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Related Concept Videos

Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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  1. Home
  2. Multi-ancestry, Multitrait Polygenic Risk Scores For Myopia: Improved Accuracy And Clinical Potential.
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  2. Multi-ancestry, Multitrait Polygenic Risk Scores For Myopia: Improved Accuracy And Clinical Potential.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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Multi-Ancestry, Multitrait Polygenic Risk Scores for Myopia: Improved Accuracy and Clinical Potential.

Benyapa Insawang1,2, Guiyan Ni1,3, Nicholas Clark1,3

  • 1https://ror.org/004y8wk30QIMR Berghofer Medical Research Institute, Brisbane, Australia.

Twin Research and Human Genetics : the Official Journal of the International Society for Twin Studies
|May 18, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Developing new polygenic risk scores (PRSs) improves the genetic prediction of myopia across diverse ancestries. These multi-ancestry PRSs enable earlier and more equitable identification of at-risk individuals for myopia.

Keywords:
Multitrait GWASMyopiaPolygenic risk scoresSpherical equivalent refractive error

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Inducement and Evaluation of a Murine Model of Experimental Myopia
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Inducement and Evaluation of a Murine Model of Experimental Myopia
07:20

Inducement and Evaluation of a Murine Model of Experimental Myopia

Published on: January 22, 2019

Area of Science:

  • Ophthalmology
  • Genetics
  • Public Health

Background:

  • Myopia is a growing global health issue and a primary cause of vision impairment.
  • Genetic factors significantly contribute to myopia development.
  • Current polygenic risk scores (PRSs) often lack accuracy across diverse ancestries due to European-centric data.

Purpose of the Study:

  • To develop and assess PRSs for spherical equivalent refractive error (SER) and myopia using multi-ancestry data.
  • To evaluate the predictive performance of these PRSs across different ancestral populations.
  • To explore the potential of multi-trait, multi-ancestry PRSs for early and equitable myopia risk stratification.

Main Methods:

  • Utilized multitrait and multi-ancestry genomewide association study data.
  • Generated PRSs using SBayesRC for individual and combined ancestry models.
  • Validated PRSs in the Australian Twins Eye Study and UK Biobank participants.
  • Main Results:

    • European PRSs explained up to 20% of SER variance in Europeans and showed transferability to other ancestries.
    • A multi-ancestry PRS improved prediction in African populations.
    • PRSs accurately predicted high myopia risk (AUC ≥ 0.70) and axial length in children.
    • PRSs showed good predictive accuracy across diverse ancestral groups, with a multi-ancestry model enhancing prediction in African populations.

    Conclusions:

    • Multi-trait, multi-ancestry PRSs significantly enhance the genetic prediction of myopia.
    • These advanced PRSs hold potential for early and equitable risk stratification in children.
    • Improved genetic prediction can aid in developing targeted interventions for myopia prevention and management.