passionless Droning about autism

Archive for the ‘Prevalance’ Category

Hello friends –

These have been rough times for the people who are heavily invested in the kissing cousin theories of autism as a predominantly genetic disorder and the static, or near static rate of autism.  The California twin study that is old news by the time I get this finished showed much different rates of genetic participation than previously believed.  These findings exposed the underlying frailty of gene-based causation theories, namely that some of the most widely referenced studies in the autism literature, studies used repeatedly as a basis for the notion that autism was ‘the most highly heritable neurodevelopmental disorder’, were, in fact, relatively underpowered, and suffered from serious temporal and methodological shortcomings.    

By contrast, the California study looked at two hundred twin pairs, a lot more twins than any previous study and actually performed autism diagnostics on all of the participating children, whereas other studies relied on medical records.  Performing dedicated ADOS diagnosis prospectively on the children allowed the researchers to discern between autism and PDD-NOS, something that not all previous studies were not able to perform, if for no other reason than the DSM-IV wasn’t even released when several of the most often cited studies were published.   This is from the Comment section of the California twin study:

The results suggest that environmental factors common to twins explain about 55%  of the liability to autism. Although genetic factors also play an important role, they are of substantially lower magnitude than estimates from prior twin studies of autism. Nearly identical estimates emerged for ASD, suggesting that ASD presents the same liability spectrum as strict autism.

This is on top of the fact that there is a quiet, but growing acknowledgement of the fact that literally decades of genetic studies have failed to be able to explain more than a fraction of autism cases despite sequencing of tens of thousands of genomes.   This is a very similar situation to a great number of other disorders which we thought we would cure once the human genome was decoded.   [Note: That isn’t to say that we haven’t learned a lot from sequencing the genome, just that we didn’t quite get what we thought we were going to get.]

This ‘double hit’, so to speak, has reached a critical mass such that health officials are making politically shrewd, but refreshingly realistic statements, and dare I say, a sliver of common sense may be about to infiltrate the discussion about autism prevalence.  For example, as pointed out by Sullivan, Tom Insel, head of the National Institute of Mental Health keeps a blog where he recently blogged ‘Autism Spring’, which included this nugget within the context of continued failure of genetic studies to explain any substantial part of autism, “It is quite possible that these heritability estimates were too high. . .” Ouch. (I would recommend the entire blog posting by Mr. Insel.) 

The high heritability estimates, and implicit genetically-mediated cause of autism, are foundational pillars of the argument that autism rates have not changed over time.  Though overused, or used wrongly in many instances, there is a kernel of dispassionate reality behind the statement, ‘there is no such thing as a genetic epidemic’.  Without the crutch of exceedingly high heritability to rely on, the notion of a stable rate of autism loses the only hard science (read: replicable, biologically-plausible), i.e.,genetics, it ever had, and must place complete reliance on the softer sciences (read: unquantifiable, ‘greater awareness’), i.e.,sociology.  This is great news if you love impossible to verify estimates of prevalence and anecdotes about crazy uncle George who would have been diagnosed with autism forty years ago.  However, if you think we should be relying less on psychologists and cultural anthropologists to answer critical questions, and rely more on hard science, this means that the old narrative on autism prevalence holds even less allure than it did in the past, for those of you who thought this was possible.

Before Kid Autism came around, I would occasionally read discussion boards on the creationism versus evolution ‘debate’.  One thing that I noticed was that the creationists would often employ a ‘God of the Gaps’-style argument: anything that couldn’t be explained by science (yet), or anything necessary to support whatever fanciful construct had been erected to protect biblical creation fables, was ascribed to the work of God.  That’s one thing you have to give to God, he (or she!) can handle it all; it didn’t matter what primitive logical test biblical creation was failing to pass, the golden parachute clause was always that God could have just made things that way.  It was a nifty out on the part of the creationists, kind of like a get out of jail free card. The autism prevalence discussion has been working just like this, and the funny part is that the people that are always claiming to have the intellectual high ground, the supposed skeptics, are playing the part of the creationists!  Zing! 

Here is how it works:

Concerned Parent: It sure does seem like there is more autism than there used to be, what with there being X in a thousand kids with it!  That’s much, much more than even ten years ago!  My brothers, sisters and I all knew kids with mental retardation and Down’s syndrome, but we just don’t remember kids like we see today.

Supposed Skeptic: It is diagnostic substitution and ‘greater awareness’; autism incidence has been stable.  The DSM was changed which resulted in more children being labeled.

Concerned Parent:  It sure does seem like there’s more autism than there used to be.  Now there are Y kids in a thousand having autism!  Why does my son’s preschool teacher keep insisting something is changing?

Supposed Skeptic: It is diagnostic substitution and ‘greater awareness’; autism incidence has been stable.  The DSM was changed which resulted in more children being labeled.

Concerned Parent:  What the hell?  Now there are Z kids in a thousand having autism!  When are those genetic studies going to figure autism out, anyway? 

Supposed Skeptic: It is diagnostic substitution and ‘greater awareness’; autism incidence has been stable.  When does the new DSM come out again? 

(Replace X/Y/Z with any progressively larger numbers.)

It doesn’t matter what prevalence number is thrown about–even the astronomical one in thirty-eight figure bandied about for South Korean children didn’t cause so much as a raised eyebrow; the autism equivalent of God of the Gaps, greater awareness and loosening of diagnostic criteria can handle any amount of increase gracefully.  It is the equivalent of an uber-absorbent autism paper towel, capable of soaking up any number of new children with a diagnosis; there is, literally, no amount of an increase that the God of the Gaps can’t handle.   

If, instead the question was posed like this, ‘How much of the apparent increase in autism is real?’, the answer was always, ‘Zero’, regardless of what the current rates of autism were when you asked the question

Then a funny thing happened, a series of studies from several researchers showed a consistent trend of older parents giving rise to more children with autism than younger parents. There were differences between the studies on just how much of an effect an older parent had, but the overall direction of association was clear.  In this instance, there was also the luxury of a plausible biological mechanism that involved the mediator in favor, genetics.  The idea is that advancing age in the parent meant more years for gametes to get knocked by a random cosmic zap or other environmental nastygram and this disturbance created genetic problems down the line for the offspring, a theory I think is probably pretty good.   Once a couple of these studies started to pile up, there was a small shift in the narrative regarding autism prevalence; after all, nobody could bother to try to deny that parents were getting older compared to past generations.  Here is how it looked:

Concerned Parent:  What the hell?  Now there are X kids in a thousand having autism! 

Supposed Skeptic: Greater awareness and diagnostic substitution are primarily responsible for our observations of increased autism, although, ‘a real, small increase’ cannot be ruled out.   

And with that, there was a little less autism prevalence for the God of the Gaps to handle.   It never seemed to bother anyone that implicit in this argument is an impossible to quantify concept ‘small increase’.  If you were to ask someone what rate of autism ‘a small increase’ amounted to with more precision, the answer is whatever amount rises to the level of autism minus the difficult to quantify effect of older parents.  That is some lazy stuff.

Here are some examples of prominent online skeptics discussing the possibility of a true rise in autism.  See if you can detect a pattern.

Here is Stephen Novella pushing The Fairytale in 2009:

While a real small increase cannot be ruled out by the data, the observed increase in diagnostic rates can be explained based upon increased surveillance and a broadening of the definition – in fact autism is now referred to as autism spectrum disorder.

[Here we see the notion that everything can be explained by the God of the Gaps.]

Here is an example of Orac toying around with this filibuster just the other day, in August of 2011:

True, the studies aren’t so bulletproof that they don’t completely rule out a small real increase in autism/ASD prevalence, but they do pretty authoritatively close the door on their being an autism “epidemic.”

These aren’t the only examples, far from it.   Check it out:

It should be noted that the data cannot rule out a small true increase in autism prevalence. (Stephen Novella in 2008)

If the true prevalence rate of autism and ASDs has increased, it has not increased by very much. (David Gorski, 2010)

It should also be noted that all of this research, while supporting the hypothesis that the rise in autism diagnoses is not due to a true increase in the incidence but rather is due to a broadening of the definition  increased surveillance, does not rule out a small genuine increase in the true incidence. A small real increase can be hiding in the data. (Stephen Novella, 2008)

We should have the curiosity to wonder, what, exactly, does small mean in these contexts?  What percentage size increase should we consider small enough to hide within the data?  Five percent?  Ten percent?  What does ‘small’ mean, numerically, within a range?   Is a ten to twenty percent rise in autism rates reason for us to take comfort in the fact that the effect of greater awareness is real?  At what level does the percentage of ‘real’ autism increase mandate more than superficial lip service, more than a paragraph about ‘gene-environment interactions’ at the end of a two-thousand word blog post that takes pride in the intellectual chops of outthinking Jenny McCarthy?  You won’t get anyone to answer this question; they can’t, because they don’t really know what they mean when they say, ‘small’, other than, ‘it can’t be vaccination’. 

