More than 2 million babies are born to HIV-infected mothers every year.1 With improved implementation of prevention of mother-to-child transmission programs, an increasing majority of these infants are HIV uninfected.2 However, an increased risk of morbidity and mortality has been observed in HIV-exposed uninfected (HEU) infants compared with HIV-unexposed (UE) infants.3–9 The etiology of the increased infection risk in HEU infants is unknown.
Risk of severe infections is greater early in life, especially for acute respiratory infections, which are the leading cause of mortality in HIV-exposed infants.10,11 Specifically, the risk for severe lower respiratory tract infection is greater during life's earliest months.7,12 We previously reported a similar incidence of infectious episodes between UE and HEU infants but noted that the frequency of severe infectious events was substantially higher in HEU infants9 (using the Division of AIDS Table for Grading Severity of Adult and Pediatric Adverse Events13). The relative risk for severe infectious events in HEU compared with UE infants was 3.5 in the first 6 months of life, the majority being lower respiratory tract infections. This strongly suggests an altered host response to pathogens in HEU vs. UE infants.
Innate immunity orchestrates the initial response to pathogens while shaping future adaptive responses14; therefore, differences in early life innate immunity between HEU and UE infants may be associated with increased risk of infectious morbidity.15 It is essential to understand how common exposures affect the trajectory of innate immune development in resource-poor regions, such as sub-Saharan Africa, where the risk of infant morbidity and mortality is greater.16 This region carries the heavy burden of HIV. For example, in South Africa, the prevalence of HIV infection in pregnant women visiting antenatal clinics is 30%.17
In this study, we provide the most comprehensive functional analysis of antigen-presenting cells (APCs) in HEU and a detailed description of HEU innate immune development to date. Cytokine secretion was characterized in South African infants over the first year of life to determine if differences between HEU and UE innate immune development exist.
The Health Research Ethics Committee of Stellenbosch University and the Institutional Review Board of the University of British Columbia approved the study (protocols H09-02064 and H11-01947, respectively). Informed consent was obtained from next of kin, caregivers, or guardians on behalf of infant participants.
Prospective Birth Cohort Study Design
A prospective longitudinal cohort study commenced in 2009 in Cape Town, South Africa, to evaluate immune function early in life. Infants born from mothers infected or uninfected with HIV were enrolled at birth at Tygerberg Academic Hospital. Exclusion criteria included the following: (1) parent or legal guardian was unable to read and/or comprehend the consent process, (2) diagnosis of a significant chronic medical condition, or (3) any maternal febrile illness within the last 24 hours. Infants were confirmed HIV negative by HIV polymerase chain reaction. Infants were seen by health professionals, and blood was collected at 2 and 6 weeks, and 6 and 12 months of age. Maternal and infant data were collected as previously described.9
Blood Sample Processing
Three to 5 mL of peripheral blood was drawn into sodium–heparin tubes and then immediately processed as described previously.18,19 Samples were diluted 1:1 with Roswell Park Memorial Institute-1640 media and added to prefabricated stimulation plates containing pathogen-associated molecular patterns (PAMPs) at concentrations that elicit optimal cytokine expression.18 Six Toll-like receptor (TLR) and nucleotide-oligomerization domain (NOD) receptor agonists were used, which represent canonical bacterial vs. viral stimuli, eg, bacteria [CpG and PAM3CSK4 (PAM)], Gram-negative bacteria [lipopolysaccharide (LPS)], single-stranded RNA viruses (R848), or double-stranded RNA viruses (pI:C). CpGA (CpG; Coley Pharmaceutical Group, Massachusetts, USA) stimulates signaling through TLR9, PAM3CSK4 (PAM; EMC Microcollections, Tübingen, Germany) signals via TLR2/1, 0111:B4 LPS (LPS; InvivoGen, California) through TLR4, PGN (InvivoGen) via TLR2 and NOD1/2, TLR7/8 is stimulated by R848 (InvivoGen), and pI:C (Amersham, Buckinghamshire, UK) through TLR3.20 Stimulation plates contained the vesicle transport inhibitor Brefeldin A (added at T = 0 h for PGN, PAM, LPS, and R848, or at T = 3 h for pI:C and CpG as described18) and were incubated for 6 hours at 37° C in 5% CO2. Cell pellets were stored frozen in FACS Lysing Solution (BD Biosciences, New Jersey) as previously described.18
Staining, Acquisition, and Flow Cytometric Analysis
A detailed description of antibodies (source, clone, and dilution), machine setup, and data acquisition compliant with MiFlowCyt reporting standards21,22 is provided in the Supplemental Methods (see Supplemental Digital Content, http://links.lww.com/QAI/A517). Samples were prepared for flow cytometric analysis as previously described.18 Stained and fixed cells were analyzed on a FACSAria flow cytometer (BD Biosciences) setup using a biological standard, according to published guidelines.22 B cells, monocytes, classical dendritic cells (cDCs), and plasmacytoid dendritic cells (pDCs) were differentiated, and intracellular tumor necrosis factor alpha (TNF-α), interleukin (IL) 6, IL-12, and interferon alpha (IFN-α) were detected; 300,000 events were acquired per sample for analysis with FlowJo software (Tree Star, Oregon), and gates were set based on the fluorescence minus one principle.23 Negative controls from unstimulated samples that produced cytokine above cutoffs were negligible and were subtracted from stimulated samples.23
This study was exploratory with the intent to generate and not to test a particular hypothesis. The data were strongly interdependent, although the degree of correlation is not quantified between different cytokines produced in response to particular PAMPs. Therefore, controlling specifically for familywise error rate because of multiple comparisons was inappropriate.24 The null hypothesis was that no differing trends in longitudinal data would be identified between HEU vs. UE innate immune development. The P values from Mann–Whitney test comparisons between proportion of responder cells and cytokine produced per cell in HEU vs. UE APCs are reported (see Table S1 and Table S3, Supplemental Digital Content, http://links.lww.com/QAI/A517, and Table S2 and Table S4, Supplemental Digital Content, http://links.lww.com/QAI/A517, respectively); P values <0.05 were considered significant for the purpose of trend identification. To assess polyfunctionality, the percentage of cells in a given cytokine combination category was calculated (eg, there are 7 possible cytokine combination categories for 3 cytokines in which at least one cytokine is positive). Each of the 7 cytokine combination categories was compared using Mann–Whitney test. Total response (shown as total bar height, see Figure S3, Supplemental Digital Content, http://links.lww.com/QAI/A517) for each cell type was compared by Student t test. Bonferroni correction for multiple comparisons was applied to compare infant housing characteristics between HEU and UE, and P <0.01 was considered significant.
Racial Background and Housing Attributes Differed Between HEU and HIV-UE Infants
No significant difference was identified between HEU and UE mothers' age, education, smoking, or alcohol consumption during pregnancy. The mean antenatal CD4 count of HIV-positive mothers was 337 (range 131–673). A significant difference was identified in racial composition between HEU and UE groups. Eighty-one percent of HEU was of African origin, whereas 71% of UE had mixed racial backgrounds (P = 0.001). HEU infants did not breast-feed; however, failure to thrive was not identified by anthropometrics throughout the study period. The primary caregiver was the mother for 73% and 80% of HEU and UE infants, respectively. The majority (58%) of HEU infants lived in informal housing, compared with 15% of UE infants (P = 0.007), with the same proportion of HEU infants lacking access to running water relative to UE infants (P = 0.007). More people occupied UE infant households (mean 5.8) vs. HEU households (mean 3.9) (P = 0.01), and UE infants also shared a room with more occupants (mean 3.4) relative to HEU infants who shared with an average of 2.3 (P = 0.008) (Table 1).
