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American Journal of Clinical Nutrition, Vol. 72, No. 3, 809-815, September 2000
© 2000 American Society for Clinical Nutrition


Original Research Communication

Status of selected nutrients and progression of human immunodeficiency virus type 1 infection1,2,3,4

John D Bogden, Francis W Kemp, Shenggao Han, Wenjie Li, Kay Bruening, Thomas Denny, James M Oleske, Joan Lloyd, Herman Baker, George Perez, Patricia Kloser, Joan Skurnick and Donald B Louria

1 From the Departments of Preventive Medicine and Community Health, Pediatrics, and Medicine, the University of Medicine and Dentistry of New Jersey–New Jersey Medical School, Newark.

2 Presented in part at the Keystone Symposia HIV Pathogenesis and Treatment, Park City, UT, March 13–19, 1998 and AIDS Pathogenesis, Keystone, CO, January 7–13, 1999.

3 Supported in part by NIH grant N01-AI-95013 and by Accuhealth, Inc.

4 Address reprint requests to JD Bogden, Department of Preventive Medicine and Community Health, UMDNJ–New Jersey Medical School, 185 South Orange Avenue, Newark, NJ 07103-2714. E-mail: bogden{at}umdnj.edu.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Immune function is highly dependent on nutritional status because the large mass and high rate of cellular turnover of the immune system make it a major user of nutrients. Furthermore, nutrient requirements may be increased during acute and chronic infections, including HIV-1 infection.

Objective: The current study was designed to assess relations among HIV-1 progression and 11 nutritional and demographic variables.

Design: The participants were 106 HIV-infected outpatients and 29 uninfected control subjects (n = 89 men and 46 women; age range: 35–57 y). The HIV-infected subjects represented a broad range of disease progression.

Results: We found lower concentrations of plasma and erythrocyte magnesium and of erythrocyte reduced glutathione beginning early in the course of HIV-1 infection. Significantly decreased hematocrit and increased serum copper concentration developed only late in the course of the disease. Statistically significant univariate associations were found between the CD4+ T lymphocyte count and hematocrit, plasma magnesium concentration, and plasma zinc concentration. The lowest erythrocyte magnesium concentrations occurred in HIV-infected subjects who consumed alcoholic beverages. Independent variables that were significant joint predictors of CD4+ cell count in multiple regression analyses were hematocrit and plasma free choline and zinc concentrations. These 3 factors together explained 43% of the variability in CD4+ cell counts.

Conclusion: The results provide evidence that compromised nutritional and antioxidant status begin early in the course of HIV-1 infection and may contribute to disease progression.

Key Words: HIV-1 infection • HIV infection • AIDS • HIV progression • glutathione • magnesium • hematocrit • choline • copper • zinc • ethanol • alcohol • antioxidants


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
It is well known that nutrition has a profound influence on the immune system. Infections, no matter how mild, have adverse effects on nutritional status. Conversely, almost any nutrient deficiency, especially if sufficiently severe, will impair resistance to infection (1). Furthermore, because the immune system functions as a large organ, its size and high rate of cellular turnover make it a major user of nutrients (2). Thus, it is not surprising that nutritional status can greatly influence the course of an acute or chronic infectious disease, especially a severe, chronic infection such as HIV-1. Causes of compromised nutrition in HIV-infected individuals, even in the early stages of HIV infection, may include anorexia, changes in nutrient absorption, and a high level of immune system activity that depletes nutrients (2, 3).

In the current study, we investigated relations between 9 nutritional or biochemical variables and the progression of HIV-1 infection. The variables were hematocrit, erythrocyte concentrations of magnesium and reduced glutathione (GSH), ethanol consumption, and plasma concentrations of magnesium, copper, zinc, and free and total choline. These variables were chosen because each may independently influence the course of an infectious disease or may be altered by an infection, but few studies have assessed their relation to HIV-1 infection and its progression (1, 36). The objective of the present study was to assess relations between HIV progression and these variables, both individually and jointly in multiple regression models.

This study was based on 2 hypotheses: 1) the status of some nutrients, as assessed on the basis of circulating concentrations, will decline early in the course of HIV-1 infection but will not decline further with disease progression, and 2) the status of other nutrients will change progressively with increasing severity of HIV-1 infection or will only be altered in the late stages of infection.


    SUBJECTS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
The subjects in this cross-sectional study were men and women with HIV-1 infection who were outpatients at either of 2 infectious disease clinics at 2 large hospitals in Newark, NJ. Control subjects of comparable ages were recruited from uninfected friends or relatives of the subjects (n = 12) and hospital and medical school employees (n = 17). A total of 106 HIV-infected and 29 uninfected subjects were enrolled. Subjects responded to a 24-item questionnaire that assessed nutritional and health status and included questions about variables such as height and weight; use of prescription medications; consumption of alcoholic beverages; use of vitamin, mineral, or herbal supplements; and symptoms such as anorexia, fatigue, diarrhea, vomiting, and weight loss during the past year. Informed consent was obtained from all subjects and the study protocol was approved by the New Jersey Medical School Institutional Review Board.

HIV-infected subjects were classified into Centers for Disease Control and Prevention (CDC) stages A, B, or C on the basis of the presence of opportunistic infections or other conditions (7), without regard for CD4+ cell counts. The recruitment goal was >=25 subjects in each category and >=25 uninfected control subjects. Further subdivision of subjects by both CDC stage and CD4+ cell count was not done because this would have resulted in small numbers of subjects in some subgroups, precluding statistical analysis of the laboratory data.

Blood collection and analysis
We collected 15 mL whole blood on one occasion from each participant. Blood samples were delivered to the laboratory within 4 h of collection. Blood for choline and GSH measurements was collected in evacuated tubes (Becton Dickinson & Co, Rutherford, NJ) containing EDTA as the anticoagulant. Blood used for analyses of magnesium, copper, and zinc concentrations was collected into heparin-treated evacuated tubes recommended for trace metal analysis (Becton Dickinson & Co). Hematocrit was determined on the same sample by using a microhematocrit centrifuge. CD4+ T lymphocyte counts of infected subjects were assessed by using fluorescence-activated cell sorting. Serologic status for HIV infection was confirmed by Western blot. Plasma free and total choline concentrations were measured by using a microbiological method as described previously (8). Plasma copper, zinc, and magnesium and erythrocyte magnesium concentrations were measured by using flame atomic absorption spectrophotometry (9, 10). Erythrocyte concentrations of GSH were measured by visible spectrophotometry at 412 nm with the method of Beutler et al (11).

Statistical analyses
The data were analyzed by using the SAS SYSTEM FOR WINDOWS (release 6.12; SAS Institute, Cary, NC) and are presented as means ± SE. Mean concentrations of biochemical variables and other data for stage-of-infection groups (uninfected and disease stages A, B, and C) were compared by using a general linear models approach to analysis of variance (ANOVA). Groups were compared pairwise by using Tukey's studentized range test when the ANOVA indicated a significant overall group effect. Univariate associations between nutrient concentrations and CD4+ T lymphocyte counts were evaluated by calculating Pearson's product-moment correlation coefficients. Multiple regression analyses with forward selection across disease stages A, B, and C were used to determine relations of CD4+ cell counts to the independent variables hematocrit, erythrocyte magnesium and GSH concentrations, ethanol consumption, age, sex, and plasma magnesium, copper, zinc, and free and total choline concentrations. Stepwise and backward-elimination regressions were also conducted to check the consistency of the results from forward selection. Values for male and female subjects were compared by using t tests. The Mantel-Haenszel chi-square test for trend was used to relate the fractions of subjects with low zinc concentrations to increasing disease severity (uninfected through stage C). All P values for the above tests are two-tailed with P < 0.05 considered statistically significant.

