Fat Distribution in Men With HIV Infection (FRAM)
From the Study of Fat Redistribution and Metabolic Change in HIV Infection (FRAM)
JAIDS Journal of Acquired Immune Deficiency Syndromes: Volume 40(2) 1 October 2005 pp 121-131. Results were previously reported at conferences by Carl Grunfeld, University of California, San Francisco Veterans Affairs Medical Center, Metabolism Section.
".....Both peripheral and central subcutaneous lipoatrophy was found in HIV infection. Lipoatrophy in HIV-positive men is not associated with reciprocally increased VAT.... we find evidence for a syndrome of subcutaneous lipoatrophy in HIV-infected men, with lower body depots affected more than upper body depots.... Furthermore, HIV-infected men who did not have the clinical syndrome of peripheral lipoatrophy also had less SAT in the legs, lower trunk, and upper trunk than controls.....Although increased VAT is not statistically associated with decreased adipose tissue in the periphery, individual patients may have high VAT and low subcutaneous fat......"
38% of HIV-positives in this study had 1 or more reported sites of lipoatrophy. HIV-infected men were more likely to have peripheral lipoatrophy in at least one site compared with controls (38% vs. 5%; P < 0.001). HIV-infected men commonly had multiple sites of peripheral lipoatrophy, whereas this was uncommon in controls. More HIV-infected men than controls had clinical central lipoatrophy (8% vs. 3%, P = 0.03, although this finding was less common than peripheral lipoatrophy. In contrast, controls were more likely to have lipohypertrophy at one or more sites, be they central or peripheral. Of note, these are the approximate percentages of fat loss in HIV+ individuals in specific body parts found in this cross-sectional study: cheeks 23%; face 19%; arms 11%; buttocks 20%; legs 19%. The percentages in HIV-positives were much higher than control individuals used in the study. About 30-35% of HIV-positives had fat accumulation in the waist/abdominal area, but interestly the controls had a significantly higher percentage of fat in these areas. 50-55% of HIV-positives reported fat gain in the waist & abdominal areas, but control study participants reported fat gain in these areas equally or greater in percent.
Factors Associated With Leg SAT and VAT
Finally, we assessed whether similar factors were associated with leg SAT (the most affected subcutaneous depot) and VAT (an important central depot that is associated with metabolic changes) in HIV-infected men by a multivariate model that included CD4 cell count, HIV RNA level, and ARV therapy duration, as well as the non-HIV-related predictors used above. The effects of race, smoking, and physical activity all followed known patterns in the general population.43 Of note, age was associated with less leg SAT, but more VAT, in HIV-infected subjects. Higher current HIV RNA levels were associated with more leg SAT but did not appear to be associated with VAT. Duration of use of stavudine was strongly associated with less leg SAT, as was that of indinavir. There was a trend for an association of duration of use of didanosine with less leg fat. However, stavudine and indinavir were not associated with more VAT. No ARV was estimated to have a substantial positive association with VAT; the largest point estimate for an ARV was much smaller in magnitude than those for race, age, or physical activity. In contrast, duration of nevirapine use was associated with less VAT. There were no apparent associations with any ARV class or HAART after adjusting for stavudine and indinavir for leg SAT or nevirapine for VAT.
See EDITORIAL following main study report.
Received for publication May 17, 2005; accepted August 4, 2005.
Supported by National Institutes of Health grants RO1-DK57508, HL74814, HL 53359, and AI 027767 and NIH GCRC grants M01-RR00036, RR00051, RR00052, RR00054, RR0636, and RR00865. The funding agency reviewed the study design but played no role in collection, management, analysis, or interpretation of the data or in preparation of the manuscript. NIH personnel participated as members of the CARDIA Publications Committee that reviewed and approved the manuscript.
Objective: Both peripheral fat loss and central fat gain have been reported in HIV infection. Which changes are specific to HIV were determined by comparison with control subjects and the associations among different adipose tissue depots were determined.
Methods: Cross-sectional analysis of HIV-positive and control men from the study of Fat Redistribution and Metabolic Change in HIV Infection. Lipoatrophy or lipohypertrophy was defined as concordance between participant report of change and examination. Regional adipose tissue volume was measured by magnetic resonance imaging (MRI).
