Abstract
Improved understanding of cholesterol levels in HIV and HCV-infected persons in Argentina will guide optimal antiretroviral therapy. We conducted a cross-sectional study in Argentina to describe associations between HIV, Hepatitis C and cholesterol. Of 202 participants, 21 were HIV-infected, 15 HCV-infected, 46 were HIV/HCV co-infected and 120 were HIV/HCV uninfected. HIV/HCV uninfected participants had the highest total cholesterol (TC) and LDL levels. Multivariate modeling revealed that HIV/HCV co-infected patients had the lowest TC levels (−28.7 mg/dl, p<0.001) compared to the HIV/HCV uninfected reference group. HCV and HIV/HCV co-infection were associated with lower LDL levels (−21.4 mg/dL, p=0.001 and −20.3 mg/dL, p<0.0001, respectively). HIV and HIV/HCV co-infection, but not HCV alone, were associated with lower HDL levels (−9.1 mg/dL, p=0.0008 and −6.8 mg/dl, p=0.0006 respectively). Further study is needed to examine if the more favorable lipid profile observed in HIV/HCV co-infected persons is associated with a reduction in cardiovascular risk.
Introduction
As HIV-infected persons are living longer as a result of highly active antiretroviral therapy (HAART),1 research efforts have focused on the effects of HIV and its treatment on major co-morbid conditions including dyslipidemia and cardiovascular disease. Specific alterations in lipid profiles have been described in persons with HIV. Studies conducted early in the HIV epidemic, prior to the availability of HAART, noted increased triglycerides (TG) and reduced high-density lipoprotein (HDL) among persons with untreated, advanced HIV infection. 2, 3 Initiation of HAART has been associated with increases in total, LDL, and HDL cholesterol as well as further elevation in triglycerides.3 The atherogenic lipid profile associated with HAART often requires switching of antiretroviral agents or initiation of lipid lowering therapy to mitigate increased cardiovascular risk. 4
HIV and hepatitis C virus (HCV) often co-exist due to shared transmission risks. In drug using populations, rates of co-infection approach 75%. 5, 6 HCV infection is associated with lower total cholesterol, lower LDL cholesterol and insulin resistance. 7–10 Further, studies conducted in drug using populations in the US have demonstrated that, after initiation of HAART, HIV/HCV co-infected persons do not experience elevations in total and LDL cholesterol to the extent seen in HIV-monoinfected persons. 11, 12 Nonetheless, whether the reduced cholesterol associated with HCV confers a reduction in cardiovascular risk remains unclear.
HIV-related global health efforts focus on access, delivery, and management of HAART in developing nations. In 2013 it was estimated that 110,000 persons were living with HIV in Argentina.13 The prevalence of HIV infection among injection drug users (IDUs) in Argentina ranges from 27–80%.14 The epidemic is largely concentrated in urban areas, with approximately 80% of cases in Buenos Aires.15 Although there have been several reports of hypertriglyceridemia, insulin resistance, and cardiovascular disease in HIV-infected persons in the US, 16–18 less is known regarding the metabolic profile of HIV-infected persons in Argentina.
As such, we sought to examine nutritional status and serum lipids in HIV and/or HCV-infected Argentinean drug users. Improved understanding of the effect of HIV and/or HCV on cholesterol levels in this subgroup will guide the selection of optimal antiretroviral regimens and will better enable physicians in Argentina to manage HAART-related toxicities and modify cardiovascular risk. The primary objective of this study is: 1) to provide descriptive data regarding nutritional status and cholesterol levels in HIV and/or HCV infected drug users in Argentina, a population that has not been well studied and 2) to examine the association of HIV and HCV on cholesterol levels in a cohort of Argentinean drug users.
Materials and Methods
As part of a cross-sectional study to describe the associations between HIV infection, drug use, co-morbidities, and nutritional and metabolic abnormalities, 202 participants were enrolled from 2007–2008 at two sites in Buenos Aires: the FUNDAI (Fundación de Ayuda al Inmunodeficiente) HIV/AIDS clinic at the Hospital Muñiz and CENARESO (Centro Nacional de Reeducación Social), a national drug rehabilitation center. Participants were eligible if they were between 18 and 65 years of age and had injected, smoked or snorted cocaine or coca paste in the past 5 years. Female participants who were pregnant (determined by self-report) were excluded. Persons who agreed to participate signed informed consent and underwent pretest counseling and HIV testing. The protocol was approved by the Institutional Review Boards of CENARESO, FUNDAI, and Tufts Medical Center, Boston, MA, USA.