For infected participants, we also determined the effects on the 8 biochemical variables of subject-reported changes in appetite or weight, use of vitamin supplements or nutritional drinks, use of antiretroviral medications, and presence of vomiting or diarrhea. These effects were evaluated in pairwise comparisons with t tests. Because 56 comparisons were made, P < 0.02 was considered statistically significant for these comparisons; this was done so that the expected number of type I errors would be {approx}1.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Subject characteristics
Subject characteristics, including infection status and stage, age, sex, CD4+ cell count, and body mass index (BMI, in kg/m2), are shown in Table 1Go. We did not have enough information to classify 2 of the 106 infected subjects into CDC categories, but data from these subjects were used for calculations not involving CDC classification. The range of CD4+ cell counts was broad, from 1 to 1129 x 106 cells/L. Infected male and female subjects had similar mean BMIs (24.7 ± 0.5 and 24.7 ± 1.3, respectively). BMI did not differ significantly with infection status or stage (ANOVA).


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TABLE 1. Subject characteristics1
 
Nutrient concentrations and stage of infection
Five of the 8 biochemical variables studied differed significantly with stage of infection (ANOVA, P < 0.05; Table 2Go). Hematocrit values were significantly lower and plasma copper concentrations were significantly higher in stage-C subjects than in the other 3 groups. For plasma magnesium concentrations, we found significant differences between uninfected subjects and stage-B but not stage-A subjects. A comparable difference between plasma magnesium concentrations in uninfected and stage-C subjects was not statistically significant (0.05 < P < 0.062) because fewer subjects were classified as stage C than as stage B. Erythrocyte magnesium concentrations were significantly lower in stage-A but not in stage-B or -C subjects than in control subjects. Stage of infection did not influence mean plasma zinc, free choline, or total choline concentrations significantly. However, the lowest zinc concentrations occurred in stage-C subjects: 36% had concentrations below the normal range of 10.7–18.3 µmol/L (70–120 µg/dL). The percentages of uninfected and stage-A and -B subjects with values <10.7 µmol/L were 14.3%, 14.7%, and 30.2%, respectively. These percentages show a significant increase in below-normal zinc concentrations with infection and increasing disease severity (Mantel-Haenszel chi-square test for trend, P < 0.05).


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TABLE 2. Biochemical variables by stage of HIV-1 infection1
 
At all 3 stages of HIV infection, erythrocyte GSH concentrations were significantly and considerably lower than those of uninfected control subjects. Individual erythrocyte GSH values of uninfected subjects and infected subjects at each CDC stage are shown in Figure 1Go. A considerable percentage (37.2%) of the infected subjects had concentrations lower than the lowest value of any uninfected control subject.



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FIGURE 1. Erythrocyte reduced glutathione (GSH) concentrations by HIV status and Centers for Disease Control and Prevention stage for individual subjects. Mean values are indicated by horizontal lines and differ significantly (ANOVA, P < 0.0001). The percentage of infected subjects with GSH concentrations below the lowest value for any uninfected control subject was 37.2%. n = 29 for seronegative, 29 for stage A, 32 for stage B, and 24 for stage C.

