Article in Circulation. Genomic and precision medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
2 · The registry
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.
Ebuka OnyenobiDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.ORCID 0009-0002-9982-5506
Michael ZhongDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.
Opeyemi SoremekunThe African Computational Genomics Research Group, Medical Research Council/Uganda Virus Research Institute, and London School of Hygiene and Tropical Medicine (MRC/UVRI & LSHTM), Entebbe, Uganda (O.S., A.K., S.F.).
Abram KamizaThe African Computational Genomics Research Group, Medical Research Council/Uganda Virus Research Institute, and London School of Hygiene and Tropical Medicine (MRC/UVRI & LSHTM), Entebbe, Uganda (O.S., A.K., S.F.).ORCID 0000-0002-3919-7651
Romuald BouaClinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, Nanoro, Burkina Faso (R.B.).ORCID 0000-0001-8325-2665
Tinashe ChikoworeDepartment of Medicine, Harvard Medical School, Boston, MA (T.C.).ORCID 0000-0002-6743-751X
ACCME Research Group
Segun FatumoThe African Computational Genomics Research Group, Medical Research Council/Uganda Virus Research Institute, and London School of Hygiene and Tropical Medicine (MRC/UVRI & LSHTM), Entebbe, Uganda (O.S., A.K., S.F.).ORCID 0000-0003-4525-3362
Ananyo ChoudhurySydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences (R.B., A.C., S.H., M.R.), University of the Witwatersrand, Johannesburg, South Africa.ORCID 0000-0001-8225-9531
Scott HazelhurstSydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences (R.B., A.C., S.H., M.R.), University of the Witwatersrand, Johannesburg, South Africa.ORCID 0000-0002-0581-149X
Clement AdebamowoDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.ORCID 0000-0002-6571-2880
Michèle RamsaySydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences (R.B., A.C., S.H., M.R.), University of the Witwatersrand, Johannesburg, South Africa.ORCID 0000-0002-4156-4801
Bamidele TayoDepartment of Public Health Sciences, Loyola University Parkinson School of Health Sciences and Public Health, Maywood, IL (B.T.).
Jennifer S AlbrechtDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.ORCID 0000-0003-4838-2274
Timothy D O'ConnorDepartment of Medicine (T.D.O., B.D.M.), University of Maryland School of Medicine, Baltimore.
Yuji ZhangDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.ORCID 0000-0002-5429-6762
Braxton D MitchellDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.ORCID 0000-0003-4920-4744
Sally N AdebamowoDepartment of Epidemiology and Public Health (E.O., M.Z., C.A., J.S.A., Y.Z., B.D.M., S.N.A.), University of Maryland School of Medicine, Baltimore.ORCID 0000-0003-4713-2433
Funding
Polygenic Risk Score (PRS) Methods and Analysis for Populations of Diverse Ancestry - Study SitesU01HG011717 · NHGRI · UNIVERSITY OF MARYLAND BALTIMORE · PI ADEBAMOWO, SALLY NNEOMA, TAYO, BAMIDELE OLUSEGUN · 2021 to 2025
$4.6M
Leveraging pleiotropy to develop polygenic risk scores for cardiometabolic diseasesR03HL172139 · NHLBI · UNIVERSITY OF MARYLAND BALTIMORE · PI ADEBAMOWO, SALLY NNEOMA · 2023 to 2024
backgroundMost polygenic risk scores (PRS) have been developed in European populations, frequently leading to limited transferability across diverse ancestry populations. This study aimed to develop and evaluate PRS for blood pressure (BP) traits in continental African populations and investigate how African genetic diversity influences PRS performance.
methodsWe generated PRS for systolic BP, diastolic BP, pulse pressure, and hypertension. We used a pan-African cohort as the target population and compared single-ancestry and multi-ancestry PRS methods. We compared the performance of African ancestry-derived PRS against multi-ancestry PRS on the entire data set and within South, East, and West African subpopulations.
resultsMulti-ancestry PRS demonstrated significantly higher predictive accuracy compared with single-ancestry PRS models. PRS predictive accuracy varied across different African regions, with the highest performance observed in East Africa. In the combined population, the difference in mean BP values between the first multi-ancestry PRS quartile and the top quartile was 6.53 (95% CI, 5.3-7.74), 3.81 (95% CI, 3.9-4.52), and 3.59 (95% CI, 2.4-4.32) mm Hg for systolic BP, diastolic BP, and pulse pressure, respectively. Individuals in the highest PRS risk quartile had odds of hypertension that were 1.47 (95% CI, 1.7-1.69) times greater than those in the lowest risk quartile.
conclusionsThese findings highlight the importance of integrating diverse ancestries in PRS development and accounting for subpopulation genetic variation to improve the predictive accuracy of BP PRS in African populations.
Indexed as
Black PeopleBlood PressureHypertensionMultifactorial InheritanceAdultFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansMaleMiddle AgedPolymorphism, Single NucleotideRisk Factorsblack peopleblood pressuregenetic risk scoregenetic variationgenome-wide association studyhypertension
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.
Development and Validation of Polygenic Risk Scores for Blood Pressure Traits in Continental African Populations. · full record | OpenQuestion