HIV-positive men reported more fat loss than controls in all peripheral and most central depots. Peripheral lipoatrophy was more frequent in HIV-positive men than in controls (38.3% vs. 4.6%, P < 0.001), whereas central lipohypertrophy was less frequent (40.2% vs. 55.9%, P = 0.001).
Among HIV-positive men, the presence of central lipohypertrophy was not positively associated with peripheral lipoatrophy (odds ratio = 0.71, CI: 0.47 to 1.06, P = 0.10).
On MRI, HIV-positive men with clinical peripheral lipoatrophy had less subcutaneous adipose tissue (SAT) in peripheral and central sites and less visceral adipose tissue (VAT) than HIV-positive men without peripheral lipoatrophy.
HIV-positive men both with and without lipoatrophy had less SAT than controls, with legs and lower trunk more affected than upper trunk.
Use of the antiretroviral drugs stavudine or indinavir was associated with less leg SAT but did not appear to be associated with more VAT; nevirapine use was associated with less VAT.
Conclusion: Both peripheral and central subcutaneous lipoatrophy was found in HIV infection. Lipoatrophy in HIV-positive men is not associated with reciprocally increased VAT.
Our study demonstrates that HIV-infected men who had the clinical syndrome of peripheral lipoatrophy had less adipose tissue in each peripheral and central depot than HIV-infected men without peripheral lipoatrophy. Furthermore, HIV-infected men with or without the clinical syndrome of peripheral lipoatrophy had less adipose tissue in both peripheral and central subcutaneous sites compared with control subjects, with lower body more affected than upper body using direct measurements of adipose tissue volume. Clinically, HIV-infected men were more likely to have peripheral lipoatrophy than controls, but they also had more central lipoatrophy and less central lipohypertrophy. The findings from self-report also show that loss of fat in peripheral and most central subcutaneous depots distinguished all HIV-infected men from controls. Furthermore, use of stavudine or indinavir was associated with less leg SAT, but the use of these drugs did not appear to be associated with more VAT.
Thus, our results argue against the proposals in earlier reports of a reciprocal syndrome of lipodystrophy in which peripheral fat loss is accompanied by central fat gain, including increased VAT. Likely reasons for these differences between our study and prior reports include our use of bidirectional scales (most studies only inquired about peripheral fat loss and central fat gain6,11,12,15,17,21,23,24,29-32,34), our highly accurate regional measurements of affected adipose tissue depots, and the comparison of HIV-infected men with a control group. A recent study of anthropometric measurements in HIV-infected and control men also found that waist, hip, arm, and thigh circumferences were lower in HIV-infected men compared with HIV-negative controls, although their examiners reported more fat accumulation in the abdomen.38
Our study evaluated the associations between peripheral fat and central fat without assuming a link between loss of peripheral fat and gain of central fat. We found that peripheral lipoatrophy was not associated with central lipohypertrophy, whether determined by self-report, examination, or concordance. Furthermore, measurement by MRI found that the clinical syndrome of peripheral lipoatrophy was not associated with increased VAT. Finally, the factors associated with leg SAT were not the same as those associated with VAT. For example, the use of stavudine or indinavir was associated with less leg SAT. In contrast, neither of these ARVs appeared to be associated with more VAT. Nevirapine use was associated with less VAT. Combining findings that are inversely correlated with each other (peripheral lipoatrophy and central lipohypertrophy) could lead to misunderstandings of their prevalence, causes, and consequences.
Our finding that leg fat was much lower in HIV-infected men compared with controls, whereas upper trunk fat was relatively spared, may explain the proposed association of peripheral lipoatrophy with central lipohypertrophy.11-13,15,17,18,20,21,23,24,29-32 Furthermore, the finding that even HIV-infected men without clinical peripheral lipoatrophy had less SAT in most depots than controls, especially in the legs and lower trunk, suggests that the clinical syndrome of lipoatrophy underestimates the extent of adipose tissue loss in HIV-infected men. Indeed, the qualitative comparisons vs. controls were similar among HIV-infected men both with and without the clinical syndrome, differing only in the extent of decreased fat. In both HIV-infected groups, lower body adipose tissue depots were affected more than upper body depots or VAT (Fig. 5).
