Prevalence of the most common pathogenic variants in three genes for inborn errors of metabolism associated with sudden unexpected death in infancy: a population-based study in south Brazil

Improving the second-tier classification of methylmalonic acidemia patients using a machine learning ensemble method

INTRODUCTION

Methylmalonic acidemia (MMA) is a disorder of autosomal recessive inheritance, with an estimated prevalence of 1:50,000. First-tier clinical diagnostic tests often return many false positives [five false positive (FP): one true positive (TP)]. In this work, our goal was to refine a classification model that can minimize the number of false positives, currently an unmet need in the upstream diagnostics of MMA.

METHODS

We developed machine learning multivariable screening models for MMA with utility as a secondary-tier tool for false positives reduction. We utilized mass spectrometry-based features consisting of 11 amino acids and 31 carnitines derived from dried blood samples of neonatal patients, followed by additional ratio feature construction. Feature selection strategies (selection by filter, recursive feature elimination, and learned vector quantization) were used to determine the input set for evaluating the performance of 14 classification models to identify a candidate model set for an ensemble model development.

RESULTS

Our work identified computational models that explore metabolic analytes to reduce the number of false positives without compromising sensitivity. The best results [area under the receiver operating characteristic curve (AUROC) of 97%, sensitivity of 92%, and specificity of 95%] were obtained utilizing an ensemble of the algorithms random forest, C5.0, sparse linear discriminant analysis, and autoencoder deep neural network stacked with the algorithm stochastic gradient boosting as the supervisor. The model achieved a good performance trade-off for a screening application with 6% false-positive rate (FPR) at 95% sensitivity, 35% FPR at 99% sensitivity, and 39% FPR at 100% sensitivity.

CONCLUSIONS

The classification results and approach of this research can be utilized by clinicians globally, to improve the overall discovery of MMA in pediatric patients. The improved method, when adjusted to 100% precision, can be used to further inform the diagnostic process journey of MMA and help reduce the burden for patients and their families.

Methylmalonic acidemia: Neurodevelopment and neuroimaging

Methylmalonic acidemia (MMA) is a genetic disease of abnormal organic acid metabolism, which is one of the important factors affecting the survival rate and quality of life of newborns or infants. Early detection and diagnosis are particularly important. The diagnosis of MMA mainly depends on clinical symptoms, newborn screening, biochemical detection, gene sequencing and neuroimaging diagnosis. The accumulation of methylmalonic acid and other metabolites in the body of patients causes brain tissue damage, which can manifest as various degrees of intellectual disability and severe neurological dysfunction. Neuroimaging examination has important clinical significance in the diagnosis and prognosis of MMA. This review mainly reviews the etiology, pathogenesis, and nervous system development, especially the neuroimaging features of MMA.

Prenatal diagnosis of citrullinemia type 1; seven families with c.1168G > A mutation of Argininosuccinate synthetase 1 gene in Southwest Iran: A case series

Background

Citrullinemia type 1 is an autosomal recessive disease resulting in ammonia accumulation in the blood, and if uncontrolled may progress to coma or death in the early months after birth.

Cases presentation

7 families from Southwest Iran having one or more children in their families or relatives, who died in the early months after birth due to citrullinemia type 1 visited for genetic counseling and prenatal diagnosis. Whole-exome sequencing was performed on peripheral blood specimens and chorionic villus samples. Sanger sequencing confirmed the genetic results. Both parents were identified as carriers for the exon 15 c.1168G > A mutation in each family. The fetus in 6 out of 7 families was homozygote for A substitution on the argininosuccinate synthetase 1 gene.

Conclusion

The presence of a common mutation in the argininosuccinate synthetase 1gene in all affected families of Southwest Iran shows a possible population cluster in this area.