Evolution of aberrant brain-wide spatiotemporal dynamics of resting-state networks in a Huntington’s disease mouse model
Authors: Vasilkovska Tamara , Verschuuren Marlies , Pustina Dorian , van den Berg Monica , van Audekerke Johan , Pintelon Isabel , Cachope Roger , De Vos Winnok H. , Van der Linden Annemie , Adhikari Mohit H. , Verhoye Marleen 
Published: November 2023

Distinct resting-state networks (RSNs) are differentially altered in the course of Huntington’s disease (HD). However, these RSN changes are depicted using traditional functional connectivity analyses which ignore the dynamic brain states that constitute these RSNs and their time-dependent relationship. Dynamic states are represented by recurring spatiotemporal patterns of propagating cortical and subcortical brain activity observed in low-frequency BOLD fluctuations, called quasi-periodic patterns (QPPs). In this study, we used resting-state fMRI to investigate QPPs in the zQ175DN mouse model of HD at 3, 6 and 10 months of age. We identified age- and genotype-specific short (3s) QPPs, representative of the lateral cortical network (LCN) and the default mode-like network (DMLN), and a long (10s) QPP, the homolog of the human primary QPP, exhibiting the propagation of activity between the LCN and the DMLN. Hyperactivity was present in the caudate putamen and the somatosensory cortex in zQ175DN mice at 3 and 6 months of age. Moreover, DMLN-wide reduction in activation was observed at all ages, where at 6 and 10 months of age the reduced activity gradually advanced into a breakdown of the LCN-to-DMLN propagation. We then investigated the relationship in the timing of peak activity of six brain regions involved in the long QPPs and found that the retrosplenial cortex, a transmodal region which orchestrates multisensory integration, has a premature peak of BOLD activation in zQ175DN mice at 6 months of age, as compared to age-matched controls. Irrespective of either LCN or DMLN activation, this resulted in an asynchrony of the retrosplenial cortex in the peak timing relationships relative to other regions during the long (10s) QPPs. Finally, the normative, age-dependent, wild-type QPPs were significantly decreased in occurrence in the zQ175DN group at each age, indicating the presence of phenotypically-driven LCN and DMLN states as captured with QPPs. As BOLD-dependent variations result from neurovascular coupling, we assessed mutant huntingtin (mHTT) deposition in astrocytes and pericytes, known components of the neurogliovascular unit. These analyses showed increased cell-type dependent deposition starting at 6 months in the caudate putamen, somatosensory and motor cortex, regions that are prominently involved in HD pathology as seen in humans. Our findings provide meaningful insights into the development and progression of altered functional brain dynamics in this HD model, opening potential new avenues for its application in clinical HD research.

Huntington’s disease (HD) is marked by irreversible loss of neuronal function for which currently no availability for disease-modifying treatment exists. Advances in the understanding of disease progression can aid biomarker development, which in turn can accelerate therapeutic discovery. We characterized the progression of altered dynamics of whole-brain network states in the zQ175DN mouse model of HD using a dynamic functional connectivity (FC) approach to resting-state fMRI and identified quasi-periodic patterns (QPPs) of brain activity constituting the most prominent resting-state networks. The occurrence of the normative QPPs, as observed in healthy controls, was reduced in the HD model as the phenotype progressed. This uncovered progressive cessation of synchronous brain activity with phenotypic progression, which is not observed with the conventional static FC approaches. This work opens new avenues in assessing the dynamics of whole brain states, through QPPs, in clinical HD research.