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.

…But this study is compelling in showing an association between mercury exposure and autism rates, and scientists can not just ignore it under the basis of its imperfect design and inability to make causal links – if that is the case, then only carefully controlled laboratory studies, with poor external validity, should be published and accepted as contributors to our greater scientific knowledge.

A review of: PALMER, R., BLANCHARD, S., WOOD, R. (2008). Proximity to point sources of environmental mercury release as a predictor of autism prevalence. Health & Place DOI: 10.1016/j.healthplace.2008.02.001

This fascinating, yet bound to be controversial, study hit the news yesterday as it was made available (pre-publication) by the Journal Health & Place. The study is simple, straightforward, elegant, with some powerful findings. In fact, the findings are somewhat daunting given the simplicity of the design. The researchers reviewed the amount of mercury release reported by industrial facilities and power plants in the State of Texas in 1997 from data provided by US Environmental Protection Agency Toxics Release Inventory. They compared these data against autism rates in 1997 and 2002 as measured by schools’ autism classifications provided by the Texas Education Agency. Using a specialized geographical analysis system, the authors were able to locate each source of mercury and calculate the distance between each mercury source and each school. The results:

Industrial release of mercury and distance to industrial sources independently predicted increased rates of autism. The association with industrial release of mercury was not linear, instead the statistical model fit suggested an accelerated risk. This association remained statistically significant after controlling for specific variables such as SES, urbanicity, and race.

Power plant release of mercury and distance to power plant independently predicted increased rates of autism. In this case the association was linear (not accelerated). Again, this association remained statistically significant after controlling for other variables.

It is easy to dismiss these findings as inconsequential because they are ‘correlational’ in nature, or do not really prove anything. Researchers are too often guilty of selective acceptance of research: those studies that fit the consensus are accepted while those that don’t are dismissed for their methodological flaws – even though the studies we accept are equally flawed.

In the spirit of fairness I have to say that these findings are strong. Their methodology and analytical process are not any different from what is commonly seen in social science or epidemiology research. Is it perfect? Far from it. Is it useful or informative? Definitively! The data speak very clearly: In Texas, mercury release from industrial sources and power plants in 1997, and school proximity to these sources, are associated with rates of autism in 2002 as measured by school special education classifications.

Does this mean that mercury causes autism? Not at all. In the last sentence of the previous paragraph you can not replace the words are associated with with the word cause. There is a major difference. The data, albeit strong, have limitations. For example, the most obvious (to me) alternative explanation is that mercury release and proximity to these sources is also associated with another mystery factor that is causing this apparent association and that in fact, mercury release has nothing to do with autism rates in 2002. Let’s hypothesize that these power plants and industrial sources also release another toxin – let’s call this toxin autisimic (this is a made up toxin). These sources release mercury and autisimic at the same rate, so for each pound of mercury released there is a pound of autisimic released. It is possible then that this autisimic toxin directly increases the risk for autism, and this could explain completely the strong (but now obviously inaccurate) association between mercury release and autism.

Does this study show that vaccines cause autism? Absolutely not. I know this question may sound ludicrous to some, but I pose it rhetorically because I am certain that some will make the wide leap and link these findings to the vaccine issue.

There are other problems and limitations with this study, such as how autism rates were calculated (using all children instead of only those born inor after 1997), whether the autism rates are truly climbing and not explained by other factors, whether there are other variables that could be explaining this relation, etc, etc — and yes, this study does not prove or directly indicate that autism is caused by mercury exposure (click here for a much more critical review of this study). But this study is compelling in showing an association between mercury exposure and autism rates, and scientists can not just ignore it under the basis of its imperfect design and inability to make causal links – if that is the case, then only carefully controlled laboratory studies, with poor external validity, should be published and accepted as contributors to our greater scientific knowledge. This is study is far, far, from perfect, and many changes should have been requested prior to publication, but I can say the same of 90% of what is published today.

A commentary on: Aschner, M. (2008). Response to Article by DeSoto and Hitlan on the Rlationship Between Mercury Exposure and Autism. Journal of Child Neurology, 23(4), 463-463. DOI: 10.1177/0883073808314647

DeSoto, M.C., Hitlan, R.T. (2008). Concerning Blood Mercury Levels and Autism: A Need to Clarify. Journal of Child Neurology, 23(4), 463-465. DOI: 10.1177/0883073808314718

The latest issue of the Journal of Child Neurology includes two letters regarding the mercury-autism controversy. For most people familiar with this issue, this summary will not present anything new, but for those interested in knowing the basics of this latest controversy, here is a micro-crash course on the mercury-autism link.

