ABSTRACT
HIV reservoirs persist in anatomic compartments despite antiretroviral therapy (ART). Characterizing archival HIV DNA in the central nervous system (CNS) and other tissues is crucial to inform cure strategies. We evaluated paired autopsy brain—frontal cortex (FC), occipital cortex (OCC), and basal ganglia (BG)—and peripheral lymphoid tissues from 63 people with HIV. Participants passed away while virally suppressed on ART at the last visit and without evidence of CNS opportunistic disease. We quantified total HIV DNA in all participants and obtained full-length HIV-envelope (FL HIV-env) sequences from a subset of 14 participants. We detected HIV DNA (gag) in most brain (65.1%) and all lymphoid tissues. Lymphoid tissues had higher HIV DNA levels than the brain (P < 0.01). Levels of HIV gag between BG and FC were similar (P > 0.2), while OCC had the lowest levels (P = 0.01). Females had higher HIV DNA levels in tissues than males (gag, P = 0.03; 2-LTR, P = 0.05), suggesting possible sex-associated mechanisms for HIV reservoir persistence. Most FL HIV-env sequences (n = 143) were intact, while 42 were defective. Clonal sequences were found in 8 out of 14 participants, and 1 participant had clonal defective sequences in the brain and spleen, suggestive of cell migration. From 10 donors with paired brain and lymphoid sequences, we observed evidence of compartmentalized sequences in 2 donors. Our data further the idea that the brain is a site for archival HIV DNA during ART where compartmentalized provirus may occur in a subset of people. Future studies assessing FL HIV-provirus and replication competence are needed to further evaluate the HIV reservoirs in tissues.
IMPORTANCE HIV infection of the brain is associated with adverse neuropsychiatric outcomes, despite efficient antiretroviral treatment. HIV may persist in reservoirs in the brain and other tissues, which can seed virus replication if treatment is interrupted, representing a major challenge to cure HIV. We evaluated reservoirs and genetic features in postmortem brain and lymphoid tissues from people with HIV who passed away during suppressed HIV replication. We found a differential distribution of HIV reservoirs across brain regions which was lower than that in lymphoid tissues. We observed that most HIV reservoirs in tissues had intact envelope sequences, suggesting they could potentially generate replicative viruses. We found that women had higher HIV reservoir levels in brain and lymphoid tissues than men, suggesting possible sex-based mechanisms of maintenance of HIV reservoirs in tissues, warranting further investigation. Characterizing the archival HIV DNA in tissues is important to inform future HIV cure strategies.
KEYWORDS: brain, CNS, lymphoid tissue, archival HIV, sex differences, sequencing
INTRODUCTION
Antiretroviral therapy (ART) suppresses viral replication in most people with HIV (PWH) and drastically reduces morbidity and mortality. However, since ART does not eradicate cells harboring HIV DNA (1, 2), plasma viremia generally rebounds quickly after treatment interruption (3–6). Replication-competent HIV DNA that remains in cellular reservoirs despite effective ART represents a major challenge for an HIV cure (7, 8). Most research trying to understand the characteristics and dynamics of these reservoirs focuses on blood CD4+ T cells (9–11). However, characterizing residual sources of virus in other cell types and anatomic compartments, including the central nervous system (CNS) (12), is a crucially relevant area of investigation. Several considerations motivate a better understanding of the HIV reservoir in the CNS, as follows: (i) HIV enters the CNS immediately after systemic infection and creates a site of persistence that harbors replication-competent HIV that can rebound upon ART interruption (4, 13, 14); (ii) HIV infection of the CNS can lead to neurocognitive (NC) impairment, which still has a prevalence up to 50% among PWH, despite sustained viral suppression (15); (iii) any pharmacological interventions must overcome the blood-brain barrier, which may limit the ability of a drug to achieve effective concentrations in the CNS; (4) the CNS hosts unique cellular targets for HIV, including microglia, perivascular macrophages, and possibly astrocytes, that may enable the persistence of a distinctive HIV reservoir and may respond differently to interventions compared with cellular targets in other tissues (16–18); and (v) the CNS contains viral variants, including some resistant to antiretroviral drugs, that may influence the effectiveness of cure interventions (19–24). The factors associated with the maintenance of the HIV reservoirs and its effects in the CNS during ART remain to be fully understood. In this study, we sought to characterize the archival HIV DNA in the CNS by studying a unique set of postmortem samples collected in the National NeuroAIDS Tissue Consortium (NNTC) from PWH with viral suppression. Notably, viral suppression in PWH is a characteristic inadequately explored in prior publications. We quantified the levels of HIV DNA in three different brain regions and lymphoid tissues, and for a subset of these participants, we evaluated full-length HIV envelope (FL HIV-env) sequences.
