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* Columbia University, New York, New York
C-TASC, Baltimore, Maryland
National Institute of Allergy and Infectious Diseases, Bethesda, Maryland
|| University of Puerto Rico, San Juan, Puerto Rico
¶ State University of New York Downstate, New York, New York
# Boston Medical Center, Boston, Massachusetts
** Baylor College of Medicine, Houston, Texas
University of Illinois, Chicago, Illinois
National Institute of Child Health and Human Development, Bethesda, Maryland
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONREFERENCES |
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Methods. Maternal hard drug use was identified by self-report and/or urine toxicology. Infant evaluations occurred at birth and at 1, 2, 4, 6, 9, 12, 18, and 24 months of age.
Results. A total of 401 (28%) of the 1436 uninfected infants were born to drug-using mothers. Maternal CD4 lymphocyte percentage and RNA at delivery were not significantly different between drug users and nonusers. Infants who were born to drug-using mothers had lower mean gestational age (37.8 vs 38.5 weeks) and birth weight (2.9 vs 3.1 kg). Infants with intrauterine drug exposure had lower CD4 lymphocyte percentage over the first 4 months of life after adjusting for covariates and higher natural killer lymphocyte percentage. When the analysis was stratified by time period of entry, the incidence of clinical events was not different between infants who were born to drug users versus nonusers.
Conclusion. Maternal hard drug use is associated with immunologic changes in infants early in life, although these changes did not seem to be associated with increased risk of infections.
Key Words: HIV exposed infants • drug use • infant lymphocyte markers
Abbreviations: NK, natural killer • HIV, human immunodeficiency virus • WITS, Women and Infants Transmission Study • ART, antiretroviral therapy • HAART, highly active antiretroviral therapy • HSV, herpes simplex virus • TMP/SMX, trimethoprim-sulfamethoxazole
Drug use (specifically hard drugs, eg, cocaine, injection drugs, opiates) has been postulated to affect both immune functions and clinical outcomes of the drug-using individual.1,2 The effect of hard drug use during pregnancy is especially important to study as it may affect the health of the infant, particularly in the first year of life. Data on the effect of antenatal maternal drug use on immunologic parameters in the infant are limited and dated.3
Several studies have documented an increased risk of a variety of infections in drug users, especially intravenous drug users.4,5 A study in mice showed that morphine exposure increased host susceptibility to oral Salmonella typhimurium infection.6 The mechanisms by which drugs affect the cellular and humoral immune systems are still unclear. Studies have shown that drug use may affect both the quantity and the function of immune cells. A study in drug users that did not have human immunodeficiency virus (HIV)-1 infection showed that methadone users had significantly lower CD4 lymphocyte percentage and CD4/CD8 ratios as well as a higher percentage of CD8 lymphocytes than non-drug users.7 However, this phenomenon has not been found in other studies.8 A study by Carr and France9 showed that rhesus monkeys had a decrease in their CD4 and natural killer (NK) cells after receiving morphine on a daily basis. Other studies showed an increased or an unchanged number of NK cells after exposure to cocaine.10,11
Animal and in vitro studies have demonstrated cell surface receptors on lymphocytes that are closely related to opioid receptors.12 In vitro exposure of peripheral blood mononuclear cells to morphine resulted in suppression of the respiratory-burst activity of monocytes13 and decreased B-cell proliferation.14 Morphine has been shown to depress chemotaxis and phagocytic activities of macrophages and polymorphonuclear neutrophils.15–17 Studies have shown that morphine also inhibits NK cell cytotoxicity.2 Studies have shown that the inhibition of chemotaxis may be related to inhibition of the release of chemokines such as interleukin-8 and macrophage inflammatory protein-1 
or ß.18,19 In addition, morphine may induce immunosuppression by inhibiting nuclear factor-
B binding by neutrophils and monocytes.20
Although there are data available to suggest that hard drug use may cause immunosuppression and thus increase risk for clinical infections in the drug user herself, few data exist about the effects of maternal hard drug use on HIV-uninfected infants who are born to HIV-infected women who use hard drugs such as cocaine and heroin. The purpose of our study was to describe differences in immunologic parameters between HIV-uninfected infants who were exposed to hard drugs and HIV-uninfected infants who were not exposed to drugs in utero.