How do we know the amount of this increase must, in fact, even be ‘small’?  This becomes especially problematic when we consider the smackdown that the canard of autism as ‘among the most heritable neurological conditions’ has taken as of late.  If the high heritability estimates of autism are incorrect, yet so often repeated as gospel, why should we also assign confidence to the idea that the increase is trivial?  Isn’t one argument the foundation of the other?   Did either really have quality data behind them? 

This is a terrible, awful, horrible, completely fucking idiotic way to address a question as important as whether or not a generation of children is fundamentally different.  We cannot afford the ramifications of being wrong on this, but we seem to find ourselves in an epidemic of otherwise intelligent people willing to accept the pontifications of cultural anthropologists and the feebleness of social scientists on this critical question.   I am not arguing against the realities of diagnostic switching and greater awareness affecting autism diagnosis rates.  But we can understand that while they are a factor, we must also admit that we have little more than a rudimentary understanding of these impacts, and when we consider the implications of being incorrect, the potential disaster of a very real, not ‘small’ increase in the number of children with autism, we shouldn’t be overselling our knowledge for the sake of expedient arrival at a comforting conclusion.   We should be doing the opposite.

If we can’t have the robustly defendable values on autism rates right now, that’s fine, because that is the reality, but we should at least have the courage to acknowledge this truth.  This is the nature of still learning about something, which we are obviously doing in terms of autism, but in that situation, we don’t have the currency of scientific debate, decent data, to be saying with authority that any true increase in autism is small. 

Unfortunately for the purveyors of The Fairytale, things are going to get a lot worse.  The problem is that we are starting to identify extremely common, in some cases, recently more common, environmental influences that subtly increase the risk of autism.  These are further problems for a genetic dominant model and effectively mandate that the ‘small increase’ is going to have to start getting bigger as a measurement, with a correlated decrease in the amount of autism that cultural shuffling can be held responsible for.  Will anyone notice?

By way of example, we now have several studies that link the seasons of gestation with neurodevelopmental disorders including autism and schizophrenia; i.e., Season of birth in Danish children with language disorder born in the 1958-1976 period, Month of conception and risk of autism, or Variation in season of birth in singleton and multiple births concordant for autism spectrum disorders, which includes in the abstract, “The presence of seasonal trends in ASD singletons and concordant multiple births suggests a role for non-heritable factors operating during the pre- or perinatal period, even among cases with a genetic susceptibility.”  Right!  As I looked up some of these titles, I found that the evidence for this type of relationship has been well known for a long time; schizophrenia, in particular has a lot of studies in this regard, i.e., Seasonality of births in schizophrenia and bipolar disorder: a review of the literature, which is a review of over 250 studies that show an effect, and I also found Birth seasonality in developmentally disabled children, which includes children with autism and was published in 1989, which is like 1889 in autism research years. 

Our seasons have remained constant (but probably won’t stay too constant for much longer. . . ), but this still throws a whole barrel of monkey wrenches into the meme of a disorder primarily mediated through genetics. 

More damning for the Fairytale are some studies presented at this year’s IMFAR, and some others just published, that tell us that abnormal immune profiles during pregnancy appear to provide slightly increased risk for autism, roughly doubling the chance of a child receiving a diagnosis.  The groovy part is that the studies utilized both direct and indirect measurements of an activated immune system to draw similar conclusions, a sort of biomarker / phenotype crossfire.

From the direct measurement end, we have Cytokine Levels In Amniotic Fluid : a Marker of Maternal Immune Activation In Autism?, which reports that mothers with the highest decile of tnf-alpha levels in the amniotic fluid had about a one and a half times increased risk for autism in their children.  This makes a lot of sense considering the robustness of animal models of an acute inflammatory response during pregnancy and its impact on behavior. 