 
Laboratory data by subject sex
Because the percentages of male and female study participants (Table 1Go) differed among the 4 groups of subjects (uninfected and stages A, B, and C), we compared laboratory data of the male and female subjects for the 8 biochemical variables listed in Table 2Go. For the 29 uninfected subjects, there was a significant difference between female and male subjects for hematocrit (0.397 ± 0.013 compared with 0.481 ± 0.005, respectively) and plasma copper concentration (18.9 ± 1.1 compared with 15.9 ± 0.6 µmol/L, respectively) by t test (P < 0.05). For the 106 HIV-infected subjects, men had significantly higher values than women for hematocrit (0.426 ± 0.006 compared with 0.369 ± 0.008, respectively) and plasma zinc concentration (13.0 ± 0.4 compared with 11.6 ± 0.5 µmol/L, respectively). For subjects with stage-C infection, only plasma zinc concentration differed between female and male subjects (10.1 ± 0.7 compared with 13.6 ± 0.8 µmol/L, respectively). The only variable that differed between men and women at stages A and B was hematocrit. For stage A, the mean values were 0.453 ± 0.007 and 0.386 ± 0.018 for men and women, respectively; for stage B, the means were 0.423 ± 0.009 and 0.335 ± 0.010 for men and women, respectively. There were no other significant differences in the measured variables between men and women. Erythrocyte GSH concentrations were remarkably similar in women and men for uninfected subjects and those at each stage of infection. For example, mean concentrations were 2.22 ± 0.10 and 2.18 ± 0.10 mmol/L for uninfected female and male subjects, respectively, and 1.53 ± 0.19 and 1.69 ± 0.18 mmol/L for stage-C female and male subjects, respectively.

Alcoholic beverages
Mean ethanol consumption of those subjects who drank alcoholic beverages was 4.6 ± 3.5 g/d (<= 2.6% of energy) for uninfected subjects and 9.9 ± 2.0 g/d (<= 4.4% of energy) for infected subjects. No stage-C subjects reported consumption of alcoholic beverages. However, ethanol consumption did not differ significantly by infection status or stage of infection.

Each subject was classified into 1 of 4 groups on the basis of infection status (uninfected or infected) and use of alcoholic beverages (did or did not consume alcohol). For subjects who did not consume alcoholic beverages, mean erythrocyte magnesium concentrations were 2.03 ± 0.09 mmol/L for 7 uninfected subjects and 1.91 ± 0.04 mmol/L for 46 infected subjects. Corresponding values for uninfected (n = 5) and infected (n = 16) subjects who drank alcoholic beverages were 2.02 ± 0.12 and 1.76 ± 0.05 mmol/L, respectively. The infected subjects who consumed alcoholic beverages had significantly lower erythrocyte magnesium concentrations than did subjects in the other 3 groups (ANOVA, P < 0.05).

Relations between nutrient concentrations and CD4+ T lymphocyte counts
In Figures 2, 3, and 4GoGoGo we show the relations between CD4+ T lymphocyte count and hematocrit, plasma magnesium concentration, and plasma zinc concentration, respectively. These were the only variables that were significantly (P < 0.05) associated with CD4+ cell counts. Linear correlation coefficients were 0.40 for hematocrit, 0.25 for plasma magnesium concentration, and 0.21 for plasma zinc concentration. The association between CD4+ cell count and plasma free choline concentration was not significant (r = 0.20, P = 0.077). Additionally, there were no significant associations between plasma or erythrocyte magnesium concentrations and erythrocyte GSH concentration. Erythrocyte magnesium and GSH concentrations were not significantly associated with hematocrit.



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FIGURE 2. Relation of CD4+ cell count to hematocrit (n = 94). The relation between the variables is best described by a straight line defined by the equation y = ax + b, where y = CD4+ cell count, x = hematocrit, a = 1800, and b = -388.

 


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FIGURE 3. Relation of CD4+ cell count to plasma magnesium concentration (n = 94). The relation between the variables is best described by a straight line defined by the equation y = ax + b, where y = CD4+ cell count, x = plasma magnesium concentration, a = 862, and b = -314.

 


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FIGURE 4. Relation of CD4+ cell count to plasma zinc concentration (n = 92). The relation between the variables is best described by a straight line defined by the equation y = ax + b, where y = CD4+ cell count, x = plasma zinc concentration, a = 17.2, and b = 141.

