Schizophrenia and bipolar disorder genetics blog

Perhaps it was the frustration over the slow speed of progress in the identification of complex disease genes, or maybe the fact that we live in an era where Big Science has become routine, or even the rapid improvements and cost reductions in the facilitating genetic technologies. Whatever it was, someone woke up one morning and said “How about solving seven genetic disorders at once�. The results of this seeming pipe dream reached fruition recently in the form of a titanic Nature paper and its gargantuan accompanying supplementary online data. Of relevance to this blog is the fact that bipolar disorder is among the list of diseases which also number coronary artery disease, hypertension, Crohn’s disease, rheumatoid arthritis, type 1 and type 2 diabetes.

Genome-wide association (GWA) is the name of the procedure which has been used here – not a new technique, as such, but a new scale with which to apply the familiar case-control association study approach that I have mentioned previously. Instead of the hundreds of cases and handful of markers tested in previous case-control association studies, GWA experiments use thousands of samples (for the bipolar study it was 2000 cases and 3000 controls) and over half a million markers, the idea being that it is both an objective and also statistically rigorous screen. The grand scale of this approach cuts both ways: the greater sensitivity and coverage is accompanied by the greater risk of false positives. Such large numbers mean that, by chance alone, particular markers will appear to be associated but in reality are not. To this end, the statisticians have been busy trying to figure out the thresholds which have to be achieved to separate the real from the spurious. Here, the statistics are pretty much reduced to rank ordering of the p-values associated with each marker and some comparison between disease.

The Wellcome Trust coughed up £8 million to fund this study but it is not the first to reach publication.

The Malhotra group published a schizophrenia WGA earlier this year (admittedly with a rather small sample size) which identified one candidate gene, CSF2RA (colony stimulating factor, receptor 2 alpha) on the X/Y pseudoautosomal region.

More relevant to the Nature paper is last month’s paper from the McMahon et al. group detailing the results of their bipolar disorder GWA.

In that paper 461 cases and 563 controls were tested from the US population and 772 cases and 876 controls from the German population but using a pooling protocol rather than an individual genotyping approach. Positive findings from this first stage (1887/550,000 SNP markers) had fulfilled criteria such as being reasonably common frequency, of reasonable strength of effect and located near a gene. These are somewhat arbitrary, especially the last one (regulatory mutations have been found up to 2000000 base pairs away from genes), but are a necessary start in terms of cost feasibility at the small-lab scale. The positive findings were replicated through individual genotyping of a large set of German samples and the surviving SNP markers identified.

Before we look at the results I have to register my concerns over the use of entirely family-derived samples in the US population group. Not only do I believe such samples are inappropriate for use in a protocol designed to find low penetrance general risk factors (see a previous post), but I also think that the fact that the German sample was only 13% family-derived meant that it was not an ideal comparative study group.

However, having said this, it is up to me to explain how the experiment came up with positive findings. 88/1887 US positive SNPs were replicated between the two geographic populations and a proportion of a subset of these also survived being genotyped individually too. My current thoughts are that perhaps the success of these studies derives just as much from the power of the controls (not subject to familial influences but necessarily reduced in population risk alleles) .

80 genes were identified and, of these, Diacylglycerol Kinase Eta (DGKH) and SORCS2 seem to contain the most positive SNPs each and reasonable odds ratio values (a measure of their strength of effect). The former of these genes can be connected to the lithium-sensitive phosphatidyl inositol pathway (thus providing a potential link to a commonly used treatment regime) whereas the latter is much less well characterised.

So how does this compare with the mother of all GWAs from Wellcome? Well, there is no clear evidence of large-scale overlap between the McMahon and Wellcome results although, to be fair, the papers were published so close together that no comparisons were actually formally carried out. Even though DGKH and SORCS2 are absent from the top-ranking gene list there are some very interesting points of overlap (see below). But before that, some bad news: of the seven diseases tested, bipolar disorder was, on the face of it, among the least productive. For many of the others, previously suspected genes were nicely confirmed and those fields now also have a set of novel genes to analyse – some intriguingly spanning disease boundaries. Bipolar disease failed to have any such big-hitting genes identified. All we are left with are some moderately associated genes. Before I go into the properties of those genes, we must address the possible reasons for the lack of dramatic success. Again, I am not sure of the sample selection criteria for the study in terms of familial versus sporadic cases but, perhaps more importantly, the other diseases studied all have bona fide quantifiable diagnostic criteria –we just don’t have this in psychiatry where it’s not possible to take a reading like blood pressure, lung capacity, blood sugar levels etc. So I think there’s clearly an issue of non-homogeneity of the bipolar classification. This is a very hard problem to solve: the irony is that perhaps the only biomarkers for psychiatric illness will be the genetic markers that we have yet to clarify. Despite this rather circular problem, I’m very much against the notion, proposed in some quarters, that psychiatric disorders have some special genetic qualities that render them immune to such genetic approaches.

I’ve had a look at the markers which show strong/moderate and moderate association with bipolar disorder in the Wellcome study. The paper did very little in the way of overspeculation on the function of the identified genes. Dynactin 5 was mentioned because it interacts with one of our lab’s key genes, DISC1. KCNC2 which encodes a potassium channel, GABRB1 and GRM7 both encoding neurotransmitter receptors, and SYN3, a synaptic protein were also briefly discussed. This was a very general paper and I guess there wasn’t the space to expand beyond these. For your amusement, I’ve annotated the top-most genes in a pretty haphazard way. For those in the field, it might prove useful to be able to quickly scan down this list for any of interest.

The list starts off with the chromosome number, then the SNP marker i.d. (rs number) and finally the rough description of genes in the region. If you type the SNP i.d. or gene name into the human genome browser dialogue box and click ‘submit’, you’ll be able to look at the genomic locale and link out to other information on the gene (especially OMIM for neat biographies of the genes). See how many of the associations are nowhere near known genes (or occasionally near ‘ests’ which are uncharacterised possible genes).

