Schizophrenia Research Forum - A Catalyst for Creative Thinking

Autism Genes: A Handful, or More?

17 March 2007. Two major studies on the genetic causes of autism suggest that copy number variations play an unexpectedly important role in the risk for the disease. These sub-microscopic deletions or insertions in the genome were recently shown to contribute much of the variation among people (see SRF related news story), and are the subject of intense study as the source of a number of diseases.

The autism studies, the largest linkage analysis carried out in families with autism to date and a fine dissection of genome-wide copy number variation, find no single smoking gun. Instead, the results suggest that potentially hundreds of genes play a role in the disease. One of the studies points to genes involved in glutamate signaling, which has also been implicated in the pathology of schizophrenia. If these studies, one in the February 18 issue of Nature Genetics online, and the other in this week’s Science, are any indication, then researchers probing the genetics of other complex disorders, such as schizophrenia, had better have plenty of stamina, funding, and a taste for surprises.

Like schizophrenia, autism is a complex neurodevelopmental disorder, encompassing a spectrum of behavioral symptoms. Genetics clearly play a role in autism since the condition runs in families. At the same time, most cases appear as isolated occurrences, and many families have just one affected child. Previous single nucleotide polymorphism (SNP) linkage studies have suggested risk genes on multiple chromosomes. In addition, researchers have found chromosomal abnormalities in up to 5 percent of cases. However, no specific genes that cause autism have been identified.

To remedy that situation, researchers formed the Autism Genome Project Consortium in 2002. With funding from private and government sources, researchers from 50 institutions pooled samples and expertise to perform large-scale analysis of genetic variation in autism spectrum disorders. The Nature Genetics report is their first, a preliminary analysis of SNP linkage data from more than 8,000 people in 1,400 families.

The consortium researchers chose to analyze only families with more than one affected member, reasoning that taking families with a strong genetic tendency to autism would boost the chances of finding common gene variants on a heterogeneous background. After mapping 10,000 SNPs, they further probed the data for a gain or loss of signal intensity at individual SNP positions to detect copy number variations (CNVs). Because of the large sample size, the investigators were also able to analyze associations of SNPs independent of CNVs, and break the sample into subgroups (e.g., families with only females or only males affected, and narrow vs. broad diagnosis) for linkage analysis.

By the SNP results, one region (11p12-p13) showed a suggestive linkage with autism across all the families. In some subsets, they confirmed the 11p12-p13 result and found additional suggestive linkages, including one on chromosome 15, which had been noted in previous studies. While none of the detected linkages were statistically significant, the authors conclude that the results call for a thorough fine mapping of 11p12-p13, which has been previously linked to autism but not extensively studied.

The analysis of CNVs based on the SNP results revealed a higher frequency of disease-associated changes than expected. Depending on the method of analysis, about 8 to 11 percent of families showed chromosomal abnormalities that were shared among affected family members. Some of the changes occurred in regions linked to other neurodevelopmental diseases. One deletion, which the investigators found in two sisters, removed coding regions of the neurexin gene. Rare mutations in the neurexin gene have been reported to increase risk for autism and mental retardation, and neurexin’s binding partners, the neuroligins, have also been implicated in autism. Together, the proteins regulate glutamatergic synaptogenesis, and their involvement fits with the hypothesis that aberrant glutamatergic transmission underlies the developmental defects that give rise to autism.

The Other Autism
The second study, a genome-wide scan for sub-microscopic copy number variation, also demonstrated a high level of disease-related changes, but in a different group of patients. That work, from Jonathan Sebat and Michael Wigler at the Cold Spring Harbor Laboratory in New York, appears in this week’s online issue of Science.

For some diseases, a cytogenetic search for de novo chromosomal abnormalities in affected children has led researchers to important causative mutations. Sebat, Wigler, and a bevy of collaborators from the U.S., the U.K., and Finland, took that idea one step further. They replaced the low-resolution microscopic analysis of chromosome structure with a high-resolution array-based search for micro-deletions and insertions. Since they were hunting for de novo mutations, the investigators probed 118 families with a single affected child (simplex families), and compared them to 47 with multiple affected children (multiplex families, like the group in the consortium study), plus 99 control families.

They found that children with autism frequently showed de novo gene copy number changes, which were far more common in children from families with sporadic disease. In the simplex families, the researchers found that 10 percent of children with autism or a related disorder showed copy number changes that were not seen in their parents. This compared to only 2 percent in children in the multiplex families and 1 percent in controls.

An association of de novo CNVs with autism spectrum disorders does not prove they cause the disease, the authors point out. Establishing causation will require pinpointing the genes involved and studying variation in additional patients and their families. Five of the 16 confirmed changes involved single genes, each of which makes a good candidate for further genetic and biological studies. While some overlapping deletions were detected, the CNVs occurred on eight different chromosomes among the 14 affected children. This suggests that rare changes at many loci could contribute to autism spectrum disorders, and might explain why previous work has failed to find common heritable variants with a major effect on disease risk, the authors write.

The enrichment for CNVs in the simplex families suggests that there may be two genetically distinct forms of autism. The idiopathic or sporadic cases make up one class, while the less common, inherited cases make up another. The two may be related, and the authors speculate that a high rate of spontaneous mutations in autism could account for heritable disease. If new mutations have incomplete penetrance, then apparently unaffected parents could pass damaged genes on to their children who might be the first to manifest the disease.

The findings likely represent the tip of the iceberg. The limited resolution of current genomic CNV scans probably results in a severe underestimate of the prevalence of genetic changes. “As technology for discovering spontaneous germline mutations in children improves, the proportion of autism cases with detectable events is bound to rise,” the authors write.

“The implications of this for future research are that different genetic approaches should be used for sporadic disease, and it is very important to initiate the recruitment efforts that focus on sporadic cases,” lead author Jonathan Sebat told SRF. “As a result of our study, a private foundation has begun to organize a consortium of several sites to recruit well-characterized simplex families,” he said.—Pat McCaffrey.

References:
The Autism Genome Project Consortium; Szatmari P, Paterson AD, Zwaigenbaum L, Roberts W, Brian J, Liu XQ, Vincent JB, Skaug JL, Thompson AP, Senman L, Feuk L, Qian C, Bryson SE, Jones MB, Marshall CR, Scherer SW, Vieland VJ, Bartlett C, Mangin LV, Goedken R, Segre A, Pericak-Vance MA, Cuccaro ML, Gilbert JR, Wright HH, Abramson RK, Betancur C, Bourgeron T, Gillberg C, Leboyer M, Buxbaum JD, Davis KL, Hollander E, Silverman JM, Hallmayer J, Lotspeich L, Sutcliffe JS, Haines JL, Folstein SE, Piven J, Wassink TH, Sheffield V, Geschwind DH, Bucan M, Brown WT, Cantor RM, Constantino JN, Gilliam TC, Herbert M, Lajonchere C, Ledbetter DH, Lese-Martin C, Miller J, Nelson S, Samango-Sprouse CA, Spence S, State M, Tanzi RE, Coon H, Dawson G, Devlin B, Estes A, Flodman P, Klei L, McMahon WM, Minshew N, Munson J, Korvatska E, Rodier PM, Schellenberg GD, Smith M, Spence MA, Stodgell C, Tepper PG, Wijsman EM, Yu CE, Roge B, Mantoulan C, Wittemeyer K, Poustka A, Felder B, Klauck SM, Schuster C, Poustka F, Bolte S, Feineis-Matthews S, Herbrecht E, Schmotzer G, Tsiantis J, Papanikolaou K, Maestrini E, Bacchelli E, Blasi F, Carone S, Toma C, Van Engeland H, de Jonge M, Kemner C, Koop F, Langemeijer M, Hijimans C, Staal WG, Baird G, Bolton PF, Rutter ML, Weisblatt E, Green J, Aldred C, Wilkinson JA, Pickles A, Le Couteur A, Berney T, McConachie H, Bailey AJ, Francis K, Honeyman G, Hutchinson A, Parr JR, Wallace S, Monaco AP, Barnby G, Kobayashi K, Lamb JA, Sousa I, Sykes N, Cook EH, Guter SJ, Leventhal BL, Salt J, Lord C, Corsello C, Hus V, Weeks DE, Volkmar F, Tauber M, Fombonne E, Shih A. Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nat Genet. 2007 Mar;39(3):319-28. Epub 2007 Feb 18. Abstract

