Levels of the heavy metals cadmium, lead, and arsenic and the essential mineral manganese, measured in maternal blood during pregnancy, were associated with increased risk of ADHD and/or autism in the child. This was reported in a new study from the Norwegian Institute of Public Health.
This research does not show that metals and minerals are a direct cause of ADHD or autism because observed associations may have other explanations; however, the findings show the importance of more knowledge about how environmental contaminants may impact fetal development.
Environmental contaminants can impact children’s development even in the mother’s womb. Several heavy metals such as lead, mercury, arsenic, and cadmium are known or suspected to interfere with brain development and can reach the fetus through the placenta.
This is also the case for minerals such as manganese, selenium, and copper, which in sufficient doses are important for a normal fetal brain development, while levels that are too low or too high can potentially be harmful. The research question in this study was whether any of these substances could increase risk for ADHD or autism in children.
There are few studies that have investigated metals and minerals during fetal life and associations with ADHD or autism in children.
Heavy metals and minerals were measured in maternal blood during pregnancy in 2136 mothers from the Norwegian Mother, Father and Child Cohort Study (MoBa), where 705 children had an ADHD diagnosis, 397 had an autism diagnosis, and 1034 did not have a diagnosis.
The study showed that levels of some of the heavy metals and minerals were associated with increased risk of ADHD, autism or both diagnoses.
In some cases, both high and low levels in maternal blood were associated with increased risk, compared to normal levels. This study also took into consideration other factors that could be associated with metal and mineral exposures and developmental diagnoses, like maternal education, age, parity, seafood consumption, smoking and child sex and birth year.
Even after considering these other factors, there was increased risk of autism diagnosis with both the highest and the lowest levels of lead in maternal blood, in addition to increased risk with elevated levels of arsenic. For ADHD, there was an increased risk of diagnosis with both low and high levels of arsenic. The highest levels of cadmium were associated with increased risk of both ADHD and autism, compared to the lowest levels.
Children of mothers with both low and high levels of manganese had increased risk of ADHD. Among children of mothers with the highest levels of manganese (compared to the lowest), there was increased risk of autism.
Most people, including pregnant women and the unborn children, are exposed to thousands of chemicals. Still, we know surprisingly little about how this can impact the fetal brain development. We need more research to gain knowledge about causal relationships between environmental contaminants and brain development, says Thea Skogheim and Gro Villanger, two of the researchers of the study.
It is important to emphasize that the associations that were found in the study are on a group level and that factors that were not included may have affected the results. Thus, one cannot claim that these metals and minerals is a direct cause of ADHD and autism.
There are many different factors that contribute to the development of these disorders, where particularly heredity is important. Yet, there is likely a complex interplay between genes and environmental factors, such as environmental contaminants.
Previous studies in this field have mainly focused on the most known and toxic heavy metals, such as lead and mercury. They have also based their research more on parent-reported ADHD symptoms in the children than on register-based diagnoses. The findings in this study support results from similar studies from other countries. However, this study is among the first that have investigated 11 different metals and minerals together with ADHD and autism diagnoses. The exposures were investigated both individually and as mixtures.
Toxic heavy metals such as mercury, lead, arsenic, and cadmium are naturally occurring in the environment, but due to human activity such as pollution from industry and mining, there are elevated levels in the environment. According to the Norwegian Environment Agency, the use of lead ammunition is the greatest source (67%) of emission of lead in the environment in Norway.
Both natural occurrence and emission from industry to soil and water leads to food being the greatest source of metals and minerals. Some of the substances (mercury, lead, cadmium) accumulate in the food chain and can be transferred from mother to child during pregnancy.
Lead and cadmium are found in many of the food items that we most frequently ingest, such as grain products and vegetables, in addition to beverages. There are elevated levels of cadmium in organ meat (kidney and liver) and brown crab meat. Cigarettes are also an important source of cadmium.
Families that have game meat as part of their daily diet get additionally exposed to lead, combined with the exposure from other food products. According to warnings from the Norwegian Food Safety Authority, young, pregnant, and breastfeeding women as well as children below the age of seven, should not eat game meat that is shot with lead ammunition.