Strong or moderate associations

1 rs2989476 Nothing near
2 rs4027132 LIPIN1 and est
2 rs7570682 est
2 rs1375144 DPP10, dipeptidyl peptidase 10 isoform long
2 rs11888446 Nothing near
2 rs4673905* DNA polymerase-transactivated protein 6 (DNAPTP6) mRNA
2 rs2953145 ANKMY1, DUSP28, MPEPL1, CAPN10, GPR35
3 rs4276227 CMTM8, CKLF-like MARVEL transmembrane domain containing…chemokine like
3 rs9834970 Serine/threonine-protein kinase DCAMKL3 (EC 2.7.11.1) (Doublecortin- like and CAM kinase-like 3) and KIAA0342 protein (Fragment).
3 rs683395 LAMP3, lysosomal-associated membrane protein 3
6 rs6458307 TBCC (beta-tubulin cofactor C|), KIAA0240
6 rs6901299 TRDN, triadin1 calcium receptor interacting
7 rs1405318 KIAA0960 protein
8 rs2609653 Nothing near
9 rs10982256 DFNB31= CASK-interacting protein CIP98 isoform 1, =whirler mouse mutant
14 rs10134944 SLC35F4, solute carrier family 35 member F4,
14 rs11622475 TDRD9, tudor domain containing 9,
16 rs420259 PALB2, (partner and localizer of BRCA2) and DCTN5 (dynactin5)
16 rs1344484 quite a way from CHD9, chromodomain helicase DNA binding protein 9
20 rs3761218 CDC25B, cell division cycle 25B isoform 2,
X rs975687 CAPN6, calpain6

Moderate strength associations

1 rs10888879 PARS2 (prolyl-tRNA synthetase), ttc22 (tetratricopeptide repeat domain 22)
1 rs10889189 Nothing near
1 rs4916031 AK3L1 (adenylate kinase 3-like 1 isoform 7)
1 rs6691577 LRRC1 (leucine rich repeat containing 7)
1 rs1776905 Nothing near
1 rs10779279 ESRRG (estrogen-related receptor gamma isoform 2)
1 rs12070036 zinc finger protein 678
2 rs2049674 TMEM17 quite a way away
2 rs17029753 Nothing near
2 rs13386690 DPP10, dipeptidyl peptidase 10 isoform long
2 rs4407218 not in database
2 rs4673905* DNA polymerase-transactivated protein 6 (DNAPTP6) mRNA
3 rs1485171 GRM7, metab glut receptor
3 rs6762678 ZNF659, zinc finger 659
3 rs711715 Nothing near
3 rs4858594 THRB, thyroid hormone receptor beta
3 rs33460 CCK1(cholecystokinin preproprotein), lyzl4(lysozyme-like 4)
3 rs13074575 PTPRG1, protein tyrosine phosphatase receptor type G
4 rs7680321 GABRB1, gaba receptor
4 rs1996755 DKFZp586K0717
5 rs5009031 Nothing near
5 rs1428006 Nothing near
5 rs17701996 FBL3B/FBXL21( F-box and leucine-rich repeat protein 21…ubiquitin ligase), LECT2 (leukocyte cell-derived chemotaxin 2 precursor) cluster
5 rs999580 Nothing near
6 rs365237 NHLRC1 (malin ubiquitin ligase), tpmt1(thiopurine S-methyltransferase), AOF1 (amine oxidase (flavin containing) domain 1), DEK oncogene
6 rs6926599 ests
6 rs17739564 TRDN, triadin1 calcium receptor interacting
6 rs6906574 MOXD1, monooxygenase DBH-like 1 isoform 2, senescence protein
6 rs2763025 SYNE1, = synaptic nuclear envelope protein 1=nesprin 1 isoform longer,
7 rs2286492 FAM126A = down-regulated by Ctnnb1 = myelination gene involved in congenital cataract
8 rs2875734 Nothing near
8 rs16919670 Nothing near
8 rs9643449 Nothing near
8 rs10097578 ZNF706 quite a way away
8 rs1993980 TRAP25, TRAP/Mediator complex component TRAP25, thyroid hormone receptor-associated protein 6
9 rs7030123 Nothing near
9 rs1573257 PAX5, paired box 5
9 rs10993698 SYK, spleen tyrosine kinase
9 rs4978927 SVEP1, sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1
9 rs10982246 DFNB31= CASK-interacting protein CIP98 isoform 1, =whirler mouse mutant
10 rs788261 Nothing near
10 rs10826258 Nothing near
10 rs1866437 similar type of clusters as
10 rs7896131 HHEX1 AND EXOC1 quite a way away
10 rs2096285 PTPRE, protein tyrosine phosphatase receptor type E
11 rs858719 ZBTB44, BTB (POZ) domain containing 15
12 rs7136898 SOX5, SRY (sex determining region Y)-box 5 isoform b
12 rs17309820 Nothing near
13 rs4770394 Nothing near
13 rs2806922 KIAA0853=znf protin?
13 rs12584910 Nothing near
14 rs221703 DHRS2=dehydrogenase/reductase (SDR family) member 2
14 rs17108400 FLJ43028 fis
14 rs17113911 Nothing near
14 rs10146912 KLHDC1=kelch domain containing 1
14 rs3784005 FLVCR2=feline leukemia virus subgroup C cellular
14 rs10438244 FLJ25257 fis,
15 rs7163502 TBC1D21=TBC1 domain family member 21
16 rs1420239 Nothing near
16 rs4567706 Nothing near
16 rs12149894 Nothing near
16 rs7184080 Nothing near
16 rs10220973 FLJ43761 fis
17 rs203466 AKAP10. A-kinase anchor protein 10 precursor
18 rs7243929 Nothing near
18 rs1893146 Nothing near
19 rs12979795 ZNF490
19 rs7408169 not found in database
19 rs2061332 ZNF224/ZNF225
19 rs7248493 ZNF274
20 rs4815603 CENPB, CDC25B
20 rs6031991 KCNS1=potassium voltage-gated channel
21 rs2833193 Nothing near
22 rs11089599 SYN3=synapsin III isoform IIIc
22 rs16997510 CSF2RB=colony stimulating factor 2 receptor beta

There are also a few interesting points about the list which were not properly covered by the paper: a number of the SNPs pick up the same four genes which are:

DPP10, dipeptidyl peptidase 10

TRDN, triadin1 calcium receptor interacting

DFNB31= CASK-interacting protein CIP98

CDC25B, cell division cycle 25B isoform 2

Even more exciting is that one of these genes, DFNB31, together with the GRM7 gene are to found in both GWA bipolar studies. The DFNB31 gene is especially provocative because it has been implicated in deafness/blindness previously. Hard to see how that relates to bipolar disorder until you realise that a skin condition and a form of deafness can be caused by the same gene AND when you read abstracts like this.

You heard it here first (actually, SRF has a broadly similar perspective) - perhaps these genes will be the Next Big Things in bipolar disorder genetics, surely a clear justification for Big Science.

And after the previous post, here is a negative view of DSM. Both articles fascinating for the non-clinician.

Talking parrots, cursing Sumatran orang utans, accidental gene therapy on your family, biotech industrial espionage through cell line contamination, body-snatching, legally-enforced tissue sampling by bounty-hunters, illegal human-chimp hybrids etc. etc. These are some of the plot-points in ‘Next‘, Michael ‘Jurassic Park’ Crichton’s new book. Of late, Crichton has turned away from the straight techno-thriller to issue-based thrillers. His last book, ‘State of Fear‘ tackled the politics of climate change. In this book, the focus is the ethical dilemmas raised by the rapid progress made in the area of medical genetics.

Crichton needs a vent for his polemic and many of the characters in the book are merely poorly fleshed-out mouthpieces for his beliefs - a disappointment from the creator of ER, an accomplished character ensemble piece. In fact, Crichton’s fundamental anger at scientists and the ramifications of modern genetics clouds the book to such an extent that the only protagonists that the reader can begin to empathise with are of the non-human variety: the aforementioned wise-cracking African grey parrot and the faeces-tossing human-chimp hybrid! The human characters, especially the scientists, are portrayed as unscrupulous, money-grabbing, self-aggrandising monsters.

