The answer is unequivocally, “yes”
In co-highlighting the papers from Need et al., 2009, and Tomppo et al., 2009, you pose the question “CNV’s, interacting loci or both?” to which my immediate answer is an unequivocal “yes,” but it actually goes further than that. These two studies, interesting in their own rights, add just two more pieces of evidence now accumulated from case only, case-control, and family-based linkage on the genetic architecture of schizophrenia. Thus, we can reject with confidence a single evolutionary and genetic origin for schizophrenia. If it were so, it would have been found already by the plethora of genomewide studies now completed, studies specifically designed to detect causal variants, should they exist, which are both common to most if not all subjects and ancient in origin—the Common Disease, Common Variant (CDCV) hypothesis.

Moreover, for DISC1, NRG1, NRXN1, and a few others, the criteria for causality are met in some subjects, but none of these is the sole cause of schizophrenia. Their net contributions to individual and...  Read more

The answer is unequivocally, “yes”
In co-highlighting the papers from Need et al., 2009, and Tomppo et al., 2009, you pose the question “CNV’s, interacting loci or both?” to which my immediate answer is an unequivocal “yes,” but it actually goes further than that. These two studies, interesting in their own rights, add just two more pieces of evidence now accumulated from case only, case-control, and family-based linkage on the genetic architecture of schizophrenia. Thus, we can reject with confidence a single evolutionary and genetic origin for schizophrenia. If it were so, it would have been found already by the plethora of genomewide studies now completed, studies specifically designed to detect causal variants, should they exist, which are both common to most if not all subjects and ancient in origin—the Common Disease, Common Variant (CDCV) hypothesis.

Moreover, for DISC1, NRG1, NRXN1, and a few others, the criteria for causality are met in some subjects, but none of these is the sole cause of schizophrenia. Their net contributions to individual and population risk remain uncertain and await large scale resequencing as well as SNP and CNV studies to capture the totality of genetic variation and how that contributes to the incidence of major mental illness. Meanwhile, nosological and epidemiological evidence has also forced a re-evaluation of the categorical distinction between schizophrenia and bipolar disorder, let alone schizoaffective disorder (Lichtenstein et al., 2009).

In this regard, DISC1 serves again as an instructive paradigm, with good evidence for genetic association to schizophrenia, BP, schizoaffective disorder, and beyond (Chubb et al., 2008). The study by Hennah et al. (2008) added a further nuance to the DISC1 story by demonstrating intra-allelic interaction. Tomppo et al. (2009) now build upon their earlier evidence to show that DISC1 variants affect subcomponents of the psychiatric phenotype, treated now as a quantitative than a dichotomous trait. In much the same way and just as would be predicted, DISC1 variation also contributes to normal variation in human brain development and behavior (e.g., Callicott et al., 2005). Self-evidently, different classes of genetic variants (SNP or CNV, regulatory or coding) will have different biological and therefore psychiatric consequences (Porteous, 2008).

That Need et al. (2009) failed to replicate previous genomewide association studies (or find support for DISC1, NRG1, and the rest) is just further proof, if any were needed, that there is extensive genetic heterogeneity and that common variants of ancient origin are not major determinants of individual or population risk (Porteous, 2008). Variable penetrance, expressivity, and gene-gene interaction (epistasis) all need to be considered, but these intrinsic aspects of genetic influence are best addressed by family studies (currently lacking for CNV studies) and poorly addressed by large-scale case-control genomewide association studies. Power to test the CDCV hypothesis may increase with increasing numbers of subjects, but so does the inherent heterogeneity, both genetic and diagnostic.

That said, genetics is without doubt the most incisive tool we have to dissect the etiology of major mental illness. The criteria for success (and certainly for causality, rather than mere correlation) must be less about the number of noughts after the “p” and much more about the connection between candidate gene, gene variant, and the biological consequences for brain development and function. In this regard, both studies have something to say and offer.

References:

Lichtenstein P, Yip BH, Björk C, Pawitan Y, Cannon TD, Sullivan PF, Hultman CM. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. 2009 Lancet 373:234-9. Abstract

Chubb JE, Bradshaw NJ, Soares DC, Porteous DJ, Millar JK. Mol Psychiatry. The DISC locus in psychiatric illness. 2008 Jan;13(1):36-64. Epub 2007 Oct 2. Abstract

Callicott JH, Straub RE, Pezawas L, Egan MF, Mattay VS, Hariri AR, Verchinski BA,Meyer-Lindenberg A, Balkissoon R, Kolachana B, Goldberg TE, Weinberger DR. Variation in DISC1 affects hippocampal structure and function and increases risk for schizophrenia. 2005 Proc Natl Acad Sci U S A. 2005 102:8627-32. Abstract

Porteous D. Genetic causality in schizophrenia and bipolar disorder: out with the old and in with the new. 2008 Curr Opin Genet Dev. 18:229-34. Abstract

The results reported by Tomppo et al. and Need et al. collectively instantiate the complexities of the genetic architecture underlying risk for psychiatric illness. Paradoxically, however, while the results of Need et al. suggest that the answer to the complex question of risk genes for schizophrenia (SZ) may be found by searching a very select population for rare changes in genetic sequence, the results of Tomppo et al. suggest that the answer may be found by searching for common variants in large heterogeneous populations. So which is it? Is SZ the result of rare, novel genetic mutations or an accumulation of common ones? Such a conundrum is not a novel predicament in the process of scientific inquiry and such conundrums are often resolved by the reconciliation of both opposing views. Thus, if we allow history to serve as our guide it seems reasonable that the answer to the current question of what genetic mechanisms are responsible for SZ, is that SZ is caused by both rare and common variants.

Although considerable efforts, by our lab and others, are currently being...  Read more

The results reported by Tomppo et al. and Need et al. collectively instantiate the complexities of the genetic architecture underlying risk for psychiatric illness. Paradoxically, however, while the results of Need et al. suggest that the answer to the complex question of risk genes for schizophrenia (SZ) may be found by searching a very select population for rare changes in genetic sequence, the results of Tomppo et al. suggest that the answer may be found by searching for common variants in large heterogeneous populations. So which is it? Is SZ the result of rare, novel genetic mutations or an accumulation of common ones? Such a conundrum is not a novel predicament in the process of scientific inquiry and such conundrums are often resolved by the reconciliation of both opposing views. Thus, if we allow history to serve as our guide it seems reasonable that the answer to the current question of what genetic mechanisms are responsible for SZ, is that SZ is caused by both rare and common variants.

Although considerable efforts, by our lab and others, are currently being directed towards seeking the type of rare variants that Need et al. suggest may be responsible for risk for SZ, a less concerted effort is being directed towards parsing the effects of more specific, common genetic variations. To date, there are limited data seeking to elucidate the effects of previously identified risk variants for SZ on phenotypic variation within the diagnostic group. The data that are available, however, suggest that risk variants do influence phenotypic variation. Our work with DISC1, for example, has produced relatively robust, and replicated findings linking variation in the gene to cognitive dysfunction (Burdick et al., 2005) as well as an increased risk for persecutory delusions in SZ (DeRosse et al., 2007). Similarly, our work with DTNBP1 indicates a strong association between variants in the gene and both cognitive dysfunction (Burdick et al., 2006) and negative symptoms in SZ (DeRosse et al., 2006). Moreover, the risk for cognitive dysfunction associated with the DTNBP1 risk genotype was also observed in a sample of healthy individuals. Thus, it seems conceivable that genetic variation associated with phenotypic variation within a diagnostic group may also be associated with similar, sub-syndromal phenotypes in non-clinical samples.

The data reported by Tomppo et al. provide support for the utility of parsing the specific effects of genetic variants on phenotypic variation and extend this approach to populations with sub-syndromal psychiatric symptoms. Such an approach is attractive in that it allows us to study the effects of genotype on phenotype without the confound imposed by psychotropic medications. Although the current data linking genes to specific dimensions of psychiatric illness are provocative, the study groups utilized are comprised of patients undergoing varying degrees of pharmacological intervention. Thus, in these analyses quantitative assessment of psychosis is to some extent confounded by treatment history and response. By measuring lifetime history of symptoms, which for most patients includes substantial periods without effective medication, many studies (including our own) may partially overcome this limitation. Still, assessment of the relation between genetic variation and dimensions of psychosis in study groups not undergoing treatment with pharmacological agents would be a compelling source of confirmation for these preliminary findings.

Perhaps most importantly, the data reported by Tomppo et al. suggest that previously identified risk genes should not be marginalized but rather, should be studied in non-clinical samples to identity phenotypic variation that may be related to the signs and symptoms of psychiatric illness.

References:

Burdick KE, Hodgkinson CA, Szeszko PR, Lencz T, Ekholm JM, Kane JM, Goldman D, Malhotra AK. DISC1 and neurocognitive function in schizophrenia. Neuroreport. 2005; 16(12):1399-402. Abstract

Burdick KE, Lencz T, Funke B, Finn CT, Szeszko PR, Kane JM, Kucherlapati R, Malhotra AK. Genetic variation in DTNBP1 influences general cognitive ability. Hum Mol Genet. 2006; 15(10):1563-8. Abstract

DeRosse P, Hodgkinson CA, Lencz T, Burdick KE, Kane JM, Goldman D, Malhotra AK. Disrupted in schizophrenia 1 genotype and positive symptoms in schizophrenia. Biol Psychiatry. 2007; 61(10):1208-10. Abstract

DeRosse P, Funke B, Burdick KE, Lencz T, Ekholm JM, Kane JM, Kucherlapati R, Malhotra AK. Dysbindin genotype and negative symptoms in schizophrenia. Am J Psychiatry. 2006; 163(3):532-4. Abstract

Has anyone considered the possibility that the CNVs found to be elevated in schizophrenia versus controls could be a peripheral effect and perhaps not present in brain tissue? For example, the diet of the typical schizophrenia patient is poor, and it is conceivable that chronic folate deficiency could predispose to problems in DNA structure or repair in lymphocytes. Thus, the CNVs could be an effect of the illness, and not a cause. Someone needs to do the experiment that compares CNVs in blood to those in the brain of the same individual. And then we need studies of the stability of CNVs over the lifetime of an individual.

View all comments by James L. Kennedy

The papers by Need et al. and Tomppo et al. seem to present conflicting evidence for the involvement of common or rare variants in the etiology of schizophrenia.

On the one hand, Need et al., in a very large and well-powered sample, find no evidence for involvement of any common SNPs or CNVs. Importantly, they show that while any one SNP with a small effect and modest allelic frequency might be missed by their analysis, the likelihood that all such putative SNPs would be missed is vanishingly small. They come to the reasonable conclusion that common variants are unlikely to play a major role in the etiology of schizophrenia, except under a highly specific and implausible genetic model. Does this sound the death knell for the common variants, polygenic model of schizophrenia? Yes and no. These and other empirical data are consistent with theoretical analyses which show that the currently popular purely polygenic model, without some gene(s) of large effect, cannot explain familial risk patterns (Hemminki et al., 2007;   Read more

The papers by Need et al. and Tomppo et al. seem to present conflicting evidence for the involvement of common or rare variants in the etiology of schizophrenia.

On the one hand, Need et al., in a very large and well-powered sample, find no evidence for involvement of any common SNPs or CNVs. Importantly, they show that while any one SNP with a small effect and modest allelic frequency might be missed by their analysis, the likelihood that all such putative SNPs would be missed is vanishingly small. They come to the reasonable conclusion that common variants are unlikely to play a major role in the etiology of schizophrenia, except under a highly specific and implausible genetic model. Does this sound the death knell for the common variants, polygenic model of schizophrenia? Yes and no. These and other empirical data are consistent with theoretical analyses which show that the currently popular purely polygenic model, without some gene(s) of large effect, cannot explain familial risk patterns (Hemminki et al., 2007; Hemminki et al., 2008; Bodmer and Bonilla, 2008). It has been suggested that epistatic interactions may generate discontinuous risk from a continuous distribution of common alleles; however, while comparisons of risk in monozygotic and dizygotic twins are consistent with some contribution from epistasis, they are not consistent with the massive levels that would be required to rescue a purely polygenic mechanism, whether through a multiplicative or (biologically unrealistic) threshold model.

Thus, it seems most parsimonious to conclude that most cases of schizophrenia will involve a variant of large effect. As such variants are likely to be rapidly selected against, they are also likely to be quite rare. The findings of specific, gene-disrupting CNVs or mutations in individual genes in schizophrenia cases by Need et al. and numerous other groups support this idea. Excitingly, they also have highlighted specific molecules and biological pathways that provide molecular entry points to elucidate pathogenic mechanisms. The possible convergence on genes interacting with DISC1, including PCM1 and NDE1 in the current study, provides further support for the importance of this pathway, though, clearly, there may be many other ways to disrupt neural development or function that could lead to schizophrenia. (Conversely, it is becoming clearer that many of the putative causative mutations identified so far predispose to multiple psychiatric or neurological conditions.)

Despite the likely involvement of rare variants in most cases of schizophrenia, it remains possible that common alleles could have a modifying influence on risk—indeed, one early paper commonly cited as supporting a polygenic model for schizophrenia actually provided strong support for a model of a single gene of large effect and two to three modifiers (Risch, 1990). A rare variants/common modifiers model would be consistent with the body of literature on modifying genes in model organisms, where effects of genetic background on the phenotypic expression of particular mutations are quite common and can sometimes be large (Nadeau, 2001). Whether such genetic background effects would be mediated by common or rare variants is another question—there is certainly good reason to think that rare or even private mutations may make a larger contribution to phenotypic variance than previously suspected (Ng et al., 2008; Ji et al., 2008).

Nevertheless, common variants are also likely to be involved, and these effects might be detectable in large association studies, though they would be expected to be diluted across genotypes. This might explain inconsistent findings of association of common variants with disease state for various genes, including COMT, BDNF, and DISC1, for example. This issue has led some to look for association of variants in these genes with endophenotypes of schizophrenia in the general population—psychological or physiological traits that are heritable and affected by the symptoms of the disease, such as working memory, executive function, or, in the study by Tomppo et al., social interaction.

These approaches have tended to lead to statistically stronger and more consistent associations and are undoubtedly revealing genes and mechanisms contributing to normal variation in many psychological traits. How this relates to their potential involvement in disease etiology is far from clear, however. The implication of the endophenotype model is that the disorder itself emerges due to the combination of minor effects on multiple symptom parameters (Gottesman and Gould, 2003; Meyer-Lindenberg and Weinberger, 2006). An alternative interpretation is that these common variants may modify the phenotypic expression of some other rare variant, either due to their demonstrated effect on the psychological trait in question or through a more fundamental biochemical interaction, but that in the absence of such a variant of large effect, no combination of common alleles would lead to disease.

References:

Hemminki K, Försti A, Bermejo JL. The 'common disease-common variant' hypothesis and familial risks. PLoS ONE. 2008 Jun 18;3(6):e2504. Abstract

Hemminki K, Bermejo JL. Constraints for genetic association studies imposed by attributable fraction and familial risk. Carcinogenesis. 2007 Mar;28(3):648-56. Abstract

Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet. 2008 Jun;40(6):695-701. Abstract

Risch N. Linkage strategies for genetically complex traits. I. Multilocus models. Am J Hum Genet. 1990 Feb;46(2):222-8. Abstract

Nadeau JH. Modifier genes in mice and humans. Nat Rev Genet. 2001 Mar;2(3):165-74. Abstract

Ng PC, Levy S, Huang J, Stockwell TB, Walenz BP, Li K, Axelrod N, Busam DA, Strausberg RL, Venter JC. Genetic variation in an individual human exome. PLoS Genet. 2008 Aug 15;4(8):e1000160. Abstract

Ji W, Foo JN, O'Roak BJ, Zhao H, Larson MG, Simon DB, Newton-Cheh C, State MW, Levy D, Lifton RP. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat Genet. 2008 May;40(5):592-9. Abstract

Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003 Apr;160(4):636-45. Abstract

Meyer-Lindenberg A, Weinberger DR. Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat Rev Neurosci. 2006 Oct;7(10):818-27. Abstract

The fact that the PRODH alteration studied in Gogos et al. leads to alterations in glutamate release, and this corresponds to deficits in associative learning and response to psychotomimetics, provides a nice parallel to the human condition. The Reiss paper examines humans with the 22q11.2 deletion, and shows that the COMT low-activity allele of this deletion syndrome correlates with cognitive decline, PFC volume, and development of psychotic symptoms. This is a nice addition to the Weinberger and Bilder papers about how COMT can lead to psychosis vulnerability.

View all comments by Anthony Grace

I echo Jeff Lieberman's comment regarding previous reports of a weak association between the Val COMT functional allele and schizophrenia. Notably, the most recent meta-analysis (Munafo et al., 2005) shows no significant association. Even in 22q11.2 deletion syndrome (22qDS), our group (unpublished) and Murphy et al. (1999) have reported that there is no association between COMT genotype and schizophrenia, and Bearden et al. reported that Val-hemizygous patients performed significantly worse than Met-hemizygous patients on executive cognition ( 2004) and childhood behavioral problems (2005). Though important as an initial prospective study, there is a risk in the Gothelf et al. small sample size and multiple testing for type 1 errors. Certainly, there is little...  Read more

I echo Jeff Lieberman's comment regarding previous reports of a weak association between the Val COMT functional allele and schizophrenia. Notably, the most recent meta-analysis (Munafo et al., 2005) shows no significant association. Even in 22q11.2 deletion syndrome (22qDS), our group (unpublished) and Murphy et al. (1999) have reported that there is no association between COMT genotype and schizophrenia, and Bearden et al. reported that Val-hemizygous patients performed significantly worse than Met-hemizygous patients on executive cognition ( 2004) and childhood behavioral problems (2005). Though important as an initial prospective study, there is a risk in the Gothelf et al. small sample size and multiple testing for type 1 errors. Certainly, there is little evidence, even in 22qDS, for COMT (or PRODH) as “key” risk factors for schizophrenia. There may be some evidence for small effects on cognitive or other measures. Regardless, there is not “extreme deficiency” in COMT activity in the many individuals with Met-hemizygosity in 22qDS, or Met-Met homozygosity in the general population.

Regarding the news item, there are a few widely held misconceptions about 22qDS. Our recent article (Bassett et al., 2005) shows that, accounting for ascertainment bias, the rate of schizophrenia was 23 percent, and congenital heart defects was 26 percent. Of the other 41 common lifetime features of 22qDS (found in 5 percent or more patients), neuromuscular palatal anomalies were common but overt cleft palate was so rare it did not meet inclusion criteria; intellectual disabilities ranged from severe mental retardation (rare) to average intellect (rare) with most patients falling in the borderline range of intellect; and on average, patients had nine of 43 common features. We propose clinical practice guidelines for adults with 22qDS which may be directly applicable to the 1-2 percent of patients with a 22qDS form of schizophrenia.

