Kiefer, Elizabeth M. MD, MPH*; Shi, Qiuhu PhD†; Hoover, Donald R. PhD, MPH‡; Kaplan, Robert PhD§; Tracy, Russell PhD‖; Augenbraun, Michael MD¶; Liu, Chenglong MD, PhD#; Nowicki, Marek PhD**; Tien, Phyllis C. MD, MSc††; Cohen, Mardge MD‡‡; Golub, Elizabeth T. PhD, MPH§§; Anastos, Kathryn MD‖‖
Coinfection with HIV and hepatitis C virus (HCV) is common in the United States.1,2 HIV infection itself and HIV treatment with highly active antiretroviral therapy (HAART) have been associated with a hypercoagulable state3,4 and increased risk for thrombotic events such as deep vein thrombosis or pulmonary embolism.5–10 However, thrombosis in HCV has been evaluated mainly in end-stage liver disease and cirrhosis.11–16
Proposed markers of hemostasis in HIV include higher levels of D-dimer, Factor VIII%, and plasminogen activator inhibitor-1 (PAI-1) antigen and lower levels of total Protein S% (TPS), both in patients on antiretroviral therapy and in the pre-HAART era.17–23 HCV coinfection occurs commonly in HIV-infected patients and may accelerate immunologic progression of HIV infection.24 However, little is known about the independent association between HCV and markers of hemostasis.
Our main objective in this study was to investigate the independent association of HCV with each of the 4 measures of hemostasis: D-dimer, Factor VIII%, TPS, and PAI-1, in a sample of HIV- and HCV-infected and uninfected women in the United States. In order to isolate the independent effect of HCV on levels of these 4 measures of hemostasis, we strategized to adjust for known confounders of this relationship, including HIV and other covariates, which are associated with HCV itself and are possible predictors of the outcome measures of hemostasis.
The Women's Interagency HIV Study (WIHS) is a multicenter, prospective study of the natural history of HIV infection and associated diseases in women. Women with HIV and women at risk for HIV were recruited at 6 national sites (Los Angeles, CA; San Francisco, CA; Chicago, IL; Bronx, NY; Brooklyn, NY; and Washington, DC) from October 1994 through November 1995 and from October 2001 through September 2002. Detailed methods and characteristics of the study population have been previously published.25 At the enrollment visit (visit 1) and then prospectively every 6 months, interviews were conducted, a physical exam was performed, and blood specimens were collected. The protocol was approved by the Institutional Review Boards at each study site, and all participants provided written informed consent.
This study presents cross-sectional analyses of data and specimens collected from participants during their first year of enrollment in WIHS. We randomly selected 450 HCV-positive women (HCV seropositive with detectable plasma RNA) from 1023 potentially eligible, nonpregnant, HCV-infected women and 450 HCV negative (HCV seronegative) from 2709 potentially eligible, nonpregnant, HCV-uninfected women. All HIV-seroprevalent and HIV-seronegative women in the WIHS were eligible to be part of the population. Samples were selected from the WIHS central repository. We limited the population to women with known HCV status (as described above) and with available plasma in our national specimen repository. These women were randomly assigned a sorting (selection) value using the RANUNI function in SAS, and the 450 lowest randomly assigned values within each population of interest were selected for testing. The repository contains all WIHS sites, and selection was thus random across all the WIHS sites.
Outcome Variables: Measures of Hemostasis
Factor VIII%, D-dimer, TPS, and PAI-1 were the main outcomes (dependent variables) of interest. These measures of hemostasis were measured at the Laboratory for Clinical Biochemistry Research, University of Vermont, in previously unthawed serum collected at the first visit after study enrollment and frozen at −80°C. All test assays used Stago products (Parsippany, NJ). D-dimer was measured on citrated plasma using the immunoturbidimetric method for quantitative determination. PAI-1 was measured on citrated plasma using PAI-1, the quantitative determination of PAI-1 antigen by enzyme-linked immunosorbent assay. Factor VIII% was measured on citrated plasma via a clot-based FVIII activity assay using a Diagnostica Stago STA-R Evolution coagulation analyzer. TPS was measured for quantitative determination by enzyme-linked immunosorbent assay. The laboratory was blinded to HCV and HIV status.
