The use of HAART in HIV-infected patients has decreased the high levels of mortality and morbidity, but it has also facilitated the emergence of other previously hidden morbidities such as dyslipidemia, insulin resistance and alterations in body fat distribution, which are associated with increased cardiovascular risk . Epidemiological data have shown an increase in cardiovascular disease in HIV-infected patients being treated with HAART . Recent studies suggest that the rate of coronary heart disease and myocardial infarction has increased in HIV-infected patients [3,4], although it is still unknown if cardiovascular alterations are a consequence of HIV infection itself or are due to long-term use of HAART. Thus, HAART may partly contribute to endothelial dysfunction and the subsequent formation of atheromatous plaque, but the process of chronic inflammation in these patients facilitating the formation of unstable atheromatous plaque more likely causes cardiovascular events.
Coinfection with hepatitis C virus (HCV) is common among HIV-infected patients . The association between HCV infection and cardiovascular disease is up for debate but HCV infection is undeniably associated with such metabolic abnormalities as insulin resistance and dyslipidemia [6,7]. These factors could lead to cardiovascular complications. A recent epidemiologic study showed that HCV-infected patients had higher rates of cardiovascular mortality compared with uninfected control patients . Furthermore, HCV infection is known to cause chronic immune stimulation, leading to an inflammatory response and cytokine production .
A higher risk of cardiovascular disease has been associated with elevated levels of circulating soluble cellular adhesion molecules (CAMs) released by the vascular endothelium, like soluble intercellular adhesion molecule-1 (sICAM-1) and vascular adhesion molecule-1 (sVCAM-1) . Additionally, an increment in circulation levels of endothelial cell-derived markers has been reported in HIV-infected patients, particularly in individuals with high-viral loads and advanced disease . Furthermore, these increased levels of CAMs have been associated with certain metabolic parameters and inflammation markers [12,13].
The aim of the present study was to quantify serum levels of sICAM-1 and sVCAM-1 in HIV/HCV coinfected patients to examine their association with several clinical and epidemiological characteristics and the therapeutic responsiveness to HCV antiviral treatment.
Patients and methods
We carried out a cross-sectional study on 183 HIV/HCV-coinfected patients of the Hospital Gregorio Marañón in Madrid (Spain) who underwent a liver biopsy between May 2000 and May 2007. In addition, we carried out a longitudinal study on the 30 out of 183 patients who started HCV antiviral treatment. Twenty-four HIV seronegative individuals participated as healthy controls.
The inclusion criteria were as such liver biopsy, no prior HCV antiviral treatment, availability of a serum sample collected and frozen on the day of the liver biopsy, no clinical evidence of hepatic decompensation, detectable HCV RNA by polymerase chain reaction, negative for hepatitis B surface antigen, CD4+ lymphocyte count higher than 200 cells/μl, and stable HAART. The exclusion criteria were active opportunistic infections, active drug or alcohol addiction, and other concomitant diseases or conditions such as diabetes, nephropathies, autoimmune diseases, hemochromatosis, primary biliary cirrhosis, Wilson's disease, α1-antitrypsin deficiency, and neoplasia.
All work was conducted in accordance with the Declaration of Helsinki. All patients gave their written consent for the liver biopsy and the Institutional Ethics Committee approved the study.
Clinical and laboratory data
On the day of the biopsy, the following information was obtained from medical records age, sex, risk category, weight, height, CDC clinical category, nadir CD4 T-cell count, prior antiretroviral therapy, antiretroviral treatment at the time of liver biopsy, and total time on HAART. The duration of HCV infection for patients with a history of intravenous drug use was estimated to begin the first year needles were shared. Patients were questioned in relation to alcohol consumption. We considered the consumption of greater than 50 g of alcohol per day for at least 12 months as a high intake.
