Immune Responses in the Central Nervous System Are Anatomically Segregated in a Non-Human Primate Model of Human Immunodeficiency Virus Infection

Biological agents and the aging brain: glial inflammation and neurotoxic signaling

Neuroinflammation is a universal characteristic of brain aging and neurological disorders, irrespective of the disease state. Glial inflammation mediates this signaling, through astrocyte and microglial polarization from neuroprotective to neurotoxic phenotypes. Glial reactivity results in the loss of homeostasis, as these cells no longer provide support to neurons, in addition to the production of chronically toxic pro-inflammatory mediators. These glial changes initiate an inflammatory brain state that injures the central nervous system (CNS) over time. As the brain ages, glia are altered, including increased glial cell numbers, morphological changes, and either a pre-disposition or inability to become reactive. These alterations induce age-related neuropathologies, ultimately leading to neuronal degradation and irreversible damage associated with disorders of the aged brain, including Alzheimer's Disease (AD) and other related diseases. While the complex interactions of these glial cells and the brain are well studied, the role additional stressors, such as infectious agents, play on age-related neuropathology has not been fully elucidated. Both biological agents in the periphery, such as bacterial infections, or in the CNS, including viral infections like SARS-CoV-2, push glia into neuroinflammatory phenotypes that can exacerbate pathology within the aging brain. These biological agents release pattern associated molecular patterns (PAMPs) that bind to pattern recognition receptors (PRRs) on glial cells, beginning an inflammatory cascade. In this review, we will summarize the evidence that biological agents induce reactive glia, which worsens age-related neuropathology.

Machine Learning Prediction and Phyloanatomic Modeling of Viral Neuroadaptive Signatures in the Macaque Model of HIV-Mediated Neuropathology

In human immunodeficiency virus (HIV) infection, virus replication in and adaptation to the central nervous system (CNS) can result in neurocognitive deficits in approximately 25% of patients with unsuppressed viremia. While no single viral mutation can be agreed upon as distinguishing the neuroadapted population, earlier studies have demonstrated that a machine learning (ML) approach could be applied to identify a collection of mutational signatures within the virus envelope glycoprotein (Gp120) predictive of disease. The S[imian]IV-infected macaque is a widely used animal model of HIV neuropathology, allowing in-depth tissue sampling infeasible for human patients. Yet, translational impact of the ML approach within the context of the macaque model has not been tested, much less the capacity for early prediction in other, noninvasive tissues. We applied the previously described ML approach to prediction of SIV-mediated encephalitis (SIVE) using gp120 sequences obtained from the CNS of animals with and without SIVE with 97% accuracy. The presence of SIVE signatures at earlier time points of infection in non-CNS tissues indicated these signatures cannot be used in a clinical setting; however, combined with protein structural mapping and statistical phylogenetic inference, results revealed common denominators associated with these signatures, including 2-acetamido-2-deoxy-beta-d-glucopyranose structural interactions and high rate of alveolar macrophage (AM) infection. AMs were also determined to be the phyloanatomic source of cranial virus in SIVE animals, but not in animals that did not develop SIVE, implicating a role for these cells in the evolution of the signatures identified as predictive of both HIV and SIV neuropathology. IMPORTANCE HIV-associated neurocognitive disorders remain prevalent among persons living with HIV (PLWH) owing to our limited understanding of the contributing viral mechanisms and ability to predict disease onset. We have expanded on a machine learning method previously used on HIV genetic sequence data to predict neurocognitive impairment in PLWH to the more extensively sampled SIV-infected macaque model in order to (i) determine the translatability of the animal model and (ii) more accurately characterize the predictive capacity of the method. We identified eight amino acid and/or biochemical signatures in the SIV envelope glycoprotein, the most predominant of which demonstrated the potential for aminoglycan interaction characteristic of previously identified HIV signatures. These signatures were not isolated to specific points in time or to the central nervous system, limiting their use as an accurate clinical predictor of neuropathogenesis; however, statistical phylogenetic and signature pattern analyses implicate the lungs as a key player in the emergence of neuroadapted viruses.