In 2004 authors Ip, Wong, HO, Lee, and Wong, published an article in the Journal of Child Neurology comparing the blood and hair mercury levels of children with and without autism in order to examine if a mercury-autism link existed. The results were as follow:

There was no difference in the mean mercury levels [between the group]. The mean blood mercury levels of the autistic and control groups were 19.53 and 17.68 nmol/L, respectively (P = .15), and the mean hair mercury levels of the autistic and control groups were 2.26 and 2.07 ppm, respectively (P = .79).

The conclusion, which was supposedly inconsistent with the theory that mercury causes autism, shocked some members of the autism community. I said ‘supposedly’ because whether or not the mercury theory is correct, the manner in which the results are presented goes beyond what the data can actually say. Specifically, the authors concluded that:

Thus, the results from our cohort study with similar environmental mercury exposure indicate that there is no causal relationship between mercury as an environmental neurotoxin and autism.

The problem here is that this data only speak to concurrent levels of mercury and autism diagnosis. So it is entirely possible that in some children pre- or post-natal exposure to this toxin results in neurodevelopmental changes leading to autism symptoms. This idea does not imply that mercury levels would remain high in affected children. It only implies that that these children were exposed to this toxin. A similar example would be exposure to alcohol during pregnancy leading to fetal alcohol syndrome (FAS). Children with FAS do not have higher levels of alcohol in their blood than typically developing kids. I am not endorsing the mercury theory, but I am stating that the conclusions as stated by Ip go beyond what their data say.

But back to the Ip et al. (2004) study. In 2007, DeSoto and Hitlan published an article in the Journal of Child Neurology after they found a major mathematical mistake in the original findings reported by Ip. Specifically, they found that the non-significant differences in blood levels reported by Ip was an error and significant differences were actually observed. I did the calculations myself, and yes in fact, the kids with autism had significantly higher mercury levels than the control group (t = 2.6163; df = 135; p>.01).

Then in the latest issue of the Journal of Child Neurology, Dr. Michael Aschner published the following short correspondence:

In a recent article DeSoto and Hitlan1 reanalyzed an original data set, concluding that a relationship exists between blood mercury levels and the diagnosis of autism spectrum disorder (ASD). The conclusion is based on the reanalysis of hair to blood mercury ratios. Hair to mercury concentration ratios while informative need to be considered within the context of a temporal relationship. As elegantly demonstrated by Grandjean and colleagues, mercury levels in the hair reflect a delayed average compared to the blood mercury level averages. That is, mercury hair concentrations at hypothetical time point T reflect blood mercury levels at T minus 1 to 2 months. Chelation therapy and changes in diet and fish consumption (both more likely to occur in the ASD group) in the 2 months preceding the mercury analysis are likely to affect blood, but not hair mercury sample concentrations. The analysis by DeSoto and Hitlan, which presumes that the 2 biomarkers are equally affected, is clearly erroneous. Thus, absent appropriate corrections for the temporal fluctuations in mercury levels, the conclusions should be interpreted with utmost caution and revalidated taking the above issue into account.

This was followed by a response from DeSoto and Hitlan explaining further that their 2007 study addressed directly the error in blood sample Mean differences as reported by Ip et al in 2004. DeSoto and Hitlan re-analyzed Ip’s data showing that in fact blood mercury levels in the autistic group were higher than in the control group. This finding, and the original Ip error, had nothing to do with hair-to-blood ratios as described by Dr. Aschner. Dr. Aschner criticism is much more applicable to a separate hair analysis performed by DeSoto and Hitlan showing that the autism group had lower hair mercury levels than expected based on their blood samples, which is inconsistent with the idea that chelation therapy may have affected the blood levels. I explain: blood levels reflect immediate levels of mercury while hair levels reflect levels 1 to 2 month prior to testing. Thus, if blood levels at Time 1 were 20 (I’m using random numbers as example), then hair levels at Time 2 (2 month later) should be 20. If after Time 1 the child undergoes chelation therapy, then theoretically, blood levels at time 2 (2 month later) should be lower than 20 but hair levels should remain 20. Thus at Time 2, blood levels should be lower than hair levels. This was not supported by DeSotos’ analyses. What does this mean? Simply that the differences in blood levels found between the autism and control group are unlikely to have been affected by chelation therapy in the autistic group since the hair-blood analysis was not consistent with what is expected if chelation therapy had occur. WARNING: this is not a statement supporting chelation therapy, it is just a clarification of a possible interpretation of this data.

Does this mean that vaccines cause autism? Not at all. Again, although we would like to think that data can give us the entire story, data speak in morphemes rather than words, or sentences. This data only indicate that this particular group of children with autism had higher mercury levels than typically developing children. This could mean many things, such as that the children with autism have difficulty processing mercury or that the children with autism were exposed to higher levels of mercury, and these explanations in turn, may or may not have anything to do with the symptoms observed in children with autism, both in terms of symptom presentation, severity, or causes. These data simply do not give us that information.

More recent articles about the Autism and Mercury controversy and the Autism and Vaccines controversy can be found here.