Sebat J, Lakshmi B, Malhotra D, Lese-Martin C, Troge J, Walsh T, Yamrom B, Yoon S, Krasnitz A, Kendall J, Leotta A, Pai D, Zhang R, Lee Y, Hicks J, Spence SJ, Lee AT, Puura K, Lehtimäki T, Ledbetter D, Gregersen PK, Bregman J, Sutcliffe JS, Jobanputra J, Chung W, Warburton D, King M-C, Skuse D, Geschwind DH, Gilliam TC, Ye K, Wigler M. Strong association of de novo copy number mutations with autism. Science. 2007 March 15 [Epub ahead of print] Abstract

Comments on News and Primary Papers
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 WeinbergerComment 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.

References:

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 PattersonComment 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

Comments on Related News


Related News: New Human Genome Map Shows Extensive Copy Number Variation

Comment by:  Jonathan Sebat
Submitted 27 November 2006
Posted 27 November 2006

This study is the first to systematically map large-scale copy number variation (CNV) across a large sample representing different populations. The investigators have significantly enhanced our knowledge of genomic diversity by identifying approximately 1,000 CNVs that had not been previously reported in the literature, thereby almost doubling the catalogue of published structural variants in healthy individuals. This data set will serve as the framework for a genomic resource on structural variation. It will continue to be refined through continued efforts of many groups and may soon be a very comprehensive map. It is currently just the tip of the iceberg.

View all comments by Jonathan Sebat

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.

References:

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

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

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

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

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

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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.

References:

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

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

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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.

References:

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

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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.

References:

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.

References:

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

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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.

References:

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

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

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

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Related News: More Evidence for CNVs in Schizophrenia Etiology—Jury Still Out on Practical Implications

Comment by:  Christopher RossRussell L. Margolis
Submitted 1 August 2008
Posted 1 August 2008

The two recent papers in Nature, from the Icelandic group (Stefansson et al., 2008), and the International Schizophrenia Consortium (2008) led by Pamela Sklar, represent a landmark in psychiatric genetics. For the first time two large studies have yielded highly significant consistent results using multiple population samples. Furthermore, they arrived at these results using quite different methods. The Icelandic group used transmission screening and focused on de novo events, using the Illumina platform in both a discovery population and a replication population. By contrast, the ISC study was a large population-based case-control study using the Affymetrix platform, which did not specifically search for de novo events.

Both identified the same two regions on chromosome 1 and chromosome 15, as well as replicating the previously well studied VCFS region on chromosome 22. Thus, we now have three copy number variants which are replicated and consistent across studies. This provides data on rare highly penetrant variants complementary to the family based study of DISC1 (Porteous et al., 2006), in which the chromosomal translocation clearly segregates with disease, but in only one family. In addition, they are in general congruent with three other studies (Walsh et al., 2008; Kirov et al., 2008; Xu et al., 2008) which also demonstrate a role for copy number variation in schizophrenia. These studies together should put to rest many of the arguments about the value of genetics in psychiatry, so that future studies can now begin from a firmer base.

