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Evidence for Three Subgroups of Female FMR1 Premutation Carriers Defined by Distinct Neuropsychiatric Features: A Pilot Study.
Schmitt, Lauren M; Dominick, Kelli C; Liu, Rui; Pedapati, Ernest V; Ethridge, Lauren E; Smith, Elizabeth; Sweeney, John A; Erickson, Craig A.
Afiliación
  • Schmitt LM; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
  • Dominick KC; College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
  • Liu R; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
  • Pedapati EV; College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
  • Ethridge LE; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
  • Smith E; Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
  • Sweeney JA; College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
  • Erickson CA; Department of Psychology, University of Oklahoma, Norman, OK, United States.
Front Integr Neurosci ; 15: 797546, 2021.
Article en En | MEDLINE | ID: mdl-35046780
Over 200 Cytosine-guanine-guanine (CGG) trinucleotide repeats in the 5' untranslated region of the Fragile X mental retardation 1 (FMR1) gene results in a "full mutation," clinically Fragile X Syndrome (FXS), whereas 55 - 200 repeats result in a "premutation." FMR1 premutation carriers (PMC) are at an increased risk for a range of psychiatric, neurocognitive, and physical conditions. Few studies have examined the variable expression of neuropsychiatric features in female PMCs, and whether heterogeneous presentation among female PMCs may reflect differential presentation of features in unique subgroups. In the current pilot study, we examined 41 female PMCs (ages 17-78 years) and 15 age-, sex-, and IQ-matched typically developing controls (TDC) across a battery of self-report, eye tracking, expressive language, neurocognitive, and resting state EEG measures to determine the feasibility of identifying discrete clusters. Secondly, we sought to identify the key features that distinguished these clusters of female PMCs. We found a three cluster solution using k-means clustering. Cluster 1 represented a psychiatric feature group (27% of our sample); cluster 2 represented a group with executive dysfunction and elevated high frequency neural oscillatory activity (32%); and cluster 3 represented a relatively unaffected group (41%). Our findings indicate the feasibility of using a data-driven approach to identify naturally occurring clusters in female PMCs using a multi-method assessment battery. CGG repeat count and its association with neuropsychiatric features differ across clusters. Together, our findings provide important insight into potential diverging pathophysiological mechanisms and risk factors for each female PMC cluster, which may ultimately help provide novel and individualized targets for treatment options.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Integr Neurosci Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Integr Neurosci Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza