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Genetics 101: Genetic Risk to Disease and Polygenic Risk Scores (Webcast 2 of 4)

In this second of a series of four webcasts, Dr Richard Russell, Lead Health Data Scientist at RGA, explores the latest genetics research concerning human susceptibility to disease and examines the pertinent question: can genetic information transform clinical risk assessment in terms of disease prediction and stratification?

Genetic variation describes the natural genetic differences that occur between individuals. The human genome is over 3 billion base pairs long (the ‘building blocks’ of DNA), but only about 0.01% of the human DNA sequence varies between any two persons.

The most common type of genetic variation is known as a single nucleotide polymorphism or SNP (pronounced “snip”). A SNP occurs when a base pair in a particular position in the genome is different between individuals, and geneticists have long observed that certain SNPs occur more commonly in people with a particular disease or trait. In recent years, statistical geneticists have developed the ‘polygenic risk score’ (PRS), which is a metric that condenses information from tens, hundreds, thousands, or even millions of a person’s SNPs into a single score that measures the individual’s genetic predisposition to specific diseases or complex traits.

Clinicians commonly test for high-penetrance single gene mutations such as BRCA1 or BRCA2, which confer significant increased risk for breast cancer. Such simple one-to-one relationships between a gene and susceptibility to disease, however, are very rare. Rather, the genetic architecture of most disease is overwhelmingly polygenic, with multiple SNPs, each of small effect, cumulatively affecting disease risk.

PRSs are simple to calculate and remain constant over a lifetime. In the past few years, academic researchers have developed PRSs for many conditions and have tested them in their studies. PRSs are already proving useful to predict disease onset. For example, a PRS to predict coronary artery disease risk has already demonstrated that people with a PRS in the highest 5% have a threefold increased risk of experiencing the condition compared to individuals with lower PRSs. In a study on genetic risk and breast cancer, women whose PRSs were in the top 20% were shown to have a 17.2% lifetime risk of breast cancer compared to a 5.3% lifetime risk for women whose scores were in the lowest quintile.

Disease prevention and early disease detection are critical for extending human longevity. During the past few years, hundreds of research papers have been published demonstrating that PRSs can capture important information about an individual’s risk of developing common diseases. Many scientific, clinical, and social obstacles must still be overcome to bring PRSs into clinical practice. Regardless, recent scientific advances have brought us to a point where PRSs will almost certainly have a place in clinical risk prediction in the near future.

View additional webcasts in this series:

The Presenter

  • Richard Russell
    Lead Health Data Scientist, 
    Global Research and Data Analytics,

    RGA

Summary

Dr Richard Russell, Lead Health Data Scientist at RGA, explores the latest genetics research concerning human susceptibility to disease and examines the pertinent question: can genetic information transform clinical risk assessment in terms of disease prediction and stratification?
https://player.vimeo.com/video/281697352
  • antiselection
  • anti-selection
  • APS
  • Attending Physician Statement
  • coronary
  • demographic trends
  • genetic
  • genome
  • medical underwriting
  • morbidity
  • mortality assumptions
  • mortality experience
  • mortality trends
  • precision medicine
  • predictive modeling