Structural and Functional Brain Abnormalities in Human Immunodeficiency Virus Disease Revealed by Multimodal Magnetic Resonance Imaging Fusion: Association With Cognitive Function

Matrix-Variate Regression for Sparse, Low-Rank Estimation of Brain Connectivities Associated With a Clinical Outcome

OBJECTIVE

We address the problem of finding brain connectivities that are associated with a clinical outcome or phenotype.

METHODS

The proposed framework regresses a (scalar) clinical outcome on matrix-variate predictors which arise in the form of brain connectivity matrices. For example, in a large cohort of subjects we estimate those regions of functional connectivities that are associated with neurocognitive scores. We approach this high-dimensional yet highly structured estimation problem by formulating a regularized estimation process that results in a low-rank coefficient matrix having a sparse set of nonzero entries which represent regions of biologically relevant connectivities. In contrast to the recent literature on estimating a sparse, low-rank matrix from a single noisy observation, our scalar-on-matrix regression framework produces a data-driven extraction of structures that are associated with a clinical response. The method, called Sparsity Inducing Nuclear-Norm Estimator (SpINNEr), simultaneously constrains the regression coefficient matrix in two ways: a nuclear norm penalty encourages low-rank structure while an l1 norm encourages entry-wise sparsity.

RESULTS

Our simulations show that SpINNEr outperforms other methods in estimation accuracy when the response-related entries (representing the brain's functional connectivity) are arranged in well-connected communities. SpINNEr is applied to investigate associations between HIV-related outcomes and functional connectivity in the human brain.

CONCLUSION AND SIGNIFICANCE

Overall, this work demonstrates the potential of SpINNEr to recover sparse and low-rank estimates under scalar-on-matrix regression framework.

Data-driven multimodal fusion: approaches and applications in psychiatric research

In the era of big data, where vast amounts of information are being generated and collected at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal fusion methods. These methods aim to integrate diverse neuroimaging perspectives to extract meaningful insights and attain a more comprehensive understanding of complex psychiatric disorders. However, analyzing each modality separately may only reveal partial insights or miss out on important correlations between different types of data. This is where data-driven multi-modal fusion techniques come into play. By combining information from multiple modalities in a synergistic manner, these methods enable us to uncover hidden patterns and relationships that would otherwise remain unnoticed. In this paper, we present an extensive overview of data-driven multimodal fusion approaches with or without prior information, with specific emphasis on canonical correlation analysis and independent component analysis. The applications of such fusion methods are wide-ranging and allow us to incorporate multiple factors such as genetics, environment, cognition, and treatment outcomes across various brain disorders. After summarizing the diverse neuropsychiatric magnetic resonance imaging fusion applications, we further discuss the emerging neuroimaging analyzing trends in big data, such as N-way multimodal fusion, deep learning approaches, and clinical translation. Overall, multimodal fusion emerges as an imperative approach providing valuable insights into the underlying neural basis of mental disorders, which can uncover subtle abnormalities or potential biomarkers that may benefit targeted treatments and personalized medical interventions.

Probing bundle-wise abnormalities in patients infected with human immunodeficiency virus using fixel-based analysis: new insights into neurocognitive impairments

BACKGROUND

Changes in white matter (WM) underlie the neurocognitive damages induced by a human immunodeficiency virus (HIV) infection. This study aimed to examine using a bundle-associated fixel-based analysis (FBA) pipeline for investigating the microstructural and macrostructural alterations in the WM of the brain of HIV patients.

METHODS

This study collected 93 HIV infected patients and 45 age/education/handedness matched healthy controls (HCs) at the Beijing Youan Hospital between January 1, 2016 and December 30, 2016.All HIV patients underwent neurocognitive evaluation and laboratory testing followed by magnetic resonance imaging (MRI) scanning. In order to detect the bundle-wise WM abnormalities accurately, a specific WM bundle template with 56 tracts of interest was firstly generated by an automated fiber clustering method using a subset of subjects. Fixel-based analysis was used to investigate bundle-wise differences between HIV patients and HCs in three perspectives: fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC). The between-group differences were detected by a two-sample t -test with the false discovery rate (FDR) correction ( P <0.05). Furthermore, the covarying relationship in FD, FC and FDC between any pair of bundles was also accessed by the constructed covariance networks, which was subsequently compared between HIV and HCs via permutation t -tests. The correlations between abnormal WM metrics and the cognitive functions of HIV patients were explored via partial correlation analysis after controlling age and gender.