We found evidence against any reciprocal increase in VAT in HIV-infected with peripheral lipoatrophy; indeed VAT was slightly lower in HIV-infected with peripheral lipoatrophy compared with HIV-infected without peripheral lipoatrophy. There were positive, not negative, correlations between VAT and SAT in most peripheral depots (data not shown). These results argue against a single syndrome of peripheral fat loss and central fat gain. We found relative sparing of VAT in HIV-infected men with lower quantity of leg SAT, consistent with other smaller studies in HIV infection15,47 and with what is seen with fat loss in cancer and anorexia nervosa.48,49 Although increased VAT is not statistically associated with decreased adipose tissue in the periphery, individual patients may have high VAT and low subcutaneous fat.
Therefore, we used actual adipose tissue volumes in the leg and VAT to assess the associated factors. The findings that stavudine or indinavir use was associated with less leg SAT, but apparently not with more VAT, also supports the contention that HIV-related lipoatrophy is not linked to visceral obesity, thus contradicting the concept of an HIV-specific reciprocal syndrome of fat redistribution. Conversely, older age, a factor unrelated to HIV infection, was associated both with less leg SAT and with more VAT.
Given our findings that HIV-infected men report more fat loss and have lower adipose tissue volumes in most subcutaneous sites than control men, it is not surprising that BMI was lower in HIV-infected men than controls. We did not control for or match by BMI, as BMI is influenced by the phenomenon being studied: quantity of fat. Thus matching for BMI would constitute overcontrolling and could lead to erroneous comparisons. For example, if HIV caused loss of fat in a single depot, with no change in other depots, then BMI matching would lead to an apparent, but artifactual, increase in nonaffected depots. We controlled for body size by normalizing to height squared, analogous to BMI. An alternative way to account for body size while avoiding overcontrolling is to normalize for lean body mass; this analysis produced similar results.
We chose a control group that was representative of whites and African Americans in the United States 15 years earlier, whose BMI is similar to the larger, nationally representative National Health and Nutrition Examination Survey (NHANES) III. BMI in FRAM CARDIA participants is similar to values in the entire CARDIA cohort (data not shown). It is difficult to find control subjects that are identical to HIV-infected men in all aspects except HIV infection. Two recent reports from the Multicenter AIDS Cohort Study (MACS) and the Woman's Interagency HIV Study also found that HIV-infected participants had lower BMI than their HIV-negative controls, who were selected from similar demographic groups.37,38 Both groups reported that lipoatrophy, using anthropometrics, was the dominant feature distinguishing HIV-infected men from controls. In the MACS report, demographically matched HIV-negative subjects had average BMI that was higher than the national average in NHANES III.38 The controls in FRAM have a BMI that is closer to that of the subjects in NHANES. Thus the finding of lower BMI in HIV-infected subjects may be common. Furthermore the similarity of conclusions from comparing HIV-infected men with clinical lipoatrophy and HIV-infected men without lipoatrophy, as well as comparing HIV-infected men with controls, provides strong support for the concept that peripheral lipoatrophy is not linked to central lipohypertrophy. Finally, multivariate adjustment for differences in race, illicit drug use, food adequacy, smoking, and other factors that differed between groups found that such factors did not appear to account for the differences in body composition between HIV-infected men and controls.
There are several limitations to our data. We report only on men here. This is a cross-sectional study, so further changes in adipose tissue distribution may occur over time. However, the study was done approximately 5 years after the introduction of highly active ARV therapy, which is more than adequate time to see the syndromes studied by others. It is not possible to determine what regional body composition would have been in the HIV-infected group in the absence of HIV infection or the syndrome of lipoatrophy.
In summary, we find evidence for a syndrome of subcutaneous lipoatrophy in HIV-infected men, with lower body depots affected more than upper body depots. There is no association of peripheral lipoatrophy with central lipohypertrophy or increased VAT; our use of bidirectional scales and rigorous measurements produces findings that argue against the existence of a single syndrome with reciprocal changes in fat. Compared with controls, the similar pattern of decreased fat seen in HIV-infected men both with and without the clinical syndrome of lipoatrophy suggests that the clinical syndrome of lipoatrophy represents only the most severely affected group of the spectrum. Finally, ARV drugs that were associated with lipoatrophy, as assessed by volume of subcutaneous adipose tissue in the leg, did not appear to be associated with central lipohypertrophy, as assessed by volume of VAT. Thus, these data suggest that future research studies of fat distribution in HIV-infected persons should focus on subcutaneous lipoatrophy and that direct measurements of regional adipose tissue (rather than surveys or subjective examination) should be used to determine cause and associated metabolic findings.
HIV-infected and control men had similar age ranges and percentage of whites; both groups included significant numbers of African Americans, but the HIV-infected cohort included other ethnic groups. Mean height was 2% lower, weight 15% lower, and BMI 11% lower in the HIV-infected men than in control subjects. The dominant HIV risk factor for men was having sex with men. HIV RNA and CD4 counts spanned the full spectrum of HIV infection.
Lipoatrophy and Lipohypertrophy by Self-Report, Examination, and Concordance
Figure 1A shows that more HIV-infected men than control subjects reported fat losses in the peripheral sites: cheeks, face, arms, buttocks, and legs (all P < 0.001). Half of fat loss changes reported in HIV-infected men were mild. Likewise, for central sites, higher proportions of HIV-infected men than control subjects reported decreases in waist size and chest fat and possibly neck and upper back fat. These results indicate that a significantly greater proportion of HIV-infected men lost fat in peripheral and central sites compared with control men.
Some HIV-infected men reported gain in fat (50%). However, the prevalence of fat gain was significantly lower in HIV-infected men than controls in most central and peripheral sites.
Findings on examination were similar to those from self-report (data not shown). Using the commonly accepted standard of self-report confirmed by physical examination, clinical lipoatrophy was more prevalent in all peripheral sites in HIV-infected men than in controls. HIV-infected men were also more likely to have lipoatrophy in the central site of abdominal fat and possibly neck, but the prevalence of central lipoatrophy was much lower than in the periphery. With regard to clinical lipohypertrophy defined as concordance of self-report and examination, HIV-infected men had less lipohypertrophy in the neck, chest, abdomen, waist, cheeks, face, arms, and buttocks compared with controls.
We then separately assessed the prevalence of lipoatrophy and lipohypertrophy at any peripheral or central site. HIV-infected men were more likely to have peripheral lipoatrophy in at least one site compared with controls (38% vs. 5%; P < 0.001). HIV-infected men commonly had multiple sites of peripheral lipoatrophy, whereas this was uncommon in controls. More HIV-infected men than controls had clinical central lipoatrophy (8% vs. 3%, P = 0.03), although this finding was less common than peripheral lipoatrophy. In contrast, controls were more likely to have lipohypertrophy at one or more sites, be they central or peripheral.
MRI Measurement of Regional Adipose Tissue Volumes
Because peripheral lipoatrophy was the most common characteristic that distinguished HIV-infected men from control subjects and because peripheral lipoatrophy has been reported as a distinct clinical syndrome, we compared adipose tissue volume measured by MRI in HIV-infected men with and without clinical peripheral lipoatrophy and controls. Compared with HIV-infected men without peripheral lipoatrophy, HIV-infected men with clinical peripheral lipoatrophy had less SAT in peripheral depots of legs and arms, but they also had less SAT in central depots of the lower trunk/abdomen and upper trunk/chest, and possibly VAT. The findings were similar when adipose tissue volume was adjusted per lean body mass rather than height (data not shown).
HIV-infected men with clinical lipoatrophy had less adipose tissue than controls in all depots. Furthermore, HIV-infected men who did not have the clinical syndrome of peripheral lipoatrophy also had less SAT in the legs, lower trunk, and upper trunk than controls. When adipose tissue volume was adjusted per lean body mass rather than height, the findings were similar, except that median VAT volumes, although following the same pattern, were closer together and differences did not reach statistical significance (data not shown).
We also performed an analysis controlling for factors unrelated to HIV infection that might contribute to differences in body composition among HIV-infected men and controls (including lean body mass, age, race, physical activity, and substance abuse) by multivariate adjustment. The amount of adipose tissue adjusted remained significantly lower in all depots in HIV-infected men with peripheral lipoatrophy compared with controls (Fig. 5). HIV-infected men who did not have lipoatrophy also had significantly less adipose tissue in lower trunk, leg, and possibly VAT than controls. HIV-infected men who did not have lipoatrophy had similar upper trunk fat compared with controls and possibly more arm fat. Thus even after adjustment for these factors and lean body mass, there is no evidence for a reciprocal increase in VAT in HIV-infected men with peripheral lipoatrophy.
Is Clinical Peripheral Lipoatrophy Associated With Central Lipohypertrophy?
The findings that HIV-infected men with the clinical syndrome of peripheral lipoatrophy have less adipose tissue volume in central sites than HIV-positive men without peripheral lipoatrophy suggested that there was no association of peripheral lipoatrophy with central lipohypertrophy in men with HIV infection. We found evidence against such an association using multiple approaches. First, the amount of adipose tissue measured by MRI in most sites was positively correlated with the amount of adipose tissue in most other sites regardless of whether the sites were peripheral or central, or whether correlations were examined among HIV-infected men with peripheral lipoatrophy, HIV-infected men without peripheral lipoatrophy, or control subjects (data not shown). An interesting exception was that there was no correlation between leg SAT and VAT in HIV-infected men with peripheral lipoatrophy (r = 0.00, P = 0.99); men with low leg SAT had a wide range of VAT.
Likewise, loss of fat in individual peripheral sites by self-report was associated with loss of or less gain in fat at central sites (data not shown). Similarly, less fat in individual peripheral sites on examination was associated with less fat in central sites. Among HIV-infected men, the presence of the clinical syndromes of central lipohypertrophy and peripheral lipoatrophy had no positive association with each other (OR: 0.71, CI: 0.47 to 1.06, P = 0.10). In contrast, the presence of central lipoatrophy was strongly associated with peripheral lipoatrophy (OR: 18.9, CI: 5.7 to 63, P < 0.0001).
The protocol was approved by institutional review boards at all sites. HIV-infected subjects were selected from coded lists of patients seen in 16 HIV or infectious disease clinics or cohorts during 1999. Each list was randomly ordered and grouped into blocks of 5 potential subjects. Sites were given sets of blocks; only after extensive recruitment efforts by multiple methods were completed for a block was a new block provided. Analyses of female participants are incomplete and will be reported subsequently. Of 2094 male patients active in the HIV clinics, 414 did not answer multiple contact attempts; 154 were dead; 269 were ineligible (institutionalized, n = 23; communication difficulty, n = 37; primary care provider refused, n = 13; or excluded by study criteria, n = 196 [age <18 years; factors prevented imaging: weight >136 kg, height >6'5, metal in body, claustrophobia]). The remaining 1257 eligible men were approached for informed consent. Of those, 279 declined participation and 163 did not return for data collection. Examinations were completed from June 2000-January 2002 on 825 men (65.6% of 1257 contacted and eligible).
Control subjects were recruited from 2 centers of the Coronary Artery Risk Development in Young Adults (CARDIA) study.39,40 CARDIA subjects were originally recruited as a population-based sample of healthy 18- to 33-year-old white and African American men and women from 4 cities in 1986 for a longitudinal study of cardiovascular risk factors. Participants in the CARDIA study were stratified for the 2 races and genders. Of 377 participants who agreed to the year 15 CARDIA examination who were approached to participate in FRAM, 339 (90%) agreed to participate; 28 (7%) did not return for examination; and 14 (4%) were excluded from FRAM for factors preventing imaging. HIV testing was not done in the CARDIA cohort, but the prevalence of HIV infection was estimated to be <1% based on previous data, and no CARDIA participant was taking an ARV medication.
Here we report findings for the 425 HIV-infected men and 152 control men in the 33- to 45-year age range; we excluded 11 HIV-infected men who had an opportunistic infection or malignancy within the same or previous calendar month as the examination, to remove confounders of acute changes in fat.
The HIV-infected and control groups underwent identical standardized questionnaires and examinations performed by uniformly trained research associates (completion rate >99%). Each subject was asked to report whether he had had any change in fat over the past 5 years in the cheeks next to the nose, lateral aspect of the face, legs, arms, buttocks (peripheral sites), back, chest, neck, or abdomen or change in waist size (central sites). If subjects answered yes, they were asked whether the change was an increase or decrease and to grade it as mild, moderate, or severe. Subjects could also answer No change or Don't know. Don't know represented <10% of responses and was pooled with No change. Research associates were asked to determine whether subjects had more or less fat compared with normal healthy people in each of those body areas, rating amount of fat using criteria from the HIV Outpatient Study (HOPS): mild = only seen if looked for; moderate = easily seen; severe = obvious immediately.20
Clinical lipoatrophy at each anatomic site was defined as concordance between participant report of loss of fat (mild, moderate, or severe) and examination finding of less fat than a normal healthy person at the same anatomic site. Lipohypertrophy was defined as concordance of self-report of increased fat and examination finding of more fat than normal at the same site.
Physical activity, alcohol intake, smoking, illicit drug use, education, and adequacy of food intake were assessed by standardized instruments.40-43 Research associates interviewed HIV-infected subjects and reviewed medical charts to determine the dates of use of individual ARV medications. Blood was drawn for determination of CD4 cell counts and HIV RNA by polymerase chain reaction, which were measured in a single laboratory (Covance, Indianapolis, Indiana).
Height and weight were measured. Body composition was measured by MRI with subjects in the supine position, arms extended over head.44 Using the intervertebral space between the 4th and 5th lumbar vertebrae as origin, transverse images (10-mm slice thickness) were obtained every 40 mm from hand to foot. MRI scans were segmented using image analysis software (Tomovision, Inc., Montreal, Canada). Tissue areas (cm2) were calculated by summing specific tissue pixels, then multiplying by individual pixel surface area. Volume per slice (cm3) of each tissue was calculated by multiplying area by thickness. Volume of each tissue for the space between 2 consecutive slices was calculated via a mathematical algorithm.45 Volumes were normalized by dividing by height2 with summaries back-transformed to 1.75 m of height. We did not adjust to body mass index (BMI), as BMI is influenced by the phenomenon being studied: quantity of fat. However, we also analyzed adipose tissue volume adjusted to the subject's total lean body mass. Ninety-two percent of participants had MRI performed. Eleven percent of scans had at least one body area outside the field of view. When a single limb was outside the field of view, volume in the measured limb was doubled to obtain total limb volume. Using this method we quantified adipose tissue volume in the leg, lower trunk (abdomen and back), upper trunk (chest and back), arm, and VAT.
For prevalence, P values were calculated by Fisher exact test. Numerical values were compared by Mann-Whitney U test, which can produce small P values even when confidence intervals for medians overlap. Associations between dichotomous variables were quantified by odds ratios (ORs) from logistic regression models and those between numeric variables by rank correlations.
Multivariate analysis was performed to determine whether factors unrelated to HIV infection and its therapies could account for observed differences in MRI measures between the control and HIV-infected groups with and without clinical peripheral lipoatrophy. Separate analyses were performed for each of the following 5 anatomic sites: visceral, legs, lower trunk, arms, and upper trunk. For each anatomic site, separate comparisons were made of control subject vs. HIV infected with lipoatrophy and control vs. HIV infected without lipoatrophy. These models were fitted to logarithmic transformations of MRI measures to produce estimated percentage differences in amounts of adipose tissue. To control for body size, we included logarithm of total lean mass by MRI as a predictor in all models. This appeared to have nonlinear associations with adipose tissue volume in some depots, so we also included the square of log lean mass to model this nonlinearity. Results were very similar when we instead used height to control for body size. We note that controlling for BMI would not be appropriate, because BMI includes the outcomes being modeled as part of its definition. Variables controlled for in the models include the following: age, ethnicity, smoking, alcohol intake, illicit drug use (crack/cocaine, marijuana, heroin, and speed), adequacy of food intake, and level of physical activity. As the purpose of these analyses was to examine possible changes in the estimated HIV effects, we included a relatively more expansive set of variables than would be appropriate for building predictive models. Variables selected included those that had P < 0.05 in preliminary (unbootstrapped) multivariate models for any of the 5 anatomic sites considered, along with some that had high a priori plausibility as potential confounders. Confidence intervals were determined using the bias-corrected accelerated bootstrap method,46 with P values defined as the one minus the highest confidence level that still excluded zero. This was necessary both because many outcome measures appeared to be non-Gaussian, even after log transformation, and to control for multiple important predictors.
Multivariate analyses were separately performed to determine which factors related and unrelated to HIV infection were predictive of lipoatrophy as assessed by leg SAT or of lipohypertrophy as assessed by VAT in HIV-infected subjects. To control for body size, we adjusted for logarithm of total lean mass by MRI as described above. Confidence intervals were constructed for the estimated percentage differences from the multivariate models using the bias-corrected accelerated bootstrap model as described above. In addition to the predictors listed above, these models included HIV RNA level (log 10) and CD4 count (log 2) at the time of study visit. In multivariate models controlling for the above factors, we evaluated total duration of use of each individual ARV drug and ARV class: nucleoside reverse transcriptase inhibitor (NRTI), nonnucleoside reverse transcriptase inhibitor (NNRTI), protease inhibitor (PI), and highly active antiretroviral therapy (HAART) as defined by ≥2 NRTIs in combination with at least one PI or NNRTI; one NRTI in combination with at least one PI and at least one NNRTI; a regimen containing ritonavir and saquinavir in combination with one NRTI and no NNRTIs; or an abacavir-containing regimen of ≥3 NRTIs in the absence of both PIs and NNRTIs. We checked linearity by fitting more complex models using linear splines, finding that linearity appeared reasonable in all cases. Duration of each ARV, ARV class, and HAART was added to the model in a forward stepwise manner, and results for ARV not reaching P < 0.05 are shown controlling for those that did.
Morphologic Changes in HIV-Infected Men: Sorting Fact From Fiction
JAIDS Journal of Acquired Immune Deficiency Syndromes
1 October 2005
Khara, Milan MD, CCFP; Conway, Brian MD, FRCPC
From the University of British Columbia, Department of Anesthesia, Pharmacology and Therapeutics and Vancouver Coastal Health, Vancouver, British Columbia, Canada.
Reprints: Brian Conway, University of British Columbia, Department of Anesthesia, Pharmacology and Therapeutics, 201-1200 Burrard Street, Vancouver, British Columbia, Canada V6Z2C7 (e-mail: email@example.com).
In 1996, the availability of highly active antiretroviral therapy (HAART) revolutionized the model of care for HIV infection. It was hypothesized that the consistent use of such therapy could lead to a cure for this condition in as little as 3 years,1 but subsequent research soon showed this model to be incorrect.2 In addition, long-term use of HAART has now been associated with significant metabolic and morphologic abnormalities, which may lead to unintended morbidity.3 Accordingly, current recommendations for antiretroviral therapy have become more conservative. Indeed, it is now believed that a well-monitored individual with chronic HIV infection and a CD4 count of >350 cells/mL can safely delay initiation of HAART.4 Some would further argue that delaying treatment until the CD4 count approaches 200 cells/mL has little, if any, clinical consequences.5
Of the adverse effects associated with HAART, those that have received the most attention in the lay HIV press are the changes in body shape. These were first called Crix belly, in that an apparent increase in subcutaneous abdominal fat was seen in patients on long-term indinavir therapy.6 Very quickly, the development of lipodystrophy was associated with all protease inhibitors.7 Syndromes of fat loss were also described, and a combination of fat loss in the limbs and fat accumulation in the abdomen was described as typical of patients on chronic antiretroviral therapy.8 Given enough time, this disfiguring change in body habitus was described by some as inevitable as death and taxes!