References:
Bassett AS, Chow EWC, Husted J, Weksberg R, Caluseriu O, Webb GD, Gatzoulis MA. Clinical features of 78 adults with 22q11 Deletion Syndrome. Am J Med Genet A. 2005 Nov 1;138(4):307-13. Abstract

Bearden CE, Jawad AF, Lynch DR, Sokol S, Kanes SJ, McDonald-McGinn DM, Saitta SC, Harris SE, Moss E, Wang PP, Zackai E, Emanuel BS, Simon TJ. Effects of a functional COMT polymorphism on prefrontal cognitive function in patients with 22q11.2 deletion syndrome. Am J Psychiatry . 2004 Sep;161(9):1700-2. Abstract

Bearden CE, Jawad AF, Lynch DR, Monterossso JR, Sokol S, McDonald-McGinn DM, Saitta SC, Harris SE, Moss E, Wang PP, Zackai E, Emanuel BS, Simon TJ. Effects of COMT genotype on behavioral symptomatology in the 22q11.2 Deletion Syndrome. Neuropsychol Dev Cogn C Child Neuropsychol. 2005 Feb;11(1):109-17. Abstract

Munafo MR, Bowes L, Clark TG, Flint J. Lack of association of the COMT (Val158/108 Met) gene and schizophrenia: a meta-analysis of case-control studies. Mol Psychiatry. 2005 Aug;10(8):765-70. Abstract

Murphy KC, Jones LA, Owen MJ. High rates of schizophrenia in adults with velo-cardio-facial syndrome. Arch Gen Psychiatry. 1999 Oct 1;56(10):940-5. Abstract

Many linkage analyses have reproducibly reported 8p21-22 as a linkage hot locus for schizophrenia. The gene coding for neuregulin-1 is regarded as a factor that contributes to the linkage peak, but other genes may also be involved. Dr. Gurling and colleagues have conducted an excellent association study and obtained evidence that the gene coding for pericentriolar material 1 (PCM1) is associated with schizophrenia.

The results from the genetic portions of this are consistent with our unpublished biological study. (The abstract of Kamiya et al. has been submitted to SFN meeting at Atlanta in October 2006.) In exploring protein interactors of disrupted-in-schizophrenia-1 (DISC1), a promising risk factor for schizophrenia and bipolar disorder, we already came across PCM1 as a potential protein interactor of DISC1. This interaction has been confirmed by yeast two-hybrid and biochemical methods. In immunofluorescent cell staining, a pool of DISC1 and PCM1 are co-stained at the centrosome. Therefore, this genetic study is really encouraging us to move beyond our preliminary...  Read more

Many linkage analyses have reproducibly reported 8p21-22 as a linkage hot locus for schizophrenia. The gene coding for neuregulin-1 is regarded as a factor that contributes to the linkage peak, but other genes may also be involved. Dr. Gurling and colleagues have conducted an excellent association study and obtained evidence that the gene coding for pericentriolar material 1 (PCM1) is associated with schizophrenia.

The results from the genetic portions of this are consistent with our unpublished biological study. (The abstract of Kamiya et al. has been submitted to SFN meeting at Atlanta in October 2006.) In exploring protein interactors of disrupted-in-schizophrenia-1 (DISC1), a promising risk factor for schizophrenia and bipolar disorder, we already came across PCM1 as a potential protein interactor of DISC1. This interaction has been confirmed by yeast two-hybrid and biochemical methods. In immunofluorescent cell staining, a pool of DISC1 and PCM1 are co-stained at the centrosome. Therefore, this genetic study is really encouraging us to move beyond our preliminary study on DISC1 and PCM1.

Of interest, Gurling and colleagues reported in the paper that the cases with the PCM1 genetic susceptibility showed a significant relative reduction in the volume of orbitofrontal cortex gray matter in comparison with patients with non-PCM1-associated schizophrenia, who showed gray matter volume reduction in the temporal pole, hippocampus, and inferior temporal cortex. This may be in accordance with our previous publication (Sawamura et al., 2005) reporting the alteration in subcellular distribution of DISC1 in the orbitofrontal cortex of the patients with schizophrenia.

Although a possible link of DISC1 and PCM1 in the pathophysiology of schizophrenia is still hypothetical, the intriguing work by Dr. Gurling and colleagues may now open a window in studying the centrosomal “pathway” in association with schizophrenia. Epistatic interactions on DISC1, PCM1, and related molecules may also be of interest for future studies.

Regarding the possibility that PCM1 may have ties to DISC1, it's of interest that when PCM1 function is inhibited there is reduced targeting of centrin, pericentrin and ninein to the centrosome (1). Miyoshi and colleagues (2) report that their data indicate that DISC1 localizes to the centrosome by binding to kendrin/pericentrinB. Might there be a failure of DISC1 to localize in the centrosome in PCM1 deficiency?

Do these families with PCM1-associated schizophrenia also have a history of scleroderma? It is also of interest that PCM1 is an autoantigen target in scleroderma (3), and there is a report of cerebral involvement of scleroderma presenting as schizophrenia-like psychosis (4).

Abelson Helper Integration Site 1 (AHI1) gene is a candidate gene for schizophrenia and mutations in AHI1 underlie the autosomal recessive Joubert Syndrome in which cerebellar vermis hypoplasia is reported.(5) Increased cerebellar vermis white-matter volume has recently been reported in males with schizophrenia.(6)

It's interesting that mutations in the centrosomal protein...  Read more

Regarding the possibility that PCM1 may have ties to DISC1, it's of interest that when PCM1 function is inhibited there is reduced targeting of centrin, pericentrin and ninein to the centrosome (1). Miyoshi and colleagues (2) report that their data indicate that DISC1 localizes to the centrosome by binding to kendrin/pericentrinB. Might there be a failure of DISC1 to localize in the centrosome in PCM1 deficiency?

Do these families with PCM1-associated schizophrenia also have a history of scleroderma? It is also of interest that PCM1 is an autoantigen target in scleroderma (3), and there is a report of cerebral involvement of scleroderma presenting as schizophrenia-like psychosis (4).

Abelson Helper Integration Site 1 (AHI1) gene is a candidate gene for schizophrenia and mutations in AHI1 underlie the autosomal recessive Joubert Syndrome in which cerebellar vermis hypoplasia is reported.(5) Increased cerebellar vermis white-matter volume has recently been reported in males with schizophrenia.(6)

It's interesting that mutations in the centrosomal protein nephrocystin-6 may also cause Joubert syndrome and that it activates ATF4. (7) Morris and colleagues (8) find that DISC1 interacts with ATF4 - a schizophrenia locus on 22q13 and ATF5. Perhaps failure of DISC1 to localize to the centrosome due to PCMI deficiency may also result in reduced activation of ATF4/5.

In view of the study by Al Sarraj and colleagues (9) finding that ATF4/5 stimulate asparagine synthetase activity might we suspect that reduced activation of ATF4 and ATF5 in schizophrenia may explain the decreased CSF asparagine levels reported (10) Perhaps asparagine synthetase might be a suitable drug target in schizophrenia. Of further relevance is the processed pseudogene for asparagine synthetase found upstream of GNAL -18p11, a region linked to bipolar disorder and schizophrenia. (11) Hirotsune and colleagues (12) report that an expressed pseudogene regulates messenger-RNA stability of its homologous coding gene.

Might we also suspect a role for DISC1 in oligodendrocyte dysfunction in schizophrenia? Reduced myelination is reported in neonatal rats deprived of asparagine?(13) It would seem relevant however that Mason and colleagues (14) find that ATF5 regulates proliferation and differentiation of oligodendrocytes, with loss of function resulting in accelerated oligodendrocyte differentiation

References:

1. Dammermann A, Merdes A. Assembly of centrosomal proteins and microtubule organization depends on PCM-1. J Cell Biol. 2002 Oct 28;159(2):255-66. Epub 2002 Oct 28. Abstract

2. Miyoshi K, Asanuma M, Miyazaki I, Diaz-Corrales FJ, Katayama T, Tohyama M, Ogawa N. DISC1 localizes to the centrosome by binding to kendrin. Biochem Biophys Res Commun. 2004 May 14;317(4):1195-9. Abstract

3. Bao L, Zimmer WE, Balczon R. Autoepitope mapping of the centrosome autoantigen PCM-1 using scleroderma sera with anticentrosome autoantibodies. Autoimmunity. 1995;22(4):219-28. Abstract

4. Muller N, Gizycki-Nienhaus B, Botschev C, Meurer M. Cerebral involvement of scleroderma presenting as schizophrenia-like psychosis. Schizophr Res. 1993 Aug;10(2):179-81. Abstract (5) Eur J Hum Genet. 2006 Jun 14; [Epub ahead of print] AHI1, a pivotal neurodevelopmental gene, and C6orf217 are associated with susceptibility to schizophrenia. Amann-Zalcenstein D, Avidan N, Kanyas K, Ebstein RP, Kohn Y, Hamdan A, Ben-Asher E, Karni O, Mujaheed M, Segman RH, Maier W, Macciardi F, Beckmann JS, Lancet D, Lerer B. (6) J Psychiatr Res. 2006 Apr 18; [Epub ahead of print] Increased cerebellar vermis white-matter volume in men with schizophrenia. Lee KH, Farrow TF, Parks RW, Newton LD, Mir NU, Egleston PN, Brown WH, Wilkinson ID, Woodruff PW (7) Nat Genet. 2006 Jun;38(6):674-81. Epub 2006 May 7. The centrosomal protein nephrocystin-6 is mutated in Joubert syndrome and activates transcription factor ATF4. Sayer JA, Otto EA, O'Toole JF, Nurnberg G, Kennedy MA, Becker C, Hennies HC, Helou J, Attanasio M, Fausett BV, Utsch B, Khanna H, Liu Y, Drummond I, Kawakami I, Kusakabe T, Tsuda M, Ma L, Lee H, Larson RG, Allen SJ, Wilkinson CJ, Nigg EA,Shou C, Lillo C, Williams DS, Hoppe B, Kemper MJ, Neuhaus T, Parisi MA, Glass IA, Petry M, Kispert A, Gloy J, Ganner A, Walz G, Zhu X, Goldman D, Nurnberg P, Swaroop A, Leroux MR, Hildebrandt F. (8) Hum Mol Genet. 2003 Jul 1;12(13):1591-608. Links DISC1 (Disrupted-In-Schizophrenia 1) is a centrosome-associated protein that interacts with MAP1A, MIPT3, ATF4/5 and NUDEL: regulation and loss of interaction with mutation. Morris JA, Kandpal G, Ma L, Austin CP. (9) Biol Chem. 2005 Sep;386(9):873-9. Links Regulation of asparagine synthetase gene transcription by the basic region leucine zipper transcription factors ATF5 and CHOP. Al Sarraj J, Vinson C, Thiel G. (10) Nippon Rinsho. 1992 Jul;50(7):1643-9. Links [Amino acid metabolism in endogenous psychoses: significance of amino acids as neurotransmitter, precursor of monoamines and allosteric regulator of neuro-receptors] Doi N. (11) Mol Psychiatry. 2000 Sep;5(5):495-501. Links Sequence and genomic organization of the human G-protein Golfalpha gene (GNAL) on chromosome 18p11, a susceptibility region for bipolar disorder and schizophrenia. Vuoristo JT, Berrettini WH, Overhauser J, Prockop DJ, Ferraro TN, Ala-Kokko L. (12) Nature. 2003 May 1;423(6935):26-8. An expressed pseudogene regulates the messenger-RNA stability of its homologous coding gene. Hirotsune S, Yoshida N, Chen A, Garrett L, Sugiyama F, Takahashi S, Yagami K, Wynshaw-Boris A, Yoshiki A. (13) Dev Neurosci. 1982;5(4):332-44. Brain development in neonatal rats nursing asparagine-deprived dams. Newburg DS, Fillios LC. (14) Mol Cell Neurosci. 2005 Jul;29(3):372-80. ATF5 regulates the proliferation and differentiation of oligodendrocytes. Mason JL, Angelastro JM, Ignatova TN, Kukekov VG, Lin G, reene LA, Goldman JE.

Den Hollander and colleagues (1) report that mutations in CEP290-nephrocystin-6 are a frequent cause of Leber's Congenital Amaurosis (LCA). Autistic signs are reported in both Joubert syndrome and LCA (2,3). Perhaps asparagine may be useful for those with LCA and dysmyelination.

References:

1. den Hollander AI, Koenekoop RK, Yzer S, Lopez I, Arends ML, Voesenek KE, Zonneveld MN, Strom TM, Meitinger T, Brunner HG, Hoyng CB, van den Born LI, Rohrschneider K, Cremers FP. Mutations in the CEP290 (NPHP6) Gene Are a Frequent Cause of Leber Congenital Amaurosis. Am J Hum Genet. 2006 Sep;79(3):556-61. Epub 2006 Jul 11. Abstract

2. Curless RG, Flynn JT, Olsen KR, Post MJ. Leber congenital amaurosis in siblings with diffuse dysmyelination. Pediatr Neurol. 1991 May-Jun;7(3):223-5. Abstract

3. Rogers SJ, Newhart-Larson S. Characteristics of infantile autism in five children with Leber's congenital amaurosis. Dev Med Child Neurol. 1989 Oct;31(5):598-608. Abstract

View all comments by Mary Reid

The asparagine synthetase gene has been mapped to 7q21.3 (1). Childhood-onset schizophrenia/autistic disorder has been described in a child with a translocation breakpoint at 7q21. Of further interest is that alcohol/drug abuse, severe impulsivity, paranoid personality, and language delay have been reported in other family members carrying this translocation.

Maybe the increased risk of schizophrenia following famine may be explained by the fact that starvation induces expression of ATF4 and asparagine synthetase. Is there an increased risk of mutation in these genes as a long-term response to famine?

References:

1. Heng HH, Shi XM, Scherer SW, Andrulis IL, Tsui LC. Refined localization of the asparagine synthetase gene (ASNS) to chromosome 7, region q21.3, and characterization of the somatic cell hybrid line 4AF/106/KO15. Cytogenet Cell Genet. 1994;66(2):135-8. Abstract

2. Yan WL, Guan XY, Green ED, Nicolson R, Yap TK, Zhang J, Jacobsen LK, Krasnewich DM, Kumra S, Lenane MC, Gochman P, Damschroder-Williams PJ, Esterling LE, Long RT, Martin BM, Sidransky E, Rapoport JL, Ginns EI. Childhood-onset schizophrenia/autistic disorder and t(1;7) reciprocal translocation: identification of a BAC contig spanning the translocation breakpoint at 7q21. Am J Med Genet. 2000 Dec 4;96(6):749-53. Abstract

View all comments by Mary Reid

Although DISC1 is multifunctional, its role for neurite outgrowth has been substantially characterized for the past couple of years (Ozeki et al., 2003; Miyoshi et al., 2003; Kamiya et al., 2006). These studies indicated that DISC1 is involved in neurite outgrowth by more than one mechanism, such as interactions with NUDEL/NDEL1 and FEZ1.

These two papers from Kaibuchi’s lab provide further understanding of how DISC1 is involved in neuronal outgrowth. Kaibuchi’s group identified kinesin heavy chain of kinesin-1 as a novel interactor of DISC1. In their papers, a novel role for DISC1, to link kinesin-1 (microtubule-dependent and plus-end directed motor) to several cellular molecules, including NUDEL, LIS1, 14-3-3, and Grb2, is reported. DISC1 and kinesin-1 are, therefore, responsible to sort Grb2 to the distal part of axons where Grb2...  Read more

Although DISC1 is multifunctional, its role for neurite outgrowth has been substantially characterized for the past couple of years (Ozeki et al., 2003; Miyoshi et al., 2003; Kamiya et al., 2006). These studies indicated that DISC1 is involved in neurite outgrowth by more than one mechanism, such as interactions with NUDEL/NDEL1 and FEZ1.

These two papers from Kaibuchi’s lab provide further understanding of how DISC1 is involved in neuronal outgrowth. Kaibuchi’s group identified kinesin heavy chain of kinesin-1 as a novel interactor of DISC1. In their papers, a novel role for DISC1, to link kinesin-1 (microtubule-dependent and plus-end directed motor) to several cellular molecules, including NUDEL, LIS1, 14-3-3, and Grb2, is reported. DISC1 and kinesin-1 are, therefore, responsible to sort Grb2 to the distal part of axons where Grb2 functions as an adaptor and plays a role in NT-3-induced phosphorylation of ERK1/2. This mechanism well explains our previous work, led by Ryota Hashimoto, reporting that knockdown of DISC1 expression results in decreased levels of phosphorylation of ERK1/2 and Akt in primary cortical neurons (Hashimoto et al., 2006).

The interaction of DISC1 and kinesin-1 may also be interesting from the perspective of psychiatric genetics. First, the mechanism proposed in one of the papers (Taya et al., 2007) supports the notion that the C-terminal truncated DISC1 fragment—that occurs due to the balanced translocation in an extended Scottish family—functions as a dominant-negative. Second, the domain of DISC1 responsible for kinesin-1 is overlapped with the haplotype block region(s) that are positive in more than one association study of DISC1 and major mental illnesses.

Two recent back-to-back papers, published this month in Journal of Neuroscience, highlight the value of protein-protein interactions in determining the biological role of a key schizophrenia risk factor, DISC1, in processes that are important for the proper development of neurons.

Key questions need to be addressed once having established a set of interactors for a given protein. First, where do these proteins interact on the target molecule? Second, do these interactions take place at the same time (i.e., do they form a complex)? Third, in what context do these interactions occur (temporal, tissue/cell compartment, signaling), and, fourth, are the biological processes of the interacting molecules affected/regulated by the protein of interest? The Kaibuchi lab, as exemplified in the works by Taya et al. and Shinoda et al., elegantly address some of these questions in the context of DISC1 interactions with Grb2, Nudel (NDEL1), 14-3-3ε, and kinesin-1. The key findings of these papers are as follows:

1. Identification of the interaction sites, or more importantly,...  Read more

Two recent back-to-back papers, published this month in Journal of Neuroscience, highlight the value of protein-protein interactions in determining the biological role of a key schizophrenia risk factor, DISC1, in processes that are important for the proper development of neurons.

Key questions need to be addressed once having established a set of interactors for a given protein. First, where do these proteins interact on the target molecule? Second, do these interactions take place at the same time (i.e., do they form a complex)? Third, in what context do these interactions occur (temporal, tissue/cell compartment, signaling), and, fourth, are the biological processes of the interacting molecules affected/regulated by the protein of interest? The Kaibuchi lab, as exemplified in the works by Taya et al. and Shinoda et al., elegantly address some of these questions in the context of DISC1 interactions with Grb2, Nudel (NDEL1), 14-3-3ε, and kinesin-1. The key findings of these papers are as follows:

1. Identification of the interaction sites, or more importantly, which part of DISC1 is involved in particular processes, for example, that axon elongation is dependent on the N-terminal, but not the C-terminal portion of DISC1. This suggests that the DISC1 role in axon elongation is mediated by interactions with the N-terminal portion of DISC1 that could be competed for by the truncated protein in a dominant negative fashion (Camargo et al., 2007).