Participants completed a standardized questionnaire which collected data regarding sociodemographics, medical history and medication use, illicit drug use, and 24 hour dietary recall. The frequency and amount of alcohol intake over the past 30 days was assessed. Responses were categorized as hazardous or non hazardous using the National Institute on Alcohol Abuse and Alcoholism guidelines. 19 Body composition measurements, including height and weight, and blood samples, including fasting lipid profile (total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides) were also obtained. For HIV-infected participants, CD4 cell count and HIV viral load was also measured.
Hepatitis C Antibody was detected using IMx-HCV (Version 3.0; Abbott, Buenos Aires, Argentina). HIV-1 status was determined by ELISA (IMx EIA HIV-1/HIV-2 III Plus, Abbott, Buenos Aires, Argentina), with confirmation by western blot (HIV Blot 2.2, Genelabs Diagnostics, Singapore Science Park, Singapore). HIV-1 viral load copies were quantified by RT-PCR using the AMPLICOR HIV-1 Monitor 1.5 (Roche, Indianapolis, Indiana). Viral load <400 copies/mL were considered undetectable. C-reactive protein was quantified by PCR-latex (Wiener Laboratory, Rosario, Argentina) which qualitatively detects levels above 6 mg/l as reactive. Our statistical models therefore included C-reactive protein as a dichotomous reactive/non-reactive variable.
Statistical Analysis
T-tests and chi-square tests were used to compare means and proportions of sociodemographic, drug use, laboratory, and clinical characteristics by HCV status, stratified by HIV status. The ANOVA F-test was used to assess overall differences by both HIV and HCV status. The independent associations of HIV and HCV status on cholesterol levels were assessed using multivariate linear regression analysis. Separate models were run using each type of cholesterol (TC, HDL, and LDL) as the outcome. HIV/HCV status was entered in as three dummy variables: HIV-monoinfection, HCV-monoinfection, and HIV/HCV co-infection. The HIV/HCV negative group was used as the reference. Covariates included gender, race, age, triglyceride levels, BMI, dietary intake, and alcohol use. Among HIV-infected participants we examined the following variables as potential confounders: protease inhibitor (PI), nucleoside/nucleotide reverse transcriptase inhibitor (NRTI), and non-nucleoside reverse transcriptase inhibitor (NNRTI) use as well as CD4 cell count and HIV viral load. All analyses were performed using SAS v.9.1 (Cary, NC).
Results
Table 1 shows the demographic, drug use, nutritional and clinical characteristics of the 202 study participants stratified by HIV and HCV status. The majority of participants in all subgroups were white males. HCV-positive participants were significantly older than those without HCV infection, regardless of HIV status. Non-injection drug use was high across groups, although HIV/HCV co-infected participants had the lowest percentage of current use of non-injection drugs. HCV-infected participants had the highest percentage of injection drug use. Due to study design, recruitment site differed significantly between groups, whereby HIV-uninfected participants were more likely to be recruited from the drug rehabilitation center and HIV-infected participants were more likely to be recruited from the HIV clinic.
Table 1.
