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Neurology vs Psychiatry

Neurology and psychiatry are related fields - if for no other reason, because neurological disorders can often manifest as, and get misdiagnosed as, psychiatric ones.

But what's the borderline between neurology and psychiatry? What makes one disease "neurological" and another "mental"? Are some psychiatric disorders more "neurological" than others?

It's a rather philosophical question and you could discuss it for as long as you wanted. Rather than doing that I thought I'd have a look to see which disorders are, at the moment, considered to fall into each category.

To do this I did a quick search the archives of two journals, Neurology which the world's leading journal of... well, guess, and the American Journal of Psychiatry. I looked to see how many papers from the past 20 years had either a Title or an Abstract which referred to various different diseases. You can see the results above. Note that the total number of papers varied, obviously, and I've only plotted the proportion.

Some interesting results. Schizophrenia, which is probably considered "the most neurological" psychiatric disorder, is in fact the least talked about in Neurology. Depression is top amongst the "core" psychiatric ones.

Autism occupies a middle ground, discussed by psychiatrists at 70% and neurologists at 30%. That didn't surprise me, but what did was that ADHD is almost as neurological as autism. Mental retardation is also intermediate, though it's 30:70 in favour of neurology. Whether autism is really less neurological than mental retardation, is a good question.

Then out of the disorders with a known neuropathology, Alzheimer's disease, Huntington's disease and "dementia" (which overlaps with Alzheimer's) are a bit psychiatric while stuff like headache and epilepsy is almost 100% neurological. Why this is, is not entirely clear, since both dementia and epilepsy are caused by neurological damage, and they can both cause "psychiatric" symptoms.

I suspect the difference is that it's just much harder to treat Alzheimer's, Huntington's and dementia. With epilepsy or meningitis, neurologists have a very good chance of controlling the symptoms and few patients will be left with ongoing psychiatric problems. But with the neurodegenerative disorders, neurologists can't really do much, leaving a large pool of people for psychiatrists to study.

Someone once said that neurologists take all of the curable diseases and leave psychiatrists with the ones they can't help. These figures suggest that there may be some truth in this.

Shotgun Psychiatry

There's a paradox at the heart of modern psychiatry, according to an important new paper by Dr Charles E. Dean, Psychopharmacology: A house divided.

It's a long and slightly rambling article, but Dean's central point is pretty simple. The medical/biological model of psychiatry assumes that there are such things as psychiatric diseases. Something biological goes wrong, presumably in the brain, and this causes certain symptoms. Different pathologies cause different symptoms - in other words, there is specificity in the relationship between brain dysfunction and mental illness.

Psychiatric diagnosis rests on this assumption. If and only if we can use a given patient's symptoms to infer what kind of underlying illness they have (schizophrenia, bipolar disorder, depression), diagnosis makes sense. This is why we have DSM-IV which consists of a long list of disorders, and the symptoms they cause. Soon we'll have DSM-V.

The medical model has been criticized and defended at great length, but Dean doesn't do either. He simply notes that modern psychiatry has in practice mostly abandoned the medical model, and the irony is, it's done this because of medicines.

If there are distinct psychiatric disorders, there ought to be drugs that treat them specifically. So if depression is a brain disease, say, and schizophrenia is another, there ought to be drugs that only work on depression, and have no effect on schizophrenia (or even make it worse.) And vice versa.

But, increasingly, psychiatric drugs are being prescribed for multiple different disorders. Antidepressants are used in depression, but also all kinds of anxiety disorders (panic, social anxiety, general anxiety), obsessive-compulsive disorder, PTSD, and more. Antipsychotics are also used in mania and hypomania, in kids with behaviour problems, and increasingly in depression, leading some to complain that the term "antipsychotics" is misleading. And so on.

So, Dean argues, in clinical practice, psychiatrists don't respect the medical model - yet that model is their theoretical justification for using psychiatric drugs in the first place.

He looks in detail at one particularly curious case: the use of atypical antipsychotics in depression. Atypicals, like quetiapine (Seroquel) and olanzapine (Zyprexa), were originally developed to treat schizophrenia and other psychotic states. They are reasonably effective, though most of them are no more so than older "typical" antipsychotics.

Recently, atypicals have become very popular for other indications, most of all mood disorders: mania and depression. Their use in mania is perhaps not so surprising, because severe mania has much in common with psychosis. Their use in depression, however, throws up many paradoxes (above and beyond how one drug could treat both mania and its exact opposite, depression.)

