Machine Learning Approaches to Understand Cognitive Phenotypes in People With HIV

Cognitive reserve, depressive symptoms, obesity, and change in employment status predict mental processing speed and executive function after COVID-19

The risk factors for post-COVID-19 cognitive impairment have been poorly described. This study aimed to identify the sociodemographic, clinical, and lifestyle characteristics that characterize a group of post-COVID-19 condition (PCC) participants with neuropsychological impairment. The study sample included 426 participants with PCC who underwent a neurobehavioral evaluation. We selected seven mental speed processing and executive function variables to obtain a data-driven partition. Clustering algorithms were applied, including K-means, bisecting K-means, and Gaussian mixture models. Different machine learning algorithms were then used to obtain a classifier able to separate the two clusters according to the demographic, clinical, emotional, and lifestyle variables, including logistic regression with least absolute shrinkage and selection operator (LASSO) (L1) and Ridge (L2) regularization, support vector machines (linear/quadratic/radial basis function kernels), and decision tree ensembles (random forest/gradient boosting trees). All clustering quality measures were in agreement in detecting only two clusters in the data based solely on cognitive performance. A model with four variables (cognitive reserve, depressive symptoms, obesity, and change in work situation) obtained with logistic regression with LASSO regularization was able to classify between good and poor cognitive performers with an accuracy and a weighted averaged precision of 72%, a recall of 73%, and an area under the curve of 0.72. PCC individuals with a lower cognitive reserve, more depressive symptoms, obesity, and a change in employment status were at greater risk for poor performance on tasks requiring mental processing speed and executive function. Study registration: www.ClinicalTrials.gov , identifier NCT05307575.

An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives

Infectious diseases, including tuberculosis (TB), HIV/AIDS, and emerging pathogens like COVID-19 pose severe global health challenges due to their rapid spread and significant morbidity and mortality rates. Next-generation sequencing (NGS) and machine learning (ML) have emerged as transformative technologies for enhancing disease diagnosis and management.

OBJECTIVE

This review aims to explore integrating ML techniques with NGS for diagnosing infectious diseases, highlighting their effectiveness and identifying existing challenges.

METHODS

A comprehensive literature review spanning the past decade was conducted using reputable databases, including IEEE Xplore, PubMed, Scopus, SpringerLink, and Science Direct. Research papers, articles, and conference proceedings meeting stringent quality criteria were analysed to assess the performance of ML algorithms applied to NGS and metagenomic NGS (mNGS) data.

RESULTS

The findings reveal that ML algorithms, such as deep neural networks (DNNs), support vector machines (SVM), and K-nearest neighbours (KNN), achieve high accuracy rates, often exceeding 95 %, in diagnosing infectious diseases. Deep learning methods excel in genomic and metagenomic data analysis, while traditional algorithms like Gaussian mixture models (GMM) also demonstrate robust classification capabilities. Challenges include reliance on single data types and difficulty distinguishing closely related pathogens.

CONCLUSION

The integration of ML and NGS significantly advances infectious disease diagnosis, offering rapid and precise detection capabilities. Addressing current limitations can further enhance the effectiveness of these technologies, ultimately improving global public health outcomes.

Predicting Neurobehavioral Outcomes in People with HIV

We aimed to identify complex, multidimensional, longitudinal biopsychosocial phenotypes (MLBPSPs) in people with HIV (PWH) and evaluate their associations with baseline clinical characteristics. We included 506 PWH in the multi-site CHARTER study who underwent assessments at four visits, six months apart. Using machine learning, we identified four MLBPSP clusters based on means and nonlinear trajectories of biopsychosocial characteristics. These characteristics included neurocognition, depressed mood, self-reported cognitive symptoms, and activities of daily living at each visit. The largest MLBPSP cluster (C1, N = 231) had the best average scores across all domains and remained stable over 18 months of follow-up. Other clusters showed varying degrees of cognitive impairment, depressed mood, and functional disability. In multivariable analyses, several baseline clinical characteristics, including chronic pulmonary disease, distal neuropathic pain, polypharmacy, and creatinine levels, significantly predicted one or more adverse MLBPSP trajectories. These findings have implications for HIV care by identifying PWH at risk for future adverse trajectories. The results may lead to insights informing future personalized interventions targeted to vulnerable subpopulations of PWH.

Multimodality Fusion Aspects of Medical Diagnosis: A Comprehensive Review

Utilizing information from multiple sources is a preferred and more precise method for medical experts to confirm a diagnosis. Each source provides critical information about the disease that might otherwise be absent in other modalities. Combining information from various medical sources boosts confidence in the diagnosis process, enabling the creation of an effective treatment plan for the patient. The scarcity of medical experts to diagnose diseases motivates the development of automatic diagnoses relying on multimodal data. With the progress in artificial intelligence technology, automated diagnosis using multimodal fusion techniques is now possible. Nevertheless, the concept of multimodal medical diagnosis is still new and requires an understanding of the diverse aspects of multimodal data and its related challenges. This review article examines the various aspects of multimodal medical diagnosis to equip readers, academicians, and researchers with necessary knowledge to advance multimodal medical research. The chosen articles in the study underwent thorough screening from reputable journals and publishers to offer high-quality content to readers, who can then apply the knowledge to produce quality research. Besides, the need for multimodal information and the associated challenges are discussed with solutions. Additionally, ethical issues of using artificial intelligence in medical diagnosis is also discussed.

Biopsychosocial phenotypes in people with HIV in the CHARTER cohort

Neuropsychiatric complications such as neurocognitive impairment and depression are common in people with HIV despite viral suppression on antiretroviral therapy, but these conditions are heterogeneous in their clinical presentations and associated disability. Identifying novel biopsychosocial phenotypes that account for neurocognitive performance and depressive and functional symptoms will better reflect the complexities encountered in clinical practice and may have pathological and therapeutic implications. We classified 1580 people with HIV based on 17 features, including 7 cognitive domains, 4 subscales of the Beck depression inventory-II, 5 components of the patient's assessment of own functioning inventory, and dependence in instrumental and basic activities of daily living. A two-stage clustering procedure consisting of dimension reduction with self-organizing maps and Mahalanobis distance-based k-means clustering algorithms was applied to cross-sectional data. Baseline demographic and clinical characteristics were compared between the phenotypes, and their prediction on the biopsychosocial phenotypes was evaluated using multinomial logistic regression. Four distinct phenotypes were identified. Participants in Phenotype 1 overall did well in all domains. Phenotype 2 had mild-to-moderate depressive symptoms and the most substance use disorders. Phenotype 3 had mild-to-moderate cognitive impairment, moderate depressive symptoms, and the worst daily functioning; they also had the highest proportion of females and non-HIV conditions that could affect cognition. Phenotype 4 had mild-to-moderate cognitive impairment but with relatively good mood, and daily functioning. Multivariable analysis showed that demographic characteristics, medical conditions, lifetime cocaine use disorder, triglycerides, and non-antiretroviral therapy medications were important variables associated with biopsychosocial phenotype. We found complex, multidimensional biopsychosocial profiles in people with HIV that were associated with different risk patterns. Future longitudinal work should determine the stability of these phenotypes, assess factors that influence transitions from one phenotype to another, and characterize their biological associations.

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.

Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease

Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.

Recent advances in HIV-associated neurocognitive disorders: a focus on older adults and sub-Saharan Africa

PURPOSE OF REVIEW

We reviewed recent literature on prevalence and interventional approaches for cognitive impairment in the context of HIV infection alongside current controversies and challenges around its nomenclature, screening, and diagnosis.

RECENT FINDINGS

Prevalence estimates for HIV-associated neurocognitive disorder (HAND) indicate that HAND remains highly prevalent despite combination antiretroviral treatment (cART) widely used. The available data are heterogeneous, particularly in sub-Saharan Africa (SSA) where recent reviews indicate substantial heterogeneity, wide prevalence estimates and lack of data from the majority SSA countries, despite them currently experiencing the greatest burden worldwide of both HIV and HAND.Several alternative approaches to diagnosis and classification of cognitive impairment in HIV have been published, taking into account changing clinical phenotypes.

SUMMARY

Cognitive impairment remains a significant challenge in the care of people living with HIV despite advances in treatment. Ongoing controversies exist around nomenclature and classification, screening measures, and the phenotype and aetiology of observed impairments. Two current areas of research priority and focus include understanding current phenotypes of individuals living and ageing with treated HIV and differing levels of risk for HAND in these phenotypes, alongside the effects of commonly occurring comorbidities.The current evidence base for interventional approaches is limited, but growing. The most promising avenues appear to be multidisciplinary. These are currently focussed on high income settings rather than SSA where the majority of people living with HIV, and affected by cognitive impairment in the context of HIV, currently reside.

Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given the current progress in the fields of ML and DL, there exists the promising potential for both to provide support in the realm of healthcare. This study offered an exhaustive survey on ML and DL for the healthcare system, concentrating on vital state of the art features, integration benefits, applications, prospects and future guidelines. To conduct the research, we found the most prominent journal and conference databases using distinct keywords to discover scholarly consequences. First, we furnished the most current along with cutting-edge progress in ML-DL-based analysis in smart healthcare in a compendious manner. Next, we integrated the advancement of various services for ML and DL, including ML-healthcare, DL-healthcare, and ML-DL-healthcare. We then offered ML and DL-based applications in the healthcare industry. Eventually, we emphasized the research disputes and recommendations for further studies based on our observations.

CSF Extracellular Vesicle Aβ42 and Tau/Aβ42 Ratio Are Associated with Cognitive Impairment in Older People with HIV

HIV-associated neurocognitive disorders (HAND) remain prevalent despite viral suppression on antiretroviral therapy (ART). Older people with HIV (PWH) are also at risk for amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). β-amyloid (Aβ) and Tau biomarkers are associated with aMCI/AD, but their relationship to HAND is unclear. Given the role of extracellular vesicles (EVs) in age-related neurological disorders, we investigated soluble and EV-associated Aβ42, total Tau, NFL, GFAP, ICAM-1, VCAM-1, and CRP in relation to cognitive impairment in PWH. Plasma and CSF EVs were isolated from 184 participants (98 PWH on ART and 86 HIV- controls). Biomarkers were measured using Meso Scale Discovery assays. The median age of PWH was 53 years, and 52% were diagnosed with mild forms of HAND. PWH had increased plasma NFL (p = 0.04) and CSF Aβ42 (p = 0.0003) compared with HIV- controls but no significant difference in Tau or EV-associated forms of these markers. CSF EV Aβ42 was decreased (p = 0.0002) and CSF EV Tau/Aβ42 ratio was increased (p = 0.001) in PWH with HAND vs. no HAND, while soluble forms of these markers showed no significant differences. Decreased CSF EV Aβ42 (p < 0.0001) and an increased CSF EV Tau/Aβ42 ratio (p = 0.0003) were associated with lower neurocognitive T scores in age-adjusted models; an optimal model included both CSF EV Aβ42 and plasma NFL. Levels of soluble, but not EV-associated, ICAM-1, VCAM-1, and CRP were increased in PWH with HAND vs. no HAND (p < 0.05). These findings suggest that decreased Aβ42 and an increased Tau/Aβ42 ratio in CSF EVs are associated with cognitive impairment in older PWH, and these EV-associated biomarkers may help to distinguish aMCI/AD from HIV-related cognitive disorders in future studies.

Vascular injury markers associated with cognitive impairment in people with HIV on suppressive antiretroviral therapy

OBJECTIVE

Human immunodeficiency virus (HIV)-associated neurocognitive disorders (HAND) remain prevalent despite viral suppression on antiretroviral therapy (ART). Vascular disease contributes to HAND, but peripheral markers that distinguish vascular cognitive impairment (VCI) from HIV-related etiologies remain unclear.

DESIGN

Cross-sectional study of vascular injury, inflammation, and central nervous system (CNS) injury markers in relation to HAND.

METHODS

Vascular injury (VCAM-1, ICAM-1, CRP), inflammation (IFN-γ, IL-1β, IL-6, IL-8, IL-15, IP-10, MCP-1, VEGF-A), and CNS injury (NFL, total Tau, GFAP, YKL-40) markers were measured in plasma and CSF from 248 individuals (143 HIV+ on suppressive ART and 105 HIV- controls).

