Abstract
Background
The association of inflammatory biomarkers with clinical events after antiretroviral therapy (ART) initiation is unclear.
Methods
A5202 randomized 1857 treatment-naive subjects to abacavir/lamivudine or tenofovir-DF/emtricitabine with efavirenz or atazanavir/ritonavir. Substudy A5224s measured inflammatory biomarkers on subjects with available plasma from baseline and weeks 24 or 96. An exploratory analysis of the association of hsCRP, IL-6, sTNF-RI, sTNF-RII, TNF-α, sVCAM-1, and sICAM-1 with times to AIDS and to non-AIDS events used Cox proportional hazards models.
Results
Analysis included 244 subjects; 85% male, 48% white non-Hispanic, with median age 39 years, HIV-1 RNA 4.6 log10 copies/mL, and CD4 240 cells/μL. Overall, 13 AIDS events (9 opportunistic infections; 3 AIDS-cancers, 1 recurrent bacterial pneumonia) and 18 non-AIDS events (6 diabetes, 4 cancers, 3 cardiovascular, 5 pneumonias) occurred. Higher baseline IL-6, sTNF-RI, sTNF-RII, and sICAM-1 were significantly associated with increased risk of AIDS-defining events. Adjustment for baseline HIV-1 RNA did not change results, while adjusting for baseline CD4 count left only sTNF-RI and sICAM-1 significantly associated with increased risk. Time-updated values of IL-6, sTNFR-I and II, and sICAM-1 were also associated with an increased risk. For non-AIDS events, only higher baseline hsCRP was significantly associated with increased risk, while higher IL-6 was marginally associated with higher risk. Analyses of time-updated biomarker values showed TNF-α to be significantly associated with increased risk, even after adjustment for ART, and CD4 count or HIV-1 RNA.
Conclusion
Higher levels of several inflammatory biomarkers were independently associated with increased risk of AIDS and non-AIDS events.
Keywords: Inflammation markers, AIDS events, non-AIDS events, C-reactive protein, interleukin-6, endothelial activation markers, TNF-α
INTRODUCTION
In the current era of potent antiretroviral therapy (ART), cross-sectional measurements of inflammation markers, notably interleukin-6 (IL-6) and high-sensitivity C-reactive protein (hsCRP), are linked to higher risk of subsequent mortality1. Recently the INSIGHT study group reported that higher pre-ART levels of IL-6 and hsCRP were associated with increased risk of AIDS events and mortality on ART2. Detailed measurements of markers of tumor necrosis factor-α (TNF-α) and adhesion molecules were not performed in these aforementioned studies. Moreover, in past cross-sectional studies (not necessarily pre-ART measurements), the results have been conflicting in terms of the association between TNF-α levels and higher mortality or AIDS progession3–5. No study has yet investigated the association between time-updated inflammatory marker levels after ART initiation and the occurrence of AIDS and non-AIDS events in the setting of a prospective randomized ART-initiation study.
METHODS
AIDS Clinical Trials Group (ACTG) A5224s was a metabolic substudy of ACTG A5202. In A5202, ART-naïve subjects ≥16 years old with HIV-1 RNA >1,000 copies/mL were randomized in a double-blinded fashion to co-formulated tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) or abacavir/lamivudine (ABC/3TC), along with open-labeled efavirenz (EFV) or atazanavir/ritonavir (ATV/r). Randomization was stratified by screening HIV-1 RNA (< vs. ≥100,000 copies/mL) and by intent to participate in A5224s. A secondary biomarker substudy of A5224s included all subjects with available stored plasma at baseline and week 24 and/or 96, and was designed with the primary objective to compare the effect of ART initiation on inflammation markers, results that were already published6. A secondary objective was to assess the association between baseline and on-ART markers of inflammation and clinical events, separately categorized as AIDS-defining event (CDC Category C clinical events) or non-AIDS defining events (including cardiovascular disease, non-AIDS-defining malignancies, diabetes, liver disease, serious infection that does not fit CDC Category C clinical event) and bone fractures. The non-AIDS events classification was similar to that used in a recently published analysis conducted within the ACTG7, except that a priori, we selected to consider bone fractures as a separate events category and not lump them within the non-AIDS events category, since all bone fractures that occurred within A5224s were the result of a trauma. A5224s’ major exclusion criteria were endocrine diseases including diabetes mellitus. The duration of the substudy was 96 weeks after the last subject enrolled into A5202 and subjects were followed regardless of their antiretroviral treatment status. Each subject signed an informed consent, which was approved by participating site’s local Institutional Review Board.
BIOMARKER ASSAYS
Plasma samples were stored at −80°C without prior thawing until analysis. Assays were performed at Johns Hopkins Bayview Advanced Chemistry Laboratory, Baltimore, MD, USA. We measured 7 markers, hsCRP (μg/mL), IL-6 (pg/mL), TNF-α (pg/mL), and the soluble receptors of TNF-α, (sTNFR-I,-II-both in pg/mL), along with the endothelial activation markers soluble vascular cellular and intercellular adhesion molecules (sVCAM-1 and sICAM-1, both in ng/mL). hsCRP was measured using a highly sensitive ELISA (ALPCO Diagnostics, Windham, NH). Other markers were measured using an enzyme-immunosorbent assay (R&D Systems, Minnesota, WI, USA). Markers were measured in duplicate and values averaged for analysis. The intra-assay and inter-assay precisions of these assays were 1.3–7.6% coefficient of variation (CV) (average 3.3%) and 1.8–9.0% CV (average 6.9%), respectively.