Monocyte, cDC, and pDC Cell Composition Was Similar, and B-Cell Composition Differed Between HEU and HIV-UE Infants
Monocytes, cDCs, pDCs, and B cells were identified by flow cytometry as illustrated in Figure 1A. The relative proportion of each cell type was compared between HEU and UE groups (Fig. 1B) and between subjects of African and mixed racial backgrounds (Fig. 1C). Differences in proportion of B cells were observed between HEU and UE groups at 2 weeks (UE > HEU) and between African and mixed groups at 2 weeks and 6 months (mixed > African). Differences were also observed between African and mixed racial groups in cDC proportions at 6 weeks (African > mixed) and pDC proportions at 6 months (mixed > African). No other differences were identified in HEU vs. UE APC subsets.
Enhanced Pro-inflammatory Response of Monocytes and Conventional Dendritic Cells in HEU vs. HIV-UE Infants
Whole blood was stimulated with PAMPs before single-cell analysis of cytokine production (IL-6, IL-12, TNF-α, and IFN-α) in monocytes, cDCs, pDCs, and B cells. B cells did not produce a detectable amount of cytokine in response to PAMP stimulation. The overall trend of evolving reactivity of monocytes, cDCs, and pDCs in HEU and UE infants was similar throughout the first year of life (Figure S1); however, when compared at individual time points, several differences were observed between groups (Fig. 2). HEU monocyte and cDC responses are illustrated in Figure 2A, and these cell types produced significantly more IL-6 and TNF-α in response to stimulation with the bacterial PAMPs, PAM, and LPS. HEU cDCs also produced more IL-6 and IL-12 in response to PGN and the single-stranded RNA–like ligand R848 (IL-6 only). All 10 significantly different responses detected at 2 weeks represented higher responses in HEU neonates compared with their UE counterparts. Blood samples collected at 6 weeks of age similarly demonstrated higher monocyte and cDC responses in HEU as compared with UE, but differences were restricted to bacterial LPS (TLR4) stimulation only. On the other hand, at 6 weeks, UE monocytes produced more IL-12 in response to pI:C (double-stranded RNA). Only a single difference was detected between pDCs of HEU and UE, with HEU pDCs producing more IL-6 in response to R848, although the median response was similar between groups (Fig. 2B). The only difference detected past 6 weeks was for UE monocytes producing more TNF-α in response to R848 stimulation at 6 months. By 12 months of age, any difference in the reactivity between HEU and UE mononuclear cells had completely disappeared (see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A517).
HEU Infant Mononuclear Cells Produced More Cytokines on a Per-Cell Basis Than Their HIV-UE Counterparts
Measuring the proportion of cells responding to stimulation does not account for the strength of response per cell. We therefore quantified the difference in mean fluorescence intensity between HEU and UE infants for monocyte, cDC (Fig. 3A), and pDC (Fig. 3B). The overall trend of evolving cytokine production per cell was similar between groups throughout the first year of life (Figure S2); however, multiple differences were detected when mean fluorescence intensity was compared between the 2 groups (see Table S2, Supplemental Digital Content, http://links.lww.com/QAI/A517). At 2 weeks of life, HEU monocytes produced more IL-12 per cell for all PAMPs tested except for the viral stimuli R848. Similarly, HEU cDC produced more IL-12 per cell for the bacterial PAMPs (PGN, LPS, and PAM). HEU monocytes and cDCs produced more IL-6 in response to TLR2/1 stimulation. HEU cDC displayed higher TNF-α production in response to stimulation of TLR4 and TLR7/8. By 6 weeks of age, HEU and UE monocyte cytokine production was similar, with no significant difference detected except the UE monocyte TLR3 response, which was the only instance where UE APCs mounted a higher per-cell response compared with the HEU group. HEU pDCs produced more TNF-α and IFN-α per cell in response to stimulation of TLR7/8 and TLR9, but only within the first 6 months of life.
