Alteration of brain network topology in HIV-associated neurocognitive disorder: A novel functional connectivity perspective

Multimodal Approach to Neurocognitive Function in People Living with HIV in the cART Era: A Comprehensive Review

Combination antiretroviral treatment (cART) has revolutionized the management of human immunodeficiency virus (HIV) and has markedly improved the disease burden and life expectancy of people living with HIV. HIV enters the central nervous system (CNS) early in the course of infection, establishes latency, and produces a pro-inflammatory milieu that may affect cognitive functions, even in the cART era. Whereas severe forms of neurocognitive impairment (NCI) such as HIV-associated dementia have declined over the last decades, milder forms have become more prevalent, are commonly multifactorial, and are associated with comorbidity burdens, mental health, cART neurotoxicity, and ageing. Since 2007, the Frascati criteria have been used to characterize and classify HIV-associated neurocognitive disorders (HAND) into three stages, namely asymptomatic neurocognitive impairment (ANI), mild neurocognitive disorder (MND), and HIV-associated dementia (HAD). These criteria are based on a comprehensive neuropsychological assessment that presupposes the availability of validated, demographically adjusted, and normative population data. Novel neuroimaging modalities and biomarkers have been proposed in order to complement NCI assessments, elucidate neuropathogenic mechanisms, and support HIV-associated NCI diagnosis, monitoring, and prognosis. By integrating neuropsychological assessments with biomarkers and neuroimaging into a holistic care approach, clinicians can enhance diagnostic accuracy, prognosis, and patient outcomes. This review interrogates the value of these modes of assessment and proposes a unified approach to NCI diagnosis.

Altered large-scale brain network interactions associated with HIV infection and error processing

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

Structural network alterations induced by ART-naive and ART-treated subjects infected with HIV

OBJECTIVE

To investigate how the structural connectivity altered in combined antiretroviral therapy-treated (cART+) HIV patients and cART-naive (cART-) HIV patients by conducting Network analysis of Diffusion Tensor Imaging (DTI) data.

METHODS

We enrolled 22 cART-, 23 cART+ and 28 normal controls (NC) in our current study. Firstly, the DTI imaging data pre-processing was conducted and the asymmetric 90 × 90 matrix for each participant from their DTI data was obtained with the use of PANDA. Then, we applied a graph-theoretical network analysis toolkit, GRETNA v2.0, to calculate metrics such as small-"worldness," characteristic path length, clustering coefficient, global efficiency, local efficiency, and nodal "betweenness". Finally, we took comparisons among the three groups to investigate topological alterations.

RESULTS

Results (1) the regional characteristics (nodal efficiency) were altered in cART- and cART+ patients predominantly in the frontal cortical regions; (2) changes in various network properties in cART+treat and cART-patients were associated with the performance of behavior functions; (3) Hubs redistributed in HIV subjects especially in cART+ patients.

CONCLUSION

The regional characteristics (nodal efficiency) were altered in cART- and cART+ patients predominantly in the frontal cortical region, and changes in various network properties in cART- and cART+ patients were associated with the performance of behavior functions. In addition, Hubs redistributed in HIV subjects especially in cART+ patients.

Rich-Club Analysis of Structural Brain Network Alterations in HIV Positive Patients With Fully Suppressed Plasma Viral Loads

Objective

Even with successful combination antiretroviral therapy (cART), patients with human immunodeficiency virus positive (HIV+) continue to present structural alterations and neuropsychological impairments. The purpose of this study is to investigate structural brain connectivity alterations and identify the hub regions in HIV+ patients with fully suppressed plasma viral loads.

Methods

In this study, we compared the brain structural connectivity in 48 patients with HIV+ treated with a combination of antiretroviral therapy and 48 healthy controls, using diffusion tensor imaging. Further comparisons were made in 24 patients with asymptomatic neurocognitive impairment (ANI) and 24 individuals with non-HIV-associated neurocognitive disorders forming a subset of HIV+ patients. The graph theory model was used to establish the topological metrics. Rich-club analysis was used to identify hub nodes across groups and abnormal rich-club connections. Correlations of connectivity metrics with cognitive performance and clinical variables were investigated as well.

