Biopsychosocial Phenotypes and Potential Mechanisms in CHARTER

中枢神经系统(CNS)并发症在艾滋病毒(PWH)患者中很常见，即使是那些 正在接受抗逆转录病毒治疗(ART)。中枢神经系统并发症的范围很广，从轻微的认知 从不影响日常功能的缺陷到危及生命的脑炎。认知和情绪障碍是 影响PWH的最常见的中枢神经系统疾病中，有一个共同的危险因素，即炎症。 炎症在有效治疗的PWH中持续存在，原因有很多，包括产生艾滋病毒RNA和 蛋白质和肠道生物失调和微生物易位。Charge是一家总部设在美国的多地点神经艾滋病毒队列 这项研究由NIH资助，研究PWH的中枢神经系统障碍已近20年， 它已经完成了6,000多项评估，产生了1000多万个数据点。特许状 在了解这些疾病的频率、危险因素和发病机制方面做出了重要贡献 精神错乱。近年来，在异质性、生物学基础、临床影响、 和中枢神经系统疾病的管理。这场辩论突出了创建新的中枢神经系统分类的必要性 PWH中的疾病更多是基于生物学的。我们建议使用机器学习和A-N等方法 对查特的高维神经行为、神经内科、精神病学、 物质使用和成像数据。这样的分析不仅会产生认知表型，还会产生生物心理社会 (BPS)可识别导致临床有用的诊断测试的新机制的表型，新的 治疗和更好地处理PWH中的中枢神经系统障碍。 我们的首要目标是通过使用其数据和存储的样本来利用对Charge的先前投资 A)更好地了解PWH的认知和BPS表型，b)将它们与生物学机制联系起来。至 为此，我们将使用无监督和有监督的机器学习方法来分析来自 查特的全面评估，目标是确定新的认知和BPS表型(AIM 1)。然后我们将把这些新的表型与查特完成的高维数据进行比较 全基因组关联研究以及我们将生成的有关炎症的新数据(45-plex珠基阵列) 以及血液和脑脊液中微生物组和代谢组的高度新颖的分析(目标2)。我们的分析将 包括一个具体的关注点，说明性行为如何影响观察到的关系。以确定这一新方法是否与 比以前的方法更接近生物学，我们还将比较新表型的性能与 那些由2007年的HAND标准定义的。这一高度创新的应用程序得到了强大的初步支持 数据，很好地回应了艾滋病研究办公室的优先事项，并将解决该领域的主要差距，包括 需要更好地了解合并症的发病机制。

Central nervous system (CNS) complications are common among people with HIV (PWH), even those who are taking antiretroviral therapy (ART). The spectrum of CNS complications is broad, ranging from mild cognitive deficits that do not affect daily functioning to life-threatening encephalitis. Cognitive and mood disorders are among the most common CNS diseases that affect PWH and share a common risk factor, inflammation. Inflammation persists in effectively treated PWH for multiple reasons, including production of HIV RNA and proteins and gut dysbiosis and microbial translocation. CHARTER is a multisite, U.S.-based, neuroHIV cohort study that is funded by NIH and that has investigated CNS disorders in PWH for nearly two decades, during which it has completed more than 6,000 assessments generating more than 10 million data points. CHARTER has made important contributions to understanding the frequency, risk factors, and pathogenesis of these disorders. In recent years, new questions have arisen about the heterogeneity, biological basis, clinical impact, and management of CNS disorders. This debate has highlighted the need to create new classifications of CNS disorders in PWH that are more biology-based. We propose to use methods such as machine learning and an agnostic approach to categorize CHARTER’s high-dimensional neurobehavioral, neuromedical, psychiatric, substance use, and imaging data. Such analyses would yield not just cognitive phenotypes but biopsychosocial (BPS) phenotypes that could identify new mechanisms that lead to clinically useful diagnostic tests, new therapies, and better management of CNS disorders in PWH. Our overarching goal is to leverage prior investment in CHARTER by using its data and stored specimens to a) better understand cognitive and BPS phenotypes in PWH and b) relate them to biological mechanisms. To accomplish this, we will use unsupervised and supervised machine learning methods to analyze data from CHARTER’s comprehensive assessments with the goal of identifying new cognitive and BPS phenotypes (Aim 1). We will then compare these new phenotypes to high-dimensional data from CHARTER’s completed genomewide association study as well as new data we will generate on inflammation (45-plex bead-based array) and highly novel assays of the microbiome and the metabolome in blood and CSF (Aim 2). Our analyses will include a specific focus how sex affects the observed relationships. To determine if this novel approach relates more strongly to biology than prior methods, we will also compare the performance of the new phenotypes to those defined by the 2007 HAND criteria. This highly innovative application is supported by strong preliminary data, responds well to Office of AIDS Research priorities, and will address key gaps in the field, including the need to better understand the pathogenesis of comorbid disease.