Liver biopsies were performed as previously described . Grading and staging of liver biopsies were carried out by METAVIR score . In addition, a blood sample was taken from each patient to analyze complete blood counts, CD4+ T cells, plasma HIV viral load (HIV-RNA) and plasma HCV viral load (HCV-RNA), liver panel, basic metabolic panel, and coagulation tests. A serum sample was immediately frozen and stored (at −70°C) for further assays.
Treatment schedules and outcomes
Patients were treated for 48 weeks with the combination of interferon-alpha plus ribavirin (IFN-α + RBV). Three types of interferons were used as standard nonpegylated IFN-α-2b (Intron-A; Schering-Plough, Alcobendas, Madrid, Spain) at a dose of three million units three times per week, peg-IFN-α-2a (Pegasys; Roche Farma S.A., Madrid, Spain) at a dose of 180 μg per week, or peg-IFN-α-2b (Peg-Intron; Schering-Plough) at a dose of 1.5 μg/kg per week. All patients received ribavirin (Rebetol; Schering-Plough) at a dose of 800–1200 mg per day according to body weight. No patients had been previously treated with IFN and/or RBV prior to the treatment regimen described here.
Anti-HCV therapy was stopped in all patients with detectable HCV RNA at week 24 of treatment. A sustained virologic response (SVR) was defined as an undetectable serum HCV-RNA level (<50 IU per milliliter) up to 24 weeks after the end of treatment. A nonresponder to treatment was defined as a patient with detectable plasma HCV RNA at the end of treatment or at 24 weeks after the end of treatment.
Serum markers analyzed
Insulin, sICAM-1, and sVCAM-1 were measured using Multiplex kits (LINCOplexTM; LINCO Research, St. Charles, Missouri, USA). The Multiplex suspension bead array immunoassay was performed using a Luminex 100 analyzer (Luminex Corporation, Austin, Texas, USA) to identify serum protein levels from frozen serum samples according to the manufacturer's specifications. These markers were detected in 100% of the samples tested.
In each patient, the degree of insulin resistance was estimated by the homeostatic model assessment method (HOMA) described by Matthews . In particular, an insulin resistance score (HOMA-IR) was obtained from samples acquired from fasting patients via the formula plasma glucose (mmol/l) times serum insulin (milliunits per liter, mU/l) divided by 22.5.
The Kolmogorov–Smirnov test was performed to assess the distribution normality of each variable. Logarithmic transformations were performed for all variables that were not normally distributed. All tests were two-tailed with P values 0.05 considered significant. Statistical analysis was performed by SPSS 15.0 software (SPSS Inc., Chicago, Illinois, USA).
Categorical data and proportions were analyzed using the chi-squared test or Fisher's exact test as required. The analysis of variance test was used to compare differences of means between two or more groups adjusted by the Bonferroni test, which is a preplanned statistical procedure that adjusts the alpha level to allow multiple t-tests to be used following the analysis of variance. We determined the Pearson correlation coefficient for several variables. Values ranged from −1 (a perfect negative relationship) to +1 (a perfect positive relationship). A value of 0 indicated no linear relationship.
For analysis of factors of importance for the level of circulation markers, univariate and multivariate linear regression analyses were performed. This test analyzed the association of several epidemiological and clinical factors (sex, age, years since HIV infection, log10 CD4+/μl, log10 HIV-RNA (copies/ml), log10 time on HAART, abacavir, log10 HOMA, HCV-RNA ≥500 000 IU/ml, HCV-genotype 1 (genotype 1 versus non 1), advanced fibrosis (F≥3 or F3 to F4), and moderate to severe activity grade (A≥2) with serum sICAM-1 and sVCAM-1 levels. We used the Enter (Forced Entry) linear regression algorithm for variable entry in multivariate linear regression analysis.
The factors with significant correlation in univariate analysis were also included in a multiple linear regression model with a stepwise algorithm (at each step, all eligible variables are considered for removal and entry a P-value for entry and exit of 0.05 and 0.10 respectively) of the least significant factors. The final models included the factors considered to be independently important for serum sICAM-1 and sVCAM-1 levels.
