It’s common knowledge that DNA gets transcribed into RNA, which then gets translated into a protein (often called the central dogma of molecular biology), but there’s a key step in the process that often gets overlooked: post-translational modification. It’s sort of a catch-all term for all of the edits proteins undergo after synthesis (e.g., adding new chemical bonds or snipping off parts of the amino acid chain). One of the most common post-translation modifications, glycosylation, is ancient, versatile, and could help predict diseases a lot earlier, according to a new review published in Nature Chemical Biology.
During glycosylation, short, complex sugar chains (glycans) get tacked on to proteins and can change the way they fold. These glycans have been pretty difficult to study, in part because they’re not hardwired by our DNA. Instead, they’re constantly changing in response to our environment, lifestyle factors, and even hidden diseases. In fact, the study found shifting glycosylation patterns may be able to predict type 2 diabetes up to 10 years before it’s formally diagnosed. It’s this feature of glycans researchers hope to exploit in the emerging field of glycomics.
Read more: “These “Junk” Proteins May Fuel Adaptation”
“This flips medicine on its head,” study author Wei Wang of Edith Cowan University in Australia said in a statement. “Instead of waiting for people to get sick, we could spot the risk early and step in sooner.”
In the review, which examined several studies on glycans, Wang and his colleagues identified key patterns in the glycosylation of the immune system’s most common antibody (IgG) associated with a variety of different illnesses—from cancer to infectious diseases. And that’s just one protein.
Because glycans are so responsive, they’re also highly individualized. In the future, the researchers say, your glycomic profile could offer unprecedented insights into your health, and targets for more personalized treatments. Or as Wang put it, “We’re at a turning point. If we get this right, it could transform how we diagnose and treat disease.” 
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Lead image: peshkova / Adobe Stock