2. Although a protein may have many interacting partners, such as DISC1, these interactions may not occur at the same time. For example, DISC1 is able to form a ternary complex with kinesin-1 and NDEL1 or with kinesin-1 and Grb2. However, a ternary complex of DISC1-Grb2-NDEL1 is not possible as Grb2 and NDEL1 may be competing for the same interaction site on DISC1.

3. Protein interactions may occur in certain cellular compartments, in the case of DISC1, the cell body and the distal part of axons.

4. Neurotrophin-induced axon elongation requires DISC1.

These papers confirm some of the hypotheses raised by the interactions that we have recently derived for DISC1 and some of its interacting partners (see Camargo et al., 2007). From the DISC1 interactome, we concluded that DISC1 may affect key intracellular transport mechanisms, such as those regulated by kinesins, and that DISC1 may be downstream of neurotrophin receptors, via its interaction with SH3BP5, an adaptor protein, which we found to interact with SOS1, a guanine exchange factor that binds Grb2 and responds to signaling of neurotrophin receptors. These observations have been validated by Taya et al. and Shinoda et al. and demonstrate the value of the DISC1 interactome in understanding the role of DISC1, and as a valuable resource to the wider community.

The molecular function of DISC1, as defined by its structure, still remains elusive, requiring a more dedicated effort on this front. The good news is that, via its protein-protein interactions, significant progress on the role of DISC1 in key biological processes has been achieved, as illustrated by the work of different labs (Brandon et. al., 2004; Millar et al., 2005; Kamiya et al., 2005; and now by Shinoda et al. and Taya et al.).

The paper by Walsh et al. is an important addition to the expanding literature on copy number variations in the human genome and their potential role in causing neuropsychiatric disorders. It is clear that copy number variations are important aspects of human genetic variation and that deletions and duplications in diverse genes throughout the genome are likely to affect the function of these genes and possibly the development and function of the human brain. So-called private variations, such as those described in this paper, i.e., changes in the genome found in only a single individual, as all of these variations are, are difficult to establish as pathogenic factors, because it is hard to know how much they contribute to the complex problem of human behavioral variation in a single individual. If the change is private, i.e., only in one case and not enriched in cases as a group, as are common genetic polymorphisms such as SNPs, how much they account for case status is very difficult to prove.

An assumption implicit in this paper is that these private variations may be...  Read more

The paper by Walsh et al. is an important addition to the expanding literature on copy number variations in the human genome and their potential role in causing neuropsychiatric disorders. It is clear that copy number variations are important aspects of human genetic variation and that deletions and duplications in diverse genes throughout the genome are likely to affect the function of these genes and possibly the development and function of the human brain. So-called private variations, such as those described in this paper, i.e., changes in the genome found in only a single individual, as all of these variations are, are difficult to establish as pathogenic factors, because it is hard to know how much they contribute to the complex problem of human behavioral variation in a single individual. If the change is private, i.e., only in one case and not enriched in cases as a group, as are common genetic polymorphisms such as SNPs, how much they account for case status is very difficult to prove.

An assumption implicit in this paper is that these private variations may be major factors in the case status of the individuals who have them. The data of this paper suggest, however, this is actually not the case, at least for the childhood onset cases. Here’s why: mentioned in the paper is a statement that only two of the CNVs in the childhood cases are de novo, i.e., spontaneous and not inherited (and one of these is on the Y chromosome, making its functional implications obscure). If most of the CNVs are inherited, they can’t be causing illness per se as major effect players because they are coming from well parents.

Also, if you add up all CNVs in transmitted and non-transmitted chromosomes of the parents, it’s something like 31 gene-based CNVs in 154 parents (i.e., 20 percent of the parents have a gene-based deletion or duplication in the very illness-related pathways that are highlighted in the cases), which is at least as high a frequency as in the adult-onset schizophrenia sample in this study…and three times the frequency as found in the adult controls. This is not to say that such variants might not represent susceptibility genetic factors, or show variable penetrance between individuals, like other polymorphisms, and contribute to the complex genetic risk architecture, like other genetic variations that have been more consistently associated with schizophrenia. However, the CNV literature has tended to seek a more major effect connotation to the findings.

As new technologies are applied to understanding the etiology and pathophysiology of schizophrenia, considering the clinical features of the cases studied and the implications of the findings is of value. The conclusion of the Walsh et al. paper, “these results suggest that schizophrenia can be caused by rare mutations….“ is worth considering carefully.

What evidence is needed to link an observation in the laboratory or clinic to cause? Recent recommendations for the content of papers in epidemiology (von Elm et al., 2008) remind us of the suggestions of A.V. Hill (Hill, 1965). To discern the implications of a finding, or association, for causality, Hill suggests assessment of the following:

1. Strength of the association: this is not the observed p-value, but a measure of the magnitude of the association. In the Walsh et al. study, the primary outcome measure, structural variants duplicating or deleting genes was observed in 15 percent of cases, and 5 percent of controls. But...  Read more

As new technologies are applied to understanding the etiology and pathophysiology of schizophrenia, considering the clinical features of the cases studied and the implications of the findings is of value. The conclusion of the Walsh et al. paper, “these results suggest that schizophrenia can be caused by rare mutations….“ is worth considering carefully.

What evidence is needed to link an observation in the laboratory or clinic to cause? Recent recommendations for the content of papers in epidemiology (von Elm et al., 2008) remind us of the suggestions of A.V. Hill (Hill, 1965). To discern the implications of a finding, or association, for causality, Hill suggests assessment of the following:

1. Strength of the association: this is not the observed p-value, but a measure of the magnitude of the association. In the Walsh et al. study, the primary outcome measure, structural variants duplicating or deleting genes was observed in 15 percent of cases, and 5 percent of controls. But what is the association with? The diagnostic entity of schizophrenia, or some risk factor for the illness? Of interest, and noted in the Supporting Online Material, these variants were present in 7/15 (47 percent) of the cases with presumed IQ <80, but only 15/135 (11 percent) of the cases with IQ >80. Are the structural variants more strongly associated with mental retardation (within schizophrenia 47 percent vs. 11 percent) than with diagnosis (11 percent vs. 5 percent of controls, assuming normal IQ)? This is of particular interest in the context of the speculation in the paper concerning the importance of genes putatively involved with brain development in the etiology of schizophrenia.

2. Consistency of results in the literature across studies and research groups: there are now several papers examining copy number variation in schizophrenia, including a report from our group (Wilson et al., 2006). The authors of the present paper state that each variant observed was unique, and so consistency of the specific findings could be argued to be irrelevant, if the model is of novel mutations (more on models below). Undoubtedly, future meta-analyses and accumulating databases help determine if there is anything consistent in the findings, other than a higher frequency of any abnormalities in cases rather than controls.

3. Specificity of the findings to the illness in question: this was not addressed experimentally in the paper. However, the findings of more abnormalities in the putative low IQ cases, and the similarity of the findings to reports in autism and mental retardation, suggest that this criterion for supporting causality is unlikely to be met.

4. Temporality: the abnormalities should precede the illness. If DNA from terminally differentiated neurons harbors the same variants as DNA from constantly renewed populations of lymphocytes, then clearly this condition is met. While it seems highly likely that this is the case, it is worthwhile considering the possibility that DNA structure may vary between tissue types, or between cell populations. Even within human brain there is some evidence for chromosomal heterogeneity (Rehen et al., 2005).

5. Biological gradient: presence of a “dose-response” curve strengthens the likelihood of a causal relationship. This condition is not met within cases: only 1/115 appeared to have more than one variant. However, in the presumably more severe childhood onset form of schizophrenia, four individuals carried multiple variants, and the observation of a higher prevalence of variants overall. Still, the question of what the observations of CNV are associated with is relevant, since one of the inclusion/exclusion criteria for COS allowed IQ 65-80, and it is uncertain how many of these cases had some degree of intellectual deficit.

6. Plausibility: biological likelihood—quite difficult to satisfy as a criterion, in the context of the limits of knowledge concerning the mechanisms of illness of schizophrenia.

7. Coherence of the observation with known facts about the illness: the genetic basis of schizophrenia is quite well studied, and there is no dearth of theories concerning genetic architecture. However, a coherent model remains lacking. As examples, the suggestion is made that the observations concerning inherited CNVs in the COS cases are linked with a severe family history in this type of illness. This appears inconsistent with a high penetrance model for CNVs as suggested in the opening of the paper (presuming the parents in COS families are unaffected, as would seem likely). Elsewhere, CNVs are proposed by the authors to be related to de novo events, and an interaction with an environmental modifier, folate (and exposure to famine), is posited (McClellan et al., 2006). A model of the effects of CNVs, which generates falsifiable hypotheses is needed.

8. Experiment: the ability to intervene clinically to modify the effects of CNVs disrupting genes seems many years away.

9. Analogy: the novelty of the CNV findings is both intriguing, but limiting in understanding the likelihood of causal relationships.

The intersection of clinical realities and novel laboratory technologies will fuel the need for better translational research in schizophrenia for many, many more years.

References:

von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008 Apr 1;61(4):344-349. Abstract

HILL AB. THE ENVIRONMENT AND DISEASE: ASSOCIATION OR CAUSATION? Proc R Soc Med. 1965 May 1;58():295-300. Abstract

Wilson GM, Flibotte S, Chopra V, Melnyk BL, Honer WG, Holt RA. DNA copy-number analysis in bipolar disorder and schizophrenia reveals aberrations in genes involved in glutamate signaling. Hum Mol Genet. 2006 Mar 1;15(5):743-9. Abstract

Rehen SK, Yung YC, McCreight MP, Kaushal D, Yang AH, Almeida BSV, Kingsbury MA, Cabral KMS, McConnell MJ, Anliker B, Fontanoz M, Chun J: Constitutional aneuploidy in the normal human brain. J Neurosci 2005; 25:2176-2180. Abstract

McClellan JM, ESusser E, King M-C: Maternal famine, de novo mutations, and schizophrenia. JAMA 2006; 296:582-584. Abstract

The new study by Walsh et al. (2008), as well as recent data from other groups working in schizophrenia, autism, and mental retardation, make a strong case for including copy number variants as an important source of risk for neurodevelopmental phenotypes. These findings raise several intriguing new questions for future research, including: the degree of causality/penetrance that can be attributed to individual CNVs; diagnostic specificity; and recency of their origins. While these questions are difficult to address in the context of private mutations, one potential source of additional information is the examination of common, recurrent CNVs, which have not yet been systematically studied as potential risk factors for schizophrenia.

Still, the association of rare CNVs with schizophrenia provides additional evidence that genetic transmission patterns may be a complex hybrid of common, low-penetrant alleles and rare, highly penetrant variants. In diseases ranging from Parkinson's to colon cancer, the literature demonstrates that rare penetrant loci are...  Read more

The new study by Walsh et al. (2008), as well as recent data from other groups working in schizophrenia, autism, and mental retardation, make a strong case for including copy number variants as an important source of risk for neurodevelopmental phenotypes. These findings raise several intriguing new questions for future research, including: the degree of causality/penetrance that can be attributed to individual CNVs; diagnostic specificity; and recency of their origins. While these questions are difficult to address in the context of private mutations, one potential source of additional information is the examination of common, recurrent CNVs, which have not yet been systematically studied as potential risk factors for schizophrenia.

Still, the association of rare CNVs with schizophrenia provides additional evidence that genetic transmission patterns may be a complex hybrid of common, low-penetrant alleles and rare, highly penetrant variants. In diseases ranging from Parkinson's to colon cancer, the literature demonstrates that rare penetrant loci are frequently embedded within an otherwise complex disease. Perhaps the most well-known example involves mutations in amyloid precursor protein and the presenilins in Alzheimer’s disease (AD). Although extremely rare, accounting for <1 percent of all cases of AD, identification of these autosomal dominant subtypes greatly enhanced understanding of pathophysiology. Similarly, a study of consanguineous families in Iran has very recently identified a rare autosomal recessive form of mental retardation (MR) caused by glutamate receptor (GRIK2) mutations, thereby opening new avenues of research (Motazacker et al., 2007). In schizophrenia, we have recently employed a novel, case-control approach to homozygosity mapping (Lencz et al., 2007), resulting in several candidate loci that may harbor highly penetrant recessive variants. Taken together, these results suggest that a diversity of methodological approaches will be needed to parse genetic heterogeneity in schizophrenia.

References:

Motazacker MM, Rost BR, Hucho T, Garshasbi M, Kahrizi K, Ullmann R, Abedini SS, Nieh SE, Amini SH, Goswami C, Tzschach A, Jensen LR, Schmitz D, Ropers HH, Najmabadi H, Kuss AW. (2007) A defect in the ionotropic glutamate receptor 6 gene (GRIK2) is associated with autosomal recessive mental retardation. Am J Hum Genet. 81(4):792-8. Abstract

Lencz T, Lambert C, DeRosse P, Burdick KE, Morgan TV, Kane JM, Kucherlapati R,Malhotra AK (2007). Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia. Proc Natl Acad Sci U S A. 104(50):19942-7. Abstract

In my mind, the study of CNVs in autism (and likely soon in schizophrenia/bipolar disorder, which are a little behind) is likely to put biological meat on the bones of illness etiology and finally lay to rest the annoyingly persistent taunts that genetics hasn’t delivered on its promises for psychiatric illness.

I don’t think it’s necessary at the moment to wring our hands at any inconsistencies between the Walsh et al. and previous studies of CNV in schizophrenia (e.g., Kirov et al., 2008). There are a number of factors which I think are going to influence the frequency, type, and identity of CNVs found in any given study.

1. CNVs are going to be found at the rare/penetrant/familial end of the disease allele spectrum—in direct contrast to the common risk variants which are the targets of recent GWAS studies. In the short term, we are likely to see a large number of different CNVs identified. The nature of this spectrum, however, is that there will be more common pathological CNVs which should be replicated sooner—NRXN1, APBA2 (Kirov et al., 2008), CNTNAP2...  Read more

In my mind, the study of CNVs in autism (and likely soon in schizophrenia/bipolar disorder, which are a little behind) is likely to put biological meat on the bones of illness etiology and finally lay to rest the annoyingly persistent taunts that genetics hasn’t delivered on its promises for psychiatric illness.

I don’t think it’s necessary at the moment to wring our hands at any inconsistencies between the Walsh et al. and previous studies of CNV in schizophrenia (e.g., Kirov et al., 2008). There are a number of factors which I think are going to influence the frequency, type, and identity of CNVs found in any given study.

1. CNVs are going to be found at the rare/penetrant/familial end of the disease allele spectrum—in direct contrast to the common risk variants which are the targets of recent GWAS studies. In the short term, we are likely to see a large number of different CNVs identified. The nature of this spectrum, however, is that there will be more common pathological CNVs which should be replicated sooner—NRXN1, APBA2 (Kirov et al., 2008), CNTNAP2 (Friedman et al., 2008)—and may be among some of these “low hanging fruit.” For the rarer CNVs, proving a pathological role is going to be a real headache. Large studies or meta-analyses are never going to yield significant p-values for rare CNVs which, nevertheless, may be the chief causes of illness for those few individuals who carry them. Showing clear segregation with illness in families is likely to be the only means to judge their role. However, we must not expect a pure cause-and-effect role for all CNVs: even in the Scottish t(1;11) family disrupting the DISC1 gene, there are several instances of healthy carriers.

2. Sample selection is also likely to be critical. In the Kirov paper, samples were chosen to represent sporadic and family history-positive cases equally. In the Walsh paper, samples were taken either from hospital patients (the majority) or a cohort of childhood onset schizophrenia. Detailed evidence for family history on a case-by-case basis was not given but appeared far stronger in the childhood onset cases. CNVs appeared to be more prevalent, and as expected, more familial, in the latter cohort. A greater frequency was also observed in the Kirov study familial subset.

3. Inclusion criteria are likely to be important—particularly in the more sporadic cases without family history. This is because CNVs found in this group may be commoner and less penetrant—they will be more frequent in cases than in controls but not exclusively found in cases. Any strategy, such as that used in the Kirov paper, which discounts a CNV based on its presence—even singly—in the control group is likely to bias against this class.

4. Technical issues. Certainly, the coverage/sensitivity of the method of choice for the “event discovery” stage is going to influence the minimum size of CNV detectable. However, a more detailed coverage often comes with a greater false-positive rate. Technique choice may also have more general issues. In both of the papers, the primary detection method is based on hybridization of case and pooled control genomes prior to detection on a chip. Thus, a more continuously distributed output may result—and the extra round of hybridization might bias against certain sequences. More direct primary approaches such as Illumina arrays or a second-hand analysis of SNP genotyping arrays may provide a more discrete copy number output, but these, too, can suffer from interpretational issues.

The other major implication of these and other CNV studies is the observation that certain genes “ignore” traditional disease boundaries. For example, NRXN1 CNVs have now been identified in autism and schizophrenia, and CNTNAP2 translocations/CNVs have been described in autism, Gilles de la Tourette syndrome, and schizophrenia/epilepsy. This mirrors the observation of common haplotypes altering risk across the schizophrenia-bipolar divide in numerous association studies. It might be the case that these more promiscuous genes are likely to be involved in more fundamental CNS processes or developmental stages—with the precise phenotypic outcome being defined by other variants or environment. The presence of mental retardation comorbid with psychiatric diagnoses in a number of CNV studies suggests that this might be the case. I look forward to the Venn diagrams of the future which show us the shared neuropsychiatric and disease-specific genes/gene alleles. It will also be interesting to see if the large deletions/duplications involving numerous genes give rise to more severe, familial, and diagnostically more defined syndromes or, alternatively, a more diffuse phenotype. Certainly, it has not been easy to dissect out individual gene contributions to phenotype in VCFS or the minimal region in Down syndrome.

References:

Friedman JI, Vrijenhoek T, Markx S, Janssen IM, van der Vliet WA, Faas BH, Knoers NV, Cahn W, Kahn RS, Edelmann L, Davis KL, Silverman JM, Brunner HG, van Kessel AG, Wijmenga C, Ophoff RA, Veltman JA. CNTNAP2 gene dosage variation is associated with schizophrenia and epilepsy. Mol Psychiatry. 2008 Mar 1;13(3):261-6. Abstract

We agree with the comments of Weinberger, Lencz and Malhotra, and Pickard, and the question raised by Honer about the extent to which the association may be more to mental retardation than schizophrenia. These new studies of copy number variation represent important advances, but need to be interpreted carefully.