Antipsychotics block dopamine D2 receptors. Psychosis is generally considered to be a disorder of "too much dopamine", so that makes sense. The dopamine hypothesis of psychosis and antipsychotic action is 50 years old, and still the best explanation going.

But depression is widely considered to involve too little dopamine, and there is lots of evidence that almost all antidepressants (indirectly) increase dopamine release. Wouldn't that mean that antidepressants could cause psychosis (they don't?). And why, Dean asks, would atypicals, that block dopamine, help treat depression?

Maybe it's because they also act on other systems? On top of being D2 antagonists, atypicals are also serotonin 5HT2A/C receptor blockers. Long-term use of antidepressants reduces 5HT2 levels, and some antidepressants are also 5HT2 antagonists, so this fits. However, it creates a paradox for the many people who believe that 5HT2 antagonism is important for the antipsychotic effect of atypicals as well - if that were true, antidepressants should be antipsychotics as well (they're not.) And so on.

There may be perfectly sensible answers. Maybe atypicals treat depression by some mechanism that we don't understand yet, a mechanism which is not inconsistent with their also treating psychosis. The point is that there are many such questions standing in need of answers, yet psychopharmacologists almost never address them. Dean concludes:

it seems increasingly obvious that clinicians are actually operating from a dimensional paradigm, and not from the classic paradigm based on specificity of disease or drug... the disjunction between those paradigms and our approach to treatment needs to be recognized and investigated... Bench scientists need to be more familiar with current clinical studies, and stop using outmoded clinical research as a basis for drawing conclusions about the relevance of neurochemical processes to drug efficacy. Bench and clinical scientists need to fully address the question of whether the molecular/cellular/anatomical findings, even if interesting and novel, have anything to do with clinical outcome.
ResearchBlogging.orgDean CE (2010). Psychopharmacology: A house divided. Progress in neuro-psychopharmacology & biological psychiatry PMID: 20828593

Are "Antipsychotics" Antipsychotics?

This is the question asked by Tilman Steinert & Martin Jandl in a letter to the journal Psychopharmacology.

They point out that in the past 20 years, the word "antipsychotic" has exploded in popularity. Less than 100 academic papers were published with that word in the title in 1990, but now it's over 600 per year.

The older term for the same drugs was "neuroleptics". This terminology, however, has slowly but surely fallen into disuse over the same time period.

To illustrate this they have a nice graph of PubMed hits. Neuroskeptic readers will be familiar with these as I have often posted my own and I recently wrote a bash script to harvest this data automatically. Now you too can be a historian of medicine from the comfort of your own home...

Why does it matter what we call them? A name is just a name, right? No, that's the problem. Actually, neuroleptic is just a name, because it doesn't mean anything. The term derives from the Greek "neuron", meaning... neuron, and "lambanō" meaning "to take hold of". However, no-one knows that unless they look it up on Wikipedia because it's just a name.

Antipsychotic, on the other hand, means something: it means they treat psychosis. But whether or not this is an accurate description of what "antipsychotics" actually do, is controversial. For one thing, these drugs are also used to treat many non-psychotic illnesses, like depression, and PTSD.

More fundamentally, it's not universally accepted that they have a direct anti-psychotic effect. All antipsychotics are powerful sedatives. There's a school of thought that says that this is in fact all they are, and rather than treating psychosis, they just sedate people until they stop being obviously psychotic.

Personally, I don't believe that, but that's not really the point: the point is that it's controversial, and calling them antipsychotics makes it hard to think about that controversy in a sensible way. To say that antipsychotics aren't actually antipsychotic is a contradiction in terms. To say they are antipsychotic is a tautology. Names shouldn't dictate the terms of a debate in that way. A name should just be a name.

The same point applies to more than just antipsychotics - I mean neuroleptics - of course. Perhaps the worst example is "antidepressants". Prozac, for example, is called an antidepressant. Implying that it treats depression.

But according to clinical trials, Prozac and other SSRIs are a lot more effective, relative to placebo, in obsessive-compulsive disorders (OCD) than they are in depression (though this is not necessarily true of all "antidepressants", yet more evidence that the word is unhelpful.)

So, as I asked in a previous post: "Are SSRIs actually antiobsessives that happen to be helpful in some cases of depression?" Personally, I think the only name for them which doesn't make any questionable assumptions, is simply 'SSRIs'.