There are particular warnings from the Norwegian Food Safety Authority about the intake of seafood from polluted areas in Norway (ports, fjords and lakes). The population is exposed to arsenic mainly through food and drinks, and in Norway fish and seafood are one of the greatest sources. In fish and seafood most of the arsenic are organic forms that are considered less toxic than inorganic forms. Both human and animal studies have shown harmful effects on the nervous system following exposure to inorganic forms.
Even though manganese is essential for many biochemical processes in the body, excessive levels over a long period of time can also be harmful, especially for the brain and nervous system. The greatest human exposure source is food (grain products, green vegetables, nuts) and multivitamin supplements. Additionally, exposure can occur through cosmetics, drinking water, air pollution, and occupational sources.
In the Norwegian population, there are some occupational groups working with metals that are exposed to high levels of manganese. In areas of the world with high levels of manganese in the soil and groundwater (such as drinking water) or where mining contributes to high air concentrations, studies have shown associations with behavioral problems, cognitive deficits, reduced learning abilities, and lower school performance in children.
A need for more knowledge about environmental contaminants in the population
This study includes children born between 2002 and 2009. There is, however, limited knowledge about present day levels of exposure. Even though bans and regulations for some of the heavy metals (e.g. mercury and lead) have been implemented, many metals are transported through air and ocean currents across the globe. Thus, we do not know the levels of metals and other environmental contaminants in the Norwegian population as of today, nor in vulnerable groups such as pregnant women and children. It is therefore important that we gain more knowledge about this, says Skogheim and Villanger.
The Norwegian health authorities estimates that about 3–5 percent of children and youth below the age of 18 have ADHD. This entails that on average, there is one child with ADHD in each school class. In Norway, around 1 percent of all children will have received a diagnosis of autism by the age of eight years. By discovering potential environmental risk factors that contribute to ADHD and autism, this can support and initiate preventive measures.
Autism Spectrum Disorder: Epidemiology and Etiology
Autism spectrum disorder (ASD) is a complex condition characterized by impaired social communication and restricted, repetitive behaviors (Lord et al., 2018). Globally, it is estimated that 0.76% of children have ASD. The United States of America (USA) prevalence rates are higher at 1.9%, and have increased since 2000 (Maenner et al., 2020). The USA prevalence varies by race and ethnicity: prevalence in Hispanic children is approximately 17% lower than that of white children. Approximately one third of children with ASD also have an intellectual disability.
ASD is a heterogeneous condition which is likely caused by multiple environmental and genetic factors, and many risk factors have been identified. In a recent literature review of 67 environmental risk factors and 52 biomarkers, the most convincing risk factors for ASD were maternal factors before or during pregnancy.
These included maternal age (≥35 years), maternal chronic and gestational hypertension, maternal overweight pre-pregnancy or during pregnancy, maternal pre-eclampsia, pre-pregnancy maternal antidepressant use (Kim et al., 2019), and maternal immune activation (Bilbo et al., 2018). The gut microbiome is also implicated in ASD symptomatology. In fact, gut microbiome plays an integral role in immune reactions and inflammation.
One hypothesis is that various antigens induce peripheral immunoreactions through the GI tract, which subsequently alters CNS activity (Cristiano et al., 2018). Further, mouse models of maternal immune activation results in ASD-like behaviors as well as decreased gastrointestinal tract permeability. Because of this, diet modulations have been suggested as a therapeutic option for ASD (Rosenfeld, 2015). Other likely environmental risk factors for ASD include to paternal age (>45 years) (Gabis et al., 2010; Simard et al., 2019), and family history of autoimmune diseases (Wu et al., 2015) such as psoriasis (Croen et al., 2019), rheumatoid arthritis (Rom et al., 2018), placenta morphology (Straughen et al., 2017), and type 1 diabetes (Atladottir et al., 2009).
Since early twin studies in the late 1980’s, a strong genetic influence is seen for ASD. A recent literature review of all twin studies on ASD found a 0.98 correlation between monozygotic twins and an overall heritability estimate of approximately 64–91% (Tick et al., 2016). Today, over 900 autism susceptibility genes have been reported (Banerjee-Basu and Packer, 2010), indicating the condition’s heterogeneous nature. Both common single nucleotide polymorphisms (SNPs) and more rare copy number variations (CNVs) likely play a role in ASD incidence. A study looking at common SNPs across the genome found that ASD may be caused by a collective effort of many small effect SNPs rather than one or a few genes (Klei et al., 2012). CNVs in ASD are common on nine of 23 chromosomes (Bergbaum and Ogilvie, 2016), and have been reported on every chromosome. While most genetic variations are inherited in ASD, approximately 10% of ASD can be attributed to de novo genetic variations (Sebat et al., 2007).