RESULTS
Study population.
Table 1 summarizes the clinical and demographic characteristics of the entire study sample, which was divided by sex at birth. The sample included 63 cases, who were enrolled into the NNTC between 1999 and 2014, with a median age of 55 years, with an estimated duration of infection of 14 years and 5.6 years of lifetime exposure to ART by the time of death, and without evidence of CNS opportunistic disease. In this study, we had 12 (19%) women and 51 (81%) men, and the two groups did not differ significantly for most characteristics (Table 1). Participants were considered virally suppressed at last visit prior to death (median 3 months prior to death) with viral loads of <50 cps/mL of plasma (n = 37 participants, n = 9 female) or <400 cps/mL (n = 26 participants, n = 4 female), which were assay dependent, according to the NNTC guidelines.
TABLE 1.
Demographics and clinical characteristics of the study population
| Parameter | Values by category |
P valuea | ||
|---|---|---|---|---|
| All (n = 63) | Female (n = 12, 19%) | Male (n = 51, 81%) | ||
| Ageb | 55.0 (48.5, 61.0) | 56.0 (49.5, 62.3) | 54.0 (48.0, 61.0) | 0.563 |
| White (%) | 60.3 | 25 | 68.6 | 0.005 |
| Current CD4 T cell countsb | 164 (80, 390) | 330 (126, 453) | 155 (77, 285) | 0.134 |
| EDI (yrs)b | 14.0 (9.75, 19.0) | 17.0 (15.5, 19.0) | 13.0 (8.75, 18.3) | 0.085 |
| Estimated LT ART (yrs)b | 6.07 (2.74, 9.43) | 9.09 (6.15, 13.45) | 5.04 (2.32, 8.50) | 0.076 |
P values were calculated for continuous variables using Mann-Whitney U test and for categorical variables using the χ2 test between female and male sex.
Data are expressed as median (interquartile range). ART, antiretroviral therapy; LT, lifetime; EDI, estimated duration of infection.
HIV DNA in brain and lymphoid tissues.
We measured HIV DNA levels in a total of 237 autopsy tissue samples, from paired postmortem frontal cortex (FC; n = 63), occipital cortex (OCC; n = 56), basal ganglia (BG; n = 59), and peripheral lymphoid tissue (n = 59) across 63 participants (Table 2). We detected HIV DNA gag in a majority (65.1%) of brain tissues, ranging from 1.5 to 2,968 copies per 106 cells, and in all lymphoid tissues evaluated, ranging from 7.3 to 3,741 copies per 106 cells. We further detected 2-LTR circles in 23.6% of brains and 57.6% of lymph tissues. To investigate differences in levels among brain and lymphoid tissues, we performed a contrast analysis, as described in the Materials and Methods. Lymphoid tissue had significantly higher levels of HIV DNA than brain tissues in both HIV gag and 2-LTR (P < 0.01), regardless of sex. HIV DNA levels in brain and lymphoid tissues were not correlated (P > 0.2). Next, we evaluated for the differential distribution of HIV DNA in brain tissues. We found that levels of HIV gag in BG and FC were similar (P > 0.2), while OCC had lower levels than the other two brain regions (P = 0.01). The 2-LTR levels were similar between the 3 brain regions (P > 0.2). We tested the potential confounding effect of relevant covariates, such as age, CD4 T cells, time on ART, race (white, black, and other), ethnicity (Hispanic and non-Hispanic), and EDI that were included in the model one at a time. None of these covariates was associated with HIV gag levels (P > 0.14), while all P values for the above contrast analysis remained significant, regardless of which covariate was included in the model.
TABLE 2.
