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Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

6 November 2009. The bright diagnostic line between autism and schizophrenia, only about 30 years old, has again begun to blur, prompted by genomic studies of copy number variations (CNVs) that have implicated the same chromosomal regions in both disorders. Four recent CNV studies continue this trend, and further evidence for shared genetic causes of autism and schizophrenia comes from new behavioral and electrophysiological experiments with knockout mice lacking the presynaptic protein neurexin-1α, the gene for which has been implicated in both disorders.

Are schizophrenia and autism two sides of one coin?
Though now thought of as quite different disorders, historically autism and schizophrenia have been tightly intertwined. Bleuler (1911 [Bleuler, E. Dementia praecox oder Gruppe der Schizophrenien. Leipzig und Wien: F. Deuticke]) coined the term “autism” to describe social withdrawal as a negative symptom of schizophrenia. In his classic description of children with autism, Kanner (1943: Autistic disturbances of affective contact. Nerv Child 2: 217–50. Reprinted in Acta Paedopsychiatr, 1968) made a convincing case that a pervasive disposition to aloneness could occur in the absence of psychosis (see SRF related news story), but it wasn’t until Kolvin’s (1971) differentiation of autism and schizophrenia based on age of onset that this idea began to enter the psychiatric mainstream, capped in 1980 by the inclusion of autism as a diagnostic category distinct from schizophrenia in DSM-III.

Not surprisingly, many genes in the putative shared chromosomal regions reported in recent studies are involved in neural development and synaptogenesis (see SRF related news story; SRF news story), and researchers have begun to formulate genetic, epigenetic, and environmental hypotheses to explain how variations in a suite of shared chromosomal regions could lead to either an autistic or schizophrenic phenotype.

One of the most provocative ideas, proposed by Bernard Crespi of Simon Fraser University and Christopher Badcock of the London School of Economics, holds that autism and schizophrenia are diametrically opposed disorders of the “social brain,” and that genomic imprinting of the same set of mutated genes can cause schizophrenia or autism, respectively, depending on developmental biases toward the expression of maternally versus paternally imprinted genes (see, e.g., Crespi and Badcock, 2008). One of the new studies appears to provide some supporting data for this hypothesis in the broad sense of two mutually exclusive disorders.

16p11.2: a clear-cut case?
“Crespi and colleagues are right on for the most part,” says Jonathan Sebat of Cold Spring Harbor Laboratory, who led the latest CNV study (McCarthy et al., 2009). Sebat and colleagues report that, in a cohort of 1,906 cases of schizophrenia and 3,971 controls, both drawn from a variety of sources, microduplications in a ~500-kb region of 16p11.2 were strongly associated with schizophrenia, a finding that was replicated in an independent sample of 2,645 cases and 2,420 healthy controls. However, because members of five families in their original sample had a range of psychiatric diagnoses other than schizophrenia, the team also performed a meta-analysis on a sample assembled from publicly available datasets that included 8,590 individuals with schizophrenia, 2,172 with autism, 4,822 with bipolar disorder, and 30,492 controls. In the meta-analysis, the duplication was strongly associated with schizophrenia (P = 4.8 x 10-7), autism (P = 1.9 x 10-7), and bipolar disorder (P = 0.017), but the reciprocal microdeletion was associated only with developmental delay or autism (P = 2.3 x 10-13). The microdeletion was also significantly associated with larger head circumference, a phenotype that has been associated with brain hypertrophy early in development in autism (see, e.g., Courchesne, 2007).

Sebat says the findings do not perfectly reflect the complex models, which involve imprinting, proposed by Crespi and Badcock. However, he adds, “Crespi has also proposed that reciprocal deletion and duplication syndromes would possibly create diametrically opposed disorders, including schizophrenia and autism.”

More overlap
Though perhaps not as clear-cut as these 16p11.2 findings, a series of recent CNV studies have also reported genetic overlaps between schizophrenia and autism. In April, members of Michael O’Donovan’s group at Cardiff University reported a deletion at 22q11.2 in two cases of schizophrenia (Kirov et al., 2009); deletions in this region are associated with velo-cardio-facial syndrome and with autism (Ousley et al., 2007). Other large deletions, one disrupting exons in neurexin-1 (NRXN1) and the other affecting the neurexophilin (NXPH2) gene, which interacts with NRXN1, were found in cases of schizophrenia. Neither neurexin-related deletion achieved significance, but it is notable that deletions affecting neurexin-1 have previously been implicated in both autism and schizophrenia (see SRF related news story).

Recent work with neurexin-1α knockout mice by Thomas Südhof and colleagues (Etherton et al., 2009) revealed an electrophysiological phenotype related to a loss of presynaptic strength at excitatory synapses. Though these mice exhibited no notable deficits in social behaviors, they displayed marked changes in behaviors with face validity to autism (repetitive grooming) and to autism and schizophrenia (impaired prepulse inhibition).

The Cardiff team also found a large duplication on 16p13.1 that has been associated with autism and mental retardation (Ullmann et al., 2007; Behjati et al., 2008) in three schizophrenia cases, and a 5-Mb duplication in one case in the Prader-Willi/Angelman syndrome critical region on chromosome 15. A large international team (Ingason et al., 2009) also found that duplications in the 16p13.1 region containing NTAN1 and NDE1, neurodevelopmental genes previously associated with mental retardation, are three times more common in schizophrenia cases than in controls. A link between NDE1, a DISC1 binding partner, and schizophrenia in women has been previously reported (see SRF related news story).

In a clever paradigm, a French-Italian team (Guilmatre et al., 2009) combed the literature, identifying 28 candidate CNV loci that have been associated with schizophrenia, autism, or mental retardation in microarray studies. After assembling a sample of individuals representing each diagnosis roughly equally, the groups used several methods in a fine-grained analysis of the candidate loci. They found recurrent or overlapping CNVs at nearly 40 percent of these locations for all three diagnoses. A particularly strong association was found between a 350-kb deletion at 22q11 spanning the PRODH and DGCR6 genes. Deletions affecting this chromosome have been tied to schizoaffective disorder and autism (see SRF related news story). “This implies the existence of shared biologic pathways in these three neurodevelopmental conditions,” the authors write.

According to Sebat, both genomewide association and CNV studies are spurring interest in commonalities between psychiatric disorders. He says, “Clearly there is genetic overlap between psychiatric brain disorders—between schizophrenia and bipolar disorder, between schizophrenia and autism. Maybe a large set of brain genes can give rise to multiple disorders, and it’s how those genes are mutated that influences the phenotype. People have said that you can’t place autism and schizophrenia on a spectrum. Well, maybe you can.”—Pete Farley.