ResearchBlogging.orgTilman Steinert and Martin Jandl (2010). Are antipsychotics antipsychotics? Psychopharmacology DOI: 10.1007/s00213-010-1927-3

Predicting Psychosis

"Prevention is better than cure", so they say. And in most branches of medicine, preventing diseases, or detecting early signs and treating them pre-emptively before the symptoms appear, is an important art.

Not in psychiatry. At least not yet. But the prospect of predicting the onset of psychotic illnesses like schizophrenia, and of "early intervention" to try to prevent them, is a hot topic at the moment.

Schizophrenia and similar illnesses usually begin with a period of months or years, generally during adolescence, during which subtle symptoms gradually appear. This is called the "prodrome" or "at risk mental state". The full-blown disorder then hits later. If we could detect the prodromal phase and successfully treat it, we could save people from developing the illness. That's the plan anyway.

But many kids have "prodromal symptoms" during adolescence and never go on to get ill, so treating everyone with mild symptoms of psychosis would mean unnecessarily treating a lot of people. There's also the question of whether we can successfully prevent progression to illness at all, and there have been only a few very small trials looking at whether treatments work for that - but that's another story.

Stephan Ruhrmann et al. claim to have found a good way of predicting who'll go on to develop psychosis in their paper Prediction of Psychosis in Adolescents and Young Adults at High Risk. This is based on the European Prediction of Psychosis Study (EPOS) which was run at a number of early detection clinics in Britain and Europe. People were referred to the clinics through various channels if someone was worried they seemed a bit, well, prodromal

Referral sources included psychiatrists, psychologists, general practitioners, outreach clinics, counseling services, and teachers; patients also initiated contact. Knowledge about early warning signs (e.g., concentration and attention disturbances, unexplained functional decline) and inclusion criteria was disseminated to mental health professionals as well as institutions and persons who might be contacted by at-risk persons seeking help.
245 people consented to take part in the study and met the inclusion criteria meaning they were at "high risk of psychosis" according to at least one of two different systems, the Ultra High Risk (UHR) or the COGDIS criteria. Both class you as being at risk if you show short lived or mild symptoms a bit like those seen in schizophrenia i.e.
COGDIS: inability to divide attention; thought interference, pressure, and blockage; and disturbances of receptive and expressive speech, disturbance of abstract thinking, unstable ideas of reference, and captivation of attention by details of the visual field...
UHR: unusual thought content/delusional ideas, suspiciousness/persecutory ideas, grandiosity, perceptual abnormalities/hallucinations, disorganized communication, and odd behavior/appearance... Brief limited intermittent psychotic symptoms (BLIPS) i.e. hallucinations, delusions, or formal thought disorders that resolved spontaneously within 1 week...
Then they followed up the 245 kids for 18 months and saw what happened to them.

What happened was that 37 of them developed full-blown psychosis: 23 suffered schizophrenia according to DSM-IV criteria, indicating severe and prolonged symptoms; 6 had mood disorders, i.e depression or bipolar disorder, with psychotic features, and the rest mostly had psychotic episodes too short to be classed as schizophrenia. 37 people is 19% of the 183 for whom full 18 month data was available; the others dropped out of the study, or went missing for some reason.

Is 19% high or low? Well, it's much higher than the rate you'd see in randomly selected people, because the risk of getting schizophrenia is less than 1% lifetime and this was only 18 months; the risk of a random person developing psychosis in any given year has been estimated at 0.035% in Britain. So the UHR and COGDIS criteria are a lot better than nothing.

On the other hand 19% is far from being "all": 4 out of 5 of the supposedly "high risk" kids in this study didn't in fact get ill, although some of them probably developed illness after the 18 month period was over.

The authors also came up with a fancy algorithm for predicting risk based on your score on various symptom rating scales, and they claim that this can predict psychosis much better, with 80% accuracy. As this graph shows, the rate of developing psychosis in those scoring highly on their Prognostic Index is really high. (In case you were wondering the Prognostic Index is [1.571 x SIPS-Positive score >16] + [0.865 x bizarre thinking score] + [0.793 x sleep disturbances score] + [1.037 x SPD score] + [0.033 x (highest GAF-M score in the past year – 34.64)] + [0.250 x (years of education – 12.52)]. Use it on your friends for hours of psychiatric fun!)

However they came up with the algorithm by putting all of their dozens of variables into a big mathematical model, crunching the numbers and picking the ones that were most highly correlated with later psychosis - so they've specifically selected the variables that best predict illness in their sample, but that doesn't mean they'll do so in any other case. This is basically the "voodoo" non-independence problem that has so troubled fMRI, although the authors, to their credit, recognize this and issue the appropriate cautions.