Early Life Variability Detected in Polyfunctional Mononuclear Cell Responses of HEU and HIV-UE Infants
Total proportion of monocytes (Figure S3a), cDCs (Figure S3b), and pDCs (Figure S3c) that responded to PAMP stimulation was compared between HEU and UE infants (total bar height). Overall, a greater proportion of HEU monocytes and cDCs responded to bacterial ligand stimulation (PAM, LPS) up to 6 weeks of age. Conversely, UE monocytes responded more strongly to viral ligand stimulation (pI:C and R848) at 6 months. No significant differences in total responders were detected at 12 months of age.
Mononuclear cell responses were subsequently differentiated into monofunctional and polyfunctional subtypes. For monocytes and cDCs, 7 permutations were theoretically possible for cytokine expression of TNF-α, and/or IL-6, and/or IL-12 (Figures S3a and b, respectively). For pDCs, there were 7 possible permutations for TNF-α and/or IL-6 and/or IFN-α (Figure S3c). Comparisons between HEU and UE were performed for each subtype's percent responder cells. Overall, 27 differences were identified, 16 at 2 weeks, 9 at 6 weeks, none at 6 months, and only 2 at 12 months of age (Fig. 4A). Of the differences identified between HEU and UE, 13 were found in response to LPS, 4 in response to PAM, 3 for PGN, 2 for CpG, 2 for pI:C, and 3 for R848 (Fig. 4B). At 2 weeks of age, when most differences between HEU and UE were observed, the majority of differences were detected in cytokine production in cDCs. For all statistical differences, the HEU subset responses were higher than UE responses.
Comparisons of APC Responses Between Groups Defined by Race Were Dissimilar to Comparisons Between Groups Defined by Maternal HIV Infection
Because of differences in racial composition between HEU and UE groups, additional analysis was performed to compare groups defined by race (African vs. mixed descent). In contrast to the increased proportion of HEU vs. UE APCs responding primarily to bacterial stimuli at 2 weeks of age (see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A517), less than a third of the differences were observed in African vs. mixed race infants (see Table S3, Supplemental Digital Content, http://links.lww.com/QAI/A517). No pattern was evident that would indicate a greater responsiveness of any cell type to a particular stimuli or at a particular time point. Differences in per-cell cytokine production were identified between infants of African and mixed races. Infants of mixed race exhibited a pattern of stronger per-cell responses to pattern recognition receptor (PRR) stimulation at 6 weeks of age (see Table S4, Supplemental Digital Content, http://links.lww.com/QAI/A517). Specifically, mixed race cDCs produced more TNF-α, IL-6, and IL-12 in response to PGN. More TNF-α and/or IL-6 was produced by mixed race cDCs after LPS and PAM stimulation at 6 weeks. African monocytes produced more TNF-α and IL-12 in response to R848 at 2 weeks and 6 months, respectively. R848 elicited more IL-12 from mixed race cDCs at 6 weeks and IFN-α from African pDCs at 2 weeks.
HEU infants are at an increased risk of life-threatening infections,3–9 and differences in innate immunity in early life potentially contribute to their vulnerabilities.15 This study examined early life HEU innate immune development and contrasted it to UE infants using multiparameter flow cytometry to measure cytokine production in monocytes, cDCs, and pDCs. Overall, HEU innate APCs responded more strongly than UE to stimulation with PAMPs in both the proportion of responder cells and quantity of cytokine produced per cell. The majority of differences occurred at the earliest time points and in response to bacterial PAMPs.
Previous comparisons of early life innate immunity in HEU relative to UE demonstrate altered secretion of immune-mediating cytokines, increased soluble indicators of inflammation,25,26 and cell surface receptor expression suggestive of APC activation in HEU.27 Many of these observations have been in cord blood, and these changes are no longer detected later in life. Functional comparison of natural killer cell activity at 1 month of age also demonstrates an increase of an intermediate natural killer phenotype for activation and perforin expression in HEU vs. UE, which “normalizes” by 1 year.28 These findings are in line with our observations at the cellular level. Our single-cell focus now provides the sensitivity to detect differences of smaller magnitude (often less than 15% for any single parameter). Analysis focused at the single-cell level also offers the necessary resolution to observe trends when comparing HEU and UE innate immune development, which resulted in the most striking observations. These data delineate the time- (≤6 weeks) and stimulus (bacterial PAMPs)-restricted nature of differences in innate immune ontogeny between HEU and UE infants. Time-restricted differences in innate immune responses to PAMPs may be pertinent to corresponding periods of increased susceptibility of HEU infants to infectious diseases.
