Conceived and designed the experiments: TS RGMB MY ES. Performed the experiments: YD HW. Analyzed the data: YD HW. Wrote the paper: YD. Critically revised the statistical methods: IA LCR. Designed the statistical analysis: LCR.
The authors have declared that no competing interests exist.
Exposure to environmental factors during fetal life and infancy is thought to play an important role in the early development of innate and adaptive immunity. The immunological relationship between mother and infant and the effect that environmental exposures have during pregnancy and early childhood have not been studied extensively. Here the production of cytokines was measured in 146 pairs of mothers and their 2- month-old infants. The effect of place of residence, socio-economic variables, parasitic infections as well as maternal and child characteristics on measured cytokine production was determined. Mothers producing high levels of IL-10, IFN-γ and IL-5 were more likely to have infants who also produced high levels of these cytokines either spontaneously (OR 2.6(95%CI 1.2–5.4), OR 2.9(CI 1.3–6.6), OR 11.2(CI 4.6–27.2), respectively) or in response to PHA (IL-10: OR 3.0(CI 1.4–6.6), IFN-γ: OR 2.0(CI 1.0–4.2), respectively) even after adjustment for potential confounding variables. This was not the case for TNF-α. In response to LPS, place of residence was a strong determinant of infant IL-10 (OR 0.2(CI 0.1–0.9)) and TNF-α (OR 0.3(CI 0.1–0.9)) production. Maternal protozoan infections was independently associated with reduced infant IL10 in response to PHA and to LPS as well as reduced TNF-α and IFN-γ in response to PHA. These results indicate strong relationship between maternal and infant's cellular immune responses even after taking into account many environmental influences that could affect infant's response directly or indirectly through uterine microenvironment. However, place of residence and intestinal infections may still directly affect the immune responses of the infant. Taken together, the study provides evidence for imprinted cytokine responses of an infant which may have implications for their reaction to incoming antigens, warranting further investigation into the role that genetics or epigenetics play in shaping the cytokine response by an infant to self or external antigens.
In utero environment has evolved to ensure that the semi-allogeneic fetus can grow optimally, with placenta as an immunological barrier between maternal and fetal circulation. It is known that maternal nutrient imbalance or exposure to allergens or pathogens may modulate the immune responses of the fetus. The capacity of cord blood mononuclear cells (CBMC) of neonates born to mothers infected with filarial parasite
In the present study we have investigated in Indonesia where environmental exposures are highly varied, the relationship between maternal and infant's cellular immune responses at early life before the start of vaccinations. This would circumvent the problems when studying cord blood responses, namely the effect that physiological stress caused during birth might exert and the possible cross contamination with maternal blood. The specific aims of this study were twofold: a) to assess how close the relationship is between cytokine responses in pregnant women and their children and b) to evaluate the associations between environmental factors and maternal characteristics that in turn affect cytokine responses of their children. To this end, a conceptual framework was proposed to define the relationship between environmental factors and maternal characteristics and the infant's immune system. This framework was used to then guide the inclusion of the influential variables in the multiple logistic regression model.
This study was conducted according to the principles expressed in the Declaration of Helsinki. The study was approved by Ethics Committee of Faculty of Medicine, University of Indonesia. All mothers were provided written informed consent for the collection of samples from themselves and their children and for subsequent analysis.
The present study was part of a birth cohort study examining the immune responses of children born to helminth infected mothers in Bekasi District, located approximately 30 km from the capital city Jakarta, Indonesia. Between 2002 and 2004, pregnant mothers and their infants were recruited from two adjacent villages, Jati Sampurna (JS) and Jati Karya (JK). These villages are in a peri-urban area, with a mixture of farmers and small traders. All pregnant mothers in second and third trimester from the villages were invited via midwives to participate in the study. Demographic and socio-economic data, as well as maternal characteristics during pregnancy were collected by questionnaires. Gestation age at the time of blood collection was estimated from the last menstrual date and confirmed by palpation and measurement of fundal height. Information about child gender and birth weight was obtained from the mothers during house-to-house visits.
