Secondary Logo

Journal Logo

Translational Research

Exosomal MicroRNAs Associate With Neuropsychological Performance in Individuals With HIV Infection on Antiretroviral Therapy

O'Meara, Tess BAa; Kong, Yong PhDb; Chiarella, Jennifer BSa; Price, Richard W. MDc; Chaudhury, Rabib BE, MSd; Liu, Xinran MD, PhDa; Spudich, Serena MD, MAa; Robertson, Kevin PhDe; Emu, Brinda MDa; Lu, Lingeng MD, PhDb

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: December 15, 2019 - Volume 82 - Issue 5 - p 514-522
doi: 10.1097/QAI.0000000000002187

Abstract

INTRODUCTION

Widespread use of combined antiretroviral therapy (cART) has greatly reduced central nervous system (CNS)-related morbidity associated with HIV-1 infection; nonetheless, HIV-associated neurocognitive disorder (HAND) remains common, affecting an estimated 20%–50% of people living with HIV (PLWH) and 19% of PLWH with well-suppressed HIV on cART.1,2 HAND represents a constellation of cognitive, motor, and behavioral symptoms with a wide spectrum of severity.3 Detection of cerebrospinal fluid (CSF) HIV RNA and elevated markers of inflammation in the blood and CSF during suppressive cART suggests that persistent reservoirs of HIV in the CNS and inflammatory cross-talk between the 2 compartments may be implicated in clinically relevant neuronal injury.4–6

Exosomes have emerged as potential mediators of long-term immune activation and CNS perturbation during HIV infection.7 Exosomes are cell-secreted lipid bilayer membrane microvesicles ranging from 30 to 150 nm in size that are released via exocytosis into a variety of body fluids, including the blood and CSF.8,9 Exosomes contain donor cell–derived lipids, proteins, messenger RNAs, and microRNAs that affect the functioning of target cells in the immediate microenvironment or at distant sites. Exosomal microRNAs (exo-miRNAs) regulate gene expression by post-transcriptionally controlling the translation and stability of their mRNA targets in recipient cells, thereby affecting cell proliferation, apoptosis, and differentiation.10,11

Pro-inflammatory microRNAs, encapsulated in exosomes, may traffic between the CNS and the peripheral circulation, with systemically derived exosomes contributing to neurological sequelae in people living with chronic HIV infection and/or CNS-derived exosomes in the plasma reflecting the state of ongoing CNS processes. CNS inflammation promotes the ability of exosomes to cross the blood–brain barrier, facilitating the transport of pathologic or pro-inflammatory molecules between the blood and CSF.12 Previous studies have implicated exosomal signaling in CNS pathologies. For example, pro-inflammatory exo-miRNAs have been shown to modulate microglial-mediated immune responses in neurodegenerative diseases including Parkinson and Alzheimer's diseases13,14 and can reflect disease status in multiple sclerosis.15 In studies of HIV, exosomes released from HIV-1 infected cells have been shown to induce quiescent CD4+ lymphocytes to produce HIV-1 and promote the release of pro-inflammatory cytokines from target monocyte-derived macrophages.16,17

Given that microRNAs are enriched in exosomes, in this study, we explore the association between exo-miRNAs and neurocognitive dysfunction during chronic HIV infection in people who have obtained viral suppression on cART. We hypothesized that there is a link between exosomal signaling patterns and neuropsychological testing (NP) performance as a clinical index of the effects of systemic inflammation on the brain as a target organ. This investigation of patterns of plasma exo-miRNAs in the pathogenesis of neurocognitive dysfunction during treated suppressed infection provides new potential targets for intervention for affected individuals.

MATERIALS AND METHODS

Study Participants

Study participants included: participants from the Primary Infection CNS Events Study (University of California, San Francisco) enrolled during primary HIV infection (PHI), defined as within 12 months of HIV acquisition (n = 19), participants from the HIV Associated Reservoirs and Comorbidities study (Yale University) who initiated cART during chronic HIV infection (n = 12), and HIV-uninfected participants without clinical diagnoses of neurologic disease who were recruited from the community [5 men, median age = 49 years, interquartile range (IQR) = 48–53 years]. For participants with HIV (n = 31), plasma, bloodwork, lumbar puncture, and NP testing were performed after at least 1 year of cART initiation and systemic viral suppression (plasma viral load ≤40 copies/mL) were documented.

