Causation vs. correlation. What does that even mean? If you ask your friend who majored in philosophy for a semester-and-a-half in college, you’ll probably get an explanation that sounds more like Klingon than English.

However, the different between causation and correlation is incredibly important for you if you have a rare genetic disorder, like acrocephaly, amyotrophic lateral sclerosis, protein C deficiency, or tuberous sclerosis complex.

The Human Genome Project took 13 years to successfully map a person’s complete genetic code. The scientists involved wanted to find out more about the most amazing organism alive—humans. They hoped that by breaking down the genes they could discover how the body functions.

Since its completion in 2003, numerous institutions have sought to add to this knowledge by collecting and sequencing the genes of human volunteers.

How does this relate, or correlate, to rare genetic disorders?

We know that the aforementioned disorders are passed down through the genes—which means that by analyzing a person’s genetic code we can make a more educated guess on what illnesses and disorders they are predisposed to develop.

How great would it be to know for sure your child is safe, and will continue to be safe, from certain disorders?

How amazing would it be to predict the probability of disease-development so that you can begin taking precautions sooner rather than later?

Never again would you have to hear the words, “It’s just too late.”

We could know with a reasonable degree of certainty which genetic disorders will manifest and which will not.

Herein lies the importance of knowing the difference between correlation and causation. If two or more things are correlated, it means there is a relationship of some kind—positive or negative—between them. For example, as a person’s level of education broadens, so, too, might that person’s average yearly salary. This is an example of positive or direct correlation. An example of inverse or negative correlation? Take the pirate population, steadily decreasing since the 17^th century, as the global average temperature climbs.

The relationships of the data are clear. But does one cause the other?

If the answer is yes, then there’s causation. Otherwise, it’s simply correlation—an observation at best.

You might be able to make the argument that education and yearly income are causally linked, but how many variables are being ignored? For example, socio-economic class, ethnicity, parental income, geographical location, and even the motivations and skills of the individual.

Scientists work hard to provide data when a claim has been made for causation. Having hundreds or thousands or hundreds of thousands of genetic codes will allow scientists to see how the genes translate to diseases and disorders.

You can volunteer to be a part of the Personal Genome Project. Find out more by clicking here.

You might be afraid to volunteer. Who wants to be sequenced only to find out you’re probably gonna develop ovarian cancer or Huntington’s disease? Talk about a buzzkill.

You might see this increased likelihood as a death sentence, but you don’t have to.

You can adopt the position Canadian Michael Smith has. He knows what genetic disorders he is likely to develop and considers this knowledge one more tool to stave them off. He’s told his doctor, and he’s working to manage his risks.

You can read Michael Smith’s post on MedPage Today by clicking here.

Now you know a bit more about what scientists need, as well as how to recognize the difference between causation and correlation. Tell us about your personal journey with a genetic disorder!