Cardiovascular disease (CVD) is increasingly common among HIV-infected patients, with recent studies demonstrating increased rates compared with non-HIV-infected patients [1–3]. In addition, significant subclinical coronary artery disease is seen even among HIV patients without known heart disease . Metabolic abnormalities, including diabetes mellitus, dyslipidemia, hypertension, and abdominal obesity are common in HIV-infected patients and may contribute to the increased risk of CVD in this population. Metabolic syndrome is increased among HIV-infected patients [5–8] and associated with increased coronary artery calcification (CAC) .
Clinical guidelines for HIV and non-HIV-infected patients with metabolic syndrome stress the importance of lifestyle modification (LSM) [10–12]. In addition, interest has focused on modulating insulin resistance. Metformin was shown to significantly reduce CVD events in the United Kingdom Prospective Diabetes Study (UKPDS) of 1704 non-HIV, overweight, type II diabetic patients randomized to receive dietary management alone, metformin, sulfonylurea or conventional therapy . However, longer term studies with these strategies have not been performed among HIV-infected patients, investigating effects on atherosclerotic indices.
In the present study, we investigated LSM and metformin, alone and in combination, among HIV-infected patients with metabolic syndrome over a relatively long-treatment period of 1 year. We hypothesized that treatment with LSM and metformin would improve measures of subclinical atherosclerosis in this population.
The study was conducted at the Massachusetts General Hospital (MGH) between December 2006 and July 2010. Eligibility requirements included: previously documented HIV infection, age between 18 and 65 years, on a stable HIV treatment regimen for more than 6 months and demonstration of National Cholesterol Education Program (NCEP)-defined metabolic syndrome .
Participants were excluded if they had had any new serious opportunistic infection within the past 6 weeks, history of unstable angina, aortic stenosis, uncontrolled hypertension, contraindication to physical activity, current therapy with insulin, other diabetic agents, or fasting blood sugar more than 6.99 mmol/l, alanine aminotransferase (ALT) level more than 2.5 × upper limit of normal (ULN), creatinine more than 132.6 μmol/l, lactic acid more than than 2 × ULN, history of allergy to metformin or intravenous (i.v.) contrast dye, glucocorticoid therapy, estrogen, or progestational derivative within 3 months of the study, current substance abuse, hemoglobin less than 100 g/l, pregnant, or using supraphysiological doses of testosterone or physiological testosterone replacement for less than 3 months.
Participants were recruited through advertising in the Boston area. Informed written consent was obtained before study participation and the protocol was approved by the Partners Human Research Committee.
The effects of metformin and/or LSM were studied over 1 year in a randomized, placebo-controlled 2 × 2, four group factorial study. Eligible participants were randomly assigned to one of four groups: no LSM–placebo; LSM–placebo; no-LSM–metformin or LSM–metformin. Randomization was stratified by sex, age, and protease inhibitor use. The treatment groups received metformin or identical placebo 500 mg twice a day, with a dose increase to 850 mg twice a day after 3 months, if lactic acid and creatinine levels were within normal limits and no side effects were reported. Investigators and study staff were blinded to treatment assignment. Randomization was performed by the Harvard Catalyst Biostatistics Program at MGH. A computer generated stratified permuted blocks randomization table was created and kept by the MGH pharmacy. Those randomized to LSM in the study participated in three supervised exercise sessions/week during the 12 months of the study with dietary counseling occurring once a week (see Supplemental Methods, http://links.lww.com/QAD/A196).
Computed tomography (CT) imaging was performed using a SOMATOM Sensation (Siemens Medical Solutions, Forchheim, Germany) 64-slice CT-scanner as previously described  (see Supplemental Methods, http://links.lww.com/QAD/A196). Carotid intima–media thickness (cIMT) imaging of the common carotid artery was conducted using a high-resolution 7.5-MHz phased-array transducer (SONOS 2000/2500) as previously described  (see Supplemental Methods, http://links.lww.com/QAD/A196).
