Age-Dependent Structural Connectivity Effects in Fragile X Premutation

Wang, Jun Yi; Hessl, David H; Hagerman, Randi J.; Tassone, Flora; Rivera, Susan M.

doi:10.1001/archneurol.2011.2023

Cited by 51 publications

(62 citation statements)

References 35 publications

(48 reference statements)

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“…In older fXPCs (> 40 years old), diffusion tensor imaging (DTI) was used to show that mean diffusivity was elevated in the MCP and left cerebral peduncle (Hashimoto, Srivastava, Tassone, Hagerman, & Rivera, 2011b). DTI tractography and tract-based spatial statistics (TBSS) were used to show that fXPCs with FXTAS, relative to controls, exhibited lower structural connectivity and white matter integrity, and greater age-related decline in these measures (Wang, Hessl, Hagerman, Tassone, & Rivera, 2012). These differences were observed in several white matter tracts, including the motor fiber tract through the cerebellar peduncle.…”

Section: Discussionmentioning

confidence: 99%

Eye movements reveal impaired inhibitory control in adult male fragile X premutation carriers asymptomatic for FXTAS.

Wong¹,

Goodrich-Hunsaker²,

McLennan³

et al. 2014

Neuropsychology

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Objective: Fragile X premutation carriers (fXPCs) have an expansion of 55 —200 CGG repeats in the FMR1 gene. Male fXPCs are at risk for developing a neurodegenerative motor disorder (FXTAS) often accompanied by inhibitory control impairments, even in fXPCs without motor symptoms. Inhibitory control impairments might precede, and thus indicate elevated risk for motor impairment associated with FXTAS. We tested whether inhibitory impairments are observable in fXPCs by assessing oculomotor performance. Method: Participants were males aged 18–48 years asymptomatic for FXTAS. FXPCs (n = 21) and healthy age-matched controls (n = 22) performed four oculomotor tasks. In a Fixation task, participants fixated on a central cross and maintained gaze position when a peripheral stimulus appeared. In a Pursuit task, participants maintained gaze on a square moving at constant velocity. In a Prosaccade task, participants fixated on a central cross, then looked at a peripheral stimulus. An Antisaccade task was identical to the Prosaccade task, except participants looked in the direction opposite the stimulus. Inhibitory cost was the difference in saccade latency between the Antisaccade and Prosaccade tasks. Results: Relative to controls, fXPCs had longer saccade latency in the Antisaccade task. In fXPCs, inhibitory cost was positively associated with vermis area in lobules VI-VII. Conclusion: Antisaccades require inhibitory control to inhibit reflexive eye movements. We found that eye movements are sensitive to impaired inhibitory control in fXPCs asymptomatic for FXTAS. Thus, eye movements may be useful in assessing FXTAS risk or disease progression.

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Section: Discussionmentioning

confidence: 99%

Eye movements reveal impaired inhibitory control in adult male fragile X premutation carriers asymptomatic for FXTAS.

Wong¹,

Goodrich-Hunsaker²,

McLennan³

et al. 2014

Neuropsychology

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“…Reduced levels (or percentage) of FMRP has been associated with intellectual disability (Reiss and Dant, 2003), cognitive and behavioral impairments (Van der Molen et al, 2012), and high prevalence of autism symptomatology (Gabis et al, 2011). Further, FXS is linked with altered structural and functional brain connectivity (Haas et al, 2009; Hall et al, 2013; Wang et al, 2012). …”

Section: Introductionmentioning

confidence: 99%

Estimating individual contribution from group-based structural correlation networks

et al. 2015

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Coordinated variations in brain morphology (e.g., cortical thickness) across individuals have been widely used to infer large-scale population brain networks. These structural correlation networks (SCNs) have been shown to reflect synchronized maturational changes in connected brain regions. Further, evidence suggests that SCNs, to some extent, reflect both anatomical and functional connectivity and hence provide a complementary measure of brain connectivity in addition to diffusion weighted networks and resting-state functional networks. Although widely used to study between-group differences in network properties, SCNs are inferred only at the group-level using brain morphology data from a set of participants, thereby not providing any knowledge regarding how the observed differences in SCNs are associated with individual behavioral, cognitive and disorder states. In the present study, we introduce two novel distance-based approaches to extract information regarding individual differences from the group-level SCNs. We applied the proposed approaches to a moderately large dataset (n=100) consisting of individuals with fragile X syndrome (FXS; n=50) and age-matched typically developing individuals (TD; n=50). Additionally, we tested the stability of proposed approaches using permutation analysis. Lastly, to test the efficacy of our method, individual contributions extracted from the group-level SCNs were examined for associations with intelligence scores and genetic data. The extracted individual contributions were stable and were significantly related to both genetic and intelligence estimates, in both typically developing individuals and participants with FXS. We anticipate that the approaches developed in this work could be used as a putative biomarker for altered connectivity in individuals with neurodevelopmental disorders.

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“…These controls and 26 of the premutation carriers were the same participants in a recent investigation of age-related changes in fragile X premutation. 13 We identified premutation alleles using FMR1 DNA testing 17 and measured FMR1 mRNA using a quantitative-fluorescence reverse transcription–polymerase chain reaction method. 4 In addition, we assessed FXTAS stage with tremor or ataxia intensity, 8,18 behavioral self-regulation using the Behavioral Dyscontrol Scale 2, 19 and dexterity using the Purdue Pegboard Dexterity Test.…”

Section: Methodsmentioning

confidence: 99%

“…13 To summarize, we used the FSL software package (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/; University of Oxford) for performing eddy current and motion correction and skull stripping. 21 We conducted DTI tractography in DTI Studio (http://www.mristudio.org; The Johns Hopkins Medical Institute) by applying a multiple regions-of-interest approach.…”

Section: Methodsmentioning

confidence: 99%