Simian immunodeficiency virus-infected rhesus macaques with AIDS co-develop cardiovascular pathology and encephalitis

Abstract

Despite effective antiretroviral therapy, HIV co-morbidities remain where central nervous system (CNS) neurocognitive disorders and cardiovascular disease (CVD)-pathology that are linked with myeloid activation are most prevalent. Comorbidities such as neurocogntive dysfunction and cardiovascular disease (CVD) remain prevalent among people living with HIV. We sought to investigate if cardiac pathology (inflammation, fibrosis, cardiomyocyte damage) and CNS pathology (encephalitis) develop together during simian immunodeficiency virus (SIV) infection and if their co-development is linked with monocyte/macrophage activation. We used a cohort of SIV-infected rhesus macaques with rapid AIDS and demonstrated that SIV encephalitis (SIVE) and CVD pathology occur together more frequently than SIVE or CVD pathology alone. Their co-development correlated more strongly with activated myeloid cells, increased numbers of CD14+CD16+ monocytes, plasma CD163 and interleukin-18 (IL-18) than did SIVE or CVD pathology alone, or no pathology. Animals with both SIVE and CVD pathology had greater numbers of cardiac macrophages and increased collagen and monocyte/macrophage accumulation, which were better correlates of CVD-pathology than SIV-RNA. Animals with SIVE alone had higher levels of activated macrophage biomarkers and cardiac macrophage accumulation than SIVnoE animals. These observations were confirmed in HIV infected individuals with HIV encephalitis (HIVE) that had greater numbers of cardiac macrophages and fibrosis than HIV-infected controls without HIVE. These results underscore the notion that CNS and CVD pathologies frequently occur together in HIV and SIV infection, and demonstrate an unmet need for adjunctive therapies targeting macrophages.

Introduction

HIV-associated comorbidities affect 20-50% of people living with HIV (PLWH) despite effective antiretroviral therapy (ART) (1–6). Of these, cardiovascular diseases (CVD) and HIV-associated neurocognitive disorders (HAND) are the most prevalent and are likely linked, although this has not been thoroughly documented (7–11). Traditional biomarkers of CVD are insufficient for predicting CVD risk in HIV-infected individuals on ART, highlighting the necessity to further investigate the etiologies of HIV-associated CVD pathogenesis (2, 5, 12, 13). Anecdotally, it appears that the incidence of cardiac and central nervous system (CNS) pathologies, and of CVD and neurocognitive dysfunction among HIV-uninfected individuals often are concomitant and are linked; likely through systemic inflammation and cardiovascular risk factors (14–21). Importantly, both are associated with increased monocyte/macrophage activation and accumulation in tissues (22–26). The development of pre-ART HIV encephalitis (HIVE) among HIV-infected adults and children is associated with myocardial dysfunction, underscoring the possible connection between cardiac and CNS pathogenesis with HIV-infection (27–29).

Central to CVD and CNS pathologies in PLWH and SIV-infected monkeys is myeloid cell activation. This has been demonstrated in many ways including elevated plasma soluble CD14 (sCD14) and CD163 (sCD163), increased numbers of activated CD14+CD16+ monocytes, and the accumulation of CD163+, CD206+, and MAC387+ macrophages (30–38). Monocyte/macrophage activation and accumulation in the CNS also are correlated with neuroinflammation, encephalitis, and HAND with HIV and SIV infection (26, 32–34, 39–46). Whether such cardiac inflammation and fibrosis, and HAND/HIVE and SIV encephalitis (SIVE) pathogenesis co-occur and correlate with higher levels of monocyte and macrophage activation have not been thoroughly addressed. We and others have shown that blocking monocyte traffic or inhibiting macrophage activation experimentally in SIV-infected macaques reduces cardiac inflammation and CNS pathology, highlighting the importance of monocytes and macrophages in the pathogenesis of both SIV comorbidities (47–49). Plasma galectin-3 and -9, are β-galactoside-binding lectins secreted, inpart, by activated macrophages (50, 51) and correlate with HIV comorbidities (52, 53). Galectin-3 correlates with myocardial fibrosis and cardiac inflammation in HIV-uninfected and HIV-infected cohorts, and plasma and cerebrospinal fluid (CSF) galectin-9 correlates with acute HIV-1 infection and HAND (50, 54–60). Plasma interleukin-18 (IL-18) is an inflammatory cytokine associated with macrophage activation and pyroptosis, plasma viral load, atherosclerosis, and CVD in symptomatic, HIV-infected patients and SIV-infected monkeys (61–64). In addition, sCD163 made solely by myeloid cells correlates with CVD and non-calcified plaque, HAND, and plasma virus in HIV-infected individuals on or off ART and SIV-infected monkeys (30, 31, 39, 65).

In this study, we asked whether SIV infected animals with AIDS codevelop CVD and SIVE, and whether animals that codevelop CVD pathology and SIVE had more monocyte and macrophage activation than animals with CVD pathology alone or SIVE alone, and animals with no significant cardiac pathology and SIV with no encephalitis (SIVnoE). Twenty-three CD8+ T lymphocyte-depleted, SIV-infected macaques with AIDS were examined for the prevalence of cardiac fibrosis, inflammation, and cardiomyocyte degeneration, and SIVE. We assessed the numbers of cardiac macrophages, cardiac collagen, monocyte activation, productive infection in the heart and CNS, and plasma sCD163, IL-18, and galectin-3 and -9. Corollary, translational studies were done in PLWH with and without HAND, where significantly increased numbers of cardiac macrophages were found in HAND versus non HAND individuals.

Results

A greater number of animals with AIDS co-develop CVD pathology and SIVE than CVD pathology or SIVE alone

Of twenty-three animals sacrificed with AIDS defining criteria (weight loss, intractable diarrhea, recurrent secondary infections) (Table 1), based on histopathology, 10 (43.5%) co-developed CVD pathology (macrophage accumulation, collagen deposition, cardiomyocyte degeneration) and SIVE [SIV-RNA, macrophage accumulation, multi-nucleated giant cells (MNGC)], 6 (26.1%) had CVD pathology or SIVE alone, and 7 (30.4%) had no significant histopathological findings (NSF) and SIV no encephalitis (SIVnoE). Of the sixteen animals with AIDS defining histopathology (Table 1), 10 (62.5%) co-developed CVD pathology and SIVE, and 6 (37.5%) had CVD pathology or SIVE alone (Table 1). There were greater percentages of animals with a) cardiomyocyte degeneration [NSF and SIVnoE (0/7), CVD-pathology or SIVE alone (1/6) and CVD pathology and SIVE (5/10)]; b) degree of cardiac fibrosis [NSF or SIVnoE (0/7), CVD-pathology or SIVE alone (3/6; 1 severe), CVD pathology and SIVE (6/10; 2 severe)]; and c) cardiac inflammation [NSF and SIVnoE (0/7), CVD pathology or SIVE (3/6, 1 mild) and CVD pathology and SIVE (9/10; moderate-to-severe)] in animals that co-developed CVD pathology and SIVE. There were no significant differences in the average survival days post infection (dpi) among animals with CVD and SIVE (104.8 ± 9.4 dpi), CVD or SIVE alone (99.8 ± 10.9 dpi), and NSF and SIVnoE (168.6 ± 47.2 dpi) nor in age or weight among CVD pathology and SIVE (7.7 ± 0.9 years, 10 ± 0.8 kg), CVD pathology or SIVE alone (6.9 ± 0.7 years, 8.6 ± 1.6 kg), and NSF and SIVnoE (5.7 ± 1.5 years, 7.3 ± 1.2 kg) (Supplementary Table 1).

Animals with CVD pathology and SIVE have greater numbers of cardiac macrophages than animals with NSF and SIVnoE

Animals with CVD and SIVE had increased numbers of CD68+ (2.5-fold), CD163+ (2.7-fold), CD206+ (2.5-fold), and MAC387+ (1.8-fold) cardiac macrophages, compared to animals with NSF and SIVnoE (one-way Kruskal-Wallis ANOVA, p<0.05, with Dunn’s multiple comparisons) (Table 2). There were similar numbers of cardiac CD163+, CD206+, CD68+, and MAC387+ macrophages in animals with CVD and SIVE compared to animals with CVD or SIVE alone, and similar numbers of cardiac CD3+ T lymphocytes (Table 2).

Animals with CVD pathology and SIVE have greater cardiac collagen deposition than animals with NSF and SIVnoE

Animals with both CVD and SIVE (2.5-fold; 20 ± 1.5%), and CVD or SIVE alone (1.9-fold; 15.4 ± 2.1%) had similar areas of collagen deposition, but greater percent of collagen deposition than animals with NSF and SIVnoE (7.9 ± 0.5%) (one-way Kruskal-Wallis ANOVA, p<0.05, with Dunn’s multiple comparisons)(Figure 1). There were no correlations between the numbers of cardiac macrophages and percent area of cardiac collagen deposition in any of the groups.

Figure 1

Animals with SIVE alone have greater cardiac inflammation and collagen deposition than animals with SIVnoE

Animals with SIVE alone had greater numbers of CD68+ (1.9-fold), CD163+ (2.1-fold), CD206+ (2.4-fold), and MAC387+ (1.9-fold) cardiac macrophages compared to animals with SIVnoE alone (Mann-Whitney t-test, p<0.05) (Supplementary Table 2A). SIVE alone animals had more cardiac collagen deposition (1.8-fold) than SIVnoE animals (Mann-Whitney t-test, p<0.01) (Supplementary Table 2B). There were no significant differences between the numbers of cardiac CD3+ T lymphocytes in these groups.

Animals with both CVD and SIVE have more SIV-RNA+ and SIV-gp41+ cells in the CNS and heart than animals with CVD or SIVE alone, and NSF and SIVnoE animals

Overall, we found a greater number of SIV-RNA+ cells (3.8-fold) (Mann-Whitney t-test, p<0.05) and SIV-gp41+ cells (8.2-fold) in the CNS compared to the cardiac tissues in all animals. Animals with CVD pathology and SIVE had a greater number of SIV-RNA+ (3.6-fold) and SIV-gp41+ cells (8.7-fold) in the CNS compared to the heart. Animals with CVD and SIVE had a trend of increased numbers of CNS SIV-RNA+ cells (3.8-fold), CNS SIV-gp41+ cells (1.7-fold), cardiac SIV-RNA+ (2.7-fold), cardiac SIV-gp41+ cells (3.6-fold) than animals with CVD or SIVE alone (Table 3). All cardiac SIV-RNA+ cells were CD68+ and CD206+ macrophages not CD3+ T lymphocytes (Figure 2).

