Clinical Infectious Diseases MAJOR ARTICLE HIV/AIDS
Inflammatory Biomarkers and Mortality Risk Among HIV-Suppressed Men: A Multisite Prospective Cohort Study Nikolas I. Wada,1 Jay H. Bream,2 Otoniel Martínez-Maza,3 Bernard Macatangay,4 Shannon R. Galvin,5 Joseph B. Margolick,2 and Lisa P. Jacobson1 Departments of 1Epidemiology, and 2Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; 3University of California, Los Angeles AIDS Institute; 4Department of Medicine, University of Pittsburgh, Pennsylvania; and 5Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Background. Human immunodeficiency virus (HIV)–induced inflammation and immune activation persist after initiation of combination antiretroviral therapy (cART) and HIV suppression and may contribute to mortality risks that exceed those in HIVuninfected populations, though associations are unclear. Methods. In the prospective Multicenter AIDS Cohort Study, comprising men who have sex with men from Baltimore, Chicago, Los Angeles, and Pittsburgh, concentrations of 24 biomarkers of inflammation and immune activation were measured in stored serum from HIV-positive men obtained after cART-induced HIV suppression between 1996 and 2009. The outcome was nonaccidental death, with follow-up until 2014. We used Cox proportional hazards models to test whether biomarker concentrations predict time from HIV suppression to death and adjusted for multiple tests. Exploratory factor analysis (EFA) was employed to identify groupings of biomarkers that predict mortality risk. Results. Of 670 men followed up from HIV suppression, 54 died by the end of 2013. After adjustment for age, CD4+ cell count, hepatitis B or C virus infection, and smoking, concentrations in the highest quartile of 4 biomarkers were significantly associated with mortality risk after controlling the false discovery rate at 5%: interleukin (IL) 6 (hazard ratio, 3.54; 95% confidence interval, 2.06– 6.10), soluble IL 2Rα (3.29, 1.85–5.85), soluble CD14 (2.67, 1.55–4.61), and chemokine (CXC motif ) ligand 13 (CXCL13; 2.26; 1.29– 3.95). EFA yielded 2 biomarker groupings that were independent predictors of mortality risk. Conclusions. Despite having undetectable HIV RNA levels during cART, men with higher concentrations of several biomarkers (particularly IL 6, soluble IL 2Rα, soluble CD14, and CXCL13) had higher hazards of long-term mortality. Correlations observed among biomarker concentrations may represent underlying inflammatory processes that contribute to mortality risk. Keywords. HIV; cART; inflammation; mortality; biomarkers.
Human immunodeficiency virus (HIV)–infected individuals receiving combination antiretroviral therapy (cART) still face higher morbidity and mortality risks than HIV-uninfected individuals [1]. Notably, HIV infection increases the risk of certain serious non–AIDS-related diseases and death from some nonAIDS causes [2–6]. In addition to immune deficiency, HIV infection causes chronic immune activation and dysregulation of inflammatory processes [7]. Concentrations of serological biomarkers of inflammation and immune activation are higher in individuals with untreated HIV infection than in HIV-uninfected individuals [8]. Suppressive cART diminishes inflammation, but not all biomarkers return to the lower concentrations observed in HIVuninfected individuals [9, 10]. Residual chronic inflammation
Received 21 March 2016; accepted 10 June 2016; published online 25 June 2016. Correspondence: N. I. Wada, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, E7011, Baltimore, MD 21205 ([email protected]). Clinical Infectious Diseases® 2016;63(7):984–90 © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail [email protected]. DOI: 10.1093/cid/ciw409
984
•
CID 2016:63 (1 October)
•
HIV/AIDS
