Autoimmunity Probability

This activity is part of our Science Lab series. Check out the ANU Science Lab for more experiments! In this activity, you will model immune system checkpoints using coloured sticks and dice to discover how genetic risk factors and probability lead to autoimmune diseases like type 1 diabetes and lupus.

Autoimmunity probability experiment materials & ingredients

• Popsicle sticks in different colours (at least 3 sticks of each colour)
• A non-transparent bag or bowl to hold the sticks
• 1 six-sided die
• Results logging sheet 
• Pen

How to model autoimmunity checkpoints: Step-by-step instructions

Step 1: Set up the general population test (Normal Risk)

1. Place equal numbers of each coloured popsicle stick into your bag or bowl and mix them thoroughly.
2. Determine self-colour: Without looking, draw one stick from the bag to set the "self-colour" for Person 1. Record this colour in your results table.
3. Checkpoint 1 (Immune cell creation): Randomly draw a stick from the bowl.
   • If the stick matches your self-colour: Roll your six-sided die. If you roll a 4, 5, or 6, the body successfully destroys the self-reactive cell - end testing for this person. If you roll a 1, 2, or 3, the cell escapes regulation; put the stick back and proceed to Checkpoint 2.
   • If the stick does not match: Put the stick back and move directly to Checkpoint 2.
4. Checkpoint 2 & Checkpoint 3: Repeat the same procedure for Checkpoint 2 and Checkpoint 3.
5. Determine outcome: If a self-reactive cell survives all three checkpoints, record a "Yes" in your results sheet for whether the person developed an autoimmune disease. Repeat this for multiple people to build a representative sample.

Step 2: Test higher genetic risk groups

1. Repeat the experiment for high-risk profiles using the provided high-risk tables.
2. For high-risk checkpoints, alter the die roll threshold to model genetic variations that make the body less effective at regulating autoimmune cells.

Step 3: Analyse the population data

1. Count the number of "Yes" outcomes for each testing group.
2. Divide the total number of "Yes" answers by the total number of people tested in that group, then multiply by 100 to calculate the percentage of individuals developing an autoimmune condition.

How autoimmunity models work: The science explained

This simulation demonstrates how immune system checkpoints prevent the body from attacking its own healthy tissues:

• Self vs Non-Self Recognition: White blood cells (made in bone marrow) and T cells (developed in the thymus) protect the body from infections. However, some developing cells accidentally produce antibodies that bind to human cells.
• Biological Checkpoints: Under normal conditions, strict biological checkpoints catch and destroy self-reactive cells before they escape into the bloodstream.
• Genetic Risk Factors: Differences in specific genes can make these immune checkpoints less efficient at filtering self-reactive cells. When self-reactive cells bypass multiple checkpoints, the immune system begins attacking its own organs, resulting in autoimmune conditions such as type 1 diabetes, rheumatoid arthritis, multiple sclerosis, or lupus.

Modeling experimental systems with probability allows scientists to visualize how slight genetic variations multiply the likelihood of disease across large populations.

Science fair projects & taking it further: Experimenting with variables

• Graph your data: Plot your calculated percentages on a bar chart comparing normal risk against 1, 2, and 3 high-risk checkpoints. How sharply does disease incidence rise as more checkpoints become less effective?
• Classroom population: Combine your trial results with your classmates to build a dataset of hundreds of simulated individuals, observing how larger sample sizes improve data accuracy.

Enjoyed this experiment? Explore more hands-on activities on the Science Lab ANU YouTube channel.