Figure 2

Animals with SIVE alone have increased numbers of CNS SIV-RNA+ macrophages compared to SIVnoE animals

Animals with SIVE alone had increased numbers of CNS SIV-RNA+ cells (18.4-fold), but similar, low numbers of cardiac SIV-RNA+ cells and SIV-gp41+ cells, and CNS SIV-gp41+ cells compared to animals with SIVnoE alone (Mann-Whitney t-test p<0.01) (Supplementary Table 3). Animals with CVD-pathology alone had similar numbers of CNS SIV-RNA+ cells, cardiac SIV-RNA+ cells, and CNS SIV-gp41+ cells compared to NSF animals (Supplementary Table 3).

Animals with CVD-pathology and SIVE have greater numbers of CD14+CD16+ monocytes compared to NSF and SIVnoE animals

Animals with CVD and SIVE had increased numbers of CD14+CD16+ monocytes early [8 dpi (81.3 ± 13.4 CD14+CD16+ monocytes; 2.8-fold) and 19 dpi (104.8 ± 23.6 CD14+CD16+ monocytes; 3.1-fold)] and terminally (223.6 ± 63.1 CD14+CD16+ monocytes; 5.9-fold) compared to animals with NSF and SIVnoE (29.5 ± 5.1, 34 ± 11.7, and 37.8 ± 3.1 CD14+CD16+ monocytes, respectively) (one-way Kruskal-Wallis ANOVA, *p<0.05, with Dunn’s multiple comparisons) (Figure 3A). Animals with CVD and SIVE had similar numbers of CD14+CD16+ monocytes early (8 dpi; 1.3-fold) and a trend of increased CD14+CD16+ monocytes terminally (2.9-fold) compared to CVD-pathology or SIVE alone animals (62.5 ± 15.9 and 78.1 ± 18.6 respectively) (Figure 3A). There was a correlation between the numbers of CD14+CD16+ monocytes early (8 dpi; r= 0.70, p<0.01 and 19 dpi; r= 0.57, p<0.05) and terminally (r= 0.61, p<0.05) with cardiac collagen deposition (Spearman’s correlation, p<0.05) (Figures 3B–D).

Figure 3

Animals with CVD and SIVE have increased plasma biomarkers associated with monocyte and macrophage activation

Animals with CVD and SIVE had a trend of increased plasma sCD163 (2.6-fold) and IL-18 (2.4-fold), galectin-3 (1.2-fold) and galectin-9 (1.5 fold) compared to animals with CVD or SIVE along, and NSF and SIVnoE animals (one-way Kruskal-Wallis ANOVA, *p<0.05, with Dunn’s multiple comparisons) (Table 4). Plasma sCD163 positively correlated with galectin-3 (r= 0.74, p<0.05) and IL-18 (r= 0.93, p<0.001), and trended to correlate with galectin-9 (r= 0.67, p= 0.06). Consistent with previous studies in HIV infected individuals (60, 66), there was a positive correlation between plasma galectin-9 and plasma viral load (r= 0.76, p<0.01) (Spearman’s correlation, p<0.05) (Figure 4) but there were no significant correlations between plasma virus and galectin-3, IL-18, and sCD163. Animals with CVD-pathology alone had a trend of increased plasma sCD163 (2.2-fold) and similar levels of IL-18, galectin-3, and galectin-9 compared to NSF animals (Mann-Whitney t-test p<0.05) (Table 5). SIVE alone animals had greater plasma IL-18 (2.9-fold) and a trend of increased galectin-3 (1.5-fold) and galectin-9 (2.1-fold). There were similar levels of sCD163 between animals with SIVE and SIVnoE (Table 5). Animals with CVD-pathology alone had similar levels of sCD163, IL-18 and galectin-9 compared as NSF animals (Table 5).

Figure 4

HIV-infected individuals with HIVE have greater cardiac inflammation and fibrosis than HIVnoE individuals

We next sought to determine whether HIV-infected individuals with HIVE (n =11) had increased cardiac inflammation and fibrosis over that seen in HIV infected individuals without encephalitis (HIVnoE) (n =11) (Table 6). In age-, race- and sex-matched individuals, we found that the HIVE group had greater numbers of CD68+ (1.7-fold, 200.62 ± 12.41 cells), CD163+ (1.5-fold, 254.29 ± 8.05 cells), and MAC387+ (1.7-fold, 78.52 ± 4.94 cells) cardiac macrophages compared to individuals with HIVnoE (120.49 ± 8.44 CD68+ macrophage, 173.42 ± 7.55 CD163+ macrophage, and 46.58 ± 4.29 MAC387+ macrophage) (Mann-Whitney t test, p<0.05) (Figures 5A-C). There were similar numbers of cardiac CD3+ T lymphocytes in individuals with HIVE (28.15 ± 6.97 cells) compared to individuals with HIVnoE (22.11 ± 5.39 cells) (Figure 5D). Additionally, there was a higher percentage of cardiac collagen deposition (1.8-fold, 29.87 ± 1.63%) in the HIVE group compared to the HIVnoE group (17.06 ± 1.26%) (Mann-Whitney t test, p<0.05) (Figure 5E). These data are similar to the results we find in SIV infected monkeys, supporting the translational nature of the monkey data.

Figure 5

Conclusion- Discussion

Monocyte and macrophage activation and accumulation in the heart or the CNS are consistently correlated with the development of CVD and CVD pathology, HAND and HIVE, and SIVE (22, 67–70). Less is known or reported about the frequency that CVD, CVD pathology, HIVE and HAND with AIDS in humans and animal models, and in PLWH (27–29), or whether co-development is associated with increased monocyte activation, macrophage accumulation, or HIV and SIV infection. Here, we find that animals with AIDS co-developed CVD pathology and SIVE more frequently than CVD pathology or SIVE alone, and individuals with HIVE have increased numbers of cardiac macrophages and fibrosis compared to age- and sex-matched non-HIVE controls. We report that animals that co-developed CVD-pathology and SIVE have higher numbers of CD14+CD16+ monocytes, and plasma sCD163, IL-18, and galectin-3 and -9, and cardiac macrophage accumulation/collagen deposition than animals with CVD or SIVE alone, and NSF and SIVnoE animals. These observations support the notion of increased monocyte activation and cardiac macrophage accumulation with the co-development of cardiac inflammation and fibrosis and SIVE, and underscore the translational findings in the monkey studies with those in HIV infected individuals.

Macrophages are key regulators of fibrogenesis through their interactions with myofibroblasts, wound healing responses, and production of profibrotic factors like galectin-3, osteopontin, and transforming growth factor- beta (TGF-β) (71–74). We and others have previously shown that CD163+ and CD206+ cardiac macrophage accumulation and monocyte activation correlates with cardiac inflammation and fibrosis with HIV and SIV infection (38, 75–77). Similarly, CD163+ and CD206+ perivascular macrophages and 5-bromo-2’-deoxyuridine-labeled (BrdU+) MAC387+ macrophage accumulation in the CNS are major components of HIVE and SIVE lesions (43–46). These observations are consistent with the notion that macrophage accumulation in the heart and CNS correlate with cardiac and SIVE pathogenesis. Our findings extend those observations to suggest that higher levels of monocyte activation, biomarkers of myeloid cell activation in plasma, and macrophage accumulation in the heart correlate with the co-development of cardiac inflammation and fibrosis and SIVE. We have previously shown, by blocking macrophage accumulation with the anti-alpha-4 integrin antibody (47, 48), the polyamine biosynthesis inhibitor methylglyoxal-bis-guanylhydrazone (MGBG) (37) or minocycline (49) correlates with decreased cardiac and CNS inflammation, cardiac fibrosis and tissue histopathology further supporting the role that macrophage accumulation has in the development of CVD alone and SIVE alone (37). Here, we report that animals with CVD and SIVE had more CD68+, CD163+, CD206+, and MAC387+ cardiac macrophages, and cardiac collagen deposition than animals with CVD or SIVE alone, demonstrating that concomitant CVD-pathology and SIVE correlates with higher levels of cardiac macrophage activation, plasma markers of myeloid activation and cardiac fibrosis than CVD-pathology or SIVE alone. We report that animals with CVD alone had more cardiac macrophages and collagen deposition than animals with NSF alone, consistent with previous reports (71, 76, 78). We demonstrate parallel observations in an HIVE cohort compared to age- and sex-matched controls with HIV infection without HIVE, that have increased cardiac macrophages and collagen. Increased cardiac collagen deposition is linked to cardiac macrophage accumulation, although we did not find a statistically significant correlation between macrophage accumulation and percent collagen in the CVD-pathology and SIVE groups. It is possible that we did not find a correlation between the numbers of cardiac macrophages and cardiac collagen in this study due in part to the CD8+ T lymphocyte-depletion model of rapid AIDS. SIV infected macaques with CD8+ T lymphocyte-depletion are more likely to develop AIDS and SIVE and CVD-pathology within 3-4 months, as opposed to 1-3 years, but do not develop chronic cardiovascular diseases (79, 80). Indeed, Shannon et al. (2000) found that acutely infected rhesus macaques did not develop contractile dysfunction and cardiac pathology when compared to chronically infected macaques (81), suggesting that rapid AIDS pathogenesis in macaques does not consistently result in severe cardiomyopathy. We found that animals with SIVE alone had a greater number of cardiac macrophages and collagen deposition than animals with SIVnoE alone, and we found higher numbers of cardiac macrophages and fibrosis in individuals with HIVE, than age and sex matched HIV infected controls without HIVE. Overall, these findings suggest that increased cardiac macrophage accumulation and fibrosis correlate with HIVE in HIV infected individuals and SIVE in SIV infected macaques. Kuroda et al. (2019), demonstrated that CD163+ and CD206+ cardiac macrophages are the most abundant cardiac macrophage subsets in uninfected rhesus macaques with severe cardiac inflammation (82). We report that CD163+ and CD206+ cardiac macrophage subsets are the most abundant cardiac in SIV infected macaques with AIDS. We found that animals with CVD-pathology and SIVE have higher numbers of CD163+ and CD206+ cardiac macrophages than animals with NSF and SIVnoE, indicating that CD163+ and CD206+ cardiac macrophage subsets are correlated with the severity of CVD and SIVE pathologies. Similarly, we find that CD163+ cardiac macrophages are the most abundant cardiac macrophage subset in HIV infected individuals with HIVE, suggesting that CD163+ cardiac macrophage accumulation is associated with HIVE pathogenesis.

