ArticleScientific reports2017
Automated screening for Fragile X premutation carriers based on linguistic and cognitive computational phenotypes.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 15 citations in OpenAlex.
- Discourse Marker Use in Mothers of Autistic Individuals and FMR1 Premutation Carriers.Journal of autism and developmental disorders · 2026Article
- Semantic and Syntactic Language Differences Associated with theJournal of neurolinguistics · 2026Article
- The use of artificial intelligence in sexual and reproductive health: a comprehensive scoping review.npj women's health · 2025Article
- Brief Report: Linguistic Mazes and Perseverations in School-Age Boys with Fragile X Syndrome and Autism Spectrum Disorder and Relationships with Maternal Maze Use.Journal of autism and developmental disorders · 2022Article
- Family history of FXTAS is associated with age-related cognitive-linguistic decline among mothers with the FMR1 premutation.Journal of neurodevelopmental disorders · 2022Article
- The Phenotypic Profile Associated With theFrontiers in psychiatry · 2021Article
- Fragile X-Associated Tremor/Ataxia Syndrome (FXTAS): Pathophysiology and Clinical Implications.International journal of molecular sciences · 2020Review
- Data-driven phenotype discovery ofScience advances · 2019Article
- Article
- Health Profiles of Mosaic Versus Non-mosaicFrontiers in genetics · 2018Article
- Curvilinear Association Between Language Disfluency andFrontiers in genetics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
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 children with autism spectrum disorders, the comparison group. By using a random forest classifier, FX premutation carriers could be identified in an automated fashion with high precision and recall (0.81 F1 score). Linguistic and cognitive phenotypes that were highly associated with FX premutation carriers were high language dysfluency, poor ability to organize material, and low self-monitoring. Our framework sets the foundation for computational phenotyping strategies to pre-screen large populations for this genetic variant with nominal costs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.