We are now getting two different kinds of data on schizophrenia, which can be seen as two opposite poles. The first is from association studies with common variants, in which large numbers of people are required to see significance, and the strengths of the associations are quite modest. These kinds of vulnerability factors would presumably contribute a very modest increase in risk, and many taken together would cause the disease. By contrast, the “private” mutations, as identified by the Sebat study, could potentially be completely causative, but because they are present in only single individuals or very small numbers of individuals, it is difficult to be certain of causality. Furthermore, since some of them in the early-onset schizophrenia patients were...  Read more

We agree with the comments of Weinberger, Lencz and Malhotra, and Pickard, and the question raised by Honer about the extent to which the association may be more to mental retardation than schizophrenia. These new studies of copy number variation represent important advances, but need to be interpreted carefully.

We are now getting two different kinds of data on schizophrenia, which can be seen as two opposite poles. The first is from association studies with common variants, in which large numbers of people are required to see significance, and the strengths of the associations are quite modest. These kinds of vulnerability factors would presumably contribute a very modest increase in risk, and many taken together would cause the disease. By contrast, the “private” mutations, as identified by the Sebat study, could potentially be completely causative, but because they are present in only single individuals or very small numbers of individuals, it is difficult to be certain of causality. Furthermore, since some of them in the early-onset schizophrenia patients were present in unaffected parents, one might have to assume the contribution of a common variant vulnerability (from the other parent) as well.

If a substantial number of the private structural mutations are causal, then one might expect to have seen multiple small Mendelian families segregating a structural variant. The situation would then be reminiscent of the autosomal dominant spinocerebellar ataxis, in which mutations (currently about 30 identified loci) in multiple different genes result in similar clinical syndromes. The existence of many small Mendelian families would be less likely if either 1) structural variants that cause schizophrenia nearly always abolish fertility, or 2) some of the SVs detected by Walsh et al. are risk factors, but are usually not sufficient to cause disease. The latter seems more likely.

We think these two poles highlight the continued importance of segregation studies, as have been used for the DISC1 translocation. In order to validate these very rare “private” copy number variations, we believe that it would be important to look for sequence variations in the same genes in large numbers of schizophrenia and control subjects, and ideally to do so in family studies.

One very exciting result of the new copy number studies is the implication of whole pathways rather than just single genes. This highlights the importance of a better understanding of pathogenesis. The study of candidate pathways should help facilitate better pathogenic understanding, which should result in better biomarkers and potentially improve classification and treatment. In genetic studies, development of pathway analysis will be fruitful. Convergent evidence can come from studies of pathogenesis in cell and animal models, but this will need to be interpreted with caution, as it is possible to make a plausible story for so many different pathways (Ross et al., 2006). The genetic evidence will remain critical.

References:

Ross CA, Margolis RL, Reading SA, Pletnikov M, Coyle JT. Neurobiology of schizophrenia. Neuron. 2006 Oct 5;52(1):139-53. Abstract

The idea that a proportion of schizophrenia is associated with rare chromosomal abnormalities has been around for some time, but it has been difficult to be sure whether such events are pathogenic given that most are rare. Two instances where a pathogenic role seems likely are first, the balanced ch1:11 translocation that breaks DISC1, where pathogenesis seems likely due to co-segregation with disease in a large family, and second, deletion of chromosome 22q11, which is sufficiently common for rates of psychosis to be compared with that in the general population. This association came to light because of the recognizable physical phenotype associated with deletion of 22q11, and the field has been waiting for the availability of genome-wide detection methods that would allow the identification of other sub-microscopic chromosomal abnormalities that might be involved, but whose presence is not predicted by non-psychiatric syndromal features. This technology is now upon us in the form of various microarray-based methods, and we can expect a slew of studies addressing this...  Read more

The idea that a proportion of schizophrenia is associated with rare chromosomal abnormalities has been around for some time, but it has been difficult to be sure whether such events are pathogenic given that most are rare. Two instances where a pathogenic role seems likely are first, the balanced ch1:11 translocation that breaks DISC1, where pathogenesis seems likely due to co-segregation with disease in a large family, and second, deletion of chromosome 22q11, which is sufficiently common for rates of psychosis to be compared with that in the general population. This association came to light because of the recognizable physical phenotype associated with deletion of 22q11, and the field has been waiting for the availability of genome-wide detection methods that would allow the identification of other sub-microscopic chromosomal abnormalities that might be involved, but whose presence is not predicted by non-psychiatric syndromal features. This technology is now upon us in the form of various microarray-based methods, and we can expect a slew of studies addressing this hypothesis in the coming months.

Structural chromosomal abnormalities can take a variety of forms, in particular, deletions, duplication, inversions, and translocations. Generally speaking, these can disrupt gene function by, in the case of deletions, insertions and unbalanced translocations, altering the copy number of individual genes. These are sometimes called copy number variations (CNVs). Structural chromosomal abnormalities can also disrupt a gene sequence, and such disruptions include premature truncation, internal deletion, gene fusion, or disruption of regulatory or promoter elements.

It is, however, worth pointing out that structural chromosomal variation in the genome is common—it has been estimated that any two individuals on average differ in copy number by a total of around 6 Mb, and that the frequency of individual duplications or deletions can range from common through rare to unique, much in the same way as other DNA variation. Also similar to other DNA variation, many structural variants, indeed almost certainly most, may have no phenotypic effects (and this includes those that span genes), while others may be disastrous for fetal viability. Walsh and colleagues have focused upon rare structural variants, and by rare they mean events that might be specific to single cases or families. For this reason, they specifically targeted CNVs that had not previously been described in the published literature or in the Database of Genomic Variants. The reasonable assumption was made that this would enrich for CNVs that are highly penetrant for the disorder. Indeed, Walsh et al. favor the hypothesis that genetic susceptibility to schizophrenia is conferred not by relatively common disease alleles but by a large number of individually rare alleles of high penetrance, including structural variants. As we have argued elsewhere (Craddock et al., 2007), it seems entirely plausible that schizophrenia reflects a spectrum of alleles of varying effect sizes including common alleles of small effect and rare alleles of larger effect, but data from genetic epidemiology do not support the hypothesis that the majority of the disorder reflects rare alleles of large effect.

Walsh et al. found that individuals with schizophrenia were >threefold more likely than controls to harbor rare CNVs that impacted on genes, but in contrast, found no significant difference in the proportions of cases and controls carrying rare mutations that did not impact upon genes. They also found a similar excess of rare structural variants that deleted or duplicated one or more genes in an independent series of cases and controls, using a cohort with childhood onset schizophrenia (COS).

The results of the Walsh study are important, and clearly suggest a role for structural variation in the etiology of schizophrenia. There are, however, a number of caveats and issues to consider. First, it would be unwise on the basis of that study to speculate on the likely contribution of rare variants to schizophrenia as a whole. It is likely correct that, due to selection pressures, highly penetrant alleles for disorders (like schizophrenia) that impair reproductive fitness are more likely to be of low frequency than they are to be common, but this does not imply that the converse is true. That is, one cannot assume that the penetrance of low frequency alleles is more likely to be high than low. Thus, and as pointed out by Walsh et al., it is not possible to know which or how many of the unique events observed in their study are individually pathogenic. Whether individual loci contribute to pathogenesis (and their penetrances) is, as we have seen, hard to establish. Estimating penetrance by association will require accurate measurement of frequencies in case and control populations, which for rare alleles, will have to be very large. Alternatively, more biased estimates of penetrance can be estimated from the degree of co-segregation with disease in highly multiplex pedigrees, but these are themselves fairly rare in schizophrenia, and pedigrees segregating any given rare CNV obviously even more so.

As Weinberger notes, the case for high penetrance (at the level of being sufficient to cause the disorder) is also undermined by their data from COS, where the majority of variants were inherited from unaffected parents. This accords well with the observation that 22q11DS, whilst conferring a high risk of schizophrenia, is still only associated with psychosis in ~30 percent of cases. It also accords well with the relative rarity of pedigrees segregating schizophrenia in a clearly Mendelian fashion, though the association of CNVs with severe illness of early onset might be expected to reduce the probability of transmission.

Third, there are questions about the generality of the findings. Cases in the case control series were ascertained in a way that enriched for severity and chronicity. Perhaps more importantly, the CNVs were greatly overrepresented in people with low IQ. Thus, one-third of all the potentially pathogenic CNVs in the case control series were seen in the tenth of the sample with IQ less than 80. The association between structural variants and low IQ is well known, as is the association between low IQ and psychotic symptoms, and it seems plausible to assume that forms of schizophrenia accompanied by mental retardation (MR) are likely to be enriched for this type of pathogenesis. The question that arises is whether the CNVs in such cases act simply by influencing IQ, which in turn has a non-specific effect on increasing risk of schizophrenia, or whether there are specific CNVs for MR plus schizophrenia, and some which may indeed increase risk of schizophrenia independent of IQ. In the case of 22q11 deletion, risk of schizophrenia does not seem to be dependent on risk of MR, but more work is needed to establish that this applies more generally.

Another reason to caution about the generality of the effect is that Walsh et al. found that cases with onset of psychotic symptoms at age 18 or younger were particularly enriched for CNVs, being greater than fourfold more likely than controls to harbor such variants. There did remain an excess of CNVs in cases with adult onset, supporting a more general contribution, although it should be noted that even in this group with severe disorder, this excess was not statistically significant (Fisher’s exact test, p = 0.17, 2-tailed, our calculation). The issue of age of onset clearly impacts upon assessing the overall contribution CNVs may make upon psychosis, since onset before 18, while not rare, is also not typical. A particular contribution of CNVs to early onset also appears supported by the second series studied, which had COS. However, this is a particularly unusual form of schizophrenia which is already known to have high rates of chromosomal abnormalities. Future studies of more typical samples will doubtless bear upon these issues.

Even allowing for the fact that many more CNVs may be detected as resolution of the methodology improves, the above considerations suggest it is premature to conclude a substantial proportion of cases of schizophrenia can be attributed to rare, highly penetrant CNVs. Nevertheless, even if it turns out that only a small fraction of the disorder is attributable to CNVs, as seen for other rare contributors to the disorder (e.g., DISC1 translocation), such uncommon events offer enormous opportunities for advancing our knowledge of schizophrenia pathogenesis.

References:

Craddock N, O'Donovan MC, Owen MJ. Phenotypic and genetic complexity of psychosis. Invited commentary on ... Schizophrenia: a common disease caused by multiple rare alleles.Br J Psychiatry. 2007 90:200-3. Abstract

Walsh et al. claim that rare and severe chromosomal structural variants (SVs) (i.e., not described in the literature or in the specialized databases as of November 2007) are highly penetrant events each explaining a few, if not singular, cases of schizophrenia.

However, their definition of rareness is questionable. Indeed, it is unclear why SVs that are rare (<1 percent) but previously described should be omitted from their analysis. In addition, contrary to their own definition of rareness, the authors included in the COS sample several SVs that have been previously mentioned in the literature (e.g. “115 kb deletion on chromosome 2p16.3 disrupting NRXN1”). Furthermore, some of these SVs (entire Y chromosome duplication) are certainly not rare (by the authors’ definition), nor highly penetrant with regard to psychosis (Price et al., 1967). Finally, as their definition of rareness depends on a specific date, the results of this study will change over time.

As to the assessment of...  Read more

Walsh et al. claim that rare and severe chromosomal structural variants (SVs) (i.e., not described in the literature or in the specialized databases as of November 2007) are highly penetrant events each explaining a few, if not singular, cases of schizophrenia.

However, their definition of rareness is questionable. Indeed, it is unclear why SVs that are rare (<1 percent) but previously described should be omitted from their analysis. In addition, contrary to their own definition of rareness, the authors included in the COS sample several SVs that have been previously mentioned in the literature (e.g. “115 kb deletion on chromosome 2p16.3 disrupting NRXN1”). Furthermore, some of these SVs (entire Y chromosome duplication) are certainly not rare (by the authors’ definition), nor highly penetrant with regard to psychosis (Price et al., 1967). Finally, as their definition of rareness depends on a specific date, the results of this study will change over time.

As to the assessment of severity, it can equally be concluded from table 2 and using their statistical approach that "patients with schizophrenia are significantly more likely to harbor rare structural variants (6/150) that do not disrupt any gene compared to controls(2/268) (p = 0.03)", thus contradicting their claim. In fact, had they used criteria in the literature (Lee et al., 2007; (Brewer et al., 1999) (i.e., deletion SVs are more likely than duplications to be pathogenic) and appropriate statistical contrasts, deletions are significantly (p = 0.02) less frequent in patients (5/23) than in controls (9/13) who have SVs. In addition, the assumption of high penetrance is questionable given the high level (13 percent) of non-transmitted SVs in parents of COS patients. Is the rate of psychosis proportionately high in the parents? From the data presented, we know that only 2/27 SVs in COS patients are de novo and that “some” SVs are transmitted. Adding this undetermined number of transmitted SVs to the reported non-transmitted SVs will lead to an even larger proportion of parents carrying SVs. Disclosing the inheritance status of SVs in COS patients along with information on diagnoses in parents from this “rigorously characterised cohort,” represents a major criterion for assessing the risk associated with these SVs.

Consequently, it appears that the argument of rareness is rather idiosyncratic and contains inconsistencies, and the one of severity is very open to interpretation. Most importantly, it should be emphasized that amalgamated gene effects at the population level do not allow one to conclude that any single SV actually contributes to schizophrenia in an individual. Thus it is unclear how this study of grouped events differs from the thousands of controversial and underpowered association studies of single genes.

References:

Price WH, Whatmore PB. Behaviour Disorders and Pattern of Crime among XYY males Identified at a Maximum Security Hospital. Brit Med J 1967;1:533-6.

Lee C, Iafrate AJ, Brothman AR. Copy number variations and clinical cytogenetic diagnosis of constitutional disorders. Nat Genet 2007 July;39(7 Suppl):S48-S54.

Brewer C, Holloway S, Zawalnyski P, Schinzel A, FitzPatrick D. A chromosomal duplication map of malformations: regions of suspected haplo- and triplolethality--and tolerance of segmental aneuploidy--in humans. Am J Hum Genet 1999 June;64(6):1702-8.

The three companion papers published in Nature provide important new evidence for a role of the MHC complex and common variation across the genome in risk for schizophrenia. These studies have exploited the availability of comprehensive genotyping technologies, coupled with large cohorts of cases and controls, to identify candidate loci for disease susceptibility.

A notable feature of these papers is the clear willingness of each of the groups to share its data, and to provide overlapping presentations of each others’ results. The combination of datasets permitted the statistical significance of the MHC findings to emerge, thereby increasing confidence in results. The implication that immune processes may interact with genetic risk to influence schizophrenia risk is consistent with several lines of evidence, including our own small GWAS study (Lencz et al., 2007) implicating cytokine receptors in schizophrenia susceptibility.

Perhaps most intriguing is the finding from the International Schizophrenia Consortium demonstrating that a “score” test—combining...  Read more

The three companion papers published in Nature provide important new evidence for a role of the MHC complex and common variation across the genome in risk for schizophrenia. These studies have exploited the availability of comprehensive genotyping technologies, coupled with large cohorts of cases and controls, to identify candidate loci for disease susceptibility.

A notable feature of these papers is the clear willingness of each of the groups to share its data, and to provide overlapping presentations of each others’ results. The combination of datasets permitted the statistical significance of the MHC findings to emerge, thereby increasing confidence in results. The implication that immune processes may interact with genetic risk to influence schizophrenia risk is consistent with several lines of evidence, including our own small GWAS study (Lencz et al., 2007) implicating cytokine receptors in schizophrenia susceptibility.

Perhaps most intriguing is the finding from the International Schizophrenia Consortium demonstrating that a “score” test—combining information from many thousands of common variants—can reliably differentiate patients and controls across multiple psychiatric cohorts. These results indicate that hundreds, if not thousands, of genes of small effect may contribute to schizophrenia risk. Moreover, these same genes were shown to contribute to bipolar risk (but not risk for non-psychiatric disorders such as diabetes).

Much more work remains to be done in psychiatric genetics. While the score test accounted for about 3 percent of the observed case-control variance, statistical modeling suggested that common variation could explain as much as one-third or more of the total risk. Nevertheless, there remains a substantial proportion of genetic “dark matter” (unexplained variance), given the high heritability of a disorder such as schizophrenia. Complementary approaches are needed to further parse the source of the common genetic variance, as well as to identify rare yet highly penetrant mutations. Additional techniques, such as pharmacogenetic studies and endophenotypic research, will help to explicate the functionality and clinical significance of observed risk alleles.

The three Nature papers reporting GWAS results in a large sample of cases of schizophrenia and controls from around Western Europe and the U.S. are decidedly disappointing to those expecting this strategy to yield conclusive evidence of common variants predicting risk for schizophrenia. Why has this extensive and very costly effort not produced more impressive results? There are likely to be many explanations for this, involving the usual refrains about clinical and genetic heterogeneity, diagnostic imprecision, and technical limitations in the SNP chips. But the likely, more fundamental problem in psychiatric genetics involves the biologic complexity of the conditions themselves, which renders them especially poorly suited to the standard GWAS strategy. The GWA analytic model assumes fixed, predictable relationships between genetic risk and illness, but simple relationships between genetic risk and complex pathophysiological mechanisms are unlikely. Many biologic functions show non-linear relationships, and depending on the biologic context, more of a potential pathogenic...  Read more

The three Nature papers reporting GWAS results in a large sample of cases of schizophrenia and controls from around Western Europe and the U.S. are decidedly disappointing to those expecting this strategy to yield conclusive evidence of common variants predicting risk for schizophrenia. Why has this extensive and very costly effort not produced more impressive results? There are likely to be many explanations for this, involving the usual refrains about clinical and genetic heterogeneity, diagnostic imprecision, and technical limitations in the SNP chips. But the likely, more fundamental problem in psychiatric genetics involves the biologic complexity of the conditions themselves, which renders them especially poorly suited to the standard GWAS strategy. The GWA analytic model assumes fixed, predictable relationships between genetic risk and illness, but simple relationships between genetic risk and complex pathophysiological mechanisms are unlikely. Many biologic functions show non-linear relationships, and depending on the biologic context, more of a potential pathogenic factor, can make things worse or it can make them better. Studies of complex phenotypes in model systems illustrate that individual gene effects depend upon non-linear interactions with other genes (Toma et al., 2002; Shaoa et al, 2008). Similar observations are beginning to emerge in human disorders, e.g., in risk for cancer (Lo et al., 2008) and depression (Pezawas et al., 2008).