RESULTS

Among FD, FC and FDC, FD was the only metric that showed significant bundle-wise alterations in HIV patients compared to HCs. Increased FD values were observed in the bilateral fronto pontine tract, corona radiata frontal, left arcuate fasciculus, left corona radiata parietal, left superior longitudinal fasciculus III, and right superficial frontal parietal (SFP) (all FDR P <0.05). In bundle-wise covariance network, HIV patients displayed decreased FD and increased FC covarying patterns in comparison to HC ( P <0.05) , especially between associated pathways. Finally, the FCs of several tracts exhibited a significant correlation with language and attention-related functions.

CONCLUSIONS

Our study demonstrated the utility of FBA on detecting the WM alterations related to HIV infection. The bundle-wise FBA method provides a new perspective for investigating HIV-induced microstructural and macrostructural WM-related changes, which may help to understand cognitive dysfunction in HIV patients thoroughly.

Comparison of Resting State Functional Connectivity in Persons With and Without HIV: A Cross-sectional Study

BACKGROUND

This study examined the effects of human immunodeficiency virus (HIV) on resting state functional connectivity (RSFC) in a large cohort of people with HIV (PWH) and healthy controls without HIV (PWoH). Within PWH analyses focused on the effects of viral suppression and cognitive impairment on RSFC.

METHODS

A total of 316 PWH on stable combination antiretroviral therapy and 209 demographically matched PWoH were scanned at a single institution. Effects of the virus were examined by grouping PWH by detectable (viral load > 20 copies/mL; VLD) and undetectable (VLU) viral loads and as being cognitively impaired (CI) (Global Deficit Score ≥ 0.5) or cognitively normal (CN). Regression analysis, object oriented data analysis, and spring embedded graph models were applied to RSFC measures from 298 established brain regions of interest comprising 13 brain networks to examine group differences.

RESULTS

No significant RSFC differences were observed between PWH and PWoH. Within PWH, there were no significant differences in RSFC between VLD and VLU subgroups and CI and CN subgroups.

CONCLUSIONS

There were no significant effects of HIV on RSFC in our relatively large cohort of PWH and PWoH. Future studies could increase the sample size and combine with other imaging modalities.

A new perspective on HIV: effects of HIV on brain-heart axis

The human immunodeficiency virus (HIV) infection can cause damage to multiple systems within the body, and the interaction among these various organ systems means that pathological changes in one system can have repercussions on the functions of other systems. However, the current focus of treatment and research on HIV predominantly centers around individual systems without considering the comprehensive relationship among them. The central nervous system (CNS) and cardiovascular system play crucial roles in supporting human life, and their functions are closely intertwined. In this review, we examine the effects of HIV on the CNS, the resulting impact on the cardiovascular system, and the direct damage caused by HIV to the cardiovascular system to provide new perspectives on HIV treatment.

Imaging of Brain Structural and Functional Effects in People With Human Immunodeficiency Virus

Before the introduction of antiretroviral therapy, human immunodeficiency virus (HIV) infection was often accompanied by central nervous system (CNS) opportunistic infections and HIV encephalopathy marked by profound structural and functional alterations detectable with neuroimaging. Treatment with antiretroviral therapy nearly eliminated CNS opportunistic infections, while neuropsychiatric impairment and peripheral nerve and organ damage have persisted among virally suppressed people with HIV (PWH), suggesting ongoing brain injury. Neuroimaging research must use methods sensitive for detecting subtle HIV-associated brain structural and functional abnormalities, while allowing for adjustments for potential confounders, such as age, sex, substance use, hepatitis C coinfection, cardiovascular risk, and others. Here, we review existing and emerging neuroimaging tools that demonstrated promise in detecting markers of HIV-associated brain pathology and explore strategies to study the impact of potential confounding factors on these brain measures. We emphasize neuroimaging approaches that may be used in parallel to gather complementary information, allowing efficient detection and interpretation of altered brain structure and function associated with suboptimal clinical outcomes among virally suppressed PWH. We examine the advantages of each imaging modality and systematic approaches in study design and analysis. We also consider advantages of combining experimental and statistical control techniques to improve sensitivity and specificity of biotype identification and explore the costs and benefits of aggregating data from multiple studies to achieve larger sample sizes, enabling use of emerging methods for combining and analyzing large, multifaceted data sets. Many of the topics addressed in this article were discussed at the National Institute of Mental Health meeting "Biotypes of CNS Complications in People Living with HIV," held in October 2021, and are part of ongoing research initiatives to define the role of neuroimaging in emerging alternative approaches to identifying biotypes of CNS complications in PWH. An outcome of these considerations may be the development of a common neuroimaging protocol available for researchers to use in future studies examining neurological changes in the brains of PWH.

