For the first time, we investigated the relationship between white matter integrity and changes in cortical morphometry in pre- and symp-HD individuals. We found that baseline tractography measures (FA, RD, AD) did not significantly predict change in cortical morphometry (LGI and cortical thickness) in any of the chosen regions of interest. This finding was somewhat surprising given previous theories posit that reduced gyrification of the cortical surface could be the result of reduced white matter tension (Ronan & Fletcher, 2015; Van Essen, 1997) or that disease agents travel along white matter tracts from the striatum to the cortical surface through a prion-like process (Babcock & Ganetzky, 2015). Indeed one previous study found that trans-neuronal propagation of the mutant Huntington protein contributed to the spread of cortico-striatal degeneration (G R Poudel et al., 2019). Furthermore, our previous study found a network diffusion model across the human brain connectome was adequately able to explain the spread of pathology across the brain (G R Poudel et al., 2019). On the contrary, our current results indicate that neural dysfunction and cortical morphometry changes in HD may be unrelated, occurring independently of one another. However, when these changes occur and over what period, could not be determined by the current study.
We also reported that baseline tractography and changes in cortical morphometry did not together significantly predict changes in measures of clinical severity. As many theories of neurological and cognitive deficit are predicated upon damage to white and grey matter structures (GET SOURCES), this was not an expected finding. However, it has been well established that the striatum is the key site of pathology in HD (Georgiou-Karistianis, Scahill, et al., 2013; Tabrizi et al., 2012), and motor symptoms seen in HD could be due primarily to changes in this region. A simplified biological explanation for this is that mutant huntingtin proteins cause the striatum to produce weaker chemical signals, leading to fewer inhibitory transmitters, less inhibition of the motor cortex and ultimately, chorea (Labbadia & Morimoto, 2013)). Thus, the involvement of cortico-striatal tracts and cortical morphometry changes may be independent to the development of motor deficits in HD, or merely secondary to this process. The present study did not include cognitive measures of clinical severity, and further research would be required to determine whether abnormal white matter integrity and cortical morphometry could account for some of these deficits.
Group classification was the most significant predictor of change in these clinical measures over and above tractography and morphometry changes. This finding mimics those from previous studies (Tan et al., 2022), both of which found no significant associations between tractography or cortical morphometry measures and changes in clinical measures (despite UHDRS-TMS and DBS being significantly different between time points). Thus, the findings of the present study provide evidence that baseline tractography and changes in cortical morphometry in these regions are unrelated to the severity of motor symptoms seen in symp-HD (UHDRS-TMS) or severity of disease exposure (DBS). As previously mentioned above, and as noted in other studies (Tan et al., 2022), changes occurring in other regions of the brain (both subcortical and cortical) could be responsible for some of the clinical outcomes observed in HD. For example, the superior parietal lobe (responsible for visuomotor control and motor planning) may be one region of interest in further studies.
It is possible that methodological limitations prevented the detection of a relationship between tractography and cortical morphometry measures. For example, the time-period between baseline and 30-month follow-up could be inadequate to detect subtle longitudinal changes impacting white matter tracts and cortical morphometry. Previous studies have been similarly unable to find longitudinal change to white matter tracts or cortical morphometry (Tan et al., 2022), and have suggested that methodological limitations (i.e. inadequate time period between testing, and relatively small sample sizes)could be responsible for these non-findings.