 of one letter for another with for example, a C instead of a T in a person’s code. They are inherited and are not mutations, but rather variations. These tiny genetic differences can have a major impact on a number of different factors from the way we metabolize different nutrients, to how we synthesize neurotransmitters, to how we respond to light, to our hormone production, to our likelihood to develop disease, to our muscle growth, to our sleep quality, and beyond.
Genome-Wide Association Studies and Gene Specific Candidate Studies
So how do we know what these variations actually mean in real life? Genome-Wide Association Studies (GWAS for short) involve taking a group of people with a specific condition or trait and comparing their genome to a control group of people who don’t have that condition or trait. If they find there are specific SNPs that appear significantly more often in the trait-related group than the control group, it is likely that there is a correlation between that SNP and the condition or trait. For example, in the chart to the left, you can see that the C version of this specific allele appears more often in the group with heart disease. It is important to note that correlation does not necessarily equal causation, but this type of study allows further investigation into the genetic reasons for the difference in outcome. Sometimes, there are very specific reasons we can understand why a SNP produces an outcome, and other times it is simply correlation without a specific cause. Understanding the cause allows us to use precise and targeted interventions to modify the outcome, which is what I focus on.
Gene Specific Candidate Studies are to GWAS similar but are a more narrow approach. Instead of comparing the whole genome of two groups of people, they select a specific gene that they believe might cause a different outcome between the two groups. For example, if a study examines the genetic basis for vitamin D deficiency, they might choose to look at only the differences in the Vitamin D Receptor gene. This allows for a more granular approach that is more likely to help us understand of the cause of the outcome.
Epigenetic Modifications: Changing the Recipe
So you might be asking yourself, if 62% of the people in the above graphic have heart disease, why don’t all of them who have the same SNP? While we can often identify a pattern, the human genome is a complex and dynamic multi-factoral system that is not necessarily linear. And, this is where epigenetics comes in. Just as the methylation marks changed the expression of the genes in the agouti mice and queen bee in the example above, there are 100’s of possible ways beyond methylation to change the outcome of the gene SNP, and many different complex networks of interactions.
Our cells are in constant communication with the genome and use the epigenome to tell it how to respond the environment. Think of the genome as a recipe for a pie. It’s just a list of instructions, not the actual pie. The epigenome is like the chef, who assembles the ingredients and bakes the pie. The cells are like the customers, who might give him feedback on how the pie tastes. After he gets feedback, he might decide to add some extra salt, bake the pie for longer, or add some extra blueberries. The epigenetic modifications are like his notes written in the recipe. The important thing to remember, is that it acts as a feedback loop. As he gets a response from his customers, he modifies the recipe. This is how our genes respond and react to the signals they get from nutrients and other environmental factors to make sure the products they create are exactly what are cells need for their current situation. This is how nutrigenomics works. By inputting the right signals through food, nutrients, or herbs, we can instruct the epigenome to change the recipe so we get the result we want.
Its important to understand that through this process, we actually have more control over our health than previously thought. When I look at your SNPs, understand that what I tell you is not a progn