This syndrome of lipodystrophy (often graphically depicted at medical meetings and in journals) inspired fear and led some of our patients to make unwise decisions regarding the initiation of HAART for fear of being irreversibly disfigured. As we tried to make sense of the reports in the lay and scientific press, we were hampered by a lack of systematic evaluation of this phenomenon of fat loss and accumulation, and a lack of complete understanding of the mechanism of these changes. Although the second issue has not yet been entirely resolved, the paper by Grunfeld et al9 in this issue of JAIDS goes a long way towards describing what the syndrome is, and what it is not.
This study compares fat distribution in 425 HIV-infected men and 152 control men, aged 33-45 years at the time of their evaluation. All subjects were asked to describe whether they had noticed any changes in fat distribution in their bodies over the previous 5 years, and whether this was a mild, moderate, or severe increase or decrease. Subjective findings were confirmed by clinical examination and magnetic resonance imaging. In attributing any changes to concomitant HIV infection or its treatment, a number of variables known to affect fat distribution were controlled for in the models. The key finding was that a significantly greater proportion of HIV-infected men lost peripheral and central fat compared to control men, and that this was mild in half or more of the cases. There was no reciprocal increase in visceral fat. In fact, fat accumulation was more prevalent in the control group. Fat loss was associated with the use of stavudine and indinavir, but no other antiretroviral agents. There was no association of fat accumulation with any HAART components, except that nevirapine perhaps exerted a protective effect.
So what can we make of this? In a group of HIV-infected individuals primarily composed of men who have sex with men, the main morphologic abnormality observed in 2000-2002 was lipoatrophy. This was associated with the long-term use of indinavir (a finding of largely historical value) or stavudine (a finding that may soon be of historical value). Fat accumulation is not reciprocally associated with peripheral fat loss, nor does it even seem to be a long-term feature of HIV infection, with or without treatment. These findings are robust for a number of reasons. Bi-directional scales of evaluation were used, allowing patients to report both fat loss and fat gain, thus avoiding a bias towards the evaluation of a specific type of change, as might be obtained by asking a yes/no question about abdominal obesity, for example. Self-reported data were cross-referenced with objective measurements to confirm their validity. A carefully matched control group of sufficient size was used to help establish what was truly attributable to HIV infection or HAART. A particularly insightful approach was to not control for body mass index (BMI) in the analysis. HIV-infected patients have lower BMIs. If one had a localized lipoatrophy in a single location, it may be that controlling for BMI might lead to the interpretation of the other sites where no fat loss has occurred as artificially enlarged and lead one to conclude that fat accumulation were present. Controlling for lean body mass (as was done here) avoids this pitfall while making the groups comparable. This strategy is one of the key reasons the study was able to conclude that even in the earlier HAART era, fat accumulation was not as prevalent as we believed at the time.
This study is most applicable to homosexual/bisexual men who received the first and second generations of HAART regimens. It is unclear how these data would apply to women, intravenous drug users, or those receiving non-nucleoside-based combinations containing nucleoside agents other than stavudine. The observation that nevirapine is associated with less fat accumulation is an interesting finding, one that is in keeping with the favorable metabolic profile seen in patients taking this agent.10 It would be interesting to see how some of the newer protease inhibitors such as atazanavir would fare in such a comparison.
One of the key lessons from this rigorous observational study is that there is no single morphologic syndrome in which an individual develops fat loss in the limbs and face and fat accumulation in the abdomen. This is not to say that the latter phenomenon does not exist, but we should cease trying to develop a single pathophysiologic explanation for all the physical changes that are observed. We should focus our efforts on the phenomenon of lipoatrophy, which appears to be far more common. Whether this will still be the case in an era where both indinavir and stavudine are used sparingly-if at all-remains to be seen. However, now that we know what we are looking for and how to best measure it, we can not only more clearly establish which patients have it before we even start therapy, but we can also determine who seems to be developing it most rapidly after HAART is started (and which of these patients may wish to change some element of their regimen in response to this, given that the reversibility of the changes is not assured). Finally, the methodology of Grunfeld et al shows us the way in terms of evaluating if this phenomenon still exists in the new HAART era, how prevalent it is, and what may be causing it. Hopefully, this will lead to the identification of the biochemical mechanism of the observed changes, and how they can be prevented or treated. We can now reassure our patients that we know what we are looking for, and that we are working on how to make sure it doesn't happen to them.