I have received many emails about yesterday’s post on the CDC autism prevalence study. I thought I would spend some time to briefly address 3 specific issues.

1. Prevalence Rates and Home Schooling.

I received a thoughtful email about the impact of home schooling on the CDC prevalence rate and autism research in general, given that many children with ASDs may be home schooled. Here is my response: Read More

A review of: D GEIER, J KERN, C GARVER, J ADAMS, T AUDHYA, R NATAF, M GEIER (2008). Biomarkers of environmental toxicity and susceptibility in autism☆ Journal of the Neurological Sciences DOI: 10.1016/j.jns.2008.08.021

One bio-social model of the etiology of autism suggests that a genetic predisposition, in the form of limited ability to remove toxins from the body (e.g., mercury), combined with exposure to such toxins, leads to an increased risk for developing autism. As I previously described in this study, researchers have examined urinary porphyrins as a measure of mercury exposure, and some studies have found increased levels of porphyrins in children with autism. In this study, the authors examined urinary porphyrin metabolites (a proposed measure of heavy metal toxicity) and plasma sulfates (a proposed measure of detoxification capacity) among children with autism.

The sample included 28 children between the ages of 2 and 16 recruited from the Dallas/Fort Worth community. These children had a diagnosis of autism (Childhood Autism Rating Scale scores above 30). This group was categorized into a mild (CARS
38.5) autism. Blood and urine samples were collected for analysis. A laboratory standard control sample of typically developing children was also included in the plasma analysis only.

The mild ASD group had significantly lower ratios of key porphyrin levels when compared with kids with severe ASD. The following group means are statistically significantly different from each other:

Porphyrin
Pentacarboxyporphyrin
MILD ASD = 4.92±2.79 VS. SEVERE ASD = 6.0±1.58

Precoproporphyrin
MILD ASD = 17.3±8.9 VS. SEVERE ASD = 24.05±7.28

Ratios:
Pentacarboxyporphyrin/uroporphyrins I and III
MILD ASD = 0.19±0.06 VS. SEVERE ASD = 0.27±0.08

Precoprophyrin/uroporphyrins I and III
MILD ASD = 0.68±0.28 VS. SEVERE ASD = 1.09±0.36

Coproporphyrins I and III/ uroporphyrins I & and III
MILD ASD = 9.54±2.97 VS. SEVERE ASD = 12.64±3.47

(Precoproporphyrin+ pentacarboxyporphyrin) / (uroporphyrins I & and III+ heptacarboxyporphryin)
MILD ASD = 0.73±0.26 VS. SEVERE ASD = 1.1±0.29

The authors concluded that increased urinary porphyrin metabolites were associated with more severe autism based on CARS scores. Urinary porphyrin are believed to represent mercury toxicity.

Furthermore, the authors found significantly lower levels of plasma sulfates (Plasma cysteine, Plasma reduced glutathione, Plasma oxidized glutathione) among children with autism when compared to typically developing kids. Decreased sulfation (low plasma levels of sulfates) can indicate limited detoxification capacity, especially of heavy metals such as mercury.

In conclusion, the study presents some compelling evidence regarding differences in urinary porphyrin metabolites between kids with mild and severe autism symptoms, as well as differences in plasma sulfates between kids with autism when compared to neurotypical kids. This is consistent with the author’s theory that mercury exposure plays a role in autism. However, given the controversy regarding the mercury-autism association, I would like to clarify that these results do not indicate that mercury causes autism. Yes, it is possible that mercury toxicity and reduced detoxification capacity plays a role in autism, both, in the onset and severity. However, it is also possible that Autism itself results in reduced detoxification capacity and mercury toxicity via other mechanisms, but that such toxicity is not associated at all with the development of the disorder. For example, erythrocyte sedimentation rate and C-reactive protein are tests used in arthritis. Atypical results on these tests are found in people with arthritis. Yet, neither one is related to any of the proposed causes of arthritis, and instead reflect a consequence of the disorder itself (inflammation).

