Abstract
Background and Objectives
The complex cytokine network in seminal fluid during human immunodeficiency virus (HIV) infection remains incompletely understood. This study aimed to investigate inflammatory cytokine levels in the semen of individuals with chronic HIV infection and assess the effects of antiretroviral therapy ART on cytokine networks.
Materials and Methods
A total of 26 HIV infected individuals were recruited, including 16 treatment-naïve (TN) patients, 10 patients receiving ART for over 2 years with plasma HIV viral loads of < 20 copies/mL (CR group), and 4 healthy controls (HC). Differences in inflammatory cytokine levels were analyzed using the Olink assay in paired seminal plasma and blood samples, along with correlations between cytokine levels and indicators of disease progression. Moreover, differences in cytokine networks between seminal plasma and blood plasma were analyzed, and the effects of ART on these networks were evaluated.
Results
HIV infection and ART altered cytokine networks in seminal plasma compared with those in HC. The levels of semen cluster 1 (interferon-γ, IL-12B, MCP-2, MCP-4, and Flt3L) in the TN group were significantly higher than those in the HC group. HIV infection was associated with increased rigidity of the seminal cytokine network, and significant differences were observed between the cytokine networks of seminal and blood plasma, both with and without ART. Additionally, seminal plasma levels of Flt3L, MCP-4, IL-1alpha, OSM, TWEAK, VEGFA, transforming growth factor-alpha, HGF, NT-3, IL-4, IL-17C, beta-NGF, FGF-19, and TRAIL were significantly correlated with baseline HIV RNA levels and CD4+ T cell counts.
Conclusion
ART had a greater effect on cytokine levels in blood plasma than in seminal plasma. Seminal plasma also exhibited higher concentrations of cytokines associated with indicators of HIV disease progression than blood plasma.
Keywords: cytokine, human immunodeficiency virus, plasma, seminal
Introduction
Human immunodeficiency virus (HIV) infection remains a major global public health concern. The widespread use of combination antiretroviral therapy (ART) has markedly improved the management of HIV infection by suppressing viral replication, promoting CD4+ T cell recovery, prolonging survival, and improving the quality of life of people living with HIV.1 However, ART cannot eliminate HIV-associated immune activation or viral reservoirs. Persistent immune dysregulation may occur despite sustained suppression of plasma viremia, and the extent and characteristics of this residual immune response may differ among anatomical compartments.
The male reproductive tract is an immunologically and pharmacologically distinct compartment because of the blood–testis and blood–paratestis barriers.2–4 Although antiretroviral drugs can reach the reproductive tract, their penetration and distribution may be limited or heterogeneous, potentially resulting in drug exposure that differs from that in peripheral blood.5 Accordingly, HIV suppression in plasma may not necessarily indicate equivalent control of HIV infection or complete immune normalization within the male reproductive tract. Consistent with this possibility, our preliminary study detected HIV-positive signals in sperm-associated fractions after at least 2 years of ART, despite undetectable HIV levels in peripheral blood.2 This finding, together with previous evidence of HIV compartmentalization between blood and semen,3,4 suggests that the male reproductive tract may serve as a site of HIV persistence and local immune dysregulation during ART.
Seminal plasma contains a complex network of inflammatory cytokines that reflects the local immune environment of the male reproductive tract. These mediators may contribute to local inflammation, alterations in barrier and epithelial function, and the regulation of HIV shedding and potential sexual transmission risk.6–9 Importantly, the immune microenvironment of semen differs substantially from that of blood in people living with HIV, including differences in cytokine concentrations and the organization of cytokine interactions.6,7 Previous studies comparing cytokines in semen and blood have generally examined a limited number of analyses. In our earlier analysis of 34 inflammatory cytokines, interleukin (IL)-7 and IL-15 indicated significant differences between seminal plasma and blood plasma before and after ART.7 Additionally, IL-15 has been associated with HIV disease progression.10 These findings suggest that seminal cytokines may provide information that is not fully captured by systemic measurements. However, the broader inflammatory cytokine network in seminal plasma and its response to ART, relative to the systemic cytokine network, remain incompletely understood.
We hypothesized that ART would normalize inflammatory cytokines in blood plasma more effectively than in seminal plasma because of anatomical compartmentalization, differences in drug distribution, and distinct local immune regulation within the male reproductive tract. To test this hypothesis, we profiled 92 inflammation-related proteins in treatment-naïve individuals with HIV infection (TN group), individuals with HIV infection who achieved a complete response to ART (CR group), and healthy controls (HC group). We compared cytokine levels between seminal plasma and blood plasma and assessed the rigidity of cytokine networks in TN and CR groups. Characterizing the differential effects of ART on systemic and seminal immune responses may improve our understanding of residual HIV transmission risk and viral persistence within the male reproductive tract. It may also provide a basis for developing strategies to target compartmentalized HIV reservoirs and improve the prospects of achieving a functional cure.
Materials and Methods
Participants and Samples
This exploratory study enrolled 26 individuals with HIV infection from the Fifth Medical Center of the Chinese PLA General Hospital. Of these, 16 individuals were assigned to the TN group, and 10 were assigned to the CR group, which included individuals who had received ART for over two years and had plasma HIV viral loads of < 20 copies/mL. Four HCs were also included. Patients were excluded if they were pregnant, had chronic hepatitis B or hepatitis C infection, were receiving immunosuppressive therapy or had a moribund condition. Clinical characteristics, including age, CD4+ T cell count, CD8+ T cell count, and plasma HIV RNA load, are presented in Table 1.
Table 1.