and immune activation may increase mortality risks among HIV-infected individuals receiving cART. If so, serological biomarkers may provide prognostic value and help define harmful processes that could be targets of therapy. Inflammatory biomarkers, particularly interleukin (IL) 6 and C-reactive protein (CRP), predict mortality and serious morbidity risks in HIV-uninfected populations [11, 12]. Most studies examining associations between inflammation and mortality risk among HIV-infected individuals have examined biomarker concentrations before cART initiation [13–16] or irrespective of cART use [17, 18]. Two studies restricted to individuals who became virologically suppressed on cART showed associations between death and biomarker concentrations immediately before death. Hunt et al [19] found very strong relationships between death and inflammatory markers measured within 1 year of death, and Boulware et al [20] linked CRP and IL-6 levels to incident AIDS or death in a case-control study that selected for outcomes within 1 year after cART initiation [20]. A case-control study examining 6 inflammatory biomarkers among HIV-suppressed individuals found that concentrations of IL-6, soluble tumor necrosis factor (TNF) receptor 1, soluble TNF receptor 2
(sTNFR2), D-dimer, and soluble CD14 (sCD14) before and after HIV suppression were associated with higher odds of non–AIDSrelated disease or death, and its authors called for long-term prospective cohort studies to further investigate these associations [21]. It is still poorly understood whether biomarkers of inflammation and immune activation may have longer-term prognostic value among the broader population of individuals on treatment when measured soon after HIV suppression. Most of the few studies to date have been limited by case-control study designs and/or few numbers of biomarkers measured. We tested whether 24 biomarkers measured after HIV suppression could predict long-term mortality risk in a large cohort of men with a wide spectrum of comorbidity risk and immunologic status, followed up for up to 18 years. METHODS Study Cohort
The Multicenter AIDS Cohort Study (MACS; http://aidscohortstudy.org/) is an ongoing prospective cohort study of HIV infection in men who have sex with men from 4 sites (Baltimore, Maryland/Washington, DC; Chicago, Illinois; Los Angeles, California; and Pittsburgh, Pennsylvania). Follow-up began in 1984, with later waves of recruitment. Details of the MACS have been described elsewhere [22]; briefly, participants are followed up at semiannual study visits with standardized interviews, physical examinations, and phlebotomy for concurrent laboratory testing and storage of plasma and serum (at −80°C) and viable peripheral blood mononuclear cells (at −135°C). This study was approved by the institutional review boards of participating institutions.
according to the manufacturer’s protocols (R&D Systems). A single lot of assay kits was used to eliminate lot-to-lot variability. Serum samples were diluted 1:50. The Luminex platform is a fluorescent bead-based assay; data were collected and analyzed using a BioPlex 200 apparatus and BioPlex Manager software (Bio-Rad). All samples from a given individual were tested on a single plate to minimize variability. Each plate contained samples from both HIV-infected and HIV-uninfected men. One additional marker, CRP, was measured by a reference laboratory (Quest Diagnostics) using a high-sensitivity immunonephelometric assay. Outcome and Covariate Measurement and Definitions
All-cause death was the outcome of interest. Deaths and their dates were ascertained via death certificates and matching with National Death Index records. When injury or poisoning was reported as the primary cause of death (n = 7), men were right censored at the date of death, because we assumed that residual inflammation/immune activation is unlikely to cause accidental death. Plasma concentrations of HIV RNA were measured with the Roche Amplicor assay sensitive to 50 copies/mL, and visits with undetectable concentrations were classified as HIV suppressed. CD4+ T-cell counts were measured with flow cytometry [23] and dichotomized as ≤200 or >200 cells/µL. Hepatitis infection was defined as chronic infection with either hepatitis B virus (defined by presence of hepatitis B surface antigen) or hepatitis C virus (defined by detectable hepatitis C RNA). Smoking at baseline (yes or no) was defined by self-report. Age at baseline was treated as continuous.