 
The results of the multiple regression analyses performed by using forward selection with CD4+ cell count as the dependent variable are shown in Table 3Go. Similar results were obtained by using a stepwise approach or backward elimination (data not reported). The independent variables were hematocrit, erythrocyte magnesium and GSH concentrations, ethanol consumption, age, sex, and plasma magnesium, copper, zinc, free choline, and total choline concentrations. Independent variables that were significant joint predictors of CD4+ cell count were hematocrit (partial R2 to enter model = 0.27), plasma free choline concentration (R2 = 0.087), and plasma zinc concentration (R2 = 0.067). Together, these 3 variables explained 43% of the variability in CD4+ cell counts. The absence of plasma magnesium concentration in the multiple regression model appears to be a result of its association with hematocrit (r = 0.19, P = 0.027).


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TABLE 3. Multiple regression models of CD4+ cell counts on biochemical variables1
 
Symptoms, supplements, and medications
Responses to questions about nutrition and medication use during the past year were tabulated. Of the 106 infected subjects, 24 (22.6%) reported reduced appetite, 17 (16.0%) reported moderate weight loss, 12 (11.3%) reported episodes of vomiting, and 21 (19.8%) reported diarrhea. Fifty-six subjects (52.8%) were taking antiretroviral drugs at the time of blood sampling and 25 (23.6%) reported a recent weight loss of >=2.25 kg (5 lb). Fifty subjects (47.2%) reported use of vitamin supplements and 38 (35.8%) consumed nutritional drinks. Of these drinks, the most frequently used was Sustacal (n = 28). The above percentages were highest for the 26 stage-C subjects, with the exception of the percentage reporting diarrhea.

Weight loss of >=2.25 kg, use of antiretroviral drugs, diarrhea, and use of vitamin or herbal supplements did not significantly (P < 0.02) influence any of the 8 biochemical variables measured. Hematocrit was significantly lower (P < 0.02) in subjects who reported loss of appetite (0.381 ± 0.013 compared with 0.418 ± 0.006) or use of nutritional drinks (0.390 ± 0.010 compared with 0.421 ± 0.007) than in subjects who did not. Significantly lower plasma zinc concentrations were found in subjects who reported loss of appetite (11.0 ± 0.6 compared with 13.1 ± 0.4 µmol/L) or vomiting (10.6 ± 0.5 compared with 12.9 ± 0.4 µmol/L) than in subjects who did not. No other significant differences were found for subjects who reported loss of appetite, vomiting, or use of nutritional drinks.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The HIV-infected subjects who participated in this study were classified into CDC stages A, B, or C on the basis of their symptoms and the presence of opportunistic infections. The mean (±SE) CD4+ cell counts decreased substantially with increasing severity of infection (600 ± 43, 310 ± 23, and 108 ± 18 x 106 cells/L for stages A, B, and C, respectively) and thus were consistent with the CDC classification of the infected subjects. Nevertheless, CD4+ cell counts and stage of infection provide different measures of disease progression, and this must be considered when interpreting the results of this study.

Differences between uninfected and infected subjects were particularly large for erythrocyte GSH; concentrations were already low early in the course of HIV infection, but there was considerable variability among infected subjects, especially those in stages B and C (Figure 1Go). However, erythrocyte GSH concentrations were not lower with increasing severity of HIV infection. Thus, GSH was not associated with disease progression as assessed by CD4+ cell counts or stage of disease of infected subjects. Nevertheless, because GSH is a key cellular antioxidant, the relatively low concentrations found even early in the course of infection may contribute to HIV pathogenesis, especially because other investigations have found evidence that compromised status of antioxidants is associated with HIV progression. For example, Herzenberg et al (12) found that CD4+ lymphocyte glutathione concentrations have prognostic value for predicting the rate of progression when measured in asymptomatic seropositive patients. These authors suggested that the use of acetaminophen and other drugs known to deplete GSH should be minimized or avoided in persons with HIV infection.

Garcia de la Asuncion et al (13) found that mitochondrial glutathione oxidation increases substantially with aging in rats and mice, with a remarkably high degree of correlation between oxidized glutathione and mitochondrial DNA damage (r = 0.95–0.98). The present study focused on GSH concentrations in erythrocytes. However, if the decreased GSH concentrations that we found at all stages of infection are associated with mitochondrial DNA damage, then the latter could be an important adverse effect of HIV-1 infection.

