Introduction of combination antiretroviral therapy (cART) has improved survival in patients infected with HIV. However, even in the cART era excess mortality in HIV-infected individuals is found.1,2 Non-AIDS–related disorders, such as hypertension and cardiovascular disease (CVD), have emerged as increasing clinical problems contributing to excess mortality.3,4 A premature aging process has been suggested to occur for which several contributing factors have been proposed, including persistent viral replication, lifestyle factors, low-grade inflammation, and immune activation.3
During primary HIV infection, CD4+ cells and especially pro-inflammatory Th17 cells are depleted from the gastrointestinal tract leaving the mucosal integrity distorted.5–9 Subsequently, bacterial products more easily cross the intestinal epithelium to the systemic circulation, a process termed microbial translocation. The concentration of lipopolysaccharide (LPS) in plasma is a marker of microbial translocation. Markers of microbial translocation are elevated in HIV infection and have been suggested to drive HIV-associated inflammation and immune activation, possibly through stimulation of Toll-like receptors (TLRs).8,10–15 Importantly, measures of immune activation and microbial translocation independently predict disease progression and mortality in patients with and without cART.13,16,17 Moreover, immune activation and microbial translocation are reduced but not normalized despite prolonged treatment with cART.10,18,19 Recently, serum LPS in HIV-uninfected patients with type 1 diabetes or kidney disease has been associated with components of the metabolic syndrome, mainly elevated triglycerides.20 Furthermore, increased microbial translocation has been associated with development of type 2 diabetes, hypertension, obesity, and insulin resistance.20–24
It therefore seems plausible that microbial translocation promotes inflammation and may be associated with increased risk of CVD. Our hypothesis was that microbial translocation induces alterations in fat and glucose metabolism, resulting in increased risk of CVD. In the present study, we examined a cohort of 60 HIV-infected patients on cART and 31 matched controls. Microbial translocation was measured as the concentration of LPS in plasma. Furthermore, lipids, insulin sensitivity, and blood pressure were determined. Body composition was determined using whole-body dual-energy x-ray absorptiometry scans and magnetic resonance imaging (MRI). Finally, it was determined whether the LPS concentration was associated with estimated risk of subsequent CVD using Framingham risk score.
Sixty-one HIV-infected patients aged 40–65 years were recruited from the outpatient clinic at the Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, during the period October 2010 to June 2011. One patient fulfilled the criteria for diabetes mellitus and was according to exclusion criteria excluded from further analysis. For comparison, 31 healthy individuals matched for age, gender, education, and comorbidity were included. Clinical characteristics are shown in Table 1. Nineteen of the controls also participated as controls in a study regarding diabetes,25 and HIV-infected patients also participated in a study regarding cognitive function.26 All HIV-infected patients had been on treatment with cART for a minimum of 2 years and had suppressed viral replication with <500 copies/mL for at least 1 year before inclusion. Exclusion criteria were ART before cART, acute illness, chronic infection with hepatitis B virus or hepatitis C virus, intravenous drug use, autoimmune disease, diabetes, cancer, and pregnancy.
The study was approved by the National Committee on Health Research Ethics of the Capital Region of Denmark (VEK nr. H-2-2010-089) and was performed in accordance with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all participants after written and oral information.
All participants were interviewed to obtain detailed medical history. Comorbidity was assessed according to Charlson comorbidity index.27,28 From all participants, a venous blood sample was obtained. Routine analyses included full blood count and CD4+ cell count. HIV RNA was measured with polymerase chain reaction quantitative kit (COBAS AmpliPrep/COBAS TaqMan System; Roche, Basel, Switzerland), detection limit 20 copies/mL.
Markers of Microbial Translocation
Lipopolysaccharide was analyzed by limulus amebocyte lysate colometric assay (Lonza, Walkersville, MD) according to the manufacturer's instructions, with the following modifications: Samples were diluted 10-fold to avoid interference with background color and preheated to 68°C for 12 minutes before analyses to dissolve immune complexes. LPS was measured in all participants; valid measurements were obtained in 50 HIV-infected patients and 30 controls.
Lipids and Glucose Metabolism
Fasting triglycerides, total cholesterol, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) were measured as routine analyses. Fifty-six HIV-infected patients and all the controls participated in an oral glucose tolerance test performed after an overnight fast. Four HIV-infected patients declined to participate. Participants ingested 75 g of glucose dissolved in 300 mL of water. Blood samples were collected at 0, 30, 60, 90, and 120 minutes. Glucose, insulin, and C-peptide were measured at all time points by colorimetric hexokinase assay (Roche) for plasma glucose and enzyme-linked immunosorbent assay (Roche) for serum insulin and C-peptide. Insulin sensitivity was assessed using the Matsuda composite index,29 where a high index is equivalent to high insulin sensitivity. In 4 cases, a time point for insulin was missing because of hemolysis in the sample; here, interpolation was used to assess area under the curve.