Neuropsychological Testing

For each PLWH, a 1.5-hour NP battery was performed. Participants were assessed across 5 common domains of neurocognitive functioning: motor (Timed Gait, Grooved Pegboard), executive function (Trail-Making A-B, Controlled Oral Word Association), processing speed (Digit Symbol, Stroop tests), memory (Figure Delay), and learning (Hopkins Verbal Learning Test, Rey Auditory Verbal Learning).18,19 Total z scores were derived by averaging individual test z scores across domains and externally normalizing individual raw test scores for age, gender, ethnicity, and years of education to the general population.20–27 Executive function z scores were derived similarly, using only executive function domain tests. Study participants were divided into 2 groups, higher- and lower-performing, based on normalized total z or executive function z score of >0 and <0, respectively. Other studies have used similar methods of studying participants by NP performance.28,29

Exosome Isolation From Plasma

The isolation of exosomes was performed using a solution of 20% polyethylene glycol (PEG, Mn 6,000; Sigma-Aldrich, St. Louis, MO) as previously reported.30–32 Briefly, the mixture of plasma and the solution (500 µL solution/500 µL plasma) was incubated at 4°C for 2 hours, followed by centrifugation at 13,000 rpm for 2 minutes to obtain the exosome pellet with 2 washes of 1× Dulbecco phosphate buffered saline (DPBS, Sigma-Aldrich).

Confirmation of Exosomes

Transmission electron microscopy (TEM) was performed to validate exosome morphology. DPBS-suspended exosomes were deposited on formvar carbon-coated electron microscopy grids. After negative staining with 2% uranyl acetate (pH 4), the grids were examined and imaged with a FEI TECNAI F20 FEG microscope running at 200 kV of accelerating voltage, the digital images were recorded with a FEI Eagle CCD camera (4k × 4k). Images of 100 representative vesicles were measured with ImageJ (https://imagej.nih.gov). Nanoparticle tracking analysis (NTA) was performed to measure exosomal size and concentration using a Nanosight LM10 instrument equipped with a 405-nm laser (NanoSight, Salisbury, United Kingdom, Malvern Instruments, Malvern, United Kingdom) at 21°C. The Brownian movement of particles was tracked by the NTA software (version 3.1, NanoSight). Quantitative ELISA assay was performed to measure exosome marker CD6333 using an ExoELISA-Ultra CD63 kit (System Biosciences, Inc., Palo Alto, CA, cat. EXEL-ULTRA-CD63-1) following the manufacturer's protocol.34 The total protein concentration of each exosome suspension was measured using NanoDrop_1000 spectrophotometer with a wavelength 280 nm. DPBS exosome suspensions (normalized to 100 μg of protein) were plated and run in duplicate. The absorbance of exosomal CD63 was determined using a Biotek spectrophotometric 96-well microplate reader with a wavelength of 450 nm.

RNA Preparation and Library Construction

Total RNA was extracted from purified exosomes using the SeraMir Exosome RNA purification kit (System Biosciences, Inc., cat. RA806A-1), and the quality and concentration of RNA were determined by the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA). Small RNA libraries were prepared using an NEBNext multiplex small RNA library prep set for Illumina kit (New England BioLabs, Inc., Ipswich, MA) following the manufacturer's instructions.

Next-Generation Small RNA Sequencing and Analysis

Single-end deep sequencing was performed on all cDNA libraries with a 75-nucleotide (nt) read length using the HiSeq-2500 Genome Analyzer (Illumina, San Diego, CA). Adaptors and low quality regions were trimmed from raw sequences using btrim with options “-3 -P -l 15.”35 The trimmed sequences were mapped to the human genome (hg38) with Burrows-Wheeler Aligner.36 For microRNA annotation, miRBase v21 was used.37 Differential gene expression analysis was performed using the R package “DESeq2.”38 MicroRNAs with base mean expression <10 were excluded, and differential expression was defined as absolute log2(fold-change) >1.0.

Functional Analysis of Predicted mRNA Targets of Differentially Expressed exo-miRNAs

To examine functional annotations of the mRNAs that the differentially expressed exo-miRNAs targets, KEGG pathway and Gene Ontology (GO) analyses were performed using the DiANA tool of mirPath v.3.39

Measurement of BDNF in Plasma

The concentration of brain-derived neurotrophic factor (BDNF) was measured as a read-out of exo-miRNA activity on axonal modeling pathways. The concentration of free BDNF in plasma was determined using a commercial ELISA assay (R&D Systems, Inc., Minneapolis, MN) following the manufacturer's protocol. Correlation coefficients were generated between BDNF and both miR-30a-5p and miR-206 levels, 2 reported inhibitors of BDNF translation.40,41

Statistical Analysis

Fisher exact and Wilcoxon Rank Sum tests were used to compare clinical characteristics. To test for the ability of exo-miRNA expression to distinguish participants' NP status, principal component analysis and receiver operating characteristic (ROC) analysis were performed. ROC analysis was performed in SAS v9.4. All other statistical analyses were performed in R v3.5.0.