We found that higher numbers of activated CD14+CD16+ monocytes occur with the co-development of CVD pathology and SIVE. The CD14+CD16+ monocyte subset normally comprises 5-10% of the total monocyte population, but their expansion with SIV infection and AIDS correlates with the development of CVD-pathology alone, or SIVE alone (32, 69, 83–85). Moreover, animals with CVD and SIVE had greater numbers and percentages of CD14+CD16+ monocytes early in infection and terminally compared to CVD or SIVE alone animals, and animals with NSF and SIVnoE, suggesting that CD14+CD16+ monocyte activation is a biomarker of AIDS pathogenesis and concomitant CVD pathology and SIVE similar to CVD with HIV and HAND in humans (67, 86–88). Prior reports have shown that CD14+CD16+ monocytes are increased/associated with HAND alone (89), and CVD-pathology alone (35, 90). These blood monocytes are thought to be a mature subset of activated monocytes (84, 91) that are persistently activated and are more susceptible to HIV and SIV infection (92, 93). Indeed, early infection and trafficking of C-C chemokine receptor 2 (CCR2)-positive CD14+CD16+ monocytes into the CNS correlates with the development of HIVE and SIVE (93–95). Further, increased CD14+CD16+ monocyte activation correlates with cardiovascular and cerebrovascular inflammation in HIV infected individuals on ART, suggesting that monocyte activation persists despite ART and is linked to the development of CVD and vasculopathy with infection (36, 90, 96). Here, we show that numbers of CD14+CD16+ monocytes early and terminally also correlate with the percentage of cardiac collagen deposition in all animals with AIDS, indicating that increased CD14+CD16+ monocytes correlate with cardiac fibrogenesis. Together our findings suggest that the development of concomitant CVD-pathology and SIVE with AIDS is correlated with increased levels of CD14+CD16+ monocyte activation, and plasma biomarkers of monocyte activation.

We find that animals with concomitant CVD-pathology and SIVE had more SIV-RNA+ and SIV-gp41+ cells in the CNS and heart than animals with CVD-pathology or SIVE alone, and NSF and SIVnoE animals. We note that in all SIV infected monkeys with AIDS, there are far fewer SIV-RNA+ and SIV-gp41+ cells in the heart than the CNS suggesting that macrophage accumulation more so than SIV-RNA+ and SIV-gp41+ cells, are linked to the co-development of CVD pathology and SIVE. This remains the case when plasma virus is undetectable with ART because both CVD-pathology, and HAND persists in the post-ART era, and correlates with markers of monocyte/macrophage activation like plasma sCD163 and sCD14, IL-18, galectin -3 and -9 (30, 39, 41, 97). This is consistent with previous studies showing few SIV-RNA+ cells in the heart regardless of the severity of cardiac inflammation (76, 98). Conversely, other studies have shown that myocardial SIV-RNA correlates with diastolic dysfunction (99, 100). We found that cardiac SIV-RNA+ cells are CD68+CD206+ macrophages and not CD3+ T lymphocytes in all animals, suggesting that a small population of macrophage are productively infected in the heart. We found little to no SIV-DNA+ latently infected cells in the heart. We postulate that the difference of magnitudes in SIV-DNA+, SIV-RNA+, and SIV-gp41+ cells is likely due to the sensitivity of the assays used. We and others have previously shown that productively infected, CD14+CD163+ perivascular macrophages and multinucleated giant cells (MNGCs) comprise the main population of infected macrophages in the brain and correlate with the development of SIVE lesions (43, 46, 69, 83, 101, 102). Overall, our findings support the notion that animals with concomitant CVD-pathology and SIVE have more SIV-RNA+ macrophages and SIV-gp41+ productively infected cells in the heart and CNS than animals with CVD-pathology or SIVE alone.

We found higher levels of biomarkers of plasma sCD163 and IL-18 in animals with CVD and SIVE compared to animals with CVD or SIVE alone, and animals with NSF and SIVnoE consistent with the notion that concomitant CVD and SIVE is correlated with higher monocyte/macrophage activation, and numbers of CD14+CD16+ monocytes. We and others have previously reported that increased plasma sCD163 correlates with non-calcified coronary plaque (30), HAND (39), and all-cause mortality (65) in HIV infected individuals on ART, and in SIV infected rhesus macaques (39, 103). Similarly, plasma IL-18 is produced by macrophages and is also increased with atherosclerosis and CVD in HIV infected individuals (64, 104, 105), and SIV infected macaques (63). Increased NLR Family Pyrin Domain-Containing 3 (NLRP3) inflammasome activation occurs in macrophages with HIV-infection and drives IL-18 and IL-1β production. NLRP3 inflammasome activation is correlated with macrophage activation and pyroptosis (106, 107), disease progression in gut-associated lymphoid tissues (62), neuroinflammation (108, 109) and atherosclerosis in HIV infected individuals (110). This data, and that of others show higher levels of plasma IL-18 in animals that co-developed CVD-pathology and SIVE, suggesting that NLRP3 inflammasome activation may drive both cardiac inflammation and SIVE pathogenesis. We also found similar levels of plasma galectin-3 and -9 in all animals regardless of pathology. Other studies have shown that plasma galectin-3 is increased with HIV-infection (54) and correlates with non-calcified coronary plaque in HIV infected individuals (55); and increased plasma galectin-9 correlates with acute HIV-infection (59, 60, 66), neurocognitive dysfunction (58), and all-cause mortality (111). We found increased galectin-3 and -9 in animals with SIVE alone animals compared to SIVnoE animals. Studies in mice show that increased galectin-3 expression in the brain correlates with microglia activation and neuroinflammation post-CNS injury (112–115), suggesting that there may be a connection between increased galectin-3 and SIVE pathogenesis. We did not find increased plasma galectin-3 in animals with CVD alone likely because of the acute nature of our rapid AIDS model. Previous studies have shown that increased plasma galectin-3 correlates with cardiac inflammation and fibrosis in the uninfected population (116–121) and may correlate with cardiac pathogenesis in HIV infected individuals (54, 55, 68). Our findings indicate that plasma galectin-3 and -9, biomarkers of myeloid cell activation, are higher in animals with SIVE and may correlate with the severity of AIDS pathologies. We also find that plasma sCD163 correlates with plasma galectin-3 and -9, and IL-18 in all animals, and plasma galectin-9, but not sCD163, galectin-3, and IL-18, correlates with plasma viral load. This is consistent with recent reports showing that plasma galectin-9 correlates with plasma viral load in HIV infected individuals (66). Together, these data demonstrate that plasma IL-18 and galectin-3 and -9, are better correlated with monocyte/macrophage activation than plasma viral load. Our findings are consistent with previous data from the Multicenter AIDS Cohort Study (MACS) showing that subclinical atherosclerosis and cognitive dysfunction are correlated with increased biomarkers of monocyte/macrophage activation despite plasma HIV suppression with ART (88, 122, 123).

The concept of the “heart-brain axis,” in which pathogenesis in the heart and CNS are linked, has been discussed in the uninfected population (17, 20, 124), but has not been thoroughly studied with HIV- or SIV- infection. In this study, we report that animals with AIDS co-developed CVD and SIVE and had higher levels of CD14+CD16+ monocyte activation, plasma biomarkers of myeloid cell activation, cardiac inflammation and fibrosis, and SIV-RNA+ and SIV-gp41+ cells in the CNS and heart than animals with CVD or SIVE alone, and animals with NSF and SIVnoE. We also show that cardiac SIV-RNA+ cells are CD68+CD206+ cardiac macrophage. Importantly, we show that HIV infected individuals with HAND also have more cardiac inflammation and fibrosis than individuals with no HAND. This study sheds further light on the importance of monocyte and macrophage activation in AIDS pathogenesis, and suggests that the development of future therapies in HIV infected individuals should target and inhibit myeloid cell activation in the heart and CNS together.

Materials and methods

Animals, SIV-infection, and CD8+ T-lymphocyte depletion

Twenty-three rhesus macaques were utilized in this study. Five were housed at Harvard University’s New England Primate Research Center (NEPRC) and eighteen were housed at Tulane University’s Tulane National Primate Research Center (TNPRC) in accordance with standards of the American Association for Accreditation of Laboratory Animal Care. This was a retrospective study using all male Rhesus macaques (Macaca mulatta). Animals were experimentally infected intravenously (i.v) by inoculation with bolus of SIVmac251 viral swarm (20 ng of SIV p28) provided by Ronald Desrosiers, over a 5 minute time-period. Animals were adult (3.6-12.6 years old). Animals with the Mamu B^*08 and B^*17 alleles were excluded. Blood samples were taken prior to, on the day of infection, and weekly thereafter. Animals underwent CD8+ T-lymphocyte depletion for rapid AIDS and consistent SIVE. CD8+ T-lymphocyte depletion was achieved with subcutaneous administration of human anti-CD8 antibody, cM-T807 (10 mg/kg) at day 6 post-infection, and i.v. administration (5 mg/kg) on days 8 and 12 post-infection. Simian AIDS was determined postmortem by the presence of opportunistic infections, tumors, and the development of SIV giant cell pneumonia, cytomegalovirus pneumonia, SIVE with giant cells, pneumocystis jirovecii, or lymphoma. With the presence of AIDS, animals were anesthetized with ketamine-HCl and euthanized with i.v. pentobarbital overdose and exsanguinated.

Plasma viral load

Plasma SIV-RNA was quantified using real-time PCR, as previously describe (125–127). Five hundred µL of EDTA plasma was collected and SIV virions were pelleted by centrifugation at 20,000 g for 1 hour. The PCR assay targets conserved sequences of SIV-gag The threshold sensitivity was 100 copy Eq/mL, with an average inter-assay coefficient variation of less than 25%. The CT cut off for SIV DNA is 39-40 cycles.

Assessment of inflammation and fibrosis in cardiac tissues and CNS SIVE

Following exsanguination, a standard necropsy was performed and lymph nodes and parenchymal organs including heart and brain, were fixed in 10% neutral buffered formalin. Tissues were paraffin embedded, sectioned at 5µm, and stained with hematoxylin and eosin. Sections of cardiac (left ventricle) and central nervous system (CNS) cortical tissues were analyzed blindly by a veterinary pathologist. Ten randomly selected images of cardiac and CNS cortical tissues were taken using an Olympus BX43 Light Microscopy (Evident, Tokyo, Japan) at 400x fields and graded subjectively and blindly by an ACVP certified Veterinary Pathologist, and categorized based on the degree of cardiac inflammation, cardiac fibrosis, and cardiomyocyte degeneration as having: A) no significant findings (NSF), B) mild, C) moderate, or D) severe pathology. SIVE was diagnosed based on the presence of MNGCs, accumulation of perivascular macrophages, and productive SIV infection (103, 128–130).

