Since it was first described in 1998 (1,2), abnormal fat distribution in HIV-1–infected patients, now termed lipodystrophy, has been studied intensively in an effort to understand its epidemiology and pathophysiology. Several retrospective cohort analyses, including our own (3–10), have found associations with host factors such as patient age, gender, and race; the severity of HIV-1 disease as assessed by CD4 T-lymphocyte counts or viral loads; history of AIDS; and the use and duration of antiretroviral drugs (11–16). In addition, a number of laboratory studies have suggested the possible interaction of antiretroviral medications with several enzymes or hormones associated with lipid metabolism (17–20), mitochondrial toxicity of nucleoside reverse transcriptase inhibitor (NRTI) drugs (21–29), insulin resistance associated with protease inhibitor (PI) drugs, and cytokine dysregulation (30). Despite these multiple hypotheses, the pathophysiologic mechanisms of lipodystrophy and the role of antiretroviral drugs remain unclear.
We perceive several methodologic problems with previous clinical-epidemiologic studies of lipodystrophy. The first is that all studies to date have evaluated the time period after the introduction of highly active antiretroviral therapy (HAART) regimens. This necessarily makes associations between lipodystrophy and any specific antiretroviral drug or class of drugs as well as associations with HIV-1 infection in the pre-HAART era difficult to assess. A second problem is that many previous studies have not differentiated between abnormal fat accumulation (lipoaccumulation) and abnormal fat loss (lipoatrophy). Lipoatrophy is the primary manifestation of this syndrome and is the most stigmatizing and resistant to therapeutic interventions. Lipoaccumulation has most recently been associated with the metabolic syndrome (31). Thus, the various manifestations of lipodystrophy may not all be the same syndrome, and different mechanisms are likely to contribute to fat accumulation versus fat loss. Finally, some studies have controlled for CD4 T-lymphocyte counts and viral loads in an effort to study the association of specific antiretroviral drugs with lipodystrophy. This precludes the ability to study the contribution of these disease factors to this syndrome.
To address these issues, we performed a prospective analysis of the risk factors associated with lipodystrophy. This analysis focused only on patients who had no lipoatrophy at an initial survey who did or did not develop moderate or severe superficial fat loss at a second survey about 2 years later.
The HIV Outpatient Study
The HIV Outpatient Study (HOPS) has been described elsewhere (32). This dynamic cohort includes HIV-1–infected persons seen at eight clinics specializing in the treatment of HIV in seven cities (Philadelphia, PA; Tampa, FL; Oakland, CA; Washington, DC; Chicago, IL; Stony Brook, NY; and Denver, CO). The physicians at these sites routinely care for over 2500 HIV-1–infected patients every year. Data from ongoing physician-patient interactions are electronically collected and submitted for central processing and analysis. These data include demographic characteristics, symptoms, diseases, treatments, and laboratory values. More than 5900 HIV-1–infected ambulatory (nonhospitalized) patients have been seen in approximately 115,000 outpatient visits to their HIV clinicians since 1992. The ethical conduct of this study undergoes yearly review by federal (Centers for Disease Control and Prevention), contractor (Cerner Corporation), and local institutional research review boards of the eight clinics.
Incidence of Lipoatrophy
In the initial survey, patients seen at HOPS sites between October 1 and December 31, 1998 were evaluated for physical evidence of fat maldistribution (lipodystrophy). A total of 1077 patients were voluntarily surveyed for signs of lipodystrophy, which were then verified by physician examination. This process was repeated again with 1244 patients seen at HOPS clinics between July 1 and September 30, 2000, who were again evaluated by their physicians using a second survey that included information collected in a manner identical to the first survey (3). Five hundred forty-six patients were seen at both surveys, and these patients are the basis of this analysis of incident lipoatrophy.
We used the same criteria for evaluating superficial fat loss as in the previous analysis (3). Three body areas were evaluated for lipoatrophy at both surveys: superficial fat loss (thinning) of the extremities, thinning of the hips/buttocks, and sunken cheeks. Each sign was graded, first by the patient and then by physician examination, as “subtle” (noticeable only if specifically looked for, no change in clothing fit), “moderate” (easily noted by patient or physician, clothing has become loose), or “severe” (obvious to the casual observer, has required a change in clothing size). The final severity rating for each sign was based on patient and physician agreement. In most instances, there was agreement between the patient and the physician. If there were disagreements, they were often minor, with the physician's assessment prevailing. For this analysis, patients were categorized with moderate to severe lipoatrophy if they had either one severe sign or two or more signs with at least one moderate or severe sign.
Lipoatrophy, localized superficial fat loss, is clinically (visually) distinct from HIV wasting, which reflects total body weight loss. To base this analysis on objective criteria, we verified that patients with moderate or severe lipoatrophy by Survey 2 did not have significantly different changes in weight than the control group.
To enhance our ability to find true factors associated with the development of lipoatrophy and to limit the possibility of finding factors with only weak or spurious associations, two important conditions were required for this analysis. First, only patients with absolutely no signs of lipoatrophy at the first survey were included in the analysis, and, second, a dichotomous outcome was used, comparing patients who had developed moderate or severe lipoatrophy at the second survey with those who had no signs or only mild physical signs of lipoatrophy.
Laboratory values (including CD4 T-lymphocyte counts and percentages and plasma HIV-1 RNA), height, weights, HIV/AIDS status, history of and current opportunistic infections and other illnesses, and drug treatment history were obtained from the HOPS database.
Specific factors examined for their associations with the appearance of significant new atrophy included demographic factors (age, HIV transmission risk group, race/ethnicity, gender, study site); use of antiretroviral drugs both by class (NRTIs, non-NRTIs [NNRTIs], and PI drugs) and individually; HIV-1 disease characteristics such as time since HIV or AIDS diagnosis; immunologic factors throughout the clinical course of each patient, particularly CD4 T-lymphocyte count and percentage; CD8 T-lymphocyte count and percentage; CD4:CD8 ratio; virologic factors measured by HIV-1 plasma RNA; and body mass index (BMI).
Analyses were performed using a standard statistical package (SAS Version 6.12; SAS Institute, Cary, NC, U.S.A.). Univariate analyses of potentially related factors were performed as an initial review. To assess associations with new lipoatrophy, the χ2 test was performed for each categoric variable and the nonparametric Kruskal-Wallis test of medians was used for each continuous variable. The incidence of lipoatrophy may vary by clinic site because of the differences in populations seen at the sites (33) and by interobserver variability (despite analysis of only moderate or severe changes). Accordingly, all multivariate analyses were performed both with and without site as a variable. Distributions of values for explanatory variables measured as continuous (e.g., time since AIDS diagnosis, Survey 2 CD4 T-lymphocyte count) were examined, and corresponding categoric variables were created using clinical and statistical criteria. Some variables were constructed to categorize severity of HIV-1 infection over a particular time period better, using combinations of both nadir and peak values of certain variables during a specific time period (e.g., pre-HAART CD4 categories “all values <100 cells/mm3,” “minimum <100 cells/mm3,” or “maximum 350+ cells/mm3”).
Because both age and Survey 2 CD4+ T-lymphocyte count were strongly associated with incidence of lipoatrophy, stratified analyses were performed on all other categorized variables adjusting for those factors. For the analysis of the relationships between each potentially related factor and presence of moderate/severe lipoatrophy, Cochran-Mantel-Haenszel (CMH) χ2 tests for grouped data were performed, controlling for race (white/nonwhite) and Survey 2 CD4 T-lymphocyte count (less than 100, 100–199, 200–349, 350 cells/mm3 and over).
There was “colinearity” among many of the variables shown in the stratified analyses to be related to lipoatrophy, because many variables reflect the same underlying quality of disease severity. Logistic regression models were constructed to assess further the existence of associations found in categoric analyses while adjusting for a large number of correlated effects. Variables that appeared to have an association in the stratified analysis were entered into multivariate models; models with various combinations of variables were compared to evaluate the significance of each factor and the fit of the model. To estimate relative risk for variables where risk increased across each level, categoric variables were used. For some comparisons, risk factors were further categorized into dichotomous groups.
Of the 546 patients seen at both surveys, 337 (61.7%) had no lipoatrophy at Survey 1, but 44 (13.1%) of them developed moderate/severe lipoatrophy by the second survey. (Persons with “mild” [equivocal] lipoatrophy at Survey 2 were considered not to have developed lipoatrophy and were categorized with those who had no lipoatrophy.) The median time between the two surveys was 20.01 months (range: 19.12–21.29 months).
In this incidence analysis, we found similar host and disease factors to those we had seen in our previous prevalence analysis of lipodystrophy [lipoatrophy, lipoaccumulation, or both (3)], except that the drug factors found in that earlier prevalence analysis were not seen in this specific study of lipoatrophy. Risk factors for incident lipoatrophy in unadjusted analyses (Table 1, left side) included clinic site, increasing age, and white race as well as severity of HIV-1 infection as measured by presence of AIDS diagnosis; absolute values, percentages, and ratios of CD4 and CD8 T-lymphocyte counts at any time since infection; HIV-1 plasma RNA (“viral load”); and BMI.
Many of these factors are related to one another (“colinear”), so we analyzed them against one another (data not shown). When stratified by CD4 T-lymphocyte count at Survey 2, lipoatrophy rates in white and nonwhite patients still differed significantly. Age greater than 40 years was not statistically significant (OR = 1.34, 95% CI: 0.67–2.70, p = .48) at any CD4 stratification. BMI <24 kg/m2 at Survey 2 (OR = 2.43; 95% CI: 1.14–5.35;p = .024) and gain in CD4 cell count from nadir value to Survey 2 <50 cells/mm3 (OR = 2.73; 95% CI: 1.03–6.97;p = .038) are each statistically significant factors even when controlling for Survey 2 CD4 T-lymphocyte count, race, and age.
All measurements of disease severity, such as CD4 T-lymphocyte count <100 cells/mm3 (p < .001) or viral load >10,000 copies/mL (p = .022), were statistically significant when considered individually. The strongest significant factor for new atrophy was CD4 T-lymphocyte count at Survey 2. Also, those patients whose nadir CD4 T-lymphocyte counts did not improve with treatment were more likely to develop lipoatrophy. Other measures of disease severity, even if significant in multivariate models, did not add much more predictive power to the incidence of lipoatrophy than measurements of Survey 2 CD4 T-lymphocyte counts (see Table 1).
Patients with low CD4 T-lymphocytes cell counts at Survey 2 were more likely to have low CD4 T-lymphocyte cell counts at earlier points in time. We also found statistically significant differences in lipoatrophy rates based on nadir CD4 T-lymphocyte cell counts on record over the 6 years prior to the second survey. When evaluated over time, lower CD4 T-lymphocyte cell counts were consistently associated with a higher incidence of lipoatrophy and were the strongest predictor of its development. Nadir CD4 T-lymphocyte cell counts <100 cells/mm3 dating as early as 1994 were predictive of which patients (individual patients could be represented in more than 1 year) were more likely to develop lipoatrophy during the period of time between our two surveys (OR = 2.42; 95% CI: 1.76–3.33;p < .001) (Table 2, Fig. 1). Changes in CD8 T-lymphocyte counts and percentages were not statistically different for 126 patients with mild or no lipoatrophy compared with 14 who had moderate/severe lipoatrophy (median decline: −349 cells/mm3 vs. −201.5 cells/mm3; Kruskal Wallis test, p = .20).
Those patients who had low CD4 T-lymphocyte cell counts (<100 cells/mm3), low BMIs (<24 kg/m2), and higher viral burdens (plasma HIV RNA >1000 copies/mL) at any time in their illness were more likely to develop fat atrophy than those with less advanced HIV-1 infection (see Table 2). These relationships held throughout the subject's HIV course whether present at pre-HAART, Survey 1, or Survey 2 time points. We distinguished lipoatrophy from HIV wasting syndrome clinically. In addition, the change in weight between the two surveys was not statistically different between the two groups of patients (p = .065).
We also attempted to address the influence of other clinical illnesses on those subjects who developed lipoatrophy. During the period of study, we identified five diagnoses in the cohort that could have led to weight loss and influenced our results. These included Mycobacterium avium infection, renal failure, pneumonia, depression, and reactive airway disease. In the lipoatrophy group, 18.2% (8/44) were diagnosed with these illnesses, whereas 40.8% (120/197) of the group with no lipoatrophy carried these diagnoses (OR = 0.32; 95% CI: 0.13–0.75;p = .004).
Nevertheless, and in distinction to our prevalence study of lipodystrophy (both atrophy and accumulation), there was no association of any antiretroviral medication with superficial fat loss (Table 3). When evaluating for total time on drug, time of drug initiation, drug continuation, and drug discontinuation, we could find no clear relationship to the incidence of lipoatrophy. To clarify these conflicting data, we evaluated the time on and use of antiretroviral medications with the nondrug-associated factors mentioned above to better understand the relationship of drug factors to the nondrug factors. When controlling for time on any individual drug or class of drug, the incidence of lipoatrophy was consistently higher in persons with nadir CD4 T-lymphocyte counts <200 cells/mm3 at any time in their illness regardless of the length of time on antiretroviral drugs (OR = 2.91; 95% CI: 1.38–6.25;p = .003) (Fig. 2).
There is now an emerging appreciation that various host, disease, and medication factors are associated with lipodystrophy (34). Our two surveys permitted us to explore the factors associated with the incidence of lipoatrophy in a prospective manner in a large cohort of patients. Additionally, we were able to evaluate the course of the disease over a continuum that antedated the use of HAART through the time of the second survey. In this analysis, several findings were strongly associated with lipoatrophy and are noteworthy of further research.
Severity of disease, mainly as determined by low CD4 T-lymphocyte count, was consistently and strongly associated with lipoatrophy in both the previous prevalence study (3) and this incidence analyses. An in-depth analysis of changes from Survey 1 to Survey 2 brought to light several issues that may influence how we approach our understanding of the pathophysiology of this syndrome.
Throughout the course of HIV infection, lower CD4 T-lymphocyte counts and percentages were associated with a higher incidence of lipoatrophy. Likewise, patients with a history of AIDS were more likely to have fat loss. Additionally, individuals with low CD4 T-lymphocyte counts (<100 cells/mm3) as early as 1994 were more likely to develop lipoatrophy in subsequent years. After medications are later given that reverse the progression of HIV infection and prolong life, the syndrome may become clinically apparent. Whether this is due to the viral infection itself or to factors associated with immune reconstitution such as cytokine dysregulation has yet to be established. Perhaps specific clones of CD4 or CD8 T-lymphocytes are destroyed as the HIV infection advances. When antiretroviral therapy is then administered, those remaining clones of T lymphocytes may proliferate and produce unopposed proinflammatory cytokines (e.g., tumor necrosis factor alpha) that may influence lipolysis or adipose tissue apoptosis.
We did not find a statistically significant difference between the two groups when evaluating the CD8 T-lymphocyte cell counts, percentages, and change from peak value to Survey 2 value. This analysis was limited by the small number of patients that could be evaluated, because a few HOPS sites did not obtain CD8 T-lymphocyte cell values on some of the patients.
Kotler et al. (35) have found that HIV-1–infected patients have lower indices of subcutaneous fat, both pre- and post-HAART, than uninfected controls. In those individuals treated with HAART, fat distribution was significantly associated with viral load but not with CD4 T-lymphocyte counts or with antiretroviral therapy. These findings argue in favor of an HIV-1–induced syndrome.
These findings suggest that factors associated with more advanced HIV disease predispose individuals to later development of this syndrome and that initiation of antiretroviral therapy in less advanced HIV disease may minimize the risk of development of lipoatrophy.
This finding has not been reported in other studies on lipoatrophy and can be explained in several ways. Some previous studies controlled for CD4 T-lymphocyte counts and viral loads in an attempt to study the effect of antiretroviral agents on lipodystrophy (8–10,13–16). They also did not distinguish between those patients who had previous CD4 T-lymphocyte count nadirs that were extremely low versus those who never had counts lower than those measured at the time of the study. Other studies analyzed patients with higher median CD4 T-lymphocyte counts, potentially excluding those individuals who may have been more likely to develop lipoatrophy (4). This would limit a complete analysis of the disease-related factors. None of the studies have reviewed the entire history of CD4 T-lymphocyte counts or viral loads during the course of HIV-1 infection, particularly the time period antedating HAART, with the exception of the Lipodystrophy Case Definition Study, which found a strong statistical association with the “lowest ever” CD4 T-lymphocyte count (36).
We have continued to find an association of fat loss with white race. This relationship is difficult to analyze owing to the diversity of sociologic, attitudinal, and cultural factors concerning the disease and adherence to its treatment as well as possible pharmacogenomic differences. Further analysis in this study is not possible; however, the racial differences observed in this study were not explained by other factors we analyzed.
Analyses of BMI are more difficult due to the question of previous wasting and its relationship to lipoatrophy. Although we associate wasting with loss of total body fat and lean body mass and lipoatrophy with loss of superficial fat, we found that individuals with a previously low BMI prior to the initiation of HAART were more likely to develop lipoatrophy. Low CD4 T-lymphocyte count and BMI could easily be associated with HIV wasting syndrome. Although we had strict definitions to define lipoatrophy, as distinct from wasting, this methodology may not be entirely accurate. We did review the bioelectric impedance analyses on a small subset of patients in this study both with and without lipoatrophy who had these studies performed at the time of the two surveys for other reasons and did not find results consistent with wasting (33).
It has not been clear whether the fat loss is due to preexisting damage to adipocytes or mechanisms that regulate adipocyte metabolism, mitochondrial toxicity, or cytokine dysregulation or whether fat atrophy is the result of a direct toxicity of medications. Although we attempted to evaluate the association of specific medications with the development of lipoatrophy, we could not find a statistically significant association in either the stratified or multivariate analysis. Our study suggests that HIV infection or factors associated with immune reconstitution may play a greater role in the development of lipoatrophy than the use of any specific medication. It does not rule out the possibility, however, that the medications may exacerbate an underlying predisposition to lipoatrophy induced by the disease or its response to treatment.
