Human immune deficiency virus‐related structural alterations in the brain are dependent on age

Abstract

Currently, it is still unknown whether human immune deficiency virus (HIV)‐related structural alterations in the brain are dependent on age. With people living with HIV at different ages, we aim to investigate age‐specific structural alterations in HIV patients. Eighty‐three male HIV patients and eighty‐three age‐matched male controls were enrolled, and high‐resolution T1 weighted images were collected and analyzed with four morphological metrics. Then, statistical analyses were respectively conducted to ascertain HIV effects, age effects, and medication effects in brain structure of HIV patients, and the relationship with neuropsychological evaluations were further explored. Finally, discriminative performances of these structural abnormalities were quantitatively testified with three machine learning models. Compared with healthy controls, HIV patients displayed lower gray matter volumes (GMV), lower gyrification index, deeper sulcus depth, and larger cortical thickness (CTH). Age‐specific differences were found in GMV and CTH: young‐aged HIV patients displayed more obvious morphological alterations than middle‐aged HIV patients when comparing corresponding age‐matched healthy controls. Furthermore, age‐specific long‐term medication effect of combination antiretroviral therapy were also presented. Additionally, several subcortical structural changes were negatively associated with language, attention and motor functions. Finally, three machine learning models demonstrated young‐aged HIV patients were easier to be recognized than middle‐aged HIV patients. Our study indicated young‐aged HIV patients were more vulnerable to HIV infection in brain structure than middle‐aged patients, and future studies should not ignore the age effect in studying the HIV‐related abnormalities.

Probing bundle-wise abnormalities in patients infected with human immunodeficiency virus using fixel-based analysis: new insights into neurocognitive impairments

“…dMRI has been used to accurately detect the effect of HIV on brain WM abnormalities and determine the relationship between cognitive functions and other factors, such as smoking, age, and drug use. [40,[49][50][51] Our findings not only revealed CPT, FX, and SLF abnormalities in HIV patients, which have been reported in previous DTI studies, [52][53][54][55] but also reported some new findings in FPT, CRF, RST, CBT, CPT and VLPC tracts. Indeed, recent fixel-based analytical approaches have been widely applied for characterizing a specific fiber population within a voxel (i.e., a "fixel").…”

Seed-based morphometry of nodes in the default mode network among patients with Alzheimer’s disease in Klang Valley, Malaysia

“…We identified some similarities with other studies such as atrophy of the precuneus (47). We detected that AD had reduced GMV at the ITG r and ITG l (48), SFG l (49), MSFG r (49), right gyrus rectus or straight gyrus (49) right temporal lobe (50), left putamen (51) and right precuneus. Furthermore, Guo, Chen (52) found decreased GMV in the ventral precuneus and postulated that this region helps to boost the efficiency of conscious processes, allowing individuals to transition between different temporal frames depending on the situation and leading to more balanced time perspectives, which then becomes impaired in AD patients.…”

A Reparametrized CNN Model to Distinguish Alzheimer's Disease Applying Multiple Morphological Metrics and Deep Semantic Features From Structural MRI

“…The reparametrized module was designed to constrain the similarity of deep semantic features, achieving the most distinguishing features. The morphological metrics were derived from VBM (Jing et al, 2018;Zhao et al, 2021), where GMV, white matter volume, and cerebrospinal fluid volume were computed using CAT-12.…”