STATISTICAL ANALYSIS
This exploratory and secondary analysis of the association between baseline and time-updated biomarker levels and times to first AIDS-defining event, non-AIDS-defining event, and bone fracture used Cox proportional hazards regression. Multivariable models adjusted for the following pre-specified covariates that could affect inflammation: ART assignment, then ART assignment plus each of the following individually; baseline CD4, baseline HIV-1 RNA, time-updated CD4, time-updated HIV-1 RNA suppression <50 copies/mL, and time-updated HIV-1 RNA suppression < 200 copies/mL.
In time-updated analysis, for subjects with missing week 24 or 96 biomarker levels their last observed value, including the baseline value, was carried forward. In addition, to account for the potential confounding effect on the time-updated analysis of the early events that occurred before week 24, we performed a 24 week landmark analysis that excluded subjects with early events before week 24, subjects with missing week 24 sample and subjects with HIV-1 RNA level ≥50 copies/ml at week 24. In all models, CD4 was modeled with a linear and a quadratic term. P-values below 0.05 were considered statistically significant; no adjustments were made for multiple comparisons. Analyses were performed using SAS, version 9.2 (SAS Institute). Due to skewed distributions, biomarkers were loge transformed prior to analysis.
RESULTS
Subject Characteristics
As previously detailed8–9, 269 subjects were enrolled in A5224s. Of these 269 subjects, 244 (91%) with available stored plasma from baseline and week 24 and/or 96 were included in this biomarker substudy. Baseline characteristics were previously reported6. Supplementary Table is added to show baseline characteristics by study population. Overall, 85% were male, 48% white non-Hispanics, and among 205 subjects with available data, 41% were smokers. Median age was 39 years, CD4 240 cells/μL, and HIV-1 RNA 4.64 log10 copies/mL. None of the subjects had a prior history of myocardial infarction and one had a history of stroke. Baseline characteristics were similar between the 244 included in the biomarker substudy and the 25 A5224s subjects not included (data not shown).
At week 24, 171 (70%) had HIV-1 RNA<50 copies/mL [70% on TDF/FTC; 70% on ABC/3TC]. Among subjects who had screening HIV-1 RNA ≥100,000 copies/mL, 56% on TDF/FTC and 60% on ABC/3TC had HIV-1 RNA <50 copies/mL.
Characteristics of Clinical Events
Only the first clinical event was considered for each subject in time to event analyses There were a total of 13 AIDS-events that occurred during the study: recurrent bacterial pneumonia (1), CMV retinitis (1), cryptosporidiosis (1), esophageal candidiasis (1), non-Hodgkin’s lymphoma (2), Kaposi sarcoma (1), Mycobacterium avium complex (4), and Pneumocystis jirovecii pneumonia (2). These AIDS events happened after a median (range) of 15.6 (2.0 – 132.6) weeks on study, with seven events occurring before week 24. A total of 18 subjects had at least one non-AIDS event that occurred during the study: acute myocardial infarction (2), pulmonary embolism (1), cancers (4: Hodgkin’s disease 1; hypopharyngeal cancer 1; prostate cancer 2), diabetes (6), isolated episode of non-PCP pneumonia (5). These non-AIDS events happened after a median (range) of 81.4 (3.6 – 165.1) weeks on study, with four events occurring before week 24. When considering time to first AIDS- or non-AIDS event, a total of 28 subjects had at least one event that occurred during study, 11 of which occurring before week 24. In addition, a total of 15 bone fractures occurred during the study, all of which were associated with a trauma.
Deaths were not included in the AIDS-event or in the non-AIDS events. A total of 2 deaths were reported in the analysis sample. One subject was diagnosed with diabetes at week 24 then at week 106 was diagnosed with septic shock, non-Hodgkin’s lymphoma, and a pulmonary embolism followed by death. The second subject died without a prior event at week 25 with the cause of death reported as substance abuse.
The week 24 landmark analysis included 5 AIDS defining events (3 that occurred between weeks 24 and 96 and 2 that occurred after week 96), 12 non-AIDS defining events (6 between weeks 24 and 96 and 6 after week 96), and for the combined event analysis, 14 AIDS or non-AIDS events (9 between 24 and 96 weeks and 5 after week 96).
Biomarker Associations with CD4 Counts
At baseline CD4 count was inversely but not strongly correlated with levels of IL-6 (Spearman rank correlation r= −0.20, p=0.002), sTNF-RI (r = −0.25, p<0.001), and sTNF-RII (r = −0.30, p<0.001) (Supplementary table). Also, the change in CD4 count from baseline to week 24 was inversely correlated with baseline to week 24 changes in levels of sVCAM-1 (r = −0.40, p<0.001), sICAM-1 (r = −0.22, p =0.001), sTNF-RII (r = −0.36, p<0.001), sTNF-RI (r = −0.16, p=0.015), and TNF-α (r = −0.29, p<0.001). Similarly, the change in CD4 count from baseline to week 96 was correlated with baseline to week 96 changes in levels of sVCAM-1 (r = −0.36, p<0.001), sTNF-RII (r = −0.23, p=0.001), sTNF-RI (r =−0.14, p=0.046), and TNF-α (r = −0.22, p=0.001). Notably, neither baseline nor changes in CD4 count correlated with baseline or changes in hsCRP levels (r ≤ 0.07; p ≥ 0.31).
