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Background: In utero or early-life exposure to aflatoxin, which contaminates staple crops in disadvantaged settings, may compromise pregnancy and infant outcomes, but investigations into the extent, persistence, and determinants of aflatoxin exposure at these life stages have lacked longitudinal data collection and broad geographic representation. Objectives: Aflatoxin exposure and selected determinants thereof were characterized in mother-child dyads with serial plasma/serum samples in prenatal, perinatal, and early life in Malawi and Bangladesh. Methods: Circulating aflatoxin B1 (AFB1)-lysine albumin adducts were measured in dyads from Bangladesh (n = 573; maternal first and third trimester, 3 mo postpartum, cord blood, infant 24 mo) and Malawi (n = 255; maternal second and third trimester, 6 mo postpartum, infant 6 and 18 mo) with isotope dilution mass spectrometry. We examined AFB1-lysine adduct magnitude, persistence, seasonality, and associations with infant feeding, and estimated daily AFB1 intake. Results: Maternal AFB1-lysine was higher in Malawi (98% detectable; median: 0.469, IQR: 0.225-1.027 pg/μL) than in Bangladesh (59%; 0.030, nondetectable [nd]-0.077 pg/μL). Although estimated dietary exposure in Malawi was temporally stable (648 ng AFB1/day), estimated intake in Bangladesh was reduced by 94% between rainy and winter seasons (98 to 6 ng/day). AFB1-lysine was low in cord blood from Bangladesh (15% detectable; 0.045, 0.031-0.088 pg/μL among detectable) and in Malawian infants at 6 mo of age (0.072, nd-0.236 pg/μL), but reached maternal concentrations by 18 or 24 mo (Bangladesh: 0.034, nd-0.063 pg/μL; Malawi: 0.370, 0.195-0.964 pg/μL). In Malawian infants, exclusive breastfeeding at 3 mo was associated with 58% lower AFB1-lysine concentrations at 6 mo compared with other feeding modes (P = 0.010). Conclusions: Among pregnant women, aflatoxin exposure was persistently high in Malawi, while lower and seasonal in Bangladesh. Infants were partially protected from exposure in utero and with exclusive breastfeeding, but exposures reached adult levels by 18-24 mo of age.
This study utilized serum or plasma samples and data previously collected from 2 completed trials: the cluster-randomized, controlled, double-blind JiVitA-3 trial in the Gaibandha and Rangpur Districts of Bangladesh (clinicaltrials.gov registration {“type”:”clinical-trial”,”attrs”:{“text”:”NCT00860470″,”term_id”:”NCT00860470″}}NCT00860470) (22) and the individually randomized, controlled, partially double-blind iLiNS-DYAD-M trial in the Mangochi District of Malawi (clinicaltrials.gov registration {“type”:”clinical-trial”,”attrs”:{“text”:”NCT01239693″,”term_id”:”NCT01239693″}}NCT01239693) (23). The JiVitA-3 trial was approved by institutional review boards at the Johns Hopkins Bloomberg School of Public Health (Baltimore, MD, USA) and the Bangladesh Medical Research Council (Dhaka, Bangladesh). The iLiNS-DYAD-M trial was approved by the College of Medicine Research and Ethics Committee of the University of Malawi (Blantyre, Malawi) and the Ethics Committee of the Pirkanmaa Hospital District (Tampere, Finland). All participants confirmed their informed consent orally (JiVitA-3) or with signatures or thumbprints on consent forms (iLiNS-DYAD-M). In both studies, consent was provided with the understanding that their samples or (anonymized) data may be used in future analysis. Local communities were given opportunities to provide input on study design and implementation. All data used in the present analysis were anonymized; only principal investigators and appropriate members of the respective research teams have access to the secured, nonanonymized data. Among many other endpoints, both studies collected data for the assessment of pregnancy outcomes and child anthropometrics from birth until 24 mo of age in the JiVitA-3 trial and until 18 mo of age in iLiNS-DYAD-M. The JiVitA-3 trial was designed to test the effects of an antenatal multiple micronutrient supplement (MMS) compared with a standard-of-care control iron and folic acid (IFA) supplement. Similarly, the iLiNS-DYAD-M trial also examined the effects of MMS and IFA prenatal supplementation (although with slightly different formulations than JiVitA-3), but used these controls as active comparators against an experimental prenatal lipid-based nutrient supplement (LNS) arm. Details on the formulations of these supplements have been published elsewhere (22, 23). Newly married women aged 12 to 45 y old were recruited to the JiVitA-3 trial through a pregnancy surveillance program to identify and enroll women during the first trimester of pregnancy. A substudy in a predetermined geographic subregion of the JiVitA-3 trial site was conducted from June 2008 to February 2011 for more intensive data collection, including blood samples in early pregnancy (∼10 wk gestation; here designated M-1TM) and late pregnancy (32 wk gestation; M-3TM), and at 3 mo postpartum in women (M-3mo), in cord blood (C-Cord) in a limited subset of substudy participants, and in children at 2 y of age (C-24mo) in an even smaller subset. Among these available samples, a cohort of 1526 women was identified in whom complete serial data collection was available either through the cord blood study or through 3 mo postpartum; this cohort has been previously described (24), as has the group from which cord blood was collected (25, 26), and forms the sampling frame for this study. Pregnant Malawian women seeking prenatal care at clinics within the iLiNS-DYAD-M study catchment area were recruited for enrollment, provided they were >15 y of age and ≤20 wk of gestation. A total of 869 women were enrolled for complete follow-up in the study and followed until their children were 18 mo of age; recruitment and follow-up occurred from October 2011 to April 2015. Blood samples were collected from mothers at baseline during the second trimester (M-2TM), 36 wk of gestation (M-3TM), and 6 mo postpartum (M-6mo). Blood samples were also collected from children 6 mo after birth (C-6mo) and at 18 months of age (C-18mo). In both studies, extensive demographic, socioeconomic, dietary, anthropometric, and other data were collected to describe household, maternal, and infant characteristics. Infant feeding practices were assessed differently between sites, with the JiVitA project administering a questionnaire at 3 and 6 mo of age regarding feeding practices occurring in the prior ∼3 mo, to ascertain usual feeding practices as exclusive, predominant, or partial breastfeeding. The ILiNS-DYAD-M study used the Infant and Young Child Feeding Indicators questionnaire (27) at 3 and 6 mo of age to assess feeding practices in the last 24 h. The JiVitA-3 trial used the Food Access Survey Tool (FAST) (28) to determine household food security for the period encompassing the first 6 mo postpartum, while the iLiNS-DYAD-M study used the Household Food Insecurity Access Scale (HFIAS) (29) at maternal baseline enrollment. The Cronbach’s ɑ value for the HFIAS instrument within the iLiNS-DYAD-M trial was 0.81, while the corresponding value for the FAST questionnaire was 0.85 in the JiVitA-3 trial. Supplemental Figure 1 depicts flow diagrams of sample selection for the current study, for each trial site. Aliquots from 1152 plasma samples from 230 mother–child dyads were selected for analysis from the iLiNS-DYAD-M trial. All of these 230 dyads had “complete” sets of plasma samples—that is, plasma was available for each sample type within a dyad (M-2TM, M-3TM, M-6mo, C-6mo, C-18mo). Plasma was also available for analysis at midpregnancy (M-2TM) and late pregnancy (M-3TM) from an additional 25 mothers (without matched postpartum or child samples), bringing the total number of pregnancies included to n = 255 and the total samples analyzed to n = 1202. Based on available samples and outcome data, serum samples from JiVitA-3 pregnancies were selected for analysis in groups composed of the following combinations of maternal–child sample types: 1) first and third trimester of