Background

Persons with human immunodeficiency virus (PWH) are characterized by altered brain structure and function. As they attain normal lifespans, it has become crucial to understand potential interactions between human immunodeficiency virus (HIV) and aging. However, it remains unclear how brain aging varies with viral load (VL).

Methods

In this study, we compare magnetic resonance imaging (MRI) biomarkers among PWH with undetectable VL (UVL; ≤50 genomic copies/mL; n = 230), PWH with detectable VL (DVL; >50 copies/mL; n = 93), and HIV-uninfected (HIV-) controls (n = 206). To quantify gray matter cerebral blood flow (CBF), we utilized arterial spin labeling. To measure structural aging, we used a publicly available deep learning algorithm to estimate brain age from T1-weighted MRI. Cognitive performance was measured using a neuropsychological battery covering 5 domains.

Results

Associations between age and CBF varied with VL. Older PWH with DVL had reduced CBF vs PWH with UVL (P = .02). Structurally predicted brain aging was accelerated in PWH vs HIV- controls regardless of VL (P < .001). Overall, PWH had impaired learning, executive function, psychomotor speed, and language compared to HIV- controls. Structural brain aging was associated with reduced psychomotor speed (P < .001).

Conclusions

Brain aging in HIV is multifaceted. CBF depends on age and current VL and is improved by medication adherence. By contrast, structural aging is an indicator of cognitive function and reflects serostatus rather than current VL.

Background

Combination antiretroviral therapy (cART) has allowed for viral load (VL) suppression and increased life expectancy for persons with HIV (PWH). Altered brain integrity, measured by neuropsychological (NP) performance and neuroimaging, is still prevalent among virally suppressed PWH. Age-related conditions such as cardiovascular disease may also affect brain integrity. This study investigated the effects of cardiovascular risk, VL, and HIV serostatus on cerebral blood flow (CBF), brain volumetrics, and cognitive function in PWH and persons without HIV (PWoH).

Methods

Ten-year cardiovascular risk, using the Framingham Heart Study criteria, was calculated in PWH (n = 164) on cART with undetectable (≤20 copies/mL; n = 134) or detectable (>20 copies/mL; n = 30) VL and PWoH (n = 66). The effects of cardiovascular risk on brain integrity (CBF, volume, and cognition) were compared for PWH (undetectable and detectable VL) and PWoH.

Results

PWH had smaller brain volumes and worse NP scores than PWoH. PWH with detectable and undetectable VL had similar brain integrity measures. Higher cardiovascular risk was associated with smaller volumes and lower CBF in multiple brain regions for PWH and PWoH. Significant interactions between HIV serostatus and cardiovascular risk on brain volumes were observed in frontal, orbitofrontal, and motor regions. Cardiovascular risk was not associated with cognition for PWH or PWoH.

Conclusions

Neuroimaging, but not cognitive measures, was associated with elevated cardiovascular risk. HIV serostatus was associated with diminished brain volumes and worse cognition while CBF remained unchanged, reflecting potential protective effects of cART. Neuroimaging measures of structure (volume) and function (CBF) may identify contributions of comorbidities, but future longitudinal studies are needed.

Background

Persons with HIV (PWH) have both more frequent depression and higher levels of plasma inflammatory biomarkers compared to persons without HIV (PWoH). Inflammation and depressive symptoms are linked, including in PWH; however, it is unclear whether these associations differ by HIV serostatus and biological sex.

Methods

Six plasma inflammatory biomarkers were assessed using samples from PWH and PWoH who participated in six NIH-funded studies through the UCSD HIV Neurobehavioral Research Program (HNRP) from 2011 to 2019. Factor analysis was performed to identify intercorrelated groups of biomarkers. Factors and their components were then examined for relationships with Beck Depression Inventory-II (BDI-II) and modifying effects of sex or HIV serostatus using multivariable linear regression, adjusting for demographics, substance use diagnoses, and relevant co-morbidities.

Results

Participants included 150 PWH (age = 48.3 ± 13.1 yr; 88% biologically male) and 138 PWoH (age = 46.3 ± 15.9; 56% male). Two inflammatory factors were identified: Factor 1 loaded on interleukin-6 (IL-6), C-reactive protein (CRP), and D-dimer; Factor 2 loaded on interleukin-8, chemokine C-C ligand 2 (CCL2), and chemokine C-X-C ligand 10 (CXCL10). Sex modified the effect of Factor 1 on BDI-II, with a more positive association for men than women (p = 0.04). No significant association between Factor 2 and BDI-II was found. Of the biomarkers in Factor 1, only IL-6 was significantly associated with BDI-II and was modified by sex (p = 0.003). In sex-stratified analysis, a positive association was found for men (β = 5.42; 95% confidence interval = [1.32, 9.52]) but not women (β = -3.88; 95% C.I. = [-11.02, 3.26]). No HIV-related interactions were detected.

Interpretation

We identified a depression-associated inflammatory factor present in both PWH and PWoH, consistent with prior studies of PWH only. The association was driven by a correlation between IL-6 and depression exclusively in men, suggesting that the depression-inflammation link differs by sex. Future studies of depression etiology or treatment, including those on persons with HIV, should consider the impact of biological sex in both design and analysis.

Cognitive disorders are prevalent in people with HIV (PWH) despite antiretroviral therapy. Given the heterogeneity of cognitive disorders in PWH in the current era and evidence that these disorders have different etiologies and risk factors, scientific rationale is growing for using data-driven models to identify biologically defined subtypes (biotypes) of these disorders. Here, we discuss the state of science using machine learning to understand cognitive phenotypes in PWH and their associated comorbidities, biological mechanisms, and risk factors. We also discuss methods, example applications, challenges, and what will be required from the field to successfully incorporate machine learning in research on cognitive disorders in PWH. These topics were discussed at the National Institute of Mental Health meeting on "Biotypes of CNS Complications in People Living with HIV" held in October 2021. These ongoing research initiatives seek to explain the heterogeneity of cognitive phenotypes in PWH and their associated biological mechanisms to facilitate clinical management and tailored interventions.