Etherton MR, Blaiss CA, Powell CM, Südhof TC. Mouse neurexin-1alpha deletion causes correlated electrophysiological and behavioral changes consistent with cognitive impairments. Proc Natl Acad Sci U S A. 2009 Oct 20;106(42):17998-8003. 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

Ingason A, Rujescu D, Cichon S, Sigurdsson E, Sigmundsson T, Pietiläinen OP, Buizer-Voskamp JE, Strengman E, Francks C, Muglia P, Gylfason A, Gustafsson O, Olason PI, Steinberg S, Hansen T, Jakobsen KD, Rasmussen HB, Giegling I, Möller HJ, Hartmann A, Crombie C, Fraser G, Walker N, Lonnqvist J, Suvisaari J, Tuulio-Henriksson A, Bramon E, Kiemeney LA, Franke B, Murray R, Vassos E, Toulopoulou T, Mühleisen TW, Tosato S, Ruggeri M, Djurovic S, Andreassen OA, Zhang Z, Werge T, Ophoff RA; GROUP Investigators, Rietschel M, Nöthen MM, Petursson H, Stefansson H, Peltonen L, Collier D, Stefansson K, Clair DM. Copy number variations of chromosome 16p13.1 region associated with schizophrenia. Mol Psychiatry. 2009 Sep 29. Abstract

Kirov G, Grozeva D, Norton N, Ivanov D, Mantripragada KK, Holmans P; International Schizophrenia Consortium; Wellcome Trust Case Control Consortium, Craddock N, Owen MJ, O'Donovan MC. Support for the involvement of large copy number variants in the pathogenesis of schizophrenia. Hum Mol Genet. 2009 Apr 15;18(8):1497-503. 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

Comments on News and Primary Papers

Primary Papers: Recurrent rearrangements in synaptic and neurodevelopmental genes and shared biologic pathways in schizophrenia, autism, and mental retardation.

Comment by:  Todd Lencz
Submitted 24 September 2009
Posted 25 September 2009
  I recommend this paper

The headline news on this important new paper includes: 1) strong support for a role of copy number variants (CNVs) in schizophrenia; and 2) evidence of non-specificity of phenotype between schizophrenia, autism, and mental retardation. These findings further strengthen the CNV story that has been emerging over the last few years, while still demonstrating limited (<5 percent) attributable risk.

However, the most intriguing new finding is the presence of missense alleles on the remaining chromosome in patients carrying the PRODH deletion on chromosome 22. This raises the possibility of a mode of transmission marked by compound heterozygosity. This phenomenon could account for the presence of unaffected carriers of CNVs in multiplex families, and might even help explain the multiplicity of phenotypes associated with CNVs.

More broadly, these results support the exploration of recessive models of disease, which will undoubtedly be aided in the immediate future by next-generation sequencing platforms.

View all comments by Todd LenczComment by:  Katie Rodriguez
Submitted 7 November 2009
Posted 7 November 2009

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 RodriguezComment by:  Bernard Crespi
Submitted 12 November 2009
Posted 12 November 2009

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.

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View all comments by Bernard CrespiComment by:  Suzanna Russell-SmithDonna BaylissMurray Maybery
Submitted 9 February 2010
Posted 10 February 2010

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.


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

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

Bolte, S., Poustka, F. (2006). The broader cognitive phenotype of autism in parents: How specific is the tendency for local processing and executive function. Journal of Child Psychology and Psychiatry, 47, 639-645. Abstract

Crespi, B., Badcock, C. (2008). Psychosis and autism as diametrical disorders of the social brain. Behavioral and Brain Sciences, 31, 241-261. Abstract

Grinter, E., Maybery, M., Van Beek, P., Pellicano, E., Badcock, J., Badcock, D. (2009). Global visual processing and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 1278-1290. Abstract

Grinter, E., Van Beek, P., Maybery, M., Badcock, D. (2009). Brief Report: Visuospatial analysis and self-rated autistic-like traits. Journal of Autism and Developmental Disorders, 39, 670–677. Abstract

Mason, O., Linney, Y., Claridge, G. (2005). Short scales for measuring schizotypy. Schizophrenia Research, 78, 293-296. Abstract

Russell-Smith, S., Maybery, M., Bayliss, D. Are the autism and positive schizotypy spectra diametrically opposed in local versus global processing? Journal of Autism and Developmental Disorders. 2010 Jan 28. Abstract

Witkin, H., Oltman, P., Raskin, E., Karp, S. (1971). A manual for the Embedded Figures Test. Palo Alto, CA: Consulting Psychologists Press.

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Comments on Related News

Related News: Chromosome 22 Link to Schizophrenia Strengthened

Comment by:  Anthony Grace, SRF Advisor (Disclosure)
Submitted 5 November 2005
Posted 5 November 2005

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

Related News: Chromosome 22 Link to Schizophrenia Strengthened

Comment by:  Caterina Merendino
Submitted 5 November 2005
Posted 5 November 2005
  I recommend the Primary Papers

Related News: Chromosome 22 Link to Schizophrenia Strengthened

Comment by:  Leboyer Marion
Submitted 6 November 2005
Posted 6 November 2005
  I recommend the Primary Papers

Related News: Chromosome 22 Link to Schizophrenia Strengthened

Comment by:  Anne Bassett
Submitted 7 November 2005
Posted 7 November 2005
  I recommend the Primary Papers

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.

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

View all comments by Anne Bassett

Related News: DISC1 Delivers—Genetic, Molecular Studies Link Protein to Axonal Transport

Comment by:  Akira Sawa, SRF Advisor
Submitted 12 January 2007
Posted 12 January 2007

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.

View all comments by Akira Sawa

Related News: DISC1 Delivers—Genetic, Molecular Studies Link Protein to Axonal Transport

Comment by:  Luiz Miguel Camargo (Disclosure)
Submitted 13 January 2007
Posted 13 January 2007

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.).

View all comments by Luiz Miguel Camargo

Related News: Autism Genes: A Handful, or More?

Comment by:  Daniel Weinberger, SRF Advisor
Submitted 19 March 2007
Posted 19 March 2007

Sense and Nonsense: General Lessons from Genetic Studies of Autism
The capability to characterize genetic variation across the entire genome in one fell swoop has generated considerable enthusiasm and expectation that the important genes for mental illness will “finally” be found. Whole genome association (WGA) is being touted as the path to genetic success in psychiatry. Is this sensible? Before considering the likely successes and limitations of this new capability, it is worth reminding ourselves of how we got here.

With respect to schizophrenia, over 50 years of studies of twin samples and of infants adopted away at birth have demonstrated that the lion’s share of risk for schizophrenia is determined by genes, to the tune of over 70 percent of the variance in liability (“heritability”). Family segregation studies have shown that the pattern of relative risk across relationships is most consistent with at minimum oligogenic inheritance, and more likely polygenic inheritance (Gottesman, I. I., Schizophrenia Genesis: The Origin of Madness, New York: W.H. Freeman.1991). After over a decade of linkage studies, it is clear that across diverse family samples, schizophrenia is not related to a common genetic locus, and no locus accounts for more than a fraction of risk for illness. Because we know that schizophrenia is highly heritable, the failure of linkage to reveal a chromosomal locus providing a highly significant LOD score in most samples is not because there are no genetic variations accounting for the heritability, but because, among other reasons, there is just too much locus heterogeneity across samples.

