Objective: This study aimed to investigate changes in large-scale network effective connectivity of the default mode network (DMN) and striatum in the expression of depression in premanifest Huntington’s disease (pre-HD).

Background: HD is increasingly being conceptualised as a circuitopathy [1] and two large-scale brain networks surmised to contribute to the expression of depressive symptoms in pre-HD include striatal circuitry and the DMN. The effective connectivity of these networks in pre-HD in association with depression was investigated using Dynamic Causal Modelling (DCM).

Method: We analysed 3T resting state fMRI data from 93 pre-HD participants (51.6% females; mean age = 42.7). Assessment included depression history, the Beck Depression Inventory, 2nd Edition (BDI-II) and the Hospital Anxiety and Depression Scale, depression subscale (HADS-D). We categorised clinically significant depressive symptoms using optimal cut-offs recommended for HD [2]. Brain regions of interest were the medial prefrontal cortex, posterior cingulate cortex, and bilateral hippocampi, caudate, and putamen. We used Spectral DCM [3], [4] to estimate subject level connectivity and Parametric Empirical Bayes [5] to estimate group level effective connectivity changes between participants with and without a history of depression.

Results: DCM revealed significant changes in effective connectivity between pre-HD participants with and without history of depression, shown in Figure 1. [figure1] Various pathways that differed between participants, with and without history of depression, showed associations with both measures, shown in Figure 2. [figure2] Associations included: a negative relationship between left caudate self-connectivity and clinical cut-offs for both measures for those with history of depression and a negative relationship between posterior cingulate self-connectivity and both measures for all participants.

Conclusion: Patterns in effectivity connectivity changes in association with state measures of depressive symptoms differed between pre-HD people with or without a previous history of depression. This is the first study, to our knowledge, to demonstrate a relationship between depression and the effective connectivity of the striatum and DMN in premanifest HD. These findings suggest large-scale network dysfunction contributes to the expression of depression in Huntington’s disease.

References: [1] A. J. Hannan, ‘Synaptopathy, circuitopathy and the computational biology of Huntington’s disease’, BMC Biology, vol. 16, no. 1, p. 71, Jun. 2018, doi: 10.1186/s12915-018-0539-y.
[2] J. De Souza, L. A. Jones, and H. Rickards, ‘Validation of self-report depression rating scales in Huntington’s disease’, Mov Disord, vol. 25, no. 1, pp. 91–96, Jan. 2010, doi: 10.1002/mds.22837.
[3] K. J. Friston, J. Kahan, B. Biswal, and A. Razi, ‘A DCM for resting state fMRI’, NeuroImage, vol. 94, pp. 396–407, Jul. 2014, doi: 10.1016/j.neuroimage.2013.12.009.
[4] A. Razi, J. Kahan, G. Rees, and K. J. Friston, ‘Construct validation of a DCM for resting state fMRI’, NeuroImage, vol. 106, pp. 1–14, Feb. 2015, doi: 10.1016/j.neuroimage.2014.11.027.
[5] K. J. Friston et al., ‘Bayesian model reduction and empirical Bayes for group (DCM) studies’, NeuroImage, vol. 128, pp. 413–431, Mar. 2016, doi: 10.1016/j.neuroimage.2015.11.015.
[6] E. R. Orchard, P. G. D. Ward, S. Chopra, E. Storey, G. F. Egan, and S. D. Jamadar, ‘Neuroprotective Effects of Motherhood on Brain Function in Late Life: A Resting-State fMRI Study’, Cereb Cortex, vol. 31, no. 2, pp. 1270–1283, Jan. 2021, doi: 10.1093/cercor/bhaa293.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/the-role-of-the-default-mode-network-and-striatal-circuits-in-the-expression-of-depressive-symptoms-in-premanifest-huntingtons-disease/