The very first page sets the scene for the pervasive criminality and moral bankruptcy among the scientists (and had particular resonance for me!):

“It wouldn’t be the first time a postdoc got tired of working on salary. Or the last.”

Now scientists are of course prone to all human frailties but Crichton tends to forget a) some might be doing their job because they believe it will do some good b) medical science has actually made tangible contributions to the modern world. He prefers to concentrate, Mary Shelley-style, on scientists as destroyers of the natural order or devious prospectors in a genetic goldrush. One gets the impression that Crichton has cut and pasted the merciless personalities of lawyers or financiers from his previous thrillers straight into this book.

His need to get his concerns across has meant that ‘Next’ is a book of two halves. In the first half, numerous bizarre vignettes and press clippings serve to dramatise the ethics of human genetic research and commercialisation. These are mixed with a multi-strand plot set-up for the latter half of the book, which follows a much more conventional, if rather weak, thriller structure. As such, Crichton tests the patience of the reader looking for the filmic flowing story that he normally produces.

However, if you can get beyond Crichton’s leaden writing style and sensational plotting, there are some interesting opinions to be found which have particular relevance to the research work carried out in psychiatric genetics. This is especially evident in a tagged-on chapter at the end in which he proposes five main changes which he believes will save medical genetics from itself (see below).

But before I discuss that, Crichton has some explaining to do…
Generally Crichton knows the science (he is a Harvard medical school graduate and directed ‘Coma’ which shares similar themes), although he does make a few howlers. These include the laughable (although perhaps suitably sensationalist) mislabelling of a transgenic chimp as a ‘transgender’ chimp and a misconception that human-chimp homology refers to genes rather than nucleotides (’humans have 500 different genes compared to chimps’)! But, more importantly, has Crichton chosen the right medium to voice his concerns? The problem I have is that the lay reader is ill-equipped to make the distinction between the outrageous actions of the portrayed scientists (the thriller) and the author’s calmly reasoned arguments set out in the book’s post-script. The former appears to be used as justification for the latter. Neither the standard procedural controls on scientific research nor the the typical motives of scientists are presented to the reader. Real research involving experimentation of any sort is regulated ad infinitum. In the UK for example, if you want to carry out an animal experiment you would, quite rightly, need a personal license, a project license and a site license…then you would have to convince a funding body that your research was ethically justifiable….all before you started…and then your procedures are monitored throughout: including vet inspections. In terms of real-world motives, scientists in UK academia are within a nation-wide pay-scale, with any consultancy work negotiated through (and capped by) the University. Aside from setting up spin-off companies, there are no opportunities for amassing vast personal wealth through fair means or foul. Scientists really want publications and money for research and that is the basis for much commercialisation of their findings…as leverage for funding from industry. In ‘Next’ we have scientists accidently taking viral gene therapy materials home in the car and infecting family members….impossible. We have scientist carrying out an apparently unfunded and unauthorised human-chimp hybridisation experiment as some sort of sabbatical afterthought…..in the full knowledge that it would be utterly unpublishable: in the Real World there would be no point, quite aside from the illegality of the procedure. So Crichton’s fiction and fact approach is a little dishonest if entertaining.

Apart from the attempt by a character to forcibly genetically test his wife for Bipolar Disorder as part of a custody battle, it’s not until the sober manifesto at the end of the book that there is much to debate for those working in psychiatric genetics. Readers should be aware that Crichton is writing with respect to US law and practice but there are many crossovers into more universal problems. His five points are:

1. Genes should not be patented
2. Tighter regulation on the use of human tissues
3. Full disclosure of gene therapy/drug testing data to the public
4. Remove all bans on particular aspects of genetic research (e.g. stem cells)
5. Rescind the Bayh-Dole act (reducing the ties between academia and industry….a US issue)

The first two points are particularly interesting. Crichton has issue with speculative gene patenting….as epitomised by Myriad Genetics’ actions. He presents some compelling examples where patents have hindered the pace of research relating to important public health issues. However, Crichton sees gene patenting as some sort of ‘people ownership’: the removal of some innate freedom of the individual. Not mentioned is the astronomical cost of new drug development and testing - a burden that only industry can realistically carry. It is simple economics that they want to protect that huge investment, and gene patenting is the first step to safeguarding intellectual property along the length of the pipeline leading to the new therapy. In this light, patenting can be thought of as advantageous to the individual - it’s the only viable model for the production of new medicines. Moreover, gone are the days of vague gene patents…now experimental evidence and a precisely defined scope is required to persuade patent assessors that a gene patent merits granting.

Tissue/patient samples are cause for concern because Crichton believes that the ‘ownership’ of the samples is not clearly defined in law: does the patient retain rights, the clinician or the academic body? Should the patients’ permission be sought if samples are to used for different research purposes. Crichton touches on the implications for family members should an individual be found to be genetically compromised. This point is going to be very important for psychiatric genetics in the next decade as a multitude of discovered genetic risk factors are identified and converted into diagnostic reagents. Who within and without the family circle should be privy to such information?

Given the public exposure of this book, scientists should be prepared not only to answer questions arising from it but also engage in the ongoing debate over changes in regulations and laws.

A gene for…

Barely a week goes by without a press release describing the identification of ‘a gene for X disorder’. But what does that mean exactly? Naturally, it doesn’t mean that the purpose of that gene is to cause the disorder - rather, damage to that gene (a mutation) directly causes, or increases the risk of, disorder X. The normal function of that gene, probably making a protein which has a role in some process in the cell, has been changed in a harmful way. Maybe the ‘encoded ‘ protein is not made, or its activity is changed.

Cases and controls

Schizophrenia and bipolar disorder are complex genetic disorders which means that each individual gene mutation is likely only to contribute to a small fraction of illness in the population (even if it can be a major contributory factor for particular affected individuals). That is why ‘case-control association studies’ are employed by researchers wishing to assess how important their particular gene of interest is in the general scheme of things. Basically, they use natural gene variants (sequence differences) that exist in the population and ask whether they are more common in individuals with the disorder (cases) compared to the well population (controls). If the variant is more common then either it, (or more likely) a mutation nearby in the gene, is responsible for predisposing some people towards developing the illness (the variant, and the gene in general, is said to be ‘associated’ with the illness).

