Good Science, Bad History, in the British Journal of Psychiatry

The latest February 2012 issue of the British Journal of Psychiatry features a paper about the association between child abuse and later mental health problems. I haven't read it yet, but it looks pretty good.

However, it also includes an editorial from John Read and Richard Bentall which argues that:

Just 20 years ago, however, it would have been difficult to get the paper published. Mental health professions have been slow, even resistant, to recognise the role of childhood adversities in psychiatric disorder... Until very recently the hypothesis that abuse in childhood has a causal role in psychosis was regarded by many biologically oriented psychiatrists as heresy...

Really? I checked the BJP from exactly 20 years ago. The February 1992 issue contained:

• A paper about child sexual abuse in female psychiatric patients.
• A letter praising a different article, on the same topic.
• A review of 11 studies on psychosocial family interventions as treatments for schizophrenia.
• A paper looking at the effect of the social environment on symptoms of schizophrenia.

Four strikes and they're out. It's not true that this kind of thing wasn't being discussed 20 years ago.

Such grandstanding is bad for science. Few would deny that psychiatry in recent years has undervalued psychosocial factors and overvalued genetics and neuroscience, but it's actually quite a complicated story, not a Punch and Judy show with bad guys on one side and good guys on the other.

Rhetorical flourishes like this editorial certainly get attention but in the long run, down that road lies madness.

Read, J., and Bentall, R. (2012). Negative childhood experiences and mental health: theoretical, clinical and primary prevention implications The British Journal of Psychiatry, 200 (2), 89-91 DOI: 10.1192/bjp.bp.111.096727

Visualizing The Connected Brain

So it seems as though the "connectome" is the latest big thing in neuroscience. This is the brain's wiring diagram, in terms of the connections between neurons and on a larger scale, between brain regions.

We certainly won't understand the brain without getting to grips with the connections but equally, it's not the whole story. I previously emphasised that the brain is not made of soup; it's not made of spaghetti, either.

Connectomics does however unquestionably provide some of the prettiest images in neuroscience. And they just got prettier, with a new technique for visualizing connections, just revealed in Neuroimage: Circular representation of human cortical networks for subject and population-level connectomic visualization.

See above. It's a rather lovely vista (for which the authors Irimia et al share credit with the folks behind the Circos visualization tool they used).

All you need are some MRI scans, and a lot of image processing, and you can produce one of these "Connectograms". But what does it mean? Here's the authors' description:

The outermost ring shows the various brain regions arranged by lobe (fr — frontal; ins — insula; lim — limbic; tem — temporal; par — parietal; occ — occipital; nc — non-cortical; bs — brain stem; CeB — cerebellum) and further ordered anterior-to-posterior. The color map of each region is lobe-specific and maps to the color of each regional parcellation.

In other words, the outer ring is just a list of brain regions, each with an assigned colour. The inner rings tell us about those regions:

Proceeding inward towards the center of the circle, these measures are: total GM volume, total area of the surface associated with the GM–WM interface (at the base of the cortical ribbon), mean cortical thickness, mean curvature and connectivity per unit volume. For non-cortical regions, only average regional volume is shown.

So each of the five inner rings displays data about one aspect of brain anatomy, for each of the regions. The colors are a heat map of the numbers.

Finally, the lines between regions represent the degrees of connectivity between regions via white matter tracts, as measured with diffusion tensor imaging:

The links represent the computed degrees of connectivity between segmented brain regions. Links shaded in blue represent DTI tractography pathways in the lower third of the distribution of FA, green lines the middle third, and red lines the top third (see text for details).

You can also make a pooled connectogram of the average neuroanatomy across a group of people. Still, it remains to be seen whether these are as useful as they are beautiful.

Irimia A, Chambers MC, Torgerson CM, and Van Horn JD (2012). Circular representation of human cortical networks for subject and population-level connectomic visualization. NeuroImage PMID: 22305988

Mystery Joker Parodies Neuroscience

Someone has created a hilarious spoof paper poking fun at neuropsychoanalysis (but all of fMRI takes some hits too): A Triple Dissociation of Neural Systems Supporting ID, EGO, and SUPEREGO.

Featuring gems such as

• Authors "Steven Z. Fisher and Stephen T. Student" with contact details "mother@amaliastate.edu".
• "Twenty-four healthy participants (all 19-year-old white, male undergraduates who sat near each other in an Introductory Psychology course and were raised in upper middle class suburban New
  England neighborhoods) were scanned but 17 were excluded for not following instructions or falling asleep in the scanner."
• "If you’re like us, you’ve probably been thinking that Social Neuroscience, Neuroeconomics, and Developmental Social Cognitive Affective Clinical Neuroscience are just not cutting edge enough
  anymore. Do not despair. This study represents the first of what is likely to be a productive and active new field of Psychoanalytic Neuroscience."

It really is very funny, but it's also deadly accurate in its highlighting serious problems that plague a certain genre of neuroimaging papers. Who made it? The PDF appeared on Dropbox a couple of weeks ago and, while a few people have Tweeted about it, no-one has claimed ownership, yet.

For the record, it wasn't me.

Psychiatry's True Blood? Pt 1.

Imagine that there was a blood test that could detect depression. Wouldn't that be useful?

It depends.

Ridge Diagnostics are a US company who offer such a test. They've just published some results of the technology in Molecular Psychiatry. In two samples of patients with major depressive disorder (MDD), they report differences in the "MDDScore", between the patients and healthy controls.

The MDDScore is an aggregate value, calculated from the levels of 9 metabolites in blood serum. They're all well-known molecules, including hormones, such as cortisol and prolactin. The novelty is in how they're put together to make the MDDScore. We're given equations - but the key variables are not provided, because they're proprietary:

Long-term Neuroskeptic readers will recall that this "secret ingredients" approach to publishing science was also adopted by another company offering a different depression test.

Anyway, the performance of the test was impressive. In both the pilot and the replication samples, the MDDScore was significantly higher in the depressed people than in the controls. In both cases, the test had a sensitivity of over 91% and a specificity of over 81%, which is pretty good. Ridge Diagnostics are already offering the MDDScore clinically. For $745 a pop.

However...

Although there were two depressed patient groups (n=36 and 34), there was only one set of controls (n=43); both patient samples were compared to it. This means the second, "replication", test was not fully independent of the first one. If the first finding was a fluke caused by the control group having weird results by chance, for instance, then the second study would just repeat the fluke.

The patients were significantly older, and with a higher BMI, than the controls. They did control for these variables, which is good, but this raises the question of whether these folks differed in other ways, that they didn't measure, and hence couldn't control for.

In both samples, the patients had a very significantly higher MDDScore than the controls (p less than 0.0001, both times). But in both cases, the difference in levels of EGF (epidermal growth factor) was almost as strong: p=0.0003 and p less than 0.0001, respectively. Other metabolites weren't far behind. Testing for EGF would almost certainly be cheaper than getting an MDDScore.

Finally, all these data demonstrate is that the test can distinguish between people with MDD and entirely healthy people. But how often are doctors going to need to do that? More likely, they'll want to distinguish depression from other things that are often confused with it, such as: bipolar disorder, anxiety disorders, chronic fatigue syndrome, bereavement, "stress", and all manner of physical illnesses e.g. thyroid problems. Daniel Carlat said last year that

If the test cannot distinguish different psychiatric problems, then the MDDScore is simply a non-specific "biomarker" for emotional difficulties of all stripes, and would be essentially useless.

How disorder-specific is the MDDScore? This paper doesn't tell us. And to date, this is the only published paper mentioning the MDDScore. The website mentions some conference presentations, but none have yet appeared in a peer reviewed journal.

Ridge Diagnostics have an interesting history. But that's another story - stay tuned for Part 2.

Papakostas, G., Shelton, R., Kinrys, G., Henry, M., Bakow, B., Lipkin, S., Pi, B., Thurmond, L., and Bilello, J. (2011). Assessment of a multi-assay, serum-based biological diagnostic test for major depressive disorder: a Pilot and Replication Study Molecular Psychiatry DOI: 10.1038/mp.2011.166

Science Majors are from Mars...

According to a new study, students with a family history of autism tend to major in math and science, while substance abuse and depression are more common in the ancestors of humanities fans.

In an online survey, over 1,000 new Princeton undergrads were asked about their intended major and whether anyone in their family had been diagnosed with one of 16 neurological and psychiatric disorders. More details here.

Of the 16 maladies, 5 were so rare that there wasn't enough data to analyze. Of the remaining 11, there were significant differences between the three types of students in four. The categories being humanities, social sciences, and "technical" i.e. science, engineering and maths. Social science majors were in the middle, except for autism.

See the graph I made above.

It's an interesting study. The autism result seems tenuous though because only 24 of 1077 students reported any autism in their immediate family. That's 3% of "technical" students and 1% of others, so not very many. The authors excluded schizophrenia and epilepsy from the analysis on the grounds of being too rare - and they had 18 each. Substance abuse and depression had over 150 each, so those differences are rather more solid.

The authors note that this fits with various previous studies and they discuss their findings in Baron-Cohen-esque terms:

It has been suggested that autism represents an extreme manifestation of a ‘‘systemizing’’ nature. Since ASDs have complex inheritance, shared genetic variation between close relatives might establish a continuous phenotype which in milder forms confers interest or benefits in understanding highly structured fields... Similarly, affective disorders may represent an extreme phenotype of emotional lability that, in milder forms, is commensurate with interest in the humanities.

Hmm. OK, but does that really make sense? Sure, it fits with the popular image of the Geeky Scientist vs the Tortured Artist - but that's not science, that's stereotypes. Why would emotional lability make you favor the humanities, exactly?

Imagine if the stereotype was the Geeky Artist vs the Tortured Scientist (and there really have been plenty of both, over the years). Couldn't we rationalize that equally well? Picture the scene... -

"People with autistic traits are drawn to study the humanities because they wish to learn about humans and their emotions, something they find hard to do in day-to-day life... While emotionally volatile people like science and maths because they offer a calming sense of order and stability..."

Campbell BC, and Wang SS (2012). Familial Linkage between Neuropsychiatric Disorders and Intellectual Interests. PloS one, 7 (1) PMID: 22291951