pregnancy, mother at 3 mo postpartum, cord blood, child at 24 mo of age (n = 58); 2) first and third trimester of pregnancy, mother at 3 mo postpartum, child at 24 mo of age (n = 77); 3) first and third trimester of pregnancy, mother at 3 mo postpartum, cord blood (n = 235); 4) first and third trimester, mother at 3 mo postpartum (n = 203). Missing, low-volume, or misattributed samples resulted in the combinations shown in Supplemental Figure 1. In total, n = 573 maternal–infant dyads were represented, with first trimester n = 569, third trimester n = 566, 3 mo postpartum n = 565, cord blood n = 295, and 24-mo-old n = 138, for a total of n = 2133 samples. AFB1-lysine concentrations were measured using modifications to the method reported by McCoy et al. (8). Due to volumes available and requirements for detection, 70 µL of plasma was used for samples from Malawi, while 170 µL of serum was used in samples from Bangladesh. PBS (pH 7.2) was added to bring the total volume of all samples to 200 µL. Quality control (QC) samples were processed alongside unknowns for each batch, and prepared using AFB1-lysine–negative pooled human donor serum (Innovative Research, Inc.) and AFB1-dosed rat serum (diluted with PBS to ∼13 pg AFB1-lysine/µL), as follows: QC0, 200 µL human serum, 0 µL diluted rat serum; QCL, 195 µL human serum, 5 µL diluted rat serum; QCM, 190 µL human serum, 10 µL diluted rat serum; QCH, 180 µL human serum, 20 µL diluted rat serum. All samples were combined with an isotopically labeled internal standard (100 µL at 5 pg AFB1-d4-lysine/µL) and 500 µL of a 6.5-mg/mL PBS solution of Pronase protease (537,088; EMD Millipore), and incubated with agitation for 18 h at 37°C. After enzymatic digestion, samples were centrifuged (3 min at room temperature at 14,000 × g) and the supernatant was processed on Oasis MAX solid-phase extraction 96-well plates (186,000,373; Waters), using a Positive Pressure-96 processor (186,006,961; Waters). Eluate (800 µL) was dried in a Speedvac (SPD120-15; ThermoFisher Scientific) at 35°C for 4 h, and wells were washed with 100 µL methanol, which was transferred to a V-well PCR plate. Samples were again dried in a Speedvac (35°C for 1 h), reconstituted in 40 µL of 25% aqueous methanol, and transferred to an autosampler plate (60,180–10217B; ThermoFisher Scientific; Zone-Free sealing film, ZAF-PE-50; Excel Scientific) for ultra-high-performance LC–tandem MS (UHPLC-MS/MS) analysis. Analysis was performed on a Vanquish Flex Quaternary UHPLC system coupled to a TSQ Quantis triple quadrupole mass spectrometer (ThermoFisher). Twenty microliters of sample was injected onto an Accucore Vanquish C18+ column (150 mm × 2.1 mm × 1.5 µm; ThermoFisher) preceded by a HyperSil GOLD C18 guard column (10 mm × 2.1 mm × 5 µm; ThermoFisher), which were held at 55°C. Samples were separated with an 18-min isocratic chromatography method, composed of water (mobile phase A), acetonitrile (B), and 0.6% aqueous formic acid (C). Initial conditions were 80% A/10% B/10%C for 1 min, stepped to 74% A/16% B/10% C and held for 7 min, followed by a step to 0% A/90% B/10% C for 3 min, and finally a step back to initial conditions, where the column was re-equilibrated for 7 min. Flow was diverted from the detector to waste from 10–14.5 min. The flow rate was held constant at 250 µL/min. Mass spectrometry electrospray ionization source conditions were as follows: 3525 V in positive mode, sheath gas (nitrogen) 20 arbitrary units, auxiliary gas (nitrogen) 24 arbitrary units, sweep gas (nitrogen) 0 arbitrary units, ion transfer tube 350°C, vaporizer 350°C, and cone voltage 10 V. Data acquisition was via selected reaction monitoring using a collision gas pressure of 2 mTorr (argon) and the following transitions: 457.2 → 394.2 (AFB1-lysine), 461.2 → 398.2 (AFB1-d4-lysine). Cycle time was set at 0.35 s, resulting in a dwell time of 173 ms per transition. Collision energy and radio frequency transmission voltages were set at 21 V and 138 V, respectively, for both transitions. Q1 resolution was set at 