For determination of microfilaremia, one ml of maternal venous blood collected between 8–11 pm was filtered through 5 µm pore membrane (Millipore, Billerica, MA, USA). Circulating
The procedures of whole blood culture are based on optimized protocols developed during pilot studies. Heparinized venous blood obtained from pregnant mothers and their babies was processed within 6 hours after venipuncture. The whole blood was diluted 10 times as described before
The beads used to determine cytokine levels were prepared by using reagents described in
Recombinant protein | Capture Ab | Detection Ab | ||||||
Cytokine | Cat. No. | Source | Clone | Cat. No. | Source | Clone | Cat. No. | Source |
IL-10 | M191003 | Sanquin | IL10-5 | M9210 | Sanquin | IL10-2 | M9216 | Sanquin |
TNF-α | PHC3015 | BS | TNFα-7 | M9179 | Sanquin | TNFα-5 | M9218 | Sanquin |
IL-13 | 94/622 | NIBSC | IL13-1 | M9186 | Sanquin | IL13-2 | M9217 | Sanquin |
IFN-γ | PHC4031 | BS | MD5 | M9159 | Sanquin | MD2 | M9219 | Sanquin |
*All reagents listed were obtained from the sources indicated from the following abbreviations: Sanquin = Stichting Sanquin Bloedvoorziening (Amsterdam, The Netherlands); BS = BioSource (Nivelles, Belgium); NIBSC = National Institute for Biological Standards & Controls (Potters Bar, UK), with catalogue numbers (Cat. No.) for each reagent given.
The optimizations of multiple bead-based assay and the cytokine measurements were performed as described
Mean fluorescent intensity from all cytokines was measured using Luminex IS 100 (Luminexcorp, Austin, TX, USA) and data were analyzed by Star Station software analysis (Applied Cytometry, Sheffield, UK). The measurements were done once, and blank values were substracted from all readings. The minimum detection limit was determined by adding two standard deviations to the mean of mean fluorescence intensity from 30 blanks assayed separately. The detection limits for IL-10, TNF-α, IL-13 and IFN-γ were 6.5 pg/ml, 1.7 pg/ml, 12.5 pg/ml, and 3.6 pg/ml, respectively.
IL-5 was measured by ELISA as described previously
All cytokine levels below detection limit were given half of the threshold value. Raw cytokine productions were used for analysis, since the results showed the cytokine responses to antigen stimulation not only higher or the same, but also lower than spontaneous cytokine productions.
Mothers were classified into high producers (H) or low producers (L) based on median cytokine levels. Since almost all cytokine data from mothers and infants were not normally distributed, the Mann-Whitney
We used multivariable logistic regression model to investigate the association between mother's cytokine production and infant's cytokine production. The outcome for logistic regression model was infant's cytokine which was grouped into: high producer and low producer, based on the median. Mother's cytokine production was treated as exposure variable. Other variables, such as demographic and socio-economic factors, maternal characteristics, maternal parasitological data and child characteristics, were treated as potential confounders.
The original plan for the logistic regressions was based on a conceptual framework (
Mother Block 1 consists of univariate and multivariate logistic regression models for maternal demographic and socio-economic data, such as place of residence, nativity, education, material of house, water supply, cooking fuel. The outcome variable is maternal cytokine producer status. Mother Block 2 consists of univariate and multivariate logistic regression models for maternal characteristics, such as number of age, number of pregnancies, parasitological data. The outcome variable is maternal cytokine producer status. Child Block 1 consists of univariate and multivariate logistic regression models for maternal demographic and socio-economic data, such as place of residence, nativity, education, material of house, water supply, cooking fuel. The outcome variable is child cytokine producer status. Child Block 2 consists of univariate and multivariate logistic regression models for maternal characteristics, such as number of age, number of pregnancies, parasitological data. The outcome variable is child cytokine producer status. Child Block 3 consists of univariate and multivariate logistic regression models for child characteristics, such as birth weight, mode of delivery, breast feeding. The outcome variable is child cytokine producer status.
