You’ve seen them – every week a new story about genes for this or that, or the environmental cause of some effect or other. Often the stories say opposite things; red wine is good for us in one article, bad in the next, depending on the study. Or it might be about coffee, eggs or vitamin supplements, and health advice to pregnant women is often contradictory. The gene for autism or dyslexia or asthma is found one week, but the finding can’t be replicated the next. Does hydraulic fracturing of rocks to mine natural gas and oil contaminate ground water? Are GMO foods good or bad for us? You’d think figuring out these things would be easy – genes do something, they make us what we are, while people who eat a given food get sick and those who don’t stay well, so what’s the problem?
The problem is complexity. Modern scientific methods are very good at finding cause when an effect is large or clear-cut – the fact that smoking causes lung cancer was easy to see once the question was asked, the genetic variant that causes cystic fibrosis was relatively straightforward to find because the effect of the mutation is so major. But determining causation gets thorny when a disease or effect is caused by multiple genes, or genes plus some environmental factor, or when there are many pathways to the same outcome - all of which are common scenarios. The fact that everyone is unique to start with makes it even thornier.
|When an object casts a shadow, we know it's not the shadow causing the light or creating the object. Cause and effect are easy to determine. But sometimes causality can be a lot trickier to determine. Image credit: Dhilung Kirat|