Additional resolution was provided by detecting APCs' ability to produce more than one cytokine after stimulation (termed polyfunctionality), which is a functional parameter previously correlated with clinical outcomes.29 We subdivided innate responses into polyfunctional subgroups and observed heightened responses in HEU, which were almost exclusively induced by bacterial PAMPs in cDCs and monocytes. In contrast, no consistent difference in polyfunctionality between HEU and UE was observed after stimulation with viral PAMPs, or in pDCs, which are instrumental in viral responses. These data suggest that differences in polyfunctionality may be pathogen specific and correspondingly also APC subtype specific. However, our data do not allow for inference of causality for, eg, bacterial infections; they solely indicate that differences in innate response to these PAMPs exist in a time frame closely associated with increased risk for severe infection.
The etiological factors driving the observed early life differences in innate immune ontogeny between HEU and UE are likely multifactorial.6,30 Future analysis will be needed to evaluate how genetic and environmental differences between HEU and UE infants affect innate immune ontogeny. Direct comparisons would provide a better understanding of why there is variability between observations of innate immune development in resource-rich settings31–33 vs. resource-poor settings.34–37 For example, lacking access to running water correlates positively with the expression of IL-10 in childhood.38 The majority (58%) of HEU infants in our study lacked access to running water, whereas only 15% of UE infants did. However, HEU APCs responded more strongly to PAMPs, suggesting that elevated IL-10 production associated with this basic measure of sanitation was unlikely a dominant factor influencing differences in innate immune development. Antiretroviral therapy (ART) exposure in utero and in the perinatal period may also affect immune development. In adults, ART is associated with anemia, neutropenia, relative lymphopenia, and downregulation of selected pattern recognition receptor genes.39–42 However, there are currently no data measuring the effect of ART exposure on functional innate immune ontogeny early in life.
Varied racial background was identified between our groups (81% vs. 29% African in HEU vs. UE, respectively). Different ethnic groups (with varied genetic backgrounds by extrapolation) can exhibit varied innate immune responses to, and protection from, infectious challenge.43,44 More specifically, TLR polymorphisms are associated with heterogeneity of innate responses.45 To test the relative impact of race on our observations, we redefined comparison groups by racial background (African vs. mixed). Given the increased African composition in the HEU group, we expected to find a similar pro-inflammatory pattern in African vs. mixed responses as was seen in HEU vs. UE. This was not observed. When the proportion of responder APCs (to PAMP stimulation) was compared between African and mixed groups, only 6 differences were detected, which were within the expected level of error using a P value of <0.05. When the amount of cytokine produced per cell was compared, a pattern emerged that may suggest a pro-inflammatory cDC in mixed vs. African infants at 6 weeks. This pattern was weaker and distinct in its timing compared with changes in HEU vs. UE (and does not support a pro-inflammatory pattern in African vs. mixed). Therefore, although genetic variability is a probable contributor, differences in racial composition between groups were likely not the cardinal factor determining the observed variability in innate immune responses between HEU and UE infants.
Differences in breast-feeding practices may have contributed to the differences in innate immune development between HEU and UE. Breast milk contains compounds that modulate PRR-mediated immune responses, including immunoglobulins, antimicrobial proteins/peptides, nucleotides, and oligosaccharides.46,47 Breast milk can also alter TLR responses to PRR-specific agonists.48 Clinical evidence indicates that the period of increased morbidity from diarrheal infections in HEU infants coincides with the average time of weaning.49 The median duration of exclusive breast-feeding in UE infants of this cohort was 12 weeks, whereas HEU infants were not breast-fed as recruitment occurred before the shift toward recommended breast-feeding for infants born to HIV-positive mothers.9 However, it is noteworthy that breast-feeding provides greater protection from diarrheal disease as opposed to respiratory tract infections,50 which was the leading cause of severe illness and hospitalization of HEU infants in this study and infectious morbidity and mortality in HEU infants.7,12 Lack of breast-feeding is thus likely to only partially explain increased morbidity and altered immune status in HEU vs. UE infants.
