Autistic disorder is characterized by qualitative deficits in reciprocal social interaction and communication skills with restricted patterns of behavior. The estimated prevalence of autism varies widely from 1 in 166 for autism spectrum disorder (ASD) to 1 in 750 for the narrowest diagnostic criteria . The reported rates of autism have increased sharply in the United States and in the United Kingdom. One possible factor underlying its rising prevalence is exposure to mercury through thimerosal-containing vaccines, but vaccine exposures need to be evaluated in the context of cumulative exposures during gestation and early infancy . However, Volkmar  pointed that the role of environmental factors in autism, particularly mumps, measles, rubella vaccine, is still controversial and the effect of thimerosal (a mercury-containing compound) has not been supported consistently in large controlled studies. Many lines of evidence point to similarities between mercury poisoning and autism, including similarities in clinical picture . Mercury poisoning and autism have nearly identical symptoms, such as self-injurious behavior, social withdrawal, lack of eye contact, lack of facial expression, hypersensitivity to noise and touch, and repetitive behaviors . Common affection of certain areas in the brain e.g., amygdala, hippocampus, basal ganglia, cerebral cortex , shared abnormalities in neurotransmitters namely serotonin, dopamine and epinephrine [7,8].
Much concern has been raised over the link between exposure to heavy metal toxins and neurological brain damage associated with learning and behavioral disorders in children. Researches show that exposure to heavy metals, such as lead and mercury, can impair brain development at very early ages, even at low doses that were earlier deemed ‘harmless.’ Children are particularly susceptible to the deleterious effects of heavy metal exposure for several reasons. First, their developing nervous systems are more sensitive. Second, their bodies absorb toxins more rapidly; yet, the toxins are cleared from the system more slowly than adults. Finally, a child's blood–brain barrier, the natural protective mechanism that blocks harmful substances from entering and damaging the brain, is not yet fully formed .
Some possible sources of heavy metal poisoning include chemical products, fertilizers, industrial paint, building materials, fish that is high in mercury, silver dental fillings, mercury preservatives in vaccines, nasal sprays, and many more. Lead may be found in the dirt near roads and is commonly present in paint from older houses. Children with pica or who eat paint chips may develop toxic lead levels. Children with autism may be less able to detoxify toxic agents to which they are exposed to from the environment, and this inability may predispose children to suffer neural damage consistent with autistic behavioral traits .
Geier et al.  suggested that emerging evidence supports the theory that some ASDs may result from a combination of genetic biochemical susceptibility, specifically reduced ability to excrete mercury, and exposure to mercury at critical developmental periods. They also pointed the role played by protective factors (e.g. estrogen, glutathione, selenium, and vitamins) and exacerbating factors (e.g. antibiotics, concurrent heavy metal exposure, such as lead, arsenic, and androgens).
As a preliminary step in understanding the possible role of some metals in the etiology of autism in our culture, this study aimed at detecting the difference in the level of mercury, lead, copper, and zinc in the hair of children with autism versus normal controls and whether the levels of these substances are correlated with the severity of autism or not.
Materials and methods
This was a cross-sectional study and was carried out at the Mansoura University Hospital. Thirty-two children were recruited from the phonetic and the psychiatric outpatient clinics after taking consent from their parents to join the study. Cases included all children diagnosed as autistic disorder according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, and excluded all children with another axis I psychiatric disorder or having another chronic medical comorbid condition.
A control group was selected, which included 32 children who were age-matched and sex-matched without any psychiatric or medical disorders.
All children were tested for, (i) the presence of psychiatric disorders and diagnosis of pervasive developmental disorder using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition Childhood Diagnoses . (ii) The severity of autistic symptomatology was measured by the Childhood Autism Rating Scale (CARS)  using the Arabic version that was translated by El-Dafrawi. It consists of 15 categories, each rated on a four-point scale. The individual is considered nonautistic when his total score falls in the range of 15–29, mild-to-moderately autistic when his total score falls in the range of 30–36, and severely autistic when his total score falls in the range of 37–60. (iii) Intelligence quotient (IQ) using Stanford Binet Intelligence test , arabic version by Abdelsalam and Melika, was used.