Biomarker Associations with HIV-1 RNA Levels
At baseline HIV-1 RNA level correlated with levels of IL-6 (r = 0.17, p=0.008), sVCAM-1 (r = 0.45, p<0.001), sICAM-1 (r = 0.26, p<0.001), sTNF-RII (r = 0.52, p<0.001), sTNF-RI (r = 0.43, p<0.001), and TNF-α (r = 0.38, p<0.001), but not with hsCRP (r = 0.04, p =0.49). Only for sTNFR-I was mean change from baseline to week 24 significantly different between subjects who at week 24 were virologically suppressed (<50 copies/mL) or not (estimated mean (SD) −0.18 (0.23) vs. −0.12 (0.17) pg/mL; p=0.018). The mean (SD) change from baseline to week 96 in sTNFR-II, sVCAM-1, and TNF-α were statistically significantly different between subjects who were virologically suppressed (<50 copies/mL) or not (−0.73 (0.43) vs. −0.52 (0.56) pg/mL; p=0.019 and −0.53 (0.33) vs. −0.25 (0.42) ng/mL; p<0.001, and −0.75 (0.42) vs. −0.37 (0.52) pg/mL; p<0.001, respectively).
Biomarker Association with AIDS-Defining Event
We first examined for each of the 7 biomarkers the association between baseline biomarker value and time to first AIDS-defining event (Table 1). Higher values in baseline IL-6, sTNF-RI, sTNF-RII, and sICAM-1 were significantly associated with an increased risk of AIDS-defining event. Adjustment for ART assignment and for baseline HIV-1 RNA did not change the results (data not shown). Adjusting for baseline CD4 count attenuated the association of higher values with increased risk with these biomarkers, with baseline sICAM-1 remaining significantly associated with increased risk of events.
Table 1.
Biomarker Associations with AIDS-defining Events
| Baseline and Time-Updated Biomarker Association with AIDS-Defining Events | ||||||
|---|---|---|---|---|---|---|
| Biomarker | Unadjusted | Baseline CD4, NRTI and NNRTI/PI Adjusted | Time-Updated CD4, NRTI and NNRTI/PI Adjusted | |||
| HR (95% Cl) | P-value | HR (95% Cl) | P-value | HR (95% Cl) | P-value | |
| Baseline hsCRP (per 0.5 loge ug/ml higher) | 1.10 (0.89, 1.35) | 0.36 | 1.14 (0.94, 1.39) | 0.19 | ||
| Time-updated hsCRP (per 0.5 loge ug/ml higher) | 1.08 (0.88, 1.33) | 0.44 | 1.10 (0.90, 1.34) | 0.37 | 1.10 (0.91, 1.35) | 0.33 |
| Baseline IL-6 (per 0.5 loge pg/ml higher) | 1.41 (1.03, 1.92) | 0.032 | 1.26 (0.91, 1.75) | 0.16 | ||
| Time-updated IL-6 (per 0.5 loge pg/ml higher) | 1.43 (1.06, 1.94) | 0.020 | 1.33 (0.98, 1.82) | 0.068 | 1.30 (0.95, 1.77) | 0.10 |
| Baseline sICAM-1 (per 0.5 loge ng/ml higher) | 2.88 (1.39, 5.97) | 0.004 | 2.28 (1.17, 4.42) | 0.015 | ||
| Time-updated sICAM-1 (per 0.5 loge ng/ml higher) | 2.11 (1.09, 4.08) | 0.027 | 1.85 (0.99, 3.47) | 0.055 | 1.80 (0.95, 3.39) | 0.071 |
| Baseline sTNF-RI (per 0.5 loge pg/ml higher) | 3.20 (1.44, 7.09) | 0.004 | 2.04 (0.88, 4.74) | 0.096 | ||
| Time-updated sTNF-RI (per 0.5 loge pg/ml higher) | 4.26 (1.71, 10.58) | 0.002 | 2.95 (1.15, 7.59) | 0.024 | 2.90 (1.14, 7.35) | 0.025 |
| Baseline sTNF-RII (per 0.5 loge pg/ml higher) | 1.86 (1.13, 3.05) | 0.015 | 1.64 (0.96, 2.82) | 0.071 | ||
| Time-updated sTNF-RII (per 0.5 loge pg/ml higher) | 1.87 (1.13, 3.11) | 0.015 | 1.69 (0.98, 2.90) | 0.059 | 1.59 (0.92, 2.75) | 0.099 |
| Baseline sVCAM-1 (per 0.5 loge ng/ml higher) | 1.51 (0.77, 2.99) | 0.23 | 1.49 (0.74, 3.01) | 0.26 | ||
| Time-updated sVCAM-1 (per 0.5 loge ng/ml higher) | 1.33 (0.64, 2.76) | 0.45 | 1.33 (0.64, 2.77) | 0.45 | 1.22 (0.59, 2.52) | 0.58 |
| Baseline TNF-α (per 0.5 loge pg/ml higher) | 1.51 (0.82, 2.79) | 0.19 | 1.60 (0.86, 2.95) | 0.14 | ||
| Time-updated TNF-α (per 0.5 loge pg/ml higher) | 1.39 (0.73, 2.64) | 0.31 | 1.39 (0.72, 2.68) | 0.33 | 1.38 (0.71, 2.69) | 0.35 |
Table 1 also shows the associations between time-updated biomarker values and time to first AIDS-event. The time-updated values in IL-6, sTNF-RI, sTNF-RI and sICAM-1 were significantly associated with increased risk of AIDS-defining events. Adjustment for ART assignment and for baseline or time-updated CD4 counts attenuated the relationship (Table 1). Also, adjustment for ART assignment and for baseline HIV-1 RNA levels or for achieving virologic suppression did not change the results. Results were similar whether virologic suppression was defined as HIV-1 RNA <50 copies/mL or <200 copies/mL.