RESULTS

Participant Characteristics

Characteristics for all study participants are summarized in Table 1. Of the 19 participants enrolled during PHI, the median time between estimated date of infection and treatment initiation was 0.6 years (IQR 0.2–1.8). Patients enrolled during PHI had median age 43 years (IQR 35.5–48), whereas patients enrolled during chronic infection had median age 58.5 years (IQR 51.75–62.5, P = 0.0001). Based on total z scores on NP testing, 13 participants with HIV were sorted into the NP higher-performing group (NP-higher, median total z = 0.3) and 18 into the NP lower-performing group (NP-lower, median total z = −0.7). Based on executive function z scores, 14 participants with HIV were sorted into executive function higher-performing (median z-score = 0.44, 64% enrolled during PHI) and 16 into executive function lower-performing (median z-score = −0.49%, 56% enrolled during PHI). Seven patients enrolled during PHI had incomplete learning and memory NP data, 1 patient had incomplete executive function data, and 2 patients enrolled during chronic infection had incomplete motor NP data; missing domains were not included in the total z-score calculations for these patients. Participants enrolled during PHI were more prevalent in the NP-higher group, whereas most of the participants enrolled during chronic infection were in the NP-lower group (P = 6.5 × 10−6). NP-lower participants had an overall longer duration of cART treatment (P = 0.035), fewer years of education (P = 6.0 × 10−4), and lower CSF protein level (P = 0.009) relative to NP-higher.

TABLE 1.
TABLE 1.:
Participant Characteristics, All Participants and PHI Participants Alone

Characterization of Circulating Exosomes in Plasma

TEM images showed that the morphology of PEG-purified exosomes was vesicular with diameters ranging from 20 to 70 nm (Fig. 1A). NTA, which is based on the principle of Brownian motion of particles in liquid, demonstrated that most purified vesicles ranged 110–210 nm in diameter and were approximately 1010–1011 particles per mL of plasma (Fig. 1B). The smaller sizes of exosomes measured under TEM versus NTA may be because of sample preparation and dehydration for TEM imaging and lower sensitivity of NTA to detect vesicles in the 20–60 nm range.42,43 ELISA assay confirmed that all purified exosomes were CD63-positive and revealed no significant difference in exosome abundance, quantified by the CD63 ELISA signal, between the NP-higher (median = 1.56 × 1010) versus NP-lower groups (median = 1.73 × 1010, P = 0.569) or between cohorts enrolled during PHI (median = 1.55 × 1010) versus chronic infection (median = 1.78 × 1010, P = 0.371).

FIGURE 1.
FIGURE 1.:
Characterization of plasma exosomes. A, Representative TEM image of purified exosomes from plasma using PEG-based solution; scale bar: 200 nm. The histogram represents the distribution of vesicle sizes in the TEM image, with an average size of 36.7 nm (dashed black line). B,. Representative Nanoparticle tracking analysis (NTA) graph showing the size (x-axis) and concentration (y-axis) of diluted exosomes (1:1000) in 1× PBS solution. Gray shading indicates ± 1SE of the mean.

Differential exo-miRNA Expression Between Neuropsychological Higher- and Lower-Performance Groups

Expression levels of exo-miRNAs identified by NGS were compared between NP-higher and NP-lower groups (see Table 1, Supplemental Digital Content, http://links.lww.com/QAI/B380). Principal component analysis performed on the exo-miRNA expression data demonstrated that NP-higher and NP-lower separated into distinct groups, particularly along the second component (Fig. 2A). After correcting for multiple comparisons using false discovery rate (FDR < 0.1), we found 11 exo-miRNAs were significantly differentially expressed between the groups (miR-206, miR-193b-5p, miR-193a-5p, miR-30a-5p, miR-216b-3p, miR-499a-5p, miR-499b-3p, miR-708-3p, miR-1183, miR-375, and miR-483-5p). All 11 differentially expressed exo-miRNAs were upregulated in NP-lower relative to NP-higher (Fig. 2B). Exo-miRNA expression was also compared between PLWH with higher-versus lower-executive function performance. Three exo-miRNA (miR-216b-3p, miR-148a-3p, and miR-504-5p) were significantly upregulated in participants with lower executive function performance relative to higher performance by P < 0.05.

FIGURE 2.
FIGURE 2.:
Distinct exo-miRNA expression patterns between neuropsychological lower- and higher-performing groups. A, Principle component analysis plot based on small RNA-seq data, where the black and dark gray points represent participants with higher and lower neuropsychological (NP) performance, respectively. B, Volcano plot of differential micoRNA expression between lower and higher NP performance groups. The black points indicate exo-miRNA with differential expression FDR <0.1, and the gray points represent no significant difference between the groups. X-axis represents log2(fold-change) of exo-miRNA (lower versus higher NP performance), and y-axis represents the −log10(P-value) of differences in exo-miRNA expression (lower versus higher NP performance). C, Predictive performance (ROC analysis) of the differentially expressed exo-miRNAs in distinguishing lower from higher NP performance. FDR, false discovery rate.

