Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
Lancet HIV. 2023 Apr;10(4):e244-e253. doi: 10.1016/S2352-3018(22)00373-3. Epub 2023 Feb 7.
Neuroimaging reveals structural brain changes linked with HIV infection and related neurocognitive disorders; however, group-level comparisons between people with HIV and people without HIV do not account for within-group heterogeneity. The aim of this study was to quantify the effects of comorbidities such as cardiovascular disease and adverse social determinants of health on brain ageing in people with HIV and people without HIV.
In this retrospective case-control study, people with HIV from Washington University in St Louis, MO, USA, and people without HIV identified through community organisations or the Research Participant Registry were clinically characterised and underwent 3-Tesla T-weighted MRI between Dec 3, 2008, and Oct 4, 2022. Exclusion criteria were established by a combination of self-reports and medical records. DeepBrainNet, a publicly available machine learning algorithm, was applied to estimate brain-predicted age from MRI for people with HIV and people without HIV. The brain-age gap, defined as the difference between brain-predicted age and true chronological age, was modelled as a function of clinical, comorbid, and social factors by use of linear regression. Variables were first examined singly for associations with brain-age gap, then combined into multivariate models with best-subsets variable selection.
In people with HIV (mean age 44·8 years [SD 15·5]; 78% [296 of 379] male; 69% [260] Black; 78% [295] undetectable viral load), brain-age gap was associated with Framingham cardiovascular risk score (p=0·0034), detectable viral load (>50 copies per mL; p=0·0023), and hepatitis C co-infection (p=0·0065). After variable selection, the final model for people with HIV retained Framingham score, hepatitis C, and added unemployment (p=0·0015). Educational achievement assayed by reading proficiency was linked with reduced brain-age gap (p=0·016) for people without HIV but not for people with HIV, indicating a potential resilience factor. When people with HIV and people without HIV were modelled jointly, selection resulted in a model containing cardiovascular risk (p=0·0039), hepatitis C (p=0·037), Area Deprivation Index (p=0·033), and unemployment (p=0·00010). Male sex (p=0·078) and alcohol use history (p=0·090) were also included in the model but were not individually significant.
Our findings indicate that comorbid and social determinants of health are associated with brain ageing in people with HIV, alongside traditional HIV metrics such as viral load and CD4 cell count, suggesting the need for a broadened clinical perspective on healthy ageing with HIV, with additional focus on comorbidities, lifestyle changes, and social factors.
National Institute of Mental Health, National Institute of Nursing Research, and National Institute of Drug Abuse.
神经影像学揭示了与 HIV 感染和相关神经认知障碍相关的结构性大脑变化;然而,HIV 感染者和非 HIV 感染者之间的组水平比较并未考虑组内异质性。本研究的目的是量化心血管疾病等合并症和健康的不利社会决定因素对 HIV 感染者和非 HIV 感染者大脑老化的影响。
在这项回顾性病例对照研究中,来自美国密苏里州圣路易斯华盛顿大学的 HIV 感染者和通过社区组织或研究参与者登记处确定的非 HIV 感染者在 2008 年 12 月 3 日至 2022 年 10 月 4 日期间接受了 3T 磁共振 T1 加权成像。排除标准是通过自我报告和病历相结合确定的。DeepBrainNet 是一种公开的机器学习算法,用于从 HIV 感染者和非 HIV 感染者的 MRI 中估计大脑预测年龄。脑龄差距定义为大脑预测年龄与实际年龄之间的差异,通过使用线性回归模型,将临床、合并症和社会因素作为函数进行建模。首先单独检查变量与脑龄差距的关联,然后使用最佳子集变量选择将变量组合到多变量模型中。
在 HIV 感染者(平均年龄 44.8 岁[15.5 岁];78%[379 名中的 296 名]为男性;69%[260 名]为黑人;78%[295 名]病毒载量不可检测)中,脑龄差距与弗雷明汉心血管风险评分(p=0.0034)、可检测病毒载量(>50 拷贝/ml;p=0.0023)和丙型肝炎合并感染(p=0.0065)有关。经过变量选择,HIV 感染者的最终模型保留了弗雷明汉评分、丙型肝炎,并增加了失业(p=0.0015)。通过阅读能力检测的教育成就与非 HIV 感染者的脑龄差距降低有关(p=0.016),但与 HIV 感染者无关,表明这是非 HIV 感染者的一个潜在恢复因素。当 HIV 感染者和非 HIV 感染者联合建模时,选择结果是一个包含心血管风险(p=0.0039)、丙型肝炎(p=0.037)、区域贫困指数(p=0.033)和失业(p=0.00010)的模型。男性(p=0.078)和饮酒史(p=0.090)也包含在模型中,但没有单独的显著意义。
我们的研究结果表明,合并症和健康的社会决定因素与 HIV 感染者的大脑老化有关,同时还有传统的 HIV 指标,如病毒载量和 CD4 细胞计数,这表明需要对 HIV 感染者的健康老龄化有更广泛的临床视角,额外关注合并症、生活方式改变和社会因素。
美国国立卫生研究院、美国国立护理研究院和美国国立药物滥用研究所。