Longitudinal identification of clinically distinct neurophenotypes in young children with fragile X syndrome

Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):10767-10772. doi: 10.1073/pnas.1620994114. Epub 2017 Sep 18.

Abstract

Fragile X syndrome (FXS), due to mutations of the FMR1 gene, is the most common known inherited cause of developmental disability. The cognitive, behavioral, and neurological phenotypes observed in affected individuals can vary considerably, making it difficult to predict outcomes and determine the need for interventions. We sought to examine early structural brain growth as a potential marker for identification of clinically meaningful subgroups. Participants included 42 very young boys with FXS who completed a T1-weighted anatomical MRI and cognitive/behavioral assessment at two longitudinal time points, with mean ages of 2.89 y and 4.91 y. Topological data analysis (TDA), an unsupervised approach to multivariate pattern analysis, was applied to the longitudinal anatomical data to identify coherent but heretofore unknown subgroups. TDA revealed two large subgroups within the study population based solely on longitudinal MRI data. Post hoc comparisons of cognition, adaptive functioning, and autism severity scores between these groups demonstrated that one group was consistently higher functioning on all measures at both time points, with pronounced and significant unidirectional differences (P < 0.05 for time point 1 and/or time point 2 for each measure). These results support the existence of two longitudinally defined, neuroanatomically distinct, and clinically relevant phenotypes among boys with FXS. If confirmed by additional analyses, such information may be used to predict outcomes and guide design of targeted therapies. Furthermore, TDA of longitudinal anatomical MRI data may represent a useful method for reliably and objectively defining subtypes within other neuropsychiatric disorders.

Keywords: MRI; autism spectrum behavior; fragile X syndrome; longitudinal development; multivariate pattern classification.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Brain / pathology*
  • Child Development*
  • Child, Preschool
  • Cognition*
  • Female
  • Fragile X Syndrome / pathology*
  • Humans
  • Image Processing, Computer-Assisted
  • Longitudinal Studies
  • Magnetic Resonance Imaging / methods*
  • Male
  • Neuropsychological Tests
  • Phenotype