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Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease. | LitMetric

AI Article Synopsis

  • Huntington's disease (HD) is a neurodegenerative disorder caused by genetic mutations that lead to neuron dysfunction and death, particularly affecting the striatum and cortex.
  • This study focused on the zQ175 delta-neo mouse model to examine early functional brain changes using resting-state fMRI, observing these changes at 3, 6, and 10 months of age.
  • Results showed significant alterations in brain activity patterns, with distinct co-activation behaviors emerging as the mice aged; predictive metrics for these patterns achieved high classification accuracy, helping to differentiate affected mice from healthy ones.

Article Abstract

Huntington's disease (HD) is a neurodegenerative disorder caused by expanded (≥ 40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and clinical signs and symptoms of the disease are better known, changes in the functional architecture of the brain, especially before the clinical expression becomes apparent, are not fully and consistently characterized. In this study, we sought to uncover functional changes in the brain in the heterozygous (HET) zQ175 delta-neo (DN) mouse model at 3, 6, and 10 months of age, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that worsen through age. Motor function disturbances are manifested in this model at 6 and 10 months of age. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the 10-months time point; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three ages and became progressively more pronounced at 6-, and 10 months of age. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three ages with 80% classification accuracy at 6 and 10 months of age.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10290061PMC
http://dx.doi.org/10.1038/s41598-023-36812-yDOI Listing

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