Biomarkers
Serum samples from MACS participants were chosen for a study of biomarkers of inflammation and immune activation at 1-year intervals for men with a known date of seroconversion, from visits immediately before and after cART initiation (and at 2-year intervals thereafter) for all cART users and from a sample of HIV-uninfected men [10]. Serum concentrations of 24 biomarkers were measured in these samples. The cytokines IL-1β, IL-2, IL-6, IL-10, IL-12p70, TNF-α, granulocyte-macrophage colony-stimulating factor, and interferon γ were measured with the Human Pro Inflammatory 9-Plex Ultra-Sensitive Kit (Meso Scale Discovery [MSD]); and chemokine (CC motif ) ligand (CCL) 2, CCL4, CCL11, CCL13, CCL17, chemokine (CXC motif ) ligand (CXCL) 10, and IL-8 were measured with the MSD Human Chemokine 7-Plex Ultra-Sensitive Kit, according to the manufacturer’s protocols. The MSD platform is a solidphase electrochemiluminescence-based assay; MSD plates were analyzed with the SECTOR Imager 2400 (MSD). The markers sCD14, soluble CD27 (sCD27), soluble GP130 (sGP130), soluble IL 2Rα (sIL-2Rα), soluble IL 6R (sIL-6R), sTNFR2, B-cell activating factor (BAFF), and CXCL13 were measured with the Luminex xMAP platform (Luminex),
Statistical Analyses
Individual Biomarkers as Predictors of Mortality Risk
Men were followed up from baseline to death or to the administrative censoring date of 1 January 2014. Baseline was the date of HIV suppression, defined as the midpoint between the last cART-exposed visit with detectable HIV RNA and the first visit with HIV RNA 13 drinks/wk)
14 (2)
HBV infection
42 (6)
HCV infection
58 (9)
HBV or HCV infection Overweight (BMI >25)a
RESULTS Characteristics of Study Population
Table 1 summarizes characteristics of the 670 men followed up from HIV suppression, who contributed 6742 person-years to the analysis. The median year of HIV suppression was 2001 (interquartile range [IQR], 1998–2004). Baseline biomarker measurements were taken at a median (IQR) of 0.7 (0.2–1.7) years after HIV suppression, and the median follow-up time was 9.9 (7.0–13.8) years. The median (IQR) age at baseline was 44.1 (39.0–49.5) years, and the median CD4+ cell count was 479/ µL (332–651/µL). By the end of 2013, 54 men had died ( primary causes of death: AIDS in 23, cardiovascular in 9, cancer in 5, gastrointestinal in 3, liver disease in 3, and other/unknown
•
CID 2016:63 (1 October)
94 (14) 283 (43)
Obese (BMI >30)a
73 (11)
Prior ART exposure
148 (23)
Hypertensionb
55 (8)
Diabetesc
111 (17)
Anemiad
180 (27)
Depressive symptomse
173 (26)
Abbreviations: ART, antiretroviral therapy; BMI, body mass index; HBV, hepatitis B virus; HCV, hepatitis C virus. BMI is calculated as the weight in kilograms divided by height in meters squared.
Hypertension was defined as systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg. b
We hypothesized that patterns of observed biomarker concentrations reflect at least one unobserved immune process that contributes to mortality risk. To identify these processes and test their relationship with mortality risk, we performed EFA. EFA is a data reduction technique assuming underlying factors that give rise to observed correlations among variables; for every factor identified by EFA (corresponding to a hypothesized inflammatory process), an individual was assigned a factor score that was assessed as an independent predictor of mortality risk. For the purposes of EFA, we log-transformed biomarker concentrations; concentrations below the lower limit of detection were imputed from lognormal models. We used principal component analysis on all 24 markers with parallel analysis to select the number of extracted factors. We performed EFA using iterative principal factor estimation and varimax rotation, keeping the factors orthogonal to one another for the sake of interpretability. We generated factor scores for each individual, then fit Cox models assessing the association of factors with mortality risk. Details of the EFA can be found in the Supplementary Materials.
986
30 (4)
Injection drug user
a
EFA Methods
Characteristics of Study Population at Baseline (n = 670)
•
HIV/AIDS
c
Diabetes was defined as hemoglobin A1C ≥6.5% or fasting glucose ≥126 mg/dL.
d
Anemia was defined as hemoglobin level below the fifth percentile.
e
Depressive symptoms were defined as Center for Epidemiologic Studies depression score ≥16.