Differentiate preterm and term infant brains and characterize the corresponding biomarkers via DICCCOL-based multi-modality graph neural networks

Preterm birth is a worldwide problem that affects infants throughout their lives significantly. Therefore, differentiating brain disorders, and further identifying and characterizing the corresponding biomarkers are key issues to investigate the effects of preterm birth, which facilitates the interventions for neuroprotection and improves outcomes of prematurity. Until now, many efforts have been made to study the effects of preterm birth; however, most of the studies merely focus on either functional or structural perspective. In addition, an effective framework not only jointly studies the brain function and structure at a group-level, but also retains the individual differences among the subjects. In this study, a novel dense individualized and common connectivity-based cortical landmarks (DICCCOL)-based multi-modality graph neural networks (DM-GNN) framework is proposed to differentiate preterm and term infant brains and characterize the corresponding biomarkers. This framework adopts the DICCCOL system as the initialized graph node of GNN for each subject, utilizing both functional and structural profiles and effectively retaining the individual differences. To be specific, functional magnetic resonance imaging (fMRI) of the brain provides the features for the graph nodes, and brain fiber connectivity is utilized as the structural representation of the graph edges. Self-attention graph pooling (SAGPOOL)-based GNN is then applied to jointly study the function and structure of the brain and identify the biomarkers. Our results successfully demonstrate that the proposed framework can effectively differentiate the preterm and term infant brains. Furthermore, the self-attention-based mechanism can accurately calculate the attention score and recognize the most significant biomarkers. In this study, not only 87.6% classification accuracy is observed for the developing Human Connectome Project (dHCP) dataset, but also distinguishing features are explored and extracted. Our study provides a novel and uniform framework to differentiate brain disorders and characterize the corresponding biomarkers.

Cardiorespiratory Fitness Is Associated With Better White Matter Integrity in Persons Living With HIV

BACKGROUND

Despite improved survival rates, neurocognitive impairment persists in persons living with HIV (PLWH). An active lifestyle is linked to improved cognition among PLWH, yet the neural substrates remain unclear. Diffusion tensor imaging and diffusion basis spectrum imaging measure HIV-related changes in brain white matter integrity. We used these measures of structural brain integrity to assess white matter changes, physical fitness, and cognition in a cross-sectional study of PLWH.

METHODS

Forty-four virologically well-controlled PLWH were recruited (average age of 56 years, a median recent CD4+ count of 682 cells/mm3). Diffusion tensor imaging -derived fractional anisotropy (FA) and diffusion basis spectrum imaging-derived axonal density were calculated. Cardiorespiratory fitness [maximal volume of oxygen consumption (VO2 max)] was measured by performing indirect calorimetry during exercise to volitional exhaustion. Cardiovascular risk was assessed by the Framingham risk score. Neuropsychological performance (NP) testing evaluated learning, memory, psychomotor/processing speed, and executive function. Partial correlations assessed the relationships among cardiorespiratory fitness, neuroimaging, NP, and HIV clinical metrics (CD4+ count and time since diagnosis).

RESULTS

Higher VO2 max was associated with higher FA and higher axonal density in multiple white matter tracts, including the corticospinal tract and superior longitudinal fasciculus. Better NP in the motor/psychomotor domain was positively associated with FA and axonal density in diverse tracts including those associated with motor and visuospatial processing. However, higher VO2 max was not associated with NP or HIV clinical metrics.

CONCLUSIONS

An active lifestyle promoting cardiorespiratory fitness may lead to better white matter integrity and decreased susceptibility to cognitive decline in virologically well-controlled PLWH.