Environmental factors included were demographic and socio-economic variables (
Demographic and socio-economic data | Maternal parasitological data | ||
Jati Sampurna village | 86/170 (51%) | Microfilaria positive | 8/170 (5%) |
Jati Karya village | 84/170 (49%) | ICT positive | 41/170 (24%) |
Native | 119/169 (70%) | ||
Non-native | 50/169 (30%) | 24/161 (15%) | |
12/161 (7%) | |||
Never schooled or primary school | 113/169 (67%) | Hookworm | 28/161 (17%) |
Higher education | 56/169 (33%) | 57/161 (35%) | |
79/161 (49%) | |||
Unemployed | 156/169 (92%) | ||
Others (trader, employee) | 13/169 (8%) | 36/161 (22%) | |
6/161 (4%) | |||
Wood | 44/169 (26%) | 5/161 (3%) | |
Brick | 121/169 (72%) | 1/161 (1%) | |
Semi wood/brick | 4/169 (2%) | 2/161 (1%) | |
44/161 (27%) | |||
Well | 47/169 (28%) | ||
Pump | 120/169 (71%) | No IH or IP infection | 82/161 (51%) |
Pipe | 2/169 (1%) | IH infection only | 35/161 (21%) |
IP infection only | 22/161 (14%) | ||
Wood | 22/167 (13%) | Co-infection of IH and IP | 22/161 (14%) |
Kerosene | 125/167 (75%) | ||
Gas | 20/167 (12%) | ||
Primigravid | 56/169 (34%) | ||
Multigravid | 113/169 (66%) | ||
25.5 (5.9) | |||
< 25 yrs | 84/169 (50%) | ||
≥25 yrs | 85/169 (50%) | ||
3200 (3000–3500) | |||
Vaginal | 138/142 (97%) | ||
Caesarian section | 4/142 (3%) | ||
Exclusive breast feeding | 101/119 (85%) | ||
Partial breast feeding | 13/119 (11%) | ||
No breast feeding | 5/119 (4%) |
*any helminth infection: either single or mixed infections of intestinal helminth and filarial.
IH = Intestinal helminth, IP = Intestinal protozoan.
The same steps were applied to identify the variables which influenced the infant production of cytokines, logistic regressions with the binary outcome producer status of the child, and exposures were grouped into the two previous blocks, environmental factors and maternal characteristics during pregnancy and a third block of child characteristics: gender, birth weight, mode of delivery and breast feeding status: exclusive breast-feeding (receiving only breast milk for at least 6 months), partial breast-feeding (receiving breast and formula milk), or no breast-feeding. The variables from first and second child blocks were considered as more distal determinants than the third child block
All statistical analyses were performed using SPSS version 15. Hosmer-Lemeshow Goodness-of-Fit test was done at final step for each cytokine/stimuli, to ensure that the final model adequately fit the data.
One hundred and seventy mothers in second and third trimester of pregnancy donated their blood for immunological studies and subsequently after birth one hundred and forty six infants between 1 to 17 weeks old (before any vaccination) participated in the study. Twenty four infants could not be included in the study due to refusal of parents to donate their infant blood or due to infant death, being sick, moving outside the study area, or being untraceable. The analysis of maternal and infant relationships was done for 146 pairs of mother and child for spontaneous or mitogen-induced cytokine production, and 74 pairs of mother and child for LPS-induced cytokine production. The reason for lower number for LPS is the late arrival of this stimulus, at a time point when the study has already started.
Maternal cytokine responses, spontaneous (to medium), to PHA and to LPS are given in
Solid lines represent median levels of each cytokine; broken lines represent the detection limits of each cytokine. Each dot represents one individual. The number of non-detectables are given in parenthesis: (A) IL-10 medium, PHA, LPS (93, 1, 0); (B) TNF-α medium, PHA, LPS (135, 6, 0); (C) IFN-γ medium, PHA, LPS (119, 22, 28); (D) IL-5 medium, PHA, LPS (91, 2, 37).