Results

At the regional level, HIV+ patients demonstrated lower degree centrality (DC), betweenness centrality (BC), and nodal efficiency (NE) at the occipital lobe and the limbic cortex; and increased BC and nodal cluster coefficient (NCC) in the occipital lobe, the frontal lobe, the insula, and the thalamus. The ANI group demonstrated a significant reduction in the DC, NCC, and NE in widespread brain regions encompassing the occipital lobe, the frontal lobe, the temporal pole, and the limbic system. These results did not survive the Bonferroni correction. HIV+ patients and the ANI group had similar hub nodes that were mainly located in the occipital lobe and subcortical regions. The abnormal connections were mainly located in the occipital lobe in the HIV+ group and in the parietal lobe in the ANI group. The BC in the calcarine fissure was positively correlated with complex motor skills. The disease course was negatively correlated with NE in the middle occipital gyrus.

Conclusion

The results suggest that the occipital lobe and the subcortical regions may be important in structural connectivity alterations and cognitive impairment. Rich-club analysis may contribute to our understanding of the neuropathology of HIV-associated neurocognitive disorders.

Human immunodeficiency virus-related decreases in corpus callosal integrity and corresponding increases in functional connectivity

People living with human immunodeficiency virus (PLWH) often have neurocognitive impairment. However, findings on HIV-related differences in brain network function underlying these impairments are inconsistent. One principle frequently absent from these reports is that brain function is largely emergent from brain structure. PLWH commonly have degraded white matter; we hypothesized that functional communities connected by degraded white matter tracts would show abnormal functional connectivity. We measured white matter integrity in 69 PLWH and 67 controls using fractional anisotropy (FA) in 24 intracerebral white matter tracts. Then, among tracts with degraded FA, we identified gray matter regions connected to these tracts and measured their functional connectivity during rest. Finally, we identified cognitive impairment related to these structural and functional connectivity systems. We found HIV-related decreased FA in the corpus callosum body (CCb), which coordinates activity between the left and right hemispheres, and corresponding increases in functional connectivity. Finally, we found that individuals with impaired cognitive functioning have lower CCb FA and higher CCb functional connectivity. This result clarifies the functional relevance of the corpus callosum in HIV and provides a framework in which abnormal brain function can be understood in the context of abnormal brain structure, which may both contribute to cognitive impairment.

MRI imaging features of HIV-related central nervous system diseases: diagnosis by pattern recognition in daily practice

With the advent of antiretroviral therapy (ART), the prognosis of people infected with human immunodeficiency virus (HIV) has improved, and the frequency of HIV-related central nervous system (CNS) diseases has decreased. Nevertheless, mortality from HIV-related CNS diseases, including those associated with ART (e.g., immune reconstitution inflammatory syndrome) remains significant. Magnetic resonance imaging (MRI) can improve the outlook for people with HIV through early diagnosis and prompt treatment. For example, HIV encephalopathy shows a diffuse bilateral pattern, whereas progressive multifocal leukoencephalopathy, HIV-related primary CNS lymphoma, and CNS toxoplasmosis show focal patterns on MRI. Among the other diseases caused by opportunistic infections, CNS cryptococcosis and CNS tuberculosis have extremely poor prognoses unless diagnosed early. Immune reconstitution inflammatory syndrome shows distinct MRI findings from the offending opportunistic infections. Although distinguishing between HIV-related CNS diseases based on imaging alone is difficult, in this review, we discuss how pattern recognition approaches can contribute to their early differentiation.

Functional brain network reorganization in HIV infection

BACKGROUND AND PURPOSE

To investigate the reorganization of the central nervous system provided by resting state-functional MRI (rs-fMRI), graph-theoretical analysis, and a newly developed functional brain network disruption index in patients with human immunodeficiency virus (HIV) infection.