in 9). These men died at a median (IQR) of 5.6 (3.0–9.0) years after HIV suppression, at a median age of 57.0 (52.0– 61.6) years. Supplementary Table 1 displays biomarker distributions at baseline for the study population and for HIV-uninfected MACS men. Supplementary Figure 1 displays covariate-adjusted comparisons; as seen elsewhere [10], concentrations of 13 biomarkers were significantly higher (after adjustment for multiple comparisons) among men with suppressed HIV RNA relative to HIV-uninfected men, and concentrations of 2 markers (granulocyte-macrophage colony-stimulating factor and CCL11) were significantly lower in HIV-suppressed men. Results From Adjusted Proportional Hazards Models
Figure 1 displays mortality hazard ratios (HRs) for each biomarker from multivariable proportional hazards models adjusted for hepatitis B or C infection, age, low CD4+ cell count (≤200/µL), and smoking. Higher concentrations of IL-6 were most strongly associated with mortality risk (HR, 3.54; 95% confidence interval [CI], 2.06–6.10). Three other markers were also statistically significant after adjustment for multiple comparisons: sIL-2Rα (HR, 3.29; 95% CI, 1.85–5.85), sCD14 (2.67; 1.55–4.61), and CXCL13 (2.26; 1.29–3.95). Six additional biomarkers (GP130, sTNFR2, CD27, IL-6R, CRP, and TNF-α) exhibited mortality HRs whose 95% CIs did not include the null, but these were not significant after adjustment for multiple comparisons. Detailed model estimates are provided in Table 2.
Table 2.
Results From Adjusted Cox Proportional Hazards Modelsa Highest Quartile of Biomarker Concentrations Relative to Lower 3 Quartiles
Figure 1. Mortality hazard ratios (HRs) for men with the highest quartile of biomarker concentrations relative to the lower 3 quartiles, displayed on a natural log scale. Models are adjusted for age, CD4+ cell count, hepatitis B or C infection, and smoking status. Error bars represent 95% confidence intervals. Red squares denote HRs that are statistically significant after adjustment for multiple tests, with the Benjamini-Hochberg procedure used to control the false discovery rate at 5% [24]; orange squares, HRs significant at P < .05. Abbreviations: BAFF, B-cell activating factor; CCL, chemokine (CC motif ) ligand; CRP, C-reactive protein; CXCL, chemokine (CXC motif ) ligand; GM-CSF, granulocyte-macrophage colony-stimulating factor; IFN, interferon; IL-1β, interleukin 1β; IL-2, interleukin 2; IL-6, interleukin 6; IL-8, interleukin 8; IL-10, interleukin 10; IL-12p70, interleukin 12p70; sCD14, soluble CD14; sCD27, soluble CD27; sGP130, soluble GP130; sIL-2Rα, soluble interleukin 2Rα; sIL6R, soluble interleukin 6R; sTNFR2, soluble tumor necrosis factor receptor 2; TNF, tumor necrosis factor.
High concentrations of IL-6 (HR, 2.50; 95% CI, 1.41–4.45), sIL2Rα (2.21; 1.20–4.10), and sCD14 (1.85; 1.03–3.32) retained strong relationships with mortality risk in an adjusted model that included the 4 biomarkers listed above that were significantly associated with mortality risk after adjustment for multiple tests. Model estimates are provided in Supplementary Table 2. Because multiple collinearity could obscure associations with mortality risk in this multivariable model, we report results from EFA below.