Subjects who were infected and also drank alcoholic beverages had the lowest erythrocyte magnesium concentrations. This is not surprising because seropositive status and consumption of ethanol are each associated with decreased circulating magnesium concentrations (9, 14). The ethanol intake of infected subjects who consumed alcoholic beverages was low (: <= 4.4% of energy). The fact that no stage-C subjects reported regular consumption of alcoholic beverages may have contributed to their higher erythrocyte magnesium concentrations compared with those of the stage-A and -B participants. These data suggest that HIV-infected subjects who consume alcoholic beverages, even in modest amounts, may be especially likely to develop compromised magnesium status.

Relatively high plasma copper concentrations, which we found in the stage-C subjects, were also observed by other investigators and most likely reflect a nonspecific increase in plasma concentrations of the copper-containing protein ceruloplasmin (15, 16). Plasma concentrations of ceruloplasmin and copper increase as an acute-phase response in a variety of infections and inflammatory conditions, and thus are not specific for HIV infection. We did not observe significantly lower plasma zinc concentrations with disease progression (as assessed by stage of infection) in HIV-positive subjects as was found in some other studies (17, 18), although the stage-C subjects did have the lowest mean concentration (11.9 µmol/L) and the highest percentage of subjects with below-normal values (36%). In addition, there was a significant association between plasma zinc concentration and CD4+ cell count. These observations are consistent with the idea that CD4+ cell count and CDC stage provide different, although complementary, measures of disease progression.

Hematocrit values were lowest in the stage-C subjects. This result agrees with other studies in which reduced hematocrit values were found late in the course of HIV infection (1922). In addition, the development of anemia is an independent risk factor for an early death in HIV-infected individuals (1922). Several studies showed that HIV-infected patients with anemia may benefit from treatment with recombinant human erythropoietin (23, 24), which can improve survival. In our multiple regression model, hematocrit was the independent variable that was the best predictor of CD4+ cell count. In addition, plasma zinc and free choline concentrations were significant joint predictors of the CD4+ cell count. There is considerable evidence that zinc is vital to cellular immune function. Choline was recognized as an essential dietary nutrient by the Institute of Nutrition of the National Academy of Sciences, and dietary reference intakes have been established for it (25). Because choline is required for cellular functions such as phospholipid synthesis (25), it is plausible that serum concentrations might be depleted with progression of HIV infection as the immune system attempts to respond to progression with increased synthesis of cells and molecules such as cytokines. Although CD4+ cell counts were significantly associated with free choline concentrations in the multiple regression models, there were no significant differences in mean choline concentrations between the different stages of infection. This is an example of CD4+ cell counts and stage of infection having different relations to the status of a nutrient.

In Figures 3, 4GoGo, and 5, we illustrated the significant associations between CD4+ cell count and hematocrit, plasma magnesium concentration, and plasma zinc concentration, respectively. Despite significant group associations, in these figures it is evident that some individual points were situated a substantial distance from the regression line. Therefore, an individual's CD4+ cell count cannot be predicted from laboratory data on hematocrit or plasma concentrations of magnesium or zinc. This is not surprising because numerous factors contribute to the CD4+ cell counts of individual HIV patients and any single nutritional variable is likely to have only a moderate association with CD4+ cell count. However, the 4 nutritional variables in the multiple regression model collectively explained {approx}43% of the variability in CD4+ cell counts. Because hematocrit is frequently measured in clinical medicine, it may be particularly useful for monitoring individual HIV-infected patients.

Limitations of the present study are that the results describe associations that may not represent a causal relation and that blood concentrations are only one measure of nutrient status.

