Association and interaction between metal aluminum and iron exposure and the risk of offspring’ congenital heart defects in northwestern China

doi:10.21203/rs.3.rs-2062875/v1

Download PDF

Research Article

Association and interaction between metal aluminum and iron exposure and the risk of offspring’ congenital heart defects in northwestern China

https://doi.org/10.21203/rs.3.rs-2062875/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Congenital heart disease (CHDs) is the leading cause of mortality from birth defects, affecting up to 1% of live births. However, there have been inconsistent results of the relationship between aluminum (Al) /iron (Fe) level and risk of CHDs. We performed a pair-matched case–control study and included 97 cases and 194 controls to investigate the association and interaction between Al/Fe exposure and the risk of CHDs in a birth cohort study conducted in Lanzhou, China. Compared to < 25th percentile of Al in CB, risk differences were significantly detected in > 75th percentile of Al in total CHDs (aOR = 2.826, 95% CI: 1.009–7.266) and isolated CHDs (aOR = 10.713, 95% CI: 1.017–112.851). Although a similar pattern was not detected in MB of Al and Fe in both MB and CB, a significant dose-effect was observed between the Al level and total CHDs in both MB and CB (Ptrend < 0.05). Compared to both lowest tertile of Al and Fe level in umbilical cord blood, the highest tertile was associated with an increased risk of CHDs, especially for multiple CHDs, septal defects and patent ductus arteriosus. Overall, our study suggests a significant association between pregnancy Al exposure (≥ 2.408 mg/L) and risk of CHDs, especially for septal defects, and high Al and Fe elicited a strong correlation on fetal heart development. Future studies are needed to elucidate the underlying mechanism.

aluminum

iron

metal exposure

congenital heart defects

cord blood

birth cohort

interaction test

Congenital heart defects (CHDs) are the leading type of congenital disabilities with an incidence of 1/100 [1] and associated with a high incidence of neonatal lethality and disability worldwide [2, 3]. While several studies have demonstrated that either environmental or genetic factors contribute to CHDs [4]. However, the fundamental etiology for the majority of CHDs cases of the disease remains unknown. The epidemiological studies revealed that prenatal exposure to environmental factors, such as heavy metal, has been associated with birth defects, especially CHDs [5–7].

Aluminum (Al), the third metallic toxic pollutant on earth, is ubiquitous in human life. Al has found a wide utility as cookers, utensils, food additives, pharmaceutical ingredients, and water purifying agents [8, 9]. Meanwhile, Al is a harmful element and has a prolonged half-life in the human body. The Al accumulated in the human body is positively correlated with that ingested. The more Al is ingested, the more it is accumulated in the human body, becoming detrimental to human health. [10] confirmed that Al accumulates in the offspring through the placental barrier, causing developmental damage. Animal experiments [11–14] have shown that excessive Al intake exerts embryonic developmental toxicity in rats and mice, which is mainly manifested in exposed brain malformation and skeletal hypoplasia. It also causes intrauterine growth retardation and death of embryos and is a potential risk to female infertility. ElMazoudy et al.[15] reported that Al is a cardiac teratogen for chicken in a dose-dependent pattern. Moreover, chicken embryos showed a high rate of suffering due to ventricular septal and ventricular myocardial defects when exposed to 4.0 mg/Al. In addition, several occupational or environmental studies revealed that women workers at an Al smelter had a high incidence of congenital anomalies [16], and higher hair Al concentrations exposure increased significantly for women who had CHDs baby[17].

Several studies supported that maternal mineral nutrition was associated with adverse birth outcomes, especially in those with cardiovascular defects [18–21]. Iron (Fe) is an essential nutrient for embryonic development; however, the conclusion varies across studies. Numerous studies have demonstrated that Fe status plays a vital role in embryonic development [22, 23], as assessed in animal models; also, optimal Fe status is essential for cardiovascular development [18, 24]. Some studies demonstrated that Fe overload leads to heart defects [25, 26], while according to a few studies, maternal Fe deficiency is a risk factor for CHDs [27, 28]. In addition, previous studies proved that Fe can interfere with the protein binding of Al and induce oxidative stress [29]. These mechanisms maybe induce the cardiac structural abnormalities in humans.

Furthermore, to our knowledge, few studies evaluated the biomarkers in the birth cohorts of gestational trace element exposure and human CHDs, while no comprehensive studies have yet been published to analyze the levels of aluminum (Al) and iron (Fe) levels in maternal peripheral blood (MB) and cord blood (CB) and the interaction effect to the risk of CHDs in the offspring. So, we collected clinical data and analyzed the Al/Fe concentration in MB and CB to further explored environmental risk factors of CHDs.

2.1 Study design

A total of 10,542 (response rates:73.42%) birth cohort study was conducted (2020-2012) at the Gansu Provincial Maternity and Child Care Hospital in Lanzhou, northwest of China. In a nutshell, individuals were enrolled following informed written consent and completed a face-to-face interview. Demographic information, medical history, medication use, lifestyle habits (for example, smoking and drinking status, physical activity, etc.), nutrient supplements and diet were collected using structured questionnaires. Maternal and birth outcomes records were reviewed from medical records. The detailed recruitment procedure is described in our previous study [30]. Ethical approval was obtained from the Gansu Provincial Maternity and Child Care Hospital’s the Human Investigation Committees.

Individuals were presented to assess with multiple gestation, stillbirths, and/or with noncardiac birth defects were excluded. 10,087 with live-born singleton were included. Among them, 94 mothers who gave birth to live, singleton infants-CHDs can be grouped into isolated defects (43 cases), multiple defects (46 cases), and syndrome defects (5 cases). According to location of cardiac defects, 69 were abnormalities of the great arteries, 58 were septal defects, and 18 were other types. Finally, a matched birth-cohort study with 194 controls and 97 cases (proportion=2:1) with CHDs was included in this study. The CHDs cases and non-CHDs controls were matched by maternal age and living area (residence location within 2 kilometers radius). Fig.1 illustrates the recruitment procedure.