To evaluate the ability of differentially expressed circulating exo-miRNAs to distinguish NP performance groups, we conducted ROC analyses with the 11 identified exo-miRNAs. The 11 differentially expressed exo-miRNAs between NP-higher and NP-lower showed high area under the curve with a value of 0.93 [95% confidence interval (CI): 0.83 to 1.00] in distinguishing the performance groups (Fig. 2C).

Biological Role of Differentially Expressed exo-miRNAs

To better understand the biological relevance of the differentially expressed microRNAs between NP performance groups, we performed canonical KEGG pathway and GO enrichment analyses using the 11 differentially expressed exo-miRNAs. Axon guidance ranked highest of the enriched KEGG pathways (Fig. 3), with 9 of the 11 identified exo-miRNAs targeting genes in this pathway.

FIGURE 3.
FIGURE 3.:
KEGG pathway analysis for differentially expressed exo-miRNAs between neuropsychological lower- and higher-performing groups. Predicted KEGG pathways enriched with the 11 significantly differentially expressed exo-miRNAs (lower- versus higher-neuropsychological (NP) performing, FDR < 0.1). −1og10(P.value) indicates the statistical significance that the pathway is enriched with gene targets of the microRNAs, X.mRNA is the number of exo-miRNAs targeting genes in the enriched pathway, and X.genes is the number of genes in the pathway targeted by the differentially expressed microRNAs, represented by the color and size of the dot. FDR, false discovery rate.

GO analysis demonstrated that genes involved in organelle function, ion binding, cellular nitrogen compound metabolic process, cellular protein modification, biosynthesis, and neurotrophin tyrosine receptor kinase (TRK) signaling were predicted targets of the 11 differentially expressed exo-miRNAs (Fig. 4A). Two identified exo-miRNAs, miR-30a-5p and miR-206, are known inhibitors of BDNF translation. Measurement of BDNF in the 31 plasma samples revealed a significant negative correlation between both exosomal miR-206 and miR-30a-5p expression and BDNF levels (Fig. 4B). Pearson correlation coefficients were −0.50 [95% CI: (−0.72 to −0.16); P value = 0.004] and −0.47 [95% CI: (−0.91 to −0.13); P value = 0.008], respectively. There was no difference in BDNF levels between the NP-higher (7.64, range 1.43–15.4) and NP-lower (5.57, range 0.64–39.0) groups (P = 0.514). There was no significant correlation between BDNF levels and CD4+/CD8+ cell count ratios (P = 0.16) or CD8+ cell counts (P = 0.60) across all participants.

FIGURE 4.
FIGURE 4.:
TRK signaling is a target pathway of differentially expressed exo-miRNAs between neuropsychological lower- and higher-performing groups. A, Heatmap of GO enrichment analysis, where the color key to log(P value) indicates the statistical significance that the GO category (column) is enriched with a given exo-miRNA (row). B, Plasma BDNF levels negatively correlate with exosomal miR-206 and exosomal miR-30a-5p expression. The black line is the line of best fit between the 2 markers, and the grey ribbon represents the 95% CI of the line of best fit. Log10 expression of the exo-miRNA is on the x-axis, and log10 levels of plasma BDNF are on the y-axis.

Differential exo-miRNA Expression Between NP Higher- and Lower-Performing Groups in the PHI Group Alone

Our analysis of differentially expressed exo-miRNAs between the NP-higher and NP-lower groups encompassed 2 distinct populations: participants from the San Francisco, USA, area, treated during early HIV infection, and HIV Associated Reservoirs and Comorbidities participants from the New Haven, USA, area, initially treated during chronic infection. To ensure that our findings were not driven by demographic differences between these 2 populations, differential exo-miRNA expression analyses were performed between NP-higher and -lower performing participants within the PHI study alone, where participants were distributed more evenly between NP-higher and -lower than the chronic infection group.

Using the same threshold of total z-score greater than or less than 0, 12 participants were classified as NP-higher (median total z = 0.4) and 7 participants were classified as NP-lower (median total z = −0.5) within the PHI study alone. There was no significant difference in clinical characteristics between the NP groups (Table 1).