METHODS

Forty HIV-positive patients without neurological impairment and 20 age- and sex-matched healthy controls underwent rs-fMRI at 3T; blood sampling was obtained the same day to evaluate biochemical variables (absolute, relative, and nadir CD4 T-lymphocytes value and plasmatic HIV-RNA). From fMRI data, disruption indices, as well as global and local graph theoretical measures, were estimated and examined for group differences (HIV vs. controls) as well as for associations with biochemical variables (HIV only). Finally, all data (global and local graph-theoretical measures, disruption indices, and biochemical variables) were tested for putative differences across three patient groups based on the duration of combined antiretroviral therapy (cART).

RESULTS

Brain function of HIV patients appeared to be deeply reorganized as compared to normal controls. The disruption index showed significant negative association with relative CD4 values, and a positive significant association between plasmatic HIV-RNA and local graph-theoretical metrics in the left lingual gyrus and the right lobule IV and V of right cerebellar hemisphere was also observed. Finally, a differential distribution of HIV clinical biomarkers and several brain metrics was observed across cART duration groups.

CONCLUSION

Our study demonstrates that rs-fMRI combined with advanced graph theoretical analysis and disruption indices is able to detect early and subtle functional changes of brain networks in HIV patients.

Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data

A key challenge to gaining insight into complex systems is inferring nonlinear causal directional relations from observational time-series data. Specifically, estimating causal relationships between interacting components in large systems with only short recordings over few temporal observations remains an important, yet unresolved problem. Here, we introduce large-scale nonlinear Granger causality (lsNGC) which facilitates conditional Granger causality between two multivariate time series conditioned on a large number of confounding time series with a small number of observations. By modeling interactions with nonlinear state-space transformations from limited observational data, lsNGC identifies casual relations with no explicit a priori assumptions on functional interdependence between component time series in a computationally efficient manner. Additionally, our method provides a mathematical formulation revealing statistical significance of inferred causal relations. We extensively study the ability of lsNGC in inferring directed relations from two-node to thirty-four node chaotic time-series systems. Our results suggest that lsNGC captures meaningful interactions from limited observational data, where it performs favorably when compared to traditionally used methods. Finally, we demonstrate the applicability of lsNGC to estimating causality in large, real-world systems by inferring directional nonlinear, causal relationships among a large number of relatively short time series acquired from functional Magnetic Resonance Imaging (fMRI) data of the human brain.

Atypical Resting-State Functional Connectivity Dynamics Correlate With Early Cognitive Dysfunction in HIV Infection

Purpose: Previous studies have shown that HIV affects striato-cortical regions, leading to persisting cognitive impairment in 30-70% of the infected individuals despite combination antiretroviral therapy. This study aimed to investigate brain functional dynamics whose deficits might link to early cognitive decline or immunologic deterioration. Methods: We applied sliding windows and K-means clustering to fMRI data (HIV patients with asymptomatic neurocognitive impairment and controls) to construct dynamic resting-state functional connectivity (RSFC) maps and identify states of their reoccurrences. The average and variability of dynamic RSFC, and the dwelling time and state transitioning of each state were evaluated. Results: HIV patients demonstrated greater variability in RSFC between the left pallidum and regions of right pre-central and post-central gyri, and between the right supramarginal gyrus and regions of the right putamen and left pallidum. Greater variability was also found in the frontal RSFC of pars orbitalis of the left inferior frontal gyrus and right superior frontal gyrus (medial). While deficits in learning and memory recall of HIV patients related to greater striato-sensorimotor variability, deficits in attention and working memory were associated with greater frontal variability. Greater striato-parietal variability presented a strong link with immunologic function (CD4+/CD8+ ratio). Furthermore, HIV-infected patients exhibited longer time and reduced transitioning in states typified by weaker connectivity in specific networks. CD4+T-cell counts of the HIV-patients were related to reduced state transitioning. Conclusion: Our findings suggest that HIV alters brain functional connectivity dynamics, which may underlie early cognitive impairment. These findings provide novel insights into our understanding of HIV pathology, complementing the existing knowledge.

