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Untargeted metabolomic profiling enhances diagnosis for newborn metabolic errors

Jason Martinez

Newborn childManuel Schinner/Unsplash

HOUSTON, TX – A screening method that can enhance the diagnostic rate for inborn errors of metabolism, a group of rare genetic conditions, by about seven times when compared to the traditional metabolic screening approach, has been discovered.

Known as untargeted metabolomic profiling, this method was developed by the research team at Baylor College of Medicine. The researchers hope that the adoption of metabolomics to screen for inborn errors of metabolism will result in a more efficient, faster, and less expensive diagnostic journey for individuals and families with rare metabolic disorders.

Corresponding author and professor of molecular and human genetics at Baylor and senior director of biochemical genetics at Baylor Genetics, Dr. Sarah Elsea, said, “Currently, newborn screening is conducted in every infant born in the U.S. to check for serious but rare health conditions at birth. Screening includes blood, hearing and heart tests.”

“While newborn screening in general has improved in the last 10 years, clinically screening for inborn errors of metabolism has not changed substantially in the last 40 to 50 years,” she added.

Compared to traditional methods, untargeted metabolomics identifies more disorders with a greater variety including disorders for which no biochemical tests were clinically available according to the study published in JAMA Network Open.

Besides useful in confirming a diagnosis with a high degree of confidence, the use of untargeted metabolomics in combination with genetic screening also helps researchers and clinicians to rule out potential conditions.

This new, broader screening approach identifies severe forms of diseases as well as mild forms that may not quite match the characteristics observed in more severe cases.

Also a member of Baylor’s Dan L Duncan Comprehensive Cancer Center and Center for Drug Discovery, Dr. Elsea, explained, “We are finding individuals with milder forms of a disease are more common in our populations than those with severe forms.”

“Our approach has been quite successful identifying seizure disorders, movement disorders and autism spectrum disorders. Our analyses have taught us to open our minds to a much greater spectrum of disease, allowing us to improve early diagnosis,” she added.

Meanwhile, co-author and professor of molecular and human genetics at Baylor, Dr. V. Reid Sutton, explained, “In addition, our analysis of many metabolic compounds in a single blood sample reduces the need of having to take more samples to do further testing looking for specific conditions. This includes taking samples of cerebrospinal fluid, which involves a more invasive procedure than drawing a blood sample.”

Colleagues from Baylor College of Medicine, Baylor Genetics, and Metabolon, Inc. such as Ning Liu, Jing Xiao, Charul Gijavanekar, Kirk Pappan, Kevin Glinton, Brian Shayota, Adam Kennedy, and Qin Sun have also contributed to this research work as co-authors.

In addition, the National Institutes of Health grant T32 GM007526, the Takeda American College of Medical Genetics and Genomics Foundation Next Generation Medical Biochemical Subspecialty Fellowship, and the Urea Cycle Disorders Consortium also supported this work.

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