RESULTS

Median age was 53 years, median CD4 + cell count, and duration of HIV infection were 505 cells/μl and 16 years, respectively. Vascular injury, inflammation, and CNS injury markers were increased in HIV+ compared with HIV- individuals ( P < 0.05). HAND was associated with increased plasma VCAM-1, ICAM-1, and YKL-40 ( P  < 0.01) and vascular disease ( P  = 0.004). In contrast, inflammation markers had no significant association with HAND. Vascular injury markers were associated with lower neurocognitive T scores in age-adjusted models ( P  < 0.01). Furthermore, plasma VCAM-1 correlated with NFL ( r  = 0.29, P  = 0.003). Biomarker clustering separated HAND into three clusters: two clusters with high prevalence of vascular disease, elevated VCAM-1 and NFL, and distinctive inflammation profiles (CRP/ICAM-1/YKL-40 or IL-6/IL-8/IL-15/MCP-1), and one cluster with no distinctive biomarker elevations.

CONCLUSIONS

Vascular injury markers are more closely related to HAND and CNS injury in PWH on suppressive ART than inflammation markers and may help to distinguish relative contributions of VCI to HAND.

Neurological, Behavioral, and Pathophysiological Characterization of the Co-Occurrence of Substance Use and HIV: A Narrative Review

Combined antiretroviral therapy (cART) has greatly reduced the severity of HIV-associated neurocognitive disorders in people living with HIV (PLWH); however, PLWH are more likely than the general population to use drugs and suffer from substance use disorders (SUDs) and to exhibit risky behaviors that promote HIV transmission and other infections. Dopamine-boosting psychostimulants such as cocaine and methamphetamine are some of the most widely used substances among PLWH. Chronic use of these substances disrupts brain function, structure, and cognition. PLWH with SUD have poor health outcomes driven by complex interactions between biological, neurocognitive, and social factors. Here we review the effects of comorbid HIV and psychostimulant use disorders by discussing the distinct and common effects of HIV and chronic cocaine and methamphetamine use on behavioral and neurological impairments using evidence from rodent models of HIV-associated neurocognitive impairments (Tat or gp120 protein expression) and clinical studies. We also provide a biopsychosocial perspective by discussing behavioral impairment in differentially impacted social groups and proposing interventions at both patient and population levels.

CSF Inflammation Markers Associated with Asymptomatic Viral Escape in Cerebrospinal Fluid of HIV-Positive Individuals on Antiretroviral Therapy

HIV establishes a viral reservoir in the CNS despite viral suppression in the blood on antiretroviral therapy (ART). In a minority of people with HIV (PWH), HIV RNA is detectable in CSF when HIV RNA in plasma is undetectable or HIV RNA levels are higher in CSF compared with plasma, an event termed CSF viral escape that can occur with or without neurological symptoms. Asymptomatic CSF viral escape occurs in 3-20% of PWH on ART, yet associated biomarkers are unclear. To identify biomarkers associated with asymptomatic CSF viral escape, we performed a matched group study of PWH on ART with vs. without CSF viral escape (n = 10 and n = 60, respectively, matched for age, duration of HIV infection, nadir CD4 count, and ART regimen) and 50 HIV-negative controls. PWH were on 3 or more ART drugs for >1 year, and the group with no CSF viral escape was suppressed below 50 copies/mL in plasma and CSF. Biomarkers of inflammation (IFN-γ, IL-1β, IL-6, IL-8, IL-15, IP-10, MCP-1, VEGF), cell adhesion (ICAM-1, VCAM-1), CNS injury (NFL), and glial activation (GFAP, YKL-40) were measured in paired plasma and CSF using the Meso Scale Discovery platform. PWH with vs. without CSF viral escape had more individuals (40%) with a plasma viral load (VL) > 50 copies/mL, higher CSF VL (median 156 vs. 40 copies/mL; p < 0.0001), lower CD4 count (318 vs. 512; p = 0.045), and higher CSF WBC (median [IQR] 4 [0-22] vs. 2 [0-4] cells/µL; p = 0.15) but similar proportions with HIV-associated neurocognitive disorders (HAND) (50% vs. 47%). CSF viral escape was associated with increased IL-1β, IFN-γ, IP-10, ICAM-1, and VCAM-1 in CSF but not plasma; IP-10 had the strongest association (p = 0.0008). CSF VL and WBC correlated with IFN-γ, IP-10, ICAM-1, and VCAM-1 (p < 0.05). Although markers of CNS injury showed no significant association with asymptomatic CSF viral escape, CSF YKL-40 correlated positively with CSF IL-1β (p = 0.003), IFN-γ (p = 0.0008), IP-10 (p < 0.0001), and NFL (p = 0.06) and negatively with neurocognitive T scores (p = 0.02). These findings identify CSF inflammation and glial activation markers that may serve as surrogate measures of HIV persistence in the CNS for future studies on therapeutics targeting the CNS reservoir.

