Nature Medicine, Journal Year: 2025, Volume and Issue: unknown
Published: March 11, 2025
Language: Английский
Nature Medicine, Journal Year: 2025, Volume and Issue: unknown
Published: March 11, 2025
Language: Английский
Nature, Journal Year: 2024, Volume and Issue: 627(8003), P. 340 - 346
Published: Feb. 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.
Language: Английский
Citations
244Nature Reviews Genetics, Journal Year: 2023, Volume and Issue: 25(1), P. 8 - 25
Published: Aug. 24, 2023
Language: Английский
Citations
132Circulation Genomic and Precision Medicine, Journal Year: 2024, Volume and Issue: 17(3)
Published: Feb. 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;
Language: Английский
Citations
11JAMA, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 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.
Language: Английский
Citations
8Nature, Journal Year: 2025, Volume and Issue: 637(8046), P. 554 - 556
Published: Jan. 8, 2025
Language: Английский
Citations
1bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 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.
Language: Английский
Citations
1Human Genomics, Journal Year: 2025, Volume and Issue: 19(1)
Published: Jan. 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.
Language: Английский
Citations
1Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)
Published: Feb. 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.
Language: Английский
Citations
1Nature Reviews Rheumatology, Journal Year: 2024, Volume and Issue: 20(10), P. 635 - 648
Published: Sept. 4, 2024
Language: Английский
Citations
7The American Journal of Human Genetics, Journal Year: 2024, Volume and Issue: 111(6), P. 999 - 1005
Published: April 29, 2024
Language: Английский
Citations
6