However, these studies also raise at least as many questions as they answer. One is the role of copy number variation in schizophrenia in the general population. The number of cases accounted for by the deletions on chromosome 1 and 15 in the ISC and Icelandic studies is extremely small--on the order of 1% or less. The extent to which copy number variation, including very rare or even private de novo variants, will account for the genetic risk for schizophrenia in the general population is still unknown. The ISC study indicated that there is a higher overall load of copy number variations in schizophrenia, broadly consistent with Walsh et al and Xu et al but backed up by a much larger sample size, allowing the results to achieve high statistical significance. The implications of these findings are still undeveloped,

Another issue is the relationship to the phenotype of schizophrenia in the general population. Many more genotype-phenotype studies will need to be done. It will be important to determine whether there is a higher rate of mental retardation in the schizophrenia in these studies than in other populations.

Another question is the relationship between these copy number variations (and other rare events) and the more common variants accounting for smaller increases in risk, as in the recent O’Donovan et al. (2008) association study in Nature Genetics. It is far too early to know, but there may well be some combination of rare mutations plus risk alleles that account for cases in the general population. This would then be highly reminiscent of Alzheimer’s disease, Parkinson’s disease, and other diseases which have been studied for a longer period of time.

For instance, in Alzheimer’s disease there are rare mutations in APP and presenilin, as well as copy number variation in APP, with duplications causing the accelerated Alzheimer’s disease seen in Down syndrome. These appear to interact with the risk allele in APOE, and possibly other risk alleles, and are part of a pathogenic pathway (Tanzi and Bertram, 2005). Similarly in Parkinson’s disease, rare mutations in α-synuclein, LRRK2 and other genes can be causative of PD, though notably the G2019S mutation in LRRK2 has incomplete penetrance. In addition, duplications or triplications of α-synuclein can cause familial PD, and altered expression due to promoter variants may contribute to risk. By contrast, deletions in Parkin cause an early onset Parkinsonian syndrome (Hardy et al., 2006). Finally, much of PD may be due to genetic risk factors or environmental causes that have not yet been identified. Further studies will likely lead to the elucidation of pathogenic pathways. These diseases can provide a paradigm for the study of schizophrenia and other psychiatric diseases. One difference is that the copy number variations in the neurodegenerative diseases are often increases in copies (as in APP and α-synuclein), consistent with gain of function mechanisms, while the schizophrenia associations were predominantly with deletions, suggesting loss of function mechanisms. The hope is that as genes are identified, they can be linked together in pathways, leading to understanding of the neurobiology of schizophrenia (Ross et al., 2006).

The key unanswered questions, of course, are what genes or other functional domains are deleted at the chromosome 1, 15, and 22 loci, whether the deletions at these loci are sufficient in themselves to cause schizophrenia, and, if sufficient, the extent to which the deletions are penetrant. Both of the current studies identified deletions large enough to include several genes. The hope is that at least a subset of copy number variations (unlike SNP associations identified in schizophrenia to date) may be causative, making the identification of the relevant genes or other functional domains—at least in principle—more feasible.

Another tantalizing observation is that the copy number variations associated with schizophrenia were defined by flanking repeat regions. This raises the question of the extent to which undetected smaller insertions, deletions or other copy number variations related to other repetitive motifs, such as long tandem repeats, may also be associated with schizophrenia. Identification and testing of these loci may prove a fruitful approach to finding additional genetic risk factors for schizophrenia.

References:

Hardy J, Cai H, Cookson MR, Gwinn-Hardy K, Singleton A. Genetics of Parkinson's disease and parkinsonism. Ann Neurol. 2006 Oct;60(4):389-98. Abstract

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

Porteous DJ, Thomson P, Brandon NJ, Millar JK. The genetics and biology of DISC1—an emerging role in psychosis and cognition. Biol Psychiatry. 2006 Jul 15;60(2):123-31. Abstract

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

Singleton A, Myers A, Hardy J. The law of mass action applied to neurodegenerative disease: a hypothesis concerning the etiology and pathogenesis of complex diseases. Hum Mol Genet. 2004 Apr 1;13 Spec No 1:R123-6. Abstract

Tanzi RE, Bertram L. Twenty years of the Alzheimer's disease amyloid hypothesis: a genetic perspective. Cell. 2005 Feb 25;120(4):545-55. Abstract