Biomarker Association with non AIDS-Defining Event
We also examined the associations between biomarker levels at baseline and time to first non-AIDS-defining event (Table 2). Baseline hsCRP was significantly associated with developing a non-AIDS-event, and there was a trend for an association with IL-6. Adjustment for ART assignment and for baseline HIV-1 RNA levels did not change either of the results. Adjustment for baseline CD4 did not change the hsCRP results.
Table 2.
Biomarker Associations with non-AIDS Defining Events
| Baseline and Time-Updated Biomarker Association with Non-AIDS-Defining Events | ||||||
|---|---|---|---|---|---|---|
| Biomarker | Unadjusted | Baseline CD4, NRTI and NNRTI/PI Adjusted | Time-Updated CD4, NRTI and NNRTI/PI Adjusted | |||
| HR (95% Cl) | P-value | HR (95% Cl) | P-value | HR (95% Cl) | P-value | |
| Baseline hsCRP (per 0.5 loge ug/ml higher) | 1.29 (1.07, 1.55) | 0.007 | 1.29 (1.07, 1.55) | 0.009 | ||
| Time-updated hsCRP (per 0.5 loge ug/ml higher) | 1.07 (0.90, 1.28) | 0.44 | 1.08 (0.90, 1.30) | 0.40 | 1.08 (0.90, 1.29) | 0.42 |
| Baseline IL-6 (per 0.5 loge pg/ml higher) | 1.30 (0.98, 1.71) | 0.068 | 1.30 (0.96, 1.76) | 0.087 | ||
| Time-updated IL-6 (per 0.5 loge pg/ml higher) | 0.98 (0.71, 1.35) | 0.91 | 1.01 (0.74, 1.39) | 0.94 | 0.99 (0.72, 1.37) | 0.97 |
| Baseline sICAM-1 (per 0.5 loge ng/ml higher) | 0.90 (0.73, 1.12) | 0.33 | 0.87 (0.70, 1.08) | 0.21 | ||
| Time-updated sICAM-1 (per 0.5 loge ng/ml higher) | 0.95 (0.74, 1.20) | 0.64 | 0.93 (0.73, 1.17) | 0.52 | 0.95 (0.74, 1.20) | 0.64 |
| Baseline sTNF-RI (per 0.5 loge pg/ml higher) | 1.15 (0.49, 2.69) | 0.75 | 1.07 (0.41, 2.77) | 0.89 | ||
| Time-updated sTNF-RI (per 0.5 loge pg/ml higher) | 1.61 (0.58, 4.45) | 0.36 | 1.63 (0.56, 4.75) | 0.37 | 1.60 (0.56, 4.62) | 0.38 |
| Baseline sTNF-RII (per 0.5 loge pg/ml higher) | 1.29 (0.83, 2.00) | 0.26 | 1.34 (0.85, 2.11) | 0.21 | ||
| Time-updated sTNF-RII (per 0.5 loge pg/ml higher) | 1.44 (0.87, 2.37) | 0.15 | 1.50 (0.90, 2.51) | 0.12 | 1.47 (0.88, 2.47) | 0.14 |
| Baseline sVCAM-1 (per 0.5 loge ng/ml higher) | 1.02 (0.57, 1.82) | 0.95 | 1.13 (0.62, 2.07) | 0.69 | ||
| Time-updated sVCAM-1 (per 0.5 loge ng/ml higher) | 1.46 (0.78, 2.75) | 0.24 | 1.56 (0.82, 2.96) | 0.18 | 1.46 (0.76, 2.80) | 0.25 |
| Baseline TNF-α (per 0.5 loge pg/ml higher) | 1.53 (0.90, 2.60) | 0.12 | 1.49 (0.90, 2.48) | 0.12 | ||
| Time-updated TNF-α (per 0.5 loge pg/ml higher) | 1.94 (1.14, 3.28) | 0.014 | 2.00 (1.17, 3.40) | 0.011 | 1.97 (1.16, 3.34) | 0.012 |
Table 2 shows the associations between time-updated biomarkers and non-AIDS-events. Only the time-updated TNF-α values were statistically significantly associated with an increased risk of non-AIDS-defining events. Adjustment for ART assignment, and for baseline or time-updated CD4 count, or baseline HIV-1 level or for achieving virologic suppression (defined at <50 copies/mL or <200 copies/mL) did not change the results.
We considered fracture events as a separate category because of its unclear association with inflammation and the other categories of non-AIDS-events. Neither baseline nor time-updated biomarker values were significantly associated with time to first fracture (data not shown).
Biomarker Association with First Clinical Event (AIDS or non-AIDS events)
A total of 28 first clinical events (AIDS or non-AIDS) were combined (Table 3). Higher values in baseline hsCRP, IL-6, sTNF-RI, and sTNF-RII were significantly associated with an increased risk of time to first AIDS- or non-AIDS clinical event. The Kaplan-Meier plots are shown in Figure 1, stratified by tertiles for these 4 markers. There was also a trend towards higher baseline TNF-α being associated with increased risk. Adjustment for ART assignment and for baseline HIV-1 RNA or CD4 count did not change the results for any of the baseline biomarkers associations with clinical events with the exception of sTNF-RI after adjustment for baseline CD4 which was no longer statistically significant.
Table 3.