Biomarker
HR
95% LL
95% UL
P Value
BAFF
1.45
0.81
2.58
.21
CCL11
1.10
0.60
2.02
.76
CCL13
1.04
0.53
2.07
.90
CCL17
0.85
0.45
1.60
.61
CCL2
1.43
0.81
2.51
.21
CCL4
0.66
0.33
1.34
.25
CRP
1.82b
1.03
3.20
.04
CXCL10
1.71
0.95
3.09
.07
CXCL13
2.26b,c
1.29
3.95
.005
GM-CSF
0.91
0.49
1.69
.76
IFN-γ
1.21
0.66
2.21
.54
IL-10
1.03
0.57
1.87
.92
IL-12p70
0.60
0.30
1.17
.13
IL-1β
1.06
0.56
2.01
.86
IL-2
0.75
0.39
1.41
.37
IL-6
3.54b,c
2.06
6.10
Inflammatory Biomarkers and Mortality Risk Among HIV-Suppressed Men: A Multisite Prospective Cohort Study Nikolas I. Wada,1 Jay H. Bream,2 Otoniel Martínez-Maza,3 Bernard Macatangay,4 Shannon R. Galvin,5 Joseph B. Margolick,2 and Lisa P. Jacobson1 Departments of 1Epidemiology, and 2Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; 3University of California, Los Angeles AIDS Institute; 4Department of Medicine, University of Pittsburgh, Pennsylvania; and 5Feinberg School of Medicine, Northwestern University, Chicago, Illinois
Background. Human immunodeficiency virus (HIV)–induced inflammation and immune activation persist after initiation of combination antiretroviral therapy (cART) and HIV suppression and may contribute to mortality risks that exceed those in HIVuninfected populations, though associations are unclear. Methods. In the prospective Multicenter AIDS Cohort Study, comprising men who have sex with men from Baltimore, Chicago, Los Angeles, and Pittsburgh, concentrations of 24 biomarkers of inflammation and immune activation were measured in stored serum from HIV-positive men obtained after cART-induced HIV suppression between 1996 and 2009. The outcome was nonaccidental death, with follow-up until 2014. We used Cox proportional hazards models to test whether biomarker concentrations predict time from HIV suppression to death and adjusted for multiple tests. Exploratory factor analysis (EFA) was employed to identify groupings of biomarkers that predict mortality risk. Results. Of 670 men followed up from HIV suppression, 54 died by the end of 2013. After adjustment for age, CD4+ cell count, hepatitis B or C virus infection, and smoking, concentrations in the highest quartile of 4 biomarkers were significantly associated with mortality risk after controlling the false discovery rate at 5%: interleukin (IL) 6 (hazard ratio, 3.54; 95% confidence interval, 2.06– 6.10), soluble IL 2Rα (3.29, 1.85–5.85), soluble CD14 (2.67, 1.55–4.61), and chemokine (CXC motif ) ligand 13 (CXCL13; 2.26; 1.29– 3.95). EFA yielded 2 biomarker groupings that were independent predictors of mortality risk. Conclusions. Despite having undetectable HIV RNA levels during cART, men with higher concentrations of several biomarkers (particularly IL 6, soluble IL 2Rα, soluble CD14, and CXCL13) had higher hazards of long-term mortality. Correlations observed among biomarker concentrations may represent underlying inflammatory processes that contribute to mortality risk. Keywords. HIV; cART; inflammation; mortality; biomarkers.
Human immunodeficiency virus (HIV)–infected individuals receiving combination antiretroviral therapy (cART) still face higher morbidity and mortality risks than HIV-uninfected individuals [1]. Notably, HIV infection increases the risk of certain serious non–AIDS-related diseases and death from some nonAIDS causes [2–6]. In addition to immune deficiency, HIV infection causes chronic immune activation and dysregulation of inflammatory processes [7]. Concentrations of serological biomarkers of inflammation and immune activation are higher in individuals with untreated HIV infection than in HIV-uninfected individuals [8]. Suppressive cART diminishes inflammation, but not all biomarkers return to the lower concentrations observed in HIVuninfected individuals [9, 10]. Residual chronic inflammation
Received 21 March 2016; accepted 10 June 2016; published online 25 June 2016. Correspondence: N. I. Wada, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, E7011, Baltimore, MD 21205 ([email protected]). Clinical Infectious Diseases® 2016;63(7):984–90 © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail [email protected]. DOI: 10.1093/cid/ciw409
984
•
CID 2016:63 (1 October)
•
HIV/AIDS