Strange associations

Even though the title of this post is a little misleading, there have been some unexpected and provocative findings from association studies that have been treated with great suspicion (generally by those who review the data presented in scientific papers). In brief, some genes seem to contribute to illness in one ‘sex‘ only and other genes seem to offer ‘protection‘ against illness rather than contributing to it. Because the strength of these studies critically depends on the number or cases and controls used (the more, the better the study) and the mathematical analyses used, it is easy for those suspicious people mentioned above to dismiss these observations as mere ‘lies, damned lies and statistics’ - researchers trying to wring something of interest from their favourite gene.
If you don’t look, you won’t find…
Perhaps these findings are only a surprise because the older, and more widely used, method of gene hunting - ‘linkage analysis’ - is not well-equipped to find such associations. Firstly, to find a protective effect for a gene would require a linkage-using researcher to look for ‘well’ families - the opposite of normal - and ask why they were normal. Not a particularly precise approach - and one not likely to find financial support for investigation. [Having said that....] Linkage studies can also examine if an illness is passed down a maternal or paternal line (indicating processes such as imprinting, mitochondrial disease or sex-linkage…topics that I can’t do justice to here) but which gender is affected is not often monitored.

So the advent of widespread asociation studies has revealed these two peculiarities, but is there any biology to explain them? Let’s look at protective effects first.

Newtonian genetics

One explanation of the observation of protection is a simple mathematical counterpart of ‘an action causing an equal and opposite reaction’. Below, I’ve pasted in a real-world example of some data from a gene, NPAS3, we are working on (the data is being presented initially at the World Congress of Psychiatric Genetics in Sardinia this weekend).

One part of the gene has 6 principal variants (‘haplotypes’: 111, 121….etc.). The four columns for each variant represent how common each one is in healthy control individuals (CONT), individuals with schizophrenia (SCZ), individuals with bipolar disorder (BPD) and a combined group made up of both conditions (COMB). What you can see is that there is a big shift for the ‘212’, and to a lesser extent, ‘211’, variants. 212 appears to represent a ‘susceptibility’ variant (more common in cases) whereas 211 seems to be a ‘protective’ variant (lower in cases). But is it really? A more plausible explanation is that the 211 decrease is just a passive response to the 212 increase – something has to ‘give’ to compensate for more people being in the 212 group. If indeed this is the case, then the other variants would also show a similar (if proportional) drop. 122 fits this model nicely but the others are not so clear - so you can see how this is not always the easiest trend to spot. Incidentally, the SCZ and COMB groups for 212 show the most statistically significant p-values for this data set (an indication, perhaps, that they are the driving force in this shifting picture).

Real protection

A clearer picture of protection comes from the study of the genes GRIK4 and DISC1…… In the former case (link to review in the Schizophrenia Research Forum) there is a schizophrenia susceptibility region in the centre of the gene and a clear bipolar disorder protective variant (haplotype) at the end of the gene which is present in around 16% of individuals with bipolar disorder and about 23% of control individuals.

We are all schizophrenic…….

Let me propose a strange and unlikely situation where the forces driving the evolution of the human brain have led to schizophrenia (or bipolar disorder) becoming more prevalent….possibly even the default state. In a contemporaneous evolutionary arms race, gene variants would have appeared and been selected for their protective effect against schizophrenia. In this way a large set of protective variants might exist at relatively high frequencies in the population such that 99% of people would not develop the disorder.

This is an exaggeration to make the point that it would be theoretically possible to construct a genetic model of schizophrenia using only protective factors. However, despite its wackiness, there are a couple of concepts in complex genetic disorder-speak that seem to cry out for an acknowledged role for protective variants. First, there is ‘reduced penetrance’, which refers to the phenomenon where mutation carriers don’t always develop the full-blown disease. Something is compensating for the mutation. This ‘something’ is often described as ‘genetic background’ - a rather nebulous term meaning ‘a whole load of genetic (and maybe environmental) influences we cannot hope to quantify or understand’. Surely, it would be better to bite the bullet and admit that some of the protective variants we are observing could be active components of this background? Second, and closely related, is the concept of disease ‘threshold’ – susceptibility and, by implication, protective factors, are competing in a genetic tug-of-war. The net result is that the host human ends up on one side or other of the disease threshold.

The next phase of industrial scale genetic research into psychiatric disorders will involve the use of ‘whole genome associations’ – testing each gene simultaneously for its role in illness. I predict that people are going to be surprised at just how many gene variants are protective. I also predict that these variants might give us more of an idea of the biological strategies that could be adopted in the rational design of new therapies – essentially, we would be following Mother Nature’s lead.

Gender issues

If you find the idea of protective factors is rather outlandish, then the existence of gender-specific associations is going to be even harder to accept. The fact is that some gene variants only seem to alter the risk of illness when you look at just one sex in isolation. DISC1’s effect on both bipolar disorder and schizophrenia (Thomson et al 2005) and GPR50 on bipolar disorder (Thomson et al 2005) are both clear examples of this phenomenon. I think that some of the prejudice against the existence of sex-specific associations comes from the misapprehension that this doesn’t fit with the commonly quoted fact that schizophrenia and bipolar disorder affect both sexes equally. I would argue that, just as there are multiple susceptibility and protective variants, there are likely to be multiple male-specific and female-specific variants – the biases must average themselves out in the end. Having said that, my concern at present is that most sex-specific associations seem to be female in type.

What about biological mechanisms? There is an established and growing set of non-psychiatric genes that also possess sex-dependent risk variants (Weiss et al 2006). For example, a gain-of-function mutation with a sex-specific (and protective) effect against Parkinson Disease (Glatt et al 2006) and a sex-dependent risk polymorphism for non-familial Hirschsprung disease (Emison et al 2005) have both been recently described and go some way towards a functional explanation for such phenomena. Schizophrenia usually has its onset post-pubertally in teenage and early adult life in both sexes. As both these sex-specific examples result from regulatory polymorphisms, hormonal influences on transcriptional control can be postulated as an underlying mechanism – as documented for the cAMP response element binding (CREB) protein (Auger 2003, Abraham et al 2005, Zubenko et al 2003). In other words, a gene variant would exist in both sexes as per normal genetic rules, but it only has a biological consequence in one sex because of an altered interaction with some sex-hormone-linked process. Hence, a plausible strategy for future research would be a search for neuroendocrine-modulated intronic regulatory element polymorphisms in the DNA of carriers of sex-specific variants.

In summary, we have had a glimpse of some intriguing variations to the normal risk gene action for psychiatric illness. It will be interesting to see how these phenomena develop over the next few years.

The last few months have been a good time for readers of reviews in the field of schizophrenia and bipolar disorder genetics. What makes the recent batch more impressive is that they are not merely collating primary research but using that data to construct theories and models that seek to provide an overview of the biological systems failing in these conditions. It is that ‘added value’ that makes these papers ‘even better than the real thing’, where the ‘real thing’ is the incremental output of most primary papers. Below I’ve listed three of the best and provided a summary for those who can’t access the primary papers.

A pathological paradigm for the therapy of psychiatric disease
Spedding, Jay, Costa e Silva and Perret.

