Salience network connectivity predicts frontotemporal dementia progression

Baseline measures of salience network connectivity involving the left insula may predict behavioral changes in patients with frontotemporal dementia, according to a study published in the October issue of JAMA Neurology.

The salience network (SLN) is comprised of the anterior cingulate, insula, striatum and amygdala. In healthy patients, the SLN is activated when tasks require attentional selection, task switching and self-regulation of behavior. The SLN is an important neural substrate in frontotemporal dementia (FTD) whose dysfunction is confirmed with histopathology and resting-state functional magnetic resonance (fMR) imaging.

Moreover, the SLN’s insula is a nodal point of particular importance for frontolimbic function and dysfunction. Insular atrophy is one of the earliest structural biomarkers in behavioral variant FTD (bvFTD) and semantic dementia.

“Abnormal activity within intrinsic brain networks may be clinically relevant, indicative of neurodegenerative disease,” wrote the study’s author, Gregory S. Day, MD, MSc, of the University of Toronto, and colleagues.” “Resting-state fMR imaging may provide a noninvasive biomarker for the diagnosis and longitudinal monitoring of patients with FTD.”

With little research on whether this emerging technique can identify patterns of network disruption in patients before the development of changes on clinical examination or structural neuroimaging, Day and colleagues developed a study to correlate baseline resting-state measures within the salience network and changes in behavior among 15 patients with clinically diagnosed FTD. The patients were taking the clinical intervention, memantine hydrochloride, two times daily.

Participants were from a tertiary academic care center that specializes in assessment and management of patients with neurodegenerative disease. Baseline fMRI data and longitudinal measures were obtained from them during eight weeks using Frontal Behavioral Inventory (FBI) total score. Resting-state activity in the patients was compared with that of healthy control subjects to identify SLN hubs.

Forward linear regression analysis used baseline resting-state scores within regions of interest (ROIs) to predict the percentage of change on behavioral scales after eight weeks. Findings indicated that low frequency fluctuations in the left insula significantly predicted changes in FBI scores, accounting for a 28 percent change variance. The trend was driven by changes in measures of apathy independent of dementia severity.

“Limitations notwithstanding, the results of this analysis expand on prior studies,” wrote Day and colleagues. “Resting-state measures of neural connectivity may provide a noninvasive means of assessing network functioning in neurodegenerative disease.”