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Implementation of individualised polygenic risk score analysis: a test case of a family of four

Manuel Corpas1,2,3, Karyn Megy4,5, Antonio Metastasio4,6

  • 1Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, UK. m.corpas@cpm.onl.

BMC Medical Genomics
|October 3, 2022
PubMed

Insights

Polygenic risk scores (PRS) can stratify populations by disease risk. However, implementing PRS for individual risk assessment in healthcare requires further standardization and validation for accurate clinical translation.

Area of Science:

  • Genomics
  • Computational Biology
  • Precision Medicine

Background:

  • Polygenic risk scores (PRS) are utilized in research to stratify populations by disease risk.
  • Healthcare systems are exploring PRS for population health management.
  • Limited research exists on implementing PRS at an individual level.

Observation:

  • 15 PRS phenotypes (cancer, cardiovascular, metabolic, autoimmune) were curated, utilizing over 37 million SNPs.
  • Whole genome sequencing data from a family of four was used for phenotype testing.
  • Individual PRS were calculated and assigned percentile values against reference populations (1000 Genomes Iberians, Europeans, or all samples).

Findings:

  • Over 96 billion allele effects were computed to derive individual PRS.
  • Results underscore the necessity for standardized PRS development and data sharing.
  • Individual risk assessment is crucial, moving beyond generalized population averages.

Implications:

  • Translating PRS into actionable clinical risk metrics presents current challenges.
  • Standardization is key for the reliable clinical application of PRS.
  • Future work should focus on refining PRS for individual-level predictive accuracy in healthcare.
Abstract

Keywords:
Disease preventionGenetic riskPhenotypesPolygenic risk scores

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