Synergistic effects of HIV and marijuana use on functional brain network organization

HIV is associated with disruptions in cognition and brain function. Marijuana use is highly prevalent in HIV but its effects on resting brain function in HIV are unknown. Brain function can be characterized by brain activity that is correlated between regions over time, called functional connectivity. Neuropsychiatric disorders are increasingly being characterized by disruptions in such connectivity. We examined the synergistic effects of HIV and marijuana use on functional whole-brain network organization during resting state. Our sample included 78 adults who differed on HIV and marijuana status (19 with co-occurring HIV and marijuana use, 20 HIV-only, 17 marijuana-only, and 22 controls). We examined differences in local and long-range brain network organization using eight graph theoretical metrics: transitivity, local efficiency, within-module degree, modularity, global efficiency, strength, betweenness, and participation coefficient. Local and long-range connectivity were similar between the co-occurring HIV and marijuana use and control groups. In contrast, the HIV-only and marijuana-only groups were both associated with disruptions in brain network organization. These results suggest that marijuana use in HIV may normalize disruptions in brain network organization observed in persons with HIV. However, future work is needed to determine whether this normalization is suggestive of a beneficial or detrimental effect of marijuana on cognitive functioning in HIV.

Pathomechanisms of HIV-Associated Cerebral Small Vessel Disease: A Comprehensive Clinical and Neuroimaging Protocol and Analysis Pipeline

Rationale: We provide an in-depth description of a comprehensive clinical, immunological, and neuroimaging study that includes a full image processing pipeline. This approach, although implemented in HIV infected individuals, can be used in the general population to assess cerebrovascular health.

Aims: In this longitudinal study, we seek to determine the effects of neuroinflammation due to HIV-1 infection on the pathomechanisms of cerebral small vessel disease (CSVD). The study focuses on the interaction of activated platelets, pro-inflammatory monocytes and endothelial cells and their impact on the neurovascular unit. The effects on the neurovascular unit are evaluated by a novel combination of imaging biomarkers.

Sample Size: We will enroll 110 HIV-infected individuals on stable combination anti-retroviral therapy for at least three months and an equal number of age-matched controls. We anticipate a drop-out rate of 20%.

Methods and Design: Subjects are followed for three years and evaluated by flow cytometric analysis of whole blood (to measure platelet activation, platelet monocyte complexes, and markers of monocyte activation), neuropsychological testing, and brain MRI at the baseline, 18- and 36-month time points. MRI imaging follows the recommended clinical small vessel imaging standards and adds several advanced sequences to obtain quantitative assessments of brain tissues including white matter microstructure, tissue susceptibility, and blood perfusion.

Discussion: The study provides further understanding of the underlying mechanisms of CSVD in chronic inflammatory disorders such as HIV infection. The longitudinal study design and comprehensive approach allows the investigation of quantitative changes in imaging metrics and their impact on cognitive performance.

Whole-brain computational modeling reveals disruption of microscale brain dynamics in HIV infected individuals

MRI‐based neuroimaging techniques have been used to investigate brain injury associated with HIV‐infection. Whole‐brain cortical mean‐field dynamic modeling provides a way to integrate structural and functional imaging outcomes, allowing investigation of microscale brain dynamics. In this study, we adopted the relaxed mean‐field dynamic modeling to investigate structural and functional connectivity in 42 HIV‐infected subjects before and after 12‐week of combination antiretroviral therapy (cART) and compared them with 46 age‐matched healthy subjects. Microscale brain dynamics were modeled by a set of parameters including two region‐specific microscale brain properties, recurrent connection strengths, and subcortical inputs. We also analyzed the relationship between the model parameters (i.e., the recurrent connection and subcortical inputs) and functional network topological characterizations, including smallworldness, clustering coefficient, and network efficiency. The results show that untreated HIV‐infected individuals have disrupted local brain dynamics that in part correlate with network topological measurements. Notably, after 12 weeks of cART, both the microscale brain dynamics and the network topological measurements improved and were closer to those in the healthy brain. This was also associated with improved cognitive performance, suggesting that improvement in local brain dynamics translates into clinical improvement.

Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19

Coronavirus disease 2019 is a newly emerging infectious disease currently spreading across the world. It is caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike (S) protein of SARS-CoV-2, which plays a key role in the receptor recognition and cell membrane fusion process, is composed of two subunits, S1 and S2. The S1 subunit contains a receptor-binding domain that recognizes and binds to the host receptor angiotensin-converting enzyme 2, while the S2 subunit mediates viral cell membrane fusion by forming a six-helical bundle via the two-heptad repeat domain. In this review, we highlight recent research advance in the structure, function and development of antivirus drugs targeting the S protein.

Altered Brain Function in Young HIV Patients with Syphilis Infection: A Voxel-Wise Degree Centrality Analysis

Objective

This study assessed the possible effect of syphilis co-infection in the brain function in young HIV patients by using voxel-wise degree centrality (DC) analysis.

Methods

Forty-four syphilis-co-infected HIV patients (HIV+/syphilis+), 45 HIV patients without syphilis history (HIV+/syphilis-) and 43 matched healthy controls (HC) underwent resting-state fMRI examinations. Laboratory tests and a battery of neuropsychological tests were performed before each MRI examination. One-way ANOVA was used to compare the differences of DC among the three groups. The correlations between MRI metrics and laboratory/neuropsychological tests in each patient's group were performed by Pearson correlation analysis.

Results

Compared with HIV+/syphilis-, worse performance in complex motor skills was found in HIV+/syphilis+. Compared with HC, HIV+/syphilis+ and HIV+/syphilis- groups showed attenuated DC in the right orbital frontal cortex and increased DC in the left parietal/temporal cortex. Besides, we also found increased DC in the left inferior frontal cortex and bilateral posterior cingulated cortex/precuneus in HIV+/syphilis+ compared with HC. Moreover, compared with HIV+/syphilis-, HIV+/syphilis+ displayed decreased DC in the left middle occipital cortex. Additionally, in HIV+/syphilis+ group, the mean z value of DC was correlated to the CD4+ cell counts and the learning and delayed recall score.

Conclusion

Syphilis co-infection might be related to more brain functional reorganization in young HIV patients which could be reflected by DC value.

Detecting cognitive impairment in HIV-infected individuals using mutual connectivity analysis of resting state functional MRI

It is estimated that more than 50% of the individuals affected with Human Immunodeficiency Virus (HIV) present deficits in multiple cognitive domains, collectively known as HIV-associated neurocognitive disorder (HAND). Early stages of brain injury may be clinically silent but potentially measurable via neuroimaging. A total of 40 subjects (20 HIV positive and 20 age-matched controls) volunteered for the study. All subjects underwent a standard battery of neuropsychological tests used for the clinical diagnosis of HAND. Fourteen HIV+ and five healthy subjects showed signs of neurological impairment. Connectivity was computed using mutual connectivity analysis (MCA) with generalized radial basis function neural network, a framework for quantifying non-linear connectivity as well as conventional correlation from 160 regional time-series that were extracted based on the Dosenbach (DOS) atlas. We subsequently applied graph theoretic as well as network analysis approaches for characterizing the connectivity matrices obtained and localizing between-group differences. We focused on trying to detect cognitive impairment using the subset of 29 (14 subjects with HAND and 15 cognitively normal controls) subjects. For the global analysis, significant differences (p < 0.05) were seen in the variance in degree, modularity and Smallworldness. Regional analysis revealed changes occurring mainly in portions of the lateral occipital cortex and the cingulate cortex. Furthermore, using Network Based Statistics (NBS), we uncovered an affected sub-network of 19 nodes comprising predominantly of regions of the default mode network. Similar analysis using the conventional correlation method revealed no significant results at a global scale, while regional analysis shows some differences spread across resting state networks. These results suggest that there is a subtle reorganization occurring in the topology of brain networks in HAND, which can be captured using improved connectivity analysis.