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METHODS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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Sample Collection and Definitions
Blood specimens were collected routinely in infants at days 0 to 2 and 7 to 10 of life and at 1, 2, 4, 6, 9, 12, 18, and 24 months of age. Infants were defined as uninfected for HIV-1 when their peripheral blood mononuclear cultures or HIV-1 DNA polymerase chain reaction tests were negative twice on separate visits after 1 month of age and the patient had no positive test results. Maternal hard drug use was defined as the use of cocaine, methadone, heroin, or injecting drugs. Drugs used by injection included heroin, cocaine, or methadone and other opiates. Maternal hard drug use was ascertained by self-reported and/or urine toxicology-proven use of drugs during any perinatal or delivery visit.21 Maternal urine samples obtained at study entry and during labor or immediately postpartum underwent drug toxicology screening; positive urine tests were confirmed by gas chromatography-mass spectrometry. Women who did not use drugs were defined as those with a negative self-report for the drug in question accompanied by a negative urine toxicology or a negative self-report when the urine specimen was unavailable.
Laboratory Analysis
Commercially available enzyme-linked immunoassays and confirmatory Western blot assays were used to determine the serologic status of the mothers. Qualitative peripheral blood mononuclear cell cultures and HIV-DNA polymerase chain reaction were performed according to the AIDS Clinical Trials Group consensus protocol in National Institute of Allergy and Infectious Diseases-certified laboratories to assess infant infection status.22 CD4, CD8, CD19, and NK cell lymphocyte percentage and absolute numbers were measured using 2-color and later 3-color flow cytometry at local laboratories that participated in the National Institute of Allergy and Infectious Diseases quality assurance program.23
Clinical Outcomes
Infants were clinically evaluated at birth and at 1, 2, 4, 6, 9, 12, 18, and 24 months of age. History of illness and clinical findings were recorded using standardized collection instruments for medical history and medical chart abstraction.
Statistical Analysis
Cross-sectional analyses, F and 
2 tests, were performed to compare demographic characteristics across the hard drug use and nonuse cohorts. A Cox proportional hazards model stratified by time period of entry into the study (before 1994, 1994–1996, and after 1996) was used to analyze the relative risk of clinical outcomes. The time of entry variable was introduced because during the 10 years of this study, there were 3 distinct eras of antiretroviral use during pregnancy. Before 1994, antiretroviral therapy (ART; generally single-drug therapy) was used in only small numbers of women for their own health. Between 1994 and late 1996, zidovudine monotherapy was used in almost all women for prevention of perinatal HIV transmission. After 1996, although zidovudine continued to be used for prevention of transmission, many pregnant women received combination ART for their own health. The time of entry variable was also included in all models as the blocking factor in a randomized block design. This was done because the prevalence of drug use decreased over time and we were concerned about the possibility of the confounding effect of time on comparisons involving the hard drug use exposure group. All statistical programing was performed using SAS software (SAS version 8; SAS Institute, Cary, NC) or S-PLUS software (S-PLUS 2000; MathSoft, Seattle, WA).
A longitudinal analysis was used to analyze mean lymphocyte over time. The longitudinal linear models assumed Gaussian distributed errors and had parameters that were estimated using the general estimating equations method.24 The covariates that were included in the models were gender; ethnicity; birth weight; gestational age; a potency variable for maternal ART during pregnancy; the time of entry variable; infant prophylaxis; clinic site; maternal age at delivery; and other drug (eg, marijuana), alcohol, and cigarette use during pregnancy. Categories of maternal ART included no ART, monotherapy, combination therapy not including a potent drug, and highly active ART (HAART), which was subdivided into HAART including 1 potent drug versus HAART including 2 or more potent drugs. Potent drugs were defined as protease inhibitors, nonnucleoside reverse transcriptase inhibitors, and abacavir. Maternal ART was defined as the most potent ART therapy received before or at birth. Infant antiretroviral prophylaxis included no prophylaxis, 6 weeks of zidovudine, or 6 weeks zidovudine plus 1 or more additional drugs, usually lamivudine or nevirapine. Backward elimination was used to eliminate covariates that did not explain variability in the model.
To investigate whether differences in mean lymphocytes depended on time, we included in the models interaction terms between hard drug use and study visit. By doing this, cross-sectional comparisons of adjusted means at each study visit could be made within these models. Cross-sectional differences were then summarized by these adjusted means in Fig 1. The means were adjusted to reflect typical values for the covariates in the model. That is, these adjusted means are estimates that assumed that continuous covariates are fixed at their mean levels and factors are fixed at their most commonly observed levels. The P values for the comparisons of these adjusted means and for the overall general association of hard drug exposure also appear in Fig 1. General association is the test for the main effect across time of hard drug exposure after adjusting for the interaction between hard drug exposure and study visit, if that interaction was statistically significant.