Biomarker Associations with Any Clinical Events (combined AIDS-defining Events or non-AIDS defining Events)
| Baseline and Time-Updated Biomarker Association with AIDS- and Non-AIDS-Defining Events | ||||||
|---|---|---|---|---|---|---|
| Biomarker | Unadjusted | Baseline CD4, NRTI and NNRTI/PI Adjusted | Time-Updated CD4, NRTI and NNRTI/PI Adjusted | |||
| HR (95% Cl) | P-value | HR (95% Cl) | P-value | HR (95% Cl) | P-value | |
| Baseline hsCRP (per 0.5 loge ug/ml higher) | 1.21 (1.05, 1.40) | 0.008 | 1.22 (1.06, 1.40) | 0.005 | ||
| Time-updated hsCRP (per 0.5 loge ug/ml higher) | 1.05 (0.92, 1.21) | 0.46 | 1.06 (0.92, 1.22) | 0.40 | 1.06 (0.93, 1.22) | 0.37 |
| Baseline IL-6 (per 0.5 loge pg/ml higher) | 1.38 (1.10, 1.71) | 0.004 | 1.29 (1.02, 1.62) | 0.032 | ||
| Time-updated IL-6 (per 0.5 loge pg/ml higher) | 1.13 (0.89, 1.44) | 0.31 | 1.11 (0.87, 1.41) | 0.42 | 1.08 (0.84, 1.38) | 0.54 |
| Baseline sICAM-1 (per 0.5 loge ng/ml higher) | 1.03 (0.77, 1.38) | 0.83 | 1.01 (0.76, 1.35) | 0.95 | ||
| Time-updated sICAM-1 (per 0.5 loge ng/ml higher) | 1.04 (0.79, 1.37) | 0.77 | 1.03 (0.77, 1.36) | 0.86 | 1.03 (0.79, 1.35) | 0.83 |
| Baseline sTNF-RI (per 0.5 loge pg/ml higher) | 2.26 (1.25, 4.07) | 0.007 | 1.77 (0.93, 3.34) | 0.080 | ||
| Time-updated sTNF-RI (per 0.5 loge pg/ml higher) | 2.77 (1.37, 5.62) | 0.005 | 2.32 (1.12, 4.80) | 0.024 | 2.35 (1.13, 4.89) | 0.022 |
| Baseline sTNF-RII (per 0.5 loge pg/ml higher) | 1.59 (1.13, 2.24) | 0.008 | 1.48 (1.04, 2.13) | 0.031 | ||
| Time-updated sTNF-RII (per 0.5 loge pg/ml higher) | 1.53 (1.06, 2.21) | 0.024 | 1.46 (1.00, 2.15) | 0.051 | 1.42 (0.96, 2.10) | 0.078 |
| Baseline sVCAM-1 (per 0.5 loge ng/ml higher) | 1.14 (0.72, 1.82) | 0.57 | 1.15 (0.72, 1.85) | 0.55 | ||
| Time-updated sVCAM-1 (per 0.5 loge ng/ml higher) | 1.18 (0.71, 1.97) | 0.52 | 1.20 (0.73, 1.99) | 0.47 | 1.12 (0.67, 1.85) | 0.67 |
| Baseline TNF-α (per 0.5 loge pg/ml higher) | 1.46 (0.96, 2.23) | 0.076 | 1.48 (0.99, 2.24) | 0.059 | ||
| Time-updated TNF-α (per 0.5 loge pg/ml higher) | 1.53 (1.00, 2.36) | 0.052 | 1.54 (1.00, 2.38) | 0.051 | 1.53 (0.99, 2.37) | 0.058 |
Figure 1.
Kaplan-Meier plots stratified by tertiles for hCRP, IL-6, sTNFR-I, and sTNF-RII
The association between time-updated biomarker value and the composite endpoint of clinical events was also assessed. Only the time-updated values for sTNF-RI and sTNF-RII were significantly associated with an increased risk of clinical events. In addition, time-updated biomarker value for TNF-α trended towards being associated with increased risk. Adjustment for ART assignment, for baseline or time-updated CD4 count, or baseline HIV-1 level, or for achieving virologic suppression (defined at <50 copies/mL or <200 copies/mL) did not change the results for sTNF-RI but sTNF-RII was no longer statistically significant. Adjusting for ART assignment and for achieving virologic suppression (HIV-1 RNA <200 copies/mL) did strengthen the TNF-α association.
Week 24 Landmark Analysis
Among virologically suppressed subjects (HIV-1 RNA <50 copies/mL at week 24), additional analyses were undertaken to explore the association between week 24 biomarker level and time to first event occurring after week 24 (Table 4).
Table 4.
Landmark Analyses, Week 24 Biomarker Associations among Subjects without a prior event and HIV RNA level < 50 copies/mL at Week 24.