Primary Exposure of Interest: HCV Infection
Presence of active HCV infection (HCV seropositivity with a detectable plasma HCV RNA) was the main exposure of interest. At enrollment, all women were screened for HCV using HCV antibody enzyme immunoassay (EIA) Abbott EIA 2.0 and 3.0 assays (Abbott Laboratories, Abbott Park, IL). As previously described,26 HCV RNA was measured on frozen specimens from HCV-seropositive women using either the COBAS Amplicor Monitor 2.0 assay (Roche Diagnostics, Branchburg, NJ) or the COBAS Taqman assay (Roche Diagnostics).
We included covariates with known associations (from the literature) with HCV and with any of our 4 measures of hemostasis.
HIV has known associations with HCV and is associated with higher levels of D-dimer, Factor VIII%, and PAI-1 and with lower levels of TPS.17,19–23 HIV infection was defined as HIV-positive antibody status using commercial EIA kits and Western blot confirmation, with HIV-negative serostatus confirmed at all visits. We further characterized a positive HIV infection by CD4 count and viral load (VL). HIV antibody, CD4 counts, and VL were obtained from the first visit after enrollment, which was the same visit these specimens were collected for the main outcomes of interest. If CD4 or VL was missing at that visit, they were obtained from the enrollment visit. CD4 was categorized as CD4 >500, 350–500, 200–350, or <200 cells per microliter. VL was divided into approximate distribution tertiles: 0–4000 copies, 4001–55,000 copies, and >55,000 copies per milliliter. HIV treatment was self-reported among those with HIV and defined as none, monotherapy (single agent use), combination therapy (more than 1 antiretroviral agent not meeting definition of HAART), or HAART. The definition of HAART was guided by the Department of Health and Human Services/Kaiser Panel guidelines and was defined as use of 3 or more antiretroviral medications, one of which had to be a protease inhibitor, a nonnucleoside reverse transcriptase inhibitor, one of the nucleoside reverse transcriptase inhibitors Abacavir or Tenofovir, an integrase inhibitor (eg, Raltegravir), or an entry inhibitor (eg, Maraviroc or enfuvirtide).27
Demographic covariates included age (in years) and race/ethnicity (self-reported and defined as black including Hispanics, white including Hispanic and other), as both HCV and measures of hemostasis are noted to vary by age and race.28–34
Behavioral covariates from the visit of blood draw included smoking status, use of drugs, including cocaine and heroin, alcohol use, and female sex hormone use. Smoking has been associated with higher prevalence of HCV and is theorized to interact with HCV to accelerate hepatocellular damage35–38; smoking is also a predictor of several measures of hemostasis.39–41 Smoking status was defined as never, former, or current (in the last 6 months). Alcohol use in the last 6 months was categorized as abstinent, light, moderate, and heavy use. Drug use and alcohol use have been associated with both HCV42–44 and measures of hemostasis.45–47 Estrogen has been associated with decreased viremia in HCV and predicts measures of hemostasis.48–55 Drug use was a composite variable, which included crack, cocaine, heroin, or injection drug use, and defined as never, previous, or current (in the last 6 months). Hormone use in the last 6 months was a composite variable comprised of oral contraceptive use, estrogen replacement therapy (alone or in combination), Norplant, or Depo-Provera.
We included a noninvasive calculated measure of fibrosis, FIB-4, which has been developed and validated in HIV/HCV-coinfected individuals56 and predicts fibrosis in HCV, hepatitis B, HIV, and nonalcoholic fatty liver disease.57–61 Liver fibrosis is associated with the predictor variable HCV,1,62,63 and fibrosis/cirrhosis is also associated with several of the markers of hemostasis.12,16,64,65 We calculated FIB-4 from the Sterling's formula using aspartate aminotransferase (AST) and alanine aminotransferase (ALT)56: [age (in years) × AST]/[platelet (109/L) × ALT1/2].
