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Background: Most 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.
Methods: We 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.
Results: Multi-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.
Conclusions: These 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.
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http://dx.doi.org/10.1161/CIRCGEN.124.005048 | DOI Listing |
Mil Med Res
August 2025
Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China.
Background: Antipsychotic-induced movement disorders (AIMDs) are prevalent side effects of antipsychotics, particularly during the acute phase of treatment. This study aimed to elucidate the genetic mechanisms underlying AIMDs using a genome-wide association study (GWAS).
Methods: GWASs on AIMDs were conducted in 3 independent cohorts: a discovery cohort of 3067 patients (2016 subjects were reserved after quality control), a validation cohort of 277 patients, and a multi-ancestry validation cohort of 766 patients.
HGG Adv
August 2025
Department of Genetics, Stanford University, Stanford, CA, USA; Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA. Electronic address:
Genetic factors play an important role in prostate cancer (PCa) development with polygenic risk scores (PRS) predicting disease risk across genetic ancestries. However, there are few convincing modifiable factors for PCa and little is known about their potential interaction with genetic risk. Our study explores the role of neighborhood socioeconomic status (nSES)-and how it may interact with PRS-on PCa risk.
View Article and Find Full Text PDFBackground: Cardiometabolic diseases (CMD) are a leading cause of morbidity and mortality. While both family history (FH) and polygenic risk scores (PRS) are predictive of CMD risk, few studies have systematically evaluated their independent and joint effects. This study aimed to quantify the individual contributions of FH and PRS, as well as their combined impact on CMD risk.
View Article and Find Full Text PDFLancet Reg Health Am
September 2025
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Background: The Polygenic risk score (PRS) is effective in predicting Alzheimer's Disease (AD) risk among Europeans but remains understudied in Hispanics. Genome-wide association studies (GWAS) based on multiple ancestries can improve PRS prediction. We used GWAS data from the largest available African, European, and Hispanic populations and performed PRS analyses using novel methodologies to evaluate the performance of single- and multi-ancestry PRS models in predicting AD risk among Hispanic population.
View Article and Find Full Text PDFHum Genomics
July 2025
Department of Medicine, Division of Medical Genetics, University of Washington Medical Center, Seattle, WA, USA.
Background: Many factors, including environmental and genetic variables, contribute to Colorectal Cancer (CRC) risk. The genetic components of risk can be divided into monogenic and polygenic factors. Just as monogenic factors can increase risk for more than one condition, polygenic factors may also underlie multiple phenotypes, including behavioral traits.
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