and immune activation may increase mortality risks among HIV-infected individuals receiving cART. If so, serological biomarkers may provide prognostic value and help define harmful processes that could be targets of therapy. Inflammatory biomarkers, particularly interleukin (IL) 6 and C-reactive protein (CRP), predict mortality and serious morbidity risks in HIV-uninfected populations [11, 12]. Most studies examining associations between inflammation and mortality risk among HIV-infected individuals have examined biomarker concentrations before cART initiation [13–16] or irrespective of cART use [17, 18]. Two studies restricted to individuals who became virologically suppressed on cART showed associations between death and biomarker concentrations immediately before death. Hunt et al [19] found very strong relationships between death and inflammatory markers measured within 1 year of death, and Boulware et al [20] linked CRP and IL-6 levels to incident AIDS or death in a case-control study that selected for outcomes within 1 year after cART initiation [20]. A case-control study examining 6 inflammatory biomarkers among HIV-suppressed individuals found that concentrations of IL-6, soluble tumor necrosis factor (TNF) receptor 1, soluble TNF receptor 2
(sTNFR2), D-dimer, and soluble CD14 (sCD14) before and after HIV suppression were associated with higher odds of non–AIDSrelated disease or death, and its authors called for long-term prospective cohort studies to further investigate these associations [21]. It is still poorly understood whether biomarkers of inflammation and immune activation may have longer-term prognostic value among the broader population of individuals on treatment when measured soon after HIV suppression. Most of the few studies to date have been limited by case-control study designs and/or few numbers of biomarkers measured. We tested whether 24 biomarkers measured after HIV suppression could predict long-term mortality risk in a large cohort of men with a wide spectrum of comorbidity risk and immunologic status, followed up for up to 18 years. METHODS Study Cohort
The Multicenter AIDS Cohort Study (MACS; http://aidscohortstudy.org/) is an ongoing prospective cohort study of HIV infection in men who have sex with men from 4 sites (Baltimore, Maryland/Washington, DC; Chicago, Illinois; Los Angeles, California; and Pittsburgh, Pennsylvania). Follow-up began in 1984, with later waves of recruitment. Details of the MACS have been described elsewhere [22]; briefly, participants are followed up at semiannual study visits with standardized interviews, physical examinations, and phlebotomy for concurrent laboratory testing and storage of plasma and serum (at −80°C) and viable peripheral blood mononuclear cells (at −135°C). This study was approved by the institutional review boards of participating institutions.
according to the manufacturer’s protocols (R&D Systems). A single lot of assay kits was used to eliminate lot-to-lot variability. Serum samples were diluted 1:50. The Luminex platform is a fluorescent bead-based assay; data were collected and analyzed using a BioPlex 200 apparatus and BioPlex Manager software (Bio-Rad). All samples from a given individual were tested on a single plate to minimize variability. Each plate contained samples from both HIV-infected and HIV-uninfected men. One additional marker, CRP, was measured by a reference laboratory (Quest Diagnostics) using a high-sensitivity immunonephelometric assay. Outcome and Covariate Measurement and Definitions
All-cause death was the outcome of interest. Deaths and their dates were ascertained via death certificates and matching with National Death Index records. When injury or poisoning was reported as the primary cause of death (n = 7), men were right censored at the date of death, because we assumed that residual inflammation/immune activation is unlikely to cause accidental death. Plasma concentrations of HIV RNA were measured with the Roche Amplicor assay sensitive to 50 copies/mL, and visits with undetectable concentrations were classified as HIV suppressed. CD4+ T-cell counts were measured with flow cytometry [23] and dichotomized as ≤200 or >200 cells/µL. Hepatitis infection was defined as chronic infection with either hepatitis B virus (defined by presence of hepatitis B surface antigen) or hepatitis C virus (defined by detectable hepatitis C RNA). Smoking at baseline (yes or no) was defined by self-report. Age at baseline was treated as continuous.