Our goal had not been to delineate precise etiological cause–effect relationships, but was to first determine if differences in innate immunity between HEU and UE existed at all, and if so for how long they persisted. Our data indicate that innate immune response to PRR stimulation differed between HEU and UE infants. Specifically, innate ontogeny initially followed a different trajectory in HEU compared with UE infants, but this difference became less apparent as the infant matured. No clear etiology for these differences can at this stage be assigned because several factors may have contributed to our observation of significant differences in innate immune response between HEU and UE in the earliest postnatal period. Follow-up studies can now focus on examining the relative contribution of potential etiological factors (ranging from HIV exposure to variables associated with host genetics) to differences in innate immune ontogeny. Our data support the notion that early life represents a window of significant vulnerability for altered immune development.14,51 Elucidating the mechanisms that drive these changes in innate immune development may move us closer to identifying targeted strategies to decrease infectious morbidity and mortality in HEU infants. This has potentially broad implications for the rapidly growing population of HEU infants.
The authors sincerely thank the participants and their families for their ongoing support of this study. The authors gratefully acknowledge the support of the Immunology Unit and Virology Division at the National Health Laboratory Service at Tygerberg Hospital, the Tygerberg Children's Hospital and Children's Infectious Disease Clinical Research Unit (KID-CRU), Dr Emma Krzesinski, Dr Elke Maritz, Dr Magdel Roussouw, Dr Sadeeka Williams, Ronell Taylor, Sharifah Sylvester, and Kurt Smith.
3. Thea DM, St Louis ME, Atido U, et al.. A prospective study of diarrhea and HIV-1 infection among 429 Zairian infants. N Engl J Med. 1993;329:1696–1702.
4. Brahmbhatt H, Kigozi G, Wabwire-Mangen F, et al.. Mortality in HIV-infected and uninfected children of HIV-infected and uninfected mothers in rural Uganda. J Acquir Immune Defic Syndr. 2006;41:504–508.
5. Marinda E, Humphrey JH, Iliff PJ, et al.. Child mortality according to maternal and infant HIV status in Zimbabwe. Pediatr Infect Dis J. 2007;26:519–526.
6. Filteau S. The HIV-exposed, uninfected African child. Trop Med Int Health. 2009;14:276–287.
7. Koyanagi A, Humphrey JH, Ntozini R, et al.. Morbidity among human immunodeficiency virus-exposed but uninfected, human immunodeficiency virus-infected, and human immunodeficiency virus-unexposed infants in Zimbabwe before availability of highly active antiretroviral therapy. Pediatr Infect Dis J. 2011;30:45–51.
8. Epalza C, Goetghebuer T, Hainaut M, et al.. High incidence of invasive group B streptococcal infections in HIV-exposed uninfected infants. Pediatrics. 2010;126:e631–638.
9. Slogrove A, Reikie B, Naidoo S, et al.. HIV-exposed uninfected infants are at increased risk for severe infections in the first year of life. J Trop Pediatr. 2012;58:505–508.
10. Bryce J, Boschi-Pinto C, Shibuya K, et al.. WHO estimates of the causes of death in children. Lancet. 2005;365:1147–1152.
11. Rudan I, Boschi-Pinto C, Biloglav Z, et al.. Epidemiology and etiology of childhood pneumonia. Bull World Health Organ. 2008;86:408–416.
12. Punpanich W, Groome M, Muhe L, et al.. Antibiotic and systemic therapies for pneumonia in human immunodeficiency virus (HIV)-infected and HIV-exposed children. J Infect Dev Ctries. 2012;6:109–119.