Analysis of increases in the levels of sICAM-1 and sVCAM-1 of 30 HIV/HCV coinfected patients on HCV antiviral therapy was performed by the Wilcoxon test for paired samples. The serum samples used in this analysis were at day 0 (baseline) and at week 72 after starting HCV antiviral therapy regardless of whether treatment was withdrawn for lack of efficacy. Moreover, we did not have included relapsers. We also analyzed the differences of increases in sICAM-1 and sVCAM-1 between nonresponder patients and SVR patients (change pattern in serum) by the U-Mann–Whitney test.
Our study cohort included 183 HIV/HCV coinfected patients whose characteristics at the time of liver biopsy are shown in Table 1.
HIV/HCV coinfected patients according to HIV/HCV clinical and epidemiological characteristics
HIV/HCV coinfected patients had higher values of sICAM-1 and sVCAM-1 than the healthy control group (Fig. 1a). We did not find significant differences between patients when we analyzed sICAM-1 and sVCAM-1 levels according to insulin resistance (HOMA < or ≥3.8), CD4+/μl, plasma HIV-RNA or HCV-RNA (Fig. 1b, 1c, 1d and 1e). However, we found that patients with HCV-genotype 1 had higher values of sICAM-1 and sVCAM-1 than patients with non HCV-genotype 1 (Fig. 1F). Furthermore, we found significant differences in sICAM-1 and sVCAM-1 levels between patients according to degree of fibrosis and activity grade metavir score (Fig. 1g and h). Patients with advanced fibrosis (F≥3) or moderate to severe activity grade (A≥2) had the highest values of sICAM-1 and sVCAM-1.
We also carried out univariate and multivariate linear regression analyses (Table 2). When we carried out a univariate analysis for sICAM-1 or sVCAM-1, we found CD4+/μl, time on HAART, HOMA, HCV-genotype 1 and advanced fibrosis (F≥3) had significant positive relationships with both sICAM-1 and sVCAM-1 (Table 2).
When we carried out a multivariate analysis for sICAM-1, we only found a significant positive relationship between HCV-genotype 1 and advanced fibrosis (F≥3) with sICAM-1 (R = 0.549; P < 0.001) (Table 2). Moreover, HCV-genotype 1 and advanced fibrosis (F≥3) were also significant variables in the multivariate stepwise linear regression analysis (R = 0.398; P < 0.001).
When we carried out a multivariate analysis for sVCAM-1, we only found significant positive relationships between HCV-genotype 1 and advanced fibrosis (F≥3) with sVCAM-1 (R = 0.624; P < 0.001) (Table 2). Moreover, HCV-genotype 1 and advanced fibrosis (F≥3) were significant variables in the multivariate stepwise linear regression analysis (R = 0.560; P < 0.001).
We also analyzed the relationship of CAMs with the serum biomarkers of hepatic injury. We found a positive correlation of sICAM-1 with aspartate aminotransferase (AST) (r = 0.246; P < 0.01), gamma glutamyl transpeptidase (GGT) (r = 0.196; P < 0.01) and alkaline phosphatase (ALP) (r = 0.213; P < 0.01). We also found a positive correlation of sVCAM-1 with AST (r = 0.278; P < 0.01) and ALP (r = 0.207; P < 0.01). However, we did not find any relationship between CAMs and alanine aminotransferase (ALT).
HIV/HCV coinfected patients on IFN-α plus ribavirin therapy
Fifteen patients showed SVR whereas 15 patients were nonresponder. Moreover, nonresponder patients had a positive increase in sICAM-1 and sVCAM-1 serum levels and patients showing SVR had a significant decrease in sICAM-1 (P = 0.001) and sVCAM-1 (P = 0.019) (Fig. 2). In addition, the change pattern of these serum molecules was significantly different between nonresponder patients and SVR patients (P < 0.05) (Fig. 2).