The Role of Metals in ASD
There is a growing interest in the role of metals in ASD incidence. The increasing environmental dissemination of toxic metals and chemicals are likely a cause for ASD, among other neurodevelopmental disorders (Grandjean and Landrigan, 2014). Typical ASD characteristics such as intellectual disability and language problems have been associated with exposure of toxic metals prior to or during pregnancy. In a review of almost 100 studies, 74% suggest that physiological mercury levels are a risk factor for ASD (Kern et al., 2016), likely due to autoimmune activation, oxidative stress, and subsequent neuroinflammation. Aluminum is found at high levels in both white and gray matter of ASD patients, and is hypothesized to be able to cross the blood-brain barriers and taken up by microglial cells (Mold et al., 2018). Further, animal studies examining neurodevelopmental effects of metals found changes in brain structures also implicated in ASD (Arora et al., 2017).
Aside from heavy and toxic metals, which actively disrupt neurodevelopmental processes, dyshomeostasis of metal micronutrients may also be involved in ASD etiology. Zinc, copper, selenium, iron, and magnesium levels have been associated with ASD incidence.
Zinc is the second most abundant element in the human body and is involved in a plethora of cellular functions. Approximately 2,800 proteins or 10% of the human proteome may bind zinc in vivo (Andreini et al., 2006). Zinc is particularly involved in glutamatergic transmission (i.e., GABA pathway) during embryonic and childhood development. Deficiency of zinc in mice models leads to altered neural tube closure (Li et al., 2018) and ASD-related behavior such as weakened vocalization and social behavior through SHANK proteins, a family of postsynaptic scaffolding proteins (Grabrucker et al., 2014). When dietary zinc is added, non-ASD behavior is restored in SHANK3-mutant mice (Fourie et al., 2018). Brain zinc levels are 10-fold higher than serum Zinc levels, indicating a larger role of Zinc in neurodevelopment (Portbury and Adlard, 2017). Zinc is more abundant in neuronal-rich areas, and is important in neuronal modulation, synaptic plasticity, learning, and memory (Qi and Liu, 2019). Of note, current literature link zinc to ASD in the context of the central nervous system, and therefore a lot remains unknown within the context of the peripheral nervous system. Novel pharmacological therapies for brain injury target levels of free zinc in the brain to restore homeostasis, indicating the significance of zinc homeostasis in the brain (Frederickson et al., 2005).
Zinc is also involved in the gut-brain interaction, and many ASD patients also have gastrointestinal symptoms. Maternal zinc levels are likely a factor in fetal gut formation and therefore the gut-brain interaction in ASD (Vela et al., 2015). Prenatal zinc levels also influence the morphology of placenta (Wilson et al., 2017), and placental function is notable in ASD (Straughen et al., 2017).
There is a well-known link between autism and the immune system (Meltzer and Van de Water, 2017; Hughes et al., 2018), to which zinc plays an integral role in both innate and adaptive immunity, such as monocytes, natural killer, T-, and B-cells (Shankar and Prasad, 1998).
There is considerable evidence for an association between zinc deficiency and ASD (Yasuda and Tsutsui, 2013; Li et al., 2014; Goyal et al., 2019). Zinc-binding genes associated with ASD are up-regulated in all neurodevelopmental stages (Supplementary Table S1). In a study examining 1,967 children with ASD, almost 30% had low zinc concentration in hair samples (Yasuda et al., 2011). Another small study found lower zinc levels in saliva of autistic children when compared to healthy controls (Deshpande et al., 2019). Zinc levels may also be correlated to severity of ASD presentation (Guo et al., 2018). It is important to note, however, that significant variance is observed when comparing zinc from hair and nails (Giuseppe De Palma et al., 2011; Lakshmi Priya and Geetha, 2011), suggesting that serum may be a better source for zinc measurement. When serum was evaluated in 78 children with autism, 71.8% of children had zinc levels either in the lowest 10% or below the reference range (Faber et al., 2009).