So overall, we can predict psychosis, sometimes, but far from perfectly. More research is needed. One of the proposed additions to the new DSM-V psychiatric classification system is "Psychosis Risk Syndrome" i.e. the prodrome; it's not currently a disorder in DSM-IV. This idea has been attacked as an invitation to push antipsychotic drugs on kids who aren't actually ill and don't need them. On the other hand though, we shouldn't forget that we're talking about terrible illnesses here: if we could successfully predict and prevent psychosis, we'd be doing a lot of good.

ResearchBlogging.orgRuhrmann, S., Schultze-Lutter, F., Salokangas, R., Heinimaa, M., Linszen, D., Dingemans, P., Birchwood, M., Patterson, P., Juckel, G., Heinz, A., Morrison, A., Lewis, S., Graf von Reventlow, H., & Klosterkotter, J. (2010). Prediction of Psychosis in Adolescents and Young Adults at High Risk: Results From the Prospective European Prediction of Psychosis Study Archives of General Psychiatry, 67 (3), 241-251 DOI: 10.1001/archgenpsychiatry.2009.206

Dope, Dope, Dopamine

When you smoke pot, you get stoned.
Simple. But it's not really, because stoned can involve many different effects, depending upon the user's mental state, the situation, the variety and strength of the marijuana, and so forth. It can be pleasurable, or unpleasant. It can lead to relaxed contentment, or anxiety and panic. And it can feature hallucinations and alterations of thinking, some of which resemble psychotic symptoms.

In Central nervous system effects of haloperidol on THC in healthy male volunteers, Liem-Moolenaar et al tested whether an antipsychotic drug would modify the psychoactive effects of Δ9-THC, the main active ingredient in marijuana. They took healthy male volunteers, who had moderate experience of smoking marijuana, and gave them inhaled THC. They were pretreated with 3 mg haloperidol, or placebo.

They found that haloperidol
reduced the "psychosis-like" aspects of the marijuana intoxication. However, it didn't reverse the effects of THC of cognitive performance, the sedative effects, or the user's feelings of "being high".

This makes sense, if you agree with the theory that the psychosis-like effects of THC are related to
dopamine. Like all antipsychotics, haloperidol blocks dopamine D2 receptors, and increased dopamine transmission has long been implicated in psychosis; some studies have found that THC causes increased dopamine release in humans (although others have not.)

Heavy marijuana use probably raises the risk of psychotic illnesses, like schizophrenia, although this is still a bit controversial, but it's accepted that some people do experience psychotic-type symptoms while stoned. So Liem-Moolenaar et al's conclusion that "psychotic-like effects induced by THC are mediated by dopaminergic systems" while the other aspects of being stoned are mediated by other brain systems, is not unreasonable, and this study is a nice example of the 'pharmacological dissection' of drug effects.

Still, like most papers of this kind, this leaves me wanting to know more about the subjective effects experienced by the volunteers. What did it feel like to get stoned on haloperidol? The paper tells us that

THC caused a significant increase of 2.5 points in positive PANSS, which was significantly reduced by 1.1 points after pre-treatment with haloperidol... Haloperidol completely reversed THC-induced increases in ‘delusions’ and ‘conceptual disorganization’ and almost halved the increase in ‘hallucinatory behaviour’. Although not statistically significant, haloperidol seemed to increase the items ‘conceptual disorganization’, ‘suspiciousness/persecution’ and ‘hostility’ compared with placebo.
The PANSS being a scale used to rate someone's "psychotic symptoms". On the other hand haloperidol had no significant effect on the users' self-rated Visual Analogue Scales (VAS) scores for things like "altered external perception" and "feeling high".

But surely the haloperidol must have changed what it felt like in some way. It must have changed how people thought, felt, perceived, heard, and so forth. These kinds of rating scales are useful for doing statistics with, but they can no more capture the full depth of human experience than a score out of 5 stars substitutes for a full Roger Ebert movie review.

This matters, because it's not clear whether haloperidol really reduced "psychosis-like experiences", or whether it just sedated people to the extent that they were less likely to talk about them. In other words, its not clear whether the scores on the rating scales changed in "specific" or a "non-specific" way. This is no criticism of Liem-Moolenaar, though, because it's a general problem in psychopharmacology. For example, a sleeping pill could reduce your score on most depression rating scales, even if it had no effect on your mood, because insomnia is a symptom of depression.

There are various ways to try to work around these issues, but ultimately I suspect that there's no substitute for personal experience, with direct observation of other people taking the drugs coming second, and rating scales a distant third. Of course, direct observation is unsystematic, and prone to bias, and few would say it was practical for psychopharmacologists to go around drugging themselves and each other... but life is more than a series of numbers.

Link: On Being Stoned (1971) by Charles Tart is a classic book which used a very detailed questionnaire to investigate what it's like to be stoned, although the methodology was hardly rigorous.

ResearchBlogging.orgLiem-Moolenaar, M., Te Beek, E., de Kam, M., Franson, K., Kahn, R., Hijman, R., Touw, D., & van Gerven, J. (2010). Central nervous system effects of haloperidol on THC in healthy male volunteers Journal of Psychopharmacology DOI: 10.1177/0269881109358200

Good News for Armchair Neuropathologists

Ever wanted to crack the mysteries of the brain? Dreamed of discovering the cause of mental illness?

Well, now, you can - or, at any rate, you can try - and you can do it from the comfort of your own home, thanks to the new Stanley Neuropathology Consortium Integrative Database.

Just register (it's free and instant) and you get access to a pool of data derived from the Stanley Neuropathology Consortium brain collection. The collection comprises 60 frozen brains - 15 each from people with schizophrenia, bipolar disorder, and clinical depression, and 15 "normals".

In a Neuropsychopharmacology paper announcing the project, administrators Sanghyeon Kim and Maree Webster point out that

Data sharing has become more important than ever in the biomedical sciences with the advance of high-throughput technology and web-based databases are one of the most efficient available resources to share datasets.
The Institute's 60 brains have long been the leading source of human brain tissue for researchers in biological psychiatry. Whenever you read about a new discovery relating to schizophrenia or bipolar disorder, chances are the Stanley brains were involved. The Institute provide slices of the brains free of charge to scientists who request them, and they've sent out over 200,000 to date.

Until now, if you wanted to find out what these scientists discovered about the brains, you'd have to look up the results in the many hundreds of scientific papers where the various results were published. If you knew where to look, and if you had a lot of time on your hands. The database collates all of the findings. That's a good idea. To ensure that they get all of the results, the Institute have another good idea:
Coded specimens are sent to researchers with the code varying from researcher to researcher to ensure that all studies are blinded. The code is released to the researcher only when the data have been collected and submitted to the Institute.
The data we're provided about the brains is quite exciting, if you like molecules, comprising 1749 markers from 12 different parts of the brain. Markers include levels of proteins, RNA, and the number and shape of various types of cells.

It's easy to use. While waiting for my coffee to brew, I compared the amount of the protein GFAP76 in the frontal cortex between the four groups. There was no significant difference. I guess GFAP76 doesn't cause mental illness - darn. So much for my Nobel Prize winning theory. But I did find that levels of GFAP76 were very strongly correlated with levels of another protein, "phosphirylated" (I think they mean "phosphorylated") PRKCA. You read it here first.

In the paper, Kim and Webster used the Database to find many differences between normal brains and diseased brains, including increased levels of dopamine in schizophrenia, and increased levels of glutamate in depression and bipolar. And decreased GAD67 proteins in the frontal cortex in bipolar and schizophrenia. And decreased reelin mRNA in the frontal cortex and cerebellum in bipolar and schizophrenia. And...

This leaves open the vital questions of what these differences mean, as I have complained before. And the problem with giving everyone in the world the results of 1749 different tests, and letting us cross-correlate them with each other and look for differences between 4 patient groups, is that you're making possible an awful lot of comparisons. With only 15 brains per group, none of the results can be considered anything more than provisional, anyway - what we really need are lots more brains.

But this database is still a welcome move. This kind of data pooling is the only sensible approach to doing modern science, and it's something people are advocating in other fields of neuroscience as well. It just makes sense to share results rather than leaving everyone to do there own thing in near-isolation from each other, now that we have the technology to do so. In fact, I'd say it's a... no-brainer.

ResearchBlogging.orgKim, S., & Webster, M. (2009). The Stanley Neuropathology Consortium Integrative Database: a Novel, Web-Based Tool for Exploring Neuropathological Markers in Psychiatric Disorders and the Biological Processes Associated with Abnormalities of Those Markers Neuropsychopharmacology, 35 (2), 473-482 DOI: 10.1038/npp.2009.151

Schizophrenia: The Mystery of the Missing Genes

It's a cliché, but it's true - "schizophrenia genes" are the Holy Grail of modern psychiatry.

Were they to be discovered, such genes would provide clues towards a better understanding of the biology of the disease, and that could lead directly to the development of better medications. It might also allow "genetic counselling" for parents concerned about their children's risk of schizophrenia.

Perhaps most importantly for psychiatrists, the definitive identification of genes for a mental illness would provide cast-iron proof that psychiatric disorders are "real diseases", and that biological psychiatry is a branch of medicine like any other. Schizophrenia, generally thought of as the most purely "biological" of all mental disorders, is the best bet.

With this in mind, let's look at three articles (1,2,3) published in Nature last month to much excited fanfare along the lines of 'Schizophrenia genes discovered!' All three were based on genome-wide association studies (GWAS). In a GWAS, you examine a huge number of genetic variants in the hope that some of them are associated with the disease or trait you're interested in. Several hundred thousand variants per study is standard at the moment. This is the genetic equivalent of trying to find the person responsible for a crime by fingerprinting everyone in town.

The Nature papers were based on three seperate large GWAS projects - the SGENE-plus, the MGS, and the ICS. In total, there were over 8,000 schizophrenia patients and 19,000 healthy controls in these studies - enormous samples by the standards of human genetics research, and large enough that if there were any common genetic variants with even a modest effect on schizophrenia risk, they would probably have found them.

What did they find? On the face of it, not much. The MGS(1) "did not produce genome-wide significant findings...power was adequate in the European-ancestry sample to detect very common risk alleles (30–60% frequency) with genotypic relative risks of approximately 1.3 ...The results indicate that there are few or no single common loci with such large effects on risk." In the SGENE-plus(2), likewise, "None of the markers gave P values smaller than our genome-wide significance threshold".

The ISC study(3) did find one significantly associated variant in the Major Histocompatability Complex (MHC) region on chromosome 6. The MHC is known to be involved in immune function. When the data from all three studies were pooled together, several variants in the same region were also found to be significantly associated with schizophrenia.

Somewhat confusingly, all three papers did this pooling, although they each did it in slightly different ways - the only area in which all three analyses found a result was the MHC region. The SGENE team's analysis, which was larger, also implicated two other, unrelated variants, which were not found in other two papers.

To summarize, three very large studies found just one "schizophrenia gene" even after pooling their data. The variant, or possibly cluster of related ones, is presumably involved in the immune system. Although the authors of the Nature papers made much of this finding, the main news here is that there is at most one common variant which raises the relative risk of schizophrenia by even just 20%. Given that the baseline risk of schizophrenia is about 1%, there is at most one common gene which raises your risk to more than 1.2%. That's it.

So, what does this mean? There are three possibilites. First, it could be that schizophrenia genes are not "common". This possibility is getting a lot of attention at the moment, thanks to a report from a few months back, Walsh et al, suggesting that some cases of schizophrenia are caused by just one rare, high-impact mutation, but a different mutation in each case. In other words, each case of schizophrenia could be genetically almost unique. GWAS studies would be unable to detect such effects.

Second, there could be lots of common variants, each with an effect on risk so tiny that it wasn't found even in these three large projects. The only way to identify them would be to do even bigger studies. The ISC team's paper claims that this is true, on the basis of this graph:

They took all of the variants which were more common in schizophrenics than in controls, even if they were only slightly more common, and totalled up the number of "slight risk" variants each person has.

The graph shows that these "slight risk" markers were more common in people with schizophrenia from two entirely seperate studies, and are also more common in people with bipolar disorder, but were not associated with five medical illnesses like diabetes. This is an interesting result, but these variants must have such a tiny effect on risk that finding them would involve spending an awful lot of time (and money) for questionable benefit.

The third and final possibility is that "schizophrenia" is just less genetic than most psychiatrists think, because the true causes of the disorder are not genetic, and/or because "schizophrenia" is an umbrella term for many different diseases with different causes. This possibility is not talked about much in respectable circles, but if genetics doesn't start giving solid results soon, it may be.

Edit: I missed it at the time but the great Prof. David Colhoun wrote an extremely good piece about this study.


ResearchBlogging.org
Purcell, S., & et Al (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder Nature DOI: 10.1038/nature08185

Shi, J., & et Al (2009). Common variants on chromosome 6p22.1 are associated with schizophrenia Nature DOI: 10.1038/nature08192

Stefansson, H., & et Al (2009). Common variants conferring risk of schizophrenia Nature DOI: 10.1038/nature08186

 
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