Not a light read but an important review nevertheless. This paper deals with the past, present and future of drug therapies for psychiatric illness, perhaps with a bias towards depression and affective disorders, but with valuable lessons for schizophrenia and bipolar disorder too. What separates this from just a summary of drug trials and clinical outcomes is that the authors have a set of criteria they believe will lead to better therapies. These are: an understanding of the precise brain regions affected in each disorder and the targeting of specific drugs to them and, once there, these drugs should re-establish normal physiological ‘set points’. According to the authors, these set points can be thought of as changeable states of ‘plasticity’ - the levels of connectedness/communication between nerve cells.
Like the next review, the authors have focussed on a few key neural circuits in which plasticity properties have been well described. They integrate this knowledge with our current understanding of several polymorphisms in neurotransmitter systems as well as highlighting the influence of stress on these pathways.
The authors have, therefore, managed to bridge the gaps between several disparate fields of research in an attempt to synthesize a holistic model for rational therapy design. While not fully explaining how measurable readouts for therapy-mediated changes in plasticity might be obtained, the review does a good job in exposing the reader to the various levels of physiology affected by these conditions.

Intermediate phenotypes and genetic mechanisms of psychiatric disorders
Meyer-Lindenberg and Weinberger

What is an ‘intermediate phenotype’? To quote the authors:

“As genes do not encode for psychopathology, it is reasonable to expect that the association or penetrance of gene effects will be greater at the level of relatively more simple and biologically based phenotypes.�

Put simply, a car is not made for breaking down (except a white Ford Fiesta ‘Popular Plus’ 1986 vintage which I spent ££££ on but sold for enough money to buy a tub of ice cream)…. it’s made for travelling. Therefore, it is not always immediately obvious from the outside what is going on when it stops working. However, if you have a rudimentary understanding of the normal performance of basic engine systems then you might be able to figure out what’s wrong and pin it down to individual components.
The authors argue the schizophrenia is too complex and varied to be examined in any way other than by breaking it down into smaller functional units – these are the ‘intermediate phenotypes’ that are also described as ‘endophenotypes’ by others. They list a number of these such as electrophysiology, neurochemistry and neuropsychology but really focus the review on what functional imaging studies have told us. Two brain circuits are described:

1) Cortex/thalamus > neostriatum > globus pallidus > substantia nigra > prefrontal cortex.

2) Dorso-lateral prefrontal cortex <> hippocampal formation

which are observable in action during these functional brain imaging studies. These circuits can be tied in with particular neuropsychological correlates (episodic memory, working memory, emotional regulation, reward) which in turn can be placed in the context of the features of schizophrenia (the first two) or depression (the last two). The authors explain how traditionally gene polymorphisms can be tested for their effect on these phenotypic systems allowing a prediction to be made whether they might have relevance to the disease state. With respect to their main hypothesis, the authors also show how gene polymorphisms can examined in an analogous way using their effect on the function of the two neural circuits as the intermediate phenotypic readout.

This is cutting edge technical stuff and the correlation between particular gene polymorphisms (e.g. in the DISC1 and COMT genes) and precise functional changes in particular brain regions has been nothing less than spectacular. Actually, this success is why I have certain conceptual issues with this approach. The kind of sample numbers (cases studied) involved are relatively low compared to the numbers employed in straight genetic studies trying to match up particular genetic changes with the disease state and yet the former are yielding statistically robust findings while the latter are most definitely not. This could be telling us one of three things:

1) Like the deleterious effects that many, many gene knockout experiments have on mouse learning and memory tests/electrophysiology, the biology of these circuits might be very susceptible to genetic changes.
2) The distance between gene polymorphism and intermediate phenotype is a lot less than between intermediate phenotype (or gene polymorphism) and disease. i.e. other genes/intermediate phenotypes are required in parallel before the sub-clinical becomes clinical.
3) Testing a pre-selected genotype for defined functional neural changes is a much purer experiment than asking whether your particular population of schizophrenia cases is enriched for that genotype (i.e. it avoids locus and allelic heterogeneity issues).

So there are several questions to be answered (as the authors acknowledge) such as the heritability of these functional brain activities, their extent of variation in the disease state, the contribution of other, less tractable neural circuits to disease and, most importantly, the effect of the emerging better-characterised pathogenic polymorphisms/haplotypes. Overall, however, this is a thought-provoking review which bodes well for a deeper understanding of the building blocks of mental illness – a subject discussed in a previous post.

Neurobiology of Schizophrenia
Ross, Margolis, Reading, Pletnikov and Coyle

Out of the three, this is perhaps the best review for the novice to dive into. It is an impressively comprehensive ‘State of the Nation’ piece for psychiatric disorders - as befits its publication in the prestigious journal Neuron: normally a place where schizophrenia and bipolar disorder don’t get a look in. Like its cousin, Cell, Neuron is a journal that, in my opinion, sometimes suffers from its preference for rather turgid, hard-core cell biology/electrophysiology. Does this mean that this field of psychiatric genetics is gathering a veneer of respectability?
The paper begins with a suggestion that we should look to the established genetics of neurodegenerative diseases such as Parkinson’s and Alzheimer’s to get a model for the genetic architecture of schizophrenia and bipolar disorder: rare mutations can tell us a lot about the biology of the disorders even if they don’t affect the majority of sufferers. They also suggest disorders of the brain such as Lissencephaly can be a model for the Neurodevelopmental Hypothesis of psychiatric illnesses.
This review also goes into the basics of endophenotypes, as described above, and also mentions the work into neuropsychology, neuroimaging, neuropathology, pathophysiology and recent progress in pharmacology. After introducing the readers to these fields, the review then shifts gear into a summary of genetic progress. This covers animal models and the key methodologies employed in the field for the identification of candidate genes: linkage, association and cytogenetics. 19 candidate genes are listed in their ‘Billboard’ chart. In fact, I’m embarrassed to say I didn’t even recognise a couple of the acts on this chart so there’s some homework for me….but, equally, I couldn’t see a few expected names either. I think the Schizophrenia Research Forum has a current list of ‘top’ candidate genes…..I wonder if it would be profitable for this blog to do so as well? Neuregulin, Dysbindin, D Amino Acid Oxidase Activator, COMT and DISC1 are described in more detail, particularly the advanced state of cell biological investigation into the last of these.

Overall, this is the current gold-standard review of the field – required reading for all. Just as important is the feeling that the reader gets when going through it: this is a field that is maturing nicely and with a lot to be positive about.

You may have seen the various press snippets (link 1, 2, 3, 4) surrounding the advanced online publication of a paper in the journal Nature this week (also comment in John Hawks’ Blog). This work is part of a field where bioinformaticians (those who study the large sets of data generated by projects such as the Human Genome Project and the HapMap Project) study the evolutionary footprints that are to be found in the DNA sequence of our chromosomes.

Since the Human Genome Project was completed five years ago, it has been joined by genome projects from a wide variety of inhabitants of the evolutionary tree so that it is possible to dissect the genetic differences between them. In the most part, this has been used to identify similarities between species. These ‘conserved’ regions have arisen because they have been subject to strong selective pressure not to accrue random mutations. Conserved regions usually indicate the presence of genes (which have to be kept intact in order to make functional protein) or regulatory regions (which control the use of particular genes). You can think of these conserved regions as being responsible for the core properties of a protein, and on a larger scale, responsible for the general features of an organism - head, limbs, organs, metabolism, muscle etc. It also stands to reason that mutations in these conserved regions are likely to have the most serious consequences……that of causing genetic disorders.

However, some researchers have looked at the flipside of this coin - hunting out the regions of the genome which show the greatest differences between species. These, it is hypothesized, represent the sites where natural selection and speciation events have occurred - they are responsible for what makes us different from our evolutionary ancestors.

This Nature paper details the application of this latter approach: the assumption that genes showing fast evolution between the homininae lineage (human, chimpanzee, gorilla and orang-utan) and hominina lineage (humans and their ancestors since the split with chimpanzees circa 6 million years ago) are responsible for our defining and distinguishing evolutionary features, in particular, increased brain size/cognitive power.

So, in brief, the reasoning goes like this: fast-evolved human genes > used in brain > they made us what we are today.

It’s not the first time that such an approach has been tried. Indeed, genes such as ASPM and Microcephalin have shown fast evolution and appear to play a role in brain development (lots of nice reviews here: link 1, link 2, link 3, link 4). There are even genes which are entirely specific to humans - for example the SIGLEC11 gene is expressed in brain microglial cells.

The first author of the paper, Katherine Pollard, carried out a systematic screen of the human genome, comparing it with chimp, in order to identify what she calls ‘Human Accelerated Regions’ (HARs) - the fast-evolved regions. The most significant finding was called HAR1 and shows 66 times more sequence changes than would be expected of an average stretch of DNA. The HAR1 region seems to be correlated with two overlapping genes, HAR1F and HAR1R. The genes themselves are odd in that they don’t make proteins - their function must be carried out in their mRNA form. Most RNA genes are regulatory in that they control the actions of other genes, but no such role has yet been shown for HAR1F/R. Again, the authors show that this humanised gene acts in the brain, and more specifically, the developing foetal brain. It is found in the precursor cells that will go on to produce the cerebral cortex - the higher functioning, business end of the brain.

How does schizophrenia fit into this story? A related hypothesis follows directly on from the ‘fast-evolved human gene’ argument. This states that schizophrenia is a uniquely human disease caused by dysfunction of uniquely human cognitive faculties and is, therefore, likely to have genetic causation in those brain genes that have driven human speciation. In other words, genes like the HARs are possible candidates for schizophrenia genes. Here are three papers that originally stated this idea.

Brune, M. (2004) Schizophrenia-an evolutionary enigma? Neurosci Biobehav Rev 28 (1), 41-53

Randall, P.L. (1998) Schizophrenia as a consequence of brain evolution. Schizophr Res 30 (2), 143-148

Crow, T.J. (1995) A theory of the evolutionary origins of psychosis. Eur Neuropsychopharmacol 5 Suppl, 59-63

It has to be said that this idea has been in the wilderness for a while, overtaken by more pharmacological thoughts on the genes involved in schizophrenia. Does it deserve another shot at glory? It’s hard to say just yet, but there are a few intriguing clues:-

1. HAR1F/R is found in the same cortex precursor cells as Reelin, itself a reasonably well-established schizophrenia candidate gene.
2. Another brain capacity gene, like ASPM and Microcephalin, is Nde1 (’Nude 1‘) which is a direct interactor with the DISC1 schizophrenia candidate gene.
3. A previous paper on fast-evolving brain genes identified GRIK4 (a glutamate responsive neurotransmitter receptor in the brain). We have just described its involvement in the genetics of schizophrenia and bipolar disorder.
4. Similarly, the NPAS3 gene was identified as ‘HAR21′ (also incorrectly labeled HAR30 in table S8) by Pollard et al. We have shown that this gene is involved in schizophrenia too - and described a region of the gene/protein that is human-specific (although this is not the same region flagged up in HAR21).

Circumstantial at best maybe, but certainly the basis for future study.

What an chillingly emotive idea, though. The genetic forces that boosted our cognitive faculties in Africa’s Rift Valley may contribute to the debilitating characteristics of psychiatric illness.

I wonder if this relatively unsung story could be the biggest advance in the genetics of psychiatric illness so far this year. It’s been a slow story building - I can remember hearing a talk given by Nicholas Barden, the French-Canadian head of the group behind this finding, at a conference in Dublin almost two years ago where he was on the verge of announcing the identity of the gene subject to its patent protection. Sometimes, the perceived importance of a gene can make the road to publication more rocky than usual. Certainly, it’s baffling to hear the hoops that some papers have to jump through to reach dusty library shelves. No doubt the jostling for position in this young field plays a part.

The story starts with the study of mental illness in isolated populations in the North-East of Canada. This is a genetic trick that has been employed widely in the study of modern complex human genetics. The ‘trick’ is that these populations usually start off with a few pioneers and if one carried a gene mutation then it will go on to be relatively common in the present population and will contribute to a larger proportion of the genetic risk. This approach has been used very effectively in Finland and Iceland.

Barden’s group identified a region on chromosome 12 which contained a gene mutation which increased the risk of bipolar disorder. The laborious task of refining the location of the gene led to the pinpointing of P2RX7 (a.k.a. P2X7) as the most likely source of the risk. Indeed, a change in DNA sequence (with the reference number rs2230912)which leads to a change in the amino acid sequence (a glutamine to an arginine residue) of the P2RX7 protein was found.

This is what sets this finding apart: many candidate genes have been found that seem to increase risk of mental illness but the underlying mutations have not yet been found (e.g. NRG1). Add to that a number of gene mutations which seem to remain as genetic candidates more through tearful sentimentality and half-hearted dabbling rather than thorough replication (COMT), then it can be seen what it means to have both gene and mutation under your belt.

The statistical power of the studies is another favourable sign. Their first paper, from earlier this year, looking at families with bipolar disorder in the French-Canadian population found that the mutation was significantly associated with the disease. This has very recently been backed up by a study with German colleagues which has found a similarly pronounced effect of the mutation on disease risk through the study of 1000 individuals with unipolar depression.

So much for the genetic story, but what exactly does the P2RX7 protein do, and what relevance does it have for the biology (or treatment) of bipolar disorder and unipolar depression? Here the story becomes a little less clear. Adenosine TriPhosphate (ATP) is the cell’s universal energy currency, converted from sugar energy by mitochondria. Many enzymatic processes (e.g. muscle contraction) in the cell rely on ATP power. However, recently it has been appreciated that ATP can also act as a signalling molecule outside of the cell. A number of classes of genes encode proteins which act as ATP receptors (detectors) on the cell surface. The P2RX class of receptors is one of these and consists of seven members, including P2RX7, which let ions pass across the cell membrane when they sense the presence of ATP. Online Mendelian Inheritance in Man (OMIM, a good resource for summaries on gene function) has already got a substantial entry for P2RX7, one that focuses more on its role in leukaemia, inflammation and diabetes. This is mirrored in a more up-to-date and comprehensive review which discusses P2RX7’s role in arthritis and other inflammatory disorders. As is so often the case for a given gene, the field that discovers it describes it only in its own terms. Thus mice with the gene ‘knocked out’ have been studied in terms of their resistance to arthritis and bone growth deficits. However, there is an emerging literature (1, 2, 3, 4) which suggests a role for this receptor in the brain and, potentially, with glutamate release in the hippocampus.

A final point of interest is that the harmful effect of this mutation is only felt when in the heterozygous state (one good copy of the gene and one bad) which results in the production of 50% normal and 50% abnormal protein. The fact that P2RX7 protein acts in a homomeric complex (it binds to other P2RX7 proteins to form the active receptor), and the changed amino acid resides in the part of the protein responsible for this self-association suggests that the normal-normal and abnormal-abnormal associations are non-harmful but the abnormal-normal combination is.

A Quantitative Trait (QT) is a phenotype/feature/measurement of an organism that can fall anywhere on a continuous range. So height, intelligence, metabolic rate, longevity etc. all sit within this class of traits. On the other hand, there are traits such as eye colour, blood group, tongue rolling etc. which are qualitative and discrete in nature. As common sense might dictate, the distinction between these two sets of traits is mirrored in the complexity of the genetics behind them. Many genes are predicted to simultaneously contribute to quantitative traits and these genes are termed QT Loci (QTLs: loci referring to the locations of these genes on the chromosomes). A handful of genes at most are thought necessary to control a qualitative trait.
A very recent paper from Jonathan Flint’s laboratory (Oxford, UK) describes a large mouse genetics study that aimed to uncover the genetic contributions to a number of measurable traits (including behavioural, metabolic, weight, biochemical, blood properties etc.).

The considerable advance described in this paper was the scale of the project coupled with the use of what they call heterogeneous stock mice. Basically these are derived from the interbreeding of a different original mouse strains (each with their own particular trait characteristics) so that, after many generations, mice are produced with an apparently random mix of these traits caused by the shuffling and mixing of the original genetic material on their chromosomes. By using markers which can tell which parts of which chromosomes came from which original mouse strain it was possible, with necessarily powerful and complicated statisitical methods (I don’t understand them so won’t attempt to summarise them!), to work out the approximate location and contribution of many QTLs for a given trait. The exact identity of the QTLs will doubtless follow in subsequent publications.
The upshot of this gargantuan effort is that, for the average trait, many QTLs are responsible, but each one is unlikely to contribute to much more than 5% of the trait and that only 75% of the genetic effect on the trait could be pinned down to detectable QTLs (i.e. many other undetectable QTLs exist, each contributing very small amounts to the final trait measurement).

What are the implications of this work? The authors have achieved the first steps in making the identification of QTLs a realistic possibility. However, the link to human disease is a little harder to make.

Of course, I have a vested interest in hoping that the QTL story is not relevant to the identification of genes involved in mental illness because it would make it a much harder task. And in that respect, there are also a few conceptual issues I have with equating QTLs with diasease genes.

Firstly, these mice are all well. A few years back I heard a suggestion that the genes for intelligence could be cloned by identifying the genes responsible for mental retardation (UK: learning disability). Yes, both intelligence and mental retardation can be defined in terms of IQ but the comparison prety much ends there. An analogy illustrates the problem: if the speed of a car represents IQ then it is possible to list the modifications/properties (QTLs) which might alter the performance - engine capacity, tyre type, turbo-charging, air intakes, computer tuning etc. etc. However, contrast this with the things that can go wrong - fan belt broken, accelerator pedal snapped, puncture, oil leak etc. etc. - and bear in mind that these factors play only minor roles in determining the car’s ‘performance’ per se. Despite this being only an analogy, we should not be surprised if natural variations in the ’state of wellness’ have little bearing on common illness.
Secondly, the genes responsible for mental illness (or any other complex genetic disorder, for that matter) exist as a consequence of spontaneous mutations in genes which have then been distributed and selected among populations which have then been scattered by numerous ancient migrations. All these factors have determined the current set of mental illness gene variants present at reasonable frequencies in our human populations. This is also true for the specific QTLs present in the parental strains of mice used in these experiments. Whether there is likely to be susbtantial overlap in contributory genes for any trait/disease between mouse and man should be a subject for debate rather than an assumption.

In summary, is mental illnes (in an individual rather than a population) caused by small-effect changes in many genes acting in concert or by the actions of one or few genes with stronger effects? I believe the current state of play, as evidenced by the emerging genes, suggests the latter is more likely. Indeed, the current techniques such as linkage and case-control association studies employed in the search for these genes have a definite lower limit in their sensitivity which means that we have to hope that this is the case. I guess the fact that those are the kinds of genes we are seeing published recently may just be a result of the use of these techniques - ascertainment bias as it is known - but there is nothing to suggests that we are looking solely at a QTL effect.
Next post I will discuss another recent paper which describes further work linking a variant of a gene and its link with bipolar disorder and major depression: a potentially important major candidate for these disorders.

The late 80s saw a shift in mouse genetics away from the study of naturally occurring (spontaneous and random) mutations towards the targeted mutation of genes of interest. This was the result of the development of homologous recombination and embryonic stem cell technologies. The resulting ‘knockout’ mice lack the gene you are interested in so that is possible to see what effect that has on body development, size, behaviour, metabolism, memory, etc. (this is known as the ‘phenotype‘) or model a human disease.

With DISC1 being such an intriguing candidate gene for psychiatric illness, a knockout was an obvious next step to examine the function of the gene on mouse brain development and resulting behaviour. However, until recently (and not yet published) none existed despite the reported best efforts of several labs. According to accepted wisdom, some genes are just difficult to knock out.
Now, two recent papers by Koike and colleagues and Clapcote and Roder describe a serendipitous and ironic finding - that a mouse strain that is normally used in the production of knockout mice actually already possesses a naturally existing mutation in the Disc1 gene. This has most likely been around since 1948 when the 129 strain was first bred.
Apart from being a salutory reminder that pre-knockout era mouse genetics still has a role to play today, what does this finding mean for DISC1 genetics specifically?

1. Which is worse: no gene or a half a gene? Since the original discovery of DISC1 in a family where its presence as a translocation disrupted (’chopped in half’) form of the gene strongly predisposed individuals towards psychiatric illness, one aim has been to uncover the consequences this mutation. One theory states that this gene mutation results in a lack of DISC1 protein and this lack (’haploinsufficiency‘) results in increased disease risk. The second theory argues that the mutated gene can make half a DISC1 protein but that this ‘truncated’ protein is essentially toxic through a proces known as dominant negativity. The ‘new’ mouse mutation is very similar to the human mutation in form - and the relevant finding is that no truncated protein can be detected. While this in no way harms research characterising the effects of artificially produced truncated Disc1 protein (which, in fact, neatly probes the processes in which Disc1 participates), it strongly supports the first theory as the correct pathological model in the human cases.
2. The mutant mouse strain in question, 129 (and its various substrains), is the choice of mouse geneticists when it comes to generating knockouts and other transgenic lines. Despite being good for the technical part of the knockout, 129 mice are relatively poor specimens as mice go. Therefore knockout mice are often backcrossed onto other, fitter, strains. Essentially, this is replacing all the 129-derived genetic information (but keeping your mutated gene) with that from another mouse strain. However, even if backcross breeding is continued for 10 generations then around 0.2% of the genetic material is still derived from the original (129) strain. Assuming the mouse genome is around 3 billion bases in size, that represents a stretch of DNA (presumably mostly around your mutated gene) of approximately 6 million bases. For mouse Disc1 this could include any of these genes. Two practical considerations arise. Firstly, if you are studying the knockout of a gene near Disc1 on mouse chromosome 8, you have to be sure that any resulting phenotype is the result of the lack of your gene and not the nearby 129 Disc1 mutation. Secondly, if you are looking at working on Disc1 function by breeding the 129 mutation onto another strain, you have to be sure the phenotype is due to lack of Disc1 and not due to 129-specific mutations in neighbouring genes.
3. One of the studies also looked at the behaviour of mice with the 129 Disc1 mutation and discovered problems with ‘working memory‘. Certain aspects of human memory are altered in indiviudlas with schizophrenia. By contrast, in another mouse behavioural test, Prepulse Inhibition, the 129 Disc1 mutant mice were pretty much indistinguishable from normal mice. This was unexpected as the human form of the P.I. test can detect differences between individuals with schizophrenia and normal controls and the test is often used as a first-line test of any mouse gene mutant for its relevance to schizophrenia.
4. One of the explanations of why 129 mice may be generally poor to work with could be that the Disc1 mutation is affecting certain aspects of their behaviour. Notable behavioural differences between various mouse strains have been described in the past. Click on these links to see examples where 129 mice behave differently in certain tests or have other brain-related phenotype differences: A B C D E F G H I J and K (free to download a PDF). What role the 129 Disc1 mutation has in these phenotype differences remains to be discovered.

Even the most ardent ‘nature’-lover would have to concede that the genetic contribution to schizophrenia or other psychiatric illness cannot explain 100% of the risk. However, those who support the ‘nurture’ side of the story seldom make any acknowledgement of the fact that a family history of mental illness presents the greatest risk to an individual.

This latter entrenched opinion is the subject of this post.

At the end of least year an article was published in the Guardian newspaper in the UK. Written by the psychologist Oliver James it championed the work of a New Zealand psychologist, John Read. Read’s work has recently been further highlighted by its airing at recent conferences co-presented with a Manchester researcher, Paul Hammersley.

In brief, they propose that the experience of abuse (predominantly sexual) during childhood, in combination with negative or confusing maternal behaviour (dubbed ‘mystifying’ behaviour) is a/the major cause of schizophrenia.

There is an excellent summary of the points of the paper from the clinical stand-point at schizophrenia.com including a clear rebuttal/criticism and subsequent reply from Read.

I cannot add much to this with regard to the comments on the clinical details. However, there are a number of other points that I think this issue raises.

1) Although a number of other means of abuse are mentioned by the authors, sexual abuse appears to be the crux of their new theory. While no-one would belittle the horror of such criminal acts against children, it is hard for me to understand the specificity of its action in causing schizophrenia in young adulthood. In other words, why don’t the myriad of other forms of childhood misery (death of a parent, divorce, chronic illness, neglect, bullying at school, exam stres etc. etc.) also result in schizophrenia. And why doesn’t sexual abuse result in other psychiatric conditions equally…indeed, there is some evidence that it does.

2) Added to the ’sexual’ dimension of the argument is the role of maternal ‘mystification’ in pushing children towards future schizophrenia. This seems very similar to early theories surrounding the role of the mother’s personality in triggering autism and schizophrenia in her children.

Because this has echoes of the Freudian school of thought, alarm bells immediately ring. Interpretational swings tend to be a feature of social sciences and the humanities rather than ’science sciences’. Text books are written and re-written according to the current fashionable mind-set. For example, in archaeology, research has been directed by the processual and then the post-processual schools of thought. I would argue that science is data-driven rather than interpretation-driven. That’s not to say that emerging data doesn’t change the predominant thoughts of the field, but rather that this process is not moulded to fit a pre-existing model. So my criticism from this point of view is that perhaps the psychologists not only have pre-conceived ideas of the basis of schizophrenia but also have an ideological position to defend. In all honesty, I have to counter this criticism somewhat by noting that mouse models of behavioural disorders sometimes feature (genetically dictated) failures in nurturing/nesting. In fact Prof. James Watson (yes, that one) in an online lecture described the work of Simon Baron-Cohen (yes, the father of that other one) that seems to suggest a genetic effect on parenting that might contribute to autism in children…I haven’t had a chance to look up the source material myself yet.
3) It’s been mentioned before but there is a danger that a culture of parental blame could result from a theory such as this. Moreover, if the link between schizophrenia and child abuse is considered so strong, would this diagnosis be considered a suitable trigger for the instigation of criminal investigations?
4) If, as the authors claim, the link between sexual abuse and schizophrenia is a ‘risk’ effect then perhaps the sample sizes investigated in the cross-fostering study are on the small size. In genetic case-control association studies on complex disorders (i.e. looking for genetic ‘risks’) it is generally thought appropriate to look at hundreds of cases rather than tens (as in their study), in order to be able to discriminate real signals from random noise.
5) The rather evangelical and dismissive tone of the press releases and original Guardian article is not often observed from scientists. They clearly feel passionately about their subject and the perceived sea-change in schizophrenia understanding it represents. However, the frontal attack on biological science was probably a tactical error as it erects barriers that were probably not there in the first place. The last example of vociferous backing of an anti-science hypothesis was in the form of the Intelligent Design fiasco earlier this year. In that case too, the proponents relied far too heavily on the statement that ‘evolutionary science can’t explain everything’. In the case against biological psychiatry, the often picked up on statements from various luminaries (who should know better) that no biological markers or genes are known for schizophrenia, have been used to batter the biological side of the argument. My reply would be:

a) those are old statements describing a young science (see first post) - people haven’t been keeping up with the literature.

b) saying there aren’t any now is not the same thing as saying there won’t be any soon. Science is a slow, progressive process but there is nothing to suggest that, in this instance, it is heading in the wrong direction.

6) Finally, here I am trying to defend my career-choice in the face of those telling me I’m wasting my time! While I am confident that the field of molecular psychiatry will earn its appropriate place in the end, it is a very sobering prospect that there are many that seem to feel as if the acceptance of a biological root cause of psychiatric illness is another example of some state-controlled removal of free will or some license for blanket prescription medication. Personally, I have no conceptual problem in accepting that my character, my thoughts and feelings are all the result of processes in my brain and that, because that organ is a biological entity, it is going to be subject to the vagaries of my DNA inheritance and life-time experience. Treating a malfunctioning organ is no different if that organ absorbs oxygen into the bloodstream (lungs) or is responsible for our thoughts (our brains).