| Week 24 Biomarker | Unadjusted | Week 24 CD4, NRTI and NNRTI/PI Adjusted | ||
|---|---|---|---|---|
| HR (95% Cl) | P-value | HR (95% Cl) | P-value | |
| Biomarker Association with AIDS-Defining Events | ||||
| hsCRP (per 0.5 loge ug/ml higher) | 0.89 (0.64, 1.24) | 0.48 | 0.78 (0.49, 1.24) | 0.29 |
| L-6 (per 0.5 loge pg/ml higher) | 0.94 (0.50, 1.78) | 0.85 | 0.83 (0.37, 1.83) | 0.64 |
| sICAM-1 (per 0.5 loge ng/ml higher) | 2.82 (0.84, 9.49) | 0.094 | 2.57 (0.56, 11.88) | 0.23 |
| sTNF-RI (per 0.5 loge pg/ml higher) | 1.69 (0.21, 13.44) | 0.62 | 2.26 (0.14, 37.02) | 0.57 |
| sTNF-RII (per 0.5 loge pg/ml higher) | 1.60 (0.58, 4.39) | 0.36 | 2.07 (0.26, 16.41) | 0.49 |
| sVCAM-1 (per 0.5 loge ng/ml higher) | 2.69 (1.01, 7.13) | 0.047 | 1.88 (0.51, 7.00) | 0.34 |
| TNF-α (per 0.5 loge pg/ml higher) | 1.60 (0.61, 4.19) | 0.33 | 1.20 (0.23, 6.31) | 0.83 |
| Biomarker Association with Non-AIDS-Defining Events | ||||
| hsCRP (per 0.5 loge ug/ml higher) | 0.97 (0.78, 1.19) | 0.76 | 0.96 (0.76, 1.22) | 0.74 |
| L-6 (per 0.5 loge pg/ml higher) | 1.07 (0.75, 1.53) | 0.73 | 1.00 (0.68, 1.46) | 0.98 |
| sICAM-1 (per 0.5 loge ng/ml higher) | 1.60 (0.75, 3.43) | 0.22 | 1.26 (0.57, 2.81) | 0.57 |
| sTNF-RI (per 0.5 loge pg/ml higher) | 2.56 (0.69, 9.60) | 0.16 | 2.94 (0.70, 12.41) | 0.14 |
| sTNF-RII (per 0.5 loge pg/ml higher) | 1.76 (0.98, 3.16) | 0.060 | 1.72 (0.89, 3.35) | 0.11 |
| sVCAM-1 (per 0.5 loge ng/ml higher) | 1.60 (0.74, 3.42) | 0.23 | 1.43 (0.64, 3.18) | 0.38 |
| TNF-α (per 0.5 loge pg/ml higher) | 1.66 (0.93, 2.96) | 0.085 | 1.63 (0.86, 3.08) | 0.13 |
| Biomarker Association with AIDS- and Non-AIDS Events | ||||
| hsCRP (per 0.5 loge ug/ml higher) | 0.96 (0.79, 1.17) | 0.69 | 0.94 (0.76, 1.17) | 0.59 |
| L-6 (per 0.5 loge pg/ml higher) | 1.04 (0.74, 1.47) | 0.82 | 1.01 (0.71, 1.44) | 0.95 |
| sICAM-1 (per 0.5 loge ng/ml higher) | 1.74 (0.85, 3.54) | 0.13 | 1.42 (0.68, 2.99) | 0.35 |
| sTNF-RI (per 0.5 loge pg/ml higher) | 3.53 (1.02, 12.18) | 0.046 | 4.20 (1.10, 16.03) | 0.036 |
| sTNF-RII (per 0.5 loge pg/ml higher) | 1.80 (1.05, 3.08) | 0.033 | 1.83 (0.98, 3.41) | 0.059 |
| sVCAM-1 (per 0.5 loge ng/ml higher) | 1.96 (1.02, 3.76) | 0.044 | 1.76 (0.90, 3.44) | 0.10 |
| TNF-α (per 0.5 loge pg/ml higher) | 1.75 (1.04, 2.96) | 0.035 | 1.76 (0.98, 3.16) | 0.060 |
For time to first AIDS- or non-AIDS defining event, 171 subjects were virologically suppressed and an additional 8 subjects were removed due to having an early event within the first 24 weeks (5 subjects) or having their baseline biomarker level carried forward to week 24 (3 subjects). Among the 163 subjects analyzed, there were 14 events (9 between week 24 and 96 and 5 after week 96). Week 24 sTNF-RI, sTNFR-II, TNF-α and sVCAM-1 (per 0.5 loge higher were significantly associated with developing an AIDS- or non-AIDS-event (HR 3.53 (95% CI 1.02, 12.18), p=0.046 and HR 1.80 (95% CI 1.05, 3.08), p=0.033 and HR 1.75 (95% CI 1.04, 2.96), p=0.035 and HR 1.96 (95% CI 1.02, 3.76), p=0.044, respectively). After adjustment for ART assignment and week 24 CD4 count, only sTNF-RI remained statistically significant (HR 4.20 (95% CI 1.10, 16.03), p=0.036).
DISCUSSION
The absolute CD4 cell count has been extensively used as a tool to predict HIV disease progression and morbidities. A more recent focus has been on the association between immune activation and inflammatory biomarkers and HIV mortality and co-morbidities on ART. Thus far, several studies have linked a single measurement of an inflammatory marker to subsequent mortality10–12, myocardial infarction risk13, and increased intima media thickness14–15 (a marker of vascular disease). In contrast, very limited data exist on the association between either pre-ART or on-ART biomarker values to clinical events. To our knowledge, our study is the largest and longest study to use such an approach to assess this association in a randomized ART-initiation clinical trial. We showed that higher pre-ART and on-ART levels of several inflammatory biomarkers were associated independently of CD4 count with increased risk of progression to AIDS and/or non-AIDS events.
The association between pre-ART inflammatory marker levels and the risk of progression to clinical events on suppressive ART has been investigated in few studies. Our findings that higher pre-ART IL-6 is associated with increased risk of AIDS-defining event is consistent with the results of two case-control studies2,16. One of these studies also found that pre-ART sTNF-RI (but not sTNF-RII) was associated with such a risk16. However, in contrast to one of these studies2, we did not find an association with baseline hsCRP. Rather, we found that higher baseline hsCRP is associated with increased rate of progression to a non-AIDS event. When we combined progression to AIDS and non-AIDS events baseline hsCRP and IL-6 were associated with increased risk of clinical progression.
