Association Between Processing Speed and Segregation/Integration of Large-scale Functional Networks in Middle-aged and Older People Living With HIV
Monica Diaz1, Matthew Harris2, Jacqueline Koble3, Keely Copperthite4, Jordan Jimenez5, Eran Dayan5
1Department of Neurology, University of North Carolina at Chapel Hill, 2Department of Physical Medicine & Rehabilitation, 3Department of Neurology, 4Division of Infectious Diseases, 5Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill School of Medicine
Objective:
This study investigated whether the balance of segregation and integration in large-scale functional networks is associated with processing speed in middle-aged and older PWH.
Background:
Neurocognitive impairment (NCI) is a common comorbidity among aging people with HIV (PWH), despite effective antiretroviral therapy (ART). Processing speed is often the earliest affected cognitive domain and may be linked to disrupted functional brain network organization.
Design/Methods:
In a prospective, cross-sectional study, 26 virologically suppressed PWH aged ≥50 years, enrolled from the University of North Carolina-Chapel Hill Infectious Diseases clinic, underwent neuropsychological testing and resting-state functional MRI (rs-fMRI). Functional brain networks were constructed using a 300-node cortico-subcortical parcellation. System segregation index and node-level participation coefficient (PC) were calculated to quantify the global and local balance between integration and segregation, respectively. Associations with age-adjusted Wechsler Adult Intelligence Scale (WAIS-III) Symbol Search (WAISsys) T-scores were assessed using regression and correlational analyses.
Results:
Higher system segregation within associative networks was significantly associated with better WAISsys T-scores (β = 0.544, p = 0.004), whereas segregation in sensorimotor networks was not. The majority of nodal PC values were negatively correlated with WAISsys T-scores, indicating that lower processing speed was associated with less segregated and more integrated connectivity. Nodes showing the strongest negative associations with WAISsys T-scores were disproportionately located in the default mode and frontoparietal networks.
Conclusions:
In middle-aged and older PWH, greater segregation within associative networks is linked to better processing speed. Disruptions in network segregation and modularity, especially in cognitive control systems, may be associated with processing speed deficits despite viral suppression. These findings highlight the importance of functional brain network topology and organization as a potential biomarker for cognitive aging in HIV.
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