Other clinical covariates from the visit of blood draw included any history of diabetes mellitus, a history of a prior AIDS-defining illness (ADI), and body mass index (BMI). Diabetes has been associated with both HCV and markers of hemostasis.66–73 There is some evidence that development of ADIs are associated with HCV infection,74,75 and worsening HIV/AIDS increases the risk of thrombosis.8,22,76 Obesity has known associations with HCV progression and treatment77–79 and the development of thrombosis.80–83 Diabetes and a history of ADI were self-reported. BMI was calculated as weight in kilograms divided by height (in square meters).
Our strategy in this article was to examine the independent effect of HCV infection on levels of each of the 4 measures of hemostasis, adjusting for known confounders of this relationship.
We examined the distribution of each of the 4 markers of hemostasis for normality. Three markers, Factor VIII%, TPS, and PAI-1, were reasonably close to normally distributed. The distribution of D-dimer was skewed to the right and was log transformed to log10 D-dimer for statistical analysis. We present the geometric mean of the D-dimer in the figures for easier interpretation.
As other studies of clotting factors and related measures have observed and referred to as a batch effect,84–88 we noted that all 4 hemostasis measures varied systematically by WIHS site/laboratory testing date of the sample units. As these previous studies concluded, this likely reflected differences in sample preparations and testing and was not of direct interest to the analysis; we thus adjusted for these WIHS site/laboratory test date batch effects when performing our analyses of markers of hemostasis in an approach analogous to age adjustment.89 For example, using the least squares mean statement in SAS (Version 9.2, SAS Institute, Cary, NC), the descriptive means and other statistics reported here are adjusted to the overall marginal distributions of WIHS site/test date among all women in the study. We examined the association between HCV and markers of hemostasis in WIHS site/test date effect–adjusted linear models, which have been noted to give the same results for linear models such as these as does a recently published conditional likelihood approach to incorporate batch effects.90 It should be noted that the qualitative direction and statistical significance of the results observed here were the same in models that did not adjust for these WIHS site/test date effects. We examined HCV-positive compared with HCV-negative women across tertiles of HIV status/VL in generalized linear models for each of the 4 markers of hemostasis and present LS means and SEs for these groups.
The distribution of FIB-4 in this population was right skewed. We therefore log transformed the data for use in our analyses.
Backward stepwise linear regression analysis was used to identify independent predictors of each of the 4 markers of hemostasis. A P value of ≤0.1 kept variables in the model, and a P value of ≤0.05 was otherwise used as the criteria for significant variables. In regression models, including all women, and in models limited to HIV-positive women only, we preliminarily assessed the comparative relationship of both CD4 and VL with each of the 4 markers of hemostasis. After adjusting for HIV VL, there was no significant association between CD4 and each of the 4 markers of hemostasis (data not shown); however, there were strong associations between the VL and the marker outcomes even after adjusting for CD4. Therefore, as CD4 and VL are inversely collinear, in multivariate analysis among all women, we used VL and not CD4 as our predictor variable for HIV stage of disease. We forced HCV into multivariate models, as it was the primary predictor; WIHS site, laboratory test date, and HIV status/VL were forced into the models as well.
The 443 HCV-positive and 425 HCV-negative women were included in this study; 121 were both HCV negative and HIV negative; 304 were HIV-positive only (one person was missing CD4 count); 73 were HCV-positive only; and 370 were coinfected with both HCV and HIV (one person was missing CD4 count). Table 1 compares HCV-positive and negative women by demographic and clinical characteristics. Compared with HCV-uninfected women, women with HCV were older, more likely to be black, and more likely to use tobacco. HCV-positive women were more likely to abstain from alcohol and to be heavy drinkers but less likely to be nonheavy drinkers compared with HCV negatives. HCV positives were more likely to use drugs, to be HIV infected, have a higher VL and lower CD4 count, have reported a prior ADI, and less likely to be on HAART compared with HCV negatives. The HCV-negative women were more likely to use hormones and have a higher BMI. As expected, HCV-negative women had lower FIB-4 scores.
