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

Area of Science:

• Neuroscience
• Genetics
• Developmental Biology

Background:

• Fragile X syndrome (FXS), caused by FMR1 gene mutations, is a leading inherited cause of developmental disability.
• Varied cognitive, behavioral, and neurological phenotypes in FXS complicate outcome prediction and intervention planning.
• Identifying early biological markers is crucial for understanding FXS heterogeneity.

Purpose of the Study:

• To investigate early structural brain growth patterns in young boys with FXS.
• To identify distinct neuroanatomical subgroups within the FXS population using longitudinal MRI data.
• To explore the potential of topological data analysis (TDA) for defining clinically relevant subtypes.

Main Methods:

• Longitudinal T1-weighted anatomical MRI scans were acquired from 42 young boys with FXS at two time points (mean ages 2.89 and 4.91 years).
• Topological data analysis (TDA), an unsupervised machine learning technique, was applied to the MRI data to identify subgroups.
• Cognitive, adaptive functioning, and autism severity scores were compared between identified subgroups post hoc.

Main Results:

• TDA successfully identified two distinct subgroups based solely on longitudinal brain MRI data.
• One subgroup consistently demonstrated higher functioning across cognitive, adaptive, and autism severity measures at both time points.
• Significant differences (P < 0.05) were observed between the subgroups, indicating neuroanatomically distinct and clinically relevant phenotypes.

Conclusions:

• The study supports the existence of two longitudinally defined, neuroanatomically distinct phenotypes in boys with FXS.
• Early structural brain growth, analyzed by TDA, can serve as a marker for identifying clinically meaningful subgroups.
• This approach may enhance outcome prediction, guide targeted therapies for FXS, and potentially define subtypes in other neuropsychiatric disorders.