If we accept that schizophrenia is polygenic and genetically heterogeneous, meaning that in any sample under study, some cases will be ill because they have risk genes W, X, Y, and Z, while other cases will be ill because they have risk genes C, D, E, and F, then any common linkage signals will be diluted by this genetic heterogeneity if these genes are spread throughout the genome. In light of this situation, why, then, have some recent linkage studies of schizophrenia revealed significant and replicable linkage regions? Notwithstanding improvement in ascertainment methods and the informativeness of DNA marker sets, it is likely that linkage has worked in some regions of the genome because some of the genetic heterogeneity is concentrated in these areas, meaning that heterogeneity across families does not necessarily dilute the linkage signal at these loci. For example, in the 8p linkage peak, there are at least five genes that have been found to show association with schizophrenia in various samples: NRG1, PCM1, PPP3CC, DRP2, and FZD3, so if 10 percent of the families have risk alleles in NRG1 that contribute to their risk profile, and even if 10 percent have no NRG1 risk alleles but PCM1 alleles, and the same for PPP3CC and so on, this genetic heterogeneity will not dilute the linkage signal and the 8p locus containing these five genes will be positive in these families. Of course, in a subsequent association study, samples will be positive or negative for any one of these individual genes depending on which alleles happen to be enriched in that sample. This is how heterogeneity affects the prospects for positive linkage and association. Many observers of psychiatric genetics who argue against the validity of linkage and association in psychiatry like to talk about multifactorial medical illnesses such as heart disease and schizophrenia being genetically heterogeneous, but they do not like the walk when it comes to acknowledging the implications for finding association, positive or negative.

Heterogeneity has obvious implications for studies that attempt to survey variation in the entire genome and compare allele frequencies across ill and well samples. Heterogeneity in such studies dilutes the statistical effect of any single DNA polymorphism in the entire sample. Because literally hundreds of thousands of variations may be typed at one time, many of which have no prior probability of being related to the phenotype of interest, it is critical to employ some approach to statistical correction for the possibility of random positive associations. If one were to correct for 500,000 tests, the likelihood that any SNP related to a condition like schizophrenia will survive this level of correction, at least to the extent that the illness is polygenic and heterogeneous, is very small. Based on the strength of the existing data, none of the well-supported candidate susceptibility genes for schizophrenia that have been identified to date (e.g., DTNPB1, NRG1, DISC1, etc.) would survive such correction. It has been argued that the solution to this conundrum is the collection of very large datasets. This may increase power and generate impressive p values for a few genes, but the effect size of the association does not change with sample size, only the p value. It is also important to remember that the larger the sample size, the greater the potential for heterogeneity, because the collection of very large samples often requires multiple collection centers, each with their own ascertainment quirks. Thus, this approach runs the risk of a paradoxical reduction in the strength of linkage and association (see Brzustowicz, 2007).

These considerations have implications for studies of the genetic origins of other neuropsychiatric disorders, such as depression, bipolar disorder, anxiety disorders, and autism. Two recent important papers related to autism illustrate each of these points and offer important lessons for WGA studies that will be emerging soon related to schizophrenia and other psychiatric disorders.

The paper by the Autism Genome Project Consortium (AGPC) reports the largest linkage study of families (over 1,490 families) with children having the autism spectrum syndrome and the most informative set of linkage markers yet reported. This study illustrates in dramatic detail the complications alluded to above. Many areas of the genome show evidence of linkage, i.e., locus heterogeneity, but the individual signals are statistically weak. Indeed, using strict criteria for statistical analysis, no region would have been considered positive, and the region that was closest (11p12-13) was not identified as a promising region in earlier linkage studies.

In a series of exploratory post-hoc reanalyses of the data, trying to create more theoretically homogeneous clinical samples (e.g., gender specific, narrower diagnosis), several linkage signals became slightly more positive, but also involving regions of the genome not highlighted in earlier linkage studies. Does this failure to find an impressive statistical result in such an impressively large sample mean that this study is negative? Not if we expect autism to be genetically complex in the ways enumerated above. The results are exactly what would be predicted. Indeed, similar results have been reported before (Risch et al., 1999). The AGPC study also discovered regions where evidence of genomic structural changes, so-called sequence copy number variations (CNVs), might be associated with clinical diagnosis. Their data suggest that as many as 253 CNVs were discovered in 196 cases. The CNVs were found in many chromosomal regions (i.e., locus heterogeneity); involved duplications more often than deletions; varied considerably from one family to another; were spontaneous in most cases but inherited in some; and were most often found only in one individual, though recurrences occurred across ill subjects in some instances. It is very difficult to determine from these data how much of the genetic contribution to autism in this sample is explained by these copy number variations. In a few families, where multiple affected individuals had the same deletion, the data look convincing. However, it appears that CNVs were just as frequent, just as large (average 3.4 Mb) and just as likely to be duplications or deletions in the unaffected siblings of the children with autism.

The paper by Sebat and colleagues surveys the genome exclusively for evidence of structural changes related to variable copy numbers of DNA sequences and uses a putatively more sensitive method. They discovered submicroscopic deletions of 17 chromosomal regions in 14 children with autism spectrum disorder (7 percent of their ill sample). By design, all of the deletions described in this report were de novo, or spontaneous, meaning they were not found in the parents of the affected offspring and were thus not inherited. In other words, these deletions do not explain the very substantial heritability of autism, nor did they map to the regions of the genome that have shown up in linkage studies, which look specifically for loci that contribute to heritable risk (including the regions in the AGPC), nor did they highlight genes that have emerged from linkage studies as likely candidates accounting for the heritability of autism. Moreover, with one exception, all of the deletions were private, meaning they occurred in only one individual. As Sebat and colleagues point out, however, the infrequency of these copy number variations does not preclude them from pointing to more generalizable insights about genetic risk factors that operate in other cases. The genes affected by these infrequent structural variations may in other cases show common variations (e.g., SNPs) that contribute more widely to genetic liability. It is not clear how much overlap there is between the findings of these two studies, but clearly there are major differences.

The bottom line here is that genetic heterogeneity appears to be the rule in autism. While most cases are related to a complex set of inherited risk factors, some may be related to spontaneous genetic lesions, with many different lesions producing a similar clinical phenotype. None of this should surprise us, as diverse congenital encephalopathies can manifest the autism syndrome, e.g., fragile X syndrome, Rett syndrome, tuberous sclerosis. From a genetic point of view, autism is a syndrome that can be reached from many directions, along many paths. It is not likely that autism is any more of a discrete disease entity than, say, blindness or mental retardation.

So where does this leave us with respect to the goal of fully defining the genetic origins of mental disorders such as schizophrenia? The current list of promising candidate genes for schizophrenia is growing rapidly, and some already are leading to insights about potential pathophysiologic mechanisms and potential treatment targets (Straub and Weinberger, 2006). Genome variation scans will hopefully uncover many more novel genes that contribute to the risk for schizophrenia, and regardless of their outcome, these types of studies will be very important. It is likely that within the next 5 years we will have a good sense of all the common genetic variants that contribute to schizophrenia across many world samples. It is also likely that some cases will be related to structural variations (e.g., the 22q11 deletion associated with the velocardiofacial syndrome [VCFS]), both spontaneous and inherited. But, a phoenix rising from this newest chapter of investigation is not likely. Rather, as the recent autism studies illustrate, many genetic loci and many genes, again each accounting for only a relatively small percentage of ill subjects, will likely be the legacy of these studies. It is the legacy of all the work up to this point, and it is not likely to be different now that we can do many more of the same SNP assays all at one time. I doubt that genes that are discovered via WGA or related approaches will show greater effect sizes than the current top candidates, but there certainly will be more of them. Schizophrenia, like autism, is almost certainly a disorder that can be reached from many directions, along many paths. This being said, is it likely that a few genes with “highly significant” p values will be observed in a few of the multitude of WGA studies that will hit the press over the next year or two? Of course it is. Will these be the most important genes? Not necessarily. The challenge for our using these new data will be to make strategic choices about which of the various signals to pursue further and how to pursue them. The most important genes will be the ones that can be translated into meaningful information about disease mechanisms, therapeutic target identification, and clinical prediction.