Hair sample collection
Approximately 100 mg of scalp hair samples were cut from each child, both patients and controls, with stainless-steel scissors in the nape or occipital regions, as close to the scalp as possible. Hair collection was carried out in a dust-free environment and hair treated with artificial color was excluded from the study. The distal ends of the hair were cut from the samples. Each hair sample was comminuted, washed consecutively in neutral detergent, such as ether and acetone, and dried before analysis according to the procedure originally described [15,16].
Analysis of the studied heavy metals and trace elements [lead (Pb); mercury (Hg); copper (Cu), and zinc (Zn)] was carried out in the Toxicology Department by a Perkin Elmer 2380 (Perkin-Elmer, Atomic Absorption Spectrophotometer, United States) after wet ashing using reagent-grades HNO3 and HClO4 [17,18]. Instrument start-up and optimization were carried out as detailed in the operating manual. The source of the flame was an air–acetylene mixture. Hydride generation method was used for mercury. Wavelengths were set at 217, 253.7, 324.8, and 213.9 nm for Pb, Hg, Cu, and Zn, respectively. Working standard solutions were prepared by appropriate dilution of stock solutions. Preparation of standards and samples was carried out under clean conditions using deionized water. All chemicals and reagents that were used were of ultra pure reagent grade (BDH Laboratory Reagents Ltd., Poole, England). All the glasswares were washed three times with deionized water, and then soaked in 20% nitric acid overnight. After soaking, the glasswares were rinsed three times with deionized water and dried. Quality assurance was achieved by measuring blank test solutions.
Patients and controls were matched with regard to the age, ranging from 3.8 to 4.6 years with an average of 4.1 years. The t-test was carried out which showed no significant difference in age of children in both the groups. Chi-square test was carried out which showed significant difference in sex in both the groups (male children more than female children) (Table 1).
Results showed highly significant differences between the studied cases and the controls. The level of lead was significantly higher in cases (9.75±1.8 ug/mg) than in controls (6.8±0.86 μg/mg). The level of mercury was significantly lower in cases (0.55±0.06 μg/mg) than in controls (3.2±0.2 μg/mg). The level of copper was significantly higher in cases (26.5±1.9 μg/mg) than in controls (19.1±4.4 μg/mg). The level of zinc was significantly lower in cases (304.99±25.8 μg/mg) than in controls (419.5±45.96 μg/mg) (Table 2).
Correlation studies were carried out, which showed that CARS score was significantly positively correlated with levels of both mercury (r=0.615, P=0.000) and copper (r=0.404, P=0.022) in the hair but insignificantly correlated with levels of lead (r=−0.307, P=0.087) in the hair, whereas IQ was only significantly negatively correlated with levels of lead in the hair (r=−0.402, P=0.023). The level of zinc does not correlate with either CARS score (r=0.102, P=0.580) or IQ (r=0.085, P=0.645) (Table 3). As shown in Table 4, a significant correlation between CARS score and sex (female) was found.
The result of this study shows significantly decreased level of mercury in the hair of children with autism than controls. This was supported by Holmes et al. , who found low levels of mercury in the hair of children with autism, whereas another study carried out by Adams et al.  found normal levels. On interpreting their results, they stated that the normal level of mercury could indicate no abnormality in metal excretion, or they could indicate a combination of high metal body burden and low glutathione, yielding an average excretion rate of toxic metal into hair. In addition, current levels of mercury in hair are not a good way to check for mercury exposure during fetal development or infancy. However, lower levels of mercury in the hair of children with autism in this study and the positive correlation between mercury level and CARS scores may favor the lowered excretion explanation with higher body burden that can be supported by the negative correlation between the level of mercury in the hair and IQ.
The level of lead in hair is significantly higher in children with autism than controls. This result was the same as that of Fido et al. . Lead is known to adversely promote inflammatory responses and/or autoimmunity. Children at risk of autism may be particularly susceptible to chemical triggers that have biological targets shared by both the immune and nervous systems .