Demographic and Clinical Characteristics by HIV and Hepatitis C (HCV) status
| HIV Negative |
HIV Positive |
Overall ANOVA p-value |
|||||
|---|---|---|---|---|---|---|---|
| (Mean ± SD or n (%)) | HCV Negative (n=120) |
HCV Positive (n=15) |
P- Value |
HCV Negative (n=21) |
HCV Positive (n=46) |
P- Value |
|
| Sociodemographic | |||||||
| Age (in years) | 28.4 ± 6.5 | 34.6 ± 8.6 | 0.001 | 31.0 ± 5.4 | 36.1 ± 5.2 | 0.0004 | <0.001 |
| Female | 16 (13%) | 2 (13%) | 0.99* | 5 (24%) | 2 (4%) | 0.03* | 0.11* |
| Amerindios White (1) |
22 (18%) 198 (82%) |
5 (33%) 10 (67%) |
0.18* | 9 (43%) 12 (57%) |
14 (30%) 32 (70%) |
0.41 | 0.06 |
| Recruitment Site: Cenareso Fundai |
105 (88%) 15 (13%) |
10 (67%) 5 (33%) |
0.05* |
7 (33%) 14 (67%) |
17 (37%) 29 (63%) |
0.77 | <0.001 |
| Drug, Smoking, Alcohol | |||||||
| Cigarette smoker (1) | 109 (91%) | 11 (73%) | 0.06* | 15 (71%) | 38 (84%) | 0.32* | 0.03* |
| Hazardous alcohol consumption (1,2) | 59 (50%) | 9 (60%) | 0.45 | 14 (67%) | 28 (61%) | 0.65 | 0.34 |
| In the past 6 months: (1) Injection Drug User Non-Injection Drug User Clean |
7 (6%) 104 (87%) 9 (8%) |
2 (13%) 13 (87%) 0 (0%) |
0.30* |
1 (5%) 18 (86%) 2 (10%) |
11 (24%) 28 (62%) 6 (13%) |
0.14* | 0.01* |
| Coca Paste user in past 6 mo | 87 (73%) | 11 (73%) | 0.99 | 16 (76%) | 29 (63%) | 0.29 | 0.60 |
| Dietary Intake (24 Hour Recall) | |||||||
| Total Caloric intake (kcal) | 2829.1 ± 1120.5 | 3257.2 ± 1238.2 | 0.17 | 2597.0 ± 927.6 | 2817.0 ± 929.6 | 0.37 | 0.34 |
| Fat intake (% of total kcal) | 31.7 ± 8.3 | 27.8 ± 5.4 | 0.07 | 29.5 ± 10.7 | 29.3 ± 9.7 | 0.94 | 0.17 |
| Total fat (g) | 100 ± 51 | 105 ± 57 | 0.75 | 91 ± 45 | 95 ± 46 | 0.77 | 0.77 |
| Mono-unsaturated fat (g) | 32.0 ± 17.5 | 34.5 ± 18.7 | 0.61 | 29.0 ± 15.9 | 29.7 ± 17.7 | 0.89 | 0.69 |
| Poly-unsaturated fat (g) | 18.8 ± 12.6 | 20.9 ± 17.5 | 0.57 | 15.2 ± 104 | 15.4 ± 8.4 | 0.93 | 0.20 |
| Saturated fat (g) | 36.1 ± 20.7 | 34.8 ± 15.6 | 0.82 | 34.1 ± 21.2 | 32.6 ± 20.1 | 0.78 | 0.79 |
| Cholesterol intake (mg)* | 428 ± 241 | 376 ± 209 | 0.42 | 291 ± 158 | 337 ± 233 | 0.41 | 0.02 |
| Clinical Measures | |||||||
| BMI (kg/m2) | 24.8 ± 4.2 | 23.7 ± 3.8 | 0.36 | 22.2 ± 2.4 | 23.1 ± 3.0 | 0.23 | 0.008 |
| Systolic blood pressure (mmHg) | 115 ± 9 | 115 ± 12 | 0.77 | 108 ± 12 | 112 ± 17 | 0.34 | 0.03 |
| Diastolic blood pressure(mmHg) | 71 ± 7 | 72 ± 9 | 0.71 | 69 ± 9 | 71 ± 11 | 0.56 | 0.80 |
| Laboratory | |||||||
| Total Cholesterol (mg/dL) | 176 ± 40 | 149 ± 30 | 0.01 | 155 ± 24 | 144 ± 31 | 0.16 | <0.001 |
| HDL Cholesterol (mg/dL) | 46 ± 12 | 47 ± 18 | 0.81 | 39 ± 14 | 39 ± 13 | 0.86 | 0.005 |
| LDL Cholesterol (mg/dL) | 102 ± 34 | 77 ± 25 | 0.007 | 89 ± 21 | 78 ± 24 | 0.09 | <0.001 |
| TC:HDL ratio | 4.1 ± 1.5 | 3.5 ± 1.1 | 0.12 | 4.6 ± 2.0 | 4.1 ± 1.7 | 0.29 | 0.19 |
| Triglycerides (mg/dL) | 142 ± 75 | 125 ± 68 | 0.40 | 140 ± 57 | 135 ± 61 | 0.72 | 0.79 |
| C-Reactive Protein – Reactive (3) | 24 (20%) | 3 (20%) | 0.99* | 9 (43%) | 18 (39%) | 0.77 | 0.02 |
Fisher’s Exact test used because 25% or more of cells had expected counts less than 5.0
Race, Alcohol, cigarette smoking, and drug use missing data for one participant.