Single-label immunohistochemistry of cardiac tissues

Sections of formalin-fixed, paraffin-embedded cardiac tissues were immunohistochemically assessed for numbers of macrophages and CD3+ T-lymphocytes, as previously described (48). Macrophages were identified using monoclonal antibodies against CD163 (clone EdHu-1, Serotec; Oxford, UK), CD68 (clone KP1, Dako; Glostrup, Denmark), Myeloid/Histiocyte Antigen (clone MAC387, Dako), and CD206 (clone 685645, R&D Systems; Minneapolis, MN); T-lymphocytes were identified using a polyclonal antibody against CD3 (Agilent- cat A0452, Dako, Santa Clara, CA). Data are presented as the mean positive number of cells/mm² from 20 non-overlapping fields of view plus or minus the standard error of the mean (SEM). SIV-productively infected cells in cardiac and CNS cortical tissues were immunohistochemically stained for SIV-gp41+ cells (clone: KK41, NIH AIDS Reagent Program; Germantown, MD). Quantitation of SIV-gp41+ cells/mm² was achieved by counting SIV-gp41+ cells from 20 random, non-overlapping images of brain and cardiac sections at 400x total magnification using the Zeiss Axio Imager.M1 microscope and AxioVision (Version 4.8, Zeiss; Oberkochen, Germany).

Measurement of myocardial fibrosis

Cardiac collagen deposition was measured using a modified Massons Trichrome stain, as previously described (48). Tissue sections were imaged using a Zeiss Axio Imager M1 microscope with Plan-Apochromat x20/0.8 Korr objectives. The percent collagen per total tissue area was determined using ImageJ Analysis software from 20 non-overlapping 200x microscopic fields (field area= 0.148mm²) and data are presented as the percent collagen per total tissue area plus or minus the SEM.

Immunohistochemical analysis of samples from the Manhattan HIV Brain Bank cohort

Sections of cardiac tissues were examined post-mortem, from n=22 individuals from the Manhattan HIV Brain Bank (MHBB) cohort. All HIV infected individuals were ART naïve and matched with regard to age, race, and sex. All individuals examined were male. Eleven patients had HIV no encephalitis (HIVnoE) and eleven patients had HIV encephalitis (HIVE). HIVnoE patients had an average age of 44.7 ± 1.15 years, and HIVE patients had an average age of 43.5 ± 1.27 years. Four patients were white, ten were Hispanic, and eight were black. Nine HIVnoE patients, and ten HIVE patients had CD4+ T cell counts < 200 cells. Single-label immunohistochemistry was performed on formalin-fixed, paraffin-embedded sections of cardiac tissues. Macrophages were identified with monoclonal antibodies against CD68 (KP1, Bio-RaD), CD163 (EDHU, Bio-Rad), CD206 (MMR/CD206, RD Systems), and Myeloid/Histiocyte Antigen MAC387 (MAC387, Bio-Rad) cardiac macrophages. Cardiac T-lymphocytes were identified using the polyclonal antibody against CD3. Data are presented as the mean number of positive cells/mm² from 20 non-overlapping 200x fields of view plus or minus the SEM. Cardiac collagen deposition was measured using a modified Massons Trichrome stain. Tissue sections were imaged using a Zeiss Axio Imager M1 microscope with Plan-Apochromat x20/0.8 Korr objectives. The percent collagen per total tissue area was determined using ImageJ Analysis software from 20 non-overlapping 200x microscopic fields (field area = 0.148mm²) and data are presented as the percent collagen per total tissue area plus or minus the SEM.

SIV-RNA and SIV-DNA detection using RNAscope and DNAscope

SIV-RNA was detected in situ using the RNAscope ^® 2.5 HD Assay-Red (Advanced Cell Diagnostics [ACD]; Newark, CA) on formalin-fixed, paraffin-embedded, 5-µm thick sections of three CNS cortical and one cardiac tissue per animal, as previously described (131). Sections were deparaffinized in xylenes and 100% ethanol and air dried. Antigen retrieval with boiling citrate buffer for 15 min and protease digestion at 40°C for 30 min was performed (131). SIV-RNA-specific probes targeting SIVmac239 envelope (ACD), RNAscope^® positive control Mmu-PPIB (ACD) or RNAscope^® negative control DapB (ACD) were applied to sections. Quantitation of SIV-RNA+ cells/mm² in the CNS and heart were achieved by counting and averaging the numbers of SIV-RNA+ cells from 20 random, non-overlapping images taken from three CNS cortical sections and one cardiac section, respectively, at 400x total magnification using the Zeiss Axio Imager.M1 microscope and AxioVision. SIV-DNA was detected in situ using an SIV-DNA sense probe (ACD) for RNAscope^® Assay on one cardiac section per animal. DNAscope was performed, as previously described (25, 132). To reduce non-specific signal, heart tissues were pre-treated with 2N HCL for 30 min at room temperature. Following DNAscope, cardiac sections were scanned and digitized with Aperio CS2 Scanscope. SIV-DNA+ cells/mm² were quantified using a positive pixel count algorithm in Aperio’s Spectrum Plus analysis program (version 9.1, Aperio ePathology Solutions, Leica Biosystems; Wetzlar, Germany), as previously described (133).

Plasma biomarker ELISAs

Plasma IL-18 (R & D Systems; Minneapolis, MN), galectin-3 (R & D Systems), galectin-9 (R & D Systems) and soluble CD163 (sCD163) (IQ Products; Groningen, Netherlands) concentrations were analyzed with ELISAs according to the manufacturer’s protocol. Concentrations of galectin-3 and galectin-9 were measured using BioTek Powerwave 340 (BioTek; Winooski, VT) at a wavelength of 450 nm and a correction wavelength of 540 nm. Concentrations of plasma galectin-3 and -9, and sCD163 were presented as ng/mL. Concentrations of plasma IL-18 were presented as pg/mL.

Flow cytometry

Flow cytometric analysis was conducted on 100 μl aliquots of whole blood collected in EDTA-coated tubes. Blood samples were taken at 0, 8, 19 days post infection (dpi) and terminally. Samples from animals housed at the NERPC were shipped and analyzed the same day and samples from animals at the TNPRC were shipped overnight. Erythrocyte lysis was performed (ImmunoPrep Reagent System, Beckman Coulter; Brea, CA), followed by 2 washes with PBS, and incubation with fluorochrome-conjugated antibodies including anti-CD14-APC (clone: M5E2, BD Pharmingen; San Diego, CA), anti-CD16-PE (clone: 3G8, BD Pharmingen) anti-HLA-DR-PerCP-Cy5.5 (clone: L243, BD Pharmingen). All samples were fixed in 2% paraformaldehyde and results were acquired on a BD FACS Aria (BD Biosciences; San Jose, CA) and analyzed with Tree Star Flow Jo version 8.7. Monocytes were first selected based on size and granularity (FSC vs SSC) followed by selection of HLA-DR⁺ CD14⁺ cells. From this acquisition gate the percentage of monocyte subsets expressing CD14 and/or CD16 could be determined. The absolute number of peripheral blood monocytes for each animal was calculated by multiplying the total white blood cell count by the total percentage of monocytes determined by flow cytometry.

Statistical analysis

Statistical analyses were done using Prism version 10 software (GraphPad Software, Inc.; San Diego, CA). Comparisons between animals with CVD and SIVE, animals with CVD or SIVE alone, and NSF and SIVnoE animals were made using a one-way analysis of variance (ANOVA) with Dunn’s multiple comparisons. Comparisons between CVD only and NSF only, and SIVE only and SIVnoE only animals were made using a non-parametric Mann-Whitney t-test. A Spearman rank test was used for all correlations. Statistical significance was accepted at p< 0.05.

Study approval

Animals were housed at Harvard University’s New England Regional Primate Research Center (NEPRC) or Tulane University’s National Primate Center (TNPRC) and handled in strict accordance with Harvard University’s and Tulane University’s National Primate Research Center Institutional Animal Care and Use Committee (IACUC). Animal IACUC approval from NEPRC and TNPRC was granted for all procedures: The NERPC protocol number for this study was 04420 and the animal welfare assurance number was A3431-01. The TNRPC the protocol number is 3497 and the animal welfare assurance number is A4499-01. All human cardiac tissues from the Manhattan HIV Brain Bank cohort were obtained and examined with the written informed consent of all individuals prior to participation in this study. These were de-identified post mortem tissue specimens and were therefor IRB exempt.

References

• 1

  EsserSGelbrichGBrockmeyerNGoehlerASChadendorfDErbelRet al. Prevalence of cardiovascular diseases in HIV-infected outpatients: results from a prospective, multicenter cohort study. Clin Res Cardiol (2013) 102(3):203–13. doi: 10.1007/s00392-012-0519-0

  • CrossRef
  • Google Scholar

• 2

  DuprezDANeuhausJKullerLHTracyRBellosoWDe WitSet al. Inflammation, coagulation and cardiovascular disease in HIV-infected individuals. PloS One (2012) 7(9):e44454. doi: 10.1371/journal.pone.0044454

  • CrossRef
  • Google Scholar

• 3

  MesquitaECCoelhoLEAmancioRTVelosoVGrinsztejnBLuzPet al. Severe infection increases cardiovascular risk among HIV-infected individuals. BMC Infect diseases (2019) 19(1):319. doi: 10.1186/s12879-019-3894-6

  • CrossRef
  • Google Scholar

• 4

  HsuePYTawakolA. Inflammation and fibrosis in HIV: getting to the heart of the matter. Circ Cardiovasc imaging (2016) 9(3):e004427. doi: 10.1161/CIRCIMAGING.116.004427

  • CrossRef
  • Google Scholar

• 5

  FreibergMSChangCCKullerLHSkandersonMLowyEKraemerKLet al. HIV infection and the risk of acute myocardial infarction. JAMA Internal Med (2013) 173(8):614–22. doi: 10.1001/jamainternmed.2013.3728

  • CrossRef
  • Google Scholar

• 6

  EggersCArendtGHahnKHusstedtIWMaschkeMNeuen-JacobEet al. HIV-1-associated neurocognitive disorder: epidemiology, pathogenesis, diagnosis, and treatment. J neurol (2017) 264(8):1715–27. doi: 10.1007/s00415-017-8503-2