Cognitive concerns are a risk factor for mortality in people with HIV and coronavirus disease 2019

BACKGROUND

Data supporting dementia as a risk factor for coronavirus disease 2019 (COVID-19) mortality relied on ICD-10 codes, yet nearly 40% of individuals with probable dementia lack a formal diagnosis. Dementia coding is not well established for people with HIV (PWH), and its reliance may affect risk assessment.

METHODS

This retrospective cohort analysis of PWH with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR positivity includes comparisons to people without HIV (PWoH), matched by age, sex, race, and zipcode. Primary exposures were dementia diagnosis, by International Classification of Diseases (ICD)-10 codes, and cognitive concerns, defined as possible cognitive impairment up to 12 months before COVID-19 diagnosis after clinical review of notes from the electronic health record. Logistic regression models assessed the effect of dementia and cognitive concerns on odds of death [odds ratio (OR); 95% CI (95% confidence interval)]; models adjusted for VACS Index 2.0.

RESULTS

Sixty-four PWH were identified out of 14 129 patients with SARS-CoV-2 infection and matched to 463 PWoH. Compared with PWoH, PWH had a higher prevalence of dementia (15.6% vs. 6%, P  = 0.01) and cognitive concerns (21.9% vs. 15.8%, P  = 0.04). Death was more frequent in PWH ( P  < 0.01). Adjusted for VACS Index 2.0, dementia [2.4 (1.0-5.8), P  = 0.05] and cognitive concerns [2.4 (1.1-5.3), P  = 0.03] were associated with increased odds of death. In PWH, the association between cognitive concern and death trended towards statistical significance [3.92 (0.81-20.19), P  = 0.09]; there was no association with dementia.

CONCLUSION

Cognitive status assessments are important for care in COVID-19, especially among PWH. Larger studies should validate findings and determine long-term COVID-19 consequences in PWH with preexisting cognitive deficits.

Vascular injury markers associated with cognitive impairment in people with HIV on suppressive antiretroviral therapy

Objective

Human immunodeficiency virus (HIV)-associated neurocognitive disorders (HAND) remain prevalent despite viral suppression on antiretroviral therapy (ART). Vascular disease contributes to HAND, but peripheral markers that distinguish vascular cognitive impairment (VCI) from HIV-related etiologies remain unclear.

Design

Cross-sectional study of vascular injury, inflammation, and central nervous system (CNS) injury markers in relation to HAND.

Methods

Vascular injury (VCAM-1, ICAM-1, CRP), inflammation (IFN-γ, IL-1β, IL-6, IL-8, IL-15, IP-10, MCP-1, VEGF-A), and CNS injury (NFL, total Tau, GFAP, YKL-40) markers were measured in plasma and CSF from 248 individuals (143 HIV+ on suppressive ART and 105 HIV- controls).

Results

Median age was 53 years, median CD4 count, and duration of HIV infection were 505 cells/μl and 16 years, respectively. Vascular injury, inflammation, and CNS injury markers were increased in HIV+ compared with HIV- individuals (p<0.05). HAND was associated with increased plasma VCAM-1, ICAM-1, and YKL-40 (p<0.01) and vascular disease (p=0.004). In contrast, inflammation markers had no significant association with HAND. Vascular injury markers were associated with lower neurocognitive T scores in age-adjusted models (p<0.01). Furthermore, plasma VCAM-1 correlated with NFL (r=0.29, p=0.003). Biomarker clustering separated HAND into three clusters: two clusters with high prevalence of vascular disease, elevated VCAM-1 and NFL, and distinctive inflammation profiles (CRP/ICAM-1/YKL-40 or IL-6/IL-8/IL-15/MCP-1), and one cluster with no distinctive biomarker elevations.