A multivoxel pattern analysis framework with mutual connectivity analysis investigating changes in resting state connectivity in patients with HIV associated neurocognitve disorder

Functional MRI (fMRI) quantifies brain activity non-invasively by measuring the blood oxygen level dependent (BOLD) response to neuronal activity. It was recently demonstrated, on realistic fMRI simulations, that nonlinear connectivity approaches, such as Mutual Connectivity Analysis with Local Models (MCA-LM), are better suited for extracting connectivity measures than conventional techniques of cross-correlating time-series pairs. In this work, we investigate the application of MCA-LM in extracting meaningful connectivity measures aiding in distinguishing healthy controls from individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND), which occurs as a result of HIV infection of the central nervous system. The pairwise connectivity measures provide a high-dimensional representation of connectivity profiles for subjects and are used as features for classification. We adopt feature selection (FS) techniques reducing the number of redundant and noisy features, while also controlling the complexity of the classifiers. We investigate three FS techniques: 1) Kendall's τ, 2) Information Gain Attribute selection 3) ReliefF and two classifiers:1) AdaBoost and 2) Random Forests. Our results demonstrate that MCA-LM consistently outperforms correlation in terms of Area under the Receiver Operating Characteristic Curve and accuracy. Improved performance with MCA-LM suggests that such a nonlinear approach is better at capturing meaningful connectivity relationships between brain regions. This demonstrates potential for developing novel neuroimaging-derived biomarkers for HAND. Furthermore, FS helps identify connections between anatomical regions that are affected by HAND. In this work, we show that the regions of the basal ganglia and frontal cortex, which are known to be affected by HAND according to current literature, are identified as most discriminative.

Automated diagnosis of HIV-associated neurocognitive disorders using large-scale Granger causality analysis of resting-state functional MRI

HIV-associated neurocognitive disorders (HAND) represent an important source of neurologic complications in individuals with HIV. The dynamic, often subclinical, course of HAND has rendered diagnosis, which currently depends on neuropsychometric (NP) evaluation, a challenge for clinicians. Here, we present evidence that functional brain connectivity, derived by large-scale Granger causality (lsGC) analysis of resting-state functional MRI (rs-fMRI) time-series, represents a potential biomarker to address this critical diagnostic need. Brain graph properties were used as features in machine learning tasks to 1) classify individuals as HIV⁺ or HIV^- and 2) to predict overall cognitive performance, as assessed by NP scores, in a 22-subject (13 HIV^-, 9 HIV⁺) cohort. Over nearly all seven brain parcellation templates considered, support vector machine (SVM) classifiers based on lsGC-derived brain graph features significantly outperformed those based on conventional Pearson correlation (PC)-derived features (p<0.05, Bonferroni-corrected). In a second task for which the objective was to predict the overall NP score of each subject, the lsGC-based SVM regressors consistently outperformed the PC-based regressors (p<0.05, Bonferroni-corrected) on nearly all templates. With the widely used Automated Anatomical Labeling (AAL90) template, it was determined that the brain regions that figured most strongly in the SVM classifiers included those of the default mode network (posterior cingulate cortex, angular gyrus) and basal ganglia (caudate nucleus), dysfunction in both of which have been observed in previous structural and functional analyses of HAND.