However, there is no significant correlation between the level of lead and CARS scores (severity of autism). Meanwhile, it correlated significantly negatively with IQ. This was supported by Lanphear et al.  who confirmed that high levels of lead result in a drop of IQ and that a proportionally greater decrease is seen at levels of lead higher than 7.5 μg/dl. This gives evidence for dangerous effects of lead poisoning on intelligence and may suggest different roles of mercury and lead in the etiology of autism.
The study results show significantly increased levels of copper and decreased levels of zinc in the hair of children with autism compared with controls. Copper is a component of several metalloenzymes that are linked to dopamine synthesis, in biochemical pathways involving either antagonism of dopamine production or catalysis of its breakdown . As dopamine is implicated in autism, copper homeostasis may be particularly relevant; an excess of copper may be associated with dopamine dysregulation. Zinc is required for structural integrity and/or catalysis of more than 200 enzymes, the majority of which are zinc metalloenzymes involved in nucleic acid and protein syntheses . Whenever zinc becomes deficient, copper tends to accumulate . Zinc and copper normally exist in a delicate balance. Zinc is a primary copper antagonist. When zinc is deficient, copper tends to accumulate in various storage organs.
The frequency of zinc deficiency, copper toxicity, and low zinc/copper in children with ASDs may indicate a decrease in the functioning of the metallothionein system. A retrospective review of plasma zinc, serum copper, and zinc/copper was done on data from 230 children with autism, pervasive developmental disorder not otherwise specified, and Asperger's syndrome. The entire cohort's mean zinc level was 77.2 μg/dl, mean copper level was 131.5 μg/dl, and mean Zn/Cu level was 0.608μg/dl, which was below the 0.7 cutoff of the lowest 2.5% of healthy children. The plasma zinc/serum copper ratio may be a biomarker of heavy metal toxicity, particularly mercury toxicity, in children with ASDs .
In this study, it is evident that levels of mercury and copper in hair are significantly associated with higher CARS scores. This was supported by Adams et al.  who found that severity of a child's autism coincided with the levels of toxic metals excreted in their urine after treatment with metal removal therapy; the higher the levels of antimony and other metals excreted, the more severe was the child's autism.
Results also showed that the severity of autism is highly significant in female children with autism, which could be explained by the fact that, because autism is rarer in female children, it may take more number of risk genes for a female child to have autism. In addition, there is a possibility that there might be a biological difference in autism for female children versus male children .
The relatively low prevalence of the disorder and the economic cost limited the participant number and testing of other substrates in this study. However, the investigators tried to choose representatives of the protective and exacerbating factors that were suggested earlier.
This study points out significant differences between children with autism and controls with increased levels of lead and copper, and decreased levels of mercury and zinc in hair sample analysis. CARS scores correlated positively with mercury and copper, whereas the IQ correlated negatively with lead. These results suggest a complementary role for the studied elements in the pathogenesis of autistic disorder, which should be considered in the management plane.
It is important to first reduce exposure to toxic metals as much as possible and recommend nutritional supplementation especially for children with autism who have a need for increased amounts of vitamins, minerals, and some amino acids. More in-depth studies involving larger sample size to investigate the precise way of gene-environment interaction are recommended. In addition, population-based human epidemiological studies are needed to specify and explore the relationships between environmental chemical insults and the expression of key genes that are already linked to autism.
There is no conflict of interest to declare.
1. Palmer RF, Blanchard S, Wood R. Proximity to point sources of environmental mercury release as a predictor of autism prevalence. Health Place 2009; 15:18–24
2. Holmes AS, Blaxill MF, Haley BE. Reduced levels of mercury in first baby haircuts of autistic children Int J Toxicol. 2003;22:277–285
3. Volkmar FAlbert H, Loosen T, Nurcombe B, Leckerman F. Autism and the pervasive developmental disorder Current diagnosis and treatment in psychiatry. 20082nd ed USA McGraw-Hill Companies, Inc
4. Elsner J. Testing strategies in behavioral teratology: : III microanalysis of behavior Neur Teratology. 1986;8:573–584
5. Geier DA, King PG, Sykes LK, Geier MR. A comprehensive review of mercury provoked autism. Indian J Med Res 2008; 128:383–411.