Endothelial dysfunction is known to be the first step for the subsequent pathophysiological formation of atheromatous plaque; and sICAM-1 and sVCAM-1 have been validated as indicators of endothelial damage [17,18]. Our results confirm that the signs of endothelial dysfunction are present in HIV/HCV coinfected patients stably treated with HAART but maintaining an active HCV infection. This could be because these processes cause chronic inflammation. Therefore, these findings suggest that HCV infection may also be responsible for endothelial dysfunction in HIV/HCV coinfected patients on HAART.
It is known that HIV-infected patients have an increased cardiovascular risk because the infection involves chronic inflammation, and therefore, endothelial lesion and especially HAART therapy produce a shift in the lipid profile, which contributes to the increased cardiovascular risk [19,20]. HIV replication involves increased immune activation and endothelial dysfunction via imbalance in the cytokine microenvironment , activation of inflammatory pathways in endothelial cells [21–23], endothelial cell apoptosis and increased endothelial permeability . In our study, we did not find an association between HIV viral load and sICAM-1 or sVCAM-1 levels because our patients were on stable HAART and more than 80% had HIV-RNA less than 50 cp/ml. However, we found that patients who had been treated with HAART the longest had the lowest levels of sICAM-1 and sVCAM-1. We believe that this effect is a result of decreased levels of plasma HIV-RNA and circulating CAMs due to HAART as has been previously found in HIV monoinfected patients [1,24,25]. Thus, HAART could improve endothelial cell function and decrease cardiovascular risk for coninfected patients the same way as for HIV-monoinfected patients. In addition to, the fact that HAART also improves T-cell number and function might result in a significant decrease of immune activation [26,27]. HIV-1 infection induces severe CD4+ T-cell depletion, alterations in T-cell subsets, and a progressive impairment of the immune system with immune activation . In our study, we found that HIV/HCV coinfected patients with low levels of CD4+ had increased sICAM-1 and sVCAM-1 levels showing an association between a higher degree of immunodeficiency and inflammation.
Despite the fact that HIV-associated factors might have a possible influence on cardiovascular disease through serum levels of sICAM-1 and sVCAM-1, this relationship disappeared when we performed a multivariate analysis, whereas the association remained significant for chronic hepatitis C dependent factors.
In our study, there was a correlation between serum biomarkers of hepatic injury with sICAM-1 and sVCAM-1 serum levels, and patients with advanced fibrosis and moderate to severe activity grade had high levels of endothelial CAMs. The increased serum levels of sICAM-1 and sVCAM-1 may indicate a high inflammatory state, which could be local (liver) or systemic (immune system activation), and an increased risk of cardiovascular disease in HCV chronic hepatitis. During HCV infection, a process described as ‘chronic immune activation’ or ‘hyperactivation’ occurs accompanied by a higher expression of inflammatory cytokines in T cells . Increased endothelial cell expression of CAMs has been demonstrated in response to a number of inflammatory cytokines (IL-1, IL-4, TNF-α, IFN-γ), and after cytokine activation, CAMs are released from the surface of endothelial cells . Moreover, HCV infection is reported to cause chronic immune activation involving an inflammatory response and cytokine production , and HCV monoinfected patients with advanced fibrosis and liver necroinflammation have shown higher serum levels of sICAM-1 and sVCAM-1 [31,32]. Furthermore, chronic hepatitis C causes a state of liver inflammation and consequently endothelial and other types of cells in the liver may release CAM.
Another important factor in connection with serum levels of CAMs was the HCV genotype. Genotype 1 could be associated with higher activation of the immune system . Some authors have described that patients infected with HCV genotype 1 showed greater T-cell responses than those patients infected with other genotypes independent of their HIV status . In addition, we recently reported that CD81 levels in peripheral blood T cells were significantly higher in patients with HCV genotype 1 than in non-HCV genotype 1 patients . In lymphocytes, CD81 plays a role in cell activation by lowering the threshold of cell activation and promoting cell proliferation . Therefore, patients with HCV genotype 1 could have a major immune response contributing to liver and systemic inflammation, which might explain the sICAM-1 and sVCAM-1 elevation. Furthermore, HCV genotype 1 is associated with a significantly higher extent of oxidative damage , which could induce a high rate of inflammation and further explain the higher serum levels of sICAM-1 and sVCAM-1.