Levels of HIV DNA in brain and lymphoid tissues
| Parameter | Data by category |
|||||
|---|---|---|---|---|---|---|
| All (n = 63) |
Female (n = 12, 19%) |
Male (n = 51, 81%) |
||||
| gag | 2-LTR | gag | 2-LTR | gag | 2-LTR | |
| HIV DNA gag and 2-LTRa | ||||||
| Frontal cortex | 69.8 (44/63) | 22.2 (14/63) | 75 (9/12) | 41.6 (5/12) | 68.6 (35/51) | 17.6 (9/51) |
| Occipital cortex | 55.4 (31/56) | 21.4 (12/56) | 75 (9/12) | 33.3 (4/12) | 50 (22/44) | 11.4 (5/44) |
| Basal ganglia | 69.5 (41/59) | 27.1 (16/59) | 81.8 (9/11) | 54.5 (6/11) | 66.7 (32/48) | 20.8 (10/48) |
| Lymphoid tissue | 100 (59/59) | 57.6 (34/59) | 100 (9/9) | 55.5 (5/9) | 100 (50/50) | 58 (29/50) |
| HIV DNA gag and 2-LTR (cps/million cells)b | ||||||
| Frontal cortex | 186.3 (1.5–2,968.1) | 44.4 (1.4–284.7) | 187.8 (4.2–1,270.7) | 22.4 (5.2–78.3) | 163.7 (1.5–2,968.1) | 56.6 (1.4–284.7) |
| Occipital cortex | 78.5 (2.5–1,401.6) | 15.9 (2.7–50.9) | 177.6 (2.8–1,401.6) | 14.9 (2.7–40.3) | 37.9 (2.5–283.9) | 16.6 (3.3–50.9) |
| Basal ganglia | 230.5 (1.6–2,120.2) | 32.4 (2.1–172.8) | 423.4 (2.5–2,120.2) | 39 (2.1–172.8) | 183.5 (1.6–2,096.4) | 28.4 (3.2–107.6) |
| Lymphoid tissue | 364.7 (7.3–3,741.9) | 29.9 (1–171) | 501.1 (12.2–2,801.6) | 53.5 (2–171) | 313.7 (7.3–3,741.9) | 26.5 (2.6–149.1) |
Data are shown as % (n of positive/available processed samples).
Data are shown as mean (range) of detectable samples.
HIV DNA in tissues between sexes.
Since previous studies support sex differences in viral loads and HIV persistence, we included sex as a predictor in our statistical models to evaluate if levels of HIV DNA in tissues were associated with sex. First, we observed that among women’s brain tissues, HIV DNA gag was detected in 75% of frontal and occipital cortexes and 81.8% of basal ganglia. Levels of total HIV DNA (gag) in women’s brains ranged from 2.5 to 2,802 copies per 106 cells. For men’s brain tissues, we detected HIV DNA (gag) in 68.6% of frontal cortex and 50% of occipital and 66.7% of basal ganglia (Table 2). In men’s brains, levels of HIV DNA ranged from 1.5 to 3,742 copies per 106 cells. Overall, we found that female sex was associated with higher levels of HIV gag (P = 0.03) and a trend in higher 2-LTR levels (P = 0.05) in brain and lymphoid tissues, regardless of brain region (Fig. 1). The female and male patients did not significantly differ in the distributions of HIV gag and 2-LTR among the three brain regions and the lymphoid tissues (all P > 0.27 and P > 0.52, respectively).
FIG 1.
HIV DNA levels by tissue location and sex. Small dots represent individual observations. Large dots and vertical bars represent means and their 95% confidence intervals.
Full-length HIV envelope (FL HIV-env) sequences.
To evaluate genetic composition and relationships of HIV provirus, we performed single-genome amplification (SGA) coupled with PacBio sequencing to obtain FL HIV-env sequences. We obtained a total of 185 individual FL HIV-env sequences across 14 participants (FC, n = 9; OCC, n = 5; lymph node (LN), n = 3; spleen (SP), n = 8) (Fig. 2 and Table 3). Overall, 143 FL HIV-env sequences were genetically intact, while 42 sequences were nonfunctional, with major deletions and frameshift and stop codon mutations (Fig. 2 and Table 3). Table 3 summarizes the demographics and HIV DNA features of participants with available FL HIV-env sequences. Clonal sequences were found in brain or lymphoid tissues from 8 participants. Interestingly, for donor 54, we found the same clonal sequence with a frameshift mutation in both the brain (15 sequences) and spleen (7 sequences), suggesting a migration of cells with a defective clonal provirus between tissue compartments. For 10 donors, FL HIV-env sequences were obtained from paired brain and lymphoid tissues. Sequence diversity within each tissue was assessed both including and excluding sequences with identified apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) hypermutation. HIV compartmentalization patterns differed between some donors, with two (cases 2, viral load [VL] of <50 cp/mL; case 49, VL of <400 cp/mL) showing evidence of HIV DNA compartmentalization between brain tissues and lymph node (Fst test, P < 0.05). In silico tropism prediction identified likely R5-tropic sequences in both brain and lymphoid tissue in all but one participant with sequences from both tissue types (case 60). Four participants yielded sequences which were either likely X4-tropic or with a tropism prediction in an indeterminate range (cases 21, 54, 60, and 690) (Fig. 2; see Fig. S1 in the supplemental material; Table 3).
FIG 2.