Differential expression analyses revealed 15 exo-miRNAs that were significantly differentially expressed (P < 0.05) between NP-higher and -lower within this subset of participants. 5 exo-miRNAs (miR-454-3p, miR-548k, let-7a-5p, let-7e-5p, and let-7f-5p) were upregulated in NP-higher, whereas 10 exo-miRNAs (miR-30d-3p, miR-125b-5p, miR-193a-5p, miR-4742-3p, miR-4755-3p, miR-141-3p, miR-125b-2-3p, miR-205-5p, miR-1183, miR-708-3p) were upregulated in NP-lower (see Figure 1 and Table 2, Supplemental Digital Contents, http://links.lww.com/QAI/B380 and http://links.lww.com/QAI/B380, respectively). 3/10 exo-miRNAs that were upregulated in NP-lower (miR-193a-5p, miR-1183, and miR-708-3p) within the PHI-only group were also upregulated in NP-lower in the combined PHI and chronic infection group analysis. These 3 exo-miRNAs, differentially expressed in both analyses, demonstrated area under the curve of 0.86 (95% CI: 0.73 to 0.99) in distinguishing NP performance groups within the PHI cohort.

KEGG pathway analysis revealed that the axon guidance pathway was again significantly enriched for the 15 differentially expressed exo-miRNAs between the NP-higher and -lower groups in this PHI group, targeting 54 genes in the pathway (see Table 3, Supplemental Digital Content, http://links.lww.com/QAI/B380). The 3 exo-miRNAs differentially expressed in both analyses were specifically implicated in the phosphatidylinositol signaling (P = 0.01) and glycan degradation (P = 0.0016) KEGG pathways and were predicted to target genes involved in nervous system development (P = 1.5E-06), neurotrophin TRK signaling (1.6E-04), and ion binding (P = 6.69E-20) by GO analysis.

Differential exo-miRNA Expression Between Individuals With and Without HIV Infection

In an exploratory analysis, we compared exo-miRNA expression between a small group of HIV-negative individuals (n = 5) and participants with HIV (n = 31) to investigate whether the 11 exo-miRNA associated with NP status would differentiate by infection status. 25 exo-miRNAs were found to be differentially expressed (P < 0.05) between the participants with and without HIV infection (see Table 4, Supplemental Digital Content, http://links.lww.com/QAI/B380). miR-375, which was found to be up-regulated in NP-lower HIV-infected participants was also found to be 5.7-fold higher in HIV-infected participants relative to HIV-uninfected participants. Otherwise, the differential exo-miRNA expression between infection status did not overlap with those that were found when stratifying groups by NP testing.

DISCUSSION

In this study, we demonstrated that PLWH with higher versus lower neuropsychological performance have different circulating exo-miRNA content. Our analysis of exo-miRNA transcriptomic data revealed that the expression of 11 exo-miRNAs in plasma is associated with lower neuropsychological performance in PLWH, and certain processes, including axon guidance, Epidermal growth factor receptor signaling, and TRK receptor signaling, are predicted targets of these 11 microRNAs. Three of these exo-miRNAs, along with the axon guidance KEGG pathway, were further validated in the exo-miRNA expression analysis within the group of PHI participants alone, suggesting that these exo-miRNA may be implicated in cognitive function during chronic HIV infection that is not specific to the timing of ART initiation.

Several of the differentially expressed exo-miRNAs have been implicated in inflammatory pathways, suggesting that exo-miRNAs may play a role in regulating inflammation during chronic HIV infection. For example, miR-483-5p and miR-30a-5p were up-regulated in NP-lower individuals. miR-483-5p has been shown to attenuate the host antiviral immune response following hepatitis C infection through down-regulation of NF-kB, whereas miR-30a-5p has been shown to enhance antiviral inflammation via up-regulation of IFN-1.44,45 The interplay between anti- and pro-inflammatory exo-miRNAs may contribute to damaging, prolonged inflammation in PLWH and downstream clinical sequelae such as HAND, although this was not reflected by a difference in blood neopterin concentration by the NP group.

Deep sequencing of exo-miRNAs allowed us to take an unbiased approach to detecting biologic processes that are differentially regulated in PWLH with different NP performance. Interestingly, a high proportion of exo-miRNAs in both the full group and subset group analyses were predicted to target genes in the axon guidance KEGG pathway. Integrated transcriptomic analyses of mRNAs and microRNAs in the frontal cortex have suggested that dysregulated axon guidance plays a key role in HIV-mediated neurodegeneration.46 These results suggest that exo-miRNAs may traffic between the periphery and CNS, interfering with neuron repair pathways or reflecting ongoing degenerative processes associated with HAND. We were particularly interested in the executive function NP domain because of the known involvement of the frontal cortex in HIV-mediated neurodegeneration. We found that 3 exo-miRNA, including miR-148a-3p, which has been shown to promote apoptosis by targeting Bcl-2, were more highly expressed in PLWH with lower executive function performance.47 miR-216b-3p was upregulated in both NP-lower and in the cohort with lower executive function, suggesting that this exo-miRNA may specifically contribute to deficits in executive function in PLWH. In addition, processing speed and motor function, 2 domains tested by our standardized neuropsychological exams, are commonly compromised in participants with HAND because of damage to myelinated white matter tracts.48,49 Defects in axon guidance would impede maintenance and normal functioning of these tracts.