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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Eighty-two percent of the population was of minority race/ethnicity (Table 1). More hard drug-exposed children were born during the early years of the study. Hard drug-using mothers were older than non-drug users (29.1 vs 26.6 years; P < .01) and had higher mean CD4 absolute counts (579 vs 524 cells/µ;L; P = .01). Women who used hard drugs were significantly less likely than non-drug-using women to receive potent ART. However, at delivery, there were no significant differences between hard drug-using and non-drug-using mothers in regard to CD4 lymphocyte percentage or maternal viral loads. Concomitant use of alcohol, other drugs (eg, marijuana), and cigarette use were more common among women who used hard drugs than those who did not (63.1% vs 30.2%, 89.0% vs 46.1%, 77.1% vs 28.2%, respectively; P < .01). Infants of hard drug-using mothers were born at a younger gestational age (37.8 vs 38.5 weeks; P < .01) and had lower birth weights (2.9 vs 3.1 kg; P < .01). Infants of hard drug-using mothers were born at a younger gestational age (37.8 vs 38.5 weeks; P < .01) and had lower birth weights (2.9 vs 3.1 kg; P < .01). When infants who were born to mothers who reported injecting drug use alone were studied, these comparisons remained statistically significant (data not shown). There was no difference in the gender of the infants who were born to this cohort of women.
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In the longitudinal analysis using a linear model with normally distributed errors and backward elimination to identify important confounding variables, the average CD4 lymphocyte percentage difference was significant throughout the study (P < .01), with an overall 2.6% lower CD4 percentage in hard drug-exposed compared with unexposed infants during the first 2 years of life. However, when included in the model, the interaction term between visit and hard drug use was significant (P = .02). This suggests that the difference in adjusted mean CD4 percentage depends on the time of the visit. This cohort difference in the longitudinal analysis is driven by the differences in CD4 percentage between birth and 4 months of age. The general association between hard drug exposure and mean CD4 lymphocyte percentage remained significant (P = .01) in the model that included the interaction term between visit and hard drug use. There was a trend toward significance for the CD4 count in longitudinal analysis. In Fig 1, the means have been adjusted by the significant covariates in the models. The number of observations for each cohort at each time point in the model is displayed in Fig 1. Figure 1 also displays the P values associated with cross-sectional comparisons of the hard drug-exposed and unexposed adjusted means at each study visit. The longitudinal analysis of NK cell percentage and counts revealed that the hard drug-exposed infants’ mean percentage was 4.3% higher (P = .03) and the mean NK cell absolute counts were 4.6% larger (P = .05) than the unexposed infants’ adjusted means. No differences were found in the longitudinal analysis for the total white cell count, absolute lymphocyte count, or CD8 lymphocyte percentage between hard drug-exposed and unexposed infants.
Clinical Outcomes
When the risk of infections is compared ignoring the confounding effects of time era, infants who were exposed to hard drugs had an estimated 3.6-fold increase in the risk of a single episode of herpes simplex virus (HSV) stomatitis compared with infants who were not exposed to hard drugs. In addition, hard drug-exposed infants had a higher risk of dermatitis than nonexposed infants (relative risk: 1.16; P = .04). There was a borderline increase in the risk of bacterial sepsis in the hard drug-exposed group (relative risk: 3.48; P = .05), but there were only a small number of episodes (5 in the exposed group vs 4 in the unexposed group). Because there were significant differences in the proportion of hard drug- versus non-drug-exposed infants over the 3 time eras in the analysis, the hazard ratios of clinical outcomes were also tested after stratifying for the time cohort variable. The incidence of clinical outcomes was highest in the early time era, a time when more hard drug-exposed infants were also more prevalent. For example, the HSV stomatitis events declined from 8 to 5 to 0 events over the 3 time periods. After stratifying for the time cohort variable, there was no significant difference in risk of infection between the 2 groups of infants (Table 2). This indicates that the apparent increase in risk of infections in the drug-exposed infants was attributable to differences in the prevalence of such infections over time rather than a direct consequence of drug exposure. We performed a subanalysis of this data set including trimethoprim-sulfamethoxazole (TMP/SMX) as a covariate as TMP/SMX was used for Pneumocystis pneumonia prophylaxis and may affect the incidence of clinical events. As expected, the inclusion of TMP/SMX in the models had no effect on the comparisons of the incidence of clinical events (HSV/dermatitis) for the 2 populations. In addition, no differences were seen for the comparison of the cohort lymphocyte means when controlling for TMP/SMX.