As a whole, the comparison between cytokine levels of infants born to high and low producer mothers revealed that infants born to high producer mothers had significantly higher IL-10, IL-5 and IFN-γ responses (
A: IL-10, B: TNF-α, C: IFN-γ, D: IL-5. The line within the box represents the median (50th percentile), with the lower and upper borders representing the interquartile range (25th and 75th percentiles). The whiskers extend to the 10th and 90th percentiles. The closed dots represent values above the 90th percentiles. Detection limit of each cytokine is shown as a broken line. *0.05>
Maternal Cytokine | Medium | PHA | LPS | |||
Crude OR (95% CI) | Crude OR (95% CI) | Crude OR (95% CI) | ||||
IL-10 | ||||||
Low producers | reference | reference | reference | |||
High producers | 2.9 (1.5–5.8) | 0.002 | 4.2 (2.1–8.3) | <0.001 | 3.3 (1.3–8.5) | 0.02 |
TNF-α | ||||||
Low producers | reference | reference | reference | |||
High producers | 1.8 (0.8–4.0) | 0.14 | 1.7 (0.9–3.4) | 0.10 | 0.7 (0.3–1.8) | 0.49 |
IFN-γ | ||||||
Low producers | reference | reference | reference | |||
High producers | 2.6 (1.2–5.4) | 0.01 | 1.9 (1.0–3.7) | 0.06 | 3.0 (1.2–7.8) | 0.02 |
IL-5 | ||||||
Low producers | reference | reference | reference | |||
High producers | 8.4 (3.9–17.9) | <0.001 | 1.7 (0.9–3.3) | 0.11 | 2.7 (1.1–6.9) | 0.03 |
Medium | PHA | LPS | ||||
Adjusted OR (95% CI) | Adjusted OR (95% CI) | Adjusted OR (95% CI) | ||||
Maternal IL-10 | ||||||
Low producers | reference | reference | reference | |||
High producers | 2.6 (1.2–5.4) | 3.0 (1.4–6.6) | 1.6 (0.5–5.9) | 0.45 | ||
Village | ||||||
JS | reference | reference | ||||
JK | 0.7 (0.3–1.5) | 0.38 | 0.2 (0.1–0.9) | |||
Education | ||||||
Low | reference | |||||
High | 0.7 (0.3–1.7) | 0.44 | ||||
Cooking fuel | ||||||
Wood | reference | |||||
Kerosene | 1.3 (0.4–3.7) | 0.68 | ||||
Gas | 0.5 (0.1–2.3) | 0.34 | ||||
Status of IH and IP infections | ||||||
Negative | reference | reference | reference | |||
IH only | 0.5 (0.2–1.4) | 0.20 | 0.7 (0.3–1.7) | 0.39 | 0.5 (0.1–2.3) | 0.38 |
IP only | 0.5 (0.2–1.4) | 0.47 | 0.3 (0.1–0.9) | 0.1 (0.03–0.6) | ||
IH + IP | 0.8 (0.3–2.3) | 0.71 | 0.5 (0.2–1.7) | 0.29 | 0.2 (0.1–0.9) | |
Maternal TNF-α | ||||||
Low producers | reference | reference | reference | |||
High producers | 1.7 (0.7–4.1) | 0.20 | 1.9 (0.9–4.0) | 0.11 | 0.5 (0.2–1.5) | 0.23 |
Village | ||||||
JS | reference | reference | ||||
JK | 1.7 (0.8–3.8) | 0.16 | 0.3 (0.1–0.9) | |||
Native | reference | |||||
Non native | 1.9 (0.8–4.5) | 0.17 | ||||
Education | ||||||
Low | reference | reference | ||||
High | 0.4 (0.2–0.9) | 0.7 (0.3–1.7) | 0.44 | |||
Cooking fuel | ||||||
Wood | reference | |||||
Kerosene | 2.6 (0.8–7.8) | 0.10 | ||||
Gas | 17.1 (3.0–98.1) | |||||
Status of IH and IP infections | ||||||
Negative | reference | |||||
IH only | 1.3 (0.5–3.4) | 0.54 | ||||
IP only | 0.2 (0.04–0.6) | |||||
IH + IP | 0.7 (0.2–2.1) | 0.56 | ||||
Maternal IFN-γ | ||||||
Low producers | reference | reference | reference | |||
High producers | 2.9 (1.3–6.6) | 2.0 (1.0–4.2) | 2.8 (1.03–7.8) | |||
Village | ||||||
JS | reference | reference | ||||
JK | 0.4 (0.2–0.9) | 0.2 (0.1–0.6) | ||||
Education | ||||||
Low | reference | |||||
High | 0.4 (0.2–0.9) | |||||
Occupation | ||||||
Unemployed | reference | |||||
Others | 0.7 (0.2–2.8) | 0.62 | ||||
No. of pregnancies | ||||||
Primigravid | reference | |||||
Multigravid | 0.5 (0.2–1.2) | 0.11 | ||||
Status of IH and IP infections | ||||||
Negative | reference | |||||
IH only | 0.9 (0.4–2.1) | 0.79 | ||||
IP only | 0.2 (0.1–0.7) | |||||
IH + IP | 0.6 (0.2–1.7) | 0.37 | ||||
Maternal IL-5 | ||||||
Low producers | reference | reference | ||||
High producers | 11.2 (4.6–27.2) | 1.7 (0.8–3.3) | 0.15 | |||
Village | ||||||
JS | reference | |||||
JK | 1.3 (0.6–2.9) | 0.51 | ||||
Maternal age | ||||||
<25 yrs | reference | |||||
≥25 yrs | 2.8 (1.2–6.9) | |||||
Status of IH and IP infections | ||||||
Negative | reference | |||||
IH only | 2.2 (0.9–5.3) | 0.08 | ||||
IP only | 1.2 (0.4–3.2) | 0.76 | ||||
IH + IP | 1.5 (0.5–4.1) | 0.43 |
OR = Odds ratio;
JS = Jati Sampurna, JK = Jati Karya, IH = Intestinal helminth, IP = Intestinal protozoan.
Mothers with higher spontaneous IL-10 production had children with higher spontaneous IL-10 release (OR 2.6(95%CI 1.2–5.4)) (
Mothers with high IL-10 in response to PHA had children with high IL-10 in response to PHA (OR 3.0(95%CI 1.4–6.6)), but the value is much lower than before controlling for environmental measures; this was most marked when controlling for maternal intestinal protozoa, indicating that intestinal protozoan infection is an independent predictor of a child's IL-10 production in response to PHA and a confounder of this relationship. Village of residence and maternal education, which were associated with high IL-10 production of a child in response to PHA were no longer significant after adjustment for mother's IL-10 production against PHA.
Mothers with high IL-10 in response to LPS had children with high IL-10 in response to LPS, but the magnitude of association was much smaller and no longer significant when maternal intestinal parasitic infections and village of residence were adjusted for. Both mothers (Chi-Square test,
There were no significant associations between maternal and infant TNF-α production (
Intestinal protozoan infection of mothers was significantly associated with lower TNF-α responses to mitogen in infants (OR 0.2(95%CI 0.04–0.6)). Other variables were not significant anymore after adjustment. TNF-α production of infant in response to LPS was not associated with any of maternal factors, except for residence, where infants born and living in JK had significantly lower levels than those born in JS (OR 0.3(95%CI 0.1–0.9)).
Maternal spontaneous IFN-γ response was significantly associated with child cytokine response (OR 2.9(95%CI 1.3–6.6)), after adjustment for residence (OR 0.4(95%CI 0.2–0.9)) and educational level (OR 0.4(95%CI 0.2–0.9)). Residence factor increased the crude OR for maternal-infant relationship in spontaneous IFN-γ by 19% (adjusted OR 3.1(95%CI 1.4–6.8)). As seen for maternal IL-10 response to LPS, maternal spontaneous IFN-γ production was the mediator between residence factor and infant spontaneous IFN-γ. Number of pregnancies, which was significantly associated with maternal IFN-γ production, lost significance in the final child model.