2.2 Classification of CHDs

Each baby was examined after birth by 2-3 pediatric cardiologists reached a consensus diagnosis of CHDs using heart auscultation and 2-dimensional echocardiography. The clinical phenotypes of CHDs were categorized using the ICD-10 code (Q20–Q28). All the CHDs were classified into two groups: “Isolated CHDs” means the case with only one type cardiac defects; and “Multiple CHDs” means the case with one more cardiac malformation. Then, the cases were classified into three mainly subtypes based on the anatomical structures: septal defects, atrial septal defect (ASD) and patent ductus arteriosus (PDA). Subtypes with too few cases are not discussed in our study. The recruitment procedure has been followed as described previously [31].

2.3 Samples collection and analysis

Peripheral blood samples were collected from participating women at time of admission for labor and Umbilical cord blood of newborns was collected immediately after delivery. Before analysis, all samples were kept frozen at −80 °C in our hospital’s central laboratory. Elements Whole Blood L-1(No.: 210113, bought from Beijing Fubo Biotechnology Co., Ltd) was used for quality control. Concentrations of ²⁷Al and ⁵⁶Fe were measured with Inductively coupled plasma mass spectrometry (ICP-MS, Themo Scientific, Bremen, Germany). In whole blood, the limits of detection (LOD) of Al and Fe were both 0.001 mg/L, respectively, and they were measured above the LOD.

2.4 Statistical analysis

The distribution of sociodemographic and lifestyle characteristics between CHDs and non-CHDs controls was compared using χ²-test or Fisher’s exact test. Skewed continuous variables were conducted as median (range [min–max]) and then analyzed using the Wilcoxon–Mann–Whitney U test. The distribution of Al and Fe is shown in the graphs grouped as CHDs and non-CHDs controls. We also assessed the inter-correlations among Al and Fe. Since no previous reference information were available to explore the dose threshold of these metal elements, their concentrations were divided into low (<25^th percentile), medium (25^th–75^thpercentile), and high levels (>75^th percentile) based on their distribution among controls.

Maternal and umbilical cord blood AL/Fe levels were used as predictors to explore the association with CHDs and its subtypes. Conditional multivariable logistic regression was conducted for the outcome to adjust for confounding. To estimates with the associations of joint risk exposure, double-elements (that is including Al and Fe predictors, simultaneously) models were constructed. In the final models, the putative confounding variables, including maternal hypertensive disorders during pregnancy (yes or no), gestational diabetes (yes or no), and cesarean delivery (yes or no), folic acid supplement (yes or no) and average dietary energy intake during pregnancy (yes or no), were adjusted. We additionally adjusted for smoking and drinking status, and the gender of each neonate which did not affect the multivariable-adjusted estimates. Hence, our models did not adjust for additional covariates.

Herein, we used categorical variables, multiplicative and additive interaction to explore the modifying effects among Al/Fe and CHDs. First, in order to assessed analogous effects between Al and Fe, we reclassified the levels of Al and Fe into "low concentration group" (≤75^th percentile) and "high concentration group" (>75^th percentile), and then analyzed each group of effects, including low Al and low Fe, low Al and high Fe, high Al and low Fe, and high Al and high Fe. Second, multiplicative interaction and interaction contrast ratios (ICRs) were used to explore the possible interaction between Al and Fe on CHDs. All analyses were conducted using SAS 9.3 software (SAS Institute Inc., Cary, NC, USA), and statistical tests were considered significant if P<0.05 or the confidence intervals (95% CI) did not include 1.0.

3.1 Characteristics of participants

The maternal baseline demographic information are listed in Table 1. Maternal hypertensive disorders during pregnancy, gestational diabetes and cesarean delivery were significantly different between the two groups (P<0.05), while no significant differences were detected in other maternal characteristics.

The median concentrations (range) of maternal blood Al in the control and case groups were 2.117 (0.578-7.528) mg/L and 2.450 (0.607-63.821) mg/L, respectively. The median (range) cord blood Al concentrations were 1.654 (0.104-8.238) mg/L and 2.575 (0.453-24.424) mg/L in the non-CHDs and CHDs groups, respectively, indicating that the Al concentration of MB and CB in the case group was significantly greater than that in the non-CHDs group (P<0.001). The iron levels in the maternal and cord blood in CHDs were not significantly higher than those in the controls (P<0.01).

3.2 Multivariable logistic regression model underling single-element

Al/Fe exposure and CHD risk were first explored separately using a multivariate single -element logistic regression model. Multivariable models were adjusted for hypertensive disorders during pregnancy, diabetes, cesarean delivery, folic acid supplement and average dietary energy intake during pregnancy. Table 2 shows that the correction of the medium/high concentration of Al/ Fe was statistically significant difference in CHDs and their subtypes in maternal blood compared to the low level of Al/Fe in multivariable single-element logistic regression models, respectively; however, a significant dose-effect was observed between the Al level and total CHDs in the maternal blood (P=0.0274) and ASD in the maternal blood (P=0.0474).

Table 3 listed the associations between the element in cord blood and CHDs using multivariable single-element logistic regression models. Compared with the low quartiles (<25^th) of Al level, the difference was statistically significant in the high level of Al in cord blood in the total CHDs (OR=3.037, 95% CI: 1.205–7.655, P=0.0091) and isolated CHDs (OR=11.109, 95% CI: 1.017–114.888) when the confounders were adjusted under single-element mode. However, a similar pattern in the Al and Fe of cord blood was not found in multivariable double-element logistic regression models in other subtypes of CHDs, while statistical significance was detected in some subtypes of CHDs, such as total CHDs (P=0.0091) in Al, multiple CHDs (P=0.0263) in Al, and PAD (P=0.0263) in Al, as well as total CHDs (P=0.0127) in Fe, multiple CHDs (P=0.0315) in Fe, and septal defects in Fe (P=0.0201) for the trend.

3.3 Al/Fe exposure and CHD risk using multivariable double-element logistic regression models

Next, we analyzed the effect of Al/Fe on CHDs in multivariable double-elements logistic regression models (Table 4) and did not find a significant influence on other CHD types. However, total CHDs (P=0.0284) in Al and PAD in Al (P=0.0441) show a dose-dependent effect in maternal blood.

As shown in Table 5, compared to the low quartiles (<25^th) of Al level, significant differences were noted in the high level of Al in cord blood in total CHDs (OR=2.826, 95% CI: 1.009–7.266) and isolated CHDs (OR=10.713, 95% CI: 1.017–112.851) when the confounders were adjusted under double elements mode. Conversely, a similar pattern was not detected in the Fe of cord blood under multivariable double-element logistic regression models. However, a significant dose-effect was observed between the level of Al and total CHDs in cord blood (P=0.0483). In a model including Al element and adjusted for confounders, there was no significant deviation was observed between Fe level and risk of CHDs in cord blood.

3.4 Interaction effects between Al and Fe

In addition, we explored interaction effects among MB and CB’s Al and Fe to determine whether the effect of Al and Fe combinations were synergistic, additive or antagonistic on the incidence of CHDs. First dichotomized as “low” (≤75^th percentile) and “high” (>75^th percentile), and We modelled cross-product terms into multivariable logistic regression, adjusted for confounders as previous (Table 6). No not significantly correlated were observed in maternal blood between categorical variables in CHDs and all the subtypes. In CB, high aluminum and high iron elicited a strong positive association on offspring’s cardiac development than high Al alone in total CHDs (aOR=5.273, 95% CI: 1.897–14.657), multiple CHDs (aOR=7.820, 95% CI: 1.672–36.588), septal defects (aOR=4.747, 95% CI: 1.428–15.780) and PDA (aOR=13.147, 95% CI: 2.415–71.565). However, no significant multiplicative and additive interactions were detected for Al and Fe in maternal and cord blood (Table 6).

In present study, we aimed to identify the interaction between maternal exposure to Al and Fe during pregnancy and CHDs in offspring, measured in maternal and cord blood simultaneously. The results showed that the Al exposed in MB and CB were higher in the CHDs groups than in the non-CHDs groups (Table 1). Maternal exposure to Al has a significant association with the risk of CHDs in the offspring in logistic analysis model, and higher concentrations of Al may be at increased risk of CHDs. The current study was consistent for CHDs subtypes, including the septal defects, PDA, and isolated CHDs in CB (Tables 4 and 5). Finally, our findings suggested that mothers with high Al merge high Fe upped the ante for CHDs compared to mothers with low blood Al and low Fe meanwhile.

4.1. Associations between Al and CHDs

Aluminum is the third enriched element in the crust. In addition, environmental Al pollution is common due to the vigorous exploitation of Al or for smelting, use in cookers, utensils, and toys, Al agents to treat gastrointestinal diseases, Al salt to purify water, and as a food additive [32, 33]. Al is a hazardous element to the human body. It can accumulate and exert teratogenic, carcinogenic, and mutagenic effects. However, there is a lack of understanding of maternal Al exposure and the risk of congenital disabilities, especially CHDs. A previous study [29] reported that accumulation of Al in a healthy person would be probably 30–50 mg/kg, and the levels of Al in serum are likely 1–3 μg/L under normal circumstances [34]. The current findings showed that the presence of Al (median=2.117 mg/L) in MB was higher than that reported in a normal person (1–3 μg/L). However, the median Al levels in CB (1.654 mg/L) were significantly less than MB collected at birth (2.117 mg/L), indicating the presence of Al in CB, but the placenta might provide a physical barrier against metallic elements (Table 1). Animal experiments revealed that Al is teratogenic to the nervous system, and the differentiation and formation of yolk blood vessels, the heart, and the neurons are sensitive to Al toxicity [15]. The development of the tube is sensitive to Al toxicity, which provides clues for the effect of Al on human embryonic heart development. In previous studies in China [17, 33], they evaluated hair samples by ICP-MS, and find a statistically significant difference in hair Al content and the occurrence of total CHDs in the offspring (aOR=2.32, 95% CI: 1.72–3.13). Thus, it could be deduced that Al is involved in the occurrence of CHD through oxidative stress. A Polish study showed that Al in maternal serum (mean±SD: 250.3±176.2 µg/L) and amniotic fluid (144.8±54.1 µg/L) in women who have a birth defects baby. Moreover, a high level of Al is the best predictor of birth defects (β coefficient=-0.28; P=0.02) [17]. Accumulating evidence, including our recent study, showed that high Al in MB significantly increases the risk of birth with CHDs, such as hair, amniotic fluid, or cord blood. Notably, in this study, the risk of Al exposure was related to fetal CHDs occurrence in a dose-dependent manner with elevated aluminum levels (≥2.408 mg/L in the cord blood), supporting the theory that maternal Al exposure increases the risk of CHDs in offspring.

4.2. Associations between Fe and CHDs

Comparatively, Fe have received great attention for their role in the occurrence of CHDs event. Fe has an important role in the growth and development of the embryo in many animal studies [22, 35, 36], especially for cardiovascular development [19]. However, molecular mechanisms underlying this relationship are ill-defined and the evidence on the correlations between Fe nutritional status and CHDs among humans has been controversial in the past decade. Some studies have pointed out that maternal Fe deficiency is a risk factor for CHDs [27, 28]. Moreover, by interacting with other nutrients (such as folate), low ferritin status may alter the utilization of folate despite adequate intake [37]. A meta-analysis study suggested that maternal folate deficiency reduce the risk of CHDs [38]. Our previous study also showed that pregnant women who did not take a folate supplement and had low folic acid intake from dietary increased the rate of CHDs by two-fold in their offspring [39]. Hence in the current study, we considered pregnant women’s folate intake as a confounder. Among iron-deficient women of childbearing age, iron demands are exceedingly high pre-existing during pregnancy, and pregnant women were found more susceptible to iron deficiency. The resulting of that may induce tissue hypoxia and stress response, this in turn affects subsequent early and late consequences for fetal cardiac development in general[40]. However, recent studies showed that Fe status overload could also cause heart defects [26] . To the best of our knowledge, one research in China explored that maternal Fe nutritional in low status were correlated with the rate of offspring’s CHDs [27]. Our study classifies the exposure of Fe status both in MB and CB directly and found that the association of the high concentration of Fe in the MB and CB did not differ statistically in CHDs and their subtypes adjusting hypertensive disorders during pregnancy, diabetes, cesarean delivery, folic acid supplement and average energy intake of dietary during pregnancy. The mechanisms underlying these associations between Fe deficiency and the development remain unclear and needs an in-depth investigation.