Exercise and dietary assessment
A submaximal exercise stress test was conducted on a cycle ergometer to measure endurance. Dietary intake information was assessed by a 4-day self-documented food record using Nutrition Data System for Research software version 2006, developed by the Nutrition Coordinating Center, University of Minnesota (Minneapolis, Minnesota, USA). One repetition maximum was determined for six major muscle groups (see Supplemental Methods, http://links.lww.com/QAD/A196).
Metabolic, biochemical and immunological parameters
Fasting HDL, triglycerides, glucose, lactate levels, creatine, and ALT, were determined using standard techniques. Insulin was measured by chemiluminescence immunoassay (Beckman Coulter Inc., La Brea, California, USA) and homeostatic model of assessment-insulin resistance (HOMA-IR) was determined. High-sensitivity C-reactive protein (hsCRP; R&D Systems, Minneapolis, Minnesota, USA), PAI-1 (Siemens Healthcare Diagnostics Inc., Deerfield, Illinois, USA) and hemoglobin A1C (HbA1C; Roche Diagnostics, Indianapolis, Indiana, USA) were determined. CD4+ T-cell counts were assessed by flow cytometry. HIV viral load was determined by the COBAS Ampliprep (Roche Diagnostics).
Body composition assessment
Abdominal visceral adipose area (VAT) and subcutaneous area were assessed by MRI at the level of the L4 pedicle [15,16]. Intramyocellular lipid (IMCL) of the tibialis anterior was determined using 1H-MRS (Siemens, Munich, Germany) . Dual energy X-ray absorptiometry (Hologic A, Waltham, Massachusetts, USA) was used to assess extremity fat.
Participants returned 1, 3, and 9 months after baseline for safety visits to assess lactic acid, creatinine, complete blood count (CBC) and ALT. At 6 months, all measurements performed at baseline were repeated except MRI/MRS and cardiac CT. At 12 months, a visit identical to the baseline visit occurred. Patients were discontinued for creatinine more than 132.6 μmol/l, ALT more than 2.5 × ULN, lactic acid more than 2 × ULN and hemoglobin less than 100 g/l .
Baseline variables were compared among the four groups by ANOVA for continuous variables and by χ 2 test for categorical variables. For outcomes that were not normally distributed, the Kruskal–Wallis test was used. All data were included in the analysis by intention to treat principle. For participants who did not complete a 12-month visit, last observation carried forward (LOCF) was performed for those participants for whom interim data post the baseline visit was available. For the primary endpoint, calcium score, additional sensitivity analyses were performed carrying forward the baseline data on any patient who dropped out during the study as well as performing an analysis imputing change based on the median percentage change in each category among completers and transforming this to an absolute change imputed for those without 12-month data.
We first compared the change over time between metformin and placebo and LSM and no-LSM, as per the 2 × 2 factorial design. These contrasts compared the change among all patients receiving LSM vs. those not, regardless of metformin/placebo assignment and separately the changes among all those receiving metformin vs. those receiving placebo, regardless of the LSM assignment. Prior to performing this analysis, we tested for an interaction between the LSM assignment and metformin/placebo assignment. In addition, we determined the net effect of metformin (vs. placebo) controlling for the LSM randomization and the net effect of LSM (vs. no-LSM) controlling for the metformin randomization in a factorial analysis. Change over 12 months was compared between the groups by ANOVA for normally distributed outcomes and by the Wilcoxon test for nonnormally distributed outcomes.
We then compared the change over 12 months in each of the four groups: no-LSM–placebo; LSM–placebo; no-LSM–metformin and LSM–metformin, using all available data and carrying forward any interim data postbaseline. The overall comparison was by ANOVA. For data that were not normally distributed, rank-based Kruskal–Wallis test was applied. If significant, post-hoc testing between individual groups was performed. In the four-group analysis, a test for linear trend was performed.
With 40 evaluable patients in each of the two factorial comparisons, we were able to detect a 1 SD or greater change from baseline difference between the groups with 85% power at α = 0.05. Prespecified endpoints were changes in CAC score, cIMT as well as metabolic syndrome parameters. All results are reported as mean ± SEM, for those variables that are not normally distributed results are also reported as median (IQR).
See Figure 1 for flow of participants through the study. Fourteen participants withdrew for an overall dropout rate of 28% (Fig. 1). The dropout rates were not statistically significantly different among the groups in the factorial analysis, metformin (32%) vs. placebo (23%; P = 0.46) and LSM (35%) vs. no-LSM (21%; P = 0.28) or in the four-group analysis (Fig. 1). Forty-two participants (84%) had evaluations at 6 months.
At baseline, there were no significant between group differences for age, race, sex, smoking status, or HIV parameters including CD4 cell count, HIV viral load, and duration of HIV infection or antiretroviral therapy (ART) use. Duration of HIV infection was on average 14 ± 1 year and duration of antiretroviral therapy was 6 ± 1 year. HbA1c was 5.5 ± 0.1%. There were no between-group differences for baseline parameters (Table 1). CAC was more than 0 in 51% of participants, with similar percentages in the study groups.
There were no differences between the groups for dietary parameters at baseline. For the entire cohort, caloric intake was 2253 calories/day, with 36% of calories from fat, 12% from saturated fat, 6% from polyunsaturated fat, and 14% from monounsaturated fat. Total daily fiber intake was 19 g. Vitamin B12 intake was adequate at baseline (6.7 ± 0.5 μg/day) among the entire cohort and similar in the study groups.
Among participants completing the protocol, the compliance with lifestyle sessions (percentage of sessions attended) was 84 ± 4% for the LSM–placebo group and 84 ± 4% for the LSM–metformin group. Metformin compliance, determined by pill count, was 88 ± 0%.
Effects of lifestyle modification and metformin
Metformin-treated patients demonstrated significantly less progression of CAC than placebo-treated patients [−1 ± 2 vs. 33 ± 17; 0 (0,0) vs. 14 (0,34)] P = 0.004, metformin vs. placebo] (Fig. 2a). In contrast, CAC progression was not significantly different between LSM and no-LSM groups [8 ± 6 vs. 21 ± 14; 6 (0,14) vs. 0 (0,14)] P = 0.82, LSM vs. no LSM] Fig. 2b. The corresponding percentage changes in calcium score were [2 (−59,85) vs. 19% (5,77)] metformin vs. placebo and [12 (−23,34) vs. 66% (−64,81)] LSM vs. no-LSM. Metformin had a significantly greater effect on CAC than LSM (P = 0.01). Metformin-treated patients also demonstrated significantly less progression in calcified plaque volume than placebo-treated patients (−0.4 ± 1.9 vs. 27.6 ± 13.8 μl, P = 0.008). In an additional sensitivity analysis using LOCF from baseline for all noncompleters in the study, metformin-treated patients similarly demonstrated decreased deterioration in CAC score (−1 ± 1 vs. 26 ± 14, P = 0.004) and calcified plaque volume (−0.2 ± 1.2 vs. 22.7 ± 11.6 μl, P = 0.005) compared with placebo. Similar results were seen in a sensitivity analysis with imputed data based on median percentage change among completers. In addition, metformin significantly prevented plaque progression in the subset with CAC more than 0 at baseline (−3 ± 6 vs. 46 ± 23, P = 0.003, metformin vs. placebo). No significant effects on calcified plaque volume or cIMT parameters were observed in the comparison of LSM vs. no-LSM.
In the four-group analysis, a significant overall effect between the groups was seen for CAC (ANOVA, P = 0.03; Table 2). A significant overall linear trend (P = 0.03) was also seen demonstrating that CAC progression was greatest among the group receiving no-LSM, placebo, in whom the change represented a median increase of 56% (−40,79), and smallest in the group receiving LSM–metformin (Fig. 2c). Compared with the group receiving no-LSM–placebo, the change over 12 months was significantly smaller in the group receiving LSM–metformin (P = 0.03). In addition, CAC progression was significantly less in the group receiving no-LSM–metformin than in the group receiving LSM–placebo (P = 0.01; Fig. 2c). For calcified plaque volume, a similar pattern was seen. Average changes from baseline in cIMT were nearly zero in all four treatment arms, and the between-group comparisons were not statistically significant.
Exercise and diet parameters
LSM was associated with improvements compared with no-LSM on VO2max, endurance (time on cycle ergometer), tricep dip, knee flexor, lateral pulldown, knee extension, chest press, and leg press (P < 0.01 for all parameters), and this effect was also seen in the four-group analysis (Table 2). There were no statistically significant effects of metformin for exercise parameters. Participants in the LSM group reduced total calories from fat by −4 ± 2 vs. 0 ± 2%, P = 0.08 (LSM vs. no-LSM), and increased total fiber by 7 ± 4 vs. 1 ± 2 g/day, P = 0.08 (LSM vs. no-LSM). Changes in saturated fat were −2 ± 1 vs.−1 ± 1%, P = 0.39 (LSM vs. no-LSM). Vitamin B12 intake remained adequate throughout the study in all groups (data not shown).
HDL improved in those randomized to LSM vs. no-LSM (0.08 ± 0.03 vs. −0.03 ± 0.03 mol/l, P = 0.03) and a significant trend was seen across the groups in the four-group analysis. Metformin improved HOMA-IR (−0.09 ± 0.43 vs. 1.10 ± 0.41, P = 0.05) compared with placebo. In the four-group analysis, the improvement in HOMA-IR was most significant in the LSM-metformin group and a significant trend was seen across the groups (Table 2). LSM decreased hsCRP compared with no-LSM (−1.57 ± 0.70 vs. 0.08 ± 0.45 mg/l, P = 0.05). LSM also tended to improve PAI-1 compared with no LSM (−12.9 ± 12.7 vs. 22.3 ± 11.1 ng/ml; P = 0.06). No other significant changes were observed for metabolic parameters.
Body composition parameters
IMCL improved in those randomized to LSM compared with those randomized to no-LSM (−0.13 ± 0.16 vs. 0.68 ± 0.23 mmol/kg, P = 0.005), but did not differ in the comparison of metformin vs. placebo. VAT decreased −31.6 ± 15.2 cm2 in those randomized to metformin vs. −13.4 ± 10.2 cm2 to placebo, although this difference was not significant. Extremity fat did not change significantly in response to LSM (−0.5 ± 0.3 vs. −0.2 ± 0.4 kg, P = 0.46, LSM vs. no LSM) or metformin (−0.5 ± 0.4 vs. −0.2 ± 0.3 kg, P = 0.49, metformin vs. placebo).
LSM had a small but significant effect to decrease CD4 compared with those not randomized to LSM (−15 ± 30 vs. 84 ± 36 cells/μl, P = 0.04). This effect persisted when baseline CD4 cell count was adjusted for in the analysis of 12-month CD4 change between the LSM and no-LSM groups. No effect of metformin on CD4 was seen. Viral load was not affected by randomization to either LSM or metformin (P > 0.05 for both groups). Percentage of participants with detectable viral load was also not affected by LSM (P = 0.14, LSM vs. no-LSM) or metformin (P = 0.80, metformin vs. placebo).
Two participants in the LSM–metformin group experienced minor elevations in creatinine level after the 3-month visit that returned to within normal limits after a dose reduction to metformin 500 mg twice daily. No patient in a metformin group demonstrated an elevated lactic acid level above the normal limit. One participant in the metformin group withdrew from the study due to gastrointestinal side effects. Five participants in the metformin group reported gastrointestinal side effects from the study drug, necessitating a temporary hold of study drug and reduction to 500 mg twice daily or 500 mg once daily. No gastrointestinal distress was reported in the placebo-treated groups. Two participants in the LSM group experienced muscle strains related to the resistance training necessitating modification of weights. There were no significant differences between groups for ALT, creatinine or lactic acid (P > 0.05). There were no serious adverse events and the LSM program was well tolerated.
To our knowledge, this study is the first to evaluate the effects of LSM and metformin on atherosclerotic indices among HIV-infected patients. Our data demonstrate that metformin had a robust effect to prevent progression of CAC and calcified plaque volume, while improving HOMA-IR over 1 year in HIV patients with metabolic syndrome. LSM had an effect to improve HDL, hsCRP and IMCL of the tibialis anterior, but demonstrated a lesser effect to prevent progression of CAC in this population.
CVD and diabetes are prevalent in HIV-infected patients [1,18]. Modification of risk factors for these illnesses is an important element in the management of HIV-infection. The only approved treatment for metabolic changes in HIV-infected patients, tesamorelin, targets abdominal obesity, does not improve insulin resistance, and has not been assessed with respect to critical atherosclerotic indices. In this study, we assessed LSM, widely recommended, but little studied, as a treatment for metabolic abnormalities in HIV patients, and simultaneously assessed metformin, which is known to reduce insulin resistance in HIV-infected patients  and has been shown to reduce CVD events in non-HIV-infected patients (UKPDS) . Moreover, metformin is widely available, has a long established safety record, and is inexpensive.
CAC score is a measure of atherosclerotic heart disease; elevated CAC scores signify a greater risk of predicted coronary heart disease [21,22]. Several studies have evaluated CAC scores among HIV-infected patients. Fitch et al.  recently demonstrated that HIV-infected men with metabolic syndrome had significantly higher CAC scores compared with HIV-infected and non-HIV-infected controls. Similarly, Mangili et al.  found presence of CAC to be significantly more common among HIV-infected men and women with metabolic syndrome compared with HIV-infected individuals without metabolic syndrome.
We saw an effect of metformin to prevent a significant increase in CAC and calcified plaque volume over 1 year of follow-up. We stratified for antiretroviral therapy use, which did not differ between groups. Compliance with the medication was good by pill count. Safety and tolerance were good.
The increase in CAC of 43 in patients receiving placebo without LSM is clinically significant and represents a median change of 56%. This data highlights the natural history of plaque progression over 1 year in HIV patients with metabolic syndrome. Recent data from the Multi-Ethnic Study of Atherosclerosis (MESA) study, showing a 26% increase in coronary events for a doubling of CAC , put this increase in context and suggest a significant increase in CVD risk based on progression of CAC in the untreated HIV population. These data extend the data of Guaraldi et al.  who demonstrated HIV infection was independently associated with a CAC score increase of 15% or more per year. The magnitude of this increase in CAC score shown in our study confirms the urgent need to develop effective therapies to prevent CVD in this group of patients and suggests that chronic use of metformin in this population might prevent significant coronary atherosclerosis if a similar degree of prevention was multiplied over several years. The effect of metformin on CAC was seen within the entire cohort and also among those individuals with demonstrated calcium at baseline. Indeed, the MESA study tells us that the participants who demonstrate any CAC are at higher risk for CVD . Demonstration of a significant effect of metformin to prevent plaque progression in this subgroup is an important observation of our study. Future studies limiting enrollment to participants with demonstrated CAC at baseline will be important to assess treatment effects in those at the highest risk.
One potential mechanism by which metformin could affect plaque progression is via AMP-kinase (AMPK) activation. AMPK has a distinct role to regulate fatty acid oxidation and cholesterol in the heart . Also, activation of AMPK may phosphorylate and inhibit HMG-CoA reductase activity, reducing cholesterol levels ; therefore, some beneficial vasoprotective and cardioprotective effects that are more commonly recognized to be induced by statins may also be related to AMPK activation in vascular tissues.
In contrast to metformin's effect to prevent progression of CAC and calcified plaque volume, we did not see a significant effect of metformin on cIMT, another measure of subclinical atherosclerosis. One possible explanation for this finding is that development and progression of atherosclerosis may occur via different mechanisms within the vasculature . As a result, thickening of the carotid arteries and deposition of calcium in the coronary arteries may be influenced by different factors and represent different stages in the atherosclerotic process. For example, Mangili et al.  recently showed that progression of cIMT in the common carotid in HIV was related to age, waist circumference, triglycerides and insulin, whereas CAC progression was related more specifically to insulin resistance. Metformin effects on insulin sensitivity may contribute in part to differential effects on cIMT and CAC, although further studies are needed to understand these relationships. We assessed the common carotid artery and it is possible that different results would have been seen had we assessed different segments, including the internal carotid and bifurcation, areas in which HIV infection has recently been shown to be more highly associated with increased cIMT [31,32].