Markers of Hemostasis by HCV Status
Table 2 reports markers of hemostasis by HCV status. There were 5 specimens for FVIII% and 1 specimen for PAI-1 with insufficient volume remaining in the sample to run the test and were reported as missing. HCV-positive women had higher levels of Factor VIII% (mean ± SE) (124.4% ± 3.9% vs. 101.8% ± 3.7%, P < 0.001) and lower levels of TPS (75.7% ± 1.1% vs. 84.3% ± 1.1%, P < 0.001), independent of HIV status. There was no significant association of HCV with levels of PAI-1 or log10 D-dimer (P = 0.42 and P = 0.41, respectively).
Markers of Hemostasis Levels by HCV and HIV Status
Figures 1, 2 and Supplemental Digital Content (see Figures S1 and S2, http://links.lww.com/QAI/A381) display the predicted LS mean levels of each marker of hemostasis by HCV status (dark gray bars vs. light gray bars) and HIV status/VL (HIV negative, HIV positive with low, medium, and high tertiles of VL). Factor VIII% was higher in the HCV-positive women compared with HCV-negative women of the same HIV status/VL. These differences were statistically significant in the HCV/HIV-coinfected women with a low VL compared with HIV positives with low VL alone and those with HCV/HIV coinfection and medium HIV VL compared with HIV positives with medium VL alone (Fig. 1). TPS was statistically lower in HCV-positive compared with HCV-negative women across all categories of HIV/VL (Fig. 2). Higher HIV VL was associated with higher Factor VIII and lower TPS (P value for the trend P < 0.0001 and P < 0.0001, respectively, Figs. 1, 2). There was no significant difference in PAI-1 between HCV-positive and negative women, and PAI-1 was not significantly higher with increasing HIV VL (see Figure S1, Supplemental Digital Content, http://links.lww.com/QAI/A381). Supplemental Digital Content (see Figure S2, http://links.lww.com/QAI/A381) shows the geometric mean of D-dimer. D-dimer was not associated with HCV infection but was significantly higher with higher HIV VL (P = 0.0001; see Figure S2, Supplemental Digital Content, http://links.lww.com/QAI/A381).
We examined the independent association of HCV with the markers of hemostasis in multivariate analyses as described in the statistical methods, adjusting for both HIV status and treatment and other covariates: age, race, smoking status, drug use, alcohol use, hormone use, history of diabetes, history of ADI, and BMI. In addition, we adjusted for WIHS site and date of laboratory test. Significant associations from multivariate analysis are shown in Table 3. HCV was independently significantly associated with higher levels of Factor VIII% (adjusted difference +11.70%, P = 0.008) and lower levels of TPS (adjusted difference −7.55%, P < 0.0001) after adjustment. Thus, an HCV-positive woman would have 11.70% higher Factor VIII% compared with an HCV-negative woman with all other variables in the model equal. An HCV-positive woman would have 7.55% lower TPS compared with an HCV-negative woman with all other variables equal. HCV was not significantly associated with PAI-1 or log10 D-dimer (P = 0.34 and P = 0.91, respectively). HCV remained an independent predictor of Factor VIII and TPS even after adjusting for FIB-4.
In these multivariate models, HIV status/VL was significantly and independently associated with higher Factor VIII% and log10 D-dimer and lower TPS but was not statistically associated with PAI-1. In models restricted to HIV-infected women, higher tertiles of VL were statistically associated with higher Factor VIII% and log10 D-dimer levels (data not shown). Self-reported HIV treatment category was also significantly associated with TPS, for example, compared with no treatment HAART was associated with higher TPS levels (4.92%, P = 0.05) after adjustment for all other variables in the model.