4.3. Interactions between trace elements

To the best of our knowledge, none of the previous studies have systematically explored the trace Al and Fe elements interactions on CHDs. However, this negative finding could be due to the low sample size. Since the scarcity of research on the co-exposed effects of mental elements for offspring’s heart development, fetal susceptibility to environmental exposure is warranted to further studies. The current study no significant differences were observed between categorical variables in CHDs and the subtypes in MB. However, in CB, high Al in addition to high Fe exist a stronger correction on fetal heart development than high Al alone in total CHDs, multiple CHDs, septal defects and PDA. The potential pathogenic mechanisms of Al-induced CHD are as follows. First, aluminum accumulates in lysosomes, causing damage to cardiomyocytes. Second, transferrin can bind to approximately 90% of the aluminum circulating in the blood[35, 41-43], thereby disrupting the normal synthesis of transferrin receptors and ferritin, then increasing free iron levels in cells and activation abnormal reactive oxygen species (ROS) which lead to increased lipid peroxidation, DNA damage, and even cell apoptosis ([36, 44, 45]. Third, Al binds to nuclear chromatin, affecting the metabolism of phosphorus and calcium and the normal physiological functions of cells, which in turn interferes with cytoskeleton polymerization [46]. The current study also demonstrates that simultaneous high levels of iron exposure may enhance the effects of aluminum exposure.

The current study has several advantages, which makes our results effective. Frist, maternal and fetal biomarkers were identified during pregnancy, and the demographic, pregnancy, and birth data were collected from clinical records, which are not susceptible to cause the recall bias. Second, we had age-matched controls and their radius of a residential area within 2 km, which ensured the representation of the sampling framework. Third, we evaluated the two elements (Al/ Fe) both in MB and CB, as well as their co-correlation with CHDs adjusted for a set of potential confounding variables

Nevertheless, the present study has some limitations. First, our cohort cannot be considered representative of the pregnant women in China because the sample size was small, and hence, the current findings may not be extended to adult pregnant women. However, the prevalence of CHDs (9.3‰ live births) in current population was similar to the reported prevalence in other study in China [47]. Second, the small sample size is a major limitation of our study, which limits the statistical power of the association and interaction studies of CHDs subtypes in this study. Nonetheless, a possible pathogenic role of Al in CHDs and a synergistic effect with Fe in pathogenicity were observed.

We observed a strong association between exposure to high levels of Al in fetal CB (≥2.408 mg/L) and an increased risk of fetal CHDs in pregnant women. Interestingly, we found that at these exposure levels, concurrent high levels of Fe exposure may increase the effects of Al on cardiac development. Combined with fetal echocardiography, the present results can be used to identify high-risk pregnancies with aluminum contamination in Gansu Province and prevent the rate of birth defects.

MB, maternal blood; CB, cord blood; Al, aluminum; Fe, iron; CHDs, congenital heart defects; aOR: adjust odds ratio; CI, Confidence interval; PDA, patent ductus arteriosus; ASD, atrial septal defect.

Funding This work was supported by the Special Support for Long Yuan Youth Innovation and Entrepreneurship Personnel Training Program of Gansu Province (2021LQTD10) and the Key Research and Development Program of Gansu Province (20YF8WA095). The funding bodies had no role in the design of the study, the collection, analysis, and interpretation of data, and the writing of the manuscript.

Competing interests The authors have no relevant financial or non-financial interests to disclose.

Authors’ contributions All authors contributed to the study conception and design. Data collection, analysis, and the first draft of the manuscript were performed by Jing Li and Chunhua Zhang. Bin Yi and Qing Liu conceived the study and oversaw the field implementation. Material preparation and the manuscript review were performed by Baohong Mao, Qian Liu, and Yanxia Wang, and Zhirong Dai collected the data. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. All authors read and approved the final manuscript.

Ethics approval All study procedures were approved by the Human Investigation Committees at the Gansu Provincial Maternity and Child-Care Hospital (File No:2021 GSFY Approval Letter of Institutional Review Boards No.9). Informed consent was obtained from all individual participants included in the study

Consent to participate Informed consent was obtained from all individual participants included in the study

Consent for publication Not applicable

Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments We thank all the study participants from the Gansu Provincial Maternity and Child Care Hospital, Lanzhou, Gansu province, China.