Maximum likelihood phylogeny of 185 FL HIV-env sequences obtained from postmortem brain and lymphoid tissues from 14 PWH donors enrolled as part of the NNTC cohort. Each taxon is an individual env sequence. Each sequence is labeled with the participant’s number, followed by the tissue type (FC, frontal cortex; OCC, occipital cortex; LN, lymph node; SP, spleen). Individual participants are also represented by colors, and different tissues within a participant are represented by a shade of that color. Nonintact env sequences are indicated for APOBEC hypermutations (HM), deletions (DEL), and frameshifts due to stop codon (STOP), following the sequence name. Sequence nodes are colored based on in silico Geno2Pheno predictions of coreceptor tropism (see Materials and Methods). Cutoffs for classifying sequences based on the X4 FPR were defined as follows: less than 2% for likely CXCR4-tropic, 2% to 10% for an “indeterminate” range, and greater than or equal to 10% as likely CCCR5-tropic. A missing node indicates the V3 loop was not identifiable by the Geno2Pheno tool (FPR, false-positive rate).
TABLE 3.
Demographics and HIV DNA features for the subset of participants with available FL HIV-env sequences
| Case no. | Sex | Age at death | EDI (yrs) | VL (mo prior death) | Last known ART regimen | Tissue typea | HIV DNA gag (cps/106 cells) | HIV DNA 2-LTR (cps/106 cells) | No. of intact sequences/total | No. of clonal sequences/total | Diversityb | Fst P value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 21 | M | 54 | 10 | <400 (4) | 3TC/D4T/FTV/NVP | FC | 24.2 | 0 | 5/5 | 0/5 | 0.003 | 0.002 |
| LN | 83.3 | 2.0 | 6/8 | 0/8 | 0.032 | |||||||
| 40 | M | 41 | 14 | <50 (3) | EFV/FTC/TDF | FC | 18.2 | 0 | 1/2 | 0/2 | 0.011 | NA |
| 43 | M | 51 | 13 | <400 (1) | 3TC/AZT/NFV | FC | 3.3 | 0 | 1/1 | NA | NA | NA |
| SP | 13.1 | 0 | 5/6 | 0/6 | 0.016 | |||||||
| 45 | F | 64 | 14 | <50 (5) | 3TC/ZDV/EFV | OCC | 3.1 | 0 | 6/6 | 2/6 | 0.017 | 0.332 |
| LN | 2,801.6 | 2.0 | 15/15 | 0/15 | 0.017 | |||||||
| 46 | M | 59 | 19 | <50 (6) | 3TC/ABC/EFV | SP | 1,338.1 | 26.4 | 5/6 | 0/6 | 0.013 | NA |
| 48 | F | 64 | 6 | <50 (4) | 3TC/D4T | FC | 118.2 | 7.9 | 8/9 | 2/9 | 0.025 | 0.424 |
| SP | 826.4 | 29.9 | 11/12 | 2/12 | 0.009 | |||||||
| 49 | M | 50 | 10 | <50 (3) | ABC/NVP/ZDV | FC | 27.5 | 0 | 4/4 | 0/4 | 0.024 | 0.001 |
| OCC | 25.2 | 0 | 3/3 | 0/3 | 0.028 | 0.007 | ||||||
| LN | 1,726.9 | 149.2 | 12/13 | 9/13 | 0.002 | |||||||
| 52 | M | 66 | 7 | <50 (4) | 3TC/ABC/EFV | FC | 5.5 | 0 | 6/7 | 0/7 | 0.021 | 0.215 |
| SP | 75.2 | 0 | 5/7 | 2/7 | 0.018 | |||||||
| 54 | M | 52 | 15 | <50 (3) | EFV/FTC/TDF | FC | 12.4 | 0 | 2/17 | 15/17 | 0.006 | 0.133 |
| SP | 39.4 | 0 | 3/11 | 7/11 | 0.011 | |||||||
| 56 | M | 52 | 13 | <50 (3) | 3TC/D4T/EFV | OCC | 283.9 | 50.9 | 21/25 | 17/25 | 0.003 | NA |
| SP | 9.3 | 0 | 1/1 | NA | NA | |||||||
| 58 | F | 40 | 16 | <400 (2) | TDF/FTC/RGV | OCC | 11.6 | 3.2 | 2/2 | 0/2 | 0.007 | 0.333 |
| SP | 113.3 | 0 | 1/2 | 0/2 | NA | |||||||
| 60 | M | 50 | 19 | <50 (1) | TDF/FTC/ATV/RTV | FC | 10.8 | 0 | 1/1 | NA | NA | NA |
| SP | 185.9 | 53.6 | 7/9 | 3/9 | 0.020 | |||||||
| 64 | M | 66 | 24 | <50 (unknown) | ABC/EFV/LPV/RTV | FC | 24.4 | 9.5 | 11/12 | 7/12 | 0.008 | NA |
| 69 | M | 69 | 26 | <50 (unknown) | 3TC/ABC/ATV | OCC | 3.4 | 0 | 1/1 | NA | NA | NA |
FC, frontal cortex; OCC, occipital cortex; LN, lymph node; SP, spleen; NA, not applicable.