0.7 full width at half-maximum (FWHM), and Q3 resolution was set at 1.2 FWHM. Peak areas were integrated automatically within TraceFinder 4.0 software (ThermoFisher Scientific), followed by visual inspection and manual integration where necessary. Quantitation was performed using an 8-point, serially diluted, isotope dilution calibration curve in 25% aqueous methanol (vol:vol). Purified synthetic AFB1-lysine (200 pg/µL) was diluted with 25% aqueous methanol to 45 pg/µL (calibrator 1), followed by serial 3-fold dilution to 0.021 pg/µL (calibrator 8). These calibrators were then each mixed with synthetic isotopically labeled AFB1-d4-lysine (5.0 pg/µL) in a 1:1 ratio, to create an 8-point isotope dilution calibration curve with a constant AFB1-d4-lysine concentration of 2.5 pg/µL and AFB1-lysine concentrations of 22.5–0.010 pg/µL. AFB1-lysine concentration was plotted against AFB1-lysine:AFB1-d4-lysine peak area ratios and a linear curve was fit with an intercept of 0 and 1/X weighted least-squares regression. Samples were processed and analyzed in batches of 92 unknowns and 4 QCs [QC0 (matrix blank), QCL, QCM, and QCH], with separate 8-point calibration curves run in duplicate for each batch. Samples within a mother–child dyad were processed together and analyzed sequentially. In total, 26 batches were run for the Bangladesh study and 14 for Malawi samples, amounting to approximately 4500 total injections. Valid LC-MS data was available for 2107 of 2133 serum samples from Bangladesh (98.8%) and 1164 of 1202 plasma samples from Malawi (96.8%). QC sample performance across all batches was consistent: %CV for calculated AFB1-lysine concentrations in QCL (0.33 pg/µL), QCM (0.66 pg/µL), and QCH (1.31 pg/µL) samples was 11.3%, 10.8%, and 10.3%, respectively. Longitudinal quantitative accuracy was within 20% of the calculated concentration for each QC level (Supplemental Figure 2). Across all batches, the mean slope for the 3 dilutions of QC samples was 0.421 ± 0.009 (12.0% CV), while the mean slope of the calibrators in 25% methanol was 0.424 ± 0.003 (4.5% CV), demonstrating that the presence of serum matrix did not alter quantitation (Supplemental Figure 3). Performance of the calibration curve was highly consistent across batches, with R2 values ranging from 0.997 to 0.999. The limit of detection (LOD) for the assay (CV ≤20%) with 200 µL input serum was 0.01 pg/µL. Experiments using 100, 80, 60, or 40 µL of serum input demonstrated assay linearity down to 0.067 pg/µL (the lowest concentration tested) with all input volumes, but >20% inaccuracy at 0.067 pg/µL with serum input ≤100 µL (Supplemental Figure 4). All statistical analyses were conducted separately by site. Demographic attributes of the participating populations are summarized as means ± SDs for continuous variables or count and % for categorical variables. AFB1-lysine values are presented in units of pg/µL serum/plasma and reported as medians and IQRs, unless indicated otherwise. Nondetectable samples were imputed as LOD/2 (0.005 pg AFB1-lysine/µL). Medians and IQR values are inclusive of imputed nondetectable values, unless stated otherwise. AFB1-lysine adduct levels have historically been reported as adduct concentration normalized to total serum albumin (e.g., pg adduct/mg albumin), requiring the use of a separate assay and serum aliquot for total albumin quantification. As noted above, available sample volumes were limited and were less than the typical assay volume of 200 μL (Bangladesh, 170 μL; Malawi, 70 μL). In order to maximize sample availability for AFB1-lysine detection in the absence of prior exposure data (particularly in cord blood and infants), we did not quantify total albumin concentrations and thus are not presenting AFB1-lysine concentrations as normalized to total albumin. Seasonality of sample collection in Bangladesh was defined as follows: winter, 16 October–15 February; dry, 16 February–15 June; rainy, 16 June–15 October. Seasons in Malawi were defined as follows: rainy, 16 November–15 April; dry, 16 