Biomarkers
Serum samples from MACS participants were chosen for a study of biomarkers of inflammation and immune activation at 1-year intervals for men with a known date of seroconversion, from visits immediately before and after cART initiation (and at 2-year intervals thereafter) for all cART users and from a sample of HIV-uninfected men [10]. Serum concentrations of 24 biomarkers were measured in these samples. The cytokines IL-1β, IL-2, IL-6, IL-10, IL-12p70, TNF-α, granulocyte-macrophage colony-stimulating factor, and interferon γ were measured with the Human Pro Inflammatory 9-Plex Ultra-Sensitive Kit (Meso Scale Discovery [MSD]); and chemokine (CC motif ) ligand (CCL) 2, CCL4, CCL11, CCL13, CCL17, chemokine (CXC motif ) ligand (CXCL) 10, and IL-8 were measured with the MSD Human Chemokine 7-Plex Ultra-Sensitive Kit, according to the manufacturer’s protocols. The MSD platform is a solidphase electrochemiluminescence-based assay; MSD plates were analyzed with the SECTOR Imager 2400 (MSD). The markers sCD14, soluble CD27 (sCD27), soluble GP130 (sGP130), soluble IL 2Rα (sIL-2Rα), soluble IL 6R (sIL-6R), sTNFR2, B-cell activating factor (BAFF), and CXCL13 were measured with the Luminex xMAP platform (Luminex),
Statistical Analyses
Individual Biomarkers as Predictors of Mortality Risk
Men were followed up from baseline to death or to the administrative censoring date of 1 January 2014. Baseline was the date of HIV suppression, defined as the midpoint between the last cART-exposed visit with detectable HIV RNA and the first visit with HIV RNA 13 drinks/wk)
14 (2)
HBV infection
42 (6)
HCV infection
58 (9)
HBV or HCV infection Overweight (BMI >25)a
RESULTS Characteristics of Study Population
Table 1 summarizes characteristics of the 670 men followed up from HIV suppression, who contributed 6742 person-years to the analysis. The median year of HIV suppression was 2001 (interquartile range [IQR], 1998–2004). Baseline biomarker measurements were taken at a median (IQR) of 0.7 (0.2–1.7) years after HIV suppression, and the median follow-up time was 9.9 (7.0–13.8) years. The median (IQR) age at baseline was 44.1 (39.0–49.5) years, and the median CD4+ cell count was 479/ µL (332–651/µL). By the end of 2013, 54 men had died ( primary causes of death: AIDS in 23, cardiovascular in 9, cancer in 5, gastrointestinal in 3, liver disease in 3, and other/unknown
•
CID 2016:63 (1 October)
94 (14) 283 (43)
Obese (BMI >30)a
73 (11)
Prior ART exposure
148 (23)
Hypertensionb
55 (8)
Diabetesc
111 (17)
Anemiad
180 (27)
Depressive symptomse
173 (26)
Abbreviations: ART, antiretroviral therapy; BMI, body mass index; HBV, hepatitis B virus; HCV, hepatitis C virus. BMI is calculated as the weight in kilograms divided by height in meters squared.
Hypertension was defined as systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg. b
We hypothesized that patterns of observed biomarker concentrations reflect at least one unobserved immune process that contributes to mortality risk. To identify these processes and test their relationship with mortality risk, we performed EFA. EFA is a data reduction technique assuming underlying factors that give rise to observed correlations among variables; for every factor identified by EFA (corresponding to a hypothesized inflammatory process), an individual was assigned a factor score that was assessed as an independent predictor of mortality risk. For the purposes of EFA, we log-transformed biomarker concentrations; concentrations below the lower limit of detection were imputed from lognormal models. We used principal component analysis on all 24 markers with parallel analysis to select the number of extracted factors. We performed EFA using iterative principal factor estimation and varimax rotation, keeping the factors orthogonal to one another for the sake of interpretability. We generated factor scores for each individual, then fit Cox models assessing the association of factors with mortality risk. Details of the EFA can be found in the Supplementary Materials.
986
30 (4)
Injection drug user
a
EFA Methods
Characteristics of Study Population at Baseline (n = 670)
•
HIV/AIDS
c
Diabetes was defined as hemoglobin A1C ≥6.5% or fasting glucose ≥126 mg/dL.
d
Anemia was defined as hemoglobin level below the fifth percentile.
e
Depressive symptoms were defined as Center for Epidemiologic Studies depression score ≥16.