Mean normalized hamming distance after removing hypermutated sequences.
DISCUSSION
In this study, we sought to characterize the archival HIV DNA by studying a unique set of postmortem brain samples. Assessing tissue samples from different brain regions and lymphoid tissues across a total of 63 PWH and using the sensitive droplet digital PCR (ddPCR) method, we detected HIV DNA in a majority of these tissues (65% of brain and 100% of lymphoid samples). Few previous studies have evaluated brain tissues using quantitative PCR methods or tissue hybridization techniques, and the number of cases was comparatively small. In a study from Lamers et al. (25), HIV DNA was quantified in different autopsy tissues, including brain and lymphoid tissues, from 20 virally suppressed participants (plasma VL prior death of <40 or <400 copies/mL, assay dependent). In that study, HIV DNA was detected in 55% of brain tissues (48/87), with levels ranging from 266 to 49,401 copies per 106 cells using ddPCR for HIV gag (detection limit of 200 copies per 106 cells), which are levels similar to those seen in the current study. A second study from Ko et al. (12) investigated the presence of cells harboring HIV RNA and DNA in brains from 16 virally suppressed cases using RNAscope and DNAscope ISH technologies, respectively. In that study, cells harboring HIV DNA were detected in brains tissues from all virally suppressed individuals evaluated. Recently, our group evaluated autopsy tissues, including brain and lymphoid tissues, from six participants from the Last Gift (LG) cohort, of which four had confirmed viral suppression (<20 copies/mL) until the time of death (26). HIV DNA was detected in brain tissues from three out of the four LG participants with an undetectable plasma viral load, with HIV DNA levels in brain tissues up to 9.1 copies per 106 cells in the occipital cortex and up to 33.6 copies/106 cells in the frontal cortex. In the present study, we found a higher range of HIV DNA levels in brain tissues (Table 2) than that in our LG study. While participants from the Last Gift cohort had confirmed viral suppression at the time of or within days close to death, the NNTC cohort participants included in this study had reported viral loads at a median 3 months prior to death. It is possible that some NNTC participants had detectable viral loads between their last visit and time of death, which could have resulted in a replenishment of HIV reservoirs in their tissues. In our study, we also found that total HIV DNA levels, normalized to estimated numbers of host cellular input (RPP30 gene), were typically 1 to 2 log lower in the brain than in lymphoid tissue, which is consistent with previous reports (25, 26). This is not unexpected since the density of target cells is much lower in the CNS than that in lymphoid tissues, which are considered the major site for HIV persistence (26–28). The lack of correlation between brain and lymphoid tissues suggests that brain HIV DNA levels contain information that is not redundant with lymphoid tissue and therefore might reflect biological differences in target cells and viral variants. The brain reservoir has some other unique characteristics relative to lymphoid tissue. Target cells for HIV in brain tissue are mostly long-lived cells such as macrophages, microglia, and possibly astrocytes (29–32), which might influence the timing (later) and extent of rebound after antiretroviral withdrawal. Also, brain HIV DNA can affect the expression of host genes and epigenetics depending on the integration site, even in those with no viral RNA (29, 30). The relatively lower HIV DNA levels in the occipital cortex than those in the frontal lobe and basal ganglia may reflect biological differences, such as the density or activation states of target cells (microglia and macrophages) in the different tissues.