6. Davis L, Kornfeld M, Mooney HS, Fiedler KJ, Haaland KY, Orrison WW, et al. Methyl mercury poisoning: long term clinical, toxicological, and pathological studies of an affected family Ann Neur. 1994;35:680–686
7. Nishio H, Nezasa KI, Hirano J, Nakata Y. Effects of thimerosal, an organic sulfhydryl modifying agent, on serotonin transport activity into rabbit blood platelets Neurochem Int. 1996;29:391–396
8. Rajanna B, Hobson M. Influence of mercury on uptake of (3H) dopamine and (3H) norepinephrine by rat brain synaptosomes Toxicol Lett. 1985;27:7–14
9. Faber S, Zinn GM, Kern Ii JC, Skip Kingston HM. The plasma zinc/serum copper ratio as a biomarker in children with autism spectrum disorders Biomarkers. 2009;14:171–180
10. Geier DA, Kern JK, Garver CR, Adams JB, Audhya T, Nataf R, et al
. Biomarkers of environmental toxicity and susceptibility in autism. J Neurol Sci 2009; 280:101–108
11. Geier DA, King PG, Sykes LK, Geier MR. A comprehensive review of mercury provoked autism Indian J Med Res. 2008;128:383–411
12. Hien D, Matzner F, First M, Spitzer R, Williams J, Gibbon M. Structured clinical interview for DSM IV childhood diagnoses. KID - SCID; 2004.
13. Schopler E, Reichler RJ, DeVellis RF, Daly K. Toward objective classification of childhood autism: childhood autism rating scale (CARS) J Autism Dev Disord. 1980;10:91–103
14. Alfred B The development of intelligence in children: the Binet-Simon scale (Publications of the Training school at Department of Research, Vineland, New Jersey). 1916 Baltimore Williams & Wilkins Company
15. Sorenson JR, Melby EG, Nord PJ, Petering HG. Interferences in the determination of metallic elements in human hair. An evaluation of zinc, copper, lead and cadmium, using atomic absorption spectrophotometry Arch Environ Health. 1973;27:36–39
16. Van Loon JC Selected methods of trace metal analysis: biological and environmental samples. 1985 New York Wiley-Interscience
17. Eads EA, Lambdin CE. A survey of trace metals in human hair Environ Res. 1973;6:247–252
18. Stockwell PB, Corns WT. The role of atomic fluorescence spectrometry in the automatic environmental monitoring of trace element analysis J Automatic Chem. 1993;15:79–84
19. Adams JB, Baral M, Geis E, Mitchell J, Ingram J, Hensley A, et al. The severity of autism is associated with toxic metal body burden and red blood cell glutathione levels J Toxicol. 2009 [Epub ahead of print] doi:10.1155/2009/532640.
20. Fido A, Al-Saad S. Toxic trace elements in the hair of children with autism. Autism 2005; 9:290–298.
21. Lanphear BP, Hornung R, Khoury J, Yolton K, Baghurst P, Bellinger DC, et al. Low-level environmental lead exposure and children's intellectual function: an international pooled analysis Environ Health Perspect. 2005;113:894–899
22. Abdel Mageed AB, Oehme FW. A review of the biochemical roles, toxicity and interactions of zinc, copper and iron: I. Zinc Vet Hum Toxicol. 1990;32:34–39
23. Bowman MB, Lewis MS. The copper hypothesis of schizophrenia: a review Neurosci Biobehav Rev. 1982;6:321–328
24. Yanik M, Kocyigit A, Tutkun H, Vural H, Herken H. Plasma manganese, selenium, zinc, copper and iron concentrations in patients with schizophrenia Biol Trace Elem Res. 2004;98:109–117