Exo-miRNAs up-regulated in NP-lower participants were also predicted to be involved in neurotrophin TRK signaling by GO analysis, and 2 of these microRNAs, miR-30a-5p and miR-206, have previously been shown to specifically inhibit translation of an important TRK ligand, BDNF.50–53 We were able to corroborate this association by showing that there were significant negative correlations between plasma BDNF and both exosomal miR-30a-5p and miR-206. BDNF and its high-affinity receptor, tropomysin-related kinase B, are important mediators of axon guidance and synaptic plasticity. Functional suppression of BDNF leads to the deficits of long-term synaptic potentiation, a major cellular mechanism underlying learning and memory.54 Therefore, up-regulation of miR-30a-5p and miR-206 observed in NP-lower participants may cause neuropsychological deficits in PLWH by impeding BDNF signaling, and in turn, axon guidance.

In studies not focused on CNS deficits, it has been consistently shown that HIV infection alters the microRNA content of exosomes.45,55,56 We similarly found significant differences in circulating exo-miRNA expression between individuals with and without HIV infection. These differences motivated our choice to focus on HIV-infected participants alone for our study of neuropsychological function. Elucidating whether the 11 exo-miRNA associated with neurocognitive status in PLWH are specific to HIV infection requires a larger, controlled study of uninfected volunteers with neuropsychological testing.

This study was an effort to investigate the relationship of exo-miRNA signaling and clinical sequelae of chronic HIV after viral suppression, and there are limitations to our analyses. Primarily, a higher proportion of participants who initiated cART during chronic infection sorted into the NP lower-performing group compared with those who started cART during early infection. Although NP tests have been standardized and validated to control for education level, age, and other demographic variables, performing differential exo-miRNA analysis in the more demographically homogenous PHI cohort alone was an important validation step. It is highly suggestive that 3 differentially expressed exo-miRNAs in both analyses are implicated in pathways of inflammation and neuronal function; however, repeating this analysis in a larger cohort of demographically homogenous individuals would strengthen this finding. In addition, our study included only one female patient, and studying a more balanced cohort would increase the generalizability of these results. Second, without enriching for neuronal-derived exosomes in the plasma, we cannot know that the exosomes examined in this study would traffic to or from the CNS. Several studies have investigated NDEs specifically in the circulation as read-outs of CNS biology in neurocognitive disorders which could be used in future work.28,57,58 Nonetheless, this study provided a snapshot of biologic processes occurring in PLWH that may have widespread effects across various organs.

In summary, we found there was a distinct exo-miRNA pattern that distinguished lower versus higher NP performance groups in PLWH. The differentially expressed exo-miRNAs were predicted to be involved in inflammation and neurodegeneration pathways. These findings suggest that circulating exo-miRNAs may reflect processes ongoing in the CNS in PLWH in the setting of durable viral suppression. Exo-miRNA content may serve as a useful diagnostic tool for individuals with chronic HIV infection on cART and provide further insight into potential targetable mechanisms of NP sequelae in this population.