Clinical Characteristics of Study Population
| TN (n=16) | CR (n=10) | HC (n=4) | Pa | |
|---|---|---|---|---|
| Age (years) | 28 (23–33.5) | 32.5 (26.25–37.25) | 29 (27.75–30.5) | 0.27 |
| CD4 T cell (cells/μL) | 308.5 (207–355) | 551 (552.5–601) | 774 (731.25–816.50) | 0.0004 |
| CD8 T cell (cells/μL) | 1004.97 (823.17–1300) | 1287.78 (1010.24–1400.45) | 811.88 (786.24–840) | 0.17 |
| Viral load (log 10 copies/mL) | 4.65 (4.10–5.01) | 1.30 (1.30–1.30) | NA | <0.0001 |
| ART regimen, n (%) | 0.66 | |||
| NRTIs + NNRTIs | 12 (75%) | 6 (60%) | NA | |
| c | 4 (25%) | 4 (40%) | NA |
Notes: Continuous variables are expressed as the median (interquartile range, IQR) and categorical variables are expressed as the number of cases (%). aThe P value is the statistical difference analysis between the TN group and the CR group by the Mann–Whitney U-test. The difference was statistically significant when P < 0.05.
Abbreviations: HIV, human immunodeficiency virus; ART, antiretroviral therapy; TN, treatment-naïve HIV-infected individual; HC, health control; NRTIs, nucleoside reverse transcriptase inhibitors; NNRTIs, non-nucleoside reverse transcriptase inhibitors; PIs, protease inhibitors.
Sample Collection
Peripheral blood mononuclear cells were isolated using Ficoll–Hypaque (MD Pacific Biotechnology, Tianjin, China) density-gradient centrifugation. Plasma samples were collected and stored at –80 °C until further analysis. Semen samples were obtained by masturbation and collected directly into sterile containers. For TN participants, the first dose of ART was administered after the collection of semen samples. All semen samples were processed within 2 h of collection. Fresh semen samples were centrifuged at 2000 rpm for 10 min, and the upper-layer supernatant was collected as seminal plasma and stored at –80 °C until further analysis.
Flow Cytometry
Peripheral blood mononuclear cells (at least 1×106 cells) were stained with fluorescently labeled antibodies in the dark at 4 °C for 30 min and subsequently washed. Antibodies were used at a concentration of 5 μL per test (1 × 106 cells in 100 μL of staining buffer). Antibody titration was performed to determine the optimal working concentration for the multicolor flow cytometry panel. Multicolor flow cytometry was performed using fluorescently conjugated antibodies, including CD3-APC-Cy7, CD4-BV605, and CD8-BV510, obtained from BD Biosciences (Franklin Lakes, NJ, USA). Cells were analyzed using a FACS flow cytometer (BD Biosciences). Fluorescence-minus-one controls were not used. The data were analyzed using FlowJo software (version 10.8; Tree Star, Ashland, OR, USA). Lymphocytes were initially gated, followed by the identification of CD3-positive cells. CD4-positive and CD8-positive T cell subsets were further identified within the CD3⁺ cell population.
Quantification of Plasma HIV RNA
HIV RNA levels were quantified using the COBAS AmpliPrep/TaqMan HIV Test, a real-time reverse transcription-polymerase chain reaction (PCR) assay (Roche, Basel, Switzerland).
Proteomic Profiling of Soluble Factors in Semen and Plasma
Plasma and seminal plasma samples from the cohort were quantified using an Olink multiplex proximity extension assay (PEA) inflammation panel, which measures 92 inflammation-related proteins (Olink Bioscience AB, Uppsala, Sweden; Supplementary Box S1). PEA uses pairs of oligonucleotide-labeled antibodies that specifically bind to target proteins. When two antibodies bind in proximity, a proximity-dependent DNA polymerization reaction generates a new DNA sequence that serves as a target for the polymerase chain reaction.
The resulting sequences were detected and quantified using real-time PCR. The normalized protein expression (NPX) values derived from the Olink platform have distributional characteristics similar to those of log2-transformed protein concentrations. Of the 60 samples initially included, two were excluded from the final analysis because of quality-control failure or deviation from the target population. Additional details on the Olink assay can be found at http://www.olink. com. Venn diagrams were constructed using an online platform (http://www.ehbio.com/test/venn). Raw PEA signals were converted to log2-scaled NPX values and globally intensity-normalized to correct for inter-plate variation using the Olink Analyze R package. For each assay, the limit of detection (LOD) was defined as the median negative-control signal + three standard deviations. Proteins with > 25% of measurements below the LOD were excluded, whereas sporadic values below LOD were replaced with LOD/√2. Samples that failed quality control and proteins with a missing-data rate of > 20% were discarded. The remaining randomly missing values were imputed using the k-nearest neighbors algorithm. The preprocessed NPX data were used for all subsequent statistical comparisons.
The normality of NPX values for each protein was evaluated separately. Graphical diagnostics, including histograms with fitted normal distribution curves and quantile–quantile plots, were used for visual assessment. Skewness and kurtosis were calculated as descriptive indicators, and the Shapiro–Wilk test was used to quantitatively assess normality. For proteins with a substantial proportion of values below the LOD, all sub-LOD NPX signals were replaced with the LOD threshold before the normality evaluation. Data were considered approximately normally distributed when the Shapiro–Wilk P value was > 0.05, the graphical assessments indicated an approximately symmetric distribution, and the skewness and kurtosis values were within acceptable ranges. Non-parametric statistical analyses were used for proteins that violated normality assumptions.
Statistical Analysis
Data were analyzed using the Statistical Package for the Social Sciences (version 22.0; Inc., Chicago, IL, USA), GraphPad Prism (version 8.0; GraphPad, Inc., San Diego, CA, USA), and RStudio (version 3.6.4; RStudio, Boston, MA, USA) software. Continuous variables are presented as median interquartile ranges, whereas categorical variables are presented as counts (%). The chi-square χ2 test was used to compare categorical data between groups.
The Kruskal–Wallis test was used for comparisons involving more than two groups, whereas the Mann–Whitney U-test was employed for between-group comparisons of continuous data. Correlations between two continuous variables were assessed using Spearman’s rank correlation test. For correlation analyses presented in the cytokine correlation heatmaps, statistical significance was determined using two-sided Benjamini–Hochberg-adjusted Author Proof Photograph P values, with statistical significance defined as an adjusted P < 0.05. The remaining statistical analyses were reported using nominal Author Proof Photograph P values because they were not included in the predefined correlation-analysis families. Unless otherwise specified, a two-sided P < 0.05 was considered statistically significant.
Results
HIV Infection Alters Seminal Plasma Cytokine Levels
To clarify the effects of HIV infection on inflammatory cytokine levels, we examined 92 inflammation-related proteins in blood plasma and seminal plasma using the Olink system. We compared inflammatory cytokine levels among individuals in the TN, CR, and HC groups. The overall expression patterns of the 92 inflammatory cytokines in seminal plasma are depicted in Figure 1A. Compared with the HC group, the TN group had significantly higher seminal plasma levels of IL-18, IL-20RA, matrix metallopeptidase (MMP)-1, programmed death-ligand 1 (PD-L1), cluster of differentiation 5 (CD5), C-C motif chemokine (CCL19), and hepatocyte growth factor (HGF) (Figure 1B). In the CR group, seminal plasma levels of Fms-related tyrosine kinase 3 receptor ligand (Flt3L), interferon (IFN)-γ, IL-12B, MMP-1, HGF, and caspase 8 (CASP-8) were significantly higher than those in the HC group (Figure 1C). Additionally, compared with the CR group, the TN group had significantly lower seminal plasma levels of latency-associated peptide (LAP), transforming growth factor (TGF)-β1, C-X-C motif chemokine ligand (CXCL) 6, extracellular newly identified receptor for advanced glycation end-products binding protein (EN-RAGE), and leukemia inhibitory factor (LIF). Conversely, the TN group had significantly higher levels of monocyte chemoattractant protein (MCP)-2, IL-10RB, CCL19, and CUB domain-containing protein 1 (CDCP1) than in the CR group (Figure 1D). Blood plasma cytokine levels are indicated in Supplementary Figure 1. These results suggest that HIV infection alters cytokine levels in seminal plasma and that ART does not completely normalize all HIV-associated alterations in seminal inflammatory factors.
Figure 1.
Differences in seminal cytokine levels between individuals with HIV infection and HCs. (A) Heatmap of seminal plasma cytokine levels of individuals with HIV infection and HCs. (B) Volcano plots of seminal cytokines that significantly differed between TN individuals infected with HIV and HCs. Blue dots in the graph represent proteins that were significantly lower in the TN group than in HCs. Gray dots on the lower side represent proteins that did not significantly differ between the two groups. (C) Volcano plots of significantly different seminal cytokine levels between individuals with HIV infection on ART who achieved a CR and HCs. Red dots in the graph represent proteins that were significantly increased in the individuals in the CR group compared with HCs. Gray dots on the lower side represent proteins that did not significantly differ between the two groups. (D) Volcano plots of significantly different seminal cytokine levels between the individuals in TN and CR groups. Red and blue dots in the graph represent proteins that were significantly increased and decreased in the individuals in the TN group compared with those in the CR group. Gray dots on the lower side represent proteins that did not significantly differ between the two groups. P < 0.05 and false discovery rate < 0.05 were considered significant.
Different Patterns Across Five Seminal Cytokine Clusters
To better understand inflammatory cytokine levels in the seminal plasma, cytokines that differed significantly among TN, CR, and HC groups were classified into five clusters according to their functional characteristics.11 Cluster 1 (T helper [Th]1/Th2 cytokines) included IFN-γ, IL-10RB, IL-12B, MCP-2, MCP-4, Flt3L, CDCP1, and CCL19. Cluster 2 (Th17 cytokines) included IL-17C, IL-20RA, IL-18, CD5, IL-15RA, and LAP TGF-β1. Cluster 3 (cell growth and development cytokines) included HGF, TGF-α, and MMP-1. Cluster 4 (pro-inflammatory cytokines) included LIF and EN-RAGE. Cluster 5 (T cell exhaustion) included PD-L1 and CASP-8.
Within cluster 1, seminal plasma levels of IFN-γ, IL-12B, MCP-2, MCP-4, Flt3L, and CCL19 were significantly higher in the TN group than in the HC group. Additionally, IL-10RB, MCP-2, CDCP1, and CCL19 levels were significantly higher in the TN group than in the CR group (Figure 2A, cluster 1). Within cluster 2, seminal plasma IL-20RA levels were significantly higher in the TN group than in the CR group. Additionally, the seminal plasma levels of IL-18, IL-17C, IL-15RA, and CD5 were significantly higher in the CR group than in the HC group (Figure 2B, cluster 2). Within cluster 3, seminal plasma HGF and MMP-1 levels were significantly higher in the TN group than in the HC group. However, HGF levels were significantly lower in the TN group than in the CR group, whereas TGF-α levels were significantly higher in the CR group than in the HC group (Figure 2C, cluster 3). Within cluster 4, seminal plasma levels of LIF and EN-RAGE were significantly higher in the CR group than in the TN group (Figure 2D, cluster 4). Within cluster 5, CASP-8 levels were significantly higher in the CR group than in the HC group, whereas PD-L1 levels were significantly higher in the TN group than in the HC group (Figure 2E, cluster 5). The levels of cytokines in the five corresponding blood plasma cytokine clusters are depicted in Supplementary Figure 2.
Figure 2.
Seminal cytokines indicating significant differences in TN, CR, and HC groups were classified into five clusters. (A) Levels of eight semen cytokines in cluster 1 (Th1/Th2 cytokines) significantly differed among TN, CR, and HC groups. (B) Levels of six semen cytokines in cluster 2 (Th17 cytokines) significantly differed among TN, CR, and HC groups. (C) Levels of three semen cytokines in cluster 3 (cell growth and development cytokines) significantly differed among TN, CR, and HC groups. (D) Levels of two seminal cytokines in cluster 4 (pro-inflammatory cytokines) and (E) cluster 5 (T cell exhaustion) significantly differed among TN, CR, and HC groups. *P < 0.05, **P < 0.01, ***P < 0.001.
Abbreviations: ns, not significant.
Differences in Cytokine Networks Between Seminal and Blood Plasma
To assess the correlation between inflammatory cytokines in seminal plasma and blood plasma, we constructed clustered heatmaps based on pairwise Spearman correlation coefficients between the measured proteins. The cytokine networks in seminal plasma and blood plasma differed significantly between untreated individuals with HIV infection and those receiving ART. In particular, ART was associated with significant alterations in the rigidity of the cytokine network in both seminal plasma (Figures 3A and B) and blood plasma (Figure 3C and D). Among TN individuals, the rigidity of the cytokine network differed significantly between seminal plasma (Figure 3A) and blood plasma (Figure 3C). Similarly, among individuals receiving ART, significant differences were observed between the cytokine networks in seminal plasma (Figure 3B) and blood plasma (Figure 3D). These results indicate that the inflammatory cytokine networks and immune microenvironments differ substantially between the male reproductive tract and the peripheral blood compartment.
Figure 3.
Seminal and plasma cytokine network in HIV infection. (A) Heatmap of the correlation between cytokines in the semen of TN individuals infected with HIV. (B) Heatmap of the correlation between cytokines in the semen of individuals infected with HIV on ART who achieved a CR. (C) Heatmap of the correlation between cytokines in the plasma of individuals in the TN group. (D) Heatmap of the correlation between cytokines in the plasma of individuals in the CR group. Horizontal and vertical coordinates in the graph represent protein names. Red indicates a positive correlation, blue indicates a negative correlation, and a darker color indicates a higher degree of correlation. *P < 0.05, **P < 0.01, ***P < 0.001.
As depicted in Figure 4A, seminal plasma exhibited significantly higher levels of CXCL9, CXCL10, and CXCL11 and significantly lower levels of IL-18 and Flt3L than blood plasma. Among individuals in the TN group, seminal plasma levels of IL-8, IL-10B, and LAP TGF-β1 were significantly higher than those in blood plasma, whereas levels of MMP-1, IL-2, IL-10RA, CD8A, and CD6 were significantly lower (Figure 4B). Among individuals in the CR group, seminal plasma levels of IL-8, CASP-8, STAMBP, MMP-10, CXCL10, CXCL6, and TGF-α were significantly higher than those in blood plasma, whereas only IL-18 levels were significantly lower in seminal plasma (Figure 4C). These results indicate that seminal and blood plasma exhibit distinct inflammatory cytokine profiles and that ART may differentially affect cytokine regulation in the hematological and reproductive systems.
Figure 4.
Differences in cytokines between semen and plasma in TN, CR, and HC groups. (A) Volcano plots of significantly different cytokine levels between semen and plasma in HCs. (B) Volcano plots of significantly different cytokine levels between semen and plasma in the individuals in the TN group. (C) Volcano plots of significantly different cytokine levels between semen and plasma in the individuals in the CR group. Red and blue dots in the graph represent proteins that were significantly increased and decreased, respectively, in the former group compared with the latter group. Gray dots on the lower side represent proteins that did not significantly differ between the two groups. P < 0.05 and false discovery rate < 0.05 were considered significant.
Cytokine Levels in Seminal Plasma are Associated with Disease Progression
To clarify the correlation between cytokine levels and indicators of HIV disease progression, we analyzed the correlations between cytokine levels in seminal and blood plasma and baseline HIV RNA levels and CD4+ T cell counts among individuals in the TN group. In seminal plasma, Flt3L and MCP-4 levels were significantly positively correlated with baseline HIV RNA levels. In contrast, IL-1α, oncostatin M, TNF-related weak inducer of apoptosis, and VEGFA levels were significantly negatively correlated with baseline HIV RNA levels (Figure 5A). Additionally, seminal plasma levels of Flt3L, TGF-α, MCP-4, HGF, NT-3, IL-4, IL-17C, and β-NGF were significantly negatively correlated with baseline CD4+ T cell counts. Conversely, levels of FGF-19, IL-1α, TNF-related apoptosis-inducing ligand, TNF-related weak inducer of apoptosis, and VEGFA were significantly positively correlated with baseline CD4+ T cell counts (Figure 5B). In the blood plasma, Flt3L levels were significantly positively correlated with baseline HIV RNA levels (Figure 6A) and significantly negatively correlated with baseline CD4+ T cell counts (Figure 6B). These results indicate that multiple cytokines in seminal plasma were correlated with indicators of HIV disease progression, whereas only Flt3L indicated significant associations with both baseline HIV RNA levels and CD4+ T-cell counts in blood plasma.
Figure 5.
Correlation analysis of seminal cytokine levels with plasma HIV RNA and CD4+ T cell counts. (A) Linear regression between seminal cytokine levels and baseline plasma HIV RNA levels. (B) Linear regression between seminal cytokine levels and baseline CD4+ T cell counts. P < 0.05 is considered significant. Gray color represents the 95% confidence interval.
Figure 6.
Correlation analysis of blood plasma cytokine levels with plasma HIV RNA and CD4+ T cell counts. (A) Linear regression between plasma cytokine levels and baseline plasma HIV RNA levels. (B) Linear regression between plasma cytokine levels and baseline CD4+ T cell count. Pearson’s correlation coefficient. P < 0.05 is considered significant. Gray color represents the 95% confidence interval.
Discussion
In this study, we examined 92 inflammatory cytokines in paired seminal plasma and plasma samples from individuals infected with HIV, including TNs, CRs, and HCs. We found significant differences in the cytokine networks between seminal plasma and blood plasma. Our results indicate that cytokine networks between the semen and blood have distinct rigidities, providing insight into the potential differential roles of systemic and testicular immunity in HIV infection and the inflammatory response. HIV infection reduces the freedom of cytokine networks by increasing the correlation between cytokines,9,12,13 which aligns with our findings. Changes in the cytokine network persist throughout the chronic phase of infection, even after ART and suppression of plasma HIV RNA levels.13 Cytokine networks should be flexible to respond to various microbial challenges. Therefore, increased correlations in cytokine networks induced by HIV infection may be a crucial factor contributing to HIV-mediated immune deficiency.12
Our cluster-level observations align with earlier reports of increased seminal inflammatory cytokines, including IFN-γ, IL-15, LAP-TGF-β1, and TGF-α in HIV infection.9,13–20 The most prominent alterations in our study occurred in the Th1/Th2 and Th17-related cytokine clusters. Within the Th1/Th2 cluster, seminal IFN-γ, IL-12B, MCP-2, MCP-4, Flt3L and CCL19 were higher in TNs than HCs; IL-10RB, MCP-2, CDCP1 and CCL19 were also higher in TNs than CRs. These results indicate that untreated HIV triggers coordinated activation of cytokines regulating T-cell polarization, antigen-presenting cell function and immune cell recruitment, rather than isolated upregulation of single inflammatory mediators. This finding aligns with prior work indicating enriched Th1/Th2-associated cytokines in semen of HIV-positive individuals.21 As a canonical Th1 cytokine, IFN-γ enhances cytotoxic T-cell and anti-HIV lymphocyte activity.22 Elevated seminal IFN-γ in TNs may reflect ongoing local antiviral responses; however, this inflammatory milieu recruits HIV-susceptible cells and fails to contain viral replication. In the male genital tract, innate mediators and chemokines synergistically promote T-cell activation, immune trafficking, and local viral replication.23 Therefore, increased IFN-γ and related cytokines mark not only protective immunity but also an immune-activated microenvironment permissive to HIV persistence.
The Th17-related cluster indicated distinct expression patterns: IL-20RA was higher in TNs than CRs, while IL-18, IL-17C, IL-15RA, and CD5 were increased in CRs compared with HCs. Th17 cytokines maintain mucosal barrier homeostasis and immune surveillance; IL-22, produced by Th17, Th22, and mucosal invariant T cells, regulates mucosal immunity.24 HIV infection commonly disrupts Th17/Th22 mucosal function, and ART cannot fully reverse such mucosal immunopathology.25,26 Accordingly, sustained Th17-related signals in CRs suggest incomplete normalization of genital immunity despite systemic viral suppression, possibly reflecting ongoing tissue-specific immune reconstitution.
Seminal plasma contains abundant inflammatory chemokines and adaptive immune mediators with more activated T cells than blood plasma,9 forming a local feedback loop of cytokine release, immune recruitment and target cell activation. For example, IL-2 expands HIV target cells to facilitate replication;27 IL-7 maintains antiviral CD8+ T cells in genital epithelium;22,28,29 IL-8 recruits neutrophils for opsonized HIV clearance,30–32 whereas IL-15 enhances HIV progression.32–34 Collectively, seminal cytokines exert context-dependent roles balancing antiviral defense, mucosal protection, and viral persistence.
Inflammation is the primary feature of HIV infection, and changes in inflammatory cytokines exhibit distinct characteristics in the blood and male reproductive systems. The timing and efficacy of ART can affect the blood and semen, which aligns with our findings depicted in Figures 3 and 4. The differences in the correlation of cytokine networks in semen and blood, and the differences in the levels of inflammatory factors, may be attributed to the stronger interplay of cytokines in the semen after HIV infection. This leads to the establishment of a new and more rigid cytokine network.12,35,36 In the male reproductive system, the enrichment of cytokines involved in innate immune responses and chemokines in males with HIV infection complement each other, creating an environment favorable for T cell activation and viral replication.37 The unique immune status characterized by cytokine and chemokine enrichment in the semen further contributes to their elevation upon HIV infection, creating a suitable immunological environment for HIV infection and replication.15
A significant difference in semen cytokine levels has been reported between individuals who transmitted HIV to their sexual partners and men who had sex with men.7 In individuals with HIV, numerous cytokines or chemokines are increased in genital secretions,9,13–15,37–39 contributing to enhanced local HIV replication and dissemination, potentially promoting the sexual transmission of HIV.24 However, this difference was not observed in plasma cytokine levels,7 suggesting that the local immune environment in the male reproductive system, as reflected by semen cytokine levels, plays a role in HIV transmission dynamics among men who have sex with men. Systematic and in-depth research on semen cytokine levels that reflect the risk of sexual transmission is lacking.
Moreover, our results demonstrate that cytokines associated with HIV RNA and CD4+ T cell counts were significantly more prevalent in the seminal plasma than the blood plasma. Consistent with previous reports, the levels of several cytokines (IL-1α, IL-15, and TNF-α) in the semen of individuals infected with HIV were significantly higher than in individuals without HIV and were correlated with the viral load.9,40 MCP-2/MCP-3 increase HIV replication through their pro-inflammatory effects and the recruitment of macrophages/dendritic cells.41 We observed a significant positive correlation between Flt3L levels in seminal plasma and plasma HIV RNA, and a significant negative correlation with the baseline CD4+ T cell count. Similar results were observed in the blood plasma. These results suggest a close correlation between HIV infection and Flt3L levels in the semen and blood. Flt3L, a tyrosine kinase receptor, belongs to the colony-stimulating factor family. It can stimulate the proliferation and differentiation of stem cells and induce the maturation of IFN-secreting plasmacytoid dendritic cells, CD8+ dendritic cells, and their CD103+ tissue counterpart dendritic cells, thereby linking the innate and adaptive immune responses.42 Our findings indicate that Flt3L levels are significantly higher in both semen and blood among individuals with HIV infection, suggesting an association between Flt3L and HIV pathogenesis. Increased Flt3L levels may be attributed to viral infection of immune cells within the semen, leading to the secretion of this cytokine as a part of the immune response against HIV.43
Collectively, our results demonstrate HIV-induced remodeling of the seminal immune microenvironment, with coordinated activation of antiviral and mucosal pathways, persistent tissue remodeling and inflammation post-ART, and coexisting immune activation and inhibitory signaling that differ from semen and blood. Seminal cytokine clusters may serve as biomarkers of genital inflammation and complement conventional blood indices. Additionally, persistent cytokine perturbation under ART suggests inflammation-targeted interventions should consider tissue-specific immunity instead of relying solely on systemic monitoring. The implications remain hypothesis-generating. This correlational profiling study cannot establish causality, and we did not characterize cellular cytokine sources, functional effects, or the link between cytokine signatures and HIV shedding/transmission. Larger longitudinal cohorts, independent validation, cellular assays, and functional experiments are required to verify the reproducibility and clinical utility of these cytokine clusters for monitoring genital inflammation and HIV transmission risk.
Our study has several limitations. Initially, obtaining semen samples was challenging, resulting in a relatively small number of samples. Nevertheless, we will continue to collect additional specimens to expand the sample size. Second, longitudinal changes in semen cytokine levels were not examined. Establishing a longitudinal cohort to analyze variations in semen cytokine levels before and after ART in the same infected individuals would provide a deeper, more comprehensive understanding of the impact of ART on the semen immune microenvironment. Further studies are needed to determine the detailed quantitative relationship between semen cytokines. They may present potential implications for HIV sexual transmission and clearing the viral reservoir from the reproductive system.
In conclusion, seminal and blood plasma cytokine levels were changed by HIV infection. However, even after long-term effective ART, significant changes in cytokine levels in the seminal plasma remained observed, even when patients achieved CR. Furthermore, levels of various cytokines in the seminal plasma were closely related to the HIV RNA levels and CD4+ T-cell count, indicating the severity of HIV infection. These findings improve our understanding of the immune environment of the seminal fluid in HIV infection.
Acknowledgments
Thanks for the support from the National Natural Science Foundation of China.
Funding Statement
This work was funded by the National Natural Science Foundation of China (82302510).
Abbreviations
ART, antiretroviral therapy; CCL19, C-C motif chemokine 19; CD5, cluster of differentiation 5; CR, complete response; CASP-8, caspase 8; CXCL6, C-X-C motif chemokine ligand 6; CDCP1, CUB domain-containing protein 1; CST-5, cystatin D; EN-RAGE, glycation end-products binding protein; Flt3L, The ligand of Fms-related tyrosine kinase 3 ligand receptor; FGF, fibroblast growth factor; HIV, human immunodeficiency virus; HGF, hepatocyte growth factor; HC, healthy control; IFN-γ, Interferon γ; IL-15, Interleukin 15; LAP, latency-associated peptide; LIF, leukemia inhibitory factor; MMP-1, matrix metallopeptidase 1; MCP-2, monocyte chemoattractant protein 2; NGF, β-nerve growth factor; NT-3, neurotrophin-3; PD-L1, programmed death-ligand 1; SIRT2, sirtuin 2; SLAMF1, signaling lymphocytic activation molecule family member 1; ST1A1, signaling lymphocytic activation molecule 1; STAMBP, STAM binding protein; TN, treatment-naïve; TGF-α, growth factor α; TNF, tumor necrosis factor; TNFRSF9, receptor superfamily member 9; VEGFA, vascular endothelial growth factor A.
Data Sharing Statement
The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.
Ethics Approval and Consent to Participate
This study was conducted in accordance with the declaration of Helsinki. This study was conducted with approval from the Ethic committee of The Second Qilu Hospital of Shandong University (KYLL-2023-044). The written informed consent was obtained from the participants or their guardians.
Consent for Publication
The written informed consent was obtained from the participants or their guardians.
Disclosure
All authors declare that they have no conflict of interests.
References
- 1.Hayes RJ, Donnell D, Floyd S, et al. Effect of universal testing and treatment on HIV incidence - HPTN 071 (PopART). New Engl J Med. 2019;381(3):207–14. doi: 10.1056/NEJMoa1814556 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Gao L, Jiao YM, Ma P, et al. Characterization and distribution of HIV-infected cells in semen. Emerging Microbes Infect. 2022;11(1):860–872. doi: 10.1080/22221751.2022.2049982 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Chaillon A, Gianella S, Wertheim JO, Richman DD, Mehta SR, Smith DM. HIV migration between blood and cerebrospinal fluid or semen over time. J Infect Dis. 2014;209(10):1642–1652. doi: 10.1093/infdis/jit678 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chaillon A, Smith DM, Vanpouille C, et al. HIV trafficking between blood and semen during early untreated HIV infection. J Acquired Imm Deficiency Syndr. 2017;74(1):95–102. doi: 10.1097/qai.0000000000001156 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Matusali G, Dereuddre-Bosquet N, Le Tortorec A, et al. Detection of simian immunodeficiency virus in semen, urethra, and male reproductive organs during efficient highly active antiretroviral therapy. J Virol. 2015;89(11):5772–5787. doi: 10.1128/jvi.03628-14 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Nguyen PV, Kafka JK, Ferreira VH, Roth K, Kaushic C. Innate and adaptive immune responses in male and female reproductive tracts in homeostasis and following HIV infection. Cell Mol Immunol. 2014;11(5):410–427. doi: 10.1038/cmi.2014.41 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Rawlings SA, Torres F, Wells A, et al. Effect of HIV suppression on the cytokine network in blood and seminal plasma. AIDS. 2022;36(5):621–630. doi: 10.1097/qad.0000000000003146 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Vanpouille C, Frick A, Rawlings SA, et al. Cytokine network and sexual human immunodeficiency virus transmission in men who have sex with men. Clinl Infect Dis. 2020;71(10):2655–2662. doi: 10.1093/cid/ciz1150 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Olivier AJ, Masson L, Ronacher K, et al. Distinct cytokine patterns in semen influence local HIV shedding and HIV target cell activation. J Infect Dis. 2014;209(8):1174–1184. doi: 10.1093/infdis/jit649 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Santarelli L, Gaetani S, Monaco F, et al. Four-miRNA signature to identify asbestos-related lung malignancies. Cancer Epidemiol Biomarkers Prev. 2019;28(1):119–126. doi: 10.1158/1055-9965.Epi-18-0453 [DOI] [PubMed] [Google Scholar]
- 11.Nganou-Makamdop K, Talla A, Sharma AA, et al. Translocated microbiome composition determines immunological outcome in treated HIV infection. Cell. 2021;184(15):3899–3914.e16. doi: 10.1016/j.cell.2021.05.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Lisco A, Introini A, Munawwar A, et al. HIV-1 imposes rigidity on blood and semen cytokine networks. Am J Reprod Immunol. 2012;68(6):515–521. doi: 10.1111/aji.12015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Vanpouille C, Introini A, Morris SR, et al. Distinct cytokine/chemokine network in semen and blood characterize different stages of HIV infection. AIDS. 2016;30(2):193–201. doi: 10.1097/qad.0000000000000964 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Lisco A, Munawwar A, Introini A, et al. Semen of HIV-1-infected individuals: local shedding of herpesviruses and reprogrammed cytokine network. J Infect Dis. 2012;205(1):97–105. doi: 10.1093/infdis/jir700 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Berlier W, Bourlet T, Lévy R, Lucht F, Pozzetto B, Delézay O. Amount of seminal IL-1beta positively correlates to HIV-1 load in the semen of infected patients. J Clin Virol. 2006;36(3):204–207. doi: 10.1016/j.jcv.2006.04.004 [DOI] [PubMed] [Google Scholar]
- 16.Katsikis PD, Mueller YM, Villinger F. The cytokine network of acute HIV infection: a promising target for vaccines and therapy to reduce viral set-point? PLoS Pathogens. 2011;7(8):e1002055. doi: 10.1371/journal.ppat.1002055 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hoffman JC, Anton PA, Baldwin GC, et al. Seminal plasma HIV-1 RNA concentration is strongly associated with altered levels of seminal plasma interferon-γ, interleukin-17, and interleukin-5. AIDS Res Hum Retroviruses. 2014;30(11):1082–1088. doi: 10.1089/aid.2013.0217 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kafka JK, Osborne BJ, Sheth PM, et al. Latent TGF-β1 is compartmentalized between blood and seminal plasma of HIV-positive men and its activation in semen is negatively correlated with viral load and immune activation. Am J Reprod Immunol. 2015;73(2):151–161. doi: 10.1111/aji.12300 [DOI] [PubMed] [Google Scholar]
- 19.Rametse CL, Adefuye AO, Olivier AJ, et al. Inflammatory cytokine profiles of semen influence cytokine responses of cervicovaginal epithelial cells. Front Immunol. 2018;9:2721. doi: 10.3389/fimmu.2018.02721 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Houzet L, Pérez-Losada M, Matusali G, et al. Seminal simian immunodeficiency virus in chronically infected cynomolgus macaques is dominated by virus originating from multiple genital organs. J Virol. 2018;92(14). doi: 10.1128/jvi.00133-18 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Liao W, Lin JX, Leonard WJ. IL-2 family cytokines: new insights into the complex roles of IL-2 as a broad regulator of T helper cell differentiation. Curr Opin Immunol. 2011;23(5):598–604. doi: 10.1016/j.coi.2011.08.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Rihn SJ, Foster TL, Busnadiego I, et al. The envelope gene of transmitted HIV-1 resists a late interferon gamma-induced block. J Virol. 2017;91(7). doi: 10.1128/jvi.02254-16 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Politch JA, Tucker L, Bowman FP, Anderson DJ. Concentrations and significance of cytokines and other immunologic factors in semen of healthy fertile men. Hum Reprod. 2007;22(11):2928–2935. doi: 10.1093/humrep/dem281 [DOI] [PubMed] [Google Scholar]