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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The clinical significance of changes in infant immunologic parameters secondary to maternal hard drug use is unclear. Studies done in the 1980s by Rosen and Johnson28 and Rich29 showed that clinical infections such as otitis media, oral thrush, bronchiolitis, and chlamydial pneumonia were more common in infants who were exposed to hard drugs during pregnancy. Our analysis of this large cohort of HIV-1-exposed but uninfected infants reveals that hard drug exposure for the infants affects CD4 lymphocyte and NK cell percentage over the first 2 years of life. The decrease in CD4 percentage was more prominent during the first 4 months of life. The difference in CD4 percentage is small; therefore, one would not expect to see major clinical outcome differences for the hard drug-exposed infants when compared with the unexposed infants. However, this transient decline in CD4 percentage could place these infants at higher risk for primary acquisition of infection. In addition, our study did not measure CD4 cell function and therefore cannot assess whether abnormalities in the immune function might be present even in the presence of normal CD4 cell numbers. One might also hypothesize that early acquisition of certain infections may predispose infants to recurrences although CD4 lymphocyte percentages normalize. For example, infants with early cutaneous herpes infection are at higher risk for developing recurrences during the first 6 months and even during childhood.30 Teele et al31 in a longitudinal study of >2000 children found that children who experienced their first episode of otitis media before age 2 were at risk for having additional episodes (P < .01).
The overall risk of clinical events in HIV-exposed infants declined over time as did the hard drug use among the women. Although we found an apparent increase in dermatitis and HSV stomatitis in the hard drug-exposed infants, we found no significant difference in the risk of clinical outcomes when we controlled for time period. The reasons for the decline in infectious events during the 10-year study period are unknown. In 1995, guidelines for prophylaxis of Pneumocystis carinii pneumonia were modified to recommend TMP/SMX prophylaxis of HIV-exposed infants for the first year of life or until the infant can be presumptively diagnosed as uninfected (which is not possible until after 4 months of age). However, when TMP/SMX was added as a covariate for the analysis, it did not affect the incidence of bacterial infections in the overall cohort over time (analysis not shown).
Our study describes a large cohort; the methods of obtaining drug use information have been validated, and the children have been observed for a substantial period of time. We have shown that a correlation exists between hard drug exposure and changes in CD4 lymphocyte percentage and NK cell percentage. We suggest that future studies evaluating immunologic parameters in HIV-uninfected but exposed infants should control for the effect of hard drug exposure. Additional study that includes functional assays of lymphocyte cell populations need to be done to evaluate the effects of hard drug exposure on immune function in addition to phenotype, whether such effects are transient or persist over time, and whether there is any clinical significance of such findings.
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ACKNOWLEDGMENTS |
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Scientific Leadership Core: Kenneth Rich, principal investigator (1 U01 AI 50274-01), and Delmyra Turpin.
Additional support has been provided by local Clinical Research Centers as follows: Baylor College of Medicine, Houston, TX (NIH GCRC RR00188); and Columbia University, New York, NY (NIH GCRC RR00645).
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FOOTNOTES |
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Reprint requests to (N.N.) Columbia University, 622 W 168th St, PH4-468, New York, NY 10032. E-mail: nn45{at}columbia.edu
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REFERENCES |
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B nuclear binding in human neutrophils and monocytes by a nitric oxide-dependent mechanism.
Anesthesiology. 2000;6
:1677
–1684This article has been cited by other articles:
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  H. Minkoff, L. S. Xian, D. H. Watts, R. Leighty, R. Hershow, J. Palefsky, R. Tuomala, N. Neu, C. D. Zorrilla, M. Paul, et al. Relationship of Pregnancy to Human Papillomavirus Among Human Immunodeficiency Virus-Infected Women. Obstet. Gynecol., October 1, 2006; 108(4): 953 - 960. [Abstract] [Full Text] [PDF]
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M. Foca, J. Moye, C. Chu, Y. Matthews, K. Rich, E. Handelsman, K. Luzuriaga, M. Paul, C. Diaz, and Women and Infants Transmission Study Gender Differences in Lymphocyte Populations, Plasma HIV RNA Levels, and Disease Progression in a Cohort of Children Born to Women Infected With HIV Pediatrics, July 1, 2006; 118(1): 146 - 155. [Abstract] [Full Text] [PDF]
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Deceased. 