in 9). These men died at a median (IQR) of 5.6 (3.0–9.0) years after HIV suppression, at a median age of 57.0 (52.0– 61.6) years. Supplementary Table 1 displays biomarker distributions at baseline for the study population and for HIV-uninfected MACS men. Supplementary Figure 1 displays covariate-adjusted comparisons; as seen elsewhere [10], concentrations of 13 biomarkers were significantly higher (after adjustment for multiple comparisons) among men with suppressed HIV RNA relative to HIV-uninfected men, and concentrations of 2 markers (granulocyte-macrophage colony-stimulating factor and CCL11) were significantly lower in HIV-suppressed men. Results From Adjusted Proportional Hazards Models
Figure 1 displays mortality hazard ratios (HRs) for each biomarker from multivariable proportional hazards models adjusted for hepatitis B or C infection, age, low CD4+ cell count (≤200/µL), and smoking. Higher concentrations of IL-6 were most strongly associated with mortality risk (HR, 3.54; 95% confidence interval [CI], 2.06–6.10). Three other markers were also statistically significant after adjustment for multiple comparisons: sIL-2Rα (HR, 3.29; 95% CI, 1.85–5.85), sCD14 (2.67; 1.55–4.61), and CXCL13 (2.26; 1.29–3.95). Six additional biomarkers (GP130, sTNFR2, CD27, IL-6R, CRP, and TNF-α) exhibited mortality HRs whose 95% CIs did not include the null, but these were not significant after adjustment for multiple comparisons. Detailed model estimates are provided in Table 2.
Table 2.
Results From Adjusted Cox Proportional Hazards Modelsa Highest Quartile of Biomarker Concentrations Relative to Lower 3 Quartiles
Figure 1. Mortality hazard ratios (HRs) for men with the highest quartile of biomarker concentrations relative to the lower 3 quartiles, displayed on a natural log scale. Models are adjusted for age, CD4+ cell count, hepatitis B or C infection, and smoking status. Error bars represent 95% confidence intervals. Red squares denote HRs that are statistically significant after adjustment for multiple tests, with the Benjamini-Hochberg procedure used to control the false discovery rate at 5% [24]; orange squares, HRs significant at P < .05. Abbreviations: BAFF, B-cell activating factor; CCL, chemokine (CC motif ) ligand; CRP, C-reactive protein; CXCL, chemokine (CXC motif ) ligand; GM-CSF, granulocyte-macrophage colony-stimulating factor; IFN, interferon; IL-1β, interleukin 1β; IL-2, interleukin 2; IL-6, interleukin 6; IL-8, interleukin 8; IL-10, interleukin 10; IL-12p70, interleukin 12p70; sCD14, soluble CD14; sCD27, soluble CD27; sGP130, soluble GP130; sIL-2Rα, soluble interleukin 2Rα; sIL6R, soluble interleukin 6R; sTNFR2, soluble tumor necrosis factor receptor 2; TNF, tumor necrosis factor.
High concentrations of IL-6 (HR, 2.50; 95% CI, 1.41–4.45), sIL2Rα (2.21; 1.20–4.10), and sCD14 (1.85; 1.03–3.32) retained strong relationships with mortality risk in an adjusted model that included the 4 biomarkers listed above that were significantly associated with mortality risk after adjustment for multiple tests. Model estimates are provided in Supplementary Table 2. Because multiple collinearity could obscure associations with mortality risk in this multivariable model, we report results from EFA below.
Biomarker
HR
95% LL
95% UL
P Value
BAFF
1.45
0.81
2.58
.21
CCL11
1.10
0.60
2.02
.76
CCL13
1.04
0.53
2.07
.90
CCL17
0.85
0.45
1.60
.61
CCL2
1.43
0.81
2.51
.21
CCL4
0.66
0.33
1.34
.25
CRP
1.82b
1.03
3.20
.04
CXCL10
1.71
0.95
3.09
.07
CXCL13
2.26b,c
1.29
3.95
.005
GM-CSF
0.91
0.49
1.69
.76
IFN-γ
1.21
0.66
2.21
.54
IL-10
1.03
0.57
1.87
.92
IL-12p70
0.60
0.30
1.17
.13
IL-1β
1.06
0.56
2.01
.86
IL-2
0.75
0.39
1.41
.37
IL-6
3.54b,c
2.06
6.10