Houyel L, SM Meilhac (2021) Heart Development and Congenital Structural Heart Defects. Annu Rev Genomics Hum Genet. 22:257 – 84. https://doi.org/10.1146/annurev-genom-083118-015012
Vecoli C, S Pulignani, I Foffa, MG Andreassi (2014) Congenital heart disease: the crossroads of genetics, epigenetics and environment. Curr Genomics. 15:390–9. https://doi.org/10.2174/1389202915666140716175634
Khoshnood B, N Lelong, L Houyel, AC Thieulin, JM Jouannic, S Magnier, AL Delezoide, JF Magny, C Rambaud, D Bonnet, F Goffinet (2012) Prevalence, timing of diagnosis and mortality of newborns with congenital heart defects: a population-based study. Heart. 98:1667–73. https://doi.org/10.1136/heartjnl-2012-302543
Wessels MW, PJ Willems (2010) Genetic factors in non-syndromic congenital heart malformations. Clin Genet. 78:103 – 23. https://doi.org/10.1111/j.1399-0004.2010.01435.x
Jenkins KJ, A Correa, JA Feinstein, L Botto, AE Britt, SR Daniels, M Elixson, CA Warnes, CL Webb (2007) Noninherited risk factors and congenital cardiovascular defects: current knowledge: a scientific statement from the American Heart Association Council on Cardiovascular Disease in the Young: endorsed by the American Academy of Pediatrics. Circulation. 115:2995–3014. https://doi.org/10.1161/circulationaha.106.183216
Liu S, J Liu, J Tang, J Ji, J Chen, C Liu (2009) Environmental risk factors for congenital heart disease in the Shandong Peninsula, China: a hospital-based case-control study. J Epidemiol. 19:122–30. https://doi.org/10.2188/jea.je20080039
Ibrahimou B, AN Albatineh, HM Salihu, J Gasana (2017) Ambient PM2.5 Aluminum and Elemental Carbon and Placental Abruption Morbidity. J Occup Environ Med. 59:148–53. https://doi.org/10.1097/jom.0000000000000927
Kumar V, KD Gill (2009) Aluminium neurotoxicity: neurobehavioural and oxidative aspects. Arch Toxicol. 83:965 – 78. https://doi.org/10.1007/s00204-009-0455-6
Campbell A, A Becaria, DK Lahiri, K Sharman, SC Bondy (2004) Chronic exposure to aluminum in drinking water increases inflammatory parameters selectively in the brain. J Neurosci Res. 75:565–72. https://doi.org/10.1002/jnr.10877
Golub MS, JL Domingo (1998) Fetal aluminum accumulation. Teratology. 58:225–6. https://doi.org/10.1002/(sici)1096-9926(199812)58:6<225::aid-tera1>3.0.co;2-4
Cranmer JM, JD Wilkins, DJ Cannon, L Smith (1986) Fetal-placental-maternal uptake of aluminum in mice following gestational exposure: effect of dose and route of administration. Neurotoxicology. 7:601–8.
Paternain JL, JL Domingo, JM Llobet, J Corbella (1988) Embryotoxic and teratogenic effects of aluminum nitrate in rats upon oral administration. Teratology. 38:253–7. https://doi.org/10.1002/tera.1420380309
Malekshah A (2005) Developmental Toxicity of Aluminum from High Doses of AlCl3 in Mice.
Fu Y, FB Jia, J Wang, M Song, SM Liu, YF Li, SZ Liu, QW Bu (2014) Effects of sub-chronic aluminum chloride exposure on rat ovaries. Life Sci. 100:61–6. https://doi.org/10.1016/j.lfs.2014.01.081
ElMazoudy RH, GA Bekhet (2016) In ovo toxico-teratological effects of aluminum on embryonic chick heart and vascularization. Environ Sci Pollut Res Int. 23:21947–56. https://doi.org/10.1007/s11356-016-7461-z
Sakr CJ, OA Taiwo, DH Galusha, MD Slade, MG Fiellin, F Bayer, DA Savitz, MR Cullen (2010) Reproductive outcomes among male and female workers at an aluminum smelter. J Occup Environ Med. 52:137–43. https://doi.org/10.1097/JOM.0b013e3181cb59bc
Liu Z, Y Lin, X Tian, J Li, X Chen, J Yang, X Li, Y Deng, N Li, J Liang, S Li, J Zhu (2016) Association between maternal aluminum exposure and the risk of congenital heart defects in offspring. Birth Defects Res A Clin Mol Teratol. 106:95–103. https://doi.org/10.1002/bdra.23464
Yang J, Y Cheng, L Pei, Y Jiang, F Lei, L Zeng, Q Wang, Q Li, Y Kang, Y Shen, S Dang, H Yan (2017) Maternal iron intake during pregnancy and birth outcomes: a cross-sectional study in Northwest China. Br J Nutr. 117:862–71. https://doi.org/10.1017/s0007114517000691
Anand IS, P Gupta (2018) Anemia and Iron Deficiency in Heart Failure: Current Concepts and Emerging Therapies. Circulation. 138:80–98. https://doi.org/10.1161/circulationaha.118.030099
Puri K, JF Price, JA Spinner, JM Powers, SW Denfield, AG Cabrera, HP Tunuguntla, WJ Dreyer, MD Shah (2020) Iron Deficiency Is Associated with Adverse Outcomes in Pediatric Heart Failure. J Pediatr. 216:58–66.e1. https://doi.org/10.1016/j.jpeds.2019.08.060
McAlpine JM, DR McKeating, L Vincze, JJ Vanderlelie, AV Perkins (2019) Essential Mineral Intake During Pregnancy and Its Association With Maternal Health and Birth Outcomes in South East Queensland, Australia. Nutr Metab Insights. 12:1178638819879444. https://doi.org/10.1177/1178638819879444
Toyokuni S (2002) Iron and carcinogenesis: from Fenton reaction to target genes. Redox Rep. 7:189–97. https://doi.org/10.1179/135100002125000596
Shaw GM, SL Carmichael, W Yang, EJ Lammer (2010) Periconceptional nutrient intakes and risks of conotruncal heart defects. Birth Defects Res A Clin Mol Teratol. 88:144–51. https://doi.org/10.1002/bdra.20648