The GWA approach also assumes that diagnosis represents a unitary biological entity, but most clinical diagnoses are syndromal and biologically heterogeneous, and this is especially true in psychiatric disorders. Type 2 diabetes is the clinical expression of changes in multiple physiologic processes, including in pancreatic function, in adipose cell function, as well as in eating behavior. Likewise, hypertension results from abnormalities in many biologic processes (e.g., vascular reactivity, kidney function, CNS control of blood pressure, metabolic factors, sodium regulation), and even a large effect on any specific process within a subset of individuals will seem small when measured in large unrelated samples (Newton-Cheh et al., 2009). In the case of the cognitive and emotional problems associated with psychiatric disorders, the biologic pathways to clinical manifestations are probably much more heterogeneous. While the results of GWAS in disorders like type 2 diabetes and hypertension have been more informative than in the schizophrenia results so far, they, too, have been disappointing, considering all the fanfare about their expectations. But given the pathophysiologic realities of diabetes, hypertension, or psychiatric disorders, how could the effect of any common genetic variant acting on only one of the diverse pathophysiological mechanisms implicated in these disorders be anything other than small when measured in large pathophysiologically heterogeneous populations? Other approaches, e.g., family studies, studies of smaller but much better characterized samples, and studies of genetic interactions in these samples, will be necessary to understand the variable genetic architectures of such biologically complex and heterogeneous disorders.

References:

Toma DP, White KP, Hirsch J and Greenspan RJ: Identification of genes involved in Drosophila melanogaster geotaxis, a complex behavioral trait. Nature Genetics 2002; 31: 349-353. Abstract

Shaoa H, Burragea LC, Sinasac DS et al : Genetic architecture of complex traits: Large phenotypic effects and pervasive epistasis. PNAS 2008 105: 19910–19914. Abstract

Lo S-W, Chernoff H, Cong L, Ding Y, and Zheng T: Discovering interactions among BRCA1 and other candidate genes associated with sporadic breast cancer. PNAS 2008; 105: 12387–12392. Abstract

Pezawas L, Meyer-Lindenberg A, Goldman AL, et al.: Biologic epistasis between BDNF and SLC6A4 and implications for depression. Mol Psychiatry 2008;13:709-716. Abstract

Newton-Cheh C, Larson MG, Vasan RS: Association of common variants in NPPA and NPPB with circulating natriuretic peptides and blood pressure. Nat Gen 2009; 41: 348-353. Abstract

The synthesis and extraction of the essence of the 3 Nature papers by Heimer and Farley represents science reporting at its best. Completion of the task while the ink was still wet shows that SRF is indeed in good hands. Congratulations on being concise, even-handed, non-judgmental, and challenging under the pressure of time.

View all comments by Irving Gottesman

Schizophrenia Genetics: Glass Half Full?
While it may be disappointing that the GWAS described above did not identify more genes, they nevertheless represent a landmark in psychiatric genetics and suggest a dual approach for the future: continued large-scale genetic association studies along with alternative genetic approaches leading to the discovery of new genetic etiologies, and more functional investigations to identify pathways of pathogenesis—which may themselves suggest new etiologies.

The consistent identification of an association with the MHC locus reinforces (without proving, as pointed out in the SRF news story) long-standing interest in the involvement of infectious or immune factors in schizophrenia pathogenesis (Yolken and Torrey, 2008). Epidemiologic and neuropathological studies that include patients selected for the presence or absence of immunologic genetic risk variants could potentially clarify etiology; cell and mouse model studies could clarify pathogenesis (  Read more

Schizophrenia Genetics: Glass Half Full?
While it may be disappointing that the GWAS described above did not identify more genes, they nevertheless represent a landmark in psychiatric genetics and suggest a dual approach for the future: continued large-scale genetic association studies along with alternative genetic approaches leading to the discovery of new genetic etiologies, and more functional investigations to identify pathways of pathogenesis—which may themselves suggest new etiologies.

The consistent identification of an association with the MHC locus reinforces (without proving, as pointed out in the SRF news story) long-standing interest in the involvement of infectious or immune factors in schizophrenia pathogenesis (Yolken and Torrey, 2008). Epidemiologic and neuropathological studies that include patients selected for the presence or absence of immunologic genetic risk variants could potentially clarify etiology; cell and mouse model studies could clarify pathogenesis (Ayhan et al., 2009). It is striking that a major genetic finding in schizophrenia serves to reinforce the concept of environmental risk factors.

The two specific genes identified by the SGENE consortium, NRGN and TCF4, offer intriguing new leads into schizophrenia. This should foster a number of further genetic and neurobiological studies. Deep resequencing (and CNV analysis) can detect rare causative mutations, as exemplified by TCF4 mutations leading to Pitt-Hopkins syndrome. Neurogranin already has clear connections to interesting signaling pathways related to glutamate transmission. A hope is that further studies of both gene products and their interactions will identify pathogenic pathways.

The ISC used common genetic variants “en masse” to generate a “polygene score” from discovery samples of patients; that score was able to predict case status in test populations. The success of this approach provides very strong evidence that a portion of schizophrenia risk status is attributable to common genetic variants acting in concert and that schizophrenia shares genetic factors with bipolar disorder, but not with other diseases. This analysis has multiple practical implications for the direction of research. First, since polygenic factors explain only a portion of the genetic risk, the search for other genetic factors—rare mutations of major effect detectable by deep sequencing, CNVs, variations in tandem repeats (Bruce et al., 2009, in press), and other genomic lesions—takes on new importance. Second, a meaningful integration of polygenic factors in a way that facilitates understanding of schizophrenia pathogenesis and the discovery of therapeutic targets will require identification of relevant pathways. Examination of patient-derived material—such as neurons differentiated from induced pluripotent stem cells taken from well-characterized, patient populations—may be of great value.

The remarkable overlap between the genetic factors of schizophrenia and bipolar disorder suggests the need for further and more inclusive clinical studies—not just of “endophenotypes,” but also of the phenotypes themselves, together, rather than in isolation (Potash and Bienvenu, 2009). For instance, it is only within the past few years that the importance of cognitive dysfunction in schizophrenia has been appreciated. Cognition in bipolar disorder is even less well studied.

How much is really known about the longitudinal course of both disorders? Do genetic factors predict disease outcome? It is only recently that studies have focused intensively on the early course of schizophrenia and its prodrome. Much more is still to be learned, and even less is known about bipolar disorder. In conjunction with this greater understanding of clinical phenotype, it will clearly be necessary to refine the approach to phenotype by establishing the biological framework for these diseases and by establishing biomarkers, such as disruption in white matter (Karlsgodt et al., 2009) or abnormalities in functional networks (Demirci et al., 2009), that cut across current nosological categories. In turn, longitudinal study of clinical, imaging, and functional outcomes of schizophrenia and bipolar disorders should facilitate both focused candidate genetic studies and GWAS of large populations.

References:

Yolken RH, Torrey EF. Are some cases of psychosis caused by microbial agents? A review of the evidence. Mol Psychiatry. 2008 May;13(5):470-9. Abstract

Ayhan Y, Sawa A, Ross CA, Pletnikov MV. Animal models of gene-environment interactions in schizophrenia. Behav Brain Res. 2009 Apr 18. Abstract

Potash JB, Bienvenu OJ. Neuropsychiatric disorders: Shared genetics of bipolar disorder and schizophrenia. Nat Rev Neurol. 2009 Jun;5(6):299-300. Abstract

Karlsgodt KH, Niendam TA, Bearden CE, Cannon TD. White matter integrity and prediction of social and role functioning in subjects at ultra-high risk for psychosis. Biol Psychiatry. 2009 May 6. Epub ahead of print. Abstract

Demirci O, Stevens MC, Andreasen NC, Michael A, Liu J, White T, Pearlson GD, Clark VP, Calhoun VD. Investigation of relationships between fMRI brain networks in the spectral domain using ICA and Granger causality reveals distinct differences between schizophrenia patients and healthy controls. Neuroimage. 2009 Jun;46(2):419-31. Abstract

Bruce HA, Sachs NA, Rudnicki DD, Lin SG, Willour VL, Cowell JK, Conroy J, McQuaid D, Rossi M, Gaile DP, Nowak NJ, Holmes SE, Sklar P, Ross CA, DeLisi LE, Margolis RL. Long tandem repeats as a form of genomic copy number variation: structure and length polymorphism of a chromosome 5p repeat in control and schizophrenia populations. Psychiatric Genetics, in press.

This report is unnecessarily negative, from my point of view. The three studies show not only that GWAS can identify susceptibility alleles for schizophrenia, but that the majority of risk comes from common variants of small effect. These can be found, but as in other complex traits and diseases, such as obesity and height, considerable power is needed, because effect sizes are small, meaning greater samples sizes. This approach works: there are now almost 60 variants influencing height (Hirschhorn et al., 2009; Soranzo et al., 2009; Sovio et al., 2009). Furthermore, the genes identified so far from both traditional mapping, CNV analysis and GWAS, point to two biological pathways, the integrity of the synapse (neurexin 1, neurogranin, etc.) and the wnt/GSK3β signaling pathway (DISC1, TCF4, etc.), which is involved in functions such as neurogenesis in the brain. The identification of disease pathways for schizophrenia has major...  Read more

This report is unnecessarily negative, from my point of view. The three studies show not only that GWAS can identify susceptibility alleles for schizophrenia, but that the majority of risk comes from common variants of small effect. These can be found, but as in other complex traits and diseases, such as obesity and height, considerable power is needed, because effect sizes are small, meaning greater samples sizes. This approach works: there are now almost 60 variants influencing height (Hirschhorn et al., 2009; Soranzo et al., 2009; Sovio et al., 2009). Furthermore, the genes identified so far from both traditional mapping, CNV analysis and GWAS, point to two biological pathways, the integrity of the synapse (neurexin 1, neurogranin, etc.) and the wnt/GSK3β signaling pathway (DISC1, TCF4, etc.), which is involved in functions such as neurogenesis in the brain. The identification of disease pathways for schizophrenia has major implications and should not be underestimated. It would be daft to lose nerve now and turn away from GWAS just as they are bearing fruit.

I would like to correct/expand on my comments to Peter Farley, to say that while statistical significance for some markers may be reached sooner, significance for many of the hundreds if not thousands of common schizophrenia susceptibility alleles of small effect might not emerge until samples of 100,000 cases and more than 100,000 controls have been collected. Another point is that organizations such the Wellcome Trust are already assembling case samples for schizophrenia as well as control samples.

Also, I would like to clarify that I believe the remainder of genetic variation, after common variation has been taken into account, will come from some combination of rare CNVs, other rare variants such as SNPs and other types of genetic marker such as variable number of tandem repeats (VNTRs) and of course the much neglected contribution from gene-environment interactions, in which main genetic effects may be obscured.

References:

Hirschhorn JN, Lettre G. Progress in genome-wide association studies of human height. Horm Res. 2009 Apr 1 ; 71 Suppl 2():5-13. Abstract

Soranzo N, Rivadeneira F, Chinappen-Horsley U, Malkina I, Richards JB, Hammond N, Stolk L, Nica A, Inouye M, Hofman A, Stephens J, Wheeler E, Arp P, Gwilliam R, Jhamai PM, Potter S, Chaney A, Ghori MJ, Ravindrarajah R, Ermakov S, Estrada K, Pols HA, Williams FM, McArdle WL, van Meurs JB, Loos RJ, Dermitzakis ET, Ahmadi KR, Hart DJ, Ouwehand WH, Wareham NJ, Barroso I, Sandhu MS, Strachan DP, Livshits G, Spector TD, Uitterlinden AG, Deloukas P. Meta-analysis of genome-wide scans for human adult stature identifies novel Loci and associations with measures of skeletal frame size. PLoS Genet. 2009 Apr 1 ; 5(4):e1000445. Abstract

Sovio U, Bennett AJ, Millwood IY, Molitor J, O'Reilly PF, Timpson NJ, Kaakinen M, Laitinen J, Haukka J, Pillas D, Tzoulaki I, Molitor J, Hoggart C, Coin LJ, Whittaker J, Pouta A, Hartikainen AL, Freimer NB, Widen E, Peltonen L, Elliott P, McCarthy MI, Jarvelin MR. Genetic determinants of height growth assessed longitudinally from infancy to adulthood in the northern Finland birth cohort 1966. PLoS Genet. 2009 Mar 1 ; 5(3):e1000409. Abstract

Some commentators in their reflections take a rather negative view on what has been achieved through the application of GWAS technology to schizophrenia and psychiatric disorders more generally. We strongly disagree with this position. Below, we give examples of a number of statements that can be made about the aetiology of schizophrenia and bipolar disorder that could not be made at high levels of confidence even two years ago that are based upon evidence deriving from the application of GWAS.

1. We know with confidence that the role of rare copy number variants in schizophrenia is not limited to 22q11DS (VCFS) (reviewed recently in O’Donovan et al., 2009). We do not yet know how much of a contribution, but we know the identity of an increasing number of these. Most span multiple genes so it may prove problematic as it has in 22q11DS to identify the relevant molecular mechanisms. However, for one locus, the CNVs are limited to a single gene: Neurexin1 (Kirov et al., 2008;   Read more

Some commentators in their reflections take a rather negative view on what has been achieved through the application of GWAS technology to schizophrenia and psychiatric disorders more generally. We strongly disagree with this position. Below, we give examples of a number of statements that can be made about the aetiology of schizophrenia and bipolar disorder that could not be made at high levels of confidence even two years ago that are based upon evidence deriving from the application of GWAS.

1. We know with confidence that the role of rare copy number variants in schizophrenia is not limited to 22q11DS (VCFS) (reviewed recently in O’Donovan et al., 2009). We do not yet know how much of a contribution, but we know the identity of an increasing number of these. Most span multiple genes so it may prove problematic as it has in 22q11DS to identify the relevant molecular mechanisms. However, for one locus, the CNVs are limited to a single gene: Neurexin1 (Kirov et al., 2008; Rujescu et al., 2009). Genetic findings are merely the start of the journey to a deeper biological understanding, but no doubt many neurobiological researchers have already embarked on that journey in respect of neurexin1.

2. Although we have argued in this forum that some of the major pre-GWAS findings in schizophrenia very likely reflect true susceptibility genes (DTNBP1, NRG1, etc), we now have at least 4 novel loci where the evidence is more definitive (ZNF804A, MHC, NRGN, TCF4), (O’Donovan et al., 2008a; ISC, 2009; Shi et al., 2009; Stefansson et al., 2009) and two novel loci (Ferreira et al., 2008) in bipolar disorder (ANK3 and CACNA1C), at least one of which (CACNA1C) additionally confers risk of schizophrenia (Green et al., 2009). This is obviously a small part of the picture, but it is certainly better than no picture at all. These findings also offer a much more secure foundation than the earlier findings upon which to build follow up studies, for example brain imaging, and cognitive phenotypes (Esslinger et al., 2009), and even candidate gene studies. We would not regard the first convincing evidence that altered calcium channel function is a primary aetiological event in at least some forms of psychosis as a trivial gain in knowledge.

3. We can say with confidence that common alleles of small effect are abundant in schizophrenia, and that they contribute to a substantial part of the population risk (ISC, 2009). Identifying any one of these at stringent levels of statistical significance may be challenging in terms of sample sizes. As we have pointed out before, merging multiple datasets may indeed obscure some true associations because of sometimes unpredictable relationships between risk alleles and those assayed indirectly in GWAS studies (Moskvina and O’Donovan, 2007). Nevertheless, that many of the same alleles are overrepresented in multiple independent GWAS datasets from different countries (ISC, 2009) means that larger samples offer the prospect of identifying many more of these. This is not to say that large samples are the only approach; genetic heterogeneity may well underpin some aspects of clinical heterogeneity (Craddock et al., 2009a). However, with the exception of individual large pedigrees, it is not yet evident which type of clinical sample one should base a small scale study on. It should also be self-evident that the analysis of multiple samples, each with a different phenotypic structure, will pose major problems in respect of multiple testing and subsequent replication. Moreover, ascertaining special samples that represent putative subtypes of the clinical (and endophenotypic) spectrum of psychosis will first require large samples to be carefully assessed and the relevant subjects extracted. Subsequently, downstream, evaluation of specific genotype-phenotype relationships will require the remainder of the clinical population to be genotyped in a suitably powered way to show that those effects are specific to some clinical features of the disorder. Increasingly, it is ascertainment and assessment that dominate the cost of GWAS studies so it is not clear this approach will achieve any economies. We must also remember that after a GWAS study, there remains the opportunity to look in a controlled manner for relatively specific associations in the context of the heterogeneous clinical picture. For example we are aware of a number of papers in development that will exploit the sorts of multi-locus tests reported by the ISC to refine diagnostics, and no doubt many other applications of this will emerge in the next year or so.

Critics should bear in mind that the GWAS data are not just there for the ‘headline’ genome-wide findings, but that the data will be available to mine for years to come. The findings reported to date are based on only the simplest analyses.

4. If it were the case that the thousands of SNPs of small effect were randomly distributed across biological systems, none being of more relevance to pathophysiology than another, identifying them would probably be a pointless endeavour. However, there is no reason to believe this will be the case. We have recently shown that in bipolar disorder, the GWAS signals are enriched in particular biological pathways (Holmans et al., 2009) and we also published strong evidence for a relatively selective involvement of the GABAergic system in schizoaffective disorder (Craddock et al., 2009b). We are aware of an as-yet unpublished independent sample with similar findings. We would not regard the first convincing evidence that altered GABA function is a primary aetiological event in at least some forms of psychosis as a trivial gain in knowledge.

Incidentally it is a common misconception that the identification of risk alleles of small effect necessarily confers no useful insights into pathogenesis and possible drug targets. For example, common alleles in PPARG and KCNJ11 have been robustly shown to confer risk to Type 2 diabetes (T2D) but with odds ratios in the region of only 1.14 (of similar magnitude to those revealed by GWAS of schizophrenia). PPARG encodes the target for the thiazolidinedione class of drugs used to treat T2D. KCNJ11 encodes part of the target for another class of diabetes drug, the sulphonylureas (Prokopenko et al., 2008). Moreover, studies of novel associated variants identified in T2D GWAS in healthy, non-diabetic, populations have demonstrated that for most, the primary effect on T2D susceptibility is mediated through deleterious effects on insulin secretion, rather than insulin action (Prokopenko et al., 2008). Further examples of insights into the biology of common diseases coming from the identification of loci of small effect are the implication of the complement system in age-related macular degeneration and autophagy in Crohn’s disease (Hirschhorn, 2009). Already, efforts are under way to translate the new recognition of the role of autophagy in Crohn’s disease into new therapeutic leads (Hirschhorn, 2009). Of course many of the loci identified in GWAS implicate genes whose functions are as yet largely or completely unknown, and determining those functions is a prerequisite of translating those findings. Nevertheless, we believe that the greatest benefits that will accrue from the continued discovery of risk loci through GWAS will come from the assembly of that information into novel disease pathways leading to novel therapeutic targets.

