Using Untargeted Metabolomics to Diagnose Inborn Errors of Metabolism

 

What do phenylketonuria (PKU), galactosemia, and maple syrup urine disease (MSUD) have in common? All three are considered inborn errors of metabolism, or rare genetic disorders in which the body cannot effectively or adequately metabolize certain parts of food, causing health issues. For example, people with PKU have an over-accumulation of phenylalanine. According to Technology Networks, a research team from the Baylor College of Medicine recently discovered a newborn screening method which can improve inborn error of metabolism diagnosis by 7x. This method? Untargeted metabolomics.

Check out the full study findings published in JAMA Network Open.

Untargeted Metabolomics

At birth, hospitals perform newborn screening, a public health tool intended to assist in the diagnosis of rare, metabolic, or hormone-related conditions. During the newborn screening process, doctors take blood samples and perform hearing and heart tests, among others. However, tests vary from state to state; some states test for certain conditions while others do not. The lack of standardization may reduce the efficacy of these tests. Additionally, shares Dr. Sarah Elsea, screening for inborn errors of metabolism has remained relatively stagnant over the prior 4-5 decades. Thus, researchers knew that something needed to change to best improve patient outcomes.

To begin, researchers developed an untargeted metabolomics profiling test to evaluate a variety of metabolic compounds within blood samples. According to Creative Proteomics:

Untargeted metabolomics, namely discovery metabolomics, involves the comparison of the metabolome between the control and test groups, to identify differences between their metabolite profiles which may be relevant to specific biological conditions.

In evaluating a broader range of metabolic compounds, researchers are better able to screen for a wider range of conditions. The research found:

  • Untargeted metabolomics is more efficient and provides a faster diagnosis than the current diagnostic standards. Compared to other diagnostic methods, this process is also less invasive.
  • After comparing 4,464 clinical samples, researchers were able to achieve a positive diagnosis rate of 7%, compared to 1% with traditional methods.
  • Using untargeted metabolomics, researchers determined that mild forms of rare disease are more common than once believed. Additionally, this process has been helpful in diagnosing various movement, seizure, and autism spectrum disorders. Despite the process finding more mild conditions, it is also helpful in diagnosing those with severe inborn errors of metabolism.
  • Utilizing untargeted metabolomics in conjunction with newborn screening could help make more definitive diagnoses.