Higher log FIB-4 scores were independently associated with higher Factor VIII% and lower TPS (in the direction of worse thrombosis) (P = 0.0014 and P < 0.0001, respectively). Age, race, smoking, drug use, hormone use, and BMI were significant independent predictors for some of the markers of hemostasis in multivariable models. In particular, higher BMI was significantly associated with higher Factor VIII%, PAI-1, and also TPS (all P < 0.05). Hormone use was independently associated with a lower level of Factor VIII% (adjusted difference 6.71% lower, P = 0.04), and current smoking was independently associated with greater PAI-1 (adjusted difference 6.87 ng/mL, P = 0.02). Black compared with white race was independently associated with higher Factor VIII% and log10 D-dimer (adjusted differences 22.23% and 0.09 µg/mL higher, P < 0.0001 and P = 0.01, respectively). Older age was associated with higher Factor VIII and TPS (adjusted differences 5.25% and 4.65% higher per 10 years, P = 0.068 and P < 0.0001, respectively).
This study of 868 women in the WIHS cohort found a highly statistically significant association of hepatitis C infection, defined by HCV viremia, with both higher Factor VIII% and lower TPS, independent of HIV infection. Higher Factor VIII% and D-dimer and lower TPS were strongly associated with HIV infection and levels of HIV viremia, independent of HCV infection. Greater levels of Factor VIII% and lower TPS are consistent with hypercoagulability. Thus, both HCV and HIV infection were each independently associated with markers of hypercoagulability. Coinfection with both HCV and HIV was associated with greater Factor VIII% among women with low and medium VL and lower TPS across all tertiles of VL, compared with HIV infection alone. To our knowledge, this is the first study to examine the associations of these markers of hemostasis in a large cohort of HIV-infected and uninfected women with and without HCV infection.
These markers have not been well characterized in general HCV infection. Previous studies examined the association between advanced HCV disease state and hemostasis marker levels. Abdo et al91 found significant differences in TPS levels in a small number of patients with HCV and elevated liver enzymes and patients with liver cirrhosis. In a study of markers of hemostasis among 34 patients with HCV and extensive fibrosis and/or cirrhosis compared with 34 patients with HCV but without extensive fibrosis and/or cirrhosis, Factor VIII% was significantly elevated in the group with more advanced disease (160% vs. 120%, respectively).92 Among patients with cirrhosis, including those with HCV, Fimognari et al12 found higher levels of D-dimer associated with advanced liver disease. Hepatocellular damage from HCV may explain some of these marker levels, as HCV targets primarily hepatocytes in vivo.93,94 Hepatocytes are the primary site for synthesis of Protein S, PAI-1, and fibrinogen, the source of the fibrin degradation product, D-dimer,1,95,96 whereas Factor VIII is made primarily by sinusoidal epithelial cells.2
HIV has known associations with the markers of hemostasis measured here.17–19,21,23,97,98 Our results were similar to another analysis from the WIHS that showed decreases in Protein S and increases in Factor VIII among women with advancing HIV disease compared with controls22 and a study by Abdollahi et al97 showing greater Factor VIII and decreased Protein S in HIV-infected patients compared with controls in Tehran, Iran. Trotti et al17 showed significantly higher levels of PAI-1 in a small number of HIV-infected patients compared with healthy controls. Bissuel et al98 examined HIV-infected patients compared with healthy controls and found significantly decreased plasma-free protein S levels in HIV-infected patients. Some of these studies reported the exclusion of liver disease17; however, most investigations of the associations of HIV infection with measures of clotting diathesis did not adjust for infectious hepatitis or report liver disease.18–21,23,99
HCV and HIV occur commonly together,1,2 and we found in this study that HIV/HCV coinfection was significantly associated with higher levels of Factor VIII%, among those with low and medium VL, compared with HIV infection alone and lower levels of TPS, among those with low, medium, and high VL, compared with HIV infection alone. This prothrombotic profile may have clinical implications in the form of plaque formation or cardiovascular outcomes such as stroke or myocardial infarction. Whereas HIV infection and treatment has known associations with cardiovascular disease100–106 and endothelial dysfunction,107 the association between HCV infection and cardiovascular risk is less clear. A small number of studies have reported increased risk of coronary artery disease in HCV108,109 or increased risk of intermediate outcomes such as subclinical atherosclerosis.110–112 Ishizaka et al111,112 found an independent association between HCV seropositivity and carotid artery plaques and intimal media thickening among patients in Japan; these associations were also confirmed using an HCV core protein assay as a better marker of active virus. However, this result was not replicated in the WIHS cohort: Tien et al113 found that the prevalence of carotid plaques was higher in the HIV/HCV-coinfected women in the WIHS group compared with HCV-monoinfected women, with a higher carotid intimal media thickness in the coinfected group compared with HCV-monoinfected women, but after adjustment, HCV was not associated with greater carotid intimal media thickness, in contrast to other studies. Thus, further investigation is needed to determine if HCV might be an independent risk factor for cardiovascular disease through prothrombotic mechanisms.
We confirmed several other previously observed associations with these 4 markers of hemostasis. Greater age, a known risk factor for thrombosis,114 was associated with higher Factor VIII and lower TPS in our study. Higher BMI, also a known risk factor for thrombosis,114 was significantly associated with all the clotting factors except D-dimer. Interestingly, hormone use was associated with lower Factor VIII%. One previous study has shown no association of oral or transdermal contraception with Factor VIII% levels.54
We found that self-reported antiretroviral therapy was associated with an increase in TPS levels compared with no treatment. Monotherapy and HAART were significantly associated with this increase but combination therapy was not, perhaps reflecting type 2 error. There is some prior evidence that HAART is associated with increases in Protein S.115 However, Protease inhibitors have also been linked to an increase in thrombotic events and a decrease in Protein S.4,21 Viral replication may play a role in modulating these markers; others have found that interruptions in HAART based on CD4 counts, compared with continuous treatment, resulted in increases in D-dimer.116
This study has several limitations. We cannot make any causal inferences from the study, as it is a cross-sectional design. The generalizability of this study to the modern HIV era may be limited as nearly 40% of HIV-infected women were not treated and only 23% were taking HAART. However, new studies have suggested that markers of hemostasis such as D-dimer are elevated in those not on continuous HAART,116 and we would hypothesize that the overall effect of HAART would lead to markers of hemostasis in the direction of decreased thrombosis. In addition, the WIHS cohort may not be representative of women living with HIV or HCV in the United States, and caution must be used in applying these results from this cohort study to the general population. Finally, very few patients were receiving treatment for HCV; so, this article cannot address whether HCV treatment improves markers of hemostasis. We also acknowledge that FIB-4 is an imperfect measure of fibrosis and may not be completely capturing the influence of fibrosis on these markers of hemostasis.
In summary, in a large group of women with and without HCV defined by viremia, we found an independent association of HCV infection with 2 markers of hemostasis, Factor VIII and TPS, independent of HIV infection. We have also found a significant association of level of HIV viremia with 3 of these markers, Factor VIII%, D-dimer, and TPS. These findings suggest that prior studies demonstrating an association of markers of hemostasis with HIV infection may have been partially confounded by coinfection with HCV. Future studies of hemostatic markers in HIV/HCV-coinfected populations should control for both level of HIV viremia and HCV infection. Further investigation of HCV and markers of hemostasis in clinical outcomes is warranted.
Data were collected by the Women's Interagency HIV Collaborative Study Group with centers (Principal Investigators) at New York City/Bronx Consortium (Kathryn Anastos); Brooklyn, NY (Howard Minkoff); Washington, DC, Metropolitan Consortium (Mary Young); The Connie Wofsy Study Consortium of Northern California (Ruth Greenblatt); Los Angeles County/Southern California Consortium (Alexandra Levine); Chicago Consortium (Mardge Cohen); Data Coordinating Center (Stephen Gange).
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