View all comments by Daniel Weinberger

Related News: Autism Genes: A Handful, or More?

Comment by:  Paul Patterson
Submitted 21 March 2007
Posted 22 March 2007

Regarding the very high "heritability" of schizophrenia and autism: these values are usually based on twin studies, and there is good reason to be skeptical about these numbers.

For instance, the frequency of schizophrenia in dizygotic twins is twice as high as for siblings, suggesting a role for the fetal environment. Second, the concordance for monozygotic twins is 60 percent if they share a placenta, but only 11 percent if they have separate placentas, again highlighting the importance of the fetal environment. (Two-thirds of monozygotic twins share a placenta.) It is also relevant that roughly two-thirds of schizophrenia subjects do not have a primary or secondary relative with the disorder.

No one questions that genes play a role in the risk for schizophrenia and autism, but twins share a fetal environment as well as genes. The importance of the fetal environment is very well illustrated by the work of Brown and colleagues in their studies of the risk factor, maternal respiratory infection.


Phelps J, Davis J, Schartz K. Nature, Nurture, and Twin Research Strategies. Curr. Directions in Pyschol. Sci. 1997;6:117-120.

Brown AS. Prenatal infection as a risk factor for schizophrenia. Schizophr Bull. 2006 Apr;32(2):200-2. Epub 2006 Feb 9. Abstract

Brown AS, Susser ES. In utero infection and adult schizophrenia. Ment Retard Dev Disabil Res Rev. 2002;8(1):51-7. Review.

Ryan B, Vandenbergh J. Intrauterine position effects. Neuroscience and Biobehavioral Reviews. 2002;26:665–678. Abstract

View all comments by Paul Patterson

Related News: Autism Genes: A Handful, or More?

Comment by:  Ben Pickard
Submitted 24 March 2007
Posted 24 March 2007

The Curious Incident of the Gap in the Chromosome
Our bodies are accustomed to a double dose of genes. The cellular ecosystem has been evolutionarily fine-tuned to this baseline of gene expression. Even the exceptions to the rule such as the sex-specific imbalance of X/Y chromosomes or the set of imprinted genes serve to highlight the compensatory mechanisms that have allowed the cell to adapt. Therefore, it is not surprising that chromosomal dosage changes are associated with disease states.

An ever-increasing appreciation of the link between disease and gene copy number has followed closely behind advances in techniques that have enabled the measurement of copy number variation at ever-greater resolution and sensitivity. Starting with Giemsa-stained chromosomes in classical cytogenetics, which identified visible aneuploidies such as trisomy 21, the field has progressed through fluorescence in situ hybridization (FISH) studies which pinpointed finer abnormalities, including those discovered through comparative genomic hybridization and sub-telomeric analysis, to today’s chip-based approaches, which can survey the whole genome at once. (In fact, as an aside, the sensitivity of the current state-of-the-art techniques is only likely to be truly improved upon with the advent of whole-genome sequencing—realistically, that is not likely for a decade or so.)

Despite this progress, the one-off nature and scarcity of many chromosome abnormalities have often led to their dismissal as genetic quirks and not relevant to disease biology at the population level. Perhaps the tide is now turning in their favor as recent studies of sub-microscopic gene copy number changes have yielded intriguing and provocative discoveries. The two papers summarized on this site asked whether a proportion of autism spectrum disorders are caused by CNVs. The same question could, and doubtless will, be asked of schizophrenia, bipolar disorder, and other psychiatric conditions and so is worthy of discussion in this forum. The answer for autism seems to be a resounding “yes,” and this is likely to precipitate a sea change in autism research, both at the genetic and biological levels. Sebat et al. (Science, 15 March, 2007) and The Autism Genome Project Consortium (“AGPC,” Nature Genetics, 18 February, 2007) used slightly different variations on the chip theme in their studies: the former had the advantage of a more discrete output for copy number compared to the continuous distribution from the latter approach. This had consequences for the setting of statistical detection thresholds, but both groups were quite thorough in the confirmation of many of their findings using secondary detection approaches.

Understanding the Consequences of Experimental Design: Choice of Samples and Assessment
The samples chosen for analysis by both research groups focused on nominally family-based collections rather than sporadic cases. Thus, the mutations represented are highly likely to be of higher penetrance and relatively rare. In my opinion, the high level of locus heterogeneity that accompanies such a sample set makes the multiple-family linkage approach unlikely to yield practical dividends—indeed, the linkage component from the AGPC group is the least impressive aspect of their paper. The main linkage peak at 11p12-p13 was not a replication of the typical autism linkage findings (e.g., chromosome 7q, etc.; for review see Klauck, 2006). Additionally, above-threshold LOD scores were not significantly improved when diagnostic boundaries were changed or CNV carriers removed from the data. In fact, one of the most impressive features of the Sebat paper was the enlightened subdivision of the samples based not on phenotype, but rather by the nature of the inheritance patterns of autistic spectrum disorders within the families (the same may be true for the AGPC data, but the information is not explicitly categorized). This stratification into “simplex” (single case within the family) and “multiplex” (more than one affected individual) must be telling us something about the genetic architecture of complex genetic disorders. The results indicate that de novo CNVs were four times more common in the simplex families than multiplex. Let’s examine a hypothetical explanation for this finding. First, the simplex families may not be, or rather may not go on to be, true “families” in the genetic sense—their mutations are of the lower penetrance, “susceptibility altering” class. Such CNV mutations would not produce the densely affected families that are so attractive to gene mappers and so will never be collected and categorized as “multiplex.” The fact that three CNV regions (2q37.3, 3p14.2, and 20p13) are independently present twice in the Sebat simplex group adds weight to these CNVs being “common” risk variants—perhaps they are ripe candidates for a case-control association study in a larger simplex/sporadic cohort? The type of CNVs present in the multiplex families are, by definition, of sufficient penetrance for the multiplex classification to become possible: this class of mutations will probably be rarer. One supportive observation for the distinction between the two CNV types rests on the fact that there is no overlap between identified multiplex and simplex CNV regions—will that remain the case as further studies are carried out? Another, from the AGPC paper, is that many of their familial CNVs lie over previously identified linkage hotspots or known balanced chromosomal rearrangements (breakpoints, see below).