13. Division of AIDS. Table for Grading the Severity of Adult and Pediatric Adverse Events. Version 1.0 December 2004; clarification August 2009. Available at: http://rcc.tech-res.com/tox_tables.htm
. Accessed August 2012.
14. Kollmann TR, Levy O, Montgomery RR, et al.. Innate immune function by Toll-like receptors: distinct responses in newborns and the elderly. Immunity. 2012;37:771–783.
15. Dauby N, Goetghebuer T, Kollmann TR, et al.. Uninfected but not unaffected: chronic maternal infections during pregnancy, fetal immunity, and susceptibility to postnatal infections. Lancet Infect Dis. 2012;12:330–340.
16. Black RE, Morris SS, Bryce J. Where and why are 10 million children dying every year? Lancet. 2003;361:2226–2234.
17. National Department of Health SA. The National Antenatal Sentinel HIV and Syphilis Prevalence Survey, South Africa. Pretoria, South Africa: South African National Department of Health; 2010.
18. Jansen K, Blimkie D, Furlong J, et al.. Polychromatic flow cytometric high-throughput assay to analyze the innate immune response to Toll-like receptor stimulation. J Immunol Methods. 2008;336:183–192.
19. Blimkie D, Fortuno ES III, Yan H, et al.. Variables to be controlled in the assessment of blood innate immune responses to Toll-like receptor stimulation. J Immunol Methods. 2011;366:89–99.
20. Engel AL, Holt GE, Lu H. The pharmacokinetics of Toll-like receptor agonists and the impact on the immune system. Expert Rev Clin Pharmacol. 2011;4:275–289.
21. Lee JA, Spidlen J, Boyce K, et al.. MIFlowCyt: the minimum information about a Flow Cytometry Experiment. Cytometry A. 2008;73:926–930.
22. Blimkie D, Fortuno ES III, Thommai F, et al.. Identification of B cells through negative gating—an example of the MIFlowCyt standard applied. Cytometry A. 2010;77:546–551.
23. Maecker HT, Trotter J. Flow cytometry controls, instrument setup, and the determination of positivity. Cytometry A. 2006;69:1037–1042.
24. Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. 1990;1:43–46.
25. Chougnet C, Kovacs A, Baker R, et al.. Influence of human immunodeficiency virus-infected maternal environment on development of infant interleukin-12 production. J Infect Dis. 2000;181:1590–1597.
26. Schramm DB, Kuhn L, Gray GE, et al.. In vivo effects of HIV-1 exposure in the presence and absence of single-dose nevirapine on cellular plasma activation markers of infants born to HIV-1-seropositive mothers. J Acquir Immune Defic Syndr. 2006;42:545–553.
27. Velilla PA, Montoya CJ, Hoyos A, et al.. Effect of intrauterine HIV-1 exposure on the frequency and function of uninfected newborns' dendritic cells. Clin Immunol. 2008;126:243–250.
28. Slyker JA, Lohman-Payne B, John-Stewart GC, et al.. The impact of HIV-1 infection and exposure on natural killer (NK) cell phenotype in Kenyan infants during the first year of life. Front Immunol. 2012;3:399.
29. Aghaeepour N, Chattopadhyay PK, Ganesan A, et al.. Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays. Bioinformatics. 2012;28:1009–1016.
30. Shapiro RL, Lockman S. Mortality among HIV-exposed infants: the first and final frontier. Clin Infect Dis. 2010;50:445–447.
31. Nguyen M, Leuridan E, Zhang T, et al.. Acquisition of adult-like TLR4 and TLR9 responses during the first year of life. PLoS One. 2010;5:e10407.
32. Belderbos ME, van Bleek GM, Levy O, et al.. Skewed pattern of Toll-like receptor 4-mediated cytokine production in human neonatal blood: low LPS-induced IL-12p70 and high IL-10 persist throughout the first month of life. Clin Immunol. 2009;133:228–237.