Andersen HS, L Gambling, G Holtrop, HJ McArdle (2006) Maternal iron deficiency identifies critical windows for growth and cardiovascular development in the rat postimplantation embryo. J Nutr. 136:1171–7. https://doi.org/10.1093/jn/136.5.1171
Rodriguez A, M Hilvo, L Kytömäki, RE Fleming, RS Britton, BR Bacon, S Parkkila (2007) Effects of iron loading on muscle: genome-wide mRNA expression profiling in the mouse. BMC Genomics. 8:379. https://doi.org/10.1186/1471-2164-8-379
Wang M, Y Tian, P Yu, N Li, Y Deng, L Li, H Kang, D Chen, H Wang, Z Liu, J Liang (2021) Association between congenital heart defects and maternal manganese and iron concentrations: a case-control study in China. Environ Sci Pollut Res Int.10.1007/s11356-021-17054-9 https://doi.org/10.1007/s11356-021-17054-9
Yang J, Y Kang, Y Cheng, L Zeng, Y Shen, G Shi, Y Liu, P Qu, R Zhang, H Yan, S Dang (2020) Iron intake and iron status during pregnancy and risk of congenital heart defects: A case-control study. Int J Cardiol. 301:74–9. https://doi.org/10.1016/j.ijcard.2019.11.115
Deugnier Y (2003) Iron and liver cancer. Alcohol. 30:145 – 50. https://doi.org/10.1016/s0741-8329(03)00129-0
Greger JL, JE Sutherland (1997) Aluminum exposure and metabolism. Crit Rev Clin Lab Sci. 34:439–74. https://doi.org/10.3109/10408369709006422
Li J, J Qiu, L Lv, B Mao, L Huang, T Yang, C Wang, Q Liu (2021) Paternal factors and adverse birth outcomes in Lanzhou, China. BMC Pregnancy Childbirth. 21:19. https://doi.org/10.1186/s12884-020-03492-9
Jin L, J Qiu, Y Zhang, W Qiu, X He, Y Wang, Q Sun, M Li, N Zhao, H Cui, S Liu, Z Tang, Y Chen, L Yue, Z Da, X Xu, H Huang, Q Liu, ML Bell, Y Zhang (2015) Ambient air pollution and congenital heart defects in Lanzhou, China. Environ Res Lett. 10 https://doi.org/10.1088/1748-9326/10/7/074005
Ward RJ, Y Zhang, RR Crichton (2001) Aluminium toxicity and iron homeostasis. J Inorg Biochem. 87:9–14. https://doi.org/10.1016/s0162-0134(01)00308-7
Liu Z, C He, M Chen, S Yang, J Li, Y Lin, Y Deng, N Li, Y Guo, P Yu, X Li (2018) The effects of lead and aluminum exposure on congenital heart disease and the mechanism of oxidative stress. Reprod Toxicol. 81:93–8. https://doi.org/10.1016/j.reprotox.2018.07.081
Wiesner A, D Gajewska, P Paśko (2021) Levothyroxine Interactions with Food and Dietary Supplements-A Systematic Review. Pharmaceuticals (Basel). 14 https://doi.org/10.3390/ph14030206
Harris WR, L Messori (2002) A comparative study of aluminum(III), gallium(III), indium(III), and thallium(III) binding to human serum transferrin. Coordination Chemistry Reviews. 228:237 – 62. https://doi.org/https://doi.org/10.1016/S0010-8545(02)00037-1
Kell DB (2009) Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases. BMC Med Genomics. 2:2. https://doi.org/10.1186/1755-8794-2-2
O'Connor DL (1991) Interaction of iron and folate during reproduction. Prog Food Nutr Sci. 15:231–54.
Feng Y, S Wang, R Chen, X Tong, Z Wu, X Mo (2015) Maternal folic acid supplementation and the risk of congenital heart defects in offspring: a meta-analysis of epidemiological observational studies. Sci Rep. 5:8506. https://doi.org/10.1038/srep08506
Mao B, J Qiu, N Zhao, Y Shao, W Dai, X He, H Cui, X Lin, L Lv, Z Tang, S Xu, H Huang, M Zhou, X Xu, W Qiu, Q Liu, Y Zhang (2017) Maternal folic acid supplementation and dietary folate intake and congenital heart defects. PLoS One. 12:e0187996. https://doi.org/10.1371/journal.pone.0187996
Fisher SA, WW Burggren (2007) Role of hypoxia in the evolution and development of the cardiovascular system. Antioxid Redox Signal. 9:1339–52. https://doi.org/10.1089/ars.2007.1704
Day JP, J Barker, LJ Evans, J Perks, PJ Seabright, P Ackrill, JS Lilley, PV Drumm, GW Newton (1991) Aluminum absorption studied by 26Al tracer. Lancet. 337:1345. https://doi.org/10.1016/0140-6736(91)93016-3
Hémadi M, G Miquel, PH Kahn, JM El Hage Chahine (2003) Aluminum exchange between citrate and human serum transferrin and interaction with transferrin receptor 1. Biochemistry. 42:3120–30. https://doi.org/10.1021/bi020627p
Chen B, Y Zeng, B Hu (2010) Study on speciation of aluminum in human serum using zwitterionic bile acid derivative dynamically coated C18 column HPLC separation with UV and on-line ICP-MS detection. Talanta. 81:180–6. https://doi.org/10.1016/j.talanta.2009.11.057
Gorsky JE, AA Dietz, H Spencer, D Osis (1979) Metabolic balance of aluminum studied in six men. Clin Chem. 25:1739–43.
Oteiza PI (1994) A mechanism for the stimulatory effect of aluminum on iron-induced lipid peroxidation. Arch Biochem Biophys. 308:374–9. https://doi.org/10.1006/abbi.1994.1053
Zhang Q, Z Cao, X Sun, C Zuang, W Huang, Y Li (2016) Aluminum Trichloride Induces Hypertension and Disturbs the Function of Erythrocyte Membrane in Male Rats. Biol Trace Elem Res. 171:116–23. https://doi.org/10.1007/s12011-015-0504-3
Zhao Q, H Chen, G Zhang, W Chen, B Jia, F Liu, X Ma, W Yan, C Niu, G Huang (2021) High Prevalence of Unrecognized Congenital Heart Disease in School-Age Children in Rural China: A Population-Based Echocardiographic Screening Study. Circulation. 144:1896–8. https://doi.org/10.1161/circulationaha.121.056455

Table 1

Socio-demographic and lifestyle characteristics of pregnant women
Characteristics		Controls(n = 194)	CHDs (n = 97)	P-value
Characteristics		n(%) or median ± SD or median(range)	n(%) or median ± SD or median(range)	P-value
Maternal age(mean ± SD)		28.46 ± 4.33	29.54 ± 5.33	0.3045
Ethnic group
	Han	189(97.42)	90(92.78)	0.0611
	Others	5(2.58)	7(7.22)
BMI (kg/m²) (mean ± SD)		20.82 ± 2.73	21.29 ± 3.54	0.2645
	Missing	7	0
Education, years
	≤ 9	57(29.84)	31(32.98)	0.531
	10–15	69(36.13)	34(36.17)
	≥ 16	65(34.03)	29(30.85)
	Missing	3	3
Smoking ^a
	No smoking	155(79.9)	77(79.38)	0.918
	Smoking	39(20.1)	20(20.62)
Alcohol use				0.480
	No	193(99.48)	97(100)
	Yes	1(0.52)	0(0)
Employment status
	No	91(46.91)	47(48.45)	0.8037
	Yes	103(53.09)	50(51.55)
Sex of the child				0.480
	boy	84(43.52)	46(47.92)
	girl	109(56.48)	50(52.08)
Parity
	Nulliparous	129(66.49)	66(68.04)	0.7918
	Parous	65(33.51)	31(31.96)
Cesarean delivery				0.0002
	No	126(65.97)	41(42.71)
	Yes	65(34.03)	55(57.29)
	Missing	3	1
Hypertensive disorders during pregnancy
	No	194(100)	87(89.69)	< 0.0001
	Yes	0(0)	10(10.31)
Diabetes
	No	194(100)	91(93.81)	0.0005
	Yes	0(0)	6(6.19)
History of conception birth defect
	No	193(99.48)	96(98.97)	0.6165
	Yes	1(0.52)	1(1.03)
Family’s average monthly income (yuan)
	≤ 3000	107(59.78)	57(67.06)	0.2553
	> 3000	72(40.22)	28(32.94)
	missing	15	12
Average dietary energy intake during pregnancy(kcal)				0.7406
	< 1572.56	98(50.52)	47(48.45)
	≥ 1572.56	96(49.48)	50(51.55)
Folic acid supplement				0.2148
	Nonusers	50(25.77)	32(32.99)
	Users	144(74.23)	65(67.01)
Al concentrations in MB (mg/L)[median(range)]		2.117(0.578–7.528)	2.450(0.607–63.821)	0.0078
	< 1.567	48(24.74)	16(16.49)
	1.567–2.891	98(50.52)	42(43.30)
	> 2.891	48(24.74)	39(40.21)
Al concentrations in CB (mg/L)		1.654(0.104–8.238)	2.575(0.453–24.424)	< 0.0001
	< 1.285	49(25.26)	14(14.43)
	1.285–2.408	97(50.00)	30(30.93)
	> 2.408	48(24.74)	53(54.64)
Fe concentrations in MB (mg/L)[median(range)]		306.89(17.45-834.78)	320.25(61.72-928.64)	0.4801
	< 228.973	49(25.26)	20(20.62)
	228.973-379.056	96(49.48)	51(52.58)
	> 379.056	49(25.26)	26(26.80)
Fe concentrations in CB (mg/L) [median(range)]		431.09 (0.45-930.13)	500.70(81.28-1312.09)	0.1125
	<336.272	48(24.74)	17(17.53)
	336.272-530.785	97(50.00)	49(50.52)
	≥530.785	49(25.26)	31(31.96)
a. Maternal smoking including active smoking and passive smoking
b. The analysis did not account for missing data.
Abbreviation: BMI, Body mass index; MB, maternal blood ;CB, cord blood

Table 2 Associations between element levels in MB and congenital heart defects using multivariable single-element logistic regression models
Elements	Low level		Middle level		High level		P for trend
Elements	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	P for trend
Al Element
Total CHD	16/48	ref.	42/98	1.415(0.570,3.512)	39/48	1.831(0.730,4.586)	0.0274
Multiple CHDs	9/48	ref.	20/98	0.988(0.316,3.085)	17/48	1.108(0.336,3.651)	0.0638
Isolated CHDs	4/48	ref.	20/98	3.790(0.415,34.636)	19/48	6.311(0.711,56.014)	0.1526
Septal defects	12/48	ref.	23/98	1.309(0.466,3.679)	25/48	1.416(0.494,4.055)	0.0701
ASD	10/48	ref.	19/98	1.176(0.394,3.509)	19/48	1.589(0.499,5.056)	0.0474
PDA	10/48	ref.	29/98	1.308(0.453,3.771)	26/48	1.372(0.449,4.195)	0.0859

Fe Element
Total CHD	20/49	ref.	51/96	1.083(0.464,2.530)	26/49	1.275(0.493,3.296)	0.3083
Multiple CHDs	10/49	ref.	22/96	1.055(0.313,3.559)	14/49	1.587(0.368,6.849)	0.1260
Isolated CHDs	7/49	ref.	25/96	3.025(0.536,17.084)	11/49	1.731(0.320,9.357)	0.9947
Septal defects	12/49	ref.	32/96	1.501(0.528,4.265)	16/49	2.341(0.703,7.791)	0.0948
ASD	10/49	ref.	26/96	1.450(0.467,4.504)	12/49	2.017(0.557,7.303)	0.1019
PDA	14/49	ref.	34/96	0.949(0.340,2.648)	17/49	1.024(0.317,3.303)	0.5583
MB, maternal blood; Al, aluminum; Fe, iron; CHDs, congenital heart defects; aOR: adjust odds ratio; CI, Confidence interval; PDA, Patent ductus arteriosus; ASD, atrial septal defect. A Low level serves as the reference group. Conditional logistic regression models were adjusted for hypertensive disorders during pregnancy, diabetes, cesarean delivery, folic acid supplement and average dietary energy intake during pregnancy.

Table 3 Associations between element in CB and congenital heart defects using multivariable single-element logistic regression models
Elements	Low level		Middle level		High level		P for trend
Elements	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	P for trend
Al element
Total CHD	14/49	ref.	30/97	0.861(0.330,2.249)	53/48	3.037(1.205,7.655)	0.0091
Multiple CHDs	10/49	ref.	14/97	0.419(0.125,1.406)	22/48	2.055(0.682,6.190)	0.0263
Isolated CHDs	4/49	ref.	14/97	4.405(0.472,41.066)	25/48	11.109(1.074,114.888)	0.1521
Septal defects	11/49	ref.	17/97	0.527(0.176,1.574)	32/48	1.739(0.629,4.809)	0.0596
ASD	10/49	ref.	15/97	0.572(0.183,1.784)	23/48	1.587(0.517,4.872)	0.1699
PDA	12/49	ref.	18/97	0.598(0.190,1.889)	35/48	2.651(0.893,7.868)	0.0335