April–15 November. These classifications are consistent with climate data reported by The World Bank (30, 31). To explore associations of AFB1-lysine with season within each study site, locally weighted scatterplot smoothing (LOWESS) curves were fit to AFB1-lysine data separately for each sample type (e.g., M-1TM, M-3TM, etc.) using either 5-point (Malawi) or 10-point (Bangladesh) smoothing, using date of sample collection as the independent variable. Differences in distributions of AFB1-lysine concentrations between participant groups or between season of collection were assessed by the nonparametric Kruskal-Wallis test, using the Dwass, Steel, Critchlow-Fligner multiple comparison procedure in PROC NPAR1WAY of SAS (SAS Institute). Tests were considered significant at α = 0.05. Post hoc regression analyses of seasonal adduct accumulation and clearance rates were conducted using tobit analysis (32, 33) in PROC QLIM of SAS. The IDMS assay’s LOD (0.01 pg/μL) was used as the lower-bound censoring limit, day as the independent variable (as an integer relative to the day of the year defined as the beginning of accumulation or clearance), log10-transformed AFB1-lysine adduct concentrations as the dependent variable, and repeated measurements were grouped by mother to account for within-subject variance. Within the Bangladesh dataset, only maternal data were included in this analysis, due to the limited sample size for 24-mo-old children and the high percentage of nondetectable values in cord blood samples. Data were pooled across all years of sample collection and aligned by date, irrespective of the year in which a sample was collected. Estimates of daily intakes of AFB1 were calculated as in Equation 1 below, with the following variables and constants: W, body weight in kilograms; H, height in meters; BV, blood volume in liters as estimated in women by Equation 2 (34) or by body weight [estimated with weight-for-age z score (WAZ)] in prepubertal children (35); hematocrit (Hct), estimated by hemoglobin/3 (36, 37); 2% conversion rate of ingested AFB1 to AFB1-lysine adduct (38); 30-fold accumulation in AFB1-lysine adduct concentration resulting from chronic exposure relative to an equivalent single dose, assuming a 28-day lifetime of albumin (7). To ascertain persistence of exposure over the time course from early pregnancy to 18 or 24 mo of child’s age within maternal and infant dyads, correlation analysis and partial correlation analysis were performed among data at all time points per study site. Partial correlations were calculated between log10-transformed AFB1-lysine concentrations at each sample collection time (including imputed nondetectable values), adjusting for seasonal variability in exposure to ascertain whether some dyads were perpetually at higher risk of exposure even as environmental aflatoxin may have changed. For samples from Malawi, which had few nondetectable samples, Spearman’s rank-order correlation is appropriate. Due to the higher percentage of nondetectable values in the Bangladesh dataset, correlation analysis of AFB1-lysine concentrations for samples from Bangladesh was also conducted using Kendall’s tau-b rank-order correlation (39), which does not yield a P value with partial correlation analyses (40). Both correlation coefficients are presented for each site. Finally, within the Malawi dataset, which uniquely contained data in 6-mo-old infants, regression analysis was conducted to ascertain the potential protective role of breastfeeding behaviors and other demographic factors on aflatoxin exposure in infancy. We report findings that followed an extensive model fitting exercise (41) to generate a parsimonious model relating breastfeeding, household food security, maternal parity, and season of sample collection to log10-AFB1-lysine concentrations at 6 mo of age, with β-coefficients expressed as geometric mean ratios with 95% CIs. Statistical analysis and data visualization were performed in SAS version 9.4 (SAS Institute) and GraphPad Prism 8 (GraphPad Software).