33. Corbett NP, Blimkie D, Ho KC, et al.. Ontogeny of Toll-like receptor mediated cytokine responses of human blood mononuclear cells. PLoS One. 2010;5:e15041.
34. Burl S, Townend J, Njie-Jobe J, et al.. Age-dependent maturation of Toll-like receptor-mediated cytokine responses in Gambian infants. PLoS One. 2011;6:e18185.
35. Lisciandro JG, Prescott SL, Nadal-Sims MG, et al.. Ontogeny of Toll-like and NOD-like receptor-mediated innate immune responses in Papua New Guinean infants. PLoS One. 2012;7:e36793.
36. Teran R, Mitre E, Vaca M, et al.. Immune system development during early childhood in tropical Latin America: evidence for the age-dependent down regulation of the innate immune response. Clin Immunol. 2011;138:299–310.
37. Reikie BA, Adams RC, Ruck CE, et al.. Ontogeny of Toll-like receptor mediated cytokine responses of South African infants throughout the first year of life. PLoS One. 2012;7:e44763.
38. Figueiredo CA, Alcantara-Neves NM, Veiga R, et al.. Spontaneous cytokine production in children according to biological characteristics and environmental exposures. Environ Health Perspect. 2009;117:845–849.
39. Sperling RS, Shapiro DE, McSherry GD, et al.. Safety of the maternal-infant zidovudine regimen utilized in the Pediatric AIDS Clinical Trial Group 076 Study. AIDS. 1998;12:1805–1813.
40. Bunders MJ, Bekker V, Scherpbier HJ, et al.. Haematological parameters of HIV-1-uninfected infants born to HIV-1-infected mothers. Acta Paediatr. 2005;94:1571–1577.
41. Bunders M, Thorne C, Newell ML, et al.. Maternal and infant factors and lymphocyte, CD4 and CD8 cell counts in uninfected children of HIV-1-infected mothers. AIDS. 2005;19:1071–1079.
42. Boulware DR, Meya DB, Bergemann TL, et al.. Antiretroviral therapy down-regulates innate antiviral response genes in patients with AIDS in sub-Saharan Africa. J Acquir Immune Defic Syndr. 2010;55:428–438.
43. Arama C, Giusti P, Bostrom S, et al.. Interethnic differences in antigen-presenting cell activation and TLR responses in Malian children during Plasmodium falciparum
malaria. PLoS One. 2011;6:e18319.
44. Kollmann TR. Variation between populations in the innate immune response to vaccine adjuvants. Front Immunol. 2013;4:81.
45. Randhawa AK, Shey MS, Keyser A, et al.. Association of human TLR1 and TLR6 deficiency with altered immune responses to BCG vaccination in South African infants. PLoS Pathog. 2011;7:e1002174.
46. M'Rabet L, Vos AP, Boehm G, et al.. Breast-feeding and its role in early development of the immune system in infants: consequences for health later in life. J Nutr. 2008;138:1782S–1790S.
47. Peroni DG, Pescollderungg L, Piacentini GL, et al.. Immune regulatory cytokines in the milk of lactating women from farming and urban environments. Pediatr Allergy Immunol. 2010;21:977–982.
48. LeBouder E, Rey-Nores JE, Raby AC, et al.. Modulation of neonatal microbial recognition: TLR-mediated innate immune responses are specifically and differentially modulated by human milk. J Immunol. 2006;176:3742–3752.
49. Kourtis AP, Wiener J, Kayira D, et al.. Health outcomes of HIV-exposed uninfected African infants. AIDS. 2013;27:749–759.
50. WHO Collaborative Study Team on the Role of Breastfeeding on the Prevention of Infant Mortality. Effect of breastfeeding on infant and child mortality due to infectious diseases in less developed countries: a pooled analysis. Lancet. 2000;355:451–455.
51. Dietert RR. Developmental immunotoxicology (DIT): windows of vulnerability, immune dysfunction and safety assessment. J Immunotoxicol. 2008;5:401–412.