Automated screening for Fragile X premutation carriers based on linguistic and cognitive computational phenotypes.

ABSTRACT: Millions of people globally are at high risk for neurodegenerative disorders, infertility or having children with a disability as a result of the Fragile X (FX) premutation, a genetic abnormality in FMR1 that is underdiagnosed. Despite the high prevalence of the FX premutation and its effect on public health and family planning, most FX premutation carriers are unaware of their condition. Since genetic testing for the premutation is resource intensive, it is not practical to screen individuals for FX premutation status using genetic testing. In a novel approach to phenotyping, we have utilized audio recordings and cognitive profiling assessed via self-administered questionnaires on 200 females. Machine-learning methods were developed to discriminate FX premutation carriers from mothers of

SUBMITTER: Movaghar A 

PROVIDER: S-EPMC5454004 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature