Abstract
Background
Initial studies suggest higher serum levels of some pro-inflammatory cytokines may be associated with decreased cervical human papillomavirus (HPV) clearance. However, the relationship of cytokines with oral HPV clearance has not been explored.
Methods
From 2010 to 2014, oral rinse and serum samples were collected semi-annually from 1,601 adults. Oral rinse samples were tested for HPV DNA using PCR. Based on oral HPV results, 931 serum samples were selected for cytokine evaluation to include a roughly equal number of prevalent (n=307), incident (n=313), and no oral HPV infections (n=311). Electrochemiluminescence multiplex assays were used to determine the concentrations of IL-6, IL-8, TNF-α, IFN-γ, IL-1β, IL-2, IL-4, IL-10, IL-12 and IL-13. The relationship between serum cytokine concentrations (categorized into quartiles) and oral HPV clearance was evaluated with Wei-Lin-Weissfeld regression models, adjusting for HPV infection type (prevalent vs. incident), age, HIV status, and CD4 T cell count.
Results
Higher TNF-α concentration was associated with decreased clearance in men (highest vs. lowest quartile, adjusted hazard ratio [aHR]=0.52, 95% CI=0.34-0.79) and women (aHR=0.76, 95% confidence interval [CI]=0.55-1.04), with stronger associations in men than women (p-interaction=0.049). Higher IL-2 concentration was associated with reduced clearance in men (aHR=0.69, 95% CI=0.50-0.95), but not women (p-interaction=0.058). Results were similar within CD4 T cell strata (CD4 ≥500 or CD4<500 cells/μl) among HIV-infected participants. No other cytokines were associated with clearance.
Conclusion
High serum TNF-α is associated with reduced clearance of oral HPV infection.
Keywords: oral HPV, persistence, TNF, natural history, infection
1. Introduction
Oral infection with human papillomavirus (HPV) is an established causal factor for oropharyngeal squamous cell carcinoma (OPSCC).(1) In the U.S., approximately 70% of OPSCC is caused by HPV, with higher incidence among men <60 years old and individuals with human immunodeficiency virus (HIV) infection.(1-4) Similar to HPV infection at other anatomic sites, most oral HPV infections clear in 1-2 years.(5) However, some individuals have persistently detected oral HPV infection, which is believed to be the precursor to HPV-related OPSCC.(6) Understanding key immune differences in individuals with persistent oral HPV may help explain the disproportionate burden of HPV-related OPSCC in population subgroups.
While the role of host immunity in oral HPV infection has not been explored, studies of cervical HPV infection have established that cell-mediated T cell responses are critical for viral clearance and lesion regression.(7, 8) Attempts to characterize these responses have found that women with persistent cervical HPV have distinct systemic and/or local cytokine profiles as compared to women who clear HPV or women without HPV infection.(9-13) In particular, higher circulating or local levels of interleukin (IL)-6, IL-8 and tumor necrosis factor-alpha (TNF-α) have been associated with reduced cervical HPV clearance,(9-11) suggesting that cytokines secreted may be predictive of disease progression and outcome, although results have been mixed.(14, 15) The relationships between cytokines and oral HPV infection, and any differences by biologic sex, have not been described. However, men have been noted to have a reduced inflammatory response to infection, compared to women.(16)
Given that innate and acquired immune responses effectively resolve most HPV infections, persistent oral infection may reflect disruption or alteration of host anti-viral or inflammatory responses.(17, 18) Alternatively, immunologic differences between individuals may influence oral HPV clearance. For example, women with persistent cervical HPV infection have reduced lymphoproliferative responses to HPV16.(19) HIV infection may further impact immune response, as HIV can alter cytokine secretion patterns, resulting in elevated circulating levels of pro-inflammatory cytokines such as IL-1, IL-6 and TNF-α.(20-26) Furthermore, pro-inflammatory cytokines can modulate HPV transcription, suggesting that HIV-related immune perturbations at the systemic level could affect oral infection.(20)
Current technology allows simultaneous measurement of multiple immune markers in a single sample using a multiplex format. Characterizing the serum cytokine profiles associated with oral HPV clearance may provide insight on immune cofactors relevant to oral HPV infection. The goals of this study were to evaluate whether select serum cytokines associated with inflammation may be related to oral HPV clearance and to explore differences by sex and degree of HIV-related immunosuppression as measured by CD4 T cell count.
2. Methods
2.1. Study population
From 2010 to 2014, 1,601 participants were enrolled in the “Persistence of Oral Papillomavirus Study” (POPS), a longitudinal cohort for studying oral HPV natural history. POPS was nested within two ongoing observational studies of men and women with or at risk for HIV: the Multicenter AIDS Cohort Study (MACS) and the Women’s Interagency HIV Study (WIHS). POPS participants were enrolled at 5 study centers: Baltimore (MACS), Pittsburgh (MACS), Brooklyn (WIHS), Bronx (WIHS), and Chicago (MACS and WIHS).(27-29) Each study center’s Institutional Review Board approved the study. All participants provided written informed consent.
2.2. Data collection
At each semi-annual study visit, a 30-second Scope® oral rinse and gargle sample was collected and tested for 37 types of HPV DNA. A blood sample was also obtained, from which HIV status, CD4 T cell count, and cytokine profile were determined. Data on behavioral cofactors were collected by survey. Additional details of data collection methods have been previously described.(30)
2.3. Oral HPV detection and genotyping
DNA was extracted from oral exfoliated cells using the Puregene DNA isolation kit (Gentra Systems, Minneapolis, MN). Extracted DNA samples were tested for HPV DNA using a polymerase chain reaction (PCR) assay targeting the L1 region of the viral genome using PGMY primers.(31) HPV-positive samples were genotyped using reverse line-blot hybridization (Roche Molecular Systems, Pleasanton, CA).(31) Each sample was evaluated for the presence of high-risk/oncogenic types (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66) and low-risk/non-oncogenic types (6, 11, 26, 38, 40, 42, 53, 54, 55, 61, 62, 64, 67, 68, 69, 70, 71, 72, 73, 81, 83, 84, 89, IS39), classified according to criteria from the International Agency for Research on Cancer.(32-34) Participants with any of these HPV types were considered HPV-infected.
Prevalent oral HPV infection was defined as any type-specific oral HPV infection detected at study enrollment. Incident infection was defined as newly detected type-specific infection that was preceded by at least one HPV-negative oral rinse. Clearance was defined as two consecutive HPV-negative oral rinses, with time of clearance as the visit of the first negative oral rinse sample. A secondary less conservative definition of clearance was considered, requiring only one HPV-negative oral rinse sample.
2.4. Selection of serum samples for cytokine testing
We selected 931 serum samples for cytokine evaluation. Serum samples were selected based on oral rinse HPV results in order to include a roughly equal number of prevalent (n=307), incident (n=313), and no oral HPV infections (n=311). We included all prevalent HPV samples, a random selection of incident HPV samples (55% of all incident HPV samples), and a comparison group of samples with no oral HPV DNA at study enrollment, frequency matched to samples with prevalent HPV by study participant’s HIV status and biologic sex. All of the serum samples selected for cytokine testing were from participants who contributed at least 3 oral rinses overall and at least 2 oral rinses after incident oral HPV detection.
Cytokines were evaluated using serum samples collected at the visit of incident HPV detection, or at study enrollment for participants with prevalent or no HPV infections. Some participants had prevalent infection at study enrollment and subsequent incident HPV that was also included in the study sample. For these cases, cytokines were determined separately in the serum sample corresponding to first detection of prevalent HPV and in the sample corresponding to incident HPV. Therefore, the 620 prevalent and incident serum samples selected for cytokine evaluation were obtained from 459 HPV-infected participants.
2.5. Serum cytokine testing
Serum cytokines were determined using the MSD V-PLEX Human Proinflammatory Panel 1 kit (Meso Scale Discovery −MSD Gaithersburg, MD), which consists of the following: TNF-α, IL-6, IL-8, IFN-γ, IL-1β, IL-2, IL-4, IL-10, IL-12 and IL-13. Cytokine testing was analyzed using the MSD 2400 Sector Imager using a standard protocol. The multiplex cytokine assay was previously validated and found to reliably quantify cytokine concentrations in both HIV-infected and HIV-uninfected individuals.(35)
To confirm acceptable assay performance, 10% of the samples were tested in duplicate and coefficients of variation (CV) were calculated for each duplicate test. Duplicated cytokine results were considered acceptable if CV≤20%. The primary analysis was restricted to the cytokines that could be reliably detected in ≥60% of the samples tested: TNF-α, IL-6, IL-8, IFN-γ, IL-2 and IL-10. The other cytokines tested (IL-1β, IL-4, IL-12 and IL-13) were excluded from this primary analysis because >40% of samples had cytokine concentrations below the lowest detectable limit, but were evaluated based on presence or absence of detectable cytokine.
2.6. Statistical analyses
Demographic and health characteristics of men and women in the study were compared using χ2 tests. Median cytokine concentrations were compared in serum samples that had prevalent, incident and no oral HPV DNA using a nonparametric test for trends across ordered groups.
The analysis included 917 type-specific oral HPV infections from 620 samples among 459 participants (some participants were infected with multiple HPV types at the same visit and the cytokine values at that visit were applied to clearance analysis of all of those infections). Concentrations of each cytokine were categorized into quartiles (see Table 4 footnote for quartile cutoffs). Alternative analyses considered cytokine quartiles based on sex-specific cytokine distributions and continuous cytokine concentrations (i.e. the per natural log increase in cytokine concentration), with similar results. Cytokines with low detectability were categorized as detectable vs. non-detectable).
Table 4.
Multivariable risk factors for oral HPV clearance among 459 participants with 917 oral HPV infections, by sexa
| Infections in Men, n=472 | Infections in Women, n=445 | |||||
|---|---|---|---|---|---|---|
| Characteristic at visit of first oral HPV detection |
No. of cleared infections |
Person- months |
aHR (95% CI) | No. of cleared infections |
Person- months |
aHR (95% CI) |
| TNF-α concentration (pg/ml) b | ||||||
| Quartile 1 | 115 | 2,557 | Ref | 59 | 1,443 | Ref |
| Quartile 2 | 77 | 3,593 | 0.56 (0.40-0.79) | 69 | 1,869 | 0.97 (0.70-1.34) |
| Quartile 3 | 62 | 2,713 | 0.60 (0.44-0.82) | 84 | 2,392 | 1.07 (0.76-1.49) |
| Quartile 4 | 46 | 2,432 | 0.52 (0.34-0.79) | 81 | 3,264 | 0.76 (0.55-1.04) |
| p for interaction=0.049 | ||||||
|
| ||||||
| IL-2 concentration (pg/ml) c | ||||||
| Quartile 1 | 124 | 3,612 | Ref | 101 | 3,053 | Ref |
| Quartile 2 | 39 | 1,868 | 0.66 (0.45-0.96) | 33 | 1,243 | 0.90 (0.58-1.37) |
| Quartile 3 | 69 | 2,703 | 0.70 (0.52-0.93) | 79 | 2,442 | 1.09 (0.82-1.47) |
| Quartile 4 | 65 | 2,906 | 0.69 (0.50-0.95) | 79 | 2,223 | 1.15 (0.85-1.57) |
| p for interaction=0.058 | ||||||
|
| ||||||
| Infection type | ||||||
| Incident | 140 | 2,908 | Ref | 148 | 2,480 | Ref |
| Prevalent | 160 | 8,388 | 0.52 (0.40-0.67) | 146 | 6,494 | 0.45 (0.34-0.59) |
| Age (years) | ||||||
| <45 | 63 | 1,995 | Ref | 107 | 2,929 | Ref |
| 45-54 | 124 | 4,423 | 0.83 (0.61-1.12) | 137 | 4,036 | 0.95 (0.74-1.22) |
| ≥55 | 113 | 4,877 | 0.67 (0.48-0.92) | 50 | 2,009 | 0.82 (0.58-1.15) |
| HIV and current CD4 cell count (cells/μL) | ||||||
| HIV uninfected | 74 | 2,326 | Ref | 53 | 1,370 | Ref |
| HIV infected, CD4≥500 | 124 | 4,386 | 0.89 (0.66-1.21) | 93 | 3,157 | 0.78 (0.56-1.08) |
| HIV infected, CD4<500 | 102 | 4,584 | 0.87 (0.64-1.19) | 148 | 4,447 | 0.92 (0.68-1.25) |
TNF-α and IL-2 were each analyzed in separate multivariable models adjusting for infection type, age, and HIV status/CD4 count. Covariates shown are from the model with TNF-α. Bolding indicates adjusted hazard ratios (aHR) with p<0.05.
TNF-α quartiles: 0.0-2.56 (Q1), 2.57-3.58 (Q2), 3.59-4.93 (Q3), 4.94-19.33 (Q4).
IL-2 quartiles: 0.0-0.0 (Q1), 0.21-0.37 (Q2), 0.38-0.58 (Q3), 0.59-20.62 (Q4).
Predictors of type-specific oral HPV clearance were explored using Wei-Lin-Weissfeld regression models, accounting for within-participant clustering of HPV infections.(36) The effect of each cytokine was modeled separately in unadjusted models, and then in multivariable models adjusting for prevalent vs. incident infection type, age, HIV status, and CD4 T cell count at time of oral HPV detection, based on prior evidence that these factors are associated with oral HPV clearance. Stata 12 statistical software package was used for statistical analyses.(37) Statistical significance was defined by a two-sided p-value <0.05.
3. Results
Characteristics of study participants are described in Table 1. Among the 766 participants, half were men (52%) and the median age was 50 years. Approximately 74% of participants were HIV-infected, and 82% of these reported current use of antiretroviral therapy (ART). Compared to men, women were younger, more likely to be Black, HIV-infected, and current smokers (p-values<0.05, Table 1). Among HIV-infected participants, women had higher current HIV RNA viral load (p<0.0001), but similar CD4 T cell count, as compared to men (p=0.17).
Table 1.
Description of study participant characteristics at baseline, overall and by sexa
| n (%) | ||||
|---|---|---|---|---|
| Characteristic | Overall (N=766) |
Men (N=402) |
Women (N=364) |
p-value |
| Infection type | 0.88 | |||
| Incident only | 152 (19.8) | 77 (19.2) | 75 (20.6) | |
| Any prevalent | 307 (40.1) | 163 (40.5) | 144 (39.6) | |
| None | 307 (40.1) | 162 (40.3) | 145 (39.8) | |
| Age (years) | <0.0001 | |||
| <45 | 200 (26.1) | 58 (14.5) | 142 (39.0) | |
| 45-54 | 328 (42.9) | 171 (42.6) | 157 (43.1) | |
| ≥55 | 238 (31.1) | 173 (43.0) | 65 (17.9) | |
| Race/Ethnicity | <0.0001 | |||
| White, non-Hispanic | 254 (33.2) | 238 (59.2) | 16 (4.4) | |
| Black, non-Hispanic | 413 (53.9) | 144 (35.8) | 269 (73.9) | |
| Other race or Hispanic | 99 (12.9) | 20 (5.0) | 79 (21.7) | |
| Study site | ||||
| Baltimore, Maryland | 140 (18.3) | 140 (34.8) | NA | |
| Bronx, New York | 116 (15.1) | NA | 116 (31.9) | |
| Brooklyn, New York | 134 (17.5) | NA | 134 (36.8) | |
| Chicago, Illinois | 253 (33.0) | 139 (34.6) | 114 (31.3) | |
| Pittsburgh, Pennsylvania | 123 (16.1) | 123 (30.6) | NA | |
| HIV status | 0.02 | |||
| Uninfected | 197 (25.7) | 117 (29.1) | 80 (22.0) | |
| Infected | 569 (74.3) | 285 (70.9) | 284 (78.0) | |
| Current CD4 T cell count (cells/μL) | 0.17 | |||
| ≥500 | 313 (55.0) | 165 (57.9) | 148 (52.1) | |
| <500 | 256 (45.0) | 120 (42.1) | 136 (47.9) | |
|
Current HIV RNA viral load
(copies/mL) |
<0.0001 | |||
| <200 | 415 (73.3) | 228 (80.9) | 187 (66.5) | |
| 200-19,999 | 94 (16.7) | 32 (11.3) | 62 (22.1) | |
| ≥20,000 | 54 (9.6) | 22 (7.8) | 32 (11.4) | |
| Current ART use | 0.43 | |||
| No | 101 (17.8) | 47 (16.5) | 54 (19.0) | |
| Yes | 468 (82.2) | 238 (83.5) | 230 (81.0) | |
| Smoked cigarettes in the last 6 months | <0.0001 | |||
| No | 439 (57.8) | 271 (68.3) | 168 (46.3) | |
| Yes | 321 (42.2) | 126 (31.7) | 195 (53.7) | |
For HPV-uninfected participants and participants with prevalent HPV, baseline was defined as POPS enrollment. For participants with incident HPV, baseline was defined as visit of incident HPV detection.
Median follow-up time for infections was 16.7 months (interquartile range, IQR: 6.1-36.6). For infections that cleared, the median time to clearance was 6.5 months, with longer clearance time for prevalent infections (11.7 months; IQR 6.0-21.6) than incident infections (6.2 months; IQR 5.9-11.9).
3.1. Comparison of serum cytokine concentrations by HPV status
Median serum concentrations of TNF-α, IL-8, IFN-γ, IL-10 and IL-2 increased by HPV infection status (each p-trend<0.05, Table 2). The lowest median concentrations of each of these cytokines were in samples from participants with no oral HPV infection, followed by samples from participants with incident HPV, and the highest concentrations were in samples from participants with prevalent HPV. When comparing samples with any oral HPV infection (prevalent or incident) to samples without oral HPV infection, the median serum concentrations of TNF-α, IL-8, IFN-γ, IL-10 and IL-2 were significantly higher (each p<0.05) in samples from HPV-infected participants (data not shown). Results were similar when restricted to only HIV-infected, or only HIV-uninfected participants (results not shown).
Table 2.
Comparison of baseline serum cytokine concentrations (pg/ml) in 931 samples, by oral HPV statusa
| Median serum concentration at baseline (IQR) | ||||
|---|---|---|---|---|
| Cytokine | No Oral HPV n=311 |
Incident Oral HPV n=313 |
Prevalent Oral HPV n=307 |
p-trend |
| TNF-α | 3.1 (2.4-4.3) | 3.3 (2.5-4.5) | 3.5 (2.6-4.8) | 0.009 |
| IL-6 | 1.0 (0.7-1.8) | 1.1 (0.7-1.7) | 1.1 (0.7-1.7) | 0.41 |
| IL-8 | 15.2 (10.7-38.1) | 16.4 (11.4-37.5) | 19.5 (13.0-62.3) | 0.001 |
| IFN-γ | 8.0 (5.2-14.1) | 8.2 (5.4-15.7) | 9.4 (5.7-16.5) | 0.03 |
| IL-10 | 0.47 (0.27-0.76) | 0.55 (0.32-0.89) | 0.60 (0.37-0.94) | 0.001 |
| IL-2 | 0.27 (0-0.55) | 0.34 (0-0.55) | 0.38 (0-0.59) | 0.007 |
For samples with no oral HPV or prevalent HPV, baseline was defined as POPS enrollment. For samples with incident HPV, baseline was defined as visit of incident HPV detection. Unadjusted (no log transformation) median cytokine concentrations and interquartile ranges (IQR, 25th to 75th percentiles, in parentheses) are shown. Bolding indicates values with p<0.05 in tests for trend. Results were similar when restricted to only HIV-infected, or only HIV-uninfected participants (results not shown).
3.2. Association of cytokines with oral HPV clearance
Of the cytokines included in the analysis, TNF-α was most strongly associated with oral HPV clearance (Table 3). In unadjusted analyses, the highest quartile of TNF-α was significantly associated with reduced oral HPV clearance in both men (HR=0.50, 95% CI=0.35-0.72) and women (HR=0.67, 95% CI=0.48-0.94), as compared to the lowest TNF-α quartile (p for interaction=0.24). The second and third quartiles of TNF-α concentration were also associated with reduced oral HPV clearance in men but not in women (each p for interaction<0.05, Table 3).
Table 3.
Unadjusted association of cytokine concentration (by quartile) with oral HPV clearance among 459 participants with 917 infections, by sex.a
| Hazard ratio (95% CI) |
||||||
|---|---|---|---|---|---|---|
| Infections in Men, n=472 | Infections in Women, n=445 | |||||
|
| ||||||
| Cytokine | Quartile 2 | Quartile 3 | Quartile 4 | Quartile 2 | Quartile 3 | Quartile 4 |
|
| ||||||
| TNF-α | 0.55 (0.40-0.76) | 0.56 (0.40-0.78) | 0.50 (0.35-0.72) | 0.93 (0.67-1.30) | 0.97 (0.68-1.39) | 0.67 (0.48-0.94) |
| IL-6 | 0.72 (0.53-0.99) | 0.71 (0.49-1.02) | 0.83 (0.61-1.12) | 1.41 (0.97-2.05) | 1.04 (0.71-1.52) | 1.05 (0.71-1.54) |
| IL-8 | 0.88 (0.64-1.20) | 0.74 (0.51-1.07) | 1.05 (0.75-1.48) | 0.83 (0.58-1.20) | 0.95 (0.71-1.29) | 0.73 (0.53-1.00) |
| IFN-γ | 0.97 (0.70-1.34) | 0.98 (0.69-1.40) | 0.79 (0.53-1.17) | 0.79 (0.54-1.14) | 0.86 (0.63-1.17) | 0.84 (0.61-1.16) |
| IL-10 | 0.78 (0.58-1.06) | 0.81 (0.58-1.14) | 0.82 (0.58-1.15) | 0.89 (0.63-1.24) | 0.88 (0.61-1.25) | 0.74 (0.55-1.00) |
| IL-2 | 0.63 (0.42-0.93) | 0.73 (0.54-1.00) | 0.69 (0.50-0.96) | 0.80 (0.52-1.22) | 0.98 (0.71-1.36) | 1.10 (0.80-1.50) |
Reference is quartile 1. Bolding indicates hazard ratios with p<0.05
In unadjusted analyses, the highest quartile of IL-2 concentration was associated with significantly reduced oral HPV clearance among men (HR=0.69, 95% CI=0.50-0.96), but not among women (HR=1.10, 95% CI=0.80-1.50), p for interaction=0.047. This finding should be interpreted with caution as IL-2 had the most values (35%) below the lower limit of detection, of all the cytokines included in the analysis. IL-6, IL-8, IFN-γ, and IL-10 concentration were not strongly associated with oral HPV clearance; marginal associations were observed in single quartiles for some of these cytokines in unadjusted analyses (Table 3), but none remained significant predictors of oral HPV clearance in adjusted analyses (results not shown).
After adjusting for the effects of HPV infection type (prevalent vs. incident), age, HIV status and CD4 T cell count in a multivariable model, serum TNF-α concentration remained significantly associated with reduced oral HPV clearance in all quartiles for men (each p<0.01) and remained marginally associated with reduced clearance in the highest quartile for women (p for interaction=0.049, Table 4). IL-2 also remained associated with decreased oral HPV clearance in all quartiles in men only (each p<0.05). The associations of higher TNF-α and IL-2 concentrations on oral HPV clearance were stronger in men than women (TNF-α, p for interaction=0.049; IL-2, p for interaction=0.058).
Results were similar when restricted to HIV-infected participants with baseline CD4 ≥500 or CD4<500 cells/μl (results not shown) and when evaluating TNF-α and IL-2 concentrations as continuous variables instead of quartiles (Supplemental Table S1). When using sex-specific cytokine quartile cutoffs, results were also similar but the highest TNF-α quartile in women remained significantly associated with reduced clearance in the adjusted model (p=0.02, Supplemental Table S2). When using a less strict clearance definition of 1 HPV-negative oral rinse, similar patterns were observed, but associations were attenuated (data not shown). When considering cytokines with low detectability (IL-1β, IL-4, IL-12 and IL-13), detection of these cytokines was not associated with reduced oral HPV clearance (Supplemental Table S3).
4. Discussion
We found that while most cytokines were not associated with oral HPV clearance, the highest serum TNF-α concentration quartile in our study population (4.94-19.33 pg/ml) was associated with decreased oral HPV clearance in both sexes, with stronger associations in men than women. IL-2 concentration above the first quartile (≥0.21 pg/ml) was associated with reduced oral HPV clearance in men only. These results suggest that higher levels of some inflammatory cytokines may decrease oral HPV clearance and thus contribute to explaining why some individuals may be at increased risk for persistent oral HPV infection.
Our finding that higher TNF-α was associated with reduced oral HPV clearance is consistent with previous studies of cervical HPV, which found that women with persistent cervical HPV have higher serum TNF-α at their final study visit, as compared to women who cleared infection.(9, 10) In addition, our results show that higher serum TNF-α at first detection of oral HPV infection was associated with longer time to clearance, suggesting that TNF-α may be relevant in early stages of oral HPV infection, in addition to being a marker of long-term infection. Furthermore, while previous studies restricted the study population to HIV-uninfected participants,(9-11, 14) the association between TNF-α and clearance in our study remained similar after adjusting for HIV infection and CD4 T cell count, suggesting that the relationship between TNF-α and oral HPV may be independent of HIV-related immunosuppression.
TNF-α plays an important role in inflammatory reactions and viral clearance. Since HPV infection of epithelial cells is sequestered from systemic immunity, and typically does not cause a highly inflammatory immune response,(38, 39) the reason why higher concentrations of TNF-α are associated with reduced clearance remains unclear. It is possible that these participants had higher systemic TNF-α resulting from other pro-inflammatory co-factors, such as concurrent illness or chronic conditions, which may promote or facilitate HPV persistence. Previous research suggests that although initial HPV infection does not cause an inflammatory reaction,(38, 39) persisting infection can activate inflammatory pathways, including ones with established roles in cancer promotion.(40) Repeated longitudinal cytokine measurements, or cytokine measurements taken directly from the oropharynx, may show a decrease in TNF-α following HPV clearance, and may help clarify temporal patterns of immune response over the course of oral HPV infection.
Some sex differences in the association of cytokines with oral HPV clearance were observed in this study. Genetic or hormonal differences that influence immune responses and HPV infection may explain the difference between men and women in strength of association of TNF-α and IL-2 with reduced clearance. Sex differences in cellular and humoral immune responses, as well as cytokine activity, have been consistently documented in previous research (16, 41, 42), (16, 41, 42), and findings from several studies suggest that men have weaker immune responses to HPV infection as compared to women.(43) This may due to previous cervical HPV infection prompting a stronger immune response when exposed to oral HPV infection. It is also possible that immune differences may be influenced by other unmeasured sex-related factors. Higher incidence of HPV-associated oropharyngeal cancer has consistently been reported in men compared to women,(5) Reasons for this difference in cancer rate are not fully understood, and may be explained, in part, by sex-based differences in immune response. Given that our study population was primarily middle-aged, it is also possible that hormonal changes related to oral contraceptive use and menopause in women might influence immune responses.(45, 46)
Previous clinical studies have not found evidence that serum IL-2 may be related to clearance of HPV infection. However, a previous study that measured IL-2 reactivity when stimulated with HPV E6/E7 oncoproteins in culture supernatants of peripheral blood mononuclear cells found that IL-2 responsiveness was strongly associated with cervical HPV16 persistence.(47) Other studies have shown that plasma IL-2 levels can differ depending on cervical HPV positivity and/or disease stage, although results have varied.(13) Our finding that IL-2 is related to decreased clearance in men may have been affected by its lower detectability, and may not represent true sex differences in IL-2. Therefore, the association of IL-2 with oral HPV clearance observed in this study warrants confirmation from other studies.
In contrast to previous studies on cervical HPV,(9-11) IL-6 and IL-8 were not strongly associated with oral HPV clearance in this study. This may be due to differences in the biology of HPV infection in the oropharynx and cervix. It is also possible that these cytokines were expressed at time points not captured by the testing schedules, that concentrations differed between studies or that they may be involved in oral HPV clearance, but not at concentrations detectable in serum. Two previous analyses, which reported associations between IL-8 and reduced cervical HPV clearance were conducted in a weighted subpopulation of women with type-specific HPV infection persistently detected over a 9-year interval.(9, 10) Therefore, it is possible that IL-8 is associated with HPV infection at a later stage, or may be more relevant for established infections. We found that the concentrations of nearly all cytokines were indeed different across participants by HPV infection status, suggesting a linkage between cytokine profile and presence or duration of HPV infection. While the current analysis controlled for incident vs. prevalent infection type, longitudinal repeated measurements may be more informative of differences between short- and long-term persistence.
Our study had several strengths, including: enrollment of a large study population with high oral HPV prevalence, including men and women at multiple U.S. study sites; racial and ethnic diversity; inclusion of HIV-infected and HIV-uninfected participants; ability to control for biological and behavioral risk factors; evaluation of oral HPV infection in a prospective manner; and, centralized testing of cytokines using a validated multiplex assay. This study also had several limitations. Cytokine levels were only measured in serum, not saliva, although results of a recent study indicate that serum cytokine measurement may reflect markers detectable in oral samples.(48) It remains uncertain how cytokine concentrations in the periphery may be related to viral clearance at the local site of infection, or how clearance may be affected by the contributing effects of the mucosal immunologic environment. Cytokines were measured at the time of first oral HPV detection so subsequent changes in cytokine concentration during infection could not be evaluated. We did not have data on concurrent genital HPV infections in the study participants. Finally, the 6-month study visit intervals limited our ability to identify time of infection and time of clearance with greater precision.
To our knowledge, this is the first study to explore the association of circulating immune markers with oral HPV clearance. While the majority of cytokines were not related to oral HPV clearance, these results suggest higher TNF-α concentration may be associated with reduced clearance of oral HPV infection, and that the strength of association may be stronger in men than women. Future studies, which include longitudinal cytokine evaluation, are needed to clarify the role of TNF-α in oral HPV natural history.
Supplementary Material
Article highlights.
Higher serum TNF-α concentration was associated with reduced oral HPV clearance
The association of TNF-α with oral HPV clearance was stronger among men than women
Results are consistent with studies of TNF-α and decreased cervical HPV clearance
Acknowledgements
We thank Palak Shah for cytokine testing, performed in the laboratory of Dr. Jay Bream at the Johns Hopkins Bloomberg School of Public Health. Oral rinse samples were processed and tested in the laboratory of Dr. Maura Gillison at The Ohio State University. Data in this manuscript were collected by the Multicenter AIDS Cohort Study (MACS). MACS (Principal Investigators): Johns Hopkins University Bloomberg School of Public Health (Joseph Margolick), U01-AI35042; Northwestern University (Steven Wolinsky), U01-AI35039; University of California, Los Angeles (Roger Detels), U01-AI35040; University of Pittsburgh (Charles Rinaldo), U01-AI35041; the Center for Analysis and Management of MACS, Johns Hopkins University Bloomberg School of Public Health (Lisa Jacobson), UM1-AI35043. The MACS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional co-funding from the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA), and the National Institute of Mental Health (NIMH). The MACS website is located at http://aidscohortstudy.org/. Data in this manuscript were also collected by the Women’s Interagency HIV Study (WIHS). WIHS (Principal Investigators): U01-AI-103408; Bronx WIHS (Kathryn Anastos), U01-AI-035004; Brooklyn WIHS (Howard Minkoff and Deborah Gustafson), U01-AI-031834; Chicago WIHS (Mardge Cohen and Audrey French), U01-AI-034989; WIHS Data Management and Analysis Center (Stephen Gange and Elizabeth Golub), U01-AI-042590. The WIHS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA), and the National Institute on Mental Health (NIMH).
Financial support: This work was supported by grant R01DE021395 (NIDCR, NIH; Gypsyamber D’Souza). The MACS and WIHS cohorts receive primary funding from NIAID, with additional funding from NCI, NIDA, NIMH and NICHD (full acknowledgements at end of paper).
GD, DJW and RDC have/had research support from Merck & Co., Inc. DJW is a member of the speakers bureau for Merck & Co., Inc. MLG has been a consultant for Merck & Co., Inc and GSK. RDC also reports institutional grant funding and royalties from UptoDate (on HPV related topics).
Footnotes
JOL, JHB, EAS, CLC, KMW, RDB, SR, JBM, HDS, AW, LJ, YG and WX have no conflicts of interest to report.
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References
- 1.Gillison ML, Chaturvedi AK, Anderson WF, Fakhry C. Epidemiology of Human Papillomavirus-Positive Head and Neck Squamous Cell Carcinoma. J Clin Oncol. 2015;33(29):3235–42. doi: 10.1200/JCO.2015.61.6995. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Beachler DC, Abraham AG, Silverberg MJ, Jing Y, Fakhry C, Gill MJ, et al. Incidence and risk factors of HPV-related and HPV-unrelated Head and Neck Squamous Cell Carcinoma in HIV-infected individuals. Oral Oncol. 2014;50(12):1169–76. doi: 10.1016/j.oraloncology.2014.09.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Beachler DC, D'Souza G. Oral human papillomavirus infection and head and neck cancers in HIV-infected individuals. Curr Opin Oncol. 2013;25(5):503–10. doi: 10.1097/CCO.0b013e32836242b4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Shiels MS, Cole SR, Kirk GD, Poole C. A meta-analysis of the incidence of non-AIDS cancers in HIV-infected individuals. J Acquir Immune Defic Syndr. 2009;52(5):611–22. doi: 10.1097/QAI.0b013e3181b327ca. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Gillison ML, Castellsague X, Chaturvedi A, Goodman MT, Snijders P, Tommasino M, et al. Comparative epidemiology of HPV infection and associated cancers of the head and neck and cervix. Int J Cancer. 2013;134(3):497–507. doi: 10.1002/ijc.28201. [DOI] [PubMed] [Google Scholar]
- 6.Rautava J, Syrjanen S. Biology of human papillomavirus infections in head and neck carcinogenesis. Head Neck Pathol. 2012;6(Suppl 1):S3–15. doi: 10.1007/s12105-012-0367-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Best SR, Niparko KJ, Pai SI. Biology of human papillomavirus infection and immune therapy for HPV-related head and neck cancers. Otolaryngol Clin North Am. 2012;45(4):807–22. doi: 10.1016/j.otc.2012.04.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Hibma MH. The immune response to papillomavirus during infection persistence and regression. Open Virol J. 2012;6:241–8. doi: 10.2174/1874357901206010241. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Baker R, Dauner JG, Rodriguez AC, Williams MC, Kemp TJ, Hildesheim A, et al. Increased plasma levels of adipokines and inflammatory markers in older women with persistent HPV infection. Cytokine. 2011;53(3):282–5. doi: 10.1016/j.cyto.2010.11.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kemp TJ, Hildesheim A, Garcia-Pineres A, Williams MC, Shearer GM, Rodriguez AC, et al. Elevated systemic levels of inflammatory cytokines in older women with persistent cervical human papillomavirus infection. Cancer Epidemiol Biomarkers Prev. 2010;19(8):1954–9. doi: 10.1158/1055-9965.EPI-10-0184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Scott ME, Shvetsov YB, Thompson PJ, Hernandez BY, Zhu X, Wilkens LR, et al. Cervical cytokines and clearance of incident human papillomavirus infection: Hawaii HPV cohort study. Int J Cancer. 2013;133(5):1187–96. doi: 10.1002/ijc.28119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Song SH, Lee JK, Lee NW, Saw HS, Kang JS, Lee KW. Interferon-gamma (IFN-gamma): a possible prognostic marker for clearance of high-risk human papillomavirus (HPV) Gynecol Oncol. 2008;108(3):543–8. doi: 10.1016/j.ygyno.2007.11.006. [DOI] [PubMed] [Google Scholar]
- 13.Koshiol J, Kovacic M. Cytokines and Markers of Immune Response to HPV Infection. In: Kanwar J, editor. Recent Advances in Immunology to Target Cancer, Inflammation and Infections. InTech; 2012. [Google Scholar]
- 14.Hong JH, Kim MK, Lee IH, Kim TJ, Kwak SH, Song SH, et al. Association between serum cytokine profiles and clearance or persistence of high-risk human papillomavirus infection: a prospective study. Int J Gynecol Cancer. 2010;20(6):1011–6. doi: 10.1111/IGC.0b013e3181e513e5. [DOI] [PubMed] [Google Scholar]
- 15.Mbulaiteye SM, Kemp T, Gage JC, Ajenifuja KO, Kiruthu C, Wentzensen NA, et al. Plasma cytokine levels and human papillomavirus infection at the cervix in rural Nigerian women. Cytokine. 2013;64(1):146–51. doi: 10.1016/j.cyto.2013.07.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Klein SL. Sex influences immune responses to viruses, and efficacy of prophylaxis and treatments for viral diseases. Bioessays. 2012;34(12):1050–9. doi: 10.1002/bies.201200099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Boccardo E, Lepique AP, Villa LL. The role of inflammation in HPV carcinogenesis. Carcinogenesis. 2010;31(11):1905–12. doi: 10.1093/carcin/bgq176. [DOI] [PubMed] [Google Scholar]
- 18.Kadish AS, Ho GY, Burk RD, Wang Y, Romney SL, Ledwidge R, et al. Lymphoproliferative responses to human papillomavirus (HPV) type 16 proteins E6 and E7: outcome of HPV infection and associated neoplasia. J Natl Cancer Inst. 1997;89(17):1285–93. doi: 10.1093/jnci/89.17.1285. [DOI] [PubMed] [Google Scholar]
- 19.Garcia-Pineres AJ, Hildesheim A, Herrero R, Trivett M, Williams M, Atmetlla I, et al. Persistent human papillomavirus infection is associated with a generalized decrease in immune responsiveness in older women. Cancer Res. 2006;66(22):11070–6. doi: 10.1158/0008-5472.CAN-06-2034. [DOI] [PubMed] [Google Scholar]
- 20.Palefsky J. Biology of HPV in HIV infection. Adv Dent Res. 2006;19(1):99–105. doi: 10.1177/154407370601900120. [DOI] [PubMed] [Google Scholar]
- 21.Bebell LM, Passmore JA, Williamson C, Mlisana K, Iriogbe I, van Loggerenberg F, et al. Relationship between levels of inflammatory cytokines in the genital tract and CD4+ cell counts in women with acute HIV-1 infection. J Infect Dis. 2008;198(5):710–4. doi: 10.1086/590503. [DOI] [PubMed] [Google Scholar]
- 22.Keating SM, Golub ET, Nowicki M, Young M, Anastos K, Crystal H, et al. The effect of HIV infection and HAART on inflammatory biomarkers in a population-based cohort of women. AIDS. 2011;25(15):1823–32. doi: 10.1097/QAD.0b013e3283489d1f. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Nixon DE, Landay AL. Biomarkers of immune dysfunction in HIV. Curr Opin HIV AIDS. 2010;5(6):498–503. doi: 10.1097/COH.0b013e32833ed6f4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Norris PJ, Pappalardo BL, Custer B, Spotts G, Hecht FM, Busch MP. Elevations in IL-10, TNF-alpha, and IFN-gamma from the earliest point of HIV Type 1 infection. AIDS Res Hum Retroviruses. 2006;22(8):757–62. doi: 10.1089/aid.2006.22.757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Stacey AR, Norris PJ, Qin L, Haygreen EA, Taylor E, Heitman J, et al. Induction of a striking systemic cytokine cascade prior to peak viremia in acute human immunodeficiency virus type 1 infection, in contrast to more modest and delayed responses in acute hepatitis B and C virus infections. J Virol. 2009;83(8):3719–33. doi: 10.1128/JVI.01844-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.von Sydow M, Sonnerborg A, Gaines H, Strannegard O. Interferon-alpha and tumor necrosis factor-alpha in serum of patients in various stages of HIV-1 infection. AIDS Res Hum Retroviruses. 1991;7(4):375–80. doi: 10.1089/aid.1991.7.375. [DOI] [PubMed] [Google Scholar]
- 27.Bacon MC, von Wyl V, Alden C, Sharp G, Robison E, Hessol N, et al. The Women's Interagency HIV Study: an observational cohort brings clinical sciences to the bench. Clin Diagn Lab Immunol. 2005;12(9):1013–9. doi: 10.1128/CDLI.12.9.1013-1019.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Barkan SE, Melnick SL, Preston-Martin S, Weber K, Kalish LA, Miotti P, et al. The Women's Interagency HIV Study. WIHS Collaborative Study Group. Epidemiology. 1998;9(2):117–25. [PubMed] [Google Scholar]
- 29.Kaslow RA, Ostrow DG, Detels R, Phair JP, Polk BF, Rinaldo CR., Jr. The Multicenter AIDS Cohort Study: rationale, organization, and selected characteristics of the participants. Am J Epidemiol. 1987;126(2):310–8. doi: 10.1093/aje/126.2.310. [DOI] [PubMed] [Google Scholar]
- 30.Beachler DC, Weber KM, Margolick JB, Strickler HD, Cranston RD, Burk RD, et al. Risk factors for oral HPV infection among a high prevalence population of HIV-positive and at-risk HIV-negative adults. Cancer Epidemiol Biomarkers Prev. 2012;21(1):122–33. doi: 10.1158/1055-9965.EPI-11-0734. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Broutian TR, He X, Gillison ML. Automated high throughput DNA isolation for detection of human papillomavirus in oral rinse samples. J Clin Virol. 2011;50(4):270–5. doi: 10.1016/j.jcv.2010.12.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Munoz N, Bosch FX, de Sanjose S, Herrero R, Castellsague X, Shah KV, et al. Epidemiologic classification of human papillomavirus types associated with cervical cancer. N Engl J Med. 2003;348(6):518–27. doi: 10.1056/NEJMoa021641. [DOI] [PubMed] [Google Scholar]
- 33.Schiffman M, Clifford G, Buonaguro FM. Classification of weakly carcinogenic human papillomavirus types: addressing the limits of epidemiology at the borderline. Infect Agent Cancer. 2009;4:8. doi: 10.1186/1750-9378-4-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.International Agency for Research on Cancer . Human Papillomaviruses. International Agency for Research on Cancer; Lyon, France: 2012. [Google Scholar]
- 35.Dabitao D, Margolick JB, Lopez J, Bream JH. Multiplex measurement of proinflammatory cytokines in human serum: comparison of the Meso Scale Discovery electrochemiluminescence assay and the Cytometric Bead Array. J Immunol Methods. 2011;372(1-2):71–7. doi: 10.1016/j.jim.2011.06.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Wei L, Lin D, Weissfeld L. Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. Journal of the American Statistical Association. 1989;84(408):1065–1073. [Google Scholar]
- 37.StataCorp . Stata Statistical Software. Release 12 ed 2011. [Google Scholar]
- 38.Frazer IH. Interaction of human papillomaviruses with the host immune system: a well evolved relationship. Virology. 2009;384(2):410–4. doi: 10.1016/j.virol.2008.10.004. [DOI] [PubMed] [Google Scholar]
- 39.Stanley MA. Epithelial cell responses to infection with human papillomavirus. Clin Microbiol Rev. 2012;25(2):215–22. doi: 10.1128/CMR.05028-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Fernandes JV, Fernandes TA, Azevedo JC, Cobucci RN, Carvalho MG, Andrade VS, et al. Link between chronic inflammation and human papillomavirus-induced carcinogenesis (Review) Oncol Lett. 2015;9(3):1015–1026. doi: 10.3892/ol.2015.2884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Bhatia A, Sekhon HK, Kaur G. Sex hormones and immune dimorphism. ScientificWorldJournal. 2014;2014:159150. doi: 10.1155/2014/159150. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Torcia MG, Nencioni L, Clemente AM, Civitelli L, Celestino I, Limongi D, et al. Sex differences in the response to viral infections: TLR8 and TLR9 ligand stimulation induce higher IL10 production in males. PLoS One. 2012;7(6):e39853. doi: 10.1371/journal.pone.0039853. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Chaturvedi AK, Graubard BI, Broutian T, Pickard RK, Tong ZY, Xiao W, et al. NHANES 2009-2012 Findings: Association of Sexual Behaviors with Higher Prevalence of Oral Oncogenic Human Papillomavirus Infections in U.S. Men. Cancer Res. 2015;75(12):2468–77. doi: 10.1158/0008-5472.CAN-14-2843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.D'Souza G, Wentz A, Kluz N, Zhang Y, Sugar E, Youngfellow RM, et al. Gender differences in risk factors and natural history of oral human papillomavirus (HPV) infection. J Infect Dis. 2016 doi: 10.1093/infdis/jiw063. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Bouman A, Heineman MJ, Faas MM. Sex hormones and the immune response in humans. Hum Reprod Update. 2005;11(4):411–23. doi: 10.1093/humupd/dmi008. [DOI] [PubMed] [Google Scholar]
- 46.Malutan AM, Dan M, Nicolae C, Carmen M. Proinflammatory and anti-inflammatory cytokine changes related to menopause. Menopause Review. 2014;13(3):162–8. doi: 10.5114/pm.2014.43818. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.de Gruijl TD, Bontkes HJ, Walboomers J, Stukart MJ, Doekhie FS, Remmink AJ, et al. Differential T helper cell responses to human papillomavirus type 16 E7 related to viral clearance or persistence in patients with cervical neoplasia: a longitudinal study. Cancer Research. 1998;58:1700–1706. [PubMed] [Google Scholar]
- 48.Kemp T, Shelton G, Giuliano AR, Pinto L. HPV2015. Lisbon, Portugal: 2015. Evaluation of Multiplex Assay Performance Characteristics of 52 Cytokines/Chemokines in Oral Fluids Collected in Oral Rinses or Merocel Sponges. [Google Scholar]
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