Zinc levels may also be affected by geographic-specific factors (Table 1); studies in Ireland (Sweetman et al., 2019) and Brazil (Saldanha Tschinkel et al., 2018) found zinc levels in ASD children to be equivalent to that of healthy controls. One study in Oman found higher levels of zinc in ASD patients than in controls (Al-Farsi et al., 2013). Geographical differences may be attributed to differences in social determinants of health such as nutrition, economic status, and associated illnesses. Zinc deficiency in infants is prevalent in countries with malnourishment, and is globally a recognized public health issue (Ackland and Michalczyk, 2016). Geographic-specific differences may also be due to sample size and age variability between studies.
Geographical differences in physiological zinc levels.
|Country||Gender*† (male: female)||Age in years*||Source||ASD mean zinc level||Control mean zinc level||p-value||References|
|Egypt||3:1||4.1 ± 0.8||Hair||304.99 ± 25.8 μg/mg||419.5 ± 45.96 μg/mg||n/a||Eman Elsheshtawy et al., 2011|
|China||4:1||3.78 (SD 1.22)||Serum||78.7 (SD 7.0) μg/dl||87.7 (SD 8.7) μg/dl||<0.001||Li et al., 2014|
|India||4:1||4–12||Hair||130.46 (SD 15.65) μg/g||171.68 (SD 20.60) μg/g||<0.01||(Lakshmi Priya and Geetha, 2011)|
|Nails||150.83 (SD 18.09) μg/g||193.98 (SD 23.27) μg/g||<0.01||Lakshmi Priya and Geetha, 2011|
|Japan||3.8:1||0–15||Hair||∼30% of ASD patients had a > 2 SD lower zinc concentration than reference||129 (range 86.3–193) ppm||Yasuda and Tsutsui, 2013|
|Oman||4.4:1||3–14 (mean 5.3)||Hair||Median 5.4 (quartile 0.82) μg/g||Median 2.9 (quartile 2.2) μg/g||0.0001||Al-Farsi et al., 2013|
|Saudi Arabia||5.3:1||3–9||Hair||67.04 (SD 23.78) mg/kg||110–227 mg/kg||n/a||Blaurock-Busch et al., 2012|
|Ireland (Northern)||7.2:1||2–18||Serum||11.68 (SD 1.7) μmol/L||11.63 (SD 2.1) μmol/L||0.86||Sweetman et al., 2019|
|Romania||Not reported||5.83 ± 3.10||Whole blood||5.54 (SD 0.78) μg/ml||6.14 (SD 0.76) μg/ml||0.005||Craciun et al., 2016|
|United Kingdom||3.8:1||2–16 (mean 7.0)||Serum||10.01 (SD 1.52) μmol/L||11.76 (SD 2.14) μmol/L||<0.001||Goyal et al., 2019|
|Italy||3:1||2–6||Serum||1021.52 (SD 100.76) ng/g||808.03 (SD 131.89) ng/g||0.01||Vergani Lauraad et al., 2011|
|5.3:1||9.00 ± 4.05||Hair||Median 149 (25th to 75th percentile 89.00—187.75) μg/g||Median 143(25th to 75th percentile 105.50—166.35) μg/g||0.428||Giuseppe De Palma et al., 2011|
|Slovenia||7.8:1||1–16||Serum||10.74 (SD 1.81) μmol/L||12.10 (SD 1.52) μmol/L||0.007||Marta Macedoni-Lukšič et al., 2014|
|Russia||Not reported||2–9 (mean 5.12 ± 2.36)||Hair||Median 124.6 (25th to 75th percentile 77.0–174.2) μg/g||Median 113.3 (25th to 75th percentile 69.4–166.3) μg/g||0.365||Skalny et al., 2017|
|United States||3.5:1||6.3 (SD 3.67)||Serum||76.89 (SD 14.1) μg/dl||Reference 66 μg/dl||n/a||Faber et al., 2009|
|6.2:1||11.7 ± 5.62||Serum||78.36 (SD 20.32) mg/dL||84.42 (SD 24.18) mg/dL||0.3541||Russo and Devito, 2011|
|Canada||4:1||3.90 ± 1.68||Red-cell||134.95 (SD 23.94) μmol/L||148.27 (SD17.09) μmol/L||0.08||Joan Jory, 2008|
|Brazil||Not reported||<18||Serum||105 (SD 0.73) mg/dl||Not reported.||n/a||Saldanha Tschinkel et al., 2018|
|Venezuela||Not reported||Not reported||Serum||180.50 ± 57.72 μg/dl||219.49 ± 72.10 μg/dl||N.S.||Semprún-Hernández et al., 2012|
Copper also has important roles in the human body, and is involved in cell growth, among many others. Copper is involved in reactions connected to neurological diseases, and dyshomeostasis of copper has been seen in disorders such as Parkinson’s, Alzheimer’s, and Huntington’s Diseases (Faber et al., 2009). Further, copper is integral in several autism-related biological processes, such as immunity (Kelley et al., 1995) and placental development. Copper levels are typically higher than average in ASD patients.