The Framingham risk score was used to calculate the 10-year risk score of having a myocardial infarction (MI) and of developing CVD.30 The Framingham score used included data on gender, age, smoking status, diabetes, left ventricular hypertrophy, systolic blood pressure, total cholesterol, and HDL according to European AIDS Clinical Society guidelines.30 Electrocardiogram was not available; hence, all participants were characterized as having no left ventricular hypertrophy.31
A whole-body dual-energy x-ray absorptiometry scan (GE Lunar Prodigy; GE Medical Systems, Madison, WI) was used to measure body composition, including whole-body fat as well as upper and lower limb fat in 58 HIV-infected patients and all controls. Two HIV-infected patients declined to participate.
Three-Tesla MRI (Magnetom Total imaging matrix magnetic resonance scanner; Siemens, Erlangen, Germany) was used to assess intra-abdominal fat content (visceral fat). During a breath hold, 60 slides T1-weighted abdominal slides were acquired with a thickness of 5 mm. Images were analyzed using MANGO (Multi-Image Analysis GUI) version 2.5 (The University of Texas Health Science Center, San Antonio, TX). Adipose tissue located from the diaphragm to the first sacral vertebra, except subcutaneous tissue, was characterized as visceral fat. MRI scans were performed in 40 HIV-infected patients and 29 controls. The remaining participants were excluded because of contraindications to MRI.
The circumference of hip and waist were measured to calculate a hip/waist ratio, and the height and weight were measured and used to calculate the body mass index.
Data were tested for normal distribution and when necessary, nonparametric statistics were used (fasting insulin, and Framingham risk score of CVD). Data are given as mean and 95% confidence interval unless otherwise stated. Unpaired t test and χ2 test was used to compare the 2 groups, a level of P < 0.05 was considered significant. Analysis of variance was used to compare multiple groups, and only if significance was obtained, further comparisons between groups were performed. Pearson test was used to investigate associations. General linear model was used to test the effect of protease inhibitor (PI) and abacavir on the association between LPS and triglycerides and cholesterol. Analysis was performed using GraphPad Prism 4 (GraphPad Software, La Jolla, CA) and SPSS 18 (SPSS, Inc, Quarry Bay, Hong Kong).
Higher Level of Microbial Translocation in HIV-Infected Patients
Mean CD4+ cell count in HIV-infected patients was 581 cells/μL and nadir CD4 count was 192 cells/μL. Median HIV RNA was 19 copies/mL (Table 1). A higher proportion of HIV-infected patients were smokers (35% vs. 13% of controls, P = 0.014). Compared with controls, HIV-infected patients had higher level of microbial translocation measured as plasma LPS (64.5 pg/mL vs. 50.6 pg/mL, P = 0.002) (Table 1). Plasma LPS in nonsmoking and smoking HIV-infected patients was comparable (64.0 pg/mL vs. 65.3 pg/mL, P = 0.235). Furthermore, LPS in HIV-infected patients receiving PI-based treatment (n = 27) was comparable with LPS in patients on non-PI–based treatment (67.7 pg/mL vs. 61.9 pg/mL, P = 0.674). Twenty-two patients received lamivudine/abacavir as part of cART. There was no difference in LPS in patients on lamivudine/abacavir vs. patients receiving other backbone therapy (68.2 pg/mL vs. 62.0 pg/mL, P = 0.332) (see Figures S1 and S2, Supplemental Digital Content,http://links.lww.com/QAI/A438, which illustrates metabolic and physical parameters in patients receiving PI or abacavir vs. other backbone therapy).
Higher Triglycerides and Lower Insulin Sensitivity in HIV-Infected Patients
Lipids were determined in all participants. HIV-infected patients had higher triglycerides compared with controls (1.5 mmol/L vs. 1.0 mmol/L, P < 0.001). In contrast, no differences were found in total cholesterol, HDL, or LDL (Table 2). Three HIV-infected patients and 4 controls received lipid-lowering medication.
Glucose metabolism was determined in all participants, and differences in fasting blood glucose, fasting C-peptide, or HgA1c were not found between the groups. However, HIV-infected patients had higher fasting insulin than controls (59.2 pmol/L vs. 44.4 pmol/L, P = 0.014). Furthermore, using Matsuda index, lower insulin sensitivity was found in HIV-infected patients compared with controls (6.3 vs. 9.8, P = 0.003) (Table 2).
Finally, HIV-infected patients had lower hip/waist ratio compared with controls (P = 0.002), but no differences were found in visceral fat or fat percentage. To detect possible lipodystrophy, total lower upper and lower limb fat mass was determined, and HIV-infected patients had lower limb fat compared with healthy controls (6491 vs. 7905 g, P = 0.025) (Table 2).
To examine possible impact of either abacavir or PI on lipids, glucose metabolism, and body composition, HIV-infected patients were divided into groups according to treatment (PI vs. non-PI or abacavir vs. other backbone therapy). Significant difference was not found for any of the measured parameters. Specifically, triglycerides and total cholesterol in patients receiving PI-based treatment (n = 27) vs. patients on a non-PI–based treatment was 1.5 mmol/L vs. 1.5 mmol/L, P = 0.949 and 5.3 mmol/L vs. 5.3 mmol/L, P = 0.931, respectively. Likewise, no differences in triglycerides and total cholesterol were found in patients on lamivudine/abacavir (n = 22) vs. patients receiving other backbone therapy (1.6 mmol/L vs. 1.4 mmol/L, P = 0.152 and 5.5 mmol/L vs. 5.2 mmol/L, P = 0.284, respectively) (see Figures S1 and S2, Supplemental Digital Content, http://links.lww.com/QAI/A438, which illustrates metabolic and physical parameters in patients receiving PI or abacavir vs. other backbone therapy).
Higher Risk of Having a Myocardial Infarction in HIV-Infected Patients
Ten-year risk of developing CVD and MI was assessed by the Framingham score. HIV-infected patients had a higher risk of MI (5.1 vs. 3.0, P = 0.026) and a higher, albeit not significant, risk of developing CVD (13.1 vs. 10.2, P = 0.272) (Table 2). No differences were found in blood pressure between HIV-infected patients and controls. Three HIV-infected patients and 2 controls were treated with antihypertensive medication.
To determine if differences between HIV-infected patients and healthy controls regarding metabolic parameters and Framingham risk score were because of more smokers among HIV-infected patients, a comparison of non-smoking HIV-infected patients and non-smoking controls was done (Table 2). Nonsmoking HIV-infected patients had increased triglycerides and evidence of decreased insulin sensitivity. Likewise, HIV-infected nonsmoking patients showed signs of lipodystrophy compared with healthy controls. In contrast, nonsmoking HIV-infected patients did not have increased Framingham risk scores compared with nonsmoking controls.
HIV-Infected Patients With High LPS had Higher Level of Serum Lipids, Impaired Glucose Metabolism, and a Higher Framingham Risk Score
LPS was measured in 50 HIV-infected patients; patients were divided into tertiles (17, 16, and 17 subjects, respectively) by increasing LPS level with a mean (95% confidence interval) of 46.1 (43.2 to 49.1) pg/mL, 62.4 (60.0 to 64.7) pg/mL, and 84.7 (72.0 to 97.5) pg/mL, respectively. Patients in the 3 groups did not differ in age [46 (40 to 65) years, 50 (40 to 60) years, and 50 (40 to 64) years, P = 0.270, respectively], and no differences were found in CD4+ cell count, nadir CD4, or HIV RNA between groups (Fig. 1).
Higher level of triglycerides was found in the third tertile compared with the first and second tertiles (P = 0.006 and P = 0.046, respectively). Furthermore, total cholesterol was higher in the second and third tertiles compared with the first (P = 0.022 and P = 0.016, respectively), and LDL was higher in the second and third tertiles compared with the first (P = 0.009 and P = 0.002, respectively) (Figs. 2A–D). No differences were found in HDL concentration (Fig. 2D).
Patients in the highest LPS tertile had higher level of fasting C-peptide compared with the first and second tertiles (P = 0.036 and P = 0.011, respectively) and a lower Matsuda index (P = 0.006 and P = 0.003, respectively), indicating lower insulin sensitivity (Figs. 2E–G). In contrast, no difference in fasting blood glucose or fasting insulin was found between patients in the 3 LPS tertiles.
Importantly, HIV-infected patients in the 2 highest LPS tertiles had a significantly higher risk of CVD (P = 0.001 and P < 0.001) and MI (P = 0.001 and P < 0.001) (Figs. 2H, I). No differences were found in any of the parameters describing body composition. Nor were differences in blood pressure found.
