In:
Alzheimer's & Dementia, Wiley, Vol. 18, No. S5 ( 2022-12)
Abstract:
With increasing longevity, the incidence of age‐associated functional decline and dementia is on the rise, with Alzheimer’s disease, the third most common type of dementia, projected to affect 13.8 million people by 2050. Previous studies on aging populations have reported that while people chronologically age at the same rate, an individual’s brain maturation/aging trajectory, which can be quantified by measuring the deviation of their brain’s structure and function from normative data, can be predictive of more serious forms of cognitive decline. Software capable of accurately computing this trajectory based on commonly acquired clinical scans, such as BrainAGE R, could provide reliable biomarkers of pre‐clinical disease states thereby enhancing clinicians’ ability to make early diagnosis of cognitive decline. In this study, we evaluate the relationship between resting‐state functional connectivity (rsFC) and BrainAGE measures in healthy older adults. Method Sixty participants (40 Female, 20 Male) aged between 60‐80 (M = 66.78, SD = 6.98) were recruited as part of the Aging Brain Cohort dataset at the University of South Carolina (ABC@UofSC). Participants completed structural T1‐weighted (T1w) and resting‐state fMRI (rsfMRI) scans. Preprocessing of the data was done using default preprocessing steps specified by the CONN toolbox. Following image preprocessing and denoising, ROI‐to‐ROI connectivity matrices in CONN were created for each participant. Individual brain age was estimated using BrainAGE R computer algorithm based on their T1w scans. BrainAGE difference scores were then calculated by computing the difference between each participant’s chronological age and their estimated brain age. Finally, a univariate general linear model analysis was used to identify significant relationships between BrainAGE difference scores and rsFC while controlling for participants’ chronological age. Result Our analysis revealed a significantly negative association between BrainAGE scores and rsFC of several brain networks. In particular, higher BrainAGE scores were associated with decreased connectivity between 1) default mode and salience networks, 2) default mode and fronto‐parietal networks (bilateral), and 3) visual and salience networks. Conclusion Our results provide novel evidence that accelerated brain maturation/aging, as indexed by BrainAGE scores, is associated with specific patterns of decreased rsFC in healthy older adults.
Type of Medium:
Online Resource
ISSN:
1552-5260
,
1552-5279
Language:
English
Publisher:
Wiley
Publication Date:
2022
detail.hit.zdb_id:
2201940-6
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