In 78 children with ASD, 15.4% had higher copper levels than the reference range, and 30.8% were in the highest 10% of the copper reference range (Faber et al., 2009). In another study, mean serum copper levels were significantly higher in ASD children than in healthy controls (Li et al., 2014). A third study of 79 autistic individuals found a similar pattern, in which autistic and Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS) patients had significantly higher plasma levels of copper (Russo and Devito, 2011). Increase in physiological copper levels may also correlate with increasing severity of ASD (Lakshmi Priya and Geetha, 2011). Copper levels in ASD patients do not seem to vary by geographical region (Table 2); regardless of region, copper levels vary in comparison to controls between studies.
Geographical differences in physiological copper levels.
|Country||Gender*† (male: female)||Age in years*||Source||ASD mean copper level||Control mean copper level||p-value||References|
|Egypt||3:1||4.1 ± 0.8||Hair||26.5 ± 1.9 μg/mg||19.1 ± 4.4 μg/mg||n/a||Eman Elsheshtawy et al., 2011|
|China||4:1||3.78 (SD 1.22)||Serum||129.9 (SD 13.1) μg/dl||121.2 (SD 11.3) μg/dl||<0.001||Li et al., 2014|
|India||4:1||4–12||Hair||36.62 (SD 4.39) μg/g||12.31 (SD 1.47) μg/g||<0.001||Lakshmi Priya and Geetha, 2011|
|Nails||28.85 (SD 3.46) μg/g||9.62 (SD 1.15) μg/g||<0.001|
|Oman||4.4:1||3–14 (mean 5.3)||Hair||Median 1.2 (quartile 0.1) μg/g||Median 6.6 (quartile 0.7) μg/g||0.02||Al-Farsi et al., 2013|
|Saudi Arabia||5.3:1||3–9||Hair||133.86 (SD 115.47) mg/kg||6.7–37 mg/kg||n/a||Blaurock-Busch et al., 2012|
|Romania||Not reported||5.83 ± 3.10||Whole blood||1.26 (SD 0.16) μg/ml||1.22 (SD 0.18) μg/ml||0.460||Craciun et al., 2016|
|Italy||3:1||2–6||Serum||1390.99 (SD 213.55) ng/g||1190.36 (SD 478.57) ng/g||N.S.||Vergani Lauraad et al., 2011|
|5.3:1||9.00 ± 4.05||Hair||Median10.20 (25th to 75th percentile 8.12—13.00) μg/g||Median 9.40 (25th to 75th percentile 7.40–14.45) μg/g||0.374||Giuseppe De Palma et al., 2011|
|Slovenia||7.8:1||1–16 (mean 6.2 ± 3.0)||Serum||20.57 (SD 3.29) μmol/L||19.87 (SD 4.12) μmol/L||0.327||Marta Macedoni-Lukšič et al., 2014|
|Russia||Not reported||2–9 (mean 5.12 ± 2.36)||Hair||Median 10.2 (25th to 75th percentile 8.7–12.5) μg/g||Median 10.5 (25th to 75th percentile 9.2–12.6) μg/g||0.356||Skalny et al., 2017|
|USA||3.5:1||6.3 (SD 3.67)||Serum||129.68 (SD 29.1) μg/dl||Reference 153 μg/dl||n/a||Faber et al., 2009|
|6.2:1||11.7 ± 5.62||Serum||111.50 (SD 27.73) mg/dL||90.42 (SD 19.55) mg/dL||0.0133||Russo and Devito, 2011|
|Canada||4:1||3.90 ± 1.68||Red-cell||14.38 (SD 1.39) μmol/L||14.90 (SD 2.29) μmol/L||0.22||Joan Jory, 2008|
|Brazil||Not reported||<18||Serum||83 (SD 0.37) mg/dl||Not reported.||n/a||Saldanha Tschinkel et al., 2018|
|Venezuela||Not reported||Not reported||Serum||128.62 ± 21.89 μg/dl||109.87 ± 24.65 μg/dl||<0.05||Semprún-Hernández et al., 2012|
Interestingly, copper and zinc play competing roles physiologically, such that an increase in copper leads to zinc deficiency (Grabrucker, 2012). The zinc/copper ratio has therefore been examined in the ASD setting. Patients and children with ASD tend to have lower zinc/copper ratios than controls (Bjorklund, 2013), even if differences are not seen in copper levels alone (Craciun et al., 2016). Such differences are not known to be sex-dependent (Faber et al., 2009), though copper levels alone may differ by sex due to oral contraceptive use (Babic et al., 2013). One study found that the zinc/copper ratio could be used as a diagnostic biomarker (Li et al., 2014). Zinc/copper cycles may play a role in ASD occurrence, and the rhythmicity of these cycles can be used as a diagnostic tool to classify ASD (Curtin et al., 2018).
