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Altered connectivity of the default mode network in cognitively stable adults with Down syndrome: “Accelerated aging” or a prelude to Alzheimer's disease?

Abstract Introduction Most individuals with Down syndrome (DS) have the neuropathological changes of Alzheimer's disease (AD) by age 40 and will have developed dementia by age 60. Alterations of the intrinsic connectivity of the default mode network (DMN) are associated with AD in the neurotypical population. In this study, we sought to determine whether, and how, connectivity between the hubs of the DMN were altered in cognitively stable adults with DS who did not have evidence of either mild cognitive impairment or AD. Methods Resting state functional MRI scans were collected from 26 healthy adults with DS and 26 healthy age‐matched non‐DS controls. Nodes comprising the DMN were generated as ROI's (regions of interest) and inter‐nodal correlations estimated. Results Analysis of intra‐network connectivity of the DMN revealed anterior‐posterior DMN dissociation and hyper‐ and hypo‐connectivity, suggesting “accelerated aging” in DS. Discussion Disruption of the DMN may serve as a prelude for AD in DS.


INTRODUCTION
By the age of 40, virtually all adults with Down syndrome (DS), the most common genetic cause of neuro-developmental delay, 1 develop Alzheimer's disease (AD)-associated neuropathology and most will be clinically diagnosed with dementia by age 60, 2,3 although not in all cases. The triplication of amyloid precursor protein on chromosome 21 is associated with increased deposition of extracellular amyloid beta (Aβ) in the brain in DS. 4 The neuropathological hallmarks of AD, including Aβ senile plaques and tau neurofibrillary tangles, begin to develop years before cognitive impairment are observed in both the neurotypical and DS populations. 5,6 Several studies have also reported subtle early neuronal and synaptic changes in individuals with mild cognitive impairment (MCI) in the general population, 7,8 suggesting that these early pathological changes could interfere with typical patterns of brain connectivity.
Functional connectivity is a functional magnetic resonance imaging (fMRI) analysis method which compares correlations in the timeseries of blood-oxygen level dependent (BOLD) activity across the brain to assess the functional relationships between distinct brain areas. Analyses of regions with comparable BOLD fluctuations over time have revealed the presence of a number of different "functional networks" in the brain. The default mode network (DMN), one of the most studied and best characterized functional networks in humans, is a group of brain regions characterized by a shared pattern of increased level of activation during rest and reduced activation during attention-demanding, externally directed tasks. 9 Regions of the classically defined DMN include: the prefrontal cortex, angular gyrus, precuneus/posterior cingulate cortex, and temporal areas. 10,11 The DMN has received particular attention in studies of neurotypical AD, in which reduced intra-network connectivity has been reported, [11][12][13] and is hypothesized to be associated with regional Aβ deposition.
Previous functional connectivity studies in healthy young adults with DS have suggested increases in inter-network functional connectivity of the DMN to other brain networks such as the dorsal and ventral attention networks. 14,15 However, studies focusing on the distinct components of the DMN in cognitively stable adults with DS, before clinical decline caused by AD-related neuropathology, have not as of yet been conducted. The aim of this study was to better characterize the functional architecture of the DMN in cognitively normal adults with DS. We therefore examined differences in network connectivity within the DMN in a subset of cognitively stable adults with DS (ie, no diagnosis of MCI or of dementia) and compared them to healthy age-matched adults without DS.

Participants
Participants with DS were recruited through the Alzheimer's Dis-

Automated anatomical segmentation
Individual T1-weighted MEMPRAGE images were automatically segmented into gray and white matter, with automated cortical parcellations and subcortical segmentations performed using the FreeSurfer reconstruction (https://surfer.nmr.mgh.harvard.edu, version 6.0). All raw imaging data and reconstructions were visually assessed for artifacts and accuracy of surface-boundary before analysis.

Resting state fMRI processing
All functional images also underwent an initial visual quality assurance.
In addition, after the application of the MCFLIRT tool from the FMRIB Software Library (FSL), resting state scans were eliminated from analysis if more than 10% of the frames (ie, > 40 out of 408 total frames) exceeded a threshold of 0.7 mm for framewise displacement, a measure of the translation and rotation from one frame to the next 20 as differences in motion can affect functional connectivity results. 21 We chose this threshold to avoid removing any frames of data and to control for between-group differences in motion, as clinical populations are shown to move more during scans than controls. 14 Resting state data were preprocessed with the FreeSurfer-based FS-FAST

Highlights
• Default mode network connectivity is altered in cognitively stable adults with Down syndrome (DS). • A similar pattern of DMN connectivity is found in sporadic Alzheimer's disease (AD).
• This pattern suggests "accelerated aging" in DS or prelude to AD. analysis pipeline, which includes the following steps: motion correction, slice-timing correction, rigid anatomical-functional registration, masking of nonbrain tissue, intensity normalization, resampling of functional time series data to common surface space (fsaverage), and spatial smoothing using a 5 mm full width half maximum.