To the best of our knowledge, this is the largest study of HIV DNA quantification in brain tissues from virally suppressed PWH. Our current findings are consistent with the previously published reports with respect to brain HIV DNA detection and quantitation in virally suppressed PWH. These data support the idea that the brain may serve as a reservoir, albeit significantly smaller than lymphoid tissues, from which HIV might possibly re-emerge after discontinuation of ART (4). The majority of HIV proviruses in the periphery have been shown to be defective (33), making the characterization of replication competence key to understanding the potential impact of viral reservoirs in tissues, including the CNS. To partially address this question, recognizing the inability to perform quantitative viral outgrowth assays on archived snap-frozen brain tissues, we obtained FL HIV-env sequences to estimate the proportion of intact proviruses in brain and lymphoid tissues. We found that most FL HIV-env sequences obtained from brain and lymphoid tissues in this study were intact. Overall, this result is similar to what we found across LG tissues (including brain and lymphoid tissues) and peripheral blood mononuclear cell (PBMC), using FL HIV-env SGA coupled with Illumina sequencing, where 89.5% of all sequences were intact (26). Particularly, in that study, a total of 10 FL HIV-env sequences from brain tissues were obtained across three out of the four LG participants who were consistently HIV suppressed until the time of death, and all sequences were intact. For lymphoid tissues (lymph node and spleen), a total of 107 out of 115 sequences obtained across the 4 participants were intact (26). In contrast, previous studies in blood (33) reported that near FL-HIV provirus sequences have a considerably larger proportion of defective HIV genomes containing large deletions, point mutations, and APOBEC hypermutations, likely upward of 90% (33–36). This discrepancy could be explained by a limitation of this and previous studies (26), where sequencing analysis was focused on the FL HIV-env gene only, which has been shown previously to be frequently deleted in HIV proviruses in blood (33). By targeting the HIV FL-env gene for sequencing, we likely enriched our analysis for proviruses containing intact env genes, while we might have missed proviruses with a deleted, nonintact envelope gene. We cannot affirm that other regions of the HIV genomes we detected were intact. We have attempted to obtain near FL HIV genome sequences from these samples, however unsuccessfully, likely due to long-term storage which can lead to DNA shearing over time, posing a challenge to obtaining longer DNA amplicons.
We also found clonal sequences across both tissues, which varied in proportion between participants and tissues, consistent with the known ability of HIV-infected cells to undergo clonal expansion as an important mechanism of HIV persistence (37). Although this idea could be a possible explanation for our findings, our conclusions are limited by only evaluating HIV FL-env gene sequences. While we did not evaluate integrations sites or FL HIV genome sequences to directly assess clonal expansion in this study, intriguingly, one participant had 22 clonal sequences containing the same frameshift mutation in both spleen and frontal cortex tissues, which suggests a clonal expansion of cells harboring the HIV provirus that migrated to different body tissues in this participant. An additional technical limitation is the fact that at the time of collection, tissues has not been perfused which could result in a potential contamination of tissues with blood. This possible contamination is likely to have a small impact on our analysis, given the small size of capillaries compared with that of the overall tissue mass and the settling of blood in tissues, i.e., livor mortis. We also found that a subset of two out of seven cases showed evidence of virus compartmentalization between brain and lymphoid tissues and in silico tropism predictions of R5-tropic viruses in most tissues. As the power to detect compartmentalization increases with the number of sequences, the limited number of sequences obtained for some participants is a limitation of the study and likely represents an underestimated observation. Our results further suggest that HIV can independently evolve under the unique selective pressures of those tissue environments and is stored in tissues, at least in a subset of people (4, 38, 39).
In this study, we also found that women had higher levels of total HIV DNA in tissues than men. The consistency of these differences across brain regions and lymphoid tissues warrants further investigation. Sex differences in HIV-1 disease phenotypes and the risk of acquisition have long been noted by epidemiologic studies (40) and include lower viral loads during acute infection and stronger antiviral responses in women than those in men. Sex-based differences in HIV-1 infection are partially due to differences in socioeconomic factors and in comorbid risks. More recently, there has been increasing evidence that biological differences between the sexes, such as immune cell phenotypes, drug penetration to mucosal sites, and microbiome features, may also play an important role during HIV infection (41). One recent study has shown that women have a lower inducible HIV reservoir in blood (as measured by inducible cell-associated HIV RNA) than men and suggested significant sex differences in HIV reactivation response to ex vivo exposure to hormones (42–45). While the factors that underlie the establishment and maintenance of the HIV reservoirs in tissues are largely unknown and require investigation, it is possible that they could be impacted by sex-based social and biological variables, supporting the idea that HIV cure approaches may be impacted by factors associated with sex differences. Future studies should evaluate the mechanisms by which sex could affect the establishment of HIV reservoirs both in the circulation and in tissues, including the brain.