5. We can say with confidence that bipolar disorder and schizophrenia substantially overlap, at least in terms of polygenic risk (ISC, 2009). As clinicians, we do not regard that knowledge as a trivial achievement.

6. We can say with confidence from studies of CNVs that schizophrenia and autism share at least some risk factors in common (O’Donovan et al., 2009). We believe that is also an important insight.

The above are major achievements in what we expect to be a long but accelerating process of picking apart the origins of schizophrenia and other psychotic disorders. We do not think that any other research discipline in psychiatry has done more to advance that knowledge in the past 100 years.

Like that other common familial diseases, the genetics of schizophrenia and bipolar disorder is a “mixed economy” of common alleles of small effect and rare alleles of large and small effects, including CNVs. Those who are concerned at the cost of collecting large samples for GWAS studies must bear in mind that the robust identification of both types of mutation will require similarly large samples; we will just have to get used to that fact if we want to make progress. Collecting samples like this may be expensive, but as clinicians, we know those costs are trivial compared with the human and economic costs of psychotic disorders.

The question of phenotype definition is one which we have repeatedly addressed (Craddock et al., 2009a). Unquestionably, if we knew the true pathophysiological basis of these disorders, we could do better. The fact is that we don’t. Given that, it must be extremely encouraging that despite the problems, risk loci can be robustly identified by GWAS using samples defined by current diagnostic criteria. Moreover, armed with GWAS data in these heterogeneous populations, additional risk genes can be identified through strategies aimed at refining the phenotype that are not constrained by the current dichotomous view of the functional psychoses. We have shown at least one way in which this might be achieved without imposing a further burden of multiple testing (Craddock et al., 2009b), and have little doubt that others will emerge. We agree that approaches to phenotyping that more directly index underlying pathophysiology are highly appealing, and will ultimately be necessary for understanding the mechanistic relationships between gene and disorder. However, the two cardinal assumptions upon which the use of endophenotypes is predicated for gene discovery are questionable. First, there is little good evidence that putative endophenotypes are substantially simpler genetically than “exophenotypes” (Flint and Munafo, 2007). Second, there is rarely good evidence that the current crop of popular putative endophenotypes lie on the disease pathway, indeed there seems to be substantial pleiotropy in the genetics of complex traits, psychosis included (Prokopenko et al., 2008; O’Donovan et al., 2008b).

Finally, we reiterate that while only small parts of the heritability of any complex disorder have been accounted for, large-scale genetic approaches have been extremely successful in studies of non-psychiatric diseases (Manolio et al., 2008) and have led to substantial advances in our understanding of pathogenesis, even for diseases like Crohn’s disease where there was already prior knowledge of pathogenesis from other research methods (Mathew, 2008).

Psychiatry starts from a situation in which there is no robust prior knowledge of pathogenesis for the major phenotypes. Recent findings suggest that mental illness may be the medical field that will actually benefit most over the coming years from application of these powerful molecular genetic technologies.

References:
Craddock N, O'Donovan MC, Owen MJ. (2009a) Psychosis Genetics: Modeling the Relationship between Schizophrenia, Bipolar Disorder, and Mixed (or "Schizoaffective") Psychoses. Schizophrenia Bulletin 35(3):482-490. Abstract

Craddock N, Jones L, Jones IR, Kirov G, Green EK, Grozeva D, Moskvina V, Nikolov I, Hamshere ML, Vukcevic D, Caesar S, Gordon-Smith K, Fraser C, Russell E, Norton N, Breen G, St Clair D, Collier DA, Young AH, Ferrier IN, Farmer A, McGuffin P, Holmans PA, Wellcome Trust Case Control Consortium (WTCCC), Donnelly P, Owen MJ, O’Donovan MC. Strong genetic evidence for a selective influence of GABAA receptors on a component of the bipolar disorder phenotype. Molecular Psychiatry advanced online publication 1 July 2008; doi:10.1038/mp.2008.66. (b) Abstract

Esslinger C, Walter H, Kirsch P, Erk S, Schnell K, Arnold C, Haddad L, Mier D, Opitz von Boberfeld C, Raab K, Witt SH, Rietschel M, Cichon S, Meyer-Lindenberg A. (2009) Neural mechanisms of a genome-wide supported psychosis variant. Science 324(5927):605. Abstract

Ferreira MAR, O’Donovan MC, Meng YA, Jones IR, Ruderfer DM, Jones L, Fan J, Kirov G, Perlis RH, Green EK, Smoller JW, Grozeva D, Stone J, Nikolov I, Chambert K, Hamshere ML, Nimgaonkar V, Moskvina V, Thase ME, Caesar S, Sachs GS, Franklin J, Gordon-Smith K, Ardlie KG, Gabriel SB, Fraser C, Blumenstiel B, Defelice M, Breen G, Gill M, Morris DW, Elkin A, Muir WJ, McGhee KA, Williamson R, MacIntyre DJ, McLean A, St Clair D, VanBeck M, Pereira A, Kandaswamy R, McQuillin A, Collier DA, Bass NJ, Young AH, Lawrence J, Ferrier IN, Anjorin A, Farmer A, Curtis D, Scolnick EM, McGuffin P, Daly MJ, Corvin AP, Holmans PA, Blackwood DH, Wellcome Trust Case Control Consortium (WTCCC), Gurling HM, Owen MJ, Purcell SM, Sklar P and Craddock NJ. (2008) Collaborative genome-wide association analysis of 10,596 individuals supports a role for Ankyrin-G (ANK3) and the alpha-1C subunit of the L-type voltage-gated calcium channel (CACNA1C) in bipolar disorder. Nature Genetics 40:1056-1058. Abstract

Flint J, Munafò MR. (2007) The endophenotype concept in psychiatric genetics. Psychological Medicine 37(2):163-180. Abstract

Green EK, Grozeva D, Jones I, Jones L, Kirov G, Caesar S, Gordon-Smith K, Fraser C, Forty L, Russell E, Hamshere ML, Moskvina V, Nikolov I, Farmer A, McGuffin P, Wellcome Trust Case Consortium, Holmans PA, Owen MJ, O’Donovan MC and Craddock N. (2009) Bipolar disorder risk allele at CACNA1C also confers risk to recurrent major depression and to schizophrenia. Molecular Psychiatry (in press).

Hirschhorn JN. (2009) Genomewide association studies--illuminating biologic pathways. New England Journal of Medicine 360(17):1699-1701. Abstract

Holmans P, Green E, Pahwa J, Ferreira M, Purcell S, Sklar P, Owen M, O’Donovan M, Craddock N. Gene ontology analysis of GWAS datasets provide insights into the biology of bipolar disorder. The American Journal of Human Genetics 2009 Jun 17 [Epub ahead of print]. International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009 Jul 1 [Epub ahead of print]. Abstract

Kirov G, Gumus D, Chen W, Norton N, Georgieva L, Sari M, O'Donovan MC, Erdogan F, Owen MJ, Ropers HH, Ullmann R. (2008) Comparative genome hybridization suggests a role for NRXN1 and APBA2 in schizophrenia. Human Molecular Genetics 17(3):458-465. Abstract

Manolio TA, Brooks LD, Collins FS. (2008) A HapMap harvest of insights into the genetics of common disease. Journal of Clinical Investigation 118(5):1590-1605. Abstract

Mathew CG. (2008) New links to the pathogenesis of Crohn disease provided by genome-wide association scans. Nature Review Genetics 9(1):9-14. Abstract

Moskvina V and O'Donovan MC. (2007) Detailed analysis of the relative power of direct and indirect association studies and the implications for their interpretation. Human Heredity 64(1):63-73. Abstract

O’Donovan MC, Kirov G, Owen MJ. (2008a) Phenotypic variations on the theme of CNVs. Nature Genetics 40(12):1392-1393. Abstract

O’Donovan MC, Craddock N, Norton N, Williams H, Peirce T, Moskvina V, Nikolov I, Hamshere M, Carroll L, Georgieva L, Dwyer S, Holmans P, Marchini JL, Spencer C, Howie B, Leung H-T, Hartmann AM, Möller H-J, Morris DW, Shi Y, Feng G, Hoffmann P, Propping P, Vasilescu C, Maier W, Rietschel M, Zammit S, Schumacher J, Quinn EM, Schulze TG, Williams NM, Giegling I, Iwata N, Ikeda M, Darvasi A, Shifman S, He L, Duan J, Sanders AR, Levinson DF, Gejman P, Molecular Genetics of Schizophrenia Collaboration , Cichon S, Nöthen MM, Gill M, Corvin A, Rujescu D, Kirov G, Owen MJ. (2008b) Identification of novel schizophrenia loci by genome-wide association and follow-up. Nature Genetics 40:1053-1055. Abstract

O’Donovan MC, Craddock N, Owen MJ. Genetics of psychosis; Insights from views across the genome. Human Genetics 2009 Jun 12 [Epub ahead of print]. Abstract

Prokopenko I, McCarthy MI, Lindgren CM. (2008) Type 2 diabetes: new genes, new understanding. Trends in Genetics 24(12):613-621. Abstract

Rujescu D, Ingason A, Cichon S, Pietiläinen OP, Barnes MR, Toulopoulou T, Picchioni M, Vassos E, Ettinger U, Bramon E, Murray R, Ruggeri M, Tosato S, Bonetto C, Steinberg S, Sigurdsson E, Sigmundsson T, Petursson H, Gylfason A, Olason PI, Hardarsson G, Jonsdottir GA, Gustafsson O, Fossdal R, Giegling I, Möller HJ, Hartmann AM, Hoffmann P, Crombie C, Fraser G, Walker N, Lonnqvist J, Suvisaari J, Tuulio-Henriksson A, Djurovic S, Melle I, Andreassen OA, Hansen T, Werge T, Kiemeney LA, Franke B, Veltman J, Buizer-Voskamp JE; GROUP Investigators, Sabatti C, Ophoff RA, Rietschel M, Nöthen MM, Stefansson K, Peltonen L, St Clair D, Stefansson H, Collier DA. (2009) Disruption of the neurexin 1 gene is associated with schizophrenia. Human Molecular Genetics 18(5):988-996. Abstract

Shi J, Levinson DF, Duan J, Sanders AR, Zheng Y, Pe'er I, Dudbridge F, Holmans PA, Whittemore AS, Mowry BJ, Olincy A, Amin F, Cloninger CR, Silverman JM, Buccola NG, Byerley WF, Black DW, Crowe RR, Oksenberg JR, Mirel DB, Kendler KS, Freedman R & Gejman PV. (2009) Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature doi:10.1038/nature08192. Abstract

Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D, Werge T, Pietiläinen OPH, Mors O, Mortensen PB, Sigurdsson E, Gustafsson O, Nyegaard M, Tuulio-Henriksson A, Ingason A, Hansen T, Suvisaari J, Lonnqvist J, Paunio T, Børglum AD, Hartmann A, Fink-Jensen A, Nordentoft M, Hougaard D, Norgaard-Pedersen B, Böttcher Y, Olesen J, Breuer R, Möller H-J, Giegling I, Rasmussen HB, Timm S, Mattheisen M, Bitter I, Réthelyi JM, Magnusdottir BB, Sigmundsson T, Olason P, Masson G, Gulcher JR, Haraldsson M, Fossdal R, Thorgeirsson TE, Thorsteinsdottir U, Ruggeri M, Tosato S, Franke B, Strengman E, Kiemeney LA, GROUP†, Melle I, Djurovic S, Abramova L, Kaleda V, Sanjuan J, de Frutos R, Bramon E, Vassos E, Fraser G, Ettinger U, Picchioni M, Walker N, Toulopoulou T, Need AC, Ge D, Yoon JL, Shianna KV, Freimer NB, Cantor RM, Murray R, Kong A, Golimbet V, Carracedo A, Arango C, Costas J, Jönsson EG, Terenius L, Agartz I, Petursson H, Nöthen MM, Rietschel M, Matthews PM, Muglia P, Peltonen L, St Clair D, Goldstein DB, Stefansson K, Collier DA & Genetic Risk and Outcome in Psychosis (GROUP). (2009) Common variants conferring risk of schizophrenia. Nature doi:10.1038/nature08186. Abstract

GWAS Results: Is the Glass Half Full or 95 Percent Empty?
The publication of the latest schizophrenia GWAS papers represents the culmination of a tremendous amount of work and unprecedented cooperation among a large number of researchers, for which they should be applauded. In addition to the hope of finding new “schizophrenia genes,” GWAS have been described by some of the researchers involved as, more fundamentally, a stern test of the common variants hypothesis. Based on the meagre haul of common variants dredged up by these three studies and their forerunners, this hypothesis should clearly now be resoundingly rejected—at least in the form that suggests that there is a large, but not enormous, number of such variants, which individually have modest, but not minuscule, effects. There are no common variants of even modest effect.

However, Purcell and colleagues now argue for a model involving vast numbers of variants, each of almost negligible effect alone. The authors show that an aggregate score derived from the top 10-50 percent of a set of 74,000...  Read more

GWAS Results: Is the Glass Half Full or 95 Percent Empty?
The publication of the latest schizophrenia GWAS papers represents the culmination of a tremendous amount of work and unprecedented cooperation among a large number of researchers, for which they should be applauded. In addition to the hope of finding new “schizophrenia genes,” GWAS have been described by some of the researchers involved as, more fundamentally, a stern test of the common variants hypothesis. Based on the meagre haul of common variants dredged up by these three studies and their forerunners, this hypothesis should clearly now be resoundingly rejected—at least in the form that suggests that there is a large, but not enormous, number of such variants, which individually have modest, but not minuscule, effects. There are no common variants of even modest effect.

However, Purcell and colleagues now argue for a model involving vast numbers of variants, each of almost negligible effect alone. The authors show that an aggregate score derived from the top 10-50 percent of a set of 74,000 SNPs from the association results in a discovery sample can predict up to 3 percent of the variance in a target group. Simply put, a set of putative “risk alleles” can be defined in one sample and shown, collectively, to be very slightly (though highly significantly in a statistical sense) enriched in the test sample, compared to controls. This is consistent across several different schizophrenia samples and even in two bipolar disorder samples. The authors go on to perform a set of control analyses that suggest that these results are not due to obvious population stratification or genotype rate effects (although effects at this level are obviously prone to cryptic artifacts).

If taken at face value, what do these results mean? They imply some kind of polygenic effect on risk, but of what magnitude? The answer to that depends on the interpretation of the additional simulations performed by the authors. They argue that the risk allele set inevitably contains very many false positives, which dilute the predictive power of the real positives hidden among them. Based on this logic, if we only knew which were the real variants to look at, then the variance explained in the target group would be much greater.

To try and estimate the magnitude of the effect of the polygenic load of “true risk” alleles, the authors conducted a series of simulations, varying parameters such as allele frequencies, genotype relative risks, and linkage disequilibrium with genotyped markers. They claim that these analyses converge on a set of models that recapitulate the observed data and that all converge on a true level of variance explained of around 34 percent, demonstrating a large polygenic component to the genetic architecture of schizophrenia.

These simulations adopt a level of statistical abstraction that should induce a healthy level of skepticism or at least reserved judgment on their findings. Most fundamentally, they rely explicitly for their calculations of the true variance on a liability-threshold model of the genetic architecture of schizophrenia. In effect, the “test” of the model incorporates the assumption that the model is correct.

The liability-threshold model is an elegant statistical abstraction that allows the application of the powerful statistics of normal distributions. Unfortunately, it suffers from the fact that it has no support whatsoever and makes no biological sense. First, there is no justification for assuming a normal distribution of “underlying liability,” whatever that term is taken to mean. Second, as usual when it is invoked, the nature of this putative threshold is not explained, though it surreptitiously implies some form of very strong epistasis (to explain the difference in risk between someone with x liability alleles and someone else with x+1 alleles). If this model is not correct, then these simulations are fatally flawed.

Even if the model were correct, the calculations are far from convincing. From a starting set of 560 models, the authors arrive at seven that are consistent with the observed degree of prediction in the target samples. According to the authors, the fact that these seven models converge on a small range of values for the underlying variance explained by the markers is evidence that this value (around 34 percent) represents the true situation. What is not highlighted is the fact that the values for the actual additive genetic variance (taking into account incomplete linkage disequilibrium between the markers and the assumed causal variants) across these models ranges from 34 percent to 98 percent and that the number of SNPs assumed to be having an effect ranges from 4,625 to 74,062. This extreme variation in the derived models hardly inspires confidence in the authors’ claim that their data “strongly support a polygenic basis to schizophrenia that (1) involves common SNPs, [and] (2) explains at least one-third of the total variation in liability.” (italics added)

From a more theoretical perspective, it should be noted that a polygenic model involving thousands of common variants of tiny effect cannot explain and will not contribute to the observed heightened familial relative risks. Such risk can only be explained by a variant of large effect or by an oligogenic model involving at most two to three loci (Bodmer and Bonilla, 2008; Hemminki et al., 2008; Mitchell and Porteous, in preparation). It seems much more likely that the observed predictive power in the target samples represents a modest “genetic background” effect, which could influence the penetrance and expressivity of rare, causal mutations. However, if the point of GWAS is to find genetic variants that are predictive of risk or that shed light on the pathogenic mechanisms of the disease, then clearly, even if such variants can be found by massively increasing sample sizes, their identification alone would not achieve or even appreciably contribute to either of these goals.

References:

Hemminki K, Försti A, Bermejo JL. The “common disease-common variant” hypothesis and familial risks. PLoS ONE. 2008 Jun 18;3(6):e2504. Abstract

Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet. 2008 Jun;40(6):695-701. Abstract

Thumbs up or down on schizophrenia GWAS?
The triumvirate of schizophrenia GWAS studies just published in Nature gives cause for thought, and bears close scrutiny and reflection. To my reading, these three studies individually and collectively lead to an unambiguous conclusion—there is a lot of genetic heterogeneity and not one individual variant of common ancient origin accounts for a significant fraction of the genetic liability. To put it another way, there is no ApoE equivalent for schizophrenia. Strong past claims for ZNF804A and others look to have fallen by the statistical wayside. Putting the results of all three studies together does appear to provide support for a long known, pre-GWAS association with HLA, but otherwise it is hard to give a strong "thumbs up" to any specific result, not least because of the lack of replication between studies. The results are nevertheless important because the common disease, common variant model, on which GWAS are based and the associated cost justified, is strongly rejected as the main contributor to the genetic...  Read more

Thumbs up or down on schizophrenia GWAS?
The triumvirate of schizophrenia GWAS studies just published in Nature gives cause for thought, and bears close scrutiny and reflection. To my reading, these three studies individually and collectively lead to an unambiguous conclusion—there is a lot of genetic heterogeneity and not one individual variant of common ancient origin accounts for a significant fraction of the genetic liability. To put it another way, there is no ApoE equivalent for schizophrenia. Strong past claims for ZNF804A and others look to have fallen by the statistical wayside. Putting the results of all three studies together does appear to provide support for a long known, pre-GWAS association with HLA, but otherwise it is hard to give a strong "thumbs up" to any specific result, not least because of the lack of replication between studies. The results are nevertheless important because the common disease, common variant model, on which GWAS are based and the associated cost justified, is strongly rejected as the main contributor to the genetic variance.

The ISC proposes a highly polygenic model with thousands of variants having an additive effect on both schizophrenia and bipolar disorder. I find no fault with their evidence, but its meaning and interpretation remains speculative. Simply consider the fact that SNPs carefully selected to tag half the genome account for about a third of the variance. It follows that the lion's share has gone undetected and will, by design and limitation, remain impervious to the GWAS strategy.

Part of the GWAS appeal is that the genotyping is technically facile and it is easier to collect lots of cases than it is families, but for as long as a diagnosis of schizophrenia or BP depends upon DSM-IV or ICD-10 classification, then diagnostic uncertainty will have a major effect on true power and validity of statistical association, both positive or negative. Indeed, the longstanding evidence from variable psychopathology amongst related individuals, the recent epidemiology evidence for shared genetic risk for schizophrenia and BP, and the further evidence supporting this from the ISC GWAS, all suggest that we should be returning more to family-based studies as a strategy to reduce genetic heterogeneity and find explanatory genetic variants. Plainly, adding ever more uncertainty through ever larger sample sizes is neither smart nor efficient.

I would certainly give the thumbs up to the full and unencumbered release of the primary data to the community as a whole, as this could usefully recoup some of the GWAS investment. It would facilitate a range of statistical and bioinformatics analyses and, who knows, there might be hidden nuggets of statistical support for independent genetic and biological studies.

The main question that arises from the three large genomewide association studies published in Nature is, What should we do next?

One important way forward would be to follow up the association findings in the MHC region. We need to understand the biological mechanism underlying this association. If the association signal is indeed related to infectious diseases, this line of inquiry may lead to the highly desired development of a treatment that might prevent the diseases in some cases.

One possible explanation for the association between schizophrenia and the MHC region (6p22.1) is that infection during pregnancy leads to disturbances of fetal brain development and increases the risk of schizophrenia later in life. A possible test for the theory of infectious diseases as risk factors for schizophrenia would be to study the associated SNPs in 6p22.1 in fathers and mothers of subjects with schizophrenia relative to parents of control subjects. If the 6p22.11 region is related to the tendency of mothers to be infected by viruses during pregnancy, we would expect the SNPs...  Read more

The main question that arises from the three large genomewide association studies published in Nature is, What should we do next?

One important way forward would be to follow up the association findings in the MHC region. We need to understand the biological mechanism underlying this association. If the association signal is indeed related to infectious diseases, this line of inquiry may lead to the highly desired development of a treatment that might prevent the diseases in some cases.

One possible explanation for the association between schizophrenia and the MHC region (6p22.1) is that infection during pregnancy leads to disturbances of fetal brain development and increases the risk of schizophrenia later in life. A possible test for the theory of infectious diseases as risk factors for schizophrenia would be to study the associated SNPs in 6p22.1 in fathers and mothers of subjects with schizophrenia relative to parents of control subjects. If the 6p22.11 region is related to the tendency of mothers to be infected by viruses during pregnancy, we would expect the SNPs in 6p22.1 to be most strongly associated with being a mother to a subject with schizophrenia.

Another broader and more complicated part of the question is: What would be the best strategy for continued study of the genetic causes of schizophrenia? There shouldn’t be only one way to proceed. Testing samples that are 10 times larger seems likely to lead to the identification of more genes, but with much smaller effect size. Testing the association of common variants with schizophrenia is unlikely to lead to the development of genetic diagnostic tools in the near future. If we want to understand the biology of the disease, it might be easier to concentrate our efforts on the identification of rare inherited and non-inherited variants with large effect on the phenotype. Such rare variants are easier to model in animals (relative to common variants with very small functional effect) and might even account for a larger proportion of cases.

The three companion papers in this week’s issue of Nature, in our view, support the case for investigating interaction between susceptibility genes and infectious exposures in schizophrenia. We and others have argued previously that genetic studies conducted in isolation from environmental factors, and studies of environmental influences in the absence of genetic data, are necessarily limited. Maternal influenza, rubella, toxoplasmosis, herpes simplex virus, and other infections have each been associated with an increased risk of schizophrenia, with effect sizes ranging from twofold to over fivefold. While these epidemiologic findings clearly require replication in independent cohorts, two new developments provide further support for the hypothesis. First, a growing number of animal studies of maternal immune activation have documented behavioral and brain phenotypes in offspring that are analogous to findings from clinical research in schizophrenia, and these findings are mediated in large part by specific cytokines (Meyer et al.,...  Read more

The three companion papers in this week’s issue of Nature, in our view, support the case for investigating interaction between susceptibility genes and infectious exposures in schizophrenia. We and others have argued previously that genetic studies conducted in isolation from environmental factors, and studies of environmental influences in the absence of genetic data, are necessarily limited. Maternal influenza, rubella, toxoplasmosis, herpes simplex virus, and other infections have each been associated with an increased risk of schizophrenia, with effect sizes ranging from twofold to over fivefold. While these epidemiologic findings clearly require replication in independent cohorts, two new developments provide further support for the hypothesis. First, a growing number of animal studies of maternal immune activation have documented behavioral and brain phenotypes in offspring that are analogous to findings from clinical research in schizophrenia, and these findings are mediated in large part by specific cytokines (Meyer et al., 2009; Patterson, 2008). Second, recent evidence indicates that maternal infection is also related to deficits in executive and other cognitive functions and neuropathology thought to arise from disruptions in brain development (Brown et al., 2009a; Brown et al., 2009b).

While the MHC region contains genes not involved in the immune system, in light of the epidemiologic findings on maternal infection, it is intriguing to see that this region is once more implicated in genetic studies of schizophrenia as the importance of this region in the response to infectious insults cannot be ignored. Although it is heartening to see that the potential implications of these findings for infectious etiologies were raised in the article from the SGENE plus group, an analysis of the frequency of SNPs by season of birth falls well short of the type of research that will yield definitive findings on the relationships between susceptibility genes and infectious insults. Hence, we advocate a strategy aimed at large scale genetic analyses of schizophrenia cases using birth cohorts with infectious exposures documented from prospectively collected biological samples from the prenatal period. If the schizophrenia-related pathogenic mechanisms by which MHC-related genetic variants operate involve interactions with prenatal infection, we would expect that studies of gene-infection interaction will yield larger effect sizes than those found in these new papers. The evidence from these papers and the epidemiologic literature should also facilitate narrowing of the number of candidate genes to be tested for interactions with infectious insults, thereby ameliorating the potential for type I error due to multiple comparisons.

References:

Meyer U, Feldon J, Fatemi SH. In-vivo rodent models for the experimental investigation of prenatal immune activation effects in neurodevelopmental brain disorders. Neurosci Biobehav Rev . 2009 Jul 1; 33(7):1061-79. Abstract

Patterson PH. Immune involvement in schizophrenia and autism: Etiology, pathology and animal models. Behav Brain Res. 2008 Dec 24; Abstract

Brown AS, Vinogradov S, Kremen WS, Poole JH, Deicken RF, Penner JD, McKeague IW, Kochetkova A, Kern D, Schaefer CA. Prenatal exposure to maternal infection and executive dysfunction in adult schizophrenia. Am J Psychiatry . 2009a Jun 1 ; 166(6):683-90. Abstract

Brown AS, Deicken RF, Vinogradov S, Kremen WS, Poole JH, Penner JD, Kochetkova A, Kern D, Schaefer CA. Prenatal infection and cavum septum pellucidum in adult schizophrenia. Schizophr Res . 2009b Mar 1 ; 108(1-3):285-7. Abstract

Two hundred years after Darwin’s birth and 150 years after the publication of On the Origin of Species, these three papers in Nature show the important role of natural selection in shaping the genetic architecture of schizophrenia susceptibility. If we compare the GWAS results for schizophrenia with those obtained for other diseases, it seems that there are less common risk alleles and/or lower effect sizes in schizophrenia than in many other complex diseases (see, for instance, the online catalog of published GWAS at NHGRI). This fact strongly suggests that negative selection limits the spread of susceptibility alleles, as expected due to the decreased fertility of schizophrenic patients.

Interestingly, the MHC region may be an exception. This region represents a classical example of balancing selection, i.e., the presence of several variants at a locus maintained in a population by positive natural selection (Hughes and Nei, 1988). In the case of the MHC, this...  Read more

Two hundred years after Darwin’s birth and 150 years after the publication of On the Origin of Species, these three papers in Nature show the important role of natural selection in shaping the genetic architecture of schizophrenia susceptibility. If we compare the GWAS results for schizophrenia with those obtained for other diseases, it seems that there are less common risk alleles and/or lower effect sizes in schizophrenia than in many other complex diseases (see, for instance, the online catalog of published GWAS at NHGRI). This fact strongly suggests that negative selection limits the spread of susceptibility alleles, as expected due to the decreased fertility of schizophrenic patients.

Interestingly, the MHC region may be an exception. This region represents a classical example of balancing selection, i.e., the presence of several variants at a locus maintained in a population by positive natural selection (Hughes and Nei, 1988). In the case of the MHC, this balancing selection seems to be related to pathogen resistance or MHC-dependent mating choice. Therefore, the presence of common schizophrenia susceptibility alleles at this locus might be explained by antagonistic pleiotropic effects of alleles maintained by natural selection.

If negative selection limits the spread of schizophrenia risk alleles, most of the genetic susceptibility to schizophrenia is likely due to rare variants. Resequencing technologies will allow the identification of many of these variants in the near future. In the meantime, it would be interesting to focus our attention on non-synonymous SNPs at low frequency. Based on human-chimpanzee comparisons and human sequencing data, Kryukov et al. (2008) have shown that a large fraction of de novo missense mutations are mildly deleterious (i.e., they are subject to weak negative selection) and therefore they can still reach detectable frequencies. Assuming that most of these mildly deleterious alleles may be detrimental (i.e., they confer risk for disease) the authors conclude that numerous rare functional SNPs may be major contributors to susceptibility to common diseases Kryukov et al., 2008. Similar conclusions were obtained by the analysis of the relative frequency distribution of non-synonymous SNPs depending on their probability to alter protein function (Barreiro et al., 2008; Gorlov et al., 2008). As shown by Evans et al. (2008), genomewide scans of non-synonymous SNPs might complement GWAS, being able to identify rare non-synonymous variants of intermediate penetrance not detectable by current GWAS panels.

References:

Barreiro LB, Laval G, Quach H, Patin E, Quintana-Murci L (2008) Natural selection has driven population differentiation in modern humans. Nat Genet 40: 340-5. Abstract

Evans DM, Barrett JC, Cardon LR (2008) To what extent do scans of non-synonymous SNPs complement denser genome-wide association studies? Eur J Hum Genet 16: 718-23. Abstract

Gorlov IP, Gorlova OY, Sunyaev SR, Spitz MR, Amos CI (2008) Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms. Am J Hum Genet 82: 100-12. Abstract

Hughes AL, Nei M (1988) Pattern of nucleotide substitution at major histocompatibility complex class I loci reveals overdominant selection. Nature 335: 167-70. Abstract

Kryukov GV, Pennacchio LA, Sunyaev SR (2007) Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am J Hum Genet 80: 727-39. Abstract

If schizophrenia and autism are on a spectrum, how can there be people who are both autistic and schizophrenic? I know of a few people who suffer from both diseases.

View all comments by Katie Rodriguez

One Hundred Years of Insanity: The Relationship Between Schizophrenia and Autism
The great Colombian author Gabriel García Márquez reified the cyclical nature of history in his Nobel Prize-winning 1967 book, One Hundred Years of Solitude. Eugen Bleuler’s less-famous book Dementia Præcox or the Group of Schizophrenias, originally published in 1911, saw first use of the term “autism,” a form of solitude manifest as withdrawal from reality in schizophrenia. This neologism, about to celebrate its centenary, epitomizes an astonishing cycle of reification and change in nosology, a cycle only now coming into clear view as molecular-genetic data confront the traditional, age-old categories of psychiatric classification.

The term autism was, of course, redefined by Leo Kanner (1943) for a childhood psychiatric condition first considered as a subset of schizophrenia, then regarded as quite distinct (Rutter, 1972) or even opposite to it (Rimland, 1964; Crespi and Badcock, 2008), and most recently seen by some researchers as returning to its original...  Read more

One Hundred Years of Insanity: The Relationship Between Schizophrenia and Autism
The great Colombian author Gabriel García Márquez reified the cyclical nature of history in his Nobel Prize-winning 1967 book, One Hundred Years of Solitude. Eugen Bleuler’s less-famous book Dementia Præcox or the Group of Schizophrenias, originally published in 1911, saw first use of the term “autism,” a form of solitude manifest as withdrawal from reality in schizophrenia. This neologism, about to celebrate its centenary, epitomizes an astonishing cycle of reification and change in nosology, a cycle only now coming into clear view as molecular-genetic data confront the traditional, age-old categories of psychiatric classification.

The term autism was, of course, redefined by Leo Kanner (1943) for a childhood psychiatric condition first considered as a subset of schizophrenia, then regarded as quite distinct (Rutter, 1972) or even opposite to it (Rimland, 1964; Crespi and Badcock, 2008), and most recently seen by some researchers as returning to its original Bluelerian incarnation (e.g., Carroll and Owen, 2009). An outstanding new paper by McCarthy et al. (2009), demonstrating that duplications of the CNV locus 16p11.2 are strongly associated with increased risk of schizophrenia, has brought this question to the forefront of psychiatric inquiry, because deletions of this same CNV are one of the most striking recently-characterized risk factors for autism. Additional CNVs, such as those at 1q21.1 and 22q11.21 have also been associated with autism and schizophrenia in one or more studies (e.g., Mefford et al., 2008; Crespi et al., 2009; Glessner et al., 2009), which has led some authors to infer that since an overlapping set of loci mediates risk of both conditions, autism and schizophrenia must be more similar than previously conceived (e.g., Carroll and Owen, 2009; Guilmatre et al., 2009). Similar considerations apply to several genes, such as CNTNAP2 and NRXN1, various disruptions of which have likewise been linked with both conditions (Iossifov et al., 2008; Kirov et al., 2008; Burbach and van der Zwaag, 2009).

So does this plethora of new molecular-genetic data imply that Blueler was indeed correct, if not prescient, that autism and schizophrenia are manifestations of similar disease processes? The answer may appear tantalizingly close, but will likely remain inaccessible without explicit consideration of alternative hypotheses and targeted tests of their differentiating predictions. This approach is simply Platt’s (1964) classic method of strong inference, which has propelled molecular biology so far and fast but left psychiatry largely by the wayside (Cannon, 2009). The alternative hypotheses in this case are clear: with regard to causation from specific genetic and genomic risk factors, autism and schizophrenia are either: 1) independent and discrete, 2) partially yet broadly overlapping, 3) subsumed with autism as a subset of schizophrenia, or 4) diametrically opposite, with normality in the centre. CNVs are especially useful for testing among such alternative hypotheses, because they naturally involve highly-penetrant perturbations in two opposite directions, due to deletions vs duplications of more or less the same genomic regions. Hypotheses 2), 3) and 4) thus predict that autism and schizophrenia should share CNV risk loci, but 2) and 3) predict specific rearrangements (deletions, duplications, or both) shared across both conditions; by contrast, hypothesis (4) predicts that, as highlighted by McCarthy et al. (2009), reciprocal CNVs at the same locus should mediate risk of autism versus schizophrenia. This general approach was pioneered by Craddock et al. (2005, 2009), in their discussion of explicit alternative hypotheses for the relationship between schizophrenia and bipolar disorder, which are now known to share a notable suite of risk alleles.

A key assumption that underlies tests of hypotheses for the relationship between autism and schizophrenia is accuracy of diagnoses. For schizophrenia, this is seldom at issue. However, diagnoses of autism, or autism spectrum disorders such as PDD-NOS, are normally made at an age well before the first manifestations of schizophrenia in adolescence or early adulthood, which generates a risk for false-positive diagnoses of premorbidity to schizophrenia as autism or autism spectrum (e.g., Eliez, 2007). The tendencies for males to exhibit worse premorbidity to schizophrenia than females (Sobin et al., 2001; Tandon et al., 2009), for CNVs to exert severe effects on diverse aspects of early neurodevelopment (Shinawi et al., 2009), and for schizophrenia of earlier onset to exhibit a higher male sex-ratio bias and a stronger tendency to be associated with CNVs rather than other causes (Remschmidt et al., 1994; Rapoport et al., 2009), all suggest a high risk for false-positive diagnoses of autistic spectrum conditions in individuals with these genomic risk factors (Feinstein and Singh, 2007; Reaven et al., 2008; Sugihara et al., 2008; Starling and Dossetor, 2009). Possible evidence of such risk comes from diagnoses of autism spectrum conditions in children with deletions at 15q11.2, 15q13.3, and 22q11.21, and duplications of 16p11.2, CNVs for which schizophrenia risk has been well established from studies of adults (Antshel et al., 2007; Stefansson et al., 2008; Weiss et al., 2008; Ben-Shachar et al., 2009; Doornbos et al., 2009; McCarthy et al., 2009). By contrast, autism-associated CNVs, such as deletions at 16p11.2 (Kumar et al., 2008), or duplications at 22q11.21 (Glessner et al., 2009; Crespi et al., 2009) have seldom also been reported in individuals diagnosed with schizophrenia, which suggests that false-positive diagnoses of schizophrenia as autism are uncommon.

Differentiating between a hypothesis of false-positive diagnoses of premorbidity to schizophrenia as autism, compared to a hypothesis of specific deletions or duplications shared between autism and schizophrenia, requires some combination of longitudinal studies, judicious use of endophenotypes, and adoption of relatively new diagnostic categories such as multiple complex developmental disorder (Sprong et al., 2008). Moreover, to the degree that such false positives are not uncommon, and autism and schizophrenia are underlain by diametric genetically based risk factors, inclusion of children premorbid for schizophrenia in studies on the genetic bases of autism will substantially dilute the probability of detecting significant results.

Ultimately, robust evaluation of alternative hypotheses for the relationship of autism with schizophrenia will require evidence from studies of common and rare SNP variants as well as CNVs, in-depth analyses of the neurodevelopmental and neuronal-function effects of different alterations to genes such as NRXN1, CNTNAP2, and SHANK3, and integrative data from diverse disciplines other than genetics, especially the neurosciences and psychology. Unless such interdisciplinary studies are deployed—in hypothesis-testing frameworks that use strong inference—we should expect to remain, as penned by García Márquez, in “permanent alternation between excitement and disappointment, doubt and revelation, to such an extreme that no one knows for certain where the limits of reality lay”—for yet another 100 years.

References
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Bleuler E. 1950. Dementia praecox or the group of schizophrenias. (Internat Univ Press, New York). (Translation from 1911 German original).

Burbach JP, van der Zwaag B. Contact in the genetics of autism and schizophrenia. Trends Neurosci. 2009 Feb;32(2):69-72. Abstract

Cannon TD. What is the role of theories in the study of schizophrenia? Schizophr Bull. 2009 May;35(3):563-7. Abstract

Carroll LS, Owen MJ. Genetic overlap between autism, schizophrenia and bipolar disorder. Genome Med. 2009 Oct 30;1(10):102. Abstract

Craddock N, Owen MJ. The beginning of the end for the Kraepelinian dichotomy. Br J Psychiatry. 2005 May;186:364-6. Abstract

Craddock N, O'Donovan MC, Owen MJ. Psychosis genetics: modeling the relationship between schizophrenia, bipolar disorder, and mixed (or "schizoaffective") psychoses. Schizophr Bull. 2009 May;35(3):482-90. Abstract

Crespi B, Badcock C. Psychosis and autism as diametrical disorders of the social brain. Behav Brain Sci. 2008 Jun;31(3):241-61; discussion 261-320.

Crespi B, Stead P, Elliot M. Comparative genomics of autism and schizophrenia. Proc Natl Acad Sci U S A. 2009 (in press).

Doornbos M, Sikkema-Raddatz B, Ruijvenkamp CA, Dijkhuizen T, Bijlsma EK, Gijsbers AC, Hilhorst-Hofstee Y, Hordijk R, Verbruggen KT, Kerstjens-Frederikse WS, van Essen T, Kok K, van Silfhout AT, Breuning M, van Ravenswaaij-Arts CM. Nine patients with a microdeletion 15q11.2 between breakpoints 1 and 2 of the Prader-Willi critical region, possibly associated with behavioural disturbances. Eur J Med Genet. 2009 Mar-Jun;52(2-3):108-15. Abstract

Eliez S. Autism in children with 22q11.2 deletion syndrome. 2007 Apr;46(4):433-4; author reply 434-4.

Feinstein C, Singh S. Social phenotypes in neurogenetic syndromes. Child Adolesc Psychiatr Clin N Am. 2007 Jul;16(3):631-47. Abstract

Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S, Zhang H, Estes A, Brune CW, Bradfield JP, Imielinski M, Frackelton EC, Reichert J, Crawford EL, Munson J, Sleiman PM, Chiavacci R, Annaiah K, Thomas K, Hou C, Glaberson W, Flory J, Otieno F, Garris M, Soorya L, Klei L, Piven J, Meyer KJ, Anagnostou E, Sakurai T, Game RM, Rudd DS, Zurawiecki D, McDougle CJ, Davis LK, Miller J, Posey DJ, Michaels S, Kolevzon A, Silverman JM, Bernier R, Levy SE, Schultz RT, Dawson G, Owley T, McMahon WM, Wassink TH, Sweeney JA, Nurnberger JI, Coon H, Sutcliffe JS, Minshew NJ, Grant SF, Bucan M, Cook EH, Buxbaum JD, Devlin B, Schellenberg GD, Hakonarson H. Autism genome-wide copy number variation reveals ubiquitin and neuronal genes. Nature. 2009 May 28;459(7246):569-73. Abstract

Guilmatre A, Dubourg C, Mosca AL, Legallic S, Goldenberg A, Drouin-Garraud V, Layet V, Rosier A, Briault S, Bonnet-Brilhault F, Laumonnier F, Odent S, Le Vacon G, Joly-Helas G, David V, Bendavid C, Pinoit JM, Henry C, Impallomeni C, Germano E, Tortorella G, Di Rosa G, Barthelemy C, Andres C, Faivre L, Frébourg T, Saugier Veber P, Campion D. Recurrent rearrangements in synaptic and neurodevelopmental genes and shared biologic pathways in schizophrenia, autism, and mental retardation. Arch Gen Psychiatry. 2009 Sep;66(9):947-56. Abstract

Iossifov I, Zheng T, Baron M, Gilliam TC, Rzhetsky A. Genetic-linkage mapping of complex hereditary disorders to a whole-genome molecular-interaction network. Genome Res. 2008 Jul;18(7):1150-62. (Abstract

Kanner L. Autistic disturbances of affective contact. Nerv Child 1943 2:217-50.

Kirov G, Gumus D, Chen W, Norton N, Georgieva L, Sari M, O'Donovan MC, Erdogan F, Owen MJ, Ropers HH, Ullmann R. Comparative genome hybridization suggests a role for NRXN1 and APBA2 in schizophrenia. Hum Mol Genet. 2008 Feb 1;17(3):458-65. Abstract

McCarthy SE, Makarov V, Kirov G, Addington AM, McClellan J, Yoon S, Perkins DO, Dickel DE, Kusenda M, Krastoshevsky O, Krause V, Kumar RA, Grozeva D, Malhotra D, Walsh T, Zackai EH, Kaplan P, Ganesh J, Krantz ID, Spinner NB, Roccanova P, Bhandari A, Pavon K, Lakshmi B, Leotta A, Kendall J, Lee YH, Vacic V, Gary S, Iakoucheva LM, Crow TJ, Christian SL, Lieberman JA, Stroup TS, Lehtimäki T, Puura K, Haldeman-Englert C, Pearl J, Goodell M, Willour VL, Derosse P, Steele J, Kassem L, Wolff J, Chitkara N, McMahon FJ, Malhotra AK, Potash JB, Schulze TG, Nöthen MM, Cichon S, Rietschel M, Leibenluft E, Kustanovich V, Lajonchere CM, Sutcliffe JS, Skuse D, Gill M, Gallagher L, Mendell NR; Wellcome Trust Case Control Consortium, Craddock N, Owen MJ, O'Donovan MC, Shaikh TH, Susser E, Delisi LE, Sullivan PF, Deutsch CK, Rapoport J, Levy DL, King MC, Sebat J. Microduplications of 16p11.2 are associated with schizophrenia. Nat Genet. 2009 Nov;41(11):1223-7. Abstract

Mefford HC, Sharp AJ, Baker C, Itsara A, Jiang Z, Buysse K, Huang S, Maloney VK, Crolla JA, Baralle D, Collins A, Mercer C, Norga K, de Ravel T, Devriendt K, Bongers EM, de Leeuw N, Reardon W, Gimelli S, Bena F, Hennekam RC, Male A, Gaunt L, Clayton-Smith J, Simonic I, Park SM, Mehta SG, Nik-Zainal S, Woods CG, Firth HV, Parkin G, Fichera M, Reitano S, Lo Giudice M, Li KE, Casuga I, Broomer A, Conrad B, Schwerzmann M, Räber L, Gallati S, Striano P, Coppola A, Tolmie JL, Tobias ES, Lilley C, Armengol L, Spysschaert Y, Verloo P, De Coene A, Goossens L, Mortier G, Speleman F, van Binsbergen E, Nelen MR, Hochstenbach R, Poot M, Gallagher L, Gill M, McClellan J, King MC, Regan R, Skinner C, Stevenson RE, Antonarakis SE, Chen C, Estivill X, Menten B, Gimelli G, Gribble S, Schwartz S, Sutcliffe JS, Walsh T, Knight SJ, Sebat J, Romano C, Schwartz CE, Veltman JA, de Vries BB, Vermeesch JR, Barber JC, Willatt L, Tassabehji M, Eichler EE. Recurrent rearrangements of chromosome 1q21.1 and variable pediatric phenotypes. N Engl J Med. 2008 Oct 16;359(16):1685-99. Abstract

Platt, JR. Strong Inference: Certain systematic methods of scientific thinking may produce much more rapid progress than others. Science. 1964 Oct 16;146(3642):347-353.

Rapoport J, Chavez A, Greenstein D, Addington A, Gogtay N. Autism spectrum disorders and childhood-onset schizophrenia: clinical and biological contributions to a relation revisited. J Am Acad Child Adolesc Psychiatry. 2009 Jan;48(1):10-8. Abstract

Reaven JA, Hepburn SL, Ross RG. Use of the ADOS and ADI-R in children with psychosis: importance of clinical judgment. Clin Child Psychol Psychiatry. 2008 Jan;13(1):81-94. Abstract

Remschmidt HE, Schulz E, Martin M, Warnke A, Trott GE. Childhood-onset schizophrenia: history of the concept and recent studies. Schizophr Bull. 1994;20(4):727-45. Abstract

Rimland, B. 1964. Infantile Autism: The Syndrome and Its Implications for a Neural Theory of Behavior. New York, Appleton-Century-Crofts.

Rutter M. Childhood schizophrenia reconsidered. J Autism Child Schizophr. 1972 Oct-Dec;2(4):315-37.

Shinawi M, Liu P, Kang S-H, Shen J, Belmont JW, Scott DA, Probst FJ, Craigen WJ, Graham BH, Pursley A, Clark G, Lee J, Proud M, Stocco A, Rodriguez DL, Kozel BA,Sparagana S, Roeder ER, McGrew SG, Kurczynski TW, Allison LJ, Amato S, Savage S, Patel A,Stankiewicz P, Beaudet AL, Cheung SW, JR Lupski JR. Recurrent reciprocal 16p11.2 rearrangements associated with global developmental delay, behavioral problems, dysmorphism, epilepsy, and abnormal head size. J Med Genet. (in press).

Sobin C, Blundell ML, Conry A, Weiller F, Gavigan C, Haiman C, Karayiorgou M. Early, non-psychotic deviant behavior in schizophrenia: a possible endophenotypic marker for genetic studies. Psychiatry Res. 2001 Mar 25;101(2):101-13. Abstract

Sprong M, Becker HE, Schothorst PF, Swaab H, Ziermans TB, Dingemans PM, Linszen D, van Engeland H. Pathways to psychosis: a comparison of the pervasive developmental disorder subtype Multiple Complex Developmental Disorder and the "At Risk Mental State". Schizophr Res. 2008 Feb;99(1-3):38-47. Abstract

Starling J, Dossetor D. Pervasive developmental disorders and psychosis. Curr Psychiatry Rep. 2009 Jun;11(3):190-6. Abstract

Stefansson H, Rujescu D, Cichon S, Pietiläinen OP, Ingason A, Steinberg S, Fossdal R, Sigurdsson E, Sigmundsson T, Buizer-Voskamp JE, Hansen T, Jakobsen KD, Muglia P, Francks C, Matthews PM, Gylfason A, Halldorsson BV, Gudbjartsson D, Thorgeirsson TE, Sigurdsson A, Jonasdottir A, Jonasdottir A, Bjornsson A, Mattiasdottir S, Blondal T, Haraldsson M, Magnusdottir BB, Giegling I, Möller HJ, Hartmann A, Shianna KV, Ge D, Need AC, Crombie C, Fraser G, Walker N, Lonnqvist J, Suvisaari J, Tuulio-Henriksson A, Paunio T, Toulopoulou T, Bramon E, Di Forti M, Murray R, Ruggeri M, Vassos E, Tosato S, Walshe M, Li T, Vasilescu C, Mühleisen TW, Wang AG, Ullum H, Djurovic S, Melle I, Olesen J, Kiemeney LA, Franke B; GROUP, Sabatti C, Freimer NB, Gulcher JR, Thorsteinsdottir U, Kong A, Andreassen OA, Ophoff RA, Georgi A, Rietschel M, Werge T, Petursson H, Goldstein DB, Nöthen MM, Peltonen L, Collier DA, St Clair D, Stefansson K. Large recurrent microdeletions associated with schizophrenia. Nature. 2008 Sep 11;455(7210):232-6. Abstract

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The Diametric Opposition of Autism and Psychosis: Support From a Study of Cognition
As has been noted previously, Crespi and Badcock’s (2008) theory that autism and schizophrenia are diametrically opposed disorders is certainly a novel and somewhat controversial one. In his recent blog on Psychology Today, Badcock states that the theory stands on two completely different foundations: one in evolution and genetics, and one in psychiatry and cognitive science (Badcock, 2010). While most of the comments posted before ours have addressed the relationship between autism and schizophrenia from a genetic perspective, coming from a psychology background, we note that it is the aspects of Crespi and Badcock’s theory that relate to cognition which have particularly caught our attention. While we can therefore contribute little to the discussion of a relationship between autism and schizophrenia...  Read more

The Diametric Opposition of Autism and Psychosis: Support From a Study of Cognition
As has been noted previously, Crespi and Badcock’s (2008) theory that autism and schizophrenia are diametrically opposed disorders is certainly a novel and somewhat controversial one. In his recent blog on Psychology Today, Badcock states that the theory stands on two completely different foundations: one in evolution and genetics, and one in psychiatry and cognitive science (Badcock, 2010). While most of the comments posted before ours have addressed the relationship between autism and schizophrenia from a genetic perspective, coming from a psychology background, we note that it is the aspects of Crespi and Badcock’s theory that relate to cognition which have particularly caught our attention. While we can therefore contribute little to the discussion of a relationship between autism and schizophrenia from a genetic standpoint, we present the findings from our recent study (Russell-Smith et al., 2010), which provided the first test of Crespi and Badcock’s claim that autism and psychosis are at opposite ends of the cognitive spectrum.

In placing autism and psychosis at opposite ends of the cognitive spectrum, Crespi and Badcock (2008) propose that autistic and positive schizophrenia traits contrastingly affect preference for local versus global processing, with individuals with autism displaying a preference for local processing and individuals with positive schizophrenia displaying a preference for global processing. That is, these authors claim that while individuals with autism show a tendency to focus on detail or process features in their isolation, individuals with positive schizophrenia show a tendency to look at the bigger picture or process features as an integrated whole. Importantly, since Crespi and Badcock argue for a continuum stretching all the way from autism to psychosis, the same diametric pattern of cognition should be seen in individuals who display only mild variants of autistic and positive schizophrenia traits. This includes typical individuals who score highly on measures such as the Autism Spectrum Quotient (AQ; Baron-Cohen et al., 2001) and the Unusual Experiences subscale of the Oxford-Liverpool Inventory of Experiences (O-LIFE:UE; Mason et al., 2005). These are both reliable and commonly used measures which have been specifically designed to assess the levels of “autistic-like” traits and positive schizotypy traits in typical individuals. Since Crespi and Badcock actually argue their theory is best evaluated with reference to individuals with milder traits of autism and positive schizophrenia, it is with these populations that we investigated their claims.

A task often used to determine whether an individual has a preference for local over global processing is the Embedded Figures Test (EFT; Witkin et al., 1971), which requires individuals to detect hidden shapes within complex figures. As the test requires one to resist experiencing an integrated visual stimulus or gestalt in favor of seeing single elements, it is argued that a local processing style aids successful (i.e., faster) completion of this task (Bolte et al., 2007). Accordingly, from Crespi and Badcock’s (2008) theory, one would expect that relative to individuals with low levels of these traits, individuals with high levels of autistic-like traits should perform better on the EFT, while individuals with positive schizotypy traits should perform worse. To test this claim, our study obtained the AQ and O-LIFE:UE scores for 318 students completing psychology as part of a broader degree (e.g., a BSc or BA). Two pairs of groups (i.e., four groups in total), each consisting of 20 students, were then formed. One of these pairs consisted of High and Low AQ groups, which were selected such that they were separated substantially in their AQ scores but matched as closely as possible on their O-LIFE:UE scores. The other pair of groups, the High and Low O-LIFE:UE groups, were selected such that they were separated in their O-LIFE:UE scores, but matched as closely as possible on their AQ scores. The gender ratio was matched closely across the four groups.

To test the prediction that higher levels of autistic-like traits are associated with more skilled EFT performance, the High and Low AQ groups were compared in terms of their mean response time to accurately locate each of the embedded figures. Individuals in the High AQ group did display more skilled EFT performance than individuals in the Low AQ group, consistent with a greater preference for local over global processing in relation to higher levels of autistic-like traits (see also Almeida et al., 2010; Bolte and Poustka, 2007; Grinter et al., 2009; Grinter et al., 2009). We then compared EFT performance for the O-LIFE:UE groups to test the prediction that higher levels of positive schizotypy traits are associated with less skilled performance on this task. Consistent with a preference for global over local processing in relation to higher levels of positive schizotypy traits, individuals in the High O-LIFE:UE group displayed less skilled EFT performance than individuals in the Low O-LIFE:UE group. Therefore, results from both pairs of groups together provide support for Crespi and Badcock’s (2008) claim that autistic and positive schizophrenia traits are diametrically opposed with regard to their effect on local versus global processing.

However, the support our study offers for Crespi and Badcock’s (2008) theory was tempered slightly by our failure to find the expected contrasting patterns of non-verbal relative to verbal ability for our two pairs of groups. To display the expected patterns, relative to individuals with low levels of these traits, individuals with high levels of autistic-like traits should have displayed higher non-verbal ability relative to verbal ability, whereas individuals with high levels of positive schizotypy traits should have displayed lower non-verbal relative to verbal ability. While visual inspection of mean verbal and non-verbal scores for the O-LIFE:UE groups revealed a trend consistent with what would be expected based on Crespi and Badcock’s theory, none of the group differences was statistically significant. However, as we pointed out in our article, a study which offers a more complete assessment of this aspect of the theory is warranted. In particular, since the use of a student sample in our study no doubt led to a restriction in the range of IQ scores (especially with reference to verbal IQ), a test of community-based samples would be useful.

Therefore, while Crespi and Badcock’s (2008) theory has passed its first major test at the level of cognition, with our results indicating a contrasting effect of autistic-like and positive schizotypy traits with regard to preference for local versus global processing, further investigation of these authors’ theory at both the cognitive and genetic levels is required.

References:

Almeida, R., Dickinson, J., Maybery, M., Badcock, J., Badcock, D. A new step toward understanding Embedded Figures Test performance in the autism spectrum: The radial frequency search task. Neuropsychologia. 2010 Jan;48(2):374-81. Abstract

Badcock, C. (2010). Diametric cognition passes its first lab test. Psychology Today. Retrieved February 8, from http://www.psychologytoday.com/blog/the-imprinted-brain/201002/diametric-cognition-passes-its-first-lab-test.

Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., Clubley, E. (2001). The Autism-Spectrum Quotient (AQ): Evidence from Asperger Syndrome/High-Functioning Autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 5-17. Abstract

Bolte, S., Holtmann, M., Poustka, F., Scheurich, A., Schmidt, L. (2007). Gestalt perception and local-global processing in High-Functioning Autism. Journal of Autism and Developmental Disorders, 37, 1493-1504. Abstract

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