1. Blaurock-Busch E, Amin OR, Rabah T. {{Heavy metals and trace elements in hair and urine of a sample of arab children with autistic spectrum disorder}}. {Maedica (Buchar)};2011 (Oct);6(4):247-257.
General information: Autism is a severe developmental disorder which involves social withdrawal, communication deficits, and stereotypic/repetitive behavior. The pathophysiological etiologies which precipitate autism symptoms remain elusive and controversial in many cases, but both genetic and environmental factors (and their interactions) have been implicated. While autism is considered multicausal, environmental factors have received significant attention. International discussion has ocused on neurotoxins such as mercury and lead, suggesting that these and other toxic metals contribute to the development of the disorder. An epidemiological study released in 2006 (Palmer et al.) linking Toxic Release Inventory (TRI) data on mercury to special education data in Texas reported a 61% increase in autism prevalence rates (or 17% adjusted) per 1000 pounds of mercury released into the environment (1). We attempted to further evaluate whether exposure to variable environmental contributes to the genesis of autistic spectrum disorder, and thus is a factor increasing the risk for developing autism symptoms in utero or in early childhood.Purpose: The purpose of this study is to examine possible environmental risk factors and sources of exposure to mercury and other heavy metals in children with autism spectrum disorder versus controls. Through laboratory diagnostics we are able to distinguish between present and past exposure (i.e. hair analysis measurements reflect past exposure), urinary excretion levels of unprovoked urine represent immediate exposure. By assessing a spectrum of trace elements and heavy metals in hair and urine of both autistic and control groups, we focused on the participants approximately past and present exposure.Methodology: The participants were 25 Autistic Spectrum Disorder (ASD) children (22 boys and 3 girls) between the age of 3 and 9 years. They were either diagnosed previously by other psychiatrist, psychologist, and developmental pediatrician or suspected by their parents as being autistic. All children were attendants to the Child Psychiatric Clinic in Erfan Psychiatric Hospital in Jeddah, KSA. Samples were collected during the period of June 2006 to March 2008. A control group of 25 children without any psychiatric or medical disorders was age-matched and sex-matched. All parents signed informed consent forms. All autistic children were subjected to a full clinical child psychiatric sheet for the diagnosis of autism spectrum disorder and exclusion of other psychiatric disorders according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV). The severity of autistic symptomatology was measured by the Childhood Autism Rating Scale (CARS) and Autism Behavior Checklist (ABC) using the Arabic versions. Both groups were subjected to the Questionnaire on Exposure to Heavy Metals, Physical Symptoms, and Child Development. Hair and baseline urine samples (i.e. unprovoked urine) were taken from both groups and sent to the German clinical and environmental laboratory Micro Trace Minerals Gmbh, for the detection of heavy metals and trace elements levels where metal testing was performed via ICP-MS spectroscopy utilizing cell technique. Results: By comparing the ASD Group to the Control Group, we found a statistically significant difference in the mean hair levels of arsenic, cadmium, barium, cerium and lead (p=0.01, 0.03, 0.003, 0.003, and 0.03 respectively), and in the mean hair levels of magnesium and zinc (p=0.001 and 0.003 respectively). There were also statistically significant differences in the mean urine levels of aluminum, barium, cerium, mercury, and lead (p=0.004, 002, 0.014, 0.006 and 0.004 respectively), and in the mean urine levels of copper and germanium (p=0.049 and 0.02 respectively). An agreement was found in both specimen (hair and urine) for barium and lead. The statistically significant differences in mean hair levels of arsenic, cadmium, and cerium were not supported by urine baseline levels. Also, the statistically significant magnesium and zinc levels of hair were not supported by urine levels. A disagreement was also found with copper and germanium concentrations.
2. Chen CP, Lin SP, Su JW, Lee MS, Wang W. {{Phenotypic features associated with mosaic tetrasomy 9p in a 20-year-old female patient include autism spectrum disorder}}. {Genet Couns};2012;23(2):335-338.
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3. Haebig E, McDuffie A, Weismer SE. {{The Contribution of Two Categories of Parent Verbal Responsiveness to Later Language for Toddlers and Preschoolers on the Autism Spectrum}}. {Am J Speech Lang Pathol};2012 (Aug 9)
PURPOSE: Longitudinal associations between two categories of parent verbal responsiveness and language comprehension and production one year later were examined in 40 toddlers and preschoolers with a diagnosis of an autism spectrum disorder (ASD). METHOD: Parent-child play samples using a standard toy set were digitally captured and coded for child engagement with objects and communication acts and for parent verbal responses to play and communication. RESULTS: After controlling for parent education, child engagement and initial language level, only parent directives for language that followed into the child’s focus of attention accounted for unique variance in predicting both comprehension and production one year later. A series of exploratory analyses revealed that parent comments that followed into the child’s focus of attention also accounted for unique variance in later comprehension and production for children who were minimally verbal at the initial time period. CONCLUSIONS: Child developmental level may warrant different types of linguistic input to facilitate language learning. Children with ASD who have minimal linguistic skills may benefit from parent language input that follows into the child’s focus of attention. Children with ASD who are verbally fluent may need more advanced language input to facilitate language development.
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4. Mayor S. {{Advertising watchdog orders website to remove claims linking MMR vaccine with autism}}. {BMJ};2012;345:e5420.
5. Ouss-Ryngaert L, Alvarez L, Boissel A. {{Autisme et prématurité : état des lieux}}. {Arch Pediatr};2012 (Aug 6)
Research has shown a high rate of autism spectrum disorders among very low birth weight children over the past decade. This paper proposes a literature review on this topic. Two generations of research have followed one another. The first retrospective studies found a high rate of ASD among premature babies. The second generation of prospective studies underlined and relativized this risk. Prospective research using screening tools (M-CHAT) have found around 20 % ASD, whereas 2 studies assessing the actual diagnosis found 5 % and 8 % ASD, 10 to 12 times more than in the general population. A number of hypotheses have been put forward to explain these high rates of ASD: sensory impairment associated with prematurity, white matter abnormalities, and cerebellar impairment. The authors propose complex models that take into account neurological deficits and the effects of perinatal events on interactive dynamics between infants and their caregivers. These models aim to allow suitable prevention and care for premature children with autism, a heavy additional handicap.