Another study, this one from the MIND Institute in California (which I love), is Increased mid-gestational IFN-gamma, IL-4, and IL-5 in women giving birth to a child with autism: a case-control study (full paper). They found that in pregnant mothers, increased levels of IFN-gamma led to a roughly 50% increased risk of an autism diagnosis.  Here is a snipet:

The profile of elevated serum IFN-γ, IL-4 and IL-5 was more common in women who gave birth to a child subsequently diagnosed with ASD. An alternative profile of increased IL-2, IL-4 and IL-6 was more common for women who gave birth to a child subsequently diagnosed with DD without autism.

This study took a lot of measurements, and goes to great lengths to explicitly call for additional analysis into the phenomena.   IFN-gamma is typically considered pro-inflammatory, while IL-4 and IL-5 are considered regulatory cytokines.  In order to determine if these findings were chance or not, the researchers determined if there was a correlation between the levels of IFN-gamma, IL-4, and IL-5, which they reported with very robust results.    Less clear is what might be causing these profiles, or how, precisely, they might give rise to an increased risk of autism.  The interconnectedness of the brain and the immune systemwould be a good place to start looking for an answer to the last question though. 

What about indirect measurements? It just so happens, another paper was published at IMFAR this year that observed the flip side of the coin, conditions associated with altered cytokine profiles in the mother and this study also found an increased risk of autism.  The Role of Maternal Diabetes and Related Conditions In Autism and Other Developmental Delays, studied a thousand children and the presence of diabetes, hypertension, and obesity in their mothers in regards to the risk of a childhood autism diagnosis.   The findings indicate that having a mother with one or more of those conditions roughly doubles the chances of autism in the offspring.  Obesity, in particular, has an intriguing animal model Enduring consequences of maternal obesity for brain inflammation and behavior of offspring, a crazy study that I blogged about when it was published.   A variety of auto immune disorders in the parents have been associated with an autism diagnosis in several studies. 

The obesity data is particularly troublesome for the idea of a ‘small’ increase in autism, just like parents have been getting older, parents have also been getting fatter, waaaay fatter, (and more likely to have diabetes)  the last few decades.  There isn’t any squirming out of these facts.  If, indeed, being obese or carrying associated metabolic profiles is associated with an increased risk of autism, ‘small’ is getting ready to absorb a big chunk of real increase.  But is there any clinical data to support this possible relationship, do we have any way to link obesity data with this autism data from the perspective of harder figures?

It further turns out, there are some very simple to navigate logical jumps between the above studies.  Remembering that our clinical measurements indicated that increased INF-gamma, IL-4, and IL-5 from the plasma of the mothers was associated with increased risk, we can see very similar patterns in Increased levels of both Th1 and Th2 cytokines in subjects with metabolic syndrome (CURES-103).  Here is part of the abstract, with my emphasis.

Metabolic syndrome (MS) is a cluster of metabolic abnormalities associated with obesity, insulin resistance (IR), dyslipidemia, and hypertension in which inflammation plays an important role. Few studies have addressed the role played by T cell-derived cytokines in MS. The aim of the tudy was to look at the T-helper (Th) 1 (interleukin [IL]-12, IL-2, and interferon-gamma [IFN-gamma]) and Th2 (IL-4, IL-5, and IL-13) cytokines in MS in the high-risk Asian Indian population.

Both Th1 and Th2 cytokines showed up-regulation in MS. IL-12 (5.40 pg/mL in MS vs. 3.24 pg/mL in non-MS; P < 0.01), IFN-gamma (6.8 pg/mL in MS vs. 4.7 pg/mL in non-MS; P < 0.05), IL-4 (0.61 pg/mL in MS vs. 0.34 pg/mL in non-MS; P < 0.001), IL-5 (4.39 pg/mL in MS vs. 2.36 pg/mL in non-MS; P < 0.001), and IL-13 (3.42 pg in MS vs. 2.72 pg/mL in non-MS; P < 0.01) were significantly increased in subjects with MS compared with those without. Both Th1 and Th2 cytokines showed a significant association with fasting plasma glucose level even after adjusting for age and gender. The Th1 and Th2 cytokines also showed a negative association with adiponectin and a positive association with the homeostasis model of assessment of IR and high-sensitivity C-reactive protein.

Check that shit out!  Seriously, check that out; increased IFN-gamma, IL-4, and IL-5 in the ‘metabolic syndrome’ group, comprised of people with, among other things, obesity, insulin resistance, and hypertension; the same increased cytokines and risk factors found to increase the risk of autism. 