However, two mysteries remain: the predominance of CNV deletions in the Sebat paper compared to the stated overrepresentation of duplications in the AGPC paper. Whether this is a technical or family sample choice issue remains to be elucidated. Secondly, and perhaps more vague a problem, is the seldom addressed nature of the mutations identified in neuropsychiatric disorders. The archetypal mutations we learn about in undergraduate lectures, primarily in the context of neoplasms, include gain-of-function (oncogenes), loss-of-function (tumor suppressors), dominant negative and so on. Chromosome abnormalities in general, and CNVs in particular, seem to suggest that autism spectrum disorder (ASD), schizophrenia, and bipolar disorder are diseases in which gene dosage changes are the only pathological mechanism. Is this a real biological phenomenon or merely a methodological ascertainment bias? If the latter, how might we better adapt our gene hunting strategies to target other forms of mutation?

A Gene in the Hand Is Worth 50 Under a Linkage Peak
In the warm afterglow of an experimental tour-de-force, the biological ramifications can sometimes be sidelined. What genes have these CNVs affected and what does this tell us about the biology of autism spectrum disorder, we can ask, not forgetting that this work should be considered in the context of the history of other genetic and biological studies on ASD.

The first, and perhaps most impressive, finding is that of a CNV covering the Neurexin 1 (NRXN1) gene. The protein encoded by this gene interacts with a family of receptors called Neuroligins. Interestingly, Neuroligin 3 (NLGN3) and Neuroligin 4 (NLGN4) have been linked to ASD through chromosome abnormalities and mutations detected in rare cases. Moreover, SHANK3 has recently been identified as an ASD candidate through the study of cytogenetic abnormalities and several point mutations. SHANK3 protein has also been demonstrated to bind to neuroligins. This amazing convergence is reminiscent of another recent celebrity pairing in the schizophrenia field: the discovery of DISC1 and PDE4B through independent chromosome abnormalities followed by the discovery that their proteins functionally interact. The identification of these four ASD candidate genes is likely to stimulate much research into this nascent signaling pathway, particularly in the context of its supposed role in synaptogenesis.

Many of the CNVs affect gene clusters, and only by analyzing multiple overlapping deletions or systematically examining the gene candidates individually will the causative ASD genes be identified. This seems to be the case for the genes ZFP42 and PACRG, which have been found both in large CNVs with multiple genes affected and singly in smaller CNVs. Several additional CNVs were identified which were small enough, or within large enough genes (large size seems to be a anecdotally reported feature of genes identified through a variety of cytogenetic approaches) to implicate just that gene. These include SLC4A10, FLJ16237, A2BP1, NFIA, GAB2, PCDH7, PCDH9, CDH8, C18orf58, FHOD3, C2orf10, MAN2A1, CSMD1, and TRPM3 as a conservative selection. Two aspects of biology immediately spring to mind when viewing these genes. Firstly, the three members of the cadherin family identified fall into the same biological role as the neuroligins, namely cell adhesion. A related gene, FAT, has also been implicated in familial bipolar disorder. Secondly, the identification of MAN2A1 encoding a component enzyme in the pathway which post-translationally modifies proteins through glycosylation adds another gene from this process to a list including ALG9/DIBD1 and MGAT5 , both of which have been implicated in psychiatric illness. Together with the list of genes identified through CNV analysis, one can add USP6, NBEA, ST7, AUTS2, SSBP1, GRPR, and SHANK3, discovered in previous studies of autism spectrum disorder chromosome abnormalities. These candidates (and those identified in the psychoses) provide a wealth of resources for future functional and genetic studies. However, on the journey to a more rigorous biological definition of ASD, it may be a mistake to attempt to squeeze the functions of these genes into one unifying but unhelpfully vague cellular grouping, e.g., “signal transduction” or “metabolism.” Rather, biological investigations might benefit from trying to place these disparate genes in the context of their roles in the functioning of the brain regions or subsystems in which they are expressed. A hard task undoubtedly, but an endeavor that is likely to provide us with a more holistic understanding of the conditions.

View all comments by Ben Pickard

Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Daniel Weinberger, SRF Advisor
Submitted 27 March 2008
Posted 27 March 2008

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.

View all comments by Daniel Weinberger

Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  William Honer
Submitted 28 March 2008
Posted 28 March 2008
  I recommend the Primary Papers

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.


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


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

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Todd LenczAnil Malhotra (SRF Advisor)
Submitted 30 March 2008
Posted 30 March 2008

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.


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

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Ben Pickard
Submitted 31 March 2008
Posted 31 March 2008

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.


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

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Christopher RossRussell L. Margolis
Submitted 3 April 2008
Posted 3 April 2008

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.


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

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Michael Owen, SRF AdvisorMichael O'Donovan (SRF Advisor)George Kirov
Submitted 15 April 2008
Posted 15 April 2008

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.


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

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Related News: Copy Number Variations in Schizophrenia: Rare But Powerful?

Comment by:  Ridha JooberPatricia Boksa
Submitted 2 May 2008
Posted 4 May 2008

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.


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.

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Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  David J. Porteous, SRF Advisor
Submitted 11 February 2009
Posted 12 February 2009

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.


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

View all comments by David J. Porteous

Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  Pamela DeRosseAnil Malhotra (SRF Advisor)
Submitted 19 February 2009
Posted 22 February 2009

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.


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

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Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  James L. Kennedy, SRF Advisor (Disclosure)
Submitted 25 February 2009
Posted 25 February 2009

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

Related News: Copy-number Variants, Interacting Alleles, or Both?

Comment by:  Kevin J. Mitchell
Submitted 2 March 2009
Posted 2 March 2009

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.


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

View all comments by Kevin J. Mitchell

Related News: Autism Exome: Lessons for Schizophrenia?

Comment by:  Patrick Sullivan, SRF Advisor
Submitted 20 April 2012
Posted 23 April 2012
  I recommend the Primary Papers

Fascinating papers that likely presage work in the pipeline from multiple groups for schizophrenia. Truly groundbreaking work by some of the best groups in the business. Required reading for those interested in psychiatric genomics.

The identified loci provide important new windows into the neurobiology of ASD.

The results also pertain to the longstanding debate about the nature of ASD: does it result from many individually rare, Mendelian-like variants (potentially a different one in each person) and/or from the summation of the effects of many different common variants of subtle effects?

The multiple rare variant model now seems unlikely for ASD as, contrary to the expectations of some, ASD did not readily resolve into a handful of Mendelian-like diseases. (This comment is of course qualified by the limits of the technologies - which have, however, identified causal mutations for many monogenetic disorders.)

Readers might also want to read Ben Neale's comments on these papers at the Genomes Unzipped website.

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Related News: Chromosomal Mishaps in Autism Harbor Schizophrenia Candidate Genes

Comment by:  Ben Pickard
Submitted 23 May 2012
Posted 24 May 2012

The paper by Talkowski and colleagues describes the application of cutting edge genomics techniques to the molecular characterisation of multiple balanced chromosomal abnormalities (BCAs) linked to autism, autism spectrum disorders, and general neurodevelopmental disorders. In a single publication it has probably assigned more candidate genes than the entire conventional cytogenetic output from schizophrenia and autism in the preceding 15 years.

The authors carry out a great deal of complementary genomic analyses which add to the strength of their argument that these genes are indeed causally involved in illness. Without these additional data there would be one potential criticism of the paper in that the same power of analysis was not applied to BCAs in healthy controls. This is an important ascertainment issue because previous studies have not only identified disrupted genes in the healthy population (Baptista et al., 2005) but also shown that CNVs deregulating specific genes may only show an increased—as opposed to exclusive—representation in the ill population.

