Kit activities address 2 central questions: How are traits, such as disease risk, distributed across a population? And how can identifying an individual's risk shape health care decision-making? A polygenic risk score (PRS) combines multiple genetic risk factors for developing a disease into a single calculation. To help students understand how PRSs can affect health decisions, they use 3-D boxes to represent normal and skewed data curves as they study a person's risk for 2 diseases.

Product Details
A unique experience that teaches both graphing literacy and genetics

The How Do Polygenic Risk Scores Stack Up? Kit uses authentic data and graphical representations to address 2 central questions: How are traits, such as disease risk, distributed across a population? And how can identifying an individual's risk shape health care decision-making? Recent advances have led to models that combine the impact of genetic risk factors for an individual developing a particular disease into a single calculation known as a polygenic risk score (PRS). To help students understand how these models can affect health decisions, the activity employs 3-dimensional boxes to represent normal and skewed population curves, giving learners a visually impactful hands-on experience with the data. Students use these curves to examine polygenic risk scores and assess a person's risk for 2 different complex diseases. In addition to teaching essential data and graphing skills, the activity also highlights a weakness in current genomic research—lack of diversity—with the hope of equipping the next generation of researchers, health care workers, and consumers to address this critical issue.

Product Features

• Designed for a class of 30 students and easily adaptable to larger classes.
• Includes 30 unique boxes that stack and rotate to show 4 distinct data distributions.
• Boxes are foldable for easy storage.
• Visually impactful examples of normal and skewed distributions.
• Discusses the need for diversity in current genomic research.

Time Requirements
One 90-minute block period or two 45-minute periods.

Learning Objectives

• Analyze data on traits within a population to identify patterns within expressed traits.
• Construct a model of trait distribution across a population and analyze data to determine where an individual lies within that distribution.
• Discuss how relative diversity within a population sample can impact the clinical utility of an individual's polygenic risk score.
• Classify a distribution graph as "normal" or "skewed."
• Given a data set, build models that illustrate distribution across a population.
• Explain what a polygenic risk score is and use it to assess an individual's genetic risk of developing a complex disease.
• Describe the limitations of polygenic risk scores.