Conclusions

Vascular injury markers are more closely related to HAND and CNS injury in PWH on suppressive ART than inflammation markers and may help to distinguish relative contributions of VCI to HAND.

Translocation of bacterial LPS is associated with self-reported cognitive abilities in men living with HIV receiving antiretroviral therapy

BACKGROUND

Gut damage allows translocation of bacterial lipopolysaccharide (LPS) and fungal β-D-glucan (BDG) into the blood. This microbial translocation contributes to systemic inflammation and risk of non-AIDS comorbidities in people living with HIV, including those receiving antiretroviral therapy (ART). We assessed whether markers of gut damage and microbial translocation were associated with cognition in ART-treated PLWH.

METHODS

Eighty ART-treated men living with HIV from the Positive Brain Health Now Canadian cohort were included. Brief cognitive ability measure (B-CAM) and 20-item patient deficit questionnaire (PDQ) were administered to all participants. Three groups were selected based on their B-CAM levels. We excluded participants who received proton pump inhibitors or antiacids in the past 3 months. Cannabis users were also excluded. Plasma levels of intestinal fatty acid binding protein (I-FABP), regenerating islet-derived protein 3 α (REG3α), and lipopolysaccharides (LPS = were quantified by ELISA, while 1-3-β-D-glucan BDG) levels were assessed using the Fungitell assay. Univariable, multivariable, and splines analyses were performed.

RESULTS

Plasma levels of I-FABP, REG3α, LPS and BDG were not different between groups of low, intermediate and high B-CAM levels. However, LPS and REG3α levels were higher in participants with PDQ higher than the median. Multivariable analyses showed that LPS association with PDQ, but not B-CAM, was independent of age and level of education. I-FABP, REG3α, and BDG levels were not associated with B-CAM nor PDQ levels in multivariable analyses.

CONCLUSION

In this well characterized cohort of ART-treated men living with HIV, bacterial but not fungal translocation was associated with presence of cognitive difficulties. These results need replication in larger samples.

Intact Proviral DNA Analysis of the Brain Viral Reservoir and Relationship to Neuroinflammation in People with HIV on Suppressive Antiretroviral Therapy

HIV establishes a persistent viral reservoir in the brain despite viral suppression in blood to undetectable levels on antiretroviral therapy (ART). The brain viral reservoir in virally suppressed HIV+ individuals is not well-characterized. In this study, intact, defective, and total HIV proviral genomes were measured in frontal lobe white matter from 28 virally suppressed individuals on ART using the intact proviral DNA assay (IPDA). HIV gag DNA/RNA levels were measured using single-copy assays and expression of 78 genes related to inflammation and white matter integrity was measured using the NanoString platform. Intact proviral DNA was detected in brain tissues of 18 of 28 (64%) individuals on suppressive ART. The median proviral genome copy numbers in brain tissue as measured by the IPDA were: intact, 10 (IQR 1-92); 3' defective, 509 (225-858); 5' defective, 519 (273-906); and total proviruses, 1063 (501-2074) copies/106 cells. Intact proviral genomes accounted for less than 10% (median 8.3%) of total proviral genomes in the brain, while 3' and 5' defective genomes accounted for 44% and 49%, respectively. There was no significant difference in median copy number of intact, defective, or total proviruses between groups stratified by neurocognitive impairment (NCI) vs. no NCI. In contrast, there was an increasing trend in intact proviruses in brains with vs. without neuroinflammatory pathology (56 vs. 5 copies/106 cells, p = 0.1), but no significant differences in defective or total proviruses. Genes related to inflammation, stress responses, and white matter integrity were differentially expressed in brain tissues with >5 vs. +5 intact proviruses/106 cells. These findings suggest that intact HIV proviral genomes persist in the brain at levels comparable to those reported in blood and lymphoid tissues and increase CNS inflammation/immune activation despite suppressive ART, indicating the importance of targeting the CNS reservoir to achieve HIV cure.