The impacts of HIV infection, age, and education on functional brain networks in adults with HIV

HIV-associated neurocognitive disorders (HAND) remain highly prevalent in people with HIV (PWH). Studies suggested that certain sociodemographic factors are associated with the risk of HAND in PWH. Here we investigated the impact of HIV infection and demographics on functional brain networks. One run of 8.5 min resting state functional MRI (fMRI) data was collected from 101 PWH (41-70 years old) and 40 demographically comparable controls. Functional connectivity (FC) was calculated using average wavelet coherence. The impact of demographic factors on FCs was investigated using canonical correlation analysis (CCA). Wavelet coherence analysis revealed a reduced within-network connectivity in the dorsal somatomotor network (dSMN), along with a reduced between-network connectivity between dSMN and medial temporal lobe (MTL) in PWH (compared to controls). Across all participants, CCA revealed that older age and HIV infection had negative impacts on network connectivity measures (mainly reduced within- and between-network FCs), whereas education had an opposite effect. In addition, being female at birth or a member of a minority ethnic/racial group was also associated with network disruptions. Our data suggested that advanced age and HIV infection are risk factors for functional brain network disruptions, whereas higher educational attainment was linked to better preserved functional network connectivity.

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.

Brain multimodal co-alterations related to delay discounting: a multimodal MRI fusion analysis in persons with and without cocaine use disorder

BACKGROUND

Delay discounting has been proposed as a behavioral marker of substance use disorders. Innovative analytic approaches that integrate information from multiple neuroimaging modalities can provide new insights into the complex effects of drug use on the brain. This study implemented a supervised multimodal fusion approach to reveal neural networks associated with delay discounting that distinguish persons with and without cocaine use disorder (CUD).

METHODS

Adults with (n = 35) and without (n = 37) CUD completed a magnetic resonance imaging (MRI) scan to acquire high-resolution anatomical, resting-state functional, and diffusion-weighted images. Pre-computed features from each data modality included whole-brain voxel-wise maps for gray matter volume, fractional anisotropy, and regional homogeneity, respectively. With delay discounting as the reference, multimodal canonical component analysis plus joint independent component analysis was used to identify co-alterations in brain structure and function.

RESULTS

The sample was 58% male and 78% African-American. As expected, participants with CUD had higher delay discounting compared to those without CUD. One joint component was identified that correlated with delay discounting across all modalities, involving regions in the thalamus, dorsal striatum, frontopolar cortex, occipital lobe, and corpus callosum. The components were negatively correlated with delay discounting, such that weaker loadings were associated with higher discounting. The component loadings were lower in persons with CUD, meaning the component was expressed less strongly.

CONCLUSIONS

Our findings reveal structural and functional co-alterations linked to delay discounting, particularly in brain regions involved in reward salience, executive control, and visual attention and connecting white matter tracts. Importantly, these multimodal networks were weaker in persons with CUD, indicating less cognitive control that may contribute to impulsive behaviors.

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

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.

Mechanisms of neuronal dysfunction in HIV-associated neurocognitive disorders

HIV-associated neurocognitive disorder (HAND) is characterized by cognitive and behavioral deficits in people living with HIV. HAND is still common in patients that take antiretroviral therapies, although they tend to present with less severe symptoms. The continued prevalence of HAND in treated patients is a major therapeutic challenge, as even minor cognitive impairment decreases patient’s quality of life. Therefore, modern HAND research aims to broaden our understanding of the mechanisms that drive cognitive impairment in people with HIV and identify promising molecular pathways and targets that could be exploited therapeutically. Recent studies suggest that HAND in treated patients is at least partially induced by subtle synaptodendritic damage and disruption of neuronal networks in brain areas that mediate learning, memory, and executive functions. Although the causes of subtle neuronal dysfunction are varied, reversing synaptodendritic damage in animal models restores cognitive function and thus highlights a promising therapeutic approach. In this review, we examine evidence of synaptodendritic damage and disrupted neuronal connectivity in HAND from clinical neuroimaging and neuropathology studies and discuss studies in HAND models that define structural and functional impairment of neurotransmission. Then, we report molecular pathways, mechanisms, and comorbidities involved in this neuronal dysfunction, discuss new approaches to reverse neuronal damage, and highlight current gaps in knowledge. Continued research on the manifestation and mechanisms of synaptic injury and network dysfunction in HAND patients and experimental models will be critical if we are to develop safe and effective therapies that reverse subtle neuropathology and cognitive impairment.