To investigate the potential impact of smoking on these results, analysis of cardiometabolic parameters in LPS tertiles in HIV-infected nonsmokers were performed. Similar results were found as nonsmoking HIV-infected patients in the highest LPS tertile had a higher level of triglycerides compared with the first tertile (P = 0.009). A higher level of LDL was found in the second and third tertiles compared with the first (P = 0.013 and P = 0.008, respectively). A higher risk of CVD and MI was observed in highest LPS tertile compared with the first and second tertiles (CVD, P = 0.008 and P = 0.021; MI, P = 0.004 and P = 0.015, respectively). No differences were found between tertiles regarding insulin sensitivity in nonsmokers.
Correlations Between Microbial Translocation and Metabolic Markers in HIV-Infected Patients
In HIV-infected patients, significant associations between LPS and age, CD4+ cell count, nadir CD4 or HIV RNA were not found. In contrast, significant associations were found between LPS and triglycerides (R2 = 0.450, P < 0.001), total cholesterol (R2 = 0.147, P = 0.005), and LDL (R2 = 0.110, P = 0.018) (Figs. 3A–C). To investigate potential influence of PI or abacavir on the association between LPS and lipids, a general linear model was used with LPS and PI or abacavir as explanatory variables and triglyceride or cholesterol as dependent variables. The associations were unaffected and remained significant after adjustment for treatment regimes containing PI or abacavir [triglycerides–PI (r2 = 0.454, P < 0.0001), triglycerides–lamivudine/abacavir (r2 = 0.462, P < 0.0001), total cholesterol-PI (r2 = 0.148, P = 0.007), total cholesterol–lamivudine/abacavir (r2 = 0.155, P = 0.009)].
Furthermore, weak associations were found between LPS and fasting C-peptide (R2 = 0.085, P = 0.044), HgA1c (R2 = 0.084, P = 0.040), and insulin sensitivity by Matsuda (R2 = 0.094, P = 0.044) (Figs. 3D–F). Interestingly, significant associations were found between LPS and diastolic blood pressure (R2 = 0.142, P = 0.006) and risk of CVD (R2 = 0.105, P = 0.021) and MI (R2 = 0.106, P = 0.020) (Figs. 3G, I). In healthy controls, associations between LPS and any of the metabolic parameters measured were not found.
Microbial translocation has been suggested to be a driver of inflammation and immune activation in HIV infection. This study showed that even HIV-infected patients with suppressed viral replication have increased level of microbial translocation as measured by LPS. Furthermore, concentration of LPS was associated with metabolic risk factors, including triglycerides and LDL as well as lower insulin sensitivity. Importantly, LPS was also associated with increased risk of CVD and MI. Thus, increased microbial translocation may be a cause of excess CVD in HIV infection.
HIV-infected patients included in this study had suppressed viral replication, and median CD4+ cell count was within normal range. Despite the size of the study group, established differences between HIV-infected patients and healthy controls regarding dyslipidemia, insulin sensitivity, and risk of CVD were confirmed.32–37 The control group was carefully matched, and differences regarding age, body mass index, education, and comorbidity were not found. However, a larger fraction of HIV-infected patients were smokers, which may in part explain the finding of increased risk of CVD.4 However, when comparing nonsmoking HIV-infected patients and nonsmoking healthy controls, differences regarding dyslipidemia and insulin resistance remained significant, demonstrating that smoking does not explain all the differences in metabolic parameters between HIV-infected patients and controls. Our hypothesis was that microbial translocation results in dyslipidemia, decreased glucose tolerance, and hence increased risk of subsequent CVD.
During acute infection with HIV, the gut mucosa is depleted of CD4+ cells, leaving the mucosal barrier vulnerable for translocation of microbial products, such as LPS, 16S rRNA, and flagellin, all of which are elevated in HIV infection.38–41 LPS binds to TLR on monocytes and macrophages, resulting in increased production of pro-inflammatory cytokines, such as interleukin (IL)-1β, IL-5, and tumor necrosis factor.10,14 At present, LPS is the marker of microbial translocation most commonly used, and methods for measuring LPS are established. LPS levels are elevated in acute HIV infection and in the chronic stage of HIV infection. Following initiation of cART, a decrease in LPS is observed although it does not reach the level of healthy controls.10,19 In the present study, all HIV-infected patients had been on cART for a minimum of 2 years with suppressed viral replication, but in line with previous studies, higher level of LPS was observed compared with controls.10,19 In our cohort, LPS was not associated with current CD4+ cell count, nadir CD4, or HIV RNA as opposed to other studies.42,43 One explanation could be the homogenous composition of the studied population with a narrow range in CD4+ cell count and suppressed viral replication in all participants.
Association was found between LPS and dyslipidemia for HIV-infected patients but not in healthy controls. In HIV-uninfected individuals, LPS has been linked to metabolic parameters, including triglycerides, insulin resistance, and obesity. In particular, we found a strong association between LPS and triglycerides, in accordance with a recent report from a non-HIV cohort.22 Several mechanisms could explain this association. First, LPS and triglycerides are co-transported in chylomicrones from the gut to circulation,44 and postprandial increase in plasma LPS has been reported.45 Second, in the circulation, LPS is scavenged by HDL cholesterol, which is often low in conditions with elevated triglycerides and high levels of pro-inflammatory cytokines.46 Furthermore, LPS downregulates lipoprotein lipase activity, leading to hypertriglyceridemia.47 Finally, adipocytes express TLR, and binding of LPS may result in increased production of pro-inflammatory cytokines.23,48 Thus, it is conceivable that the disrupted gut barrier in HIV infection might fuel a possibly interacting effect of LPS and lipids on cardiometabolic risk factors. ARTs, especially PI and abacavir, have been shown to increase the levels of triglycerides and cholesterol and may increase the risk of CVD.49–54 Our study was not powered to study the impact of treatment on lipids or body composition, and differences due to treatment groups were not found. In theory, treatment group could influence our results, but adjusting for use of abacavir or PI did not alter the associations between microbial translocation and lipids.
It has been proposed that decreased insulin sensitivity in HIV infection is related to increased release of tumor necrosis factor–α, IL-6, and IL-8 by infected T cells and adipose tissues. These cytokines trigger insulin resistance both in peripheral tissues and in the central nervous system.55–57 HIV has been shown to activate and inhibit transcription factors related to insulin sensitivity.58 Also ART have been suggested to play a role in altered fat and glucose metabolism.20,23,48,59 In previous studies, the association between LPS and glucose metabolism has not been as pronounced as with dyslipidemia, and in our cohort, it was not possible to confirm the association between high LPS and decreased insulin sensitivity when looking at nonsmokers only.
Lipodystrophy is a condition with peripheral fat loss and central fat gain. ART has been known to cause lipodystrophy.60,61 HIV-infected patients in the present study showed signs of lipodystrophy with reduced peripheral fat. In contrast, no difference was found in visceral fat content assessed by MRI. No associations were found between concentration of LPS and any of the parameters describing body composition.
HIV-infected patients have increased risk of CVD.34–36 To determine if LPS in plasma was related to risk of developing CVD, the Framingham risk score was used. HIV-infected patients had increased risk of MI and CVD, and an association with LPS was found. Several mechanisms might explain this association, the most obvious being the association between LPS and dyslipidemia. Numerous studies have found higher rate of CVD in HIV-infected populations, with risk factors such as hypertension, smoking, and dyslipidemia not being able to explain the entire difference.3,4,36 Interestingly, LPS may induce endothelial dysfunction by interacting with TLR4 on endothelial cells, thereby promoting plaque formation, atherosclerosis, and CVD.23,59,62,63 The present study indicates that microbial translocation, possibly by increasing lipids, may contribute to the increased risk of CVD. In contrast, in healthy controls, LPS level was lower and no associations were found between LPS and any of the metabolic parameters measured. This suggests that LPS needs to be above a certain threshold before it exerts a clinical measurable consequence.
Morbidity and mortality among HIV-infected patients have declined since introduction of cART. Despite this, the morbidity and mortality in HIV-infected patients remain higher compared with the general population, non-AIDS–related causes, including CVD, accounting for an increasing proportion.3,4 To our knowledge, this is the first study investigating a cohort of HIV-infected patients with suppressed viral replication and low level of comorbidity in regard to possible associations between microbial translocation and metabolic parameters, such as lipid and glucose metabolism and cardiovascular risk profile. HIV-infected patients had increased level of LPS indicating increased microbial translocation compared with healthy controls. LPS was associated with known risk factors for CVD, such as dyslipidemia, decreased insulin sensitivity, and hypertension, indicating that microbial translocation may contribute to the increased risk of CVD observed in HIV infection. However, the study was limited by the cross-sectional design and the relatively small sample size, and larger and prospective studies are warranted to confirm that microbial translocation is one of the causes of increased risk of CVD in HIV infection. Furthermore, we suggest intervention studies designed to reduce microbial translocation and improve cardiometabolic risk factors should be considered.
The authors thank all the patients and the controls for their participation in this study. The authors also thank Bente Baadegaard and Lene Pors Jensen as well as the personnel at the outpatient clinic at the Department of Infectious Diseases, Rigshospitalet, for their work with recruitment of participants and also thank Ruth Rousing and Hanne Villumsen from The Centre of Inflammation and Metabolism at the Department of Infectious Diseases, Rigshospitalet, for technical assistance. The authors thank Dean Tuladhar for performing the MRIs.
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