- 24.Introini A, Vanpouille C, Lisco A, Grivel JC, Margolis L. Interleukin-7 facilitates HIV-1 transmission to cervico-vaginal tissue ex vivo. PLoS Pathogens. 2013;9(2):e1003148. doi: 10.1371/journal.ppat.1003148 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Kim CJ, Nazli A, Rojas OL, et al. A role for mucosal IL-22 production and Th22 cells in HIV-associated mucosal immunopathogenesis. Mucosal Immunology. 2012;5(6):670–680. doi: 10.1038/mi.2012.72 [DOI] [PubMed] [Google Scholar]
- 26.Kim CJ, McKinnon LR, Kovacs C, et al. Mucosal Th17 cell function is altered during HIV infection and is an independent predictor of systemic immune activation. J Iimmunol. 2013;191(5):2164–2173. doi: 10.4049/jimmunol.1300829 [DOI] [PubMed] [Google Scholar]
- 27.Haissman JM, Vestergaard LS, Sembuche S, et al. Plasma cytokine levels in Tanzanian HIV-1-infected adults and the effect of antiretroviral treatment. J Acquired Imm Deficiency Syndr. 2009;52(4):493–497. doi: 10.1097/QAI.0b013e3181b627dc [DOI] [PubMed] [Google Scholar]
- 28.Musey L, Ding Y, Cao J, et al. Ontogeny and specificities of mucosal and blood human immunodeficiency virus type 1-specific CD8(+) cytotoxic T lymphocytes. J Virol. 2003;77(1):291–300. doi: 10.1128/jvi.77.1.291-300.2003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Huang XL, Fan Z, Gupta P, Rinaldo CR. Activation of HIV type 1 specific cytotoxic T lymphocytes from semen by HIV type 1 antigen-presenting dendritic cells and IL-12. AIDS Res Hum Retroviruses. 2006;22(1):93–98. doi: 10.1089/aid.2006.22.93 [DOI] [PubMed] [Google Scholar]
- 30.Pillay T, Sobia P, Olivier AJ, et al. Semen IgM, IgG1, and IgG3 differentially associate with pro-inflammatory cytokines in HIV-infected men. Front Immunol. 2018;9:3141. doi: 10.3389/fimmu.2018.03141 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Osborne BJW, Marsh AK, Huibner S, et al. Clinical and mucosal immune correlates of HIV-1 semen levels in antiretroviral-naive men. Open Forum Infect Dis. 2017;4(2):ofx033. doi: 10.1093/ofid/ofx033 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Swaminathan S, Qiu J, Rupert AW, et al. Interleukin-15 (IL-15) strongly correlates with increasing HIV-1 viremia and markers of inflammation. PLoS One. 2016;11(11):e0167091. doi: 10.1371/journal.pone.0167091 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Manganaro L, Hong P, Hernandez MM, et al. IL-15 regulates susceptibility of CD4(+) T cells to HIV infection. Proc Natl Acad Sci USA. 2018;115(41):E9659–e9667. doi: 10.1073/pnas.1806695115 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Mueller YM, Do DH, Altork SR, et al. IL-15 treatment during acute simian immunodeficiency virus (SIV) infection increases viral set point and accelerates disease progression despite the induction of stronger SIV-specific CD8+ T cell responses. J Iimmunol. 2008;180(1):350–360. doi: 10.4049/jimmunol.180.1.350 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Huang X, Liu X, Meyers K, et al. Cytokine cascade and networks among MSM HIV seroconverters: implications for early immunotherapy. Sci Rep. 2016;6:36234. doi: 10.1038/srep36234 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Konadu KA, Chu J, Huang MB, et al. Association of cytokines with exosomes in the plasma of HIV-1-seropositive individuals. J Infect Dis. 2015;211(11):1712–1716. doi: 10.1093/infdis/jiu676 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Anderson JA, Ping LH, Dibben O, et al. HIV-1 populations in semen arise through multiple mechanisms. PLoS Pathogens. 2010;6(8):e1001053. doi: 10.1371/journal.ppat.1001053 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Sheth PM, Danesh A, Shahabi K, et al. HIV-specific CD8+ lymphocytes in semen are not associated with reduced HIV shedding. J Iimmunol. 2005;175(7):4789–4796. doi: 10.4049/jimmunol.175.7.4789 [DOI] [PubMed] [Google Scholar]
- 39.Chéret A, Durier C, Mélard A, et al. Impact of early cART on HIV blood and semen compartments at the time of primary infection. PLoS One. 2017;12(7):e0180191. doi: 10.1371/journal.pone.0180191 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Camus C, Matusali G, Bourry O, et al. Comparison of the effect of semen from HIV-infected and uninfected men on CD4+ T-cell infection. AIDS. 2016;30(8):1197–1208. doi: 10.1097/qad.0000000000001048 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Van Damme J, Proost P, Lenaerts JP, Opdenakker G. Structural and functional identification of two human, tumor-derived monocyte chemotactic proteins (MCP-2 and MCP-3) belonging to the chemokine family. J Exp Med. 1992;176(1):59–65. doi: 10.1084/jem.176.1.59 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Sathaliyawala T, O’Gorman WE, Greter M, et al. Mammalian target of rapamycin controls dendritic cell development downstream of Flt3 ligand signaling. Immunity. 2010;33(4):597–606. doi: 10.1016/j.immuni.2010.09.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Pham TNQ, Meziane O, Miah MA, et al. Flt3L-mediated expansion of plasmacytoid dendritic cells suppresses HIV infection in humanized mice. Cell Rep. 2019;29(9):2770–2782.e5. doi: 10.1016/j.celrep.2019.10.094 [DOI] [PubMed] [Google Scholar]