Limited data exist on serial measurements of inflammatory markers in HIV-infected subjects starting their first ART regimen. It was notable in our study that overall, in both unadjusted and CD4- or HIV-1 RNA- adjusted analyses, time-updated levels in markers of TNF-α levels (levels of TNF-α or its soluble receptors), were associated with clinical events whereas this was not observed for hsCRP, and less consistently so with IL-6. Importantly, our analyses were also adjusted for ART assignment. The lack of association between hsCRP and events is notable because of our previously described findings of more favorable changes in hsCRP after initiation of TDF/FTC versus ABC/3TC- containing regimens6. However, we cannot rule out the possibilty that hsCRP could be specifically associated with cardiovascular events as shown by others12, since only three cardiovascular events occured during study. Also notable is that the findings of an association between markers of TNF-α levels with events is consistent with a prior case-control study in which 48 weeks after initiation of ART, levels of sTNFR-I and sTNFR-II, but not CRP or IL-6, were independently associated with incident diabetes17.
The lack of association between any baseline or time-updated inflammatory markers and bone fractures is not too surprising since a relationship between HIV-associated heightened inflammation and changes in bone health remains speculative and not proven. Indeed, in one prior study, we showed that changes in the inflammatory markers sTNFR-I and -II were not associated with changes in whole body bone mineral density18. Also, all bone fractures that occurred in A5224s were associated with a traumatic event, and thus may not represent pathologic bone health.
Our study has some limitations, including relatively small number of events that limits the precision on the hazard ratio estimates, resulting in wide confidence intervals, possible selection bias of A5224s subjects who have available week 24 and/or 96 samples (possibly favoring healthier subjects with lower inflammation and maybe lower event rates) and the large number of analyses performed without adjustment for multiple comparisons, which may increase the probability of erroneously declaring an association Also, because we had a relatively small number of events the adjusted analyses should be interpreted with caution as the number of events per covariate in some of these models was <1019. The small number of events also limited our ability to adjust for all potential confounders such as smoking or hepatitis. The time-updated analyses need to be interpreted with caution because 7 of 13 AIDS events and 4 of 18 non-AIDS occurred before the first post-baseline biomarker measurement timepoint at week 24, where subjects had to remain event free before through that time point before the baseline value was updated. Nonetheless, this study is the longest study to date that investigated biomarker associations with clinical events in a group of subjects who recently initiated ART with regimens that are still current today. Also, an additional strength of the study is the randomization to the ART regimen which provides balance in unmeasured covariates.
In summary, we showed that higher levels of several inflammatory biomarkers were associated independently of CD4 with increased risk of AIDS or non-AIDS events. Larger and longer studies should investigate the use of these markers as predictors of clinical endpoints, especially during long-term viral suppression on ART.
Supplementary Material
Acknowledgments
The project described was supported by Award Numbers U01AI068636, AI068634, AI38855, AI065348 from the National Institute of Allergy and Infectious Diseases, and UL1 RR 025005 from the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Allergy and Infectious Diseases or the National Institutes of Health. GlaxoSmithKline and Gilead funded the cost of the inflammation marker assays. Study medications were provided by Abbott Pharmaceuticals, Bristol-Myers Squibb, Gilead Sciences, and GlaxoSmithKline.
Acknowledgment Appendix for A5224s
Sadia Shaik, M.D. and Ruben Lopez, M.D.- Harbor-UCLA Medical Center (Site 603) CTU Grant #:AI0694241, UL1-RR033176
Susan L. Koletar, MD and Diane Gochnour, RN- The Ohio State University Medical Center (Site 2301) CTU Grant # AI069474
Geyoul Kim, RN and Mark Rodriguez, RN- Washington University (Site 2101) CTU Grant #:U01AI069495; GCRC Grant: UL1 RR024992
Elizabeth Lindsey, RN and Tamara James, BS - Alabama Therapeutics CRS (Site 5801) CTU Grant #: U01 AI069452
Ann C. Collier, MD and Jeffrey Schouten, MD, JD- University of Washington (Site 1401) CTU Grant #: AI069434; UL1 RR025014
Jorge L. Santana Bagur, MD and Santiago Marrero, MD- Puerto Rico-AIDS Clinical Trials Unit (Site 5401) CTU Grant # 5 U0I AI069415-03
Jenifer Baer, RN, BSN and Carl Fichtenbaum, MD- University of Cincinnati (Site 2401) CTU Grant # AI069513
Patricia Walton BSN RN and Barbara Philpotts BSN RN- Case Western Reserve (Site 2501) CTU Grant #: AI69501
Princy Kumar, M.D. and Joseph Timpone, M.D.- Georgetown University (Site 1008) CTU Grant#: ACTG grant # 5U01AI069494
Donna Pittard RN BSN and David Currin RN- University of North Carolina (Site 3201) CTU Grant #: 5-U01 AI069423-03; UNC CFAR #: P30 AI050410(-11); UNC CTRC #: UL 1RR 025747