HOMA indicates the level of insulin resistance, which is elevated in HIV-infected patients with chronic HCV infection . HCV or HIV infection is characterized by increased production of lipids and proinflammatory cytokines, which is one way to develop insulin resistance [38,39]. In our study, we found a positive relationship between HOMA and serum levels of sICAM-1 and sVCAM-1. Furthermore, we found that patients with advanced fibrosis (F≥3) had higher values of HOMA than patients without advanced fibrosis (data not shown). Thus, HOMA and advanced fibrosis may have a synergistic effect at increasing the inflammatory state; and patients with high HOMA and F at least 3 would have a significantly elevated inflammation level, which results in a high degree of cardiovascular risk.
In HCV monoinfected patients, sICAM-1 and sVCAM-1 decreased after successful treatment with IFN-α . In our study, we found our HIV/HCV coinfected patients with SVR had a blockage in sICAM-1 and sVCAM-1 release. Thus, effective treatment involves elimination of HCV, reduction of serum levels of sICAM-1 and sVCAM-1, and decreased cardiovascular risk. However, treatment is effective in approximately less than 50% of those patients infected with HCV genotype 1 . So, HCV genotype 1 might be associated with pathogenesis and disease progression, involving a low response rate, a worse chronic hepatitis C prognosis, and elevated cardiovascular risk.
This study had several limitations that may impact our findings a retrospective design, it was limited to patients with well preserved immune function and the extrapolation to individuals with more marked immune suppression will require further study, there was no data of cardiovascular events or an indirect method of measuring the development of cardiovascular complications such as the measurement of large artery stiffness by carotid–femoral (aortic) pulse wave velocity. Clinical application of this is lacking and in the future, measuring carotid intima thickness or some other cardiovascular parameter would be appropriate. In addition, an important limitation to the assessment of soluble CAMs is that sICAM-1 and sVCAM-1 can be derived from other sources in addition to the endothelium (i.e., smooth muscle cells, leukocytes and tumor cells) . In the treatment arm of the study, we did not analyze other possible confounders due to the small sample size and, furthermore, three types of IFN were used.
In conclusion, HIV and HCV coinfection induces alterations in sICAM-1 and sVCAM-1 serum levels, which were higher in patients with HCV-genotype 1 and advanced stage of HCV infection. However, response to IFN-α + RBV may reduce these cardiovascular risk markers. The clinical significance of these findings for cardiovascular disease in HIV/HCV coinfected patients should be investigated in future studies.
I.F.C. and D.M. had primary responsibility for protocol development, participated in the design of the study, performed the statistical analysis, and contributed to the writing of the manuscript.
M.G.F. carried out the immunoassays and contributed to the writing of the manuscript.
E.A. had primary responsibility of fibrosis liver diagnosis.
J.B., P.M., P.C., J.C.L., J.C., R.L., and M.M.-F. carried out patient screening, collecting and recording data, and contributed to the writing of the manuscript.
S.R. conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
This work was supported by grants from Fondo de Investigación Sanitaria– Instituto de Salud Carlos III (FIS-ISCIII) (PI08/0738; UIPY 1467/07) to S.R. From FIS-ISCIII (ISCIII-RETIC RD06/006; Ref. PI080928) and Fundación para la Investigación y la Prevención del SIDA en España (FIPSE) (Ref. 36443/03; Ref. 36702/07) to J.B. From FIPSE (240800/09), FIS-ISCIII (PI09/02029); Red RIS RD06-0006-0035; Fundación Caja Navarra, Comunidad de Madrid (S-SAL-0159-2006), and and Task Force in Europe for Drug Development for the Young (TEDDY) to M.M.-F. M.G.-F. is supported by a grant of Instituto de Salud Carlos III (CM09/00031).
There are no conflicts of interest.
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