A review of: Austin, D., Shandley, K. (2008). An Investigation of Porphyrinuria in Australian Children with Autism. Journal of Toxicology and Environmental Health, Part A, 71(20), 1349-1351. DOI: 10.1080/15287390802271723

The journal of Toxicology and Environmental Health just published a study conducted in Australia examining the possible link between mercury and autism. The study examined urinary porphyrins as a measure of mercury exposure in children with autism. Porphyrinuria, or the excess urinary excretion of porphyrin, is purported to reflect heavy metal exposure and in particularly mercury. Two previous studies (Nataf et al., 2006, and Geier & Geier, 2007) used this urinary measure and reported increased levels of porphyrins in children with autism when compared to typically developing children. In the current study the authors examined urinary samples of 41 patients with ASD (detailed diagnostic procedure information was not provided). The age of the sample ranged from 1 to 16 (average 6). There were 30 boys and 11 girls. The authors did not include a control group. That is, no local comparison group of typically developing children was used. Instead, the authors compared the levels of porphyrins of the Australian sample with the control samples (typically developing kids) used by the two previous studies as well as to ‘normative’ laboratory ranges obtained from a French laboratory and the normative ranges published in a 1996 European study (Minder and Schneider-Yin, 1996).

The authors reported that the ratio of uroporphyrin to coproporphyrin (CP to UP) was statistically significantly higher in the Australian ASD group when compared to all control samples of the previous studies. The comparison effect sizes were very large, namely: 1.60 when compared to the Geier & Geier sample, 1.54 when compared to the Nataf et al sample, and 1.46 when compared to the 1996 normative sample. Effect size is a measure of the differences between the means of two groups that is not as sensitive (not affected by) the very large differences in sample sizes between these studies. Effect sizes in this range (1.46 to 1.60) indicate that the differences between the groups were very substantial.

A final thought. I can not discuss the merits of this particular urinary measure as reflective of mercury exposure or mercury toxicity, since this is beyond my understanding of heavy metal metabolism, thus I would simple make one final comment regarding the methodology of this study. I am very surprised that the authors did not include a local comparison sample, especially since their intention was to replicate the previous findings within a local Australian group. This is a strong limitation of the study. The results indicate that the Australian ASD group is statistically significantly different than the typically developing group used in the two previous samples (one from the USA and another from France) in regards to CP to UP ratio, but the results provide no information as how this ASD group compares to typically developing children in the sample geographical regions.

However, the data is compelling in showing a strong difference in the CP to UP ratio between the Australian sample and typically developing children in the USA and France. Does this mean that mercury causes autism? Not at all. Readers should be careful not to make conclusions about causal mechanisms from these type of association studies. There are multiple possible interpretations of the data, including the possibility that heavy metal exposure may play a role in the development of ASD. However, it is also possible that CP/UP ratio differences between these groups are the result, rather than the cause, of physiological differences in Autism. The results of this study do not support one interpretation more than the other. The results simply indicate that the groups are different in CP to UP ratio. The data do not tell us why these groups are different, or whether mercury causes autism.

Geier, D. A., and Geier, M. R. 2007. A prospective study of mercury toxicity
biomarkers in autistic spectrum disorders. J. Toxicol. Environ. Health,
A 70:1723–1730.

Minder, E. I., and Schneider-Yin, X. 1996. Age-dependent reference values
of urinary porphyrins in children. Eur. J. Clin. Chem. Clin. Biochem.
34:439–443.

Nataf, R., Skorupka, C., Amet, L., Lam, A., Springbett, A., and Lathe, R. 2006.
Porphyrinuria in childhood autistic disorder: Implications for environmental
toxicity. Toxicol. Appl. Pharmacol. 214:99–108.