REFERENCES

1. Eggers C, Arendt G, Hahn K, et al. HIV-1-associated neurocognitive disorder: epidemiology, pathogenesis, diagnosis, and treatment. J Neurol. 2017;264:1715–1727.
2. Garvey L, Surendrakumar V, Winston A. Low rates of neurocognitive impairment are observed in neuro-asymptomatic HIV-infected subjects on effective antiretroviral therapy. HIV Clin Trials. 2011;12:333–338.
3. Clifford DB, Ances BM. HIV-associated neurocognitive disorder. Lancet Infect Dis. 2013;13:976–986.
4. Ulfhammer G, Edén A, Mellgren Å, et al. Persistent central nervous system immune activation following more than 10 years of effective HIV antiretroviral treatment. AIDS. 2018;32:2171–2178.
5. van Zoest RA, Underwood J, De Francesco D, et al. Structural brain abnormalities in successfully treated HIV infection: associations with disease and cerebrospinal fluid biomarkers. J Infect Dis. 2017;217:69–81.
6. Edén A, Nilsson S, Hagberg L, et al. Asymptomatic cerebrospinal fluid HIV-1 viral blips and viral escape during antiretroviral therapy: a longitudinal study. J Infect Dis. 2016;214:1822–1825.
7. Ellwanger JH, Veit TD, Chies JAB. Exosomes in HIV infection: a review and critical look. Infect Genet Evol. 2017;53:146–154.
8. Thery C, Zitvogel L, Amigorena S. Exosomes: composition, biogenesis and function. Nat Rev Immunol. 2002;2:569–579.
9. Welton JL, Loveless S, Stone T, et al. Cerebrospinal fluid extracellular vesicle enrichment for protein biomarker discovery in neurological disease; multiple sclerosis. J Extracell Vesicles. 2017;6:1369805.
10. Valadi H, Ekström K, Bossios A, et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9:654–659.
11. Lu C, Huang X, Zhang X, et al. miR-221 and miR-155 regulate human dendritic cell development, apoptosis, and IL-12 production through targeting of p27kip1, KPC1, and SOCS-1. Blood. 2011;117:4293–4303.
12. Chen CC, Liu L, Ma F, et al. Elucidation of exosome migration across the blood-brain barrier model in vitro. Cell Mol Bioeng. 2016;9:509–529.
13. Idda ML, Munk R, Abdelmohsen K, et al. Noncoding RNAs in Alzheimer's Disease. Wiley Interdiscip Rev RNA. 2018:c1463.
14. Pogue AI, Lukiw WJ. Up-regulated pro-inflammatory MicroRNAs (miRNAs) in Alzheimer's disease (AD) and age-related macular degeneration (AMD). Cell Mol Neurobiol. 2018;38:1021–1031.
15. Ebrahimkhani S, Vafaee F, Young PE, et al. Exosomal microRNA signatures in multiple sclerosis reflect disease status. Sci Rep. 2017;7:14293.
16. Arenaccio C, Chiozzini C, Columba-Cabezas S, et al. Exosomes from human immunodeficiency virus type 1 (HIV-1)-infected cells license quiescent CD4+ T lymphocytes to replicate HIV-1 through a Nef- and ADAM17-dependent mechanism. J Virol. 2014;88:11529–11539.
17. Kadiu I, Narayanasamy P, Dash PK, et al. Biochemical and biologic characterization of exosomes and microvesicles as facilitators of HIV-1 infection in macrophages. J Immunol. 2012;189:744–754.
18. Gold JA, Grill M, Peterson J, et al. Longitudinal characterization of depression and mood states beginning in primary HIV infection. AIDS Behav. 2014;18:1124–1132.
19. Peluso MJ, Meyerhoff DJ, Price RW, et al. Cerebrospinal fluid and neuroimaging biomarker abnormalities suggest early neurological injury in a subset of individuals during primary HIV infection. J Infect Dis. 2013;207:1703–1712.
20. Heaton R, Miller SW, Taylor MJ, et al. Revised Comprehensive Norms for an Expanded Halstead–Reitan Battery: Demographically Adjusted Neuropsychological Norms for African American and Caucasian Adults. Odessa, FL: Psychological Assessment Resources, Inc.; 2004.
21. Brandt JaB, Ralph HB. The Hopkins Verbal Learning Test: Revised: Psychological Assessment Resources; 2001.
22. Wechsler D, WMS-III: Administration and Scoring Manual. San Antonio, TX: Psychological Corporation Harcourt Brace & Co; 1997.
23. Stroop J. Studies of interference in serial verbal reactions. J Exp Psychol. 1935;18:643–662.
24. Comalli PE, Wapner S, Werner H. Interference effects of Stroop color-word test in childhood, adulthood, and aging. J Genet Psychol. 1962;100:47–53.
25. Tombaugh TN, Kozak J, Rees L. Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Arch Clin Neuropsychol. 1999;14:167–177.
26. Gladsjo J, Schuman CC, Evans JD, et al. Norms for letter and category fluency: demographic corrections for age, education, and ethnicity. Assessment. 1999;6:147–178.
27. Ruff RM, Parker SB. Gender- and age-specific changes in motor speed and eye-hand coordination in adults: normative values for the Finger Tapping and Grooved Pegboard Tests. Percept Mot Skills. 1993;76:1219–1230.
28. Sun B, Dalvi P, Abadjian L, et al. Blood neuron-derived exosomes as biomarkers of cognitive impairment in HIV. AIDS. 2017;31:F9–f17.
29. Wright EJ, Grund B, Cysique LA, et al. Factors associated with neurocognitive test performance at baseline: a substudy of the INSIGHT Strategic Timing of AntiRetroviral Treatment (START) trial. HIV Med. 2015;16(suppl 1):97–108.
