CHICAGO – A first-of-its-kind test could make it easier for newborns to get care for spinal muscular atrophy, a common genetic disease that is life-threatening but treatable if caught in time. Findings on this method and a second innovative test that could improve diagnosis of pediatric urinary tract infections (UTIs) will be discussed today at the 2022 AACC Annual Scientific Meeting & Clinical Lab Expo.

Increasing Access to Spinal Muscular Atrophy Testing

Spinal muscular atrophy is the leading inherited cause of infant death after cystic fibrosis, and early diagnosis and treatment are crucial to giving affected newborns the best chances at healthy lives. However, most newborn screening panels that use next-generation sequencing (NGS) do not detect this condition. The most common form of spinal muscular atrophy is caused by an abnormal version of the gene SMN1, which produces a protein essential to nerve cells involved in muscle movement. NGS panels—which analyze hundreds of genes for disease-causing changes—typically exclude SMN1 because of difficulty distinguishing it from another gene known as SMN2. The two differ only in a small spot.

Gustavo Barcelos Barra, PhD, and colleagues at Sabin Medicina Diagnostica in Brasilia, Brazil, developed a NGS panel that detects a mutation in that small spot on the SMN1 gene that causes spinal muscular atrophy. Using this NGS panel, they tested 52 DNA samples from spinal muscular atrophy patients, then compared the results to those from a single-gene PCR test (a widely used method for diagnosing this condition). After eliminating four samples for technical reasons, the researchers found that panel results for SMN1 and the single-gene test agreed in all cases.

Including spinal muscular atrophy on NGS panels means that “parents do not have to look for an additional test for [this condition],” said Barra. He added that his innovation would save laboratories from performing an extra test for spinal muscular atrophy along with NGS newborn screening.

Identifying Children’s UTIs Quickly

UTIs are common in children and when left untreated, they can cause acute distress, septic shock, and even kidney damage. The gold standard for diagnosing UTIs, though—urine culture—is slow and labor-intensive for laboratory staff, leading doctors to sometimes inappropriately prescribe antibiotics before getting results. This is a serious issue that is contributing to the rise of antibiotic resistance.

A team led by Jingcai Wang, MD, PhD, of Nationwide Children’s Hospital in Columbus, Ohio, is the first group of researchers to show that a faster method for diagnosing UTIs in adults could also work in children. Known as UTOPIA, this method uses urinalysis results and other variables to predict UTIs, and delivers answers well before the 2-3 days needed for culture results.

In order to evaluate this method’s performance in children, the researchers used it to analyze data from the medical records of 5,353 children who previously underwent both urinalysis and urine culture for UTI. For each of these patients, the researchers entered their age, sex, risk for UTI, and urinalysis results into UTOPIA’s algorithm to see how accurately it predicted their urine culture results.

Based on receiver operating curve (ROC) value, UTOPIA predicted positive urine culture results more accurately than any individual variable did on its own. The algorithm’s ROC value was 0.825, versus values for individual variables, which ranged from 0.546 to 0.776. The closer the ROC value is to 1, the more accurate the testing strategy, Wang explained.

“UTOPIA is a simple way to predict urine culture results. You get quicker diagnosis of UTI and prevent potential kidney damage,” Wang said. “It can potentially reduce unnecessary urine cultures, save money, and reduce use of unnecessary antibiotics in children.”


Abstract Information

AACC Annual Scientific Meeting registration is free for members of the media. Reporters can register online here: https://www.xpressreg.net/register/aacc0722/media/landing.asp

Abstract A-155: Incorporating spinal muscular atrophy screening by next-generation sequencing into a comprehensive multigene panel for newborn sequencing: a pilot evaluation will be presented during:

Scientific Poster Session

Tuesday, July 26

9:30 a.m. – 5 p.m. (presenting author in attendance from 1:30 – 2:30 p.m.)

Abstract B-243: Evaluation of a prediction algorithm value in predicting positive urine culture in pediatrics: a retrospective cohort study at Nationwide Children’s Hospital will be presented during:

Scientific Poster Session

Wednesday, July 27

9:30 a.m. – 5 p.m. (presenting author in attendance from 1:30 – 2:30 p.m.)

Both sessions will take place in the Poster Hall of the Clinical Lab Expo show floor at the McCormick Place Convention Center in Chicago.

About the 2022 AACC Annual Scientific Meeting & Clinical Lab Expo

The AACC Annual Scientific Meeting offers 5 days packed with opportunities to learn about exciting science from July 24-28. Plenary sessions will explore artificial intelligence-based clinical prediction models, advances in multiplex technologies, human brain organogenesis, building trust between the public and healthcare experts, and direct mass spectrometry techniques.

At the AACC Clinical Lab Expo, more than 750 exhibitors will fill the show floor of the McCormick Place Convention Center in Chicago with displays of the latest diagnostic technology, including but not limited to COVID-19 testing, artificial intelligence, mobile health, molecular diagnostics, mass spectrometry, point-of-care, and automation.

About AACC

Dedicated to achieving better health through laboratory medicine, AACC brings together more than 70,000 clinical laboratory professionals, physicians, research scientists, and business leaders from around the world focused on clinical chemistry, molecular diagnostics, mass spectrometry, translational medicine, lab management, and other areas of progressing laboratory science. Since 1948, AACC has worked to advance the common interests of the field, providing programs that advance scientific collaboration, knowledge, expertise, and innovation. For more information, visit www.myadlm.org.