Additional limitations of our study must further be considered, including the small sample size, particularly the limited number of available female participants. The limited number of sequences obtained from a subset of tissues/participants could also have been a consequence of DNA shearing from long-term stored tissues, impairing our ability to obtain long amplicons. Moreover, the use of a 400-copy HIV RNA detection limit assay leaves the possibility of residual low-level replication in some cases, which could have confounded our viral compartmentalization analysis. Although most participants with available sequences had last antemortem viral loads below 50 cps/mL of plasma, single-copy assays have shown evidence of low-level replication in a substantial fraction of PWH with virologic suppression by the 50-copy assay (46–48). It is also possible that some individuals could have discontinued antiretroviral treatment between the last clinical assessment and death with potential antemortem virus rebound, and if it has happened, it could have reseeded brain and lymphoid tissue HIV DNA in these cases. The duration of viral suppression prior to death was not available for these cases. It has not yet been established whether HIV replication can rebound from brain tissue. Indeed, it is unclear how one could prove unique rebound from the CNS reservoir. We have shown previously using phylogenetics that viral variants rebounding in the CSF following ART interruption are often distinguishable from blood, suggesting a separate origin (4). An important issue is whether the numbers of replication-competent viruses in the brain are sufficient to support systemic rebound. Here, we show using FL HIV-env that at least some CNS-derived variants may be nondefective, suggesting that they are indeed capable of supporting replication and could be a source for systemic viral rebound. We did not evaluate the relationship between neurocognition and brain HIV DNA levels here due to its complexity; the high prevalence of confounding neurocognitive conditions in these participants with a history of advanced HIV disease (49) makes interpretation difficult. The mechanisms and factors involved in the establishment and maintenance of the HIV reservoirs in the brain and other body tissues require future systematic investigation, as the presence of complete and replication competent provirus in the CNS need to be confirmed, which is critical in the context of HIV cure strategies.
MATERIALS AND METHODS
Ethics statement.
The study was approved by the Institutional Review Board at the University of California and at each of the other respective NNTC sites at the University of California, Los Angeles, Icahn School of Medicine at Mount Sinai—New York City and The University of Texas Medical Branch at Galveston. All adult participants (age, ≥18 years) provided written informed consent. No children were included in this study.
Study design.
(i) Study population and samples. We retrospectively selected participants and included postmortem paired brain and lymphoid tissues that were collected and stored at −80°C as part of the NNTC. The selection criteria of cases were as follows: participants had undetectable levels of HIV RNA (<50 or <400 copies/mL, assay dependent) in blood plasma and were on ART at the last visit, at least within 6 months prior to death, and had no evidence of opportunistic CNS disease at the time of autopsy. For all participants, information on demographics and clinical data, such as sex at birth, age, ethnicity, years of education, estimated duration of HIV infection (EDI), blood T lymphocyte counts, HIV RNA viral load, time on ART, and ART regimen, were available as part of the NNTC cohort. From each participant, we requested brain tissues, including frontal cortex (FC), occipital cortex (OCC), and basal ganglia and paired peripheral lymphoid tissues, including lymph nodes (LN) or spleen (SP), as available.
(ii) Quantification of HIV DNA in tissues. Total genomic DNA was extracted from 60 to 90 mg of tissues for all participants using magnetic beads per the manufacturer’s protocol (MagMax DNA multisample; Ambion, Austin, TX). Levels of HIV gag DNA (HXB2 coordinates 1366 to 1619) and 2-LTR circles (HXB2 coordinates 9585 to 51) were measured by droplet digital PCR (ddPCR) (4, 50). Briefly, 1 μg of total genomic DNA per replicate was digested with the BanII enzyme (New England BioLabs, Ipswich, MA). ddPCR was performed with the following cycling conditions: 10 min at 95°C, 40 cycles of a 30 s denaturation at 94°C followed by a 60°C extension for 60 s, and a final extension at 98°C for 10 min. HIV copy numbers were calculated as the mean of triplicate measurements and were normalized to cellular input, estimated by measuring the human gene RPP30 levels, as described previously (50). HIV gag levels were used as an estimate of total HIV DNA, and 2-LTR circles were used as an estimate of unintegrated HIV DNA and a proxy of active HIV replication.
(iii) Statistical analysis. The Bayesian hierarchical regression model was used to evaluate the differences between HIV DNA levels (the outcome) in brain regions, lymphoid tissues, and sex (predictors). The model used a zero-inflated negative-binomial family with a logit and log link functions. Levels of HIV DNA were square-root-transformed to approach normality. Significance was assessed with the Bayesian P value of 2*p(θ > 0|X), indicating a portion of 2-tailed posterior predictive distribution that is greater than 0, conditioned on X (a vector of other predictors and covariates). To investigate differences in HIV gag DNA levels among brain and peripheral tissues, we performed contrast analysis. For that analysis, we computed 3 orthogonal contrast coefficients and included in the same model (i) the average DNA levels in the 3 brain regions versus the peripheral DNA level, (ii) the average in the BG and FC versus OCC, and (iii) BG versus FC. Based on the notion that potential biological sex differences could be associated with HIV measures, we included sex as a predictor in our statistical models to evaluate if levels of HIV DNA in tissues were associated with sex.