30. Zeringer E, Barta T, Li M, et al. Strategies for isolation of exosomes. Cold Spring Harb Protoc. 2015;2015:319–323.
31. Alvarez ML, Khosroheidari M, Kanchi Ravi R, et al. Comparison of protein, microRNA, and mRNA yields using different methods of urinary exosome isolation for the discovery of kidney disease biomarkers. Kidney Int. 2012;82:1024–1032.
32. Li P, Kaslan M, Lee SH, et al. Progress in exosome isolation techniques. Theranostics. 2017;7:789–804.
33. Kowal J, Arras G, Colombo M, et al. Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes. Proc Natl Acad Sci USA. 2016;113:E968–E977.
34. Hartjes TA, Mytnyk S, Jenster GW, et al. Extracellular vesicle quantification and characterization: common methods and emerging approaches. Bioengineering (Basel). 2019;6:7.
35. Kong Y. Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics. 2011;98:152–153.
36. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–1760.
37. Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42:D68–D73.
38. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.
39. Vlachos IS, Zagganas K, Paraskevopoulou MD, et al. DIANA-miRPath v3.0: deciphering microRNA function with experimental support. Nucleic Acids Res. 2015;43:W460–W466.
40. Darcq E, Warnault V, Phamluong K, et al. MicroRNA-30a-5p in the prefrontal cortex controls the transition from moderate to excessive alcohol consumption. Mol Psychiatry. 2015;20:1219–1231.
41. Varendi K, Matlik K, Andressoo JO. From microRNA target validation to therapy: lessons learned from studies on BDNF. Cell Mol Life Sci. 2015;72:1779–1794.
42. Dragovic RA, Gardiner C, Brooks AS, et al. Sizing and phenotyping of cellular vesicles using Nanoparticle Tracking Analysis. Nanomedicine. 2011;7:780–788.
43. Vestad B, Llorente A, Neurauter A, et al. Size and concentration analyses of extracellular vesicles by nanoparticle tracking analysis: a variation study. J Extracell Vesicles. 2017;6:1344087.
44. Shwetha S, Gouthamchandra K, Chandra M, et al. Circulating miRNA profile in HCV infected serum: novel insight into pathogenesis. Sci Rep. 2013;3:1555.
45. Ma Y, Wang C, Xue M, et al. The coronavirus transmissible gastroenteritis virus evades the type I interferon response through IRE1α-mediated manipulation of the MicroRNA miR-30a-5p/SOCS1/3 Axis. J Virol. 2018;92:e00728–18.
46. Zhou L, Pupo GM, Gupta P, et al. A parallel genome-wide mRNA and microRNA profiling of the frontal cortex of HIV patients with and without HIV-associated dementia shows the role of axon guidance and downstream pathways in HIV-mediated neurodegeneration. BMC Genomics. 2012;13:677.
47. Zhang H, Li Y, Huang Q, et al. MiR-148a promotes apoptosis by targeting Bcl-2 in colorectal cancer. Cell Death Differ. 2011;18:1702–1710.
48. Ketzler S, Weis S, Haug H, et al. Loss of neurons in the frontal cortex in AIDS brains. Acta Neuropathol. 1990;80:92–94.
49. Oh SW, Shin NY, Choi JY, et al. Altered white matter integrity in human immunodeficiency virus-associated neurocognitive disorder: a tract-based spatial statistics study. Korean J Radiol. 2018;19:431–442.
50. Mellios N, Huang HS, Grigorenko A, et al. A set of differentially expressed miRNAs, including miR-30a-5p, act as post-transcriptional inhibitors of BDNF in prefrontal cortex. Hum Mol Genet. 2008;17:3030–3042.
51. Croce N, Gelfo F, Ciotti MT, et al. NPY modulates miR-30a-5p and BDNF in opposite direction in an in vitro model of Alzheimer disease: a possible role in neuroprotection? Mol Cell Biochem. 2013;376:189–195.
52. Tian N, Cao Z, Zhang Y. MiR-206 decreases brain-derived neurotrophic factor levels in a transgenic mouse model of Alzheimer's disease. Neurosci Bull. 2014;30:191–197.
53. Lee ST, Chu K, Jung KH, et al. miR-206 regulates brain-derived neurotrophic factor in Alzheimer disease model. Ann Neurol. 2012;72:269–277.
54. Shen K, Cowan CW. Guidance molecules in synapse formation and plasticity. Cold Spring Harb Perspect Biol. 2010;2:a001842.
55. Aqil M, Naqvi AR, Mallik S, et al. The HIV Nef protein modulates cellular and exosomal miRNA profiles in human monocytic cells. J Extracell Vesicles. 2014;3:23129.
56. Madison MN, Okeoma CM. Exosomes: implications in HIV-1 pathogenesis. Viruses. 2015;7:4093–4118.
57. Abu-Rumeileh S, Capellari S, Stanzani-Maserati M, et al. The CSF neurofilament light signature in rapidly progressive neurodegenerative dementias. Alzheimers Res Ther. 2018;10:3.
58. Mustapic M, Eitan E, Werner JK, et al. Plasma extracellular vesicles enriched for neuronal origin: a potential window into brain pathologic processes. Front Neurosci. 2017;11:278.
Keywords:

exosomes; HIV-associated neurocognitive dysfunction; microRNA; axon guidance; inflammation

Supplemental Digital Content

Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.