Selenium and selenium-dependent proteins are essential in brain development and managing oxidative damage in the brain, and it has been suggested that dyshomeostasis in selenium may be associated with ASD incidence (Raymond et al., 2014). In a recent literature review of 10 studies comparing hair trace element levels in ASD and controls, four of them found a significant difference in Selenium levels. However, two found a significant increase in Selenium levels in children with ASD, and two found a significant decrease (Tinkov et al., 2019). Another meta-analysis found no significant differences in mean hair or erythrocyte selenium concentrations among 12 studies (Saghazadeh et al., 2017). Though dyshomeostasis is likely involved in ASD incidence, the contradictory data indicate a need for a more comprehensive study evaluating Selenium levels in ASD patients (Anatoly et al., 2018).
Iron is the most abundant trace element in the body (Wood and Sperling, 2019). Iron deficiency anemia is a major health concern in both developed and developing countries and can result in inadequate cellular function at a young age (Bener et al., 2017). Iron is involved in several neurodevelopmental processes, such as transmitter synthesis, myelin production, and synaptogenesis, and deficiency leads to malfunction of these processes (Pivina et al., 2019). Subsequently, iron deficiency is associated with developmental delay (McCann and Ames, 2007) and likely in ASD. Deficiency of iron has been seen in ASD children when compared to controls (Bener et al., 2017). While one meta-analysis in 2017 found lower iron levels in ASD patients than controls (Saghazadeh et al., 2017), another meta-analysis in 2018 found no differences in peripheral iron levels in ASD children (Tseng et al., 2018). Iron deficiency may be associated with ASD symptoms and particularly correlates with severity of emotional and behavioral problems (Saghazadeh et al., 2017).
Magnesium is involved in basic cellular processes such as nucleic acid formation and energy metabolism. In neurodevelopment, magnesium regulates glutamate-activated channels in neuronal membranes, a process highly correlated with ASD pathogenesis (Saghazadeh et al., 2017). Magnesium has been seen as deficient in children with ASD (Lakshmi Priya and Geetha, 2011). In combination with vitamin B6, magnesium has been argued as a potential nutritional intervention for ASD. However, several systematic reviews from the late 1990’s to early 2000’s found no substantial evidence for magnesium and vitamin B6 as treatment for ASD (Karhu et al., 2019). Since then, not many studies have examined the role of magnesium in ASD. A more recent review, however, found a significant magnesium deficiency in ASD patients, and suggests monitoring of magnesium status in patients with ASD (Saghazadeh et al., 2017).
reference link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759187/
More information: Thea S. Skogheim et al. Metal and essential element concentrations during pregnancy and associations with autism spectrum disorder and attention-deficit/hyperactivity disorder in children, Environment International (2021). DOI: 10.1016/j.envint.2021.106468