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Related News: More Evidence for CNVs in Schizophrenia Etiology—Jury Still Out on Practical Implications

Comment by:  Daniel Weinberger, SRF Advisor
Submitted 3 August 2008
Posted 3 August 2008

Several recent reports have suggested that rare CNVs may be highly penetrant genetic factors in the pathogenesis of schizophrenia, perhaps even singular etiologic events in those cases of schizophrenia who have them. This is potentially of enormous importance, as the definitive identification of such a “causative” factor may be a major step in unraveling the biologic mystery of the condition. I would stress several issues that need to be considered in putting these recent findings into a broader perspective.

It is very difficult to attribute illness to a private CNV, i.e., one found only in a single individual. This point has been potently illustrated by a study of clinically discordant MZ twins who share CNVs (Bruder et al., AJHG, 2008). Inherited CNVs, such as those that made up almost all of the CNVs described in the childhood onset cases of the study by Walsh et al. (Science, 2008), are by definition not highly penetrant (since they are inherited from unaffected parents). The finding by Xu et al. (Nat Gen, 2008) that de novo (i.e., non-inherited) CNVs are much more likely to be associated with cases lacking a family history is provocative but difficult to interpret as no data are given about the size of the families having a family history and those not having such a history. Unless these family samples are of comparable size and obtained by a comparable ascertainment strategy, it is hard to know how conclusive the finding is. Indeed, in the study of Walsh et al., rare CNVs were just as likely to be found in patients with a positive family history. Finally, in contrast to private CNVs, recurrent (but still rare) CNVs, such as those identified on 1q and 15q in the studies of the International Schizophrenia Consortium (Nature, 2008) and Stefansson et al. (Nature, 2008), are strongly implicated as being associated with the diagnosis of schizophrenia and therefore likely involved in the causation of the illnesses in the cases having these CNVs. In all, these new CNV regions, combined with the VCFS region on 22q, suggest that approximately five to 10 patients out of 1,000 who carry the diagnosis of schizophrenia may have a well-defined genetic lesion (i.e., a substantial deletion or duplication).

The overarching question now is how relevant these findings are to the other 99 percent of individuals with this diagnosis who do not have these recurrent CNVs. Before we had the capability to perform high-density DNA hybridization and SNP array analyses, chromosomal anomalies associated with the diagnosis of schizophrenia were identified using cytogenetic techniques. Indeed, VCFS, XXX, XXY (Kleinfelter’s syndrome), and XO (Turner syndrome) have been found with similarly increased frequency in cases with this diagnosis in a number of studies. Now that we have greater resolution to identify smaller structural anomalies, the list of congenital syndromes that increase the possibility that people will manifest symptoms that earn them this diagnosis appears to be growing rapidly. Are we finding causes for the form of schizophrenia that most psychiatrists see in their offices, or are we instead carving out a new set of rare congenital syndromes that share some clinical characteristics, as syphilis was carved out from the diagnosis of schizophrenia at the turn of the twentieth century? Is schizophrenia a primary expression of these anomalies or a secondary manifestation? VCFS is associated with schizophrenia-like phenomena but even more often with mild mental retardation, autism spectrum, and other psychiatric manifestations. The same is true of the aneuploidies that increase the probability of manifesting schizophrenia symptoms. The two new papers in Nature allude to the possibility that epilepsy and intellectual limitations may also be associated with these CNVs. The diagnostic potential of any of these new findings cannot be determined until the full spectrum of their clinical manifestations is clarified.

One of the important insights that might emerge from identification of these new CNV syndromes is the identification of candidate genes that may show association with schizophrenia based on SNPs in these regions. VCFS has been an important source of promising candidate genes with broader clinical relevance (e.g., PRODH, COMT). Stefansson et al. report, however, that none of the 319 SNPs in the CNV regions showed significant association with schizophrenia in quite a large sample of individuals not having deletions in these regions. The Consortium report also presumably has the results of SNP association testing in these regions in their large sample but did not report them. It is very important to explore in greater genetic detail these regions of the genome showing association with the diagnosis of schizophrenia in samples lacking these lesions and to fully characterize the clinical picture of individuals who have them. It is hoped that insights into the pathogenesis of symptoms related to this diagnosis will emerge from these additional studies.

