Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations.

ABSTRACT:

Background

Methylmalonic acidemia (MMA) is one of the most common hereditary organic acid metabolism disorders that endangers the lives and health of infants and children. Early detection and intervention before the appearance of a newborn's clinical symptoms can control disease progression and prevent or mitigate its serious consequences.

Methods

42,004 newborns from two Chinese populations were included in the study. The small molecular metabolite analytes were detected from the dried blood spot (DBS) samples by MS/MS. Genetic analysis of 68 Chinese MMA cases were performed by whole-exome sequencing and Sanger sequencing. Random forest classifiers (RFC) were constructed to improve the MMA screening performance and genotype prediction in two Chinese populations. Meanwhile,

SUBMITTER: Yin Z 

PROVIDER: S-EPMC11552112 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature