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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Clin Nutr. Author manuscript; available in PMC 2009 December 23.
Published in final edited form as:
PMCID: PMC2797483

Evaluation of high-protein supplementation in weight-stable HIV-positive subjects with a history of weight loss: a randomized, double-blind, multicenter trial1,2,3



HIV patients with wasting are at increased risk of opportunistic complications and fatality.


We hypothesized that augmenting dietary intake with high-biologic-value protein would enhance weight and lean tissue in weight-stable subjects with a prior unintentional weight loss of >3%.


Fifty-nine subjects with HIV RNA concentrations <5000 copies/mL were randomly assigned to receive a 280-kcal supplement containing 40 g whey protein or a matched isocaloric control supplement without added protein twice daily for 12 wk.


Before the study, intake of total energy and protein exceeded estimated requirements (44.3 ± 12.6 kcal • kg−1 • d−1 and 1.69 ± 0.55 g • kg−1 • d−1, respectively). Both supplements failed to increase total energy intake because of decreases in self-selected food intake. Changes in weight (0.8 ± 2.4 and 0.7 ± 2.4 kg) and lean body mass (0.3 ± 1.4 and 0.3 ± 1.5 kg) did not differ significantly between the whey protein and control groups, respectively. Waist-to-hip ratio improved more with whey protein (−0.02 ± 0.05) than with the control (0.01 ± 0.03; P = 0.025) at week 6 but not at week 12. Fasting triacylglycerol increased by 39 ± 98 mg/dL with the control supplement and decreased by 16 ± 62 mg/dL with whey protein at week 12 (P = 0.03). CD4 lymphocytes increased by 31 ± 84 cells/mm3 with whey protein and decreased by 5 ± 124 cells/mm3 with the control supplement at 12 wk (P = 0.03). Gastrointestinal symptoms occurred more often with whey protein.


A whey protein supplement did not increase weight or lean body mass in HIV-positive subjects who were eating adequately, but it did increase CD4 cell counts. The control supplement with rapidly assimilable carbohydrate substituted for protein increased cardiovascular disease risk factors. Careful dietary and weight history should be obtained before starting nutritional supplements in subjects with stable weight loss and good viral control.


In patients with HIV, weight loss ≥5% is associated with increased risk of morbidity and mortality (1, 2). HIV wasting has declined in the era of highly active antiretroviral therapy (HAART) (35). However, data from the Nutrition for Healthy Living (NFHL) cohort, which enrolled 713 participants between 1995 and 2003, showed that HIV wasting remains common during HAART with nearly one-third of the cohort meeting the case definitions of wasting (1). Recent data from the NFHL cohort showed a 50% increase in the 6-mo risk of ≥5% unintentional weight loss during HAART in 1998–2003 compared with 1995–1997 (6). Although reversal of wasting may occur with HAART (7), lean tissue gain is often modest (810). Finally, patients who fail to respond to HAART are at risk of recurrent wasting, because HIV RNA concentrations have been shown to correlate with the magnitude of weight loss (11, 12).

Efforts to replete body mass in HIV patients have included strategies to enhance energy intake via parenteral and enteral feeding (1321). Few controlled studies have evaluated dietary supplements (22, 23) and even fewer have focused on intake of protein—a primary substrate for the synthesis of important functional tissues. Some HIV patients with stable weight reported consuming large amounts of energy but were unable to fully restore lost weight (24, 25). Furthermore, protein intake but not energy intake has been correlated with metabolically active body cell mass (26). Thus, the failure to regain weight or lean tissue may be partly due to inadequate or low-quality protein intake.

In other catabolic conditions, positive nitrogen balance is achieved by increasing protein intake well in excess of the Recommended Dietary Allowance (RDA) (0.8 g • kg−1 • d−1) while maintaining energy intake in the physiologic range (2729). During renal failure, negative nitrogen balance was improved by increasing protein intake to 1.5–2.0 g • kg−1 • d−1 but not by increasing nonprotein intake to 40 kcal • kg−1 • d−1 at a protein intake of 0.8 –1.0 g • kg−1 • d−1 (30). In patients with burns or sepsis who achieve positive nitrogen balance, providing excess nonprotein energy increased resting energy expenditure (31, 32) and fat deposition (32) without further augmentation of LBM. Similarly, hypercaloric feeding by total parenteral nutrition in AIDS patients resulted in weight gain that was almost entirely composed of fat (14).

In HIV, convenient and palatable dietary supplements can increase total energy intake (3337). Supplementing protein intake may improve nitrogen balance and protein synthesis (3739). Furthermore, providing amino acids such as glutamine may increase body cell mass in AIDS wasting (19). We tested the hypothesis that providing supplements containing substantial high-biologic-value whey protein (undenatured milk protein, containing all essential and nonessential amino acids and rich in glutamine and cyst(e)ine) to increase protein intake to 1.5–2.0 g • kg−1 • d−1 would enhance lean tissue accrual in HIV-infected subjects.



The study population consisted of subjects with confirmed HIV-1 infection and stable weight loss, which was defined as prior unintentional weight loss >3% over the course of the HIV-1 infection, but no change in weight >3% during the 2 mo before enrollment. Additional entry criteria included no evidence of active opportunistic complications or evidence of malabsorption and HIV RNA concentrations <5000 copies/mL, but HAART was not required. The study was approved by the institutional review board at each participating site, and all subjects provided written informed consent before enrollment. All aspects of the study were conducted in accordance with the Helsinki Declaration of 1975 (revised in 1983).

Study regimen

After study entry, the subjects were randomly assigned to receive 1 of 2 twice daily study regimens: a high-protein supplement containing 40 g whey protein, 20.5 g carbohydrate, and 4.0 g fat per 280-kcal serving or an isocaloric control supplement without the added protein, which contained 0.6 g casein (protein), 60.8 g carbohydrate (high-maltose rice syrup solids), and 4.0 g fat per 280-kcal serving (Biomune Systems Inc, Salt Lake City, UT). The isocaloric control supplement was similar to the whey protein supplement in color, texture, and taste (mango flavored). Both supplements were to be taken twice daily between meals for 12 wk; thus, the supplements were intended to increase total daily energy intake by 560 kcal. All subjects and study personnel were blinded to treatment assignment.

Outcome assessments

In addition to the baseline visit, subjects were interviewed and examined by a study physician, and outcome data were collected at weeks 6 and 12. Body-composition measures were collected or calculated and included standardized height and weight measured with a calibrated scale while subjects were wearing underwear and a gown, body mass index (BMI; weight in kilogram/height squared in meters), absolute and percent LBM, and fat by single-frequency bioelectrical impedance analysis (BIA; RJL Quantum, Clinton Township, MI). For BIA, study coordinators were certified in electrode placement and body positioning during central training at AIDS Clinical Trials Group (ACTG) meetings. Fat and LBM were calculated by using published equations validated in HIV-infected and HIV-uninfected subjects (40). Anthropometric measurements included waist, thigh, and hip circumferences according to standardized ACTG procedures. Self-reported food intake was assessed by standardized ACTG data collection instruments. In brief, 3-d written food intake diaries were administered and reviewed by certified dietitians for verification of entries and portion sizes before centralized calculation of total energy and macronutrient intakes with Nutritionist V software (First Databank Inc, San Bruno, CA).

Blood was collected after an overnight fast for lipids, glucose, insulin, routine chemistries, complete blood counts, CD4 lymphocyte counts, HIV RNA concentrations, and total testosterone concentrations in men at the local clinical laboratories before study interventions. Insulin concentrations were determined in specimens during batch testing at Quest Diagnostics Laboratory (San Juan Capistrano, CA). Fasting glucose and insulin were used to calculate static markers of insulin sensitivity, namely the homeostasis model assessment of insulin resistance (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI), which are correlated with insulin sensitivity measured with the hyperinsulinemic euglycemic clamp (41, 42).

Statistical considerations

The study plan was to accrue 56 subjects to provide an 80% probability of detecting, at the 5% significance level, a clinically relevant mean difference of 1.6 ± 2.0 kg in change in LBM from baseline to study week 12 between the 2 dietary intervention groups, assuming a 10% loss to follow-up. The primary endpoint used the change in LBM from baseline to study week 12. Differences between the 2 study arms were evaluated by using a Wilcoxon’s rank-sum test for comparing medians from 2 continuous distributions. The same test was used to evaluate changes in the remaining continuous measurements. Wilcoxon’s signed-rank test was used for within-group comparisons. We also analyzed the primary endpoint using the repeated-measures analysis (PROC MIXED procedure in SAS). In this analysis, we considered both the actual LBM values over time as well as the changes in LBM. Either Fisher’s exact test or Pearson’s chi-square test was used to evaluate the differences with respect to the discrete variables, depending on a number of categories of a discrete variable. Estimates of SD and interquartile range were given for means and medians, respectively. Times to treatment discontinuation between the 2 study groups were compared by using the log-rank test.

Evaluation of the primary endpoint was done by using an intention-to-treat analysis. Results of the “as-treated” analysis are reported as well. In cases of subjects missing the week 12 measurements needed for the primary endpoint evaluation, the value was extrapolated by carrying forward the week 6 measurements. Subjects missing both postbaseline values were deemed ineligible for the analysis of the primary endpoint.

Statistical analyses were performed by using the SAS statistical package (software release 8.2; SAS Institute Inc, Cary, NC). The figure was created by using R Computing Environment (


Sixty subjects from 15 ACTG study sites were enrolled in this multicenter trial from February to December 1999. Of the 59 subjects randomly assigned to this double-blind study (there was one inadvertent enrollment of a subject who did not meet entry criteria), 29 subjects received the supplement containing whey protein and 30 received the control supplement. The 2 study groups were well balanced with respect to demographic characteristics at baseline (Table 1). The median age for the 7 women and 52 men was 41 y. Most of the subjects were white (66%), and 52 (88%) reported no prior use of intravenous drugs. The 2 groups were also balanced at baseline with respect to CD4 count, Karnofsky performance status, and 3-mo prior antiretroviral treatment, although one subject in the control group was not receiving antiretroviral therapy. The CD4 counts ranged from 33 to 1263 cells/mm3 (median = 344 cells/mm3), and 85% of subjects had a Karnofsky score of 90 or 100. Overall, the median HIV-1 RNA level was 400 copies/mL (range: <50 to 3196 copies/mL).

Baseline characteristics of the study population1

There were 35 subjects (15 treated with whey protein and 20 treated with the control supplement) who had extensively documented weight histories covering up to 50 wk before baseline. In this group, there was no difference (P = 0.67) in the median change in weight during the pretreatment period from the respective whey protein group [0.2 kg; interquartile range (IQR):−0.6, 0.7) and control group (0.5 kg; IQR: −0.9, 1.0), providing evidence of weight stability.

Of 59 eligible subjects, 41 subjects completed the study treatment: 17 in the whey protein arm and 24 in the control group. There was no evidence to suggest that the duration of treatment differed between the 2 study arms (P = 0.17). Five subjects in the whey protein group discontinued the study treatment prematurely because of protocol-defined toxicities. An equal number of subjects in the 2 treatment arms discontinued the treatment because of nonprotocol-defined, low-grade toxicities or clinical events. One subject in the whey protein group stopped the treatment because of the use of a prohibited medication, and another subject stopped treatment because they disliked the taste. Finally, in the whey protein group, 15 subjects had at least grade II gastrointestinal symptoms (eg, nausea, vomiting, bloating, cramps, or diarrhea) compared with 7 subjects in the control group (P = 0.03).

Body-composition measures at baseline and study weeks 6 and 12 are shown in Table 2. For the primary outcome, there was no difference in the change in LBM between the whey protein (0.2 ± 1.4 kg) and control (0.3 ± 1.3 kg) groups after 6 wk (P = 0.76, Wilcoxon’s rank-sum test). After 12 wk of study therapy, the respective changes were 0.3 ± 1.4 and 0.3 ± 1.5 kg (P = 0.61) in the 2 groups. Furthermore, there was no change in LBM across the time points by repeated-measures analyses. Similarly, the respective changes in total weight of 0.7 ± 1.8 and 0.7 ± 1.5 kg for the 2 groups at study week 6 were not significantly different (P = 0.96) nor were the changes of 0.8 ± 2.4 and 0.7 ± 2.4 kg at study week 12 (P = 0.63). For fat, the respective changes were 0.4 ± 1.2 and 0.3 ± 0.8 kg for the 2 groups at study week 6 (P = 0.33) and 0.5 ± 1.6 and 0.4 ± 1.7 kg at study week 12, respectively (P = 0.40). Data for 54 subjects were available for the evaluation of the primary endpoint in the intention-to-treat analysis. For 2 of the 54 subjects who did not have LBM data available from week 12, week 6 results were carried forward to week 12. Similar results were obtained when week 6 data were extrapolated by using a constant slope. The as-treated analysis of the 41 subjects who completed the full 12 wk of study therapy showed no significant changes in LBM between the 2 groups (P = 0.26). These outcomes were also analyzed after women were excluded to determine whether there was a sex effect; all changes remained nonsignificant (all P > 0.10; data not shown) without trends suggesting any benefit in terms of LBM, total weight, or fat. Furthermore, baseline BMI was not related to changes in weight in either group by Spearman correlation (high protein: −0.18, P = 0.36; placebo: 0.32, P = 0.12).

Outcome measures with study intervention

Changes in the variables listed in Table 2 over time were also analyzed by using a repeated-measures analysis with treatment group and time as model terms (PROC MIXED in SAS, with each response variable analyzed separately; Table 2). To examine the presence of interaction, a time-by-treatment interaction term was included in each of the models, but there was no statistically significant interaction in any of the models, possibly because of insufficient statistical power based on the sample size of the groups. Additional analyses showed that there was no statistically significant effect of the treatment groups, but there were significant effects of time for weight, total fat mass, and waist-to-thigh ratio.

Intakes of total energy and macronutrients at baseline and at study weeks 6 and 12 are shown in Table 3 for 17 subjects in the whey protein arm and 24 in the control group who completed the study. As designed, the change in dietary protein intake was greater in the whey protein group than in the control group at week 6 (68.7 ± 40.4 and −7.7 ± 35.6 g/d; P < 0.001) and at week 12 (64.4 ± 45.3 and −27.6 ± 38.5 g/d; P < 0.01), which resulted in a significantly greater total intake of protein per kilogram of body weight in the whey group at both time points. Despite the significant differences in protein intake between the groups, average total daily protein intake remained well above the RDA (Table 3). Also, and as designed, the change in dietary carbohydrate intake at week 6 was lower in the whey protein group (−3.3 ± 109.6 and 85.8 ± 137.6 g/d; P < 0.01), but at week 12 the difference in change was not significant between the groups (−34.4 ± 160.3 and 36.3 ± 108.9 g/d; P = 0.19).

Intake of total calories and macronutrients1

Changes in dietary intake over time were also analyzed by using a repeated-measures analysis, with treatment group and time as model terms (PROC MIXED, with dietary measurements as response variables analyzed separately). To examine the presence of an interaction, the time-by-treatment interaction term was included in each of the 4 models, but there was no statistically significant interaction in any of the models. Again, this result was possibly due to insufficient statistical power. Furthermore, for any of the 4 dietary measures, there was no statistically significant effect of treatment group, but there was a significant (P < 0.01) related effect of time for each of the macronutrients. The same results were reached in the analysis of ranks of the continuous variable in place of the response variable in the model.

As shown in Figure 1, there were no differences in the total intake of energy per kilogram of body weight (includes both self-selected food plus supplements) between the 2 study groups at study week 6 or study week 12 (P > 0.05 for each comparison). Moreover, the change from baseline in total daily energy intake at study week 12 did not differ significantly between the whey protein (177 ± 991 kcal) and control (183 ± 831 kcal) groups (P = 0.12; Figure 1). Although self-selected intake of total energy, protein, carbohydrates, or fat (excludes energy provided by supplements) did not change at study week 6 compared with baseline, and self-selected energy intake decreased less at study week 12 in the whey protein group (−325 ± 1032 kcal/d) than in the control group (−777 ± 818 kcal/d) (P = 0.04). The lack of a significant increase in total energy consumption was due to a decrease in the self-selected energy intake at study weeks 6 and 12 (Figure 1).

Total caloric intake is shown at baseline (week 0) and after 6 and 12 wk of study therapy for the 17 subjects in the whey protein arm and the 24 subjects in the control group who completed the study. Each bar shows the amount of fat, carbohydrate, and ...

Several secondary outcomes were evaluated (Table 2). An evaluation of the paired data at week 6 showed that the waist-to-hip ratio decreased in the whey protein group but increased in the control group (P = 0.025). The waist-to-thigh ratio decreased to a greater extent with whey protein (P = 0.014 compared with control), whereas the thigh-to-waist-to-hip ratio increased to a greater extent in the whey protein group (P = 0.004 compared with control). At study week 12, there were no significant changes in these variables (P ≥ 0.09; Table 2). Fasting serum triacylglycerol in subjects with paired data decreased at week 12 by 16 ± 62 mg/dL in the whey protein group and increased by 39 ± 98 mg/dL in the control group (P = 0.035). There were no significant changes in other lipids, fasting glucose, insulin, HOMA-IR, or QUICKI (data not shown).

Another secondary outcome included assessment of the effects of whey protein on immune function. From baseline to week 12, in subjects in whom paired data were available, those treated with whey protein had an average increase in CD4 lymphocytes of 31 ± 84 cells/mL (P = 0.04), whereas those who received the control supplement had a slight decrease in CD4 lymphocytes of −5 ± 124 cells/mL (P = 0.19). The difference in CD4 changes from baseline to week 12 between the 2 study groups was significant (P = 0.03). The change from baseline to week 12 in CD4 counts was also analyzed with week 0 values as a covariate in a nonparametric analysis of covariance model (PROC GLM in SAS with response variable as ranks). In this analysis, the effect of the treatment group was statistically significant (P = 0.04).


In HIV-infected subjects with stable weight loss, 12 wk of nutritional supplementation with high biologic quality (whey) protein did not increase energy intake, weight, extremity circumferences, or lean tissue more than did an isocaloric, high-carbohydrate, low-protein control supplement. However, many important lessons can be learned from this study. First, for subjects who have reached new weight equilibrium by eating an adequate diet and are not malnourished, dietary supplements alone may not be sufficient to further restore weight or LBM. Such individuals may have selected a level of total energy and protein intake and/or a new activity level sufficient to maintain their body weight in a stable range, albeit below their premorbid weight and lean tissue status. Indeed, before the study intervention began, the subjects’ energy intake (44.3 ± 12.6 kcal • kg−1 • d−1) exceeded the estimated energy requirement, and their protein intake (1.73 ± 0.63 g • kg−1 • d−1) was 2-fold greater than the RDA (0.8 g • kg−1 • d−1) and within the range that achieved positive nitrogen balance in other catabolic conditions (30). It is, therefore, not surprising that the whey protein supplement did not increase weight or lean tissue in these participants, who were habitually consuming more than adequate amounts of protein and energy.

Another important observation was that the increase in carbohydrate intake with the control supplement worsened fasting serum triacylglycerol. The small but significant changes in waist-to-hip, waist-to-thigh, thigh to waist-to-hip ratios at study week 6 also suggested that there was an unfavorable change in body composition (increased central fat) with the high-carbohydrate control supplement, which is predicted to increase cardiovascular disease risk (43, 44). Similarly, in other controlled studies of HIV-infected patients, oral liquid supplements produced increases in fat without an apparent change in lean tissue (33, 34). Thus, even with a relatively short course of therapy, our results suggest that care should be taken when consideration is given to prescribing supplements that increase the intake of carbohydrate, particularly those that are rapidly assimilable, in weight-stable patients who are below their premorbid weights but who also have preexisting cardiovascular disease risk factors such as dyslipidemia, hypertension, impaired glucose intolerance, or insulin resistance (45). Worsening triacylglycerol concentrations, which are highly sensitive to carbohydrate intake, and increasing abdominal girth would be expected to accelerate atherosclerosis in a population already at increased risk of cardiovascular disease morbidity (46).

Of some surprise was the observation that self-selected intakes of energy decreased during treatment with the nutritional supplements. This contrasts with results from other studies of HIV-infected patients, in which nutritional supplementation has increased total daily energy intake (3337). Although we designed the present study to provide supplements between meals, subjects self-selected to consume lower quantities of their regular dietary foods. An important difference may be that most studies of nutritional supplementation are performed in subjects with inadequate nutritional intake, ongoing weight loss, and often preexisting malnutrition in which the nutritional supplement may reduce but does not totally compensate for the increased intake and therefore leads to a net increase in energy intake. The present study was conducted in weight-stable subjects with a history of weight loss, a relatively normal BMI, and adequate intakes of both protein and calories.

These observations emphasize the importance of obtaining a careful weight and dietary history and quantification of total energy and macronutrient intakes (by food diaries, food frequency, or 24-h dietary recall questionnaires) before prescribing nutritional supplements for patients with HIV. Supplements are expensive, and, if energy intake is shown to be sufficient and protein intake is above the RDA, our results suggest that further augmentation of energy or protein intakes is unlikely to improve body composition or nutritional status in a population of weight-stable subjects with relatively well-controlled HIV. Finally, the whey protein supplement was not well tolerated, as evidenced by the greater gastrointestinal symptoms and attrition in this group. This was also reported in another study of relatively asymptomatic HIV patients ingesting 45 g whey protein/d (47). In a population that may already have an excessive medication burden, such symptoms may either adversely affect medication adherence or cause malabsorption of these therapies.

Of importance, subjects treated with whey protein had a significant increase in CD4 lymphocytes compared with those receiving the control supplement. These findings are consistent with other studies of whey protein supplements that produced improvements in immune function, including in mononuclear cell glutathione concentrations (33, 4852). It is possible that the improvement in CD4 counts with the whey protein supplement was related to a regression-to–the-mean because the baseline counts were lower in the whey protein group, albeit not statistically significantly so. Regardless, the potential for benefits in immune status provide additional impetus for testing whey protein in catabolic patients with active weight loss and severe CD4 lymphocyte or intracellular glutathione depletion.

This study had several limitations. In particular, these results should not be extrapolated to other populations, such as those with unstable or active weight loss or those with inadequate intakes of energy and protein, for whom studies should be conducted to establish the efficacy and utility of increasing energy intake largely in the form of high-biologic-quality protein. Indeed, whey protein improved weight by 3.6 ± 2.3 kg and lean tissue by 1.5 ± 1.9 kg as measured by dual-energy X-ray absorptiometry in an open-label study of HIV-infected women with malnutrition (53). Furthermore, we used a convenient, relatively low-tech method, namely BIA, which has proven effective and useful for the assessment of changes in lean tissue in persons with AIDS wasting before the HAART era (54). However, the test has not been validated in wasting populations at risk of or with lipodystrophy (central fat accumulation or peripheral lipoatrophy) before this study. Other methods, such as dual-energy X-ray absorptiometry, magnetic resonance imaging, or computed tomography, may have been more sensitive and accurate in detecting small but significant changes in lean tissue. Similarly, anthropometric measures made by different examiners at the same clinical research center and across multiple clinical sites has inherent limitations because of problems with interobserver variation. Finally, a more palatable formulation of whey protein could have resulted in better adherence with less treatment-limiting toxicities, which allowed more subjects to complete the study. Also, lower doses given for a longer period of time might have affected outcomes differently.

In summary, this randomized controlled study indicated that consumption of a nutritional supplement with high-biologic-quality protein was ineffective in augmenting weight or lean tissue in a weight-stable, HIV-infected population with prior weight loss but who were already ingesting protein at a range shown to increase lean tissue under other catabolic conditions. In addition, the whey protein supplement was associated with greater treatment-limiting symptoms. However, CD4 lymphocyte counts increased significantly with whey protein consumption. The increased intake of rapidly assimilable carbohydrate with the control supplement resulted in short-term increases in fasting triacylglycerol and waist-to-hip ratio—a surrogate for central adiposity. Furthermore, both supplements were ineffective at increasing the intake of total energy because of self-selected decreases in food intake. Thus, a careful weight history and assessment of dietary intake of energy and macronutrients should be undertaken before prescribing nutritional supplements in HIV patients with a history of weight loss.


The authors gratefully acknowledge the study subjects, who committed substantial time and effort to make this study successful. We also gratefully acknowledge the late Robert Zackin, who provided immense support and scientific input for the design and analysis of the study. We also appreciate and recognize the contributions from the participating ACTG clinical research sites: Jane Norris and Sandra Valle (Stanford University; A0501), Robert J Fass and Laura Laughlin (Ohio State University, Columbus, OH; A2301), Diane Havlir and Mark Jacobson (University of California at San Francisco; A0801), Sherry Lassa-Claxton and Donna Marin (Washington University, St Louis, MO; A2101), Luis Mendez and William Briggs (University of Southern California, Los Angeles, CA; A1201), Marshall Glesby and Valery Hughes (Columbia-Cornell, New York, NY; A7803), N Jeanne Conley and T Mac Hooton (University of Washington, Seattle,WA;A1401), Cecilia Shikuma and Debbie Arakaki (University of Hawaii; Honolulu, HI; A5201), Ilene Wiggins and Melody Higgins (Johns Hopkins University, Baltimore,MD;A0201), Marla Werner and Carol Greisberger (University of Rochester, Rochester, NY; A1101), Tulane University (A1701), Judith Feinberg and Diane Daria (University of Cincinnati, Cincinnati, OH; A2401), Jorge Santana and Santiago Marrero (University of Puerto Rico; San Juan, Puerto Rico; A5401), and Sarah Lammer (University of Colorado, Boulder, CO; A6101).


2Supported by the National Institute of Allergy and Infectious Diseases through the Adult AIDS Clinical Trials Group U01 grants (AI20766, AI 69474, AI27663, AI25903, AI27673, AI46386, AI34853, AI27668, AI27658, AI25897, AI34832, and AI32770) and the General Clinical Research Programs, NCRR, M01 grants (RR00070, RR00034, RR00043, RR00083, RR00052, RR00044, and RR00051). Biomune Systems, Inc, provided the whey protein and control supplements.

The authors’ responsibilities were as follows—FRS,KM,KEY, BAS, and BB: responsible for designing the study, monitoring the conduct of the trial for adherence to the protocol and safety, and interpreting the results; NR and RZ: responsible for the analysis of the global data for the project and preparation of data for the manuscript; and AZ and SLK: principal investigators at the ACTG clinical research sites that contributed the most subjects to the study. All authors contributed to the writing and editing of the manuscript. None of the authors had any financial relations with Biomune Systems Inc or any other conflicts of interest.


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