  • CrossRef
  • Google Scholar

• 7

  De FrancescoDVerboeketSOUnderwoodJBagkerisEWitFWMallonPWGet al. Patterns of co-occurring comorbidities in people living with HIV. Open Forum Infect Dis (2018) 5(11):ofy272. doi: 10.1093/ofid/ofy272

  • CrossRef
  • Google Scholar

• 8

  De FrancescoDUnderwoodJBagkerisEAndersonJWilliamsIVeraJHet al. Risk factors and impact of patterns of co-occurring comorbidities in people living with HIV. AIDS (London England) (2019) 33(12):1871–80. doi: 10.1097/QAD.0000000000002293

  • CrossRef
  • Google Scholar

• 9

  NandithaNGAPaieroATafessuHMSt-JeanMMcLindenTJusticeACet al. Excess burden of age-associated comorbidities among people living with HIV in British Columbia, Canada: a population-based cohort study. BMJ Open (2021) 11(1):e041734. doi: 10.1136/bmjopen-2020-041734

  • CrossRef
  • Google Scholar

• 10

  YangXZhangJChenSWeissmanSOlatosiBLiX. Comorbidity patterns among people living with HIV: a hierarchical clustering approach through integrated electronic health records data in South Carolina. AIDS Care (2021) 33(5):594–606. doi: 10.1080/09540121.2020.1844864

  • CrossRef
  • Google Scholar

• 11

  JakabekDRaeCDBrewBJCysiqueLA. Brain aging and cardiovascular factors in HIV: a longitudinal volume and shape MRI study. AIDS (2022) 36(6):785–94. doi: 10.1097/QAD.0000000000003165

  • CrossRef
  • Google Scholar

• 12

  LeonRReusSLopezNPortillaISanchez-PayaJGinerLet al. Subclinical atherosclerosis in low Framingham risk HIV patients. Eur J Clin Invest (2017) 47(8):591–9. doi: 10.1111/eci.12780

  • CrossRef
  • Google Scholar

• 13

  CheruvuSHollowayCJ. Cardiovascular disease in human immunodeficiency virus. Internal Med J (2014) 44(4):315–24. doi: 10.1111/imj.12381

  • CrossRef
  • Google Scholar

• 14

  Tahsili-FahadanPGeocadinRG. Heart-brain axis: effects of neurologic injury on cardiovascular function. Circ Res (2017) 120(3):559–72. doi: 10.1161/CIRCRESAHA.116.308446

  • CrossRef
  • Google Scholar

• 15

  AnsteyKJLipnickiDMLowLF. Cholesterol as a risk factor for dementia and cognitive decline: a systematic review of prospective studies with meta-analysis. Am J geriatric Psychiatry (2008) 16(5):343–54. doi: 10.1097/01.JGP.0000310778.20870.ae

  • CrossRef
  • Google Scholar

• 16

  SilbertBSScottDAEveredLALewisMSMaruffPT. Preexisting cognitive impairment in patients scheduled for elective coronary artery bypass graft surgery. Anesth analgesia (2007) 104(5):1023–8. doi: 10.1213/01.ane.0000263285.03361.3a

  • CrossRef
  • Google Scholar

• 17

  FriedmanJITangCYde HaasHJChangchienLGoliaschGDabasPet al. Brain imaging changes associated with risk factors for cardiovascular and cerebrovascular disease in asymptomatic patients. JACC Cardiovasc imaging (2014) 7(10):1039–53. doi: 10.1016/j.jcmg.2014.06.014

  • CrossRef
  • Google Scholar

• 18

  HaydenKMZandiPPLyketsosCGKhachaturianASBastianLACharoonrukGet al. Vascular risk factors for incident Alzheimer disease and vascular dementia: the Cache County study. Alzheimer Dis associated Disord (2006) 20(2):93–100. doi: 10.1097/01.wad.0000213814.43047.86

  • CrossRef
  • Google Scholar

• 19

  RussoCJinZHommaSElkindMSRundekTYoshitaMet al. Subclinical left ventricular dysfunction and silent cerebrovascular disease: the Cardiovascular Abnormalities and Brain Lesions (CABL) study. Circulation (2013) 128(10):1105–11. doi: 10.1161/CIRCULATIONAHA.113.001984

  • CrossRef
  • Google Scholar

• 20

  DaduRTFornageMViraniSSNambiVHoogeveenRCBoerwinkleEet al. Cardiovascular biomarkers and subclinical brain disease in the atherosclerosis risk in communities study. Stroke (2013) 44(7):1803–8. doi: 10.1161/STROKEAHA.113.001128

  • CrossRef
  • Google Scholar

• 21

  NewmanABFitzpatrickALLopezOJacksonSLyketsosCJagustWet al. Dementia and Alzheimer’s disease incidence in relationship to cardiovascular disease in the Cardiovascular Health Study cohort. J Am Geriatrics Society (2005) 53(7):1101–7. doi: 10.1111/j.1532-5415.2005.53360.x

  • CrossRef
  • Google Scholar

• 22

  BurdoTHLacknerAWilliamsKC. Monocyte/macrophages and their role in HIV neuropathogenesis. Immunol Rev (2013) 254(1):102–13. doi: 10.1111/imr.12068

  • CrossRef
  • Google Scholar

• 23

  AvalosCRAbreuCMQueenSELiMPriceSShirkENet al. Brain macrophages in simian immunodeficiency virus-infected, antiretroviral-suppressed macaques: a functional latent reservoir. mBio (2017) 8(4). doi: 10.1128/mBio.01186-17

  • CrossRef
  • Google Scholar

• 24

  AvalosCRPriceSLForsythERPinJNShirkENBullockBTet al. Quantitation of productively infected monocytes and macrophages of simian immunodeficiency virus-infected macaques. J virol (2016) 90(12):5643–56. doi: 10.1128/JVI.00290-16

  • CrossRef
  • Google Scholar

• 25

  KoAKangGHattlerJBGaladimaHIZhangJLiQet al. Macrophages but not Astrocytes Harbor HIV DNA in the Brains of HIV-1-Infected Aviremic Individuals on Suppressive Antiretroviral Therapy. J neuroimmune Pharmacol (2019) 14(1):110–9. doi: 10.1007/s11481-018-9809-2

  • CrossRef
  • Google Scholar

• 26

  WilliamsKCHickeyWF. Central nervous system damage, monocytes and macrophages, and neurological disorders in AIDS. Annu Rev Neurosci (2002) 25:537–62. doi: 10.1146/annurev.neuro.25.112701.142822

  • CrossRef
  • Google Scholar

• 27

  WrightEJGrundBRobertsonKBrewBJRoedigerMBainMPet al. Cardiovascular risk factors associated with lower baseline cognitive performance in HIV-positive persons. Neurology (2010) 75(10):864–73. doi: 10.1212/WNL.0b013e3181f11bd8

  • CrossRef
  • Google Scholar

• 28

  LipshultzSEEasleyKAOravEJKaplanSStarcTJBrickerJTet al. Left ventricular structure and function in children infected with human immunodeficiency virus: the prospective P2C2 HIV Multicenter Study. Pediatric Pulmonary and Cardiac Complications of Vertically Transmitted HIV Infection (P2C2 HIV) Study Group. Circulation (1998) 97(13):1246–56. doi: 10.1161/01.CIR.97.13.1246

  • CrossRef
  • Google Scholar

• 29

  AntinoriAGiancolaMLAlbaLSoldaniFGrisettiS. Cardiomyopathy and encephalopathy in AIDS. Ann New York Acad Sci (2001) 946:121–9. doi: 10.1111/j.1749-6632.2001.tb03907.x

  • CrossRef
  • Google Scholar

• 30

  BurdoTHLoJAbbaraSWeiJDeLelysMEPrefferFet al. Soluble CD163, a novel marker of activated macrophages, is elevated and associated with noncalcified coronary plaque in HIV-infected patients. J Infect diseases (2011) 204(8):1227–36. doi: 10.1093/infdis/jir520

  • CrossRef
  • Google Scholar

• 31

  LiangHDuanZLiDLiDWangZRenLet al. Higher levels of circulating monocyte-platelet aggregates are correlated with viremia and increased sCD163 levels in HIV-1 infection. Cell Mol Immunol (2015) 12(4):435–43. doi: 10.1038/cmi.2014.66

  • CrossRef
  • Google Scholar

• 32

  KimWKSunYDoHAutissierPHalpernEFPiatakMJr.et al. Monocyte heterogeneity underlying phenotypic changes in monocytes according to SIV disease stage. J leukocyte Biol (2010) 87(4):557–67. doi: 10.1189/jlb.0209082

  • CrossRef
  • Google Scholar

• 33

  NowlinBTWangJSchaferJLAutissierPBurdoTHWilliamsKC. Monocyte subsets exhibit transcriptional plasticity and a shared response to interferon in SIV-infected rhesus macaques. J leukocyte Biol (2018) 103(1):141–55. doi: 10.1002/JLB.4A0217-047R

  • CrossRef
  • Google Scholar

• 34

  BurdoTHWalkerJWilliamsKC. Macrophage polarization in AIDS: dynamic interface between anti-viral and anti-inflammatory macrophages during acute and chronic infection. J Clin Cell Immunol (2015) 6(3).

  • Google Scholar

• 35

  AngelovichTATrevillyanJMHoyJFWongMEAgiusPAHearpsACet al. Monocytes from men living with HIV exhibit heightened atherogenic potential despite long term viral suppression with ART. AIDS (London England) (2019) (34)(4):513–8. doi: 10.1097/QAD.0000000000002460

  • CrossRef
  • Google Scholar

• 36

  JaworowskiAHearpsACAngelovichTAHoyJF. How monocytes contribute to increased risk of atherosclerosis in virologically-suppressed HIV-positive individuals receiving combination antiretroviral therapy. Front Immunol (2019) 10:1378. doi: 10.3389/fimmu.2019.01378

  • CrossRef
  • Google Scholar

• 37

  WalkerJAMillerADBurdoTHMcGrathMSWilliamsKC. Direct targeting of macrophages with methylglyoxal-bis-guanylhydrazone decreases SIV-associated cardiovascular inflammation and pathology. J acquired Immune deficiency syndromes (1999) (2017) 74(5):583–92. doi: 10.1097/QAI.0000000000001297

  • CrossRef
  • Google Scholar

• 38

  ZanniMVToribioMWilksMQLuMTBurdoTHWalkerJet al. Application of a novel CD206+ Macrophage-specific arterial imaging strategy in HIV-infected individuals. J Infect diseases (2017) 215(8):1264–9. doi: 10.1093/infdis/jix095

  • CrossRef
  • Google Scholar

• 39

  BurdoTHWeiffenbachAWoodsSPLetendreSEllisRJWilliamsKC. Elevated sCD163 in plasma but not cerebrospinal fluid is a marker of neurocognitive impairment in HIV infection. AIDS (London England) (2013) 27(9):1387–95. doi: 10.1097/QAD.0b013e32836010bd

  • CrossRef
  • Google Scholar

• 40

  D’AntoniMLByronMMChanPSailasutaNSacdalanCSithinamsuwanPet al. Normalization of soluble CD163 levels after institution of antiretroviral therapy during acute HIV infection tracks with fewer neurological abnormalities. J Infect diseases (2018) 218(9):1453–63. doi: 10.1093/infdis/jiy337

  • CrossRef
  • Google Scholar

• 41

  LyonsJLUnoHAncutaPKamatAMooreDJSingerEJet al. Plasma sCD14 is a biomarker associated with impaired neurocognitive test performance in attention and learning domains in HIV infection. J acquired Immune deficiency syndromes (1999) (2011) 57(5):371–9. doi: 10.1097/QAI.0b013e3182237e54

  • CrossRef
  • Google Scholar

• 42

  WilliamsKWestmorelandSGrecoJRataiELentzMKimWKet al. Magnetic resonance spectroscopy reveals that activated monocytes contribute to neuronal injury in SIV neuroAIDS. J Clin Invest (2005) 115(9):2534–45. doi: 10.1172/JCI22953

  • CrossRef
  • Google Scholar

• 43

  FilipowiczARMcGaryCMHolderGELindgrenAAJohnsonEMSugimotoCet al. Proliferation of perivascular macrophages contributes to the development of encephalitic lesions in HIV-infected humans and in SIV-infected macaques. Sci Rep (2016) 6:32900. doi: 10.1038/srep32900

  • CrossRef
  • Google Scholar

• 44

  HolderGEMcGaryCMJohnsonEMZhengRJohnVTSugimotoCet al. Expression of the mannose receptor CD206 in HIV and SIV encephalitis: a phenotypic switch of brain perivascular macrophages with virus infection. J neuroimmune Pharmacol (2014) 9(5):716–26. doi: 10.1007/s11481-014-9564-y

  • CrossRef
  • Google Scholar

• 45

  SoulasCConerlyCKimWKBurdoTHAlvarezXLacknerAAet al. Recently infiltrating MAC387(+) monocytes/macrophages a third macrophage population involved in SIV and HIV encephalitic lesion formation. Am J pathol (2011) 178(5):2121–35. doi: 10.1016/j.ajpath.2011.01.023

  • CrossRef
  • Google Scholar

• 46

  NowlinBTBurdoTHMidkiffCCSalemiMAlvarezXWilliamsKC. SIV encephalitis lesions are composed of CD163(+) macrophages present in the central nervous system during early SIV infection and SIV-positive macrophages recruited terminally with AIDS. Am J pathol (2015) 185(6):1649–65. doi: 10.1016/j.ajpath.2015.01.033

  • CrossRef
  • Google Scholar

• 47

  CampbellJHRataiEMAutissierPNolanDJTseSMillerADet al. Anti-alpha4 antibody treatment blocks virus traffic to the brain and gut early, and stabilizes CNS injury late in infection. PloS pathogens (2014) 10(12):e1004533. doi: 10.1371/journal.ppat.1004533

  • CrossRef
  • Google Scholar

• 48

  WalkerJABeckGACampbellJHMillerADBurdoTHWilliamsKC. Anti-alpha4 integrin antibody blocks monocyte/macrophage traffic to the heart and decreases cardiac pathology in a SIV infection model of AIDS. J Am Heart Assoc (2015) 4(7). doi: 10.1161/JAHA.115.001932

  • CrossRef
  • Google Scholar

• 49

  CampbellJHBurdoTHAutissierPBombardierJPWestmorelandSVSoulasCet al. Minocycline inhibition of monocyte activation correlates with neuronal protection in SIV neuroAIDS. PloS One (2011) 6(4):e18688. doi: 10.1371/journal.pone.0018688

  • CrossRef
  • Google Scholar

• 50

  AnyfantiPGkaliagkousiEGavriilakiETriantafyllouADolgyrasPGalanopoulouVet al. Association of galectin-3 with markers of myocardial function, atherosclerosis, and vascular fibrosis in patients with rheumatoid arthritis. Clin Cardiol (2019) 42(1):62–8. doi: 10.1002/clc.23105

  • CrossRef
  • Google Scholar

• 51

  NikiTFujitaKRosenHHirashimaMMasakiTHattoriTet al. Plasma galectin-9 concentrations in normal and diseased condition. Cell Physiol biochem: Int J Exp Cell physiol biochem Pharmacol (2018) 50(5):1856–68. doi: 10.1159/000494866

  • CrossRef
  • Google Scholar

• 52

  SharmaUCPokharelSvan BrakelTJvan BerloJHCleutjensJPSchroenBet al. Galectin-3 marks activated macrophages in failure-prone hypertrophied hearts and contributes to cardiac dysfunction. Circulation (2004) 110(19):3121–8. doi: 10.1161/01.CIR.0000147181.65298.4D

  • CrossRef
  • Google Scholar

• 53

  HirashimaMKashioYNishiNYamauchiAImaizumiTAKageshitaTet al. Galectin-9 in physiological and pathological conditions. Glycoconjugate J (2002) 19(7-9):593–600. doi: 10.1023/B:GLYC.0000014090.63206.2f

  • CrossRef
  • Google Scholar

• 54

  deFilippiCChristensonRJoyceJParkEAWuAFitchKVet al. Brief report: statin effects on myocardial fibrosis markers in people living with HIV. J acquired Immune deficiency syndromes (1999) (2018) 78(1):105–10. doi: 10.1097/QAI.0000000000001644

  • CrossRef
  • Google Scholar

• 55

  FitchKVDeFilippiCChristensonRSrinivasaSLeeHLoJet al. Subclinical myocyte injury, fibrosis and strain in relationship to coronary plaque in asymptomatic HIV-infected individuals. AIDS (London England) (2016) 30(14):2205–14. doi: 10.1097/QAD.0000000000001186

  • CrossRef
  • Google Scholar

• 56

  NoguchiKTomitaHKanayamaTNiwaAHatanoYHoshiMet al. Time-course analysis of cardiac and serum galectin-3 in viral myocarditis after an encephalomyocarditis virus inoculation. PloS One (2019) 14(1):e0210971. doi: 10.1371/journal.pone.0210971

  • CrossRef
  • Google Scholar

• 57

  NguyenMNSuYViziDFangLEllimsAHZhaoWBet al. Mechanisms responsible for increased circulating levels of galectin-3 in cardiomyopathy and heart failure. Sci Rep (2018) 8(1):8213. doi: 10.1038/s41598-018-26115-y

  • CrossRef
  • Google Scholar

• 58

  PremeauxTAD’AntoniMLAbdel-MohsenMPillaiSKKallianpurKJNakamotoBKet al. Elevated cerebrospinal fluid Galectin-9 is associated with central nervous system immune activation and poor cognitive performance in older HIV-infected individuals. J neurovirol (2019) 25(2):150–61. doi: 10.1007/s13365-018-0696-3

  • CrossRef
  • Google Scholar

• 59

  SaitohHAshinoYChagan-YasutanHNikiTHirashimaMHattoriT. Rapid decrease of plasma galectin-9 levels in patients with acute HIV infection after therapy. Tohoku J Exp Med (2012) 228(2):157–61. doi: 10.1620/tjem.228.157

  • CrossRef
  • Google Scholar

• 60

  TandonRChewGMByronMMBorrowPNikiTHirashimaMet al. Galectin-9 is rapidly released during acute HIV-1 infection and remains sustained at high levels despite viral suppression even in elite controllers. AIDS Res Hum Retroviruses (2014) 30(7):654–64. doi: 10.1089/aid.2014.0004

  • CrossRef
  • Google Scholar

• 61

  HeBNieQWangFHanYYangBSunMet al. Role of pyroptosis in atherosclerosis and its therapeutic implications. J Cell Physiol (2021) 236(10):7159–75. doi: 10.1002/jcp.30366

  • CrossRef
  • Google Scholar

• 62

  FeriaMGTabordaNAHernandezJCRugelesMT. HIV replication is associated to inflammasomes activation, IL-1β, IL-18 and caspase-1 expression in GALT and peripheral blood. PloS One (2018) 13(4):e0192845. doi: 10.1371/journal.pone.0192845

  • CrossRef
  • Google Scholar

• 63

  YearleyJHXiaDPearsonCBCarvilleAShannonRPMansfieldKG. Interleukin-18 predicts atherosclerosis progression in SIV-infected and uninfected rhesus monkeys (Macaca mulatta) on a high-fat/high-cholesterol diet. Lab investigation; J Tech Methods pathol (2009) 89(6):657–67. doi: 10.1038/labinvest.2009.29

  • CrossRef
  • Google Scholar

• 64

  Wiercinska-DrapaloAJaroszewiczJFlisiakRProkopowiczD. Plasma interleukin-18 is associated with viral load and disease progression in HIV-1-infected patients. Microbes Infect (2004) 6(14):1273–7. doi: 10.1016/j.micinf.2004.07.009

  • CrossRef
  • Google Scholar

• 65

  KnudsenTBErtnerGPetersenJMøllerHJMoestrupSKEugen-OlsenJet al. Plasma soluble CD163 level independently predicts all-cause mortality in HIV-1-infected individuals. J Infect diseases (2016) 214(8):1198–204. doi: 10.1093/infdis/jiw263

  • CrossRef
  • Google Scholar

• 66

  SheteADhayarkarSDhamanageAKulkarniSGhateMSangleSet al. Possible role of plasma Galectin-9 levels as a surrogate marker of viremia in HIV infected patients on antiretroviral therapy in resource-limited settings. AIDS Res Ther (2020) 17(1):43. doi: 10.1186/s12981-020-00298-9

  • CrossRef
  • Google Scholar

• 67

  AnzingerJJButterfieldTRAngelovichTACroweSMPalmerCS. Monocytes as regulators of inflammation and HIV-related comorbidities during cART. J Immunol Res (2014) 2014:569819. doi: 10.1155/2014/569819

  • CrossRef
  • Google Scholar

• 68

  HannaDBLinJPostWSHodisHNXueXAnastosKet al. Association of macrophage inflammation biomarkers with progression of subclinical carotid artery atherosclerosis in HIV-infected women and men. J Infect diseases (2017) 215(9):1352–61. doi: 10.1093/infdis/jix082

  • CrossRef
  • Google Scholar

• 69

  KimWKCoreySAlvarezXWilliamsK. Monocyte/macrophage traffic in HIV and SIV encephalitis. J leukocyte Biol (2003) 74(5):650–6. doi: 10.1189/jlb.0503207

  • CrossRef
  • Google Scholar

• 70

  KrebsSJAnanworanichJ. Immune activation during acute HIV infection and the impact of early antiretroviral therapy. Curr Opin HIV AIDS (2016) 11(2):163–72. doi: 10.1097/COH.0000000000000228

  • CrossRef
  • Google Scholar

• 71

  WynnTABarronL. Macrophages: master regulators of inflammation and fibrosis. Semin liver disease (2010) 30(3):245–57. doi: 10.1055/s-0030-1255354

  • CrossRef
  • Google Scholar

• 72

  WynnTARamalingamTR. Mechanisms of fibrosis: therapeutic translation for fibrotic disease. Nat Med (2012) 18(7):1028–40. doi: 10.1038/nm.2807

  • CrossRef
  • Google Scholar

• 73

  MiltingHEllinghausPSeewaldMCakarHBohmsBKassnerAet al. Plasma biomarkers of myocardial fibrosis and remodeling in terminal heart failure patients supported by mechanical circulatory support devices. J Heart Lung Transplant (2008) 27(6):589–96. doi: 10.1016/j.healun.2008.02.018

  • CrossRef
  • Google Scholar

• 74

  KeranovSDörrOJafariLLiebetrauCKellerTTroidlCet al. Osteopontin and galectin-3 as biomarkers of maladaptive right ventricular remodeling in pulmonary hypertension. biomark Med (2021) 15(12):1021–34. doi: 10.2217/bmm-2021-0009

  • CrossRef
  • Google Scholar

• 75

  SubramanianSTawakolABurdoTHAbbaraSWeiJVijayakumarJet al. Arterial inflammation in patients with HIV. Jama (2012) 308(4):379–86. doi: 10.1001/jama.2012.6698

  • CrossRef
  • Google Scholar

• 76

  WalkerJASulcinerMLNowickiKDMillerADBurdoTHWilliamsKC. Elevated numbers of CD163+ macrophages in hearts of simian immunodeficiency virus-infected monkeys correlate with cardiac pathology and fibrosis. AIDS Res Hum Retroviruses (2014) 30(7):685–94. doi: 10.1089/aid.2013.0268

  • CrossRef
  • Google Scholar

• 77

  YearleyJHPearsonCShannonRPMansfieldKG. Phenotypic variation in myocardial macrophage populations suggests a role for macrophage activation in SIV-associated cardiac disease. AIDS Res Hum Retroviruses (2007) 23(4):515–24. doi: 10.1089/aid.2006.0211

  • CrossRef
  • Google Scholar

• 78

  KaniaGBlyszczukPErikssonU. Mechanisms of cardiac fibrosis in inflammatory heart disease. Trends Cardiovasc Med (2009) 19(8):247–52. doi: 10.1016/j.tcm.2010.02.005

  • CrossRef
  • Google Scholar

• 79

  MallardJWilliamsKC. Animal models of HIV-associated disease of the central nervous system. Handb Clin neurol (2018) 152:41–53. doi: 10.1016/B978-0-444-63849-6.00004-9

  • CrossRef
  • Google Scholar

• 80

  StricklandSLGrayRRLamersSLBurdoTHHueninkENolanDJet al. Efficient transmission and persistence of low-frequency SIVmac251 variants in CD8-depleted rhesus macaques with different neuropathology. J Gen Virol (2012) 93(Pt 5):925–38. doi: 10.1099/vir.0.039586-0

  • CrossRef
  • Google Scholar

• 81

  ShannonRPSimonMAMathierMAGengYJMankadSLacknerAA. Dilated cardiomyopathy associated with simian AIDS in nonhuman primates. Circulation (2000) 101(2):185–93. doi: 10.1161/01.CIR.101.2.185

  • CrossRef
  • Google Scholar

• 82

  PetkovDILiuDXAllersCDidierPJDidierESKurodaMJ. Characterization of heart macrophages in rhesus macaques as a model to study cardiovascular disease in humans. J leukocyte Biol (2019) 106(6):1241–55. doi: 10.1002/JLB.1A0119-017R

  • CrossRef
  • Google Scholar

• 83

  Fischer-SmithTBellCCroulSLewisMRappaportJ. Monocyte/macrophage trafficking in acquired immunodeficiency syndrome encephalitis: lessons from human and nonhuman primate studies. J neurovirol (2008) 14(4):318–26. doi: 10.1080/13550280802132857

  • CrossRef
  • Google Scholar

• 84

  Ziegler-HeitbrockL. The CD14+ CD16+ blood monocytes: their role in infection and inflammation. J leukocyte Biol (2007) 81(3):584–92. doi: 10.1189/jlb.0806510

  • CrossRef
  • Google Scholar

• 85

  Ziegler-HeitbrockL. Blood monocytes and their subsets: established features and open questions. Front Immunol (2015) 6:423. doi: 10.3389/fimmu.2015.00423

  • CrossRef
  • Google Scholar

• 86

  ButterfieldTRLandayALAnzingerJJ. Dysfunctional immunometabolism in HIV infection: contributing factors and implications for age-related comorbid diseases. Curr HIV/AIDS Rep (2020) 17(2):125–37. doi: 10.1007/s11904-020-00484-4

  • CrossRef
  • Google Scholar

• 87

  WallisZKWilliamsKC. Monocytes in HIV and SIV infection and aging: implications for inflamm-aging and accelerated aging. Viruses (2022) 14(2). doi: 10.3390/v14020409

  • CrossRef
  • Google Scholar

• 88

  SubramanyaVMcKayHSBruscaRMPalellaFJKingsleyLAWittMDet al. Inflammatory biomarkers and subclinical carotid atherosclerosis in HIV-infected and HIV-uninfected men in the Multicenter AIDS Cohort Study. PloS One (2019) 14(4):e0214735. doi: 10.1371/journal.pone.0214735

  • CrossRef
  • Google Scholar

• 89

  WilliamsDWVeenstraMGaskillPJMorgelloSCalderonTMBermanJW. Monocytes mediate HIV neuropathogenesis: mechanisms that contribute to HIV associated neurocognitive disorders. Curr HIV Res (2014) 12(2):85–96. doi: 10.2174/1570162X12666140526114526

  • CrossRef
  • Google Scholar

• 90

  KulkarniMBowmanEGabrielJAmburgyTMayneEZidarDAet al. Altered monocyte and endothelial cell adhesion molecule expression is linked to vascular inflammation in human immunodeficiency virus infection. Open Forum Infect Dis (2016) 3(4):ofw224. doi: 10.1093/ofid/ofw224

  • CrossRef
  • Google Scholar

• 91

  PulliamLSunBRempelH. Invasive chronic inflammatory monocyte phenotype in subjects with high HIV-1 viral load. J neuroimmunol (2004) 157(1-2):93–8. doi: 10.1016/j.jneuroim.2004.08.039

  • CrossRef
  • Google Scholar

• 92

  VeenstraMByrdDAIngleseMBuyukturkogluKWilliamsDWFleysherLet al. CCR2 on Peripheral Blood CD14(+)CD16(+) Monocytes Correlates with Neuronal Damage, HIV-Associated Neurocognitive Disorders, and Peripheral HIV DNA: reseeding of CNS reservoirs? J neuroimmune Pharmacol (2019) 14(1):120–33. doi: 10.1007/s11481-018-9792-7

  • CrossRef
  • Google Scholar

• 93

  Fischer-SmithTCroulSSverstiukAECapiniCL’HeureuxDRegulierEGet al. CNS invasion by CD14+/CD16+ peripheral blood-derived monocytes in HIV dementia: perivascular accumulation and reservoir of HIV infection. J neurovirol (2001) 7(6):528–41. doi: 10.1080/135502801753248114

  • CrossRef
  • Google Scholar

• 94

  WilliamsDWEugeninEACalderonTMBermanJW. Monocyte maturation, HIV susceptibility, and transmigration across the blood brain barrier are critical in HIV neuropathogenesis. J leukocyte Biol (2012) 91(3):401–15. doi: 10.1189/jlb.0811394

  • CrossRef
  • Google Scholar

• 95

  WilliamsKLacknerAMallardJ. Non-human primate models of SIV infection and CNS neuropathology. Curr Opin virol (2016) 19:92–8. doi: 10.1016/j.coviro.2016.07.012

  • CrossRef
  • Google Scholar

• 96

  BenjaminLABryerAEmsleyHCKhooSSolomonTConnorMD. HIV infection and stroke: current perspectives and future directions. Lancet Neurol (2012) 11(10):878–90. doi: 10.1016/S1474-4422(12)70205-3

  • CrossRef
  • Google Scholar

• 97

  BryantAKMooreDJBurdoTHLakritzJRGouauxBSoontornniyomkijVet al. Plasma soluble CD163 is associated with postmortem brain pathology in human immunodeficiency virus infection. AIDS (London England) (2017) 31(7):973–9. doi: 10.1097/QAD.0000000000001425

  • CrossRef
  • Google Scholar

• 98

  YearleyJHPearsonCCarvilleAShannonRPMansfieldKG. SIV-associated myocarditis: viral and cellular correlates of inflammation severity. AIDS Res Hum Retroviruses (2006) 22(6):529–40. doi: 10.1089/aid.2006.22.529

  • CrossRef
  • Google Scholar

• 99

  KellyKMTarwaterPMKarperJMBedjaDQueenSETuninRSet al. Diastolic dysfunction is associated with myocardial viral load in simian immunodeficiency virus-infected macaques. AIDS (London England) (2012) 26(7):815–23. doi: 10.1097/QAD.0b013e3283518f01

  • CrossRef
  • Google Scholar

• 100

  KellyKMTocchettiCGLyashkovATarwaterPMBedjaDGrahamDRet al. CCR5 inhibition prevents cardiac dysfunction in the SIV/macaque model of HIV. J Am Heart Assoc (2014) 3(2):e000874. doi: 10.1161/JAHA.114.000874