Region of interest (ROI) analysis
To evaluate the architecture and connectivity of the DMN more closely, we separated Yeo's DMN from the seven-network segmentation into its major components, generating six seeds/ROIs per hemisphere. 22 These included:  were displayed on the fsaverage inflated brain surface. 23 For each subject, partial correlation coefficients between the time-series of a given seed and ROI were calculated and compiled using the funcroi-sess and funcroi-

Demographics
Controls and participants with DS did not differ with respect to age (HC

Within-network group differences
We evaluated the within-group profiles of DMN connectivity based on the ROI analysis and found significant differences in intra-network connectivity of the DMN ( Figure 1, Table 1). We found evidence of stronger  Table 1 for additional estimates).
Group differences were similar between the unadjusted and adjusted models. Thus, only unadjusted estimates are presented, to reduce the possibility of model overfitting. Similarly, associations between connectivity and APOE ε4 status and between connectivity and age among DS participants were not observed. We further confirmed this finding in the whole-brain voxel-wise analysis. As demonstrated in Figure 2, when the DMPFC was used as the seeded region, activation in the HC group follows the typical DMN pattern, with strong correlations to the AG, MTG, and PCC. However, in the DS group, there was significantly reduced to absent activation in the posterior DMN regions accompanied by more widespread frontal connectivity, especially to the VLPFC region. In contrast, when the PCC was used as the seeded region, there appeared to be reduced activation in the anterior DMN regions (ie, DMPFC and VLPFC) in the DS group.
Similar patterns were found in both hemispheres.

DISCUSSION
We examined functional connectivity within the DMN in cognitively stable Down syndrome participants and HC by comparing the functional activity between six nodes of the DMN in each hemisphere.
We found a number of differences between the two groups that The DMPFC seed showed reduced connectivity to the AG and PCC in both hemispheres. As a target ROI, the VLPFC showed reduced connectivity to MTG and PCC in the left hemisphere, as well as subthreshold reductions to these two regions in the right hemisphere and to the AG in both hemispheres. Interestingly, in the right hemisphere, the connectivity of the DMPFC and VLPMC (both frontal DMN regions) to each other was increased, which may indicate a higher level of local connectivity within the frontal lobe in DS.
Abnormal brain synchrony in adolescents and young adults with DS has been reported previously, demonstrating evidence of an overall simplified network structure in this population; 14 therefore, it is possible that some of our findings could reflect, at least in part, differences due to atypical brain development caused by DS, beginning in utero. Taken all together, however, our findings suggest that the ante- Estimates, and 95% confidence intervals, of the median differences (Down -healthy controls) are provided by seed and target ROI and by hemisphere The asterisk superscript next to the point estimate denotes significant unadjusted comparisons (P < .05) and the double asterisk denotes significant comparisons using an FDR-adjustment (P-fdr < 0.05). Abbreviations: FDR, false discovery rate; ROI, region of interest.
early in DS; in one PET study, as many as 25% of nondemented adults were found to have increased uptake of Pittsburgh compound B, a tracer used to image amyloid deposition in humans in vivo. [32][33][34] Interestingly, the deposition of amyloid in DS follows a pattern starting first in the striatum and eventually involving rostral prefrontalcingulo-parietal regions, to caudal frontal, rostral temporal, primary sensorimotor and occipital, and finally medio-temporal regions and the rest of the basal ganglia. 35 Therefore, the parallel between the distribution of amyloid in DS and our findings of early increased connectivity in frontal regions suggests that the observed increases in connectivity could possibly represent early changes associated with amyloid deposition.
Reduced anterior to posterior DMN node connectivity was also reported in another study in adults with DS. 36 That study, however, combined both cognitively stable and demented individuals with DS within the same analysis; our study focused on exclusively cognitively stable adults, so a direct comparison is not possible. Reduced connectivity between nodes of the DMN has been reported in several studies of normal aging 37,38 and the present findings in our DS cohort are consistent with previous investigations reporting a dissociation between the "anterior" and "posterior" DMN connectivity within other aging populations. 25 In our study, participants with DS demonstrated a similar pattern of reduced and/or disrupted anterior-posterior DMN connectivity; however, our participants were on average more than 20 years younger than the neurotypical population studied previously. 39 Though we did not find an association between network connectivity and age in our sample, it is tempting to speculate that the disruptions observed in cognitively stable adults with DS (which align with findings in much older neurotypical populations) reflect a sort of "accelerated" brain aging, consistent with what has been proposed previously, [40][41][42] 12,39,43,44 In this study, we evaluated the DMN in cognitively stable adults with DS, given the high risk for dementia caused by AD.
We observed a disrupted DMN, which highlights that neuroanatomical areas are altered, even in individuals deemed to be clinically unaffected. The observed fragmentation of the DMN seems indicative of atypical brain aging and may be characteristic of functional activity changes that occur during the preclinical stage of AD. These findings also suggest that functional connectivity MRI could serve as an important and early indicator of network disruptions in DS, before the onset of clinical diagnosis of MCI or dementia.

ACKNOWLEDGMENTS
We are very grateful to the individuals who participated in this study, their families, and care providers, who so generously contributed their time and energy to this project, and without whom it would not have been possible. We thank the individuals who helped recruit and/or assess participants for this study including: Margaret Pulsifer, Sharon

CONFLICTS OF INTEREST
The authors report no conflicts of interest.