LSM had a lesser effect to prevent plaque progression than metformin. Although numerous studies have been performed assessing various LSM regimens in HIV patients, they differ in scope of intervention, target population, duration of treatment, and compliance achieved [33–38], and none, to our knowledge, have assessed the effects on CAC or atherosclerotic indices. In this study, we modeled our lifestyle program after the Diabetes Prevention Program (DPP) , and added a standardized aerobic and strength training component. Compliance was reasonable, even over 1 year of three times per week sessions. Anticipated improvement in exercise parameters, including VO2max, duration of exercise, and all strength parameters were seen, demonstrating the efficacy of the exercise program. To our knowledge, the DPP did not assess whether LSM improved cIMT in their study. In the current study, we demonstrate that LSM had a beneficial effect on HDL-cholesterol, IMCL, hsCRP and tended to improve PAI-I, a marker of impaired fibrinolysis. We did not see an effect on triglyceride. These finding are in accordance with other studies evaluating LSM in this population [35,40]. Although it is possible that a more rigorous LSM program would have resulted in better results on CAC and cIMT, the program we used is well established and did result in anticipated effects on exercise parameters and aerobic capacity as well as a number of metabolic parameters. Moreover, there was no relationship between change in VO2max or other exercise parameters and cIMT or CAC.
IMCL is elevated [41–43] and has been associated with measures of insulin resistance in HIV-infected patients . We are not aware of prior longer term studies demonstrating an effect of LSM on IMCL in HIV-infected patients, and now show that LSM significantly reduces IMCL in this population.
Elevated CRP has been associated with risk for diabetes and CVD and has been found to be elevated among HIV-infected patients [44,45]. Exercise may reduce markers of inflammation through inhibition of adipocytokine production via effects on skeletal muscle, endothelial cells, and the immune system. In our study, LSM significantly reduced CRP. This finding is similar to studies among non-HIV-infected patients evaluating LSM and CRP [46,47]. Among HIV-infected patients, Lindegaard et al.  found a significant effect of endurance training to decrease CRP, whereas resistance training did not induce the same effect.
Our study has limitations but a number of strengths. The study is randomized, placebo-controlled and of a relatively long duration demonstrating a robust effect of metformin to prevent plaque progression. The study had adequate power to show a significant effect of metformin to reduce CAC and calcified plaque volume, but was relatively small in size and may have been underpowered to assess effects on secondary endpoints and to assess the effects of LSM, which were more modest than metformin. Moreover, the sample size may have limited our ability to determine differences in dropout rates. To minimize any effects of dropout, we performed sensitivity analyses carrying forward baseline data and imputing missing data and showed similar results. Despite these limitations, the study is the first to demonstrate the potential utility of metformin to prevent a very significant, progressive increase in calcified plaque progression among HIV-infected patients with metabolic syndrome. LSM was effective to increase fitness and improve selective metabolic indices, but did not prevent progression of atherosclerosis as much as metformin. Further studies are now needed to understand the mechanisms of metformin to prevent calcified plaque progression and to determine whether metformin, alone or in combination with other strategies, might reduce or prevent CVD events in this population.
We gratefully acknowledge the participants in the study, the nurses and dieticians on the MGH General Clinical Research Center.
Funding was provided by NIH R01 DK49302 and by NIH M01-RR-01066 and 1 UL1 RR025758–01, Harvard Clinical and Translational Science Center, from the National Center for Research Resources.
Conflicts of interest
There are no conflicts of interest related to this work. S.G. has received research funding from Theratechnologies and Bristol Meyers Squibb and consulted for Theratechnologies and EMD Serono, unrelated to this work.
Clinical Trial Registration: Unique Identifier: NCT00399360.
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