Fe element
Total CHD	17/48	ref.	49/97	0.730(0.280,1.899)	31/49	1.619(0.579,4.532)	0.0127
Multiple CHDs	10/48	ref.	21/97	0.775(0.221,2.715)	15/49	2.317(0.616,8.717)	0.0315
Isolated CHDs	5/48	ref.	23/97	0.560(0.094,3.344)	15/49	0.728(0.099,5.332)	0.4975
Septal defects	12/48	ref.	28/97	0.700(0.217,2.255)	20/49	1.925(0.564,6.571)	0.0201
ASD	11/48	ref.	22/97	0.457(0.131,1.598)	15/49	1.040(0.275,3.931)	0.1127
PDA	13/48	ref.	31/97	0.741(0.247,2.220)	21/49	2.188(0.625,7.657)	0.0625

CB, cord blood; Al, aluminum; Fe, iron; CHDs, congenital heart defects; aOR: adjust odds ratio; CI, Confidence interval; PDA, Patent ductus arteriosus; ASD, atrial septal defect. A Low level serves as the reference group. Conditional logistic regression models were adjusted for hypertensive disorders during pregnancy, diabetes, cesarean delivery, folic acid supplement and average dietary energy intake during pregnancy.

Table4 Associations between element levels in MB and congenital heart defects using multivariable double-elements logistic regression models
Elements	Low level		Middle level		High level		P for trend
Elements	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	P for trend
Al element
Total CHD	16/48	ref.	42/98	1.438(0.569,3.633)	39/48	1.810(0.700,4.678)	0.0284
Multiple CHDs	9/48	ref.	20/98	1.112(0.335,3.692)	17/48	1.026(0.296,3.558)	0.1774
Isolated CHDs	4/48	ref.	20/98	3.748(0.372,37.811)	19/48	6.500(0.562,75.193)	0.1291
Septal defects	12/48	ref.	23/98	1.338(0.475,3.916)	25/48	1.016(0.315,3.272)	0.2299
ASD	10/48	ref.	19/98	1.153(0.370,3.591)	19/48	1.317(0.374,4.636)	0.1996
Patent ductus arteriosus	10/48	ref.	29/98	1.338(0.455,3.940)	26/48	1.400(0.430,4.554)	0.0441

Fe element
Total CHD	20/49	ref.	51/96	0.978(0.412,2.319)	26/49	1.071(0.387,2.963)	0.5652
Multiple CHDs	10/49	ref.	22/96	1.045(0.303,3.601)	14/49	1.646(0.303,3.601)	0.8834
Isolated CHDs	7/49	ref.	25/96	1.520(0.253,9.120)	11/49	0.755(0.091,6.245)	0.3537
Septal defects	12/49	ref.	32/96	1.466(0.501,4.292)	16/49	2.685(0.656,10.983)	0.7083
ASD	10/49	ref.	26/96	1.386(0.436,4.405)	12/49	1.785(0.419,7.617)	0.6458
Patent ductus arteriosus	14/49	ref.	34/96	0.886(0.310,2.536)	17/49	0.949(0.261,3.444)	0.1990
MB, maternal blood; Al, aluminum; Fe, iron; CHDs, congenital heart defects; aOR: adjust odds ratio; CI, Confidence interval; PDA, Patent ductus arteriosus; ASD, atrial septal defect. A Low level serves as the reference group. Conditional logistic regression models were adjusted for hypertensive disorders during pregnancy, diabetes, cesarean delivery, folic acid supplement and average dietary energy intake during pregnancy.

Table 5 Associations between element in CB and congenital heart defects using multivariable double-elements logistic regression models
	Low level		Middle level		High level		P for trend
	n cases/controls	aOR (95%CI)	n cases/controls	aOR(95%CI)	n cases/controls	aOR(95%CI)	P for trend
Al element
Total CHD	14/49	ref.	30/97	0.857(0.322,2.279)	53/48	2.826(1.009,7.266)	0.0483
Multiple CHDs	10/49	ref.	14/97	0.343(0.094,1.260)	22/48	1.679(0.542,5.197)	0.1163
Isolated CHDs	4/49	ref.	14/97	4.219(0.424,42.006)	25/48	10.713(1.017,112.851)	0.1813
Septal defects	11/49	ref.	17/97	0.471(0.147,1.507)	32/48	1.433(0.484,4.240)	0.2665
ASD	10/49	ref.	15/97	0.606(0.181,2.032)	23/48	1.541(0.475,5.004)	0.3630
Patent ductus arteriosus	12/49	ref.	18/97	0.569(0.171,1.896)	35/48	2.460(0.815,7.427)	0.0980

Fe element
Total CHD	17/48	ref.	49/97	0.701(0.257,1.912)	31/49	1.206(0.413,3.526)	1.1411
Multiple CHDs	10/48	ref.	21/97	0.784(0.221,2.789)	15/49	2.187(0.550,8.694)	0.2216
Isolated CHDs	5/48	ref.	23/97	0.655(0.063,4.711)	15/49	0.655(0.053,8.052)	0.9215
Septal defects	12/48	ref.	28/97	0.748(0.226,2.477)	20/49	1.725(0.474,6.277)	0.1246
ASD	11/48	ref.	22/97	0.521(0.141,1.924)	15/49	1.021(0.251,4.154)	0.2965
Patent ductus arteriosus	13/48	ref.	31/97	0.769(0.246,2.405)	21/49	2.011(0.554,7.301)	0.2785
CB, cord blood; Al, aluminum; Fe, iron; CHDs, congenital heart defects; aOR: adjust odds ratio; CI, Confidence interval; PDA, Patent ductus arteriosus; ASD, atrial septal defect. A Low level serves as the reference group. Conditional logistic regression models were adjusted for hypertensive disorders during pregnancy, diabetes, cesarean delivery, folic acid supplement and average dietary energy intake during pregnancy.

Table 6 is available in the Supplementary Files section.

No competing interests reported.

Table6.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Association and interaction between metal aluminum and iron exposure and the risk of offspring’ congenital heart defects in northwestern China

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methods

3. Results

4. Discussion

5 Conclusions

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1