Tag Archives: adhd

brain-based prediction of ADHD–now with 100% fewer brains!

UPDATE 10/13: a number of commenters left interesting comments below addressing some of the issues raised in this post. I expand on some of them here.

The ADHD-200 Global Competition, announced earlier this year, was designed to encourage researchers to develop better tools for diagnosing mental health disorders on the basis of neuroimaging data:

The competition invited participants to develop diagnostic classification tools for ADHD diagnosis based on functional and structural magnetic resonance imaging (MRI) of the brain. Applying their tools, participants provided diagnostic labels for previously unlabeled datasets. The competition assessed diagnostic accuracy of each submission and invited research papers describing novel, neuroscientific ideas related to ADHD diagnosis. Twenty-one international teams, from a mix of disciplines, including statistics, mathematics, and computer science, submitted diagnostic labels, with some trying their hand at imaging analysis and psychiatric diagnosis for the first time.

Data for the contest came from several research labs around the world, who donated brain scans from participants with ADHD (both inattentive and hyperactive subtypes) as well as healthy controls. The data were made openly available through the International Neuroimaging Data-sharing Initiative, and nicely illustrate the growing movement towards openly sharing large neuroimaging datasets and promoting their use in applied settings. It is, in virtually every respect, a commendable project.

Well, the results of the contest are now in–and they’re quite interesting. The winning team, from Johns Hopkins, came up with a method that performed substantially above chance and showed particularly high specificity (i.e., it made few false diagnoses, though it missed a lot of true ADHD cases). And all but one team performed above chance, demonstrating that the imaging data has at least some (though currently not a huge amount) of utility in diagnosing ADHD and ADHD subtype. There are some other interesting results on the page worth checking out.

But here’s hands-down the most entertaining part of the results, culled from the “Interesting Observations” section:

The team from the University of Alberta did not use imaging data for their prediction model. This was not consistent with intent of the competition. Instead they used only age, sex, handedness, and IQ. However, in doing so they obtained the most points, outscoring the team from Johns Hopkins University by 5 points, as well as obtaining the highest prediction accuracy (62.52%).

…or to put it differently, if you want to predict ADHD status using the ADHD-200 data, your best bet is to not really use the ADHD-200 data! At least, not the brain part of it.

I say this with tongue embedded firmly in cheek, of course; the fact that the Alberta team didn’t use the imaging data doesn’t mean imaging data won’t ultimately be useful for diagnosing mental health disorders. It remains quite plausible that ten or twenty years from now, structural or functional MRI scans (or some successor technology) will be the primary modality used to make such diagnoses. And the way we get from here to there is precisely by releasing these kinds of datasets and promoting this type of competition. So on the whole, I think this should actually be seen as a success story for the field of human neuroimaging–especially since virtually all of the teams performed above chance using the imaging data.

That said, there’s no question this result also serves as an important and timely reminder that we’re still in the very early days of brain-based prediction. Right now anyone who claims they can predict complex real-world behaviors better using brain imaging data than using (much cheaper) behavioral data has a lot of ‘splainin to do. And there’s a good chance that they’re trying to sell you something (like, cough, neuromarketing ‘technology’).

a possible link between pesticides and ADHD

A forthcoming article in the journal Pediatrics that’s been getting a lot of press attention suggests that exposure to common pesticides may be associated with a substantially elevated risk of ADHD. More precisely, what the study found was that elevated urinary concentrations of organophosphate metabolites were associated with an increased likelihood of meeting criteria for an ADHD diagnosis. One of the nice things about this study is that the authors used archival data from the (very large) National Health and Nutrition Examination Survey (NHANES), so they were able to control for a relatively broad range of potential confounds (e.g., gender, age, SES, etc.). The primary finding is, of course, still based on observational data, so you wouldn’t necessarily want to conclude that exposure to pesticides causes ADHD. But it’s a finding that converges with previous work in animal models demonstrating that high exposure to organophosphate pesticides causes neurodevelopmental changes, so it’s by no means a crazy hypothesis.

I think it’s really pleasantly surprising to see how responsibly the popular press has covered this story (e.g., this, this, and this). Despite the obvious potential for alarmism, very few articles have led with a headline implying a causal link between pesticides and ADHD. They all say things like “associated with”, “tied to”, or “linked to”, which is exactly right. And many even explicitly mention the size of the effect in question–namely, approximately a 50% increase in risk of ADHD per 10-fold increase in concentration of pesticide metabolites. Given that most of the articles contain cautionary quotes from the study’s authors, I’m guessing the authors really emphasized the study’s limitations when dealing with the press, which is great. In any case, because the basic details of the study have already been amply described elsewhere (I thought this short CBS article was particularly good), I’ll just mention a few random thoughts here:

  • Often, epidemiological studies suffer from a gaping flaw in the sense that the more interesting causal story (and the one that prompts media attention) is far less plausible than other potential explanations (a nice example of this is the recent work on the social contagion of everything from obesity to loneliness). That doesn’t seem to be the case here. Obviously, there are plenty of other reasons you might get a correlation between pesticide metabolites and ADHD risk–for instance, ADHD is substantially heritable, so it could be that parents with a disposition to ADHD also have systematically different dietary habits (i.e., parental dispositions are a common cause of both urinary metabolites and ADHD status in children). But given the aforementioned experimental evidence, it’s not obvious that alternative explanations for the correlation are much more plausible than the causal story linking pesticide exposure to ADHD, so in that sense this is potentially a very important finding.
  • The use of a dichotomous dependent variable (i.e., children either meet criteria for ADHD or don’t; there are no shades of ADHD gray here) is a real problem in this kind of study, because it can make the resulting effects seem deceptively large. The intuitive way we think about the members of a category is to think in terms of prototypes, so that when you think about “ADHD” and “Not-ADHD” categories, you’re probably mentally representing an extremely hyperactive, inattentive child for the former, and a quiet, conscientious kid for the latter. If that’s your mental model, and someone comes along and tells you that pesticide exposure increases the risk of ADHD by 50%, you’re understandably going to freak out, because it’ll seem quite natural to interpret that as a statement that pesticides have a 50% chance of turning average kids into hyperactive ones. But that’s not the right way to think about it. In all likelihood, pesticides aren’t causing a small proportion of kids to go from perfectly average to completely hyperactive; instead, what’s probably happening is that the entire distribution is shifting over slightly. In other words, most kids who are exposed to pesticides (if we assume for the sake of argument that there really is a causal link) are becoming slightly more hyperactive and/or inattentive.
  • Put differently, what happens when you have a strict cut-off for diagnosis is that even small increases in underlying symptoms can result in a qualitative shift in category membership. If ADHD symptoms were measured on a continuous scale (which they actually probably were, before being dichotomized to make things simple and more consistent with previous work), these findings might have been reported as something like “a 10-fold increase in pesticide exposures is associated with a 2-point increase on a 30-point symptom scale,” which would have made it much clearer that, at worst, pesticides are only one of many other contributing factors to ADHD, and almost certainly not nearly as big a factor as some others. That’s not to say we shouldn’t be concerned if subsequent work supports a causal link, but just that we should retain perspective on what’s involved. No one’s suggesting that you’re going to feed your child an unwashed pear or two and end up with a prescription for Ritalin; the more accurate view would be that you might have a minority of kids who are already at risk for ADHD, and this would be just one more precipitating factor.
  • It’s also worth keeping in mind that the relatively large increase in ADHD risk is associated with a ten-fold increase in pesticide metabolites. As the authors note, that corresponds to the difference between the 25th and 75th percentiles in the sample. Although we don’t know exactly what that means in terms of real-world exposure to pesticides (because the authors didn’t have any data on grocery shopping or eating habits), it’s almost certainly a very sizable difference (I won’t get into the reasons why, except to note that the rank-order of pesticide metabolites must be relatively stable among children, or else there wouldn’t be any association with a temporally-extended phenotype like ADHD). So the point is, it’s probably not so easy to go from the 25th to the 75th percentile just by eating a few more fruits and vegetables here and there. So while it’s certainly advisable to try and eat better, and potentially to buy organic produce (if you can afford it), you shouldn’t assume that you can halve your child’s risk of ADHD simply by changing his or her diet slightly. These are, at the end of the day, small effects.
  • The authors report that fully 12% of children in this nationally representative sample met criteria for ADHD (mostly of the inattentive subtype). This, frankly, says a lot more about how silly the diagnostic criteria for ADHD are than about the state of the nation’s children. It’s frankly not plausible to suppose that 1 in 8 children really suffer from what is, in theory at least, a severe, potentially disabling disorder. I’m not trying to trivialize ADHD or argue that there’s no such thing, but simply to point out the dangers of medicalization. Once you’ve reached the point where 1 in every 8 people meet criteria for a serious disorder, the label is in danger of losing all meaning.

ResearchBlogging.orgBouchard, M., Bellinger, D., Wright, R., & Weisskopf, M. (2010). Attention-Deficit/Hyperactivity Disorder and Urinary Metabolites of Organophosphate Pesticides PEDIATRICS DOI: 10.1542/peds.2009-3058