Hazardous drinker as defined by The National Institute on Alcohol Abuse and Alcoholism. (Hazardous alcohol use definition: 7 drinks per week or 3 drinks per occasion for women and 14 drinks per week or 4 drinks per occasion in men.)
C-reactive protein was quantified by PCR-latex (Wiener Laboratory, Rosario, Argentina) which detects levels above 6 mg/l as positive.
There was a significant difference in cholesterol intake, BMI, and cigarette smoking across groups with healthy uninfected participants consuming the most cholesterol, having the highest BMI and the highest proportion of cigarette smokers. Measurements of serum cholesterol levels also demonstrated that uninfected participants had the highest TC and LDL levels (p <0.001 for both). There was no difference in fat intake or serum triglycerides between or across groups.
HIV-infected participants demonstrated significantly lower BMI and HDL levels compared to HIV-uninfected persons, irrespective of HCV status. Similarly, a higher proportion of HIV-infected vs. HIV-uninfected participants demonstrated CRP reactivity. There were no statistically significant differences in triglycerides between or across groups.
Table 2 shows differences in HIV-related variables by HCV status. Nearly half (47%) of co-infected patients were on HAART compared to only 14% of those infected with HIV alone (p=0.01). When compared to HCV negative patients, the co-infected patients demonstrated lower viral loads (71,417 ± 140,351 vs. 327,527 ± 284,442, p=0.001) and increased viral load suppression (29% vs. 0%, p=0.007). There were no significant differences in CD4 cell counts by HCV status. There was no statistical difference in the number of participants receiving each type of HAART regimen.
Table 2.
Clinical Characteristics for HIV Positive participants
| HIV Positive (n=67) | |||
|---|---|---|---|
| (Mean ± SD or n (%)) | HCV Negative (n=21) |
HCV Positive (n=46) |
P-Value |
| CD4 absolute (1) | 211 ± 166 | 257 ± 168 | 0.31 |
| Viral load (copies/ml) (1) | 327,257 ± 284,442 | 71,417 ± 140,351 | 0.001 |
| Viral load suppressed (<400 Copies) (1) | 0 (0%) | 13 (29%) | 0.007* |
| HAART treatment (1) | 3 (14%) | 21 (47%) | 0.01 |
| Efavirenz (1) | 2 (10%) | 8 (18%) | 0.48* |
| Nevirapine (1) | 0 (0%) | 3 (7%) | 0.55* |
| Ritonavir and/or Kaletra (1) | 1 (5%) | 9 (20%) | 0.15* |
Fisher’s Exact test used because 25% or more of cells had expected counts less than 5.0
HAART missing data for one participant. CD4 and Viral load missing data for three participants
Table 3 shows the final multivariate model examining the association of HIV and/or HCV on cholesterol levels. Cholesterol intake and cigarette smoking were not significantly associated with HIV and/or HCV status after controlling for other covariates and therefore were dropped from the final multivariate model. HIV/HCV co-infected patients had the lowest TC levels (−28.7 mg/dl, p<0.001), while HCV-positive and HIV-positive patients also had significantly lower TC levels (−22.4 mg/dl, p<0.001 and −20.6, p=0.002, respectively) compared to the non-infected reference group. HCV and HIV/HCV co-infection were significantly associated with lower LDL levels (−21.4 mg/dL, p=0.001 and −20.3 mg/dL, p<0.0001, respectively), while HIV infection alone showed only a trend towards lower LDL levels compared to the HIV/HCV uninfected group. HIV and HIV/HCV co-infection, but not HCV infection alone, were associated with significantly lower HDL cholesterol levels (−9.1 mg/dL, p=0.0008 and −6.8 mg/dl, p=0.0006 respectively).
Table 3.