The relationship between maternal and child's IFN-γ was less significant in response to PHA (OR 2.0(95%CI 1.0–4.2)). Maternal intestinal protozoan infection had a stronger effect on child cytokine production (OR 0.2(95%CI 0.1–0.7)) than maternal IFN-γ. In responses to LPS, maternal IFN-γ production was a significant determinant of the infant's IFN-γ production (OR 2.8(95%CI 1.0–7.8)) although the effect of residence was stronger (OR 0.2(95%CI 0.1–0.6)). Since the level of IFN-γ production in response to LPS was considered low in mothers and infants (
For spontaneous IL-5 release, there was a significant association between maternal and infant responses (OR 11.2(95%CI 4.6–27.2)). Younger age of mother was associated with higher spontaneous IL-5 production (data not shown) but not with infant's IL-5; however in the final model (
Maternal IL-5 responses to PHA had no significant effect on child's IL-5 to PHA, however there was a tendency for intestinal helminth infections of mother to be associated with higher IL-5 responses to PHA of infants (OR 2.2(95%CI 0.9–5.3)).
This study indicates that maternal cytokine responses are important determinants of the corresponding cytokines in infants during early life. This was particularly the case for spontaneous production of cytokines. Spontaneous production of IL-10, IFN-γ and IL-5 by two month old infants was strongly determined by maternal cytokine and was not influenced by any other environmental variables recorded in our study. Relationship between maternal cytokine responses to PHA and the corresponding infant's cytokine production was also found in the production of IL-10, and to lesser extent of IFN-γ. The findings, especially for IL-10 production, that infants up to 17 weeks still inherited a similar intrinsic capacity to produce this cytokine as their mothers is supported by the findings of a cross-sectional study of allergic and non allergic mothers in Europe, showing that the production of IL-10 and IFN-γ in response to medium (spontaneous production) and after PHA stimulation were correlated between mothers and their 2 year-old children irrespective of maternal atopic status
TNF- α as a pro-inflammatory cytokine was shown to have no strong associations between mother and child. This may simply suggest that the environment in the first several months of an infant's life has a strong effect on the immune system. For example, infections such as rotavirus which are prevalent very early in infants may alter the TNF-α responses
We used crosstabs to find the association between education and the use of cooking fuel. The result showed that higher education may be associated with higher economic status, which explains why this group used more gas stove than wood. The finding that cooking fuel only affected the child's spontaneous TNF-α release but not maternal cytokine may indicate that child immune system is more vulnerable to this kind of environmental exposure.
With respect to maternal infections, the final model of multiple logistic regression in our study showed that intestinal parasitic infections especially protozoa influenced the relationship between maternal and infant IL-10 and IFN-γ production in responses to PHA.
In conclusion this study provides evidence for strong associations between maternal and infant cytokine responses in geographical areas where environmental exposures are highly varied such as in Indonesia. However, the mechanisms behind the strong associations have not been elucidated and form the basis for future studies. It is possible that maternal cytokine responses specifically drive the infant cytokine responses, either by crossing or transmitting signals through the maternal-fetal interface. There is so far no evidence for such direct cross talk between mother and fetus. It is also possible that as yet unidentified environmental factor affects both maternal and infant cytokine responses leading to the correlations observed. Another possibility lies in the genetic link between mother and infant. Whether such cytokine imprinting affects infant's responses to vaccinations or incoming infections needs to be studied in longitudinal manner along with possible associated genetic or epigenetic modifications.
We are indebted to all study participants in Jati Sampurna and Jati Karya and to Dr. Esther MM Siregar and her staff at PHC Jati Sampurna. We would like to thank Dr. Henk te Velthuis for generously providing the antibodies and Luminex machine at Sanquin-CLB, and Klaasse Bos for her technical advice on Luminex.