Diagnostic and prognostic biomarkers for HAND

In 2007, the nosology for HIV-1-associated neurocognitive disorders (HAND) was updated to a primarily neurocognitive disorder. However, currently available diagnostic tools lack the sensitivity and specificity needed for an accurate diagnosis for HAND. Scientists and clinicians, therefore, have been on a quest for an innovative biomarker to diagnose (i.e., diagnostic biomarker) and/or predict (i.e., prognostic biomarker) the progression of HAND in the post-combination antiretroviral therapy (cART) era. The present review examined the utility and challenges of four proposed biomarkers, including neurofilament light (NFL) chain concentration, amyloid (i.e., sAPPα, sAPPβ, amyloid β) and tau proteins (i.e., total tau, phosphorylated tau), resting-state functional magnetic resonance imaging (fMRI), and prepulse inhibition (PPI). Although significant genotypic differences have been observed in NFL chain concentration, sAPPα, sAPPβ, amyloid β, total tau, phosphorylated tau, and resting-state fMRI, inconsistencies and/or assessment limitations (e.g., invasive procedures, lack of disease specificity, cost) challenge their utility as a diagnostic and/or prognostic biomarker for milder forms of neurocognitive impairment (NCI) in the post-cART era. However, critical evaluation of the literature supports the utility of PPI as a powerful diagnostic biomarker with high accuracy (i.e., 86.7-97.1%), sensitivity (i.e., 89.3-100%), and specificity (i.e., 79.5-94.1%). Additionally, the inclusion of multiple CSF and/or plasma markers, rather than a single protein, may provide a more sensitive diagnostic biomarker for HAND; however, a pressing need for additional research remains. Most notably, PPI may serve as a prognostic biomarker for milder forms of NCI, evidenced by its ability to predict later NCI in higher-order cognitive domains with regression coefficients (i.e., r) greater than 0.8. Thus, PPI heralds an opportunity for the development of a brief, noninvasive diagnostic and promising prognostic biomarker for milder forms of NCI in the post-cART era.

Tenofovir disoproxil fumarate induces pheochromocytoma cells apoptosis

Despite the triumph of highly active antiretroviral therapy (HAART) in anti-HIV infection, more than half of the HIV infection individuals receiving antiretroviral therapy acquire HIV-associated neurocognitive disorder (HAND). Previously researches had reported that the HAART neurotoxicity is implicated in HAND-related morbidity. The molecular mechanism of HAND is not clear. Tenofovir disoproxil fumarate (TDF) is a novel nucleotide reverse transcriptase inhibitor (NRTI), which was recommended as first-line therapeutic schedule for free AIDS antiviral drugs. Whether the neurotoxicity of TDF is associated with HAND is not well known. In this study, the cell viability of TDF-treated pheochromocytoma cells (PC-12) line was detected using MTT assay, while apoptosis was evaluated by Hoechst 33342 staining, TUNEL assay, as well as flow cytometry. In addition, the level of reactive oxygen species and BAX protein expression were evaluated using DCFH-DA staining and western blotting. The results showed that the proliferation of PC-12 cells was significantly inhibited by TDF. The morphological assay, TUNEL assay and flow cytometry showed that TDF efficiently triggered apoptosis in PC-12 cells. The reactive oxygen species levels were BAX expression was markedly up-regulated in PC-12 cells after treatment with TDF. These findings indicated that TDF may induce PC-12 cell apoptosis. TDF has neural toxicity effect that is relevant to the cell apoptosis, which may be related to the increasing prevalence of HAND.

Low-frequency fluctuation characteristics in rhesus macaques with SIV infection: a resting-state fMRI study

