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

Journal: BMC bioinformatics
Published Date:

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.

Authors

  • Erin L Crowgey
    Nemours Biomedical Research, Nemours - Alfred I. duPont Hospital for Children, 1600 Rockland Rd, Wilmington, DE, 19803, USA.
  • Adam G Marsh
    Genome Profiling LLC, 4701 Ogletown Stanton Rd #4300, Newark, DE, 19713, USA.
  • Karyn G Robinson
    Nemours Biomedical Research, Nemours - Alfred I. duPont Hospital for Children, 1600 Rockland Rd, Wilmington, DE, 19803, USA.
  • Stephanie K Yeager
    Nemours Biomedical Research, Nemours - Alfred I. duPont Hospital for Children, 1600 Rockland Rd, Wilmington, DE, 19803, USA.
  • Robert E Akins
    Nemours Biomedical Research, Nemours - Alfred I. duPont Hospital for Children, 1600 Rockland Rd, Wilmington, DE, 19803, USA. robert.akins@nemours.org.