(iv) FL HIV-env sequences and sequence analysis. The genotypic composition of FL HIV-env populations was evaluated via high-throughput near-single genome amplification (near-SGA) using the PacBio platform. Briefly, up to 10 μg of genomic DNA per sample was diluted to reach up to 80% positive wells and used in a nested PCR with the outer primer pair 5′FENV_MFO (TTAGGCATCTCCTATGGCAGGAA) and 3′RENV_MFO (TCTTAAAGGTACCTGAGGTCTGACTGG) and an inner primer pair described previously (51). After positive PCR wells were identifier, the corresponding 1st round PCRs were diluted 1:100 to eliminate both excess 1st round primers and nonspecific amplification products. Diluted 1st round products were used for the 2nd round PCR using inner primers with custom-made barcodes to generate uniquely barcoded FL HIV-env amplicons. All barcoded amplicons obtained in this study were quantified and multiplexed in equimolar amounts to generate PacBio library preparations for sequencing. Single FL HIV-env sequences were reconstructed using our previously described amplicon denoising approach with adaptations for near-SGA amplicon sequencing (52). All computational code for sequence postprocessing, including intact/defective determination, alignment, and phylogenetic tree construction, and Fst permutation testing is available online at https://github.com/alecpnkw/nntc_hiv_brain_lymphoid_reservoirs (53). Briefly, sequences were aligned using MAFFT (54), and the maximum likelihood phylogeny was constructed using FastTree (55). Sequences with a stop codon before residue 750 (premature stop) or a total translated length of less than 800 residues (deletion) were interpreted as likely defective. G-to-A hypermutations were detected using Hypermut2 (Los Alamos National Laboratory) (56). Compartmentalization and diversity analyses were conducted via a nonparametric permutation test reporting a one and two-sided P value, respectively, in participants from which we obtained at least two sequences in brain and lymphoid tissues. Mean pairwise hamming distance was used as the measure of nucleotide diversity. The phylogenetic tree was annotated in FigTree (http://tree.bio.ed.ac.uk/software/figtree), and the viral tropism of the FL HIV-env sequences was predicted in silico using the Geno2Pheno online tool (https://coreceptor.geno2pheno.org/).
Data availability.
All sequences are accessible though the link https://datadryad.org/stash/dataset/doi:10.5061/dryad.931zcrjqb.
ACKNOWLEDGMENTS
We are grateful to all the participants in this study. We acknowledge all the staff from the NNTC and HNRC involved in collecting, processing, and organizing the samples and especially Antonio De LaTorre for helping with the sample shipments and Antoine Chaillon for making all proviral sequences accessible.
This work was supported by the Department of Veterans Affairs and grants from the National Institutes of Health, Texas NeuroAIDS Research Center (U24MH100930); California NeuroAIDS Tissue Network (U24MH100928); National Neurological AIDS Consortium (U24MH100929); Manhattan HIV Brain Bank (U24MH100931); Data Coordinating Center (U24MH100925, R01AG061066, AI147821, DA051915, AI134295, HD094646, and P30MH062512); Interdisciplinary Research Fellowship in NeuroAIDS (R25-MH081482); HNRP developmental grant PST-HN39; CNPq-Brazil (245954/2012); the James B. Pendleton Charitable Trust; and the San Diego Center for AIDS Research (SD CFAR), an NIH-funded program (P30AI036214), which is supported by NIH Institutes and Centers (NIAID, NCI, NHLBI, NIA, NICHD, NIDA, NIDCR, NIDDK, NIGMS, NIMH, NIMHD, FIC, and OAR). Sequencing services were conducted at the IGM Genomics Center, University of California San Diego, La Jolla, California, which is supported by P30DK063491, P30CA023100, and P30DK120515, and the Next Generation Sequencing Core at the Salk Institute, La Jolla, California. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Supplemental material is available online only.
Contributor Information
Sara Gianella, Email: gianella@health.ucsd.edu.
Guido Silvestri, Emory University.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Fig. S1 (Individual maximum-likelihood phylogeny of FL HIV-env sequences obtained from postmortem brain and lymphoid tissues from 12 PWH donors enrolled as part of the NNTC cohort with more than 2 sequences obtained across tissues). Download jvi.00543-23-s0001.tif, TIF file, 7.1 MB (7.2MB, tif)
Data Availability Statement
All sequences are accessible though the link https://datadryad.org/stash/dataset/doi:10.5061/dryad.931zcrjqb.