If we look to studies that have measured for TNF-alpha in the amniotic fluid during pregnancy, we quickly find,  Second-trimester amniotic fluid proinflammatory cytokine levels in normal and overweight women

There were significant differences in amniotic fluid CRP and TNF-alpha levels among the studied groups: CRP, 0.018 (+/-0.010), 0.019 (+/-0.013), and 0.035 (+/-0.028) mg/dL (P=.007); and TNF-alpha, 3.98 (+/-1.63), 3.53 (+/-1.38), and 5.46 (+/-1.69) pg/mL (P=.003), for lean, overweight, and obese women, respectively. Both proinflammatory mediators increased in women with obesity compared with both overweight and normal women (P=.01 and P=.008 for CRP; P=.003 and P=.01 for TNF-alpha, respectively). There were significant correlations between maternal BMI and amniotic fluid CRP (r=0.396; P=.001), TNF-alpha (r=0.357; P=.003) and resistin (r=0.353; P=.003).

Nice. 

What we are really looking at are five studies the findings of which speak directly to one another; a link to metabolic syndrome during pregnancy and increased IFN-gamma, IL-4, and IL-5, a link to obesity and hypertension in pregnant mothers and autism risk, and an increased risk of autism in mothers wherein IFN-gamma, IL-4, and IL-5 were found to be increased outside of placenta.   Further, we have a link between amniotic fluid levels of TNF-alpha and metabolic syndrome, metabolic syndrome in mothers and autism risk, and increased risk from increased tnf-alpha in the amniotic fluid. 

As I have said previously, one thing that I have learned during this journey is that when we look at a problem in different ways and see the same thing, it speaks well towards validity of the observations.  What we see above is a tough set of data to overcome; we need several types of studies looking at the relationship between metabolic syndrome, immune profiles during pregnancy, and autism from different angles to have reached the same wrong conclusion, something that is increasingly unlikely.  We are in an epidemic of obesity and the associated endocrine mish mash of metabolic syndrome, there simply isn’t any diagnostic fuzziness on this.  It is happening all around us.  Even though the total increase in risk is relatively small, the sheer quantity of people experiencing this condition of risk mandates that the numbers game looks favorable towards a real increase in autism.  If we acknowledge this, how can we continue to have faith in the concept that any true increase in the autism rates must be ‘small’?

Is the next argument going to be that besides increased parental age, and heavier or more diabetic mothers, the rest of the autism increase is the result of diagnostic three card monte?  (Just how much is the rest, anyways?)

And even though these studies, and likely more in the future, expose the crystal delicate backbone of the ‘small true increase’ argument, I have great pessimism that the people so enamored with invoking this phrase will ever acknowledge its shifting size, much less the implications of being wrong on such a grand scale.

          pD

Hello friends –

Recently there have been a few studies that tackled the issue of apparent autism clusters in California, The spatial structure of autism in California, 1993-2001, and Geographic distribution of autism in California: A retrospective birth cohort analysis.   A nice overview and some discussion of these papers can be found at LBRB, here, and here.  One of the arguments we see made there is that the rates of autism diagnosis are, in fact, a reflection of the available services in an area, as opposed to an actual difference in the number of children with autism; essentially that an undiagnosed child with autism who lives far from a center of autism services will not get a diagnosis, but a child born relatively close to such services, will be appropriately diagnosed.  We are measuring diagnosis, as opposed to autism.  I have no doubt that there is some validity to this, but have many doubts that we can, or should, assign all of our observed increases in autism as consequences of this type of artifact. 

There have been several other studies that looked at things like mercury emissions, or airborne pollutants, or Superfund sites and autism rates at larger scales.  However, on a macro level, these types of studies have, so far, been unable to design around a feature of reality; the likelihood that things like Superfund sites or airborne pollution are situated in relative proximity to an urban center, and as such, autism diagnosis services.  In effect, the argument that these observations are diagnostic only is the same; without a controlling factor for diagnostic availability, we can not assume that other parameters are actually responsible.  And again, I have no doubt that this is a force that contributes to the findings of these studies.

But.

At the end of the day, I’m just not satisfied with a God of the Gaps explanation; what we seem to be seeing is just too goddamned important to explain away with the spongy soft and ultimately unmeasurable forces of greater awareness et all. (The Fairytale, 20##). 

Anyways, the other day pubmed alerted me to the publication of  this interesting study: 

 Body burdens of brominated flame retardants and other persistent organo-halogenated compounds and their descriptors in US girls.

