Trait Predictions: The Science Behind Eye Color, Height, and More

One of the more enjoyable parts of a Genomisaur report — individual or family — is the trait predictions. Eye color, hair color, height, BMI tendency, lactose tolerance, caffeine metabolism, and so on. How do we predict traits from DNA, and how much should you trust the predictions?

Traits Are Polygenic Too

Like disease risk, most human traits are influenced by many genes acting together. Eye color was once taught as a simple "brown is dominant, blue is recessive" story. We now know at least 16 genes contribute to eye color, with two (OCA2 and HERC2) carrying most of the weight.

Height is even more complex. Over 12,000 genetic variants contribute to how tall you are, each adding or subtracting a tiny amount. Together, genetics explains about 80% of the variation in adult height; nutrition and environment account for the rest.

How We Make Predictions

For each trait, we use a model built from large-scale genetic studies that identified which variants matter and how much each one contributes. The approach is similar to PRS for disease: sum up the effects of many variants to produce a single prediction or probability.

For categorical traits like eye color, the result is a probability distribution — for example, 55% chance brown, 30% chance green, 15% chance blue. For continuous traits like height, the result is a predicted value with a range of uncertainty.

Why Some Traits Are More Predictable Than Others

The key factor is heritability — how much of the variation in a trait is explained by genetics versus environment.

Highly heritable traits (80%+ genetic) include eye color, hair color, earlobe type, and bitter taste perception. These are the most accurately predicted from DNA because genetics dominates.

Moderately heritable traits (50–80% genetic) include height, BMI tendency, and skin pigmentation. These are reasonably well predicted, but environmental factors introduce more uncertainty.

Lower heritability traits (under 50% genetic) are harder to predict from DNA alone because lifestyle and environment carry more weight. We generally don't include traits with very low heritability in our reports.

Family Reports: Trait Distributions

In a family report, trait predictions become more interesting because we show you the distribution of outcomes across 100 simulated offspring. Instead of "your child will probably be tall," you see something like 60 of 100 simulated children in the above-average height range, 15 average, and 25 below. The distribution captures the inherent randomness of inheritance more honestly than a single prediction does.

A Note on the Fun Stuff

Trait predictions are where genetics gets personal. Health risk scores matter and are actionable, but knowing whether you're genetically predisposed to love or hate cilantro, whether you tend toward early-bird sleep, or how quickly you metabolize caffeine adds a "that explains a lot" layer that makes the report more engaging.

Just remember the predictions are probabilistic. A 70% chance of brown eyes is exactly that — a 70% chance, not a guarantee.