A review of: Baird, G., Charman, T., Pickles, A., Chandler, S., Loucas, T., Meldrum, D., Carcani-Rathwell, I., Serkana, D., Simonoff, E. (2008). Regression, Developmental Trajectory and Associated Problems in Disorders in the Autism Spectrum: The SNAP Study. Journal of Autism and Developmental Disorders DOI: 10.1007/s10803-008-0571-9

Although most children with autism present very early signs and symptoms and a linear developmental trajectory, a small subset of children present a trajectory characterized by normal development followed by a loss of acquired skills or a failure to use the acquired skills. This pattern has been termed autistic regression. Possible explainations for this phenomenom have varied from a genetic effect on brain restructuring and pruning during the early stages of life, to enterocolitis due to vaccinations, to epilepsy. In this study, the authors explored differences in developmental outcomes for children with and without regressive autism, and the association between regression and enterocolitis and epilepsy. This study examined a population cohort born in the UK in 1990 and 1991. Out of 56,946 children in this cohort, 218 had and ASD diagnosis by age 10. A subset of these children were evaluated via ADOS and ADI and divided into a broad autism (N=105), narrow autism (N=53), and no autism (N=97). The narrow autism group met full criteria for autism based on ICD-10. The broad autism group met clinical consensus for autism but not full ICD-10 criteria. These children were then evaluated for history of epilepsy, gastroinstestinal problems, and developmental regression. 39% of children with narrow autism had a history of regression during development. This compared to 11% of children with broad autism, and 3% of children with no autism. On average this regression occurred around the 25 month of age. There were no differences in IQ or adaptive functioning between those with or without regression. However, those with regression classified in the broad autism group had significantly more symptoms than those without regression also classified in the broad autism group. Regression was not associated with gastroinstestinal symptoms or with epilepsy.

A review of: Schultz, S.T., Klonoff-Cohen, H.S., Wingard, D.L., Akshoomoff, N.A., Macera, C.A., Ming Ji, . (2008). Acetaminophen (paracetamol) use, measles-mumps-rubella vaccination, and autistic disorder: The results of a parent survey. Autism, 12(3), 293-307. DOI: 10.1177/1362361307089518

A study in the latest issue of the journal Autism examined the possible role of acetaminophen use after MMR vaccine and autism. The authors provided an excellent review of the MMR vaccine-autism research, which indicates that although some clinical studies have found a link, most epidemiological studies have failed to find an association between MMR and autism. The authors noted that acetaminophen is commonly used to treat the adverse reaction of MMR vaccinations such a fever and rash. In addition, one study (Alberti et al, 1999) showed that some low functioning children with autism process acetaminophen differently. Thus, the authors proposed a innovative hypothesis: Does acetaminophen use after MMR vaccination increase the risk for Autism?

The authors recruited parents of typically developing children and children with autism via internet advertisement. The total sample included 83 parents completing the survey for children with autism and 80 parents completing the control survey. The surveys included a variety of questions about the child such as age, gender, what medications were used to prevent or treat reactions to the MMR vaccine, including aspirin, acetaminophen, or ibuprofen. The survey of parents of children with autism included additional questions about their children diagnosis such as whether a regression in development was observed.

The authors found that parents of children with autism reported:
- more adverse effects of MMR vaccine, including fever, diarrhea, irritability
- increased presence of concurrent illnesses with MMR vaccine
- more acetaminophen use after the MMR vaccine among children who had a reaction to the vaccine, children who had a regression in development, and those under 5.
- more acetaminophen use between 12 and 18 months of age
No association was found between ibuprofen use and autism.

A few caveats:
The finding that parents of children with autism reported more adverse effects of MMR vaccine or more concurrent illnesses with MMR vaccine is not overly informative. Note that these results were based on parental reports via internet with no possibility of verification of accuracy of such reports. So it is completely plausible to argue that given the extended media coverage of the vaccine-autism link, some parents of children with autism are more attuned to their children histories after vaccination and thus are more likely to remember or report complications. What is informative and actually interesting is that there was a significant difference in reports of acetaminophen use as compared to ibuprofen use. This difference can not easily be explained on the basis of some report bias. The problem is that acetaminophen use was reported much more frequently than ibuprofen use by all parents. So it could be argued that since parents of children with autism were more likely to report complications (even if just a by-product of recall bias), the use of acetaminophen will also appear to be different between the two groups.