Portuguese Neonatal Screening Programme: A Retrospective Cohort Study of 18 Years of MS/MS

Maria Miguel Gonçalves1, Ana Marcão2, Carmen Sousa2

  • 1Animal Biology, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal.

Insights

The Portuguese Neonatal Screening Programme identified 681 newborns with Inborn Errors of Metabolism (IEM) using tandem mass spectrometry. This study details the molecular epidemiology of these IEM cases, aiding future diagnostic and treatment strategies.

Area of Science:

  • Biochemistry
  • Genetics
  • Pediatrics

Background:

  • The Portuguese Neonatal Screening Programme (PNSP) screens for rare diseases, including 24 Inborn Errors of Metabolism (IEM).
  • Tandem mass spectrometry (MS/MS) implementation in 2004 enhanced IEM detection, improving treatment and outcomes.
  • The PNSP covers nearly all neonates, providing a robust dataset for epidemiological studies.

Purpose of the Study:

  • To establish the molecular epidemiology of IEM diagnosed through the Portuguese Neonatal Screening Programme.
  • To analyze genetic profiles and mutation patterns of IEM identified via MS/MS screening.
  • To provide insights into the management of rare metabolic diseases based on screening data.

Main Methods:

  • Screening of 1,764,830 neonates using MS/MS technology from 2004 to 2022.
  • Molecular characterization of IEM cases through DNA extraction, PCR, and Sanger sequencing.
  • Retrospective analysis of biochemical and genetic data for diagnosed IEM.

Main Results:

  • A total of 681 newborns were diagnosed with an IEM.
  • MCAD deficiency was the most frequent IEM, with 233 cases, often showing the c.985A>G mutation.
  • Specific homozygous mutations were identified in Glutaric Aciduria type I (GCDH) and MAT II/III deficiency (MAT1A).

Conclusions:

  • The study presents the molecular epidemiology of IEM detected by neonatal screening in Portugal.
  • MS/MS implementation has significantly advanced IEM screening and diagnosis over 18 years.
  • Understanding mutation patterns, including de novo mutations, can guide the approach to diverse IEM phenotypes.
Abstract

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