The observed overlaps between some of the identified BCA genes in ASD/neurodevelopmental disorders and those identified in GWAS studies of schizophrenia and bipolar disorder is fascinating but may be a double-edged sword. On the one hand, support for rare genetic contributors (CNVs/sequence variants/BCAs) to complex genetic disorders has often been drawn from those that are co-incident between studies. In that respect, this study is remarkable for highlighting the same genes from methods that detect very different mutation types. I’m genuinely surprised that there appears to be a convergence of ancient (read subject to evolutionary selection/population effects) and recent (meaning random) mutations. On the other hand, there is the disconcerting possibility that schizophrenia GWAS are only powered to detect the causes of blunt neurodevelopmental disturbances (which are perhaps less sensitive to issues of diagnostic categorisation) and not the fine-grained genetic hits that determine a precise clinical endpoint. If this is the case then we could end up with a situation where the genotypic distance between disorders is apparently much less than the phenotypic distance. This is most likely an extreme outcome that will be remedied once the genomic analysis of complex genetic disorders is able to factor in the composite effects of BCAs, CNVs, rare SNPs, and common SNPs—at the level of the single individual, and perhaps conditioned on the presence of big neurodevelopmental hits.

Quite logically, the presence of genes spanning diagnoses has been explained in terms of shared predisposition derived from early neurodevelopmental insults that are subsequently pushed down diagnostic pathways by other genetic or environmental factors. However, this assumption needs formal testing. The problem is reminiscent of the debate that circled the early use of constitutive mouse knockouts: how is it possible to disentangle developmental from adult functional phenotypes in a null? The advent of inducible Cre-LoxP technologies allowed that question to be directly addressed and may be the means to test the neurodevelopmental contribution of diagnosis-spanning candidate genes such as TCF4.

Could the approach detailed in this paper be applied directly to schizophrenia? It would certainly add substantially to the ‘confirmed’ gene list and would detect any reciprocal relationships with ASD/neurodevelopmental disorders. One issue is that ASD appears to have a higher overall incidence of chromosomal and genomic structural rearrangements than schizophrenia, but perhaps the greater question is availability of an appropriate sample set. The concerted cytogenetic screening that took place in Scotland coupled with an ability to cross-reference these findings with incidence of psychiatric disorder was instrumental in the discovery of DISC1 and other genes in Scotland (Muir et al., 2008) but this resource is now largely exhausted of relevant BCAs. To my knowledge, the Danish registry represents the best bet for such an approach to succeed for schizophrenia (Bache et al., 2006).


Baptista J, Prigmore E, Gribble SM, Jacobs PA, Carter NP, Crolla JA. Molecular cytogenetic analyses of breakpoints in apparently balanced reciprocal translocations carried by phenotypically normal individuals. Eur J Hum Genet. 2005 Nov;13(11):1205-12. Abstract

Muir WJ, Pickard BS, Blackwood DH. Disrupted-in-Schizophrenia-1. Curr Psychiatry Rep. 2008 Apr;10(2):140-7. Abstract

Bache I, Hjorth M, Bugge M, Holstebroe S, Hilden J, Schmidt L, Brondum-Nielsen K, Bruun-Petersen G, Jensen PK, Lundsteen C, Niebuhr E, Rasmussen K, Tommerup N. Systematic re-examination of carriers of balanced reciprocal translocations: a strategy to search for candidate regions for common and complex diseases. Eur J Hum Genet. 2006 Apr;14(4):410-7. Abstract

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Related News: Chromosomal Mishaps in Autism Harbor Schizophrenia Candidate Genes

Comment by:  Patrick Sullivan, SRF AdvisorJin Szatkiewicz
Submitted 29 May 2012
Posted 29 May 2012
  I recommend the Primary Papers

In this exceptional paper, the authors combined new technology with old-school genomics to deliver convergent data about the genomic regions that predispose to neuropsychiatric disorders. The first goal of psychiatric genetics is to identify the “parts list,” an enumeration of the genes and genetic loci whose alteration clearly and unequivocally alters risk. The results of this intriguing paper connect rare and powerful genomic disruptions with loci identified via common variant genomewide association screens.

A classical approach in human genetics is to study affected individuals with balanced translocations. Using next-generation sequencing, these authors identified the precise locations of 38 rare balanced chromosomal abnormalities in subjects with neurodevelopmental disorders. They identified 33 disrupted genes, of which 22 were novel risk loci for autism and neurodevelopmental disorders. The other disrupted genes included many that had previously been identified by genomic searches for rare variation and common variation (e.g., AUTS2, CHD8, TCF4, and ZNF804A).

The authors then sought secondary genomic support for disease association with these 33 risk loci by analyzing a large collection of psychiatric GWAS data. They found an increased burden of copy number variants (CNVs) among cases as well as a significant enrichment of common risk alleles among both autism and schizophrenia cases. This research suggests that autism and neurodevelopmental disorders may have commonalities with psychiatric disorders such as schizophrenia at the molecular level, underscoring the complexity of genetic contribution to these conditions.

CNVs discovered from microarrays are mainly large, rare CNVs spanning multiple genes. Exome sequencing is limited to coding regions of the genome. In contrast, as illustrated in Talkowski et al. (2012), it is possible to identify individual lesions with nucleotide resolution in both coding and non-coding regions. Thus, this research suggests that sequencing individuals with pathogenic balanced translocations could provide a complementary strategy for mutation identification and gene discovery.

The experimental procedures were technically well done; all BCA breakpoints were confirmed by PCR and capillary sequencing. In seeking the secondary genomic support, the authors were keen on evaluating and eliminating the possibility for any confounding factors that may cause spurious association. For example, CNV burden analysis was conducted with respect to differential sensitivities from microarrays, and all results remained robust to various subset analyses and to one million simulations designed to establish empirical significance. To examine the potential for spurious enrichment of common risk alleles, the authors additionally conducted identical analysis in phenotype-permuted datasets from well-powered GWAS data for schizophrenia and autism as well as in well-powered GWAS data for eight unrelated traits, and therefore eliminated unforeseen confounders.

Impressively, many of the loci identified here now have convergent genomic results with support across multiple different samples and technical approaches. For example, TCF4 harbors common variation identified via GWAS, a Mendelian disorder, and now a gene disruption. These convergent genomic results markedly increase confidence that TCF4 is truly in the “parts list” for neurodevelopmental disorders. In contrast, there remain multiple questions about the genomic evidence for DISC1, where such convergence has not been achieved.

This paper also provides important results relevant to resolving the rare “versus” common variation debate. This appears to be a false dichotomy where, often, both rare and common variations contribute to the parts lists for these disorders.

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Related News: Chromosomal Mishaps in Autism Harbor Schizophrenia Candidate Genes

Comment by:  Bernard Crespi
Submitted 29 May 2012
Posted 29 May 2012
  I recommend the Primary Papers

Balanced chromosomal abnormalities (BCAs) provide extremely useful alterations for linking of specific loci with psychiatric conditions, because they exert penetrant effects and localize to specific genes. The recent study by Talkowski et al. (2012) used direct sequencing of breakpoints, based on 38 subjects, to generate a set of genes with putative links to different neurodevelopmental disorders, broadly construed as including autism spectrum disorders, intellectual disability, and/or developmental and other delays.

One of the most striking results from their study was the presence, in their set of breakpoint-altered genes, of five genes that have been associated from other work with schizophrenia and related psychotic-affective spectrum disorders (such as bipolar disorder and major depression), including TCF4, ZNF804A, PDE10A, GRIN2B, and ANK3. These results suggest, according to the authors, the presence of shared genetic etiology for ASD, schizophrenia, and other neurodevelopmental disorders (mainly developmental delays). The authors also show overlap of their gene list with results from CNV and GWAS of autism and schizophrenia, further suggesting genetic links between these two conditions.

Do these results mean that autism and schizophrenia share genetic risk factors? Perhaps, but also perhaps not. Two important caveats apply.

First, schizophrenia involves well-documented premorbidity, in a substantial proportion of cases, that centers on developmental, social, and language deficits and delays (e.g., Saracco-Alvarez et al., 2009; Gibson et al., 2010). In children, premorbidity to schizophrenia most commonly involves "negative" symptoms, including deficits in social interaction (Remschmidt et al., 1994; Tandon et al., 2009), which can overlap with symptoms of autism spectrum disorders (Goldstein et al., 2002; Sheitman et al., 2004; Tjordman, 2008; King and Lord, 2011). Males are more severely affected, as in autism (Sobin et al., 2001; Rapoport et al., 2009; Tandon et al., 2009). Schizophrenia mediated by CNVs, or BCAs, is likely to exhibit relatively high levels of premorbidity, due to the penetrant, syndromic, and deleterious nature of these alterations (Bassett et al., 2010; Vassos et al., 2010). A recent study by Sahoo et al. (Sahoo et al., 2011) provides evidence consistent with such premorbidity, in that of over 38,000 individuals (predominantly children) referred for developmental delay, intellectual disability, autism spectrum disorders, or multiple congenital anomalies, 704 exhibited one of seven CNVs (del 1q21.1, dup 1q21.1, del 15q11.2, del 15q13.3, dup 16p11.2, dup 16p13.11, and del 22q11.2) that have been statistically associated with schizophrenia in studies of adults (Levinson et al., 2011).

These findings suggest that the subjects in Talkowski et al. (Talkowski et al., 2012), (most of them children, for individuals with age data given) who harbor alterations to schizophrenia-associated genes may, in fact, be severely premorbid for schizophrenia. Diagnoses of ASD (commonly PDD-NOS) in such individuals may represent either false positives (Eliez, 2007 ; Feinstein and Singh, 2007), or true positives, with ASD as a developmental stage followed, in some individuals, by schizophrenia. This latter conceptualization considers autism as akin to childhood schizophrenia, a view which contrasts sharply with the classic criteria derived from Kanner (Kanner, 1943), Asperger (1991) and Rutter (Rutter, 2000, Rutter, 1972, Rutter, 1978), who consider autism as a lifelong condition present from early childhood. Of course, diagnosing premorbidity to schizophrenia as such is challenging, but if any data can help, it is data from highly penetrant alterations such as CNVs and BCAs, as well as from biological and neurological (rather than just behavioral) phenotypes.

Second, association to an overlapping set of genes need not make two disorders similar, or similar in their genetic etiology. For example, as noted by Talkowski et al. (Talkowski et al., 2012), variation in TCF4 has been associated with both Pitt-Hopkins syndrome and schizophrenia, but these conditions show essentially no overlap in phenotypes. Similar considerations apply to CACNA1C, linked to the autism-associated Timothy syndrome (via an apparent gain of function) as well as to schizophrenia and bipolar disorder. A key to sorting out the huge clinical and genetic heterogeneity in autism, and in schizophrenia, is subsetting of cases by similarity in alterations to pathways and phenotypes. Lumping of autism with schizophrenia, based on overlap in risk loci without consideration of the nature of the overlap, will make such subsetting all the more difficult.

Data on genes disrupted by balanced translocations are tremendously useful, but their usefulness will, as for other data such as CNVs, be circumscribed by diagnostic considerations, especially when the subjects are children. Bearing in mind the possibility that some childhood diagnoses may represent false positives, and that overlap in genes need not mean overlap in causation, should help in moving the study of both autism and schizophrenia forward.


Asperger H; translated and annotated by Frith U (1991) [1944]. Autistic psychopathy' in childhood. In Frith, U. Autism and Asperger syndrome. Cambridge University Press. pp. 37-92.

Bassett AS, Scherer SW, Brzustowicz LM. Copy number variations in schizophrenia: critical review and new perspectives on concepts of genetics and disease. Am J Psychiatry. 2010;167(8):899-914. Abstract

Eliez S. Autism in children with 22q11.2 deletion syndrome. J Am Acad Child Adolesc Psychiatry. 2007;46(4):433-4. Abstract

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

Gibson CM, Penn DL, Prinstein MJ, Perkins DO, Belger A. Social skill and social cognition in adolescents at genetic risk for psychosis. Schizophr Res. 2010;122(1-3):179-84. Abstract

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Related News: Family Roots for Autism, Schizophrenia, Bipolar Disorder

Comment by:  Bernard Crespi
Submitted 30 July 2012
Posted 30 July 2012

In a new paper in Archives of General Psychiatry that has received considerable media attention, Sullivan et al. (Sullivan et al., 2012) use register data from Sweden and Israel to show higher rates of ASDs among individuals with family histories of schizophrenia and bipolar disorder. The authors interpret these results as indicating that ASD, schizophrenia, and bipolar disorder share etiology. This is a very interesting hypothesis that, if supported, would have important implications for our understanding of the genetic underpinnings of schizophrenia in relation to other conditions. However, two alternative hypotheses not involving shared causation may, at least in part, help to explain their results.

First, a recent set of studies demonstrates that drug treatments for schizophrenia and bipolar disorder increase the incidence of ASDs, or their biologically based phenotypic correlates, in offspring. Croen et al. (Croen et al., 2011) reported that prenatal exposure to antidepressants (SSRIs) was associated with a twofold increase in risk of ASD. It is also notable that hyperserotoninemia has also been found in about one-third of autism cases (Burgess et al., 2006). Fetal exposure to the mood stabilizer valproate has been associated with a sevenfold increase in ASD risk (Bromley et al., 2008), and also serves as a model system for autism in animal studies. Use of clozapine and olanzapine during pregnancy has been associated with increased offspring head circumference (Bodén et al., 2012), which represents another well-validated correlate of autism (Courchesne et al., 2011). Moreover, environmental exposure to three psychoactive drugs (fluoxetine, venlafaxine, and carbamazepine) has been demonstrated to cause gene-expression changes that resemble those seen only in autism (Thomas and Klaper, 2012).

These results may help to explain mother-offspring and sib-sib associations of schizophrenia and bipolar disorder with ASDs. Such effects might be expected to be higher than those seen for fathers, but data were not presented in the report by Sullivan et al. on such parental sex differences. Effects of pharmacological treatment of fathers on ASD risk in offspring apparently have yet to be investigated, although paternal effects on offspring psychopathology and epigenetic profiles have been reported with regard to such factors as age (Hultman et al., 2011), and stress (Essex et al., 2011).

Second, the authors' data may also be attributable in part to false-positive diagnoses of premorbidity to schizophrenia (or bipolar disorder) as ASD in children, and conflation of schizotypal personality disorder (SPD) with high-functioning autism and Asperger's syndrome. Premorbidity to schizophrenia occurs in a notable proportion of cases, and most usually involves "negative symptoms" such as deficits in social interaction and language (discussed in Crespi, 2011). The clearest apparent evidence regarding this hypothesis comes from Sullivan et al. themselves, who noted that in their Study 1, 2,147 individuals had received a diagnosis of both ASD and (at discharge) schizophrenia or bipolar disorder. The authors excluded these cases as involving "diagnostic uncertainty." However, such uncertainties in the retained data may still influence the analyses. Thus, to the extent that individuals with diagnoses of ASD are under the age of onset for schizophrenia or bipolar disorder, they may exhibit false-positive diagnoses of premorbidity to schizophrenia or bipolar disorder as ASDs. Similar considerations apply to sibs differing in age.

Schizophrenia exhibits well-established genetic, symptomatic, and epidemiological overlap with both schizotypal personality disorder (SPD) and bipolar disorder (Carpenter et al., 2009). Additionally, first-order relatives of individuals with schizophrenia or affective psychosis show elevated rates of SPD (Schürhoff et al., 2005). These results indicate that SPD may show conflation in epidemiological data with high-functioning autism or Asperger's, due to the presence in both SPD and high-functioning forms of ASD of general social deficits and abnormalities. The possibility of such conflation is supported by: 1) the authors' finding that their familial association "was principally in cases without clinical indication of mental retardation," and 2) studies showing behavioral overlap of SPD with ASDs (based predominantly on questionnaires) (Barneveld et al., 2011), but a striking lack of data on overlap for developmental, physiological, or neurological phenotypes. Such conflation would falsely connect ASDs (which are actually SPD) with schizophrenia or bipolar disorder. It would appear more useful and realistic to consider the possibility and expected effects of diagnostic uncertainties than to presume that they do not exist.

This second set of considerations also applies to studies that would use GWAS data to evaluate hypotheses of how autism and schizophrenia are related to one another; even a rather small degree of false-positive conflation of premorbidity to schizophrenia with ASD could result in incorrect conclusions regarding the genetic etiologies of these sets of conditions. Such potential problems might be minimized by subsetting ASD cases into autism “sensu stricto,” given that PDD-NOS is the diagnostic category most likely to be conflated with schizophrenia premorbidity.


Sullivan PF, Magnusson C, Reichenberg A, Boman M, Dalman C, Davidson M, Fruchter E, Hultman CM, Lundberg M, Långström N, Weiser M, Svensson AC, Lichtenstein P. Family history of schizophrenia and bipolar disorder as risk factors for autism. Arch Gen Psychiatry. 2012 Jul 2:1-5. Abstract

Croen LA, Grether JK, Yoshida CK, Odouli R, Hendrick V. Antidepressant use during pregnancy and childhood autism spectrum disorders. Arch Gen Psychiatry. 2011:68(11):1104-1112. Abstract

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Bodén R, Lundgren M, Brandt L, Reutfors J, Kieler H. Antipsychotics during pregnancy: relation to fetal and maternal metabolic effects. Arch Gen Psychiatry. 2012:69(7):715-21. Abstract

Courchesne E, Mouton PR, Calhoun ME, Semendeferi K, Ahrens-Barbeau C, Hallet MJ, Barnes CC, Pierce K. Neuron number and size in prefrontal cortex of children with autism. JAMA. 2011:306(18):2001-10. Abstract

Thomas MA, Klaper RD. Psychoactive pharmaceuticals induce fish gene expression profiles associated with human idiopathic autism. PLoS One. 2012;7(6):e32917. Abstract

Hultman CM, Sandin S, Levine SZ, Lichtenstein P, Reichenberg A. Advancing paternal age and risk of autism: new evidence from a population-based study and a meta-analysis of epidemiological studies. Mol Psychiatry. 2011:16(12):1203-12. Abstract

Essex MJ, Thomas Boyce W, Hertzman C, Lam LL, Armstrong JM, Neumann SM, Kobor MS. Epigenetic vestiges of early developmental adversity: childhood stress exposure and DNA methylation in adolescence. Child Dev. 2011 Sep 2. Abstract

Crespi B. One hundred years of insanity: genomic, psychological, and evolutionary models of autism in relation to schizophrenia. In: Ritsner M, ed. Handbook of Schizophrenia Spectrum Disorders, Volume I. New York, NY: Springer; 2011:163-185.

Carpenter WT, Bustillo JR, Thaker GK, van Os J, Krueger RF, Green MJ. The psychoses: cluster 3 of the proposed meta-structure for DSM-V and ICD-11. Psychol Med. 2009: 39(12):2025-42. Abstract

Schürhoff F, Laguerre A, Szöke A, Méary A, Leboyer M. Schizotypal dimensions: continuity between schizophrenia and bipolar disorders. Schizophr Res. 2005:80(2-3):235-42. Abstract

Barneveld PS, Pieterse J, de Sonneville L, van Rijn S, Lahuis B, van Engeland H, Swaab H. Overlap of autistic and schizotypal traits in adolescents with Autism Spectrum Disorders. Schizophr Res. 2011:126(1-3):231-6. Abstract

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Related News: Family Roots for Autism, Schizophrenia, Bipolar Disorder

Comment by:  William Carpenter, SRF Advisor (Disclosure)
Submitted 30 July 2012
Posted 30 July 2012

Shared risk for ASDs in bipolar and schizophrenia families is important, and the apparent gradient in risk with schizophrenia being greater than bipolar may be informative. From the view that schizophrenia and bipolar disorder are heterogeneous syndromes, the following is surmised:

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Related News: Family Roots for Autism, Schizophrenia, Bipolar Disorder

Comment by:  John McGrath, SRF Advisor
Submitted 30 July 2012
Posted 30 July 2012
  I recommend the Primary Papers

This impressive study adds to the growing body of evidence demonstrating that heritable factors are shared among autism, schizophrenia, and bipolar disorder. The authors suggest that genetic factors could underlie the findings, but also remind the reader that environmental factors could play a role. They note that twin-based studies of heritability in schizophrenia and autism have demonstrated appreciable contributions for environmental factors that were shared between the affected individuals—usually referred to as common environmental effects. It should be noted that in this context, the word “common” does not equate with “prevalent.” With respect to shared genetic factors, the growing body of evidence regarding structural variation such as copy number variants is impressive. With respect to non-genetic factors, more work is needed—prenatal infection (which could trigger maternal immune activation) and nutrition (e.g., low vitamin D) might be candidate domains. If there are shared environmental risk factors contributing to schizophrenia, bipolar disorder, and autism, and if these were potentially modifiable, then this would be a very attractive proposition from a public health perspective.

The study is also an excellent demonstration of collaborative epidemiology—three datasets from two nations were used to examine the same research questions. This is an efficient way to do science.

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