  • CrossRef
  • Google Scholar

• 101

  LaneJHSassevilleVGSmithMOVogelPPauleyDRHeyesMPet al. Neuroinvasion by simian immunodeficiency virus coincides with increased numbers of perivascular macrophages/microglia and intrathecal immune activation. J neurovirol (1996) 2(6):423–32. doi: 10.3109/13550289609146909

  • CrossRef
  • Google Scholar

• 102

  KimWKAlvarezXFisherJBronfinBWestmorelandSMcLaurinJet al. CD163 identifies perivascular macrophages in normal and viral encephalitic brains and potential precursors to perivascular macrophages in blood. Am J pathol (2006) 168(3):822–34. doi: 10.2353/ajpath.2006.050215

  • CrossRef
  • Google Scholar

• 103

  BurdoTHSoulasCOrzechowskiKButtonJKrishnanASugimotoCet al. Increased monocyte turnover from bone marrow correlates with severity of SIV encephalitis and CD163 levels in plasma. PloS pathogens (2010) 6(4):e1000842. doi: 10.1371/journal.ppat.1000842

  • CrossRef
  • Google Scholar

• 104

  LindegaardBHansenABGerstoftJPedersenBK. High plasma level of interleukin-18 in HIV-infected subjects with lipodystrophy. J acquired Immune deficiency syndromes (1999) (2004) 36(1):588–93. doi: 10.1097/00126334-200405010-00006

  • CrossRef
  • Google Scholar

• 105

  TorreDPuglieseA. Interleukin 18 and cardiovascular disease in HIV-1 infection: a partner in crime? AIDS Rev (2010) 12(1):31–9.

  • Google Scholar

• 106

  NasiMDe BiasiSBianchiniEDigaetanoMPintiMGibelliniLet al. Analysis of inflammasomes and antiviral sensing components reveals decreased expression of NLRX1 in HIV-positive patients assuming efficient antiretroviral therapy. AIDS (London England) (2015) 29(15):1937–41. doi: 10.1097/QAD.0000000000000830

  • CrossRef
  • Google Scholar

• 107

  TriantafilouKWardCJKCzubalaMFerrisRGKoppeEHaffnerCet al. Differential recognition of HIV-stimulated IL-1β and IL-18 secretion through NLR and NAIP signalling in monocyte-derived macrophages. PloS pathogens (2021) 17(4):e1009417. doi: 10.1371/journal.ppat.1009417

  • CrossRef
  • Google Scholar

• 108

  LenartNBroughDDenesA. Inflammasomes link vascular disease with neuroinflammation and brain disorders. J Cereb Blood Flow Metab (2016) 36(10):1668–85. doi: 10.1177/0271678X16662043

  • CrossRef
  • Google Scholar

• 109

  Mazaheri-TehraniEMohrazMNasiMChesterJDe GaetanoALo TartaroDet al. NLRP3 and IL-1β Gene expression is elevated in monocytes from HIV-treated patients with neurocognitive disorders. J acquired Immune deficiency syndromes (1999) (2021) 86(4):496–9. doi: 10.1097/QAI.0000000000002588

  • CrossRef
  • Google Scholar

• 110

  MullisCSwartzTH. NLRP3 inflammasome signaling as a link between HIV-1 infection and atherosclerotic cardiovascular disease. Front Cardiovasc Med (2020) 7:95. doi: 10.3389/fcvm.2020.00095

  • CrossRef
  • Google Scholar

• 111

  PremeauxTAMoserCBMcKhannAHoeniglMLawsEIAquinoDLet al. Plasma galectin-9 as a predictor of adverse non-AIDS events in persons with chronic HIV during suppressive antiretroviral therapy. AIDS (London England) (2021) 35(15):2489–95. doi: 10.1097/QAD.0000000000003048

  • CrossRef
  • Google Scholar

• 112

  BonsackFSukumari-RameshS. Differential cellular expression of galectin-1 and galectin-3 after intracerebral hemorrhage. Front Cell Neurosci (2019) 13:157. doi: 10.3389/fncel.2019.00157

  • CrossRef
  • Google Scholar

• 113

  Lalancette-HébertMSwarupVBeaulieuJMBohacekIAbdelhamidEWengYCet al. Galectin-3 is required for resident microglia activation and proliferation in response to ischemic injury. J Neurosci (2012) 32(30):10383–95. doi: 10.1523/JNEUROSCI.1498-12.2012

  • CrossRef
  • Google Scholar

• 114

  TanYZhengYXuDSunZYangHYinQ. Galectin-3: a key player in microglia-mediated neuroinflammation and Alzheimer’s disease. Cell biosci (2021) 11(1):78. doi: 10.1186/s13578-021-00592-7

  • CrossRef
  • Google Scholar

• 115

  VenkatramanAHardasSPatelNSingh BajajNAroraGAroraP. Galectin-3: an emerging biomarker in stroke and cerebrovascular diseases. Eur J neurol (2018) 25(2):238–46. doi: 10.1111/ene.13496

  • CrossRef
  • Google Scholar

• 116

  BeslerCLangDUrbanDRommelKPvon RoederMFenglerKet al. Plasma and cardiac galectin-3 in patients with heart failure reflects both inflammation and fibrosis: implications for its use as a biomarker. Circ Heart failure (2017) 10(3). doi: 10.1161/CIRCHEARTFAILURE.116.003804

  • CrossRef
  • Google Scholar

• 117

  de BoerRAYuLvan VeldhuisenDJ. Galectin-3 in cardiac remodeling and heart failure. Curr Heart failure Rep (2010) 7(1):1–8. doi: 10.1007/s11897-010-0004-x

  • CrossRef
  • Google Scholar

• 118

  Di GregoliKSomervilleMBiancoRThomasACFrankowANewbyACet al. Galectin-3 identifies a subset of macrophages with a potential beneficial role in atherosclerosis. Arteriosclerosis thrombosis Vasc Biol (2020) 40(6):1491–509. doi: 10.1161/ATVBAHA.120.314252

  • CrossRef
  • Google Scholar

• 119

  HaraANiwaMKanayamaTNoguchiKNiwaAMatsuoMet al. Galectin-3: A potential prognostic and diagnostic marker for heart disease and detection of early stage pathology. Biomolecules (2020) 10(9). doi: 10.3390/biom10091277

  • CrossRef
  • Google Scholar

• 120

  LiMYuanYGuoKLaoYHuangXFengL. Value of galectin-3 in acute myocardial infarction. Am J Cardiovasc drugs: drugs devices other interventions (2020) 20(4):333–42. doi: 10.1007/s40256-019-00387-9

  • CrossRef
  • Google Scholar

• 121

  LópezBGonzálezAQuerejetaRZubillagaELarmanMDíezJ. Galectin-3 and histological, molecular and biochemical aspects of myocardial fibrosis in heart failure of hypertensive origin. Eur J Heart failure (2015) 17(4):385–92. doi: 10.1002/ejhf.246

  • CrossRef
  • Google Scholar

• 122

  BeckerJTKingsleyLMullenJCohenBMartinEMillerENet al. Vascular risk factors, HIV serostatus, and cognitive dysfunction in gay and bisexual men. Neurology (2009) 73(16):1292–9. doi: 10.1212/WNL.0b013e3181bd10e7

  • CrossRef
  • Google Scholar

• 123

  McKibbenRAMargolickJBGrinspoonSLiXPalellaFJJr.KingsleyLAet al. Elevated levels of monocyte activation markers are associated with subclinical atherosclerosis in men with and those without HIV infection. J Infect diseases (2015) 211(8):1219–28. doi: 10.1093/infdis/jiu594

  • CrossRef
  • Google Scholar

• 124

  ManeaMMComsaMMincaADragosDPopaC. Brain-heart axis–review article. J Med Life (2015) 8(3):266–71.

  • Google Scholar

• 125

  LifsonJDRossioJLPiatakMJr.ParksTLiLKiserRet al. Role of CD8(+) lymphocytes in control of simian immunodeficiency virus infection and resistance to rechallenge after transient early antiretroviral treatment. J virol (2001) 75(21):10187–99. doi: 10.1128/JVI.75.21.10187-10199.2001

  • CrossRef
  • Google Scholar

• 126

  HansenSGFordJCLewisMSVenturaABHughesCMCoyne-JohnsonLet al. Profound early control of highly pathogenic SIV by an effector memory T-cell vaccine. Nature (2011) 473(7348):523–7. doi: 10.1038/nature10003

  • CrossRef
  • Google Scholar

• 127

  HansenSGPiatakMJr.VenturaABHughesCMGilbrideRMFordJCet al. Immune clearance of highly pathogenic SIV infection. Nature (2013) 502(7469):100–4. doi: 10.1038/nature12519

  • CrossRef
  • Google Scholar

• 128

  LacknerAASmithMOMunnRJMartfeldDJGardnerMBMarxPAet al. Localization of simian immunodeficiency virus in the central nervous system of rhesus monkeys. Am J pathol (1991) 139(3):609–21.

  • Google Scholar

• 129

  SassevilleVGLacknerAA. Neuropathogenesis of simian immunodeficiency virus infection in macaque monkeys. J neurovirol (1997) 3(1):1–9. doi: 10.3109/13550289709015787

  • CrossRef
  • Google Scholar

• 130

  WestmorelandSVHalpernELacknerAA. Simian immunodeficiency virus encephalitis in rhesus macaques is associated with rapid disease progression. J neurovirol (1998) 4(3):260–8. doi: 10.3109/13550289809114527

  • CrossRef
  • Google Scholar

• 131

  WangFFlanaganJSuNWangLCBuiSNielsonAet al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J Mol diagnostics: JMD (2012) 14(1):22–9. doi: 10.1016/j.jmoldx.2011.08.002

  • CrossRef
  • Google Scholar

• 132

  YuanZWangNKangGNiuWLiQGuoJ. Controlling multicycle replication of live-attenuated HIV-1 using an unnatural genetic switch. ACS synthetic Biol (2017) 6(4):721–31. doi: 10.1021/acssynbio.6b00373

  • CrossRef
  • Google Scholar

• 133

  WangLXKangGKumarPLuWLiYZhouYet al. Humanized-BLT mouse model of Kaposi’s sarcoma-associated herpesvirus infection. Proc Natl Acad Sci United States America (2014) 111(8):3146–51. doi: 10.1073/pnas.1318175111

  • CrossRef
  • Google Scholar