Julie Hoffman, R.N. and Edward Seefried, R.N.- San Diego Medical Center UC (Site 701) CTU Grant # AI69432
Susan Swindells MBBS and Frances Van Meter APRN- University of Nebraska (Site 1505) CTU Grant #: AI 27661
Deborah McMahon, MD and Barbara Rutecki, MSN, MPH, CRNP- University of Pittsburgh (Site 1001) CTU Grant #: 1 U01 AI069494-01
Michael P. Dube, M.D. and Martha Greenwald, R.N., M.S.N- Indiana University (Site 2601) CTU Grant #: 5U01AI025859; GCRC #: M01 RR00750
Ilene Wiggins, RN, and Eric Zimmerman, RN- Johns Hopkins University (Site 201) CTU Grant #: AI27668; CTSA Grant # UL1 RR025005
Judith. Aberg, M.D. and Margarita Vasquez R.N.- New York University/NYC HHC at Bellevue Hospital Center (Site 401) CTU Grant #: AI27665, New grant number: AI069532
Martin McCarter and M. Graham Ray, R.N., M.S.N. - Colorado AIDS Clinical Trials Unit, (Site 6101) CTU Grant # AI69450; RR025780
Mamta Jain, MD -PI and Tianna Petersen, MS-University of Texas Southwestern Medical Center (Site 3751) CTU Grant #: 3U01AI046376-05S4
Emily Stumm, BS and Pablo Tebas MD- University of Pennsylvania, Philadelphia (Site 6201) CTU Grant #: P30-AI0450008-11; CFAR Grant #: UO1-AI069467-04
Mary Albrecht, MD and Neah Kim, NP- Beth Israel Deaconess (Partners/Harvard) CRS (Site 103) CTU Grant # U01 AI069472-04
Paul Edward Sax, M.D. and Joanne Delaney RN- Brigham and Women’s Hospital (Site 107) CTU Grant # UOI AI 069472
Christine Hurley, RN and Roberto Corales, DO- AIDS Care (Site 1108) CTU Grant #: U01AI069511-02 (as of 2/12/08); GCRC: UL1 RR 024160
Keith Henry, MD and Bette Bordenave, RN- Hennepin County Medical Center (Site 1502) CTU Grant #: N01 AI72626
Wendy Armstrong, MD and Ericka R. Patrick, RN, MSN, CCRC- Emory University HIV/AIDS Clinical Trails Unit (Site 5802) CTU Grant #: UO1Al69418-01/CFAR Grant Number: P30Al050409
Jane Reid RNC MS and Mary Adams RN MPh- University of Rochester (Site 1101) CTU Grant #: U01AI069511-02 (as of 2/12/08); GCRC: UL1 RR 024160
Gene D. Morse, Pharm.D., FCCP, BCPS- SUNY - Buffalo, Erie County Medical Ctr. (Site 1102) CTU Grant # AI27658
Michael P. Dube, M.D. and Martha Greenwald, R.N., M.S.N- Wishard Memorial Hospital Indiana University (Site 2603) CTU Grant #: 5U01AI025859; GCRC #: M01 RR00750
Kimberly Y. Smith, MD, MPH and Joan A. Swiatek, APN- Rush University Medical Center (Site 2702) CTU Grant #: U01 AI069471
Nancy Hanks, RN, and Debra Ogata-Arakaki, RN, -University of Hawaii at Manoa, Leahi Hospital (Site 5201) CTU Grant # AI34853
Ardis Moe, MD and Maria Palmer PA-C- UCLA Medical Center (Site 601) CTU Grant #1U01AI069424-01
Jeffery Meier, M.D. and Jack T. Stapleton, M.D. - University of Iowa Hospitals and Clinics (Site 1504) CTU Grant #: UL1RR024979
Gary Matthew Cox, MD and Martha Silberman, RN- Duke University Medical Center Adult CRS (Site 1601) CTU Grant # 5U01 AI069 484-02
2705 - Cook County Hospital
Gerianne Casey, RN and William O’Brien MD-University of Texas, Galveston (Site 6301) CTU Grant # AI32782
Valery Hughes, FNP and Todd Stroberg, RN- Cornell CRS (Site 7803, 7804) – CTU Grant#: U01 AI069419; CTSC #: UL1 RR024996
Nyef El-Daher MD -McCree McCuller Wellness Center at the Connection (Site 1107) CTU Grant #: U01AI069511-02 (as of 2/12/08); GCRC: UL1 RR 024160
Rebecca J. Basham, B.S. and Husamettin Erdem, M.D.-Vanderbilt Therapeutics CRS (Site 3652) CTU Grant #: AI46339-01; MO1 RR 00095
Footnotes
Clinical trials registry: NCT00118898
Potential conflicts: Grace A McComsey has served as a scientific advisor or speaker for Bristol Myers Squibb, GlaxoSmithKline, Merck, Janssen, and Gilead Sciences, has received research grants from Bristol Myers Squibb, GlaxoSmithKline, and Gilead Sciences, and is currently serving as the DSMB Chair for a Pfizer-sponsored study. Douglas Kitch has no conflict. Paul Sax serves as a consultant for Abbott, BMS, Gilead, GSK, Merck, Janssen, and ViiV and receives grant Support from Gilead, GSK, Merck, and Janssen. Camlin Tierney is a member of a Data Monitoring Committee for Tibotec. Nasreen Jahed has no conflict. Kathleen Melbourne is an employee of Gilead Sciences and owns stock in Gilead Sciences. Belinda Ha is an employee of GlaxoSmithKline. Todd Brown has served as a scientific consultant for Bristol Myers Squibb, GlaxoSmithKline, Abbott, Janssen, and Gilead Sciences, has received research grants from GlaxoSmithKline and Merck. Neal Fedarko and Anthony Bloom have no conflict. Eric S. Daar serves as a consultant for Bristol Myers Squibb, Gilead, GlaxoSmithKline, Merck, ViiV and receives research grant support from Abbott Laboratories, Merck, Gilead, ViiV, and Pfizer.
Role of authors:
All authors played a role in editing the manuscript and approved the text as submitted. Grace A McComsey designed the study and wrote the manuscript. Paul Sax and Eric Daar assisted in the design of the study, reviewed and edited the manuscript. Douglas Kitch and Camlin Tierney performed the data analysis and assisted in the interpretation of statistical data. Kathleen Melbourne, Nasreen Jahed, Anthony Bloom, Belinda Ha, and Todd Brown reviewed and edited the manuscript. Neal Fedarko ran the biomarker assays, and reviewed and edited the manuscript. Data in this manuscript were collected by AIDS Clinical Trials Group. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.
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