Sequencing Alone Inaccurate for Detecting Rare Metabolic Diseases in Newborns

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An in-depth study suggests that genome sequencing alone is not accurate enough for diagnosing rare inherited metabolic diseases, such as phenylketonuria, in newborn babies.

Researchers from the University of California San Francisco and University of California Berkeley compared the older method of using mass spectrometry testing of blood to the newer method of whole exome sequencing to diagnose these diseases in a group of over 1000 infants.

The team found that the traditional mass spectrometry screening was 99% accurate at diagnosing inherited metabolic diseases with only a 0.2% rate of false negatives, but exome sequencing was less accurate. It was only able to detect 88% of true cases accurately, although the rate of false negatives with exome sequencing was fairly low at only 1.6%

“There has been a lot of publicity about universal sequencing for newborns,” said Jennifer Puck, M.D., a professor of pediatrics at UC San Francisco and co-senior author of the study, published, in Nature Medicine. “But claims that sequencing is the key to health have been made without the support of rigorous studies.”

As the babies with these conditions often have no symptoms at first, it is important to have a very accurate test to make sure those that need it get the right treatment. Time can often be a factor with conditions like phenylketonuria that can cause cognitive damage if left untreated.

Blood samples are routinely taken from babies in California and Puck and colleagues used these archived samples to compare the accuracy of the two types of testing in over 1000 babies subsequently diagnosed with an inborn error of metabolism between 2005 and 2013. They also tested some samples from babies falsely diagnosed as having one of these diseases by mass spectrometry.

The sequencing tested for variants in 78 genes known to cause 48 different inborn errors of metabolism. All babies in California are normally screened for these diseases, which are rare and only affect around 150 out of 500,000 babies born in the state annually.

The team aren’t certain why the sequencing was less accurate, but say it may be because not enough is known about the genetics of the diseases as they are so rare.

“These are well-studied single-gene conditions, but that does not mean we have found all the genes associated with them,” said Aashish Adhikari, PhD, a researcher at UC San Francisco’s Institute for Human Genetics and UC Berkeley’s Department of Plant and Microbial Biology, and first author on the paper. “Additional genes could be involved, as well as additional biological and environmental factors that may limit our ability to predict disease from DNA sequences alone.”

The research findings suggest that hospitals should not switch to using exome sequencing as a first-line test for inborn errors of metabolism, as it can miss some cases. But it could be a useful tool to confirm a diagnosis in cases where a positive diagnosis is suspected. It could also be useful in the future for finding new genetic conditions that current screening methods do not pick up.

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