BACKGROUND: Levels of brominated flame retardants are increasing in US populations, yet little data are available on body burdens of these and other persistent hormonally active agents (HAAs) in school-aged children. Exposures to such chemicals may affect a number of health outcomes related to development and reproductive function. OBJECTIVE: Determine the distribution of biomarkers of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), and organo-chlorinated pesticides (OCPs), such as DDT/DDE, in children, and their variation by key descriptor variables. METHODS: Ethnically diverse cohorts of girls 6-8y old at baseline are being followed for growth and pubertal development in a multi-site, longitudinal study. Nearly 600 serum samples from the California and Ohio sites were analyzed for lipids, 36 PCB congeners, 11 PBDE congeners, and 9 OCPs. The biomarker distributions were examined and geometric means compared for selected analytes across categories of age, race, site, body mass index (BMI), parental education, maternal age at delivery, and breast feeding in adjusted models. RESULTS: Six PBDE congeners were detected among greater than 70% of samples, with BDE-47 having the highest concentration (median 42.2, range 4.9-855ng/g lipid). Girls in California had adjusted geometric mean (GM) PBDE levels significantly higher than girls in Ohio. Furthermore, Blacks had significantly higher adjusted GMs of all six PBDE congeners than Whites, and Hispanics had intermediate values. GMs tended to be lower among more obese girls, while other variables were not strongly associated. In contrast, GMs of the six PCB congeners most frequently detected were significantly lower among Blacks and Hispanics than Whites. PCBs and the three pesticides most frequently detected were also consistently lower among girls with high BMI, who were not breast-fed, whose mothers were younger, or whose care-givers (usually parents) were less educated. Girls in California had higher GMs than in Ohio for the pesticides and most PCB congeners, but the opposite for CB-99 and -118. CONCLUSIONS: Several of these potential HAAs were detected in nearly all of these young girls, some at relatively high levels, with variation by geographic location and other demographic factors that may reflect exposure pathways. The higher PBDE levels in California likely reflect differences in fire regulation and safety codes, with potential policy implications.

The environmental impact argument usually focuses on vaccines, or in some instances, similarly widespread environmental pollutants (i.e., mercury emissions); external forces which tend to operate more or less evenly across large geographic swaths, and also largely independent of things like culture or race.  But with this paper we can observe the counter-intuitive opposite,  chemicals that have achieved widespread distribution in society and the environment, seem to be bioaccumulating differentially according to factors such as geography, race, body type, and education levels.  The paper here mentions fire regulation as a possible factor in state by state differences, but taking things a bit further, it can quickly be seen how socio-economic factors might play a role in why we might observe different levels of chemicals.  It takes a lot of crazy chemistry to make a baby onesie not catch on fire, but at a high level, it involves dousing the material with a bunch of exotic chemicals.  Politically correct or not the facts on the ground are that the well to do white woman has baby showers where she gets a bewildering array of freshly minted, ‘extra safe’ baby clothes more often than,  say, the not so well to do Latina woman.  We have already established a connection between having older parents and a diagnosis of autism, it would seem, there is also a correlation between having older parents and your bodies burden of these molecular mimics; and again, white women tend to have babies at later stages in life than their Black or Latina counterparts; especially the ones that happen to be residing near the trendy autism diagnosis hubs (i.e., the wealthier white women).    The ability for these types of chemicals to cause a variety of difficult to predict developmental trajectories is too long, and terrifying to go into detail in this post; for purposes of this discussion, it is sufficient to understand that we have a growing body of evidence that endocrine disrupting compounds can have wide ranging effects; including epigenetic changes, changes in immune profiles, altered behaviors and neuroanatomical structures known to be abnormal in autism

I found the finding of BDE-47 particularly intriguing, considering it was used as a primer for immunological response measurement by Ashwood, who found in vitro differences in immune responses in the autism population (an exaggerated innate immune response was observed).

Of course, this study does not present sufficient evidence for us to draw conclusions about the geographic distribution of autism rates in the two California studies above; but it should give us enough to pause before we take the comforting road out and assume that our observation are the result of diagnostic artifact alone; such assumptions feel good (except for the guilt), but ultimately require that we ignore our growing knowledge of how unpredictable endocrine disruptors affect the body, and how much more we have to learn.

– pD


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