Factors associated with TC, LDL and HDL cholesterol levels (final multivariate models)
| Total Cholesterol | LDL cholesterol | HDL cholesterol | ||||
|---|---|---|---|---|---|---|
| Parameter | Coefficient (95% CI) |
p-value | Coefficient (95% CI) |
p-value | Coefficient (95% CI) |
p-value |
| HIV/HCV status | ||||||
| HIV only | −20.6 (−33.4, −7.7) | 0.002 | −11.4 (−22.9, 0.15) | 0.05 | −9.1 (−14.4, −3.8) | 0.0008 |
| HCV only | −22.4 (−33.7, −11.2) | <0.001 | −21.4 (−34.8, −8.1) | 0.001 | −0.9 (−10.4, 8.5) | 0.84 |
| HIV / HCV coinfected | −28.7 (−38.4, −18.9) | <0.001 | −20.3 (−28.9, −11.6) | <0.0001 | −6.8 (−10.8, −2.9) | 0.0006 |
| HIV-/HCV- (ref.) | ref. | --- | ref. | --- | ref. | --- |
| BMI (kg/m2) | 1.1 (0.06, 2.2) | 0.04 | 1.2 (0.6, 2.3) | 0.04 | ||
| Triglycerides (per 10 mg/dL) |
2.2 (1.4, 3.1) | <0.0001 | 0.87 (0.08, 1.7) | 0.03 | −0.60 (−0.83, −0.37) | <0.0001 |
| Glucose (per 10 mg/dL) |
3.5 (1.3, 5.7) | 0.002 | 2.5 (0.44, 4.5) | 0.02 | ||
| Hazardous Drinker | −7.8 (−15.7, 0.10) | 0.05 | ||||
| Female | 4.6 (−0.1, 9.4) | 0.06 | ||||
| Amerindios ethnicity | 5.3 (0.8, 9.8) | 0.02 | ||||
| C-Reactive Protein (Reactive =Yes) |
−4.4 (−8.2, −0.6) | 0.02 | ||||
BMI, triglyceride and glucose levels were positively associated with TC and LDL levels. Triglycerides were negatively associated with HDL levels. Hazardous drinking was negatively associated with LDL levels. Female sex, Amerindios ethnicity and CRP non-reactivity were all associated with higher HDL levels.
In a subgroup analysis of factors associated with cholesterol levels among HIV-infected participants (n=67, Table 4), daily alcohol intake was associated with increased LDL cholesterol. Participants on Ritonavir and/or Kaletra (n=10), adjusted for the effects of Hepatitis C, had significantly lower HDL levels (−7.9 mg/dL, p=0.03). Ritonavir/Kaletra was not associated with TC or LDL levels.
Table 4.
Factors associated with TC, LDL and HDL cholesterol levels (final multivariate models for HIV only), n=67
| Total Cholesterol | LDL cholesterol | HDL cholesterol | ||||
|---|---|---|---|---|---|---|
| Parameter | Coefficient (95% CI) |
p-value | Coefficient (95% CI) |
p-value | Coefficient (95% CI) |
p-value |
| Hepatitis C Co-infection | −9.9 (−23.0, 3.3) | 0.14 | −11.1 (−22.3, 0.4) | 0.06 | 1.4 (−4.7, 7.4) | 0.66 |
| Triglycerides (per 10 mg/dL) | 2.2 (1.2, 3.3) | <0.0001 | 0.8 (−0.0, 1.7) | 0.06 | −0.7 (−1.3, 0.0) | 0.06 |
| Poly-unsaturated fat (g) intake | 0.9 (0.2, 1.6) | 0.02 | 0.7 (0.1, 1.3) | 0.02 | ||
| ≥ 1 alcohol drink every day | 14.0 (0.3, 27.6) | 0.04 | ||||
| On Ritonavir and/or Kaletra | −7.9 (−14.9, −1.0) | 0.03 | ||||
| C-Reactive Protein (Reactive =Yes) | −8.3 (−14.4, −2.2) | 0.007 | ||||
Discussion
This study is one of the first to examine cholesterol levels in HIV and/or HCV-infected drug users living in Argentina. Specifically, we compared cholesterol levels among HIV-monoinfected, HCV-monoinfected, and HIV/HCV co-infected persons to a control group of uninfected persons with a similar ethnic background, diet, and drug use history. Despite similar total caloric and fat intake among the groups, HIV/HCV uninfected participants had the highest BMI, TC, and LDL levels which may be a marker of better overall health. HCV-infected persons were older than HCV-negative persons in this cohort, which could be a result of lower incidence of injection drug use and successful needle distribution and exchange programs which began in Argentina in 1999–2000. 15, 20 HIV-monoinfected persons had the lowest HDL cholesterol which supports observations early in the HIV epidemic in the US, prior to the widespread use of HAART. 2, 18 Only 14% of HIV-monoinfected persons were receiving HAART, so the low HDL observed in this group is most likely attributed to direct effects of HIV infection. The low HDL associated with HIV infection was also seen in persons co-infected with HIV/HCV.
HIV/HCV co-infected persons had the lowest total cholesterol, despite almost half of this group receiving HAART. This observation lends further support to prior studies which have demonstrated less dyslipidemia upon initiation of HAART in HIV/HCV co-infected persons 11, 12. In addition, HCV monoinfection and HIV/HCV co-infection were associated with LDL levels approximately 20 mg/dL lower than uninfected persons and approximately 10 mg/dL lower than HIV-monoinfected persons. This observed lower LDL is clinically meaningful and supports the findings of prior observational studies in the US. 9, 11 Further studies are needed to examine whether the lower total cholesterol and LDL in HIV/HCV co-infected persons confers a reduction in cardiovascular risk. Increased cardiovascular risk in HIV-infected persons has been well described in developed countries and more recent studies have confirmed this risk in Latin American countries. 16, 21, 22 In a cohort of >4000 HIV-infected persons receiving HAART in Latin America, Cahn et al. reported increased prevalence of dyslipidemia and metabolic syndrome and an intermediate 10 year risk of cardiovascular disease. 22 Further, the low HDL and increased C-reactive protein positivity observed among our HIV-infected study participants suggests increased cardiovascular risk in this population.
There are several findings worthy of emphasis. Only approximately one-third of the HIV-infected population was on HAART, despite free access to antiretroviral therapy by the National AIDS Program of Argentina since 1996. 23 This observation highlights the need to engage drug users in HIV care. Zala et al. also reported limited use of HAART in Argentina, and in particular, noted that initiation of HAART was associated with older age, AIDS-defining illness, lower CD4 cell count and higher viral load.24 Drug shortages and insufficient monitoring of response to HAART has also been reported. 25 In contrast, more recent data from the EuroSIDA Cohort, a prospective study of HIV-infected persons in Europe, Israel, and Argentina, reported that, in Argentina, over 95% of HIV-infected persons with a CD4 cell count <350 cells/mm3 were receiving HAART. However this large cohort study includes only one clinical site in Argentina; a more detailed study evaluating HAART uptake and response to treatment at several sites throughout Argentina is warranted.
Interestingly, almost half of the co-infected persons were on HAART vs. only 14% of the HIV mono-infected persons. This finding is in sharp contrast to studies conducted early in the HAART era in the US where HIV/HCV co-infected persons were less likely to be prescribed HAART vs. HIV-monoinfected persons. 5, 11 Further, 29% of HCV/HIV-infected persons had a HIV viral load <1000 copies versus none of the HIV-monoinfected persons. One possible explanation for our observation is that the co-infected patients were older and may have had more symptoms or a more advanced stage of HIV disease, thereby prompting initiation of HAART.
Some study limitations should be noted. We used HCV antibody, rather than HCV RNA, to identify persons infected with HCV. A small percentage of HIV-infected persons co-infected with HCV may be HCV antibody negative but have detectable HCV RNA. 5 Similarly, some persons may have had detectable HCV antibody but negative HCV RNA and thus cleared HCV infection. The cross-sectional design and low percentage of participants on HAART precludes us from assessing causality and the effects of HAART on serum lipids.
In summary, this work provides much needed data on cholesterol profile in HIV and/or HCV-infected Argentinian drug users. Our findings suggest that HIV-infected Argentinean drug users will benefit from interventions aimed to improve engagement in medical care, including access to and monitoring of HAART. As HAART use becomes more widespread in Argentina and the HIV-infected population ages, further study is needed to examine the effect of antiretrovirals on cardiovascular disease.
Acknowledgments
This work was funded in part by NIH grants P30DA013868 and P30AI042853.
References
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