, 2025

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory cancers, diabetes, and mental health disorders pose a significant global challenge, accounting for the majority of fatalities disability-adjusted life years worldwide. These arise from complex interactions between genetic, behavioral, environmental factors, necessitating thorough understanding these dynamics to identify effective diagnostic strategies interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability explore interactions, several challenges remain. include inherent complexity heterogeneity multi-omic datasets, limitations analytical approaches, severe underrepresentation non-European genetic ancestries most omics which restricts generalizability findings exacerbates disparities. This scoping review evaluates landscape data related NCDs 2000 2024, focusing on advancements integration, translational applications, equity considerations. We highlight need standardized protocols, harmonized data-sharing policies, advanced approaches artificial intelligence/machine learning integrate study gene-environment interactions. also opportunities translating insights (GxE) research into precision medicine strategies. underscore potential advancing enhancing patient outcomes across diverse underserved populations, emphasizing fairness-centered strategic investments build local capacities underrepresented populations regions.

Язык: Английский

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Instability of high polygenic risk classification and mitigation by integrative scoring

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Фев. 12, 2025

Polygenic risk scores (PRS) continue to improve with novel methods and expanding genome-wide association studies. Healthcare commercial laboratories are increasingly deploying PRS reports patients, but it is unknown how the classification of high polygenic changes across individual PRS. Here, we assess performance cataloged for three complex traits. We chronologically order all trait-related publications (Pubn) identify single Best(Pubn) each Pubn that has strongest target outcome. While demonstrates generally consistent population-level strengths associations, individuals in top 10% distribution varies widely. Using PRSmix framework, which integrates information several prediction, generate corresponding ChronoAdd(Pubn) combine from up including Pubn. When compared Best(Pubn), demonstrate more high-risk amongst themselves. This integrative scoring approach provides stable reliable an adaptable framework into new can be incorporated as they introduced, integrating easily current implementation strategies. Variability exists classifying diseases. Here authors show improves consistency overall toward clinical applications.

Язык: Английский

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Systemic lupus erythematosus genetics: insights into pathogenesis and implications for therapy

Nature Reviews Rheumatology, Год журнала: 2024, Номер 20(10), С. 635 - 648

Опубликована: Сен. 4, 2024

Язык: Английский

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Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network

The American Journal of Human Genetics, Год журнала: 2024, Номер 111(6), С. 999 - 1005

Опубликована: Апрель 29, 2024

Язык: Английский

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