Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

ABSTRACT:

Background

Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of this study was to evaluate epigenetic profiles as biomarkers for spastic CP. A novel analysis pipeline was employed to assess DNA methylation patterns between peripheral blood cells of adolescent subjects (14.9 ± 0.3 years old) with spastic CP and controls at single CpG site resolution.

Results

Significantly hypo- and hyper-methylated CpG sites associated with spastic CP were identified. Nonmetric multidimensional scaling fully discriminated the CP group from the controls. Machine learning based classification modeling indicated

SUBMITTER: Crowgey EL 

PROVIDER: S-EPMC6011336 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature