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

• Main Authors: Chen, F. (Author), Jing, B. (Author), Li, A. (Author), Li, H. (Author), Li, L. (Author), Ma, Z. (Author), Ren, M. (Author), Zhao, J. (Author)
• Format: Article
• Language: English
• Published: John Wiley and Sons Inc 2021
• Subjects: adult; Adult; age; age effect; Age Factors; antiretroviral therapy; Article; attention; brain; brain cortex; cART; Cerebral Cortex; controlled study; cortical thickness (brain); diagnostic imaging; discriminant analysis; efavirenz; evaluation study; gray matter; Gray Matter; gray matter volume; HIV; HIV Infections; human; Human immunodeficiency virus; Human immunodeficiency virus infected patient; Human immunodeficiency virus infection; Humans; lamivudine; language; lopinavir; machine learning; Machine Learning; Magnetic Resonance Imaging; major clinical study; male; Male; middle aged; Middle Aged; morphology; motor performance; neuropsychology; nonhuman; nuclear magnetic resonance imaging; pathology; ritonavir; scoring system; statistical analysis; structural MRI; tenofovir
• Online Access: View Fulltext in Publisher

 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. © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.