Combining newborn metabolic and DNA analysis for second-tier testing of methylmalonic acidemia.
Genet Med
; 21(4): 896-903, 2019 04.
Article
em En
| MEDLINE
| ID: mdl-30209273
ABSTRACT
PURPOSE:
Improved second-tier tools are needed to reduce false-positive outcomes in newborn screening (NBS) for inborn metabolic disorders on the Recommended Universal Screening Panel (RUSP).METHODS:
We designed an assay for multiplex sequencing of 72 metabolic genes (RUSPseq) from newborn dried blood spots. Analytical and clinical performance was evaluated in 60 screen-positive newborns for methylmalonic acidemia (MMA) reported by the California Department of Public Health NBS program. Additionally, we trained a Random Forest machine learning classifier on NBS data to improve prediction of true and false-positive MMA cases.RESULTS:
Of 28 MMA patients sequenced, we found two pathogenic or likely pathogenic (P/LP) variants in a MMA-related gene in 24 patients, and one pathogenic variant and a variant of unknown significance (VUS) in 1 patient. No such variant combinations were detected in MMA false positives and healthy controls. Random Forest-based analysis of the entire NBS metabolic profile correctly identified the MMA patients and reduced MMA false-positive cases by 51%. MMA screen-positive newborns were more likely of Hispanic ethnicity.CONCLUSION:
Our two-pronged approach reduced false positives by half and provided a reportable molecular finding for 89% of MMA patients. Challenges remain in newborn metabolic screening and DNA variant interpretation in diverse multiethnic populations.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Variação Genética
/
Triagem Neonatal
/
Erros Inatos do Metabolismo dos Aminoácidos
/
Erros Inatos do Metabolismo
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos