Newborn screening algorithm distinguishing potential symptomatic isovaleric acidemia from asymptomatic newborns

Area of Science:

• Biochemistry
• Genetics
• Neonatal Medicine

Background:

• Newborn screening (NBS) for isovaleric acidemia (IVA) aims to reduce mortality and morbidity.
• However, NBS also detects asymptomatic or mild IVA cases where early detection's neurological impact is unproven.

Purpose of the Study:

• To develop an improved NBS algorithm for IVA.
• The goal is to exclude newborns with asymptomatic or mild presentations from positive screening.

Main Methods:

• Re-evaluated biochemical and molecular data from newborns screened for IVA.
• Analyzed data from 2,794,365 newborns, identifying 412 positive for IVA, with 38 confirmed cases.
• Classified confirmed IVA cases into symptomatic (32%) and asymptomatic (68%) groups.

Main Results:

• Identified a common variant (c.932C>T; p. Ala311Val) in 69% of asymptomatic patients.
• Detected two novel variants (c.487G>A; p. Ala163Thr and c.985A>G; p. Met329Val) in the IVD gene.
• Recalculated biochemical cut-offs (C5 > 5 μM, C5/C2 > 0.2, C5/C3 > 4) to specifically flag symptomatic IVA.

Conclusions:

• The revised NBS algorithm effectively distinguishes symptomatic from asymptomatic IVA cases.
• This improved screening strategy can reduce false positives and optimize resource allocation for IVA management.