Simian immunodeficiency virus (SIV)-infected macaque is a widely used model to study human immunodeficiency virus. The purpose of the study is to discover the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) changes in SIV-infected macaques. Seven rhesus macaques were involved in the longitudinal MRI scans: (1) baseline (healthy state); (2) SIV infection stage (12 weeks after SIV inoculation). ALFF and fALFF were subsequently computed and compared to ascertain the changes caused by SIV infection. Whole-brain correlation analysis was further used to explore the possible associations between ALFF/fALFF values and immune status parameters (CD4+ T cell counts, CD4/CD8 ratio and virus load). Compared with the baseline, macaques in SIV infection stage displayed strengthened ALFF values in left precuneus, postcentral gyrus, and temporal gyrus, and weakened ALFF values in orbital gyrus and inferior temporal gyrus. Meanwhile, increased fALFF values were found in left superior frontal gyrus, right precentral gyrus, and superior temporal gyrus, while decreased fALFF values existed in left hippocampus, left caudate, and right inferior frontal gyrus. Furthermore, ALFF and fALFF values in several brain regions showed significant relationships with CD4+ T cell counts, CD4/CD8 ratio, and plasma virus load. Our findings could promote the understanding of neuroAIDS caused by HIV infection, which may provide supplementary evidences for the future therapy study in SIV model.

Changes in resting-state functional brain activity are associated with waning cognitive functions in HIV-infected children

Delayed brain development in perinatally HIV-infected children may affect the functional brain activity and subsequently cognitive function. The current study evaluated the functional brain activity in HIV-infected children by quantifying the amplitude of low frequency fluctuations (ALFF) and functional connectivity (FC). Additionally, correlation of ALFF and FC with cognitive measures was performed. Twenty-six HIV-infected children and 20 control children underwent neuropsychological (NP) assessment and resting-state functional magnetic resonance imaging (rs-fMRI). ALFF and FC maps were generated and group differences were analyzed using two-sample t-test. Furthermore, ALFF and FC showing significant group differences were correlated with NP scores using Pearson's correlation. Significantly lower ALFF in the left middle temporal gyrus, precentral and post central gyrus was observed in HIV-infected children compared to controls. FC was significantly reduced in the right inferior parietal, vermis, middle temporal and left postcentral regions, and significantly increased in the right precuneus, superior parietal and left middle frontal regions in HIV-infected children as compared to control. HIV-infected children showed significantly lower NP scores in various domains including closure, exclusion, memory, verbal meaning, quantity and hidden figure than controls. These waning cognitive functions were significantly associated with changes in ALFF and FC in HIV-infected children. The findings suggest that abnormal ALFF and FC may responsible for cognitive deficits in HIV-infected children. ALFF and FC in association with cognitive evaluation may provide a clinical biomarker to evaluate functional brain activity and to plan neurocognitive intervention in HIV-infected children undergoing standard treatment.

Identification and functional characterization of HIV-associated neurocognitive disorders with large-scale Granger causality analysis on resting-state functional MRI

Resting-state functional MRI (rs-fMRI), coupled with advanced multivariate time-series analysis methods such as Granger causality, is a promising tool for the development of novel functional connectivity biomarkers of neurologic and psychiatric disease. Recently large-scale Granger causality (lsGC) has been proposed as an alternative to conventional Granger causality (cGC) that extends the scope of robust Granger causal analyses to high-dimensional systems such as the human brain. In this study, lsGC and cGC were comparatively evaluated on their ability to capture neurologic damage associated with HIV-associated neurocognitive disorders (HAND). Functional brain network models were constructed from rs-fMRI data collected from a cohort of HIV⁺ and HIV ^- subjects. Graph theoretic properties of the resulting networks were then used to train a support vector machine (SVM) model to predict clinically relevant parameters, such as HIV status and neuropsychometric (NP) scores. For the HIV^{+ /-} classification task, lsGC, which yielded a peak area under the receiver operating characteristic curve (AUC) of 0.83, significantly outperformed cGC, which yielded a peak AUC of 0.61, at all parameter settings tested. For the NP score regression task, lsGC, with a minimum mean squared error (MSE) of 0.75, significantly outperformed cGC, with a minimum MSE of 0.84 (p < 0.001, one-tailed paired t-test). These results show that, at optimal parameter settings, lsGC is better able to capture functional brain connectivity correlates of HAND than cGC. However, given the substantial variation in the performance of the two methods at different parameter settings, particularly for the regression task, improved parameter selection criteria are necessary and constitute an area for future research.