Anyone who has worked in a public state hospital or chronic schizophrenia care facility (where I spent over 20 years) is not surprised to find an occasional patient with a rare congenital or acquired syndrome who expresses symptoms similar to those individuals also diagnosed with schizophrenia who do not have such rare syndromes. Our diagnostic procedures are not precise, and the symptoms that earn someone this diagnosis are not specific. Schizophrenia is not something someone has; it is a diagnosis someone is given. In an earlier comment for SRF on structural variations in the genome related to autism, I suggested that, “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.” These new CNV syndromes manifesting schizophrenia phenomena are probably a reminder that the same is true of what we call schizophrenia.

View all comments by Daniel Weinberger

Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

Comment 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 Rodriguez

Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

Comment 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 Crespi

Related News: Genomic Studies Draw Autism and Schizophrenia Back Toward Each Other

Comment 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.

References:

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

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

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

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

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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Related News: Cognitive Deficits Found in Controls Carrying Neuropsychiatric Risk CNVs

Comment by:  Daniel Weinberger, SRF Advisor
Submitted 19 December 2013
Posted 19 December 2013

The latest important result from the Icelandic population genetic study confirms from a new vantage point what has been clear from over two decades of research: that genetic risk for schizophrenia is associated with cognitive deficits independent of the presence of illness. The earlier work to identify this association included studies of discordant monozygotic twins (Goldberg et al., 1990; Cannon et al., 2000) and more studies of healthy siblings (Egan et al., 2001). These results are consistent with the view that susceptibility genes for developmental neuropsychiatric disorders are genes that influence brain development and function. Cognitive assays are proxies for integrative neural functions that reflect these effects.

The interpretation of the imaging data is less clear, however. While reduced measures of gray matter volume in cingulate and insula have been found in some studies of first-episode psychosis, these findings are not typical in patients with schizophrenia diagnoses and are generally not found in healthy relatives (Honea et al., 2008; Owens et al., 2012), suggesting that they are not associated with genetic risk for schizophrenia in the general population. Indeed, data linking increased genetic risk for schizophrenia with measurements made on structural MRI scans have been unconvincing, even in much larger samples.

References:

Goldberg TE, Ragland JD, Torrey EF, Gold J, Bigelow LB and Weinberger DR. Neuropsychological assessment of monozygotic twins discordant for schizophrenia. Arch Gen Psychiatry. 1990;47:1066-1072. Abstract

Cannon TD, Huttunen MO, Lonnqvist J, Tuulio-Henriksson A, Pirkola T, Glahn D, Finkelstein J, Hietanen M, Kaprio J, Koskenvuo M. The inheritance of neuropsychological dysfunction in twins discordant for schizophrenia Am J Hum Genet. 2000;67:369–382. Abstract

Egan MF, Goldberg TE, Gscheidle T, Weirich M, Rawlings R, Hyde TM, Bigelow L and Weinberger DR. Relative risk for cognitive impairments in siblings of patients with schizophrenia. Biol Psychiatry. 2001;50:98-107. Abstract

Honea RA, Meyer-Lindenberg A, Hobbs KB, Pezawas L, Mattay VS, Egan MF, Verchinski B, Passingham RE, Weinberger DR and Callicott JH. Is gray matter volume an intermediate phenotype for schizophrenia? A VBM study of patients with schizophrenia and their healthy siblings. Biol Psychiatry. 2008;63:465-474. Abstract

Owens SF, Picchioni MM, Ettinger U, McDonald C, Walshe M, Schmechtig A, Murray RM, Rijsdijk F, Toulopoulou T. Prefrontal deviations in function but not volume are putative endophenotypes for schizophrenia. Brain. 2012;135:2231–2244. Abstract

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