Furthermore, it is unlikely that compromised nutritional status functions in isolation to influence the progression of HIV-1 infection, but rather that it acts in concert with other factors such as viral load and genetics. Compromised nutritional status that develops early in the course of infection, for example, the considerable changes in GSH status that we found, may exert its most substantial adverse effects only after interacting with other factors that result in further deterioration of host defenses. It could be argued that treatment of HIV-1 infection with drugs may contribute to compromised nutrient status because of drug side effects such as anorexia and diarrhea. Alternatively, antiretroviral therapy may improve nutritional status if anorexia is present because of infection-produced effects on cytokines. However, in the current study, use of antiretroviral drugs, anorexia, and diarrhea, as well as subject sex, had little or no effect on the status of the nutrients studied. Thus, the effects of these nutrients on HIV progression may be independent of the above factors.

The present study focused on assessing relations between HIV progression and magnesium, copper, zinc, choline, and glutathione. Other studies suggested that other micronutrients, for example, vitamins A, B-6, and B-12 and selenium (2629), may also influence HIV-1 progression. Thus, the results of this study add to the body of evidence showing compromised antioxidant, mineral, and micronutrient nutritional status during HIV infection. For some nutrients, this occurs early in the course of HIV infection. Because the major minerals and micronutrients play key roles in supporting immune function, compromised status of these nutrients may contribute to the progression of HIV-1 infection.


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Scrimshaw NS, SanGiovanni JP. Synergism of nutrition, infection, and immunity: an overview. Am J Clin Nutr 1997;66(suppl):464S–77S.[Abstract/Free Full Text]
  2. Fraker P. Nutritional immunology: methodological considerations. J Nutr Immunol 1994;2:87–92.
  3. Semba RD. Micronutrients and the pathogenesis of human immunodeficiency virus infection. In: Fitzpatrick DW, Anderson JE, L'Abbe ML, eds. Proceedings of the 16th International Congress of Nutrition. Ottawa: Canadian Federation of Biological Societies, 1998:349–51.
  4. Kubena KS. The role of magnesium in immunity. J Nutr Immunol 1993;2:107–26.
  5. Moreno Diaz MT, Ruiz Lopez MD, Navarro Alarcon M, Artacho-Lagos R, Martinez Atieriza M, Perez de la Cruz A. Magnesium deficiency in patients with HIV-AIDS. Nutr Hosp 1997;12: 304–8.[Medline]
  6. Skurnick JH, Bogden JD, Baker H, et al. Micronutrient profiles in HIV-1-infected heterosexual adults. J Acquir Immune Defic Syndr Hum Retrovirol 1996;12:75–83.[Medline]
  7. National Center for Infectious Diseases, Division of HIV/AIDS. 1993 Revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Morb Mortal Wkly Rep 1992;41(RR-17):1–19.
  8. Baker H, Frank O, Tuma DJ, Barak AJ, Sorrell MF, Hutner SH. Assay for free and total choline activity in biological fluids and tissues of rats and man with Torulopsis pintolopessi. Am J Clin Nutr 1978;31:532–40.[Abstract/Free Full Text]
  9. Bogden JD, Thind IS, Kemp FW, Caterini H. Plasma concentrations of calcium, chromium, copper, iron, magnesium, and zinc in maternal and cord blood and their relationship to low birth weight. J Lab Clin Med 1978;92:455–62.[Medline]
  10. Bogden JD, Troiano RA. Plasma calcium, copper, magnesium, and zinc concentrations in patients with the alcohol withdrawal syndrome. Clin Chem 1978;24:1553–6.[Abstract/Free Full Text]
  11. Beutler E, Duron O, Kelly BM. Improved method for determination of blood glutathione. J Lab Clin Med 1963;61:882–8.[Medline]
  12. Herzenberg LA, DeRosa SC, Dubs JG, et al. Glutathione deficiency is associated with impaired survival in HIV disease. Proc Natl Acad Sci U S A 1997;94:1967–72.[Abstract/Free Full Text]
  13. Garcia de la Asuncion J, Millan A, Pla R, et al. Mitochondrial glutathione oxidation correlates with age-associated oxidative damage to mitochondrial DNA. FASEB J 1996;10:333–8.[Abstract]
  14. Flink EB. Magnesium deficiency in alcoholism. Alcoholism 1986;10:590–4.
  15. Moreno T, Artacho R, Navarro M, Perez A, Ruiz-Lopez MD. Serum copper concentration in HIV-infection patients and relationships with other biochemical indices. Sci Total Environ 1998: 217:21–6.[Medline]
  16. Periquet BA, Jammes NM, Lambert WE, et al. Micronutrient levels in HIV-1 infected children. AIDS 1995;9:887–93.[Medline]
  17. Neves I Jr, Bertho AL, Veloso VG, Nascimento DV, Campos-Mello DL, Morgado MG. Improvement of the lymphoproliferative immune response and apoptosis inhibition upon in vitro treatment with zinc of peripheral blood mononuclear cells (PBMC) from HIV+ individuals. Clin Exp Immunol 1998;111:264–8.[Medline]
  18. Basset-Sequin N, Sotto A, Guillot B, Jourdan J, Guilhou JJ. Zinc status in HIV-infected patients: relation to the presence or absence of seborrheic dermatitis. J Am Acad Dermatol 1998; 38:276–8.[Medline]
  19. Binderow SR, Cavallo RJ, Freed J. Laboratory parameters as predictors of operative outcome after major abdominal surgery in AIDS and HIV-infected patients. Am Surg 1993;59:754–7.[Medline]
  20. Moore RD, Creagh-Kirk T, Keruly J, et al. Long-term safety and efficacy of zidovudine in patients with advanced human immunodeficiency virus disease. Zidovudine Epidemiology Study Group. Arch Intern Med 1991;151:981–6.[Abstract]
  21. Colford JM Jr, Ngo L, Tager I. Factors associated with survival in human immunodeficiency virus-infected patients with very low CD4 counts. Am J Epidemiol 1994;139:206–18.[Abstract/Free Full Text]
  22. Miles SA, Wang H, Elashoff R, Mitsuyasu RT. Improved survival for patients with AIDS-related Kaposi's sarcoma. J Clin Oncol 1994;12:1910–6.[Abstract/Free Full Text]
  23. Moore RD, Keruly JC, Chaisson RE. Anemia and survival in HIV infection. J Acquir Immune Defic Syndr Hum Retrovirol 1998; 19:29–33.[Medline]
  24. Fischl M, Galpin JE, Levine JD, et al. Recombinant human erythropoietin for patients with AIDS treated with zidovudine. N Engl J Med 1990;322:1488–93.[Abstract]
  25. Institute of Medicine, National Academy of Sciences. Dietary reference intakes for thiamin, riboflavin, niacin, vitamin B6, folate, vitamin B12, pantothenic acid, biotin, and choline. Washington, DC: National Academy Press, 1998.
  26. Baum MK, Shor-Posner G, Lu Y, et al. Micronutrients and HIV-1 disease progression. AIDS 1995;9:1051–6.[Medline]
  27. Baum MK, Shor-Posner G, Lai S. High risk of mortality in HIV infection is associated with selenium deficiency. J Acquir Immune Defic Syndr Hum Retrovirol 1997;15:370–4.[Medline]
  28. Semba RD, Graham NM, Caiaffa WT, Margolick JB, Clemens L, Vlahov D. Increased mortality associated with vitamin A deficiency during human immunodeficiency virus type 1 infection. Arch Intern Med 1993;153:2149–54.[Abstract]
  29. Baum MK, Mantero-Atienza E, Shor-Posner G, et al. Association of vitamin B6 status with parameters of immune function in early HIV-1 infection. J Acquir Immune Defic Syndr 1991;4:1122–32.
Received for publication July 2, 1999. Accepted for publication March 3, 2000.




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