Proteomics Profiling with SWATH-MS Quantitative Analysis of Changes in the Human Brain with HIV Infection Reveals a Differential Impact on the Frontal and Temporal Lobes

The chronic irreversible regression of cognitive ability and memory function in human immunodeficiency virus (HIV)-associated dementia (HAND) is linked with late-stage HIV infection in the brain. The molecular-level signatures of neuroinflammation and neurodegeneration are linked with dysfunction in HAND patients. Protein expression changes and posttranslational modification are epigenetic cues for dementia and neurodegenerative disease. In this study quantitative proteome analysis was performed to comprehensively elucidate changes in protein profiles in HIV-positive (HIV+) human brains. Frontal and temporal lobes of normal and HIV+ brains were subjected to label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using the data-independent acquisition method. Comprehensive proteomic identification and quantification analysis revealed that 3294 total proteins and 251 proteins were differentially expressed in HIV+ brains; specifically, HIV+ frontal and temporal lobes had 132 and 119 differentially expressed proteins, respectively. Proteomic and bioinformatic analyses revealed protein alterations predominantly in the HIV+ frontal lobe region. The expression of GOLPH3, IMPDH2, DYNLL1, RPL11, and GPNMB proteins was significantly altered in HIV+ frontal lobes compared to that in normal brains. These proteins are associated with metabolic pathways, neurodegenerative disorders, and dementia. These proteomic-level changes may be potential biological markers and therapeutic targets to relieve the dementia-associated symptoms in individuals with HAND.

Advances in SIV/SHIV Non-Human Primate Models of NeuroAIDS

Non-human primates (NHPs) are the most relevant model of Acquired Immunodeficiency Syndrome (AIDS) and neuroAIDS, being of great importance in explaining the pathogenesis of HIV-induced nervous system damage. Simian Immunodeficiency Virus (SIV)/ Simian-Human Immunodeficiency Virus (SHIV)-infected monkeys have provided evidence of complex interactions between the virus and host that include host immune response, viral genetic diversity, and genetic susceptibility, which may explain virus-associated central nervous system (CNS) pathology and HIV-associated neurocognitive disorders (HAND). In this article, we review the recent progress contributions obtained using monkey models of HIV infection of the CNS, neuropathogenesis and SIV encephalitis (SIVE), with an emphasis on pharmacologic therapies and dependable markers that predict development of CNS AIDS.

Identification of placental genes linked to selective intrauterine growth restriction (IUGR) in dichorionic twin pregnancies: gene expression profiling study

A linkage of dichorionic (DC) twin pregnancies with selective intrauterine growth restriction (IUGR) to alterations in placental gene expression is unclear. The aim of the study was to identify placental genes related to hypoxia, adipogenesis and human growth which may contribute to IUGR development. The study group (IUGR/AGA) comprised dichorionic (DC) twin pregnancies, where the weight of the twins differed by > 15%; in addition, one twin was small for gestational age (< 10th percentile-SGA) (IUGR) while the other was appropriate for gestational age (> 10th percentile-AGA). In the control group (AGA/AGA), both fetuses were AGA and their weights differed by < 15%. In the first step (selection), placental expression of 260 genes was analysed by commercial PCR profiler array or qPCR primer assay between six pairs of IUGR/AGA twins. In the second stage (verification), the expression of 20 genes with fold change (FC) > 1.5 selected from the first stage was investigated for 75 DC pregnancies: 23 IUGR/AGA vs. 52 AGA/AGA. The expression of Angiopoetin 2, Leptin and Kruppel-like factor 4 was significantly higher, and Glis Family Zinc Finger 3 was lower, in placentas of SGA fetuses (FC = 3.3; 4.4; 1.6; and - 1.8, respectively; p < 0.05). The dysregulation of gene expression related to angiogenesis and growth factors in placentas of twins born from IUGR/AGA pregnancies suggest that these alternations might represent biological fetal adaptation to the uteral condition. Moreover, DC twin pregnancies may be a good model to identify the differences in placental gene expression between SGA and AGA fetuses.