Our findings do not preclude a toxic effect of antiretroviral therapy. They do suggest that the disease-related factors may be more influential than the medications. It is possible that those individuals predisposed to lipoatrophy may not necessarily manifest it clinically without the additive influence of the medications.
In our initial prevalence study, stavudine and indinavir were associated with lipodystrophy. Yet, the penetrance of these drugs in the study population was 80% for stavudine and 82% for indinavir. We have previously questioned whether this association was more likely to be a direct effect or a “colinear” relationship, making it difficult to factor in the contribution of either of these drugs. The findings in this study suggest that a direct effect is less likely. We were unable to demonstrate any association with use or duration of time on any individual drug or class of drug with the incidence of lipoatrophy.
This study is unavoidably limited by several factors. Because much of the clinical data was collected retrospectively, it was not possible to use measurements or imaging techniques to confirm our clinical assessments. Although some researchers have investigated anthropometric measurements, DEXA scans, and computed tomography (CT) for assessing lipodystrophy (15,35), none of these methods has actually been standardized or accepted as an improvement over clinical diagnosis of this syndrome. Anthropometric measurements have not been reliably reproducible in multisite studies. On the other hand, the Lipodystrophy Case Definition Study (36) used clinical definitions and methods similar to our own and found a correlation with anthropometric, CT scan, and DEXA scan measurements (36). Despite their limitations, they are currently the best methods we have to date to corroborate clinical assessments of lipoatrophy.
Subjects who were seen by their treating physicians in the two study periods when the surveys were conducted may have been included in the study due to an unmeasured selection bias; this process limited the number of patients (337) available for study. Despite this limitation, the consistent and incremental associations with our measures of CD4 T-lymphocyte counts over time, our inability to demonstrate these relationships with antiretroviral drugs, and the strong ORs described here are unlikely explained by these unavoidable and unmeasured biases.
Also, the design of this study may have introduced an additional selection bias. The patients who were selected for the analysis were those subjects who had no lipoatrophy at the time of the first survey. This naturally precluded the study of individuals who had developed the syndrome earlier. It is possible that those individuals may have developed the syndrome for other reasons, such as previous opportunistic infections or exposure to other medications, that our study population did not experience. Whether this selection bias influenced the results of this study cannot be determined.
In our previous study, we found that in the absence of “nondrug” factors, generalized lipodystrophy did not occur (3). In retrospect, those “nondrug” factors consisted primarily of measurements of severity of illness (CD4 T-lymphocyte counts, viral load, and BMI). This specific analysis indicates a strong relationship of incident lipoatrophy to these measures of severity of HIV-1 infection and a weak or unmeasurable relationship to specific medications or classes of antiretroviral drugs. These findings suggest the need for a re-evaluation of the current consensus regarding the development and management of lipoatrophy.
The HOPS Investigators include the following investigators and sites: Anne C. Moorman, Tony Tong, and Scott D. Holmberg, Division of HIV/AIDS Prevention, National Center for HIV, STD, and TB Prevention (NCHSTP), Centers for Disease Control and Prevention (CDC), Atlanta, GA; Kathleen C. Wood and Rose K. Baker, Cerner Corporation, Vienna, VA; Frank J. Palella, Joan S. Chmiel, Maria Deloria Knoll, Barbara Gillespie, and Erin Nekervis, Northwestern University Medical School, Chicago, IL; Kenneth A. Lichtenstein, Kenneth S. Greenberg, Benjamin Young, Barbara Wideck, Cheryl Stewart, and Peggy Zellner, Denver Infectious Disease Consultants, Rose Medical Center, Denver, CO; Bienvenido G. Yangco, Kalliope Halkias, and Cheryl Lapierre, Infectious Disease Research Institute, Tampa, FL; Douglas J. Ward and Charles A. Owen, Dupont Circle Physicians Group, Washington, DC; Jack Fuhrer, Linda Ording-Bauer, Rita Kelly, and Jane Esteves, State University of New York (SUNY), Stony Brook, NY; Ellen M. Tedaldi and Linda Walker-Kornegay, Temple University Hospital, Philadelphia, PA; Joseph B. Marszouk, Roger T. Phelps, and Mark Rachel, Adult Immunology Clinic, Oakland, CA; Robert E. McCabe and Mark Rachel, Fairmont Hospital, San Leandro, CA; and Richard M. Novak, Jonathan P. Uy, and Andrea Wendrow, University of Illinois at Chicago, Chicago, IL. The authors also acknowledge the patients in this study for their willingness to give their time to participate in the HOPS.
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